diff --git a/.github/workflows/make-multi-platform.yml b/.github/workflows/make-multi-platform.yml index 8a03330..85491f7 100644 --- a/.github/workflows/make-multi-platform.yml +++ b/.github/workflows/make-multi-platform.yml @@ -13,17 +13,17 @@ jobs: os: [ubuntu-latest, windows-latest] build_type: [Release] c_compiler: [gcc] - output_name: [CalcGenus, CalcGenus.exe] + output_name: [page, page.exe] include: - os: ubuntu-latest - output_name: CalcGenus + output_name: page - os: windows-latest - output_name: CalcGenus.exe + output_name: page.exe exclude: - os: windows-latest - output_name: CalcGenus + output_name: page - os: ubuntu-latest - output_name: CalcGenus.exe + output_name: page.exe steps: - uses: actions/checkout@v4 @@ -44,7 +44,7 @@ jobs: compiler: ${{ matrix.c_compiler }} - name: Build - working-directory: ./CalcGenus + working-directory: ./PAGE run: make all CC=${{ matrix.c_compiler }} CPPC=${{ matrix.cpp_compiler }} BTYPE=${{ matrix.build_type }} BDIR=${{ steps.strings.outputs.build-output-dir }} - name: release @@ -69,5 +69,5 @@ jobs: with: upload_url: ${{ steps.create_release.outputs.upload_url }} asset_path: ${{ steps.strings.outputs.build-output-dir }}/${{ matrix.output_name }} - asset_name: CalcGenus-${{ matrix.os }}-${{ matrix.build_type }} + asset_name: page-${{ matrix.os }}-${{ matrix.build_type }} asset_content_type: application/octet-stream diff --git a/.gitignore b/.gitignore index 235eb4f..6c7dc97 100644 --- a/.gitignore +++ b/.gitignore @@ -1,12 +1,18 @@ -Balaban10/FitCycles -Balaban10C/FitCycles -CalcGenus/CalcGenus -CalcGenus/CalcGenus.out *.o *.dSYM .DS_Store -CalcGenus/adjacency_lists/rome-graphml.tgz +__pycache__ +.venv +.matplotlib-cache + +PAGE/page +PAGE/page.exe +PAGE/page.out +PAGE/page_py.out +PAGE/adjacency_lists/rome-graphml.tgz + MultiGenus/multi_genus_128 MultiGenus/multi_genus_longtype_128 MultiGenus/planar_cutthroughedges_draw -__pycache__ + +genus_properties diff --git a/Balaban10/FitCycles.c b/Balaban10/FitCycles.c deleted file mode 100644 index ef28c35..0000000 --- a/Balaban10/FitCycles.c +++ /dev/null @@ -1,630 +0,0 @@ -// Attempts to fit the given cycles onto the given graph. -// A fitting must use each directed edge exactly once. -// Outputs a list of fitting cycles if they exist, or an error message if they -// don't. Optionally prints progress messages to stderr. -// Run with `make run` - -#include -#include -#include -#include -#include - -// configuration options: -#define PRINT_PROGRESS 1 // whether to print progress messages -#define DEBUG 0 // whether to print debug messages -#define VERTEX_LIMIT_LENIENCY 0 // how many unused edge pairs to allow a vertex - -// generated by generate.ipynb: -#define ADJACENCY_LIST_FILENAME "adjacency_list.txt" -#define CYCLES_FILENAME "cycles.txt" -#define CYCLES_BY_VERTEX_FILENAME "cycles_by_vertex.txt" - -// assumptions of the program (don't change these): -#define VERTEX_DEGREE 3 -#define VERTEX_USE_LIMIT VERTEX_DEGREE -#define MAX_VERTICES 255 -#define MAX_EDGES 65535 -#define MAX_CYCLE_LENGTH 255 -#define MAX_CYCLES 4294967295 - -// constants for the program: -#define bool uint8_t -#define true 1 -#define false 0 - -uint8_t* adj_load(char* filename, uint16_t* num_vertices, uint16_t* num_edges); -uint8_t* adj_get_neighbors(uint8_t* adjacency_list, uint8_t vertex); -void adj_remove_edge(uint8_t* adjacency_list, uint8_t start_vertex, - uint8_t end_vertex); -void adj_undo_remove_edge(uint8_t* adjacency_list, uint8_t start_vertex, - uint8_t end_vertex); -bool adj_has_edge(uint8_t* adjacency_list, uint8_t start_vertex, - uint8_t end_vertex); - -uint8_t* cycle_load(char* filename, uint8_t* cycle_length, - uint32_t* num_cycles); -uint8_t* cycle_get(uint8_t* cycles, uint8_t cycle_length, uint32_t cycle_index); - -uint32_t* cbv_load(char* filename, uint16_t num_vertices, uint8_t* cycles, - uint8_t cycle_length, uint32_t* max_cycles_per_vertex); -uint32_t* cbv_get_cycle_indices(uint32_t* cycles_by_vertex, - uint32_t max_cycles_per_vertex, uint16_t vertex, - uint32_t* num_cycles); - -void show_progress(double fraction); - -bool is_ijk_good(bool* used_cycles, uint8_t* cycles, uint8_t cycle_length, - uint32_t num_cycles, uint32_t cycle_to_check); -bool search(uint32_t cycles_to_use, bool* used_cycles, // state - uint8_t* vertex_uses, uint8_t* max_fit, // state - uint64_t* num_search_calls, // state - uint16_t num_vertices, uint16_t num_edges, uint8_t* adjacency_list, - uint8_t cycle_length, uint32_t num_cycles, uint8_t* cycles, - uint32_t max_cycles_per_vertex, uint32_t* cycles_by_vertex); - -int main(void) { - if (PRINT_PROGRESS) { - fprintf(stderr, "Loading data...\n"); - } - - uint16_t num_vertices, num_edges; - uint8_t* adjacency_list = - adj_load(ADJACENCY_LIST_FILENAME, &num_vertices, &num_edges); - - uint8_t cycle_length; - uint32_t num_cycles; - uint8_t* cycles = cycle_load(CYCLES_FILENAME, &cycle_length, &num_cycles); - - if (cycle_length > num_vertices) { - fprintf(stderr, - "Cycle length (%d) must be less than or equal to the number of " - "vertices (%d)\n", - cycle_length, num_vertices); - exit(1); - } - - uint32_t max_cycles_per_vertex; - uint32_t* cycles_by_vertex = - cbv_load(CYCLES_BY_VERTEX_FILENAME, num_vertices, cycles, cycle_length, - &max_cycles_per_vertex); - - if (PRINT_PROGRESS) { - fprintf(stderr, "Starting search...\n"); - } - show_progress(0.0); - - // keep track of used cycles and vertices - uint32_t edges_to_remove = 2 * num_edges; - uint32_t cycles_to_use = edges_to_remove / cycle_length; - bool* used_cycles = (bool*)malloc(num_cycles * sizeof(bool)); - if (used_cycles == NULL) { - fprintf(stderr, "Error allocating memory for the used cycles\n"); - exit(1); - } - for (uint32_t i = 0; i < num_cycles; i++) { - used_cycles[i] = false; - } - // vertices should be used exactly VERTEX_USE_LIMIT times - // so we keep track of the number of times each vertex has been used. - // this allows us to fail early if a vertex can't be used enough times - // and to prioritize vertices exploring vertices that have been used more - // since they constrain the number of possible cycles containing them more - uint8_t* vertex_uses = (uint8_t*)malloc(num_vertices * sizeof(uint8_t)); - if (vertex_uses == NULL) { - fprintf(stderr, - "Error allocating memory for the vertices most used order\n"); - exit(1); - } - - // search for a solution that starts with one of the cycles - uint8_t max_fit = 0; - uint64_t num_search_calls = 0; - for (uint32_t c = 0; c < num_cycles; c++) { - if (DEBUG) fprintf(stderr, "\nTrying cycle %d\n", c); - - // default all vertices to 0 uses - for (uint16_t i = 0; i < num_vertices; i++) { - vertex_uses[i] = 0; - } - - // mark start cycle as used - used_cycles[c] = true; - cycles_to_use--; - uint8_t* cycle = cycle_get(cycles, cycle_length, c); - for (uint8_t i = 0; i < cycle_length; i++) { - adj_remove_edge(adjacency_list, cycle[i], cycle[i + 1]); - - // mark cycle vertices as used once - vertex_uses[cycle[i]] = 1; - } - - if (search(cycles_to_use, used_cycles, vertex_uses, &max_fit, - &num_search_calls, num_vertices, num_edges, adjacency_list, - cycle_length, num_cycles, cycles, max_cycles_per_vertex, - cycles_by_vertex)) { - // Success! - show_progress(1.0); - if (PRINT_PROGRESS) { - fprintf(stderr, "\nFound a solution! Check the output to see it.\n"); - } - printf("Solution found in %lld iterations:\n", num_search_calls); - for (uint32_t i = 0; i < num_cycles; i++) { - if (used_cycles[i]) { - uint8_t* cycle = cycle_get(cycles, cycle_length, i); - for (uint8_t j = 0; j < cycle_length + 1; j++) { - printf("%d ", cycle[j]); - } - printf("\n"); - } - } - free(adjacency_list); - free(cycles); - free(cycles_by_vertex); - free(used_cycles); - free(vertex_uses); - return 0; - } - - // mark start cycle as unused - cycles_to_use++; - used_cycles[c] = false; - for (uint8_t i = 0; i < cycle_length; i++) { - adj_undo_remove_edge(adjacency_list, cycle[i], cycle[i + 1]); - } - - show_progress(c / (double)num_cycles); - } - - show_progress(1.0); - if (PRINT_PROGRESS) { - fprintf(stderr, - "\nDone. Did not find any solutions. Was only able to fit %d " - "cycles. Used %lld iterations.\n", - max_fit, num_search_calls); - } - free(adjacency_list); - free(cycles); - free(cycles_by_vertex); - free(used_cycles); - free(vertex_uses); - return 0; -} - -void show_progress(double fraction) { - // E.g. [########## ] 50% - - if (!PRINT_PROGRESS) { - return; - } - - fflush(stderr); - fprintf(stderr, "\r["); - for (int i = 0; i < 50; i++) { - if (i < fraction * 50) { - fprintf(stderr, "#"); - } else { - fprintf(stderr, " "); - } - } - fprintf(stderr, "] %d%%", (int)(fraction * 100)); -} - -// if sequence i -> j -> k occurs in any of the used cycles such that k -> j -> -// i occurs in the cycle_to_check return false -// if no such sequence occurs return true -bool is_ijk_good(bool* used_cycles, uint8_t* cycles, uint8_t cycle_length, - uint32_t num_cycles, uint32_t cycle_to_check) { - uint8_t* cycle = cycle_get(cycles, cycle_length, cycle_to_check); - - uint8_t* padded_cycle = - (uint8_t*)malloc((cycle_length + 2) * sizeof(uint8_t)); - if (padded_cycle == NULL) { - fprintf(stderr, "Error allocating memory for the padded cycle\n"); - exit(1); - } - for (uint8_t i = 0; i < cycle_length; i++) { - padded_cycle[i] = cycle[i]; - } - padded_cycle[cycle_length] = cycle[0]; - padded_cycle[cycle_length + 1] = cycle[1]; - - for (uint32_t c = 0; c < num_cycles; c++) { - if (used_cycles[c]) { - uint8_t* other_cycle = cycle_get(cycles, cycle_length, c); - - uint8_t* padded_other_cycle = - (uint8_t*)malloc((cycle_length + 2) * sizeof(uint8_t)); - if (padded_other_cycle == NULL) { - fprintf(stderr, "Error allocating memory for the padded other cycle\n"); - exit(1); - } - for (uint8_t i = 0; i < cycle_length; i++) { - padded_other_cycle[i] = other_cycle[i]; - } - padded_other_cycle[cycle_length] = other_cycle[0]; - padded_other_cycle[cycle_length + 1] = other_cycle[1]; - - for (uint8_t i = 0; i < cycle_length; i++) { - for (uint8_t j = 0; j < cycle_length; j++) { - if (padded_cycle[i] == padded_other_cycle[j + 2] && - padded_cycle[i + 1] == padded_other_cycle[j + 1] && - padded_cycle[i + 2] == padded_other_cycle[j]) { - free(padded_cycle); - free(padded_other_cycle); - return false; - } - } - } - - free(padded_other_cycle); - } - } - - free(padded_cycle); - return true; -} - -bool search(uint32_t cycles_to_use, bool* used_cycles, // state - uint8_t* vertex_uses, uint8_t* max_fit, // state - uint64_t* num_search_calls, // state - uint16_t num_vertices, uint16_t num_edges, uint8_t* adjacency_list, - uint8_t cycle_length, uint32_t num_cycles, uint8_t* cycles, - uint32_t max_cycles_per_vertex, uint32_t* cycles_by_vertex) { - (*num_search_calls)++; - - int8_t leniency = -1; - uint8_t - ignored_vertices[VERTEX_LIMIT_LENIENCY + 1]; // plus one to avoid zero - uint8_t num_ignored_vertices = 0; - while (leniency < VERTEX_LIMIT_LENIENCY) { - // pick a vertex to explore - // we pick the most used vertex that hasn't reached the limit since it - // constrains the search space of possible cycles more - uint8_t vertex; - int16_t max_uses = -1; - for (uint16_t i = 0; i < num_vertices; i++) { - bool ignore = false; - for (uint8_t j = 0; j < num_ignored_vertices; j++) { - if (ignored_vertices[j] == i) { - ignore = true; - break; - } - } - if (ignore) { - continue; - } - - if (vertex_uses[i] < VERTEX_USE_LIMIT && vertex_uses[i] > max_uses) { - vertex = i; - max_uses = vertex_uses[i]; - - if (max_uses == VERTEX_USE_LIMIT - 1) { - break; // we can't do better than this - } - } - } - // assert we don't reach a bad state - if (max_uses == -1) { - fprintf(stderr, "\nNo vertex to explore\n"); - for (uint16_t i = 0; i < num_vertices; i++) { - fprintf(stderr, "%d ", vertex_uses[i]); - } - fprintf(stderr, "\n"); - exit(1); - } - leniency += VERTEX_USE_LIMIT - vertex_uses[vertex]; - ignored_vertices[num_ignored_vertices++] = vertex; - - // if we've reached a new maximum fit, print it - if (2 * num_edges / cycle_length - cycles_to_use > *max_fit) { - *max_fit = 2 * num_edges / cycle_length - cycles_to_use; - printf("New max fit: %d (about to try vertex %" PRId8 ")\n", *max_fit, - vertex); - for (uint32_t i = 0; i < num_cycles; i++) { - if (used_cycles[i]) { - uint8_t* cycle = cycle_get(cycles, cycle_length, i); - for (uint8_t j = 0; j < cycle_length + 1; j++) { - printf("%d ", cycle[j]); - } - printf("\n"); - } - } - printf("\n"); - } - - // look through the possible cycles that contain this vertex - // if none can be used, this is a failed end and we backtrack - // otherwise, we have our solution - uint32_t num_cycles_for_vertex; - uint32_t* cycle_indices = - cbv_get_cycle_indices(cycles_by_vertex, max_cycles_per_vertex, vertex, - &num_cycles_for_vertex); - for (uint32_t i = 0; i < num_cycles_for_vertex; i++) { - // skip if the cycle is already used - uint32_t cycle_index = cycle_indices[i]; - if (used_cycles[cycle_index]) { - continue; - } - - uint8_t* cycle = cycle_get(cycles, cycle_length, cycle_index); - - // cycle is only usable if all edges are available - bool can_use = true; - for (uint8_t j = 0; j < cycle_length; j++) { - if (!adj_has_edge(adjacency_list, cycle[j], cycle[j + 1])) { - can_use = false; - break; - } - } - if (!can_use) { - continue; - } - - // make sure the cycle satisfies the ijk condition - if (!is_ijk_good(used_cycles, cycles, cycle_length, num_cycles, - cycle_index)) { - continue; - } - - // use the cycle - if (DEBUG) fprintf(stderr, "Using cycle %d\n", cycle_index); - used_cycles[cycle_index] = true; - for (uint8_t j = 0; j < cycle_length; j++) { - adj_remove_edge(adjacency_list, cycle[j], cycle[j + 1]); - - // mark cycle vertices as used - vertex_uses[cycle[j]]++; - - // assert that we don't reach a bad state - if (vertex_uses[cycle[j]] > VERTEX_USE_LIMIT) { - fprintf(stderr, "\nVertex %d used too many times (exploring %d)\n", - cycle[j], vertex); - for (uint16_t i = 0; i < num_vertices; i++) { - fprintf(stderr, "%d ", vertex_uses[i]); - } - fprintf(stderr, "\n"); - for (uint16_t i = 0; i < num_vertices; i++) { - fprintf(stderr, "%d: ", i); - for (uint8_t j = 0; j < VERTEX_DEGREE; j++) { - fprintf(stderr, "%d ", adj_get_neighbors(adjacency_list, i)[j]); - } - fprintf(stderr, "\n"); - } - exit(1); - } - } - - // if this is the final cycle needed to cover all edges, we're done - if (cycles_to_use == 1) { - return true; - } - // otherwise, continue adding cycles - if (search(cycles_to_use - 1, used_cycles, vertex_uses, max_fit, - num_search_calls, num_vertices, num_edges, adjacency_list, - cycle_length, num_cycles, cycles, max_cycles_per_vertex, - cycles_by_vertex)) { - return true; // as soon as we succeed, we're done - } - - // un-use the cycle - used_cycles[cycle_index] = false; - for (uint8_t j = 0; j < cycle_length; j++) { - adj_undo_remove_edge(adjacency_list, cycle[j], cycle[j + 1]); - - // un-use the cycle vertices - vertex_uses[cycle[j]]--; - } - } - } - - // if we haven't returned true by now, we've failed - return false; -} - -uint8_t* adj_load(char* filename, uint16_t* num_vertices, uint16_t* num_edges) { - FILE* fp = fopen(filename, "r"); - if (fp == NULL) { - fprintf(stderr, "Error opening file %s\n", filename); - exit(1); - } - - // number of vertices and edges are the two first numbers - if (fscanf(fp, "%hd %hd", num_vertices, num_edges) != 2) { - fprintf(stderr, "Error reading the first line of %s\n", filename); - exit(1); - } - - uint8_t* adjacency_list = - (uint8_t*)malloc(*num_vertices * VERTEX_DEGREE * sizeof(uint8_t)); - if (adjacency_list == NULL) { - fprintf(stderr, "Error allocating memory for the adjacency list\n"); - exit(1); - } - for (uint16_t i = 0; i < *num_vertices * VERTEX_DEGREE; i++) { - if (fscanf(fp, "%" SCNu8, &adjacency_list[i]) != 1) { - fprintf(stderr, "Error reading the adjacency list from %s\n", filename); - exit(1); - } - } - - fclose(fp); - - if (PRINT_PROGRESS) { - fprintf(stderr, "Read the adjacency list from %s\n", filename); - fprintf(stderr, "\tNumber of vertices: %d\n", *num_vertices); - fprintf(stderr, "\tNumber of edges: %d (%d directed)\n", *num_edges, - 2 * *num_edges); - fprintf(stderr, "\tFirst 5 vertices (with neighbors): "); - for (uint8_t v = 0; v < 5; v++) { - fprintf(stderr, "%d(%d %d %d) ", v, - adj_get_neighbors(adjacency_list, v)[0], - adj_get_neighbors(adjacency_list, v)[1], - adj_get_neighbors(adjacency_list, v)[2]); - } - fprintf(stderr, "\n"); - } - - return adjacency_list; -} - -uint8_t* adj_get_neighbors(uint8_t* adjacency_list, uint8_t vertex) { - return &adjacency_list[vertex * VERTEX_DEGREE]; -} - -void adj_remove_edge(uint8_t* adjacency_list, uint8_t start_vertex, - uint8_t end_vertex) { - uint8_t* neighbors = adj_get_neighbors(adjacency_list, start_vertex); - for (uint8_t i = 0; i < VERTEX_DEGREE; i++) { - if (neighbors[i] == end_vertex) { - neighbors[i] = MAX_VERTICES; - return; - } - } -} - -// must have been previously removed, otherwise undefined behavior -void adj_undo_remove_edge(uint8_t* adjacency_list, uint8_t start_vertex, - uint8_t end_vertex) { - uint8_t* neighbors = adj_get_neighbors(adjacency_list, start_vertex); - for (uint8_t i = 0; i < VERTEX_DEGREE; i++) { - if (neighbors[i] == MAX_VERTICES) { - neighbors[i] = end_vertex; - return; - } - } -} - -bool adj_has_edge(uint8_t* adjacency_list, uint8_t start_vertex, - uint8_t end_vertex) { - uint8_t* neighbors = adj_get_neighbors(adjacency_list, start_vertex); - for (uint8_t i = 0; i < VERTEX_DEGREE; i++) { - if (neighbors[i] == end_vertex) { - return true; - } - } - return false; -} - -uint8_t* cycle_load(char* filename, uint8_t* cycle_length, - uint32_t* num_cycles) { - FILE* fp = fopen(filename, "r"); - if (fp == NULL) { - fprintf(stderr, "Error opening file %s\n", filename); - exit(1); - } - - // cycle length and number of cycles are the two first numbers - if (fscanf(fp, "%" SCNu8 " %d", cycle_length, num_cycles) != 2) { - fprintf(stderr, "Error reading the first line of %s\n", filename); - exit(1); - } - - uint8_t* cycles = - (uint8_t*)malloc(*num_cycles * (*cycle_length + 1) * sizeof(uint8_t)); - if (cycles == NULL) { - fprintf(stderr, "Error allocating memory for the cycles\n"); - exit(1); - } - for (uint64_t i = 0; i < *num_cycles * (*cycle_length + 1); i++) { - if (fscanf(fp, "%" SCNu8, &cycles[i]) != 1) { - fprintf(stderr, "Error reading the cycles from %s\n", filename); - exit(1); - } - } - - fclose(fp); - - if (PRINT_PROGRESS) { - fprintf(stderr, "Read the cycles from %s\n", filename); - fprintf(stderr, "\tCycle length: %d\n", *cycle_length); - fprintf(stderr, "\tNumber of cycles: %d\n", *num_cycles); - fprintf(stderr, "\tFirst 5 cycles:\n"); - for (uint16_t i = 0; i < 5; i++) { - fprintf(stderr, "\t\t%d: ", i); - for (uint16_t j = 0; j < *cycle_length + 1; j++) { - fprintf(stderr, "%02d ", cycle_get(cycles, *cycle_length, i)[j]); - } - fprintf(stderr, "\n"); - } - } - - return cycles; -} - -uint8_t* cycle_get(uint8_t* cycles, uint8_t cycle_length, - uint32_t cycle_index) { - return &cycles[cycle_index * (cycle_length + 1)]; -} - -uint32_t* cbv_load(char* filename, uint16_t num_vertices, uint8_t* cycles, - uint8_t cycle_length, uint32_t* max_cycles_per_vertex) { - FILE* fp = fopen(filename, "r"); - if (fp == NULL) { - fprintf(stderr, "Error opening file %s\n", filename); - exit(1); - } - - // number of cycles per vertex is the first number - if (fscanf(fp, "%d", max_cycles_per_vertex) != 1) { - fprintf(stderr, "Error reading the first line of %s\n", filename); - exit(1); - } - - uint32_t* cycles_by_vertex = (uint32_t*)malloc( - num_vertices * (*max_cycles_per_vertex + 1) * sizeof(uint32_t)); - if (cycles_by_vertex == NULL) { - fprintf(stderr, "Error allocating memory for the cycles by vertex\n"); - exit(1); - } - for (uint16_t i = 0; i < num_vertices; i++) { - if (fscanf(fp, "%d", &cycles_by_vertex[i * (*max_cycles_per_vertex + 1)]) != - 1) { - fprintf(stderr, "Error reading the number of cycles for vertex from %s\n", - filename); - exit(1); - } - for (uint32_t j = 0; j < cycles_by_vertex[i * (*max_cycles_per_vertex + 1)]; - j++) { - if (fscanf(fp, "%d", - &cycles_by_vertex[i * (*max_cycles_per_vertex + 1) + j + 1]) != - 1) { - fprintf(stderr, "Error reading the cycles by vertex from %s\n", - filename); - exit(1); - } - } - } - - fclose(fp); - - if (PRINT_PROGRESS) { - fprintf(stderr, "Read the cycles by vertex from %s\n", filename); - fprintf(stderr, "\tMax cycles per vertex: %d\n", *max_cycles_per_vertex); - fprintf(stderr, "\tFirst 2 cycles of vertex 0 and 1:\n"); - for (uint16_t i = 0; i < 2; i++) { - uint32_t num_cycles; - uint32_t* cycle_indices = cbv_get_cycle_indices( - cycles_by_vertex, *max_cycles_per_vertex, i, &num_cycles); - fprintf(stderr, "\t\t%d:\n", i); - for (uint32_t j = 0; j < num_cycles && j < 2; j++) { - fprintf(stderr, "\t\t\t%d / %d: ", j, num_cycles); - for (uint16_t h = 0; h < cycle_length + 1; h++) { - fprintf(stderr, "%02d ", - cycle_get(cycles, cycle_length, cycle_indices[j])[h]); - } - fprintf(stderr, "\n"); - } - } - } - - return cycles_by_vertex; -} - -uint32_t* cbv_get_cycle_indices(uint32_t* cycles_by_vertex, - uint32_t max_cycles_per_vertex, uint16_t vertex, - uint32_t* num_cycles) { - uint32_t* row = &cycles_by_vertex[vertex * (max_cycles_per_vertex + 1)]; - *num_cycles = row[0]; - return &row[1]; -} diff --git a/Balaban10/FitCycles.out b/Balaban10/FitCycles.out deleted file mode 100644 index 650388d..0000000 --- a/Balaban10/FitCycles.out +++ /dev/null @@ -1,150 +0,0 @@ -New max fit: 1 (about to try vertex 0) -0 2 4 26 27 42 41 14 16 18 0 - -New max fit: 2 (about to try vertex 0) -0 2 4 26 27 42 41 14 16 18 0 -0 18 47 48 33 32 58 65 50 20 0 - -New max fit: 3 (about to try vertex 2) -0 2 4 26 27 42 41 14 16 18 0 -0 18 47 48 33 32 58 65 50 20 0 -0 20 21 36 35 60 67 52 23 2 0 - -New max fit: 4 (about to try vertex 4) -0 2 4 26 27 42 41 14 16 18 0 -0 18 47 48 33 32 58 65 50 20 0 -0 20 21 36 35 60 67 52 23 2 0 -2 23 24 25 53 58 32 8 6 4 2 - -New max fit: 5 (about to try vertex 6) -0 2 4 26 27 42 41 14 16 18 0 -0 18 47 48 33 32 58 65 50 20 0 -0 20 21 36 35 60 67 52 23 2 0 -2 23 24 25 53 58 32 8 6 4 2 -4 6 29 30 45 44 66 61 54 26 4 - -New max fit: 6 (about to try vertex 8) -0 2 4 26 27 42 41 14 16 18 0 -0 18 47 48 33 32 58 65 50 20 0 -0 20 21 36 35 60 67 52 23 2 0 -2 23 24 25 53 58 32 8 6 4 2 -4 6 29 30 45 44 66 61 54 26 4 -6 8 10 12 38 39 40 63 56 29 6 - -New max fit: 7 (about to try vertex 10) -0 2 4 26 27 42 41 14 16 18 0 -0 18 47 48 33 32 58 65 50 20 0 -0 20 21 36 35 60 67 52 23 2 0 -2 23 24 39 38 12 10 8 6 4 2 -4 6 29 30 45 44 66 61 54 26 4 -6 8 32 33 34 59 64 51 56 29 6 -8 10 35 36 37 61 66 53 58 32 8 - -New max fit: 8 (about to try vertex 12) -0 2 4 26 27 42 41 14 16 18 0 -0 18 47 48 33 32 58 65 50 20 0 -0 20 21 22 1 3 25 24 23 2 0 -2 23 52 59 64 51 56 29 6 4 2 -4 6 8 10 12 38 62 69 54 26 4 -6 29 30 45 44 66 53 58 32 8 6 -8 32 33 34 59 52 67 60 35 10 8 -10 35 36 37 61 66 44 16 14 12 10 - -New max fit: 9 (about to try vertex 16) -0 2 4 26 27 42 41 14 16 18 0 -0 18 47 48 49 19 1 22 21 20 0 -0 20 50 57 62 38 39 24 23 2 0 -2 23 52 59 34 33 32 8 6 4 2 -4 6 29 30 45 44 66 61 54 26 4 -6 8 10 35 60 55 68 63 56 29 6 -8 32 58 53 66 44 16 14 12 10 8 -10 12 38 62 69 54 61 37 36 35 10 -12 14 41 64 51 56 63 40 39 38 12 - -New max fit: 10 (about to try vertex 20) -0 2 4 26 27 42 43 65 50 20 0 -0 18 16 44 66 53 25 24 23 2 0 -0 20 21 22 1 19 49 48 47 18 0 -2 23 52 67 46 45 30 29 6 4 2 -4 6 8 32 58 53 66 61 54 26 4 -6 29 56 63 40 39 38 12 10 8 6 -8 10 35 36 37 11 9 34 33 32 8 -10 12 14 41 42 27 28 55 60 35 10 -12 38 62 57 31 30 45 44 16 14 12 -14 16 18 47 68 63 56 51 64 41 14 - -New max fit: 11 (about to try vertex 21) -0 2 4 26 27 42 43 65 50 20 0 -0 18 16 44 66 53 25 24 23 2 0 -0 20 21 22 1 19 49 48 47 18 0 -2 23 52 67 46 45 30 29 6 4 2 -4 6 8 32 58 53 66 61 54 26 4 -6 29 56 63 40 39 38 12 10 8 6 -8 10 35 36 37 11 9 34 33 32 8 -10 12 14 41 42 27 28 55 60 35 10 -12 38 62 57 31 30 45 44 16 14 12 -14 16 18 47 68 63 56 51 64 41 14 -20 50 57 62 69 54 61 37 36 21 20 - -New max fit: 12 (about to try vertex 22) -0 2 4 26 27 42 43 65 50 20 0 -0 18 16 44 66 53 25 24 23 2 0 -0 20 21 22 1 19 49 48 47 18 0 -2 23 52 67 46 45 30 29 6 4 2 -4 6 8 32 58 53 66 61 54 26 4 -6 29 56 63 40 39 38 12 10 8 6 -8 10 35 36 37 11 9 34 33 32 8 -10 12 14 41 42 27 28 55 60 35 10 -12 38 62 57 31 30 45 44 16 14 12 -14 16 18 47 68 63 56 51 64 41 14 -20 50 57 62 69 54 61 37 36 21 20 -21 36 35 60 67 52 59 64 51 22 21 - -New max fit: 13 (about to try vertex 1) -0 2 4 26 27 42 43 65 50 20 0 -0 18 16 44 66 53 25 24 23 2 0 -0 20 21 22 1 19 49 48 47 18 0 -1 22 51 56 29 30 31 7 5 3 1 -2 23 52 67 46 45 30 29 6 4 2 -4 6 8 32 58 53 66 61 54 26 4 -6 29 56 63 40 39 38 12 10 8 6 -8 10 35 36 37 11 9 34 33 32 8 -10 12 14 41 42 27 28 55 60 35 10 -12 38 62 57 31 30 45 44 16 14 12 -14 16 18 47 68 63 56 51 64 41 14 -20 50 57 62 69 54 61 37 36 21 20 -21 36 35 60 67 52 59 64 51 22 21 - -New max fit: 14 (about to try vertex 3) -0 2 4 26 27 42 43 65 50 20 0 -0 18 16 44 66 53 25 24 23 2 0 -0 20 21 22 1 19 49 48 47 18 0 -1 3 25 53 58 65 43 15 17 19 1 -1 22 51 56 29 30 31 7 5 3 1 -2 23 52 67 46 45 30 29 6 4 2 -4 6 8 32 58 53 66 61 54 26 4 -6 29 56 63 40 39 38 12 10 8 6 -8 10 35 36 37 11 9 34 33 32 8 -10 12 14 41 42 27 28 55 60 35 10 -12 38 62 57 31 30 45 44 16 14 12 -14 16 18 47 68 63 56 51 64 41 14 -20 50 57 62 69 54 61 37 36 21 20 -21 36 35 60 67 52 59 64 51 22 21 - -New max fit: 15 (about to try vertex 12) -0 2 4 26 27 42 43 65 50 20 0 -0 18 16 14 41 64 59 52 23 2 0 -0 20 21 22 1 19 49 48 47 18 0 -1 3 25 24 23 52 67 46 17 19 1 -1 22 51 64 41 42 27 28 5 3 1 -2 23 24 39 40 63 56 29 6 4 2 -3 5 7 31 57 50 65 58 53 25 3 -4 6 8 32 33 48 49 69 54 26 4 -5 28 55 60 67 52 59 34 9 7 5 -6 29 30 45 46 67 60 35 10 8 6 -7 9 11 37 61 66 44 45 30 31 7 -8 10 12 14 16 44 66 53 58 32 8 -9 34 33 32 58 65 43 15 13 11 9 -10 35 36 37 11 13 40 39 38 12 10 -24 25 53 66 61 54 69 62 38 39 24 - diff --git a/Balaban10/adjacency_list.txt b/Balaban10/adjacency_list.txt deleted file mode 100644 index 9ef5e30..0000000 --- a/Balaban10/adjacency_list.txt +++ /dev/null @@ -1,71 +0,0 @@ -70 105 -2 18 20 -3 19 22 -0 4 23 -1 5 25 -2 6 26 -3 7 28 -4 8 29 -5 9 31 -32 6 10 -34 7 11 -35 8 12 -37 9 13 -38 10 14 -40 11 15 -16 41 12 -17 43 13 -18 44 14 -19 46 15 -0 16 47 -1 17 49 -0 50 21 -36 20 22 -1 51 21 -2 52 24 -39 23 25 -3 53 24 -4 54 27 -42 26 28 -5 55 27 -6 56 30 -45 29 31 -7 57 30 -33 8 58 -32 48 34 -33 9 59 -36 10 60 -35 37 21 -36 11 61 -39 12 62 -38 40 24 -39 13 63 -64 42 14 -41 43 27 -65 42 15 -16 66 45 -44 30 46 -17 67 45 -48 18 68 -33 49 47 -48 19 69 -65 20 57 -64 22 56 -67 23 59 -66 25 58 -69 26 61 -68 60 28 -51 29 63 -50 62 31 -32 65 53 -64 34 52 -35 67 55 -66 37 54 -69 38 57 -68 40 56 -51 41 59 -50 58 43 -53 44 61 -52 60 46 -55 63 47 -49 54 62 diff --git a/Balaban10/austin_adj_max_fit.ipynb b/Balaban10/austin_adj_max_fit.ipynb deleted file mode 100644 index 12dd16b..0000000 --- a/Balaban10/austin_adj_max_fit.ipynb +++ /dev/null @@ -1,574 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import networkx as nx\n", - "import matplotlib.pyplot as plt\n", - "from sage.all import *" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "adjacency_list = [\n", - " [19, 21, 3], \n", - " [23, 20, 4], \n", - " [24, 5, 1], \n", - " [6, 26, 2], \n", - " [27, 7, 3], \n", - " [29, 4, 8], \n", - " [5, 9, 30], \n", - " [32, 10, 6],\n", - " [7, 33, 11],\n", - " [35, 12, 8],\n", - " [9, 36, 13],\n", - " [38, 14, 10],\n", - " [15, 39, 11],\n", - " [12, 41, 16],\n", - " [17, 42, 13],\n", - " [18, 44, 14],\n", - " [45, 15, 19],\n", - " [20, 16, 47],\n", - " [48, 1, 17],\n", - " [2, 18, 50],\n", - " [51, 22, 1],\n", - " [21, 23, 37],\n", - " [52, 2, 22],\n", - " [53, 3, 25],\n", - " [26, 40, 24],\n", - " [4, 25, 54],\n", - " [28, 55, 5],\n", - " [43, 27, 29],\n", - " [56, 6, 28],\n", - " [57, 31, 7],\n", - " [30, 32, 46],\n", - " [31, 8, 58],\n", - " [9, 34, 59],\n", - " [49, 35, 33],\n", - " [34, 60, 10],\n", - " [37, 61, 11],\n", - " [38, 36, 22],\n", - " [62, 12, 37],\n", - " [13, 63, 40],\n", - " [25, 41, 39],\n", - " [14, 64, 40],\n", - " [65, 43, 15],\n", - " [42, 28, 44],\n", - " [16, 66, 43],\n", - " [67, 17, 46],\n", - " [31, 47, 45],\n", - " [18, 68, 46],\n", - " [69, 49, 19],\n", - " [48, 34, 50],\n", - " [20, 49, 70],\n", - " [66, 21, 58],\n", - " [65, 23, 57],\n", - " [68, 60, 24],\n", - " [59, 67, 26],\n", - " [27, 62, 70],\n", - " [61, 29, 69],\n", - " [52, 30, 64],\n", - " [63, 51, 32],\n", - " [33, 66, 54],\n", - " [35, 65, 53],\n", - " [36, 68, 56],\n", - " [55, 38, 67],\n", - " [39, 58, 70],\n", - " [69, 57, 41],\n", - " [60, 42, 52],\n", - " [44, 59, 51],\n", - " [54, 45, 62],\n", - " [61, 53, 47],\n", - " [64, 48, 56],\n", - " [50, 55, 63],\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "adjacency_matrix = [[0 for _ in range(70)] for _ in range(70)]\n", - "for i in range(70):\n", - " for j in adjacency_list[i]:\n", - " adjacency_matrix[i][j - 1] = 1" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "M = matrix(adjacency_matrix)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 176 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = Graph(M, format='adjacency_matrix')\n", - "g.plot(layout='circular').show()" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "graphs.Balaban10Cage(embedding=2).is_isomorphic(g)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of vertices: 70\n", - "Number of edges: 105\n" - ] - } - ], - "source": [ - "NUM_VERTICES = g.num_verts()\n", - "NUM_EDGES = g.size()\n", - "CYCLE_LENGTH = 10 # minimum cycle length\n", - "print(f\"Number of vertices: {NUM_VERTICES}\")\n", - "print(f\"Number of edges: {NUM_EDGES}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "adjacency_list = [[v for v in g.neighbors(u)] for u in range(NUM_VERTICES)]" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "cycles = [ c for c in g.to_directed().all_simple_cycles(max_length=17) if len(c) > CYCLE_LENGTH]" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "# sort cycles by ascending length\n", - "cycles.sort(key=lambda x: len(x))" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "cycles_by_vertex = [[] for _ in range(NUM_VERTICES)]\n", - "for i, c in enumerate(cycles):\n", - " for v in c[:-1]:\n", - " cycles_by_vertex[v].append(i)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Trying cycle: [0, 2, 4, 26, 27, 42, 41, 14, 16, 18, 0]\n", - "New max used cycles: 1:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "New max used cycles: 2:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "New max used cycles: 3:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "New max used cycles: 4:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "New max used cycles: 5:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "New max used cycles: 6:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "New max used cycles: 7:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[6, 29, 56, 61, 36, 11, 9, 33, 34, 35, 10, 8, 6]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "New max used cycles: 8:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[6, 29, 56, 61, 36, 11, 9, 33, 34, 35, 10, 8, 6]\n", - "[11, 36, 37, 38, 12, 14, 16, 44, 66, 59, 54, 67, 45, 17, 15, 13, 11]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "New max used cycles: 9:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[6, 29, 56, 61, 36, 11, 9, 33, 34, 35, 10, 8, 6]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[2, 20, 50, 70, 63, 39, 13, 15, 42, 65, 52, 23, 2]\n", - "[11, 36, 37, 38, 12, 14, 16, 44, 66, 59, 54, 67, 45, 17, 15, 13, 11]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "New max used cycles: 10:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[6, 29, 56, 61, 36, 11, 9, 33, 34, 35, 10, 8, 6]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[17, 45, 46, 47, 68, 61, 56, 69, 48, 19, 17]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[2, 20, 50, 70, 63, 39, 13, 15, 42, 65, 52, 23, 2]\n", - "[11, 36, 37, 38, 12, 14, 16, 44, 66, 59, 54, 67, 45, 17, 15, 13, 11]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "New max used cycles: 11:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[6, 29, 56, 61, 36, 11, 9, 33, 34, 35, 10, 8, 6]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[2, 23, 22, 21, 51, 58, 32, 8, 10, 12, 38, 62, 67, 54, 26, 4, 2]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[17, 45, 46, 47, 68, 61, 56, 69, 48, 19, 17]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[2, 20, 50, 70, 63, 39, 13, 15, 42, 65, 52, 23, 2]\n", - "[11, 36, 37, 38, 12, 14, 16, 44, 66, 59, 54, 67, 45, 17, 15, 13, 11]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "New max used cycles: 12:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[6, 29, 56, 61, 36, 11, 9, 33, 34, 35, 10, 8, 6]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[2, 23, 22, 21, 51, 58, 32, 8, 10, 12, 38, 62, 67, 54, 26, 4, 2]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[17, 45, 46, 47, 68, 61, 56, 69, 48, 19, 17]\n", - "[2, 4, 6, 8, 32, 31, 30, 57, 52, 65, 60, 53, 68, 47, 18, 20, 2]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[2, 20, 50, 70, 63, 39, 13, 15, 42, 65, 52, 23, 2]\n", - "[11, 36, 37, 38, 12, 14, 16, 44, 66, 59, 54, 67, 45, 17, 15, 13, 11]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "New max used cycles: 13:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[6, 29, 56, 61, 36, 11, 9, 33, 34, 35, 10, 8, 6]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[2, 23, 22, 21, 51, 58, 32, 8, 10, 12, 38, 62, 67, 54, 26, 4, 2]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[17, 45, 46, 47, 68, 61, 56, 69, 48, 19, 17]\n", - "[2, 4, 6, 8, 32, 31, 30, 57, 52, 65, 60, 53, 68, 47, 18, 20, 2]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[2, 20, 50, 70, 63, 39, 13, 15, 42, 65, 52, 23, 2]\n", - "[4, 26, 25, 40, 39, 63, 58, 51, 66, 44, 43, 28, 29, 6, 4]\n", - "[11, 36, 37, 38, 12, 14, 16, 44, 66, 59, 54, 67, 45, 17, 15, 13, 11]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "New max used cycles: 14:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[6, 29, 56, 61, 36, 11, 9, 33, 34, 35, 10, 8, 6]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[2, 4, 6, 8, 32, 58, 63, 70, 55, 62, 38, 37, 22, 23, 2]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[13, 15, 42, 65, 60, 35, 34, 49, 50, 70, 63, 39, 13]\n", - "[17, 45, 46, 47, 68, 61, 56, 69, 48, 19, 17]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[4, 26, 25, 40, 39, 63, 58, 51, 66, 44, 43, 28, 29, 6, 4]\n", - "[11, 36, 37, 38, 12, 14, 16, 44, 66, 59, 54, 67, 45, 17, 15, 13, 11]\n", - "[21, 51, 58, 32, 31, 30, 57, 52, 23, 22, 21]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "[2, 20, 18, 47, 46, 31, 32, 8, 10, 12, 38, 62, 67, 54, 26, 4, 2]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "New max used cycles: 15:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[6, 29, 56, 61, 36, 11, 9, 33, 34, 35, 10, 8, 6]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[2, 23, 22, 21, 51, 58, 32, 8, 10, 12, 38, 62, 67, 54, 26, 4, 2]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[13, 15, 42, 65, 60, 35, 34, 49, 50, 70, 63, 39, 13]\n", - "[17, 45, 46, 47, 68, 61, 56, 69, 48, 19, 17]\n", - "[10, 35, 60, 53, 68, 47, 18, 20, 50, 49, 48, 69, 64, 41, 14, 12, 10]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[4, 26, 25, 40, 39, 63, 58, 51, 66, 44, 43, 28, 29, 6, 4]\n", - "[2, 20, 18, 16, 14, 41, 40, 25, 24, 53, 60, 65, 52, 23, 2]\n", - "[11, 36, 37, 38, 12, 14, 16, 44, 66, 59, 54, 67, 45, 17, 15, 13, 11]\n", - "[2, 4, 6, 8, 32, 31, 46, 45, 67, 62, 55, 70, 50, 20, 2]\n", - "[5, 7, 30, 31, 32, 58, 63, 70, 55, 27, 5]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "New max used cycles: 16:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[6, 29, 56, 61, 36, 11, 9, 33, 34, 35, 10, 8, 6]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[2, 23, 22, 21, 51, 58, 32, 8, 10, 12, 38, 62, 67, 54, 26, 4, 2]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[13, 15, 42, 65, 60, 35, 34, 49, 50, 70, 63, 39, 13]\n", - "[17, 45, 46, 47, 68, 61, 56, 69, 48, 19, 17]\n", - "[10, 35, 60, 53, 68, 47, 18, 20, 50, 49, 48, 69, 64, 41, 14, 12, 10]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[4, 26, 25, 40, 39, 63, 58, 51, 66, 44, 43, 28, 29, 6, 4]\n", - "[2, 20, 18, 16, 14, 41, 40, 25, 24, 53, 60, 65, 52, 23, 2]\n", - "[11, 36, 37, 38, 12, 14, 16, 44, 66, 59, 54, 67, 45, 17, 15, 13, 11]\n", - "[2, 4, 6, 8, 32, 31, 46, 45, 67, 62, 55, 70, 50, 20, 2]\n", - "[16, 18, 47, 46, 31, 30, 57, 52, 65, 42, 43, 44, 16]\n", - "[5, 7, 30, 31, 32, 58, 63, 70, 55, 27, 5]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "New max used cycles: 17:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[6, 29, 56, 61, 36, 11, 9, 33, 34, 35, 10, 8, 6]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[2, 23, 22, 21, 51, 58, 32, 8, 10, 12, 38, 62, 67, 54, 26, 4, 2]\n", - "[13, 15, 42, 65, 60, 35, 34, 49, 50, 70, 63, 39, 13]\n", - "[17, 45, 46, 47, 68, 61, 56, 69, 48, 19, 17]\n", - "[10, 35, 60, 53, 68, 47, 18, 20, 50, 49, 48, 69, 64, 41, 14, 12, 10]\n", - "[11, 36, 37, 38, 12, 14, 16, 44, 66, 59, 54, 67, 45, 17, 15, 13, 11]\n", - "[5, 7, 30, 31, 32, 58, 63, 70, 55, 27, 5]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[22, 23, 52, 57, 64, 69, 56, 29, 28, 27, 55, 62, 38, 37, 22]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[4, 26, 25, 40, 39, 63, 58, 51, 66, 44, 43, 28, 29, 6, 4]\n", - "[2, 20, 18, 16, 14, 41, 40, 25, 24, 53, 60, 65, 52, 23, 2]\n", - "[2, 4, 6, 8, 32, 31, 46, 45, 67, 62, 55, 70, 50, 20, 2]\n", - "[16, 18, 47, 46, 31, 30, 57, 52, 65, 42, 43, 44, 16]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "New max used cycles: 18:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[13, 39, 40, 25, 26, 54, 67, 45, 17, 15, 13]\n", - "[1, 21, 22, 23, 2, 4, 26, 25, 24, 3, 1]\n", - "[9, 11, 13, 15, 42, 65, 52, 23, 22, 37, 38, 62, 67, 54, 59, 33, 9]\n", - "[4, 6, 8, 10, 12, 14, 16, 44, 66, 59, 54, 26, 4]\n", - "[11, 36, 37, 22, 21, 51, 58, 63, 39, 13, 11]\n", - "[14, 41, 40, 39, 63, 70, 50, 20, 18, 16, 14]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "[8, 32, 31, 30, 57, 52, 65, 60, 35, 10, 8]\n", - "[2, 20, 50, 49, 48, 69, 56, 29, 6, 4, 2]\n", - "[6, 29, 28, 27, 55, 70, 63, 58, 32, 8, 6]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[2, 23, 52, 57, 64, 69, 48, 19, 17, 45, 46, 47, 18, 20, 2]\n", - "[3, 24, 53, 68, 61, 36, 11, 9, 7, 5, 3]\n", - "[12, 38, 37, 36, 61, 56, 69, 64, 41, 14, 12]\n", - "[16, 18, 47, 68, 53, 60, 65, 42, 43, 44, 16]\n", - "[7, 9, 33, 34, 35, 60, 53, 24, 25, 40, 41, 64, 57, 30, 7]\n", - "[10, 35, 34, 49, 50, 70, 55, 62, 38, 12, 10]\n", - "New max used cycles: 19:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[28, 29, 56, 61, 68, 47, 46, 31, 32, 58, 51, 66, 44, 43, 28]\n", - "[13, 39, 40, 25, 26, 54, 67, 45, 17, 15, 13]\n", - "[1, 21, 22, 23, 2, 4, 26, 25, 24, 3, 1]\n", - "[9, 11, 13, 15, 42, 65, 52, 23, 22, 37, 38, 62, 67, 54, 59, 33, 9]\n", - "[4, 6, 8, 10, 12, 14, 16, 44, 66, 59, 54, 26, 4]\n", - "[11, 36, 37, 22, 21, 51, 58, 63, 39, 13, 11]\n", - "[14, 41, 40, 39, 63, 70, 50, 20, 18, 16, 14]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "[8, 32, 31, 30, 57, 52, 65, 60, 35, 10, 8]\n", - "[2, 20, 50, 49, 48, 69, 56, 29, 6, 4, 2]\n", - "[6, 29, 28, 27, 55, 70, 63, 58, 32, 8, 6]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[2, 23, 52, 57, 64, 69, 48, 19, 17, 45, 46, 47, 18, 20, 2]\n", - "[3, 24, 53, 68, 61, 36, 11, 9, 7, 5, 3]\n", - "[12, 38, 37, 36, 61, 56, 69, 64, 41, 14, 12]\n", - "[16, 18, 47, 68, 53, 60, 65, 42, 43, 44, 16]\n", - "[7, 9, 33, 34, 35, 60, 53, 24, 25, 40, 41, 64, 57, 30, 7]\n", - "[10, 35, 34, 49, 50, 70, 55, 62, 38, 12, 10]\n" - ] - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[20], line 89\u001b[0m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(c) \u001b[38;5;241m-\u001b[39m Integer(\u001b[38;5;241m1\u001b[39m)):\n\u001b[1;32m 87\u001b[0m adj_list[c[i]]\u001b[38;5;241m.\u001b[39mremove(c[i \u001b[38;5;241m+\u001b[39m Integer(\u001b[38;5;241m1\u001b[39m)])\n\u001b[0;32m---> 89\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[43msearch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mused_cycles\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvertex_uses\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43madj_list\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 90\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFound solution:\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 91\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m c \u001b[38;5;129;01min\u001b[39;00m used_cycles:\n", - "Cell \u001b[0;32mIn[20], line 73\u001b[0m, in \u001b[0;36msearch\u001b[0;34m(used_cycles, vertex_uses, adj_list)\u001b[0m\n\u001b[1;32m 70\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m cycle[:\u001b[38;5;241m-\u001b[39mInteger(\u001b[38;5;241m1\u001b[39m)]:\n\u001b[1;32m 71\u001b[0m vertex_uses_cpy[j] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m Integer(\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m---> 73\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[43msearch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mused_cycles_cpy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvertex_uses_cpy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43madj_list_cpy\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n", - "Cell \u001b[0;32mIn[20], line 73\u001b[0m, in \u001b[0;36msearch\u001b[0;34m(used_cycles, vertex_uses, adj_list)\u001b[0m\n\u001b[1;32m 70\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m cycle[:\u001b[38;5;241m-\u001b[39mInteger(\u001b[38;5;241m1\u001b[39m)]:\n\u001b[1;32m 71\u001b[0m vertex_uses_cpy[j] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m Integer(\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m---> 73\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[43msearch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mused_cycles_cpy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvertex_uses_cpy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43madj_list_cpy\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n", - " \u001b[0;31m[... skipping similar frames: search at line 73 (4 times)]\u001b[0m\n", - "Cell \u001b[0;32mIn[20], line 73\u001b[0m, in \u001b[0;36msearch\u001b[0;34m(used_cycles, vertex_uses, adj_list)\u001b[0m\n\u001b[1;32m 70\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m cycle[:\u001b[38;5;241m-\u001b[39mInteger(\u001b[38;5;241m1\u001b[39m)]:\n\u001b[1;32m 71\u001b[0m vertex_uses_cpy[j] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m Integer(\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m---> 73\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[43msearch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mused_cycles_cpy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvertex_uses_cpy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43madj_list_cpy\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n", - "Cell \u001b[0;32mIn[20], line 50\u001b[0m, in \u001b[0;36msearch\u001b[0;34m(used_cycles, vertex_uses, adj_list)\u001b[0m\n\u001b[1;32m 48\u001b[0m edges_available \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 49\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(cycle) \u001b[38;5;241m-\u001b[39m Integer(\u001b[38;5;241m1\u001b[39m)):\n\u001b[0;32m---> 50\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cycle[j \u001b[38;5;241m+\u001b[39m \u001b[43mInteger\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m] \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m adj_list[cycle[j]]:\n\u001b[1;32m 51\u001b[0m edges_available \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 52\u001b[0m \u001b[38;5;28;01mbreak\u001b[39;00m\n", - "File \u001b[0;32msrc/cysignals/signals.pyx:341\u001b[0m, in \u001b[0;36mcysignals.signals.python_check_interrupt\u001b[0;34m()\u001b[0m\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] - } - ], - "source": [ - "from copy import deepcopy\n", - "VERTEX_USE_LIMIT = 3\n", - "max_used_cycles = 0\n", - "\n", - "def x_in_y(query, base):\n", - " try:\n", - " l = len(query)\n", - " except TypeError:\n", - " l = 1\n", - " query = type(base)((query,))\n", - "\n", - " for i in range(len(base)):\n", - " if base[i:i+l] == query:\n", - " return True\n", - " return False\n", - "\n", - "def ijkgood(c, solution):\n", - " c = c.copy() + [c[1]]\n", - " for i in range(len(c) - 2):\n", - " for c2 in solution:\n", - " c2 = c2.copy() + [c2[1]]\n", - " if x_in_y([c[i + 2], c[i + 1], c[i]], c2):\n", - " return False\n", - " return True\n", - "\n", - "def search(used_cycles, vertex_uses, adj_list) -> bool:\n", - " TARGET = 2 * NUM_EDGES // CYCLE_LENGTH\n", - "\n", - " global max_used_cycles\n", - " if len(used_cycles) > max_used_cycles:\n", - " print(f\"New max used cycles: {len(used_cycles)}:\")\n", - " max_used_cycles = len(used_cycles)\n", - " for c in used_cycles:\n", - " print([v + 1 for v in cycles[c]])\n", - " \n", - " # most used vertex not at limit\n", - " m = list(filter(lambda x: x < VERTEX_USE_LIMIT, vertex_uses))\n", - " if not m:\n", - " return False\n", - " vertex = vertex_uses.index(max(m))\n", - "\n", - " for i in cycles_by_vertex[vertex]:\n", - " if i in used_cycles:\n", - " continue\n", - "\n", - " cycle = cycles[i]\n", - "\n", - " edges_available = True\n", - " for j in range(len(cycle) - 1):\n", - " if cycle[j + 1] not in adj_list[cycle[j]]:\n", - " edges_available = False\n", - " break\n", - " if not edges_available:\n", - " continue\n", - "\n", - " if not ijkgood(cycle, [cycles[c] for c in used_cycles]):\n", - " continue\n", - "\n", - " if len(used_cycles) == TARGET - 1:\n", - " return True\n", - "\n", - " used_cycles_cpy = used_cycles.copy()\n", - " used_cycles_cpy.add(i)\n", - "\n", - " adj_list_cpy = deepcopy(adj_list)\n", - " for j in range(len(cycle) - 1):\n", - " adj_list_cpy[cycle[j]].remove(cycle[j + 1])\n", - "\n", - " vertex_uses_cpy = vertex_uses.copy()\n", - " for j in cycle[:-1]:\n", - " vertex_uses_cpy[j] += 1\n", - "\n", - " if search(used_cycles_cpy, vertex_uses_cpy, adj_list_cpy):\n", - " return True\n", - " \n", - " return False\n", - "\n", - "for c in cycles[:528]:\n", - " print(\"Trying cycle:\", c)\n", - " adj_list = deepcopy(adjacency_list)\n", - " used_cycles = set()\n", - " used_cycles.add(cycles.index(c))\n", - " vertex_uses = [0] * NUM_VERTICES\n", - " for v in c[:-1]:\n", - " vertex_uses[v] = 1\n", - " for i in range(len(c) - 1):\n", - " adj_list[c[i]].remove(c[i + 1])\n", - "\n", - " if search(used_cycles, vertex_uses, adj_list):\n", - " print(\"Found solution:\")\n", - " for c in used_cycles:\n", - " print([v + 1 for v in cycles[c]])" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "SageMath 10.3", - "language": "sage", - "name": "SageMath-10.3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Balaban10/austin_adj_no_21.ipynb b/Balaban10/austin_adj_no_21.ipynb deleted file mode 100644 index 6ecf703..0000000 --- a/Balaban10/austin_adj_no_21.ipynb +++ /dev/null @@ -1,1000 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "import networkx as nx\n", - "import matplotlib.pyplot as plt\n", - "from sage.all import *" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "adjacency_list = [\n", - " [19, 21, 3], \n", - " [23, 20, 4], \n", - " [24, 5, 1], \n", - " [6, 26, 2], \n", - " [27, 7, 3], \n", - " [29, 4, 8], \n", - " [5, 9, 30], \n", - " [32, 10, 6],\n", - " [7, 33, 11],\n", - " [35, 12, 8],\n", - " [9, 36, 13],\n", - " [38, 14, 10],\n", - " [15, 39, 11],\n", - " [12, 41, 16],\n", - " [17, 42, 13],\n", - " [18, 44, 14],\n", - " [45, 15, 19],\n", - " [20, 16, 47],\n", - " [48, 1, 17],\n", - " [2, 18, 50],\n", - " [51, 22, 1],\n", - " [21, 23, 37],\n", - " [52, 2, 22],\n", - " [53, 3, 25],\n", - " [26, 40, 24],\n", - " [4, 25, 54],\n", - " [28, 55, 5],\n", - " [43, 27, 29],\n", - " [56, 6, 28],\n", - " [57, 31, 7],\n", - " [30, 32, 46],\n", - " [31, 8, 58],\n", - " [9, 34, 59],\n", - " [49, 35, 33],\n", - " [34, 60, 10],\n", - " [37, 61, 11],\n", - " [38, 36, 22],\n", - " [62, 12, 37],\n", - " [13, 63, 40],\n", - " [25, 41, 39],\n", - " [14, 64, 40],\n", - " [65, 43, 15],\n", - " [42, 28, 44],\n", - " [16, 66, 43],\n", - " [67, 17, 46],\n", - " [31, 47, 45],\n", - " [18, 68, 46],\n", - " [69, 49, 19],\n", - " [48, 34, 50],\n", - " [20, 49, 70],\n", - " [66, 21, 58],\n", - " [65, 23, 57],\n", - " [68, 60, 24],\n", - " [59, 67, 26],\n", - " [27, 62, 70],\n", - " [61, 29, 69],\n", - " [52, 30, 64],\n", - " [63, 51, 32],\n", - " [33, 66, 54],\n", - " [35, 65, 53],\n", - " [36, 68, 56],\n", - " [55, 38, 67],\n", - " [39, 58, 70],\n", - " [69, 57, 41],\n", - " [60, 42, 52],\n", - " [44, 59, 51],\n", - " [54, 45, 62],\n", - " [61, 53, 47],\n", - " [64, 48, 56],\n", - " [50, 55, 63],\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "adjacency_matrix = [[0 for _ in range(70)] for _ in range(70)]\n", - "for i in range(70):\n", - " for j in adjacency_list[i]:\n", - " adjacency_matrix[i][j - 1] = 1" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "M = matrix(adjacency_matrix)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 176 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = Graph(M, format='adjacency_matrix')\n", - "g.plot(layout='circular').show()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "graphs.Balaban10Cage(embedding=2).is_isomorphic(g)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of vertices: 70\n", - "Number of edges: 105\n" - ] - } - ], - "source": [ - "NUM_VERTICES = g.num_verts()\n", - "NUM_EDGES = g.size()\n", - "CYCLE_LENGTH = 10 # minimum cycle length\n", - "print(f\"Number of vertices: {NUM_VERTICES}\")\n", - "print(f\"Number of edges: {NUM_EDGES}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "adjacency_list = [[v for v in g.neighbors(u)] for u in range(NUM_VERTICES)]" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "cycles = [ c for c in g.to_directed().all_simple_cycles(max_length=10) if len(c) > CYCLE_LENGTH]" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "cycles_by_vertex = [[] for _ in range(NUM_VERTICES)]\n", - "for i, c in enumerate(cycles):\n", - " for v in c[:-1]:\n", - " cycles_by_vertex[v].append(i)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Trying cycle: [0, 2, 4, 26, 27, 42, 41, 14, 16, 18, 0]\n", - "New max used cycles: 1:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "New max used cycles: 2:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "New max used cycles: 3:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "New max used cycles: 4:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "New max used cycles: 5:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "New max used cycles: 6:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[3, 24, 25, 26, 54, 59, 33, 9, 7, 5, 3]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[7, 9, 11, 13, 39, 40, 41, 64, 57, 30, 7]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "New max used cycles: 7:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[9, 11, 36, 37, 38, 62, 67, 54, 59, 33, 9]\n", - "[1, 21, 22, 37, 36, 61, 68, 53, 24, 3, 1]\n", - "[7, 9, 33, 34, 35, 60, 65, 52, 57, 30, 7]\n", - "[3, 24, 25, 40, 39, 13, 11, 9, 7, 5, 3]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "New max used cycles: 8:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[11, 36, 37, 38, 62, 67, 45, 17, 15, 13, 11]\n", - "[9, 33, 34, 35, 60, 53, 68, 61, 36, 11, 9]\n", - "[5, 7, 9, 11, 13, 39, 63, 70, 55, 27, 5]\n", - "[7, 30, 31, 46, 45, 67, 54, 59, 33, 9, 7]\n", - "[1, 21, 22, 23, 2, 4, 26, 25, 24, 3, 1]\n", - "[1, 19, 48, 49, 34, 33, 59, 66, 51, 21, 1]\n", - "[3, 24, 53, 60, 65, 52, 57, 30, 7, 5, 3]\n", - "New max used cycles: 9:\n", - "[1, 3, 5, 27, 28, 43, 42, 15, 17, 19, 1]\n", - "[13, 15, 42, 65, 52, 57, 64, 41, 40, 39, 13]\n", - "[3, 24, 53, 60, 35, 34, 33, 9, 7, 5, 3]\n", - "[9, 33, 59, 54, 67, 45, 17, 15, 13, 11, 9]\n", - "[5, 7, 30, 31, 46, 45, 67, 62, 55, 27, 5]\n", - "[1, 19, 48, 49, 50, 20, 2, 23, 22, 21, 1]\n", - "[7, 9, 11, 36, 61, 56, 69, 64, 57, 30, 7]\n", - "[11, 13, 39, 63, 70, 55, 62, 38, 37, 36, 11]\n", - "[1, 21, 51, 58, 63, 39, 40, 25, 24, 3, 1]\n", - "Trying cycle: [0, 2, 4, 26, 27, 42, 43, 65, 50, 20, 0]\n", - "New max used cycles: 10:\n", - "[1, 3, 5, 27, 28, 43, 44, 66, 51, 21, 1]\n", - "[15, 17, 19, 48, 69, 64, 57, 52, 65, 42, 15]\n", - "[7, 30, 57, 64, 41, 40, 39, 13, 11, 9, 7]\n", - "[11, 13, 15, 42, 43, 28, 29, 56, 61, 36, 11]\n", - "[1, 21, 22, 23, 2, 20, 50, 49, 48, 19, 1]\n", - "[3, 24, 53, 68, 47, 46, 31, 30, 7, 5, 3]\n", - "[9, 11, 36, 37, 38, 12, 10, 35, 34, 33, 9]\n", - "[5, 7, 9, 33, 59, 54, 67, 62, 55, 27, 5]\n", - "[13, 39, 63, 58, 32, 31, 46, 45, 17, 15, 13]\n", - "[1, 19, 17, 45, 67, 54, 26, 25, 24, 3, 1]\n", - "New max used cycles: 11:\n", - "[1, 3, 5, 27, 28, 43, 44, 66, 51, 21, 1]\n", - "[15, 17, 19, 48, 69, 64, 57, 52, 65, 42, 15]\n", - "[7, 30, 57, 64, 41, 40, 39, 13, 11, 9, 7]\n", - "[11, 13, 15, 42, 43, 28, 29, 56, 61, 36, 11]\n", - "[1, 21, 22, 23, 2, 20, 50, 49, 48, 19, 1]\n", - "[3, 24, 53, 68, 47, 46, 31, 30, 7, 5, 3]\n", - "[9, 11, 36, 37, 38, 12, 10, 35, 34, 33, 9]\n", - "[21, 51, 58, 63, 70, 55, 62, 38, 37, 22, 21]\n", - "[5, 7, 9, 33, 59, 54, 67, 62, 55, 27, 5]\n", - "[13, 39, 63, 58, 32, 31, 46, 45, 17, 15, 13]\n", - "[1, 19, 17, 45, 67, 54, 26, 25, 24, 3, 1]\n", - "New max used cycles: 12:\n", - "[1, 3, 5, 27, 28, 43, 44, 66, 51, 21, 1]\n", - "[15, 17, 19, 48, 69, 64, 57, 52, 65, 42, 15]\n", - "[7, 30, 57, 64, 41, 40, 39, 13, 11, 9, 7]\n", - "[11, 13, 15, 42, 43, 28, 29, 56, 61, 36, 11]\n", - "[1, 21, 22, 23, 2, 20, 50, 49, 48, 19, 1]\n", - "[3, 24, 53, 68, 47, 46, 31, 30, 7, 5, 3]\n", - "[9, 11, 36, 37, 38, 12, 10, 35, 34, 33, 9]\n", - "[21, 51, 58, 63, 70, 55, 62, 38, 37, 22, 21]\n", - "[5, 7, 9, 33, 59, 54, 67, 62, 55, 27, 5]\n", - "[22, 37, 36, 61, 68, 53, 60, 65, 52, 23, 22]\n", - "[13, 39, 63, 58, 32, 31, 46, 45, 17, 15, 13]\n", - "[1, 19, 17, 45, 67, 54, 26, 25, 24, 3, 1]\n", - "New max used cycles: 13:\n", - "[1, 3, 5, 27, 28, 43, 44, 66, 51, 21, 1]\n", - "[15, 17, 19, 48, 69, 64, 57, 52, 65, 42, 15]\n", - "[7, 30, 57, 64, 41, 40, 39, 13, 11, 9, 7]\n", - "[11, 13, 15, 42, 43, 28, 29, 56, 61, 36, 11]\n", - "[1, 21, 22, 23, 2, 20, 50, 49, 48, 19, 1]\n", - "[2, 23, 52, 57, 30, 31, 32, 8, 6, 4, 2]\n", - "[3, 24, 53, 68, 47, 46, 31, 30, 7, 5, 3]\n", - "[9, 11, 36, 37, 38, 12, 10, 35, 34, 33, 9]\n", - "[21, 51, 58, 63, 70, 55, 62, 38, 37, 22, 21]\n", - "[5, 7, 9, 33, 59, 54, 67, 62, 55, 27, 5]\n", - "[22, 37, 36, 61, 68, 53, 60, 65, 52, 23, 22]\n", - "[13, 39, 63, 58, 32, 31, 46, 45, 17, 15, 13]\n", - "[1, 19, 17, 45, 67, 54, 26, 25, 24, 3, 1]\n", - "New max used cycles: 14:\n", - "[1, 3, 5, 27, 28, 43, 44, 66, 51, 21, 1]\n", - "[15, 17, 19, 48, 69, 64, 57, 52, 65, 42, 15]\n", - "[7, 30, 57, 64, 41, 40, 39, 13, 11, 9, 7]\n", - "[2, 4, 26, 54, 59, 66, 44, 16, 18, 20, 2]\n", - "[11, 13, 15, 42, 43, 28, 29, 56, 61, 36, 11]\n", - "[1, 21, 22, 23, 2, 20, 50, 49, 48, 19, 1]\n", - "[2, 23, 52, 57, 30, 31, 32, 8, 6, 4, 2]\n", - "[3, 24, 53, 68, 47, 46, 31, 30, 7, 5, 3]\n", - "[9, 11, 36, 37, 38, 12, 10, 35, 34, 33, 9]\n", - "[21, 51, 58, 63, 70, 55, 62, 38, 37, 22, 21]\n", - "[5, 7, 9, 33, 59, 54, 67, 62, 55, 27, 5]\n", - "[22, 37, 36, 61, 68, 53, 60, 65, 52, 23, 22]\n", - "[13, 39, 63, 58, 32, 31, 46, 45, 17, 15, 13]\n", - "[1, 19, 17, 45, 67, 54, 26, 25, 24, 3, 1]\n", - "Trying cycle: [0, 2, 4, 26, 27, 28, 55, 68, 47, 18, 0]\n", - "Trying cycle: [0, 2, 4, 26, 54, 61, 66, 44, 16, 18, 0]\n", - "Trying cycle: [0, 2, 4, 26, 54, 61, 37, 36, 21, 20, 0]\n", - "Trying cycle: [0, 2, 4, 26, 54, 69, 62, 57, 50, 20, 0]\n", - "Trying cycle: [0, 2, 4, 26, 54, 69, 49, 48, 47, 18, 0]\n", - "Trying cycle: [0, 2, 4, 6, 8, 32, 33, 48, 47, 18, 0]\n", - "Trying cycle: [0, 2, 4, 6, 8, 32, 58, 65, 50, 20, 0]\n", - "Trying cycle: [0, 2, 4, 6, 8, 10, 35, 36, 21, 20, 0]\n", - "Trying cycle: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 0]\n", - "Trying cycle: [0, 2, 4, 6, 29, 56, 51, 22, 21, 20, 0]\n", - "Trying cycle: [0, 2, 4, 6, 29, 56, 63, 68, 47, 18, 0]\n", - "Trying cycle: [0, 2, 4, 6, 29, 30, 45, 44, 16, 18, 0]\n", - "Trying cycle: [0, 2, 4, 6, 29, 30, 31, 57, 50, 20, 0]\n", - "Trying cycle: [0, 2, 23, 24, 25, 3, 1, 22, 21, 20, 0]\n", - "Trying cycle: [0, 2, 23, 24, 25, 53, 66, 44, 16, 18, 0]\n", - "Trying cycle: [0, 2, 23, 24, 25, 53, 58, 65, 50, 20, 0]\n", - "Trying cycle: [0, 2, 23, 24, 39, 40, 63, 68, 47, 18, 0]\n", - "Trying cycle: [0, 2, 23, 24, 39, 38, 12, 14, 16, 18, 0]\n", - "Trying cycle: [0, 2, 23, 24, 39, 38, 62, 57, 50, 20, 0]\n", - "Trying cycle: [0, 2, 23, 52, 59, 64, 41, 14, 16, 18, 0]\n", - "Trying cycle: [0, 2, 23, 52, 59, 64, 51, 22, 21, 20, 0]\n", - "Trying cycle: [0, 2, 23, 52, 59, 34, 33, 48, 47, 18, 0]\n", - "Trying cycle: [0, 2, 23, 52, 67, 46, 45, 44, 16, 18, 0]\n", - "Trying cycle: [0, 2, 23, 52, 67, 60, 35, 36, 21, 20, 0]\n", - "Trying cycle: [0, 2, 23, 52, 67, 60, 55, 68, 47, 18, 0]\n", - "Trying cycle: [0, 18, 16, 44, 66, 61, 37, 36, 21, 20, 0]\n", - "Trying cycle: [0, 18, 16, 44, 66, 61, 54, 26, 4, 2, 0]\n", - "Trying cycle: [0, 18, 16, 44, 66, 53, 25, 24, 23, 2, 0]\n", - "Trying cycle: [0, 18, 16, 44, 66, 53, 58, 65, 50, 20, 0]\n", - "Trying cycle: [0, 18, 16, 44, 45, 46, 67, 52, 23, 2, 0]\n", - "Trying cycle: [0, 18, 16, 44, 45, 30, 29, 6, 4, 2, 0]\n", - "Trying cycle: [0, 18, 16, 44, 45, 30, 31, 57, 50, 20, 0]\n", - "Trying cycle: [0, 18, 16, 14, 41, 64, 51, 22, 21, 20, 0]\n", - "Trying cycle: [0, 18, 16, 14, 41, 64, 59, 52, 23, 2, 0]\n", - "Trying cycle: [0, 18, 16, 14, 41, 42, 27, 26, 4, 2, 0]\n", - "Trying cycle: [0, 18, 16, 14, 41, 42, 43, 65, 50, 20, 0]\n", - "Trying cycle: [0, 18, 16, 14, 12, 10, 8, 6, 4, 2, 0]\n", - "Trying cycle: [0, 18, 16, 14, 12, 10, 35, 36, 21, 20, 0]\n", - "Trying cycle: [0, 18, 16, 14, 12, 38, 62, 57, 50, 20, 0]\n", - "Trying cycle: [0, 18, 16, 14, 12, 38, 39, 24, 23, 2, 0]\n", - "Trying cycle: [0, 18, 47, 48, 33, 32, 8, 6, 4, 2, 0]\n", - "Trying cycle: [0, 18, 47, 48, 33, 32, 58, 65, 50, 20, 0]\n", - "Trying cycle: [0, 18, 47, 48, 33, 34, 59, 52, 23, 2, 0]\n", - "Trying cycle: [0, 18, 47, 48, 49, 19, 1, 22, 21, 20, 0]\n", - "Trying cycle: [0, 18, 47, 48, 49, 69, 62, 57, 50, 20, 0]\n", - "Trying cycle: [0, 18, 47, 48, 49, 69, 54, 26, 4, 2, 0]\n", - "Trying cycle: [0, 18, 47, 68, 63, 40, 39, 24, 23, 2, 0]\n", - "Trying cycle: [0, 18, 47, 68, 63, 56, 51, 22, 21, 20, 0]\n", - "Trying cycle: [0, 18, 47, 68, 63, 56, 29, 6, 4, 2, 0]\n", - "Trying cycle: [0, 18, 47, 68, 55, 28, 27, 26, 4, 2, 0]\n", - "Trying cycle: [0, 18, 47, 68, 55, 60, 67, 52, 23, 2, 0]\n", - "Trying cycle: [0, 18, 47, 68, 55, 60, 35, 36, 21, 20, 0]\n", - "Trying cycle: [0, 20, 50, 65, 43, 42, 27, 26, 4, 2, 0]\n", - "Trying cycle: [0, 20, 50, 65, 43, 42, 41, 14, 16, 18, 0]\n", - "Trying cycle: [0, 20, 50, 65, 58, 32, 8, 6, 4, 2, 0]\n", - "Trying cycle: [0, 20, 50, 65, 58, 32, 33, 48, 47, 18, 0]\n", - "Trying cycle: [0, 20, 50, 65, 58, 53, 25, 24, 23, 2, 0]\n", - "Trying cycle: [0, 20, 50, 65, 58, 53, 66, 44, 16, 18, 0]\n", - "Trying cycle: [0, 20, 50, 57, 62, 69, 49, 48, 47, 18, 0]\n", - "Trying cycle: [0, 20, 50, 57, 62, 69, 54, 26, 4, 2, 0]\n", - "Trying cycle: [0, 20, 50, 57, 62, 38, 12, 14, 16, 18, 0]\n", - "Trying cycle: [0, 20, 50, 57, 62, 38, 39, 24, 23, 2, 0]\n", - "Trying cycle: [0, 20, 50, 57, 31, 30, 29, 6, 4, 2, 0]\n", - "Trying cycle: [0, 20, 50, 57, 31, 30, 45, 44, 16, 18, 0]\n", - "Trying cycle: [0, 20, 21, 36, 35, 10, 8, 6, 4, 2, 0]\n", - "Trying cycle: [0, 20, 21, 36, 35, 10, 12, 14, 16, 18, 0]\n", - "Trying cycle: [0, 20, 21, 36, 35, 60, 67, 52, 23, 2, 0]\n", - "Trying cycle: [0, 20, 21, 36, 35, 60, 55, 68, 47, 18, 0]\n", - "Trying cycle: [0, 20, 21, 36, 37, 61, 66, 44, 16, 18, 0]\n", - "Trying cycle: [0, 20, 21, 36, 37, 61, 54, 26, 4, 2, 0]\n", - "Trying cycle: [0, 20, 21, 22, 1, 19, 49, 48, 47, 18, 0]\n", - "Trying cycle: [0, 20, 21, 22, 1, 3, 25, 24, 23, 2, 0]\n", - "Trying cycle: [0, 20, 21, 22, 51, 64, 41, 14, 16, 18, 0]\n", - "Trying cycle: [0, 20, 21, 22, 51, 64, 59, 52, 23, 2, 0]\n", - "Trying cycle: [0, 20, 21, 22, 51, 56, 29, 6, 4, 2, 0]\n", - "Trying cycle: [0, 20, 21, 22, 51, 56, 63, 68, 47, 18, 0]\n", - "Trying cycle: [1, 19, 17, 46, 67, 52, 59, 64, 51, 22, 1]\n", - "Trying cycle: [1, 19, 17, 46, 67, 52, 23, 24, 25, 3, 1]\n", - "Trying cycle: [1, 19, 17, 46, 67, 60, 35, 36, 21, 22, 1]\n", - "Trying cycle: [1, 19, 17, 46, 67, 60, 55, 28, 5, 3, 1]\n", - "Trying cycle: [1, 19, 17, 46, 45, 44, 66, 53, 25, 3, 1]\n", - "Trying cycle: [1, 19, 17, 46, 45, 30, 29, 56, 51, 22, 1]\n", - "Trying cycle: [1, 19, 17, 46, 45, 30, 31, 7, 5, 3, 1]\n", - "Trying cycle: [1, 19, 17, 15, 43, 65, 50, 20, 21, 22, 1]\n", - "Trying cycle: [1, 19, 17, 15, 43, 65, 58, 53, 25, 3, 1]\n", - "Trying cycle: [1, 19, 17, 15, 43, 42, 27, 28, 5, 3, 1]\n", - "Trying cycle: [1, 19, 17, 15, 43, 42, 41, 64, 51, 22, 1]\n", - "Trying cycle: [1, 19, 17, 15, 13, 40, 63, 56, 51, 22, 1]\n", - "Trying cycle: [1, 19, 17, 15, 13, 40, 39, 24, 25, 3, 1]\n", - "Trying cycle: [1, 19, 17, 15, 13, 11, 9, 7, 5, 3, 1]\n", - "Trying cycle: [1, 19, 17, 15, 13, 11, 37, 36, 21, 22, 1]\n", - "Trying cycle: [1, 19, 49, 48, 33, 32, 58, 53, 25, 3, 1]\n", - "Trying cycle: [1, 19, 49, 48, 33, 34, 59, 64, 51, 22, 1]\n", - "Trying cycle: [1, 19, 49, 48, 33, 34, 9, 7, 5, 3, 1]\n", - "Trying cycle: [1, 19, 49, 48, 47, 68, 63, 56, 51, 22, 1]\n", - "Trying cycle: [1, 19, 49, 48, 47, 68, 55, 28, 5, 3, 1]\n", - "Trying cycle: [1, 19, 49, 69, 62, 57, 50, 20, 21, 22, 1]\n", - "Trying cycle: [1, 19, 49, 69, 62, 57, 31, 7, 5, 3, 1]\n", - "Trying cycle: [1, 19, 49, 69, 62, 38, 39, 24, 25, 3, 1]\n", - "Trying cycle: [1, 19, 49, 69, 54, 26, 27, 28, 5, 3, 1]\n", - "Trying cycle: [1, 19, 49, 69, 54, 61, 66, 53, 25, 3, 1]\n", - "Trying cycle: [1, 19, 49, 69, 54, 61, 37, 36, 21, 22, 1]\n", - "Trying cycle: [1, 3, 5, 28, 27, 42, 41, 64, 51, 22, 1]\n", - "Trying cycle: [1, 3, 5, 28, 27, 42, 43, 15, 17, 19, 1]\n", - "Trying cycle: [1, 3, 5, 28, 27, 26, 54, 69, 49, 19, 1]\n", - "Trying cycle: [1, 3, 5, 28, 55, 68, 47, 48, 49, 19, 1]\n", - "Trying cycle: [1, 3, 5, 28, 55, 68, 63, 56, 51, 22, 1]\n", - "Trying cycle: [1, 3, 5, 28, 55, 60, 67, 46, 17, 19, 1]\n", - "Trying cycle: [1, 3, 5, 28, 55, 60, 35, 36, 21, 22, 1]\n", - "Trying cycle: [1, 3, 5, 7, 9, 34, 33, 48, 49, 19, 1]\n", - "Trying cycle: [1, 3, 5, 7, 9, 34, 59, 64, 51, 22, 1]\n", - "Trying cycle: [1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 1]\n", - "Trying cycle: [1, 3, 5, 7, 9, 11, 37, 36, 21, 22, 1]\n", - "Trying cycle: [1, 3, 5, 7, 31, 57, 50, 20, 21, 22, 1]\n", - "Trying cycle: [1, 3, 5, 7, 31, 57, 62, 69, 49, 19, 1]\n", - "Trying cycle: [1, 3, 5, 7, 31, 30, 29, 56, 51, 22, 1]\n", - "Trying cycle: [1, 3, 5, 7, 31, 30, 45, 46, 17, 19, 1]\n", - "Trying cycle: [1, 3, 25, 24, 23, 52, 59, 64, 51, 22, 1]\n", - "Trying cycle: [1, 3, 25, 24, 23, 52, 67, 46, 17, 19, 1]\n", - "Trying cycle: [1, 3, 25, 24, 39, 40, 63, 56, 51, 22, 1]\n", - "Trying cycle: [1, 3, 25, 24, 39, 40, 13, 15, 17, 19, 1]\n", - "Trying cycle: [1, 3, 25, 24, 39, 38, 62, 69, 49, 19, 1]\n", - "Trying cycle: [1, 3, 25, 53, 66, 61, 37, 36, 21, 22, 1]\n", - "Trying cycle: [1, 3, 25, 53, 66, 61, 54, 69, 49, 19, 1]\n", - "Trying cycle: [1, 3, 25, 53, 66, 44, 45, 46, 17, 19, 1]\n", - "Trying cycle: [1, 3, 25, 53, 58, 32, 33, 48, 49, 19, 1]\n", - "Trying cycle: [1, 3, 25, 53, 58, 65, 50, 20, 21, 22, 1]\n", - "Trying cycle: [1, 3, 25, 53, 58, 65, 43, 15, 17, 19, 1]\n", - "Trying cycle: [1, 22, 51, 64, 41, 42, 27, 28, 5, 3, 1]\n", - "Trying cycle: [1, 22, 51, 64, 41, 42, 43, 15, 17, 19, 1]\n", - "Trying cycle: [1, 22, 51, 64, 59, 34, 33, 48, 49, 19, 1]\n", - "Trying cycle: [1, 22, 51, 64, 59, 34, 9, 7, 5, 3, 1]\n", - "Trying cycle: [1, 22, 51, 64, 59, 52, 67, 46, 17, 19, 1]\n", - "Trying cycle: [1, 22, 51, 64, 59, 52, 23, 24, 25, 3, 1]\n", - "Trying cycle: [1, 22, 51, 56, 29, 30, 45, 46, 17, 19, 1]\n", - "Trying cycle: [1, 22, 51, 56, 29, 30, 31, 7, 5, 3, 1]\n", - "Trying cycle: [1, 22, 51, 56, 63, 40, 13, 15, 17, 19, 1]\n", - "Trying cycle: [1, 22, 51, 56, 63, 40, 39, 24, 25, 3, 1]\n", - "Trying cycle: [1, 22, 51, 56, 63, 68, 47, 48, 49, 19, 1]\n", - "Trying cycle: [1, 22, 51, 56, 63, 68, 55, 28, 5, 3, 1]\n", - "Trying cycle: [1, 22, 21, 36, 35, 60, 67, 46, 17, 19, 1]\n", - "Trying cycle: [1, 22, 21, 36, 35, 60, 55, 28, 5, 3, 1]\n", - "Trying cycle: [1, 22, 21, 36, 37, 11, 9, 7, 5, 3, 1]\n", - "Trying cycle: [1, 22, 21, 36, 37, 11, 13, 15, 17, 19, 1]\n", - "Trying cycle: [1, 22, 21, 36, 37, 61, 66, 53, 25, 3, 1]\n", - "Trying cycle: [1, 22, 21, 36, 37, 61, 54, 69, 49, 19, 1]\n", - "Trying cycle: [1, 22, 21, 20, 50, 65, 43, 15, 17, 19, 1]\n", - "Trying cycle: [1, 22, 21, 20, 50, 65, 58, 53, 25, 3, 1]\n", - "Trying cycle: [1, 22, 21, 20, 50, 57, 62, 69, 49, 19, 1]\n", - "Trying cycle: [1, 22, 21, 20, 50, 57, 31, 7, 5, 3, 1]\n", - "Trying cycle: [2, 4, 26, 27, 42, 41, 64, 59, 52, 23, 2]\n", - "Trying cycle: [2, 4, 26, 27, 28, 5, 3, 25, 24, 23, 2]\n", - "Trying cycle: [2, 4, 26, 27, 28, 55, 60, 67, 52, 23, 2]\n", - "Trying cycle: [2, 4, 26, 54, 61, 66, 53, 25, 24, 23, 2]\n", - "Trying cycle: [2, 4, 26, 54, 69, 62, 38, 39, 24, 23, 2]\n", - "Trying cycle: [2, 4, 6, 8, 32, 33, 34, 59, 52, 23, 2]\n", - "Trying cycle: [2, 4, 6, 8, 32, 58, 53, 25, 24, 23, 2]\n", - "Trying cycle: [2, 4, 6, 8, 10, 35, 60, 67, 52, 23, 2]\n", - "Trying cycle: [2, 4, 6, 8, 10, 12, 38, 39, 24, 23, 2]\n", - "Trying cycle: [2, 4, 6, 29, 56, 51, 64, 59, 52, 23, 2]\n", - "Trying cycle: [2, 4, 6, 29, 56, 63, 40, 39, 24, 23, 2]\n", - "Trying cycle: [2, 4, 6, 29, 30, 45, 46, 67, 52, 23, 2]\n", - "Trying cycle: [2, 23, 24, 25, 3, 5, 28, 27, 26, 4, 2]\n", - "Trying cycle: [2, 23, 24, 25, 53, 66, 61, 54, 26, 4, 2]\n", - "Trying cycle: [2, 23, 24, 25, 53, 58, 32, 8, 6, 4, 2]\n", - "Trying cycle: [2, 23, 24, 39, 40, 63, 56, 29, 6, 4, 2]\n", - "Trying cycle: [2, 23, 24, 39, 38, 12, 10, 8, 6, 4, 2]\n", - "Trying cycle: [2, 23, 24, 39, 38, 62, 69, 54, 26, 4, 2]\n", - "Trying cycle: [2, 23, 52, 59, 64, 41, 42, 27, 26, 4, 2]\n", - "Trying cycle: [2, 23, 52, 59, 64, 51, 56, 29, 6, 4, 2]\n", - "Trying cycle: [2, 23, 52, 59, 34, 33, 32, 8, 6, 4, 2]\n", - "Trying cycle: [2, 23, 52, 67, 46, 45, 30, 29, 6, 4, 2]\n", - "Trying cycle: [2, 23, 52, 67, 60, 35, 10, 8, 6, 4, 2]\n", - "Trying cycle: [2, 23, 52, 67, 60, 55, 28, 27, 26, 4, 2]\n", - "Trying cycle: [3, 5, 28, 27, 42, 43, 65, 58, 53, 25, 3]\n", - "Trying cycle: [3, 5, 28, 27, 26, 54, 61, 66, 53, 25, 3]\n", - "Trying cycle: [3, 5, 28, 55, 68, 63, 40, 39, 24, 25, 3]\n", - "Trying cycle: [3, 5, 28, 55, 60, 67, 52, 23, 24, 25, 3]\n", - "Trying cycle: [3, 5, 7, 9, 34, 33, 32, 58, 53, 25, 3]\n", - "Trying cycle: [3, 5, 7, 9, 34, 59, 52, 23, 24, 25, 3]\n", - "Trying cycle: [3, 5, 7, 9, 11, 13, 40, 39, 24, 25, 3]\n", - "Trying cycle: [3, 5, 7, 9, 11, 37, 61, 66, 53, 25, 3]\n", - "Trying cycle: [3, 5, 7, 31, 57, 50, 65, 58, 53, 25, 3]\n", - "Trying cycle: [3, 5, 7, 31, 57, 62, 38, 39, 24, 25, 3]\n", - "Trying cycle: [3, 5, 7, 31, 30, 45, 44, 66, 53, 25, 3]\n", - "Trying cycle: [3, 25, 24, 23, 52, 59, 34, 9, 7, 5, 3]\n", - "Trying cycle: [3, 25, 24, 23, 52, 67, 60, 55, 28, 5, 3]\n", - "Trying cycle: [3, 25, 24, 39, 40, 63, 68, 55, 28, 5, 3]\n", - "Trying cycle: [3, 25, 24, 39, 40, 13, 11, 9, 7, 5, 3]\n", - "Trying cycle: [3, 25, 24, 39, 38, 62, 57, 31, 7, 5, 3]\n", - "Trying cycle: [3, 25, 53, 66, 61, 37, 11, 9, 7, 5, 3]\n", - "Trying cycle: [3, 25, 53, 66, 61, 54, 26, 27, 28, 5, 3]\n", - "Trying cycle: [3, 25, 53, 66, 44, 45, 30, 31, 7, 5, 3]\n", - "Trying cycle: [3, 25, 53, 58, 32, 33, 34, 9, 7, 5, 3]\n", - "Trying cycle: [3, 25, 53, 58, 65, 50, 57, 31, 7, 5, 3]\n", - "Trying cycle: [3, 25, 53, 58, 65, 43, 42, 27, 28, 5, 3]\n", - "Trying cycle: [4, 26, 27, 42, 41, 64, 51, 56, 29, 6, 4]\n", - "Trying cycle: [4, 26, 27, 42, 41, 14, 12, 10, 8, 6, 4]\n", - "Trying cycle: [4, 26, 27, 42, 43, 65, 58, 32, 8, 6, 4]\n", - "Trying cycle: [4, 26, 27, 28, 5, 7, 31, 30, 29, 6, 4]\n", - "Trying cycle: [4, 26, 27, 28, 55, 68, 63, 56, 29, 6, 4]\n", - "Trying cycle: [4, 26, 27, 28, 55, 60, 35, 10, 8, 6, 4]\n", - "Trying cycle: [4, 26, 54, 61, 66, 44, 45, 30, 29, 6, 4]\n", - "Trying cycle: [4, 26, 54, 61, 66, 53, 58, 32, 8, 6, 4]\n", - "Trying cycle: [4, 26, 54, 61, 37, 36, 35, 10, 8, 6, 4]\n", - "Trying cycle: [4, 26, 54, 69, 62, 57, 31, 30, 29, 6, 4]\n", - "Trying cycle: [4, 26, 54, 69, 62, 38, 12, 10, 8, 6, 4]\n", - "Trying cycle: [4, 26, 54, 69, 49, 48, 33, 32, 8, 6, 4]\n", - "Trying cycle: [4, 6, 8, 32, 33, 48, 49, 69, 54, 26, 4]\n", - "Trying cycle: [4, 6, 8, 32, 58, 65, 43, 42, 27, 26, 4]\n", - "Trying cycle: [4, 6, 8, 32, 58, 53, 66, 61, 54, 26, 4]\n", - "Trying cycle: [4, 6, 8, 10, 35, 36, 37, 61, 54, 26, 4]\n", - "Trying cycle: [4, 6, 8, 10, 35, 60, 55, 28, 27, 26, 4]\n", - "Trying cycle: [4, 6, 8, 10, 12, 38, 62, 69, 54, 26, 4]\n", - "Trying cycle: [4, 6, 8, 10, 12, 14, 41, 42, 27, 26, 4]\n", - "Trying cycle: [4, 6, 29, 56, 51, 64, 41, 42, 27, 26, 4]\n", - "Trying cycle: [4, 6, 29, 56, 63, 68, 55, 28, 27, 26, 4]\n", - "Trying cycle: [4, 6, 29, 30, 45, 44, 66, 61, 54, 26, 4]\n", - "Trying cycle: [4, 6, 29, 30, 31, 57, 62, 69, 54, 26, 4]\n", - "Trying cycle: [4, 6, 29, 30, 31, 7, 5, 28, 27, 26, 4]\n", - "Trying cycle: [5, 28, 27, 42, 41, 64, 59, 34, 9, 7, 5]\n", - "Trying cycle: [5, 28, 27, 42, 43, 65, 50, 57, 31, 7, 5]\n", - "Trying cycle: [5, 28, 27, 42, 43, 15, 13, 11, 9, 7, 5]\n", - "Trying cycle: [5, 28, 27, 26, 54, 61, 37, 11, 9, 7, 5]\n", - "Trying cycle: [5, 28, 27, 26, 54, 69, 62, 57, 31, 7, 5]\n", - "Trying cycle: [5, 28, 55, 68, 47, 48, 33, 34, 9, 7, 5]\n", - "Trying cycle: [5, 28, 55, 68, 63, 40, 13, 11, 9, 7, 5]\n", - "Trying cycle: [5, 28, 55, 68, 63, 56, 29, 30, 31, 7, 5]\n", - "Trying cycle: [5, 28, 55, 60, 67, 46, 45, 30, 31, 7, 5]\n", - "Trying cycle: [5, 28, 55, 60, 67, 52, 59, 34, 9, 7, 5]\n", - "Trying cycle: [5, 28, 55, 60, 35, 36, 37, 11, 9, 7, 5]\n", - "Trying cycle: [5, 7, 9, 34, 33, 48, 47, 68, 55, 28, 5]\n", - "Trying cycle: [5, 7, 9, 34, 59, 64, 41, 42, 27, 28, 5]\n", - "Trying cycle: [5, 7, 9, 34, 59, 52, 67, 60, 55, 28, 5]\n", - "Trying cycle: [5, 7, 9, 11, 13, 40, 63, 68, 55, 28, 5]\n", - "Trying cycle: [5, 7, 9, 11, 13, 15, 43, 42, 27, 28, 5]\n", - "Trying cycle: [5, 7, 9, 11, 37, 36, 35, 60, 55, 28, 5]\n", - "Trying cycle: [5, 7, 9, 11, 37, 61, 54, 26, 27, 28, 5]\n", - "Trying cycle: [5, 7, 31, 57, 50, 65, 43, 42, 27, 28, 5]\n", - "Trying cycle: [5, 7, 31, 57, 62, 69, 54, 26, 27, 28, 5]\n", - "Trying cycle: [5, 7, 31, 30, 29, 56, 63, 68, 55, 28, 5]\n", - "Trying cycle: [5, 7, 31, 30, 45, 46, 67, 60, 55, 28, 5]\n", - "Trying cycle: [6, 8, 32, 33, 48, 47, 68, 63, 56, 29, 6]\n", - "Trying cycle: [6, 8, 32, 33, 34, 59, 64, 51, 56, 29, 6]\n", - "Trying cycle: [6, 8, 32, 33, 34, 9, 7, 31, 30, 29, 6]\n", - "Trying cycle: [6, 8, 32, 58, 65, 50, 57, 31, 30, 29, 6]\n", - "Trying cycle: [6, 8, 32, 58, 53, 66, 44, 45, 30, 29, 6]\n", - "Trying cycle: [6, 8, 10, 35, 36, 21, 22, 51, 56, 29, 6]\n", - "Trying cycle: [6, 8, 10, 35, 60, 67, 46, 45, 30, 29, 6]\n", - "Trying cycle: [6, 8, 10, 35, 60, 55, 68, 63, 56, 29, 6]\n", - "Trying cycle: [6, 8, 10, 12, 38, 62, 57, 31, 30, 29, 6]\n", - "Trying cycle: [6, 8, 10, 12, 38, 39, 40, 63, 56, 29, 6]\n", - "Trying cycle: [6, 8, 10, 12, 14, 16, 44, 45, 30, 29, 6]\n", - "Trying cycle: [6, 8, 10, 12, 14, 41, 64, 51, 56, 29, 6]\n", - "Trying cycle: [6, 29, 56, 51, 64, 41, 14, 12, 10, 8, 6]\n", - "Trying cycle: [6, 29, 56, 51, 64, 59, 34, 33, 32, 8, 6]\n", - "Trying cycle: [6, 29, 56, 51, 22, 21, 36, 35, 10, 8, 6]\n", - "Trying cycle: [6, 29, 56, 63, 40, 39, 38, 12, 10, 8, 6]\n", - "Trying cycle: [6, 29, 56, 63, 68, 47, 48, 33, 32, 8, 6]\n", - "Trying cycle: [6, 29, 56, 63, 68, 55, 60, 35, 10, 8, 6]\n", - "Trying cycle: [6, 29, 30, 45, 46, 67, 60, 35, 10, 8, 6]\n", - "Trying cycle: [6, 29, 30, 45, 44, 16, 14, 12, 10, 8, 6]\n", - "Trying cycle: [6, 29, 30, 45, 44, 66, 53, 58, 32, 8, 6]\n", - "Trying cycle: [6, 29, 30, 31, 57, 50, 65, 58, 32, 8, 6]\n", - "Trying cycle: [6, 29, 30, 31, 57, 62, 38, 12, 10, 8, 6]\n", - "Trying cycle: [6, 29, 30, 31, 7, 9, 34, 33, 32, 8, 6]\n", - "Trying cycle: [7, 9, 34, 33, 32, 58, 65, 50, 57, 31, 7]\n", - "Trying cycle: [7, 9, 34, 33, 48, 49, 69, 62, 57, 31, 7]\n", - "Trying cycle: [7, 9, 34, 59, 64, 51, 56, 29, 30, 31, 7]\n", - "Trying cycle: [7, 9, 34, 59, 52, 67, 46, 45, 30, 31, 7]\n", - "Trying cycle: [7, 9, 11, 13, 40, 63, 56, 29, 30, 31, 7]\n", - "Trying cycle: [7, 9, 11, 13, 40, 39, 38, 62, 57, 31, 7]\n", - "Trying cycle: [7, 9, 11, 13, 15, 17, 46, 45, 30, 31, 7]\n", - "Trying cycle: [7, 9, 11, 13, 15, 43, 65, 50, 57, 31, 7]\n", - "Trying cycle: [7, 9, 11, 37, 36, 21, 20, 50, 57, 31, 7]\n", - "Trying cycle: [7, 9, 11, 37, 61, 66, 44, 45, 30, 31, 7]\n", - "Trying cycle: [7, 9, 11, 37, 61, 54, 69, 62, 57, 31, 7]\n", - "Trying cycle: [7, 31, 57, 50, 65, 43, 15, 13, 11, 9, 7]\n", - "Trying cycle: [7, 31, 57, 50, 65, 58, 32, 33, 34, 9, 7]\n", - "Trying cycle: [7, 31, 57, 50, 20, 21, 36, 37, 11, 9, 7]\n", - "Trying cycle: [7, 31, 57, 62, 69, 49, 48, 33, 34, 9, 7]\n", - "Trying cycle: [7, 31, 57, 62, 69, 54, 61, 37, 11, 9, 7]\n", - "Trying cycle: [7, 31, 57, 62, 38, 39, 40, 13, 11, 9, 7]\n", - "Trying cycle: [7, 31, 30, 29, 56, 51, 64, 59, 34, 9, 7]\n", - "Trying cycle: [7, 31, 30, 29, 56, 63, 40, 13, 11, 9, 7]\n", - "Trying cycle: [7, 31, 30, 45, 46, 17, 15, 13, 11, 9, 7]\n", - "Trying cycle: [7, 31, 30, 45, 46, 67, 52, 59, 34, 9, 7]\n", - "Trying cycle: [7, 31, 30, 45, 44, 66, 61, 37, 11, 9, 7]\n", - "Trying cycle: [8, 32, 33, 48, 47, 18, 16, 14, 12, 10, 8]\n", - "Trying cycle: [8, 32, 33, 48, 47, 68, 55, 60, 35, 10, 8]\n", - "Trying cycle: [8, 32, 33, 48, 49, 69, 62, 38, 12, 10, 8]\n", - "Trying cycle: [8, 32, 33, 34, 59, 64, 41, 14, 12, 10, 8]\n", - "Trying cycle: [8, 32, 33, 34, 59, 52, 67, 60, 35, 10, 8]\n", - "Trying cycle: [8, 32, 33, 34, 9, 11, 37, 36, 35, 10, 8]\n", - "Trying cycle: [8, 32, 58, 65, 50, 20, 21, 36, 35, 10, 8]\n", - "Trying cycle: [8, 32, 58, 65, 50, 57, 62, 38, 12, 10, 8]\n", - "Trying cycle: [8, 32, 58, 65, 43, 42, 41, 14, 12, 10, 8]\n", - "Trying cycle: [8, 32, 58, 53, 25, 24, 39, 38, 12, 10, 8]\n", - "Trying cycle: [8, 32, 58, 53, 66, 61, 37, 36, 35, 10, 8]\n", - "Trying cycle: [8, 32, 58, 53, 66, 44, 16, 14, 12, 10, 8]\n", - "Trying cycle: [8, 10, 35, 36, 21, 20, 50, 65, 58, 32, 8]\n", - "Trying cycle: [8, 10, 35, 36, 37, 11, 9, 34, 33, 32, 8]\n", - "Trying cycle: [8, 10, 35, 36, 37, 61, 66, 53, 58, 32, 8]\n", - "Trying cycle: [8, 10, 35, 60, 67, 52, 59, 34, 33, 32, 8]\n", - "Trying cycle: [8, 10, 35, 60, 55, 68, 47, 48, 33, 32, 8]\n", - "Trying cycle: [8, 10, 12, 38, 62, 57, 50, 65, 58, 32, 8]\n", - "Trying cycle: [8, 10, 12, 38, 62, 69, 49, 48, 33, 32, 8]\n", - "Trying cycle: [8, 10, 12, 38, 39, 24, 25, 53, 58, 32, 8]\n", - "Trying cycle: [8, 10, 12, 14, 16, 18, 47, 48, 33, 32, 8]\n", - "Trying cycle: [8, 10, 12, 14, 16, 44, 66, 53, 58, 32, 8]\n", - "Trying cycle: [8, 10, 12, 14, 41, 64, 59, 34, 33, 32, 8]\n", - "Trying cycle: [8, 10, 12, 14, 41, 42, 43, 65, 58, 32, 8]\n", - "Trying cycle: [9, 34, 33, 32, 58, 65, 43, 15, 13, 11, 9]\n", - "Trying cycle: [9, 34, 33, 32, 58, 53, 66, 61, 37, 11, 9]\n", - "Trying cycle: [9, 34, 33, 48, 47, 68, 63, 40, 13, 11, 9]\n", - "Trying cycle: [9, 34, 33, 48, 49, 19, 17, 15, 13, 11, 9]\n", - "Trying cycle: [9, 34, 33, 48, 49, 69, 54, 61, 37, 11, 9]\n", - "Trying cycle: [9, 34, 59, 64, 41, 42, 43, 15, 13, 11, 9]\n", - "Trying cycle: [9, 34, 59, 64, 51, 56, 63, 40, 13, 11, 9]\n", - "Trying cycle: [9, 34, 59, 64, 51, 22, 21, 36, 37, 11, 9]\n", - "Trying cycle: [9, 34, 59, 52, 67, 46, 17, 15, 13, 11, 9]\n", - "Trying cycle: [9, 34, 59, 52, 67, 60, 35, 36, 37, 11, 9]\n", - "Trying cycle: [9, 34, 59, 52, 23, 24, 39, 40, 13, 11, 9]\n", - "Trying cycle: [9, 11, 13, 40, 63, 56, 51, 64, 59, 34, 9]\n", - "Trying cycle: [9, 11, 13, 40, 63, 68, 47, 48, 33, 34, 9]\n", - "Trying cycle: [9, 11, 13, 40, 39, 24, 23, 52, 59, 34, 9]\n", - "Trying cycle: [9, 11, 13, 15, 17, 19, 49, 48, 33, 34, 9]\n", - "Trying cycle: [9, 11, 13, 15, 17, 46, 67, 52, 59, 34, 9]\n", - "Trying cycle: [9, 11, 13, 15, 43, 65, 58, 32, 33, 34, 9]\n", - "Trying cycle: [9, 11, 13, 15, 43, 42, 41, 64, 59, 34, 9]\n", - "Trying cycle: [9, 11, 37, 36, 21, 22, 51, 64, 59, 34, 9]\n", - "Trying cycle: [9, 11, 37, 36, 35, 60, 67, 52, 59, 34, 9]\n", - "Trying cycle: [9, 11, 37, 61, 66, 53, 58, 32, 33, 34, 9]\n", - "Trying cycle: [9, 11, 37, 61, 54, 69, 49, 48, 33, 34, 9]\n", - "Trying cycle: [10, 35, 36, 21, 20, 50, 57, 62, 38, 12, 10]\n", - "Trying cycle: [10, 35, 36, 21, 22, 51, 64, 41, 14, 12, 10]\n", - "Trying cycle: [10, 35, 36, 37, 11, 13, 40, 39, 38, 12, 10]\n", - "Trying cycle: [10, 35, 36, 37, 61, 66, 44, 16, 14, 12, 10]\n", - "Trying cycle: [10, 35, 36, 37, 61, 54, 69, 62, 38, 12, 10]\n", - "Trying cycle: [10, 35, 60, 67, 46, 45, 44, 16, 14, 12, 10]\n", - "Trying cycle: [10, 35, 60, 67, 52, 59, 64, 41, 14, 12, 10]\n", - "Trying cycle: [10, 35, 60, 67, 52, 23, 24, 39, 38, 12, 10]\n", - "Trying cycle: [10, 35, 60, 55, 68, 47, 18, 16, 14, 12, 10]\n", - "Trying cycle: [10, 35, 60, 55, 68, 63, 40, 39, 38, 12, 10]\n", - "Trying cycle: [10, 35, 60, 55, 28, 27, 42, 41, 14, 12, 10]\n", - "Trying cycle: [10, 12, 38, 62, 57, 50, 20, 21, 36, 35, 10]\n", - "Trying cycle: [10, 12, 38, 62, 69, 54, 61, 37, 36, 35, 10]\n", - "Trying cycle: [10, 12, 38, 39, 40, 63, 68, 55, 60, 35, 10]\n", - "Trying cycle: [10, 12, 38, 39, 40, 13, 11, 37, 36, 35, 10]\n", - "Trying cycle: [10, 12, 38, 39, 24, 23, 52, 67, 60, 35, 10]\n", - "Trying cycle: [10, 12, 14, 16, 18, 47, 68, 55, 60, 35, 10]\n", - "Trying cycle: [10, 12, 14, 16, 44, 66, 61, 37, 36, 35, 10]\n", - "Trying cycle: [10, 12, 14, 16, 44, 45, 46, 67, 60, 35, 10]\n", - "Trying cycle: [10, 12, 14, 41, 64, 51, 22, 21, 36, 35, 10]\n", - "Trying cycle: [10, 12, 14, 41, 64, 59, 52, 67, 60, 35, 10]\n", - "Trying cycle: [10, 12, 14, 41, 42, 27, 28, 55, 60, 35, 10]\n", - "Trying cycle: [11, 13, 40, 63, 56, 51, 22, 21, 36, 37, 11]\n", - "Trying cycle: [11, 13, 40, 63, 68, 55, 60, 35, 36, 37, 11]\n", - "Trying cycle: [11, 13, 40, 39, 24, 25, 53, 66, 61, 37, 11]\n", - "Trying cycle: [11, 13, 40, 39, 38, 62, 69, 54, 61, 37, 11]\n", - "Trying cycle: [11, 13, 15, 17, 19, 49, 69, 54, 61, 37, 11]\n", - "Trying cycle: [11, 13, 15, 17, 46, 67, 60, 35, 36, 37, 11]\n", - "Trying cycle: [11, 13, 15, 17, 46, 45, 44, 66, 61, 37, 11]\n", - "Trying cycle: [11, 13, 15, 43, 65, 50, 20, 21, 36, 37, 11]\n", - "Trying cycle: [11, 13, 15, 43, 65, 58, 53, 66, 61, 37, 11]\n", - "Trying cycle: [11, 13, 15, 43, 42, 27, 26, 54, 61, 37, 11]\n", - "Trying cycle: [11, 37, 36, 21, 20, 50, 65, 43, 15, 13, 11]\n", - "Trying cycle: [11, 37, 36, 21, 22, 51, 56, 63, 40, 13, 11]\n", - "Trying cycle: [11, 37, 36, 35, 60, 67, 46, 17, 15, 13, 11]\n", - "Trying cycle: [11, 37, 36, 35, 60, 55, 68, 63, 40, 13, 11]\n", - "Trying cycle: [11, 37, 61, 66, 44, 45, 46, 17, 15, 13, 11]\n", - "Trying cycle: [11, 37, 61, 66, 53, 25, 24, 39, 40, 13, 11]\n", - "Trying cycle: [11, 37, 61, 66, 53, 58, 65, 43, 15, 13, 11]\n", - "Trying cycle: [11, 37, 61, 54, 26, 27, 42, 43, 15, 13, 11]\n", - "Trying cycle: [11, 37, 61, 54, 69, 62, 38, 39, 40, 13, 11]\n", - "Trying cycle: [11, 37, 61, 54, 69, 49, 19, 17, 15, 13, 11]\n", - "Trying cycle: [12, 38, 62, 57, 50, 65, 43, 42, 41, 14, 12]\n", - "Trying cycle: [12, 38, 62, 57, 31, 30, 45, 44, 16, 14, 12]\n", - "Trying cycle: [12, 38, 62, 69, 49, 48, 47, 18, 16, 14, 12]\n", - "Trying cycle: [12, 38, 62, 69, 54, 26, 27, 42, 41, 14, 12]\n", - "Trying cycle: [12, 38, 62, 69, 54, 61, 66, 44, 16, 14, 12]\n", - "Trying cycle: [12, 38, 39, 40, 63, 56, 51, 64, 41, 14, 12]\n", - "Trying cycle: [12, 38, 39, 40, 63, 68, 47, 18, 16, 14, 12]\n", - "Trying cycle: [12, 38, 39, 40, 13, 15, 43, 42, 41, 14, 12]\n", - "Trying cycle: [12, 38, 39, 24, 25, 53, 66, 44, 16, 14, 12]\n", - "Trying cycle: [12, 38, 39, 24, 23, 52, 59, 64, 41, 14, 12]\n", - "Trying cycle: [12, 14, 16, 18, 47, 48, 49, 69, 62, 38, 12]\n", - "Trying cycle: [12, 14, 16, 18, 47, 68, 63, 40, 39, 38, 12]\n", - "Trying cycle: [12, 14, 16, 44, 66, 61, 54, 69, 62, 38, 12]\n", - "Trying cycle: [12, 14, 16, 44, 66, 53, 25, 24, 39, 38, 12]\n", - "Trying cycle: [12, 14, 16, 44, 45, 30, 31, 57, 62, 38, 12]\n", - "Trying cycle: [12, 14, 41, 64, 51, 56, 63, 40, 39, 38, 12]\n", - "Trying cycle: [12, 14, 41, 64, 59, 52, 23, 24, 39, 38, 12]\n", - "Trying cycle: [12, 14, 41, 42, 27, 26, 54, 69, 62, 38, 12]\n", - "Trying cycle: [12, 14, 41, 42, 43, 65, 50, 57, 62, 38, 12]\n", - "Trying cycle: [12, 14, 41, 42, 43, 15, 13, 40, 39, 38, 12]\n", - "Trying cycle: [13, 40, 63, 56, 51, 64, 41, 42, 43, 15, 13]\n", - "Trying cycle: [13, 40, 63, 56, 29, 30, 45, 46, 17, 15, 13]\n", - "Trying cycle: [13, 40, 63, 68, 47, 48, 49, 19, 17, 15, 13]\n", - "Trying cycle: [13, 40, 63, 68, 55, 28, 27, 42, 43, 15, 13]\n", - "Trying cycle: [13, 40, 63, 68, 55, 60, 67, 46, 17, 15, 13]\n", - "Trying cycle: [13, 40, 39, 24, 25, 53, 58, 65, 43, 15, 13]\n", - "Trying cycle: [13, 40, 39, 24, 23, 52, 67, 46, 17, 15, 13]\n", - "Trying cycle: [13, 40, 39, 38, 62, 57, 50, 65, 43, 15, 13]\n", - "Trying cycle: [13, 40, 39, 38, 62, 69, 49, 19, 17, 15, 13]\n", - "Trying cycle: [13, 15, 17, 19, 49, 48, 47, 68, 63, 40, 13]\n", - "Trying cycle: [13, 15, 17, 19, 49, 69, 62, 38, 39, 40, 13]\n", - "Trying cycle: [13, 15, 17, 46, 67, 52, 23, 24, 39, 40, 13]\n", - "Trying cycle: [13, 15, 17, 46, 67, 60, 55, 68, 63, 40, 13]\n", - "Trying cycle: [13, 15, 17, 46, 45, 30, 29, 56, 63, 40, 13]\n", - "Trying cycle: [13, 15, 43, 65, 50, 57, 62, 38, 39, 40, 13]\n", - "Trying cycle: [13, 15, 43, 65, 58, 53, 25, 24, 39, 40, 13]\n", - "Trying cycle: [13, 15, 43, 42, 27, 28, 55, 68, 63, 40, 13]\n", - "Trying cycle: [13, 15, 43, 42, 41, 64, 51, 56, 63, 40, 13]\n", - "Trying cycle: [14, 16, 18, 47, 48, 33, 34, 59, 64, 41, 14]\n", - "Trying cycle: [14, 16, 18, 47, 68, 63, 56, 51, 64, 41, 14]\n", - "Trying cycle: [14, 16, 18, 47, 68, 55, 28, 27, 42, 41, 14]\n", - "Trying cycle: [14, 16, 44, 66, 61, 54, 26, 27, 42, 41, 14]\n", - "Trying cycle: [14, 16, 44, 66, 53, 58, 65, 43, 42, 41, 14]\n", - "Trying cycle: [14, 16, 44, 45, 46, 17, 15, 43, 42, 41, 14]\n", - "Trying cycle: [14, 16, 44, 45, 46, 67, 52, 59, 64, 41, 14]\n", - "Trying cycle: [14, 16, 44, 45, 30, 29, 56, 51, 64, 41, 14]\n", - "Trying cycle: [14, 41, 64, 51, 56, 29, 30, 45, 44, 16, 14]\n", - "Trying cycle: [14, 41, 64, 51, 56, 63, 68, 47, 18, 16, 14]\n", - "Trying cycle: [14, 41, 64, 59, 34, 33, 48, 47, 18, 16, 14]\n", - "Trying cycle: [14, 41, 64, 59, 52, 67, 46, 45, 44, 16, 14]\n", - "Trying cycle: [14, 41, 42, 27, 26, 54, 61, 66, 44, 16, 14]\n", - "Trying cycle: [14, 41, 42, 27, 28, 55, 68, 47, 18, 16, 14]\n", - "Trying cycle: [14, 41, 42, 43, 65, 58, 53, 66, 44, 16, 14]\n", - "Trying cycle: [14, 41, 42, 43, 15, 17, 46, 45, 44, 16, 14]\n", - "Trying cycle: [15, 17, 19, 49, 48, 33, 32, 58, 65, 43, 15]\n", - "Trying cycle: [15, 17, 19, 49, 69, 62, 57, 50, 65, 43, 15]\n", - "Trying cycle: [15, 17, 19, 49, 69, 54, 26, 27, 42, 43, 15]\n", - "Trying cycle: [15, 17, 46, 67, 52, 59, 64, 41, 42, 43, 15]\n", - "Trying cycle: [15, 17, 46, 67, 60, 55, 28, 27, 42, 43, 15]\n", - "Trying cycle: [15, 17, 46, 45, 44, 66, 53, 58, 65, 43, 15]\n", - "Trying cycle: [15, 17, 46, 45, 30, 31, 57, 50, 65, 43, 15]\n", - "Trying cycle: [15, 43, 65, 50, 57, 62, 69, 49, 19, 17, 15]\n", - "Trying cycle: [15, 43, 65, 50, 57, 31, 30, 45, 46, 17, 15]\n", - "Trying cycle: [15, 43, 65, 58, 32, 33, 48, 49, 19, 17, 15]\n", - "Trying cycle: [15, 43, 65, 58, 53, 66, 44, 45, 46, 17, 15]\n", - "Trying cycle: [15, 43, 42, 27, 26, 54, 69, 49, 19, 17, 15]\n", - "Trying cycle: [15, 43, 42, 27, 28, 55, 60, 67, 46, 17, 15]\n", - "Trying cycle: [15, 43, 42, 41, 64, 59, 52, 67, 46, 17, 15]\n", - "Trying cycle: [16, 18, 47, 48, 33, 32, 58, 53, 66, 44, 16]\n", - "Trying cycle: [16, 18, 47, 48, 49, 19, 17, 46, 45, 44, 16]\n", - "Trying cycle: [16, 18, 47, 48, 49, 69, 54, 61, 66, 44, 16]\n", - "Trying cycle: [16, 18, 47, 68, 63, 56, 29, 30, 45, 44, 16]\n", - "Trying cycle: [16, 18, 47, 68, 55, 60, 67, 46, 45, 44, 16]\n", - "Trying cycle: [16, 44, 66, 61, 54, 69, 49, 48, 47, 18, 16]\n", - "Trying cycle: [16, 44, 66, 53, 58, 32, 33, 48, 47, 18, 16]\n", - "Trying cycle: [16, 44, 45, 46, 17, 19, 49, 48, 47, 18, 16]\n", - "Trying cycle: [16, 44, 45, 46, 67, 60, 55, 68, 47, 18, 16]\n", - "Trying cycle: [16, 44, 45, 30, 29, 56, 63, 68, 47, 18, 16]\n", - "Trying cycle: [17, 19, 49, 48, 33, 34, 59, 52, 67, 46, 17]\n", - "Trying cycle: [17, 19, 49, 48, 47, 68, 55, 60, 67, 46, 17]\n", - "Trying cycle: [17, 19, 49, 69, 62, 57, 31, 30, 45, 46, 17]\n", - "Trying cycle: [17, 19, 49, 69, 54, 61, 66, 44, 45, 46, 17]\n", - "Trying cycle: [17, 46, 67, 52, 59, 34, 33, 48, 49, 19, 17]\n", - "Trying cycle: [17, 46, 67, 60, 55, 68, 47, 48, 49, 19, 17]\n", - "Trying cycle: [17, 46, 45, 44, 66, 61, 54, 69, 49, 19, 17]\n", - "Trying cycle: [17, 46, 45, 30, 31, 57, 62, 69, 49, 19, 17]\n", - "Trying cycle: [20, 50, 65, 43, 42, 41, 64, 51, 22, 21, 20]\n", - "Trying cycle: [20, 50, 65, 58, 53, 66, 61, 37, 36, 21, 20]\n", - "Trying cycle: [20, 50, 57, 62, 69, 54, 61, 37, 36, 21, 20]\n", - "Trying cycle: [20, 50, 57, 31, 30, 29, 56, 51, 22, 21, 20]\n", - "Trying cycle: [20, 21, 36, 37, 61, 66, 53, 58, 65, 50, 20]\n", - "Trying cycle: [20, 21, 36, 37, 61, 54, 69, 62, 57, 50, 20]\n", - "Trying cycle: [20, 21, 22, 51, 64, 41, 42, 43, 65, 50, 20]\n", - "Trying cycle: [20, 21, 22, 51, 56, 29, 30, 31, 57, 50, 20]\n", - "Trying cycle: [21, 36, 35, 60, 67, 52, 59, 64, 51, 22, 21]\n", - "Trying cycle: [21, 36, 35, 60, 55, 68, 63, 56, 51, 22, 21]\n", - "Trying cycle: [21, 22, 51, 64, 59, 52, 67, 60, 35, 36, 21]\n", - "Trying cycle: [21, 22, 51, 56, 63, 68, 55, 60, 35, 36, 21]\n", - "Trying cycle: [23, 24, 25, 53, 66, 44, 45, 46, 67, 52, 23]\n", - "Trying cycle: [23, 24, 25, 53, 58, 32, 33, 34, 59, 52, 23]\n", - "Trying cycle: [23, 24, 39, 40, 63, 56, 51, 64, 59, 52, 23]\n", - "Trying cycle: [23, 24, 39, 40, 63, 68, 55, 60, 67, 52, 23]\n", - "Trying cycle: [23, 52, 59, 64, 51, 56, 63, 40, 39, 24, 23]\n", - "Trying cycle: [23, 52, 59, 34, 33, 32, 58, 53, 25, 24, 23]\n", - "Trying cycle: [23, 52, 67, 46, 45, 44, 66, 53, 25, 24, 23]\n", - "Trying cycle: [23, 52, 67, 60, 55, 68, 63, 40, 39, 24, 23]\n", - "Trying cycle: [24, 25, 53, 66, 61, 54, 69, 62, 38, 39, 24]\n", - "New max used cycles: 15:\n", - "[1, 3, 5, 27, 28, 43, 44, 66, 51, 21, 1]\n", - "[2, 23, 52, 65, 42, 43, 28, 29, 6, 4, 2]\n", - "[1, 19, 17, 15, 42, 65, 60, 53, 24, 3, 1]\n", - "[25, 26, 54, 67, 62, 55, 70, 63, 39, 40, 25]\n", - "[7, 30, 31, 46, 47, 68, 61, 36, 11, 9, 7]\n", - "[3, 24, 25, 40, 41, 64, 57, 30, 7, 5, 3]\n", - "[1, 21, 22, 23, 2, 20, 50, 49, 48, 19, 1]\n", - "[6, 29, 56, 61, 68, 53, 60, 35, 10, 8, 6]\n", - "[5, 7, 9, 33, 34, 49, 50, 70, 55, 27, 5]\n", - "[11, 36, 37, 38, 12, 14, 41, 40, 39, 13, 11]\n", - "[8, 10, 12, 38, 62, 67, 45, 46, 31, 32, 8]\n", - "[9, 11, 13, 15, 17, 45, 67, 54, 59, 33, 9]\n", - "[2, 4, 26, 25, 24, 53, 68, 47, 18, 20, 2]\n", - "[10, 35, 34, 33, 59, 66, 44, 16, 14, 12, 10]\n", - "[4, 6, 8, 32, 58, 51, 66, 59, 54, 26, 4]\n", - "Trying cycle: [24, 25, 53, 58, 65, 50, 57, 62, 38, 39, 24]\n", - "Trying cycle: [24, 39, 38, 62, 57, 50, 65, 58, 53, 25, 24]\n", - "Trying cycle: [24, 39, 38, 62, 69, 54, 61, 66, 53, 25, 24]\n", - "Trying cycle: [26, 27, 42, 43, 65, 50, 57, 62, 69, 54, 26]\n", - "Trying cycle: [26, 27, 42, 43, 65, 58, 53, 66, 61, 54, 26]\n", - "Trying cycle: [26, 27, 28, 55, 68, 47, 48, 49, 69, 54, 26]\n", - "Trying cycle: [26, 27, 28, 55, 60, 35, 36, 37, 61, 54, 26]\n", - "Trying cycle: [26, 54, 61, 66, 53, 58, 65, 43, 42, 27, 26]\n", - "Trying cycle: [26, 54, 61, 37, 36, 35, 60, 55, 28, 27, 26]\n", - "Trying cycle: [26, 54, 69, 62, 57, 50, 65, 43, 42, 27, 26]\n", - "Trying cycle: [26, 54, 69, 49, 48, 47, 68, 55, 28, 27, 26]\n", - "Trying cycle: [27, 42, 41, 64, 51, 56, 63, 68, 55, 28, 27]\n", - "Trying cycle: [27, 42, 41, 64, 59, 52, 67, 60, 55, 28, 27]\n", - "Trying cycle: [27, 28, 55, 68, 63, 56, 51, 64, 41, 42, 27]\n", - "Trying cycle: [27, 28, 55, 60, 67, 52, 59, 64, 41, 42, 27]\n", - "Trying cycle: [29, 56, 51, 64, 59, 52, 67, 46, 45, 30, 29]\n", - "Trying cycle: [29, 56, 63, 40, 39, 38, 62, 57, 31, 30, 29]\n", - "Trying cycle: [29, 56, 63, 68, 55, 60, 67, 46, 45, 30, 29]\n", - "Trying cycle: [29, 30, 45, 46, 67, 52, 59, 64, 51, 56, 29]\n", - "Trying cycle: [29, 30, 45, 46, 67, 60, 55, 68, 63, 56, 29]\n", - "Trying cycle: [29, 30, 31, 57, 62, 38, 39, 40, 63, 56, 29]\n", - "Trying cycle: [30, 45, 44, 66, 61, 54, 69, 62, 57, 31, 30]\n", - "Trying cycle: [30, 45, 44, 66, 53, 58, 65, 50, 57, 31, 30]\n", - "Trying cycle: [30, 31, 57, 50, 65, 58, 53, 66, 44, 45, 30]\n", - "Trying cycle: [30, 31, 57, 62, 69, 54, 61, 66, 44, 45, 30]\n", - "Trying cycle: [32, 33, 48, 49, 69, 62, 57, 50, 65, 58, 32]\n", - "Trying cycle: [32, 33, 48, 49, 69, 54, 61, 66, 53, 58, 32]\n", - "Trying cycle: [32, 33, 34, 59, 64, 41, 42, 43, 65, 58, 32]\n", - "Trying cycle: [32, 58, 65, 50, 57, 62, 69, 49, 48, 33, 32]\n", - "Trying cycle: [32, 58, 65, 43, 42, 41, 64, 59, 34, 33, 32]\n", - "Trying cycle: [32, 58, 53, 66, 61, 54, 69, 49, 48, 33, 32]\n", - "Trying cycle: [33, 48, 47, 68, 63, 56, 51, 64, 59, 34, 33]\n", - "Trying cycle: [33, 48, 47, 68, 55, 60, 67, 52, 59, 34, 33]\n", - "Trying cycle: [33, 34, 59, 64, 51, 56, 63, 68, 47, 48, 33]\n", - "Trying cycle: [33, 34, 59, 52, 67, 60, 55, 68, 47, 48, 33]\n", - "Trying cycle: [35, 36, 37, 61, 66, 44, 45, 46, 67, 60, 35]\n", - "Trying cycle: [35, 60, 67, 46, 45, 44, 66, 61, 37, 36, 35]\n", - "Trying cycle: [38, 62, 69, 49, 48, 47, 68, 63, 40, 39, 38]\n", - "Trying cycle: [38, 39, 40, 63, 68, 47, 48, 49, 69, 62, 38]\n", - "Trying cycle: [50, 65, 58, 53, 66, 61, 54, 69, 62, 57, 50]\n", - "Trying cycle: [50, 57, 62, 69, 54, 61, 66, 53, 58, 65, 50]\n", - "Trying cycle: [51, 64, 59, 52, 67, 60, 55, 68, 63, 56, 51]\n", - "Trying cycle: [51, 56, 63, 68, 55, 60, 67, 52, 59, 64, 51]\n" - ] - } - ], - "source": [ - "from copy import deepcopy\n", - "VERTEX_USE_LIMIT = 3\n", - "max_used_cycles = 0\n", - "\n", - "def x_in_y(query, base):\n", - " try:\n", - " l = len(query)\n", - " except TypeError:\n", - " l = 1\n", - " query = type(base)((query,))\n", - "\n", - " for i in range(len(base)):\n", - " if base[i:i+l] == query:\n", - " return True\n", - " return False\n", - "\n", - "def ijkgood(c, solution):\n", - " c = c.copy() + [c[1]]\n", - " for i in range(len(c) - 2):\n", - " for c2 in solution:\n", - " c2 = c2.copy() + [c2[1]]\n", - " if x_in_y([c[i + 2], c[i + 1], c[i]], c2):\n", - " return False\n", - " return True\n", - "\n", - "def search(used_cycles, vertex_uses, adj_list) -> bool:\n", - " TARGET = 2 * NUM_EDGES // CYCLE_LENGTH\n", - "\n", - " global max_used_cycles\n", - " if len(used_cycles) > max_used_cycles:\n", - " print(f\"New max used cycles: {len(used_cycles)}:\")\n", - " max_used_cycles = len(used_cycles)\n", - " for c in used_cycles:\n", - " print([v + 1 for v in cycles[c]])\n", - " \n", - " # most used vertex not at limit\n", - " m = list(filter(lambda x: x < VERTEX_USE_LIMIT, vertex_uses))\n", - " if not m:\n", - " return False\n", - " vertex = vertex_uses.index(max(m))\n", - "\n", - " for i in cycles_by_vertex[vertex]:\n", - " if i in used_cycles:\n", - " continue\n", - "\n", - " cycle = cycles[i]\n", - "\n", - " edges_available = True\n", - " for j in range(len(cycle) - 1):\n", - " if cycle[j + 1] not in adj_list[cycle[j]]:\n", - " edges_available = False\n", - " break\n", - " if not edges_available:\n", - " continue\n", - "\n", - " if not ijkgood(cycle, [cycles[c] for c in used_cycles]):\n", - " continue\n", - "\n", - " if len(used_cycles) == TARGET:\n", - " return True\n", - "\n", - " used_cycles_cpy = used_cycles.copy()\n", - " used_cycles_cpy.add(i)\n", - "\n", - " adj_list_cpy = deepcopy(adj_list)\n", - " for j in range(len(cycle) - 1):\n", - " adj_list_cpy[cycle[j]].remove(cycle[j + 1])\n", - "\n", - " vertex_uses_cpy = vertex_uses.copy()\n", - " for j in cycle[:-1]:\n", - " vertex_uses_cpy[j] += 1\n", - "\n", - " if search(used_cycles_cpy, vertex_uses_cpy, adj_list_cpy):\n", - " return True\n", - " \n", - " return False\n", - "\n", - "for c in cycles:\n", - " print(\"Trying cycle:\", c)\n", - " adj_list = deepcopy(adjacency_list)\n", - " used_cycles = set()\n", - " used_cycles.add(cycles.index(c))\n", - " vertex_uses = [0] * NUM_VERTICES\n", - " for v in c[:-1]:\n", - " vertex_uses[v] = 1\n", - " for i in range(len(c) - 1):\n", - " adj_list[c[i]].remove(c[i + 1])\n", - "\n", - " if search(used_cycles, vertex_uses, adj_list):\n", - " print(\"Found solution:\")\n", - " for c in used_cycles:\n", - " print([v + 1 for v in cycles[c]])" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "SageMath 10.3", - "language": "sage", - "name": "SageMath-10.3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Balaban10/cycles.txt b/Balaban10/cycles.txt deleted file mode 100644 index 1ac69c0..0000000 --- a/Balaban10/cycles.txt +++ /dev/null @@ -1,529 +0,0 @@ -10 528 -0 2 4 26 27 42 41 14 16 18 0 -0 2 4 26 27 42 43 65 50 20 0 -0 2 4 26 27 28 55 68 47 18 0 -0 2 4 26 54 61 66 44 16 18 0 -0 2 4 26 54 61 37 36 21 20 0 -0 2 4 26 54 69 62 57 50 20 0 -0 2 4 26 54 69 49 48 47 18 0 -0 2 4 6 8 32 33 48 47 18 0 -0 2 4 6 8 32 58 65 50 20 0 -0 2 4 6 8 10 35 36 21 20 0 -0 2 4 6 8 10 12 14 16 18 0 -0 2 4 6 29 56 51 22 21 20 0 -0 2 4 6 29 56 63 68 47 18 0 -0 2 4 6 29 30 45 44 16 18 0 -0 2 4 6 29 30 31 57 50 20 0 -0 2 23 24 25 3 1 22 21 20 0 -0 2 23 24 25 53 66 44 16 18 0 -0 2 23 24 25 53 58 65 50 20 0 -0 2 23 24 39 40 63 68 47 18 0 -0 2 23 24 39 38 12 14 16 18 0 -0 2 23 24 39 38 62 57 50 20 0 -0 2 23 52 59 64 41 14 16 18 0 -0 2 23 52 59 64 51 22 21 20 0 -0 2 23 52 59 34 33 48 47 18 0 -0 2 23 52 67 46 45 44 16 18 0 -0 2 23 52 67 60 35 36 21 20 0 -0 2 23 52 67 60 55 68 47 18 0 -0 18 16 44 66 61 37 36 21 20 0 -0 18 16 44 66 61 54 26 4 2 0 -0 18 16 44 66 53 25 24 23 2 0 -0 18 16 44 66 53 58 65 50 20 0 -0 18 16 44 45 46 67 52 23 2 0 -0 18 16 44 45 30 29 6 4 2 0 -0 18 16 44 45 30 31 57 50 20 0 -0 18 16 14 41 64 51 22 21 20 0 -0 18 16 14 41 64 59 52 23 2 0 -0 18 16 14 41 42 27 26 4 2 0 -0 18 16 14 41 42 43 65 50 20 0 -0 18 16 14 12 10 8 6 4 2 0 -0 18 16 14 12 10 35 36 21 20 0 -0 18 16 14 12 38 62 57 50 20 0 -0 18 16 14 12 38 39 24 23 2 0 -0 18 47 48 33 32 8 6 4 2 0 -0 18 47 48 33 32 58 65 50 20 0 -0 18 47 48 33 34 59 52 23 2 0 -0 18 47 48 49 19 1 22 21 20 0 -0 18 47 48 49 69 62 57 50 20 0 -0 18 47 48 49 69 54 26 4 2 0 -0 18 47 68 63 40 39 24 23 2 0 -0 18 47 68 63 56 51 22 21 20 0 -0 18 47 68 63 56 29 6 4 2 0 -0 18 47 68 55 28 27 26 4 2 0 -0 18 47 68 55 60 67 52 23 2 0 -0 18 47 68 55 60 35 36 21 20 0 -0 20 50 65 43 42 27 26 4 2 0 -0 20 50 65 43 42 41 14 16 18 0 -0 20 50 65 58 32 8 6 4 2 0 -0 20 50 65 58 32 33 48 47 18 0 -0 20 50 65 58 53 25 24 23 2 0 -0 20 50 65 58 53 66 44 16 18 0 -0 20 50 57 62 69 49 48 47 18 0 -0 20 50 57 62 69 54 26 4 2 0 -0 20 50 57 62 38 12 14 16 18 0 -0 20 50 57 62 38 39 24 23 2 0 -0 20 50 57 31 30 29 6 4 2 0 -0 20 50 57 31 30 45 44 16 18 0 -0 20 21 36 35 10 8 6 4 2 0 -0 20 21 36 35 10 12 14 16 18 0 -0 20 21 36 35 60 67 52 23 2 0 -0 20 21 36 35 60 55 68 47 18 0 -0 20 21 36 37 61 66 44 16 18 0 -0 20 21 36 37 61 54 26 4 2 0 -0 20 21 22 1 19 49 48 47 18 0 -0 20 21 22 1 3 25 24 23 2 0 -0 20 21 22 51 64 41 14 16 18 0 -0 20 21 22 51 64 59 52 23 2 0 -0 20 21 22 51 56 29 6 4 2 0 -0 20 21 22 51 56 63 68 47 18 0 -1 19 17 46 67 52 59 64 51 22 1 -1 19 17 46 67 52 23 24 25 3 1 -1 19 17 46 67 60 35 36 21 22 1 -1 19 17 46 67 60 55 28 5 3 1 -1 19 17 46 45 44 66 53 25 3 1 -1 19 17 46 45 30 29 56 51 22 1 -1 19 17 46 45 30 31 7 5 3 1 -1 19 17 15 43 65 50 20 21 22 1 -1 19 17 15 43 65 58 53 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325 331 332 337 342 355 356 383 387 393 394 398 415 416 417 422 423 424 425 426 427 435 445 464 470 472 474 478 480 496 497 498 499 500 503 512 514 516 518 526 527 -78 1 8 17 30 37 43 54 55 56 57 58 59 85 86 128 129 148 149 176 184 196 197 200 211 223 240 247 265 268 275 279 280 296 297 298 302 307 313 314 330 365 366 368 374 378 396 403 405 412 413 420 430 432 433 437 438 439 440 441 442 464 465 468 470 485 486 488 489 492 494 507 508 510 512 513 514 524 525 -78 3 16 27 28 29 30 59 70 82 102 124 125 126 146 155 165 177 183 186 192 193 194 204 205 212 219 248 264 277 289 300 301 304 311 315 334 339 353 360 364 366 372 373 374 382 386 390 391 419 420 428 430 437 442 446 448 451 452 459 462 465 468 476 482 484 487 489 492 506 507 508 509 511 515 520 521 524 525 -78 24 25 26 31 52 68 78 79 80 81 109 120 134 142 154 159 163 173 174 175 179 188 230 231 235 243 250 262 271 288 294 305 322 323 329 333 341 342 343 351 354 356 363 370 402 404 409 410 422 427 435 436 444 445 450 454 456 457 460 461 472 474 476 479 482 483 497 499 500 502 503 504 517 519 520 521 526 527 -78 2 12 18 26 48 49 50 51 52 53 69 77 96 97 107 108 140 141 178 189 202 218 227 228 229 233 236 242 244 251 260 261 291 306 316 326 344 345 349 352 359 371 384 389 400 401 402 407 410 414 417 418 425 429 449 450 454 455 457 461 473 475 479 483 490 495 496 498 502 504 516 517 518 519 522 523 526 527 -78 5 6 46 47 60 61 98 99 100 101 102 103 106 116 123 125 147 150 156 169 207 208 209 210 215 220 226 241 269 278 282 283 292 308 318 335 340 348 361 362 376 377 380 381 382 388 390 395 406 408 433 434 439 443 448 451 458 459 462 463 466 469 484 487 488 490 494 495 506 509 510 511 513 515 522 523 524 525 diff --git a/Balaban10/explore.ipynb b/Balaban10/explore.ipynb deleted file mode 100644 index 07810b8..0000000 --- a/Balaban10/explore.ipynb +++ /dev/null @@ -1,1162 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import networkx as nx\n", - "import matplotlib.pyplot as plt\n", - "from sage.all import *" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "CYCLE_LENGTH = 10 # length of the cycles to fit onto the graph" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 176 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# instantiate a balaban 10-cage\n", - "g = graphs.Balaban10Cage(embedding=2)\n", - "g.show(figsize=(10,10))" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NUM_EDGES 105\n", - "CYCLES TO FIT 21\n", - "NUM_VERTICES 70\n" - ] - } - ], - "source": [ - "# get the edges of the graph\n", - "NUM_EDGES = len(g.edges())\n", - "NUM_VERTICES = len(g.vertices())\n", - "print(\"NUM_EDGES\", NUM_EDGES)\n", - "print(\"CYCLES TO FIT\", 2 * NUM_EDGES / CYCLE_LENGTH)\n", - "print(\"NUM_VERTICES\", NUM_VERTICES)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[[1, 69, 61],\n", - " [0, 2, 46],\n", - " [1, 3, 53],\n", - " [2, 32, 4],\n", - " [3, 17, 5],\n", - " [4, 6, 40],\n", - " [5, 7, 63],\n", - " [6, 48, 8],\n", - " [7, 9, 27],\n", - " [8, 34, 10],\n", - " [9, 19, 11],\n", - " [10, 52, 12],\n", - " [11, 41, 13],\n", - " [12, 30, 14],\n", - " [13, 15, 47],\n", - " [14, 16, 36],\n", - " [15, 17, 25],\n", - " [4, 16, 18],\n", - " [17, 19, 57],\n", - " [10, 18, 20],\n", - " [19, 21, 45],\n", - " [20, 38, 22],\n", - " [21, 23, 31],\n", - " [22, 24, 62],\n", - " [23, 51, 25],\n", - " [16, 24, 26],\n", - " [25, 43, 27],\n", - " [8, 26, 28],\n", - " [27, 69, 29],\n", - " [28, 56, 30],\n", - " [13, 29, 31],\n", - " [22, 30, 32],\n", - " [3, 31, 33],\n", - " [32, 34, 66],\n", - " [9, 33, 35],\n", - " [34, 36, 60],\n", - " [15, 35, 37],\n", - " [36, 38, 54],\n", - " [21, 37, 39],\n", - " [38, 68, 40],\n", - " [5, 39, 41],\n", - " [12, 40, 42],\n", - " [41, 43, 59],\n", - " [26, 42, 44],\n", - " [43, 65, 45],\n", - " [20, 44, 46],\n", - " [1, 45, 47],\n", - " [14, 46, 48],\n", - " [7, 47, 49],\n", - " [48, 50, 58],\n", - " [49, 67, 51],\n", - " [24, 50, 52],\n", - " [11, 51, 53],\n", - " [2, 52, 54],\n", - " [37, 53, 55],\n", - " [54, 64, 56],\n", - " [29, 55, 57],\n", - " [18, 56, 58],\n", - " [49, 57, 59],\n", - " [42, 58, 60],\n", - " [35, 59, 61],\n", - " [0, 60, 62],\n", - " [23, 61, 63],\n", - " [6, 62, 64],\n", - " [55, 63, 65],\n", - " [44, 64, 66],\n", - " [33, 65, 67],\n", - " [50, 66, 68],\n", - " [39, 67, 69],\n", - " [0, 28, 68]]" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# convert edges list to adjacency list\n", - "adjacency_list = [[] for _ in range(NUM_VERTICES)]\n", - "for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - "adjacency_list" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# visualize adjacency list with networkx\n", - "G = nx.Graph()\n", - "for i in range(NUM_VERTICES):\n", - " G.add_node(i)\n", - "for i in range(NUM_VERTICES):\n", - " for j in adjacency_list[i]:\n", - " G.add_edge(i, j)\n", - "pos = {}\n", - "for i in range(NUM_VERTICES):\n", - " pos[i] = (i % CYCLE_LENGTH, i // CYCLE_LENGTH)\n", - "nx.draw(G, pos, with_labels=True)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [], - "source": [ - "# save to adjacency_list.txt\n", - "with open('adjacency_list.txt', 'w') as f:\n", - " f.write(f'{NUM_VERTICES} {NUM_EDGES}\\n')\n", - " for i in range(NUM_VERTICES):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "78\n" - ] - } - ], - "source": [ - "# generate all cycles of length CYCLE_LENGTH starting at vertex 0\n", - "cycles = [ c for c in g.to_directed().all_simple_cycles(starting_vertices=[0],max_length=CYCLE_LENGTH) if len(c) == CYCLE_LENGTH + 1 ]\n", - "print(len(cycles))" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "cycles[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [], - "source": [ - "# make sure we are including cycles in both directions\n", - "for c in cycles:\n", - " assert list(reversed(c)) in cycles" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 176 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# visualize the first cycle using sage\n", - "def visualize(cycle, g):\n", - " for e in g.edges():\n", - " try:\n", - " i = cycle[:-1].index(e[0])\n", - " j = cycle[:-1].index(e[1])\n", - "\n", - " if abs(i - j) == 1 or abs(i - j) == 9:\n", - " g.set_edge_label(e[0], e[1], 1) # in cycle\n", - " else:\n", - " g.set_edge_label(e[0], e[1], 0) # not in cycle\n", - " except ValueError:\n", - " g.set_edge_label(e[0], e[1], 0) # not in cycle\n", - " g.plot(edge_colors=g._color_by_label({1: \"blue\", 0: \"black\"})).show()\n", - "\n", - "visualize(cycles[0], g)" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [], - "source": [ - "# uncomment to print out all cycles from starting vertex 0 to manually inspect\n", - "# for cycle in undirected_cycles:\n", - "# visualize(cycle, g)" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# plot number of CYCLE_LENGTH length cycles containing each vertex\n", - "num_cycles_by_vertex = [0] * NUM_VERTICES\n", - "# with open('cycles_by_vertex.txt', 'w') as f:\n", - "cycles_by_vertex = []\n", - "for v in g.vertices():\n", - " cycles = [ c for c in g.to_directed().all_simple_cycles(starting_vertices=[v],max_length=CYCLE_LENGTH) if len(c) == CYCLE_LENGTH + 1 ]\n", - " num_cycles_by_vertex[v] = len(cycles)\n", - " cycles_by_vertex.append(cycles)\n", - " # f.write(f'{max(num_cycles_by_vertex)}\\n')\n", - " # for cycles in cycles_by_vertex:\n", - " # f.write(f'{len(cycles)}:')\n", - " # for c in cycles:\n", - " # f.write(f'{\" \".join(map(str, c))};')\n", - " # f.write('\\n')\n", - "\n", - "plt.bar(range(NUM_VERTICES), num_cycles_by_vertex)\n", - "plt.ylim(min(num_cycles_by_vertex) - 1, max(num_cycles_by_vertex) + 1)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "528\n" - ] - } - ], - "source": [ - "# save all CYCLE_LENGTH length cycles to ten_cycles.txt\n", - "with open('cycles.txt', 'w') as f:\n", - " cycles = [ c for c in g.to_directed().all_simple_cycles(max_length=CYCLE_LENGTH) if len(c) == CYCLE_LENGTH + 1 ]\n", - " f.write(f'{CYCLE_LENGTH} {len(cycles)}\\n')\n", - " for c in cycles:\n", - " f.write(f'{\" \".join(map(str, c))}\\n')\n", - " print(len(cycles))" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# organize cycles by vertex\n", - "cycles_by_vertex = [[] for _ in range(NUM_VERTICES)]\n", - "for i, c in enumerate(cycles):\n", - " for v in c[:-1]:\n", - " cycles_by_vertex[v].append(i)\n", - "\n", - "with open('cycles_by_vertex.txt', 'w') as f:\n", - " f.write(f'{max([len(c) for c in cycles_by_vertex])}\\n')\n", - " for vertex_cycles in cycles_by_vertex:\n", - " f.write(f'{len(vertex_cycles)} ')\n", - " for c in vertex_cycles:\n", - " f.write(f'{c} ')\n", - " f.write('\\n')\n", - "\n", - "# plot as bar graph\n", - "plt.bar(range(NUM_VERTICES), [len(c) for c in cycles_by_vertex])\n", - "plt.ylim(min([len(c) for c in cycles_by_vertex]) - 1, max([len(c) for c in cycles_by_vertex]) + 1)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "New max used cycles: 1:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "New max used cycles: 2:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "New max used cycles: 3:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "New max used cycles: 4:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "New max used cycles: 5:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 6:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 7:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[4, 17, 18, 57, 56, 55, 64, 63, 6, 5, 4]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 8:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[4, 17, 18, 57, 56, 55, 64, 63, 6, 5, 4]\n", - "[5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 9:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[4, 17, 18, 57, 56, 55, 64, 63, 6, 5, 4]\n", - "[5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5]\n", - "[6, 63, 62, 23, 24, 51, 50, 49, 48, 7, 6]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 10:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[4, 17, 18, 57, 56, 55, 64, 63, 6, 5, 4]\n", - "[5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5]\n", - "[7, 48, 47, 14, 15, 36, 35, 34, 9, 8, 7]\n", - "[6, 63, 62, 23, 24, 51, 50, 49, 48, 7, 6]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 11:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[8, 9, 10, 19, 18, 17, 16, 25, 26, 27, 8]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[4, 17, 18, 57, 56, 55, 64, 63, 6, 5, 4]\n", - "[5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5]\n", - "[7, 48, 47, 14, 15, 36, 35, 34, 9, 8, 7]\n", - "[6, 63, 62, 23, 24, 51, 50, 49, 48, 7, 6]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 12:\n", - "[4, 17, 16, 15, 14, 47, 48, 7, 6, 5, 4]\n", - "[0, 69, 68, 39, 38, 37, 36, 35, 60, 61, 0]\n", - "[1, 46, 47, 14, 13, 12, 11, 52, 53, 2, 1]\n", - "[0, 1, 2, 3, 32, 31, 30, 29, 28, 69, 0]\n", - "[2, 53, 54, 55, 56, 57, 18, 17, 4, 3, 2]\n", - "[5, 6, 63, 62, 61, 60, 59, 42, 41, 40, 5]\n", - "[9, 10, 19, 18, 57, 58, 59, 60, 35, 34, 9]\n", - "[8, 27, 26, 25, 24, 51, 52, 11, 10, 9, 8]\n", - "[0, 61, 62, 23, 22, 21, 20, 45, 46, 1, 0]\n", - "[3, 4, 5, 40, 39, 68, 67, 66, 33, 32, 3]\n", - "[6, 7, 8, 9, 34, 33, 66, 65, 64, 63, 6]\n", - "[7, 48, 49, 50, 67, 68, 69, 28, 27, 8, 7]\n", - "New max used cycles: 13:\n", - "[4, 17, 16, 15, 14, 47, 48, 7, 6, 5, 4]\n", - "[0, 69, 68, 39, 38, 37, 36, 35, 60, 61, 0]\n", - "[1, 46, 47, 14, 13, 12, 11, 52, 53, 2, 1]\n", - "[0, 1, 2, 3, 32, 31, 30, 29, 28, 69, 0]\n", - "[2, 53, 54, 55, 56, 57, 18, 17, 4, 3, 2]\n", - "[5, 6, 63, 62, 61, 60, 59, 42, 41, 40, 5]\n", - "[9, 10, 19, 18, 57, 58, 59, 60, 35, 34, 9]\n", - "[8, 27, 26, 25, 24, 51, 52, 11, 10, 9, 8]\n", - "[10, 11, 12, 41, 42, 43, 44, 45, 20, 19, 10]\n", - "[0, 61, 62, 23, 22, 21, 20, 45, 46, 1, 0]\n", - "[3, 4, 5, 40, 39, 68, 67, 66, 33, 32, 3]\n", - "[6, 7, 8, 9, 34, 33, 66, 65, 64, 63, 6]\n", - "[7, 48, 49, 50, 67, 68, 69, 28, 27, 8, 7]\n", - "New max used cycles: 14:\n", - "[9, 10, 19, 18, 57, 58, 59, 60, 35, 34, 9]\n", - "[0, 69, 68, 39, 38, 37, 36, 35, 60, 61, 0]\n", - "[2, 53, 52, 51, 24, 25, 16, 17, 4, 3, 2]\n", - "[0, 1, 2, 3, 32, 31, 30, 29, 28, 69, 0]\n", - "[4, 17, 18, 19, 20, 21, 38, 39, 40, 5, 4]\n", - "[1, 46, 47, 14, 15, 36, 37, 54, 53, 2, 1]\n", - "[5, 40, 41, 12, 13, 14, 47, 48, 7, 6, 5]\n", - "[7, 48, 49, 50, 51, 52, 11, 10, 9, 8, 7]\n", - "[11, 52, 53, 54, 55, 56, 29, 30, 13, 12, 11]\n", - "[10, 11, 12, 41, 42, 43, 44, 45, 20, 19, 10]\n", - "[0, 61, 62, 23, 22, 21, 20, 45, 46, 1, 0]\n", - "[3, 4, 5, 6, 63, 64, 65, 66, 33, 32, 3]\n", - "[6, 7, 8, 27, 26, 25, 24, 23, 62, 63, 6]\n", - "[8, 9, 34, 33, 66, 67, 68, 69, 28, 27, 8]\n" - ] - } - ], - "source": [ - "# check if 21 10-cycles are enough to cover the graph (use each directed edge exactly once)\n", - "# only works for CYCLE_LENGTH = 10\n", - "from copy import deepcopy\n", - "VERTEX_USE_LIMIT = 3\n", - "max_used_cycles = 0\n", - "\n", - "def x_in_y(query, base):\n", - " try:\n", - " l = len(query)\n", - " except TypeError:\n", - " l = 1\n", - " query = type(base)((query,))\n", - "\n", - " for i in range(len(base)):\n", - " if base[i:i+l] == query:\n", - " return True\n", - " return False\n", - "\n", - "def ijkgood(c, solution):\n", - " c = c.copy() + [c[1]]\n", - " for i in range(CYCLE_LENGTH):\n", - " for c2 in solution:\n", - " c2 = c2.copy() + [c2[1]]\n", - " if x_in_y([c[i + 2], c[i + 1], c[i]], c2):\n", - " return False\n", - " return True\n", - "\n", - "def search(used_cycles, vertex_uses, adj_list) -> bool:\n", - " TARGET = 2 * NUM_EDGES // CYCLE_LENGTH\n", - "\n", - " global max_used_cycles\n", - " if len(used_cycles) > max_used_cycles:\n", - " print(f\"New max used cycles: {len(used_cycles)}:\")\n", - " max_used_cycles = len(used_cycles)\n", - " for c in used_cycles:\n", - " print(cycles[c])\n", - " \n", - " # most used vertex not at limit\n", - " vertex = vertex_uses.index(max(filter(lambda x: x < VERTEX_USE_LIMIT, vertex_uses)))\n", - "\n", - " for i in cycles_by_vertex[vertex]:\n", - " if i in used_cycles:\n", - " continue\n", - "\n", - " cycle = cycles[i]\n", - "\n", - " edges_available = True\n", - " for j in range(CYCLE_LENGTH):\n", - " if cycle[j + 1] not in adj_list[cycle[j]]:\n", - " edges_available = False\n", - " break\n", - " if not edges_available:\n", - " continue\n", - "\n", - " if not ijkgood(cycle, [cycles[c] for c in used_cycles]):\n", - " continue\n", - "\n", - " if len(used_cycles) == TARGET - 1:\n", - " return True\n", - "\n", - " used_cycles_cpy = used_cycles.copy()\n", - " used_cycles_cpy.add(i)\n", - "\n", - " adj_list_cpy = deepcopy(adj_list)\n", - " for j in range(CYCLE_LENGTH):\n", - " adj_list_cpy[cycle[j]].remove(cycle[j + 1])\n", - "\n", - " vertex_uses_cpy = vertex_uses.copy()\n", - " for j in cycle[:-1]:\n", - " vertex_uses_cpy[j] += 1\n", - "\n", - " if search(used_cycles_cpy, vertex_uses_cpy, adj_list_cpy):\n", - " return True\n", - " \n", - " return False\n", - "\n", - "for c in cycles:\n", - " adj_list = deepcopy(adjacency_list)\n", - " used_cycles = set()\n", - " used_cycles.add(cycles.index(c))\n", - " vertex_uses = [0] * NUM_VERTICES\n", - " for v in c[:-1]:\n", - " vertex_uses[v] = 1\n", - " for i in range(CYCLE_LENGTH):\n", - " adj_list[c[i]].remove(c[i + 1])\n", - "\n", - " if search(used_cycles, vertex_uses, adj_list):\n", - " print(\"Found solution:\")\n", - " for c in used_cycles:\n", - " print(cycles[c])" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "solution = [\n", - " [9, 10, 19, 18, 57, 58, 59, 60, 35, 34, 9],\n", - " [0, 69, 68, 39, 38, 37, 36, 35, 60, 61, 0],\n", - " [2, 53, 52, 51, 24, 25, 16, 17, 4, 3, 2],\n", - " [0, 1, 2, 3, 32, 31, 30, 29, 28, 69, 0],\n", - " [4, 17, 18, 19, 20, 21, 38, 39, 40, 5, 4],\n", - " [1, 46, 47, 14, 15, 36, 37, 54, 53, 2, 1],\n", - " [5, 40, 41, 12, 13, 14, 47, 48, 7, 6, 5],\n", - " [7, 48, 49, 50, 51, 52, 11, 10, 9, 8, 7],\n", - " [11, 52, 53, 54, 55, 56, 29, 30, 13, 12, 11],\n", - " [10, 11, 12, 41, 42, 43, 44, 45, 20, 19, 10],\n", - " [0, 61, 62, 23, 22, 21, 20, 45, 46, 1, 0],\n", - " [3, 4, 5, 6, 63, 64, 65, 66, 33, 32, 3],\n", - " [6, 7, 8, 27, 26, 25, 24, 23, 62, 63, 6],\n", - " [8, 9, 34, 33, 66, 67, 68, 69, 28, 27, 8],\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "adj_list = deepcopy(adjacency_list)\n", - "used_cycles = set()\n", - "\n", - "max_used_cycles = 0\n", - "def search_complete(used_cycles, adj_list):\n", - " TARGET = 2 * NUM_EDGES // CYCLE_LENGTH\n", - " if len(used_cycles) == TARGET:\n", - " return True\n", - " \n", - " global max_used_cycles\n", - " if len(used_cycles) > max_used_cycles:\n", - " print(f\"New max used cycles: {len(used_cycles)}:\")\n", - " max_used_cycles = len(used_cycles)\n", - " for c in used_cycles:\n", - " print(cycles[c])\n", - "\n", - " for i, c in enumerate(cycles):\n", - " if i in used_cycles:\n", - " continue\n", - "\n", - " edges_available = True\n", - " for j in range(len(c) - 1):\n", - " if c[j + 1] not in adj_list[c[j]]:\n", - " edges_available = False\n", - " break\n", - " if not edges_available:\n", - " continue\n", - "\n", - " if not ijkgood(c, [cycles[i] for i in used_cycles]):\n", - " continue\n", - "\n", - " used_cycles_cpy = used_cycles.copy()\n", - " used_cycles_cpy.add(i)\n", - "\n", - " adj_list_cpy = deepcopy(adj_list)\n", - " for j in range(len(c) - 1):\n", - " adj_list_cpy[c[j]].remove(c[j + 1])\n", - "\n", - " if search_complete(used_cycles_cpy, adj_list_cpy):\n", - " return True\n", - " \n", - " return False\n", - "\n", - "search_complete(used_cycles, adj_list)" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [], - "source": [ - "cycles = [ c for c in g.to_directed().all_simple_cycles(max_length=17) if len(c) > 10]" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [], - "source": [ - "# sort cycles by ascending length\n", - "cycles.sort(key=lambda x: len(x))" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [], - "source": [ - "cycles_by_vertex = [[] for _ in range(NUM_VERTICES)]\n", - "for i, c in enumerate(cycles):\n", - " for v in c[:-1]:\n", - " cycles_by_vertex[v].append(i)" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Trying cycle: [0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "New max used cycles: 1:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "New max used cycles: 2:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "New max used cycles: 3:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "New max used cycles: 4:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "New max used cycles: 5:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 6:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 7:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[4, 17, 18, 57, 56, 55, 64, 63, 6, 5, 4]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 8:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[4, 17, 18, 57, 56, 55, 64, 63, 6, 5, 4]\n", - "[5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 9:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[4, 17, 18, 57, 56, 55, 64, 63, 6, 5, 4]\n", - "[5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5]\n", - "[6, 63, 62, 23, 24, 51, 50, 49, 48, 7, 6]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 10:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[4, 17, 18, 57, 56, 55, 64, 63, 6, 5, 4]\n", - "[5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5]\n", - "[7, 48, 47, 14, 15, 36, 35, 34, 9, 8, 7]\n", - "[6, 63, 62, 23, 24, 51, 50, 49, 48, 7, 6]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 11:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[8, 9, 10, 19, 18, 17, 16, 25, 26, 27, 8]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[4, 17, 18, 57, 56, 55, 64, 63, 6, 5, 4]\n", - "[5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5]\n", - "[7, 48, 47, 14, 15, 36, 35, 34, 9, 8, 7]\n", - "[6, 63, 62, 23, 24, 51, 50, 49, 48, 7, 6]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 12:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[9, 34, 33, 66, 65, 44, 43, 26, 25, 16, 15, 14, 13, 12, 11, 10, 9]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5]\n", - "[7, 48, 47, 14, 15, 36, 35, 34, 9, 8, 7]\n", - "[4, 17, 18, 19, 20, 21, 38, 37, 54, 55, 64, 63, 6, 5, 4]\n", - "[6, 63, 62, 23, 24, 51, 50, 49, 48, 7, 6]\n", - "[8, 9, 10, 19, 18, 57, 56, 55, 54, 53, 52, 51, 24, 25, 26, 27, 8]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 13:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[9, 34, 33, 66, 65, 44, 43, 26, 25, 16, 15, 14, 13, 12, 11, 10, 9]\n", - "[11, 12, 41, 42, 59, 60, 35, 36, 37, 38, 39, 68, 67, 50, 51, 52, 11]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5]\n", - "[7, 48, 47, 14, 15, 36, 35, 34, 9, 8, 7]\n", - "[4, 17, 18, 19, 20, 21, 38, 37, 54, 55, 64, 63, 6, 5, 4]\n", - "[6, 63, 62, 23, 24, 51, 50, 49, 48, 7, 6]\n", - "[8, 9, 10, 19, 18, 57, 56, 55, 54, 53, 52, 51, 24, 25, 26, 27, 8]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "New max used cycles: 14:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[9, 34, 33, 66, 65, 44, 43, 26, 25, 16, 15, 14, 13, 12, 11, 10, 9]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5]\n", - "[7, 48, 47, 14, 15, 36, 35, 34, 9, 8, 7]\n", - "[11, 12, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 11]\n", - "[4, 17, 18, 19, 20, 21, 38, 37, 54, 55, 64, 63, 6, 5, 4]\n", - "[6, 63, 62, 23, 22, 31, 30, 29, 56, 57, 58, 49, 48, 7, 6]\n", - "[8, 9, 10, 19, 18, 57, 56, 55, 54, 53, 52, 51, 24, 25, 26, 27, 8]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2]\n", - "[16, 25, 24, 23, 62, 61, 60, 59, 58, 57, 18, 17, 16]\n", - "New max used cycles: 15:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[2, 53, 54, 55, 64, 63, 6, 5, 4, 3, 2]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[11, 12, 41, 40, 39, 68, 67, 50, 51, 52, 11]\n", - "[4, 5, 40, 41, 42, 43, 26, 25, 16, 17, 4]\n", - "[5, 6, 7, 48, 49, 58, 57, 18, 19, 20, 21, 38, 39, 40, 5]\n", - "[8, 27, 28, 69, 68, 39, 38, 37, 36, 15, 14, 13, 12, 11, 10, 9, 8]\n", - "[6, 63, 62, 23, 24, 25, 26, 27, 8, 7, 6]\n", - "[7, 8, 9, 34, 33, 66, 65, 44, 45, 46, 47, 48, 7]\n", - "[12, 13, 30, 31, 22, 23, 62, 61, 60, 59, 42, 41, 12]\n", - "[14, 15, 16, 25, 24, 51, 50, 49, 48, 47, 14]\n", - "[3, 4, 17, 18, 57, 56, 55, 54, 37, 38, 21, 22, 31, 32, 3]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[9, 10, 19, 18, 17, 16, 15, 36, 35, 34, 9]\n", - "New max used cycles: 16:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[2, 53, 54, 55, 64, 63, 6, 5, 4, 3, 2]\n", - "[7, 48, 49, 58, 59, 42, 43, 26, 27, 8, 7]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[4, 5, 40, 39, 38, 37, 36, 35, 34, 9, 10, 19, 18, 17, 4]\n", - "[18, 19, 20, 21, 22, 23, 62, 61, 60, 59, 58, 57, 18]\n", - "[16, 17, 18, 57, 56, 29, 28, 27, 26, 25, 16]\n", - "[6, 63, 62, 23, 24, 25, 26, 43, 44, 45, 46, 47, 48, 7, 6]\n", - "[3, 4, 17, 16, 15, 36, 37, 54, 53, 52, 51, 24, 23, 22, 31, 32, 3]\n", - "[5, 6, 7, 8, 9, 34, 33, 66, 65, 44, 43, 42, 41, 40, 5]\n", - "[12, 41, 42, 59, 60, 35, 36, 15, 14, 13, 12]\n", - "[14, 15, 16, 25, 24, 51, 50, 49, 48, 47, 14]\n", - "[8, 27, 28, 69, 68, 39, 40, 41, 12, 11, 10, 9, 8]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[11, 12, 13, 30, 31, 22, 21, 38, 39, 68, 67, 50, 51, 52, 11]\n", - "New max used cycles: 17:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[2, 53, 54, 55, 64, 63, 6, 5, 4, 3, 2]\n", - "[22, 23, 24, 51, 50, 67, 66, 33, 32, 31, 22]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[5, 6, 7, 48, 49, 58, 59, 42, 41, 40, 5]\n", - "[3, 4, 17, 18, 19, 20, 21, 38, 39, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[6, 63, 62, 23, 22, 21, 20, 45, 44, 43, 26, 27, 8, 7, 6]\n", - "[7, 8, 9, 34, 33, 66, 65, 44, 45, 46, 47, 48, 7]\n", - "[1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1]\n", - "[16, 25, 24, 23, 62, 61, 60, 59, 58, 57, 18, 17, 16]\n", - "[9, 10, 19, 18, 57, 56, 29, 28, 27, 26, 25, 16, 15, 36, 35, 34, 9]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[11, 12, 41, 42, 43, 44, 65, 64, 55, 56, 57, 58, 49, 50, 51, 52, 11]\n", - "[8, 27, 28, 69, 68, 39, 38, 37, 36, 15, 14, 13, 12, 11, 10, 9, 8]\n", - "[24, 25, 26, 43, 42, 59, 60, 35, 36, 37, 54, 53, 52, 51, 24]\n", - "[21, 22, 31, 30, 29, 56, 55, 54, 37, 38, 21]\n", - "[4, 5, 40, 39, 68, 67, 50, 49, 48, 47, 14, 15, 16, 17, 4]\n", - "New max used cycles: 18:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[22, 23, 24, 51, 50, 67, 66, 33, 32, 31, 22]\n", - "[11, 52, 53, 54, 37, 36, 15, 14, 13, 12, 11]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[1, 46, 45, 44, 65, 64, 55, 54, 53, 2, 1]\n", - "[9, 10, 19, 18, 17, 16, 15, 36, 35, 34, 9]\n", - "[7, 48, 49, 50, 51, 52, 11, 10, 9, 8, 7]\n", - "[21, 22, 31, 30, 29, 56, 57, 58, 59, 60, 35, 36, 37, 38, 21]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[4, 17, 18, 57, 56, 55, 64, 63, 6, 5, 4]\n", - "[18, 19, 20, 21, 38, 39, 68, 67, 50, 49, 58, 57, 18]\n", - "[10, 11, 12, 41, 42, 43, 44, 45, 20, 19, 10]\n", - "[2, 53, 52, 51, 24, 25, 16, 17, 4, 3, 2]\n", - "[14, 15, 16, 25, 26, 43, 42, 59, 58, 49, 48, 47, 14]\n", - "[8, 9, 34, 33, 66, 65, 44, 43, 26, 27, 8]\n", - "[6, 63, 62, 23, 22, 21, 20, 45, 46, 47, 48, 7, 6]\n", - "New max used cycles: 19:\n", - "[0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0]\n", - "[22, 23, 24, 51, 50, 67, 66, 33, 32, 31, 22]\n", - "[15, 16, 25, 26, 43, 42, 59, 60, 35, 36, 15]\n", - "[5, 6, 63, 62, 23, 22, 21, 38, 39, 40, 5]\n", - "[7, 48, 47, 14, 15, 36, 37, 38, 21, 20, 19, 10, 9, 8, 7]\n", - "[0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0]\n", - "[6, 7, 8, 27, 28, 69, 68, 39, 38, 37, 54, 55, 64, 63, 6]\n", - "[1, 46, 45, 20, 21, 22, 31, 30, 29, 56, 55, 54, 53, 2, 1]\n", - "[18, 19, 20, 45, 44, 65, 64, 55, 56, 57, 18]\n", - "[3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3]\n", - "[9, 10, 11, 52, 53, 54, 37, 36, 35, 34, 9]\n", - "[0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0]\n", - "[4, 17, 18, 57, 58, 49, 48, 7, 6, 5, 4]\n", - "[23, 62, 61, 60, 59, 58, 57, 56, 29, 28, 27, 26, 25, 24, 23]\n", - "[11, 12, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 11]\n", - "[10, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10]\n", - "[2, 53, 52, 51, 24, 25, 16, 17, 4, 3, 2]\n", - "[8, 9, 34, 33, 66, 65, 44, 43, 26, 27, 8]\n", - "[39, 68, 67, 50, 49, 58, 59, 42, 41, 40, 39]\n" - ] - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[51], line 89\u001b[0m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(c) \u001b[38;5;241m-\u001b[39m Integer(\u001b[38;5;241m1\u001b[39m)):\n\u001b[1;32m 87\u001b[0m adj_list[c[i]]\u001b[38;5;241m.\u001b[39mremove(c[i \u001b[38;5;241m+\u001b[39m Integer(\u001b[38;5;241m1\u001b[39m)])\n\u001b[0;32m---> 89\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[43msearch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mused_cycles\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvertex_uses\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43madj_list\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 90\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFound solution:\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 91\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m c \u001b[38;5;129;01min\u001b[39;00m used_cycles:\n", - "Cell \u001b[0;32mIn[51], line 73\u001b[0m, in \u001b[0;36msearch\u001b[0;34m(used_cycles, vertex_uses, adj_list)\u001b[0m\n\u001b[1;32m 70\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m cycle[:\u001b[38;5;241m-\u001b[39mInteger(\u001b[38;5;241m1\u001b[39m)]:\n\u001b[1;32m 71\u001b[0m vertex_uses_cpy[j] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m Integer(\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m---> 73\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[43msearch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mused_cycles_cpy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvertex_uses_cpy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43madj_list_cpy\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n", - "Cell \u001b[0;32mIn[51], line 73\u001b[0m, in \u001b[0;36msearch\u001b[0;34m(used_cycles, vertex_uses, adj_list)\u001b[0m\n\u001b[1;32m 70\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m cycle[:\u001b[38;5;241m-\u001b[39mInteger(\u001b[38;5;241m1\u001b[39m)]:\n\u001b[1;32m 71\u001b[0m vertex_uses_cpy[j] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m Integer(\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m---> 73\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[43msearch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mused_cycles_cpy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvertex_uses_cpy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43madj_list_cpy\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n", - " \u001b[0;31m[... skipping similar frames: search at line 73 (3 times)]\u001b[0m\n", - "Cell \u001b[0;32mIn[51], line 73\u001b[0m, in \u001b[0;36msearch\u001b[0;34m(used_cycles, vertex_uses, adj_list)\u001b[0m\n\u001b[1;32m 70\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m cycle[:\u001b[38;5;241m-\u001b[39mInteger(\u001b[38;5;241m1\u001b[39m)]:\n\u001b[1;32m 71\u001b[0m vertex_uses_cpy[j] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m Integer(\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m---> 73\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[43msearch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mused_cycles_cpy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvertex_uses_cpy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43madj_list_cpy\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 74\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n", - "Cell \u001b[0;32mIn[51], line 49\u001b[0m, in \u001b[0;36msearch\u001b[0;34m(used_cycles, vertex_uses, adj_list)\u001b[0m\n\u001b[1;32m 46\u001b[0m cycle \u001b[38;5;241m=\u001b[39m cycles[i]\n\u001b[1;32m 48\u001b[0m edges_available \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[0;32m---> 49\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(cycle) \u001b[38;5;241m-\u001b[39m \u001b[43mInteger\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m):\n\u001b[1;32m 50\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cycle[j \u001b[38;5;241m+\u001b[39m Integer(\u001b[38;5;241m1\u001b[39m)] \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m adj_list[cycle[j]]:\n\u001b[1;32m 51\u001b[0m edges_available \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n", - "File \u001b[0;32msrc/cysignals/signals.pyx:341\u001b[0m, in \u001b[0;36mcysignals.signals.python_check_interrupt\u001b[0;34m()\u001b[0m\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] - } - ], - "source": [ - "from copy import deepcopy\n", - "VERTEX_USE_LIMIT = 3\n", - "max_used_cycles = 0\n", - "\n", - "def x_in_y(query, base):\n", - " try:\n", - " l = len(query)\n", - " except TypeError:\n", - " l = 1\n", - " query = type(base)((query,))\n", - "\n", - " for i in range(len(base)):\n", - " if base[i:i+l] == query:\n", - " return True\n", - " return False\n", - "\n", - "def ijkgood(c, solution):\n", - " c = c.copy() + [c[1]]\n", - " for i in range(len(c) - 2):\n", - " for c2 in solution:\n", - " c2 = c2.copy() + [c2[1]]\n", - " if x_in_y([c[i + 2], c[i + 1], c[i]], c2):\n", - " return False\n", - " return True\n", - "\n", - "def search(used_cycles, vertex_uses, adj_list) -> bool:\n", - " TARGET = 2 * NUM_EDGES // CYCLE_LENGTH\n", - "\n", - " global max_used_cycles\n", - " if len(used_cycles) > max_used_cycles:\n", - " print(f\"New max used cycles: {len(used_cycles)}:\")\n", - " max_used_cycles = len(used_cycles)\n", - " for c in used_cycles:\n", - " print(cycles[c])\n", - " \n", - " # most used vertex not at limit\n", - " m = list(filter(lambda x: x < VERTEX_USE_LIMIT, vertex_uses))\n", - " if not m:\n", - " return False\n", - " vertex = vertex_uses.index(max(m))\n", - "\n", - " for i in cycles_by_vertex[vertex]:\n", - " if i in used_cycles:\n", - " continue\n", - "\n", - " cycle = cycles[i]\n", - "\n", - " edges_available = True\n", - " for j in range(len(cycle) - 1):\n", - " if cycle[j + 1] not in adj_list[cycle[j]]:\n", - " edges_available = False\n", - " break\n", - " if not edges_available:\n", - " continue\n", - "\n", - " if not ijkgood(cycle, [cycles[c] for c in used_cycles]):\n", - " continue\n", - "\n", - " if len(used_cycles) == TARGET - 1:\n", - " return True\n", - "\n", - " used_cycles_cpy = used_cycles.copy()\n", - " used_cycles_cpy.add(i)\n", - "\n", - " adj_list_cpy = deepcopy(adj_list)\n", - " for j in range(len(cycle) - 1):\n", - " adj_list_cpy[cycle[j]].remove(cycle[j + 1])\n", - "\n", - " vertex_uses_cpy = vertex_uses.copy()\n", - " for j in cycle[:-1]:\n", - " vertex_uses_cpy[j] += 1\n", - "\n", - " if search(used_cycles_cpy, vertex_uses_cpy, adj_list_cpy):\n", - " return True\n", - " \n", - " return False\n", - "\n", - "for c in cycles[:528]:\n", - " print(\"Trying cycle:\", c)\n", - " adj_list = deepcopy(adjacency_list)\n", - " used_cycles = set()\n", - " used_cycles.add(cycles.index(c))\n", - " vertex_uses = [0] * NUM_VERTICES\n", - " for v in c[:-1]:\n", - " vertex_uses[v] = 1\n", - " for i in range(len(c) - 1):\n", - " adj_list[c[i]].remove(c[i + 1])\n", - "\n", - " if search(used_cycles, vertex_uses, adj_list):\n", - " print(\"Found solution:\")\n", - " for c in used_cycles:\n", - " print(cycles[c])" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 176 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "viz_cycles = [\n", - " [0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0], \n", - " [0, 1, 2, 3, 32, 33, 66, 67, 68, 69, 0], \n", - " [0, 61, 60, 59, 42, 41, 40, 39, 68, 69, 0], \n", - " [0, 69, 68, 67, 50, 49, 48, 47, 46, 1, 0], \n", - " [1, 46, 45, 20, 21, 38, 37, 54, 53, 2, 1], \n", - " [2, 53, 52, 11, 12, 13, 30, 31, 32, 3, 2], \n", - "]\n", - "\n", - "def is_in_cycle(e, cycle):\n", - " try:\n", - " i = cycle.index(e[0])\n", - " j = cycle.index(e[1])\n", - "\n", - " if abs(i - j) == 1 or abs(i - j) == 9:\n", - " return True\n", - " else:\n", - " return False\n", - " except ValueError:\n", - " return False\n", - "\n", - "for e in g.edges():\n", - " if is_in_cycle(e, viz_cycles[0]):\n", - " g.set_edge_label(e[0], e[1], 1)\n", - " elif is_in_cycle(e, viz_cycles[1]):\n", - " g.set_edge_label(e[0], e[1], 2)\n", - " elif is_in_cycle(e, viz_cycles[2]):\n", - " g.set_edge_label(e[0], e[1], 3)\n", - " elif is_in_cycle(e, viz_cycles[3]):\n", - " g.set_edge_label(e[0], e[1], 4)\n", - " elif is_in_cycle(e, viz_cycles[4]):\n", - " g.set_edge_label(e[0], e[1], 5)\n", - " elif is_in_cycle(e, viz_cycles[5]):\n", - " g.set_edge_label(e[0], e[1], 6)\n", - "\n", - "g.plot(edge_colors=g._color_by_label({0: \"black\", 1: \"blue\", 2: \"purple\", 3: \"red\", 4: \"green\", 5: \"orange\", 6: \"yellow\"})).show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "SageMath 10.3", - "language": "sage", - "name": "SageMath-10.3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Balaban10/generate.ipynb b/Balaban10/generate.ipynb deleted file mode 100644 index 2206c5e..0000000 --- a/Balaban10/generate.ipynb +++ /dev/null @@ -1,258 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "import networkx as nx\n", - "import matplotlib.pyplot as plt\n", - "from sage.all import *" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "CYCLE_LENGTH = 10 # length of the cycles to fit onto the graph" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 176 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# instantiate a balaban 10-cage\n", - "g = graphs.Balaban10Cage(embedding=2)\n", - "g.show(figsize=(10,10))" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "NUM_EDGES 105\n", - "CYCLES TO FIT 21\n", - "NUM_VERTICES 70\n" - ] - } - ], - "source": [ - "# get the edges of the graph\n", - "NUM_EDGES = len(g.edges())\n", - "NUM_VERTICES = len(g.vertices())\n", - "print(\"NUM_EDGES\", NUM_EDGES)\n", - "print(\"CYCLES TO FIT\", 2 * NUM_EDGES / CYCLE_LENGTH)\n", - "print(\"NUM_VERTICES\", NUM_VERTICES)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[[1, 69, 61],\n", - " [0, 2, 46],\n", - " [1, 3, 53],\n", - " [2, 32, 4],\n", - " [3, 17, 5],\n", - " [4, 6, 40],\n", - " [5, 7, 63],\n", - " [6, 48, 8],\n", - " [7, 9, 27],\n", - " [8, 34, 10],\n", - " [9, 19, 11],\n", - " [10, 52, 12],\n", - " [11, 41, 13],\n", - " [12, 30, 14],\n", - " [13, 15, 47],\n", - " [14, 16, 36],\n", - " [15, 17, 25],\n", - " [4, 16, 18],\n", - " [17, 19, 57],\n", - " [10, 18, 20],\n", - " [19, 21, 45],\n", - " [20, 38, 22],\n", - " [21, 23, 31],\n", - " [22, 24, 62],\n", - " [23, 51, 25],\n", - " [16, 24, 26],\n", - " [25, 43, 27],\n", - " [8, 26, 28],\n", - " [27, 69, 29],\n", - " [28, 56, 30],\n", - " [13, 29, 31],\n", - " [22, 30, 32],\n", - " [3, 31, 33],\n", - " [32, 34, 66],\n", - " [9, 33, 35],\n", - " [34, 36, 60],\n", - " [15, 35, 37],\n", - " [36, 38, 54],\n", - " [21, 37, 39],\n", - " [38, 68, 40],\n", - " [5, 39, 41],\n", - " [12, 40, 42],\n", - " [41, 43, 59],\n", - " [26, 42, 44],\n", - " [43, 65, 45],\n", - " [20, 44, 46],\n", - " [1, 45, 47],\n", - " [14, 46, 48],\n", - " [7, 47, 49],\n", - " [48, 50, 58],\n", - " [49, 67, 51],\n", - " [24, 50, 52],\n", - " [11, 51, 53],\n", - " [2, 52, 54],\n", - " [37, 53, 55],\n", - " [54, 64, 56],\n", - " [29, 55, 57],\n", - " [18, 56, 58],\n", - " [49, 57, 59],\n", - " [42, 58, 60],\n", - " [35, 59, 61],\n", - " [0, 60, 62],\n", - " [23, 61, 63],\n", - " [6, 62, 64],\n", - " [55, 63, 65],\n", - " [44, 64, 66],\n", - " [33, 65, 67],\n", - " [50, 66, 68],\n", - " [39, 67, 69],\n", - " [0, 28, 68]]" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# convert edges list to adjacency list\n", - "adjacency_list = [[] for _ in range(NUM_VERTICES)]\n", - "for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - "adjacency_list" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "# save to adjacency_list.txt\n", - "with open('adjacency_list.txt', 'w') as f:\n", - " f.write(f'{NUM_VERTICES} {NUM_EDGES}\\n')\n", - " for i in range(NUM_VERTICES):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "528\n" - ] - } - ], - "source": [ - "# save all CYCLE_LENGTH length cycles to ten_cycles.txt\n", - "with open('cycles.txt', 'w') as f:\n", - " cycles = [ c for c in g.to_directed().all_simple_cycles(max_length=CYCLE_LENGTH) if len(c) == CYCLE_LENGTH + 1 ]\n", - " f.write(f'{CYCLE_LENGTH} {len(cycles)}\\n')\n", - " for c in cycles:\n", - " f.write(f'{\" \".join(map(str, c))}\\n')\n", - " print(len(cycles))" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# organize cycles by vertex\n", - "cycles_by_vertex = [[] for _ in range(NUM_VERTICES)]\n", - "for i, c in enumerate(cycles):\n", - " for v in c[:-1]:\n", - " cycles_by_vertex[v].append(i)\n", - "\n", - "with open('cycles_by_vertex.txt', 'w') as f:\n", - " f.write(f'{max([len(c) for c in cycles_by_vertex])}\\n')\n", - " for vertex_cycles in cycles_by_vertex:\n", - " f.write(f'{len(vertex_cycles)} ')\n", - " for c in vertex_cycles:\n", - " f.write(f'{c} ')\n", - " f.write('\\n')\n", - "\n", - "# plot as bar graph\n", - "plt.bar(range(NUM_VERTICES), [len(c) for c in cycles_by_vertex])\n", - "plt.ylim(min([len(c) for c in cycles_by_vertex]) - 1, max([len(c) for c in cycles_by_vertex]) + 1)\n", - "plt.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "SageMath 10.3", - "language": "sage", - "name": "SageMath-10.3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Balaban10/generate_austin.ipynb b/Balaban10/generate_austin.ipynb deleted file mode 100644 index 599e8ec..0000000 --- a/Balaban10/generate_austin.ipynb +++ /dev/null @@ -1,298 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "import networkx as nx\n", - "import matplotlib.pyplot as plt\n", - "from sage.all import *" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "adjacency_list = [\n", - " [19, 21, 3], \n", - " [23, 20, 4], \n", - " [24, 5, 1], \n", - " [6, 26, 2], \n", - " [27, 7, 3], \n", - " [29, 4, 8], \n", - " [5, 9, 30], \n", - " [32, 10, 6],\n", - " [7, 33, 11],\n", - " [35, 12, 8],\n", - " [9, 36, 13],\n", - " [38, 14, 10],\n", - " [15, 39, 11],\n", - " [12, 41, 16],\n", - " [17, 42, 13],\n", - " [18, 44, 14],\n", - " [45, 15, 19],\n", - " [20, 16, 47],\n", - " [48, 1, 17],\n", - " [2, 18, 50],\n", - " [51, 22, 1],\n", - " [21, 23, 37],\n", - " [52, 2, 22],\n", - " [53, 3, 25],\n", - " [26, 40, 24],\n", - " [4, 25, 54],\n", - " [28, 55, 5],\n", - " [43, 27, 29],\n", - " [56, 6, 28],\n", - " [57, 31, 7],\n", - " [30, 32, 46],\n", - " [31, 8, 58],\n", - " [9, 34, 59],\n", - " [49, 35, 33],\n", - " [34, 60, 10],\n", - " [37, 61, 11],\n", - " [38, 36, 22],\n", - " [62, 12, 37],\n", - " [13, 63, 40],\n", - " [25, 41, 39],\n", - " [14, 64, 40],\n", - " [65, 43, 15],\n", - " [42, 28, 44],\n", - " [16, 66, 43],\n", - " [67, 17, 46],\n", - " [31, 47, 45],\n", - " [18, 68, 46],\n", - " [69, 49, 19],\n", - " [48, 34, 50],\n", - " [20, 49, 70],\n", - " [66, 21, 58],\n", - " [65, 23, 57],\n", - " [68, 60, 24],\n", - " [59, 67, 26],\n", - " [27, 62, 70],\n", - " [61, 29, 69],\n", - " [52, 30, 64],\n", - " [63, 51, 32],\n", - " [33, 66, 54],\n", - " [35, 65, 53],\n", - " [36, 68, 56],\n", - " [55, 38, 67],\n", - " [39, 58, 70],\n", - " [69, 57, 41],\n", - " [60, 42, 52],\n", - " [44, 59, 51],\n", - " [54, 45, 62],\n", - " [61, 53, 47],\n", - " [64, 48, 56],\n", - " [50, 55, 63],\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "adjacency_matrix = [[0 for _ in range(70)] for _ in range(70)]\n", - "for i in range(70):\n", - " for j in adjacency_list[i]:\n", - " adjacency_matrix[i][j - 1] = 1" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "M = matrix(adjacency_matrix)" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 176 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = Graph(M, format='adjacency_matrix')\n", - "g.plot(layout='circular').show()" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "graphs.Balaban10Cage(embedding=2).is_isomorphic(g)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of vertices: 70\n", - "Number of edges: 105\n" - ] - } - ], - "source": [ - "NUM_VERTICES = g.num_verts()\n", - "NUM_EDGES = g.size()\n", - "CYCLE_LENGTH = 10 # minimum cycle length\n", - "print(f\"Number of vertices: {NUM_VERTICES}\")\n", - "print(f\"Number of edges: {NUM_EDGES}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "adjacency_list = [[v for v in g.neighbors(u)] for u in range(NUM_VERTICES)]" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [], - "source": [ - "cycles = [ c for c in g.to_directed().all_simple_cycles(max_length=10) if len(c) > CYCLE_LENGTH]" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [], - "source": [ - "cycles_by_vertex = [[] for _ in range(NUM_VERTICES)]\n", - "for i, c in enumerate(cycles):\n", - " for v in c[:-1]:\n", - " cycles_by_vertex[v].append(i)" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [], - "source": [ - "# save to adjacency_list.txt\n", - "with open('adjacency_list.txt', 'w') as f:\n", - " f.write(f'{NUM_VERTICES} {NUM_EDGES}\\n')\n", - " for i in range(NUM_VERTICES):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "528\n" - ] - } - ], - "source": [ - "# save all CYCLE_LENGTH length cycles to ten_cycles.txt\n", - "with open('cycles.txt', 'w') as f:\n", - " cycles = [ c for c in g.to_directed().all_simple_cycles(max_length=CYCLE_LENGTH) if len(c) == CYCLE_LENGTH + 1 ]\n", - " f.write(f'{CYCLE_LENGTH} {len(cycles)}\\n')\n", - " for c in cycles:\n", - " f.write(f'{\" \".join(map(str, c))}\\n')\n", - " print(len(cycles))" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# save cycles by vertex to cycles_by_vertex.txt\n", - "with open('cycles_by_vertex.txt', 'w') as f:\n", - " f.write(f'{max([len(c) for c in cycles_by_vertex])}\\n')\n", - " for vertex_cycles in cycles_by_vertex:\n", - " f.write(f'{len(vertex_cycles)} ')\n", - " for c in vertex_cycles:\n", - " f.write(f'{c} ')\n", - " f.write('\\n')\n", - "\n", - "# plot as bar graph\n", - "plt.bar(range(NUM_VERTICES), [len(c) for c in cycles_by_vertex])\n", - "plt.ylim(min([len(c) for c in cycles_by_vertex]) - 1, max([len(c) for c in cycles_by_vertex]) + 1)\n", - "plt.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "SageMath 10.3", - "language": "sage", - "name": "SageMath-10.3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Balaban10/makefile b/Balaban10/makefile deleted file mode 100644 index 7cb6410..0000000 --- a/Balaban10/makefile +++ /dev/null @@ -1,11 +0,0 @@ -all: FitCycles - -run: FitCycles - ./FitCycles > FitCycles.out - -FitCycles: FitCycles.c - gcc -Wall -std=c17 -pedantic -g -o FitCycles FitCycles.c - -clean: - rm -f FitCycles *.o - rm -rf *.dSYM diff --git a/Balaban10/test.ipynb b/Balaban10/test.ipynb deleted file mode 100644 index b91380e..0000000 --- a/Balaban10/test.ipynb +++ /dev/null @@ -1,2490 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import networkx as nx\n", - "import matplotlib.pyplot as plt\n", - "from sage.all import *" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "CYCLE_LENGTH = 10 # length of the cycles to fit onto the graph" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "g = graphs.Balaban10Cage(embedding=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "cycles = [ c for c in g.to_directed().all_simple_cycles(max_length=CYCLE_LENGTH) if len(c) == CYCLE_LENGTH + 1 ]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# solution = [\n", - "# [0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0],\n", - "# [22, 23, 24, 51, 50, 67, 66, 33, 32, 31, 22],\n", - "# [8, 9, 10, 19, 18, 17, 16, 25, 26, 27, 8],\n", - "# [20, 45, 44, 43, 42, 41, 40, 39, 38, 21, 20],\n", - "# [0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0],\n", - "# [0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0],\n", - "# [11, 12, 41, 42, 59, 58, 49, 50, 51, 52, 11],\n", - "# [5, 6, 7, 8, 27, 28, 69, 68, 39, 40, 5],\n", - "# [7, 48, 47, 14, 15, 36, 35, 34, 9, 8, 7],\n", - "# [23, 62, 61, 60, 59, 42, 43, 26, 25, 24, 23],\n", - "# [3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3],\n", - "# [18, 19, 20, 21, 22, 31, 30, 29, 56, 57, 18],\n", - "# [26, 43, 44, 65, 64, 55, 56, 29, 28, 27, 26],\n", - "# [1, 46, 45, 20, 19, 10, 11, 52, 53, 2, 1],\n", - "# [2, 53, 54, 37, 36, 15, 16, 17, 4, 3, 2] ,\n", - "# ]\n", - "solution = [\n", - " [0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0], \n", - " [0, 61, 62, 23, 22, 31, 30, 29, 28, 69, 0], \n", - " [0, 69, 68, 67, 66, 65, 44, 45, 46, 1, 0], \n", - " [1, 46, 47, 48, 49, 50, 51, 52, 53, 2, 1], \n", - " [4, 17, 16, 25, 24, 23, 62, 63, 6, 5, 4], \n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# only valid cycles and no duplicates edges\n", - "edges = set()\n", - "for c in solution:\n", - " for i in range(CYCLE_LENGTH):\n", - " if (c[i], c[i + 1]) in edges:\n", - " print(\"Duplicate edge\", c[i], c[i + 1])\n", - " edges.add((c[i], c[i + 1]))\n", - " assert c in cycles" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# print cycles with the same vertex set in the solution\n", - "for i, c1 in enumerate(solution):\n", - " for j, c2 in enumerate(solution):\n", - " if i == j:\n", - " continue\n", - " if list(reversed(c1)) == c2:\n", - " continue\n", - " if set(c1) == set(c2):\n", - " print(c1, c2)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def x_in_y(query, base):\n", - " try:\n", - " l = len(query)\n", - " except TypeError:\n", - " l = 1\n", - " query = type(base)((query,))\n", - "\n", - " for i in range(len(base)):\n", - " if base[i:i+l] == query:\n", - " return True\n", - " return False\n", - "\n", - "# test cases \n", - "assert x_in_y((1, 2, 3), (1, 2, 3, 4))\n", - "assert x_in_y((1, 2, 3), (4, 1, 2, 3))\n", - "assert not x_in_y((1, 2, 3), (1, 2, 4, 3))\n", - "assert x_in_y([0, 61, 60], [0, 61, 60, 59, 42, 41, 40, 39, 68, 69, 0])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# make sure if vertices i, j, k occur in the solution, k, j, i don't\n", - "for c in solution:\n", - " c = c.copy() + [c[1]]\n", - " for i in range(CYCLE_LENGTH):\n", - " for c2 in solution:\n", - " c2 = c2.copy() + [c2[1]]\n", - " if x_in_y([c[i + 2], c[i + 1], c[i]], c2):\n", - " print(\"Found\", c[i], c[i + 1], c[i + 2], \"in\", c2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tests for mixed cycle length fittings:" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "mixed = [\n", - " [0, 1, 2, 3, 32, 33, 34, 35, 60, 61, 0],\n", - " [22, 23, 24, 51, 50, 67, 66, 33, 32, 31, 22],\n", - " [15, 16, 25, 26, 43, 42, 59, 60, 35, 36, 15],\n", - " [5, 6, 63, 62, 23, 22, 21, 38, 39, 40, 5],\n", - " [7, 48, 47, 14, 15, 36, 37, 38, 21, 20, 19, 10, 9, 8, 7],\n", - " [0, 69, 28, 29, 30, 13, 14, 47, 46, 1, 0],\n", - " [6, 7, 8, 27, 28, 69, 68, 39, 38, 37, 54, 55, 64, 63, 6],\n", - " [1, 46, 45, 20, 21, 22, 31, 30, 29, 56, 55, 54, 53, 2, 1],\n", - " [18, 19, 20, 45, 44, 65, 64, 55, 56, 57, 18],\n", - " [3, 4, 5, 40, 41, 12, 13, 30, 31, 32, 3],\n", - " [9, 10, 11, 52, 53, 54, 37, 36, 35, 34, 9],\n", - " [0, 61, 62, 63, 64, 65, 66, 67, 68, 69, 0],\n", - " [4, 17, 18, 57, 58, 49, 48, 7, 6, 5, 4],\n", - " [23, 62, 61, 60, 59, 58, 57, 56, 29, 28, 27, 26, 25, 24, 23],\n", - " [11, 12, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 11],\n", - " [10, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10],\n", - " [2, 53, 52, 51, 24, 25, 16, 17, 4, 3, 2],\n", - " [8, 9, 34, 33, 66, 65, 44, 43, 26, 27, 8],\n", - " [39, 68, 67, 50, 49, 58, 59, 42, 41, 40, 39],\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "19" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(mixed)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "14" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "max([len(c) - 1 for c in mixed])" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "210" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sum([len(c) - 1 for c in mixed])" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "14" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len([c for c in mixed if len(c) == 11])" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]\n", - "All vertices used thrice\n" - ] - } - ], - "source": [ - "vertex_uses = [0] * 70\n", - "for c in mixed:\n", - " for v in c[:-1]:\n", - " vertex_uses[v] += 1\n", - "print(vertex_uses)\n", - "if all([v == 3 for v in vertex_uses]):\n", - " print(\"All vertices used thrice\")" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "All edges used exactly once\n" - ] - } - ], - "source": [ - "# convert edges list to adjacency list\n", - "adjacency_list = [[] for _ in range(70)]\n", - "for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - "\n", - "# check if every edge is used exactly once by removing them from the adjacency list\n", - "for c in mixed:\n", - " for i in range(len(c) - 1):\n", - " if c[i + 1] not in adjacency_list[c[i]]:\n", - " print(\"Edge\", c[i], c[i + 1], \"not in adjacency list\")\n", - " adjacency_list[c[i]].remove(c[i + 1])\n", - "if all([len(v) == 0 for v in adjacency_list]):\n", - " print(\"All edges used exactly once\")" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 350 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from math import pi, cos, sin\n", - "\n", - "embedding = 1 # 1 or 2\n", - "g_directed = graphs.Balaban10Cage(embedding=embedding).to_directed()\n", - "\n", - "def is_in_cycle(e, cycle):\n", - " try:\n", - " i = cycle.index(e[0])\n", - " j = cycle.index(e[1])\n", - "\n", - " if i + 1 == j or (i == len(cycle) - 2 and j == 0):\n", - " return True\n", - " else:\n", - " return False\n", - " except ValueError:\n", - " return False\n", - "\n", - "for e in g_directed.edges():\n", - " g_directed.set_edge_label(e[0], e[1], 0)\n", - " for i, c in enumerate(mixed):\n", - " if is_in_cycle(e, c):\n", - " g_directed.set_edge_label(e[0], e[1], i + 1)\n", - "\n", - "### CHANGE EMBEDDING LAYOUT ###\n", - "pos = g_directed.get_pos()\n", - "relabels = {}\n", - "\n", - "inner_vertices = [2, 48, 27, 31, 38, 42, 49, 53, 32, 8, 43, 21, 54, 58, 7, 3, 22, 26, 59, 37]\n", - "new_labels = [61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60]\n", - "for i, v in enumerate(inner_vertices):\n", - " angle = 2 * pi * (i + 5.5) / len(inner_vertices)\n", - " pos[v] = (3 * cos(angle), 3 * sin(angle))\n", - " relabels[v] = new_labels[i]\n", - "\n", - "indented_vertices = [5, 24, 35, 46, 29, 40, 51, 34, 45, 56]\n", - "new_labels = [28, 31, 34, 37, 40, 43, 46, 49, 22, 25]\n", - "for i, v in enumerate(indented_vertices):\n", - " angle = 2 * pi * i / len(indented_vertices)\n", - " pos[v] = (4.3 * cos(angle), 4.3 * sin(angle))\n", - " relabels[v] = new_labels[i]\n", - "\n", - "middle_vertices = [1, 47, 28, 30, 39, 41, 50, 52, 33, 9, 44, 20, 55, 57, 6, 4, 23, 25, 60, 36]\n", - "new_labels = [36, 38, 39, 41, 42, 44, 45, 47, 48, 50, 21, 23, 24, 26, 27, 29, 30, 32, 33, 35]\n", - "for i, v in enumerate(middle_vertices):\n", - " angle = 2 * pi * (i + 5.5) / len(middle_vertices)\n", - " pos[v] = (4.5 * cos(angle), 4.5 * sin(angle))\n", - " relabels[v] = new_labels[i]\n", - "\n", - "outer_vertices = [0, 14, 69, 13, 68, 12, 67, 11, 66, 10, 65, 19, 64, 18, 63, 17, 62, 16, 61, 15,]\n", - "new_labels = [11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n", - "for i, v in enumerate(outer_vertices):\n", - " angle = 2 * pi * (i + 5.5) / len(outer_vertices)\n", - " pos[v] = (6 * cos(angle), 6 * sin(angle))\n", - " relabels[v] = new_labels[i]\n", - "\n", - "g_directed.set_pos(pos)\n", - "g_directed.relabel(relabels, inplace=True)\n", - "### CHANGE EMBEDDING LAYOUT ###\n", - "\n", - "p = g_directed.plot(\n", - " edge_colors=g_directed._color_by_label({\n", - " 0: \"black\", \n", - " 1: \"blue\", \n", - " 2: \"purple\", \n", - " 3: \"red\", \n", - " 4: \"green\", \n", - " 5: \"orange\", \n", - " 6: \"yellow\",\n", - " 7: \"brown\",\n", - " 8: \"pink\",\n", - " 9: \"cyan\",\n", - " 10: \"magenta\",\n", - " 11: \"grey\",\n", - " 12: \"lightblue\",\n", - " 13: \"lightgreen\",\n", - " 14: \"teal\",\n", - " 15: 'salmon',\n", - " 16: 'navy',\n", - " 17: 'gold',\n", - " 18: 'lime',\n", - " 19: 'indigo',\n", - " 20: 'maroon',\n", - " 21: 'olive',\n", - " }), \n", - " vertex_size=70 if embedding == 2 else 1000,\n", - " vertex_color=\"midnightblue\",\n", - " transparent=True,\n", - ")\n", - "for object in p._objects:\n", - " if isinstance(object, sage.plot.text.Text):\n", - " object._options['rgbcolor'] = (1, 1, 1)\n", - "p.show(figsize=(10, 10))\n", - "\n", - "# export as PDF\n", - "p.save(\"BalabanGenus9Embedding.pdf\", figsize=(14, 14))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Paper Figures" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 176 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = graphs.Balaban10Cage(embedding=1)\n", - "\n", - "### CHANGE EMBEDDING LAYOUT ###\n", - "pos = g.get_pos()\n", - "relabels = {}\n", - "\n", - "inner_vertices = [2, 48, 27, 31, 38, 42, 49, 53, 32, 8, 43, 21, 54, 58, 7, 3, 22, 26, 59, 37]\n", - "new_labels = [61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60]\n", - "for i, v in enumerate(inner_vertices):\n", - " angle = 2 * pi * (i + 5.5) / len(inner_vertices)\n", - " pos[v] = (3 * cos(angle), 3 * sin(angle))\n", - " relabels[v] = new_labels[i]\n", - "\n", - "indented_vertices = [5, 24, 35, 46, 29, 40, 51, 34, 45, 56]\n", - "new_labels = [28, 31, 34, 37, 40, 43, 46, 49, 22, 25]\n", - "for i, v in enumerate(indented_vertices):\n", - " angle = 2 * pi * i / len(indented_vertices)\n", - " pos[v] = (4.3 * cos(angle), 4.3 * sin(angle))\n", - " relabels[v] = new_labels[i]\n", - "\n", - "middle_vertices = [1, 47, 28, 30, 39, 41, 50, 52, 33, 9, 44, 20, 55, 57, 6, 4, 23, 25, 60, 36]\n", - "new_labels = [36, 38, 39, 41, 42, 44, 45, 47, 48, 50, 21, 23, 24, 26, 27, 29, 30, 32, 33, 35]\n", - "for i, v in enumerate(middle_vertices):\n", - " angle = 2 * pi * (i + 5.5) / len(middle_vertices)\n", - " pos[v] = (4.5 * cos(angle), 4.5 * sin(angle))\n", - " relabels[v] = new_labels[i]\n", - "\n", - "outer_vertices = [0, 14, 69, 13, 68, 12, 67, 11, 66, 10, 65, 19, 64, 18, 63, 17, 62, 16, 61, 15,]\n", - "new_labels = [11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n", - "for i, v in enumerate(outer_vertices):\n", - " angle = 2 * pi * (i + 5.5) / len(outer_vertices)\n", - " pos[v] = (6 * cos(angle), 6 * sin(angle))\n", - " relabels[v] = new_labels[i]\n", - "\n", - "g.set_pos(pos)\n", - "g.relabel(relabels, inplace=True)\n", - "### CHANGE EMBEDDING LAYOUT ###\n", - "\n", - "p = g.plot(\n", - " edge_color=\"black\", \n", - " vertex_size=600,\n", - " vertex_color=\"midnightblue\",\n", - " transparent=True,\n", - ")\n", - "for object in p._objects:\n", - " if isinstance(object, sage.plot.text.Text):\n", - " object._options['rgbcolor'] = (1, 1, 1)\n", - "p.show(figsize=(10, 10))\n", - "\n", - "# export as PDF\n", - "p.save(\"balabanlabeled.pdf\", figsize=(14, 14))" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 176 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = graphs.Balaban10Cage(embedding=1)\n", - "\n", - "### CHANGE EMBEDDING LAYOUT ###\n", - "pos = g.get_pos()\n", - "relabels = {}\n", - "\n", - "inner_vertices = [2, 48, 27, 31, 38, 42, 49, 53, 32, 8, 43, 21, 54, 58, 7, 3, 22, 26, 59, 37]\n", - "new_labels = [61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60]\n", - "for i, v in enumerate(inner_vertices):\n", - " angle = 2 * pi * (i + 5.5) / len(inner_vertices)\n", - " pos[v] = (3 * cos(angle), 3 * sin(angle))\n", - " relabels[v] = new_labels[i]\n", - "\n", - "indented_vertices = [5, 24, 35, 46, 29, 40, 51, 34, 45, 56]\n", - "new_labels = [28, 31, 34, 37, 40, 43, 46, 49, 22, 25]\n", - "for i, v in enumerate(indented_vertices):\n", - " angle = 2 * pi * i / len(indented_vertices)\n", - " pos[v] = (4.3 * cos(angle), 4.3 * sin(angle))\n", - " relabels[v] = new_labels[i]\n", - "\n", - "middle_vertices = [1, 47, 28, 30, 39, 41, 50, 52, 33, 9, 44, 20, 55, 57, 6, 4, 23, 25, 60, 36]\n", - "new_labels = [36, 38, 39, 41, 42, 44, 45, 47, 48, 50, 21, 23, 24, 26, 27, 29, 30, 32, 33, 35]\n", - "for i, v in enumerate(middle_vertices):\n", - " angle = 2 * pi * (i + 5.5) / len(middle_vertices)\n", - " pos[v] = (4.5 * cos(angle), 4.5 * sin(angle))\n", - " relabels[v] = new_labels[i]\n", - "\n", - "outer_vertices = [0, 14, 69, 13, 68, 12, 67, 11, 66, 10, 65, 19, 64, 18, 63, 17, 62, 16, 61, 15,]\n", - "new_labels = [11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n", - "for i, v in enumerate(outer_vertices):\n", - " angle = 2 * pi * (i + 5.5) / len(outer_vertices)\n", - " pos[v] = (6 * cos(angle), 6 * sin(angle))\n", - " relabels[v] = new_labels[i]\n", - "\n", - "g.set_pos(pos)\n", - "g.relabel(relabels, inplace=True)\n", - "### CHANGE EMBEDDING LAYOUT ###\n", - "\n", - "p = g.plot(\n", - " edge_color=\"black\", \n", - " vertex_size=600,\n", - " vertex_color=\"midnightblue\",\n", - " transparent=True,\n", - ")\n", - "for object in p._objects:\n", - " if isinstance(object, sage.plot.text.Text):\n", - " object._options['rgbcolor'] = (25/255, 25/255, 112/255)\n", - "p.show(figsize=(10, 10))\n", - "\n", - "# export as PDF\n", - "p.save(\"balabanunlabeled.pdf\", figsize=(14, 14))" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n" - ], - "text/plain": [ - "Graphics3d Object" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Parametric equations for a torus; the fundamental domain is the square [0,2*pi] x [0,2*pi]\n", - "var('u,v');\n", - "a,b = 2,1 \n", - "x = (a + b*cos(u))*cos(v)\n", - "y = (a + b*cos(u))*sin(v)\n", - "z = b*sin(u)\n", - "\n", - "# A parametric curve (line) in the u-v plane\n", - "var('t');\n", - "c = (2*t,3*t)\n", - "\n", - "# the same curve in cartesian coordinates on the torus\n", - "s = [_.subs(dict(zip((u,v),c))) for _ in (x,y,z)]\n", - "# s[(cos(2*t) + 2)*cos(3*t), (cos(2*t) + 2)*sin(3*t), sin(2*t)]\n", - "\n", - "curve = parametric_plot(s,(t,0,2*pi),color='red',thickness=2,plot_points=400)\n", - "T = parametric_plot3d([x,y,z], (u,0,2*pi),(v,0,2*pi), opacity=.6,aspect_ratio=1) \n", - "T+curve" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n" - ], - "text/plain": [ - "Graphics3d Object" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plane_curves = [(i*2*pi/5 + 2*t,3*t) for i in range(5)]+[(i*2*pi/5 + 3*t,-2*t) for i in range(5)]\n", - "torus_curves = [[_.subs(dict(zip((u,v),c))) for _ in (x,y,z)] for c in plane_curves]\n", - "curve_plots = [parametric_plot(torus_curves[i], (t,0,2*pi), color=hue(2*i/10), thickness=4, plot_points=400) for i in range(10)]\n", - "from sage.plot.plot3d.base import Graphics3d\n", - "T + sum(curve_plots,Graphics3d())" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "Graphics3d Object" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Parametric equations for a torus; the fundamental domain is the square [0,2*pi] x [0,2*pi]\n", - "var('u v t');\n", - "a, b = 2, 1\n", - "x = (a + b*cos(u))*cos(v)\n", - "y = (a + b*cos(u))*sin(v)\n", - "z = b*sin(u)\n", - "\n", - "# Define the positions for the vertices of the K(3,3) graph\n", - "# We choose 3 points for houses and 3 points for utilities in (u, v) coordinates\n", - "vertices_houses = [(pi/2, pi/6), (pi/2, pi/2), (pi/2, 5*pi/6)]\n", - "vertices_utilities = [(3*pi/2, pi/6), (3*pi/2, pi/2), (3*pi/2, 5*pi/6)]\n", - "\n", - "# Function to convert (u, v) to 3D coordinates on the torus\n", - "def torus_coords(uh, vh):\n", - " return ((a + b*cos(uh))*cos(vh), (a + b*cos(uh))*sin(vh), b*sin(uh))\n", - "\n", - "# Define a function to plot edges along the torus surface by interpolating the (u, v) coordinates\n", - "# Optionally wrap around the outside of the torus by modifying the v-coordinate\n", - "def edge_on_torus(p1, p2, wrap_around=False, go_around=False, color='blue'):\n", - " uh1, vh1 = p1\n", - " uh2, vh2 = p2\n", - " \n", - " # Offset the coordinates to wrap around the outside of the torus if wrap_around is True\n", - " if wrap_around:\n", - " uh1 += pi\n", - " uh2 += pi\n", - " \n", - " # Define the interpolation for the parametric coordinates (u, v)\n", - " u_interp = (1-t)*uh1 + t*uh2\n", - " v_interp = (1-t)*vh1 + t*vh2\n", - " if wrap_around:\n", - " u_interp = (1-t)*uh2 + t*uh1\n", - " if go_around:\n", - " v_interp = (2-2*t)*vh2 + 2*t*vh1 + 1*pi/2\n", - " \n", - " # Convert the interpolated (u, v) back to 3D space using the torus parametric equations\n", - " x_interp = (a + b*cos(u_interp))*cos(v_interp)\n", - " y_interp = (a + b*cos(u_interp))*sin(v_interp)\n", - " z_interp = b*sin(u_interp)\n", - " \n", - " # Plot the edge as a parametric curve along the surface of the torus\n", - " edge_curve = parametric_plot([x_interp, y_interp, z_interp], (t, 0, 1), color=color, thickness=2)\n", - " return edge_curve\n", - "\n", - "# Parametrize the positions of the houses and utilities on the torus\n", - "positions_houses = [torus_coords(uh, vh) for uh, vh in vertices_houses]\n", - "positions_utilities = [torus_coords(uu, vu) for uu, vu in vertices_utilities]\n", - "\n", - "# Plot all edges of K(3,3), alternating between inside and outside paths\n", - "edges = []\n", - "for i, h in enumerate(vertices_houses):\n", - " for j, r in enumerate(vertices_utilities):\n", - " # Alternate wrapping some edges around the outside of the torus\n", - " wrap_around = (j, i) in [(0, 0), (1, 1), (2, 2), (0, 1), (1, 2), (0, 2)]\n", - " go_around = i == 2 and j == 0\n", - " edges.append(edge_on_torus(h, r, wrap_around=wrap_around, go_around=go_around))\n", - "\n", - "# Combine the plot of the torus and the edges\n", - "curve_edges = sum(edges)\n", - "\n", - "# Add points at the vertices\n", - "points = []\n", - "for pos in positions_houses:\n", - " points.append(point3d(pos, size=10, color='#163036')) # Change color/size as needed\n", - "for pos in positions_utilities:\n", - " points.append(point3d(pos, size=10, color='#e29231')) \n", - "\n", - "# Plot the torus\n", - "T = parametric_plot3d([(a + b*cos(u))*cos(v), (a + b*cos(u))*sin(v), b*sin(u)], (u, 0, 2*pi), (v, 0, 2*pi), opacity=0.6, aspect_ratio=1)\n", - "final_plot = T + curve_edges + sum(points)\n", - "\n", - "# Show the final plot\n", - "# final_plot.show(frame=False)\n", - "final_plot.show(frame=False, viewer='tachyon', shade='medium', antialiasing=True, figsize=20, zoom=1.5, camera_position=[2.3, 2.4, 2.2])\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 50 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "positions = {\n", - " '1': (-2, 2),\n", - " 'w': (-1, 3),\n", - " '2': (0, 3),\n", - " 'x': (1, 3),\n", - " '3': (2, 2),\n", - " 'V': (0, 1),\n", - " '4': (-2, 0),\n", - " 'y': (-1, -1),\n", - " '5': (0, -1),\n", - " 'z': (1, -1),\n", - " '6': (2, 0)\n", - "}\n", - "\n", - "cycles = [\n", - " # Cycle around 1, 2, 3 and V\n", - " ('1', 'w', '2', 'x', '3', 'V', '1'),\n", - "\n", - " # Cycle through 1, 2, and V\n", - " ('1', 'V', '2', 'w', '1'),\n", - "\n", - " # Cycle through 2, 3, and V\n", - " ('2', 'V', '3', 'x', '2'),\n", - "\n", - " # Cycle through V, 4, 5, 6\n", - " ('V', '4', 'y', '5', 'z', '6', 'V'),\n", - "\n", - " # Cycle through V, 6, 5\n", - " ('V', '6', 'z', '5', 'V'),\n", - "\n", - " # Cycle through V, 5, 4\n", - " ('V', '5', 'y', '4', 'V')\n", - "]\n", - "\n", - "edges = [c for cycle in cycles for c in list(zip(cycle[:-1], cycle[1:]))]\n", - "\n", - "# Create the directed graph\n", - "G = DiGraph(edges)\n", - "G.set_pos(positions)\n", - "\n", - "def is_in_cycle(e, cycle):\n", - " try:\n", - " i = cycle.index(e[0])\n", - " j = cycle.index(e[1])\n", - "\n", - " if i + 1 == j or (i == len(cycle) - 2 and j == 0):\n", - " return True\n", - " else:\n", - " return False\n", - " except ValueError:\n", - " return False\n", - "\n", - "for e in G.edges():\n", - " G.set_edge_label(e[0], e[1], 0)\n", - " for i, c in enumerate(cycles):\n", - " if is_in_cycle(e, c):\n", - " G.set_edge_label(e[0], e[1], i + 1)\n", - "\n", - "p = G.plot(\n", - " edge_colors=G._color_by_label({\n", - " 0: \"yellow\", \n", - " 1: \"blue\", \n", - " 2: \"purple\", \n", - " 3: \"red\", \n", - " 4: \"green\", \n", - " 5: \"orange\", \n", - " 6: \"black\",\n", - " 7: \"brown\",\n", - " 8: \"pink\",\n", - " 9: \"cyan\",\n", - " 10: \"magenta\",\n", - " 11: \"grey\",\n", - " 12: \"lightblue\",\n", - " 13: \"lightgreen\",\n", - " 14: \"teal\",\n", - " 15: 'salmon',\n", - " 16: 'navy',\n", - " 17: 'gold',\n", - " 18: 'lime',\n", - " 19: 'indigo',\n", - " 20: 'maroon',\n", - " 21: 'olive',\n", - " }), \n", - " vertex_size=1000,\n", - " vertex_color=\"midnightblue\",\n", - " transparent=True,\n", - ")\n", - "for object in p._objects:\n", - " if isinstance(object, sage.plot.text.Text):\n", - " object._options['rgbcolor'] = (1, 1, 1)\n", - "p.show(figsize=(6, 6))\n", - "\n", - "# export as PDF\n", - "p.save(\"../images/Degree6CounterExample.pdf\", figsize=(6, 6))" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 155 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "positions = {\n", - " '1': (-2, 2),\n", - " 'w': (-1, 3),\n", - " '2': (0, 3),\n", - " 'x': (1, 3),\n", - " '3': (2, 2),\n", - " 'V': (0, 1),\n", - " '4': (-2, 0),\n", - " 'y': (-1, -1),\n", - " '5': (0, -1),\n", - " 'z': (1, -1),\n", - " '6': (2, 0)\n", - "}\n", - "\n", - "cycles = [\n", - " # Cycle 0\n", - " ('1', 'w', '2', 'x', '3', 'V', '1'),\n", - "\n", - " # Cycle 1\n", - " ('1', 'V', '2', 'w', '1'),\n", - "\n", - " # Cycle 2\n", - " ('2', 'V', '3', 'x', '2'),\n", - "\n", - " # Cycle 3\n", - " ('V', '4', 'y', '5', 'z', '6', 'V'),\n", - "\n", - " # Cycle 4\n", - " ('V', '6', 'z', '5', 'V'),\n", - "\n", - " # Cycle 5\n", - " ('V', '5', 'y', '4', 'V')\n", - "]\n", - "\n", - "edges = [e for cycle in cycles for e in zip(cycle[:-1], cycle[1:])]\n", - "\n", - "# Directed graph just for bookkeeping\n", - "G = DiGraph(edges)\n", - "G.set_pos(positions)\n", - "\n", - "def is_in_cycle(e, cycle):\n", - " for a, b in zip(cycle[:-1], cycle[1:]):\n", - " if (a, b) == e:\n", - " return True\n", - " return False\n", - "\n", - "def cycle_index_of_edge(e, cycles):\n", - " \"\"\"\n", - " Later cycles overwrite earlier ones, matching your original behavior.\n", - " \"\"\"\n", - " idx = None\n", - " for i, c in enumerate(cycles):\n", - " if is_in_cycle(e, c):\n", - " idx = i\n", - " return idx\n", - "\n", - "color_map = {\n", - " -1: \"yellow\", # fallback\n", - " 0: \"blue\",\n", - " 1: \"purple\",\n", - " 2: \"red\",\n", - " 3: \"green\",\n", - " 4: \"orange\",\n", - " 5: \"black\",\n", - " 6: \"brown\",\n", - " 7: \"pink\",\n", - " 8: \"cyan\",\n", - " 9: \"magenta\",\n", - " 10: \"grey\",\n", - " 11: \"lightblue\",\n", - " 12: \"lightgreen\",\n", - " 13: \"teal\",\n", - " 14: \"salmon\",\n", - " 15: \"navy\",\n", - " 16: \"gold\",\n", - " 17: \"lime\",\n", - " 18: \"indigo\",\n", - " 19: \"maroon\",\n", - " 20: \"olive\",\n", - "}\n", - "\n", - "# Assign labels = cycle index\n", - "edge_cycle = {}\n", - "for e in G.edges():\n", - " idx = cycle_index_of_edge((e[0], e[1]), cycles)\n", - " edge_cycle[(e[0], e[1])] = idx if idx is not None else -1\n", - "\n", - "# ---------- Geometry helpers ----------\n", - "\n", - "def v_add(a, b):\n", - " return (a[0] + b[0], a[1] + b[1])\n", - "\n", - "def v_sub(a, b):\n", - " return (a[0] - b[0], a[1] - b[1])\n", - "\n", - "def v_scale(c, a):\n", - " return (c * a[0], c * a[1])\n", - "\n", - "def v_len(a):\n", - " return sqrt(a[0]^2 + a[1]^2)\n", - "\n", - "def v_unit(a):\n", - " L = v_len(a)\n", - " if L == 0:\n", - " return (0, 0)\n", - " return (a[0] / L, a[1] / L)\n", - "\n", - "def v_perp(a):\n", - " return (-a[1], a[0])\n", - "\n", - "def quadratic_bezier_point(P0, P1, P2, t):\n", - " \"\"\"\n", - " (1-t)^2 P0 + 2(1-t)t P1 + t^2 P2\n", - " \"\"\"\n", - " return v_add(\n", - " v_add(v_scale((1-t)^2, P0), v_scale(2*(1-t)*t, P1)),\n", - " v_scale(t^2, P2)\n", - " )\n", - "\n", - "def quadratic_bezier_tangent(P0, P1, P2, t):\n", - " \"\"\"\n", - " Derivative of quadratic Bezier\n", - " \"\"\"\n", - " term1 = v_scale(2*(1-t), v_sub(P1, P0))\n", - " term2 = v_scale(2*t, v_sub(P2, P1))\n", - " return v_add(term1, term2)\n", - "\n", - "def edge_curve_data(u, v, positions, all_edges, curve_amount=0.35, shorten=0.24):\n", - " \"\"\"\n", - " Return geometry for the directed edge u->v.\n", - "\n", - " If v->u also exists, use a quadratic Bezier curve with control point\n", - " offset perpendicular to the chord. The sign is chosen deterministically\n", - " from the vertex names so opposite directions land on opposite sides.\n", - " \"\"\"\n", - " P0 = positions[u]\n", - " P2 = positions[v]\n", - "\n", - " d = v_sub(P2, P0)\n", - " L = v_len(d)\n", - " if L == 0:\n", - " return None\n", - "\n", - " t_hat = v_unit(d)\n", - " n_hat = v_perp(t_hat)\n", - "\n", - " # Shorten so arrows start/end near the boundary of the vertex disks\n", - " A = v_add(P0, v_scale(shorten, t_hat))\n", - " B = v_add(P2, v_scale(-shorten, t_hat))\n", - "\n", - " # If reverse edge exists, curve it\n", - " if (v, u) in all_edges:\n", - " mid = v_scale(0.5, v_add(A, B))\n", - " C = v_add(mid, v_scale(curve_amount, n_hat))\n", - " curved = True\n", - " else:\n", - " C = None\n", - " curved = False\n", - "\n", - " return {\n", - " 'start': A,\n", - " 'end': B,\n", - " 'control': C,\n", - " 'curved': curved\n", - " }\n", - "\n", - "def point_and_tangent_on_edge(u, v, positions, all_edges, t, curve_amount=0.35, shorten=0.24):\n", - " \"\"\"\n", - " Point and tangent on the actual plotted edge at parameter t in [0,1].\n", - " \"\"\"\n", - " data = edge_curve_data(u, v, positions, all_edges, curve_amount=curve_amount, shorten=shorten)\n", - " A = data['start']\n", - " B = data['end']\n", - "\n", - " if data['curved']:\n", - " C = data['control']\n", - " pt = quadratic_bezier_point(A, C, B, t)\n", - " tg = quadratic_bezier_tangent(A, C, B, t)\n", - " else:\n", - " pt = v_add(A, v_scale(t, v_sub(B, A)))\n", - " tg = v_sub(B, A)\n", - "\n", - " return pt, tg\n", - "\n", - "# ---------- Drawing helpers ----------\n", - "\n", - "def add_directed_edge(plot_obj, u, v, color, positions, all_edges,\n", - " thickness=2.5, curve_amount=0.35, shorten=0.24,\n", - " arrow_head=0.14):\n", - " \"\"\"\n", - " Draw one directed edge, straight or curved.\n", - " \"\"\"\n", - " data = edge_curve_data(u, v, positions, all_edges,\n", - " curve_amount=curve_amount, shorten=shorten)\n", - "\n", - " A = data['start']\n", - " B = data['end']\n", - "\n", - " if data['curved']:\n", - " C = data['control']\n", - " plot_obj += bezier_path([[A, C, B]], rgbcolor=color, thickness=thickness)\n", - "\n", - " # Add arrowhead using tangent near the end of the curve\n", - " pt, tg = point_and_tangent_on_edge(u, v, positions, all_edges, 0.92,\n", - " curve_amount=curve_amount, shorten=shorten)\n", - " tg = v_unit(tg)\n", - " arrow_start = v_add(B, v_scale(-arrow_head, tg))\n", - " plot_obj += arrow(arrow_start, B, rgbcolor=color, width=thickness,\n", - " arrowsize=6)\n", - " else:\n", - " plot_obj += arrow(A, B, rgbcolor=color, width=thickness, arrowsize=6)\n", - "\n", - " return plot_obj\n", - "\n", - "def add_edge_marks(plot_obj, u, v, n_marks, color, positions, all_edges,\n", - " mark_length=0.18, mark_spacing=0.13,\n", - " thickness=2.5, curve_amount=0.35, shorten=0.24):\n", - " \"\"\"\n", - " Draw n_marks short lines across the actual plotted directed edge.\n", - " Cycle 0 gets 0 marks, cycle 1 gets 1 mark, etc.\n", - " \"\"\"\n", - " if n_marks <= 0:\n", - " return plot_obj\n", - "\n", - " # Put marks around the middle of the parameter interval\n", - " ts = [0.5 + mark_spacing * (j - (n_marks - 1)/2) for j in range(n_marks)]\n", - "\n", - " for t in ts:\n", - " # keep safely away from the arrowhead and endpoints\n", - " t = max(0.22, min(0.78, t))\n", - "\n", - " pt, tg = point_and_tangent_on_edge(u, v, positions, all_edges, t,\n", - " curve_amount=curve_amount, shorten=shorten)\n", - "\n", - " tg = v_unit(tg)\n", - " n_hat = v_perp(tg)\n", - "\n", - " a = v_add(pt, v_scale(-mark_length/2, n_hat))\n", - " b = v_add(pt, v_scale(mark_length/2, n_hat))\n", - "\n", - " plot_obj += line([a, b], rgbcolor=color, thickness=thickness)\n", - "\n", - " return plot_obj\n", - "\n", - "# ---------- Build the plot manually ----------\n", - "\n", - "p = Graphics()\n", - "\n", - "# Draw edges first\n", - "all_edges = set((u, v) for (u, v, _) in G.edges())\n", - "\n", - "for (u, v, _) in G.edges():\n", - " idx = edge_cycle[(u, v)]\n", - " color = color_map[idx]\n", - "\n", - " p = add_directed_edge(\n", - " p, u, v, color, positions, all_edges,\n", - " thickness=2.5,\n", - " curve_amount=0.25,\n", - " shorten=0.16,\n", - " arrow_head=0.14\n", - " )\n", - "\n", - " p = add_edge_marks(\n", - " p, u, v, idx, color, positions, all_edges,\n", - " mark_length=0.16,\n", - " mark_spacing=0.09,\n", - " thickness=2.5,\n", - " curve_amount=0.25,\n", - " shorten=0.16\n", - " )\n", - "\n", - "# Draw vertices on top\n", - "vertex_radius = 0.16\n", - "for v, (x, y) in positions.items():\n", - " p += circle((x, y), vertex_radius, rgbcolor=\"midnightblue\", fill=True)\n", - " p += circle((x, y), vertex_radius, rgbcolor=\"black\", fill=False, thickness=1)\n", - " p += text(v, (x, y - 0.015 if v.isdigit() else y if v.upper() != v else y - 0.02), color=\"white\", fontsize=14, zorder=10)\n", - "\n", - "# Show without axes\n", - "p.show(figsize=(6, 6), axes=False, transparent=True)\n", - "\n", - "# Save without axes\n", - "p.save(\"../images/Degree6CounterExample.pdf\", figsize=(8, 8), axes=False)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "SageMath 10.3", - "language": "sage", - "name": "SageMath-10.3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Balaban10C/FitCycles.c b/Balaban10C/FitCycles.c deleted file mode 100644 index 60f4365..0000000 --- a/Balaban10C/FitCycles.c +++ /dev/null @@ -1,728 +0,0 @@ -// Attempts to fit length 10 cycles onto the given graph. -// A fitting must use each directed edge exactly once. -// Outputs a list of fitting cycles if they exist, or an error message if they -// don't. Optionally prints progress messages to stderr. -// Run with `make run` - -#include -#include -#include -#include -#include -#include - -// configuration options: -#define PRINT_PROGRESS true // whether to print progress messages -#define DEBUG false // whether to print debug messages -#define ADJACENCY_LIST_FILENAME "adjacency_list.txt" // input file -#define ADJACENCY_LIST_START 0 // change if vertex numbering doesn't start at 0 -#define OUTPUT_FILENAME "FitCycles.out" // output file - -// assumptions of the program (don't change these): -#define VERTEX_DEGREE 3 -#define VERTEX_USE_LIMIT VERTEX_DEGREE -#define MAX_VERTICES 65535 -#define MAX_EDGES 65535 -#define MAX_CYCLE_LENGTH 65535 -#define MAX_CYCLES 4294967295 - -// consequences of assumptions: -typedef uint8_t degree_t; -#define PRIdegree_t PRIu8 -typedef uint16_t vertex_t; -#define PRIvertex_t PRIu16 -#define SCNvertex_t SCNu16 -typedef uint16_t edge_t; -#define PRIedge_t PRIu16 -#define SCNedge_t SCNu16 -typedef vertex_t cycle_length_t; // max length should always be max vertices -#define PRIcycle_length_t PRIvertex_t -#define SCNcycle_length_t SCNvertex_t -typedef uint32_t cycle_index_t; -#define PRIcycle_index_t PRIu32 -#define SCNcycle_index_t SCNu32 -typedef vertex_t* adj_t; -typedef vertex_t* cycles_t; -typedef cycle_index_t* cbv_t; - -// macros -// assert(condition, message, ...fmt_args) -#define assert(condition, ...) \ - if (!(condition)) { \ - fprintf(stderr, __VA_ARGS__); \ - exit(1); \ - } - -// static variables -static FILE* output_file = NULL; - -// auxiliary data structures -adj_t adj_load(char* filename, vertex_t* num_vertices, edge_t* num_edges); -vertex_t* adj_get_neighbors(adj_t adjacency_list, vertex_t vertex); -void adj_remove_edge(adj_t adjacency_list, vertex_t start_vertex, - vertex_t end_vertex); -void adj_undo_remove_edge(adj_t adjacency_list, vertex_t start_vertex, - vertex_t end_vertex); -bool adj_has_edge(adj_t adjacency_list, vertex_t start_vertex, - vertex_t end_vertex); - -cycles_t cycle_generate(adj_t adjacency_list, vertex_t num_vertices, - cycle_length_t cycle_length, cycle_index_t* num_cycles); -vertex_t* cycle_get(cycles_t cycles, cycle_length_t cycle_length, - cycle_index_t cycle_index); - -cycle_index_t* cbv_generate(vertex_t num_vertices, cycles_t cycles, - cycle_index_t num_cycles, - cycle_length_t cycle_length, - cycle_index_t* max_cycles_per_vertex); -cycle_index_t* cbv_get_cycle_indices(cbv_t cycles_by_vertex, - cycle_index_t max_cycles_per_vertex, - vertex_t vertex, - cycle_index_t* num_cycles); - -void show_progress(double fraction); - -bool is_ijk_good(bool* used_cycles, cycles_t cycles, - cycle_length_t cycle_length, cycle_index_t num_cycles, - cycle_index_t cycle_to_check); -bool search(cycle_index_t cycles_to_use, bool* used_cycles, // state - degree_t* vertex_uses, cycle_index_t* max_fit, // state - uint64_t* num_search_calls, // state - vertex_t num_vertices, edge_t num_edges, adj_t adjacency_list, - cycle_length_t cycle_length, cycle_index_t num_cycles, - cycles_t cycles, cycle_index_t max_cycles_per_vertex, - cbv_t cycles_by_vertex); - -int main(void) { - if (PRINT_PROGRESS) { - fprintf(stderr, "Loading adjacency list...\n"); - } - - vertex_t num_vertices; - edge_t num_edges; - adj_t adjacency_list = - adj_load(ADJACENCY_LIST_FILENAME, &num_vertices, &num_edges); - - if (PRINT_PROGRESS) { - fprintf(stderr, "Generating auxiliary data structures...\n"); - } - - cycle_length_t cycle_length = 10; - cycle_index_t num_cycles; - cycles_t cycles = - cycle_generate(adjacency_list, num_vertices, cycle_length, &num_cycles); - - assert(cycle_length <= num_vertices, - "Cycle length (%" PRIcycle_length_t - ") must be less than or equal to the number of " - "vertices (%" PRIvertex_t ")\n", - cycle_length, num_vertices); - - cycle_index_t max_cycles_per_vertex; - cbv_t cycles_by_vertex = cbv_generate(num_vertices, cycles, num_cycles, - cycle_length, &max_cycles_per_vertex); - - output_file = fopen(OUTPUT_FILENAME, "w"); - - if (PRINT_PROGRESS) { - fprintf(stderr, "Starting search...\n"); - } - show_progress(0.0); - - // keep track of used cycles and vertices - cycle_index_t cycles_to_use = 2 * num_edges / cycle_length; - bool* used_cycles = (bool*)malloc(num_cycles * sizeof(bool)); - assert(used_cycles != NULL, "Error allocating memory for the used cycles\n"); - for (cycle_index_t i = 0; i < num_cycles; i++) { - used_cycles[i] = false; - } - // vertices should be used exactly VERTEX_USE_LIMIT times - // so we keep track of the number of times each vertex has been used. - // this allows us to fail early if a vertex can't be used enough times - // and to prioritize vertices exploring vertices that have been used more - // since they constrain the number of possible cycles containing them more - degree_t* vertex_uses = (degree_t*)malloc(num_vertices * sizeof(degree_t)); - assert(vertex_uses != NULL, - "Error allocating memory for the vertices most used order\n"); - - // search for a solution that starts with one of the cycles - cycle_index_t max_fit = 0; - uint64_t num_search_calls = 0; - for (cycle_index_t c = 0; c < num_cycles; c++) { - if (DEBUG) fprintf(stderr, "\nTrying cycle %d\n", c); - - // default all vertices to 0 uses - for (vertex_t i = 0; i < num_vertices; i++) { - vertex_uses[i] = 0; - } - - // mark start cycle as used - used_cycles[c] = true; - cycles_to_use--; - cycles_t cycle = cycle_get(cycles, cycle_length, c); - for (cycle_length_t i = 0; i < cycle_length; i++) { - adj_remove_edge(adjacency_list, cycle[i], cycle[i + 1]); - - // mark cycle vertices as used once - vertex_uses[cycle[i]] = 1; - } - - if (search(cycles_to_use, used_cycles, vertex_uses, &max_fit, - &num_search_calls, num_vertices, num_edges, adjacency_list, - cycle_length, num_cycles, cycles, max_cycles_per_vertex, - cycles_by_vertex)) { - // Success! - show_progress(1.0); - if (PRINT_PROGRESS) { - fprintf(stderr, "\nFound a solution! Check the output to see it.\n"); - } - fprintf(output_file, "Solution found in %" PRId64 " iterations:\n", - num_search_calls); - for (cycle_index_t i = 0; i < num_cycles; i++) { - if (used_cycles[i]) { - cycles_t cycle = cycle_get(cycles, cycle_length, i); - for (cycle_length_t j = 0; j < cycle_length + 1; j++) { - fprintf(output_file, "%" PRIvertex_t " ", - cycle[j] + ADJACENCY_LIST_START); - } - fprintf(output_file, "\n"); - } - } - free(adjacency_list); - free(cycles); - free(cycles_by_vertex); - free(used_cycles); - free(vertex_uses); - fclose(output_file); - return 0; - } - - // mark start cycle as unused - cycles_to_use++; - used_cycles[c] = false; - for (cycle_length_t i = 0; i < cycle_length; i++) { - adj_undo_remove_edge(adjacency_list, cycle[i], cycle[i + 1]); - } - - show_progress(c / (double)num_cycles); - } - - show_progress(1.0); - if (PRINT_PROGRESS) { - fprintf(stderr, - "\nDone. Did not find any solutions. Was only able to fit " - "%" PRIcycle_index_t " cycles. Used %" PRId64 " iterations.\n", - max_fit, num_search_calls); - } - free(adjacency_list); - free(cycles); - free(cycles_by_vertex); - free(used_cycles); - free(vertex_uses); - fclose(output_file); - return 0; -} - -void show_progress(double fraction) { - // E.g. [########## ] 50% - - if (!PRINT_PROGRESS) { - return; - } - - fflush(stderr); - fprintf(stderr, "\r["); - for (int i = 0; i < 50; i++) { - if (i < fraction * 50) { - fprintf(stderr, "#"); - } else { - fprintf(stderr, " "); - } - } - fprintf(stderr, "] %d%%", (int)(fraction * 100)); -} - -// if sequence i -> j -> k occurs in any of the used cycles such that k -> j -> -// i occurs in the cycle_to_check return false -// if no such sequence occurs return true -bool is_ijk_good(bool* used_cycles, cycles_t cycles, - cycle_length_t cycle_length, cycle_index_t num_cycles, - cycle_index_t cycle_to_check) { - vertex_t* cycle = cycle_get(cycles, cycle_length, cycle_to_check); - - vertex_t* padded_cycle = - (vertex_t*)malloc((cycle_length + 2) * sizeof(vertex_t)); - assert(padded_cycle != NULL, - "Error allocating memory for the padded cycle\n"); - for (cycle_length_t i = 0; i < cycle_length; i++) { - padded_cycle[i] = cycle[i]; - } - padded_cycle[cycle_length] = cycle[0]; - padded_cycle[cycle_length + 1] = cycle[1]; - - for (cycle_index_t c = 0; c < num_cycles; c++) { - if (used_cycles[c]) { - vertex_t* other_cycle = cycle_get(cycles, cycle_length, c); - - vertex_t* padded_other_cycle = - (vertex_t*)malloc((cycle_length + 2) * sizeof(vertex_t)); - assert(padded_other_cycle != NULL, - "Error allocating memory for the padded other cycle\n"); - for (cycle_length_t i = 0; i < cycle_length; i++) { - padded_other_cycle[i] = other_cycle[i]; - } - padded_other_cycle[cycle_length] = other_cycle[0]; - padded_other_cycle[cycle_length + 1] = other_cycle[1]; - - for (cycle_length_t i = 0; i < cycle_length; i++) { - for (cycle_length_t j = 0; j < cycle_length; j++) { - if (padded_cycle[i] == padded_other_cycle[j + 2] && - padded_cycle[i + 1] == padded_other_cycle[j + 1] && - padded_cycle[i + 2] == padded_other_cycle[j]) { - free(padded_cycle); - free(padded_other_cycle); - return false; - } - } - } - - free(padded_other_cycle); - } - } - - free(padded_cycle); - return true; -} - -bool search(cycle_index_t cycles_to_use, bool* used_cycles, // state - degree_t* vertex_uses, cycle_index_t* max_fit, // state - uint64_t* num_search_calls, // state - vertex_t num_vertices, edge_t num_edges, adj_t adjacency_list, - cycle_length_t cycle_length, cycle_index_t num_cycles, - cycles_t cycles, cycle_index_t max_cycles_per_vertex, - cbv_t cycles_by_vertex) { - (*num_search_calls)++; - - // pick a vertex to explore - // we pick the most used vertex that hasn't reached the limit since it - // constrains the search space of possible cycles more - vertex_t vertex = 0; - degree_t max_uses = 0; - for (vertex_t i = 0; i < num_vertices; i++) { - if (vertex_uses[i] < VERTEX_USE_LIMIT && vertex_uses[i] > max_uses) { - vertex = i; - max_uses = vertex_uses[i]; - - if (max_uses == VERTEX_USE_LIMIT - 1) { - break; // we can't do better than this - } - } - } - // if we've explored all vertices fully, this cannot be extended further - if (max_uses == VERTEX_USE_LIMIT) { - return false; - } - - // if we've reached a new maximum fit, print it - if (2 * num_edges / cycle_length - cycles_to_use > *max_fit) { - *max_fit = 2 * num_edges / cycle_length - cycles_to_use; - fprintf(output_file, - "New max fit: %" PRIcycle_index_t - " (about to try vertex %" PRIvertex_t ")\n", - *max_fit, vertex); - for (cycle_index_t i = 0; i < num_cycles; i++) { - if (used_cycles[i]) { - vertex_t* cycle = cycle_get(cycles, cycle_length, i); - for (cycle_length_t j = 0; j < cycle_length + 1; j++) { - fprintf(output_file, "%" PRIvertex_t " ", - cycle[j] + ADJACENCY_LIST_START); - } - fprintf(output_file, "\n"); - } - } - fprintf(output_file, "\n"); - fflush(output_file); - } - - // look through the possible cycles that contain this vertex - // if none can be used, this is a failed end and we backtrack - // otherwise, we have our solution - cycle_index_t num_cycles_for_vertex; - cbv_t cycle_indices = cbv_get_cycle_indices( - cycles_by_vertex, max_cycles_per_vertex, vertex, &num_cycles_for_vertex); - for (cycle_index_t i = 0; i < num_cycles_for_vertex; i++) { - // skip if the cycle is already used - cycle_index_t cycle_index = cycle_indices[i]; - if (used_cycles[cycle_index]) { - continue; - } - - vertex_t* cycle = cycle_get(cycles, cycle_length, cycle_index); - - // cycle is only usable if all edges are available - bool can_use = true; - for (cycle_length_t j = 0; j < cycle_length; j++) { - if (!adj_has_edge(adjacency_list, cycle[j], cycle[j + 1])) { - can_use = false; - break; - } - } - if (!can_use) { - continue; - } - - // make sure the cycle satisfies the ijk condition - if (!is_ijk_good(used_cycles, cycles, cycle_length, num_cycles, - cycle_index)) { - continue; - } - - // use the cycle - if (DEBUG) - fprintf(stderr, "Using cycle %" PRIcycle_index_t "\n", cycle_index); - used_cycles[cycle_index] = true; - for (cycle_length_t j = 0; j < cycle_length; j++) { - adj_remove_edge(adjacency_list, cycle[j], cycle[j + 1]); - - // mark cycle vertices as used - vertex_uses[cycle[j]]++; - assert(vertex_uses[cycle[j]] <= VERTEX_USE_LIMIT, - "Vertex %" PRIvertex_t " used too many times\n", cycle[j]); - } - - // if this is the final cycle needed to cover all edges, we're done - if (cycles_to_use == 1) { - return true; - } - // otherwise, continue adding cycles - if (search(cycles_to_use - 1, used_cycles, vertex_uses, max_fit, - num_search_calls, num_vertices, num_edges, adjacency_list, - cycle_length, num_cycles, cycles, max_cycles_per_vertex, - cycles_by_vertex)) { - return true; // as soon as we succeed, we're done - } - - // un-use the cycle - used_cycles[cycle_index] = false; - for (uint8_t j = 0; j < cycle_length; j++) { - adj_undo_remove_edge(adjacency_list, cycle[j], cycle[j + 1]); - - // un-use the cycle vertices - vertex_uses[cycle[j]]--; - } - } - - // if we haven't returned true by now, we've failed - return false; -} - -adj_t adj_load(char* filename, vertex_t* num_vertices, edge_t* num_edges) { - FILE* fp = fopen(filename, "r"); - assert(fp != NULL, "Error opening file %s\n", filename); - - // number of vertices and edges are the two first numbers - assert(fscanf(fp, "%" SCNvertex_t " %" SCNedge_t "", num_vertices, - num_edges) == 2, - "Error reading the first line of %s\n", filename); - - adj_t adjacency_list = - (adj_t)malloc(*num_vertices * VERTEX_DEGREE * sizeof(vertex_t)); - assert(adjacency_list != NULL, - "Error allocating memory for the adjacency list\n"); - for (vertex_t i = 0; i < *num_vertices * VERTEX_DEGREE; i++) { - assert(fscanf(fp, "%" SCNvertex_t, &adjacency_list[i]) == 1, - "Error reading the adjacency list from %s\n", filename); - adjacency_list[i] -= ADJACENCY_LIST_START; - } - - fclose(fp); - - if (PRINT_PROGRESS) { - fprintf(stderr, "Read the adjacency list from %s\n", filename); - fprintf(stderr, "\tNumber of vertices: %" PRIvertex_t " \n", *num_vertices); - fprintf(stderr, - "\tNumber of edges: %" PRIedge_t " (%" PRIedge_t " directed)\n", - *num_edges, 2 * *num_edges); - fprintf(stderr, "\tFirst 5 vertices (with neighbors): "); - for (vertex_t v = 0; v < 5; v++) { - fprintf(stderr, - "%" PRIvertex_t "(%" PRIvertex_t " %" PRIvertex_t " %" PRIvertex_t - ") ", - v, adj_get_neighbors(adjacency_list, v)[0] + ADJACENCY_LIST_START, - adj_get_neighbors(adjacency_list, v)[1] + ADJACENCY_LIST_START, - adj_get_neighbors(adjacency_list, v)[2] + ADJACENCY_LIST_START); - } - fprintf(stderr, "\n"); - } - - return adjacency_list; -} - -vertex_t* adj_get_neighbors(adj_t adjacency_list, vertex_t vertex) { - return &adjacency_list[vertex * VERTEX_DEGREE]; -} - -void adj_remove_edge(adj_t adjacency_list, vertex_t start_vertex, - vertex_t end_vertex) { - vertex_t* neighbors = adj_get_neighbors(adjacency_list, start_vertex); - for (degree_t i = 0; i < VERTEX_DEGREE; i++) { - if (neighbors[i] == end_vertex) { - neighbors[i] = MAX_VERTICES; - return; - } - } -} - -// must have been previously removed, otherwise undefined behavior -void adj_undo_remove_edge(adj_t adjacency_list, vertex_t start_vertex, - vertex_t end_vertex) { - vertex_t* neighbors = adj_get_neighbors(adjacency_list, start_vertex); - for (degree_t i = 0; i < VERTEX_DEGREE; i++) { - if (neighbors[i] == MAX_VERTICES) { - neighbors[i] = end_vertex; - return; - } - } -} - -bool adj_has_edge(adj_t adjacency_list, vertex_t start_vertex, - vertex_t end_vertex) { - vertex_t* neighbors = adj_get_neighbors(adjacency_list, start_vertex); - for (degree_t i = 0; i < VERTEX_DEGREE; i++) { - if (neighbors[i] == end_vertex) { - return true; - } - } - return false; -} - -struct fifo { - vertex_t* data; - cycle_index_t head; - cycle_index_t tail; - cycle_index_t capacity; - cycle_length_t path_length; -}; -void fifo_init(struct fifo* fifo, cycle_index_t initial_capacity, - cycle_length_t path_length) { - fifo->data = - (vertex_t*)malloc(initial_capacity * path_length * sizeof(vertex_t)); - assert(fifo->data != NULL, "Error allocating memory for the fifo\n"); - fifo->head = 0; - fifo->tail = 0; - fifo->capacity = initial_capacity; - fifo->path_length = path_length; -} -bool fifo_empty(struct fifo* fifo) { return fifo->head == fifo->tail; } -void fifo_push(struct fifo* fifo, vertex_t* path) { - if ((fifo->tail + 1) % fifo->capacity == fifo->head) { - // double the capacity - vertex_t* new_data = (vertex_t*)malloc( - 2 * fifo->capacity * fifo->path_length * sizeof(vertex_t)); - assert(new_data != NULL, "Error allocating memory for the fifo\n"); - for (cycle_index_t i = 0; i < fifo->capacity; i++) { - for (cycle_length_t j = 0; j < fifo->path_length; j++) { - new_data[i * fifo->path_length + j] = - fifo->data[((fifo->head + i) % fifo->capacity) * fifo->path_length + - j]; - } - } - free(fifo->data); - fifo->data = new_data; - fifo->head = 0; - fifo->tail = fifo->capacity - 1; - fifo->capacity *= 2; - } - - for (cycle_length_t i = 0; i < fifo->path_length; i++) { - fifo->data[fifo->tail * fifo->path_length + i] = path[i]; - } - fifo->tail = (fifo->tail + 1) % fifo->capacity; -} -void fifo_pop(struct fifo* fifo, vertex_t* path) { - for (cycle_length_t i = 0; i < fifo->path_length; i++) { - path[i] = fifo->data[fifo->head * fifo->path_length + i]; - } - fifo->head = (fifo->head + 1) % fifo->capacity; -} -cycle_index_t fifo_size(struct fifo* fifo) { - return (fifo->tail - fifo->head + fifo->capacity) % fifo->capacity; -} -void fifo_free(struct fifo* fifo) { - free(fifo->data); - fifo->data = NULL; -} - -cycles_t cycle_generate(adj_t adjacency_list, vertex_t num_vertices, - cycle_length_t cycle_length, - cycle_index_t* num_cycles) { - vertex_t* buffer = (vertex_t*)malloc((cycle_length + 1) * sizeof(vertex_t)); - - struct fifo cycle_list; - fifo_init(&cycle_list, cycle_length * num_vertices, cycle_length + 1); - struct fifo queue; - fifo_init(&queue, cycle_length * num_vertices, cycle_length + 1); - - for (cycle_length_t i = 2; i < cycle_length + 1; i++) { - buffer[i] = 0; - } - for (vertex_t i = 0; i < num_vertices; i++) { - buffer[0] = 1; - buffer[1] = i; - fifo_push(&queue, buffer); - } - while (!fifo_empty(&queue)) { - fifo_pop(&queue, buffer); - cycle_length_t path_length = buffer[0]; - vertex_t* path = &buffer[1]; - vertex_t* neighbors = - adj_get_neighbors(adjacency_list, path[path_length - 1]); - if (path_length == cycle_length) { - for (degree_t i = 0; i < VERTEX_DEGREE; i++) { - if (neighbors[i] == path[0]) { - for (cycle_length_t j = 0; j < cycle_length; j++) { - buffer[j] = path[j]; - } - buffer[cycle_length] = buffer[0]; - fifo_push(&cycle_list, buffer); - break; - } - } - } else { - for (degree_t i = 0; i < VERTEX_DEGREE; i++) { - vertex_t neighbor = neighbors[i]; - if (neighbor <= path[0]) { - continue; - } - bool neighbor_in_path = false; - for (cycle_length_t j = 0; j < path_length; j++) { - if (path[j] == neighbor) { - neighbor_in_path = true; - break; - } - } - if (!neighbor_in_path) { - buffer[0] = path_length + 1; - path[path_length] = neighbor; - fifo_push(&queue, buffer); - } - } - } - } - - fifo_free(&queue); - free(buffer); - *num_cycles = fifo_size(&cycle_list); - vertex_t* cycles = (vertex_t*)realloc( - cycle_list.data, *num_cycles * (cycle_length + 1) * sizeof(vertex_t)); - assert(cycles != NULL, "Error reallocating memory for the cycles\n"); - cycle_list.data = NULL; - fifo_free(&cycle_list); - - if (PRINT_PROGRESS) { - fprintf(stderr, "Generated cycles of length: %" PRIcycle_length_t "\n", - cycle_length); - fprintf(stderr, "\tNumber of cycles: %" PRIcycle_index_t "\n", *num_cycles); - fprintf(stderr, "\tFirst 5 cycles:\n"); - for (cycle_index_t i = 0; i < 5; i++) { - fprintf(stderr, "\t\t%d: ", i); - for (cycle_length_t j = 0; j < cycle_length + 1; j++) { - fprintf(stderr, "%02" PRIvertex_t " ", - cycle_get(cycles, cycle_length, i)[j]); - } - fprintf(stderr, "\n"); - } - } - - return cycles; -} - -vertex_t* cycle_get(cycles_t cycles, cycle_length_t cycle_length, - cycle_index_t cycle_index) { - return &cycles[cycle_index * (cycle_length + 1)]; -} - -cycle_index_t* cbv_generate(vertex_t num_vertices, cycles_t cycles, - cycle_index_t num_cycles, - cycle_length_t cycle_length, - cycle_index_t* max_cycles_per_vertex) { - // find the number of cycles per vertex - cycle_index_t* cycles_per_vertex = - (cycle_index_t*)malloc(num_vertices * sizeof(cycle_index_t)); - assert(cycles_per_vertex != NULL, - "Error allocating memory for the cycles per vertex\n"); - for (cycle_index_t i = 0; i < num_cycles; i++) { - for (cycle_length_t j = 0; j < cycle_length; j++) { - cycles_per_vertex[cycle_get(cycles, cycle_length, i)[j]]++; - } - } - - // find the maximum number of cycles per vertex - *max_cycles_per_vertex = 0; - for (vertex_t i = 0; i < num_vertices; i++) { - if (cycles_per_vertex[i] > *max_cycles_per_vertex) { - *max_cycles_per_vertex = cycles_per_vertex[i]; - } - } - - cbv_t cycles_by_vertex = (cbv_t)malloc( - num_vertices * (*max_cycles_per_vertex + 1) * sizeof(cycle_index_t)); - assert(cycles_by_vertex != NULL, - "Error allocating memory for the cycles by vertex\n"); - - // fill in the cycles by vertex - for (vertex_t i = 0; i < num_vertices; i++) { - cycles_by_vertex[i * (*max_cycles_per_vertex + 1)] = cycles_per_vertex[i]; - cycle_index_t num_cycles_for_vertex = 0; - for (cycle_index_t j = 0; - j < num_cycles && num_cycles_for_vertex < cycles_per_vertex[i]; j++) { - bool cycle_contains_vertex = false; - for (cycle_length_t k = 0; k < cycle_length; k++) { - if (cycle_get(cycles, cycle_length, j)[k] == i) { - cycle_contains_vertex = true; - break; - } - } - if (cycle_contains_vertex) { - cycles_by_vertex[i * (*max_cycles_per_vertex + 1) + - num_cycles_for_vertex + 1] = j; - num_cycles_for_vertex++; - } - } - assert(num_cycles_for_vertex == cycles_per_vertex[i], - "Error filling in the cycles by vertex\n") - } - - if (PRINT_PROGRESS) { - fprintf(stderr, "Organized cycles by vertex\n"); - fprintf(stderr, "\tMax cycles per vertex: %" PRIcycle_index_t "\n", - *max_cycles_per_vertex); - fprintf(stderr, "\tLast 2 cycles of vertex 0 and 1:\n"); - for (uint8_t i = num_vertices - 2; i < num_vertices; i++) { - cycle_index_t num_cycles; - cycle_index_t* cycle_indices = cbv_get_cycle_indices( - cycles_by_vertex, *max_cycles_per_vertex, i, &num_cycles); - fprintf(stderr, "\t\t%d:\n", i); - for (cycle_index_t j = 0; j < num_cycles && j < 2; j++) { - fprintf(stderr, "\t\t\t%" PRIcycle_index_t " / %" PRIcycle_index_t ": ", - j, num_cycles); - for (cycle_length_t h = 0; h < cycle_length + 1; h++) { - fprintf(stderr, "%02" PRIvertex_t " ", - cycle_get(cycles, cycle_length, cycle_indices[j])[h]); - } - fprintf(stderr, "\n"); - } - } - } - - return cycles_by_vertex; -} - -cycle_index_t* cbv_get_cycle_indices(cbv_t cycles_by_vertex, - cycle_index_t max_cycles_per_vertex, - vertex_t vertex, - cycle_index_t* num_cycles) { - cycle_index_t* row = &cycles_by_vertex[vertex * (max_cycles_per_vertex + 1)]; - *num_cycles = row[0]; - return &row[1]; -} diff --git a/Balaban10C/FitCycles.out b/Balaban10C/FitCycles.out deleted file mode 100644 index 5cbcf7c..0000000 --- a/Balaban10C/FitCycles.out +++ /dev/null @@ -1,150 +0,0 @@ -New max fit: 1 (about to try vertex 0) -0 2 4 6 8 32 33 48 47 18 0 - -New max fit: 2 (about to try vertex 0) -0 2 4 6 8 32 33 48 47 18 0 -0 18 16 44 66 53 58 65 50 20 0 - -New max fit: 3 (about to try vertex 2) -0 2 4 6 8 32 33 48 47 18 0 -0 18 16 44 66 53 58 65 50 20 0 -0 20 21 36 35 60 67 52 23 2 0 - -New max fit: 4 (about to try vertex 4) -0 2 4 6 8 32 33 48 47 18 0 -0 18 16 44 66 53 58 65 50 20 0 -0 20 21 36 35 60 67 52 23 2 0 -2 23 24 39 38 62 69 54 26 4 2 - -New max fit: 5 (about to try vertex 6) -0 2 4 6 8 32 33 48 47 18 0 -0 18 16 44 66 53 58 65 50 20 0 -0 20 21 36 35 60 67 52 23 2 0 -2 23 24 39 38 62 69 54 26 4 2 -4 26 27 42 41 64 51 56 29 6 4 - -New max fit: 6 (about to try vertex 8) -0 2 4 6 8 32 33 48 47 18 0 -0 18 16 44 66 53 58 65 50 20 0 -0 20 21 36 35 60 67 52 23 2 0 -2 23 24 39 38 62 69 54 26 4 2 -4 26 27 42 41 64 51 56 29 6 4 -6 29 30 45 44 16 14 12 10 8 6 - -New max fit: 7 (about to try vertex 10) -0 2 4 6 8 32 33 48 47 18 0 -0 18 16 44 66 53 58 65 50 20 0 -0 20 21 36 35 60 67 52 23 2 0 -2 23 24 39 38 62 69 54 26 4 2 -4 26 27 28 5 7 31 30 29 6 4 -6 29 56 63 68 55 60 35 10 8 6 -8 10 12 14 41 42 43 65 58 32 8 - -New max fit: 8 (about to try vertex 12) -0 2 4 6 8 32 33 48 47 18 0 -0 18 16 44 66 53 58 65 50 20 0 -0 20 21 36 35 60 67 52 23 2 0 -2 23 24 25 3 5 28 27 26 4 2 -4 26 54 69 62 57 31 30 29 6 4 -6 29 56 63 68 55 60 35 10 8 6 -8 10 12 14 41 42 43 65 58 32 8 -10 35 36 37 11 13 40 39 38 12 10 - -New max fit: 9 (about to try vertex 16) -0 2 4 6 8 32 33 48 47 18 0 -0 18 16 14 41 64 51 22 21 20 0 -0 20 50 65 58 53 25 24 23 2 0 -2 23 52 67 60 55 28 27 26 4 2 -4 26 54 61 66 44 45 30 29 6 4 -6 29 56 63 68 55 60 35 10 8 6 -8 10 12 14 16 44 66 53 58 32 8 -10 35 36 37 11 13 40 39 38 12 10 -12 38 62 69 54 26 27 42 41 14 12 - -New max fit: 10 (about to try vertex 20) -0 2 4 6 29 56 51 22 21 20 0 -0 18 47 48 33 34 59 52 23 2 0 -0 20 50 57 31 30 45 44 16 18 0 -2 23 24 25 3 5 28 27 26 4 2 -4 26 54 61 66 53 58 32 8 6 4 -6 8 10 35 60 67 46 45 30 29 6 -8 32 33 48 49 69 62 38 12 10 8 -10 12 14 16 44 66 61 37 36 35 10 -12 38 39 40 13 15 43 42 41 14 12 -14 41 64 51 56 63 68 47 18 16 14 - -New max fit: 11 (about to try vertex 21) -0 2 4 6 29 56 51 22 21 20 0 -0 18 47 68 63 40 39 24 23 2 0 -0 20 50 57 31 30 45 44 16 18 0 -2 23 52 67 60 55 28 27 26 4 2 -4 26 54 69 49 48 33 32 8 6 4 -6 8 10 35 60 67 46 45 30 29 6 -8 32 58 65 43 42 41 14 12 10 8 -10 12 38 62 69 54 61 37 36 35 10 -11 13 15 43 65 50 20 21 36 37 11 -12 14 16 44 66 53 25 24 39 38 12 -14 41 64 59 34 33 48 47 18 16 14 - -New max fit: 12 (about to try vertex 13) -0 2 4 6 29 30 31 57 50 20 0 -0 18 47 68 55 60 67 52 23 2 0 -0 20 21 36 37 61 66 44 16 18 0 -1 22 21 20 50 65 43 15 17 19 1 -2 23 24 25 3 5 28 27 26 4 2 -4 26 54 69 49 48 33 32 8 6 4 -6 8 10 35 36 21 22 51 56 29 6 -8 32 58 65 50 57 62 38 12 10 8 -9 34 59 52 67 46 17 15 13 11 9 -10 12 14 16 44 45 46 67 60 35 10 -12 38 39 40 13 15 43 42 41 14 12 -14 41 64 59 34 33 48 47 18 16 14 - -New max fit: 13 (about to try vertex 3) -0 2 4 26 54 69 49 48 47 18 0 -0 18 16 44 66 61 37 36 21 20 0 -0 20 50 65 58 53 25 24 23 2 0 -1 3 5 7 31 57 50 20 21 22 1 -1 19 49 69 62 38 39 24 25 3 1 -1 22 51 64 41 42 43 15 17 19 1 -2 23 52 67 46 45 30 29 6 4 2 -4 6 8 32 58 65 43 42 27 26 4 -6 29 56 51 22 21 36 35 10 8 6 -8 10 12 14 41 64 59 34 33 32 8 -10 35 60 55 68 63 40 39 38 12 10 -12 38 62 57 31 30 45 44 16 14 12 -14 16 18 47 68 55 28 27 42 41 14 - -New max fit: 14 (about to try vertex 3) -0 2 4 26 54 69 49 48 47 18 0 -0 18 16 44 45 30 31 57 50 20 0 -0 20 21 22 1 3 25 24 23 2 0 -1 19 49 69 62 57 31 7 5 3 1 -1 22 51 64 41 42 43 15 17 19 1 -2 23 52 59 64 51 56 29 6 4 2 -4 6 8 32 58 65 43 42 27 26 4 -6 29 30 45 46 67 60 35 10 8 6 -8 10 12 14 41 64 59 34 33 32 8 -10 35 36 37 11 13 40 39 38 12 10 -12 38 62 69 54 61 66 44 16 14 12 -14 16 18 47 68 55 28 27 42 41 14 -20 50 65 58 53 66 61 37 36 21 20 -21 36 35 60 55 68 63 56 51 22 21 - -New max fit: 15 (about to try vertex 12) -0 2 23 52 59 64 41 14 16 18 0 -0 18 47 48 49 19 1 22 21 20 0 -0 20 50 65 43 42 27 26 4 2 0 -1 3 5 28 27 42 41 64 51 22 1 -1 19 17 46 67 52 23 24 25 3 1 -2 4 6 29 56 63 40 39 24 23 2 -3 25 53 58 65 50 57 31 7 5 3 -4 26 54 69 49 48 33 32 8 6 4 -5 7 9 34 59 52 67 60 55 28 5 -6 8 10 35 60 67 46 45 30 29 6 -7 31 30 45 44 66 61 37 11 9 7 -8 32 58 53 66 44 16 14 12 10 8 -9 11 13 15 43 65 58 32 33 34 9 -10 12 38 39 40 13 11 37 36 35 10 -24 39 38 62 69 54 61 66 53 25 24 - diff --git a/Balaban10C/adjacency_list.txt b/Balaban10C/adjacency_list.txt deleted file mode 100644 index 9ef5e30..0000000 --- a/Balaban10C/adjacency_list.txt +++ /dev/null @@ -1,71 +0,0 @@ -70 105 -2 18 20 -3 19 22 -0 4 23 -1 5 25 -2 6 26 -3 7 28 -4 8 29 -5 9 31 -32 6 10 -34 7 11 -35 8 12 -37 9 13 -38 10 14 -40 11 15 -16 41 12 -17 43 13 -18 44 14 -19 46 15 -0 16 47 -1 17 49 -0 50 21 -36 20 22 -1 51 21 -2 52 24 -39 23 25 -3 53 24 -4 54 27 -42 26 28 -5 55 27 -6 56 30 -45 29 31 -7 57 30 -33 8 58 -32 48 34 -33 9 59 -36 10 60 -35 37 21 -36 11 61 -39 12 62 -38 40 24 -39 13 63 -64 42 14 -41 43 27 -65 42 15 -16 66 45 -44 30 46 -17 67 45 -48 18 68 -33 49 47 -48 19 69 -65 20 57 -64 22 56 -67 23 59 -66 25 58 -69 26 61 -68 60 28 -51 29 63 -50 62 31 -32 65 53 -64 34 52 -35 67 55 -66 37 54 -69 38 57 -68 40 56 -51 41 59 -50 58 43 -53 44 61 -52 60 46 -55 63 47 -49 54 62 diff --git a/Balaban10C/explore.ipynb b/Balaban10C/explore.ipynb deleted file mode 100644 index 1d9ce56..0000000 --- a/Balaban10C/explore.ipynb +++ /dev/null @@ -1,212 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "import networkx as nx\n", - "import matplotlib.pyplot as plt\n", - "from sage.all import *" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "g = graphs.Balaban10Cage(embedding=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "NUM_VERTICES = g.num_verts()\n", - "NUM_EDGES = g.size()\n", - "VERTEX_DEGREE = g.degree()[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "adjacency_matrix = g.adjacency_matrix()\n", - "adjacency_list = [ [0 for i in range(VERTEX_DEGREE)] for j in range(NUM_VERTICES)]\n", - "for i in range(NUM_VERTICES):\n", - " d = 0\n", - " for j in range(NUM_VERTICES):\n", - " if adjacency_matrix[i][j] == 1:\n", - " adjacency_list[i][d] = j\n", - " d += 1" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "# find the number of cycles of length k\n", - "\n", - "# https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1602189\n", - "# We use a FIFO queue to store the open paths and a register to \n", - "# record the length of the path. The register is not necessary, \n", - "# because you can always get the length from the open path directly.\n", - "# The algorithm starts with all vertices of the graph. First,\n", - "# put all vertices into the queue and set the register to 0.\n", - "# Then the iteration of main loop of the algorithm starts.\n", - "# Fetch an open path from the queue. Its length is k which\n", - "# is indicated by the register.\n", - "# Verify if there is an edge which links the tail to the head\n", - "# of the open path. If it is true, a cycle is enumerated, and\n", - "# then output the cycle. When the register is 0 in such case, it\n", - "# means the cycle is a selfloop.\n", - "# Then get an adjacent edge of the tail whose end does not\n", - "# occur in the open path and the order of its end is greater than\n", - "# the order of the head. This edge and the k length open path\n", - "# construct a new k + 1 length open path. Put this new open\n", - "# path into the queue.\n", - "# After having generated all the k + 1 length open paths\n", - "# from the k length open path, if this open path is the last k\n", - "# length open path of the queue, set register to k + 1.\n", - "# If the queue is empty, the algorithm finishes, else jumps\n", - "# to where the main loop starts.\n", - "\n", - "def find_cycles(k):\n", - " cycles = []\n", - " queue = []\n", - " for i in range(NUM_VERTICES):\n", - " queue.append([i])\n", - " while len(queue) > 0:\n", - " path = queue.pop(0)\n", - " if len(path) == k:\n", - " if path[0] in adjacency_list[path[-1]]:\n", - " cycle = path + [path[0]]\n", - " cycles.append(cycle)\n", - " continue\n", - " for i in adjacency_list[path[-1]]:\n", - " if i not in path and i > path[0]:\n", - " queue.append(path + [i])\n", - " return cycles\n", - "\n", - "assert len(find_cycles(9)) == 0\n", - "assert len(find_cycles(10)) == 528\n", - "assert len(find_cycles(11)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=11) if len(c) == 11 + 1 ])\n", - "assert len(find_cycles(12)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=12) if len(c) == 12 + 1 ])\n", - "assert len(find_cycles(13)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=13) if len(c) == 13 + 1 ])\n", - "assert len(find_cycles(14)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=14) if len(c) == 14 + 1 ])\n", - "assert len(find_cycles(15)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=15) if len(c) == 15 + 1 ])\n", - "assert len(find_cycles(16)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=16) if len(c) == 16 + 1 ])\n", - "assert len(find_cycles(17)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=17) if len(c) == 17 + 1 ])" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "2160" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(find_cycles(14))" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "2160" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len([ c for c in g.to_directed().all_simple_cycles(max_length=14) if len(c) == 14 + 1 ])" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "4200" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "(14 + 13 + 12 + 11 + 10) * 70" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(find_cycles(9))" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "SageMath 10.3", - "language": "sage", - "name": "SageMath-10.3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Balaban10C/makefile b/Balaban10C/makefile deleted file mode 100644 index e8bbcba..0000000 --- a/Balaban10C/makefile +++ /dev/null @@ -1,11 +0,0 @@ -all: FitCycles - -run: FitCycles - ./FitCycles - -FitCycles: FitCycles.c - gcc -Wall -std=c17 -pedantic -g -o FitCycles FitCycles.c - -clean: - rm -f FitCycles *.o - rm -rf *.dSYM diff --git a/CITATION.cff b/CITATION.cff new file mode 100644 index 0000000..ce2a8f2 --- /dev/null +++ b/CITATION.cff @@ -0,0 +1,19 @@ +cff-version: 1.2.0 +message: "If you use this software or cite this paper, please use the metadata below." +authors: + - family-names: "Metzger" + given-names: "Alexander" + - family-names: "Ulrigg" + given-names: "Austin" +title: "An efficient genus algorithm based on graph rotations" +type: article +doi: "10.1016/j.disc.2026.115308" +journal: "Discrete Mathematics" +volume: 349 +issue: 12 +start: 115308 +year: 2026 +month: 12 +date-released: "2026-12-01" +publisher: + name: "Elsevier BV" diff --git a/CalcCycles/19CycleAdjList.txt b/CalcCycles/19CycleAdjList.txt deleted file mode 100644 index 6a67718..0000000 --- a/CalcCycles/19CycleAdjList.txt +++ /dev/null @@ -1,70 +0,0 @@ -19 3 21 -4 20 23 -1 5 24 -2 26 6 -3 27 7 -4 8 29 -9 5 30 -6 10 32 -33 11 7 -8 12 35 -9 13 36 -10 14 38 -11 15 39 -12 16 41 -13 42 17 -14 44 18 -19 45 15 -16 47 20 -1 48 17 -2 50 18 -1 22 51 -21 23 37 -22 2 52 -3 53 25 -26 24 40 -4 25 54 -55 5 28 -29 27 43 -6 28 56 -57 7 31 -30 46 32 -8 31 58 -9 34 59 -33 35 49 -34 60 10 -61 11 37 -38 36 22 -12 37 62 -40 63 13 -41 39 25 -14 40 64 -65 43 15 -44 28 42 -66 43 16 -46 67 17 -31 45 47 -68 46 18 -19 49 69 -48 34 50 -49 70 20 -58 66 21 -65 23 57 -24 68 60 -59 26 67 -70 62 27 -69 29 61 -64 30 52 -51 63 32 -66 54 33 -53 65 35 -68 36 56 -38 67 55 -58 39 70 -57 69 41 -52 60 42 -51 44 59 -54 45 62 -47 53 61 -48 56 64 -55 63 50 diff --git a/CalcCycles/BalabanOutput.txt b/CalcCycles/BalabanOutput.txt deleted file mode 100644 index 7140de6..0000000 --- a/CalcCycles/BalabanOutput.txt +++ /dev/null @@ -1,288 +0,0 @@ -19 Cycles created -Cycle 1: -Length: 10 -3, 1 -1, 21 -21, 22 -22, 23 -23, 2 -2, 4 -4, 26 -26, 25 -25, 24 -24, 3 - - -Cycle 2: -Length: 10 -1, 3 -3, 5 -5, 27 -27, 28 -28, 43 -43, 42 -42, 15 -15, 17 -17, 19 -19, 1 - - -Cycle 3: -Length: 16 -33, 9 -9, 11 -11, 13 -13, 15 -15, 42 -42, 65 -65, 52 -52, 23 -23, 22 -22, 37 -37, 38 -38, 62 -62, 67 -67, 54 -54, 59 -59, 33 - - -Cycle 4: -Length: 10 -40, 25 -25, 26 -26, 54 -54, 67 -67, 45 -45, 17 -17, 15 -15, 13 -13, 39 -39, 40 - - -Cycle 5: -Length: 10 -69, 56 -56, 29 -29, 6 -6, 4 -4, 2 -2, 20 -20, 50 -50, 49 -49, 48 -48, 69 - - -Cycle 6: -Length: 10 -5, 3 -3, 24 -24, 53 -53, 68 -68, 61 -61, 36 -36, 11 -11, 9 -9, 7 -7, 5 - - -Cycle 7: -Length: 10 -44, 16 -16, 18 -18, 47 -47, 68 -68, 53 -53, 60 -60, 65 -65, 42 -42, 43 -43, 44 - - -Cycle 8: -Length: 10 -40, 39 -39, 63 -63, 70 -70, 50 -50, 20 -20, 18 -18, 16 -16, 14 -14, 41 -41, 40 - - -Cycle 9: -Length: 10 -7, 30 -30, 31 -31, 46 -46, 45 -45, 67 -67, 62 -62, 55 -55, 27 -27, 5 -5, 7 - - -Cycle 10: -Length: 10 -70, 63 -63, 58 -58, 32 -32, 8 -8, 6 -6, 29 -29, 28 -28, 27 -27, 55 -55, 70 - - -Cycle 11: -Length: 14 -2, 23 -23, 52 -52, 57 -57, 64 -64, 69 -69, 48 -48, 19 -19, 17 -17, 45 -45, 46 -46, 47 -47, 18 -18, 20 -20, 2 - - -Cycle 12: -Length: 14 -57, 30 -30, 7 -7, 9 -9, 33 -33, 34 -34, 35 -35, 60 -60, 53 -53, 24 -24, 25 -25, 40 -40, 41 -41, 64 -64, 57 - - -Cycle 13: -Length: 12 -8, 10 -10, 12 -12, 14 -14, 16 -16, 44 -44, 66 -66, 59 -59, 54 -54, 26 -26, 4 -4, 6 -6, 8 - - -Cycle 14: -Length: 10 -37, 22 -22, 21 -21, 51 -51, 58 -58, 63 -63, 39 -39, 13 -13, 11 -11, 36 -36, 37 - - -Cycle 15: -Length: 10 -36, 61 -61, 56 -56, 69 -69, 64 -64, 41 -41, 14 -14, 12 -12, 38 -38, 37 -37, 36 - - -Cycle 16: -Length: 14 -58, 51 -51, 66 -66, 44 -44, 43 -43, 28 -28, 29 -29, 56 -56, 61 -61, 68 -68, 47 -47, 46 -46, 31 -31, 32 -32, 58 - - -Cycle 17: -Length: 10 -60, 35 -35, 10 -10, 8 -8, 32 -32, 31 -31, 30 -30, 57 -57, 52 -52, 65 -65, 60 - - -Cycle 18: -Length: 10 -48, 49 -49, 34 -34, 33 -33, 59 -59, 66 -66, 51 -51, 21 -21, 1 -1, 19 -19, 48 - - -Cycle 19: -Length: 10 -38, 12 -12, 10 -10, 35 -35, 34 -34, 49 -49, 50 -50, 70 -70, 55 -55, 62 -62, 38 - - -No cycles over 12 found. diff --git a/CalcCycles/BalabanRandomAdjCycle.java b/CalcCycles/BalabanRandomAdjCycle.java deleted file mode 100644 index 460eb16..0000000 --- a/CalcCycles/BalabanRandomAdjCycle.java +++ /dev/null @@ -1,148 +0,0 @@ -import java.io.File; -import java.io.FileNotFoundException; -import java.io.PrintStream; -import java.util.*; - -public class BalabanRandomAdjCycle { - public static void main(String[] args) throws FileNotFoundException { - File outputFile = new File("BalabanOutput.txt"); - PrintStream output = new PrintStream(outputFile); - boolean found = false; - for (int i = 0; i < 1; i++) { - // randomize(); // GET RID OF FOR NON RANDOM CALL - int[][] test = new int[70][3]; - File myFile = new File("19CycleAdjList.txt"); - Scanner fileScan = new Scanner(myFile); - int line = 0; - while (fileScan.hasNextLine()) { - String currentLine = fileScan.nextLine(); - Scanner lineScan = new Scanner(currentLine); - test[line][0] = Integer.parseInt(lineScan.next()); - test[line][1] = Integer.parseInt(lineScan.next()); - test[line][2] = Integer.parseInt(lineScan.next()); - line++; - } - Set edges = getEdges(test); - int startPrevRow = 0; - int startRow = 0; - - List cycles = new ArrayList<>(); - for (int[] curr : edges) { - List pairs = new ArrayList<>(); - startPrevRow = curr[0]; - startRow = curr[1]; - findPath(test, startPrevRow, startRow, pairs); - Cycle currCycle = new Cycle(pairs); - cycles.add(currCycle); - } - removeDuplicates(cycles); - if (cycles.size() > 12) { - writeCycles(cycles, output); - found = true; - } - } - if (!found) { - output.println("No cycles over 12 found."); - } - } - - public static void writeCycles(List cycles, PrintStream output) { - output.println(cycles.size() + " Cycles created"); - for (int i = 0; i < cycles.size(); i++) { - output.println("Cycle " + (i + 1) + ": "); - output.println("Length: " + cycles.get(i).length); - output.println(cycles.get(i)); - output.println(); - } - } - - public static void removeDuplicates(List cycles) { - for (int i = 0; i < cycles.size(); i++) { - Cycle current = cycles.get(i); - Iterator iterator = cycles.listIterator(i + 1); - while (iterator.hasNext()) { - Cycle next = iterator.next(); - if (current.compareTo(next) == 0) { - iterator.remove(); - } - } - } - } - - public static Set getEdges(int[][] test) { - Set edges = new HashSet<>(); - for (int i = 0; i < test.length; i++) { - edges.add(new int[] { test[i][0], i + 1 }); - edges.add(new int[] { test[i][1], i + 1 }); - edges.add(new int[] { test[i][2], i + 1 }); - } - return edges; - } - - public static void findPath(int[][] test, int startPrevRow, int startR, List pairs) - throws FileNotFoundException { - int startRow = -1; - int prevRow = startPrevRow; - int currRow = startR; - int nextColIndex = -1; - while (true) { - if (startRow == currRow && startPrevRow == prevRow) { - break; - } - startRow = startR; - for (int i = 0; i < test[0].length; i++) { - if (test[currRow - 1][i] == prevRow) { - if (i + 1 >= test[0].length) { - nextColIndex = 0; - } else { - nextColIndex = i + 1; - } - prevRow = currRow; - currRow = test[currRow - 1][nextColIndex]; - pairs.add(prevRow + ", " + currRow); - break; - } - } - } - } - - public static void randomize() throws FileNotFoundException { - int[][] inputData = { - { 3, 19, 21 }, { 20, 4, 23 }, { 5, 1, 24 }, { 2, 6, 26 }, { 7, 3, 27 }, - { 4, 8, 29 }, { 30, 5, 9 }, { 6, 32, 10 }, { 7, 33, 11 }, { 35, 12, 8 }, - { 13, 9, 36 }, { 10, 38, 14 }, { 39, 11, 15 }, { 16, 12, 41 }, { 13, 17, 42 }, - { 44, 14, 18 }, { 19, 45, 15 }, { 47, 20, 16 }, { 1, 17, 48 }, { 50, 2, 18 }, - { 22, 51, 1 }, { 37, 21, 23 }, { 2, 52, 22 }, { 53, 25, 3 }, { 24, 26, 40 }, - { 25, 4, 54 }, { 55, 5, 28 }, { 29, 43, 27 }, { 6, 28, 56 }, { 31, 7, 57 }, - { 46, 30, 32 }, { 8, 58, 31 }, { 9, 34, 59 }, { 33, 49, 35 }, { 60, 10, 34 }, - { 37, 61, 11 }, { 38, 36, 22 }, { 12, 37, 62 }, { 40, 63, 13 }, { 41, 25, 39 }, - { 14, 40, 64 }, { 15, 43, 65 }, { 28, 44, 42 }, { 43, 16, 66 }, { 17, 46, 67 }, - { 45, 31, 47 }, { 46, 18, 68 }, { 19, 69, 49 }, { 34, 50, 48 }, { 70, 20, 49 }, - { 66, 58, 21 }, { 23, 65, 57 }, { 68, 60, 24 }, { 26, 59, 67 }, { 70, 27, 62 }, - { 69, 29, 61 }, { 30, 52, 64 }, { 32, 63, 51 }, { 66, 33, 54 }, { 53, 35, 65 }, - { 36, 68, 56 }, { 55, 67, 38 }, { 58, 70, 39 }, { 57, 69, 41 }, { 52, 60, 42 }, - { 44, 51, 59 }, { 62, 45, 54 }, { 61, 53, 47 }, { 48, 64, 56 }, { 63, 50, 55 } - }; - - // Initialize Random object - Random random = new Random(); - - // Process each row - for (int[] row : inputData) { - // Randomly rearrange the entries in the row - for (int i = row.length - 1; i > 0; i--) { - int j = random.nextInt(i + 1); - // Swap row[i] with row[j] - int temp = row[i]; - row[i] = row[j]; - row[j] = temp; - } - } - File newFile = new File("C:\\Users\\austi\\OneDrive\\Documents\\cyclecode\\BalabanAdjList.txt"); - PrintStream newPrint = new PrintStream(newFile); - // Print the new output data - for (int[] row : inputData) { - newPrint.println(Arrays.toString(row).replaceAll("[\\[\\],]", "")); - } - } -} diff --git a/CalcCycles/CalulateCycles.java b/CalcCycles/CalulateCycles.java deleted file mode 100644 index 0b9894d..0000000 --- a/CalcCycles/CalulateCycles.java +++ /dev/null @@ -1,184 +0,0 @@ -import java.io.File; -import java.io.FileNotFoundException; -import java.io.PrintStream; -import java.util.*; - -public class CalulateCycles { -// Manually fill arrays.txt -// start binary loop -// update arrays.txt from binary -// fill int[][] from arrays.txt -// generate cycles -// remove duplicate cycles -// print cycles -// repeat binary loop - public static void main(String[] args) throws FileNotFoundException { - int[][] test = new int[70][3]; - File myFile = new File("William2OutputAdj.txt"); - Scanner fileScan = new Scanner(myFile); // arrays line scan - File outputFile = new File("calccyclesoutput.txt"); - PrintStream output = new PrintStream(outputFile);// output scan - int line = 0; - // filling int[][] test from arrays.txt - while (fileScan.hasNextLine()) { - String currentLine = fileScan.nextLine(); - Scanner lineScan = new Scanner(currentLine); - test[line][0] = Integer.parseInt(lineScan.next()); - test[line][1] = Integer.parseInt(lineScan.next()); - test[line][2] = Integer.parseInt(lineScan.next()); - line++; - } - generateBinaryCombinations(27, test, output); // CHANGE THIS FOR DIFFERENT NUMBER OF NON-FIXED ROWS - } - - // Fills choices array - public static void fillChoices(boolean[] choices, Scanner indexScanner) { - int currentIndex = 0; - while(indexScanner.hasNextLine()) { - int choice = Integer.parseInt(indexScanner.nextLine()); - if (choice == 0) { - choices[currentIndex] = false; - } else { - choices[currentIndex] = true; - } - currentIndex++; - } - } - - public static void generateBinaryCombinations(int n, int[][] test, PrintStream output) throws FileNotFoundException { - File indexFile = new File("C:\\Users\\austi\\OneDrive\\Documents\\cyclecode\\indices.txt"); - Scanner indexScanner = new Scanner(indexFile); - boolean[] choices = new boolean[70]; - fillChoices(choices, indexScanner); - // FILLING CHOICES ARRAY - - - // BINARY GENERATION LOOP STARTS - int totalCombinations = 1 << n; // Total combinations is 2^n - for (int i = 0; i < totalCombinations; i++) { // iterating through binary strings - String a = Integer.toBinaryString(i); - String binaryString = String.format("%" + n + "s", a).replace(' ', '0'); - - - // FILLING binaries WITH THE CURRENT BINARY ITERATION - int[] binaries = new int[binaryString.length()]; - for(int j = 0; j < binaryString.length(); j++) { - binaries[j] = Integer.parseInt(binaryString.substring(j, j + 1)); - } - - - // ex: choices = (t, f, f, t, f, f, f, t) -> size of the whole 2d array - // ex: binaries = (1, 0, 1) -> only the size of the things we are changing - - // UPDATING test for the choices we made and the current binary - int binaryIndex = 0; - for(int j = 0; j < test.length; j++) { - if (choices[j]) { // if we want this row changed - if (binaries[binaryIndex] == 1) { // If current binary wants this row swaapped - if (test[j][0] < test[j][1]) { // If current row is not already swapped - int hold = test[j][1]; - test[j][1] = test[j][0]; // swap index one and two - test[j][0] = hold; - } - } - binaryIndex++; // Update binaryIndex - } - } - - Set edges = getEdges(test); - int startPrevRow = 0; - int startRow = 0; - - List cycles = new ArrayList<>(); - for(int[] curr: edges) { - List pairs = new ArrayList<>(); - startPrevRow = curr[0]; - startRow = curr[1]; - findPath(test, startPrevRow, startRow, pairs); - Cycle currCycle = new Cycle(pairs); - cycles.add(currCycle); - } - removeDuplicates(cycles); - if (cycles.size() > 15) { // CHANGE FOR PRINTING DIFF NUMBER OF CYCLES - writeCycles(cycles, output); - } - } // BINARY GENERATION LOOP ENDS - } - - public static void printChoices(boolean[] choices) { - for(int i = 0; i < choices.length; i++) { - if (choices[i] == true) { - System.out.print("t "); - } else { - System.out.print("f "); - } - } - } - - public static void printCurrentAdjList(int[][] test) { - for(int i = 0; i < test.length; i++) { - System.out.print(test[i][0] + " "); - System.out.print(test[i][1] + " "); - System.out.println(test[i][2]); - } - } - - public static void writeCycles(List cycles, PrintStream output) { - output.println(cycles.size() + " Cycles:"); - for(int i = 0; i < cycles.size(); i++) { - output.println("Cycle " + (i + 1) + ": "); - output.println("Length: " + cycles.get(i).length); - output.println(cycles.get(i)); - output.println(); - } - } - - public static void removeDuplicates(List cycles) { - for (int i = 0; i < cycles.size(); i++) { - Cycle current = cycles.get(i); - Iterator iterator = cycles.listIterator(i + 1); - while (iterator.hasNext()) { - Cycle next = iterator.next(); - if (current.compareTo(next) == 0) { - iterator.remove(); - } - } - } - } - - public static Set getEdges(int[][] test) { - Set edges = new HashSet<>(); - for(int i = 0; i < test.length; i++) { - edges.add(new int[]{test[i][0], i + 1}); - edges.add(new int[]{test[i][1], i + 1}); - edges.add(new int[]{test[i][2], i + 1}); - } - return edges; - } - - public static void findPath(int[][] test, int startPrevRow, int startR, List pairs) throws FileNotFoundException { - int startRow = -1; - int prevRow = startPrevRow; - int currRow = startR; - int nextColIndex = -1; - while (true) { - if (startRow == currRow && startPrevRow == prevRow) { - break; - } - startRow = startR; - for (int i = 0; i < test[0].length; i++) { - if (test[currRow - 1][i] == prevRow) { - if (i + 1 >= test[0].length) { - nextColIndex = 0; - } else { - nextColIndex = i + 1; - } - prevRow = currRow; - currRow = test[currRow - 1][nextColIndex]; - pairs.add(prevRow + ", " + currRow); - break; - } - } - } - } -} diff --git a/CalcCycles/Cycle.java b/CalcCycles/Cycle.java deleted file mode 100644 index 1363780..0000000 --- a/CalcCycles/Cycle.java +++ /dev/null @@ -1,51 +0,0 @@ -import java.util.*; -public class Cycle implements Comparable { - public List edges; - public int length; - - public Cycle(List edges) { - this.edges = edges; - this.length = edges.size(); - } - - public int compareTo(Cycle other) { - if (other.edges.size() != edges.size()) { - return -1; - } - - int shift = -1; - String curr = edges.get(0); - - // Find the shift value - for (int i = 0; i < other.edges.size(); i++) { - if (other.edges.get(i).equals(curr)) { - shift = i; - break; // Break after finding the first occurrence - } - } - - if (shift == -1) { - return -1; - } - - // Check for equality by shifting - for (int i = 0; i < edges.size(); i++) { - int index = (shift + i) % edges.size(); - if (!other.edges.get(index).equals(edges.get(i))) { - return -1; - } - } - - return 0; - } - - public String toString() { - String s = ""; - for (String curr: edges) { - s += curr; - s += "\n"; - } - return s; - } - -} diff --git a/CalcCycles/CycleCalculator.java b/CalcCycles/CycleCalculator.java deleted file mode 100644 index dbb8750..0000000 --- a/CalcCycles/CycleCalculator.java +++ /dev/null @@ -1,192 +0,0 @@ -import java.io.File; -import java.io.FileNotFoundException; -import java.io.PrintStream; -import java.util.*; - -public class CycleCalculator { - public static void main(String[] args) throws FileNotFoundException { - // setting minimum number of cycles to print - Scanner console = new Scanner(System.in); - System.out.print("Enter minimum number of cycles: "); - int minCycles = console.nextInt(); - // filling freeLines List with user inputted lines - System.out.print("Enter line numbers of non-fixed lines (enter a letter to end): "); - List freeLines = new ArrayList<>(); - while (console.hasNextInt()) { - freeLines.add(console.nextInt()); - System.out.print("Enter next line number: "); - } - // instantiating Scanner fileScan and printStream outPut. - File myFile = new File("William2OutputAdj.txt"); - Scanner fileScan = new Scanner(myFile); // arrays line scan - File outputFile = new File("CycleCalculatorOutput.txt"); - PrintStream output = new PrintStream(outputFile);// output scan - // creating int[][] adjList from adjList.txt - int numRows = 0; - while (fileScan.hasNextLine()) { - fileScan.nextLine(); - numRows++; - } - int[][] adjList = new int[numRows][3]; - // filling int[][] adjList from adjList.txt - int currRow = 0; - Scanner adjListScan = new Scanner(myFile); - while (adjListScan.hasNextLine()) { - String currentLine = adjListScan.nextLine(); - Scanner lineScan = new Scanner(currentLine); - adjList[currRow][0] = Integer.parseInt(lineScan.next()); - adjList[currRow][1] = Integer.parseInt(lineScan.next()); - adjList[currRow][2] = Integer.parseInt(lineScan.next()); - currRow++; - } - // making sure all rows are ordered with col 1 < col 2. - orderAdjList(adjList); - // generate binary combinations - generateBinaryCombinations(adjList, output, minCycles, freeLines); - System.out.println("done."); - } - - // runs through all possible combinations for the given free rows of the adjacency list, - // generating and printing the cycles for each combination to the output.txt file - public static void generateBinaryCombinations(int[][] adjList, PrintStream output, int minCycles, List freeLines) throws FileNotFoundException { - int numFreeLines = freeLines.size(); - // total combinations for binary Strings - int totalCombinations = 1 << numFreeLines; // Total combinations is 2^numFreeLines - // BINARY GENERATION LOOP STARTS - for (int i = 0; i < totalCombinations; i++) { - String a = ""; - String binaryString = ""; - if (numFreeLines != 0) { - // creating binary string - a = Integer.toBinaryString(i); - binaryString = String.format("%" + numFreeLines + "s", a).replace(' ', '0'); - // updating adjList based on chosen free lines and current binary generation - for(int j = 0; j < freeLines.size(); j++) { - int currLine = freeLines.get(j) - 1; - int currInt = Integer.parseInt(binaryString.substring(j, j + 1)); - // if binary string wants this line switched and it's not already or if binary string wants this line switched and it's not - if ((currInt == 1 && adjList[currLine][0] < adjList[currLine][1]) || currInt == 0 && adjList[currLine][0] > adjList[currLine][1]) { - // swaps index 0 and 1 - int hold = adjList[currLine][1]; - adjList[currLine][1] = adjList[currLine][0]; - adjList[currLine][0] = hold; - } - } - } - // generating set of all edges - Set edges = getEdges(adjList); - // Iterating through every edge, finding path for it based on adjList, then add it to cycles List. - int startPrevRow = 0; - int startRow = 0; - List cycles = new ArrayList<>(); - for(int[] curr: edges) { - List pairs = new ArrayList<>(); - startPrevRow = curr[0]; - startRow = curr[1]; - findPath(adjList, startPrevRow, startRow, pairs); - Cycle currCycle = new Cycle(pairs); - cycles.add(currCycle); - } - // removing duplicate cycles from cycles List - removeDuplicates(cycles); - // print cycles if over given int minCycles - if (cycles.size() >= minCycles) { - writeCycles(cycles, output); - } - } // BINARY GENERATION LOOP ENDS - } - - // Orders every row of int[][] adjList so that the first number is less than the second without changing the order of numbers. - public static void orderAdjList(int[][] adjList) { - for(int i = 0; i < adjList.length; i++) { - int colOne = adjList[i][0]; - int colTwo = adjList[i][1]; - int colThree = adjList[i][2]; - if (colOne > colTwo) { // if the cols need to be switched - if (colThree > colOne) { // cycle left - adjList[i][0] = colTwo; - adjList[i][1] = colThree; - adjList[i][2] = colOne; - } else { // cycle right - adjList[i][0] = colThree; - adjList[i][1] = colOne; - adjList[i][2] = colTwo; - } - } - } - } - - // prints out the int[][] adjList - public static void printCurrentAdjList(int[][] adjList) { - for(int i = 0; i < adjList.length; i++) { - System.out.print(adjList[i][0] + " "); - System.out.print(adjList[i][1] + " "); - System.out.println(adjList[i][2]); - } - System.out.println(); - } - - // Prints cycles to output.txt - public static void writeCycles(List cycles, PrintStream output) { - output.println(cycles.size() + " Cycles:"); - for(int i = 0; i < cycles.size(); i++) { - output.println("Cycle " + (i + 1) + ": "); - output.println("Length: " + cycles.get(i).length); - output.println(cycles.get(i)); - output.println(); - } - } - - // removes the duplicate cycles from the given List. - public static void removeDuplicates(List cycles) { - for (int i = 0; i < cycles.size(); i++) { - Cycle current = cycles.get(i); - Iterator iterator = cycles.listIterator(i + 1); - while (iterator.hasNext()) { - Cycle next = iterator.next(); - if (current.compareTo(next) == 0) { - iterator.remove(); - } - } - } - } - - // returns a set of all edges made from the adjacency list. Each int[] is length 2 and the - // edge being line number -> value of each col of that row. - public static Set getEdges(int[][] adjList) { - Set edges = new HashSet<>(); - for(int i = 0; i < adjList.length; i++) { - edges.add(new int[]{adjList[i][0], i + 1}); - edges.add(new int[]{adjList[i][1], i + 1}); - edges.add(new int[]{adjList[i][2], i + 1}); - } - return edges; - } - - // finds a cycle for the current edge. - public static void findPath(int[][] adjList, int startPrevRow, int startR, List pairs) { - int startRow = -1; - int prevRow = startPrevRow; - int currRow = startR; - int nextColIndex = -1; - while (true) { - if (startRow == currRow && startPrevRow == prevRow) { - break; - } - startRow = startR; - for (int i = 0; i < adjList[0].length; i++) { - if (adjList[currRow - 1][i] == prevRow) { - if (i + 1 >= adjList[0].length) { - nextColIndex = 0; - } else { - nextColIndex = i + 1; - } - prevRow = currRow; - currRow = adjList[currRow - 1][nextColIndex]; - pairs.add(prevRow + ", " + currRow); - break; - } - } - } - } -} diff --git a/CalcCycles/CycleCalculatorNoInput.java b/CalcCycles/CycleCalculatorNoInput.java deleted file mode 100644 index 0111723..0000000 --- a/CalcCycles/CycleCalculatorNoInput.java +++ /dev/null @@ -1,196 +0,0 @@ -import java.io.File; -import java.io.FileNotFoundException; -import java.io.PrintStream; -import java.util.*; - -public class CycleCalculatorNoInput { - public static void main(String[] args) throws FileNotFoundException { - // setting minimum number of cycles to print - int minCycles = 16; - System.out.println("Minimum number of cycles to print: " + minCycles); - // filling freeLines List with user inputted lines - List nonFreeLines = Arrays.asList(new Integer[] {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 43, 44, 50, 51, 56, 58, 61, 63, 66}); - List freeLines = new ArrayList<>(); - for (int i = 1; i <= 70; i++) { - if (!nonFreeLines.contains(i)) { - freeLines.add(i); - } - } - System.out.println("Free lines: " + freeLines); - // instantiating Scanner fileScan and printStream outPut. - File myFile = new File("William2OutputAdj.txt"); - Scanner fileScan = new Scanner(myFile); // arrays line scan - File outputFile = new File("CycleCalculatorOutput.txt"); - PrintStream output = new PrintStream(outputFile);// output scan - // creating int[][] adjList from adjList.txt - int numRows = 0; - while (fileScan.hasNextLine()) { - fileScan.nextLine(); - numRows++; - } - int[][] adjList = new int[numRows][3]; - // filling int[][] adjList from adjList.txt - int currRow = 0; - Scanner adjListScan = new Scanner(myFile); - while (adjListScan.hasNextLine()) { - String currentLine = adjListScan.nextLine(); - Scanner lineScan = new Scanner(currentLine); - adjList[currRow][0] = Integer.parseInt(lineScan.next()); - adjList[currRow][1] = Integer.parseInt(lineScan.next()); - adjList[currRow][2] = Integer.parseInt(lineScan.next()); - currRow++; - } - // making sure all rows are ordered with col 1 < col 2. - orderAdjList(adjList); - // generate binary combinations - generateBinaryCombinations(adjList, output, minCycles, freeLines); - System.out.println("done."); - } - - // runs through all possible combinations for the given free rows of the adjacency list, - // generating and printing the cycles for each combination to the output.txt file - public static void generateBinaryCombinations(int[][] adjList, PrintStream output, int minCycles, List freeLines) throws FileNotFoundException { - int numFreeLines = freeLines.size(); - System.out.println("Number of Free lines: " + numFreeLines); - // total combinations for binary Strings - long totalCombinations = 1l << numFreeLines; // Total combinations is 2^numFreeLines - System.out.println("Total Combinations: " + totalCombinations); - // BINARY GENERATION LOOP STARTS - for (int i = 0; i < totalCombinations; i++) { - if (i % 100000 == 0) System.out.println("Iteration: " + i); - String a = ""; - String binaryString = ""; - if (numFreeLines != 0) { - // creating binary string - a = Integer.toBinaryString(i); - binaryString = String.format("%" + numFreeLines + "s", a).replace(' ', '0'); - // updating adjList based on chosen free lines and current binary generation - for(int j = 0; j < freeLines.size(); j++) { - int currLine = freeLines.get(j) - 1; - int currInt = Integer.parseInt(binaryString.substring(j, j + 1)); - // if binary string wants this line switched and it's not already or if binary string wants this line switched and it's not - if ((currInt == 1 && adjList[currLine][0] < adjList[currLine][1]) || currInt == 0 && adjList[currLine][0] > adjList[currLine][1]) { - // swaps index 0 and 1 - int hold = adjList[currLine][1]; - adjList[currLine][1] = adjList[currLine][0]; - adjList[currLine][0] = hold; - } - } - } - // generating set of all edges - Set edges = getEdges(adjList); - // Iterating through every edge, finding path for it based on adjList, then add it to cycles List. - int startPrevRow = 0; - int startRow = 0; - List cycles = new ArrayList<>(); - for(int[] curr: edges) { - List pairs = new ArrayList<>(); - startPrevRow = curr[0]; - startRow = curr[1]; - findPath(adjList, startPrevRow, startRow, pairs); - Cycle currCycle = new Cycle(pairs); - cycles.add(currCycle); - } - // removing duplicate cycles from cycles List - removeDuplicates(cycles); - // print cycles if over given int minCycles - if (cycles.size() >= minCycles) { - writeCycles(cycles, output); - } - } // BINARY GENERATION LOOP ENDS - } - - // Orders every row of int[][] adjList so that the first number is less than the second without changing the order of numbers. - public static void orderAdjList(int[][] adjList) { - for(int i = 0; i < adjList.length; i++) { - int colOne = adjList[i][0]; - int colTwo = adjList[i][1]; - int colThree = adjList[i][2]; - if (colOne > colTwo) { // if the cols need to be switched - if (colThree > colOne) { // cycle left - adjList[i][0] = colTwo; - adjList[i][1] = colThree; - adjList[i][2] = colOne; - } else { // cycle right - adjList[i][0] = colThree; - adjList[i][1] = colOne; - adjList[i][2] = colTwo; - } - } - } - } - - // prints out the int[][] adjList - public static void printCurrentAdjList(int[][] adjList) { - for(int i = 0; i < adjList.length; i++) { - System.out.print(adjList[i][0] + " "); - System.out.print(adjList[i][1] + " "); - System.out.println(adjList[i][2]); - } - System.out.println(); - } - - // Prints cycles to output.txt - public static void writeCycles(List cycles, PrintStream output) { - output.println(cycles.size() + " Cycles:"); - for(int i = 0; i < cycles.size(); i++) { - output.println("Cycle " + (i + 1) + ": "); - output.println("Length: " + cycles.get(i).length); - output.println(cycles.get(i)); - output.println(); - } - } - - // removes the duplicate cycles from the given List. - public static void removeDuplicates(List cycles) { - for (int i = 0; i < cycles.size(); i++) { - Cycle current = cycles.get(i); - Iterator iterator = cycles.listIterator(i + 1); - while (iterator.hasNext()) { - Cycle next = iterator.next(); - if (current.compareTo(next) == 0) { - iterator.remove(); - } - } - } - } - - // returns a set of all edges made from the adjacency list. Each int[] is length 2 and the - // edge being line number -> value of each col of that row. - public static Set getEdges(int[][] adjList) { - Set edges = new HashSet<>(); - for(int i = 0; i < adjList.length; i++) { - edges.add(new int[]{adjList[i][0], i + 1}); - edges.add(new int[]{adjList[i][1], i + 1}); - edges.add(new int[]{adjList[i][2], i + 1}); - } - return edges; - } - - // finds a cycle for the current edge. - public static void findPath(int[][] adjList, int startPrevRow, int startR, List pairs) { - int startRow = -1; - int prevRow = startPrevRow; - int currRow = startR; - int nextColIndex = -1; - while (true) { - if (startRow == currRow && startPrevRow == prevRow) { - break; - } - startRow = startR; - for (int i = 0; i < adjList[0].length; i++) { - if (adjList[currRow - 1][i] == prevRow) { - if (i + 1 >= adjList[0].length) { - nextColIndex = 0; - } else { - nextColIndex = i + 1; - } - prevRow = currRow; - currRow = adjList[currRow - 1][nextColIndex]; - pairs.add(prevRow + ", " + currRow); - break; - } - } - } - } -} diff --git a/CalcCycles/CycleCalculatorOutput.txt b/CalcCycles/CycleCalculatorOutput.txt deleted file mode 100644 index edd4155..0000000 --- a/CalcCycles/CycleCalculatorOutput.txt +++ /dev/null @@ -1,279 +0,0 @@ -17 Cycles: -Cycle 1: -Length: 14 -29, 56 -56, 69 -69, 64 -64, 57 -57, 52 -52, 65 -65, 60 -60, 53 -53, 24 -24, 3 -3, 5 -5, 27 -27, 28 -28, 29 - - -Cycle 2: -Length: 16 -35, 34 -34, 33 -33, 59 -59, 54 -54, 26 -26, 4 -4, 2 -2, 23 -23, 52 -52, 57 -57, 30 -30, 31 -31, 32 -32, 8 -8, 10 -10, 35 - - -Cycle 3: -Length: 14 -1, 21 -21, 51 -51, 58 -58, 32 -32, 31 -31, 46 -46, 47 -47, 18 -18, 20 -20, 50 -50, 49 -49, 48 -48, 19 -19, 1 - - -Cycle 4: -Length: 10 -39, 13 -13, 11 -11, 9 -9, 7 -7, 30 -30, 57 -57, 64 -64, 41 -41, 40 -40, 39 - - -Cycle 5: -Length: 10 -35, 10 -10, 12 -12, 38 -38, 37 -37, 36 -36, 61 -61, 68 -68, 53 -53, 60 -60, 35 - - -Cycle 6: -Length: 10 -2, 4 -4, 6 -6, 8 -8, 32 -32, 58 -58, 63 -63, 70 -70, 50 -50, 20 -20, 2 - - -Cycle 7: -Length: 16 -21, 1 -1, 3 -3, 24 -24, 25 -25, 26 -26, 54 -54, 67 -67, 45 -45, 17 -17, 15 -15, 42 -42, 65 -65, 52 -52, 23 -23, 22 -22, 21 - - -Cycle 8: -Length: 18 -28, 27 -27, 55 -55, 62 -62, 38 -38, 12 -12, 14 -14, 41 -41, 64 -64, 69 -69, 48 -48, 49 -49, 34 -34, 35 -35, 60 -60, 65 -65, 42 -42, 43 -43, 28 - - -Cycle 9: -Length: 14 -16, 44 -44, 66 -66, 59 -59, 33 -33, 9 -9, 11 -11, 36 -36, 37 -37, 22 -22, 23 -23, 2 -2, 20 -20, 18 -18, 16 - - -Cycle 10: -Length: 10 -17, 19 -19, 48 -48, 69 -69, 56 -56, 61 -61, 36 -36, 11 -11, 13 -13, 15 -15, 17 - - -Cycle 11: -Length: 10 -31, 30 -30, 7 -7, 5 -5, 3 -3, 1 -1, 19 -19, 17 -17, 45 -45, 46 -46, 31 - - -Cycle 12: -Length: 14 -70, 63 -63, 39 -39, 40 -40, 25 -25, 24 -24, 53 -53, 68 -68, 47 -47, 46 -46, 45 -45, 67 -67, 62 -62, 55 -55, 70 - - -Cycle 13: -Length: 10 -28, 43 -43, 44 -44, 16 -16, 14 -14, 12 -12, 10 -10, 8 -8, 6 -6, 29 -29, 28 - - -Cycle 14: -Length: 10 -21, 22 -22, 37 -37, 38 -38, 62 -62, 67 -67, 54 -54, 59 -59, 66 -66, 51 -51, 21 - - -Cycle 15: -Length: 10 -39, 63 -63, 58 -58, 51 -51, 66 -66, 44 -44, 43 -43, 42 -42, 15 -15, 13 -13, 39 - - -Cycle 16: -Length: 10 -55, 27 -27, 5 -5, 7 -7, 9 -9, 33 -33, 34 -34, 49 -49, 50 -50, 70 -70, 55 - - -Cycle 17: -Length: 14 -14, 16 -16, 18 -18, 47 -47, 68 -68, 61 -61, 56 -56, 29 -29, 6 -6, 4 -4, 26 -26, 25 -25, 40 -40, 41 -41, 14 - - diff --git a/CalcCycles/William2OutputAdj.txt b/CalcCycles/William2OutputAdj.txt deleted file mode 100644 index dd31cce..0000000 --- a/CalcCycles/William2OutputAdj.txt +++ /dev/null @@ -1,70 +0,0 @@ -21 3 19 -23 20 4 -1 24 5 -6 26 2 -27 7 3 -29 4 8 -9 30 5 -32 10 6 -11 7 33 -35 12 8 -36 13 9 -38 14 10 -11 15 39 -41 16 12 -17 42 13 -14 18 44 -45 15 19 -16 47 20 -17 48 1 -18 50 2 -22 1 51 -23 21 37 -52 22 2 -3 25 53 -24 26 40 -25 54 4 -28 55 5 -43 27 29 -56 6 28 -7 57 31 -32 46 30 -58 31 8 -59 9 34 -49 35 33 -34 60 10 -61 11 37 -38 36 22 -62 12 37 -40 13 63 -41 39 25 -64 40 14 -15 65 43 -42 28 44 -66 43 16 -67 17 46 -47 45 31 -18 68 46 -19 69 49 -48 34 50 -20 49 70 -58 66 21 -65 23 57 -24 68 60 -26 67 59 -27 62 70 -69 61 29 -30 64 52 -63 51 32 -66 33 54 -35 65 53 -56 36 68 -55 38 67 -39 58 70 -57 41 69 -42 52 60 -51 44 59 -54 45 62 -47 61 53 -48 56 64 -55 63 50 diff --git a/CalcGenus/3-12-cage.out b/CalcGenus/3-12-cage.out deleted file mode 100644 index 9be5762..0000000 --- a/CalcGenus/3-12-cage.out +++ /dev/null @@ -1,585 +0,0 @@ -New max fit: 1 (about to try vertex 0) -0 63 15 73 3 72 7 66 1 67 31 64 0 - -New max fit: 2 (about to try vertex 0) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 - -New max fit: 3 (about to try vertex 63) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 - -New max fit: 4 (about to try vertex 15) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -4 75 15 63 16 102 35 84 46 109 57 77 4 - -New max fit: 5 (about to try vertex 16) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -4 75 15 63 16 102 35 84 46 109 57 77 4 -11 90 17 73 15 75 18 104 43 94 33 91 11 - -New max fit: 6 (about to try vertex 64) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -4 75 15 63 16 102 35 84 46 109 57 77 4 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 95 54 102 16 103 36 100 14 99 25 93 12 - -New max fit: 7 (about to try vertex 25) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -2 69 23 74 25 99 20 108 32 64 31 70 2 -4 75 15 63 16 102 35 84 46 109 57 77 4 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 95 54 102 16 103 36 100 14 99 25 93 12 - -New max fit: 8 (about to try vertex 3) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -2 69 23 74 25 99 20 108 32 64 31 70 2 -3 73 17 96 27 118 60 113 22 93 25 74 3 -4 75 15 63 16 102 35 84 46 109 57 77 4 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 95 54 102 16 103 36 100 14 99 25 93 12 - -New max fit: 9 (about to try vertex 9) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -2 69 23 74 25 99 20 108 32 64 31 70 2 -3 73 17 96 27 118 60 113 22 93 25 74 3 -3 74 23 81 6 82 42 121 28 87 9 72 3 -4 75 15 63 16 102 35 84 46 109 57 77 4 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 95 54 102 16 103 36 100 14 99 25 93 12 - -New max fit: 10 (about to try vertex 7) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -2 69 23 74 25 99 20 108 32 64 31 70 2 -3 73 17 96 27 118 60 113 22 93 25 74 3 -3 74 23 81 6 82 42 121 28 87 9 72 3 -4 75 15 63 16 102 35 84 46 109 57 77 4 -7 72 9 86 30 125 43 104 61 88 10 78 7 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 95 54 102 16 103 36 100 14 99 25 93 12 - -New max fit: 11 (about to try vertex 5) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -2 69 23 74 25 99 20 108 32 64 31 70 2 -3 73 17 96 27 118 60 113 22 93 25 74 3 -3 74 23 81 6 82 42 121 28 87 9 72 3 -4 75 15 63 16 102 35 84 46 109 57 77 4 -5 80 55 71 56 122 37 85 8 66 7 78 5 -7 72 9 86 30 125 43 104 61 88 10 78 7 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 95 54 102 16 103 36 100 14 99 25 93 12 - -New max fit: 12 (about to try vertex 10) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -2 69 23 74 25 99 20 108 32 64 31 70 2 -3 73 17 96 27 118 60 113 22 93 25 74 3 -3 74 23 81 6 82 42 121 28 87 9 72 3 -4 75 15 63 16 102 35 84 46 109 57 77 4 -5 79 49 92 62 107 19 106 52 98 58 80 5 -5 80 55 71 56 122 37 85 8 66 7 78 5 -7 72 9 86 30 125 43 104 61 88 10 78 7 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 95 54 102 16 103 36 100 14 99 25 93 12 - -New max fit: 13 (about to try vertex 17) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -2 69 23 74 25 99 20 108 32 64 31 70 2 -3 73 17 96 27 118 60 113 22 93 25 74 3 -3 74 23 81 6 82 42 121 28 87 9 72 3 -4 75 15 63 16 102 35 84 46 109 57 77 4 -5 79 49 92 62 107 19 106 52 98 58 80 5 -5 80 55 71 56 122 37 85 8 66 7 78 5 -7 72 9 86 30 125 43 104 61 88 10 78 7 -10 88 51 123 42 82 39 76 41 113 60 89 10 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 95 54 102 16 103 36 100 14 99 25 93 12 - -New max fit: 14 (about to try vertex 17) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -2 69 23 74 25 99 20 108 32 64 31 70 2 -2 70 34 118 27 119 50 125 30 124 56 71 2 -2 71 55 80 5 79 49 92 62 114 24 69 2 -3 73 17 96 27 118 60 113 22 93 25 74 3 -3 74 23 81 6 82 42 121 28 87 9 72 3 -4 75 15 63 16 102 35 84 46 109 57 77 4 -5 80 58 98 52 117 45 85 8 66 7 78 5 -7 72 9 86 30 125 43 104 61 88 10 78 7 -10 88 51 123 42 82 39 76 41 113 60 89 10 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 95 54 102 16 103 36 100 14 99 25 93 12 - -New max fit: 15 (about to try vertex 23) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -2 69 23 74 25 99 20 108 32 64 31 70 2 -2 70 34 118 27 119 50 125 30 124 56 71 2 -2 71 55 80 5 79 49 92 62 114 24 69 2 -3 73 17 96 27 118 60 113 22 93 25 74 3 -3 74 23 81 6 82 42 121 28 87 9 72 3 -4 75 15 63 16 102 35 84 46 109 57 77 4 -5 80 58 98 52 117 45 85 8 66 7 78 5 -7 72 9 86 30 125 43 104 61 88 10 78 7 -10 88 51 123 42 82 39 76 41 113 60 89 10 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 95 54 102 16 103 36 100 14 99 25 93 12 -13 96 17 90 29 122 37 112 48 110 38 97 13 - -New max fit: 16 (about to try vertex 18) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -2 69 23 74 25 99 20 108 32 64 31 70 2 -2 70 34 118 27 119 50 125 30 124 56 71 2 -2 71 55 80 5 79 49 92 62 114 24 69 2 -3 73 17 96 27 118 60 113 22 93 25 74 3 -3 74 23 81 6 82 42 121 28 87 9 72 3 -4 75 15 63 16 102 35 84 46 109 57 77 4 -5 80 58 98 52 117 45 85 8 66 7 78 5 -7 72 9 86 30 125 43 104 61 88 10 78 7 -10 88 51 123 42 82 39 76 41 113 60 89 10 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 95 54 102 16 103 36 100 14 99 25 93 12 -13 96 17 90 29 122 37 112 48 110 38 97 13 -18 105 45 117 26 81 23 69 24 115 61 104 18 - -New max fit: 17 (about to try vertex 9) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -1 66 8 85 37 112 48 110 38 97 40 68 1 -1 68 39 82 6 81 26 116 44 91 33 67 1 -2 71 56 122 29 123 51 108 32 64 31 70 2 -3 73 17 96 13 97 38 115 24 69 23 74 3 -3 74 25 99 14 101 59 120 28 87 9 72 3 -4 75 15 63 16 102 35 84 46 109 57 77 4 -6 82 42 121 54 95 12 94 43 125 50 83 6 -6 83 47 65 48 112 22 93 25 74 23 81 6 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 93 22 113 60 118 34 70 31 67 33 94 12 -12 95 58 98 52 106 32 108 20 99 25 93 12 -16 103 36 124 56 71 55 80 58 95 54 102 16 -19 106 52 117 45 105 59 101 49 92 62 107 19 -19 107 41 113 22 112 37 122 56 124 30 86 19 - -New max fit: 18 (about to try vertex 7) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -1 66 8 85 37 112 48 110 38 97 40 68 1 -1 68 39 82 6 81 26 116 44 91 33 67 1 -2 71 56 122 29 123 51 108 32 64 31 70 2 -3 73 17 96 13 97 38 115 24 69 23 74 3 -3 74 25 99 14 101 59 120 28 87 9 72 3 -4 75 15 63 16 102 35 84 46 109 57 77 4 -6 82 42 121 54 95 12 94 43 125 50 83 6 -6 83 47 65 48 112 22 93 25 74 23 81 6 -7 72 9 86 30 125 43 104 61 88 10 78 7 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 93 22 113 60 118 34 70 31 67 33 94 12 -12 95 58 98 52 106 32 108 20 99 25 93 12 -16 103 36 124 56 71 55 80 58 95 54 102 16 -19 106 52 117 45 105 59 101 49 92 62 107 19 -19 107 41 113 22 112 37 122 56 124 30 86 19 - -New max fit: 19 (about to try vertex 5) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 79 5 78 10 89 53 103 16 63 0 -1 66 8 84 46 119 50 83 6 82 39 68 1 -1 68 40 97 13 98 58 95 12 94 33 67 1 -2 69 24 114 35 84 8 85 37 122 56 71 2 -2 70 31 67 33 91 44 116 26 81 23 69 2 -2 71 55 77 57 111 21 87 28 120 34 70 2 -4 75 15 63 16 102 35 114 62 107 41 76 4 -5 80 58 98 52 117 45 85 8 66 7 78 5 -6 81 26 117 52 106 32 108 51 123 42 82 6 -6 83 47 65 48 112 22 93 25 74 23 81 6 -11 90 17 96 13 97 38 110 21 111 44 91 11 -12 95 54 102 16 103 36 100 14 99 25 93 12 -13 96 27 118 60 113 41 107 19 106 52 98 13 -15 75 18 104 43 125 50 119 27 96 17 73 15 -19 107 62 92 49 79 47 83 50 125 30 86 19 -20 108 32 64 31 70 34 118 27 119 46 109 20 -26 116 53 89 60 118 34 120 59 105 45 117 26 - -New max fit: 20 (about to try vertex 17) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -0 65 47 83 6 81 26 116 53 103 16 63 0 -1 66 8 84 46 119 27 96 13 97 40 68 1 -1 68 39 82 6 83 50 125 43 94 33 67 1 -2 69 23 74 25 99 20 108 32 64 31 70 2 -3 73 17 90 11 91 33 94 12 93 25 74 3 -3 74 23 81 6 82 42 121 28 87 9 72 3 -4 75 15 63 16 102 54 95 58 80 55 77 4 -5 79 47 65 48 112 37 85 8 66 7 78 5 -7 72 9 86 30 124 36 103 53 89 10 78 7 -8 85 45 105 59 120 28 121 54 102 35 84 8 -12 94 43 104 61 115 38 97 13 98 58 95 12 -12 95 54 121 42 123 29 122 37 112 22 93 12 -13 96 17 73 15 75 18 105 45 117 52 98 13 -14 99 25 93 22 113 60 118 34 120 59 101 14 -14 100 40 97 38 110 21 111 57 109 20 99 14 -14 101 49 92 62 114 35 102 16 103 36 100 14 -20 109 46 84 35 114 24 115 61 88 51 108 20 -21 87 28 120 34 70 31 67 33 91 44 111 21 - -New max fit: 21 (about to try vertex 6) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 108 20 99 14 101 49 79 47 65 0 -0 65 48 110 38 115 24 114 35 102 16 63 0 -2 69 23 74 3 73 17 96 27 118 34 70 2 -2 70 31 67 33 94 12 95 58 80 55 71 2 -2 71 56 122 29 90 11 92 62 114 24 69 2 -3 74 25 93 12 94 43 125 30 86 9 72 3 -4 75 15 63 16 103 36 124 56 71 55 77 4 -4 76 39 82 42 121 28 120 59 105 18 75 4 -4 77 57 109 46 84 35 114 62 107 41 76 4 -5 78 10 88 51 123 42 82 6 83 47 79 5 -5 79 49 92 11 91 44 111 57 77 55 80 5 -5 80 58 98 52 117 45 85 8 66 7 78 5 -6 82 39 68 40 100 14 99 25 74 23 81 6 -7 72 9 87 21 111 44 116 53 89 10 78 7 -9 86 19 106 32 64 31 70 34 120 28 87 9 -10 89 60 118 27 119 50 125 43 104 61 88 10 -11 90 17 73 15 75 18 104 43 94 33 91 11 -12 93 22 113 60 89 53 103 16 102 54 95 12 -13 96 17 90 29 123 51 108 32 106 52 98 13 -18 105 45 117 26 81 23 69 24 115 61 104 18 - -New max fit: 22 (about to try vertex 7) -0 63 15 73 3 72 9 87 21 110 48 65 0 -0 64 32 108 20 99 14 100 36 103 16 63 0 -0 65 47 79 5 78 7 66 1 67 31 64 0 -2 69 24 115 61 88 10 78 5 80 55 71 2 -2 70 34 118 60 113 22 93 25 74 23 69 2 -2 71 56 124 30 86 19 106 32 64 31 70 2 -3 73 17 90 29 123 42 82 6 81 23 74 3 -3 74 25 99 20 109 46 84 8 66 7 72 3 -4 76 39 68 40 97 13 96 17 73 15 75 4 -5 79 49 101 14 99 25 93 12 95 58 80 5 -6 82 39 76 41 107 62 92 49 79 47 83 6 -6 83 50 119 27 96 13 98 52 117 26 81 6 -8 84 35 102 16 103 53 116 26 117 45 85 8 -11 90 17 96 27 118 34 120 59 101 49 92 11 -11 91 33 94 12 93 22 112 37 122 29 90 11 -11 92 62 114 24 69 23 81 26 116 44 91 11 -12 94 43 104 18 75 15 63 16 102 54 95 12 -13 97 38 110 21 111 57 77 55 80 58 98 13 -14 101 59 105 18 104 61 115 38 97 40 100 14 -21 87 28 120 34 70 31 67 33 91 44 111 21 -27 119 46 109 57 111 44 116 53 89 60 118 27 -32 106 52 98 58 95 54 121 42 123 51 108 32 - -New max fit: 23 (about to try vertex 12) -0 63 15 73 17 90 11 92 49 79 47 65 0 -0 64 31 70 2 71 56 124 36 103 16 63 0 -0 65 48 110 38 97 13 98 52 106 32 64 0 -1 66 7 72 9 86 19 107 41 76 39 68 1 -1 67 31 64 32 108 20 109 46 84 8 66 1 -1 68 40 100 36 124 30 125 43 94 33 67 1 -2 69 23 81 26 116 44 111 57 77 55 71 2 -2 70 34 120 59 101 49 92 62 114 24 69 2 -3 72 7 78 10 89 60 118 27 96 17 73 3 -3 73 15 75 4 77 57 109 20 99 25 74 3 -3 74 23 69 24 115 38 110 21 87 9 72 3 -4 75 18 105 45 117 26 81 6 82 39 76 4 -4 76 41 113 22 93 12 95 58 80 55 77 4 -5 78 7 66 8 85 37 122 56 71 55 80 5 -5 79 49 101 14 99 20 108 51 88 10 78 5 -5 80 58 98 13 96 27 119 50 83 47 79 5 -6 81 23 74 25 93 22 112 48 65 47 83 6 -6 83 50 125 30 86 9 87 28 121 42 82 6 -8 84 35 114 62 107 19 106 52 117 45 85 8 -10 88 61 115 24 114 35 102 16 103 53 89 10 -12 94 43 104 18 75 15 63 16 102 54 95 12 -13 97 40 68 39 82 42 123 29 90 17 96 13 -19 86 30 124 56 122 29 123 51 108 32 106 19 - -New max fit: 24 (about to try vertex 4) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -1 66 8 85 37 112 48 110 38 97 40 68 1 -1 68 39 76 41 107 62 92 11 91 33 67 1 -2 70 34 120 28 121 42 82 6 81 23 69 2 -2 71 56 122 29 123 51 108 32 64 31 70 2 -3 73 17 96 13 97 38 115 24 69 23 74 3 -3 74 25 93 12 95 54 121 28 87 9 72 3 -4 76 39 82 42 123 29 90 17 73 15 75 4 -4 77 55 80 5 78 10 89 60 113 41 76 4 -5 79 49 92 62 114 35 84 8 66 7 78 5 -5 80 58 95 12 94 43 125 50 83 47 79 5 -6 83 50 119 27 118 60 89 53 116 26 81 6 -7 72 9 86 30 125 43 104 61 88 10 78 7 -10 88 51 123 42 121 54 102 16 103 53 89 10 -12 93 22 113 60 118 34 70 31 67 33 94 12 -13 98 52 117 45 105 59 101 14 100 40 97 13 -14 99 20 109 46 119 50 125 30 124 36 100 14 -14 101 49 79 47 65 48 112 22 93 25 99 14 -15 63 16 102 35 114 24 115 61 104 18 75 15 -19 107 41 113 22 112 37 122 56 124 30 86 19 -36 124 56 71 55 77 57 111 44 116 53 103 36 -0 65 47 83 6 82 39 68 40 100 36 103 16 63 0 -2 69 24 114 62 107 19 106 52 98 58 80 55 71 2 - -New max fit: 25 (about to try vertex 13) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -1 66 8 85 37 112 48 110 38 97 40 68 1 -1 68 39 76 41 107 62 92 11 91 33 67 1 -2 70 34 120 28 121 42 82 6 81 23 69 2 -2 71 56 122 29 123 51 108 32 64 31 70 2 -3 73 17 96 13 97 38 115 24 69 23 74 3 -3 74 25 93 12 95 54 121 28 87 9 72 3 -4 75 18 105 45 85 8 84 46 109 57 77 4 -4 76 39 82 42 123 29 90 17 73 15 75 4 -4 77 55 80 5 78 10 89 60 113 41 76 4 -5 79 49 92 62 114 35 84 8 66 7 78 5 -5 80 58 95 12 94 43 125 50 83 47 79 5 -6 83 50 119 27 118 60 89 53 116 26 81 6 -7 72 9 86 30 125 43 104 61 88 10 78 7 -10 88 51 123 42 121 54 102 16 103 53 89 10 -12 93 22 113 60 118 34 70 31 67 33 94 12 -13 98 52 117 45 105 59 101 14 100 40 97 13 -14 99 20 109 46 119 50 125 30 124 36 100 14 -14 101 49 79 47 65 48 112 22 93 25 99 14 -15 63 16 102 35 114 24 115 61 104 18 75 15 -19 107 41 113 22 112 37 122 56 124 30 86 19 -36 124 56 71 55 77 57 111 44 116 53 103 36 -0 65 47 83 6 82 39 68 40 100 36 103 16 63 0 -2 69 24 114 62 107 19 106 52 98 58 80 55 71 2 - -New max fit: 26 (about to try vertex 17) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -1 66 8 85 37 112 48 110 38 97 40 68 1 -1 68 39 76 41 107 62 92 11 91 33 67 1 -2 70 34 120 28 121 42 82 6 81 23 69 2 -2 71 56 122 29 123 51 108 32 64 31 70 2 -3 73 17 96 13 97 38 115 24 69 23 74 3 -3 74 25 93 12 95 54 121 28 87 9 72 3 -4 75 18 105 45 85 8 84 46 109 57 77 4 -4 76 39 82 42 123 29 90 17 73 15 75 4 -4 77 55 80 5 78 10 89 60 113 41 76 4 -5 79 49 92 62 114 35 84 8 66 7 78 5 -5 80 58 95 12 94 43 125 50 83 47 79 5 -6 83 50 119 27 118 60 89 53 116 26 81 6 -7 72 9 86 30 125 43 104 61 88 10 78 7 -10 88 51 123 42 121 54 102 16 103 53 89 10 -12 93 22 113 60 118 34 70 31 67 33 94 12 -13 96 27 119 46 84 35 102 54 95 58 98 13 -13 98 52 117 45 105 59 101 14 100 40 97 13 -14 99 20 109 46 119 50 125 30 124 36 100 14 -14 101 49 79 47 65 48 112 22 93 25 99 14 -15 63 16 102 35 114 24 115 61 104 18 75 15 -19 107 41 113 22 112 37 122 56 124 30 86 19 -36 124 56 71 55 77 57 111 44 116 53 103 36 -0 65 47 83 6 82 39 68 40 100 36 103 16 63 0 -2 69 24 114 62 107 19 106 52 98 58 80 55 71 2 - -New max fit: 27 (about to try vertex 11) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -1 66 8 85 37 112 48 110 38 97 40 68 1 -1 68 39 76 41 107 62 92 11 91 33 67 1 -2 70 34 120 28 121 42 82 6 81 23 69 2 -2 71 56 122 29 123 51 108 32 64 31 70 2 -3 73 17 96 13 97 38 115 24 69 23 74 3 -3 74 25 93 12 95 54 121 28 87 9 72 3 -4 75 18 105 45 85 8 84 46 109 57 77 4 -4 76 39 82 42 123 29 90 17 73 15 75 4 -4 77 55 80 5 78 10 89 60 113 41 76 4 -5 79 49 92 62 114 35 84 8 66 7 78 5 -5 80 58 95 12 94 43 125 50 83 47 79 5 -6 83 50 119 27 118 60 89 53 116 26 81 6 -7 72 9 86 30 125 43 104 61 88 10 78 7 -10 88 51 123 42 121 54 102 16 103 53 89 10 -11 92 49 101 59 120 34 118 27 96 17 90 11 -12 93 22 113 60 118 34 70 31 67 33 94 12 -13 96 27 119 46 84 35 102 54 95 58 98 13 -13 98 52 117 45 105 59 101 14 100 40 97 13 -14 99 20 109 46 119 50 125 30 124 36 100 14 -14 101 49 79 47 65 48 112 22 93 25 99 14 -15 63 16 102 35 114 24 115 61 104 18 75 15 -19 107 41 113 22 112 37 122 56 124 30 86 19 -36 124 56 71 55 77 57 111 44 116 53 103 36 -0 65 47 83 6 82 39 68 40 100 36 103 16 63 0 -2 69 24 114 62 107 19 106 52 98 58 80 55 71 2 - -New max fit: 28 (about to try vertex 18) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -1 66 8 85 37 112 48 110 38 97 40 68 1 -1 68 39 76 41 107 62 92 11 91 33 67 1 -2 70 34 120 28 121 42 82 6 81 23 69 2 -2 71 56 122 29 123 51 108 32 64 31 70 2 -3 73 17 96 13 97 38 115 24 69 23 74 3 -3 74 25 93 12 95 54 121 28 87 9 72 3 -4 75 18 105 45 85 8 84 46 109 57 77 4 -4 76 39 82 42 123 29 90 17 73 15 75 4 -4 77 55 80 5 78 10 89 60 113 41 76 4 -5 79 49 92 62 114 35 84 8 66 7 78 5 -5 80 58 95 12 94 43 125 50 83 47 79 5 -6 83 50 119 27 118 60 89 53 116 26 81 6 -7 72 9 86 30 125 43 104 61 88 10 78 7 -10 88 51 123 42 121 54 102 16 103 53 89 10 -11 90 29 122 37 85 45 117 26 116 44 91 11 -11 92 49 101 59 120 34 118 27 96 17 90 11 -12 93 22 113 60 118 34 70 31 67 33 94 12 -13 96 27 119 46 84 35 102 54 95 58 98 13 -13 98 52 117 45 105 59 101 14 100 40 97 13 -14 99 20 109 46 119 50 125 30 124 36 100 14 -14 101 49 79 47 65 48 112 22 93 25 99 14 -15 63 16 102 35 114 24 115 61 104 18 75 15 -19 107 41 113 22 112 37 122 56 124 30 86 19 -36 124 56 71 55 77 57 111 44 116 53 103 36 -0 65 47 83 6 82 39 68 40 100 36 103 16 63 0 -2 69 24 114 62 107 19 106 52 98 58 80 55 71 2 - -New max fit: 29 (about to try vertex 21) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -1 66 8 85 37 112 48 110 38 97 40 68 1 -1 68 39 76 41 107 62 92 11 91 33 67 1 -2 70 34 120 28 121 42 82 6 81 23 69 2 -2 71 56 122 29 123 51 108 32 64 31 70 2 -3 73 17 96 13 97 38 115 24 69 23 74 3 -3 74 25 93 12 95 54 121 28 87 9 72 3 -4 75 18 105 45 85 8 84 46 109 57 77 4 -4 76 39 82 42 123 29 90 17 73 15 75 4 -4 77 55 80 5 78 10 89 60 113 41 76 4 -5 79 49 92 62 114 35 84 8 66 7 78 5 -5 80 58 95 12 94 43 125 50 83 47 79 5 -6 83 50 119 27 118 60 89 53 116 26 81 6 -7 72 9 86 30 125 43 104 61 88 10 78 7 -10 88 51 123 42 121 54 102 16 103 53 89 10 -11 90 29 122 37 85 45 117 26 116 44 91 11 -11 92 49 101 59 120 34 118 27 96 17 90 11 -12 93 22 113 60 118 34 70 31 67 33 94 12 -13 96 27 119 46 84 35 102 54 95 58 98 13 -13 98 52 117 45 105 59 101 14 100 40 97 13 -14 99 20 109 46 119 50 125 30 124 36 100 14 -14 101 49 79 47 65 48 112 22 93 25 99 14 -15 63 16 102 35 114 24 115 61 104 18 75 15 -19 107 41 113 22 112 37 122 56 124 30 86 19 -36 124 56 71 55 77 57 111 44 116 53 103 36 -0 65 47 83 6 82 39 68 40 100 36 103 16 63 0 -2 69 24 114 62 107 19 106 52 98 58 80 55 71 2 -18 104 43 94 33 91 44 111 21 87 28 120 59 105 18 - -New max fit: 30 (about to try vertex 20) -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -1 66 8 85 37 112 48 110 38 97 40 68 1 -1 68 39 76 41 107 62 92 11 91 33 67 1 -2 70 34 120 28 121 42 82 6 81 23 69 2 -2 71 56 122 29 123 51 108 32 64 31 70 2 -3 73 17 96 13 97 38 115 24 69 23 74 3 -3 74 25 93 12 95 54 121 28 87 9 72 3 -4 75 18 105 45 85 8 84 46 109 57 77 4 -4 76 39 82 42 123 29 90 17 73 15 75 4 -4 77 55 80 5 78 10 89 60 113 41 76 4 -5 79 49 92 62 114 35 84 8 66 7 78 5 -5 80 58 95 12 94 43 125 50 83 47 79 5 -6 83 50 119 27 118 60 89 53 116 26 81 6 -7 72 9 86 30 125 43 104 61 88 10 78 7 -10 88 51 123 42 121 54 102 16 103 53 89 10 -11 90 29 122 37 85 45 117 26 116 44 91 11 -11 92 49 101 59 120 34 118 27 96 17 90 11 -12 93 22 113 60 118 34 70 31 67 33 94 12 -13 96 27 119 46 84 35 102 54 95 58 98 13 -13 98 52 117 45 105 59 101 14 100 40 97 13 -14 99 20 109 46 119 50 125 30 124 36 100 14 -14 101 49 79 47 65 48 112 22 93 25 99 14 -15 63 16 102 35 114 24 115 61 104 18 75 15 -19 107 41 113 22 112 37 122 56 124 30 86 19 -20 108 51 88 61 115 38 110 21 111 57 109 20 -36 124 56 71 55 77 57 111 44 116 53 103 36 -0 65 47 83 6 82 39 68 40 100 36 103 16 63 0 -2 69 24 114 62 107 19 106 52 98 58 80 55 71 2 -18 104 43 94 33 91 44 111 21 87 28 120 59 105 18 - -Solution with 31 cycles found in 1309592216 iterations: -0 63 15 73 3 72 7 66 1 67 31 64 0 -0 64 32 106 19 86 9 87 21 110 48 65 0 -1 66 8 85 37 112 48 110 38 97 40 68 1 -1 68 39 76 41 107 62 92 11 91 33 67 1 -2 70 34 120 28 121 42 82 6 81 23 69 2 -2 71 56 122 29 123 51 108 32 64 31 70 2 -3 73 17 96 13 97 38 115 24 69 23 74 3 -3 74 25 93 12 95 54 121 28 87 9 72 3 -4 75 18 105 45 85 8 84 46 109 57 77 4 -4 76 39 82 42 123 29 90 17 73 15 75 4 -4 77 55 80 5 78 10 89 60 113 41 76 4 -5 79 49 92 62 114 35 84 8 66 7 78 5 -5 80 58 95 12 94 43 125 50 83 47 79 5 -6 83 50 119 27 118 60 89 53 116 26 81 6 -7 72 9 86 30 125 43 104 61 88 10 78 7 -10 88 51 123 42 121 54 102 16 103 53 89 10 -11 90 29 122 37 85 45 117 26 116 44 91 11 -11 92 49 101 59 120 34 118 27 96 17 90 11 -12 93 22 113 60 118 34 70 31 67 33 94 12 -13 96 27 119 46 84 35 102 54 95 58 98 13 -13 98 52 117 45 105 59 101 14 100 40 97 13 -14 99 20 109 46 119 50 125 30 124 36 100 14 -14 101 49 79 47 65 48 112 22 93 25 99 14 -15 63 16 102 35 114 24 115 61 104 18 75 15 -19 107 41 113 22 112 37 122 56 124 30 86 19 -20 99 25 74 23 81 26 117 52 106 32 108 20 -20 108 51 88 61 115 38 110 21 111 57 109 20 -36 124 56 71 55 77 57 111 44 116 53 103 36 -0 65 47 83 6 82 39 68 40 100 36 103 16 63 0 -2 69 24 114 62 107 19 106 52 98 58 80 55 71 2 -18 104 43 94 33 91 44 111 21 87 28 120 59 105 18 - -time make run -./CalcGenus -Loading adjacency list... -Read the adjacency list from adjacency_lists/3-12-cage.txt - Number of vertices: 126 - Number of edges: 189 (378 directed) - First 5 vertices (with neighbors): 0(63 64 65) 1(66 67 68) 2(69 70 71) 3(72 73 74) 4(75 76 77) -Beginning to narrow down genus (currently between 0 and 32 with implied fit 65)... -Loading auxiliary data structures for cycles of length 3... No cycles of length 3 found. Skipping. -Loading auxiliary data structures for cycles of length 4... No cycles of length 4 found. Skipping. -Loading auxiliary data structures for cycles of length 5... No cycles of length 5 found. Skipping. -Loading auxiliary data structures for cycles of length 6... No cycles of length 6 found. Skipping. -Loading auxiliary data structures for cycles of length 7... No cycles of length 7 found. Skipping. -Loading auxiliary data structures for cycles of length 8... No cycles of length 8 found. Skipping. -Loading auxiliary data structures for cycles of length 9... No cycles of length 9 found. Skipping. -Loading auxiliary data structures for cycles of length 10... No cycles of length 10 found. Skipping. -Loading auxiliary data structures for cycles of length 11... No cycles of length 11 found. Skipping. -Loading auxiliary data structures for cycles of length 12... Found 2016 cycles of length 12. -Starting search for fit with 31 cycles or proof it doesn't exist (genus between 17 and 32)... -[##################################################] 100% -Did not find proof the fit does not exist, cannot increase lowerbound. Narrowing down the genus to between 17 and 21. Used 1290121986 iterations so far. -Loading auxiliary data structures for cycles of length 13... No cycles of length 13 found. Skipping. -Loading auxiliary data structures for cycles of length 14... Found 1728 cycles of length 14. -Starting search for fit with 31 cycles or proof it doesn't exist (genus between 17 and 21)... -[##################################################] 100% -Found a solution! The genus is 17. Check the output for the 31 cycles. -make run 46249.80s user 47.13s system 94% cpu 13:34:43.76 total diff --git a/CalcGenus/CalcGenus.c b/CalcGenus/CalcGenus.c deleted file mode 100644 index bafb79f..0000000 --- a/CalcGenus/CalcGenus.c +++ /dev/null @@ -1,1447 +0,0 @@ -// Narrows down the genus of an arbitrary graph given its adjacency list. -// Prints the maximum cycle fitting as evidence. A fitting is a set of simple -// cycles (length greater than 2) that use each directed edge exactly once. -// These are the faces in Euler's formula: F - E + V = 2 - 2g. Run with `make -// run`. Works better for regular graphs (preferably of low degree). - -#include -#include -#include -#include -#include - -// configuration options: -#define PRINT_PROGRESS true // whether to print progress messages -// whether to print a newline after each progress bar update: -#define PROGRESS_BAR_NEWLINE progress_bar_newline -#define DEBUG false // whether to print debug messages -// whether to output to stdout instead of file: -#define OUTPUT_TO_STDOUT output_to_stdout -#define ADJACENCY_LIST_FILENAME adj_filename // input file -#define ADJACENCY_LIST_START start_index // vertex numbering starts from -#define OUTPUT_FILENAME "CalcGenus.out" // output file -#define VERTEX_DEGREE vertex_degree // must be >= 2 -#define PRE_GENUS_LOWER_BOUND pre_genus_lower_bound // pre-computed lower bound on the genus -// true if it should to find the full cycle fitting, otherwise stops early once -// it is clear it exists (doesn't quite work with value false yet): -#define FIND_FULL_CYCLE_FITTING true -// true to branch on a remaining directed edge, otherwise uses the most used vertex -#define CONSTRAINED_BY_TWO true -#ifndef ONLY_SIMPLE_CYCLES -#define ONLY_SIMPLE_CYCLES false // only consider simple cycles -#endif - -// assumptions of the program (don't change these): -#define VERTEX_USE_LIMIT VERTEX_DEGREE -#define MAX_VERTICES 65535 -#define MAX_EDGES 65535 -#define MAX_CYCLE_LENGTH 65535 -#define MAX_CYCLES 4294967295 - -// consequences of assumptions: -#define START_CYCLE_LENGTH 3 -typedef uint8_t degree_t; -#define PRIdegree_t PRIu8 -typedef uint16_t vertex_t; -#define PRIvertex_t PRIu16 -#define SCNvertex_t SCNu16 -typedef uint16_t edge_t; -#define PRIedge_t PRIu16 -#define SCNedge_t SCNu16 -typedef vertex_t cycle_length_t; // max length should always be max vertices -#define PRIcycle_length_t PRIvertex_t -#define SCNcycle_length_t SCNvertex_t -typedef uint32_t cycle_index_t; -#define PRIcycle_index_t PRIu32 -#define SCNcycle_index_t SCNu32 -typedef vertex_t* adj_t; -typedef vertex_t* cycles_t; -typedef cycle_index_t* cbv_t; - -// macros -// assert(condition, message, ...fmt_args) -#define assert(condition, ...) \ - if (!(condition)) { \ - fprintf(stderr, __VA_ARGS__); \ - exit(1); \ - } - -// static variables -static FILE* output_file = NULL; -static vertex_t start_index = 0; -static degree_t vertex_degree = 3; -static cycle_index_t pre_genus_lower_bound = 0; -static char* adj_filename = NULL; -static edge_t num_edges_remaining = 0; -static cycle_length_t smallest_cycle_length; -static bool output_to_stdout = false; -static bool progress_bar_newline = false; -static degree_t* vertex_degrees = NULL; - -// auxiliary data structures -adj_t adj_load(char* filename, vertex_t* num_vertices, edge_t* num_edges); -vertex_t* adj_get_neighbors(adj_t adjacency_list, vertex_t vertex); -void adj_remove_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex); -void adj_undo_remove_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex); -bool adj_has_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex); - -cycles_t cycle_generate(adj_t adjacency_list, vertex_t num_vertices, cycle_length_t cycle_length, - cycle_index_t* num_cycles); -vertex_t* cycle_get(cycles_t cycles, cycle_length_t max_cycle_length, cycle_index_t cycle_index, - cycle_length_t* cycle_length); - -cycle_index_t* cbv_generate(vertex_t num_vertices, cycles_t cycles, cycle_index_t num_cycles, - cycle_length_t cycle_length, cycle_index_t* max_cycles_per_vertex); -cycle_index_t* cbv_get_cycle_indices(cbv_t cycles_by_vertex, cycle_index_t max_cycles_per_vertex, - vertex_t vertex, cycle_index_t* num_cycles); - -void show_progress(double fraction); -void show_solution(cycle_index_t genus_lower_bound, cycle_index_t genus_lower_bound_implied_fit, - uint64_t num_search_calls, cycle_index_t num_cycles, bool* used_cycles, - cycles_t cycles, cycle_length_t max_cycle_length); - -bool is_valid_rotation_system(bool* used_cycles, cycles_t cycles, cycle_length_t max_cycle_length, - cycle_index_t num_cycles, vertex_t num_vertices, - cycle_index_t cycle_to_check); -bool is_ijk_good(bool* used_cycles, cycles_t cycles, cycle_length_t max_cycle_length, - cycle_index_t num_cycles, cycle_index_t cycle_to_check); -bool cycle_has_directed_edge(vertex_t* cycle, cycle_length_t cycle_length, vertex_t start_vertex, - vertex_t end_vertex); -bool path_has_reverse_transition(vertex_t* path, cycle_length_t path_length, vertex_t prev_vertex, - vertex_t center_vertex, vertex_t next_vertex); -bool search(cycle_index_t cycles_to_use, // state - cycle_index_t max_used_cycles, // state - bool* used_cycles, // state - degree_t* vertex_uses, cycle_index_t* max_fit, // state - uint64_t* num_search_calls, // state - vertex_t num_vertices, edge_t num_edges, adj_t adjacency_list, - cycle_length_t max_cycle_length, cycle_index_t num_cycles, cycles_t cycles, - cycle_index_t max_cycles_per_vertex, cbv_t cycles_by_vertex, - cycle_index_t current_start_cycle); - -cycle_index_t implied_max_fit_for_genus(cycle_index_t genus, vertex_t num_vertices, - edge_t num_edges) { - return num_edges - num_vertices + 2 - 2 * genus; -} - -cycle_index_t implied_max_genus_for_fit(cycle_index_t fit, vertex_t num_vertices, - edge_t num_edges) { - int64_t val = 1 - ((int64_t)fit - num_edges + num_vertices) / 2; - return val < 0 ? 0 : val; -} - -int main(void) { - start_index = atoi(getenv("S")); - vertex_degree = atoi(getenv("DEG")); - if (getenv("GLB") != NULL) { - pre_genus_lower_bound = atoi(getenv("GLB")); - } - adj_filename = getenv("ADJ"); - output_to_stdout = getenv("STDOUT") != NULL; - progress_bar_newline = getenv("PBN") != NULL; - - if (PRINT_PROGRESS) { - fprintf(stderr, "Loading adjacency list...\n"); - } - - vertex_t num_vertices; - edge_t num_edges; - adj_t adjacency_list = adj_load(ADJACENCY_LIST_FILENAME, &num_vertices, &num_edges); - - if (OUTPUT_TO_STDOUT) { - output_file = stdout; - } else { - output_file = fopen(OUTPUT_FILENAME, "w"); - assert(output_file != NULL, "Error opening file %s\n", OUTPUT_FILENAME); - fprintf(stderr, "Output file: %s\n", OUTPUT_FILENAME); - } - - cycle_index_t genus_lower_bound = - implied_max_genus_for_fit(2 * num_edges / START_CYCLE_LENGTH, // 2E/3 rounded down - num_vertices, num_edges); - cycle_index_t genus_lower_bound_implied_fit = - implied_max_fit_for_genus(genus_lower_bound, num_vertices, num_edges); - if (PRE_GENUS_LOWER_BOUND > genus_lower_bound) { - genus_lower_bound = PRE_GENUS_LOWER_BOUND; - genus_lower_bound_implied_fit = - implied_max_fit_for_genus(genus_lower_bound, num_vertices, num_edges); - } - cycle_index_t max_fit = (2 * num_edges + num_vertices - 1) / num_vertices; - cycle_index_t genus_upper_bound = implied_max_genus_for_fit(max_fit, num_vertices, num_edges); - - if (genus_lower_bound == genus_upper_bound) { - // we've found the genus! - if (PRINT_PROGRESS) { - fprintf(stderr, - "Found the genus! It is %" PRIcycle_index_t - ". No computation needed when the genus is found via the " - "theoretical formula.\n", - genus_lower_bound); - } - fprintf(output_file, "Genus found: %" PRIcycle_index_t " in 0 iterations:\n", - genus_lower_bound); - fclose(output_file); - free(adjacency_list); - free(vertex_degrees); - return 0; - } - - if (PRINT_PROGRESS) { - fprintf(stderr, - "Beginning to narrow down genus (currently between %" PRIcycle_index_t - " and %" PRIcycle_index_t " with implied fit %" PRIcycle_index_t ")...\n", - genus_lower_bound, genus_upper_bound, genus_lower_bound_implied_fit); - } - - uint64_t num_search_calls = 0; - smallest_cycle_length = num_vertices; - cycles_t cycles = NULL; - cycle_index_t num_cycles = 0; - cycle_length_t cycles_max_cycle_length = 0; - for (cycle_length_t cur_max_cycle_length = START_CYCLE_LENGTH; - cur_max_cycle_length <= (ONLY_SIMPLE_CYCLES ? num_vertices : num_edges); - cur_max_cycle_length++) { - if (PRINT_PROGRESS) { - fprintf(stderr, - "Loading auxiliary data structures for cycles of length " - "%" PRIcycle_length_t "... ", - cur_max_cycle_length); - } - - cycle_index_t num_new_cycles; - cycles_t new_cycles = - cycle_generate(adjacency_list, num_vertices, cur_max_cycle_length, &num_new_cycles); - num_cycles += num_new_cycles; - - if (num_new_cycles == 0) { - // no cycles of this length, skip to the next length - free(new_cycles); - if (PRINT_PROGRESS) { - fprintf(stderr, "No cycles of length %" PRIcycle_length_t " found. Skipping.\n", - cur_max_cycle_length); - } - continue; - } - assert(new_cycles != NULL, "Error: new cycles is NULL but there are new cycles\n"); - if (PRINT_PROGRESS) { - fprintf(stderr, - "Found %" PRIcycle_index_t " cycles of length %" PRIcycle_length_t ".\n", - num_new_cycles, cur_max_cycle_length); - } - - // keep the smallest cycle length up to date - if (cur_max_cycle_length < smallest_cycle_length) { - smallest_cycle_length = cur_max_cycle_length; - } - - // the smallest cycle length limits how many cycles we can fit and hence the - // genus - cycle_index_t genus_lower_bound_from_smallest_cycle_length = implied_max_genus_for_fit( - 2 * num_edges / smallest_cycle_length, num_vertices, num_edges); - if (genus_lower_bound_from_smallest_cycle_length > genus_lower_bound) { - genus_lower_bound = genus_lower_bound_from_smallest_cycle_length; - genus_lower_bound_implied_fit = - implied_max_fit_for_genus(genus_lower_bound, num_vertices, num_edges); - } - - // add the new cycles to the old ones - if (cycles == NULL) { - cycles = new_cycles; - cycles_max_cycle_length = cur_max_cycle_length; - } else { - cycles_t combined = - (cycles_t)malloc(num_cycles * (cur_max_cycle_length + 2) * sizeof(vertex_t)); - assert(combined != NULL, "Error allocating memory for the combined cycles\n"); - for (cycle_index_t i = 0; i < num_cycles - num_new_cycles; i++) { - for (cycle_length_t j = 0; j < cycles_max_cycle_length + 2; j++) { - combined[i * (cur_max_cycle_length + 2) + j] = - cycles[i * (cycles_max_cycle_length + 2) + j]; - } - } - for (cycle_index_t i = 0; i < num_new_cycles; i++) { - for (cycle_length_t j = 0; j < cur_max_cycle_length + 2; j++) { - combined[(num_cycles - num_new_cycles + i) * (cur_max_cycle_length + 2) + j] = - new_cycles[i * (cur_max_cycle_length + 2) + j]; - } - } - cycles_max_cycle_length = cur_max_cycle_length; - free(cycles); - free(new_cycles); - cycles = combined; - } - - if (genus_lower_bound < PRE_GENUS_LOWER_BOUND) { - continue; - } - - cycle_index_t max_cycles_per_vertex; - cbv_t cycles_by_vertex = cbv_generate(num_vertices, cycles, num_cycles, - cur_max_cycle_length, &max_cycles_per_vertex); - - if (PRINT_PROGRESS) { - fprintf(stderr, - "Starting search for fit with %" PRIcycle_index_t - " cycles or proof it doesn't exist (genus between %" PRIcycle_index_t - " and %" PRIcycle_index_t ")...\n", - genus_lower_bound_implied_fit, genus_lower_bound, genus_upper_bound); - } - show_progress(0.0); - - // keep track of used cycles and vertices - bool* used_cycles = (bool*)malloc(num_cycles * sizeof(bool)); - assert(used_cycles != NULL, "Error allocating memory for the used cycles\n"); - for (cycle_index_t i = 0; i < num_cycles; i++) { - used_cycles[i] = false; - } - // vertices should be used exactly VERTEX_USE_LIMIT times - // so we keep track of the number of times each vertex has been used. - // this allows us to fail early if a vertex can't be used enough times - // and to prioritize vertices exploring vertices that have been used more - // since they constrain the number of possible cycles containing them more - degree_t* vertex_uses = (degree_t*)malloc(num_vertices * sizeof(degree_t)); - assert(vertex_uses != NULL, "Error allocating memory for the vertices most used order\n"); - - // search for a solution that starts with one of the cycles - for (cycle_index_t c = 0; c < num_cycles; c++) { - // for (cycle_index_t c = num_cycles - num_new_cycles; c < num_cycles; - // c++) { // TODO - if (VERTEX_DEGREE > 2 && - !is_ijk_good(used_cycles, cycles, cur_max_cycle_length, num_cycles, c)) { - continue; - } - if (!is_valid_rotation_system(used_cycles, cycles, cur_max_cycle_length, num_cycles, - num_vertices, c)) { - continue; - } - - // default all vertices to 0 uses - for (vertex_t i = 0; i < num_vertices; i++) { - vertex_uses[i] = 0; - // if it is not a regular graph, we represent it as a regular graph with - // some vertices pre-used, so we need to count them as used here: - vertex_t* neighbors = adj_get_neighbors(adjacency_list, i); - for (degree_t j = 0; j < VERTEX_DEGREE; j++) { - if (neighbors[j] == MAX_VERTICES) { - vertex_uses[i]++; - } - } - } - - // mark start cycle as used - used_cycles[c] = true; - cycle_length_t cycle_length; - cycles_t cycle = cycle_get(cycles, cur_max_cycle_length, c, &cycle_length); - for (cycle_length_t i = 0; i < cycle_length; i++) { - adj_remove_edge(adjacency_list, cycle[i], cycle[i + 1]); - - // mark cycle vertices as used - vertex_uses[cycle[i]] += 1; - } - - if (search(genus_lower_bound_implied_fit - 1, genus_lower_bound_implied_fit, - used_cycles, vertex_uses, &max_fit, &num_search_calls, num_vertices, - num_edges, adjacency_list, cur_max_cycle_length, num_cycles, cycles, - max_cycles_per_vertex, cycles_by_vertex, c)) { - // Success! - show_progress(1.0); - show_solution(genus_lower_bound, genus_lower_bound_implied_fit, num_search_calls, - num_cycles, used_cycles, cycles, cur_max_cycle_length); - free(adjacency_list); - free(vertex_degrees); - free(vertex_uses); - free(cycles); - free(cycles_by_vertex); - free(used_cycles); - fclose(output_file); - return 0; - } - - // mark start cycle as unused - used_cycles[c] = false; - for (cycle_length_t i = 0; i < cycle_length; i++) { - adj_undo_remove_edge(adjacency_list, cycle[i], cycle[i + 1]); - } - - show_progress(c / (double)num_cycles); - } - - show_progress(1.0); - - // we weren't able to find the implied fit, so the bounds need adjusting - if ((2 * num_edges - cur_max_cycle_length - 1) / smallest_cycle_length < - genus_lower_bound_implied_fit - 1) { - genus_lower_bound++; - if (PRINT_PROGRESS) { - fprintf(stderr, "\nFound proof the implied fit does not exist. "); - } - } else if (PRINT_PROGRESS) { - fprintf(stderr, - "\nDid not find proof the fit does not exist, cannot increase " - "lowerbound. "); - } - genus_lower_bound_implied_fit = - implied_max_fit_for_genus(genus_lower_bound, num_vertices, num_edges); - // as a bonus, we might have found a better upper bound - genus_upper_bound = implied_max_genus_for_fit(max_fit, num_vertices, num_edges); - - if (genus_lower_bound == genus_upper_bound && - (!FIND_FULL_CYCLE_FITTING || max_fit == genus_lower_bound_implied_fit)) { - // we've found the genus! - show_solution(genus_lower_bound, max_fit, num_search_calls, num_cycles, used_cycles, - cycles, cur_max_cycle_length); - free(used_cycles); - free(vertex_uses); - free(adjacency_list); - free(vertex_degrees); - free(cycles); - free(cycles_by_vertex); - fclose(output_file); - return 0; - } - assert(FIND_FULL_CYCLE_FITTING || (genus_lower_bound < genus_upper_bound), - "Error: genus lower bound (%" PRIcycle_index_t - ") is greater than upper bound (%" PRIcycle_index_t - " from max_fit %" PRIcycle_index_t ")\n", - genus_lower_bound, genus_upper_bound, max_fit); - - if (PRINT_PROGRESS) { - fprintf(stderr, - "Narrowing down the genus to " - "between %" PRIcycle_index_t " and %" PRIcycle_index_t ". Used %" PRId64 - " iterations so far.\n", - genus_lower_bound, genus_upper_bound, num_search_calls); - } - - free(used_cycles); - free(vertex_uses); - free(cycles_by_vertex); - } - - genus_lower_bound_implied_fit--; - genus_lower_bound = - implied_max_genus_for_fit(genus_lower_bound_implied_fit, num_vertices, num_edges); - if (PRE_GENUS_LOWER_BOUND > genus_lower_bound) { - genus_lower_bound = PRE_GENUS_LOWER_BOUND; - genus_lower_bound_implied_fit = - implied_max_fit_for_genus(genus_lower_bound, num_vertices, num_edges); - } - if (max_fit < (2 * num_edges + cycles_max_cycle_length - 1) / cycles_max_cycle_length) { - max_fit = (2 * num_edges + cycles_max_cycle_length - 1) / cycles_max_cycle_length; - genus_upper_bound = implied_max_genus_for_fit(max_fit, num_vertices, num_edges); - } - cycle_index_t max_cycles_per_vertex; - cbv_t cycles_by_vertex = cbv_generate(num_vertices, cycles, num_cycles, cycles_max_cycle_length, - &max_cycles_per_vertex); - bool* used_cycles = (bool*)malloc(num_cycles * sizeof(bool)); - assert(used_cycles != NULL, "Error allocating memory for the used cycles\n"); - for (cycle_index_t i = 0; i < num_cycles; i++) { - used_cycles[i] = false; - } - degree_t* vertex_uses = (degree_t*)malloc(num_vertices * sizeof(degree_t)); - assert(vertex_uses != NULL, "Error allocating memory for the vertices most used order\n"); - while (FIND_FULL_CYCLE_FITTING ? genus_lower_bound <= genus_upper_bound - : genus_lower_bound < genus_upper_bound) { - if (PRINT_PROGRESS) { - fprintf(stderr, - "Starting search for fit with %" PRIcycle_index_t - " cycles or proof it doesn't exist (genus between %" PRIcycle_index_t - " and %" PRIcycle_index_t ")...\n", - genus_lower_bound_implied_fit, genus_lower_bound, genus_upper_bound); - } - show_progress(0.0); - - // search for a solution that starts with one of the cycles - for (cycle_index_t c = 0; c < num_cycles; c++) { - if (VERTEX_DEGREE > 2 && - !is_ijk_good(used_cycles, cycles, cycles_max_cycle_length, num_cycles, c)) { - continue; - } - if (!is_valid_rotation_system(used_cycles, cycles, cycles_max_cycle_length, num_cycles, - num_vertices, c)) { - continue; - } - - // default all vertices to 0 uses - for (vertex_t i = 0; i < num_vertices; i++) { - vertex_uses[i] = 0; - // if it is not a regular graph, we represent it as a regular graph with - // some vertices pre-used, so we need to count them as used here: - vertex_t* neighbors = adj_get_neighbors(adjacency_list, i); - for (degree_t j = 0; j < VERTEX_DEGREE; j++) { - if (neighbors[j] == MAX_VERTICES) { - vertex_uses[i]++; - } - } - } - - // mark start cycle as used - used_cycles[c] = true; - cycle_length_t cycle_length; - cycles_t cycle = cycle_get(cycles, cycles_max_cycle_length, c, &cycle_length); - for (cycle_length_t i = 0; i < cycle_length; i++) { - adj_remove_edge(adjacency_list, cycle[i], cycle[i + 1]); - - // mark cycle vertices as used - vertex_uses[cycle[i]] += 1; - } - - if (search(genus_lower_bound_implied_fit - 1, genus_lower_bound_implied_fit, - used_cycles, vertex_uses, &max_fit, &num_search_calls, num_vertices, - num_edges, adjacency_list, cycles_max_cycle_length, num_cycles, cycles, - max_cycles_per_vertex, cycles_by_vertex, c)) { - // Success! - show_progress(1.0); - show_solution(genus_lower_bound, genus_lower_bound_implied_fit, num_search_calls, - num_cycles, used_cycles, cycles, cycles_max_cycle_length); - free(adjacency_list); - free(vertex_degrees); - free(vertex_uses); - free(cycles); - free(cycles_by_vertex); - free(used_cycles); - fclose(output_file); - return 0; - } - - // mark start cycle as unused - used_cycles[c] = false; - for (cycle_length_t i = 0; i < cycle_length; i++) { - adj_undo_remove_edge(adjacency_list, cycle[i], cycle[i + 1]); - } - - show_progress(c / (double)num_cycles); - } - - show_progress(1.0); - fprintf(stderr, - "\nFit does not exist. Adjusting bounds. Used %" PRId64 " iterations so far.\n", - num_search_calls); - genus_lower_bound_implied_fit--; - genus_lower_bound = - implied_max_genus_for_fit(genus_lower_bound_implied_fit, num_vertices, num_edges); - } - - free(adjacency_list); - free(vertex_degrees); - free(cycles); - free(cycles_by_vertex); - free(used_cycles); - free(vertex_uses); - fclose(output_file); - - if (FIND_FULL_CYCLE_FITTING) { - fprintf(stderr, - "Was not able to fit any cycles. Double check the settings " - "and adjacency list.\n"); - return 1; - } else { - fprintf(stderr, "The genus is %" PRIcycle_index_t ".\n", genus_lower_bound); - return 0; - } -} - -void show_solution(cycle_index_t genus_lower_bound, cycle_index_t genus_lower_bound_implied_fit, - uint64_t num_search_calls, cycle_index_t num_cycles, bool* used_cycles, - cycles_t cycles, cycle_length_t max_cycle_length) { - if (PRINT_PROGRESS) { - fprintf(stderr, - "\nFound a solution! The genus is %" PRIcycle_index_t - ". Check the output for the %" PRIcycle_index_t " cycles. \n", - genus_lower_bound, genus_lower_bound_implied_fit); - } - fprintf(output_file, - "Solution with %" PRIcycle_index_t " cycles (genus %" PRIcycle_index_t - ") found in %" PRId64 " iterations:\n", - genus_lower_bound_implied_fit, genus_lower_bound, num_search_calls); - for (cycle_index_t i = 0; i < num_cycles; i++) { - if (used_cycles[i]) { - cycle_length_t cycle_length; - cycles_t cycle = cycle_get(cycles, max_cycle_length, i, &cycle_length); - for (cycle_length_t j = 0; j < cycle_length + 1; j++) { - fprintf(output_file, "%" PRIvertex_t " ", cycle[j] + ADJACENCY_LIST_START); - } - fprintf(output_file, "\n"); - } - } -} - -static int prev_percent = -1; -void show_progress(double fraction) { - // E.g. [########## ] 50% - - if (!PRINT_PROGRESS || ((int)(fraction * 100) == prev_percent)) { - return; - } - - if (!PROGRESS_BAR_NEWLINE) { - fflush(stderr); - fprintf(stderr, "\r["); - } else { - fprintf(stderr, "["); - } - for (int i = 0; i < 50; i++) { - if (i < fraction * 50) { - fprintf(stderr, "#"); - } else { - fprintf(stderr, " "); - } - } - fprintf(stderr, "] %d%%", (int)(fraction * 100)); - if (PROGRESS_BAR_NEWLINE) { - fprintf(stderr, "\n"); - } - prev_percent = (int)(fraction * 100); -} - -bool is_valid_rotation_system(bool* used_cycles, cycles_t cycles, cycle_length_t max_cycle_length, - cycle_index_t num_cycles, vertex_t num_vertices, - cycle_index_t cycle_to_check) { - if (VERTEX_DEGREE <= 5) { - return true; // ijk criterion is sufficient - } - - // TODO: optimize by storing the rotation in the adjacency list as cycles - // are added - - edge_t row_size = 2 * VERTEX_DEGREE + 1; - vertex_t* pairs = (vertex_t*)malloc(row_size * num_vertices * sizeof(vertex_t)); - assert(pairs != NULL, "Error allocating memory for the pairs\n"); - bool* pair_seen = (bool*)malloc(VERTEX_DEGREE * sizeof(bool)); - assert(pair_seen != NULL, "Error allocating memory for the pair seen flags\n"); - for (vertex_t i = 0; i < num_vertices; i++) { - pairs[i * row_size] = 0; - } - - for (cycle_index_t c = 0; c < num_cycles; c++) { - if (used_cycles[c] || c == cycle_to_check) { - cycle_length_t cycle_length; - vertex_t* cycle = cycle_get(cycles, max_cycle_length, c, &cycle_length); - - degree_t num_pairs = pairs[cycle[0] * row_size]; - pairs[cycle[0] * row_size + 2 * num_pairs + 1] = cycle[cycle_length - 1]; - pairs[cycle[0] * row_size + 2 * num_pairs + 2] = cycle[1]; - pairs[cycle[0] * row_size] = num_pairs + 1; - - for (cycle_length_t i = 1; i < cycle_length - 1; i++) { - degree_t num_pairs = pairs[cycle[i] * row_size]; - pairs[cycle[i] * row_size + 2 * num_pairs + 1] = cycle[i - 1]; - pairs[cycle[i] * row_size + 2 * num_pairs + 2] = cycle[i + 1]; - pairs[cycle[i] * row_size] = num_pairs + 1; - } - - num_pairs = pairs[cycle[cycle_length - 1] * row_size]; - pairs[cycle[cycle_length - 1] * row_size + 2 * num_pairs + 1] = cycle[cycle_length - 2]; - pairs[cycle[cycle_length - 1] * row_size + 2 * num_pairs + 2] = cycle[cycle_length]; - pairs[cycle[cycle_length - 1] * row_size] = num_pairs + 1; - } - } - - for (vertex_t i = 0; i < num_vertices; i++) { - degree_t num_pairs = pairs[i * row_size]; - if (num_pairs == 0) continue; - - for (degree_t start_pair = 0; start_pair < num_pairs; start_pair++) { - vertex_t start = pairs[i * row_size + 2 * start_pair + 1]; - vertex_t next = pairs[i * row_size + 2 * start_pair + 2]; - degree_t component_size = 1; - for (degree_t j = 0; j < num_pairs; j++) { - pair_seen[j] = false; - } - pair_seen[start_pair] = true; - - while (next != start) { - bool found = false; - for (degree_t j = 0; j < num_pairs; j++) { - if (pairs[i * row_size + 2 * j + 1] == next) { - if (pair_seen[j]) { - free(pair_seen); - free(pairs); - return false; - } - next = pairs[i * row_size + 2 * j + 2]; - pair_seen[j] = true; - component_size++; - found = true; - break; - } - } - if (!found) { - break; - } - } - - if (next == start && component_size < vertex_degrees[i]) { - free(pair_seen); - free(pairs); - return false; - } - } - - if (num_pairs == vertex_degrees[i]) { - degree_t pairs_used = 0; - vertex_t start = pairs[i * row_size + 1]; - vertex_t next = start; - do { - bool found = false; - for (degree_t j = 0; j < num_pairs; j++) { - if (pairs[i * row_size + 2 * j + 1] == next) { - next = pairs[i * row_size + 2 * j + 2]; - pairs_used++; - found = true; - break; - } - } - if (!found) { - free(pair_seen); - free(pairs); - return false; - } - } while (next != start && pairs_used <= num_pairs); - - if (pairs_used != num_pairs || next != start) { - free(pair_seen); - free(pairs); - return false; - } - } - } - - free(pair_seen); - free(pairs); - return true; -} - -// Return false if the candidate cycle conflicts with an already-used cycle by -// introducing both transitions i -> j -> k and k -> j -> i at any vertex j with -// degree > 2. Candidate-internal conflicts are filtered during cycle generation. -bool is_ijk_good(bool* used_cycles, cycles_t cycles, cycle_length_t max_cycle_length, - cycle_index_t num_cycles, cycle_index_t cycle_to_check) { - // TODO: optimize by storing the rotation in the adjacency list as cycles - // are added - cycle_length_t cycle_length; - vertex_t* cycle = cycle_get(cycles, max_cycle_length, cycle_to_check, &cycle_length); - - vertex_t* padded_cycle = (vertex_t*)malloc((cycle_length + 2) * sizeof(vertex_t)); - assert(padded_cycle != NULL, "Error allocating memory for the padded cycle\n"); - for (cycle_length_t i = 0; i < cycle_length; i++) { - padded_cycle[i] = cycle[i]; - } - padded_cycle[cycle_length] = cycle[0]; - padded_cycle[cycle_length + 1] = cycle[1]; - - for (cycle_index_t c = 0; c < num_cycles; c++) { - if (used_cycles[c]) { - cycle_length_t other_cycle_length; - vertex_t* other_cycle = cycle_get(cycles, max_cycle_length, c, &other_cycle_length); - - vertex_t* padded_other_cycle = - (vertex_t*)malloc((other_cycle_length + 2) * sizeof(vertex_t)); - assert(padded_other_cycle != NULL, - "Error allocating memory for the padded other cycle\n"); - for (cycle_length_t i = 0; i < other_cycle_length; i++) { - padded_other_cycle[i] = other_cycle[i]; - } - padded_other_cycle[other_cycle_length] = other_cycle[0]; - padded_other_cycle[other_cycle_length + 1] = other_cycle[1]; - - for (cycle_length_t i = 0; i < cycle_length; i++) { - for (cycle_length_t j = 0; j < other_cycle_length; j++) { - if (padded_cycle[i] == padded_other_cycle[j + 2] && - padded_cycle[i + 1] == padded_other_cycle[j + 1] && - padded_cycle[i + 2] == padded_other_cycle[j] && - vertex_degrees[padded_cycle[i + 1]] > 2) { - free(padded_cycle); - free(padded_other_cycle); - return false; - } - } - } - - free(padded_other_cycle); - } - } - - free(padded_cycle); - return true; -} - -bool search(cycle_index_t cycles_to_use, // state - cycle_index_t max_used_cycles, // state - bool* used_cycles, // state - degree_t* vertex_uses, cycle_index_t* max_fit, // state - uint64_t* num_search_calls, // state - vertex_t num_vertices, edge_t num_edges, adj_t adjacency_list, - cycle_length_t max_cycle_length, cycle_index_t num_cycles, cycles_t cycles, - cycle_index_t max_cycles_per_vertex, cbv_t cycles_by_vertex, - cycle_index_t current_start_cycle) { - (*num_search_calls)++; - - // pick a vertex to explore - vertex_t vertex = 0; - vertex_t neighbor_vertex = MAX_VERTICES; - bool found = false; - if (CONSTRAINED_BY_TWO) { - // Pick a remaining directed edge. Every complete fitting must use it, and - // choosing the edge with the fewest available trails keeps the branching - // factor low. - degree_t max_comb_uses = 0; - cycle_index_t min_cycle_options = MAX_CYCLES; - for (vertex_t i = 0; i < num_vertices; i++) { - if (vertex_uses[i] >= VERTEX_USE_LIMIT) { - continue; - } - - vertex_t* neighbors = adj_get_neighbors(adjacency_list, i); - cycle_index_t num_cycles_for_vertex; - cycle_index_t* cycle_indices_for_vertex = cbv_get_cycle_indices( - cycles_by_vertex, max_cycles_per_vertex, i, &num_cycles_for_vertex); - for (degree_t j = 0; j < VERTEX_DEGREE; j++) { - if (neighbors[j] == MAX_VERTICES || vertex_uses[neighbors[j]] >= VERTEX_USE_LIMIT) { - continue; - } - degree_t comb_uses = vertex_uses[i] + vertex_uses[neighbors[j]]; - cycle_index_t cycle_options = 0; - for (cycle_index_t k = 0; k < num_cycles_for_vertex; k++) { - cycle_index_t cycle_index = cycle_indices_for_vertex[k]; - if (cycle_index <= current_start_cycle || used_cycles[cycle_index]) { - continue; - } - cycle_length_t cycle_length; - vertex_t* cycle = - cycle_get(cycles, max_cycle_length, cycle_index, &cycle_length); - if (cycle_has_directed_edge(cycle, cycle_length, i, neighbors[j])) { - cycle_options++; - } - } - if (!found || cycle_options < min_cycle_options || - (cycle_options == min_cycle_options && comb_uses > max_comb_uses)) { - found = true; - vertex = i; - neighbor_vertex = neighbors[j]; - max_comb_uses = comb_uses; - min_cycle_options = cycle_options; - - if (min_cycle_options == 0) { - break; // we can't do better than this - } - } - } - if (min_cycle_options == 0) { - break; // we can't do better than this - } - } - } else { - // we pick the most used vertex that hasn't reached the limit since it - // constrains the search space of possible cycles more - degree_t max_uses = 0; - for (vertex_t i = 0; i < num_vertices; i++) { - if (vertex_uses[i] < VERTEX_USE_LIMIT && (!found || vertex_uses[i] > max_uses)) { - found = true; - vertex = i; - max_uses = vertex_uses[i]; - - if (max_uses == VERTEX_USE_LIMIT - 1) { - break; // we can't do better than this - } - } - } - } - // if we've explored all vertices fully, this cannot be extended further - if (!found) { - return false; - } - - // if we've reached a new maximum fit, print it - if (max_used_cycles - cycles_to_use > *max_fit) { - // make sure all vertices are fully used - bool all_used = true; - for (vertex_t i = 0; i < num_vertices; i++) { - if (vertex_uses[i] < VERTEX_USE_LIMIT) { - all_used = false; - break; - } - } - - if (all_used) { - *max_fit = max_used_cycles - cycles_to_use; - fprintf(output_file, - "New max fit: %" PRIcycle_index_t " (about to try vertex %" PRIvertex_t ")\n", - *max_fit, vertex); - for (cycle_index_t i = 0; i < num_cycles; i++) { - if (used_cycles[i]) { - cycle_length_t cycle_length; - vertex_t* cycle = cycle_get(cycles, max_cycle_length, i, &cycle_length); - for (cycle_length_t j = 0; j < cycle_length + 1; j++) { - fprintf(output_file, "%" PRIvertex_t " ", cycle[j] + ADJACENCY_LIST_START); - } - fprintf(output_file, "\n"); - } - } - fprintf(output_file, "\n"); - fflush(output_file); - } - } - - // look through the possible cycles that contain this vertex - // if none can be used, this is a failed end and we backtrack - // otherwise, we have our solution - cycle_index_t num_cycles_for_vertex; - cbv_t cycle_indices; - if (CONSTRAINED_BY_TWO && neighbor_vertex != MAX_VERTICES) { - cycle_index_t num_cycles_for_vertex1; - cycle_index_t* cycle_indices1 = cbv_get_cycle_indices( - cycles_by_vertex, max_cycles_per_vertex, vertex, &num_cycles_for_vertex1); - if (num_cycles_for_vertex1 == 0) { - return false; - } - - num_cycles_for_vertex = 0; - cycle_indices = (cbv_t)malloc(num_cycles_for_vertex1 * sizeof(cycle_index_t)); - assert(cycle_indices != NULL, "Error allocating memory for the cycle indices\n"); - - for (cycle_index_t i = 0; i < num_cycles_for_vertex1; i++) { - cycle_index_t cycle_index = cycle_indices1[i]; - if (cycle_index <= current_start_cycle || used_cycles[cycle_index]) { - continue; - } - cycle_length_t cycle_length; - vertex_t* cycle = cycle_get(cycles, max_cycle_length, cycle_index, &cycle_length); - if (cycle_has_directed_edge(cycle, cycle_length, vertex, neighbor_vertex)) { - cycle_indices[num_cycles_for_vertex++] = cycle_index; - } - } - } else { - cycle_indices = cbv_get_cycle_indices(cycles_by_vertex, max_cycles_per_vertex, vertex, - &num_cycles_for_vertex); - } - - for (cycle_index_t i = 0; i < num_cycles_for_vertex; i++) { - // skip if the cycle is already used - cycle_index_t cycle_index = cycle_indices[i]; - if (cycle_index <= current_start_cycle) { - continue; - } - if (used_cycles[cycle_index]) { - continue; - } - - cycle_length_t cycle_length; - vertex_t* cycle = cycle_get(cycles, max_cycle_length, cycle_index, &cycle_length); - - // If the cycle is too long and doesn't leave enough edges for our desired - // fit, we can't use it; similarly, if it is too short and doesn't allow us - // to use all the edges, we can't use it - if (((cycles_to_use - 1) * smallest_cycle_length > num_edges_remaining - cycle_length) || - ((cycles_to_use - 1) * max_cycle_length < num_edges_remaining - cycle_length)) { - continue; - } - - // cycle is only usable if all edges are available - bool can_use = true; - for (cycle_length_t j = 0; j < cycle_length; j++) { - if (!adj_has_edge(adjacency_list, cycle[j], cycle[j + 1])) { - can_use = false; - break; - } - } - if (!can_use) { - continue; - } - - // make sure the cycle satisfies the ijk condition - if (VERTEX_DEGREE > 2 && - !is_ijk_good(used_cycles, cycles, max_cycle_length, num_cycles, cycle_index)) { - continue; - } - if (!is_valid_rotation_system(used_cycles, cycles, max_cycle_length, num_cycles, - num_vertices, cycle_index)) { - continue; - } - - // use the cycle - used_cycles[cycle_index] = true; - for (cycle_length_t j = 0; j < cycle_length; j++) { - adj_remove_edge(adjacency_list, cycle[j], cycle[j + 1]); - - // mark cycle vertices as used - vertex_uses[cycle[j]]++; - assert(vertex_uses[cycle[j]] <= VERTEX_USE_LIMIT, - "\nVertex %" PRIvertex_t " used too many times\n", cycle[j]); - } - - // if this is the final cycle needed to cover all edges, we're done - bool is_final_cycle = - FIND_FULL_CYCLE_FITTING - ? cycles_to_use == 1 - : (cycles_to_use == 1 || - implied_max_genus_for_fit(max_used_cycles - cycles_to_use + 1, num_vertices, - num_edges) == - implied_max_genus_for_fit(max_used_cycles, num_vertices, num_edges)); - if (is_final_cycle) { - if (FIND_FULL_CYCLE_FITTING) { - // check that all vertices have been used enough times - bool all_vertices_used = true; - for (vertex_t i = 0; i < num_vertices; i++) { - if (vertex_uses[i] < VERTEX_USE_LIMIT) { - all_vertices_used = false; - break; - } - } - if (!all_vertices_used) { - used_cycles[cycle_index] = false; - for (cycle_length_t j = 0; j < cycle_length; j++) { - adj_undo_remove_edge(adjacency_list, cycle[j], cycle[j + 1]); - - // un-use the cycle vertices - vertex_uses[cycle[j]]--; - } - continue; - } - } - if (CONSTRAINED_BY_TWO && neighbor_vertex != MAX_VERTICES) { - free(cycle_indices); - } - return true; - } - - // otherwise, continue adding cycles - if (search(cycles_to_use - 1, max_used_cycles, used_cycles, vertex_uses, max_fit, - num_search_calls, num_vertices, num_edges, adjacency_list, max_cycle_length, - num_cycles, cycles, max_cycles_per_vertex, cycles_by_vertex, - current_start_cycle)) { - if (CONSTRAINED_BY_TWO && neighbor_vertex != MAX_VERTICES) { - free(cycle_indices); - } - return true; // as soon as we succeed, we're done - } - - // un-use the cycle - used_cycles[cycle_index] = false; - for (cycle_length_t j = 0; j < cycle_length; j++) { - adj_undo_remove_edge(adjacency_list, cycle[j], cycle[j + 1]); - - // un-use the cycle vertices - vertex_uses[cycle[j]]--; - } - } - - if (CONSTRAINED_BY_TWO && neighbor_vertex != MAX_VERTICES) { - free(cycle_indices); - } - - // if we haven't returned true by now, we've failed - return false; -} - -bool cycle_has_directed_edge(vertex_t* cycle, cycle_length_t cycle_length, vertex_t start_vertex, - vertex_t end_vertex) { - for (cycle_length_t i = 0; i < cycle_length; i++) { - if (cycle[i] == start_vertex && cycle[i + 1] == end_vertex) { - return true; - } - } - return false; -} - -bool path_has_reverse_transition(vertex_t* path, cycle_length_t path_length, vertex_t prev_vertex, - vertex_t center_vertex, vertex_t next_vertex) { - if (vertex_degrees[center_vertex] <= 2) { - return false; - } - - for (cycle_length_t i = 1; i + 1 < path_length; i++) { - if (path[i - 1] == next_vertex && path[i] == center_vertex && - path[i + 1] == prev_vertex) { - return true; - } - } - return false; -} - -adj_t adj_load(char* filename, vertex_t* num_vertices, edge_t* num_edges) { - FILE* fp = fopen(filename, "r"); - assert(fp != NULL, "Error opening file %s\n", filename); - - // number of vertices and edges are the two first numbers - assert(fscanf(fp, "%" SCNvertex_t " %" SCNedge_t "", num_vertices, num_edges) == 2, - "Error reading the first line of %s\n", filename); - - adj_t adjacency_list = (adj_t)malloc(*num_vertices * VERTEX_DEGREE * sizeof(vertex_t)); - assert(adjacency_list != NULL, "Error allocating memory for the adjacency list\n"); - vertex_degrees = (degree_t*)malloc(*num_vertices * sizeof(degree_t)); - assert(vertex_degrees != NULL, "Error allocating memory for the vertex degrees\n"); - for (vertex_t i = 0; i < *num_vertices; i++) { - vertex_degrees[i] = 0; - } - for (vertex_t i = 0; i < *num_vertices * VERTEX_DEGREE; i++) { - assert(fscanf(fp, "%" SCNvertex_t, &adjacency_list[i]) == 1, - "Error reading the adjacency list from %s\n", filename); - if (adjacency_list[i] != MAX_VERTICES) { - adjacency_list[i] -= ADJACENCY_LIST_START; - vertex_degrees[i / VERTEX_DEGREE]++; - } - } - - fclose(fp); - - if (PRINT_PROGRESS) { - fprintf(stderr, "Read the adjacency list from %s\n", filename); - fprintf(stderr, "\tNumber of vertices: %" PRIvertex_t " \n", *num_vertices); - fprintf(stderr, "\tNumber of edges: %" PRIedge_t " (%" PRIedge_t " directed)\n", *num_edges, - 2 * *num_edges); - fprintf(stderr, "\tFirst 5 vertices (with neighbors): "); - vertex_t vertices_to_print = *num_vertices < 5 ? *num_vertices : 5; - degree_t neighbors_to_print = VERTEX_DEGREE < 3 ? VERTEX_DEGREE : 3; - for (vertex_t v = 0; v < vertices_to_print; v++) { - fprintf(stderr, "%" PRIvertex_t "(", v); - for (degree_t d = 0; d < neighbors_to_print; d++) { - if (d > 0) { - fprintf(stderr, " "); - } - fprintf(stderr, "%" PRIvertex_t, - adj_get_neighbors(adjacency_list, v)[d] + ADJACENCY_LIST_START); - } - fprintf(stderr, ") "); - } - fprintf(stderr, "\n"); - } - - num_edges_remaining = 2 * *num_edges; - return adjacency_list; -} - -vertex_t* adj_get_neighbors(adj_t adjacency_list, vertex_t vertex) { - return &adjacency_list[vertex * VERTEX_DEGREE]; -} - -void adj_remove_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex) { - vertex_t* neighbors = adj_get_neighbors(adjacency_list, start_vertex); - for (degree_t i = 0; i < VERTEX_DEGREE; i++) { - if (neighbors[i] == end_vertex) { - num_edges_remaining -= 1; - neighbors[i] = MAX_VERTICES; - return; - } - } -} - -// must have been previously removed, otherwise undefined behavior -void adj_undo_remove_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex) { - vertex_t* neighbors = adj_get_neighbors(adjacency_list, start_vertex); - for (degree_t i = 0; i < VERTEX_DEGREE; i++) { - if (neighbors[i] == MAX_VERTICES) { - num_edges_remaining += 1; - neighbors[i] = end_vertex; - return; - } - } -} - -bool adj_has_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex) { - vertex_t* neighbors = adj_get_neighbors(adjacency_list, start_vertex); - for (degree_t i = 0; i < VERTEX_DEGREE; i++) { - if (neighbors[i] == end_vertex) { - return true; - } - } - return false; -} - -struct fifo { - vertex_t* data; - cycle_index_t head; - cycle_index_t tail; - cycle_index_t capacity; - cycle_length_t path_length; -}; -void fifo_init(struct fifo* fifo, cycle_index_t initial_capacity, cycle_length_t path_length) { - fifo->data = (vertex_t*)malloc(initial_capacity * path_length * sizeof(vertex_t)); - assert(fifo->data != NULL, "Error allocating memory for the fifo\n"); - fifo->head = 0; - fifo->tail = 0; - fifo->capacity = initial_capacity; - fifo->path_length = path_length; -} -bool fifo_empty(struct fifo* fifo) { return fifo->head == fifo->tail; } -void fifo_push(struct fifo* fifo, vertex_t* path) { - if ((fifo->tail + 1) % fifo->capacity == fifo->head) { - // double the capacity - vertex_t* new_data = - (vertex_t*)malloc(2 * fifo->capacity * fifo->path_length * sizeof(vertex_t)); - assert(new_data != NULL, "Error allocating memory for the fifo\n"); - for (cycle_index_t i = 0; i < fifo->capacity; i++) { - for (cycle_length_t j = 0; j < fifo->path_length; j++) { - new_data[i * fifo->path_length + j] = - fifo->data[((fifo->head + i) % fifo->capacity) * fifo->path_length + j]; - } - } - free(fifo->data); - fifo->data = new_data; - fifo->head = 0; - fifo->tail = fifo->capacity - 1; - fifo->capacity *= 2; - } - - for (cycle_length_t i = 0; i < fifo->path_length; i++) { - fifo->data[fifo->tail * fifo->path_length + i] = path[i]; - } - fifo->tail = (fifo->tail + 1) % fifo->capacity; -} -void fifo_pop(struct fifo* fifo, vertex_t* path) { - for (cycle_length_t i = 0; i < fifo->path_length; i++) { - path[i] = fifo->data[fifo->head * fifo->path_length + i]; - } - fifo->head = (fifo->head + 1) % fifo->capacity; -} -cycle_index_t fifo_size(struct fifo* fifo) { - return (fifo->tail - fifo->head + fifo->capacity) % fifo->capacity; -} -void fifo_free(struct fifo* fifo) { - free(fifo->data); - fifo->data = NULL; -} - -cycles_t cycle_generate(adj_t adjacency_list, vertex_t num_vertices, cycle_length_t cycle_length, - cycle_index_t* num_cycles) { - vertex_t* buffer = (vertex_t*)malloc((cycle_length + 2) * sizeof(vertex_t)); - assert(buffer != NULL, "Error allocating memory for the buffer\n"); - - struct fifo cycle_list; - fifo_init(&cycle_list, cycle_length * num_vertices, cycle_length + 2); - struct fifo queue; - fifo_init(&queue, cycle_length * num_vertices, cycle_length + 2); - - for (cycle_length_t i = 2; i < cycle_length + 2; i++) { - buffer[i] = 0; - } - for (vertex_t i = 0; i < num_vertices; i++) { - buffer[0] = 1; - buffer[1] = i; - fifo_push(&queue, buffer); - } - while (!fifo_empty(&queue)) { - fifo_pop(&queue, buffer); - cycle_length_t path_length = buffer[0]; - vertex_t* path = &buffer[1]; - vertex_t* neighbors = adj_get_neighbors(adjacency_list, path[path_length - 1]); - if (path_length == cycle_length) { - for (degree_t i = 0; i < VERTEX_DEGREE; i++) { - if (neighbors[i] != path[0]) { - continue; // if this doesn't complete a cycle, keep looking - } - if (!ONLY_SIMPLE_CYCLES) { - // when not dealing with purely simple cycles, we need some extra - // checks - - // prevent backtracking - if (path[1] == path[path_length - 1] || path[path_length - 2] == path[0]) { - break; - } - - // prevent repeated directed edges - bool repeated_edge = false; - for (cycle_length_t j = 0; j < path_length - 1; j++) { - if (path[j] == path[path_length - 1] && path[j + 1] == path[0]) { - repeated_edge = true; - break; - } - } - if (repeated_edge) { - break; - } - - if (path_has_reverse_transition(path, path_length, path[path_length - 2], - path[path_length - 1], path[0]) || - path_has_reverse_transition(path, path_length, path[path_length - 1], - path[0], path[1])) { - break; - } - } - // we've found a cycle - buffer[cycle_length + 1] = path[0]; - fifo_push(&cycle_list, buffer); - break; - } - } else { - for (degree_t i = 0; i < VERTEX_DEGREE; i++) { - vertex_t neighbor = neighbors[i]; - if (neighbor == MAX_VERTICES) continue; - if (ONLY_SIMPLE_CYCLES ? (neighbor <= path[0]) : (neighbor < path[0])) { - continue; - } - if (ONLY_SIMPLE_CYCLES) { - // don't allow repeated vertices in the path (implicitly also prevents - // backtracking and repeated directed edges) - bool neighbor_in_path = false; - for (cycle_length_t j = 0; j < path_length; j++) { - if (path[j] == neighbor) { - neighbor_in_path = true; - break; - } - } - if (neighbor_in_path) { - continue; - } - } else { - if (path_length >= 2 && neighbor == path[path_length - 2]) { - // Skip the neighbor if it is the previous vertex in the path (no - // backtracking). - continue; - } - - // skip if any directed edge is repeated, i.e. matches the one we are - // currently adding from path[path_length - 1] to neighbor - bool repeated_edge = false; - for (cycle_length_t j = 0; j < path_length - 1; j++) { - if (path[j] == path[path_length - 1] && path[j + 1] == neighbor) { - repeated_edge = true; - break; - } - } - if (repeated_edge) { - continue; - } - - if (path_length >= 2 && - path_has_reverse_transition(path, path_length, path[path_length - 2], - path[path_length - 1], neighbor)) { - continue; - } - } - - buffer[0] = path_length + 1; - path[path_length] = neighbor; - fifo_push(&queue, buffer); - } - } - } - - fifo_free(&queue); - free(buffer); - *num_cycles = fifo_size(&cycle_list); - vertex_t* cycles = NULL; - if (*num_cycles != 0) { - cycles = (vertex_t*)realloc(cycle_list.data, - *num_cycles * (cycle_length + 2) * sizeof(vertex_t)); - assert(cycles != NULL, "Error reallocating memory for the cycles\n"); - } - cycle_list.data = NULL; - fifo_free(&cycle_list); - - if (DEBUG) { - fprintf(stderr, "Generated cycles of length: %" PRIcycle_length_t "\n", cycle_length); - fprintf(stderr, "\tNumber of cycles: %" PRIcycle_index_t "\n", *num_cycles); - fprintf(stderr, "\tFirst 5 cycles:\n"); - for (cycle_index_t i = 0; i < (*num_cycles > 5 ? 5 : *num_cycles); i++) { - fprintf(stderr, "\t\t%d: ", i); - for (cycle_length_t j = 0; j < cycle_length + 1; j++) { - fprintf(stderr, "%02" PRIvertex_t " ", cycle_get(cycles, cycle_length, i, NULL)[j]); - } - fprintf(stderr, "\n"); - } - } - - return cycles; -} - -vertex_t* cycle_get(cycles_t cycles, cycle_length_t max_cycle_length, cycle_index_t cycle_index, - cycle_length_t* cycle_length) { - vertex_t* row = &cycles[cycle_index * (max_cycle_length + 2)]; - if (cycle_length != NULL) { - *cycle_length = row[0]; - } - return &row[1]; -} - -cycle_index_t* cbv_generate(vertex_t num_vertices, cycles_t cycles, cycle_index_t num_cycles, - cycle_length_t max_cycle_length, cycle_index_t* max_cycles_per_vertex) { - // find the number of cycles per vertex - cycle_index_t* cycles_per_vertex = (cycle_index_t*)malloc(num_vertices * sizeof(cycle_index_t)); - assert(cycles_per_vertex != NULL, "Error allocating memory for the cycles per vertex\n"); - for (vertex_t i = 0; i < num_vertices; i++) { - cycles_per_vertex[i] = 0; - } - cycle_length_t cycle_length; - for (cycle_index_t i = 0; i < num_cycles; i++) { - vertex_t* cycle = cycle_get(cycles, max_cycle_length, i, &cycle_length); - for (cycle_length_t j = 0; j < cycle_length; j++) { - cycles_per_vertex[cycle[j]]++; - } - } - - // find the maximum number of cycles per vertex - *max_cycles_per_vertex = 0; - for (vertex_t i = 0; i < num_vertices; i++) { - if (cycles_per_vertex[i] > *max_cycles_per_vertex) { - *max_cycles_per_vertex = cycles_per_vertex[i]; - } - } - - cbv_t cycles_by_vertex = - (cbv_t)malloc(num_vertices * (*max_cycles_per_vertex + 1) * sizeof(cycle_index_t)); - assert(cycles_by_vertex != NULL, "Error allocating memory for the cycles by vertex\n"); - - // fill in the cycles by vertex - for (vertex_t i = 0; i < num_vertices; i++) { - cycles_by_vertex[i * (*max_cycles_per_vertex + 1)] = cycles_per_vertex[i]; - cycle_index_t num_cycles_for_vertex = 0; - for (cycle_index_t j = 0; j < num_cycles && num_cycles_for_vertex < cycles_per_vertex[i]; - j++) { - bool cycle_contains_vertex = false; - vertex_t* cycle = cycle_get(cycles, max_cycle_length, j, &cycle_length); - for (cycle_length_t k = 0; k < cycle_length; k++) { - if (cycle[k] == i) { - cycle_contains_vertex = true; - break; - } - } - if (cycle_contains_vertex) { - cycles_by_vertex[i * (*max_cycles_per_vertex + 1) + num_cycles_for_vertex + 1] = j; - num_cycles_for_vertex++; - } - } - if (ONLY_SIMPLE_CYCLES) { - // For simple cycles, each vertex can only occur once in a cycle so we - // already have the correct number of cycles - assert(num_cycles_for_vertex == cycles_per_vertex[i], - "Error filling in the cycles by vertex %" PRIvertex_t " (%" PRIcycle_index_t - " != %" PRIcycle_index_t ")\n", - i, num_cycles_for_vertex, cycles_per_vertex[i]); - } else { - // otherwise, we overcounted and need to correct - cycles_by_vertex[i * (*max_cycles_per_vertex + 1)] = num_cycles_for_vertex; - } - } - - if (DEBUG) { - fprintf(stderr, "Organized cycles by vertex\n"); - fprintf(stderr, "\tMax cycles per vertex: %" PRIcycle_index_t "\n", *max_cycles_per_vertex); - fprintf(stderr, "\tLast 2 cycles of vertex 0 and 1:\n"); - for (uint8_t i = num_vertices - 2; i < num_vertices; i++) { - cycle_index_t num_cycles; - cycle_index_t* cycle_indices = - cbv_get_cycle_indices(cycles_by_vertex, *max_cycles_per_vertex, i, &num_cycles); - fprintf(stderr, "\t\t%d:\n", i); - for (cycle_index_t j = 0; j < num_cycles && j < 2; j++) { - fprintf(stderr, "\t\t\t%" PRIcycle_index_t " / %" PRIcycle_index_t ": ", j, - num_cycles); - vertex_t* cycle = - cycle_get(cycles, max_cycle_length, cycle_indices[j], &cycle_length); - for (cycle_length_t h = 0; h < cycle_length + 1; h++) { - fprintf(stderr, "%02" PRIvertex_t " ", cycle[h]); - } - fprintf(stderr, "\n"); - } - } - } - - free(cycles_per_vertex); - return cycles_by_vertex; -} - -cycle_index_t* cbv_get_cycle_indices(cbv_t cycles_by_vertex, cycle_index_t max_cycles_per_vertex, - vertex_t vertex, cycle_index_t* num_cycles) { - cycle_index_t* row = &cycles_by_vertex[vertex * (max_cycles_per_vertex + 1)]; - *num_cycles = row[0]; - return &row[1]; -} diff --git a/CalcGenus/CalcGenus.out b/CalcGenus/CalcGenus.out deleted file mode 100644 index e69de29..0000000 diff --git a/CalcGenus/adjacency_lists/rome_temp.txt b/CalcGenus/adjacency_lists/rome_temp.txt deleted file mode 100644 index c9a1108..0000000 --- a/CalcGenus/adjacency_lists/rome_temp.txt +++ /dev/null @@ -1,23 +0,0 @@ -22 37 -1 2 20 21 -0 3 15 65535 -0 5 15 65535 -1 18 13 65535 -17 18 19 12 -2 9 21 65535 -8 16 7 65535 -6 9 10 65535 -6 13 15 65535 -5 7 10 20 -7 9 13 65535 -18 20 12 14 -4 11 14 15 -3 8 10 16 -11 12 17 65535 -1 2 8 12 -6 13 19 21 -4 14 19 65535 -3 4 11 65535 -4 16 17 65535 -0 9 11 65535 -0 5 16 65535 diff --git a/CalcGenus/explore.ipynb b/CalcGenus/explore.ipynb deleted file mode 100644 index 120b455..0000000 --- a/CalcGenus/explore.ipynb +++ /dev/null @@ -1,1721 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "import networkx as nx\n", - "import matplotlib.pyplot as plt\n", - "from sage.all import *\n", - "from math import ceil\n", - "import plotly.graph_objects as go\n", - "import numpy as np\n", - "from time import perf_counter" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Experiment with Cycle Calculation Algorithm" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "g = graphs.Balaban10Cage(embedding=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "NUM_VERTICES = g.num_verts()\n", - "NUM_EDGES = g.size()\n", - "VERTEX_DEGREE = g.degree()[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "adjacency_matrix = g.adjacency_matrix()\n", - "adjacency_list = [ [0 for i in range(VERTEX_DEGREE)] for j in range(NUM_VERTICES)]\n", - "for i in range(NUM_VERTICES):\n", - " d = 0\n", - " for j in range(NUM_VERTICES):\n", - " if adjacency_matrix[i][j] == 1:\n", - " adjacency_list[i][d] = j\n", - " d += 1" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "# find the number of cycles of length k\n", - "\n", - "# https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1602189\n", - "# We use a FIFO queue to store the open paths and a register to \n", - "# record the length of the path. The register is not necessary, \n", - "# because you can always get the length from the open path directly.\n", - "# The algorithm starts with all vertices of the graph. First,\n", - "# put all vertices into the queue and set the register to 0.\n", - "# Then the iteration of main loop of the algorithm starts.\n", - "# Fetch an open path from the queue. Its length is k which\n", - "# is indicated by the register.\n", - "# Verify if there is an edge which links the tail to the head\n", - "# of the open path. If it is true, a cycle is enumerated, and\n", - "# then output the cycle. When the register is 0 in such case, it\n", - "# means the cycle is a selfloop.\n", - "# Then get an adjacent edge of the tail whose end does not\n", - "# occur in the open path and the order of its end is greater than\n", - "# the order of the head. This edge and the k length open path\n", - "# construct a new k + 1 length open path. Put this new open\n", - "# path into the queue.\n", - "# After having generated all the k + 1 length open paths\n", - "# from the k length open path, if this open path is the last k\n", - "# length open path of the queue, set register to k + 1.\n", - "# If the queue is empty, the algorithm finishes, else jumps\n", - "# to where the main loop starts.\n", - "\n", - "def find_cycles(k):\n", - " cycles = []\n", - " queue = []\n", - " for i in range(NUM_VERTICES):\n", - " queue.append([i])\n", - " while len(queue) > 0:\n", - " path = queue.pop(0)\n", - " if len(path) == k:\n", - " if path[0] in adjacency_list[path[-1]]:\n", - " cycle = path + [path[0]]\n", - " cycles.append(cycle)\n", - " continue\n", - " for i in adjacency_list[path[-1]]:\n", - " if i not in path and i > path[0]:\n", - " queue.append(path + [i])\n", - " return cycles" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "assert len(find_cycles(9)) == 0\n", - "assert len(find_cycles(10)) == 528\n", - "assert len(find_cycles(11)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=11) if len(c) == 11 + 1 ])\n", - "assert len(find_cycles(12)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=12) if len(c) == 12 + 1 ])\n", - "assert len(find_cycles(13)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=13) if len(c) == 13 + 1 ])\n", - "assert len(find_cycles(14)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=14) if len(c) == 14 + 1 ])\n", - "assert len(find_cycles(15)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=15) if len(c) == 15 + 1 ])\n", - "assert len(find_cycles(16)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=16) if len(c) == 16 + 1 ])\n", - "assert len(find_cycles(17)) == len([ c for c in g.to_directed().all_simple_cycles(max_length=17) if len(c) == 17 + 1 ])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "len(find_cycles(14))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "len([ c for c in g.to_directed().all_simple_cycles(max_length=14) if len(c) == 14 + 1 ])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "(14 + 13 + 12 + 11 + 10) * 70" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "len([ c for c in g.to_directed().all_simple_cycles(max_length=12) if len(c) == 12 + 1 ])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "len([ c for c in g.to_directed().all_simple_cycles(max_length=13) if len(c) == 13 + 1 ])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "len([ c for c in g.to_directed().all_simple_cycles(max_length=16) if len(c) == 16 + 1 ])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "len([ c for c in g.to_directed().all_simple_cycles(max_length=17) if len(c) == 17 + 1 ])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Generate Adjacency Lists" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "g = graphs.TutteCoxeterGraph()\n", - "adjacency_list = [ [] for j in range(len(g.vertices()))]\n", - "for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - "\n", - "with open('adjacency_lists/tutte_coxeter_graph.txt', 'w') as f:\n", - " f.write(f'{len(g.vertices())} {len(g.edges())}\\n')\n", - " for i in range(len(g.vertices())):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "g = graphs.HarriesGraph()\n", - "adjacency_list = [ [] for j in range(len(g.vertices()))]\n", - "for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - "\n", - "with open('adjacency_lists/harries_10_cage.txt', 'w') as f:\n", - " f.write(f'{len(g.vertices())} {len(g.edges())}\\n')\n", - " for i in range(len(g.vertices())):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "g = graphs.HarriesWongGraph()\n", - "adjacency_list = [ [] for j in range(len(g.vertices()))]\n", - "for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - "\n", - "with open('adjacency_lists/harries_wong_10_cage.txt', 'w') as f:\n", - " f.write(f'{len(g.vertices())} {len(g.edges())}\\n')\n", - " for i in range(len(g.vertices())):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "for k in range(3, 10):\n", - " g = graphs.CompleteGraph(k)\n", - " adjacency_list = [ [] for j in range(len(g.vertices()))]\n", - " for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - "\n", - " with open(f'adjacency_lists/k{k}.txt', 'w') as f:\n", - " f.write(f'{len(g.vertices())} {len(g.edges())}\\n')\n", - " for i in range(len(g.vertices())):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "# formula (Ringel and Youngs 1968; Harary 1994, p. 118)\n", - "for k in range(3, 10):\n", - " print(f\"Complete graph k_{k} has genus {ceil((k-3)*(k-4)/12)}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "for k in range(3, 10):\n", - " g = graphs.CompleteBipartiteGraph(k, k)\n", - " adjacency_list = [ [] for j in range(len(g.vertices()))]\n", - " for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - "\n", - " with open(f'adjacency_lists/k{k}-{k}.txt', 'w') as f:\n", - " f.write(f'{len(g.vertices())} {len(g.edges())}\\n')\n", - " for i in range(len(g.vertices())):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "# formula (Ringel 1965; Beineke and Harary 1965; Harary 1994, p. 119).\n", - "for n in range(3, 10):\n", - " m = n\n", - " print(f\"Complete bipartite graph k_{m},{n} has genus {ceil((m-2)*(n-2)/4)}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "g = graphs.Tutte12Cage()\n", - "adjacency_list = [ [] for j in range(len(g.vertices()))]\n", - "for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - "\n", - "with open('adjacency_lists/tutte12.txt', 'w') as f:\n", - " f.write(f'{len(g.vertices())} {len(g.edges())}\\n')\n", - " for i in range(len(g.vertices())):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "g = graphs.Balaban11Cage()\n", - "# relabel vertices from 0 to num verts\n", - "g.relabel()\n", - "adjacency_list = [ [] for j in range(len(g.vertices()))]\n", - "for e in g.edges():\n", - " u, v = int(e[0]), int(e[1])\n", - " adjacency_list[u].append(v)\n", - " adjacency_list[v].append(u)\n", - "\n", - "with open('adjacency_lists/balaban11.txt', 'w') as f:\n", - " f.write(f'{len(g.vertices())} {len(g.edges())}\\n')\n", - " for i in range(len(g.vertices())):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')" - ] - }, - { - "cell_type": "code", - "execution_count": 184, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "g = graphs.GrayGraph()\n", - "adjacency_list = [ [] for j in range(len(g.vertices()))]\n", - "for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - "\n", - "with open('adjacency_lists/gray.txt', 'w') as f:\n", - " f.write(f'{len(g.vertices())} {len(g.edges())}\\n')\n", - " for i in range(len(g.vertices())):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')" - ] - }, - { - "cell_type": "code", - "execution_count": 91, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "# convert from https://www.win.tue.nl/~aeb/graphs/cages/cages.html format to own format\n", - "new_content = ''\n", - "file = 'adjacency_lists/7-6-cage.txt'\n", - "with open(file, 'r') as f:\n", - " lines = f.readlines()\n", - " num_vertices = int(lines[0].strip()[1:])\n", - " adjacency_matrix = [ [0 for i in range(num_vertices)] for j in range(num_vertices)]\n", - " for i in range(1, len(lines)):\n", - " line = lines[i].strip()[:-1]\n", - " for j in line.split(','):\n", - " adjacency_matrix[i - 1][int(j)] = 1\n", - " num_edges = sum([ sum(row) for row in adjacency_matrix ]) // 2\n", - "\n", - " new_content = f'{num_vertices} {num_edges}\\n'\n", - " for i in range(1, len(lines)):\n", - " line = lines[i].strip()[:-1].replace(',', ' ')\n", - " new_content += f'{line}\\n'\n", - "\n", - "with open(file, 'w') as f:\n", - " f.write(new_content)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "# K_2,...,2 graphs\n", - "for k in range(2, 6):\n", - " g = graphs.CompleteMultipartiteGraph([2] * k)\n", - " adjacency_list = [ [] for j in range(len(g.vertices()))]\n", - " for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - " with open('adjacency_lists/k' + \"-\".join(['2'] * k) + '.txt', 'w') as f:\n", - " f.write(f'{len(g.vertices())} {len(g.edges())}\\n')\n", - " for i in range(len(g.vertices())):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Test Algo on Rome dataset\n", - "https://visdunneright.github.io/gd_benchmark_sets/#moveToRome-Lib" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "import subprocess, threading\n", - "import os,signal\n", - "class Command(object):\n", - " def __init__(self, cmd):\n", - " self.cmd = cmd\n", - " self.process = None\n", - "\n", - " self.stdout = None\n", - " self.stderr = None\n", - "\n", - " def run(self, timeout, hide_output=True):\n", - " def target():\n", - " if hide_output:\n", - " self.process = subprocess.Popen(self.cmd, shell=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, preexec_fn=os.setsid)\n", - " else:\n", - " self.process = subprocess.Popen(self.cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, preexec_fn=os.setsid)\n", - " self.stdout, self.stderr = self.process.communicate()\n", - "\n", - " thread = threading.Thread(target=target)\n", - " thread.start()\n", - "\n", - " thread.join(timeout)\n", - " if thread.is_alive():\n", - " os.killpg(self.process.pid, signal.SIGTERM)\n", - " thread.join()\n", - " \n", - " return self.process.returncode\n", - "\n", - "# command = Command(\"echo 'Process started'; sleep 2; echo 'Process finished'\")\n", - "# print(command.run(timeout=3))\n", - "# print(command.run(timeout=1))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "import tarfile\n", - "import networkx as nx\n", - "from time import sleep\n", - "\n", - "valid = 0\n", - "successfull = 0\n", - "with tarfile.open('adjacency_lists/rome-graphml.tgz', 'r:gz') as tar:\n", - " for name in tar.getnames():\n", - " if not name.endswith('.graphml'):\n", - " continue\n", - "\n", - " f = tar.extractfile(name)\n", - "\n", - " # load as sage graph\n", - " g = Graph(nx.read_graphml(f))\n", - " obscure = int(name.split('.')[1]) != g.num_verts()\n", - " \n", - " # print(\"Obscure:\", obscure)\n", - " # print(\"Connected:\", g.is_connected())\n", - " # print(\"Planar:\", g.is_planar())\n", - " # print(\"Regular:\", g.is_regular())\n", - " # print(\"Max Degree:\", max(g.degree()))\n", - " if max(g.degree()) > 4:\n", - " continue\n", - "\n", - " if not obscure and g.is_connected() and not g.is_planar():\n", - " valid += 1\n", - "\n", - " while min(g.degree()) <= 1:\n", - " g.delete_vertices([ v for v in g.vertices() if g.degree(v) <= 1 ]) # remove nodes with only one edge \n", - " for v in g.vertices():\n", - " if g.degree(v) == 2:\n", - " # replace with a single edge\n", - " g.add_edge(g.neighbors(v))\n", - " g.delete_vertex(v)\n", - " g.relabel() # relabel edges to numbers\n", - " adjacency_list = [ [] for j in range(len(g.vertices()))]\n", - " for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - " max_degree = max(g.degree())\n", - " for i in range(len(g.vertices())): # pad adjacency list\n", - " while len(adjacency_list[i]) < max_degree:\n", - " adjacency_list[i].append(65535)\n", - " with open('adjacency_lists/rome_temp.txt', 'w') as f:\n", - " f.write(f'{len(g.vertices())} {len(g.edges())}\\n')\n", - " for i in range(len(g.vertices())):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')\n", - "\n", - " command = Command(f'S=\"0\" DEG=\"{max_degree}\" ADJ=\"adjacency_lists/rome_temp.txt\" make run')\n", - " terminated = command.run(timeout=10) == -15\n", - " if not terminated:\n", - " successfull += 1\n", - " break\n", - "\n", - "sleep(2)\n", - "print(valid, successfull)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Test on graphs generated with Nauty" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "def to_adj_list(g, filename):\n", - " adjacency_list = [ [] for _ in range(len(g.vertices()))]\n", - " for e in g.edges():\n", - " adjacency_list[e[0]].append(e[1])\n", - " adjacency_list[e[1]].append(e[0])\n", - " max_degree = max(g.degree())\n", - " for i in range(len(g.vertices())): # pad adjacency list\n", - " while len(adjacency_list[i]) < max_degree:\n", - " adjacency_list[i].append(65535)\n", - " with open(filename, 'w') as f:\n", - " f.write(f'{len(g.vertices())} {len(g.edges())}\\n')\n", - " for i in range(len(g.vertices())):\n", - " f.write(f'{\" \".join(map(str, adjacency_list[i]))}\\n')\n", - "\n", - " return adjacency_list, max_degree" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "def to_multi_code(adj_list, filename):\n", - " with open(filename, \"wb\") as file:\n", - " num_vertices = len(adj_list)\n", - " min_vertex_id = min(min(neighbors) for neighbors in adj_list)\n", - " num_bytes = 1 if num_vertices < 256 else 2\n", - " file.write(num_vertices.to_bytes(num_bytes, byteorder=\"little\"))\n", - " for v in range(num_vertices):\n", - " for u in adj_list[v]:\n", - " if u == 65535:\n", - " continue\n", - " u = u - min_vertex_id\n", - " if u > v:\n", - " file.write((u + 1).to_bytes(num_bytes, byteorder=\"little\"))\n", - " if v < num_vertices - 1:\n", - " file.write((0).to_bytes(num_bytes, byteorder=\"little\"))\n", - " file.flush()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "import re\n", - "def run_page(max_degree, filename, timeout=100):\n", - " command = Command(f'S=\"0\" DEG=\"{max_degree}\" ADJ=\"{filename}\" make run')\n", - " returncode = command.run(timeout=timeout, hide_output=False)\n", - " if returncode != 0:\n", - " raise Exception(f\"Error with {g}: \" + '\\n'.join(command.stderr.decode().split('\\n')[-3:]))\n", - " else:\n", - " reg = re.search(r'The genus is (\\d+)', command.stderr.decode())\n", - " genus = None\n", - " if reg:\n", - " genus = int(reg.group(1))\n", - " return genus" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "def run_multi_genus(filename, timeout=100):\n", - " command = Command(f'cat {filename} | ../MultiGenus/multi_genus_longtype_128 w')\n", - " returncode = command.run(timeout=timeout, hide_output=False)\n", - " if returncode != 0:\n", - " raise Exception(f\"Error with {g}: \" + command.stderr.decode())\n", - " else:\n", - " reg = re.search(r'with genus (\\d+)', command.stderr.decode())\n", - " genus = None\n", - " if reg:\n", - " genus = int(reg.group(1))\n", - " return genus" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "USE_PLANARITY_CHECK = False\n", - "ONLY_CONNECTED = True\n", - "# ALGORITHM = \"PAGE\"\n", - "ALGORITHM = \"MULTI\"\n", - "\n", - "# K_REGULAR = 3\n", - "# IS_REGULAR = True\n", - "K_REGULAR = \"possibly\"\n", - "IS_REGULAR = False\n", - "\n", - "assert K_REGULAR == \"possibly\" or K_REGULAR >= 3\n", - "for num_vertices in range(3, 13):\n", - " min_edges = (3 * num_vertices + 1) // 2\n", - " max_edges = 6 + 3 * num_vertices\n", - " max_possible_edges = (num_vertices * K_REGULAR // 2) if IS_REGULAR else (num_vertices * (num_vertices - 1) // 2)\n", - " if min_edges > max_possible_edges:\n", - " print(f\"No {K_REGULAR}-regular graphs with {num_vertices} vertices satisfy the constraint of at least {min_edges} edges\") \n", - " continue\n", - " non_isomorphic_graphs = list(graphs.nauty_geng(f\"{num_vertices} {min_edges}:{max_edges} {'-c' if ONLY_CONNECTED else ''} -d{K_REGULAR if IS_REGULAR else 3} -D{K_REGULAR if IS_REGULAR else num_vertices}\"))\n", - " print(f\"Found {len(non_isomorphic_graphs)} non-isomorphic connected {K_REGULAR}-regular graphs with {num_vertices} vertices and {min_edges} to {max_edges} edges\")\n", - " for g in non_isomorphic_graphs:\n", - " if USE_PLANARITY_CHECK and g.is_planar():\n", - " print(\"Skipping planar graph\")\n", - " continue\n", - "\n", - " def run_algorithm(graph):\n", - " filename = 'adjacency_lists/nauty_temp.txt'\n", - " adjacency_list, max_degree = to_adj_list(graph, filename)\n", - "\n", - " if ALGORITHM == \"PAGE\":\n", - " genus = run_page(max_degree, filename)\n", - " elif ALGORITHM == \"MULTI\":\n", - " multi_filename = '../MultiGenus/graphs/nauty_temp.mc'\n", - " to_multi_code(adjacency_list, multi_filename)\n", - " genus = run_multi_genus(multi_filename)\n", - " else:\n", - " raise Exception(\"Invalid algorithm\")\n", - " \n", - " return genus\n", - " \n", - " try:\n", - " if run_algorithm(g) == 2:\n", - " # G - e must embed on the torus\n", - " is_torus_obstruction = True\n", - " for e in g.edges():\n", - " g.delete_edge(e)\n", - " if run_algorithm(g) == 2:\n", - " is_torus_obstruction = False\n", - " break\n", - " g.add_edge(e)\n", - " if not is_torus_obstruction:\n", - " continue\n", - " # to be a a minor order obstruction, G contract e must embed on the torus\n", - " is_minor_obstruction = True\n", - " for e in g.edges():\n", - " g_contracted = g.copy()\n", - " g_contracted.contract_edge(e)\n", - " g_contracted.relabel()\n", - " if run_algorithm(g_contracted) == 2:\n", - " is_minor_obstruction = False\n", - " break\n", - " if not is_minor_obstruction:\n", - " continue\n", - "\n", - " # print in upper triangular form\n", - " adjacency_matrix = g.adjacency_matrix()\n", - " print(g.num_verts(), end=' ')\n", - " for i in range(g.num_verts()):\n", - " for j in range(i + 1, g.num_verts()):\n", - " print(adjacency_matrix[i][j], end='')\n", - " print()\n", - " except Exception as e:\n", - " g.show()\n", - " raise e\n", - "\n", - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Performance of builtin SageMath Genus Calculation" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "START_INDEX = 1\n", - "starttime = perf_counter()\n", - "\n", - "# load adjacency list from file\n", - "adjacency_list = []\n", - "with open('adjacency_lists/Johnson5-2.txt', 'r') as f:\n", - " lines = f.readlines()\n", - " num_vertices, num_edges = map(int, lines[0].strip().split())\n", - " for i in range(1, len(lines)):\n", - " neighbors = list(map(lambda x: int(x) - START_INDEX, lines[i].strip().split()))\n", - " adjacency_list.append(list(filter(lambda x: x != 65535, neighbors)))\n", - " assert len(adjacency_list) == num_vertices\n", - "print(num_vertices, num_edges, adjacency_list)\n", - "\n", - "# convert from adjacency list to adjacency matrix\n", - "adjacency_matrix = [ [0 for i in range(num_vertices)] for j in range(num_vertices)]\n", - "for i in range(num_vertices):\n", - " for j in adjacency_list[i]:\n", - " adjacency_matrix[i][j] = 1\n", - " adjacency_matrix[j][i] = 1\n", - "print(adjacency_matrix)\n", - "\n", - "# load into sagemath and calculate the genus\n", - "g = Graph(matrix(adjacency_matrix), format='adjacency_matrix')\n", - "print(f\"genus = {g.genus()}\")\n", - "\n", - "print(f'genus calculation took {perf_counter() - starttime} seconds')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Vizualize Cell Embedding" - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "# fitting = [\n", - "# [0, 63, 15, 73, 3, 72, 7, 66, 1, 67, 31, 64, 0],\n", - "# [0, 64, 32, 106, 19, 86, 9, 87, 21, 110, 48, 65, 0],\n", - "# [1, 66, 8, 85, 37, 112, 48, 110, 38, 97, 40, 68, 1],\n", - "# [1, 68, 39, 76, 41, 107, 62, 92, 11, 91, 33, 67, 1],\n", - "# [2, 70, 34, 120, 28, 121, 42, 82, 6, 81, 23, 69, 2],\n", - "# [2, 71, 56, 122, 29, 123, 51, 108, 32, 64, 31, 70, 2],\n", - "# [3, 73, 17, 96, 13, 97, 38, 115, 24, 69, 23, 74, 3],\n", - "# [3, 74, 25, 93, 12, 95, 54, 121, 28, 87, 9, 72, 3],\n", - "# [4, 75, 18, 105, 45, 85, 8, 84, 46, 109, 57, 77, 4],\n", - "# [4, 76, 39, 82, 42, 123, 29, 90, 17, 73, 15, 75, 4],\n", - "# [4, 77, 55, 80, 5, 78, 10, 89, 60, 113, 41, 76, 4],\n", - "# [5, 79, 49, 92, 62, 114, 35, 84, 8, 66, 7, 78, 5],\n", - "# [5, 80, 58, 95, 12, 94, 43, 125, 50, 83, 47, 79, 5],\n", - "# [6, 83, 50, 119, 27, 118, 60, 89, 53, 116, 26, 81, 6],\n", - "# [7, 72, 9, 86, 30, 125, 43, 104, 61, 88, 10, 78, 7],\n", - "# [10, 88, 51, 123, 42, 121, 54, 102, 16, 103, 53, 89, 10],\n", - "# [11, 90, 29, 122, 37, 85, 45, 117, 26, 116, 44, 91, 11],\n", - "# [11, 92, 49, 101, 59, 120, 34, 118, 27, 96, 17, 90, 11],\n", - "# [12, 93, 22, 113, 60, 118, 34, 70, 31, 67, 33, 94, 12],\n", - "# [13, 96, 27, 119, 46, 84, 35, 102, 54, 95, 58, 98, 13],\n", - "# [13, 98, 52, 117, 45, 105, 59, 101, 14, 100, 40, 97, 13],\n", - "# [14, 99, 20, 109, 46, 119, 50, 125, 30, 124, 36, 100, 14],\n", - "# [14, 101, 49, 79, 47, 65, 48, 112, 22, 93, 25, 99, 14],\n", - "# [15, 63, 16, 102, 35, 114, 24, 115, 61, 104, 18, 75, 15],\n", - "# [19, 107, 41, 113, 22, 112, 37, 122, 56, 124, 30, 86, 19],\n", - "# [20, 99, 25, 74, 23, 81, 26, 117, 52, 106, 32, 108, 20],\n", - "# [20, 108, 51, 88, 61, 115, 38, 110, 21, 111, 57, 109, 20],\n", - "# [36, 124, 56, 71, 55, 77, 57, 111, 44, 116, 53, 103, 36],\n", - "# [0, 65, 47, 83, 6, 82, 39, 68, 40, 100, 36, 103, 16, 63, 0],\n", - "# [2, 69, 24, 114, 62, 107, 19, 106, 52, 98, 58, 80, 55, 71, 2],\n", - "# [18, 104, 43, 94, 33, 91, 44, 111, 21, 87, 28, 120, 59, 105, 18],\n", - "# ]\n", - "# fitting = [\n", - "# [0, 15, 3, 18, 1, 19, 7, 16, 0], \n", - "# [0, 16, 8, 26, 5, 27, 12, 17, 0], \n", - "# [1, 18, 5, 26, 14, 23, 11, 20, 1], \n", - "# [2, 21, 3, 15, 4, 25, 10, 22, 2], \n", - "# [2, 23, 14, 24, 9, 29, 6, 21, 2], \n", - "# [4, 24, 14, 26, 8, 28, 13, 25, 4], \n", - "# [0, 17, 11, 23, 2, 22, 7, 19, 9, 24, 4, 15, 0], \n", - "# [3, 21, 6, 28, 8, 16, 7, 22, 10, 27, 5, 18, 3], \n", - "# ]\n", - "fitting = [\n", - " [0, 1, 4, 6, 2, 0], \n", - " [0, 2, 7, 8, 3, 0], \n", - " [0, 3, 9, 5, 1, 0], \n", - " [1, 5, 7, 2, 6, 9, 3, 8, 4, 1]\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": 100, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "flat = [item for sublist in fitting for item in sublist]\n", - "vertices = list(set(flat))" - ] - }, - { - "cell_type": "code", - "execution_count": 101, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "m = [ [0 for i in range(len(vertices))] for j in range(len(vertices))]\n", - "for cycle in fitting:\n", - " for i in range(len(cycle) - 2):\n", - " u, v = cycle[i], cycle[i + 1]\n", - " m[u][v] = 1\n", - " m[v][u] = 1" - ] - }, - { - "cell_type": "code", - "execution_count": 103, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "g = Graph(matrix(m), format='adjacency_matrix')" - ] - }, - { - "cell_type": "code", - "execution_count": 105, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "ng = g.networkx_graph() " - ] - }, - { - "cell_type": "code", - "execution_count": 120, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "def plot(pos, labels, adjacency_matrix, fitting):\n", - " Xn=[pos[k][0] for k in range(len(pos))] # x-coordinates of nodes\n", - " Yn=[pos[k][1] for k in range(len(pos))] # y-coordinates\n", - " Zn=[pos[k][2] for k in range(len(pos))] # z-coordinates\n", - " Xe=[]\n", - " Ye=[]\n", - " Ze=[]\n", - " for i in range(len(pos)):\n", - " for j in range(len(pos)):\n", - " if adjacency_matrix[i][j] == 1:\n", - " Xe+=[pos[i][0],pos[j][0], None] # x-coordinates of edge ends\n", - " Ye+=[pos[i][1],pos[j][1], None] # y-coordinates of edge ends\n", - " Ze+=[pos[i][2],pos[j][2], None] # z-coordinates of edge ends\n", - "\n", - " fig = go.Figure()\n", - " fig.add_trace(go.Scatter3d(\n", - " x=Xe,\n", - " y=Ye,\n", - " z=Ze,\n", - " mode='lines',\n", - " name='edges',\n", - " line=dict(color='rgb(125,125,125)', width=1),\n", - " hoverinfo='none'\n", - " ))\n", - " fig.add_trace(go.Scatter3d(\n", - " x=Xn,\n", - " y=Yn,\n", - " z=Zn,\n", - " mode='markers',\n", - " name='vertices',\n", - " marker=dict(\n", - " symbol='circle',\n", - " size=6,\n", - " color='blue',\n", - " line=dict(color='rgb(50,50,50)', width=0.5)\n", - " ),\n", - " text=labels,\n", - " hoverinfo='text'\n", - " ))\n", - "\n", - " for c, cycle in enumerate(fitting):\n", - " fig.add_trace(go.Mesh3d(\n", - " x=[pos[v][0] for v in cycle],\n", - " y=[pos[v][1] for v in cycle],\n", - " z=[pos[v][2] for v in cycle],\n", - " opacity=1,\n", - " color=f'rgb({c*50 % 255}, {c*100 % 255}, {c*150 % 255})',\n", - " name=f'cycle {c}',\n", - " hoverinfo='name'\n", - " ))\n", - "\n", - " fig.update_layout(\n", - " showlegend=False,\n", - " scene=dict(\n", - " xaxis=dict(visible=False),\n", - " yaxis=dict(visible=False),\n", - " zaxis=dict(visible=False)\n", - " )\n", - " )\n", - " fig.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "pos = nx.random_layout(ng, dim=3)\n", - "# nx.draw(ng, pos, with_labels=True, font_weight='bold')\n", - "plot(pos, vertices, m, fitting)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "# position based on the fitting\n", - "pos = {}\n", - "\n", - "# layout the first cycle in a circle\n", - "cycle = fitting[0]\n", - "num_vertices = len(cycle)\n", - "for i, v in enumerate(cycle):\n", - " if v not in pos:\n", - " pos[v] = [np.cos(2 * np.pi * i / num_vertices), np.sin(2 * np.pi * i / num_vertices), 0]\n", - "\n", - "for i, cycle in enumerate(fitting):\n", - " for j, v in enumerate(cycle[:-1]):\n", - " if v not in pos:\n", - " pos[v] = [i, j, i * j]\n", - "plot(pos, vertices, m, fitting)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "pos = nx.spring_layout(ng, dim=3, pos=pos)\n", - "# nx.draw(ng, pos, with_labels=True, font_weight='bold')\n", - "plot(pos, vertices, m, fitting)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Experiment with Graph Generation" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "for n in range(3, 26):\n", - " num_graphs = sum([1 for _ in graphs.nauty_geng(f\"{n} {n}:{3 * n}\")])\n", - " print(f\"number of possibly toroidal graphs with {n} vertices = {num_graphs}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Experiment with Cycle Distribution Traversal" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "# https://stackoverflow.com/questions/11916974/efficient-iteration-over-sorted-partial-sums\n", - "import heapq\n", - "\n", - "def sorted_subsets(L):\n", - " candidates = [(L[0], (0,))]\n", - "\n", - " while True:\n", - " try:\n", - " top = heapq.heappop(candidates)\n", - " except IndexError:\n", - " return\n", - " yield tuple(L[i] for i in top[1])\n", - " i = top[1][-1]\n", - " if i+1 < len(L):\n", - " heapq.heappush(candidates, (top[0] + L[i+1], top[1] + (i+1,)))\n", - " heapq.heappush(candidates, (top[0] - L[i] + L[i+1], top[1][:-1] + (i+1,)))\n", - " \n", - "# time complexity: O(k\\log k) where k is the number of subsets requested from the iterator\n", - "\n", - "it = sorted_subsets([1, 2, 5, 10, 11])\n", - "for j in range(8):\n", - " print(next(it))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "def recursive_sorted_subsets(L, i):\n", - " if i == 1:\n", - " yield (L[0], (L[0],))\n", - " yield (L[1], (L[1],))\n", - " yield (L[0] + L[1], (L[0], L[1]))\n", - " return\n", - "\n", - " iter1 = recursive_sorted_subsets(L, i - 1)\n", - " iter2 = recursive_sorted_subsets(L, i - 1)\n", - " sb, lb = L[i], (L[i],)\n", - " for sa, la in iter1:\n", - " while sb < sa:\n", - " yield (sb, lb)\n", - " _sb, _lb = next(iter2)\n", - " sb, lb = _sb + L[i], _lb + (L[i],)\n", - " yield (sa, la)\n", - " yield (sb, lb)\n", - " for _sb, _lb in iter2:\n", - " sb, lb = _sb + L[i], _lb + (L[i],)\n", - " yield (sb, lb)\n", - "\n", - "# time complexity: O(inefficient)\n", - "\n", - "it = recursive_sorted_subsets([1, 2, 5, 10, 11], 4)\n", - "for j in range(8):\n", - " print(next(it))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "random_list = sorted(list(np.random.randint(1, 100, 10)))\n", - "for a, b in zip(sorted_subsets(random_list), recursive_sorted_subsets(random_list, len(random_list) - 1)):\n", - " b = b[1]\n", - " print(a, b)\n", - " assert sum(a) == sum(b), f'{a} != {b}'" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "from heapq import merge\n", - "\n", - "def merge_sorted_subsets(L):\n", - " subsets = [()]\n", - " def add(number):\n", - " for subset in subsets:\n", - " if not subset or number > subset[-1]:\n", - " yield subset + (number,)\n", - " for subset in merge(*map(add, L), key=sum):\n", - " yield subset\n", - " subsets.append(subset)\n", - " \n", - "it = merge_sorted_subsets([1, 2, 5, 10, 11])\n", - "for j in range(8):\n", - " print(next(it))" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "TRIALS = 1000\n", - "SIZE = 1000\n", - "DEPTH = 500 # 2 ** SIZE - 1\n", - "RANGE = (1, 100)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "total_time = 0\n", - "for _ in range(TRIALS):\n", - " random_list = sorted(list(np.random.randint(RANGE[0], RANGE[1], SIZE)))\n", - " start = perf_counter()\n", - " it = recursive_sorted_subsets(random_list, len(random_list) - 1)\n", - " for _ in range(DEPTH):\n", - " next(it)\n", - " total_time += perf_counter() - start\n", - "print(f\"recursive_sorted_subsets took {total_time / TRIALS} seconds\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "total_time = 0\n", - "for _ in range(TRIALS):\n", - " random_list = sorted(list(np.random.randint(RANGE[0], RANGE[1], SIZE)))\n", - " start = perf_counter()\n", - " it = sorted_subsets(random_list)\n", - " for _ in range(DEPTH):\n", - " next(it)\n", - " total_time += perf_counter() - start\n", - "print(f'sorted_subsets took {total_time / TRIALS} seconds')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "total_time = 0\n", - "for _ in range(TRIALS):\n", - " random_list = sorted(list(np.random.randint(RANGE[0], RANGE[1], SIZE)))\n", - " start = perf_counter()\n", - " it = merge_sorted_subsets(random_list)\n", - " for _ in range(DEPTH):\n", - " next(it)\n", - " total_time += perf_counter() - start\n", - "print(f'merge_sorted_subsets took {total_time / TRIALS} seconds')" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "def enum_dist_recursive(counts, num):\n", - " if len(counts) == 1:\n", - " for i in range(1, num + 1):\n", - " yield counts[0][0] * i, tuple([counts[0][0]] * i)\n", - " return\n", - "\n", - " iter1 = enum_dist_recursive(counts[:-1], counts[-2][1]) if num == 1 else enum_dist_recursive(counts, num - 1)\n", - " iter2 = enum_dist_recursive(counts[:-1], counts[-2][1]) if num == 1 else enum_dist_recursive(counts, num - 1)\n", - " sb, lb = counts[-1][0] * num, tuple([counts[-1][0]] * num)\n", - " for sa, la in iter1:\n", - " while sb < sa:\n", - " yield sb, lb\n", - " _sb, _lb = next(iter2)\n", - " while counts[-1][0] in _lb:\n", - " _sb, _lb = next(iter2)\n", - " sb, lb = _sb + num * counts[-1][0], _lb + tuple([counts[-1][0]] * num)\n", - " yield sa, la\n", - " yield sb, lb\n", - " for _sb, _lb in iter2:\n", - " if counts[-1][0] in _lb:\n", - " continue\n", - " sb, lb = _sb + num * counts[-1][0], _lb + tuple([counts[-1][0]] * num)\n", - " yield sb, lb" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "population = [(1, 2), (2, 2), (5, 1), (10, 1), (11, 1)]\n", - "it = enum_dist_recursive(population, population[-1][1])\n", - "for j in range(28):\n", - " print(next(it))" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "def enum_dist_iterative(counts):\n", - " k = 0\n", - "\n", - " arr = [[]] # arr[i][j-1] = sorted subsets of counts[:i+1] with up to j elements of counts[i]\n", - " for j in range(1, counts[0][1] + 1):\n", - " arr[0].append([(counts[0][0] * n, tuple([counts[0][0]] * n)) for n in range(1, j + 1)])\n", - "\n", - " for i in range(1, len(counts)):\n", - " arr.append([])\n", - " for j in range(1, counts[i][1] + 1):\n", - " row = []\n", - "\n", - " lookback = arr[i - 1][-1] if j == 1 else arr[i][j - 2]\n", - " sb, lb = counts[i][0] * j, tuple([counts[i][0]] * j)\n", - " b = iter(lookback)\n", - " for sa, la in lookback:\n", - " while sb < sa:\n", - " row.append((sb, lb))\n", - " _sb, _lb = next(b)\n", - " while counts[i][0] in _lb:\n", - " _sb, _lb = next(b)\n", - " sb, lb = _sb + j * counts[i][0], _lb + tuple([counts[i][0]] * j)\n", - " row.append((sa, la))\n", - " row.append((sb, lb))\n", - " for _sb, _lb in b:\n", - " if counts[i][0] in _lb:\n", - " continue\n", - " sb, lb = _sb + j * counts[i][0], _lb + tuple([counts[i][0]] * j)\n", - " row.append((sb, lb))\n", - "\n", - " arr[i].append(row)\n", - " \n", - " while k < len(arr[i][-1]) and (i == len(counts) - 1 or arr[i][-1][k][0] < counts[i + 1][0]):\n", - " yield arr[i][-1][k]\n", - " k += 1" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "population = [(1, 2), (2, 2), (5, 1), (10, 1), (11, 1)]\n", - "it = enum_dist_iterative(population)\n", - "for j in range(28):\n", - " print(next(it))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "for k in range(10, 200, 10):\n", - " total_time = 0\n", - " for _ in range(TRIALS):\n", - " random_list = sorted(list(np.random.randint(RANGE[0], RANGE[1], SIZE)))\n", - " population = list(map(lambda x: (x, 1), random_list))\n", - " # unique, counts = np.unique(random_list, return_counts=True)\n", - " # population = list(zip(unique, counts))\n", - " start = perf_counter()\n", - " it = enum_dist_iterative(population)\n", - " for _ in range(k):\n", - " next(it)\n", - " total_time += perf_counter() - start\n", - " print(f'enum_dist_iterative took {total_time / TRIALS} seconds with k = {k}')" - ] - }, - { - "cell_type": "code", - "execution_count": 207, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "def enum_dist_iterative_as_counts(counts, target_sum=None):\n", - " k = 0\n", - "\n", - " arr = [[]] # arr[i][j-1] = sorted subsets of counts[:i+1] with up to j elements of counts[i]\n", - " for j in range(1, counts[0][1] + 1):\n", - " if target_sum and counts[0][0] * j > target_sum:\n", - " break\n", - " arr[0].append([(counts[0][0] * n, [(counts[0][0], n)]) for n in range(1, j + 1)])\n", - "\n", - " for i in range(1, len(counts)):\n", - " arr.append([])\n", - " for j in range(1, counts[i][1] + 1):\n", - " row = []\n", - "\n", - " lookback = arr[i - 1][-1] if j == 1 else arr[i][j - 2]\n", - " sb, lb = counts[i][0] * j, [(counts[i][0], j)]\n", - " b = iter(lookback)\n", - " for sa, la in lookback:\n", - " while sb < sa:\n", - " row.append((sb, lb))\n", - " _sb, _lb = next(b)\n", - " while counts[i][0] == _lb[-1][0]:\n", - " _sb, _lb = next(b)\n", - " sb, lb = _sb + j * counts[i][0], _lb + [(counts[i][0], j)]\n", - " if target_sum and sa > target_sum:\n", - " break\n", - " row.append((sa, la))\n", - " row.append((sb, lb))\n", - " for _sb, _lb in b:\n", - " if target_sum and _sb > target_sum:\n", - " break\n", - " if counts[i][0] == _lb[-1][0]:\n", - " continue\n", - " sb, lb = _sb + j * counts[i][0], _lb + [(counts[i][0], j)]\n", - " row.append((sb, lb))\n", - "\n", - " arr[i].append(row)\n", - " \n", - " while k < len(arr[i][-1]) and (i == len(counts) - 1 or arr[i][-1][k][0] < counts[i + 1][0]):\n", - " yield arr[i][-1][k]\n", - " k += 1" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "population = [(1, 2), (2, 2), (5, 1), (10, 1), (11, 1)]\n", - "it = enum_dist_iterative_as_counts(population)\n", - "for j in range(28):\n", - " s, l = next(it)\n", - " print((s, tuple(item for row in [[x] * n for x, n in l] for item in row), l))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "population = [[11, 512], [12, 1056], [13, 384], [14, 1024], [15, 1792], [16, 3912], [17, 7296]]\n", - "directed_edges = 168 * 2\n", - "for i, (v, c) in enumerate(population):\n", - " population[i][1] = min(directed_edges // v, c)\n", - "\n", - "# first = population.pop(0)\n", - "# it = enum_dist_iterative_as_counts(population, directed_edges)\n", - "# for j in range(50000):\n", - "# s, l = next(it)\n", - "# subset = tuple(item for row in [[x] * n for x, n in l] for item in row)\n", - "# num_needed, fits = divmod(directed_edges - s, first[0])\n", - "# if fits == 0 and num_needed <= first[1]:\n", - "# print([(first[0], num_needed)] + l, first[0] * num_needed + s, len(subset) + num_needed)\n", - "\n", - "# it = enum_dist_iterative_as_counts(population, directed_edges)\n", - "# for j in range(50000):\n", - "# s, l = next(it)\n", - "# subset = tuple(item for row in [[x] * n for x, n in l] for item in row)\n", - "# if s == directed_edges:\n", - "# print(l, s, len(subset))\n", - "\n", - "first = population.pop(0)\n", - "for f in range(first[1], -1, -1):\n", - " target = directed_edges - f * first[0]\n", - " it = enum_dist_iterative_as_counts(population, target)\n", - " s = population[0][0]\n", - " while s <= target:\n", - " try:\n", - " s, l = next(it)\n", - " subset = tuple(item for row in [[x] * n for x, n in l] for item in row)\n", - " if s == target:\n", - " print([(first[0], f)] + l, first[0] * f + s, len(subset) + f)\n", - " except StopIteration:\n", - " break" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "def dist_matching_sum(population, s):\n", - " array = [[()]] + [[] for _ in range(s)]\n", - " for v, c in population:\n", - " for j in range(1, c + 1):\n", - " for num in range(s - j * v, -1, -1):\n", - " if array[num]:\n", - " for subset in array[num]:\n", - " if v in subset:\n", - " continue\n", - " array[num + j * v] += [subset + tuple([v] * j)]\n", - " if num + j * v == s:\n", - " yield array[num + j * v][-1], sum(array[num + j * v][-1]), len(array[num + j * v][-1])\n", - "\n", - "it = dist_matching_sum(population, directed_edges)\n", - "# for j in range(500):\n", - "# print(next(it))\n", - "for d in it:\n", - " print(d)" - ] - }, - { - "cell_type": "code", - "execution_count": 190, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "def knapsack(items, quantities, size):\n", - " # Initialize the DP array\n", - " f = [0] * (size + 1)\n", - " \n", - " cnt = 0 # Number after packaging into a large item\n", - " w = []\n", - " v = []\n", - " \n", - " for length, quantity in zip(items, quantities):\n", - " k = 1 # Pack k small items into one large item\n", - " while k <= quantity:\n", - " cnt += 1 # Number of large items\n", - " w.append(length * k) # Weight of large items\n", - " v.append(length * k) # Value of large items\n", - " quantity -= k\n", - " k *= 2\n", - " \n", - " # Pack the remaining items into one large item\n", - " if quantity > 0:\n", - " cnt += 1\n", - " w.append(length * quantity) \n", - " v.append(length * quantity)\n", - " \n", - " # One-dimensional transformation of 0/1 knapsack problem\n", - " for i in range(cnt):\n", - " for j in range(size, w[i] - 1, -1):\n", - " f[j] = max(f[j], f[j - w[i]] + v[i])\n", - " \n", - " print(f)\n", - " return f[size]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "knapsack([1, 2, 5, 10, 11], [1, 1, 1, 1, 1], 4)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "SageMath 10.3", - "language": "sage", - "name": "SageMath-10.3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "sage", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/CalcGenus/makefile b/CalcGenus/makefile deleted file mode 100644 index e708a40..0000000 --- a/CalcGenus/makefile +++ /dev/null @@ -1,16 +0,0 @@ -CC=gcc -CPPC=g++ -BTYPE=Development -BDIR=. - -all: CalcGenus - -run: CalcGenus - $(BDIR)/CalcGenus - -CalcGenus: CalcGenus.c - $(CC) -O3 -ftree-vectorize -funroll-loops -Wall -std=c17 -pedantic -g -o "$(BDIR)/CalcGenus" CalcGenus.c - -clean: - rm -f $(BDIR)/CalcGenus $(BDIR)/*.o - rm -rf $(BDIR)/*.dSYM diff --git a/CalcGenus/verifyEmbedding.ipynb b/CalcGenus/verifyEmbedding.ipynb deleted file mode 100644 index 5e7e637..0000000 --- a/CalcGenus/verifyEmbedding.ipynb +++ /dev/null @@ -1,996 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "import networkx as nx\n", - "import matplotlib.pyplot as plt\n", - "from sage.all import *\n", - "import os" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "IGNORE_VERTEX = 65535" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0\n", - "[{8, 6, 7}, {8, 6, 7}, {8, 11, 6}, {9, 10, 7}, {9, 10, 11}, {9, 10, 11}, {0, 1, 2}, {0, 1, 3}, {0, 1, 2}, {3, 4, 5}, {3, 4, 5}, {2, 4, 5}]\n" - ] - } - ], - "source": [ - "with open(os.path.join('adjacency_lists', 'austin_test.txt'), 'r') as f:\n", - " lines = f.readlines()\n", - " num_vertices, num_edges = map(int, lines.pop(0).strip().split(' '))\n", - " adjacency_list = [set() for _ in range(num_vertices)]\n", - " min_number = min(map(int, \" \".join(lines).split()))\n", - " print(min_number)\n", - " for v, line in enumerate(lines):\n", - " neighbors = map(int, line.strip().split(' '))\n", - " for u in neighbors:\n", - " if u == IGNORE_VERTEX:\n", - " continue\n", - " adjacency_list[v].add(u - min_number)\n", - " adjacency_list[u - min_number].add(v)\n", - " print(adjacency_list)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1], [1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0]]\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 31 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "adjacency_matrix = [ [0 for i in range(num_vertices)] for j in range(num_vertices)]\n", - "for i in range(num_vertices):\n", - " for j in adjacency_list[i]:\n", - " adjacency_matrix[i][j] = 1\n", - " adjacency_matrix[j][i] = 1\n", - "print(adjacency_matrix)\n", - "\n", - "# load into sagemath and calculate the genus\n", - "g = Graph(matrix(adjacency_matrix), format='adjacency_matrix')\n", - "g.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "solution = [\n", - " [0, 6, 2, 8, 1, 7, 0], \n", - " [3, 9, 4, 11, 5, 10, 3], \n", - " [0, 8, 2, 11, 4, 10, 5, 9, 3, 7, 1, 6, 0], \n", - " [0, 7, 3, 10, 4, 9, 5, 11, 2, 6, 1, 8, 0], \n", - "]\n", - "# solution = [[x - 1 for x in y] for y in solution] # convert 1-indexed to 0-indexed" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "4" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(solution)" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "174\n" - ] - } - ], - "source": [ - "cycles = [ c for c in g.to_directed().all_simple_cycles(max_length=max(map(len, solution))) ]\n", - "print(len(cycles))" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "# only valid cycles and no duplicates edges\n", - "edges = set()\n", - "for c in solution:\n", - " for i in range(len(c) - 1):\n", - " assert (c[i], c[i + 1]) not in edges, \"Duplicate edge \" + str(c[i]) + \" \" + str(c[i + 1])\n", - " edges.add((c[i], c[i + 1]))\n", - " assert c in cycles" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "# no duplicate cycles in the solution\n", - "for i, c1 in enumerate(solution):\n", - " for j, c2 in enumerate(solution):\n", - " if i == j:\n", - " continue\n", - " if list(reversed(c1)) == c2:\n", - " continue\n", - " try:\n", - " offset = c2.index(c1[0])\n", - " except ValueError:\n", - " continue\n", - " assert c2[offset:] + c2[:offset] != c1, \"Duplicate cycles \" + str(c1) + \" \" + str(c2)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "def x_in_y(query, base):\n", - " try:\n", - " l = len(query)\n", - " except TypeError:\n", - " l = 1\n", - " query = type(base)((query,))\n", - "\n", - " for i in range(len(base)):\n", - " if base[i:i+l] == query:\n", - " return True\n", - " return False\n", - "\n", - "# test cases \n", - "assert x_in_y((1, 2, 3), (1, 2, 3, 4))\n", - "assert x_in_y((1, 2, 3), (4, 1, 2, 3))\n", - "assert not x_in_y((1, 2, 3), (1, 2, 4, 3))\n", - "assert x_in_y([0, 61, 60], [0, 61, 60, 59, 42, 41, 40, 39, 68, 69, 0])" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "# make sure if vertices i, j, k occur in the solution, k, j, i don't\n", - "for c in solution:\n", - " c = c.copy() + [c[1]]\n", - " for i in range(len(c) - 2):\n", - " for c2 in solution:\n", - " c2 = c2.copy() + [c2[1]]\n", - " assert not x_in_y([c[i + 2], c[i + 1], c[i]], c2), \"Found \" + str(c[i]) + \" \" + str(c[i + 1]) + \" \" + str(c[i + 2]) + \" in \" + str(c2)" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Missing vertex uses: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n" - ] - } - ], - "source": [ - "vertex_uses = g.degree_sequence()\n", - "for c in solution:\n", - " for v in c[:-1]:\n", - " vertex_uses[v] -= 1\n", - "print(\"Missing vertex uses:\", vertex_uses)\n", - "assert all([v == 0 for v in vertex_uses]), \"All vertices should be used fully\"" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [], - "source": [ - "# convert edges list to adjacency list\n", - "al = [[] for _ in range(g.num_verts())]\n", - "for e in g.edges():\n", - " al[e[0]].append(e[1])\n", - " al[e[1]].append(e[0])\n", - "\n", - "# check if every edge is used exactly once by removing them from the adjacency list\n", - "for c in solution:\n", - " for i in range(len(c) - 1):\n", - " assert c[i + 1] in al[c[i]], \"Edge \" + str(c[i]) + \" \" + str(c[i + 1]) + \" not in adjacency list\"\n", - " al[c[i]].remove(c[i + 1])\n", - "assert all([len(v) == 0 for v in al]), \"All edges should be used exactly once\"" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[(7, 6), (6, 8), (8, 7)], [(8, 7), (7, 6), (6, 8)], [(6, 8), (8, 11), (11, 6)], [(10, 9), (9, 7), (7, 10)], [(9, 11), (11, 10), (10, 9)], [(11, 10), (10, 9), (9, 11)], [(0, 2), (1, 0), (2, 1)], [(1, 0), (3, 1), (0, 3)], [(2, 1), (0, 2), (1, 0)], [(3, 4), (5, 3), (4, 5)], [(5, 3), (4, 5), (3, 4)], [(4, 5), (2, 4), (5, 2)]]\n", - "[[7, 6, 8], [8, 7, 6], [6, 8, 11], [10, 9, 7], [9, 11, 10], [11, 10, 9], [0, 2, 1], [1, 0, 3], [2, 1, 0], [3, 4, 5], [5, 3, 4], [4, 5, 2]]\n", - "Rotation system is valid\n" - ] - } - ], - "source": [ - "# verify the rotation system (sorted adjacency list)\n", - "adj = [[] for _ in range(num_vertices)]\n", - "pairs = [[] for _ in range(num_vertices)]\n", - "for c in solution:\n", - " ce = c[:-1]\n", - " for i in range(len(c) - 1):\n", - " pairs[c[i]].append((ce[i - 1], c[i + 1]))\n", - "print(pairs)\n", - "for i, p in enumerate(pairs):\n", - " u, v = p.pop(0)\n", - " s = u\n", - " adj[i].append(u)\n", - " while v != s:\n", - " adj[i].append(v)\n", - " u, v = list(filter(lambda x: x[0] == v, p))[0]\n", - " p.remove((u, v))\n", - " assert len(p) == 0, \"Invalid rotation system\"\n", - "print(adj)\n", - "print(\"Rotation system is valid\")" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "ename": "AssertionError", - "evalue": "Proceed to visually inspect the solution", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[26], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mProceed to visually inspect the solution\u001b[39m\u001b[38;5;124m\"\u001b[39m\n", - "\u001b[0;31mAssertionError\u001b[0m: Proceed to visually inspect the solution" - ] - } - ], - "source": [ - "assert False, \"Proceed to visually inspect the solution\"" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 60 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g_directed = g.to_directed()\n", - "\n", - "def is_in_cycle(e, cycle):\n", - " try:\n", - " i = cycle.index(e[0])\n", - " j = cycle.index(e[1])\n", - "\n", - " if i + 1 == j or (i == len(cycle) - 2 and j == 0):\n", - " return True\n", - " else:\n", - " return False\n", - " except ValueError:\n", - " return False\n", - "\n", - "for e in g_directed.edges():\n", - " g_directed.set_edge_label(e[0], e[1], 0)\n", - " for i, c in enumerate(solution):\n", - " if is_in_cycle(e, c):\n", - " g_directed.set_edge_label(e[0], e[1], i + 1)\n", - "\n", - "p = g_directed.plot(\n", - " edge_colors=g_directed._color_by_label({\n", - " 0: \"black\", \n", - " 1: \"blue\", \n", - " 2: \"purple\", \n", - " 3: \"red\", \n", - " 4: \"green\", \n", - " 5: \"orange\", \n", - " 6: \"yellow\",\n", - " 7: \"brown\",\n", - " 8: \"pink\",\n", - " 9: \"cyan\",\n", - " 10: \"magenta\",\n", - " 11: \"grey\",\n", - " 12: \"lightblue\",\n", - " 13: \"lightgreen\",\n", - " 14: \"teal\",\n", - " 15: 'salmon',\n", - " 16: 'navy',\n", - " 17: 'gold',\n", - " 18: 'lime',\n", - " 19: 'indigo',\n", - " 20: 'maroon',\n", - " 21: 'olive',\n", - " }), \n", - " vertex_size=70,\n", - " vertex_color=\"midnightblue\",\n", - " transparent=True,\n", - ")\n", - "for object in p._objects:\n", - " if isinstance(object, sage.plot.text.Text):\n", - " object._options['rgbcolor'] = (1, 1, 1)\n", - "p.show(figsize=(10, 10))\n", - "\n", - "# export as PDF\n", - "# p.save(\"Johnson5-2_Genus1Embedding.pdf\", figsize=(14, 14))" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "data": { - "image/png": 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", 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", 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", 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155xzrlWttRVxzrlGUZGlNYDVgcGE9425wGfA68CHZlZXuhE6t2CR1AMa07/baxcWSwfdAwEYI0mtHWdJ+04pPQjsyAoMoZKJ1DEM2E7Skmb2RfNj2mJmtZL2AMYCI4ENgfOBY7I9h3PdRdSKbwVgTWBpQnWEOsJNsTeBN8xsSulG6JwrZx50O+dakNQH2A8SxwErh62V9RUVPeshIbNaGhpmV0V7z5V0G3Ax8FoWAYJzrn1LAIoef57F/uMaHw0AQnG0RYAJbex/JbAjCWBNJvEKw6LrHQ2cnMtAzewHSbsSZrxrgKMlvW5mV+VyHufKkSQBawPHgPYC6wGQSPSqlaqABquvn1MBdRVh/4r3oOHfwE1mNrN0I3fOlRv552PnXCy6k/9b0F/AetbULGk9ey6bqKoaRkXFQMLnj6ChYR61tZOYP/87Zs9+t66hYWYlJF6DhsPN7O3SfRXOdW+StgUejp6eYWantLt/SsOAH4Cw+vsmADY0sxfb2L8S+BpYjFnUcRYNhHXZU4GRZja7E2M+GLg6ejof2MTMXsn1PM6VC0mrQuIKaFg7kehT16vXzyqrq0dQVTWURKKmcT8zo75+KrW1E5kz55OGefO+EGgO2F+BczwTzDkHvqbbOReRtCLoFeCM3r1X6zVs2CEaNGinRM+ey1NZOahJwA2QSNRQUzOSvn3XZdiwQyoHDtyJysoBqwOvS/qLwjSAcy53mWuys0n3nkTcq3tg47ZWi6kBWNLqgGsA6E0lI3gvemkgsHdOI43PaXYN8J/oqRdWc92WpCpJSeD1ysoBqw8c+EuGDTuksm/fdampGdkk4I72p7JyED17Ls+gQTslhg07RL16rdoLOAP0cvjd6pxb2HnQ7ZxD0hagsRUV/VcZPHgv9eu3KRUV/To+sPH4BD16LMmQIftW9umzTgXoNNB9knoVbtTOLbAyA+Yv29wrEvXqHgdk9upur5gapGelYSuGZmw/Vs3vsGXvJOD56PEI4A4vrOa6k/A7S/eDkn36rFMxZMh+lT16jCGHjnpUVPSjf//NGDx4L1VU9FsVNFbS5gUctnOuG/Cg27mFnKRNQQ9XV4+qGTJkv8rq6sW6cK5K+vbdgEGDdhYktgbdK6mm4yOdcxlynemGOOiuAvoA7cx0A1jSPgeeBGAJRlHDx9FLawDrZjvQJuc0mw/sDnwXbdoIOLcz53Ku2MLvKt0Lia0GDdpZfftugFTR6fNVVy/GkCH7V1ZXj6oB/S/8rnXOLaw86HZuISZpJOiB6uqRlYMG7ZRIJPKTEV5TswSDBu2cAG2Bf+h2Lldx0F0PfJPlMbm0DYtdCYQSahs0aUt2XJbXbMHMfgB2I6zrhjBzfnBnz+dcEZ0L2mLQoJ0TNTVL5OWEiUQVgwbtlKiuHlkJeiD8znXOLYw86HZuIRVSSHV1ItGzx8CBOyRCDbX8qakZRb9+mySAY0L6unOuI1Fqdxwwf51DEabmbcOyCbrvAUKLow1Yg1BIDWAPScOyvG4LUQG1ozM2XSppnc6ez7lCi35HHdOv36aJmppRHe6f27krGThwh0Qi0bMH6KouLN9wznVjHnQ7t/A6AGyr/v23qkwkehTkAr16rUp19Yh6SFwnqWdBLuLcgmUgEBdUyLpnNi3bho3saD21JW0ucAMAVfRgDK9HL1UDh+Vw7ZbnNrua0EYwPt/dkhbpyjmdK4TwuylxfXX1iPpevVYpyDUSiR70779VJdjWwAEFuYhzrqx50O3cQijcaU/8uaZmKevRo92ln129Dv37b1kBDSOBvQp2IecWHDkVUWt13wFASBrPJkf2ysZHOzASiPuIHqWup7+cSMvCat7VwJWbvaFhRP/+W1YUchK6R48x1NQsZZA41We7nVv4eNDt3MJpc2hYqnfv1Qv+i7+yciDV1Us0QOLXhb6WcwuAzhRRg8yZ7nTbsA5TzC1p7wEvAzCE5enVGCSPAnbM4fotzx0Kq+0BjI82bYzXeHBlJ/HrmpolGiorB3a8axf17r2aoGFpYLOCX8w5V1Y86HZu4XRIRcWAuurqEVntvO66S3LddYfxxhunMX78eWy77co5Xax371US0LCGpMLk7jm34OjsTPdU4Ccgnulufq72pGe7f86MjO3H5nD9VpnZBGBX0oXVjpN0UFfP61w+hN9JDav36rVqq5+HO/rdt912P+Pmm4/kvff+xvjx57HSSsPbvV519UgqKgbUAYfm7YtwznULHnQ7t1BKbNqjx5KV2Wa49epVzfvvf8ef/nRXp64WKsHKgPU7dQLnFh6dmulu0atbLc7VntuAmQCsziaIz6PtP5e0QrZjaHNsobDaMRmbLpW0dlfP61webACymprFW32xo999vXrV8NprX/KPfzyQ1cUk0aPHmEpIbNLpETvnuqX8lit2zpU9SYOAkVVV2Rcnfuqpj3jqqY+6cM1KKisH1tXVTVmz0ydxbuHQ2fRyCDPjq1BBKMU2Pbug25I2UyndChxGgj4szwN8yFLRy8cAXV4aYmZXSVqTUNW8hlBYba2oxZhzpbJmZeXAeqmy1c/DHf3uu+uusQCMHJl9anpV1SJAwyhJA81saocHOOcWCD7T7dzCZ2WAysqhRb1oVdUiVZBYo6gXda77iVPCZ0KT3tnZaF5MLZcqiVc0PvoFY4A50bMDJfXNcRxtOQF4IXo8ErjdC6u50kqsXlW1SFEnoDJ+9/6smNd1zpWWz3Q7t/DpC6GFSTFJNUDePrw7t8CRVEG64vgXZmbt7d+KcY2PBgBfZZ1eDvAa8C7wM3qzLn24k5nsTni/2B+4JMextGBm8yXtDrwODAc2Ac4Bju/quZ1rTin1ICy2GBD93fJP78RSCYr7uzDjd2+fol7YOVdSHnQ7t/ApZasSb5PiXNtGAPHMby5F1GLNZ7oHZJvCakkzpXQlcAEAOzGXmxtfPlbSpZ24CdDyOmYTJO0GPEPo3/1rSa+b2XVdPbdbsCglEQLTIc3+DKZlIN38eX/C91f7aoB5+R551vz3oXMLEQ+6nVv4zAQwmwf0LtpFw/VsRoc7Orfw6sp6bmi9bdgYQmXzbNwI/AuoYVm2Q7yIsQGwErAp8HQnxtSCmb0s6VjSKe2XSXrfzMbm4/yuPCmlnrQMoDv603Hg3BU1RsOc4kbdDQ2N15tZ1As750rKg27nFj7vAdTWTqKyclDRLlpbO7EOGt4q2gWd63462y6s5TEDGh8tCbyRzcGWtClK6S5gX2AwqzGWN9kgevlY8hR0A5jZlZLWAo6kaWG1ifm6hiscpVRNmHHOJYDuVeBhNQDTW/kzrY3t05ltx9bW/rAtRfw8XFc3KX74XrGu6ZwrPQ+6nVvImNmPUsX42tqJw3v2XC6rY3r1qmbMmCGNz0eNGsxKKw1n2rTZfPfdtCyuWUdd3ZQKwGeynGtbl2a6LWkzlNJkYHAnenXHriQE3bA9K/EmPwCLALtIGmFm3+U6rnYcTygmtQEwilBYbSszq83jNVwWolTuQYQlDiMIa+6H0XYA3a+Aw5kPTAJ+bOPPZNKBdPz3dGBW1DovazpNS9YxZQezOqSWH4k7+t03YEAvRowYwCKL9AdgqaVCV5CJE2cwaVLriV21tROBxHdm9bkWSnTOdWMedDu3UGp4bt68cbuZbZRVr+5VVx3FXXcd1/g8ldoZgNtue5UTT7ylw+PnzfsGMAEvd3LAzi0MuppeDiHFfDD9CP1JGnIqpgZhrfXnwFJU8XP68W9+4jigAjgCSHZyXC00K6y2GCGF/SxClXOXJ0qpFyGIHpHx94hm24YTMg7yrZ62g+e2/uQcPHfBy2CaN+9bevQY3eLFjn73bb31Spx//r6Nr1966YEAnHPO/zjnnEdanM/MmDfvyzpoeC6/X4ZzrtwpD3VRnHPdjKStgUcGD96T6urhBb/elCn3Nsyb99UH0LBKPooxObcgkvQisH70tJeZzWlv/1bPkdIdwO5AKIk2lUfNbJscz/F/wBkAfM8FXNYYdP8ALG5m83MdV7vXk9YnBPtxEbkDzOyGfF5jQaSUKghZCO0F0yPIXGzQNQZMIbcAenoRA+icSRIk3q2pWWKFQYN+WfA2uvPnf8fkyXcAbG1mjxX6es658uEz3c4tnB6HxFezZr21eHX18IJWUK2rm868eV8mgAs94HauXfGs9PedCbgj4xofDQCm5pxeDnAdcDpQwWLsAdwL7EoI8HYFbu3k2FplZi9FhdUujzZdJuktM3s3n9fpLqJU7/50HEwvSshn6KopwHfA+GZ/T6BpAD3Vklafh+vlRQiYWYRwQyjR7I9a2db8tf7Ay9Bw4bx5X15aVzedysr+BR3zrFlvGSS+goYnCnoh51zZ8aDbuYWQmTVI+sfcuZ9cNm/eytTULF6o6zB9+hMNkJgEDTd3fIRzCydJvQgBBHSuiFqseTG10ZIqzLIPlixp3yulB4BfAsPZkLG8wK7Ry8eS56AbwMyukLQOcBjQE7grKqz2U76vVWpKqR9hrf0YYDStB9X5KDo2l3QA3VpQ/R3wvSU7fYOnZCT1AF4A1ujiqWYAi4FOnz79iSGDBu2ibJZcdca8eV8zd+6nAs4ws4aCXMQ5V7Y86HZu4XUlaL9p0x7dYOjQAyoTifx3Zpkz533mz/86ARxsZrPyfgHnFhyZM9KdXc8NLduGVRGCuG9yPM8VhKAbtmRdXuADYEVgI0mrmtnbXRhjW34NrAmsDiwDXClpr+6WIRNV9l6ckLkwJuNP/HxwFy9hhFT/5gF086B6ajmndnfRonQ94AboC2wOVj1//teaM+d9evVaOQ+nbaqhYT7Tpj1SB3oB7Mq8X8A5V/Y86HZuIRXNdh/U0DDr/WnTHkoMHLhjQqrI2/nnzx/P9OlPNRBSVb+R9AkwB7gbeBt4H/gilxk45xZgXW0X1vLYAY2PliT3oPsRQuA2AvEL+nMq06N13mG2+4gujLFVZjZX0h6Ewmr9gT2A54CL8n2trlBKCULQ1zyYjh+PoPNp3z/ReiDdJO3bklbXhS9hQfAVoTDnel08z1vA/fGT6dOforJyUF5rnZjVM23aQw0NDbNrwQ72WW7nFk4edDu3EDOzLyXtMm/euAemTn2QgQO3T7TWNiVX8+d/x5Qp/22AhhcJH9AfIMxcAaySsetcSR8SAvD3or/fB77yDyZuIZOPyuXQfE13+tzP5HISS1qdUroGOBWo4FBqOJcZhJnB/ST93symdWGcrV/X7HNJBwL/jTadI+k1Mytq5wOl1J+2Z6pHAz06cVoDviXcGPmS8P88jnBD5DtgvCVtZheHvlAwM5P0Z6ArxcimA6tlPH8QGoZOmXLPmoMG7VxRXT2iS2OE0C5z6tSHGubNG9cA7GJmXbmh5pzrxrx6uXMOSTuA7q6sHFQxYMC2FVVVQzt1HrMGZs0ay4yZL0MvM2bZFmb2tKTfEVoBZWsW8AFNg/HXzMz7mroFkqTzSLfK2tTMnu30uVKaACzCDOAcAP5mZn/pxHnGkL4B8Dmn8T/CTTSAE83s/M6OscNrS/8CTo6efgOsYWY/5u38KdUAS9D6TPUY4uT83E0h/JtlBtbx468tafO6NnIXixZfPwNs3InDjVBQDaCW8L12IdAHdD9o475910v07r0WUueSFmprJzJt2iP1dXVT6sF2MbOHOnUi59wCwYNu5xwAklaHxI1gK/TuvZZ6916NioreWR1rZsyf/y0//fRsQ139pAQbABsB1zKBH1iVUPn2Q2DZLgxxFiEYeb0L53CuLEm6F9gperq4meWaDp4+V0ovEafdng7UcZOZ7d/Jcz0KbAXAyxzM/7gmeukzYLlCZaRIqgKeIB1QPQJsn8v1ov7UywLLA8vRNLgeQTroysVcWgbTjc8tueAVfitnkjYDnurCKT4H9jKz15VSb2BnXuFhHuYPwMmVlcMa+vXbuKK6eiTZFlirr5/FrFlvMWvWWAN9CA37m9mbXRijc24B4EG3c66RpGrgVNAfgKoePZahZ89lVVW1CIlEnyYfOszqqK39kfnzxzN79tvU108HNIs97XFWjAowTQSu5Fnm83NgO+C+Lg7xEDO7puPdnOteJL0LrAzMJ/To7nStA6V0C7A3EFZDT+YlM9ugk+faE7gtenoLp7EIsEX0fFsze6Sz4+zw2tJw4E1gWLTpL2b2t2bji9tGLd/KnyU6cdkGwsx6azPVXwA/LMDFybqdaLb7dULxvVzdAhzFaVQDx2P8EVHJT9RzLisD/SFxHTQsV1ExgF69VqG6ejhVVUPIXIZlZjQ0zKS29gfmzPnE5s79FKAW7Ezg9Hz3tXfOdU++pts51yj6cPAXSecDB86d+9mv5879ZAyAVFNXUdHbIIFZLfX1P1WCCagnFEjrA9abpzid5ViOCpZnGLANm3A//ySk770KrNPJ4X0C3NHVr9G5chMFDnEhta/yUFwwvW50IDC5U726Y/cCkwkVt3djIIcztTHoPpYwA10QZjZe0j7AYyRIMJCUdpFYjXmEoHqF6O9cmytPopVZatIp4LV5+yJcQUQ/M5sDp5F7wD0H+DWn8gSVnI5xGKJnY95DDyoIN3j2lXQN8M/6+mnMmPFslJIuq6joVxeSMRqor58ls3nR5+nEOLCLgGvNbGqXv1Dn3ALDg27nXAtmNgU4Lwq+RwBrms1bo65u3iBCC6I5wKeEGYZ3CK1+zgRgEkdRwW408AYJalgT+ILf8j6vEYoyPdqJIc0H9jbzIkNugTQUiNdydKWIWqx5BfNFJfUys9m5nsiSNk8pXQecBFRzDIP4O98CI4FfSBptZuPyMGagsYBZerb6NJZnFpPpwVAqEJDK8lTTgY8y/nxMSIn/0ouVdV9RsL0F8Bdgk06c4mO25Y+sx+4Yl0H0XZXpawBeV1jMfXjGKysDfcHWrK+fvgyhn3wtYR3/G8BYaBjf3VrcOeeKw4Nu51ybog8P30Z/7o23K6V9gA2Aqy1pcyVltm05mNP4M6dxDHAVEFaqfs81TGEd4Fly/7B0sq+JcwuwfLULi41rfDSgyTXe7+T5riIE3VDFocBlwN8Ia6KPBv6Qy8millsjSQfXK2Q8XrTFAe2XlviKpsF1/MfTwBcgUQC8I3AKLbOlPgJuInxPtm15XmVPppHg7nDSNvb7FIAnCTPpS0VbHzezD6LHr+Q2euec86DbOZcjpbQicHP0dDVCoaMBGbskgKf5F2twMlsg9qMG2I2eXM091PMbcgu676fM+vQ6l2f5ahcWa61Xd6eDbkvaB0rpRcKNtpXZi99zG7WErJdDJSXNbG7z45RST0KrwOZrrZcDeuUwhLnU8zmfMoYJ9OJHYB7Xsx/HWNJmdeZrct2DwuLpvYA/Ais1e/kj4K/A7WZWH9383aHpCQjfcVswjaFZLm36jobo3NdmbL28E8N3zrlGHnQ753J1RMbjjZTSJoR080zLMpuneJA92IF1EUszAtiSpXmEowm9VbfK4lpzgd96up5bwGXOdOcj6P6GuCVSuvHVkm3unZ0rCUE3rMCuhPoK+wKDqWRfpfQGsCqwCumZ69HkViF8Iq3PWn9tf7V6SesAzxOC/QM4jXtJRrOWboEiqQdwICGLonlNgreAfwB3N6t/cA5x0F1B+G7cABgCNL0x3LZ6YAJfEPrR7xJtnURGppdzznWGB93OuaxFaaG/bLb5CsRPtAyL12Ysj7I4J/Az7kZUsz7wJb/gk6xnDXoAT0nax8ye69ronStbmQFxl9PLo3XY3wEjm810d8XtwAWEYGR/fsn1jWHIMK4k++C6nnBj4SNCG8HGNdeWtCntHWhmr0o6Efh3tOkaSe+Y2We5fSmuXEnqAxwJ/BZYrNnLLwJ/Bx5ufiNW0gbEM9PLEhLR+3ZiAD8AdbxHCPiroq3XeAVy51xXedDtnMvFxoTZq0zLUsNPtEgujV67mysZwnkMj9Z97gxcyuH8xCvAuu1cazYhBXUE8LSkJHBGHio7O1du8p1eDmFd90h6A9XA/NxmupVSJSENfNWMPxXRyz1YjSN4BZgAjEeNpdXSZtD6rPXnlrR5nfuSALgY2IjQEq0fcKek9c2sebaN60YkDSIU5DweGNTs5UcIM9vPtRJsJwiz4X8j/v7cls4F3ADfAWEZRmZG15WdPJtzzjXyoNs5l4sDW2wxoJZ+7RyzKJdzDCfxPP3YiF7AbojrWJGGNo95DtgPuB7YjLBO/G/A5pL2N7PvO/8lOFd24lnoaWY2LU/n/JIQnIbE2oltB91KaSBNg+tVCetna9o8uwjlrO6Lnj/FF/yKS4G3CUHL+EIUMjMzk3QEoZ7E8tFYLwIOy/e1XOFJWgw4kVCQr0/GSwbcTbjR+nobxy4C3EDTpUrP8T19GNSpvt1x0N0ALB1tedLMPu3UuZxzLoMH3c65rCil3sAeLV6YR0gYbV9fLmEdTuRHqhnCEsCm9OUpptOyx+5UYD8z+0bSlsCfgCQh8N4CeFvSr8ysYP2BnSsWhWa/i0dP8zXLDc2LqU1kjPZUgpVYmpYB9qgszzmFMG8egqOlOYCQcj6QzxnBaVxjZj/m6wtoi5nNkLQ78CohG+ZQSc+b2bWFvrbLD0ljgJOBQ2h6c6eeUIn8n2b2YTvHbwncCCwSbTJC6nmKSdTzIu+yHiuRyHFg3wKwVsYWL6DmnMuLXN+OnHMLr11oOhMRZFs7eA7V3MBgLJrf3gQYQ39osRr8EDP7BsDM6s3sr4Rge3z0+lDgf5L+GQUsznVno0j/Ls5Hu7DYhMZHGwGH0ZsVmUHoV3074WbWL2g94LY29hsC/L5xr35sDFwTPasBDs3j+NtlZu8DR2VsuljSKsW6vuscSStKup7QmOto0gH3PMLSgaXN7MC2Am5JlZJOBx4lHXBPALY0sz+bWZ09ZcajrM7D3EIunennAZOpA34ebfkR+G8uX59zzrVFXhTYOZcNpfQYsGWLF74i/bE7GxtlnGUGcCmZgfvFZnZsq9eXhhIK5WyfsfklYB8z+yqHEThXNqIZu8eip2eZ2e/b27/F8SmJUGeh+ex1tmu4fwLeIaSFx3/es6S1Gq4opb6EJNy+wGxuYCM+543o5a+ApYpZd0HSpYTCWxACubXM7KdiXd9lR9JahB7buzR7aSYh2D7PzCa0OLDpORYFbiEsOYo9AhxgZhNbPWZV7cuGXMciWWR2fgFczw+kg/mzzezkDo9zzrkseNDtnOuQUhpF+EDdskLxB4T5sKxPBuwPLBU9/wy4CcN4ANirvYJIUdGcE4F/kl4eMw04yMy8pYvrdiQdTjqF9Wgzu7TNfUOAvRRhNfU6wJqEFl3t1VRIm8dEaniBpgH2uFzXXiuli4DjoqcncBrbANtFz39pZve1fmT+Ra2lXgDWiDbdCezpbQZLT5IIOU2nAFs3e3kKcD7wbzObmsW5NgNuJR0Q1xOyMM4ys7argwA6RnsxjFs7rK//HPAEM0lndC1nZp90NDbnnMuGr+l2zmXjV7TVEmhmjmeKy+PEZXOWBjZAvMC6hKq137V5aPhwdY6k5wgfwMYQVqz+V9LZwClmVpvjiJwrpTbbhSmlYaQD7HWAtWlZ2bk1s4F3o2PEZEJYP48LzezveRjzJaSD7mNI8FsaGoPuY0mXVys4M5sbre9+g/BesDuhAvYFxRqDayoKtrcnBNsbNHt5PHA2cIWZdfjbI7rR+n+EQprxMozxhBu0z3d4fEqLs0hji7m4e33rwm+eOOB+2gNu51w++Zpu51y7otm1llXLY9mu6W5+zN2kV3NvAYxkGKH9T9sVkyNm9iqwOnBXxubfAU9KGtGJETlXKiHorgb2ZrBS+p1Sul0pjSN0Db4f+DOwDa0H3N8ADxCKSO1JaPPVz5K2HiE7JZQam5dxrS6ypH0APBU9XZb/Yz7pGwZbS1o2H9fJejxmX9L0PepsSesXcwwOJFVI2gt4i/A9mRlwf0FYBrCkmZ2XZcA9mPT3dvx59XFg9SwD7h6E3xFDgLD44Dpgdht9M5re7vUCas65vPKZbudcR9YF2v4QnetMd3zUF9zCXGbSkxOpIMxPXcp6zOV8wjx4u8xsuqQ9CL1dzyG8n20EvCVpXzN7rN0TOFciUQ/slYF12IPNGUIoD5jgpg4OnQS8Qqja/Sow1pI2uZ39vwRG0xPoAcxtbE2WD/8BNgegmqMJs9//il47mrAMpGjM7D5JZxJ6NlcCt0taw8wmFXMcCyNJ1YRsqP8j3Wor9j6hx/btZlaXwznXIyxcigv9GZACTs+mZkB0s/g/xJXIpxBu9M7hX4znWgbxPIMybmL9RKgxEkyO9nbOubzxoNs515G2Z7kh15nuV4ArgNvMbGYUfKwDbMgAYCfgdo6S9JqZXd3RyaJ1mxdKepX0B7QhwCOSsv6A5lyhRB/+x9A0TXwNoCcQumG3bjYwlnSA/SrwdY7rr78kDowHABPyM9MduY+Q5jsc2IlfkOQB/kaoRn2ApD+a2dw8Xi8bpwLrE9YRjwRulLS9vwcUhqTehP7ovyP8e2d6lTBD/UBHa66bnVOE5QFnk/6MOonQRjKXG6mHE9qRQS1wGzCHl4FT7QarVUojmcCjLBr1sh/X5NhrzWxeDtdyzrkOeSE151ybovS87wkf2Vt3FSHBNTsrmNlHza6xOCEdcSAADwKvMQ/YyMzGZj3WkIp4A+mCThCqQu/fVmVb5/JNKQ0lrL3ODLIHt3tQAzCFmQzhZtIB9oeWzH5msI2x/Bn4KxAqIHxEA9AjX3UPlNJfCLOPAH/nNEYD+0XP9zOzm/NxnZzGJC0GvEm64FYyajvo8kTSAMLa/ROIU7fTniTMbD+ZazE7Sf0Jv1F2y9j8PLC3mbVZ66PFeVJaF3iWsGgjJJi/yzRCWvq4jP3Et5zIj/wfTzKUdM375c3s41zG7pxzHfGg2znXJqW0Bx3VJr8AaK327GhgKnOZTo+MrZeY2TGtXGcnIFQfrwOuBCbwDbBmLumhUdGdPwCn04miO87lQin1IsxaZwbY2aRwfwG8yvd8y0P8jglALdea2cF5Ht/+hBtRobHSS0Dog/x5ns6/GPA1YUZyImeyH3Ma2589Y2ab5eM6OY9L2pyw9jdBSEvexpebdJ2kYYRA+1haVsy/DzjDzF7u5LlXA+6gaXr6WcCfcrlJpJQWAV4HQm2Pl4H/AbCbmbWaMi5pE+CZ6GnJvm+dcws2Ty93zrVn1Q73yCx71oN5LM2HrMHTLMmbnEUvwlrP2IGS/tS8RYwl7T6ldCFwPJWE9d2XM4r53CJpm2zTQ6M0xjMkvUS6vcxw4GlJ/wec462EXGdESyFWpGmAvTJQ0cGhP9I0Rfw1S9qPAJJ2JqTmQgjE821c46MBjY+WBPISdFvSvldKdxMKuA3jZIbxVz4h1IDYVNKypagAbWZPSTqVMOMq4GZJq5vZt8Uey4JA0vKEYPtAaHITtYHwPvtPM3u3k+cWIUX9ItK/TaYBB+baei76Gb2NOOD+CngUgP+0FXBHDs947AXUnHMF4UG3c649VxMq0PYi1Hb9NvrzHbAe8Gt2AR7kQb7mauZyv72bnpXQaepF6KndP9rUi/AB66xWrvV7QiG0NRgC7Ajcxc+B0wjVm7NmZk9HMye3AJsRAqOzgI0lHZRNX1i3cFNKfQnrgzeO/qxN+P5tzxzCLFtmkN1eH+w224XlSfqcAxsf5bOYGoRiVXsCkOAYQs2G+Of7cODkPF8vW2cCGwI7EFKgb5e0qbcUzE4UDG8OnET4N8xUC1wL/MvMPuvCNXoTbsr+KmPzWEKf9c78PJwJbAqEwmh3AA28RfrGVmtjGATsET2Ny60551zeeXq5c65TlNJuwJ3R0z9Z0v7R6n7SRaR7+kJYAb5ka5VsldLShH67fYHQLCas6t7ezB7OeYxSJWHN6SkZm78E9jCz13M9n1twRT2xNyIdZK9G+7PYDcB7NA2w389lHXazn40NzezF3EfezvlTShBqMvfiR4i6FZ9pZv+Xx2uI0BM8lIT7gM25nUeBKsIs/8hSFaWKAqo3gCWiTeeZ2UmlGEt3EVUi35sQbDfPdJpBWPxzTi5rrNu4zgqEsDizlODFwEmd+X5RSnsTbrJCPXAN8C2zgDXay7aQ9Bvg/Oipf3845wrGg27nXKcopXUI1cgBLrWktdrmS9LPgHeabd7DzO5sdf/MYL6OMNc+nimED09fdWqs0vaEta1xi5j5hHTJSz3dfOETBYpLEKpcx0H2ch0c9hVN23W9YUnrTJf69DikB4Hto6fDzez7rpyv1Wuk9DawCvWEWtIN3GFme+b5GkcTAiaAKziN/sSz36GeQvt1IQpI0lrAC8RFtWB3M7urVOMpV1EhyiMJN4EWa/by14TqHVeZ2fQ8XGtfQhp372jTTOBwM7u1U+dLaUXCz2Q4X/pm7QFmdkM74xDhxtmK0aYVzezDzozBOec64unlzrnOyqxZPqqtnczs3WiN9foZm08gPUvedP+k3aWULgB+QyUh8e8yBjGXOyRt3JlZEDN7SNLqhKJw6xI+gF9MSDc/wsw6123cdQvRjO+KpAPsjWnZ4qi594Dn4j+WLMh64Di9fC4woQDnB/gEWIUKwrruKY2zvvl0IyG1ty+wH4PZh8mNQffhdFSMsYDMbKykEwlp8ADXSHrHzD4t1ZjKiaRlCe/HBxG3sUt7FTgHuDuXHtvtXKsHcB5wVMbm9wg3QjpVLVwp9SH8LgkB95vEAfd17QXckQ1IB9zPecDtnCskD7qdc531A2FtXxUdBzCX0zTo3lDSWu20BPs9Yc34ugwEdgZuZW3CB8Dj2jimXWb2dVSl9l/Ab6LN+wCrS9rDzN7rzHld+VFKVcCapAPsDUlnObSmjvBRPQ6yX7CkTSnoGEOl/dHR0y8LmHGRDi4HA1PavkHWWZa0GUrpekJV614cw5L8jS8INxW2lLRUviqmd9IlhKUD+xBuDNwpaT0zm1PCMZVMNMO7KSGF/BeEYnMxA+4hvNe+lK/vS0lLEtLJ18jYfB1wjJnN7tQ5Q8bK5cAKQLht9RAA7xO+FztyRMZjL6DmnCsoTy93znWaUvqSEDhMsaS12YtYUi9C667+GZvbbZEU9e9+kzhYehQIK1673P9X0u6ExPW+0aY5wFFmdn1XzutKQyn1pmnRs/VoOWuXaTahgVYcZL/S1VTxXEX9pMdHTx8ys+bFqvJznZQOIqxwhYeBVzBCr+75eb7OioRgB+ATTuMa4Izo+RlmdkrrRxaHpD6EmdsVok1Xm9mhJRxS0UXrtfckBNurN3t5FqFH9oX5vkESVem/lvT7/1zgWDO7ukvnzVzWMA+4jNDvHtY2s486GNNAws9fD0LTyxEL600Y51xxeNDtnOs0pfQsIcgB6G3JtmcsJP2bprMP8wgfdCa3c/7tiOcuGgihwzfMAtYxsw+6NHZpaUJaYmaxoCuB4/3DV3lTSoNpWvRsDdrP3JoMPE86yH7TkqWtYi1pXUIXYWijf31erpPShoSvPYSc4adpdGfrI3RwrScJFa/hM/bkRm4m/L/8AIwqdeVwSSsCr5GuQn9oVwO/7iAKMI8Afk3cTivtW+BC4Aozm5bn61YRbrz8NmPzp4SaHm936dwprU34vg5r9W8DQnL4vmZ2SxZjO4GQ6g5wgZmd0JXxOOdcRzy93DnXFc3Xdbe3Lu8KmgbdNcChhHTvVlnSHlZK/wBOIUFY330pvZnNnZLW6cpabDP7TNL6hA+ch0WbDwPWjtLNfc1nmYiyHjLXY6/Y/hF8QzrAfhb4yJLWUNBB5i5zScY3be7VdenKzelclFGEwnD5djFx0L00+wL3AbsCixDSmO8pwDWzZmYfSDocuCna9B9Jr3c1ACxX0Y3F3wCH0LLd3euEFPI7C3EzRNJIQii8QcbmO4DDzOynLp073HS7kzjgfok44L4ky4A7AWTe5LqsK+NxzrlseNDtnOuKrINuM3tb0iuEQmaxoyWdY2b17VwjSViTuyn9gN2AG1kB43JJ+3VlzWE0o324pOcJ6z57Ema+X5d0sFc5Lr5onebyNA2yOyr+9SFNi54VIqDMt8y11YUMun8EpgP9mwXdhXAvIWV3OLATIzmQb9k1eu0IShx0A5jZzZI2Ao4mpBbfGdWX6HJV7nIQrdfeiJBC/ktarte+FzgXeL5QdQQkbU24sTEk2lQbjec/Xb1mVBTxemBxINRVfwwINxFOzPI0WwDLRI+f8gJqzrliSJR6AM65bi2rCuYZmherGQ1s194BUd/jfQgpqrAUodFT2NZqm7Jcmdl1wDqkbxrExZbOj9ZBugJSSiOV0kFK6Sbge+ADwuzT/rQMuOsJKcLnArsAQy1pK1rSjrSk3dhNAm5o+vNSiMroAFjSjHi2uz/xrfaCBN1Ryn48a5jgYFYgPaO+jaRCVE7vjBOJa1zD0sDVUbDabUmqkrQPYRHBs4Tyk/HXNJvQpX1ZM9vFzJ4rRMAtqULSX4H/kQ64vwY2MrN/5+ma/0fcZm8WYe68gWmElPVsO1tkznJf3OZezjmXRz7T7ZzrilyD7lsJwVJmQbXjCJ1V22RJ+14p7QM8DiTYLLryF5wvaayZvZrTqFu7htl7ktYm3BjYO9r8G2BdSXuZ2dddvYYLlFJ/YDNgK2BL2u+RPZew9jlOFX/ZkgtEi7dizXRDCLrXRsBAYFLBZrohLCP5M1BJBYdRwSXUkyQEgIcCfyngtbNiZvMk7Qm8QWiktitwPKEXdbciaQChLdvxtOwiMZ70eu1CV+NfhDC7/fOMzQ8SemXn5dpK6efA34AwZ38XMAOAA83syyzHOZKQAQDhBt+9+Ribc851xINu51xXZAYLHc5imdlsSdcQ+sLGtpG0TEdrqC1pTymlvwCnI0Ka+aVUMYM7JK3RXkG2bJnZDEn7EoK78wlrBtcD3pS0v5k93NVrLIyUUvzvuCUh0F6HtjOtZhL+/Z8hBNqvWzK/lbbLRGaAVLCZ7kjTtmEFDLqjG2R3E6pkD2N/JnIdDYT/70Mk/TUfPZ+7ysy+lPQr4P5o01mSnjOzN0o5rmxFLbh+Q7iR0bvZy28S1mvfke8q9W2MZRPCDdXFok0NwJ+Af5nlp5aCUhoB3Ez8vvEU8AUAZ5nZfTmc6gjS7z2Xl7q4n3Nu4eFBt3OuKzJnF0ZnecwlNA26IaSJn5TFsWcQ1ndvR29gd+A6FqeBGyT9Ih8f8KIUyEskvUZIXhxNaFv2kKR/AMlyCBrKWbQue2VCkL0loSdw88AgVg+8QliZ+TihfdfC8EE4Dnwn5pAW21nNi6kVcqYb4D+EoBvGsC9hxnNHQuXs7UgHuiVlZg9IOhv4HVAF3CppTTObUeKhtSpKgd+A8F65My1vXN1PCLafLWDf98zxJICTgb8DFdHm74F9zOyZvF0npSpCUD8MCLeQngNC9fI/5TDeakJWAIT3nSvyNUbnnOuItwxzznWJUppGSBf/0pK2ZFbHSI8SZjxj0wntwzrslRxVrn2TOHB4nhCqwalm9vcchp7NOAcS+svulLH5acKHygn5vFZ3p5RGkg6ytyRUrG7Lh4T/tceAZyzZtWrG3Y2kSkLLvATwhpmtWdDrpbQWYR18SKi+j4lm1t7/T1evJ+BdYCUAbuZ4PuHC6OX7zWynto4ttigQex5YO9p0vZkdWMIhtRB9v+xKCLbXbfbyHMJ71Plm9glFImkQcB2hKn3sSULLrh/yeq2UziLcGAm/KS4F5jAJWN3Mvsv6PGFJwW3R0zvNbI98jtM559rjQbdzrkuU0pvAaoSZgx5R4bP2j5F2pmUl4yPMLKuZB6W0PiEFOWTr3AJ8TAOwtZk9ke3Ys7pWmF36HWGWPZ7NmUAIvJ/O57W6k4x12XGQvXw7u08gHWQ/YcnsPygviCSNIhSYArjXzHYu6PXC/9U0AMYRQjToUcgZdqV0NHGRqjqu4HS2I6TUNwBLmFmhU+qzJmkpwo28vtGmA8zshhIOCWi86XcIYb324s1engBcBFyWj6U1OY5rbUIWULykyIDTgVQHnShyv1ZKuwB3A+E3zNXAdxjhvf7xnM4lPU3IugHYwsyeyt9InXOufV693DnXVXGKeQUhfTQbD9ByHeux2VYQtqS9REhrDHYGBpAAbpGU7RiyYsFZhABzfLR5UeAJSadEKZYLPKVUrZQ2UUp/VUovApOB/xIK4TUPuGcRUopPJKSZD7ek/cqSdv3CHnBHitWjGwBL2nRgIpDZq7t50a18u5G4zFUl+1HT2Bs7ARxc4GvnxMw+B47M2HSJpGVLNR5Ja0q6CvgOOJumAffbwIHAaDP7RzEDbgXHAS+QDrgnA9ub2V8KEHAvTXyLCOARwr9ICO5zDbhXJh1wf0TIWHLOuaLxNd3Oua4al/F4DOkWQW0yszpJlxFXog1WJazXfj7L615A6OG8Kz2BPYCrGUo9t0naPN8FcszseUmrEyr0bkkIHv4ObCjpgGLPNhValCK8EukK49msy45ns19dQIuf5UsxK5fHPgGG0ZdQHnA+o4DPC3UxS9oMpXQ9cCzQi32ZwzUYoYr5YZL+ke8grSvM7BZJWxFuCPQmrO9evwjr7QGQ1JOwDv4YQqHB5h4kdH54qhjrtZuT1I+wBnrPjM0vAnubWd6/h5VST+BOoB8QFiuEHhWPEWbVc5XZXvLiUvwbOucWbgvFDI1zrqAyi6mNyeG4K4HmgfGx2R4c9R8+hDhwGAFsA4TA/Z85jCNrZjYR2BY4jZBSCaFn7BuSmq+17HYy+mXfSCiI9C7hg/72tAy4PySkt/4SGGRJ29CSlrSkPe8Bd4eK0qO7maYVzAtfTA0yeyAvwT6E/s0QZm63au2AEvs18HH0eHUK9D6SSdJSks4ifB9cS9OAezrh5uLyZvYLM3uyRAH3KoS+5pkB97nAZoUIuCMXEW7EwiTi0nvjgf1zvVkjqS9wQPR0NnB9vgbpnHPZ8plu51xXdaaCOWY2QdJdpHtiA+wu6SQz+z6rcyRtulLandDHuYZ1CPPs73OSpBfM7O5sx5PDuOuBlKQXCS1shhCCiOck/Q64qLvMoiilPsAWpGezs1mX/ThhXXbZrMnthoqaXh5JF9kaBHxf+KDbkvaBUnqasDRjOVblZt5mu+jlI0gH4WXBzGZJ2pv4/QROkPSEmT2Qz+tIqiBUcT+GcBOv+bKatwgV4G/JprhkIUk6mHDzpEe0aTpwsJk1r8mRv2umdDChFRrMB24H5lMP7BXd+MzV/kCf6PGNZjY9H+N0zrlceNDtnOuqcRmPc5nphvBhLjPoriS0dPlrtiewpL2llH4NXA6EOuMTgMlcI+ndjvp/d5aZPSZpNUI13A0JLYcuADaWdKhZeVbkVkpLAjsQqg5vRkg2bs0swrrHONB+P8oucF1XivTyUsx0QwgeNwNgR1bnbSYQaiLsKGmxbG+wFYuZvRXfPIs2XStp1VyqZLdF0jBCds5RpNdEx+Lw8mLg5VLfuJPUi/B/d1DG5jeBPaI18IW5bkqrkpkhcT9hphv+z8yyXXqUPl+oE3JMxqaL29rXOecKyYNu51xXjct4PDrHY58H3iMU24odKemMHNdkX0lY3/0raghJkFfSj1rujNZlzs5xXFkxs+8kbQ78g7ilTegevpqk3c3s7UJcNxdRj9sNSAfaK7Sxaz1h1WRmv2xPEy+MOOA10sX5Cq15r+5CF1KL3Uv4GodTyU704T/M5NeEzx8HEboClJv/EDI/fkn417pR0padWYMeBX3rEwK/PWh5k+sr4BLgajOb1KVR54mk5QjVyX+Wsfky4AQzm1uw64Yq+3cSz6q/RljgEr6HzunkaTci/fvlhXJ4T3bOLZx8TbdzrkssaTOJ5yJynOmOZnOazzwMJ3zYzWUMRiiU8wEQOkRvD8AqwL9zOVeuzKzWzE4m1FCP0xaXBl6WdGi2FdnzSSkNVkr7K6VbCFWrnyZUe28ecH9D+MC/MzDYkrZBtC77OQ+4CyoOun8wK9q/82eNj4o4021JqyXOQoEEezb53HFYOVb/j96XDiG93n4z4JRcziGpj6QjCLPDLwD7kQ64DXiIcBNsKTM7s4wC7r0I67fjgHsWYR31UQUOuEVoCLY0EKqUh8UHXxLS2Ts78++z3M65suB9up1zXaaUXgXWJnyY7GnJ7Cv+RkVuviPdIxfgGTPbrBPjWIEwPxKKfv2XsDoSDjWzq3M9X87Xl5YkpIiumbH5OuCYQs22Q+MH1pUJH+J3IMystRbMNBDWqz4Q/XnPU8aLS1IVMI+wjvc1M2utUnVhrp3S18Ao5gBnMsXMBnd0TJ6uuxihL3klMJEU72BsGb28Va7tn4pF0saEG1YJws/Oph2lOEtanhDoHUhceTttCnAVobd2wVK0O0NSNaE4WmYxyw+A3c3sw4JfP6UTo+vDHMK8+jTmAxuY2eudOqe0KOH7ropwY3hUsarRO+dcc2V3h9k51y3FxdREjjNoZjaDltVkN436qubEkvYhoUBTsANh1hv+E62/Ligz+4KQznhJxuYDgVeiD+N5o5R6KqXtldLFhBT/dwhp7hvS9L19OmHd+a+ARaIq42dY0t71gLskhpMunFWs9dyxkGLeE+jJoGjdbsFZ0r4H4qKGw1iT9zNePrwYY+gMM3sOSEVPE8DNkgY1309SlaTdJD1BqOr/a5oG3K8Q3gdGmtnvyzDgHk64uZAZcN8IrFOkgHtD4F+NG+4BpgEhnb1TAXfkMELADXClB9zOuVLyoNs5lw+dbRsWu6SVbce0sq1DlrSbCfMk4ePWnkANPYA7JQ3ozDlzur7ZXDM7hpBOGlceXhl4TdLuXTl31NLrSKV0PzCZ0Lv3aEL19EwfAmcR0mKHWtL2tqTdaEn7sSvXd3lRinZhsVIVU4PM1N5tWZv0kpRdJA0t4jhy9XfgmejxKOCqeMmIpOGSkoSbXncSOgHE5hBmtdcys/XM7Hozm1O8YWcnms1/g5AdAyEL4wjggGJUTldKwwjZQaHG0HPEt4ZuAS7t9HmlSuDI6KkR/05wzrkS8UJqzrl8GJfxOOeg28zel/QMsGnG5gMk/bGT7V1OIKS7r8FgQkXzO1gKuEbSrsWoDGxmN0t6g/BhfCVCy5o7JJ0J/CmbokxKqYLQtzcugrZqG7vOJ8xUPQA8aEn7outfgSuQUlQujzUtpvYto0j3pS60Z4H3gZWoZAMGci1TOYhwa+xA4OwijSMnZlYvaX/CQpXBhPoH50kaAewCVDQ75FPCTcRrzWxqEYeak+jGwXGElO74s+DXwK5dnF3Ofgzh/e1mQvZHuHX7FAAfAUd08X36F6SLBT5gZl914VzOOddlPtPtnMuHTvXqbqZ5kZvewAGdOZElbS6hUnAI2FcihK7hA/NvOzm+3Mdh9hGwLnBTxuY/AP+TNKS1Y5RSf6W0p1K6jtD87EXgT7QMuCcQZtJ2IRRB28aSdpEH3GWvFD26YyWb6Y6WMvynccOu9Mx4+fBSFBzMlpl9S9PU698QuhTEAXcDoYLE1sDyZnZemQfcvQi1Ji4kHXA/QZiVL0rAHUkCPwdgBnAX0MAcwjrymV08txdQc86VFZ/pds7lQ1fTyyF8aI17+MaOkfTvzsx4WNK+UEoHE68l3YZQru07/inplWi9ZsGZ2SxJvyK04zqX8EF9S2CspF05jTeBZUkXQduYtt+bXyOklD8AvGlJayj0+F3elcdM96AWYymGG4Ezgb6MYkcSPE8DGxG+/zchncZdNiStSljCsX8rL08kVGa/3MyK/X/ZKZLGEN4TV8vYfBZwipnVFW0cKW0H/BkItyzuBEKYfZSZvd/mgdmcW1oW2Cp6+jnwaFfO55xz+eAz3c65fPg643Gngu6oddIVzTYvT9N1krmdM2n3EFfErSDMffekArhN0iKdPW/O4wguJHwtE6PNS5DgVcYygZBOeTawOU0D7pmED8iHAotZ0taxpKUsaa97wN1tlXJN95cYYVlDcXt1A2DJJkUTe7EumQXFjmjlkJKQVCNpX0nPE9LKjyTuiNDUg2b2524UcG9NaAe2WrRpFrBnVNytmAH3EoQbMMHjhG7lodhZ86KanXFUxuNLzPy90jlXeh50O+e6LErnHh89Hd2FU10ONF/rfFwXzgfwf8BLAAwgJJiLxYBbomI7RaGUBnIaozmOsQwnfAhsoIIHGMaDQPoj7+fABYRU1SGWtN0saVdb0iYUa6yuoOKgu4H0z0xRWNJqsegGWfELqcXSqb5bsD6hjRbAbpKK0sKsLZJWkHQWIQPhJkIngNhMwlrtHUkXSDxY0t7FHWXuFPwf8DBxjkNYarCumd1R1LGkVEMonBbG8RFhAU24uXF8l88fUucPjp7OBa7t6jmdcy4fPOh2zuVLnGK+iFKda0UUrZ28t9nmnSQ1r86d/TmTVgvsRaj2DcsBGwBhVjnV1nH5oJSGKaUjlNIjhBnu6xjC9hxCokkn79eAi/iSsWwELGNJO8GS9lgu/c5dtxHPLn9fzNnFRuIjAKqB/p1eCtJplrQPCEX/oIplGcaT0Us1hLZ2RSWpn6TDJL1E6Ev9OyCzmvoHhPXcI8zsGDN7gKbrhS+XtGTxRpwbSX0JydtnkP7M9wChHViX0rg76WziChtTCIuK4CdgjzxVd9+bcHsV4FYzm5yHczrnXJd50O2cy5dxGY9Hd+E8zYveJEi3fukUS9o3hBZeYW34z4ElADhF0g5dOXdzSmmEUjpOKT0FfE9oVbM1mWnjlfzIjtzAylxGqDwO0xnDA9zBaayXz/G48iGphrhzfPFTy6NBNFnXXdT08gzpgmo7NgZIUKSCatHM78aSriX8jF4BTX7uagmzsZsBK5vZxWb2U/xilAIdp0f3JWTNVBd63LmStByhlsSu0SYjFC/7pZlNK/p4UtqbOHOpjvAvPBeAQ8zssy6fP3zvZBa88wJqzrmy4UG3cy5f8lHBHOBJWrYxOjwKWDrNkvYIcDoQ3vl2J16leYOk0V05t1IarZR+q5ReJARTFxE+sGe+x34NnAdsBCxqSTvA3rWjCIXT4gBsMeAZSUeXczVn12kjMh6Xah1wuoL5QHpL6leCMdxLnFo/ii2o5LVo+4rEeSgFIGmEpD8SCso9S2hVlpmV8y6h3eBwM9vLzJ5pp4jjMUAcKK5D/N5SJiTtTMihWT7aNB3Y0cz+Woo1zkppBeDKxg0PEcpmwgVmdleeLrMOsEb0eKyZvdbezs45V0wedDvn8iUfFcyJPuRe0mzzUEIZtK5KQZTO2hfYDRADgTtzDeqV0nJK6RSl9Drhaz8bWL/Zbp8C/yT0DB9tSTvJkvaCJdM9us3sVWBN0pWbqwgzNFdJ6pHj1+fKWykrl8ea9uouwbruaMnHZdHTBOszKePlw/N5LUnVknaV9ADhxtc/gKUzdplOeL9ZG1jVzC4wsx87Oq+ZzSCkMtdGm06WtE0+x94ZkioknQ7cQ3iXA3iP0A7swZKMKaU+hIZg4TbnW8AbALwM/D6Pl/I2Yc65suVBt3MuX8ZlPO7qWtHrgNnNth3b2o65iILdfQkppbAksCkQgt7z2jtWKUkpraKUUkrpPUIJoL+TnlmJvUcI7lcBlrOk/dGSNjbqU9z6uMwmEtqIZY7hYOC5rqxnd2WnlD26YyUPuiOXAqFmwSZsCEyLtu8paUBXTy5pJUnnELJI7iK048v8zPMkoQ3Y8Git9thcWxNGPa3/kLHpekmLtrV/oUkaRFiv/aeMzbcB6+cjfbtTY0pJhP/rFQD4gdD0MKzo3ivqWtH160hDCLU7AKYSvm7nnCsb3qfbOZcv+Uovx8ymSbqJprNe60laM/qg2/lzJ+2HaG3hk0AFmxLCn885WtILZnZTvG/0gXEtwpz4bjSdIcv0BqFY0V2WtE/a2Kf9cYWiWidJGktIw+wZXft1SXuZ2ZPtnsB1B6VsFxb7hgbqSFBZirZhMUvaRKV0E3AIVfRncZ7hazYlfN/vR+a67yxJ6k8IvA4lLtbV1LfANcC1ZvZF50ffxPmEG2bbA8MIy1W2KXYKd9RP/G7CrUQIXSB+D5yX682EPDuS8P8ZbrHcTpwbsL+Zfd3mUbk7mFCMD+AaM2t+09Y550rKZ7qdc/nyDel2X/moitxaemCXZ7sBLGnPEs8GiVBmKKxsvVzVWlkpbaiUziXcSHiVMJvVPOB+iVDpeElL2pqWtDM6G3A3GZvZzYSiTnFQMAR4TNJvfZ13t1fy9HJLWgPzo/XUA4EEpcykOL/x0bZkVgA/Itvv9ago2qaSridduDAz4J5PCPW2BUab2V/yGHDHy2EOIs6eCQH4yfk6fzYk7Ut4P4r/DX8EtjKzc0sZcCultQjtD4N7iXtI/N3MHs7bdaQEcHTGpubLk5xzruRU2hugzrkFiVIaR6gLPtWSNqiD3Ts+n/QiTddJzwVG5qMNjFJKED4G/gIIDb2+Alagjj6tZgE1EIov3QXcY0n7rqtjaHd8IVX0JkKwELsNONTMZrV+lCtnku4FdoqejjQr7PdQm+P4vZ6gN1sAcCl32Pe2ZynGAaCUHiMEqvAvPmE2y0YvrRvVO2j9OGkkoRDawcBSrezyNnAVcHMx2kZJ2hx4gnAbrx7YyMxeLvA1q4CzgN9kbB4L7JbnWeScKaVBhAyg0CfiJeARILSL2yqf7fIkbUcozQbwiJlt297+zjlXCj7T7ZzLpzjFfKBS6p+H8zWf7e4BHJKH80JYXnM9MBMIiaFrQ7OAu47wUfEIYDFL2uaWtH8XOuAGMLMphBsCf8/YvBfwsqS20txdeYtnuuuJazeXQgXvNT4e3GrAWkzpOgYbkTkLcETzHaOiaLtLeohwi+x0mgbc0whp6WsCq5vZRcXq02xmT5H+Wa0gtBEbUKjrSVoEeIymAffVwMZlEHAnCO+tIeD+BngcCN/z+xSgP70XUHPOlT0Pup1z+ZS3dd2ROwipkpmOllTRmZMppZ5KaWeldANhbvt2oE+TneoJJdJe5QZgmCVtW0vaFZa0iZ25ZleYWb2ZnQrsAsyINq8MvCZp+2KPx3VZHHSPN0tXsC+6Gt5tfDygSRuzUvgfcYvAtVgOEWdx7B23M5P0M0nnAd8R3hO2o+nnl8cJBRKHm9lxZvZGidKqU8AL0ePRwOWFWBIiaV3gdeIykGGV9FHAYWY2N9/X64Q/EArXwSzC/1g9DYSAO683m6J2jztET78mLtPmnHNlxoNu51w+jct4PLqrJzOzeWT2dg3G0DTlul1KqY9S2ksp3Q5MIrTS2R/InIlPV9CtJcxtP8TenNaY6lpSZvZfwjrVj6JNA4AHJP05Ws/oypyknoT1+VC6yuWBMiqY92NwKWsFWNIaiGe7q4FlibNIegOXSHoNeIfQP3tIxqFfE4LcMWa2lZndYmZzijXu1kQzuPuRrsS+B3BYPq8h6QjCMpf4Zsl4YBMzu6zEBdMAUEqbE/csN8JinJ8AONXMni7AJY8ipPQDXFbSm1nOOdcO/7DmnMunvPTqbuYyoPmHyePaO0Ap9VBKuymluwmB9q2ED8C9M3b7ibBmeldCSak7gJDAvidQSRVwh6TBefgauszMPiIE3ndHmwT8FbgnqtrsylvmjHJpg+7QPz4YRCXh+7+UbgCm0AAs3aSg2r6ECv6xeYSf5a0JwfZpZjauaKPMgpl9RaieHrtA0kpdPa+kGklXEN4Pq6PNzwFrFnrteLaU0nDC/0/4bPk0cTnIh4Az8349qQfpf+tawhp+55wrS94yzDmXT3kPus1snKQHiQueBdtKWjqz96xSqgA2I8w07UZcj7ypKcB/CfMvT1jS5mUcfxiwGrAMixEaAN3HKOBGSTsUuwVQa8xshqTdgf8jrB8VoTDXq5J2MbMPSjpA155yaBcWm0AtdVQ1aRs2pWSjOY0h/Ix3+ZZNmdrq55I3CeuVb45qHZQ1M7tb0iWEito9gdskrd3ZmXhJowgtCTOrsl8I/M7Mars84DxQSlWEQo/DAPiMMB8fMhIOKND75+6ksx/uNLMfCnAN55zLC5/pds7l07iMx6PzeN7WiuMcrZSklNaM2nvF5XoOpmnAPRG4lFAheRFL2qGWtIcyA24AS9pPhA9x4YPxGoRyTCGV/Y95/Fq6xIIzCOOaGm1elhB47166kbkOlLxdWMySZsyOaiUMAHrmLSsla5IGSzpS0rPAV7zLpo3fzU3daWZrmNm/u0PAneG30Lh2fiXg3M6cRNJmhPXbccA9B/iVmf2mXALuyN+BjQCYTsjHMWqBPQtYzM4LqDnnug0Pup1z+TSe9ProfH6Qf4R032oYBGzOMRgfEVrknAgslrH/DOA6YBtghCXtaEvaE5Zsv2quJe0d4PDGDdsT5gDhr5I2yscXki9m9ijhtsBb0abehHT4f3a20JwrqLIJugGYF40hASzBasW4pKRekvaSdB+hr/WlwMZNdloS+CWQaHwf2UZSb7qZaFZ7L+KbeHCUpN2yPT7qP34i4Ubi0GjzOGADM7sxn2PtKqW0M3Fv8nrCQp3ZQJiJf6Ug15RWJ91O8h3SBeycc64sedDtnMubqCjSV9HTMUrlp0CTmTUwjBtYl1CW6HhgU3qgJoXOagl9t/cizGgfZEl7tKNAu8W1knYTcAEQGv/sCfQmQWgBVBbru2Nm9iWwIZD5IfwPwP8kDWn9KFciIzMelz7onp+xrnsgKxbqMpIqJW0j6XrgB8Ka3x2BqozdPgb+wg7swAHA6sCKjcFqX0L1/m7HzD4kvFvFrpS0REfHRTcZbiLMjsc30B4lrN9+K9/j7AqlNAa4tnHDI8SLJ+4ALirgpY/OeHxxORSRc8659viabudcvo0DliG04hoEdDq1UCn1A3YG9uNotqS1EN54BnETcJcl85Z+ejLho/8m9CME3tcxkgaulrRzOX3AM7PZkg4AXiP9IX1LYKykXc3sjZIO0MXKaU03NGS0Deuf317dUTX0dQj1FfYiXufb1HjgFuBm4M34Z0opPQtswtr0z+gmfhBNbyx1J1cRfh73IiTz3yJp07ZSwyUtReiw8LOMzf8A/lJulbmjddy3EHeCeA94FYAPgEML9T4Z9T/fL3o6g3CDwjnnypoH3c65fGteTC2noFspVRPWK+9HKBLWI7yQsdMEQkLhe8BPnGJmL3ZhvC1Y0mqV0p7AG8BwliDUS/4fOxFmri7I5/W6Kvpwe6GktwgzTMOAJYAXJB1pZteXcnwOSAfdtYQZ39LqQTrtt0+TpRmdJmk5ws/tvtBqID+dUBDsZuCZNoLIc4FNWBzoyxxm0BPYQtLiZvZ1PsZZTGZmko4k3IQYQ0iJPg34U/N9JW1H+LcZEG2aARxoZvcUZbC5+zuwLhDK8N0PhK4Qu5jZjAJe9wCgV/T4OjObWcBrOedcXnh6uXMu33KuYK6UEkppE6V0GSGkvpcwv9wjY7dxTOIa/kNYCfoicf/XdtuHdZYl7QdCFfQwI7UesAoAZ0lasxDX7Coze5ZQAi4OqHoA10m6SFJ120e6IoiD7u/KoRI+w3i78XG/zrcMkzRc0kmSXif0kf8zTQPueYRuAbsCi5rZYWb2ZDuztg8AnyNgLXrGlwF+1dkxlpqZTQf2AeKlLn+UtEX8uqSEpD8DD5IOuD8G1inXgFspbUfmOu47Cf/TocjbJ20e2NXrhiyKzAJqlxTqWs45l08edDvn8m1cxuPRbe0UVR5fRSmdGR3zDHAETXsG/0ioSrshsCT/4VAm8XqzU+0uaZE8jLsFS9rLZAb1OwKLUkVoAdRaS7KSM7PvgE2ByzM2Hwc8IWnR0oxq4Rat0Y2/r0u/nhuwpE1hDiHw7U/PKJjJiqQBkg6R9AQhVf4cws2extMDTwCHAIuY2e5mdo+Zzc1iXPXEmSSrNnnpoFzGWG6igmLx7LYIN8MGSupPSCf/K+l8nv8SAu6Pij7QLET9uNPZM48RFgvA38zsvgJffgtguejx094m0TnXXXjQ7ZzLt3ZnupXSaKX0R0I7nbeB39N0vetsQorlDsBwS9qxlrQXLRl6ZQH/aXbKKjIrjuffFYR1meFKewE9WQq4tFyDADObZ2ZHEv5d4irQGwFvSFq/7SNdgWQWUSv9eu7YDEIKcH9gxSY/gy1I6iFpV0l3EbJRriIEQJk/A68DJwEjzWxLM7smmuXN1TXAdAYAo4mzApYGNujEucrJ2YSbERC+J24grILeKdpmwCnAbmb2U/GH1zGlVEFYXx8KNX4MvAzAQ4S0+ULzNmHOuW7Jg27nXL6Ny3g8BkApDVFKRyul5wlB+T8IvWtj9YQPbfsBwyxp+0W9tFsrNnQbtOjoe5SkgtSosKQZYab4NSDMV+4GiH0IM3lly8yuJLRkigO9xYBnJB1VrjcMFlDl1S4sNpNJjY8Xo8XNGEkVkraQdBUh0I7TxGsydvucMEu7vJmtZWbnmdn4rgzLkjaTcLMLVm/yOeWgrpy31KJlBQcB06JNO0BjB4apwHZmdkZZLD9o2ynA5kBY3nMvEL4H9i/0uCWNJDSUg9By7r+FvJ5zzuWTB93OuXybSNylFVZRSg8QPiDFaeKZXgSOBRazpO1gSbvZkjarvZOb2WzCTFimEaQ/jOWdJW0uIdQOQcrSxB87L5K0UpsHlgEze5XQz/uZaFMVYR3kVZJ6tHmgy6fyDLpnkS5M1jukh0f9odeQdA7wNek08f4ZR04ELiQU0VrGzJJm9nGeR3cRUM8KQBVxFey9JPVq55ju4Hvg2WbbPgDWMrNHSjCerCmlTYhnsxsI67hnM5tQOK35jdBCOJx0C7XL26oA75xz5ciDbudc3iilSkLl8fjD0HDCbE7mLPQHhLWNS1rSNrSkXWxJm0RuLm1l27G5jjcXlrRvCMnlYR3sJsDy9CSs7y7rQMDMJgJbAedlbD4YeE7S4qUZ1UKlPNPLZ5EOlKtZJyrm9SHpNPHhGXvPJKzj3QYYYWa/MbNXC9UWypL2NXAX1cBKjSns3bZnN4CkIcD/SKeTxybRNEOo7CilIYRlP+Fz49MQ3bI51Mzebeu4vF1fqiLU/IDwHnxFoa/pnHP55EG3c67LlNJySumfhFm8h2g6KwYh0DgLWA1Y2ZL2D0val3SSmX0KPNps8+aSlm1t/3yxpD1FWIMe7AIMYSXg/EJeNx/MrNbMTiKk8M+JNq8FvC5p89KNbKFQnjPd3/NpxrPNCGniy2VsqwXuI+q1bWYHmtmjZlZHcZwLhHeNtAOLdO28krQGMJbQsxtC4BjPDm8KnFiKcWVDKYmQXTQCCAuEngPgHDO7tUjD2BmIC0H+NyoY6Zxz3YYKdJPaObeAU0p9gD2AQ2mZNp7pGOAyS+Z3vZ+knYhXFKadZWa/b23/vF03fAC9GdgbCHNUVwLz2NvMbivktfNF0iqEislLRpsaCDcTzi3UzOXCTNLDhAwQCNW8J5ZwLIMJM617kWBL/kQFFYTO4enmS88QvsfvNLMpJRloRCm9SAPrcxFxiGrAEmZWPjcvOiDpV4RuAvFyjomE984KQvq+CAUP1zazd0oyyHYopROIs2RmEfKMZvAUsHWxbsBIeopwYwjg52b2ZDGu65xz+eIz3c65rEVtvjZQSlcS1iZeTdOAu44QzGWuuZ6e74A78iBkrEkNDip0P+qosNphwHsADCXMwYjLJS3Z9pHlI/pgvzYh1RXC74KzgVui9lYuv+L08vlArkspukzSolHxvMcI4fXVwDY0UMHkaKchQCV/BBY3s83M7PJSB9yR80iQ2T6s2/TsjgrRnUVIy48D7peBNczsWTN7ing2H6qBG8utzoJSWgv4V+OGe4AZfAPsVcSAe0XSAffHwFPFuK5zzuWTB93OuQ4ppUWV0u8J6z1fIMxu98nY5QPgt8AIS9quhIA41qJtWD6YWT1wWbPNQylgQbXGa4dib7tgURXiFYAN6UdY313QoD9fooDqF8DfMzbvBbwoaYnSjGqBFaeXf1usTAJJoyT9RtKzhC7KlxBSmysydhvHj1GNggrgVP5bhjPI9wBfdbee3VH/7fuB32VsvhzYrFlq9J8I7RMBfgacXpwRdkwp9QNuJRRfDO/8nzEP2NUs5zocXXF8xuNLPBvHOdcdedDtnGuVUqpSSr9USvcS1mSfSdP1njMIHyLXJazTPteSjWmzmeu1RxdwmFeRLtoWO6K1HfPNkvYZYj8sqqz8c2Ap1gLOKMb188HM6s3sVMLq9BnR5lWA1yRtVLqRLTgk9SVd46CgAa2kpST9XtIrhCyQ8wkt4zID1C8JWQ3rA0syjfRsdgMrFnJ8nWFJqwMuYiCZ7yTLQMsWZ+VC0jKEGe3tok31wDFmdqSZzcvcN3q+HyELAuCkcqixEC2juQxYCgi/AUKH8aPNbGzRxiENAg6Ins6gZecK55zrFjzods41oZSWV0r/IgQI/yWs/8ycHXuG8CFoUUvakZa0V6OU60yZQXdBZroBzOwHQuOaTFsWK83bkvYQilroCNgdGMBJknYoxvXzxcz+C6wDfBZtGgo8KenQkg1qwVHQImqSVpT0Z0lvEf7/ziT8X2b6iJDRsAawlJmdbGYvm5kxmQmNe80PbcPK0JXAzGYF1Q4qxUA6Imkr4FVg+WjTFGArM7ukrWOi6t9/jE8BXCdpQCHHmYVDiOtWzCW8yzZwqZkVO+g9HOgZPb7GzH4q8vWdcy4vPOh2zqGU+iqlQ5XSi4QU8pOBRTJ2+Y7woX0ZS9pmlrQbLGmzWztXZBoQfzgaXYAhZ/p3K9sOK/A1M51OSCMNHw33Bqq4TtLI9g4qN2b2ESFr4fFoUxVwpaTzJVW2faTrwGIZj8d39WRRH+3VJP1N0gfA+4Sq46s22/Vt4C/ASma2gpmdamZvtkjNncRXjY8bmoW1ZcKSNh24OurZHdtLUs82Dyqy6P/leOBhYEC0+X1CcbRs1iCfD8TFwUYB/8n3GLOllFbCuKhxw33ANF4CflPUcYQ2YcdFTw0yxuScc92MB93OLaSiomgbKaWrCUXRrqRpymYtYX5je2AJS9qplrTPWjlVC9HMdzzbvbhSqmhv/y56CXit2bZDog9sBRcVifsVFrVfWhTYkcHATd0tWI3WeW9H0w+3vwEekjSwNKPq9hbNePx9Z04gKSFpXUn/IsxmvwmcSqgmkOlV4A/AMma2mpn9zcw+aPfk3/NptKobKlqcr5xcQA3GSo3P+xFKGJZcVMfhCuAC0llB9wMbmNkX2ZzDzBoIs/fTok37StonvyPtmFLqBdyGotnl14AP+AHY3czmt3dsAexCugjh/WbZ/f5xzrly5EG3cwsZpbSYUvoDIeX0OeBgILNi9XuEnrHDLWl7WNIetqTVt3KqjsRBdxVxf9cCiGbuLmi2eRFCkbCisKRNR+yCMQsIq6LXZRPgz8UaQ76YWZ2ZHU9YGx+vl98KeEXS8m0f6dqQmTEyoc29mokqX28i6QLgK8Ia4ZNJt3mDMPv3POHndQkzW9fM/pVTcFLL+MYK5lUsrlR53iiypH0B/LfcUswlDSOsds5cinEGsHOuqdBREbtjMjZdImlUW/sXyPkQ3dqYADxCHSHg7nKWRieckPG4+Xu8c851Kx50O7cQiIqi7ayU7iesK/0nsGzGLj8Ruq+uDaxiSTvfkvZjFy87LuNxoddY30HLWcSiFFSLWdLeRxzcuGFrYAn+XA5FkTrDzK4glIeLvw+WAV6WtG3bR7lWZM50txt0S6qStJWkSwmp6M8QKjdnLlWoJwR5xwDDzWxjMzvfzJq3z8vW941NzBJUEhfOKk/nsTjp5G3YqpTLOCStRpgLjosOzgX2M7NTopnrnJnZLcAt0dP+hPXdRfmsppT2IqyhDmXd7gTqONHMni/G9ZuMRVqHdObVu3ibMOdcN+dBt3MLMKW0olI6m1B79h7C7G9mqvdTwP7AYpa0oy1pY1spitZZn2Y8XiZP52xVlPbYfA3kNsVufWVJu4O4p20FsAeiH7dEs2Hdjpk9R7gR8060qT/woKSTyr1lUxlpN+iWVCPpF5KuiV5/FDgSyPyeqQUeIsymLmpmW5rZJWaW9cx5OyY06xy+Uhv7lYPnSfB6xmx3yXp2S9qN0ERr8WjTeGATM7s5D6c/lvCeDbA5TWd8C0IpLYlxeeOGh4AfuZ7SrS3PXD9+vrcJc851dx50O7eAUUr9lNLhSuklQiGf39L0A/y3wN+ApSxpW1jSbuqgKFpnfZLxuKBBd+RywkxTTDRN+SyWP2FRc50+wB4sQiXXF2u2Kt/MbBywIaGSPYTfG+cAV0uqKdGwupPMoPsHAEm9JO0m6WZgEmH970HAoIx95xL+zfcHhprZDmZ2tVmXM1Caax50l13bsFh0Q/C8UvbsjtbXJwnzwL2iza8Ca5lZ89oSnWJmU4EDMzadIeln+Th3a5RSNcZtiH5AuMX2Fm8CR5Ui2JU0AtgzevojkI8bGc45V1Ld8kOgc66pqCjaJkrpWkKa9eXAehm7zAduB7YFRlvS/hKtkSykzJnuZdvcK0/MbBJwY7PNhxa7mJklrQ6xNw3RTNUoYFu2Idz86JbMbCawG6FSe+wgQluxRVo9yMXioHs+sJ2kuwiBxJ3APkDfjH1nArcRAo6hZraLmd1kZtMLOL4JTGzyvJxnugHuYCDjSeewLEuoul9wknoT/n9Oy9h8I7CpmXWqSF5bzOxJ4NzoaTWhMGOhbnKdgVgLgMnAg0wBdjWzOQW6XkeOAeL37UvNbG57OzvnXHcgz9hxrvtSSsMI/VQPBZZuZZd3gKuAmyxpk1t5vZBjSwCzgRrgQ0tawWfQotmgd5pt3snM7i/0tVuMJaU1aeAlElGTo/uo5w02MrOXiz2WfJK0F3AN6d653xL+jd8s3ajKk6TRhPWofdrZbRqhKdNdwKPFDjAkJahgLqdQFS08eceS1rz9WFlRSn/kTf7BvY2bLjOzowp6TWlx4F5oTG434P+Aswo1GyypB2EWPZ7lPtvMTs7rNVLaAXgAgDrgKhr4nm3M7PF2DyyQqA3cN8BgwrKK0SUq4uacc3nlQbdz3YxSErABYTZgDzI71wbTgZuAq4E38rhGO2dK6V1gZcIsX69OVkHP7ZrS44QCYLEHzGzHQl+31bGkdCBwLRA+0F7HeL5hJTObVorx5IukNQmpz3ERqznAgWZ2R8kGVQairIr1CbUTdqDtWeNJhH+/u4CnStCKqQlJ33AsIxkKhJ/V3pa0ulKOqT1KaRDz+Iaz6RXV1/+JsNa9IDOzkjYk1MQYGm2aAexjZg8W4nrNrr0KoVhbNSHQ/3mWfb87PndKI2jgXRKEdoAPA6/wBzP7Vz7O36kxSYcR2q8B3GRm+5dqLM45l0+eXu5cN6GU+iilI4G3CG2C9qVpwP1EtG0xS9qxlrTXSxlwR+IU82rSBYcK7fxmz7cvVYVjS9p1NHAJEJIld2c4/bmhuxchM7PXCQXW4ln7nsDtkk7rrmvXO0vSIEn7RuuzJwLPAr+nZcA9l1CUagtC1fEjzOyRUgfckcx13dUUvttAl1jSplDDdRmrz/sBvyzEtSQdQig4GQfcnwPrFSPgBjCzd4BT4uEQqpkP6Op5lVIFDdzaGHB/BLzCncBZXT13p8cU3hdPyNh0fmlG4pxz+bdQfThyrjtSSisopQuB7whtvVbJeHkycCahKNqWlrRbLFmydXitySymVvB13ZGHgMw+xQlCCn5pJDiBWsYCofb3zvyCyia9eLulqHL25sD1GZuThOC7d+tHdX8KVpb0B0nPEWatbyKszx6YsasRUstj15vZcWb2lFnZzSJ3t3XdABc069l9cOu7dY6kSknnEZbnxDc3nwDWMbMP8nmtLJxHumXWKPJRUdz4M4mo1dl04D4+Bg4pcZXwLUh/771gZmNLOBbnnMsrD7qdK0NRX+3dldKTwAfAryGqLBu8DBwAjLSk/V8RiqJ1VrErmBP1x72g2ebDJFW0tn/Bx5O0+VTxS2qZCsAY4OdcIKms181mI1p/fBBwMiHIhFBw7YVit2srJEk9JG0n6d/Al4Rg+p+E/syZv0d/IhQsPBBYhLDmN5aP9l6F0m0qmMcsaR+zBA8269k9Ih/nljQQeJCms64XAduZ2ZR8XCMX0XvagYTwGGBfSXt39nxKaTPgLwA0AHcxi9nsZGYzujbSLjsh43Hz93DnnOvWPOh2rowopRFK6TTgK+AOwkxibA5wJbCmJW19S9oNliz7qq5FrWCe4TpCABQbBWxTxOs3YUkbTxU70kADAOtTweo8JKm9AlvdggVnE9Yxx//mqwKvSdqodCPrGkkjJB0h6V5CRslDhP7JzW8mfExoobYFMMTM9jKz66Nq+u326C4j3alXd1qiSfuwvPTslrQ88AqwdbSpDjjCzI43s9qunr+zzOwbaJIhc4mkUbmeRykNpY47EWGJy1PA1+xrZp+0f2RhSVqG8B4CoZDaPSUcjnPO5Z0H3c6VWNTua3OldCch2E4Ci2Xs8glhBmC4Je1wS9obJRhmZ5UivZxoxubKZpsPL9b1W2NJe4F6TmrcsB3DGd2ixVm3ZWYPEdrUxan9QwktxUrRKz1nUf/ldSX9TdKbhKrslwE7ke7HDKGi8uOEn8llzGx5M/tdlDbePCjrLkH390yG6JYQdIOZ7siTrMxHjc+qOKor9RIkbUvIIoqzcn4kFC67ou2jisfMbgZujZ4OAK7NpYaCUkowj9uoZDAAXwAv8Dczuy/fY+2EX2c8vqgMl2A451yXeNDtXIkopf5K6deE9PEnCWm5cQp0A+FO/5bA8pa0CyzZLSteTyQ9+1mU9PIM/yYzjIAdJQ0v8hiaquJCZnE3EMpV7cQvNVRHlnRMeWRmHxJ6Jj8RbaoCrpR0XrH7pWdDUj9Ju0u6lhAUvwycCs1WC8MPhDZpuwGDzWwrM7vAzD6jfd0l6J5APWE+P1heqdIsx8iFJc0YypmNuQe1LAGsk+t5onX6JxFSyvtHm98B1jazZ/Mz2rw5hnBDCEJ2xW+yPnI+J1MTZU/NBO7jCRqa9BwviagwXFx3YzYtb5g651y350G3c0WmlFZVSpcB44ELgeUzXv4B+BuwhCVtV0vaE2VQgbzTorHHKeajlVJN0a5t9iWhLVOsgjwXW8qVJc3ozf7MYhwAg4Bt+I9qtHy7B3Yj0ZrX7QhrYGMnAA9Ga2VLStKykk6U9AQhzLyDsF52aLNdXwf+SgjihpvZIWZ2d47rXhfJeFzeQTeQkWJeAyxVorHk6hZ+lrGUpFeTGdMORb2wryEsEYg/E90DbGhm4/I0xrwxs6mEOgqxMySt3NFxSmodKjmjccN9jGcae0TrxUvtECAuvnhd9DU659wCxYNu54pAKdUopf2U0guEll9H0DRl9RlgL2BxS9pfLGnftnKa7ipOMU9Q/FZE5zd7flipW1pZ0ubQm82YxzwAlqGCzXk6+vC/QDCzWjM7nvB9HqeJbg28LGm5Yo5FUrWkn0ez7Z8Q1mCfS5glzJx9n0W4SXM4MMLM1jKzpJm91oXAJHOm+4dOnqMYmgfd0E1SzC1p81iOCxvri89nj2x/liQtSljVfGDG5r8Bu5vZzDwPNW/M7AlCRXMIN0huktq+oamU+jOfh0hE67ifp5ZP2KYcgtuowGXmjZILSzUW55wrJA+6nSsgpbSEUvoHoTDMjcAGGS/PILR+WdmStpkl7XZLlkXP3nwregXzDM8Db2Y8H01I2S8pS9pXzGP3xuT39VmEdbizpIMqgGgt7M8Ja2MhrOt/RVJBi9pJWkTSQZLujK7duAa72a5fEmbktyGkje9iZlea2fg8DSUOun8ys9l5OmchhBsC3a9tWNCX81khurlTRzUD2b+jQyStAbxGqEMAoVDlXmb2lzKZ/e3IKcB70eNVCDcLWlBK4ifuoUe0jvsb4DkOMrP3Wtu/BHYivC8D/M/MPmpnX+ec67Y86HYuz5RSQiltq5TuI3yo/yNNU1ffI6zLG2FJO86S9n4pxllEpapgTtRz9vxmm48o5hjaYufYA/zYOFsFW7CDfqZjSzikgojWxK5Numd1f+AhSSd1pehVJkm9o5Ze50p6hzBzG6/B7puxaz3wLPB7wkzuUlFV6kfNbF4+xtJMHHSX8yw3ZjYLmNEdZ7oBLGmTGZOxlKSySau2FiTtRbghNzLa9C2wkZndXqgx5lvUrm9/IL5R+ztJm7XYcQq/o1+0jnsO8BBX2Fy7uTijzMoJGY/PL9EYnHOu4Dzodi5PlNJgpfQ7wszuw8COQBxU1BKqzm4CrGJJu8SSJe+JWiwlqWCe4TaaBj2/lLRIWzsX1TB+y0RCNfoewKZcqGXUbYKdbEVrYzcE7o02JQhraK9uLy22LZIqJa0n6VRJzwBTCS29TgR+1mz3KYQsk32AoWa2qZmdZWYfRjdlCkJSL6Bf9LSc13PHJjSrYN59ZroBlue3jSXQfmQpLa8WWTVRhfq/Ed6Le0abXwLWMutWXSEAMLO3gT9FTwVcHxUlCxt+p9Xpxz8bD3iUd/m+SduxkpK0OuF3IsCHwKMlHI5zzhWUB93OdZFSWlspXQt8B5xF0wJE3xKqIS9uSdvHkvZcdy6M1kmZM93FTi8nmsG8OGNTJU0LEZWMJc3oy2ZMiwpBDSXBujyrYarq4NBuJypAtivw94zNBxHairV7EySqLr2cpGMl3UNIGX+JkFK7CZD572XAWOAMYCNgmJn9ysxuLfIa1u5SRC0WKphPaXzeLSqYx+yf9jVjeDs8ASo5N/N1SX2Auwjvx7Frgc3NrKwzETpwLvB09HgUoWsDSqk3xhNURp/zXmcGb/LzMmvFlVl5/cJC3gRzzrlS86DbuU5QSr2U0sFK6TXgVUIhnswZu8eAnYExlrS/W9K6w4fugohancWJq6WY6Qa4lHQaJsARpS6oFrN/2gymsQXzCB84l2Ew6/NIiYdVEGbWYGanAnsDc6PNGwCvRbNejaJ12ftKuprQv/4jQkCxM+m2TrHPCf/HuwNDzGxtMzvFzF4ws/rCfUXt6i7twmJhjOl13TUUv/Bh1wzg942PJ7CtTghZFJLGAC8SvncgzOefBBxSoGUFRROtPz8QmB5t2k/SXoznIfoRugVMwHiebc1sUlvnKbboRts+0dOpwA0lHI5zzhVc2fVNda6cKaURwHHAkUDz9kfTCOtIL7WkfYLL9AlhXftwpdTHksWtDGxmEyXdRLpl2JLAZoT+6CVn19jr2ksnsyJnA7Aam2s7/d4etn+VeGgFYWa3SfqMkG4+gjBD97yk8whpv1sSikO1ZTKhF/hjwBNRe7hy0z2D7pbruj9tZd+yZE/Zo1pEk5nIYCZTyWecKulx4E5gSLTbdGBvM/tf6UaaX2b2taRjCcsoYBWuYXiUPj8feIY/2RR7sXQjbNVRQHX0+PKoroBzzi2wymKmx7lyp5RWV0o3AOOA/6NpwP0GcCihMNpJHnC3KvPfZOkSjeGCZs/LoqBazG6zc/iYx4DwzrwK/9QvtXZpR1VQbxP+D76JnvcirE89iZYB91xCgP0HYA1CyvheUaXxcgy4YcEIurvXum6A3lza+PgtTiJUro8D7k+AdRekgDvDzcBtDAJ2aFyvDi/whH1gZ7R5VAlEdRziteX1hC4ezjm3QPOZbufaoJQSwA6EIGCzZi/HhdH+Dby2EK7TzlXzCuZvFXsAZvZ2VHRr02jTbpKGllPKJTPZnm8YzyiG0gsxmid1lEbYpfZTqYfWVVGl8mUIs9hbEvpkN08Tz/QGobDSY8CLUbXm7qS7Bd3fA92yV3cTX3ImlfyROhJ8R6+MVx4lzHCXvDd1IZiZaUmdxNbsSU1UwPM9ZvIM25d4aK3ZGxgWPb7LzL5pb2fnnFsQeNDtXDNKqRdhjdwJtFyDPBm4BLjYkvZ9kYfWnZW6gnnsPNJBdyVwAKGKdlmw+6xOm2h9evMRg6hkEH2YwEtK6WeW7Ba9g5uQNIzQp3tLYCtCGnlbJkPUSzhIAJeY2deFG2FBdbegO4zxR6ABI4HojjPdUI0xnabZSOcBvy+zImL5tx73s1gUcP8I3EcV4f22XHpyxzffTsjYdH5pRuKcc8Xl6eXORZTSYkrpdEK668U0DQ4/AY4mVCH/swfcOSuXoPsB0unMAMfmq1d0vtiz9jkvc0hjmbFFWZEJXFXSQWVJUi9J20o6W9JbhFZtNwOH0DLgngzcTkgxX9LMhhAyS+JZ/dWAsZI2LMbYC6B7Bt31wKzGolzdqoK5pBWBV6jPCLiHAadx/4IecGsrnc9yrAFAHWEV+3xqgJs605avgDYm/GwDvAa8XLqhOOdc8XjQ7RZ6SmnVqOXXV4Q1pYMyXn6K0G97BUvapZa02SUY4oLg84zHRW8bFosqWWfObI8hfAgsK/aK3cDT3NTYM3lRDtJJOrjdg0pAUo2kDSX9SdJThCrEDwO/BVZttnvmuuw1Sa/LviJel21mDwHrk/5+GQo8JemQInw5+Ra3DDOaJ22Xp/SNgcnMiR71IPyMlD1JvyAEcHHLxrDkZxIwlb+UaFhFoVW1M2tktN96j9uZwPvRs1WA00oxrjackPH4fG8T5pxbWMjf79zCKFqvvS1hvfbPm71cB9wCnGdJe7PYY1tQKaWvCbOdUyxpgzvav2DjkPoRAoy42NAdZrZnqcbTFkkVbMHHbBIFEXXUI9axv9obJRxTX0KLr42jP+vStFVeJgNeJxSyehx4Idt12ZIGE2bBt8jYfD5wcneZsZQ0DlgCmGRmwzrYveQkVRJqXYvtGM+6DI9e2tmSdm8Jh9auKFPl94S+7HHWyluI5zGOA8LChg1Z05Kl+9kpFA3QGHbnY0ZFveq/5QtGsjSnsQphJrmK0CJtfTN7tYRDjVu3fU74fxoPjDGz+e0f5ZxzCwaf6XYLFaXUUykdAbwPPEjTgHsq4YPbaEvaAR5w511cTG2QUipZ0G1mP0GTdO1dJA1qa/9SMbN6nmUz3on6i1dSQT2PKaVFOzg0byQNk7SbpPMlvU5oi/c/QkbIJrQMuL8ALgP2AIZG/bL/aGZP5FIIzcwmE26K/Ttj8wnAg5IGdPbrKZYoEIz/n7pDajnRzYwwI/99YysnKONialHa9LXAP0kH3HcAG2EZ3QreAiyjh/cCQlJv1uXFxoB7JvOA9SxpZmZvA3+Ndk0A10rqUaKhxo4j/f90sQfczrmFiQfdbqGglBZVSn8FviYEBctnvPwZcCwwypJ2iiXtu1KMcSGQua67ZCnmkfMzHlcSCueVHau1b3mEAxtXoVcziFoeVCr/azQVjJF0gKQrJH1MWJN9J/AbQquu5r8zvgCuAw4DljKzpczsKDO7MwqcO83Mas3s18CRhOwTgK2BVySV+vunI/1J35DoFkF3JIz1+yZV5cuymFqUDfEooRhiLAnsZWazzOwzROhNPQkYzx5KqVTtCvNOkliO+1kvurnTAPzEznZFk24MZxK6AACsQAnTzKMsmcOip3OBy0s1FuecKwUPut0CTSmtrJSuJqzX/jPpfq0AzwC/BJazpF1sSZtVijEuRMqlmBpm9jnwZMamk8qtoFrMZtqt3MOtjaWtqliDBi5TqmvjlZSQ9DNJx0i6hVBgLjOIbv5/ZMC7hJ66ewMjoyD7IDO7ysy+6Mp42mJmlxOqn8dB/LLAy5LKbi1+hsxshB9KNorchaB7MlVYY0WBspvpjm66vETItoAQxO1hZn9tskbYuKbx8VskgN8VcZiF1ZfT2ZbNGz/FTeUiu6xp/3EzqwUOIrS4BDhZ0rpFHGWmg4B+0eMby6pVo3POFYEH3W6Bo5SklLZRSo8QgoSDoTFdsg64CVjLkraZJe2+7tiKqZtq3qu71P6W8XgkYa1yeZrCEdzBt40fnRMcCJyYyykkVUtaX9LvJd1PaCr0DukgekSzQ2oJgc2/CMUEB5vZKmZ2nJndZla8jBAzewZYGxqLQw0CHpe0f7HGkKPuVrk8FsZaB9QTt2pboZwqmEvahFAwLc52+AHY1MzubGX3OyAqCvcuUMfBSmmxYoyzkCTtxs85pbFG+yw+ZDAntbavmb0LpKKnJUkzl5QAjs/YdGExr++cc+XAg263wFBKPZTSoYSepP8jpKLGphFS7cZY0va3pL1egiEu7MopvRxCpkNm+7BTSjWQjpjZDL5ld/5L+gaRcZZS2ratYyT1kbSlpJSkJwk/Ay8Sfg5+QdM+xgCzCNXF/wJsDgwwsw3M7A9m9oCZTc3vV5WbqML5htEYIdxIu0HSaWWYpdC9g26A2XwbPeoBjC7FYJqLbrI8TrrDxHvAum0VCDOz6cDdQJgL/5hqyKjy3Q1JWo2Vuamx6VYd8+jNDpZst8DgmYSihhCWVqXa2bcQtgfi1P4nohsBzjm3UPGg23V7SmmYUkoS1mtfSdN0yC+AXxPWa/+fJe3b1s7hiuJLQhdgKIOZ7igN9fSMTdtIah6Ilg0ze4X3SfJMtEEkMG5VSssBSBoiaWdJ50h6lRBkZwbRPZud8kfgv4T2XmsTguytzexvZva0Wfm1x4uCqB1ouh40CVxfZr2Iu2vQ/X3joyn8mLG9pOu6o3oDKeAGiIqGhfXcG5nZVx0cfl3jo3cAOFop9W9r53ImaRgDeIAdMgoYVnC4JUPLvbZERfIOAuLCZb+TtF7BBtrSCRmPzy/idZ1zrmx40O26LaW0olK6ghBsn0bo6Rt7HtgVWNaS9m9L2swSDNFlsKTVEgJvgGW6uiY5T66Hxp7EFYSCeuXsDJ7mBT6Mnon+zOAV9dZHhHJR9xDa4K1N+HoyfQXcSChMtiKhT/YuZnaumY3tLq24onWqRwEnE/dihv2Bx6LiWuWguwbd6bGOJ/M9s2TruqNU6BuhSa/tS4EdopswHXmS+Ov6FJhDP8L3T7ciqQZxNzszovH2WT23I27M5ngze4+maebXFCPNXNLKpLuEfAY8VOhrOudcOfKg23Ur0XrtrZTSw4T1nYeRrhJcD9wKrGtJ29iSdo8lrb6tc7mSiFPMewMlX1sZtbG6LmPT8WWYqoykGknrAEdjTOIerLE8V1/6syvLtfJu/j4hONkPWNzMRpvZr8zscjP7sEnBqW7GgrOB3UnfNNkYeKlMKpt3/6D7SzJvwpRkplvSUEI6+b7RJiNkZhyT7U0iM4t/L4QK3x8AcKJSJW+flbXoPeliNmDDxkT/Br6jgiMtmdPP8b+AsdHj5Um3FCukzHT+C828hopzbuHkQbfrFpRStVI6CHibkFaYuZb1J+BsYElL2j6WbH19nysLZVPBPEOK9IzpUELwVjJRVfHlo9Zd/45SxWcArwAXATszH3ELYRU2hNWSv2ACcA6hIv8QM1vZzI42s5vN7JvWrtXdmdndwKakK4QvQ6hsvknbRxVF9w+6v6IKSlfBXNJyhIJpG0abZgO7RpkZud4wurnxUVhNvAhl2iawDcezGIewRfTMMBLsZ0mblstJWkkz/20h08wlDSFkoUD4PX1toa7lnHPlzoNuV9aUUi+ldDzwOXAN8LOMl8cR1oqNtKSdbEn7uuUZXJkptwrmmNkEQpXu2D+KeX1Jw6O12P+Q9Djw/+ydZZgcZdaG72eiECRACBLcneDu7u6Luyy6LAssVApd5MPdXRaHxd0dgrtrSIAgCdE534/zVqq7p8dbZ+q+rrmmy9+e6a56jz3nV+ADPAJ/IJ4q3qvgsNGMZBj/Ja2SX5IZGcL7ZnZvZ3tk1xNm9iqwHC6qBbWhbJ4Y3ePx/2e9kBrd4xiI33fBFcwrNl+QtDr+nZwrrPoBWNXM7u7gKV8jufd8iZt/cGQtqbI3h6R16cVZbEVaMCJOs8iebum45jCz90j7dSdq5oV6D6ViH1yID+BKM/ujTNfJyMjIqHkyozujJlGs/op1DD5FOhdv6ZTwAp5WOo9Fdq5F2YO8jqg1BfOEf+a8XlHSVM3u2QkkTS1pLUn/knSnpG+B7/Ba7KPx2sfCaxv5RviyQH9gAb7i64IKyUsUayW6GUFMa2U8CwbcSVFNZfPE6B5WZ+m0vwFjw+sZSVu0TQbMWYkBSNoN/z8mooZv4wrlHe44ESLjabTb3TNzA1t19JyVQNJ8wK2sSwMDJq1+HRcP7AxnAK+G1/NThjRzSb1JNTIa8SydjIyMjG5LZnRn1BRBifwUXPTpZPLF0e4FVrTIVrLI7sjqteuSWkwvx8yeJ1VuFvk9vDtEqMNeRtKBkq6V9AGuKP4YcCqwBU17Y0NTI3waM1vIzHYzs4vM7FUzG29mI4G/8TqNpAUVvYA7FWu2zo6/3shRNr80Z3WEG98VUzaX1IP0vlVPqeWJcZqMeUaSCminrCnmoaziZDyjKcnseBBXKC9FecTNk16lDav+VSOCjk2Q1B+4j/npzzJhpTEa2MkiG9f8ka3TTJr5Cp05ZxG2BmYOr+8JLf8yMjIyui2Z0Z1REyjWrIp1Lh7ZPpo02teIRygWs8g2s8hebOYUGfXBt3jHXKghoztwZs7r3dpzYDAY5pe0s6TzJb2MJ7G+AlwA7IILFxXyO/A4qRE+i5nNYmZbmtl/zOyJlhSazexZ4FQewpvjOQOBexSrX3veQ1cgGBP7A/8grdPficoqmw8gfbbWldEdSMY8gPF8mLO+bGJqIb35JuCYnNUXAJuWKiXZzD4i6VX9A671D0sA65Ti/KVEUk/gFqZgPjbN3cBhFtlHpbiGmb1PqggvSphmHrJLDs1ZdW4pzpuRkZFRz2RGd0ZVUaz5FOtK3GQ4mLSX8HjgcmB+i2wni+yd5s6RUT9YZI142xiAuWuspvJc0sjPVJKaTT2VNJOkzSSdLOlR4BfgQ7wF2UF4CnjvgsPG4ymdF+IiTgviUey1zewYM7vbzL7rwLhjGnmV28IonMHANbUaxSsnQdn8//DU4Vxl85dCum65qVcRtYRkzOKzvPGXJdItaSDe1mu7sMqAQ8zs72VoY3fjpFfvTnr1rxJfoxScDqzHZnifB+ce/JlYSv4PJuXJzEcJMnwCy8Ok+PxQ4JkSnTcjIyOjbsmM7oyqoFiDFetW3FDZA+gZNo0GzgbmtMj2scg+be4cGXVLkmLeC5i9mgPJJbQWuidn1RAASVNJWkPSUZLukPQN8D1wNx6ZWxuYusgpC43wKc1sWTM7yMyuM7MPS1HvG/pW78RfjOJm0opcT+88rrPnr1fM7C5c2TwxHOfBW4qVW9m8qxjd8Bh/kiqYlzzSLWlBXKE8UdAeBWxmZueV+lqBW0kyIIYyPrxaQ7GWLdP12o2kPYDDWJZc1Ysfgb3a2R6sVXLSzJO7xuGSVizBqQ/NeX1OPbcnzMjIyCgVmdGdUVEUayXFuh94E9gWT2sDr3U9EZjdIjvcog5F/DLqg5pTMM/h1JzXi0j6CP9sPgH8B9iSfFG/hB/IN8KnMbMFzWxXM7sw1GGPLXJcSTCzT4BDGA7cQZpYDbFibVmu69Y6LSib71zGy+Ya3cOa3at2SY3uEUxDWrhQUgVzSWvhCuWJQNv3wCpmdl+prlGImX0PPAnAb/QifcocVa5rtgdJKwGXMBBYN2/TbhbZiHJc08w+oGma+eQdPZ+kWUkF6n4i6ZGekZGR0c3JjO6MsqNYUqz1FOtp4Dlgw5zNw/AJz+wW2fHlmlhk1BRVVzCX1EvSIpJ2knS6pIcl/Qi8UbDrfKSOoYQ/KDDCzWxmM9vCzE41s8eDyFmluQq4k49xqbaU6xVr8SqMpyYws6/xXs8Ph1W9gOskxWVSNq/3SPcPOa9nJHVYTIYrfncaSXsBD5FmiLwJLGtmb5bi/K2QqpgPndTpfgvFKqa5UDEkzQbcSU96sSVp7heca5E93OyBpeH/gJfD63mBkzpxrgNJm5tdXE5nY0ZGRkY90bP1XTIyOkaIimyOR/+WKtj8NV63dpVF9hcZ3YmKKphLmhZYvOBnYZrWXDfHa3jdY/LzUS22gTIzk7QPsDzPMzMzAIsBMDlwr2ItY5H9VM0xVgsz+13Sxnjbov3C6uOBeSTtUWLDoN6N7twxz4TX5G4elgeTn6nSLiQ1AKeQH1m+D9jRzP7s6HnbyR3ARUBv3qKRDYEGBBwJ7FmhMeQhqR9e2jKQtcj9BL1LBWrOzWxiaNU2FOgDHCrpTjN7rj3nCe9jn7A4DriklOPMyMjIqGeySHdGyVGsXoq1Cz5huIN8g/sjvIZsHovswszg7paUJb1cUg9JC0jaLgic/S/UX/+MR6bPxj97S1Dc4B6BK4mfRSqoBnCZmR1oZtea2Qe1aHAnmNnPuEibN9j7blKi+WzA7YrVVkdDlyPUrx4AHEGagL8jnm4+oNkD209XMrpnBN7KWe5wxkRIWf4v+Qb3ucAWFTS4CVko9wMwnin5nOTaOytWsdKRshIcEdcAg5kLSBt3jQV2tMjGFD+ytJjZh6QaEAKu7kCa+a6k/dVvNrN6/PxnZGRklIXM6M4oGYo1mWIdgBtV1+LqzAlv4MJOC1tk11pk46sxxoya4Ce8VRZ0ML1c0tSSVpF0kKTLJb2Cp31/gNcQHoP3bC42iW7M2e9ovNxhEDAwKIkfgRsHCcc0PUXtYmaPAf/HBOAWxCgSBehVgAu7o6J5QlA2PwsvCxgdVq9MaZXNu5rRPTRneXBHTihpRryWOqn1bQQOMrNDg4BhpUlTzJ+ZVLPeCzisCmM5DtiayYEtyBUcO6oKXTvOwoXtwIUHT27rgaE//RE5q84p3bAyMjIy6h9lopIZnUWxpsJTNg8HZijY/Cz+4H6k1MqrGfWLYr0KLI1HHCezqHh6b4gCzUnT9PA52nip3/BIXe7Pe2YtZ1hImof8iPzyZvZyc/vXGpL64DWaizMI2IOJ9JhUZ3mwRXZ+9UZXG0haCvgfqZH8Kx51fbqT5/0A78k+ysym6NwoK4+kvqSt1p5jCKvif5upge8ssnZFgyUtgv+dk04FfwLbmtmDJRpyuwn9qIcBUwJ/ciw96UXfMLbZLbJfWjxB6caxFXA74A3TUjf1I8AGocViRZG0AGmauQGrmdmzbThuG1Jn5aNmtm5L+2dkZGR0NzKju5ujWH8HVgX+ZZF91s5jpwMOAf4O9C/Y/CBwqkWtP6wzuh+KdROwQ1hc2CJ7P9QDLkq+cb0Y0BbDxYDPaGpgf93RdjWSPiaNxD9hZmt15DzVQtJCwOtAXxYljTHCRGB9i+yxZg7tNgTxqv/hnzvwXup7mdl1nTjnr/j98DMzm6fTg6wCOe/hUzObN4hgJq3Wpm+r4KWkdYHbgKnCqm+Bjc3sreaPqgySriEpxViHh1iJ9cOm4yyyzgiJtfX6g4HngclZEth00qafgUUtsh+KH1l+JP0DOCMsfgosbmajW9hfuJMv6c29rpk9Wt5RZmRkZNQXmdHdjVGsnfE+wuApZSu2JRqtWIPwqPa+QL+cTYZ77U+1qCIqtBl1iKTp2JzTaWQPRgDv8Sq/MS0wF02VwosxCnibfOP6nVLXhUral3whoPlCa666QdKBwAUArMcoVpj0ff0VWM6i+no/5UDSVHj/5vVzVp8IRO112BREiZ83s5VLM8rKkhOt/9PMplSsc4GDw+a1LbLH23COfYELSZWsXwc2MaueMZmLpHXwiDL04SGOZh18rCPwaHezRmYJrj0D8CowK9MB+zOBnpOEbTe3yO4p17XbQkgVf5a0wvxcMzu0hf1XA54Ki0OBJbPe3BkZGRn5ZDXd3RTFmh+4OGfV8sAGrRwzt2JdivdtPZzU4J4AXA0saJFtmxncGUHUbC5JG0o6XNJlkp6VNBwYwd3swb3AC8BvLIO3IipmcH+FS4KdiGsCzAtMZWYrmtn+ZnaJmb1YJiGmm/HIZ8KRZbhGubkIeACAR+jH15P6Rk+DK5pP3dyB3QUz+x3YhPz74XHAjcGIbg+55TX1WM+dkHxOpghiWm0WUwvf/TNxh1VicN+NpynXhMEdeJLkfY5lTf7kzrB+ALBHuS4aSj/uAGalAdiWUTkG92XVNrjB1cyB3YFExO1gSau0cMg/c16fkRncGRkZGU3JIt3dEMXqi0e2CydPrwPLFEa7FWtRvG3J9uQ7asYAlwNnWmRfl2/EGbVKSAmfH4+K5f7Mh9cEtpVRuLhZbvT67Sr1u56EpFvwaktwA3wWs/pquxWiam8DA+kDHMIPTM5MYfMDwKYWVUXMqqYIKbKH4j2LEwfQ88DmZm1Op16WtN/xhWZ2UKnHWQkk3YGLzQHMxhCmx58PANdbZLs0c1w/4AbSFmPgf8+jqiSY1iJSTgR/FiL2Ig6bvgLmLbXgZ/iMXUFi1K/DH6zElGHzx8CSFtmoZg6vOJKOAM4Mi5/haeajCvZZmLSX+9fAPGaZUGpGRkZGIVmf7u7JmRSPViyFR3zuBVCsJfBetpsX7Pc7njZ4rkU2jIwuTZgozkhTw3oBvBVVe/ge+JBefM7a7MUAoD8vcT4r1WgrrstJje5ewEH4d6JuMLNhknYH7mcscAXTcBC/0cDUuHL7qeRHqrolITp3tqTPcXXryYGVcGXzjczsozacJjfSXVfOmQJynQzTAe/jGU09aUbBXNLM+LMjaRE5ETjQzC4t3zA7zU0kRve3rIo7oTbERd+2wx0IpeQQEoN7dsax4iS9ignATrVkcAfOwZ0vK+LZSKfg7yGXf+S8PiszuDMyMjKKk0W6uxmKtSWe2tYcb+FpZcWM7RH4Q/hCi6obgcwoPZJ64ROrxKBeMOf1VC0cWsgEXPn7w/DzQfj9UUjl9evFGgYMBIZZZDMWO1G1Cerp3wAzh1W/ArMWRnvqAUkXAAcCMB+fsgNzoknpv7tYZNdXbXA1RlA2vw8mZQT8CmxpZk+1ctxueKkNuMF5UbnGWE4knYK30wNY28weV6x3gEXw7/cUuR0HJC2G975OlM3/ALYxs4crOOx2ExyKn+D3PWN7tmQB7gqb3wUWK1XXDUnr4UZ9A32BwxlBb5L+8MdYZKeW4jqlJrTSewtISi1WM7NnwrZBwBe4Q/JXYLZK9lzPyMjIqCeySHcNImlafHIzJZ7m+CfwbltTHJs9b6w5gCtb2W1xvKd2Lt8DpwNX1KAnPqOdSOpP8aj13LTvnjCS1KDO/fmijdGOD3GjewbFmrZSbXrag5k1SroK+HdYNQ0eqarHlltHAmsCC/Ix8/AKj7Eca4dtlyvWxxbVT1u0cmJmr0taDlc2Xwz/vz8iqTVl8+lyXv9czjGWmdyxJ+9pKP5c6gksBLwJIGkDvFVUErX9GtjIzN6lxjEzk3QTXsMvbmEOhvACHtldBI9639/Z60iaHxfr8/KsnXiP3iwcNj+DP19rEjP7WNKxeJkAwNWSFguOx0Nwgxvg4szgzsioDpIG4PesKXBR4z9wu6Hm5lXdmczorgGCt30NYA9oWI00WlCwX4/vofFZ4Crgsfak4ypWL1wYqn87hvY9nnp6hUU2prWdM2oDSb3xtO85c37mynk9oPmjm2B4fWOhYf0BMLyTgjnvkbYhWgh4rhPnKifXkhrdAIdLutjMJlRrQB3BzP6StCNec9ybB1mLubmPAWyC19/frVhLW2TfVXektYGZfSNpZdxY2gA3Lq6VNC9wfDOf/a5odCf3i7eAv4XXg4E3gzr+eaRaH68Cm5pZPYnI3Ywb3QA7AScQSqzwaH+njG5J04TzuWjh8rzOrJNS8H8Ddq4DTYVz8TTzlfBnyamSjsM7mACMpT4dkRkZdUnIwlsH2B0aViHNxivYr8e30Pg0HnB7KhM5rC6Z0V1FgrG9CzT8Gxrn6dGj/4S+fefq2avXQHr2nJ6GBs/mMhvL+PHDGT/+p5nHjv1iqwkTftkOGr4KKYBXtNH4PglXKG8rVwMHZMZ27ZFTY51rSOca1rPQ/s4EY4CPyE8H/xD4pKX+rJ3kvZzXC1OjRreZfSrpOSBp/zQHrqR+S9UG1UHMbKiko0nEwi5mSY7hBXqwIv6ZuluxVrXI/mr5TN0DM/tD0qZ4Wc2BYfW/gXkk7W7W5P7YVYzuwppu8Ei308hgSeeQX997B7BLGe8XZcHMPpD0JrAEsDQn8zHH8j7uCFxJsVazyJ7uyLkl9cSN+vkAmJaPWI95c3bZrx5ESM1soqQ9SNPM/447oZKyo+vqzNGSkVGXBGN7L2g4Bhpn79lzugl9+szRs1evgfTqNT3eHAEaG8cwYcJwxo//aZYxYz7fbuLEkTtBw6eSTsK/r5nxXQUyo7tKSJoFdCXYun36zGn9+i1B796Dero9VUg/evaclskmmx+zlXuOH/8Do0YNnW3MmI8vBe0YJn9fNHutWOvTfqGkFchvl5RRQSRNTfEo9Vy40dfeVkbgUetv8ZZvhZHrr6sgZPZ+zuuFKnzt9nINqdEN8E9Jt9bpg+scPHK7NhMZxLm8wWF8iZgDWBq4SrF2LFUta71jZhMk/R2v/T0bL/nZHphN0uZmNjxn965idBdLL0/bhg1jJ/Lf62nAMTUqhtgWbsSNbhjP9rhgWCKiFuFlGR3hdGA9AMQI9ud3xPxh2w0WWd047kKa+dH4dwBg72QTaep5RkZGmZA0J+gasFX79p3H+vUbTK9eMxW1G3r06EevXtMx2WQLMOWUq/QcN+5bRo0aOvfYsZ9dE+yGPc3s24q/iW5OJqRWBSStBvpfQ8Nkfaeeep2effvO2aHzjB37NSNHPjKhsXHUeLAtionWKNbMeIRi+g5cYmeLrNTqrRlM6tU6O80b1tN08NS/4Eb1F+En9/XXZqn4UbVRrIGk/YAft8jWbmn/aiJpKrzv8mQ5q9c2s8erNKROEQSQ3gamBWAxjmNL/gX0C7vUrLBTNQlR75txZXPw79eGibK5pCeB1cO2KepRcA8miWclau03mtnfABTpBxqYkb9wM9tF1fY3syuqMtAS4U5wvsYdKh+zDwszM+/DpKj0qhbZs+085x6kGioT2JtrGMReYflLYLBF9lvnR185QpTtafIdkHeb2RZVGlJGRrfAhRh1V0NDv179+6/bs0+f9jaOccaM+YLffnt0QmPjX2PANjbrWBZPRsfIjO4KI2lN0IO9e8/Sc5ppNmpIUsg7SmPjOEaOfKBx7NgvG/F+spPqzxSrB/AoXi/eET4FFrSovmpXawFJPWiaAp77ehBpL+D28Bc+YStqWOeqg9cDijUcrxn90SKbqbX9q4mk60lrWgEeMbP1qjWeziJpC+DOsDiK3fkHs3NxWDZgc4vs3uJHd19aUjaX9DawKF7jOlmdZkIkYp5JtPshM9tA0mB25kXmDlk25/A7I9nKzB6r2kBLSIHDZBmGsBCu5wDwmEW2TjvOtRLwJInI2FKcyib8E+gBNOJG/PMlGnpFkTQP3lM8eX4dZGYXVnFIGRldGkkbAXf36TNHQ//+GzY0NPTu1PkaG8fw66/3N44b9+0EsA3M7InSjDSjNTKju4JIWgj0Wu/es/aZdtpNG7zcq/OYTeTXX+9vHDv2iwlgy5uZq8rGOg+vveoMe1hkV7e+W/chRD0H4cIVgwpeJ79ngkntmNpDI96iqjBKnbweVq8T+WIo1lPAamFxulpUME9whxmFke0lzGxoFYZTEiRdDpOiby9zHPfTgxPC8p/AChbVvgp1pZE0K6myOXgpzt54WvLMwPdmNqhKw+s0IaI5HteGeBUXF7uFtejHKmGnz/i7XWcXVGuMpUbS3sBlYfFshvBPvPRm7rBuJYvshTacZzb8bzYQgMm5lH+yFjBP2OVEi+z4Uo69kkgqVHT/Elg0Uy7PyCg9kpYAvdSnz5w9p5lmowaP53Qeswn88su9jePGfTMWbGkze7/1ozI6S2Z0VwgXVNHLPXpMvdiAATv1bGjo1fpB7cBsAiNG3DxxwoRfP4LGJRjCMpRGmOoti2xwCc5T8wTV7xlpakgXGtVTNHeONjKc4unfSQp4t6mlV6yLgP3D4ioWWU2KqcEkQ+QLXBk+YVLqbT0iaQq89dMkg4AhzAdsF5a/AJa1qHPtCrsikqbExfQ2zFk9EXe2vWNmixU9sE6QNAKv2/4ZL3dpYGFgm0m7RBbZCcWPrj9CdP9HPDr9AzArQ9gF7xYC8LBFtn4r5+gHPI+33gR4guP5kgb2CMuvACtbVL/3+IKMgISLzOzAIrtnZGR0EJ+TNrzZs+c08w0YsEPPUgXqEhobxzNixI0TJk787a0QsMuyWstMexWOMzrOEWBL9O+/XskNbgCpJ/37r9cDbEFcXXeGEp267lWM5QyQtLikDSTtJSmSdKmk/0l6U9IwPCX0K+AF4Da8Tco/8TYya+AKtK0Z3IbXKb+Jp6CeBxwKbIZHxaY0s4FmtpyZbW9mx5jZ5Wb2mJl91p0M7kChgnnNEkSiri1Yvb2k2asxnlIQolM74rW5AMdyHpcDb4TlOYE7FKtz+WxdEDP7A/9e50Z7kzDEr5UfUclJHC3TkcwVfuWBnO2DKzyeshL62SbvbyY8A+cG3PEEsJ5iLdfc8cEpdy2pwf0Zh3BtjsE9Ctipzg3uZUgN7s9J5wcHhEygjIyM0vFvsAX791+/5AY3QENDL/r3X68n2JLAESW/QEYTskh3BfBokob16zd48qmmWq31AzrB778/z6hRr40Dm5Eh7AMshatEj8NTly38zv1pbt1fwIMWWU2q8IbWWf3wCVJhendhdLoURsMfeO/y73J+F77+sRsazh1GsVbHax8BzrfIDq7eaFpH0ty41kEu55jZYdUYT6mQdAxwclj8iu3YkAV5gtR5dx2wW6ZoXhxJB+Oq8Emd63BgPjMbWa0xdYaQ9fMdaY9ugFPZhONZit9wIbnPLbK5i56gTpG0Ld6XHeBKM9tLsfYCLg/rHrTINmzm2CG40jnAHyzDpmzEHSRihbCnRXZVsWPrBUn/Jc112AcXljw3LH9JlmaekVESPPNGP0wxxTK9p5xyxbJe67ffnmL06LdGgc2YfX/LS2Z0VwBJ+wIXDxy4h3r0mKrV/TvDxImj+OmnKwzsCDM7u/UjagdJffGoyoB2/HROic6ZgKcT5hrQTYzqENnKKCGKNT3wU1h8wiJbq5rjaQuSnoFJla3gEaxZzaxuo5tB+O9J0vd1A0M4H1cqTr5jx1lkJ1VjfPWApENwwzvhXWCDemvLEtoV3gHkfhePMrPTARTrRWD5sL5/vSlwt4SkyfFMpSmA34AZGUIjLhyWZLQsa5G9WnDcDsBNYdHowSYcx6FA0pHhDmCbenZaBYfjx3jWwzC8deU4/L6xatjtQjM7qCoDzMjoQkg6HHTmwIF7q0ePyVs/oBNMmPA7w4dfZcB+ZnZZqwdkdJjM6K4AUo93+vSZY6Fpp920Ten8Bx20FhtuuBjzzDOQMWPG89prX3Lyyffx2WfDWz8Y+PXXB2zMmE+/hMa5qyW6JakXzRvQza3vbK10MX6meFQ6d93wOu4vW/fUk4I5NGkFlHCsmZ1SjfGUipAm/xYwdVi1E0MYh5daJOxokd1c8cHVAZLWAR4pWP0tbnjXhRidpJmBB0kF4hIWMbP3ABTrEmDfsL7drbRqHUnXATuHxS3N7C7F2ge4NKz7n0W2Sc7+KwFPkGZT/ZMhTCTtXf09sFitZoy1FUkXAgeExUn3u2CMv41nPxiwkpm9WJ1RZmRUD8WaC9gDf47eZ5GN6dB5JEHDZ337zjvHNNNsULTLzXLLzcUBB6zJoovOwowzTs0ee1zJQw/lP2aOOGI9dtppBaaeejLefPNrjjnmDj7++Mei1/zll3sax4796n2ziYt2ZMwZbSMzustM0nqlf//1mWyyBdp0zI037sM997zJ0KHf0LNnA0cdtSELLjgTq612Gn/9Na7V48eM+ZRff/0fwCxm9l2n3gCJCBz9aV8Eeupi5yoR4/F6w+RnGMWN6u/NOnbTy6gc9aRgDpMEtH4k7dUMIfJT75+3gojd78BiDGF74D9h3VhgzbaoOHc3JG2P9/AGd/ZNF16PBDYzs2eqMa624t01eJBUKPAv0r70qyXjV6z9YFJrub9b1HUUzCHph8tDYfF2M9smaBp8Cswa1i9lkb0R2me9RPq/voLjuIAevEJqhK9tkRV2PagrJE2P651MRpHMHklHAGeGxfeAJc2s9clKRkYXQrGeIG3ROxIX2rwWeLk9WS6SZgG+mWaajenbd56i+6yxxgIss8ycvPPOt1x55R5NjO4DD1yTgw9eh0MPvYnPPx/OoYeuw3LLzc0qq5zKqFFjm5xv9OgP+O23hwGmreesvVqn9JX5GYUsCdCr18A2H7DTTvnZHYcddjPvvnsSiy02Cy+//Hmrx/fqNUlDbWlJPwJT4UZw7k//IuuaW9+vzYNvP434BHVEO37+6EptszJ4j9ToXhio6ciZmf0h6Q7SaBh47fPOpLWfdYmZ3RxaAv0Nv29czzWswW7MC+wJ9AHuUazlLLLWb0bdi+lyXg8BdgWWxu+pj0r6m5ndVuS4qiNpZVz4sX9Y9SWeEp2I6+TWdg/NeT24vCOrCo/jNfnTA5tImsrMflesU4GLwj7Hh4yX+0n/74+xFYfTg5dIDe7/q3eDO3AgqQPm8iKT8nOBHXANmYWBo4ATKze8jIyaIHeu3B/YL/x8pFjXAtdb1KZyo6Uhby7fhCef/JAnn/yw2e177bUa5533KA8++A4AhxxyE2+9dSJbbLEkN9zQNBGld+9J11qSpq1RM0pEZnSXnyWg58QePabpcHO9qabyZ93IkaPbtH9DwxRIfcxs7H8pjYBYe/iV9hnQI7PU7m5ProL5QtS40R24hnyjG+Afkq7sAp/ng4CV8ZrNVfiSo/C2bnPgdb4DgPsVa0WLMo94DrlG95d4xOO/wAb4ffhWSTOZ2XlVGFuzSNoSz27oE1a9ibdB2yRnt9z39g6eRixSpe4ug5lNkHQr/j3oA2yJf9+vAo4FBjGBzejDw4xlvnDY+8A2LMrJ+D0MPMX02IoOvgyEOvekTnsi+boFwKS/2d54f/IewL8l3WZmzVsFGRldj+YyS+cHTgFOVqzH8ej3XRbZqGb2X0LqM6GhYYoO2WizzTYdM8wwFU8//dGkdePGTeSllz5l6aXnLGp09+gxDdBzIkzIjO4ykrUMKz/T9egx2UQX2u4YQ4Zsxssvf85HHxWvxShEEg0Nk4vOGdyj8BTt94EX8bTD64Gz8YnEvsBWeIRyYTzS18vMpjWz+cxsRTPb1Mz2MLN/mtnpZnaVmd1rZi+Y2cdm9ksXMFAyOs/7Oa9rum1YDk8BXxesmw/YtPJDKS1m9hse6U6+mzFDWALYGvggrFsAuD1rJZZHrmH6c1CB3Yy0z7OAcyWdHtpLVR1JBwG3kxrcj+Cp5D+StgyDnPcWJoqfhMVFFZehl031uSnn9Y4AFtlY4D8YnhMw1qNRuBDkRgxhBeDvYd0YXP+gaR5n/bEb6f//VjP7qthOZvYmaR17b+CyWvmcZ2RUiNai2MLFFa8HflSsqxRrNcVNvifT9ejRzzpqNwwcOCUAw4fna/8OH/7npG1NBibR0DDZRNJuCxlloCs+LGuNntDQYYv7lFO2YsEFZ2bzzdsXHJF6GK6++lH4PTL8LvZTuO13M5vQ5KQZGeWhbnp1J5hZo6RrgeMKNh0l6Z56L38ws+clnYy/v57A9QxhCYawEfAynnq7JnCxYu1Vz6rMJSTP6AYws/GS9sIjIMln5UhgkKTdq1X3GoyhU4F/5qy+Dtgrp+VhrvBX7nsDTzGfDzfW5yf/O9wVeAnvzz0nsJakGYMj4gqe4hTeIpm5jgU2ZQijgatzjv+HRfY+dU7oapDbv/eMVg6JcefcXHgnhL1JBegyMro67elUMQWwe/j5QrHuBS4L942epYiJFj6VJWhpaiI1COjV6QtnNEvmhSw/Yzratvmkk7Zk3XUXZuutL+SHH9rXlcVs/ATgGjNb3szWM7PtzGwfMzvSzE4ys/PN7Dozu8fMnjazoWb2RYg+ZwZ3RsWwyIbjNZRQJ0Z34Nqc10lEa3lgpSqMpRycCLwSXs8HnGqRfYFHb5P3uwdev5lRxOgGMOd4vLYvyR7YEXhAUnl7SBYh9OC+jnyD+2RgN8t/WOUa3bk13eCp0wldMcXcSKPdDcC2AAxhC54mDRVtwBsM4RXgCtKe9g+Q1n7XO1viBjTAo2Y2tKWdzWw0qbI9wOlBET8jozvQUeHiOYFDgPcUawc6YTcA/PSTR7gLo9oDBkzB8OHNt+EO1/yrwxfOaJXM6C4/nzY2ju7V2Ni+LLOTT96SDTZYlG22uYhvvmmfmLPZBCZO/L0naQpgRkatk0TKZlCswqhaTWJmn5HWn/fJ2XRkFYZTcoIBtgvpQ/hgSWtaZC/iImEJpyrWNhUfYO2RGKaNePZQHmZ2KbAF6d9zLeCZSholwch/ANgprGoE9jezfxfJzmgt0p0wuJRjrCHyUswlrUhuNHttYDlWAP5NWv8+HNijK2R+eNuivHtZa1FuAMzsMVKH5FTA+SUeWkZGTaBYDYo1k2Itq1hb4U73zrIC8MnEib/37Gj86+uvf2bYsN9ZddX5J63r1asHyy8/D6+99kXRYxobx9LYOLoX3qUho0xk6eXl53WA8eOH06fPLG064JRTtmKLLZZi992v5M8/xzL99O6t+uOPMYwZ07r3a/z4EYApuXZGRh3wPrB6eF0vYmrgAkurhNd/4iljm0pa0Mw+aPaoOsHMPpL0L1ydGOBqSYuZ2a2KNQ9wUlh/nWJ9Y5G9VJ2R1gSJYfqrmU0stoOZ3StpLbwqeDo8SvyipPXL/XkJxv0DpJHpMcD2ZnZPM4e0ZHR36Ug3gJm9L+kt/P0th//P3Lk2Cy+zEsuFXY/POWxPi2xYRQdaPlYDlgmvhwKPtePYI3AxvumBLSVtYWZ3lXZ4GRnlRbH641HoWZv5GURp07GfwzOQBoNp/Pifc1XF85h88t7MOWeagDTrrNOx8MIzM3LkaL77biRXXPE0f//72nz++XC++GI4Bx+8Nn/9NY677nqj6PnGj/8peZnZDWUkM7rLzwegMePGfde3rUb3brutDMCddx6Ut/7QQ2/iv/99tdXjx437Hlxdtvk8koyM2qKwrrtejO7b8EjO5Lhqb8IRwF5VGVHpuQDYHFfjng04C28fdgowLx717kvaSuzL6gyz6iSG6c8t7WRmL0paCe8FPQf+N31e0iZm9nw5BiZpwXC9pAf3L8AmZs33Ww/16L/j0crC9PLvcaG1AcASiqWuEN0twk2kToVEYOhxlmdLxCfAQNJ51NUW2X2VHmAZyYtyt0enwsx+lnQIabbAhZKeCCKNGRk1gWL1w43qOcLvwtdTV2goHwN7W2TPAOg7/cEV2Lhx36k5o3vxxWfljjtSGyGONwfg1ltf4bDDbubCC5+gb99enHrq1kw99WS8+eZX7LDDJUV7dENiN2gMZB0HyonqXO+nLpB0TUPDFDsNHLhHz3KLeZoZw4dfw8SJk55tjwOXAXdXS7QnI6M1FGs1XBEc4AKL7O8t7F5TSLqOtH3YaNwAHwfMYWY/VG1gJUTS7HirqKRIbFMzuy+olz9MmqXwPrCSRTay4oOsIpJ64f9zgBfNbMU2HDMjHnleIqxyxesSRwRDD+57gWnCqi+B9c3so2YPSo/9HJ98/mxmeYa3Yj2KJ1kDzGxR1/is5yJpLuCznFX++TYbqVh34c4o8G4fgyzqGkalpEXw7zt4l4Z5rJ1FpiE9/X68ZR7AJWa2f+lGmZHRMorVF3c0FjOo58AzMTrKL8A34efbnNcX4I7KtjABOB3XT2kENucv9udtVucx6NHYn+mn35XOdD9qC2aN/PTTVRMaG/+8wcx2L+vFujlZpLsyXNTY+OeuY8d+Sd++c7W+dycYN+7bXIMbvG5wLWC4pGuAy80sq/XOqDUKe3XXE9eQGt0/4sJDvYGDgaOrNKaSYmZfSToUuDKsulzSImY2ItSyvYiLrS0E3KZYG1rUCSWY+iO3zUqLke4EM/tR0mrAHcA6eLbAHZIOMrOSCHE114M7KHG3hRH4BHUaST0K0ubfIjW6Fwe6lNEdjMbC7gT/DAb3fMB6OesnA2bEu390Bf6R8/qs9hrc4GJ0kvbH7+39gP0k3Whmz5VqkBndm9CucFaaj1Z3VC9jIu5s+gJ3Un5FalR/A3zbXI9txTqCtpXcvI5njI0GTuAX9uAVpuNNJsmUTmQk48Z9S58+s3bwbbSNsWO/pLHxz550HQHImiWLdFcAf3g3vNyzZ/8lBgzYqad34Sg9Zo2MGHHzxAkTfv4UGq8C9gHmLrLrk3gbj7vNukQf0YwugGL9hHueh1lkM1Z7PG0ltF/6AveoN+Le6974BHxWM/ujhcPrhmCE3AtsHFb918y2A1CsufFWYkmK9eXAvl005bgJkhYidRxda2a7tePY3rj69c45q08Fju1M67nQg/s8vDcseA/urdvzeZT0ILB+WBxgZpMcCor1N7zfLMDRFtl/OjrWWkTSMbiqey7/xxD+hZe/FIom3WCR7UydI2kQfj/rBfwKzBZ6znf0fIcCZ4fFD4HB2bwjoy2E/tUzk29IJ7/nBGYhv6yrrRiuNJ4Y1bm/vwC+s6hjKmaKdT+uZ9AcfwER8B3GXnzFGryEN/dtcrfX6J49p+87YMD2DeXKkjWbwIgRN02YMGHkm2YTly3LRTImkUW6K0Dw+O49YcIvr//558tMOWWrmYcdYtSo15gwYXgDsKuZvSzpTDztcx+89Uci+LBG+BmRE/3+uCyDyshoO+/hn9cZFGs6i6xNEcNqU9CzuwGPAC6D14PtjddA1z3hPrYP8C4e2d1W0l1mdotF9plibY6Xs/TG3/cntFHxuAtQtF1YWzCzcZJ2xVMUk8yIo/Fe3nu1N8rYQg/uvTtQYlQoppa73GXF1CRtR77BPRGf3O9AI7/QMMng/hRP258O2FGxTrCo7jPJDiGdK1zcGYM7cD7eIm8ZYAH8sz2kk+fM6AIolnBdhDkongI+G/486QjDyDekc19/Y1HZHD8t9ep+AXifCRzFu0zHS3huXC5iPMa1wKVgx06Y8NPmo0a9zhRTLNP0bCXgzz9fYcKEX0TX0aCpaTKju0KY2VuSTvjzz1eH9O49SH36zF7S848b9x1//PFSI3Cmmb0crtkIPAE8IWl6XPBoH1z8CFwE5x/APyQ9jUe/7zKzMSUdXEZG20iMbnAxtWeqN5R2kxjdkJ9qfJik8zuSnlmLmNkPIWX01rDqIknPmNn3FtlzirU7cGPYdppifWaR3Vmd0VaUDhvdMKkv9DGSvieNTu8CzCipzdHpEDW/irQlGLjgXbGWYG1hRM7rQgXzD/E69t50obZhoTXYtTmrjgZWBDZhBmZGxGF9I/4/WgM30BuAY4HdKjfa0iJparyfPHiSa6fbfZnZREl74em0PfHP+W1m9l4rh2bUOcGo7k/zNdVz4BooHeEXihvVXwJfWmSjO3jezlLM6B4FfMsfrMhrrMhrYU0uYhjG+RiX4Rl/twKLAPzxx4v07j0zvXsPKulAx479ij//fNWAE8zs7ZKePKMoWXp5BXGxHd0HDetMO+3mDaWq0xg37nt++eWuiWYTngPbEm/vMR3efuBBPO1zqJn9FVJEV8ON761o6kX8GZ9wXG6WqRhmVA7F2p+0pmh/i+ySao6nvUh6hrR92DPAquH1LmZ2ffGj6hNJNwPbh8UHgY0So06xjodJhslfwGoWWettF+oYSXviKeIA+4We3B09V2Ed9hv437fFOuzQg/sO0jrrRuAgM7u4E2M5DjghLG5qlq/OrVivA0uGa01ZxYluSQjCaS+TqrVfiWdtbEcPbmZvvHLb+Y9FdrRiTYVP9KfBI+LzW2S54mt1g6QjcWEn8DnAPiU89ymkmRwvAKuEwEBGHRNSwGfFgznzhd9zkBrXbRUVK+RPikepv8SN6prUT1CsXXGdl4Rx/EhvXsRzxJo2k3wVOAf4H25k/x3YFnfiAfwF+lrqOc+0027Ro3fvjpap5zN27Df88svdjdD4CNimXSUwUOtkke4KElqwbAmN9/zyy11rTjXVqg2TT754h5UJzYy//nqP3357shEaXwTbBNgUvwECrBt+ACZIeht4BZ9UnISnke2MG+Dzh/2mAw4HDg9GxGXAHVn0O6MCvJ/zeuGqjaLjXENqdOdGO4+UdENn6nNrkIPwrIQZcXXiXKPzRGAe/N4yGXCfYi1rkX1dhXFWik5FunMxszslrU2qOL4k3st7vebKgJrpwb2Dmd3dmbHQcq9u8BTzJfEJ4iL486UukTQNrradGNyPA/uHsor7WJ3xzBjSro33kKdIW2S/K9ZZ+Oe+B3AM/n2oK0KWxKFh0YD/K/ElTgS2we8NK+IR9Uy4qQ7ISQNPjOr5cl7Pg4tAtpcxBAOa4sb1L/WmCRLU0nsBf2JMwTfAY/Sm6ZNvIvAonv0xHd5i9FqK22QR2CVmEx78+ec7Vph66jUaJpts4U7ZDaNHv8Xvvz/TCPYE2FaZwV05skh3FZDUB6/zPKB370ETp5567R49e07T2mF5TJjwG7/99njjuHFfN+DphIfj7UuewFuc9Grh8IQ/gNdwI/xPfPK0EWmEJeEXvCbwcjN7n4yMMqBYA4DhYfFJi2zNao6nvUiaEq/QmhwYiaffJrWfG5jZQ1UaWlmQtCFupIDfPxYzsy8AFKsPLtyVRPvfxVuJ/V7xgVYASaeR1lCvYWZPleCcC+G9tRMn6s/Axmb2UsF+7e7B3Y4xbAfcEhb/YWZ5hphiHQycGxb3tcgu6+w1q0EwOB/CU8UBPgBWNPPWd4q1HMaLCDEReJyD7Hm7cNLxsabGDYb+uJDifBb5d6FekLQbcHVYvNvMtijDNdbA5yjg84+FzKylGtiMCqJY/WlqVCevp2z+yKJMwFW/v6R4Cvgwi7pGpoNiLYRnxOzKX0zDm/isumksfgzwE16CNkUbTj0emMbMRkmaHG9Htnvv3rM1Tj31Wg09e7avjfiECb/y22+PNY4b910D7vA6PBM1rCyZ0V1FJK0JDddB46DevWdv7NdvsYY+fWZHKp6AYDaBsWO/YfRfbzN2zBdAwzBo3N3MHpT0PrAgnuY3FDegO8KPwPd4StA8RbY/h0e/bzezvzp4jYyMoijWMNyjXlcK5glBUG2XsHgmaeudJ83qy4nQFiRdTirA8jSwZpIyqljT4a3EEg2Jh4BNOqoKW8tIuoI0urmYmb3T0v7tOO8gPIK9WFj1F7BdkuYtaSXgPjrQg7uN118LeCws/sfM8lrgKdaq+P8d4GKL7IBSXLeShJKrK4GkP+1wYLkcB9JkeKs1zwZ7AniGq8wsL5qtWBGpQNjlFpUuNbvchL/BO6QZRiuVwmnTzLVyvyv3Apt3sSygmkaxJsfndsWM6/b2rR6HB3k+Dj+fhJ/PcQXwpsnUXYRwX9ga2BdYiRGEQk7cVC4NJ+ClWofjGWWHALNBw1XQOLBPnzlt8skXa+jTZ9ZW7IavGDXq7cZx475qgIZvoXFXM3ui6AEZZSUzuquMpMmA7aDhYGhcAmQ9e04zoVevGXp5QBzMxjJ+/E8TJkz4pQeYGChY1D7gcZYx816BkoaTpsWVggtwIYd98PqSwuj3SDz6fWkW/c4oFYr1JKmY2oB6UTBPKIjkPIi37JsvLC9jZq9VZWBlItQRvw0kypCHmdk5k7bHmhd4iVRc7mLgwHpLG2wNSXcDm4XFQWb2fQnPPTVwF2kUthHYHzcObyJN7WxvD+62XHtwOC8UqfENkbFfw+ILFtlKpbp2pZB0NC42Bx6JWiM3m0CxziZJu/6eRq6ggUZ+AWbMTctUrGlwp8dUeJRvHovsq0q8h85SkLXygln5/o8hjf8DYIawahszu71c1+uOKFYvvJ66WDp4e8WEGvHP9SfkG9cfA193ZcO6GCGqvS+wC0Z/PsefcKXvWTAaj55HpHOIT8xsPkn9gB2D3bCI2w3TTuzVa2DPfLth2PgJE37tCSZoeAMazwduzQJm1SMzumsISYsBKwBLQcOSoCkBgf0BjUOB19iLoxnErAgD5kjqJCVdReqpLwU7mdlN4dzTAn/DbzQLFdn3KTxV5e6sNiSjMyjWBcCBYXE1i6yeFMyTdk2f40ZoI/AvUmGiSX2tuxKSVgeeDItjgCVyRRhDNPQx0pKXwy2ys+lCSHoWWDks9i11yl4oSboa2KGZXdrdg7uN150VJlUk3mlmWzXZJ9YXuHDSKGCqekoZlbQtqRI/wLZmdtuk7bFWJ/ezfQVP8O2kHrzrmdkjeeeLdQJpF4NLLbL9qAMkPYULrIJHnu8p8/Vy/+4/4mnmv7ZwSEYBQcBsFoqngs9J+/tXf0++QZ28/ryM7bXqguDE2Bw4AFidcbir+WXSgriU0Xh99md4tltHGUbqmEp4y8wGTxqXZ6gMxsvYloaGwcFusGA3vIHXjb+YqZPXBpmQWg0RvhQtfjFCyuaJeEuZnUl7id5H6Yzua4Cbc8b1C3CepPNxAZQk+p1EWFYPPz9IugyPiHxXorFkdC9y28jUW9uw3J7dx+PiUr3wGq6BwNaS5jKzz6s5xlJjZk9JOgePBvYFrpO0opmnkVtkzyjWHkCi4P5/ivW5ReWd2FeYRGRsVDlq5MxsrKS/Ad+RliwkXA/s1YEe3G2hNSE1cDG1OYB+wFx47+qaR9IKeLZWwjEFBveUpDXOAMfwLV/DJKN7G9zZkcs5+PdgSmAPxTrZIvumxEMvKZKWJTW4P8LnEuXmNnz+sjEuxngaPq/IyCFHwKxYKnhHBMx+oWm0+mPgU4s63Y+9y6FYg/DP5d7ATPyMa42/iTfUy+cbvMXeFWb2azCIF8Vb9XaEQoMbIK/9ZijLeJM0Gymjxski3XWGYs2Op/qA3zTnt8hM0kDcM9ZZXsNbebSoVh5SxHbBPX/zFWyeCNyNR7+fzOq1MtpKQY3oBRbZ36s5no4gaW5Sw+MDvG/1SWH5QjM7qCoDKyOhTCate4XjzezEvH1ixbgzAjwasKpF9nrlRlk+pElaBF+b2eyt7d/Ba/TGa4//VrDpATxCW9j5tVTXHY2r0L9nZos02R5rCJ4CCbCNRbWfKhxag71EWsN6Fe64mPSsUqzL8Mk2uPNvDYbQF49tTY47JGYqzO5SrJNxBXOAiyyyA6lhJN2G16YC7G1mV7S0fwmvOyvesSIRlFrdzJ5u4ZAuS46AWTHjur0tt0ZRPBX8k3or16oGwdGxBj633ZxGevAJ3peheCPA53Fn292Jo3nSufy5+CywVImGV/YslIzykhnddYhiPQ4kokwrWeSCJ5I+JJ30doThwFJmbffMB2/emvgNajOapjR9iNdxXpcowWZkNEe9K5gnSHqaVLl7HdwJ1Q8XwprNzEZUaWhlI0TMXsDvAROAZc1skgc+TGZuJE2R/gFYrtYjga0R7oHj8MyxN82soyKWLV2jsAe34c7NJFvtVVzZ/KcyXPsbPI31RzObqcn2WJvjNecAJ1tk/y71GEqJpP64wN8CYdUTuPhcbn12bo3zKGDRRI1c0n/xKDfAOmaWCM0lx06HO8anwD8Xc1tUmwrdwUH4MZ6VMwyYo5LtQSUdhEcHCeNYvCu3J1WsgXgG10Lh98L453BgO081nqYCZsnrH7qaZkYlCI6PJJA0P6OBN/Aw1Mgmu4/Fs0EvbE2nRdJseAZr+6TGizOvmdVFJlFGcbL08vrkGlKjezd8oguuLN4Zo3vH9hjcMCm95XHgcUmz4JGBffCUMfAHyrnAqZJuBC4ys6GdGGNGF8YiG6FYSTp2PfbqTriG1OjeErgcTzudDK9Zj6syqjJiZq9IOhX4N/5suU7S0km6tUVmIc18NmAlYCbgf4q1skWlrUWuMFORPktLHklqrgc3PhW8G5/MLQO8IGn9MkzKfsaN7ukkqUjm0ls5rxenhgnZAneQGtwf4rXwuQb3tKQ958E1CHLbf91GanRvQ6ruDoBF9nPQpvgX0BtvJXdwKd9HCTkcN7gBzquCwXsxsBNekzoffu+oaadNW1Cs6UmN6lwjuz1it0bLAmZdrgtENVCswbihvRMwOd/hLsx3cLdmPl/in9mr2uI4l0uK70v7sxWKMQZvt5ZRx2SR7jpEsfrh4iNTAL8DM1pkfxX02ewIj+HtaH7p1Pg0SXTiQNJasVxewFPPb896BGYUolhPkCo1T29R/UWFi/TsXhZPNe+BGzGzmdnoqg2wTASj5mVc3AXgdDM7Km8fn5C+hNf/ghuUm9XrJDKkKieJh7ea2fYlPHeLPbglLRK2DwrbhwMbmdmrJRzDY8BaYXFqs/xe6yGDYSQ+sfzWImuvOnJFCBkJVwB7hFXDgeULNRYU60Zgx7D4ELBhbuQwKAcPxx1oI/AU8wkF55gen6BPjkfF5rKodIr2pUDS9LhIXl88mj9rNcTMwmf4DVz/YgKwZKla7pWbHOM6N3LdXuN6GO78KSZg1mWj/tVEsfriJRUHACswHi90eAVXzWjKQ8CFwINmbVNrDxHum3AHcyl4w8xKlaaeUSUyo7tOUZynVr6jRXZzQS1pR/kc2NLM3mp1zzYgaWG8vc0uuLhMLiPwSdClZvZlKa6XUf8o1vlAUvdcdwrmCZKuJ62/3QJ/yO8Ulg80s4uqMrAyI2lRPCmvNx6tWbmw569iLYCn+PYPq+qyfh9A0jL4dA1KWLPf1h7coTb2QdLMkNF4G6YHSjSOW3HhTIC5kv7VefvEegZYJSzWZKs/Sf8CTg2LY/HWYC/m7RNrazySDe5IWMSipqKgBXXQaxXreatYpwNHhsVzLLLDOv0mSoiUV4t/jln1xifpRNII98t4n/CaaUUVjOtCw3oh2tfX+kdcKPQ93MR7D3jfos4FOTLajmLNgUee9wIGMBJ/Ur2B3zXzGYkHsS42s3Y1BJO0WTh2mtb2bQfXm9kuJTxfRhXIjO46RbFWw1t1ATxika0XPPnfk6Z2twXDlUP9JuT8hQuq3Fii4SaRv53w6HehGI/h9XMXAQ+b1U/LmYzSo1j7458FgAMssourOZ6OIml93BgCn8ifDAwNy58D89XSxLKUSDoK+E9Y/Ayv1cwT+lKsNXD15yQ1+xCL7LzKjbI0FPyfTzCzqKX923jOLWhHD+4gbHk3aUnDRGAfM7uqBGO5CHecQjO95hXrPCBxmqxlUVMjtJpI2gb4b86q7czsv3n7xJoBN4QSlfa/WVT8GShpO+CWsHiJme3fZB8/3xd4RHwMMKdFpeuh3hkkTY5HuafDPytzm1Wvp7ikvvi9MSmPO9jMzm/+iDKNwzVFClPCF6ZjxnViWGfGdRUJrdXWw6PaG2GIz3E36cf47DOft/Co9k3tFacMrR1Pp3g5yXA8cX3DItvawr/M7LQOHptRI2Q13fXLs/gDfU5gbcUaZGbfSXqO1APfGgZsYWb3SLoYuB2vDZwMuCFEcI4sRe/t0D/2EkmX4uk2B4Rx9sLbn20cfj4PY7narPaiJRkVobBtWL3yGP6gnR7YBHdsPQKsi6dWb0kaVetqnIkLK64AzI1PRPJUnC2yJxVrb9KSmLNDK7H/VXSknSe3lVan71mSDsTFpRRWPQps1VIP7tCiZj28BdY2eBnDlZIGASd1soNEbnlHc2mzQ3NeD8bFyWoCScuTtqsDOLaIwS3gMtL/5R2406M57scN6b7AlpIOKnSgWWTDFOtivG66Lx71PqIz76WE7E76Xm+ppsENYGZjJO1N2iLyVEn3mNnXLR3XUYJxXSxy3R5Bs2GkRvUkIzszrmuDIGi4B7AfMBdj8LvUqxS7S0/A578XAC905H4paR6893wxIc1Xga3we+mleLu89vJuB47JqDGySHcdU9Cq5WiL7D+SDsaFy9rCDmaWeOsTb/MFwJ45+zyLt6MpuYde0ozhWvsChXWAY/FIwkXAq1nbse5DeFgmE/2nLLI1Wtq/lgm97ZN0493wirFHw/JruMJ3l/xsS5oXn+ZMHlata2aPNtkvv8XSKGAVi1LV81qn4J77t45mCIVMpVNwAa6EdvXgltQAnAUckrP6MrycoUM185IOwVviQDPvT7GWwj/PANdbVBtpkJLmxNOVk0jl1cCehd85xdoVFz8E+AlPKx9OC0i6A3ecgaeqP9Vkn1gz4s7xvngG2RwWlV5hvj1I6oHH+BJNhcGlKifrLMEpn/Trvh/XL+jw/TE8S4pFrjtiXBdGrrOgQI0RnGfL4EGd7YE+DMOj2m/jmu/5fA9cAlzemTmupK3we0thCSV4CeXfc0UKC0o72sqcWRlm/ZMZ3XWM4jwBnw+BhRjCEkBbet9+DixQLIodPM4X4DWZ4DemrQvr30pFUHjcCL9Rrltkl9dx4/uWrig+ldEUxfoRmAH4ySKbodrj6SiSViDtLvAonub2OrBEWFd0st5VCFHbC8Lit8Ciha0DQ/rfTcB2YdV3eCux4pI2NYaU1398AzN7qAPn6I1PznIjIKfiUdl2PaSD8X4EcEbO6vuA7Tty/5T0N9JI8SFmTUsAFKsP8AeeufS+RVb1DJXQGuwFYMGw6km8Jj7PgaFYs+JRpERheAuL7O42nH8H0mj4RWbF+3Er1jmkTpAzLLJ/tv1dlJ6CcT9qZsWeuVUh/M/exzsbgH9mb231ODeui0Wu2/PsGEa+YZ0Z13WCYk2OG9kHAEsxEZctfRUonsPxFJ5Cfk9nMjnDfft08p2cCeOAg8zs8maOzXU2t8afuIhlVnpZ52RGd52jWE+RKoQvzxBeB37Flc2LYaRpixeb2QFFzysth6fYJaq44/EbyyXljMyF6Nh+eFpQ/4LNv+LexEvaK2yRUV90BQVzmGQAfYaXgTTi36c1SCe9D5nZBlUaXtkJkdeHSftLX2dmuzbZL9ZkeEry8mHVm8CqFtmfFRloJ5B0IT7ZA89caJdyuKQpgDvxfu7g9+iDOiu0J2lHPHrbK6x6CY8ctuu7VFCzfqKZHV90v1iv46mVBkxdzTZwoYPGg6Sq6x8CKxaqcweHT/7nM2r6+WzmGlPi5SN9cINtUDGNBsWaGXdy98HlmuZoLYpeLsL38S1SXZWiInDVRNKW+NwDPOtgwaSjimJNDSxG08h1e4zrn2gqaPZeZlzXH4o1Hz5f3B3ozx+4S/t13AWYzyi8/OYiM+t0qnZQJ/8vsFyRzd/iJUGvFNmWHC88mLQv6Zy8OV4xs2LXyagzGlrfJaPGuTbn9a4hhfCFIvuNxdugrIh74AD2l1TU6Dazl/EJ1NNhVS/8BnF1EGEpC2b2iZkdgRsne+K6kgnT4PVxH0t6WNJmIUqe0fXoEnXdwUGVGNgNeDT3NlyJGmB9SUsUObRLEDzze+CtDQF2kbR5k/0i+wuvAU+UsZcAblKsHpUYZyfpcE23pOmAx0kN7jH4ZK3TyvZmdhOwAen0c3m8l/cc7TxV7nuartm9PK4EPoEsVtdYEcJk9mJSgztpo1asHdZ+pAb3txSPWBUl1NgnzogZaKY1UGgVlkS7Jqe6dd2bkhrcL+HR/5rCzO4E7mZqYH4GsimPKdZdivUFrij9DP7//TuwJs0b3D/h7y9xiq2GO3BnsMjWtMj+bpFdbJE9kxnc9YNi9VSszRTrEeAjjMP4iv7cBpyNx7DzDe6P8M/KzGZ2QIkM7g1xx3AxQ/gpYKmWDO5AA7AAqcHdUnu491rYllFHZJHuOkdxk37AMzGEI4ETcnb7EdgsuQlI2oXUWJ+I11oW9XYHo/Y03NhNeAdPN/+4hG+lKGEClV+jk883uDDFFWY2rNzjyagMirUfPrGCOlYwB5Jey++HxVfMbLng7LowrLvDzNoqfliXSHk1s8OBhc2aRvsUa0G8ldjUYVXNtVoqRNKjpIZbfzP7rY3HzYIL6yXpzyOBjc3s+RKPb3HcOExSdr8H1jGz95s/Ku/4NvUhV6w98RR5gCMtsjM7PuqOU6CcX7Q1GIBizYNHfRMn8noW2SPtvNZOwA1h8QKz4m3vFGsW/G/YG4+4zW1RZZ9X4Vn6CrB0WLWxmd1fyTEUQ7F641HrwZN+jMFo0j2gNX6ioN4aj1zXZXZURnFCN4C9SDSAxuIz0VfwT0A+jcC9eGnTE6XKzgzz4ROAo5vZ5f9wlfFW9TMkRcCQsPgt7kA6CxcULuQIMzur3QPOqDkyo7sLoFjXkdYCbscQviDtG/smsKmZfZt3jHQG8I+w+AueFvkZzRBapFwJ9Aur/gD2MLPbS/MuWidEhXbH29fMVbB5PJ6SdiHwfFcVp+ouKNYqpEq2F1pUmt7H1ULSm/iEEmA+3Fn0Bd7ez3Aj9IPqjK78hAn/XXg0Gzydeuti31PFWgt4iLS7xoEW1W5Pc0lv4JH5CUDvttx7JM2H1/jPFlb9gDs/y6JQK2l2PI06acn0C96C7OU2HDs17hAAeNzM1i66X6zFSVXMb7WouHFeTqS8PtvQTE1wyKB4Bs/8ArjYouKlVq1cbyp8yt8H/x/O0lzdpeI8UcVzLbJD23u9ziBpXfwzAP5/WrLSz0nFmhZYnNTAXhw3uHs1f1TAGIV4C3eUvEtac12VVP2M8hOE0VbGgy5bAb0YgefUDMVdavkMx7NKLi218r2kmYCbScs5cxmFCzS2qj8QzrUaXk7VgDsIVjezZ8Nz8mC8Trx3ziHrm9nDTc+UUW9kRncXQLHWxFMUAR6wyDaStD0wM37zadJrMCiY3kvaM/ADYHkz+71w35xjFsQN2wVzVp8NHNUZMYr2EurS1sVvxBvTtB7mHTwV/kZroc1ORu3SlRTMASQdiT9IASIzO0HSEXhrLYDrzWpD8blcSJoBnywnbad2NrMbiu6bHzVtBDa2yB4stm+1kfQVbjz/ZNa66J+kJXGnQqKo/Rkeef6i+aM6j6Tp8Yj3UmHVKGBzM3usleOElyT1BIaaWdFyCMXqiZcRTAZ8bpHNXaqxt4WgQ/IUaW/zf5vZyUX3jfO+j58BgzuqHyDpHjxtG2BVM3u2mWvOiNd2T4b/Pee1qDwtsYpeX3qatI/7tmZWtnaFwViak3zjejCpk6k1vsMYyqssxpfMyo/Ar/zHGq25CGNGFyJkcO6Ez/EWpRHX23+VNOcmn5fwgMttZtbUFO/seKQ1cIO72P39fdyB3CanebgPD8Xn5wDHmdlJBfssgbcfmxe/T89uWQvdLkFmdHcBghjMF/gDrRGYxSL7odXjPILxIqkRfT8eFW9WITGI/lyK14cnvABsVxhNrwShPnFfPO2osIfsH7hwxsVmltXE1Bk5CubDLbL2tHipOUIq8de4g+hjvJarH66tOi1e5jGfmX1etUFWgNBaJcmO+Q1YpLn7hmL9BzgqLP4JrGSRvV3+UbYPSX/i/8v3zVpW7Q4RjvtIW8u8hUcxSt6SsZnrTwXcTSpSOA7Y0czuaPYgPy75Ln5jZs0aTor1PGn0eEClamXDc+Bl0lZQ1+CZWMUyKRbBpZZ641kmq1pkz3Xi2rnq7ueZWbN14QWf6Ssssr07et32IGllvP0neI3rwsVE3zp07lh9KUwPdyN7qmYPSkl0poeGn7eAt5LotaSF8Gy93mHfpaxG2ptllB7FWhjPZNwFmJJR+H//Vfxpkc8Y3BC+0Mza0rGn/ePxAM/ReEp5MQ2sG4F9iwW2WjjffaTBrifwDKemAow+194GeLtc7y+j8mRGdxdBsU4E/h0W21xPJ2kePBV9mrCqWXXanGOEC9CcQ5oCMwKfvDXpw1sJJPUBtsY9oysW2eUpPPp9dyWj8hkdR7Eex+ucAAbWexqhlNdpYGkze13ScaT6C5eZ2b5VGVwFkXQDHsUAr2levxnjqAH39if17t8Cy9dSK7Fw30kEcJ41s1Vb2HdTXO020aV4DlcTH1nWQTYdR1/gFtJU/0Z84nhFC8e8hxtWo82sX7P75bfHaneNdEcIbaaeD+ODZlqDhfH1wo3zJFrf6RZewXn9E/4s/B6YtYUU82lxB/lUuBG5oEXl78Qh6UFg/bC4m5ld29L+zZ4n1gDy08MH4077tgge/kG+cT0Ur71uSUCqsPb1NTwjryQOg4zqE2r6NycVu/M7/at4XlTT//QXBFHfckZ/JQ3AnWnrF9k8Dr/PXdqeEo2C7LbhwOJmrQfIMroOmdHdRQiiMMnD+z1gUYva9s+VtDZe65V48rYwa1Of0mXw+rnZwyrDH44ntRQtLzeSBuPe0r+RiuQk/AhcBlxejch8RttRrPNw1VGA1S2yp1vav9aRtDf+2QM428wODwbDV/gkfDwwV1f/XEqaBp9OJel1+5vZJUX39VZiTwHLhlXvAKtY1DaxsnIjaWa8rzi4Q2+LZvbbBbiK1Di5H0/xbXff7FIQBIEuB3bLWX2UmZ3ezP65qcmTm9lfRfeL86K+/7aoeHp3qQitwR4gFbL7CFihGaVyFOf1VH8fWKo1o6+N47iPVABp5ZbE8BTr38CJYfFmi2zH5vYtBZKWwo1V8K4J87XmeA4Or7nIN64Hk7YQbY2vyTeuhwJfWtT+eUFwbL1JmpF3uJmd3d7zZNQWQVxwH2BvYEbG4zPXV3DXVVMexFPIHyq300XSCrjDd9Yim7/C08lfK7KtpXMuhztaE62SrE67G5IZ3V0IxXqOtG3JMha1/aZQ4IH7ExdWa7VGRdK0eAr3RjmrHwb+Zu3sB1tqQgRiV9yDOn/B5onAPbjHtGTqlhmlo0DBvKbFtNpC+K78iIsG/YBHxCZKOoVUDfVcs8oKLFWDgt7Po3CPf9FqvaBa+wKpeOKTwAYWlb52r71IWhRIUt6vNLO9iuxzGK5Km3ATHm2sasZNSHU8E8hVhz8dV9+1gn3vBBKHwqwtlATMj/fEBrjHItu8pIPOH5PwNPJEC2EEHgVt7nO0NF772QMXvVveotKkbRZ0BDnHrHnF/VCv+jlpOdTi5SybKPjfHWCW3wkiOLYWId+4XgyYog2nn4CbSrnG9VsWeV/tUiFpJdxgAZ+fLNjVnZNdkVDrvyY+J9sM6MGvuEvoDaCpK28k7qy82Mw+Lfv4/J5yCHAGqXGcy/3ALmbt+3wH5/qbwBxh1Wlm9q+OjzSjXsmM7i6EYu1F2g/0AouKty8peqzfbG7C23KB150ua21ofxMmb0cBJ5FGy78BtmmLOm65Ce9tDfxGvzlNU+E+wo27a9ryfjMqQ4GCeYfUhWsNSXeTpvWubWaPB2GVr3CBpb+AOcysaROULoakS3A9BvAJ9erNRTAUa17c8E4MlZuBv3UkclZKJK1O2uv4dDM7Kmeb8IjmsTmHXAAcUs1MoFzCGI8GciPSVwD75f4vJF2Fd44Ar8MvqpERIqS/4pkb31tkbY2MthtJJwPHhMUxwFpm9kIz4+qLT+uTaOkQiywu4Vj64ynmvfDk2Nlb1EaJ8xwx91pkmzW3byfHtTCeVQLwAzuzHHOzIPm11wtQvF61kJHkG9dDgQ8q5fySdDFe1gYumLVtJa6b0XkUa2o8q2Z/YH4acbfTK/hMsylD8aj2TZXKBgpBmquALYtsbsTLN09r77073GNvw9XXwXWUVqu20zWjOrTlRptRP9xGWl+4U5hotIkQ2diLNGozH3BDMKhbO7bRzE4F1iHtmDgr8Kykv4ebTtUw5wnzXsizAzEeaUyYH69P/1bSuaHOPaP65EZ/Fq/aKErLTTmvdwQw71d9aVg3GfmRx67MkXh9HnhbmGbfd6h73Zg0FrIDcFpZR9c2ps15PSn6EbpDXES+wT0EOLhWDG6YdG88BZ8MJx74vYBbQlpvQm5Xi2YFsoITJIkez6xYMze3b2eQ97lPDG7D9USKGtyBk0gN7teBU0o5nlCXn+iZzAIs18ohF+PGOcCmirV8KcejWFKsWZmONDtoLfoxN1/jmWin4d+hhSg+D/wSF9wbgjuq5wCmtchWt8gOtciusciGVjjb5Bi8DhZgm9ACLaOGUax5Q5nYt8A5/Mn8PI+7Hm+g0OAejztTV8Lb2V1RQYN7Cfy+UMzg/gl3kJ/awXv3waQG90hgh8zg7r5kke4uhmJdj9cyA+xokd3cruOlOfFkn2QyGZvZkHYcPzNeC7Nyzupbgb2thtp3hVrAzfDod2E7KgP+B5xLlnpeVRTrc7z1zChgqmpHNjuLpMnwh/gUuB7rjGY2RtIg3PffGxccmr25utSuhKRVgKdxVfdx+GSr2U4DirUJbgwkhsKhFtm55R5ns+ORdsejI+DR4Usl9cZLbrbL2fVgMzu/4gNsB5K2w6fCSVrlo8CWZvanlFcLvYGZPdTseWKdBiTiZJtZZPeWeJxb4K0rE2fuQWZ2YQvjyf2MjcXruEvezULSbsDVYfEsMzuixf1j7UPqbHvcouL9z9t0bRc4Wybv5xdm4Hz8aZa48no3OXQcnh4+NOfnbYsqK+7XVgr+xp8Ai1oZWkRldJycFPJDgY1oRHyB55l8gMeM8/kOuAS4wirUxSEhBIT2Bs4jFbjM5VlgezMrXmXe+vmXD+dI7qmbmZX2fphRX2SR7q5HrgJtk/rC1jDvFbs96a0xCqq7bT3+e/yGe0bO6u2AV0OqW01gZuPN7HYzWxNYGL/pJ1E0AZsAjwFvS9ozGEsZlSdpD9MPqGjf33IQBKjuDItTE1qHmNl3pJPJKUkF5Lo05j2NkzTb3sB1wSFWfP/I7sOjsglnK9Y2ZRxia+RGfX+X1A9vCZMY3BNwfYuaNrgBzOxW/L6X3AfXAR6TNB35ke6pWznVqzmvlyndCCfV9t5EanCf2orBPQVe953s/+9yGNyBe/H/N8DWbcjwupq06/BairVmSzsnKNaUirW6Yh2pWP9VrC/wCPADeBbXxsAMPEeau7A80Jtf8BZFZ+F18IsBU1hkS1pke1hk51lkz9SqwR24jrS2e148WyajBlCsyUKJ49vAY/zBxjyLOB+XVnyPQoP7SbwzxRxmdlIVDO5+uA7DpRQ3uM8A1uyEwT0d3q0iMbjPyAzujCzS3cUIXsaP8AcSwDwWFReWafE80pG4qA545G1ZM/uwhUOKnWNz/KaWTExH461pbmjveCpBELraCzd4ZinYPAK/OV/U0ZtwRvtRnNcuZluL7LYqDqckhLTIRLX0jlD2kGSZfIJrDvyCR7v/rM4oK0doYZVbb9tqdo1inQAcFxbHAetYZM+0cEhZkHQ8buiAG9qH4SYOeKnP1mZ2f6XH1RkkrYgLBvUPq97HDcTEkbqPmV1e5FA/PtbseHoywMMWWbGWOx0Z14J4a7CkveV1uCBds5MYxXl1wK4bEJVP+bigNdfyrWmaKNZOeHYBuMjbirldR0KJ2OLkR7EXIHUiFOc3RnIuU9OIaGA0m7Isg3m/rR1NapkgXvgmfp8cg/cc/7y6o+q+hBKSA4D9aGQ6PscTtT+iWFR7OH4vucKs/K3ymkPe//020jaDufyG31fu7sT5G/BsyQ3CqudwAz5LK+/mZJHuLkZ4qOZGu/fo4KnOxNPCwSNvd0tqtpav6Fj8prUknrIG3r7rekmXhIl2TWFmv5i3zJkLn0Dn1ggOwOszv5J0Q2iXllF+hua87ip13U+Qah9sHARckiyTpOZ7WlJjoUtjZmPwyFtiDP1b0tKtHBaRZgb0Bu5RXJVMmtx74qmkBvdvwDr1ZnADhNro1XClffCJaW4v69Yi3V/jTkqApYMjuFOEsqWHSA3uR4C9WjG41yP9Do0GdiunwR3IdQpu3exeKbeQCp0tDxykWHsq1iWK9TqeYfAScD7+HVmQpgb3aHxSfzauEzEvZ3MtjWG/Rs61u+y9rmBwA5jZO3jpF0Bf4Lxq68Z0RxRrGcW6EfiK3zmWp5mOc3EXUtM08keBbYFZzOyoKhvcO+HZOMUM7qHAUp0xuAP/IjW4h+Mp6pnBnZFFursiijUjrh7eExcMm80im9DyUUXO4+k3LwKLhlX34j2826veOBleM5Ob7v46rm7+RfGjagNJy+ItJLalaQuJF3ABtrvM2v/3zWidgqjZ/RbZxi3sXjdIOhcXWAHYw8yuDusXxBPxBAwD5rRmeiJ3NSQNwY1p8GnbUi29d8Xqhd+Tksjit8AKFlWulZCky/CawFyGAeuZ2VtFDqkbJM2NG7dzFWw60cyOL3JIemysB0gnnXNZ1PH7fHD2PkPqdHsTV/9tViNEsabBe7on6ukHWJTfKqschGypYfiz4iv8+9tkkhUcEfPgkevtgLaWcI3H03dfzfn5IPf5Lmkgfs9MuiHMHsQauwySpsRb0yVCfZub2T1VHFK3QLF64mJjh9DIinyKz+Q+Ji1lSPmRNKpd9UyEEOg5h7RjRiGX450lOvW8lbQGXprYgP9V1jWzxzpzzoyuQ2Z0d1EU5/Xm7LCYTZh4vUoaYYjM7IQOnms3XLU1iXKPBHY2s/915HyVJERaDsBv2AMKNn+D63FeYe3s35jRMmFy+gue6vqdRVaY9l+XSFoOj2ABPG6WiihJuo00StaiSFRXItRyv4RnxwD8n5n9o8VjvGb3KWCpsOodYBWLKtP6T9JDwHo5q77EI9xl7ylbCSTNhBvei+Ssvt3MWqyjV5wnvLadRfbfDl6/N16rvFZY9SWwQmv1n4p1HbBzWHwUWK9SkV5JDwOJsvayDOE13PjPTRFfmjR9vzkMdz7lGthvtaYYLulUPNIGrfQMr2ckbUuajfc1sJCZjarikLosiieV3h3Eb8zKG7jr6/cmuxpeOnUZ8L9aie6GeextwBJFNv8F7G9m15bgOjPhf5kZwqohZqVrTZhR/2RGdxdFsTbE6/IA7rPI2iyG1uRc0nr4xCcpR9jUzO7r4LkWw5Vnc9tynQocXw/R4hC13xFX5lykYPNovM7wPDP7oMJD67Io1pPA6mFxoEX1H7UJ6ZCf4OJwBgwysx/CtsH4gxt8MjmvmY2rxjgrTRBbfB0XtjG8d3eLtdqKNQOedZJEZJ8ENih3O6OgvP4EaQbM+7jB3aU0HyRNg7/PwWHVRFyFt9nUecXaGBeUAzjDIvtnc/u2cN0GXIJpx7DqZ2AlM/uoxeNibUEqVvgbsKhF9k17r99RNIMOZSrOZmZgQT5lJqYAZmzHKUYQxEctal/Hj/C/+govCRsHzBVEGrsc4R76CJA4LE81s2NaOCSjnSjWgsDBTGRXPmEyXgc+pVhU+zu8i8OVZvZVZUfZMqHbwdUUL4v5BNfdeLvItvZepyce4V4trHoU7/RQ7pKWjDoiM7q7KIrVA48KzIJX18xmUccfvpKOAv4TFn/HhdVanPy0cK6pgStJexeCR6t2qLSCZUcJD/w1cON7Y5rW2T2E15090t50/Ix8FOscPMUfXDCrS6RqSXliYIeb2dk52/4HbBQW9zSzqwqP76pI+gepaNcXwOItpRIDKNa8uOGdZKHcAuxUrhZzkjYCbifN2gEY2NXSeBMkzYNPUBMmALua2U1F9/cSpx/C4lMWWWFbxrZc83RSdeq/cCGil1o4BMUaiNdITx9W7WqRXdfea7d5jLGmxDMzcqPYc7bh0B/Jj2C/hkfiVg/b97LIrmz3eKTjgCQT7TIzay6VtksgaT48u6U3nnq/WHsFXzPyUawGPFPjUH5lPd7AK52b3oEb8WDMZcCDtRY0CZlT/wEOb2aX2/Fna9N4fceudzLeSx7cCbFEV30eZHSczOjuwhSk+B1rkZ3S4XO5kXkrkKQVfggs19EbVjjfobhCehIp+gEXnKi4CnFnkDQvrni+O95/OZcPceP7+iz1rWMozuvNeqRFdmYVh1MyJC2Ap48CvGZmy+RsW4FUyO9TYIHu4jGX1AN3wq0cVl1iZvs3f0Q4LtZyeJQ7ae93pkVW8pZCQYjnWlw9OWG0mfUr9bVqhVBDW3ivN+DvzZU/KNY3uNP3D6B/exwgkg7B6y/BJ/dbtNZuJ5Si3I7XnIL3c9+yVGnlHVYSb+QPGniZfCP7u8JxKdaKuDo7eMnSfBbZmDaPT5oCj3JPi2cjzFcLtbTlRtJJuMgpeEbG2i0J7GUUR7H6AbswkUP4iPl5nbShXT7f4GK9V5lVTj+jPUiaFZ+vrlBk8wTcmXduqT4nUl5m6UQ8Q+u5Fg7J6KZkRncXRrHmAD7HJwWfA/N2JvITHuovkqZV3w1s1ZlIbui7+l9SQZSJwNHAmfX24AwR/D1wgaw5CjaPxD3CF5rZ15UdWX2jOC/d+gaLbOcWdq8rJL1OWsM8v5l9nLPtcbznPcCOZnZzpcdXLUIN3tt4xwOANczsqVaPi7UJfl9KSmEOtcjObf6Ido/r77goZMLoMMYfzGzm4kfVP8FJOhF/lgwnjSSDi9+dWHi/LtAVWciitpXcSNoGnzAnxux+ZnZpq8flt98aASxskf3UwiEtnasnrm6ca2AvCjTbQz7wF/AGXzGG11iL74BfOM3M/tXKccl178Mzp6Cdn11JR+BdRwBuMOs698mWkDQ5Lj45R1jVre6VnUWxZgMO4mf25U2m4k2gaXhgIl4ucjnwcC07gEM55I3AdEU2fwdsGzo0lOp6s+Hzk2nDqiPNukZgIKP0ZEZ3F0dxnqjLWhbZE506n6cZvkoqAnOcmZ3UyXMOxFslrZWz+h68V+LIzpy7GoRI3SZ4JH+1gs0T8XrDc4AX682xUA0UqzfwJz7hfdciW7SVQ+qGgolyXn9qSWsCj4fFd/E0625TqlBg4H6Gp46ObvW4WPsAiZFmuJBXp/q7B6MzIlVXB7gE2AGvFfzIzBbozDVqHUkj8ff6MZ4KfWzO5vOAw3I/n4p1DHByWNzFIru+DddYDa/T7R1WtaqUHq41I15Tnwh+bmWR3dnCIYXHT4dHxVYMP8uQOnyaYwJNlcTft8gmSJoeTyFvwD+787blXl/gYPwJmNsi+7PV41yZ+QvS2vGFzez91o7rKkjaBO9kAP53X8CsMmKK9UjIClmBcRzOx2zB6zRQvL/Al7ihfU2ta1WEedcQ/L5ULPvkMWAns4454pq5Zm+8s8JyYdU9eFZONq/LKEpmdHdxFGsbPJIMcItFtkOnzymtj9fyCJ/UbtKSqE4bz9kDn9Ael7P6c1zk4s3iR9U+QRTrEFwMqHfB5lfx1PPbuotQVkdRrKF4audEYIr2pF3WMpIG4el6wtPI50se2MHQe4G093O3aosThLSeAVYKq84ysyPadGycVy8/DljXInu6E+M4FzgoZ/VJeOlOEv191cyW7cj56wVJXwGzAcPMbEZJhwP/l7PLDXj7u/EAirUObkADnG+RHUwLSFoE7zedCB5djddctsVYvZ1UI6TF51yoWZ2f1MBeEU8TbwnDS4UKlcSbvQ8VZKos2dbnmGLdggupQRvLwiQdACRp/neYWVt6hHcpJN1D2nrtXDM7tIrDqUmCA3sbfuQo3mZRhuK5OvlMwI3Hy4DH6sHRK2kGPHCzZpHNBpwInFDqCH1B688v8O/5yFJeI6NrkRndXRzF6oP3rx2ATz5ntsh+7vR5paOBZDLwO7BMbmpsJ867AT55S1J1xuKT3Svr2XsYHgr7AfuTtpNI+AGfMF2WCW8UR7GuAXYNi0tbZK9XcTglRdITuCgfuEDhqznbNgKSlnqvhe11+z1oL0Eo6S1csMyAFVsT04JJkZwrcZ0F8PKOlS2y99p5/V54/XauEXeYmZ1TUOec1/atKyLpHby06C8zmzys2x2v70zS+e8DtjOzv0Kv7KSF4ksWWbH6yuTcs+ClS0lLwAdxhfRWWw4p1tZ45B08rXyh3A4HoVZ1GVIDewXS50tzfAW8Qmpgv94BJfH98BaZ0A5lbcWaH4/aN+Cf27kssl9buE4vXORu9rCqzQZ+V0LSHPjfbTJcB2ApMxtazTHVCoo1PWM4kA84hKH0p5i+uPgS4xI8qj2s0mPsKJJWxYUzZyqy+Rc8uv1QGa6be98Zhz+busy8JKM8ZEZ3N0Cx/o9UwbEkNY4hCncbaXThfWD51lSG23ju2cK5cyNH1wIHtCW9tJaR1AePYhxK056RY3GHw7lm9k6Fh1bTKNZhwFlhsUPKvrWKpD1xwwUKIjThe/YGabum9czsEboRkv4JnBYWP8CNilYzHRSrF55yun5Y9S2wgkVtE/8JtaK3AxuEVRPxSO51YfugcE6AO81sq6Zn6TpIeo4066D3pIi2tDleg51k8jyDt5X8TbE+wdtDjgGmsqipES2pP/AsqVbIa3gNf+tp1Z4W/j4wMKzaHs8OSQzslfDvTo9ixwfG49+xF3Ahsxct6nwqbXC0fo8bz3lZLK0eG+tKXB8E4BSL7Nhm91We0OSDZrZhhwdd50h5JQ0vAivXQ6S2XCjWonxJxAdsztv04K/CHUK5mxvbT9XT3ypkIP0T/383FNnlFWCbcmjoBPHc1/HWfOBz04tbOCQjAyj+Qc3oelyR83qvEAXqFGHysBsuYAIuOnNNMBI6e+6vgVWBC3JW7wq8FCJfdYuZjQ2T9qXweu87ca88eG/iPYG3JT0uaZPwYMnwpiUJg6s0hnJxB+4pB9g+lFoAk75nJ+fs++9KDqxGOAs3xAAWJL8EpVmCgbcNPjkCj6I+oFjF+rXmEQzBR0gN7rHAlonBHZgq53VJ2s7UOLnvcdJ7N7O7ccdGYiSvCjwZtDqS/1tfYOHCEwYn5N2kBvdnwEZtMbgD55Aa3N/h+ghf45Gvg/H7bKHBPQJ3xvwLWAWY2iJb3iI73CK7oxQGN0CIFiadOOYBFmvH4SeQ3hMOCb3omxDuFUfnrDq52H7diP8DklamK+BzlG6FYjXoCG2l9fUeV/I217AVLxcY3L34BvgHxkzWaNua2RN1ZnBPi6fAn0pxO+Z8YJUyGdyT4c7YxOC+Gdf3yMholWxC3w0IqrFJK5JFyI8gd/y8PjHaAkgES7YkfwLQmXOPNbO/42mdiZbmosBrIa2nrjHnmRAdmwc3LHIntWviE8OPJB0cUlm7M2/lvF68aqMoA6EGLNFEmIGmdWl34vWkAKtIWqVCQ6sJzPu/7oFHJAGOkrRkC4ekx7oI1Ua4PgT4PeSuUHZTFEkzAU+TRnX/wDMMCltWdTejO1eYKs9xYWZP4iUSSenSEsCzfMWnObstk3tMcCheRyo2ORxYvyWhI8WaTrE2VqxTFOtt4G85mweRpqfn8h4uBrUbMB8w0CLbzCI7zSJ7ziIrjP+VklwBv22a3asAi+wrUjHAfjT/XN0Kf08AT5vZ883s1y0ws7HAgTmrTpdUTMW6y6FYU2pbnco9/MJF3M7DLMQ3OTs0MJG+3A2sxnhmN7P/q8dyNknL4mKDGxfZ/CfedvbgMurknE/qQPsQ2Kc7lXxldI4svbybUNDr+AqLbO+Sndt7FP6PVFhtYzN7oITnXxD3LC6Us/oc4KiuJEAWDOtd8QjNvAWbf8drVC+wbtB7tRiKJwk5tbvvb61TUB92jZntXrB9F7zEArxly/p0MyQdD8Rh8S1cR6LVml8AxZoXTx8eEFbdAuxU+BmSNBfwKDBXWJUYgm8UGc+6wMNhsU0q2/WMpEuBfcLiEsXqZcO9+hES47cHP7EfA0ODscstsn1y9j0LOCwsjsZTyl+ZtL1jgmejgJdxJ/MLwMst1UOXG0kz4inmwlXfF2hHivmMeOR/cjzqPa9FaeQuZJW9SeqEXNfMHi3h8OsWSTfjpQbgWin7VnM85US7aWE+42y+YE2+K1JGMRk/0MjZjOVKM/ulyCnqgvB5PwjPZijWuu89XHj3wyLbSjWGXYFrwuJoXGOlXTohGd2bLNLdfbgNN1YAdlBcushpMLCTlE8BN4XWYqU6/wd4dP7GnNWHAk8FAZ4ugZn9YWYX4BPLjfEWFwlT4RPUTyXdJWm1UqTy1xlDw+8padoHvd65nzRaulVIYcvlZpjU1GU9ScvQ/fgP3qIJ3NA4qq0HWmSf4N+pJKq5PXB67j6SFsWNtcTg/hqvCW1icAeySHcB4V69Em5gwkQGchWe+A1LJ/sF5fPE4J4IbMsQ3lOs1RXrGMX6H+7weB8vj9qD5g3uH/DJ+JK4M24ti+x4i+yhahrcAGb2I2mK+XykafStHxvZj6Qt83rTtKxiI1KD+1XynxfdnSNI5zt7S1qupZ3rDcWS1tReWkifcwvv8hzr5BncPWhkOh6nByvzF4NsjJ1R5wb3VLhuxHkUN7hvBJYrs8G9CKkwIsB+mcGd0V4yo7ubYJGNwlsqgKerbdfC7h3hVOCu8Hpq4O5SpkSb2ShgZ1z9O4lurwC8KWmdUl2nFjCzRjO738zWwdNhL8eFiMCdGpsDT+HvfbfQo7U7MDTn9eAqjaEsmNlfeBo5uFNho4Lt40nFxADapITclQhZLXvgRhrA8ZKa1Ak3e3xkLwPbkmooHKFYhwJIWhE3jpI+xx8AK7XSkaG7Gd1Fa7oLCXWUq+DiZO7muBb4nMUUq6+kHYD/Yyq8ynsPnmQIQ3Cj/km8LnkjmiqMj8ej2LfnrPsTF8e70CJ70yKb0PG3VzZyx9vmFPPAGaTOjt1DxkYS9cvVdzgpS3FNMe8pnWSeCLg4VyujXtGiml6L62ouYhRPcjkfMCdjc3aYil+YkVOYyAAbYWvbBHu+3j8XkhbDtSGKfXfG4V1hdg5zxHKNYUr8e5w4w68ws+vLdb2MrktmdHcvLs95vVcpTxxEOHbFJ6vg06mrSxmNDXXQl+CRlKTpxQDgYUnHd0XRMTN718z2AWbFDa1ckZ/F8ZKBryQNCamMXZncuu7B1RpEGcnN5NixyPZrSP//m4fIbLcitGQ5Iyz2wu8xPdt8fGT/wx13CWdpS52MRwn7h3WvAquatapynhvt7Q5Gd6uR7oRQl70GXhvvnX+foAfv8jhbcwOH4f00tgFmY208Ct6S4Nmq4Zpr4eJoCUeF+uda5g687AqgXXokFtkvpJ/3HqTlFWsCSfT2HdK2ghkpF5BmxixB/ve+bpDUoEHaWrPqLT7kJ95mN34izYTqiTErrzEL6/E7A+wHO9asuhkepULSTsBLNC23A/gSb9N1aTkdC2EOexle6gLu/D+42QMyMlqgyxkpGS3yBmm0cDnFpZ20h3Zhm5NOzraiHSmg7bjOa3gqYSI+JXwy8oCkAc0eWMeY2QgzOxVPq94Rb4eRMBCIgK8lXStpcOVHWBGG5rweXKUxlJMngR/D640kTZO7MYgEnZGzqiSihXVITKpQvAxeatJmLLLLgBPDoliYY5h90iT2cWAtMxvRhlPlRnt/a3avrkObIt0AijUtQ1iFY3mZ/RjF0bibdxFWZBEamjHZE8Gz3WkqePZsEDw7CZgz7P8MdaAabGY/AM+FxQXbk50ROBdPtQcvDVsMyG0hdko9KU9XiiDAeEDOqpPqyTEtaR4N0GVMxu98z218y2Lk5nEMYDQLcSWzMMC+tmXsG3uk3qPaCZJ6SToHb6FaWGoF7mRaqkJ9sfcn1Qf4HW9DVk7xxYwuTGZ0dyMsMiO/fdieJb+Gp2PuROrZP0VSyUWfQn3Spnj0N5lwrIenXC9f6uvVCmY23sxuNrPl8PT6W0nTbXsBu+B/g0clrdvF6r6/JJ34dykFcwAzm4gLfIHXcG5ZZLfL8QggwHahX2i3wrxH9x6k95gTO9BKMOJ7XgSgJ94jYTYexdtV/dHSgTl0t/TyopFuxZJizadYeyjWlYr1Aa5i/j968U9mpF+TKsxxNGI8iRvRGwDTWmSLWGT7WGTXWGSfhOcVOddZETgkLI4B9qojMcUOp5gHBf5TJq34mAvwLAKAT8hXSM/IIai5JwKyU5PvtKw5JE0laU/10zvAJ/zM3vxFv0k79AUW5FNWYncbbv3sPdvLvqjfWu1iBMfI46Tf9VwacWfzZpWoUZe0NHB2zqrdzezT5vbPyGiNTL28m6FY0+Apqn2BX4BBFtmYlo/qwHWk4/BeowAjgaXN7LNSXydcaw3cWEn6tY7HhVQu6Cqe35aQNCvu0d8XmKZg81v4ROO/bVV6rmUU6xm8XhRgupB+2WUIAmlJFsOTZlbYPgxJR5NOwq8ys5I7z+oBSWeTRrmfBVZvS8QvOKKOpYET2YE0cdH4FrGCRa2mlSfnuYLUcbmYmb3TrjdQZ0haE58Mw5xcxq68ibf7Wp20Fr44hsudvQl8A/wENHIqcGxb7tGK1TccnYipHWmRndmR91ENJA0Cks/V+2bWrmh3eP+fALNwY3jl7GlmV5VqnF0RSdPjmTHJs3F1M3u6ikPKI5TFrYHYHdgGo3f+DsBcjGc27mcujrQruq7RFwImdwAzF9k8DG8H9lSFxjINnh06R1h1jpkd1vwRGRmtk0W6uxlBzTXxuk+L99kuBycDd4fX/XFhtSnKcaHQI9b7wjq9cJXLW4LqZZfGzL4xs6PxNj0H4G1mEhbHU7Q+lXRouf4HFWRozusuF+3GBWOSKfXqYbJeyEWkUcddJM1WkZHVHv8m7b+9Cm2o2QwT3LOAE2nEY4QjQ0q/mAV4ULH6t/H63SLSHSLZC7Mn67AN8A9gV/bBlXy3p6nBnQienc1f7MS5vMoPwEzAFHgBhbtGjqbtAlfHkxrcr5Affap5zOw7XBkfYCFJC7W0f5Pj3TF+Aj+Qa3B/g9/bM1og9KLOLcW5SFIxBeyKImkeSSfiGVyPYeyUZ3BPD6zOz+zFv9iZ/vaEbdFVDW45++IlI8UM7mfwNoVPVWo8uIbKHGHVS5ShVDKj+5EZ3d2T3BTzkgqqJeQIqyUtHBYBripXunNQK12T/PSxbYE3QopQl8fMRpvZxbjgxza4IFTCbPhE9RtJJ9dTbVsBQ3NeD67SGMpGiPolXQZEWkuWu89vwPlhsSdwZGVGV1sEtdrc+9dpkuZobv8w0b6a3BrwcfyT/gwmNd4XAe5SrD5tGEKXrOlWrAbFWlSxDlKs2/EI07vMyr9YGDec8/kTeAgv9VkVmNoiW54hHMlpbMWvLMN3+Kd5NWBOziYtDdgXbzHZu8lZ0/EsCfwzLI4H9rDIJja3fw2Tm2JerHSkNa7hSf6ctDQndwdF/4zWuYI0g2gh2qkDUSompY9Lz+Luk3/jIqlOX1ylYjfeY3+2ZnVmsMvsNItsdDXGWwlC95XLcX2GYs6Q03GdjR8qOKx/4OWL4Bmh22XftYxSkKWXd0MUS3i6VZJYOY9FZUv9nh9/2CUT1H+Z2WktHFKKa26GN6lJ6g7H417Kc7pDunlCcHCsihtlGxVsHgdcB5xpZh8VHlurhAl4Ip5ynUW2azXHUw5CfXLyP3nDzJYqss8APELSDxgLzBF6Anc7JF2CG2/gKuTrFn7PJfXB9Q82C6sagb2T1NzQiukFvBsCeLnKTi3VDEt6AddVAOgZavLrDsVqwFsTro6bxasC0zV7wBhgOD8xK2fi6uRvFLbqCvee84EDAViKsWxC4sg4kiF8h99/EuX5R4AtC9v+KFYv3HmYZLUcb5GdSB0iaXb8Owvwmpkt087jF8TF5kQ/4BBeoTfLF9a+ZxRH0lL4Z0nAaGABM/umAtf19HHYDReXzRcGEzAP7kKelwfozWnAs93h/xpK4+7AXQ2F/Absamb3VHhMq+CipkkGzoZm9mAlx5DRdcki3d2QIoJqe5TtWm7Q/S1n1amS1ivX9cI178EfYS+HVb3wlNJ7u6q6eTFCi7WnzWxjPIJ3De6AABfq2gv4QNLdklaq0jDby/ukwnFdMb08ESN8LSwuKWmBIvuMIFVu7oM3YOqu/JO0XnZtCu5nkiYH7iE1uMcBW+fWwlpknwAb412lwTMMTm/luolTb1Q9GdyK1UOxllCswxTrblyYbyhwDl5uVGhw/wbcx3iO4jL8r3IlH1pkZ1hkrzTTG/ufJAY3TKBXnijSMmZ2M/7/SP7e6wKPSk1S+48i/Z6/DfynXW+2hjCzr0gzdZaWNEs7T/Ev3ESDFYHeLIt/ZjPaQFC6vigsTk6ZSxRy0se/wJ2BfyPX4B4ArAMcznh24moWZmE72TayyJ7pJgb3GrgDvZjB/RIwuAoG90Dc4ZoY3CdnBndGKcki3d0UxZoRrwnriUvczNbM5Kk015MiYEhY/BUXVvu8+SNKcs1euDruP3NWfwfsaGbPlPPatUqoET4Y2I+mbX9ewNPz763lFjSK9Q7uRBgPTGFR10v7knQo6aTwRDM7vsg+M+ETuj7AKGB2M/u5YoOsISRtADwQFn8DFjaz7yRNifd6Xj1sG40r3z5W9DyxNsYN9MQhfZhFdk4z1/wG11H43syK1d7XBIrVA3dCrk4ayW6pz/aveA3l08BTwNtJOreksbjD7i0zG1z0etLOeBQ7YVeGcBNe9z4Z8IVFNlfYd2W8/U8ynteB9czsZ8VaGBdP64U72pazqCItgspGwXPwQDO7qIXdc4+bE09H7kEDf3IUU4S8gbeBJepIxb2qBKfOR6SiqxuY2UMlPP+UeFnbbsDKTXboi+eUDAZm5nfEJcB5Ftl3pRpDrROyYA7D3XfF9BxOA46rtPBr0JZ4CHfcgke716knh2pG7ZMZ3d0YxbqTVEhtM4vs3rJdy1Os7iKtk3kHWKEwnbBM114fnwROH1Y14r1+T+6uN9QgMLcPXttWaDB8DJwJXB/aM9UUinU9afbEEhbZ0CoOpywEgzqphP0cmKdYaYSkC0l70Z5gZlHlRllbSLoG15EAN+R2Bh4EkhaCf+Cpgs81PTrnPLH2AS4NiwZsb5H9t8j1fsMdVx+a2YKdfgMlQrF6AkviBvZquMhcS4KSP+NG9lO4of1Oc0acpJ/w++gXZm44F2xfB3d+JGnjx5jZqWFczwFJRs0Ai9xBJGlx4FHS+/M7TMV6HM5dwHJh3X8ssrrvSy9pMO5IAHjEzNqU9SXpYtxRCjCEIWwILBuWd7DIbil+ZEYhBU6hz4BFOvOcC3Ob1UnTxyfP34E0fXw+oBff4Q7Vyy2yLivAWAxJ/fAsyyZaJXgv+p3N7OHKjsqRNARInp8/4sJt3bJkK6N8ZEZ3N0axNgTuD4v3WWSbtrR/p68nTY2nfM8fVt0K7FCJOmtJM+NKr2vkrH4S+FsQYeuWBAGjHXDhkEUKNg/D6zIvrkRPzLaiWEfgTgGA3S2ya6o4nLIh6TFgrbC4vJm9XGSf2YFPcSNnJB7t7lYTuQRJ0+I1r4lI4Jek6rO/4hHUV5seWeRcsWJcMRs8HX1di9I2Q2GiPQGfUr9iZss1PUtlCHXPS5G271oJmLKFQ0aQRrGfBt5ra6RU0qfA3MAvZjZdwbYlcOM9kVq7CDgoub8r1jmkvXfXtyidXAc178dwjXNYlZ9Yc1I08iNgcDlaW1aaEOX7Apgdz9SZPggjtnTMzOGY3rho3ewMYQn87wX+/V/IovpvCVkJwv/gKTzjA2CImcUdOM/cuJNvV1yoNJ8BeE+VRUlcXu/imWS3dMXsrNaQNA8eeCmcZwA8gc/FKimWNglJ6+JRbuFBmbUqpZSe0b3Iarq7Nw+T1kJupLhoe6KSESYXm+MRJ4DtcGOv7ATDeh18Ip1MMNcA3gqpqd0SMxtnZtcCiwEb4pORhBnw9PyvJZ0TDLxaYGjO68FVGkMluDHn9U7Fdgh1oteHxf6kUe9uR3AM5b7/OcLv4cAabTW4A0OApOa7N3CPYuVOFqcgqa+tcLswxeqtWCsq1tGK9TDuUHgRr3den6YG90/Af/Ea64WBgRbZ1hbZBRZZs1HtZkgMxKlyO1GE9OcHSA3uu4GDCxyquX//vDpOM3sfN4K+ZlpglWBwG4arlde9wQ2TuhMkGWW98P9XaxwBk1pJXWRmv1hkj+NOY/A4apcTlCwX4X9wAO40Azg6GNCtImlKSXtIegZ3dhxHrsGdqI/vjX/bVgKm4kn82bqYRXZdNzW4N8J1SgoN7kb8b7huFQ3uWfBnbXI/+3dmcGeUiyzS3c0piOgca5GdUvZrurr43WGxEb/hPl7u6+ZcfxXgZvLTqs8Ejs3aQkBosXYksDX5jrmJeHbCGWbVS+lWrAG4IQXwtEW2erXGUk5CZsgwvGb7J2CQWVPdhaB2/gH+vxqOK5l32RYzLRHUcN8nNf7GAEua2QftPpdHkO8BEqfct8AKFtm3YaKWKB/fYWZbd27kLY6jDz6VXx2PZq9IYQprPj+SRrGfAj4qlTCTpCdJ6+P7mdnoIE75PJ48C64NsbaZ/ZV3bJynyn+vRbYZBaiv5uBvfMCs9AXgVf7gfpYys08K961XJK1FGqW+2cx2bGHfAcBX+P97DP7dHgagWCvgf2vwz+J8XcU5UQkknU7abvFBYKNmSnhaTh8HC+njYn6SpleNeIu4Myyy1+imhL/dv3EnZmG72G9xfZ1nKz2uhKD78xR+TwV3HG5Sy5o2GfVNZnR3cxRrDrxmNKkdnbcSoixSnrE/HK+fqZiYiKTp8J69m+SsfgXY3sy+qNQ4ahlJc+Gq2HtQ2ObEJ42nA49Vow2bYn2LO01GAtN2VbVXSbfjEz2A9Zurd5N0C545AnComZ1bifHVEiHa+gRphDthKzO7s0PnjDUFPilL2ra9C6zCEGbGU9kBrjazknWAUKy+eL3u6qRGdt8WDvmO/HTxT8r1fZB0N6kK/Ex4lP9x0rr5D4GViwn6hdZkv+LJtt9b1FR8TrH2J1GY/jW8Gs8PuBH/finfS7UIE/2f8MyU3/EU86LOXkknAceGxfPN7OC87bHuJX2GHW6RlVWRuyshaQrcWZmoyG9pZnflbG85fbw/o1iafixGrmLCX3iGzFkWlVcottYJTuPryZ9jJdwL7FFt4U9JZ5BmW36NO2i7pRhpRmXIjO4MQoriumFxLYvsibJf0z2g/yONIj0HrFlJxcqQHnkwXmfVK6z+DdjLzG6v1DhqnRBtORA4iLSPccJQPEvgvxX938X6H2nv8Tkssq8qde1KImlLvI8pwDVmtnsz+y0GvBUWvwPmNrOxFRhiTSBpftz4Swy5YXh5RPJ6oY7qEijWDHhEMREOe4qziPidpMb7XDM7tEMD9/NPhguGrY4b2SvApJ7WxfiGfCP7s0o5nSRdhwvUgaeqn0oqjvkDLo7Z7HdRsR4H1gyLgyxK9TQUazbcaSSAegABAABJREFUkeFZCjfxBR8zZ9g8AlcSHlqad1JdJN1AWjKyrpk9WmSfqfEo99R4/ffcVtBXWrEWx4XZBPwCzG2RjSzj0LsUkrbCI9Lg36tl8OfKbrgAYT49GM3C/MWyTMcgcmO3I3D9k4ssshHlHXXtI2lhvH573oJN4/HsgvOq4azPpSDjcjywSjHdlIyMUpLVdGdAfs/uvStxwZC+szNpiubKQNlT2wvGYCEiuAKuYgo+wblN0sWSCqO73RIzGxGEZmbHa+FyPfiDcYG6TyUdGqIHlWBowRi6Kg/i4kkAmwfhuyaY2duktaKDgF0qMLaaQNKiuIBXYnB/gKt3J3+PGehET16LbBhee5tMpldnd07ImXC3q6ZbsXop1kqKNUSxnsazNZ7ElXNXp6nB/RVwLZ5xMhcwu0W2s0V2pUX2aYWzPHJFv04iNbgTZfjWnF9F67oVS8BlpGUBl/Mxy+AtxMCdfU9KWpauQW7/4SZp9oEDSVupXVdocANYZG/h91+AaYG6V3ivMHfi2jYAs+LzkSvJN7gbmY4P2IIR/IvJ2ZLpmIXE4P4MfybObpGdkBncIGkbXDC30OD+FHfKnVsDBvdc+D014R+ZwZ1RCbJId0ZSM/gtPrEZB8yctHMp+7Wl5YBnSSPNW5jZ3ZW4dsE4pgIuwZW8E94BtutIPWhXJvSz3ALvf75MweaReFLo+eVst6FYWwO3hcUhFrVffbZekHQT6edyQzN7sJn9lsUnO+COkfmL1YB3JSQtBTyCGxzg0f51zGx4UH1+n9Rw2cjMHihymrZdK9ZyuHHszrhXSDqD/8PM/q+F44R3bFgn/KxOy+riX5BGsZ+2yL7s6JhLjaSTgWMKVo/H+x23qsuhOC+yeJJFdlxYvytwTVj/HbCwRfZbiPY+QFpz2aa2b7VO6Oc8AhdI+wbvOmA52/vh6vsD8Prg+c3s06Ln8gyBj3FnzVhg/q6a+VNKctLH9wRmbrJDAx+zGN+xJksyVZO+9q/i5VV3JT3suzuSegIn4/OCQm4C9q+FzhqS+uIaFEuGVbfh87zMGMooO1mkOwOLbCyp1683aQ/k8l/bvYtH5Ky6pq1KoiUex+94ut9eeF0WeLOP14JaaaEISLfFzCaG9PskJfb+nM398Un5V5IuD2m/5WBozuvBZbpGrXBbzuttmtvJzF7B+x2DR0SL9ULtMkhaEa/hTgzuV3CV8uEwqWPB4TmHXBqMuA5hkb0MbIsLCqZV10Ui3Yo1ULF2VKyr8VrBD4Dz8PrGQoP7Uzy6tjMwm0U2l0W2h0V2bS0Z3IFi7a12b4cQZq6o1DIAijUTcE7O+n0t8jZaoePFeqRdFaYEHg5iZHWLmf2Bf3bBI6xLFOyyN2kpz63NGdwAFtnXpH+/PngGQkYRgvr47pKeJlUfzze4+/IT23MPxzEHm7NGgcF9P/6tX84iuz0zuJ1QgvYQTQ3uv3Cnxt9qweAOnEVqcH+ClxNmBndGRcgi3RkAKNaCeFQIXCxosQrWCQpXxU4MijeBFc2qo8Qa6pFuxWsWE24C9guTpYwCwt/sH7jjolfOpqRFzhlm9nzJrueiTL/h6ahfWmRztnJI3RLKHH7C3+uvwAzN1c9LWo3UQPkAWKQrKrFKWgO4D+gXVj0LbFw4sQv3lofxCDPAZWa2b6euHWtn4LpJKz7kGhbgQDwlNYlmL9bCKX7ChQgfBR63qGnacK0i6XLcMZnwTzM7o83He9R/GDA9XoM8AE/x3TzscoNFtnOT4/w7cCdpi62xuPBVhzMXqo2kffHsKoATzez4sH4yPG15prBtUTN7t8VzxeqPG5FJ7/SlLLI3Sj7oOiREYNfGn01b0lR9vBF4lAEsyxpMk/fUd8bjLaXOtMjea7K1mxOyje7CnUe5vItHkGtGAFHSjqStOMcAy4XSrIyMipAZ3RmTUKzn8M6SAMuHyE5lru3p3a+Stp3p9OS4k+OZHK8D3Sdn9af4QySbzDSDpEHAIcC+5Gq6Oi/gonX3lsIQVKznSdNOp+nKAkKSbiaNXG9gZg81s5/w+uaVw6ptupoooKT18Uleouj9GLC5mY1qZv/Z8QlgUi+8llnnxCK1qR5kqbweyxOAns3s/hf+P3k0jLW9vbFrAknr4ZG+HmHVk/jfsl2TCMW6H+9bDPB3XIAK3BmxUHOlTZL64M7QpAZ6PH4/vqvY/rVOKH9IOna8bWaLh/WHkEau7zKzLdt0vjjvuCeAtbtqV4fWCPfB5YEd8a4O0xfZ7UPENezMcOZiL1zbJcX4HXEJcJ5FleusUk9I2hXXYijUGrkUOKywbWA1kbQgPsdMHLV7mtlVVRxSRjckM7ozJqFYu+FttACutMj2amH30l/fBZFeJm1PtYuZXV/JMRQiaVvgclIDchyuvnl+lpLUPCGNd2/gMJrWy32MK55f35lsBsW6EBexAVjNInumo+eqdQpUzK8ysz1b2Hd9XIANXJdgcFeJdkvaHPgvaTbF/3DHQoufI0kHABeGxS/w6GFRI73Zc8SaE49ir804NqF3s228DBcAS4zsF+q9f7KkFfD3khsljMzshHafK9YQXDQOPDU/ubduY1HLDqLQbut60vZ4E4Gdzezm9o6jFpD0Ml6oAF4S8iOuxzBjWLd4WyNxitUbz1ZLyrM2tKi4/kNXRdJCuKG9I1As+2kkcDNTchOHsRANHEHq6Hd+B14C3uEU+92ObXqKjCDoeTbp8zfhD9yYva3pUdUjaCS8AiwUVl2Ll8Vkc7iMipIZ3RmTUKx+wPf4JGgUMJNFlU2nDp7Ta8LiaDz9p8XUunITlC5vIV80rCb6TNY64eG8A+6oKEzcG4ZHuS7uSDsnxdob97IDHGKRndeZsdYyIeV0OO6l/wWYsYUUc+HTxmQy3yWi3ZK2x5Wak0jr7cBOzfU4Lji2AY/MrhpWtdrmS7GmwdtbuaGdGjPNMRE4AbiwUkKUlUDSInikfpqCTWeZ2RFFDmn5fHGeUyjhTotsq2L7FxlPD7wGftewyvC6zLqLWkk6BhefAjgU19k5KyzfYWZbt+t8sbbBnVLg2R2Du3rdsaRZ8GfMjhTX9xiDl6LcxE68xLzsiWdYzFCw37t8y41czYlMpCeeoTJ/MdX47kzI0LiL9PmS8BqeeVJT/cnD8/B60hZ97+LzytHVG1VGdyUTUsuYhEU2Cq9dBp/cb9fC7uUZg9m1pC3MJgduD0qvVSM8RFYGchWKNwWGSlq5+FEZAGY2LvxPF8X7nz6Vs3kGXPTna0nnhDTg9jA05/XgTgyz5glpev8Li9OS9joutq+RRhIBhgSjs26RtDt+b0oM7huAHdpicMOkFoV7kookHixppdx9FKuPYq2uWCcr1su4uvTteKlEvsE9jvG8j/9HxvJYWNsDF4UsrG2sW4LD8RFSg/ulnM2F5SNt5aWC5V/x9lhtwswm4u3TknpoAVdKavM5aojc1mFbAEflLHekI8PtpB0MFsH7TXc5JE0raW9JT+FChaeT/wzwOm1//zMwhCMZwurMy6f4MyfX4H4KL3dYzC63/zCRC8L6yYDTyvk+6o0w33mbpgb3mcBKtWZwBw4mNbj/BLbODO6MapFFujPyUKylSBVmX7bIlq/4GDyq9wLpQ/RWfIJd9Q+rpI3w1KREsGYibuD8J0wGM1pB0jJ45Hsr8h1/E/H/9RlmNrTV88SaDH+INgBvWmRLtnJIXSPltVu60qz58o/g3X8Br2sE2N7Mbi3zEMtCQWo4eLnHfh1JmZd0BD5BBPiIQ9iJaVgNj2SvRlORpYTx+N/zUeBRTuBEGlkXgHmZnp24nlTk6ydgZYvsk/aOr5aQNBPwHJ72DF4PuRuQiEndZmbbtvu8Lvo1nLQGfm+L7Irmj2h2fMKjwofmrG6xfVutEd7Dx8A8uKGY3A879LcFUKyVcWFB8My1+YJDva4J84JN8Ij2huQLdia8gjvnbjWzHxVrCfxZsy2pww78b307cIZFlquoj6T+uKp1oh6/Sr23qOss4XN6IHAu+c/skXi2UU0KGgZh0cdJ//ddIusro37JjO6MPIK67BukBu/iFlVe3VHSPHhdZBJNOcjMLmzhkIoRxMJuxCfpCY/jtYU/VGdU9UdoDXcYHrWarGDzY8CpwJMtOVsU6z28TmscMIVFxVOuuwJB3G84bhi2mGIe9l8XV+4GVzJftN4cQwVGMnjbrUM76oDTPzQLz/I0g5iLuWi5W7bXwycq48/kGi6SXsJb5gH0ZAh98YhwIuz3FbBSvQowSZoG7xO+aFj1Aa7OPhGPTAM8bGbrFzm85XPHTRTQV7fInu7gOIVHLnN7hx9nZnXTNkvSmeS3zTT8u9phpWzFuotUEf44i+rn75FLUB5fk1R5fIoiu32MP49vMrNPwxxmTeBfuDMtl7+Aq4CzLGo+KitpH1wMDHw+tGy93TtLRXB2XEvTdpXP4+nkNXmPC2UHrwMDw6rTzOxfVRxSRkZmdGc0RXFeZOlSi2y/qoxD2gJvEwMeaVo59CKuOqGu8Ljwk3h+f8LF3x5u9sCMJoQenwcCB5FGFxJewmse7y9maCnWTXg9H3ibu3fKOdZqI+lWPGoDsK6ZPdrCvsIjXkka9U5mdlNz+9cSYez/xmukE04Fjm2Pwa1YU8KkSPY6pEI6xfiBJJINj1lkP7YwvveBBYE/zWzKcK1p8NrnRcJu7wGrWtR+vYJqEkSHch0IX+Opo9+G+96EsP4lM1uh2DmaPXestUl7ySccY5Gd2skxH0t+f+pTgH/XQnZUa0haBf/cJNxqZts3t3+bzhlrfvzz1wPPBprHIhvWmXNWivDdX5ZUebyw9hr8u3oLbmy/YWYWjO2NgWNJHWIJI4ALcL2FEW0YQw/cYFs8rNrLzK7swNupayTNgX9f58lZbcCJwAm16ogInQ6eJv0cPAasX6vjzeg+ZEZ3RhMUayq8lckUuKDaIIvst6qMRfo/4PCw+DWwZC2Jl0laHX/w5yp0n4ZHW7ps1LUchEjubnjUZ66CzW/hE+k7ch+civVP0rq7XSyqrtp9uZG0NZAow15uZvu0sv9aMKnm+CNg4VqfeIRJ9yl4pCqhTdFLxeqJCx4mRvYKNNfKaxzwJfAN37MMGzIVb7e1xZKkb4FBwPdmNijn+jPhEaBEOfllvHXTn205b7UJwof3kKbKD8ednR/n7PMH/mx438yadjVu7tyxpsCzB+Yo2PQ/i2yTzow7jOtw8nU3zgEOr3XDO7TLHInXpgMs0ZbymlbPG+siYP+weLFFVqg0XVNIWoBUebyYaOFveAeHG4Gnk/uYYvUAtsazHRYrOOZzPFPmWovaV8cbUpOfCos/AfOZVWceVA1CF4w7yc9C+xXYwqxjmSmVQtKlpO1evwKWqqV5Y0b3pa7FdTLKg0X2O3BdWOwH7FLF4fwLr6UEmA24rpZEoczsKTwVP7em6SjgmeAlzmgjZjbazC7CW7jsgKuMJiyO13u/J2m30DoIupGYWuABXNUfYIuQftkST5BG0eYnzQqoScJ3+xzyDe4jmjO4FUuKNZ9iHRBSakfg94sT8HTo3L9PI545cSJjWIPTeIubgGeZmbPYvJ09jacOv/Mm4RbZD7ixn0QVlwPuVKw+7Th3VQjRvWtJDe7fgfVyDe6c9ZD+DdrKKaQG91NAMgleMUQpO4WZnUW+INuhwMW19Lxohv1JDW5o2mKxo8R4lBtgnxD9rikkDZJ0hKTX8RKG48g3uMfihvZWeDnNnmb2hJlNVKxeoc3p+3jUO9fgfge/181nkV3cXoMbIBiWiYNzIJ550+WR8x+8w0Cuwf0M7niodYN7L1KDewzuJMgM7oyaIIt0ZxRFsRYmNXo+BBZq56S0dGPx2pw3SVOPjzWzU6oxluYIE7tDgf/8P3tnHeW2tXXx305SSJkZ0r4yMzMzMzMzs6IyvcJXZmZmZmZmfmXmpk2anO+PczWSPbbHnrHHnhnttbJiyYLrsSzdfWBvUoGXX3DPypvL7JajAsLfdHW8XHD+orc/A05gC+5iWj4L6x62yJbtzjE2A5KuJ+2vW97MHuxg+6VwuyyAD4GZzezfsjs0CYH0nUthv+8uZnZOwXaxJiS18loeD8aVwwekJeOPWmS/ZM43Fy4ONgAvmZ7HrOP2hKIS6+fM2otNKtYc+CQ1IaY3ABu3qn1TqC44izQz+jdOuB8vsW1SWv+7mVWlYB7EvR7HyeUQvFf8VPz3DTCTRfZelz5EOr6tcUuxhMhejt+HW/GaHxP3jR8/s7rDCpaqjx/rMLwUGOBWi2ztehy3KwhCZevifdpLURhwAC9ffhjPaN9ilv5mARRrVFwH5ACg2PHiBbzN4E6LahdaLDHWQXgwYFS8xW22EkGoXoNwPd5PKsAJ/n0cBhzXA6pGFsTvMyOHVVuY9e7qtxw9CznpzlEWivUoqVjYshbZw00bi7Q8LgolPGO1nJk9Unmv7kdQ5r6OtLwU4Gw8W/d3c0bVsxEIwXI4+V6y6O2vWZbRWYCxGIWfgAmaFRzqLkgFXrznm9mOVezzCD7BBdgq2Li1DELG/hJgs7BqBE6ULlWsfsC8uOXcKsB8tJ+oJ/gRL6d/EHjAIvuszHbJeY/Grytw14aFOyJnksbGA2oAD5jZCiW3i7UoTvaTbNF5wM6teH1KOoo0kzccWMvM7iyzbYGIXEftCsFl4FW8ggVgH4vsVMU6CO/TB9jGIrukCx+heIwb4968iWrx9cBmrdbyI+lgvAIA/O/eH/gGmLwz6vztjh9rdDzwNGlYtYRF9kSFXRoCSaPi/dab4L/jkUts9iKuPH5tKUHS0J6wI7AfMEnR24/h2h8P1vv3JelIPAMPcKdZ11shWhGSZsf/juNmVv+M90K3hJZOJUiaGO/DT9p9zjSz3Zs4pBw52iEn3TnKQrE2wAkkwE0W2XpNHY90BKl36Xd479tXTRxSSYRJ+fmkglfgPckbmtUnm9NXIfdWPhRYueCNgXhsfmxms1s6r/rbExCErr7HP/UPwKRVEMUl8AkVwEd4trslCEjoI74az34BDGcidmAX/sRJ9srAhGV2/wcXi0tUxl+tJcMVBHdewTO3AAea2Ykd7DMVtFVX3GRW/r6oWKvgPdJJmfuxFtmh5bZvBiTthWedE2xmZldV2P4+IAk0jNNRn6tiHU/qP/0sbqc2XHHBNXmhRbZ9Z8ZfYZxr48+vpPLoNvwe/E89z9NZhF7uT4Dx8CDTI0BSqbOwmRX7mXfuPLG2BRJLtueAhbsj8BMqQpYmVR4vVRXxIZ7RvqbcszFYzO2OV5KNV/T2PcAxFtlT9Rl1ifP7/fY9UjK3spnd26jzNQOSdsaF5rKtGE8Aq/eEPvbQbvYAaVD+SWCZVnnG5ciRICfdOcpCsUbCxcsmwaPwgyyyL5o2Hi83vod0wvc4sGyLlg0K2B73tRw1rP4T2LXVsow9EZLmxYVz1il4ox9DGMHpwKlm9l0zxtYdkHQDLh4EXvXxUBX7PEg6qd/WzC5u1PiqRciA3QisysTADAxnQd5jDGaivObIG8C9+CTrSYtsSBfHsCDeB94PJ/FzVgqOSZotjAHgYjPbtuLxY20CXEmand/XIjulK2OuFyRtCVyaWbWHmZ3RwT7Za29qM/tf2W1jzYcT7f64dN1cFtk74b3R8J74AcDbFlUvylYtJK2Mi0El9+D7gHXMau/xrTekgtLvK/A+90Qh+3gzO7gu53GhsdeA5O+7gUV2Q4VdOn8uf+7NhxPtDWmfkQbP5F+LB9peLFeyrFgT4ZaSu1Jo7mf4d3qsRfZy/UZfHpI2wYMD4O12c/QGQhcCIzcBa2ZWG57ZP7bVy8kTSDoVD8qAK9vPY1befSJHjmYhJ905KkKxYuCIsHikRRY1dTzShLhv5hRhVUt7L4YJ+nUUWhVdgfeq9ghF41aGpFkYn7P5iSUpvJUNwasNTjZrXqCoUZAKqlDOM+vY1i9UCTwZFj8BZmzmxFEramK+5z6mYE6mp3QezPEnTrDvBu5pROBPhV7JTwNLlCublrQIrlAOcJqZ7d3h8WPtBmTJ7NYW2aWdH3HXIWlNfMKdlGDHZja4iv0uBJJAw+xm9mbJ7WKNjJcMJ17fh1pUqMWhWM+T6jWMZ5H9TJ0haRngDtzfHpzcrt7M+2+ohvoUGAcPaM+MByC+wYMz75hZJXu72s7nFRd3hcWPcI2WoXU7vjQDqfL49CU2+Z1UefyRSi0JijUFsD8etM4KeQ0HrgGOs8jertPQq0IIJjxJaqO3l5md3p1jqDckTQk8Q5rBBxdJXM7MXmjOqGpHUUBkGLCkmT3TxCHlyFEWra7qmaP5OB9/2IEroI5UaeNGw8y+x8u2k+z2gZLWaOKQKiJMSOcnzWAAbA68FISccnQBZvY2u7M5u+Ndv/3aqPdAYE/gY0nnSyplQdOTcRceWABYpwoVc8zsKVwkB1xzYMsGja0kgtL4TIq1j47QIyzI16zJnMxLKcL9LnAK3ss/vkW2tkV2QQMrbY7AS13BJ9a7Vtg2O9rfym6VgUV2JjA4s+pCxVqzzOYNRxDXu46UcJ9J2rrTEX7PvB6z7FauQJ8Q7leBk0psk50ctxOkqwfM7GFgRdJxLwXcH4hvs7AnTrgBrjSzD0JlThLMmTkQ2XrhHlycDFwdfOcK21YFSZNK2lvSC3j5dUQh4R4K3IKLPk5sZlub2YNlg1mx/qNY5+M2X3uQEu6h+DxkBots8+4m3AAh47tnZlUcEgA9EqH14iMKCffzeKtSTyLcc5K2ToBX6uSEO0fLIifdOSrCIvsSuDUsTgI0Xf003FT3z6y6TNI05bZvNoIV1nZ4FiCZ+M0APCdptxBFz9F5fMF4fMvqwJ78ipf0J4R0JDxj8r6kKyXVLXvUTJjZn6Q2dRMCS1S5a7ZS5fDQT90wKNZoirWKYp2JT/LeAf5Lf5aif0YMbQRD8c+zG/Afi2xmi2xfi+whixrfgxvKjbNl4sdJKvaKT5Ala1WR7oAjSbPd/YHrFGupGvavC0Jrxu1AYmN2FbBnDaWk2dLsgaU2UKzZSIXZ/sUz+6WqKp7OvF6kxPt1gZk9ibdWJJn0hYGHJI1ffq/GIKh37xMWh5OWmIP3nSeoW1Am9HBnn5lHhF7pmiBpbElbh1aVL/DA2HzZU+G96dvhFl/rmNmNZuVbQBRrVsW6Engfv1cngf0huH3gtBbZjhbZx7WOt54wsxdxsUfwe8CRTRxOpxDswM7Gy/OTv7MBR5vZgq3QdlEtJI2HB3WSe9DFuFhljhwti5x056gGZ2de79K0URTidLxcDTxjcGPoD21ZmNk1wDy4wia4gusZwE2Sxi27Y46KCBNKj86PzTgM5kzcD/g4UlLUD+8zfEvSTZLmacJQ641sX+b6ZbfKIIgzJSJAUwFb13tQijWNYu2qWHfjauJ34ZnjwsDYz8CL/M3b7EE/xrXIVrXIzmrW5DrYYyX3utFwj+dSAbHRM6+rLlEO1+lepKWQowC3K9a8tY+2c5A0E/79Jxnqu4Cta1TKzk7MRyt+U7EG4BPgZFJ/gkX2apljdQvpBggZvKVx8UHw2phHgupxd2Iv0sDN5Wb2Uea9hpBugND/nFx74wFV9YxLGlXSOpJuxP3nL8YDGNn548u4qviUZraMmV1kVrlVQLHmVaybcWvSTTPH+w2/dw+yyPYOgf9WwSFkvc8909ojEEjq6xRWOQwBljazw0vv1ZoIvehXkz5TXsT1cvJ+2RwtjbynO0eHUCwBbwMzhVWzW1S6j687EcoDXwSmC6vONbMul801GkEx+XhS4Q9wwbqNzezpkjvlqAjFBcr2m1hk10BbVmk3/G9dnNW6FzgmZMF6HCSNgauYj4qr+U/WkX1T2G8BXMUY4HNg+q4oOofe3cVxpfFVSO8ThTCG8TnDeIfR+AD4gW/x/sGm30sSyH1q3wKmDKs2NbOri7bZFS/HBtjSzC6v6RzeonMLbp0ETgIXq5dPddnzuur6k6Sf7Unci7um7JakfYD/hsUNzez6gvdj7QucHBbfAeauVK2gWJ/jGh1/AONa1FhhzFDt8iCpjdZ7uCBnw8ldCK5+irco/IvrKnxctE3ig254trhugpCKNTX+eUfBRQNnsKi9EJ6kgcBKeDBvdWCMEof7CCc+15i5OF6VY1gMd6BYqeitH/HM9pkWFXpztxIkHQCcEBYfxVWyW3oiHdpJ7qQwYPghsEBHwZFWhAqtHn8A5q0k6JgjR6sgz3Tn6BAhQ5PNdrcEsQ1WFusBif/1TpI2beKQqoKZ/RPEl9YAfgqrpwIel3RENf25Odoh24eWCDNhZr+Y2dF45ntfXKgowUrAE5Iek7RCTyvzD0JQSYn5RFRZYh48VxNRpSkpLKuuCoo1hWJtr1i3kHpj70N7wv0VcCFfsiPH8zkXMxrPAD/wBS5W1jKEG8DMfqewn/u0kCHKIpvdrbkcM5RZb0AqajcB8IBiTVl+r64h9J/eT0q4X8XFxDpTTlo2061Yg0jLbg333+4ooJMEGscAZuvEeGqCmb2N/1aSSfqM+L136kafG1fjTjQBLi0m3AFJtlu4t3XdEHzr/y8sjgIcnbwnaWDIaF+DB/FuBjamkHB/F/ZfCA/WHVEN4Q56Diso1mO4FVWWcH+N35sHWWRHtzLhDjgdDziA6wOsU37T5kLSAEkn4iX/WcJ9LR7w6YmEey1Swj0C2CAn3Dl6CnLSnaNaXI6rCANsoVjltYa7EWb2GoWT5PN7St+umd0BzEU6+e6PZ2sfa+Ue9RZFSdKdwMz+MLNT8HK0XUh9lsEn4PfhPfZrBmu6noKaS8wDBmdeH9JRa4ZiDVCsxRTrWMV6Fc+Qnw+sReGkfAR+PR+CX9tTMJgTuIBD+YekR/oTnHC/X8N4uw3hd5m0rkwIFPt2Z/uYO2VXZpH9hWcQXwurpgTuV6wJOnO8SpD7Qd+Dk0vwDNdKZp0mNyV7ukNF1FmkRPwsi6rymu62EvMEZvYh/rtPSO+0eABuuvJ7dQ0heLNXWPwXOKbMprdmXq/VgKEcSxLsHcpmml77SboWr5q5CdiIwt/0L7it3ErA5Ga2p5k9V012V7H6KdZauEjXfRQGBj/DA/jTWmSnWNQz3DxCVdA+mVUnh8qAlkLQpHiRwl7+EcDOZrZxjS0lLYHQHpOtLDrAzB5p1nhy5KgVPWlymaOJsMh+xb1mwR/ImzVxOAUw9xtOBE5Gw/u7S5XDtRzM7HO8zzDGH4jgE8/XJG3e07KvzYJF9gNetgkwT+grbb+d2d9mdg6usrsVXmqZYH58wvuapI1D31ir407SSo91qh1zEAW6PSxOjgsfFUCxJlKsLRS3TcifwPtAi/sYv8cnQhsBE1pki1tkx1lkrzGYmYHH8UoOcLGkJczsk6o/YXOwB6kewLaSlsy8l51gd1p4KGT0ViLNms0E3KNYlRTBa0IIptyG9y8DfAksb2bfduGw2UBDNtO9Ht5ekJznUKpDt5NuADP7DCeB74ZVU+IZ70YFbfch7aW/2Mw+LbPdC3j2F2B5SaOX2a5zGMxQHuR2bgBOQnzISbindvY8P+O926uQKo/fZ1Zd6b9i9VesjfGg0i0Uiq29h997p7fIzrXI/i5xiFbHHbiNIXgV1T7lN+1eBLG0LfBe+ey9+jdgITM7tzkj6xpC8PAW0t/QtbiQX44cPQZ5T3eOqqFYc5BmZt4GZgul502HpNFw+5k5wqpr8H7MlhhfNZC0MC50k81yX4dHpntcGVh3Q7GuJ832zmGRvdHhPk5S18EJQjGZ/BDvvb/CrH6etvWGpJtJXQWWNrNHq9xvblwACeBrJmY6dmZWvNd4FXyiXC7o8wJe2n4X8JJF7bMmwRLvAbx8GnwSuFwXCV+3QdIueOYWnCjMaWb/SDodJ+UACwdxus6fJ9Y0uFVU0mP8MLBKV1XbQ5vKTXgbC3h2c/FQXt2V466KB3sAjjCzo4IS9ju4wwXAOhbZLVUdz3vcf8WDGZ9YZOVU4xuCIKT2AKm92Q94YOLVOp5jfDwoOAbuJTxdpZJYSecBO4TFtc3s1i6ef3T8N70+/vtuJ4CHXx+34NUzD5uVVJuvfB7Xd9gct4srrhp4Dc/u32xRx9oTrQ5Js+KfqT8efJuhO3QBOhjTuMC5ePtKFm/Q9WBb0xCqz24kfc69iQcQ/iy/V44crYc8052jalhkr5OWQs9C9TZFDUfoTVyP1JJrY2Cn5o2odgQrtLmAyzKrN8Qzr0s1YUg9DRVLzEvBzIab2Q3A3Hj/ZJZATYd7gH4YrN1aroQwoFMl5mb2CmNwJ7MCazEp2/ItXgYa4X+/LOH+BQ8AbQlMYpEtYJENtsheKEO4F8D7CBPC/TKwVA+b9J1Lej3MSKr2XJdMdwKL7BNgBVI7q2WAq8tVa1SDMEm9kJRw/wms3FXCHVCqvPw4UsJ9O4Ul0hURetyT3+40ijVppe3rjXBNLk3qKjEBrmq+QB1Psy9pyfZFVfSgdlnFXNLokjaQdANejZIEJVPCPRD309iQT5mTycxsu5DRrolwK9ZAxdodD1ReSCHhfga/t85tkd3QGwg3gJm9RaHbwfFNHE4ilvYG7Qn3lcD8PezeW4wDSQn3L3ggKifcOXoc8kx3jpqgWBvhWWSAGyyy4ht8UyFpPVISMhRYNJTS9ihI2gD3nBwnrDJcMTVq5axrMxE8j5P+rnMtql3JPpTzL41nvpcpevtbvJztnCC41RIIitvf48JI3+J9lyUntqHvdg4SpXFjEVQ2+Poans2+G3i2WlVpSYuFfZIywGeAVbrQQ9w0SJodDxgMwO8nc+L+04lg4wxm9kFdzhVrYVyQLiFFFwHb11pNFK7h/+KiXeDjXtXMHqzLOKUFSYMRpzOY60hLxP8AZrHIPq/pmLGOw7OjAOtaZDfXY6w1jcHdMO4mLXH/Hb9uu+RuIGkCXMdgDPy7mC60FVXaZ1Q84z46LlQ4STWl3aGtalWcXK9CaR/1H4GbETdwKMcyoK30e1uL7OIqP5afz1shdsaDChMVvf0wLtT2aKtUxNUboU//fVJnjEVC8Lw7xzAyLl54AIWB0hG4jdtpPanirxiSVsQ1KYTPg1Yzs7sr75UjR2siz3TnqBU34xN7gLUVa7JmDqYYZnYjri4K7oN9Ywn14ZZHsOGZA7ckAX/gHAQ8I2nGcvv1cbyEP5Shykx3MczxsJktCyxMWkYLMDEe+PhM0uBWua5CAOCesDgxsFj2fcUaTbHWVKwLcAG0V3ExpcUKCPdQ4DvexMtap7TI5rLIDrHInqyRcGd9oB8FVuiJhBvAzN4gtb8aGQ+E1TXT3XauyJ7BWx2SLOO2dC57dggp4R4BbFIvwh2Q9nQPYHRcUC/BYbUS7oCm9HVnEdwwViS9544J3CepOPhWK/YjzXJf2BHhDmP5m/Q3PT4V/iaSxpS0kaSb8ODbtcC6FF6nP+Df0/I4gd/BRtgDDGDfzDZHKa6uf1yxxlOswbgY2gkUEu47gYUtsmUtskd6K+EGMLOfgKzH9endKcQZhMWewTPBWcL9Gx5oO7WHE+5p8SRP8tminHDn6MnIM905aoZiHYVnewAGW2Rxpe27GyHy+xhuawI+CVizh6p19sezCEcDI4XVQ/BJ9fk9+YHaCChu87gdBozZ1b5YaOtNPgRvX8hObP4AzgFOMbNvSuzabQhWeYnQ4VkMJsZLOtfES5fLlca/yy88x21swf8Qw/kOmLYzpXsZwp1M3O8H1jKzTil8twpCW8Gb0Ka+/iaptdX4YeJdv/PF2pDCieaBFlmxgnq5se5Mob3j9mZ2YV3H5wrfnt1fhVdZgLnCWy8BC3amfDiotn8fFp+xyJpCvKHt+76Z1NZqCJ5de7gTx5oQz3KPjoe1/mNmX1S572bAFWHxFDPbN/PemLj6/fphnKXcB74Pn+MG4LFymXLFuo20DeEwi6ycqjqKNQkuGrYzhQrnFs5zrEX2Wql9eyuCdsLLpJoAW5nZZRV2qcc5BeyIV14V39vfB9Yws/fa7diDEHR6nibVWrkdLyvvcfO4HDkS5KQ7R80IfrKf4pUSX+H+mjWLrjQSkqYEXiEt+zrIzE5o4pC6BEnzAFeT2v6AP4S2M7PvS+/V96BYlwFbhMUFLbLn63ZszyochCv3Z1XC/8b7GE9qll+opLEYl++ZiZGZhaFMwYAyZeN/42WfdwP3WOQ+wZKuI+0FPMDMTqrx/MWE+z6ccPdEZeJ2kLQ8HkQAt3tK+q0HNuIzKtZOeEAnwfYWVSbPkjbC7xEJWa/5e6xqbNJkwJeMC+zKCAbQD8+oz2+RvVx57wrHjfU+7iowFBi7marWkkbBe6ATMtop4h08khPLpjPNbPca9h0P98Xujyvcz0Mh0R6lxG6Jv/YNwONVlaTHmgkPJPXHS+qns8i+K9pmKrx8eVsKCf5wPNh3vEX2Ln0UoRriobD4Dd520pAWpBDIuQi/FopxP7BRTxdeDUGFK0jbeN4HFgjVKDly9FjkpDtHp6BYt5B6iK5nkd1UYfOmoKgXaASwbLXKzq2IEPn9L4UCcd8AW5vZvc0ZVWtBsXYDzgiLu1lkZ1XavlPnkAbhE9BtKJz4/otbZx1frz7fiuPw/ux58d/hmqTZ12J8iwdobgMeCR7Rhcdym6Q38d/KD8A0ZtX55kpaHP+d9UrCnUDSlaSTQPDsXv9GVZso1qF4hQv4/Wv9cr3OklbCbYySYMAJZnZQqW27PC5XSP6JzYH/tK0+xSLbt+xO1Rw31qW4UB/AohbZ0xU2bzhCxdQNdJJ4S5oIz3KPBvyDV5B8VeMYHiMVLB2KtzgU41sKiXZnKg3OxTOnAGdbZLuG9dPjgcYtSK8t8M9zMXCiRWWtz/oUQnn/OmGxIb+/8Du/FG8jKsapeKCtqlagVoakPYHTwuIfwIJ1EoHMkaOpyHu6c3QWWTKza9NGUQFmdh9wVFjsB1wraZIKu7Q0zOwvM9sZnwT+EFZPAtwj6fQgvtPXUbOCea0ws0/NbBfc2u2/pH29A3Ai/q6kqyWVI8GdhmKNrFjLK9ZZwP/wz3soxYT7d37Gey0XASazyHawyO4qRbjDZ3ob7wUFV2+u6jddgnDfSy8k3AH74LZKCYY2uL3jWHwiDX7/ukaxliveSNKiOOlKSNEFpErrjcBfzE6WcP8PV7zvKpre151FEKxcn9TPfiBwZw093geQiuKdVy3hljS2pM0l3Q4smnkrS7i/xdsIlsaFE3cxs0c6Q7gDBuMK9wA7KtbqinUN7mG+Dem19Sd+z5vGItslJ9wF2B8PRgDsHdow6gJJA4NV4T20J9xDgW3MbJ9eQriXxK+xBFvlhDtHb0Ge6c7RKShWP9yXdYawahaL7J0mDqkkQk/0vUAyWX0U96vs0Q+nEDy4hLTvEDxTuUkQf+qTUKxR8RLJAcDbFtmsDT+nqxPvCewOjF309q3AYLPO9zkq1ljAyng2e1VgrBKbGcN5gUeYl3fpzw98DUxRS/9bKJ9/Cyd4PwGDKpVIliHca/dSwg2ApK3xDB949nnMYFfYmPP5ffZi0gzwn8AySduEpDlw/Ypxwvs34uWlDbNl0iEaj3/5se1bh9Utsjsr7FLdcWPNhlsegXs5r9vVY9YDZTLeq5rZIxX2mQT4GCfqf+NZ7q8rbD9OOP76uAZDqYz2MFwM7QbgyXp/x4p1BFBOn+VX4P+A0y2yH+t53t4EScfg+h8At5nZWnU45hx420ipZ9l3+D23qVUh9YKkKXBtiESYr2EVOzlyNAN5pjtHpxC8ebOCPbs0ayyVECYmm+K95wBL4fYaPRpBuGsVYA/S6PpswIuS9upOBdVWQugDfT0szhwsbRp7TrMfzOxwYGp8wvVD5u21gFcl3RTsp6qCYk2mWDsp1r3heNfi3vNZwj0U783eAZjMjrQFeZK7w9knpTBLVs3neJfUDnA8PIhQenzSEvQxwh1wKf53B39+HtHIk4X77Hak2dbRgbsVa2ZJ/8F7OMcJ7z0AbNZIwg3AKJzY9q2/z2/1INwBb+OqywCLhPaJpiOT8b4jrBoI3CVp6Qq7HUAqcHVuKcItaRxJW0q6EydPl+Hih1nC/TXp/WQk4Fgze6wBhHsOvGe8GN/j97SpLbIjcsLdIY7DvzOANYMWRKcgqZ+kvfFqplKE+1Xcf7u3EO5R8KBhQrgfwKu4cuToNcgz3Tk6DcUaB/gSL6H7HS9jraoPtLsRSjAfIxXAWtHM7q+wS49BKGO+CrcYS/AAXpZVUw9hb0BRf+JSFtlj3Xp+773fHrdxmbTo7RuB2MzeLNjHCcbMpP3ZC5Q5/C+4Gv9twH0WFWaiJW2O95UDnGFme9Q49hnwCpZ+wM94tvu3om2WwMl+XyPcAEj6jdQSbTgwj5m9XmGXrp8z1kA8yLEkACP4mjP4l5+ZMmzyHLBctX34XRjHEvh91PO3Z/M/+9WmruPx78VtuwCmtcg+qdexu4qQ8b6RVMCqZMZb0qR4lnvUsM20ibtB6IdfEyfxy5M6UmTxVTjPDXjJfUQa3NnZzM6t22fy6oIId2YoxqfArOVaUnKURtE9+G1gzlor64JY4aX4NVIKN+BaLjW7TLQqJJ2HB5DBrejmNcuDPDl6F/pkNixHfWCR/YKTPfBJ6GbNG01lmNlTuCBMgssllRIj6XEIBG4B3D4kwfLA65LWasqgmouG93VXQui9Px23mNoTF7tLsB7+vVyngZpNsRZTrJNwdda3gGNoT7g/x8XhlgMmssg2t8huLCbcAbeTZmLXrbXiwczeJ7UeGzeMvw0lCPc99CHCHZAVz+sPnB/aWBoGi2wITtZeAaAfk7IpU4Zv4W2c/DWacI9C1pP7IeC3kgraXUFL9XVnETLe69FxxvtAUoXvc4ChkraWdDfei30JXqWUJdxfAqcDiwFTmtmeZvZkaA+5LbPdmvX4LIo1i2Jdh1cFZQn3N6T3q0F4O0uO2nAVHgQDmIVC4dMOIWlt/HspR7iPADbsZYR7O1LC/Tf+TMkJd45ehzzTnaNLUKy5SCaC3o83p0WteVEFAnIXaR/0/cDKvcn3MZSzXUZhhvUCYO/e9JCuhFAqmfRQX2+RbdjU8bjv747AQQxgYqYFZsLN30Yvu9tr+GT7VuDVWn5Tku7Ay1QBFjezJ2sc73S4gFJ/PLM+jZn9UoZwr9OXCHcg10nWaghpCfFuZvVXym93/o00iEl5h3ECqfuWoTzJHPZ64z15FSvCBbfga4ZwPgMxfjOzYh2DrpxjObxKBzIq2q2EMhnvVczsUUmT4/Zeo+DBrydx9fEBJQ71BWlG+9lyz6Fgn/QZMGU45oTF1SdVjz3WzATSRmotBx4MOB44D1gGr6YhfJZZLLKh5KgakhYEng2LPwPTd0QiJY2BCydul1k9gjQ59hewuVlpB4OeivC3epy0rWILM7uiwi45cvRY5JnuHF2CRfYqaXZidjxS35IIk5otSSP5KwBdsrlpNZjZA/j3cEtm9fbAy5Lma86ouh1v4xNhaEKmux0GMxqD+ZnDeY6DGcomePdklnCPwPiH54C98LLauSyyyCJ7pRNBrBsyr9evdbhm9iFpeeQ4wJ454W7DwMzrrKLucYFwNQySRuY6zuMSRm3rfJ6YkVmX84KAYOPOHWtGUoGof7mDT/CrcrSyO3UOz+NEA1os052gTI/33ZK2wL29k+z/yDiBzRLuz3FitQgwtZntbWZPVwr8BoX8JNs9MoXimVVBsWZUrKvwapqNSAn3d/gzcFqL7LRQUXE3LjgKrlFfU6Y2B5jZc6T30HEpL1AHgKT5gZcpT7g/AxbphYR7YuAmUsJ9Rk64c/Rm5JnuHF2GYm1KWpJ6rUW2cTPH0xEkLYdnuYVnrRY1czXg3oKQHdkGV5xNJsb/4lmOExsuttRkKNaTpEJiE1pkP1TavgHnnwYvBV0LWJxSAc6hwIfAe3hx+RBG4KWJR3XF5zsoIX+Hl69+CUxVazWHpGnDyAbgitkivY7uBtbtg4Q78V7+NizeiQfwkonyLWa2Tskdu37e/riC8QYATMTv7MQI+rWp5d8BrGuRDav7uV1v4GFchBLgBAazKGmAdWSz+p1XsV4F5sRJxzhl2iiajmDR+AAdB5r/R5rRfr4zlVXhmZVUAFxtZptW2r5tP/fZPgLYhMJ70PfAicA5FrWvgFKseYEXw+KPwPQW2c+1jrsvI/Rlv48HKkcAcxU7i4Tf9YE4KU+CM8MobD14AljPzL5r+KC7EZJGwq/pJcOqJ4Fl6nkvyZGj1ZBnunPUAzfiD3GAdRW3the2mT2IexiDP+iukVTKhqnHwhwXAXOR9jgPwL1/H5ZUN/GjFkW2r7vhGX7FkmLNo1hHKtZruJDSqfiEInuf/Q64CFidh5iQ6zmQ1/gx5OX7AZsD70i6NKhT1wwz+wUPKgFMDizUiWN8jAv5gE8a+zzhDshmuofgKtXJZHhtSXXpuc0iBNDOISHcMITvWIV+rEDqrbw6cJVilSpj7iq2IiXcn+DuD1lxrXpnu5PKqX6UFxRsCiSNKmkVSefjQmPlCPcPpPoMg8xsXzMrW0JeBR7DbbsAVpEqf8+KNZ1iXYa3iWxGeg/6ASd501hkJ5ci3AAW2Ut4kAdgfBqs0t8bEURMjwmL/YDTwm8ZgPAMfiRsk3yfv1BIuC/EBRJ7FeEOOJGUcH8FrJ8T7hy9HTnpztFlWGT/4A8H8AfGdhU2bxUcQdpzNS1wbvaB2FsQMqaL4g/2ZMK3BPCapJauSOgiGi6mplgjKdZyinUGXv73EnA4hSryAB8AJ+ET9Mkssu0ssjvtWfvBzE4EpsFLd38K2/fH2yDek3RxyDrXii6VmAc8UGK5LxNuKCTdf5nZz3hLQIIzpfrZ1IV70ml4iwh4tcp6ZvZk8Opeg9QycH3gouDtXZ/zx5oQODmzaqegZp0l3QOpL1pKTE3SuJI2k3QDTlrvwr+PSkKc25nZYWb2gtWhnDCQkXvD4jiUCaQp1rSKdQlOtrcgneP9BByMk+0Ty5HtIhxM2qazW+gHz1EbTsUDVeCtBmsChGfva3gVFPiz+QdS+7/huB3oDqGdoVdB0iak981h+D3tm/J75MjRO5CT7hz1wnmkpG7HBmVc6oYwidmE1Bd2Yzyj0+tgZsPM7DA8W/VZWD02cLWkKyTVTQiphdAQ0q1YYyrW+op1JZ7hfADYDdqsmxI8hxPpWYAZLbIDLLKnLGpf1m9mv5vZcTj5PgwX3gEn31vj5PtCSYNqGOpt+GQGYL1aVcwlLYmrLGfxch8n3FCY1U0IybXAfeH1FMDR9ThRINzH4pNvAMNFhu5OtrHIHgbWIf2utwDOrqPH9X9xz3aAqy1qs1kcktmm3pnuZzKvm0K6JU0laXdJD+FVXFfgKt9ZJYYh+O9sm/B+FldLWqrOw7o783qVgvHGmkaxLsLLmbcitcb8Gfc6HmSRHV+LpadF9j8KK8JObRXv9J6CcL/M6sacKulqvIogee5+i1esTBCWfwZWMrMz6hGwaTVImpM0SQOwh5k9U277HDl6E/Ke7hx1g2LdhmdeANaxyG6ptH0rQNIGwHVh8S/cG/LdJg6poQgE+ywg2xP4GbBZrSrXrYwwOfwJzxx8g2eYO3WzU6xJ8et6TWBZUtGXLIbhJkq3Abdb1Hl/9PAd7QHsQ5r5AM9yXgIcY2afldi1+Dh3kU7OF6l2YhMI992kZMrwnu4/cCXzbu2PbyVIWhTvPQQ4xcz2DeunwUWqBuJ/rwXN7IXSR6n6XIfjpdwJtjGz4kCIbxtrHVzEKyFbpwH7dMVJokhJ/BdgJovs2zC2C4Ftw3uzF/vOdwXht/sNMBFeUj2eRY11mAgBjjlwDYY1gbnLbPoj3j9/K/CAmf0VyoQ/wKu8hpN+B3/hquaP1WmMWT2B18xsLsUahJPqrSgUbPsFD5j8n0WdUzoHUKzR8Kx5ElRc3SK7s8IuOYoQrq0H8Ux3MV7AZTWTa+ZdYI2uaHq0MiSNh2sFTBNWXYxXheREJEefQJ7pzlFPnJ15vUvTRlEDzOx60qjraMC1QSCnV8LMfjWzzXDSnUzGpgYek3RUEDfp8QhkIxECmgTvba4aijWVYu2jWE/j/WbnAitTSLh/Ba7B7XcmsMhWtsjO7Qrhhrbv6Ch8YjKYtJdzAF7W+oGkcyVN1cGhai4xL0G47yb1Zh6DXqb23wmUynRjZp+Q2Gl5gOL8jvpuK0HSfhQS7l3LEW4Ai+xmPMudTF73Ao7q9PljDcSv+QT7J4Q7oGE93eG3m5SYjw00pKxZ0gBJS0k6DddgeBX/DosJ98fAKXj/6SRmtrWZ3WZmyd/gENI+3JPw8nPwv8vd4TfVZYS+3iSQM6d21RV4Zns7UsL9KxDhme2ju0K4AUIrwf6ZVacqVqmgY47yGIAHZbL4HQ/Szk9KuO8GFurFhDsRg0wI94v4fS0n3Dn6DHLSnaOeeADXYwZYLtjM9ATsCbwTXs+JC3z0apjZ1fhnTbJ2/fDS5ieDT3NvQE0l5oo1tWLtp1jP4dn//wILF232JV4psAIwkUW2iUV2fVcnt6VgZr+YWQwMwglYco6RcN/vDyWdLWmKMoeoqcS8DOFeBy+XTvoKd5c0YSc+Tm9BQU930XunAq+H13NR2OtdNSTtipO3BPua2dnltk9gkV1NoZ7GoYp1aGfGgGdPEyG/J/CMVBaN7OmGwr7u4t9gpyFpdEnrSLoczxo/gt//BxVtmugzzA5MF4TQHjezf4uONwgvLwf/fZ4ErEuDiDdjkFYjfcFmpGT/N/weMcgiO9Ii+7XE3p3F9aTPielI2x1ydABJ0+N/ux2L3voTr5pKcCKe4a7n99ZqiIEVw+sfyPVBcvRB5KQ7R90QSgDPyazauVljqQUhY7EhqSDR7pLWqLBLr4CZfYr3eR+Kly6Dq+2+KmmbXiAs1yHpVqxBirW/Yj2PqxGfRHvF5Ddx4jkfMKVFtptF9oBF3SNwE8h3hGcIjsazJOAT7p2BjySdWewTHUS+HgyLU1JBCTr0n2YJ9124D/c/ZvYFabZ7dAozX30NJTPd0KYTsT1ptjmusQ8fSdsCZ2ZWHW5mp1S7v0V2MbB7ZtXRirV3TWOINSuucA0etNmxRHl3I3u6oY5iapImlrSdpDvw8vCbcJeA8TKb/UuqzzCVmc1nZkeb2ZsdZOIOJc0yn25mP5nZP9SZeCvW5Ip1JhuyW9tKz4f+jt8TBllkkUX2S2fPUQ6h8mBP0uv6CMWqJCLX5yHHtsArpPfdf0mDoInDyz+4TsOBvdnGU9Ja+G8FvAVjAzP7X/NGlCNHc5CT7hz1xiWkE7KtFGv0Shu3CoJ/5j6ZVZdUyCD2GpjZcDM7Fp/YJmVto+O2VjdKGr9pg+s6SpLuIDp0gGK9gCvLnkh7Uv46numaySKb3SI73CJ7qSs9sl1FmNAfjpPvY/Eea/CS911x8v1/wR82QYcl5oFw30Uh4V43kIcEx5EGpXaT+uyku1KmGzN7npQ0jwacXW3wKij6XpBZdayZ1SzKZpGdiVuZJThFsXaqagyufH4+KZE83iJ7p8SmjbQMA880JwSlZtItaXpJ+0t6Evga/7uuBoyS2ex3XM9jE2BCM1vBzM4ys8+rPMc0pOKbv+KVDgDUi3gr1mSK9X/AR8CuTM5IbX/t9xnKJ0wf7k0N9dC2yF7GnwkAY5JaYeUoQnhm3oi3rSXznw9wNfgs/gaWNLNiEb5eBUkzA5dnVh1gZo80azw5cjQTOenOUVeEh/81YXFsfELTU3AOkIi/jQdcFfqQej2C6NM8FKqKrgO8Lmm55oyqy/gSF2QCWECxDlSsF/EezRNo79/9Gl5iP6NFNmfoiXyv+4ZbHczsRzM7FCffJ5B6NY+CZzk/knSapEnwEvOkimG9YgJYJeFOPGfPC4sDKSR1fQllM90ZHIZfe+A6ABuU2a4NktbFJ6bJ93NaOE6nYJGdRNpjDnCOYm1Zxa7bk5LcD/DgTik0lHRbZH/jxBtgRsWaoNL2kvpJWlDSsZLexnudT8TtErPX/Nek+gwTmtlGZnZN8LavFYeRBidOC5Ul6WdIiXeiOp4Q7yU6OrBiTapYp+Fke3eSYEE//mR83gJgOCNzGbN0YtydxaGkLS7bKNa83XjuHoHwrHwdf3YmuAB3ODiJQg/uUenlc/AgnHY7HqgB/zucWn6PHDl6N3r1Dz5H03BW5vWuPcVmJJQRbgckmY4l6MLEt6fBzP4ws+3xCUPiGT0Z8ICkkyWNUn7vlsS0pPZbYwHHA8UTxVfxyeQMFtlcFtkxFtn73TfEzsPMfjCzg3DyfRIpERoVLwf9BL9+Hw/rpyITaChBuO+kBOHO4Hg8OwOwi6RJ6/JBehYqZroBzOw3yJQBw+mSxi13QEmr4oHKJMB3LrBPHQSGjqRQn+JixSobAFCsSUgtosA9ucv1XGYDDo3o6YbCEvN2vtSSRpG0kqRzgS+AZ/FsYrHw2tt4pcaCwBRmtrOZ3VvhOu8Qkv4DJEGMX/EgSTuEc6xDIfG+pxzxVqyJFesUPDC4J/5bBr/WTgSm4fOCLPMqdBMssu/wvlzwQMbpPeXZ3miEa/G/eItCUmn0I7AR/uw5PLN5tgLr5F7QxlUSQUjyOlwHADyonSuV5+jTyEl3jrojlKI9FxbnpI5COI2Gmf2EZ+eTHsYjqslM9CaY2S24gNCDmdX7As9JmrU5o6oOijWdYh2sWC/jon6llI9fwRWHp7fI5rbIjrWo5yrGmtn3ZnYATr7/S0qIRgX2BhbLbL4mlOzhvhNYrxIRMbOvSTUbRiXt++1LqCbTjZndittKAUyMByzaIWTGbiLNgF1GnRR9QyvEQaTl7v2AqxSX1as4jdQ7+LLgAV4OjS4vhxJ93ZLGkbSJpOtw/+x7cJGqbADIgKdw7YEZzGxWMzvEzJ43q5v12GGkQZJTKmXKqyHeijWRYp2MB8r2JiXbQ4CTgWkssgMtsu+B+0mfTyvX5+NUjTPxKgLwKoINu/n8LYfwTHyewva0B4CV8Iqg5G9k+HNnEVLh1kWAtbtnpN2OU4CkSu57YE0z+7PC9jly9HrkPt05GgLF2py0j+dqi2zTStu3Goo8cr8A5jKzH5s4pG5HULveEycMiU3M3/hk9qxWiVgr1vR4v/L6uGp0OTwJbGWRfdQd42oWQln5AbjIWrH93Q94Ncc1pBnKDgl35tgT48RgIN7jPW0oPe8TkHQcTmQBlqnUmxg0Id4mLa1c3MyezLy/OHAvKWm9Dti03oJKmT7txFd7KO63fH9mm5VJSeGPuJZBWT/2IDR5W1g8NOhC1BWKNRnwJb8Cr/IBj/AZLvxYyortb5zo3AbcEey1GoLg7vAuTrp/AQZVozodrChvIs1O/8lkbMwOLI5rMmSDF3/jFpwnFlm1Jcd6mjSYPcjMPuvkx6kZirUKaa/6F3g7Tsmqj96MkKHeDa9ASO6zQ/Fg5DP4tZhoX/yB/7ZvD/uujpddg7dxzBqEGHsFJG1PKr45DFjazJ5q4pBy5GgJ5JnuHI3CDfgEH2B9xZqomYPpBI4FHg2vpwAu6q1lYOVgZiPM7FRcffWtsHpU4AzgzmaKaSnWDIp1qGK9imdejqE94X6RtBwSQL2dcAOY2Tdmtg9eXn86qQAawAR4BrZmwh2O/S1p+8gopAS0r6CqTDdAUH3PWnadn7RoSFqAwtL+24DNG6FgHJTHd8Q9csEDaLcqdlGvIHaZdZ3YpxLhDmiYZVhQfp6dwWzDOQzlVOARpsezZlnC/RMe2F0HmMDM1jCzixpJuAOOJM1y/7dam6dgj5Tt8R6d77mdT9mf9Dr4G684mMYi27cU4Q64O/O6W7PdFtndeIUB+LOxz+k7hMDmXcD/kRLut3BBzi/wuUPyfPwEWDgh3AF3krb9TA/s0OAhdxtCBUfW4nCnnHDnyOHISXeOhiD0AiZqp4mvcI9BmPxuhmd9wMtyd2neiJoHM3sNn0yckVm9CvBGd1qrKdZMinW4Yr0OvIdb5cxZtNkL+CRwWotsfotsMD7pAZhHsUplyXolzOxrM9sLJ99Pl9hkOD5RrNVhINs/vqOkKTs9yJ6HDnu6i3A2XnoK3upwgKS5gPtIM+D3Ahs2MtNlkQ3He5BvDqsGAncq1kJABEwd1j8MVKOmXFfLMEmjSVpV0ll4P/PrwFF821Zhk+BTnJQuDUxsZlua2S3dVbYqaU5g47D4A066qsdgRucg3mQ6PLgyDLgK+JSh4VjTWmR7W2TfVDgKFJLubuvrzmAfUoHGAxVrqiaMoSkIz7zXKQx2/B/+jFwZTzgkRPxxYAEzezN7jFAltl9mVSRprIYNupsQLBJvotBG7+LmjShHjtZCXl6eo2FQrKnxCVQ/XEV6kEWdF69pBorKwP4BFgwktE9C0sq4LVw2y30psFe1GZ+azhdrZtLS8dnKbPY8PtG50SL7tMQxriNVkJ7TInu93uNsdUjaAu8XLoXf8Yz4KcUKzBWOdzxpT/dFZrZd10fZ+pB0JZC0ysxg1rEWQCBqL+HZ0aG42nwirPYIsKqZVcya1wuKNTLu0JAQtT9wAt4fv7/NXo2+gaS5gZfD4rlmtnPNY3ExslXCv6UptPNKMSkwIzABJ3AjBzezrUXSncCqYXGfUAnU8X6xxsOJ6h7AmAzDmwk+bNvkL2AlM3uiynH0A77C78N/AeOHTHq3IQi+JR7w11lkG3Xn+bsbksbGAz5bZVZ/G5YfwqtFts28dxmwg5kNrXDMa3CxNXCLwEPLbdvqkDQGHtydPax6AFjFzP4tv1eOHH0LeaY7R8NgkX1GmlmZhB4oumJmd5BmM0YBrpV6hvd4I2Bm9wBzAHdkVm+FZ72Xrcc5FGsWxYoU6028JzamPeF+Ds8UDLLIFrTITi5FuANK+nX3FUhaGlfEzuIyUh/kMXFhqE8lxZLGqeKwJ+KqzQBbS5qpHmPtAag1051UipwSFkcmJdxPA2t0F+EGsMiGAuvhGW2AMUhLpY+uQVCwZiG1oPC8vKRTJb2HU87/wwWnsoR7KC7iuDursSo74p3cszGoyYR7UVLC/TmFJfml94k1jmLFeLXNoSTVDSMxjPU5n5FINAEScbXFqxlLEIRLSrxHA6rar844krSFbEPF1Y29JyI8296gkHDfgRPMZ/FqlSzhPgzYuhLhDjiE9D68T9CB6HEIQaArSAn3+3j1Tk64c+TIICfdORqNbCZg7x5qMXIAbi0FMBOeFeyzCD2Ta+KTjN/D6imBByWd0ZmghGLNqliDFestvOR5MFCslP4srqI+tUW2kEX23xDY6Qh9lnQHwn0X7ftuH8OtXM4jnfSNBRyBk+8oZHZKIqj8J3ZU/YCj6jnuFkbVPd1FuATI9mt/imeB/qjHoGqBRTYE//1+nFk9HM+AV4uqLMMkTSlpR0m34a069wN7ATMUbfoFLry0Fp61Xd7MzmQ+7icl+Is26/kR9DyOy6yKK2WWFWtsxYrw7/kI/LcF/ls7D5jOjrUdGcYqpOR5dGog3jS5xNwi+4VCzYLTFat/mc17JCSNLulMPAiUtNH8DmyD/4bGxEXTlgnv/QNsbGbHVBMgMrNPSN0FRiUVb+1piPHfLngwdo1qq6Zy5OhLyMvLczQUYZL0LC7GBbC0RfZo80bUOUiaES8RTQjlRmZ2XROH1BKQNDVOKJbOrP4Q2NLMSvUR+35+XcxKWjpeytoLfEKTlI5/XmabymOMNSY+ERDwskVW7NXdKyFpGVywJyFFT5Lah91mZmuF7abGJ89bUyhU9QueoT09eE8XH3904CPSVoP5zezF+n6K1oKkR4Elw+LAakp6JU0OPIFbuiX4GZjRzL6v+yCrgGJNjtsWjZlZ/QWweIWKkXR/aQLcBgjgLjNbLawfCVfVTsrGZy99BIbjtl53h39vliMpivUgkFTRTGuRfVJqu0YitNUkJPc9YLZSWTzFGgt3fNgHGCfz1r/4ffKY4kBhUDW/Bc/4g7cfrNxRqXmoSPkBr1R438xmrO1TdR2BZL9Eqq2xvUV2YXePoxGQtAheETRdZvXDwDZm9pmkhXEBxAnDez/gtlhln3tlzjMefh8dB7cVm8us57RASdoQuDYsjsCDifc1cUg5crQsctKdo+FQrI1wiyKA2y2yNZs5ns5C0lb4xAngN/zh2O0TwFZDKC3bFTiBlOCNwAW3okQZOxDt2UiJdrmS5Kdxon1TZ4l2uzF6Bn0WfPI7ZhD667UoQbjvwP/mn+EkeQiu+PxXZp9pcPK9FWnJMXiG8ljg7GKSKWlX0kzNA2a2Qt0/TAtB0nN4ANGA/h1ls4LC/2N4VzL4fSPJel5hZls0aqwVxxXrZlJ/4J+A8cLrT3Di/WXF/aXRcHIITp4vxEn2CqRe38X4jpRkP1DJ27porFn7xm0ssksqbV9vhPvbS6TuCBuY2Q0F28QaFRfaPAQYP/PWcFzz4phKwYIuEO/HgMTve3oz+7DS9o1AUMF/NCx+D0xvUf31PboL4buI8falpBp0CF7xdraZjQhE8zLStoh3cW2Gj4uPV+U598OflwD3mdlKlbZvFUiaFw/mJsJxVesc5MjRF5GXl+foDtyEZ1EAVles6Spt3MK4jNR2ZyzgmpDZ6dMI1mJn4JPSZ8PqfrjQ1otaXhso1lF4Zu114HDaE+6n8LLTKS2yRS2y0+pFuAOSEvMBtFc871UoQbhvJ7UFS0QBBwLLZ/czs0+CINoMFJZDjw/8F/hA0nZSgQL8BaTq8MuHc/dmJOXlQ6og3BPgZakJ4f4YJ0i/hOXNJS3XiEFWHFesNUkJ93fAQjhpAM/GP6S4vB2gpP64rkOCRfHrZX0KCbfh2gsR3tYxqZltbWY3VEu4Ax7LvF6y7FaNwwakhPsl/HkGgGINUKztcK/l/5IS7uH432QGi2y7jrLzIZi1Nt4bDGmp+WLl9wLS0nToZuuwBBbZY3iQFDzre3gzxlEPSJoHt5o8gHR+/CweYD8TMEmH4pndhHA/DCzSWcIdcCYeEAVYUdLylTZuBUiaFM/0J4T7ElxoLkeOHGWQk+4cDYdFNow0Gya8/K7HIUyyd8ZLwQAWpO/0snYIM3sfWBxxMBPzL8sAuzEbi3EdLiyTLX80PEK+JzCFRbaYRXa6RfZF+yPXBX2irzsI/hQT7vUzgj63ZjZfq9QxzOxjM9sGD4xcjX9X4J68FwBvSVpfUr9w3CMyux/Xy/3sk79rxX7uUPp7H6kA4OfAMkFULetrfK6kuvpcVxyXt1qcmVm1VxBPW460x3tG4AHFasvYShpf0saSrsCdKJ4pc4qf8aqmzXFLr4XM7EgzezGIf3UGz+P+1dDNpDsEVbP3+EPMbIRi9VOsDXD9iQvw3wb4b+VqYCaLbBuLqidiZYj3vR0Q76b5dRfhANLvaE/F6vZS965A0kiSjsCDRImWyFDgIGAxM3tf0sg4sTw6s+vFeEVCl/qXw3ef7Y8/MVRYtCQylRmTh1VPAzs3U+gwR46egLy8PEe3QLHGxbPdSVniFEGIpcdB0vz4QybJ+K1gZg80cUgtAcUaBGwS/hWLoPl0dCgvMgqXATdbZF9149gWwCdUAJdbZFt217m7C4Fw30F5wp1Mln7AJ/Q/ApN0pDAraQ7gGGC1ordexstpH8SFBhOCubaZ3dqVz9KqkPQVbmL1uZmV9CaWNCYuGLZQWPU1sERS+hsm04+SKk53m1WQYp1GGvS8D1jZIp8EhN/v48CUGPA5b3MVN/EPy+KfpRwJ+Ac4GSeAzzdCsVixHsE1zMGFFP9X73OUPK+0Ay58BvAoS7IMS7Mi3m4xd9HmdwKHdtWSMPxGbwVWDKv+xO3EniyxrfCAzuQ46R0/2zLSnVCsI0mz3HdZZMX3i5aEpFnwKrb5MqtfBbYwszfCNuPhFQ5LZbY5GDihXkQz3BdeAOYJq7Y0s8vrcex6Ilxzl+GBNfDrb34z+7Z5o8qRo2cgJ905ug2KdRbe9wZwgEV2UqXtWxlFPVjfAnP2xYeOYk2Il5VuCizSbgPDi+bewovL/+AfnKid1oXMV2fGOQquOjsS8I5FNkt3nbs7UA3hzmx7A24bBbCkmT1e5TkWxRWci9WVH8MJR/J7eBuYw8yG08sg6Wdc8KikcFXodb6bNCP7Pf43fqdou5mB1/Dr8V9gbjN7s4FDR7HmwwNP/fBM/azZsmdJYzEVmzMOJ/ExAymvq/477sG7NG5/9pWZTV526/qMfTBepg6whUV2RSPPBxAqED4EJgNgYXZgRTYj7aFO8DhwiEX2VB3PXQvxPh/YPiyuamZ3F2/THVCs0XGRueRaWMUiu6fCLk1FaJPYEw+gJKXiw8Py0cm9U9J0uANEorj/N07Ib6DOCG4TiZ3f57jYYrdZClYDSfuTOlf8hVcCvNLEIeXI0WPQsuUrOXolslZbuysu6A3taTiFtAxwYuCyVi4HqycUawzF2lSx7sKzeGfRnnA/BeyGmJRLWZAXeDdM4kfBex8fkTRtd43ZIvsH7ycHmCmU2fYKlCDct1GGcGfeT7BWtecxs6dwMrkKqYUeYd1JeGkxuGDdZtUet4ch6elul03MlFwmhPtnYPliwg0Q1iUWVAOA8xp5/wj32vNJn/kxg/lU0iyS9pP0MPAj/+NMXi9JuN/Bs9nL4AJ865J6NHdHeXwz+rp3JSHcU/ENK3I+hYT7Fbyke6l6Em5oKzdeC69GgMo93k21Dktgkf1JYevEqYpbU/MkPHsewZ9FWTG0RczsiAzhXgzv6U4I93fAUo0g3ABm9gjp9zklsEcjztNZSFoFF0xNsGVOuHPkqB59giTkaA1YZO/jGTHwB8q6TRxOlxCytFvi/Y3gGYl9mjeixkKxRlKsVRXrajyzfyU+wcuqXL+FZ7GnCT3aZ1lk35jZ83jJ3GmZbZcAXg8evt3VA5z0dQvoFbZhQbismHBvUIFwg2dtkiz0mrX8/c1xD/732wgXkEowbub1sZJGoRchZMZGDotDit4bCbgeV+8GzwavGHq4y+E44P3wehFgh/qNth32ICmHHsInHM00uADeW3jAZGkK7eL+ZrrgIr0nMJhPGcxhZvZI5tpKAg9Z7/JG4Vm8xxYKS3wbAkljo0yP7apMknn7A/zan88iuzcpz683ShDvMShNvB/C/b8BVmmypsI1eOsVuDbArk0cSzvIsSMegE0qdgw4FZgnPKuSbTfB/7aJtsHbwIJm9hyNxQG4+wfAIUGQsekI1TnX4M9PcK/6G5s4pBw5ehxy0p2ju5G1k9i7aaOoA8zsO7yvKZl0HSdpgQq79CgEsaDFFOtsPKN9J7AxhZPsz/FSszmB2S2y40r5/JrZEDPbG5/cJ++PDpwL3B28jBuNXiWmJmlxaifcBNGfJHM4LWkvdtUIivXX4b37OwDFFlOTAQ8EhdvegmxGt410BzX3q4DVw6q/cK/a7PXWDoFU7ZhZdYKkyeo01jZoaS3O8JBVN+AqpuFfdgSmLtr0Y+AMPHs7HpuxOAvwRwilrAxcU1SdlJDuUUJAomGwyIbggmoA/wk+4w2BYk3KHDyIBZ/tOUic6L/Er/VZLbLrLGp8e0wF4r1oZpvfcR94cPX5GWgSQgBiT9Jn4uDQgtR0hGfMPfgzZ/Sw+lNgaTPbJynjDsT8CPw3nQTZHgAWNevYw76rMLO3cIE2cJeUpqvBh572O0jtDm8itfHLkSNHlchJd47uxiOkZb4LKtZClTZudZjZg6TlVgNwG7GxKuzS8lCs2RXrOHwS/gSu2J71nv0JFxdaAhhkkR1okb1eTcbHzB7Fp7EXZFavBLwpadMGZ2lezLzu0aQ7BHfuIg2A3E4VhDuDWzOv1+zsOMxsmJldAEwP7A9k/XkXBz6SdJykcUseoGchS7r/gjbxo4txXQNwUbHVS/XelkL4PSS+02Ph5a5dgqRRJC0v6VRJ7zEZj9M/kIcXSM0bPXP8AB78nBGYzsz2MLN7zWyIRfYcsCppgGFt4DLFbQQ7W2Lf40vMFWtcxTqeP/iId4KoVj9gSX7GPZunt8guCG4c3YYKxDt7D2uJEnMAi+xF0mt6bJrs8BFI9GbAm6Q98uDtFnOY2WOZbUcBLsd9urPbrVqjzV1XEZH+vnYJfeVNQaaK5z9h1Wt4WXm3abLkyNFbkJPuHN2KQMx6TbY74AhSf+ppcRugHmWbpFhTK9ZBivU6HhQ5iMJM2BDcm3QNYFKLbCeL7InOZHvM7Hcz2wGfHH4dVo+Dl6zfKDUsM/I26USmx1YkSJoLn4Anfen3UhvhhtSvG2ro6y6HUMlwMn7NvJV5ayB+LX0s6WBJo5c8QM9AtsJjSPiNn0Oq4jsMV25/uN2elbE/riQPsJE64XUuaVpJO0m6LRzrfmAvZmaGtrzn78DDfImTiLVwpesVzOw0M3u/lAqzRfY4HpRJrq1NgPMUKxFjS9AdpPvRzOu6kW7FGl2xDsaDjAfyBAPbirUH8QLjM8gi+2/ItjcFGeJ9f1g1JnCfpDnDcsuQ7oBD8SsOYAfFmqsZg5A0EXAjcAWEygX4Crf52jFUCSTbjo8HoRI9CsN/mzuZdXug5SvSANwAXNytWTgFWDa8/h5Y08z+bOJ4cuToscjVy3N0OxRrVFzTeiK8t3Ta7rKAaRQkTYOLSyVZ7m3M7JLyezQfijUBrmK9KVBKoGc4Pgm5CrjNonSCUrcxeNnaGfhkPsH3wA6NsJ1SrEdJJ+yTd6dtWT0Q7G0eA5I+v0fwLEzNhEDSy6S2R1OZ2ed1GuP0uPBWqZLjb3Cf2wtqDBI0HZJmwj8XuGXOr6RCR8Nx8bpbOnnsbYELw+K7uBtC2b9P+N0sAywf/k3TbqORgN3wXCPAx+zL5ZzaGYsjxVoduJm07/tMBjMRsEFYHmRmn9V63BrHMDrwSxjDexbZTF083si46vfhJAXkv+B3I1c8+AvP/n9d8gBNQFDHv4u0r/17/H72Lh40GIQHSMY3s/L6890AxQUq148BSzeq/73k+aW18YqsbBD3KmB3K/LVljQD/ndNMspDgM3M7ObuGGspBOvBD/F5EsDCZvZshV0aMYasZd4wvBS/rqKBOXL0JeSZ7hzdDovsb+DssNgf2L2Jw6kLzOwTUtsWgDPDJL2lELI6GyvWHXiW+RzaE+5n8O9kMotsZYvsykYQbgAz+8nMNsXLc5Ns34TALZIukzROnU/5dOZ1e4uzFkYgsw+REu6ngTW6YClza+b1Gl0YWgHM7APgosyqN0mFgSYBzgTelbRZo3uB64xspnsOUsJt+AS9U4Q74BLSapmZgL2yb4aS8aUlHSvpBVw5/Aa8x7iYcH8HXMrm3NpGuOFepu0c4QawyO7AA2PJ97gb65K13Wu4mFpQx0765GdUrEkqbV8OitVfsTbHieqZJIQbRnA7H7RJDMLprUS4Acw9uNfA79Hg98qH8NLfxJ5rZDwg02z8H04awQMD3SKcKmkcSZfjQaKEcP+AB8U2K0G4l8D/ngnh/ga3+Wsa4Ya2Xv0os+rk7qygk7Qk7kySYKeccOfI0TXkpDtHs3AO3v8IsL1ijdHMwdQDZnY9abZqNODaYCPUVATl8ZUV60pcefxqYDUK1YrfAQ4D/mORLWKRnWmRfdddYwwqqLNSWPa8Bd7rvULpvTqFHkm6JQ3CJ9cJ0XgRF+vqSjYrax3W6b7uMjgS97MF7/deFhffSTANXvL5qqQ1ekg7RraEeu7M623M7NquHDj0R+5KSmqj0Je9r6R7cfuxh4GDgflIFYTBM1CP4iW98wOTMpgTmIpVw/tDgT26mmW0yG4AtiIRyZqd2TJF3t2hYA6Ffd3FftkVoVhSrDXxiqTLKQxW3Mi9rMHHbX2rv5D6zrcUAhlbBXg5rJoUvzdkhfuaXmIebBqzjh4nK1ZD2xDCs+JN0pYP8PvcbKWUtiVtDjwIjBdWvYkrlFcUQexGXIR7nwMsSh1agapBqNy7iXSOcJqZXVxhlxw5clSBnHTnaAoCobsqLI4NbN3E4dQTe5KWoM5JWl7XrQgTzEUU6yy8h+1uvIw821P7BT6xnBtX5D3GIvu4+0frMLNv8UnFlsBvYfXkeO/i2VJdAjPPZF73CNIdVHcfwm32wHvuVzSzX8vvVRVeJ1WSX7qeVQVm9iVeqAvug7upma2Hk8IHMpvOhk+Kn5K0VL3O3yCUIpa7mNmldTr+d3i7QHKu+3Fv7BVp3zP9Bt5ruTIwrpktbWbHmtmLDMbwv33ikXyiRfYBdYBFdgWwU9uKpXEq0D093VBIupeqdifFWgoPuN1KoVr/A8D8Ftn6PMs2pHOiE4ozoq2EIOq1Iql+wlR40DQJZDfbOizBnaR96FMD+zbiJJLGkHQOrnWRKNv/ij9L1g7Pluz2knQkHnxJfif34grlLdPqFnrJD8ysOj4ImzUMoaz9dlLx1Pvw3vYcOXJ0EXlPd46mQbFmJ1Uy/wiY0SIbXmGXHgFJs+NZh8SneE0zu73CLvU7d6xZcHK9Cd7fV4xf8LLUq4BOCaF1ByRNiatCL5dZ/TGumlqVMnTZY8d6By/hHQaM3UyBpI4gaWKcaMwYVr2Llz7WpQpB0ml4oAhgEzO7ph7HDcceH//OxsK7ZGc1s/fCe8vgPtXFgnb3A4eY2Uv1Gke9IOlcCi2+9jWzU7pwvDFx4pj0ZVdqR/kKJ4gPAA+Z2TdljxtrfVxtGFw7YxaL7K9y23cGirUXWUHMjzjLLrfd6nmOMucdE8/69wfetshm7WD7eXERquJqmeeAgy2yRwCCEnhiSfYN8J9Qyt3SkDQJ8DheTQLwJ2lgdXYze7MpA8sgPJNex7+zv/Dn/BeV96rh+G6deCkuYprgAWDbUjoVofrsYtz+MsE5wB5m9m+9xlUvhODJY6S+4rua2dkVdunKufrhZflJ5dP7eOb/l0acL0eOvoY8052jabDI3sBLu8B70lZr4nDqBjN7g8KyuovC5KghUKwpFesAxXoVz3wcQiHh/hufhK8FTGKR7WCRPdaqhBsgTJZWwEtuk8nvtMDjkk7qYtl+UmI+EjBvF47TUATS+iAp4f4IWLZehDvg1szrtep4XMzsR9JKj/5krIOCwvdCuA3V25ndVgBelHS9pBlpEQShsyzhvrtWwi1pgKRFJEWSnsSt927H9RPKEe7v8YqZKcxsKzO7qgPCPQaF7hB71ptwA1hkp/FG270b/sOuirVtvc9T4ry/k5ZVz1LOA1qxZlKsG/A2jCzhfgu/zhdOCHdAVh36qJ5AuAHCtbAsacVKtpKp6SXmABbZ26S9waORWmx2CZJGlXQyTkgTwv0XsAteCVSKcE+I31MTwm34s3rXViTcAEGHYb/MqsFqnC3pkaSE+1dcM+SXBp0rR44+h5x052g2ept9WIJzSHtmJ8CJd93K/RRrPMXaQbEeA/6HT2TmzGwyAs8abglMbJFtaJHdFvrsegTMcTb+uRIBF+ETkJckdZYwZ/u6F+3CEBuGUOp9P2kp7P9wwl1vtfWE/AGsHHxq64nT8bJpgPWz31n4fm/FRcm2JCUO4MJ6b0m6MFQ9NA2SNqHQVx68bLaj/SRpRkm7Zay8ngIG49ddVlNhON76cCSe0Uqu9wmB1WoQQDuctLz2bgo1EuqLm3iIxwvWXKBYm5TZup54NPO6oK9bsaZSrItwcr1e5q1PcY2IOcN9sO3vGaoukoqaT0h1OXoEArlcFviy6K1WCmIPJhXK3ESxunTflTQfHnzZl1Tf4Clc9f+cUr+XIGz6LOk9/y+89LzTAoPdBTN7nrR6ZULggHqfQ9JGuC4E+Pxhw6QyKUeOHPVBTrpzNBv3kgqFLKlYc1fauKcgPMS3x4XLwLMOO3TlmIo1mmJtqFi34SWQ59FeTOg5vFx4MotsRYvscovst+Jj9SSY2Ye4+u0BpH7BswDPSRrciR63lhZTC2XH9wDzhFVf44S77pZMIbuTEMgx8S7deh7/DzIZbkr4zZrZcDO7HM/27k76m+kPbAt8IOkUNc6/vSwkrYv3fRYHzEr69kqaSNLGki7GS7vfxfur1yC1E0zwPp4BXAu3eFrEzKLQPrELtOloHxaE9CqPNdbMpBU2/1AH8bQOMIyHyaokCLhcsdZp4DmhsK97SQDFmlCxTgE+gILe7G/xa2pGi+yK4valEAg9LrPqiJ5mZQdgZh/jxDtbBbOYpEmbNKQCWGQ/4wGhBKcHr/eaIGkkSTFOnmcOq4fiPcdLhmdFqf2Wxq/UJCP+NbCEmd1WavsWxcGk9519gtZHXRCCGFmL0/3M7L56HT9HjhyOnHTnaCpCifNpmVW9JtttZt/jpCHBKcEPtGoo1gDFWlGxLscnkNfiE/gs0XwPOAKY3iJbyCL7P4sKhWN6OgIxOwknokl5aX/cUuVZSRV7O4vwHml2dxHFLSE4BLT58N6Bl16DlxcvW24yWSc0UsUc4HzSLPYK5QTTzOwfMzsTbzU5FC9vBNdG2Bv4OARZGlVaWQBJqwLXkPqNP5F5e1jYZqCkFULLwyuk7gBbkwrfJfgB//1uC0xtZjOa2W5mdluxKJ6ZvU4qRDeQwoqg9mP1a/hM0uz58RbZR9V/2k7BCcB9wFdtpeb9gWsVq5GlzU+SqrwvrViDce2AvXG7LPBr51DcjeFMi8oS6bVIdQXexL/vHomQlVyO1DVAwL2t4KARcAEuAAje1rNlLTtLmg0PKh9B+pt8GZjHzE42K60HI2krvGponLDqdbxPueV0IyohBFaSMv2BeFVMlxECM7cCyXVyCYVzshw5ctQJuZBajqZDsUYHPgfGxSdyU1vUWv6oXUFQVU0Uf58HFguqpKW39wn0grgY2obARCU2+wqfIF4NvNLgjFZLIWS2D8XVepPJ1z9h+dRyk6+CY8S6E9oslWaol7pzVxBKu28n7UH9GVjazF5r8HlHxwnhqHgGaIpgYVXPc2wBXBYWnwUW6aikU9J4uHLvHqQTQsJYjwPONrO/S+3bVUhaDq8ASMrtL8Mn+KeH5evwMs9FM9sU42+cqD+A95G+VsvfVdLYeKY80YNY1czuLrltrA1xQg9eIj1rowUCJe0MuKBTP7bmCJbGS7jBf49rWtSYbJlivUyhbVuCIbg/9IkW2U8l3k+P4R7xr0Ob3/gaZnZHXQfaBEjaFQ/AJLgLWKcVMviKtQzuxAAeoJqho0qs8D3tAxxNGlT5NywfW+5ZGkTBjsI1ThLcDWwUbNd6HILOx0e444vh5fRvVN6r4vFGxStHksDT08AyZj2nDS1Hjp6EPNOdo+mwyP7ES6XBM7i7NHE4jcB+eNkj+MPt0FIbKdZ/FCsGPsRL4XankHD/ivt2LgtMZZHtZ5G93JcIN7iNipkNxgMTiQjXKLj92WOSpqviMC1VYh4CCdeTEu7fcDGghhJuADP7k1TQcFLcB7reuIrU3mghvFqjo3H9ZGYH4pnvc/GJNrhGwn/xsvPtJA0od4zOIGTibyMl03fi18s2mc02BJahkHAbTsxPwDOO45rZCmZ2kpm9UmsgI2S/sxZLZ5TKWgZF76yo2x7dpMifkp0RDMAz+Enf6SjAbYpVrBreJYTKn+1I1boT/IvraExnkR3UEeEO2IyUcD9DFX36PQQXkVqHgQcXr6r376QzsMgextWxASamzLMwQbiXP4YLMiaE+21gITOLKxDugXhQOku4z8CdRHok4YY2ccqkRUd0wZI0tFZcQEq4P8eDMznhzpGjQcgz3TlaAoo1OV6COgDPZE3VylZOtULSAvjEvT/eq7momT0XJszrAVvRvj8bfPJ0B57RvseixmT2eioCCTmKQkGdv/BAx7nlsqnBtzdRL77AIutSv31XECbDV+PiYeC2Pyua2VPl96r7GLYlFZA6zswOqbR9J8+xJqla+lt4lqZqi8AwAY9x5eFsS8D7eJXDTV3N0AfCfTep73TWgqkUPiO18nrYzH7oyvlLjEf4dbpkWBWZWUFZqWKdTErO77DIOgxo1GlsW+JWTeB+5eco1kh4xj3p6/4HWMMiu7/EIao/l/f/rof/1otbdN4FVqulnD5UlbyHe0cDLGVmj1XYpUdBKqjkSXAlbrnYVNcKxZoWJ86j4IGbWYsrjUKWeic8kDpaWG14sO3wShUukibCg2ZJi84IYC8zO6PcPj0J4Zn3Hu7NDrC8mT1YYZdyxzmAVEn+L3xO8mpdBpkjR46SyDPdOVoCFtmXpFmSCfAsRK9BUB91QSnRn+m4UYfrKlwQ7WIKCfcIPPO4Na48vr5FdktOuNvDzP42s/1xUvJxWD0aXvZ6XwXl6xdIhaqalukOk8uLSQn333iZa7cR7oA78UktNKavG7x0/tnwelbcT75qmNmHZrYpMBeFWckZ8HvHC5JWrNUlQNLIkpaUdAVe+jow83Y5wn1OOO80Zra9mV1fb8INbYKMu5Jm+Q+W1OZHrFizAXuFxb9JPde7A9ks40gAFtkwYCPSbOYowO2dzXgrlhRrJdz66zraE26AIZ3oX9+BlHDf15sId0C2DSG5z20GnFtPF43OwCL7GCfP4NfNaVldjXDPvg/vX04I98e48Nn+HRDuWfB7TEK4/8Tvp72CcIM/8yisEDgxPEeqRtCrOD6zasuccOfI0XjkpDtHKyErFrRXKwlc1QX7cTUr8SV7ApsxBQPYhHRSAZ6xOQiY0iJb3iK71KJCgaUcpWFmT+DWYudkVi8PvCFpi+KJZmhpeDUszqpY43THOLMIYzoH2DysGoZb2Dzc3WMxs29JS+5nkVRcvluPcxiuwJsg7oxFmZm9bmarA4tRKG42D+6G8IikhcvtHxSQF5Z0kKR7cFG9R3FSUvxMHAY8jisvX5RZf7uZfdAdVkNm9hapsNGohL7yjHhaomtwnEX2SaPHk0E70g1liXfNpeaKtQj+vdxDYf/24/h3n7RezFXL71fSGHhlRIK6V3W0AO7JvH6flHhvD5zWbOKNazIkFmerAGsFi70tcUG75TLbno1XxTxZ6YBBh+FpYJqw6ktcP+Wuuo68NXA18Ep4PTc1BDBDYOIa0mqh2MxurO/wcuTIUQo56c7RMrDIXsSVacF77eraD9gMKNaYirW1Yj3GGLzPQkzepqEKMJw/8X7VhYBZLLITLKq7F3OfgJn9YWa7ACuSTujGxkWwbpY0cdEu2WzyQnQjwqT3VFIbueHABmZ2b3eOowiNVjHHzB7Fs1gAg+iCjV6oBlgSn7S/mnlrSeBpSbdLmj1ksheVdIik+3GBuqfxif9KtM9m/473f64GjGdmS5rZ0aRWZlDGMqyBOBIXTwRYTdIaeJl9Unb+MV3o7+wkSpJuKEm8R6VK4q1YsyvW7fjvM1sB9AqwMrCURfYUqXWYcBJeLfYk1cq4wcxerrRxT4SZfQK8ExZnBHYkrWTZAzi2mcTbIvuDtEIDfucM+nE73q6QuBN8ibfZ7GpuPVgWkrbDAw1jh1Wv4Arlr9Z14C2C0CKwf2bVMaGPvSKCENvtuD0kwE3USQU9R44cHSMn3TlaDdlsd4+0D1Osfoq1tGJdRqnyccP4ALgBOI4/GMwRFtlzfU0QrVEws/uB2YArMqvXAt6U+y4naIqYWpjsHktaCjwC2MzMbu2uMZRB9vxrNfA82cziYSHz2CmY4x7cgmgjUsFCgNVxdeq/8GDeMXj1QzHJzv7u7gcmNLM9zOyuosl+VojqX7oRQfwpvR+OwhlYW4kuuHhad7eflCXdUEC8bwmrKhJvxZoqWCO+hn93CT4Ix5nPIrs3c59s59fdEQLpOCAsDqfQO7q3Icl298PLrLP2lQfRgYhZN+Am4H7eAs5mckawWua9y4HZwr28LCT1k3Q8LgiW/D7vwEvRvyy/Z8+HmT1E+h1PiQuvlkVGrPM/YdWrtECPf44cfQk56c7RargNt7wBWFGxZqm0cStBsaYN6uMfAw/j9jnty8f/ZUqu4i7eAv5lYuCCFij361Uws1/MbAtc0On7sHoC4EZJ10iakELSvWg3Du8wfNKbYFszu7bcxt0FM/uANDu2SBAkasR5XibVb5iILvYhB2GhxfGM3pe0z0L3L1r+Ci/PPAXvg05+e3fg/Z/l1HuzxLK7M93gYToXTFqKqVCbldhtFjWlhDYbeGhHuqGNeG9Ie+K9fLKNYo2tWMfhZdCbk34fX+KVELNaZNdZ1I4cPJ55XRXpxi3okkzqpebe1r0V2b7ulc3sElwfIMFRkvalWRjMBJzAUG7Ajd4A+vEj3mKzpZn9Uml3SaPh95EDM6tPC/tXzIz3IhxA6ll/SAgqlcOpuOMCwHe4kvufjRxcjhw5CpGrl+doOSjWXqQZ76YqS3cExRqDVH281MTvV7x/6lLg+SRLI2kS4A2cCAJsZ2YXldg/RxcRCPa5pIrK4Ar5uxNxEmIKPBM0jkXW0AympP1wRd4Eu5jZOeW2725IOpa077ph16SkGXAF4/64Pdq0wQ6nmn0H4u0ASwJLhdfV9ob/BES4+u9tpKJpdwDrV7LLkXQGsFtYXMDMXqjynHWDpJmYiDfYiQH0A4x/EDNZZJ82YSxZz+Xjzezgstu6qvl1wNph1d/473E64AjS+yB4+f+xwFkdOVgo1pu4KN8IYNxKns+SJsftGEfFVdWnN7PPKx2/JyPoJfwAjIEHHicxsxGBaJ+c2XRXMzu7G8clPBBzBtnvfWZgZZ5iLBbvqOortArdTmp3NQLYvTs/R6tA0kWkdoYnBpvF4m12xJ+B4AHDpZsg1pkjR59HnunO0Yq4GO+rBNhcsSaotHF3I5SPL6VYl+Ll45dQSLhH4IJOGwGTWGQ7F5ePm9k3wHaZfU6X9B9y1B1m9j0eGNkMJ13gk71ruBjh0/TRgdkbOQ5Ju1JIuPdpJcId0PC+bgAzex//3YBnHttNFBNIGk3SspKOkvQ48AteSRLhv7tiwv0ZXp66DS4ydDIwNLw3Hj7Zv48aCHdAtry8GZluGMx7bMjXbU/u5/gfg/msKWPpoLw8izIZ77uA/yMlXkPx7+o/FtnJVVpGJiXm/ei4WuXwcF6As3oz4QYI13NiJTUh3oKBmf0XD3QkOEvSVt0xJkmT4W0s15B+7z+xBt+zATAWi+JaBZWOMQPuq54Q7j+A1foi4Q4YTOrLvrukSbNvBhvEMzOrdsoJd44czUFOunO0HEK2IsmwjYr7dTYdoXx8MPAR7p27JYX9oYn6+FQW2cqhJLJsn6WZ3Ub6OUcHLg+ezTnqjND7exUu0JcqtX7O5JyFy+6MaFxfd/DBzk58DjOzU8tt30S8AHwdXi8vqZJHdVcRUzhZnBxA0uiSlpd0jKQncZL9IF6WvzgwctFxPsEJ/Fa4hdegUJ56iZm9GizlZsIn+gmSEuafgJOqINxQSCy7tac7g00ZH7fB+xF4gOlJs8fdjSzp7vC+FYj3qaSBr2xLzdXAjBbZ/hbZzzWMoaq+7uDxnvQ0/46L6PUFZEvMV8m8PppCy6iLJG3UqEEEZfJt8OqWrI/8jcAszMNWmavhFMUamxKQtBCFCuVf4P7S95Tavi8gBI+S4O1AMr36wV7wRtLf52lmdnH3jjBHjhwJ8vLyHC0JxZoGLwXsh2eTB1lU1cS43uPoVPl41ceXxsQFTRLv3cPM7JhODjdHlQiCamcBqaL5pHzN1yxsZnXNHEraBLiSlGQcY2aHVdilqZB0Lq52DLCOmd1SafsunutkIOkrfRUvO56PyiTuI9xK6jHgMTP7X5XnWgYnIaVK0W8ADjYr7/cs6TJcpwFgpu7uBw5E5D2Sa/ZK/A4JnwMzd3d/pqR5cf9sgLPNbNey28aaDie665V4+x9gNYvswRLvVR5DrInx5wPAsxZZSas4SVeTZlAHm1lc67l6IiRNgV8fAM+b2YKZ94T3QO8RVg0H1qu3oKOkQcD5uIhhgm/x1pqb27aLdQupgOP/WWQFWg+SVsdbFJIKlTfwXvVeLZhWDYL+xsd48H4Y7mf/M+4AMGvY7D68IqBZAcMcOfo88kx3jpZE8Ju9NSxOgpcmdgvqUT5eLYIq8eakYiiDJc3XpQ+Qo0OY2U3ALCijcP41k+IK57tKqsu9MZD7y0kJ96m0vmLyrZnXa9X74JLGkrSKpBOApTNvzYX3ZxcT7g9wdeLNgCnNbDoz287MrqiBcC8L3ElKuJ/HCWyC9YF3JJ1aQYyo2eXlR5IQbuNmPmyzXpuSQt/p7kKH5eWKNb5inYZnOLOE+128RBj8O7lDsZajRlhk34ZjAcynuH1lhqQ5SQn3D7iAXp+AmX2Bk1OA+YO+RfKe4bZdF4RV/YHrJK1Yj3MHZfFdcd/tLOG+HJglS7gD9sKdBgB2U6w2b/bQk3wrKeF+BFg8J9wOM/uOVAdnJLzk/AZSwv0+sFFOuHPkaC5y0p2jlZEtv91LcWMVvutdPl4tzCzxDAaf2F8RlFlzNBBm9pONsC1Ylzfa9IxddOhM4FFJ03fl+JJWxasgEvXsc4F9rfXLix4h1VRYrastD5LGkbSapJMkvYBnYO7ClXfnKbHLu8B5OFGa3MxmMLMdzOyqQCJqPf+yeN92tod7cbyHfxdcyRd8sroX8JGk/YMqehZNKy9XrDlJRdyGIPbGLYKSXvV9Jc3UnWOiAulWrFEVa3/8Xrpn5v3vgJ3xv/1SpAGeUekk8SYtMR9Aaeu/bOXQsSHQ2ZeQlJgLKCDU4V60M143Ad66cWvoA+40Qt/1o/i9NHmGfgGsElo/firexyL7DDgqLPYDztYG6ifpSPzemcxXr8Ez3L92ZYy9EP/FW3HAK3KSQMdPeIb7lxL75MiRoxuRk+4crYynSMsX5ybrdV0nKNYYirWVYj2KTxAjYFBmk1/xB/5CwCwW2QkWNSS6HgMvhdczASc04Bw5SmF27mQXgsxQGxYHXpe0X2dIp6TlcB/ahGxciqsEtzrhTgSYkh7J8YDFatlf0riS1pB0iqSX8O7jO4D98NLx4ufOu6SmQQCbmtlOZnatmX3VqQ+RjqWYcN+Ol9AONbNhQchuOrzHNRnD2MCJwLuSNslUPTTFMkyx+uGtEMk4jrLI/hcs3k7MjO3MbrYebEe6Q5XQpvh3eiL+twT/2x4NTGeRnWuR/WuRDcUrmG4N23SWeJft65a0GLBqWMz2vvYlZPud23mkm9lwYGv8fgX+PdwpqWSpfiVIGiBpf9xrffHMW+cBs1bRe30KSeXCcBbiCR6nsDLoJGCzKjUY+hQCqU7mDcl9YCiwVrhX5MiRo8nISXeOlkUo185mu/eux3FrLB+ftCvl49XCzIbhZeZJ5ny3epX55egQTzEqsDqwJjfgvXHgk8+TgKclzVbtwSQtjquAJ6XM1+H2W8U+w62MWzOvK6qYSxpP0lqSTpP0Ck6yb8N/r/PQ/jnzJp4BWx+Y2MxmptC3vC6aBpmS8izhXt/Mhma3M7PfzexwYHr8XpD8zqcGrgKeD5m/ZpWXb06qzP0+heXRxwGfhtfL4n/T7kIB6VaspfGy/Svxvx343/JiYHqL7HCLCrPMFYj3sjWMI0u6l0pehABEVjAtNut6ZVIPxDOkZdvLlQrMhLLjTfAKFPDs9D2SSlWilISk2cO5TiRVif8YWCYE0craubWNw6+HXfgHz2d/03bdG7CXmR3Qw+6j3Y1iPZIjzeyJpowkR44c7ZALqeVoaQR/10+AyfEH7wwW2YedPNY0eMn4lhRmsxO8h0+6r2xQNrtDSNoNtzQCV5GevVr/4hydg2KNj/d6AjzHYJbFyxz3Is0YDCMo/haTtoJjSQvgSttjhlW3AhuEoEqPgaRxcG/fATipmzbJ0gfRnsVwgrMkMEcHh3udVPjscTP7oXiD4Cn8HilZW8rMHiverobxJ4Q7mfyXJNxl9p0DJw7FQa/vceslgHG7o1xTscbBiXZy3hUtsvsLtpHWILV6+woXeWt4CXWwf/qSCYE1+IYpmaRok/uAAyyy1zs8VqyRgetJAzx/4+JqD5Xfq2D/D/CKhWHAOBbZX5JWISWR7wGz9dWeVkl3AyuHxdnM7K0y242KV4Yk1QY/4r/FNysce2Q8aHYYaTWI4SJth9cq8CdpYsbjbX5iPAD6MZwRbGRmN3awa5+GpPnxe+zAzOp7zGyVMrvkyJGjm5FnunO0NILNTGK1JFKl1apQVD7+MZXLx2duYPl4tTgL2gSSJgXO7eaS0T4Hi+xHUjGmeRjMCDPbB88uJutHwlsAXgiqze0gaS78u0sI9724eE2PItzQVqr4SFgcBMSSLpP0Aa48fBPeU1xMuA1XIT8Nt7KawMzmNLM9zezmUoQ7nO8f/LeZ4LjOXvclCPdtVEm4w1heN7OVcNKdJYwTZl6P25mxdQJHZc57YzHhDriDlFxORqEHc+OwIuOyGt4RXEi4X8eDAytVQ7ihLcO5AWnwwEucq894JwGakYCFQkvAsZn3D+urhDvggczrsuX7oRJgLeDJsGp84MHQo90OGQX7mJRwv4PbeO3TCcLtHtwJ4R4V2IL+DKZmLYe+BElTU9hGk/zdVw4tFjly5GgB5JnuHC0PxRoPF2EZiD9MprCofJYp9EAugdt8rUehGBp4+fj9eJ/t7RbZEFoIIYP0BoSJB2xpZpc3cUi9Hop1EbBNWFzCIi/JC5mfw4EDSQXRhuNl523lqpJmxbO5E4RtHgFWNWuta6sjBAu7BXFBqo2AmTvYZQTucv5Y+PeEWU0+y9lz98cJ2yxh1RpmdkeNxyhFuDeolnCXGdPmeMn7ZJm3/sCz4ac0yqorqDe/iAfH/wJmssg+L7mt+/G+jbc0/AvMVS6bWYdxjQ7si3EAKri3folnO6+wyIZ38tidyngr1mbQ5kRwJIN5h9SX/SVg/p6gp9AohNLvJAByl5mt1sH2Y+EVO/OHVV8AS5jZJ+H9gXiQbD8K74vHA0d3pow/eHDfiRN9GJmf2Y5xmQjwQN78FvXpwElJSBqbQmuwx/G2mPMyy0v15es/R45WQU66c/QIKNY5wE5h8UCL7MQS20yDq3ZuCUxT4jBNLx+vFpLWwy0/wJWk5zCzT5s3ot4NxdoWuDAsHmSRFQjZSZobv3bmzKx+D9gWV2R+HNqyfU8DK5rZHw0ddBcRMsmDcIKd/JuDyhVQ/+BE8GmcZD9ZTxVhSWsBiS/4mzh5rIrABfG6O6gT4S469mh4Bm+qore+wjPLl1Y7zqrO54HDJ4FEzKrdNVlijBFuFQT+3Sxdz4m2YvXHA5lH4VU4jn+Al/iIRZjDIvur9N41naeYeA8BVq9EvBVrSsDt4/7lcY5mMrzcHPy3WKpCoM8g/Na/xi3n/sTbIypW4EgaDw8eJtUsn+DB7KnxPv1s9vtVYBsze6WT42vvwT0Wq7EPt+FWggB7WGRnlNq/r0LSSHigIhHI+wC/Z/wKvEX6HfX530COHK2AnHTn6BFQrBnxSW8yeZjGIvsnTNDWBHagdNncr8C1OGF6vpFiaPWGpMvwIALAE/gkum4T+xwpFGsm/PoCr35oJx4WJjgH4CRr5LDa8KxnUlL+IrBcK9rZhL7puSkk2ZNW3MmzpomA2Np4j2DDlIMDOXgGz7YDbG5mV1bYJdmvYYQ7c44XcPV1wzP8/TNvv4FfG/fVg+gq1tY4sQFvcZgzlGBXGt+o+ER72rBqUzO7ug5jEbASntlPBQWN4bxAfx4D/uQJM6ubu0QniffHwDS8yL/c2XbNPooLefWY+36jIOlKYNOwuEQ1AltBv+Ex3FED3JJqbArVsY8ETuxsG03w4D6bNNj3CLC2mf2qWAvjAT6A3/Bqj687c57ehnCvPAfYMaz6CVgoUSqXtCE+94G82iNHjpZA3tOdo0fAInuPNAM2KbCfYp2Il71dTyHhHoH31m6Mq4/v1Gj18QZhD1I10sWBfZs4lt6O9/FJC8AipTzhg8XUMThxfS6sFinh/hjPKLQE4ZY0kaQ1JZ0g6Qk8APUM7ue6Lu0J9wjc6uccvKR6WrxXM8EUjbbqCZPCgzOrjgxCTWVRgnDfSp0Jd0BC5Ibi5PO2zHuz49ZM94fe/k5DscYltQID2K0jwg1t/bi7Z1b9N5SedmUsc+GtOHeTJdxwG8OYjbtJukdHardzF5Dp8b49rBpIx6rmjzEMeKxAZf7gnGi0oaq+7izM7DtcFT+x7huHlHA/B8xtZsd0hnDLUdGD2yJ7BrgovDcW3taTw7EPKeEuZQ12A34/BzfEXLsbx5YjR44SyDPdOXoMFGsxPONbDh/hD+jLW718vFpIWgLP1ghX5l3AzF5t5ph6KxTrTlJP3xksKu9tKmlSvKRyoqK3LgD2727iHYSjZsGz14uG/6eruJNnjp7FM0lPAc8X2/oU9YI+aGbL13Pc5SDpfiA5125mdlaZ7UoR7g0bQLiR9CbeN/mnmY0R1i0BnEza+wqeCb8cF++qWQBKsc4CdgmL11lkG9U4zltwMSyA08ysZqvFUK59NB58yQagXgD2s8geD+cajhOml8xsvlrPU8U4RsbJwxph1RC8x/vhEttuxVNckqGWt5u1r1jpq5A0Be5VDvC0mS1aafuwz9j49b1d0VtfAHOa2U/t96pqLCPhPcdbZ1afDBxYbAmmWBPgrTyJxskyFtkj9GFIWhsXs0x+myUrgiStht8fwTUf5sir5XLkaB5y0p2j5aFYMwPb473a4xW9PQy4GTgfeNSi3ufhKekEvHQVvHx0vj7qN9tQKNYhpB7RW1tkl5bcThofD4Qkmb+/SUkfuKDUTmZ2Z2NG2iZ4tgApwV4IL/ushI9wcv10+Pd2RxOwUML4Md77PQwYrzt61SXNhxM8cLX0/xQLlklaHs+ENpxwh/O9h/dI/mJm42bW98OzssdR6IzwN+6pfUJxMKPsOWLNi39u4TnkGWsNIEoahE+wB+LiVvOYVacirlhj4fZPe1N4TX+KVyBcn73HSvobF297zczmqmWc1aJa4q11NSd38yrpnXH2SlZXfRGS3sFLxYcD41cKDgbCdh6FAoJDSVtrngFWqPV+IGkM/PtcKawyYG8zO73sPrG2wwOa4G1Ac1VT/dEbUcIaLDazwWW2FX7PT7QhtjCzK0ptmyNHjsYjLy/P0ZJQrIGKtbliPYFPIPemPeH+HJjcItvIInu4NxLugCNIy8RmpdAKJ0f98HTm9SKlNgj+1feTEu7/4QrfO+O93eCe8ndIujIQ9C4hlGEOkrSppLMkvYL3Vj6Il3+vSHvCPRSfbJ2ElxVOYmbTmdmWZnaemb1RTcYjlObeHRZHwktNGw4zexFIfHknxn//behuwh2QlFAXlNKa2QgzuxYnM/vh3w1hbIcAH0raNWT3yiKIp51Fmr0a3JmKnSC4mASP+gNnd2S/plgjKdaueGDmYNK/6894W8tMFtm1Je6xyd+iruXlWQRytT6FpeZ3KtYyBRvezOZthHsOhjOY9xs1ph6MpA6gP7BkqQ0kTRD6v+8gJdy/4/e4eYDE9m9h/D43sP1RSkPSxHjAMiHcQ/HfbVnCHXAxXpUDfr+tuXqjNyBYg91OSrivpLAFqADh/n1oZtXgjtp1cuTI0TjkpDtHS0GxZlOs/8N7yC4Hsh6T/+BWGEnZ75R4L2WvRuij3Qz//AB7B2ukHPXF83gGCEqQbkmj4wR0nrDqa2BZM/vUzM7FAyL3ZnbZFHhb0vq1eE5LGlnSQpL2kXQjnjn/BJ9g7YKr+Rbfu7/FKz72C2Mfy8wWM7MDzOxWM/u22vOXwN2Z16t04Ti14jDS7+PAMGEvRbhvofGEG9Ke7pK2RWb2j5n9F/gPnuFOxjMhcCbwpqS1KlwL25AKyL0NdEREKuFk0vvkoqSCjAVQLCnW2rhS/JmklndDw2eYziI7xaKyvfwNJ91QQLyTUtkC4i1pGpJ+9gHAsvSnsOQ/h+PBzOuCVpEQ3NsAv/Y2zbx1DzCrmZ0bbOiWJw0sLQXcHEQaK0KJB7f3FxOOsYKZ3VB2p4AQ7NkF150AOEKxip0EejVCqf+dpC4ZTwDbdaRZYGaPkH7v05JaY+bIkaObkZeX52g6gu/rBngJ+cIlNnkbLx+/wiL7SbE2IvVgfcAiW6HEPr0OkvbGJ8LgRGz2znoi5ygNxW0K1QDjJn7wYVJ5B+lE9XtgSTN7p2B/J1RbAKfhokMJbgF2MbNv2p3TFYIXJlUUnx8v2S0Hw/usn878+6RRglHBLuunMKYvgKm6S5xKKrAKPAf/OxYT7o26gXAj6Wt8wvs/M5u6iu2nxatSNix660lgPzN7rm3bWOPjfatJZUSX+1YlrYALSoJfrzOY+fUczrkgTs4XK9r1WuAQi9yTuYNzfIvrGnxqZqVsGuuKUGp+I7B6WDUEWI3BbI/7yvuncZmwQy2yvCooA7n/9k94pvtdM5s5rJ8Ur7LIim39DOwFXFH8e5e0AE7kEhHJW4H1zUr7aKvYg9vvIytZjV7yISCfiAXeYpGtU8v+PRWSBuB/vxXDqg9xpfIfq9x/AVLxz6+A6cxsSN0HmiNHjorISXeOpiEo426PZ3HHKnr7b9y383zgmazyuGINwNWmk0nevBbZyw0fcJMRekfvJy3xvcbMNmnikHodFOt0XDUeYGWL7F5J/fEgz/ph/S/AUmb2WolD+HHKT2L3xu1bEoK9KB0Lnv2OZ4gSgv1ctT3C9YKke0hLQucwsze66bwT4xPMMfAs1zDSgES3Ee4wlh9w0vCRmXX0nWX3K0dur8fVtT9WrHNJlYivsag+v2tJNwDrhcWzzGw3xZoW7z/foGjzJ3CRtOdrOP4XeDvFl2Y2RT3G3OE5i4n3F/zDheGaED9xIOOFkMz9FtmKZQ7TZyHpKdJKninx58lpFAYJbwZ2LRUkzBxncTyok5Q6X4Z7dY8o2q69Bzes0kmRwbHx4NTEYdWqFtndFXbp8QiB3LNJg48F1mA1HOdWUgu+/UJVTo4cOboReXl5jm6FYo2hWNsp1vPAK3jJWJZwvwHshlt9bWWRPV1s9WWR/UuhdciBjR53KyBMZrYiLe3bWNLGTRtQ70S2r3vRMOE5h5Rwu4hTBcINYGZf47Zc2+FWXQDjApfi1/h5uDBgKfL2EXAF3kM5BzCuma1oZrGZPdDdhDugKSXmoSz+hLDYjyYR7oCK5eXlEDLaS+ABmGyf8QbAu5pZV2HsENb9gbcI1Av7kJh6DWRn7akrcd/vLOF+H1c7X7IWwh3QLeXlWRSUmhvwQKYqxIgYtc3ealHFlfvo+yiy1mF34/ekccLyd3jGet1KhBvA3Od7DdI2ii2Bk7PtE3IP7ltJCfcjwOKdIdwAFtmvFFpnnqG4+p7yHoq9SQn3MNzDvCbCHXA4XiUFcHCoesiRI0c3IifdOboFijWvYp2H98FeQGG/3V+41ddCwJwW2VlJWW8FXIpPEADWU6z/1HfErYkwWdkls+ocSVM2azy9EMViasfi1RjgZGsdM3uq1I6Sxpa0jKQDQy/2J8CFVFYVHxrOeTKFgmdbhB7KqgTPugH3ZF53Z183pCKCCZ6ge3q4i1FSSK0amONWXIBvV7zcG8RILM4mKIinDeNIi+yrcsfpxHk/Z1SOZRFgD/oxHpuSfo7vw1hms8huKw5uVoluJ90Aocd8fV7mBT4LK8fDOIB3cWVngNFJ+4dzpHgo8zqriXIlMIuZ3UiVMLMHgY1Je633Bg4J/eHFHtzXkvHg7gKuxsXYwHuUe23QXdJa+LMhwTZmbtdXK0J1UtKWNz7eOpAjR45uRF5enqNhCPYzmwA7AHOX2OQVvHz8aotqz94VWTyda5Ht3Nmx9jRIuhqf7IBnD5YrLuvL0Tko1ufAFDzJUB5ss8cxYJOgUo2kUXFBswXwANL8wIxVHH4EhcHOx4FtzezDOg2/YchYZg0HJsj2BzfwnCvgPdzZHveXgfm7+3qXNBQnl6+Y2Twdbd/BscYCDmQ+9me1QFi/Bc7jU0ZwCHBdVz9fUEPfEONYlLEyG8Ew+nEicGJn7rsF55Dewv3h/zCzMTvavp4IavBv4tekd87PzBC8MmWfsNnBFtnx3TmuVoak6fAA9xKZ1V8CO5rZXV047rZ4gDHB0xSKUZb04O70+WLNggfjBuACo7NZ1Pr30FoQbBMfpwprsBqOOR1e6dIfb1uaptq+8Bw5cnQdOenOUVcolnAisgMubDNa0SZ/4JHq8y2yl7p4rnFxy6Yx8AfvIIsql8T1FkgaFxfTSvoo9zGzU5s4pF4DxbqWl9mwzaDIcSzuVTw/LrQ2O2m5cTn8iRPEF8K/54Ef8daI7TPbDcFtXf6vRbLaJSHpVNLsyAbVqA538XzFhPtX0qqBTc3s6kaev8R4RuB2Xi+Y2QJdPl6sCRjBB/QLpb2XQFvW1q+X/Tqb1VKsJXGiM1/bSgNeBR7lZ35lOjP7qZNDT88jvQrMCfxjZqN2sHldIWlnvNcVJuIndma8UC/wN6nQ3kMW2XLdOa5WRNCl2BM4mpTEJVjUzJ5uv1fN5ziAtBUkQYce3J0+X6zjSbPc9+EaHL1iQitpKlz4LFEqvwrYvB4ClpLOJ33+nGhmvbZSIEeOVkNeXp6jLlCscRRrN3xa9yxuS5El3C/gN/pJLbIdu0q4ASyyn/HyNfCJ+R4VNu9VCKrlW2VWHSdptjKb56gSkvpxC/2KCPe/uN9yMlmZm/aEexjwIp5l2wYn5WOb2RJmtq+ZXWtmH5vZr2a2A66v/GnYdyCuSv+kpFka88nqgmxf96qNPFEJwn0ziTq147hQbdAtCKQl6VWtuby8DI5tI9y/cxefFdg5zQ88Jum2YLVU3ThjzaBYt+Hlt/Nl3nqAy7iX24BfGRcPItUDTSkvD5UCqT/xn6yFuDMsjUrau7pYH+j5rYhwT3kK+C8p4c5mNxeq06kuA4qD3sc2gnAHHAV8Hl6vCPQKJfNwbWetwZ7Eq6HqFVA4itR+dHdJk1XaOEeOHPVDnunO0WmErPYieFZ7fdpH0H/D+8QusMhebdAYJsd7Z0fCM2FTdbVksidB0il4Hx145nsBs7KeujkyCII/U5KWh8+HT0BH72DXEbiN3YukWezXa/27SxoDb4/YnZTQDQWOxDMQ9SJ3dUGwTfsR//t8B0zaiBLvcoTbzIYVqagfaGYn1vv8ZcY0Kl6RAPCYmS3VpeO5Xdcz+Pf+GzAjg/kWJw8n4b3fCYYB/wccVa4fVrHGwYWS9qAwIPQGsL9Fdp+kyfHS0jFwUrqgmb3Qpc8hPU1q89i/u0r+JR2NV4cAXG9mGyrWKLiq+WpFm69gkT1AH0Movz8Qvy6ybTL/hws1vhjW3WNmXdJpkDQ9cC/eY53FX3jr0zNdOX7Z87rH/M1h8QtgZovsj0acqzsQrMHuIL3HfYQrlf9Q5/Nk5w1nm9mu9Tx+jhw5SiMn3TlqhmKNh3sRb4/38xXjGTwreINF9mc3jOdCYNuweIBFdlKl7XsTAhl4gXSSfoKZHdTEIbUsJE2Ak+ukD3s+UuuZSviIlFy/gPf01m1iJ2lRvM8y2xP+Ki6a80q9zlMPFNnOzG9mL1bYvDPHXxG4jRKEO7w/O/636YcH2aar94S0zLjGwHsgAR4y63zJsmL1x0tHE5GvvSxKs4Ehq74lnpHKZqG+x4nmxUkbQjjWtnjZ8ISZbb/CydZlFqUtC5L2wTOe4KRroa60NEh6HFg8LI7aHQE/SVPgiusD8YDETGb2MUAZ4l03C7aeAklzAxfjuhMJ3sMzpk+FgOMX+PX1FzBeZ7+7YIl3JzBBWPUF8A6wfFj+GVjCzN7szPErntsD/3cBK4dVJ1lkB9T7PN2B8J2chbtWgP/dFjKz98vv1elzTQR8jAdQhwEzmtkn9T5Pjhw5CpGT7hxVITzclsCJ9noUChuB21hdjme16/5w7WBsM+IPeeHq6NMEdds+AUlz4mRwJDwLu7BZzdY/vQqhRG9eUnI9P2TEpDrC2PzFqozGFMBoTGGRfdmIcSYIwZMI2B8XuQEXLDsez3C2xPUsaQfc7gwgMrMj63jsioQ7s102yPZ/ZrZnvcZQYWzj4v64APea2cqVtq94rFg74W0I4JnoeYINYvE5x8AzlfuR9iiDBx32ZDACTsd7qhP8jWfKTygV8AzZz1eAWcOqnczsvOLtqv4s0kPAMmFxzHoGoyqc8xLS1prTzGzvgvedeN9BSvpGAMtaZI82emzNRriPHI5fN9n7yEm4ENffmW0vw4PnAEuZ2WPUCEmr4X7zBR7ceIDoLtwDHPy5vGgjiF1wLnkLv2/8C8xlkb1V7/M0GpL2xtuMwInwcp3VdKjyfEcBh4XFy8xsq0adK0eOHI6cdOeoCMWakDSrXUqd+QncAuxGi2xIife7BYp1E2lP1/YW2YWVtu9tkHQonu0CD0DMk51g9WZklMTnp1BJXBV2A88kvIBnzTbGbVQAHuUgnmPUNpGe9S2q3kanK5A0L56hmiOz+h086/1sd4yhEoI93f/C4nNmVpd+0BKE+yZg41Il9qEH8QNcM+Jf3OaoM761tYxvIlxfHOAOM1ujU8fx++l7uGc7wBIW2RMdnHsQcCKJV/w4OJ2ctd2m1+OVPp+1e6fweEuQ2mr9CEwfNCJqhqR78ZJ4cD/5XzpznBrONyceNBAe6J2ulPpyIN7fAYkX8V/Aqr2ZeEtaCL93zJxZ/Tp+72inoSJpczxQDnCMmR1WvE0H59sBDx4l2kCP4B7Sv4b3x8TtyRJ70I+AxTry/+4MFCsCBofFx4GlepKomqQ1gVtIn1lbmtnlFXapxznHwVvzxsEDU7OZ2TuNPGeOHH0duZBajnZQrH6KtYxiXYvbiZxMIeH+CTgVmMUiW8Iiu6KZhDsgq5p6QCi77Es4AUgmVjOTTkB6FSQNkDSnpO0knSfpZbzs9xm8V3FzYCbaE+6/8ADRKTjBng4n2VvgpCEh3C8BazIqWSKUtb5pKMLkeH48650QzpmBpyWdGTL4TYOZfY5nswAWkDRhpe2rQS2EO4zhK1Lv2gHAcV0dQxXI9km3y0rXgKNJCfflHRFuADP71Mw2YAJWZCW+ZTcKCfevfMMvrGiRbdgR4Q7He5xCv94javwMWWS/o+4QUzuR9Ld9TDm7o1DplA28jgbcpVjLltq+J0PSWJLOxG26EsI9DP9e5y9FuAOywn1Vt0tkPLjPo4IHt5n9jme9EyL3H+DeQPbqjRNwUg9ekbdpA87REIRA69Wk1/WRjSbcACFAlsyb+uFaIjly5Ggg8kx3jjYo1sR42d72+AOyGI/ivdq3WNR6WVTFehhYOiyuZ5Hd1MzxdDdCv+tL9JIyc0n9cHKczWDPTXvBvmIMwz1cs33Y7xT3rkoaG7+m5wqr3gMWN7PvFWt8IOkVft4iW7Crn6dWBDX6i0kzReC9ursDt9RRzbbWcWWtejY3syu7cKxVcZJdFeHO7DcG8CFpT/5iZvZUZ8dRxTinJlWbv97MNqz5GLHmwi3khAeKZqjG4jD4bW+CtxpM3vbGn3ge8RXA+BL/Tq6u5roIFQvv4b+lf4E5OpPlknQzsHZYnDwERBqCEJy5Nyx+hvdyl30OKdYKuJVUFv8A61hkd5fYpUch9ACvDZxBYe//C3h2u8M2L0lv4iGcEcAEHVU8hPaE84CtM6srenCHHvyngKnCqieBFc3sr47GVwsUayXgnrD4HTCjRY2tvOgqwu/wOWDSsOpqYLPuurdLGh0PViT30XnN7OXuOHeOHH0Reaa7j0OxpFjLKtaNuADK8RQS7u/xfrAZLbKlLbJrWpFwB2Sz3QeFPvQ+AzN7g9RGpx9waXfaKnUFkkaRNLekrSSdJulRvKLiPVwBf08841xMuA3v57sU2BUXSRvTzOY3s13M7BIze7ME4R6I933OFVZ9AaxgZt8DWGQ/4krPAPM0w3YoTJoXAfbFM/Xgk+ubgFvDhK0ZyBKWTqseS1oXL6msiXADhN7hwzOrTg4kpFHIZnFrVpUP96LTyGazqiPcC+CE5QpSwj2Mf/g/zuUMXmZYMMeaHP+dPC2pQw/xULFwfFgcAJzayb9ft2S6g7hcViDzkCraZ54gtUZKKrFGAW5VrB5tLyX3cb4N/80khPsv/F6xSA2iZUm2ux+wVAfnHCOcMyHcBuxlZvtXUq03sy+AFfC5BMBiwPWBwNcNFtm9+N8DYCLSdquWRKhauouUcD9Ffa3BOoSZ/Yk7aCRo6b9Zjhw9HTnp7qNQrLEUa3fc+uhBYF0KSygfBDYAprDIDrCo/gqaDcD9uMgQuHjW0uU37bUoLjOPmjiWkpA0nqSlJe0t6TJJrwF/4FnAS3CCvSQwdondPwauw8WllgTGMrPZzGxrMzvbzF7oSHQsTPauJ1Vd/gFY3sz+V7Tp0+H/ARR6HncbzOxfMzsFdwm4K/PWGsA7kvYKhKQ78QyuHA6wUmfOL2lT/HtMJt7XUSXhzuAS/P4FbvW2Xq3jqAFdLS9fF79ewTP0/1dpY8WaTLEuw7Ng2b75O4BZ7Vjb036zPXDXgjsz7y8EPCfpUnXsv3syaX/+inQugNJd5eVbALOH1y/i5cwVEVqekuqHgaTBopGA6xWrxymah/aavfDrfvXMW3fh2ganmLUX5auArJXa8uU2kjQxXhWUCAgOBTa0Kj24zew93AYrcQBYFbgkVDPVE3vjNSAAOyvWvJU2bhbk1mDXkV7THwFrNUmH5XzS+8DKkhZrwhhy5OgTyMvL+xgUa1Y8I7g57teaxbd4OetFFtlHxfv2BCjWRqT9ig9YZCs0czzNQKuUmYcJ1SA8m5z9V22G9kv8cyQl4i+W6+GscUyXAZuFVX8AS5eyvlKsbXArL4BDLLLu6B0ui5CJXA8nbJNk3noJ2KE7ywIlXU8i7FVjabek7fCJXpJZvRTYrjPWVZJWIQ1GfIwTj5qV3kPgYKTwb0DmdfJvFuDWsPntuO3WSEX7lA4+jMEo7MGpjBwsvZ7lBO5tC4wVZpdHZyTWYTUGsTb9Mw4RQ/iSF7mMh3i95H4uvLcF2fJzz/LegpfcDiuxD8CCuLc3wDd4iXqp7+HfcIzk/+T1/qRkfU1clLB4m4LXtX7PkkbDhfOSIELVStuKdTBwbFjcBf+8W4ZlA7azyC6uZTzNQuj9PR+YJ7P6a/z7u6kzGdIgdvYTfv1+YGYzlNim2IP7F5wgdkbtfKlwrOTaPgPYs57ZXcXaH+/9B3geWNii7vGPrwbhPn4mfj1CA63BahhT9ln3BLBks9qXcuTozchJdx+AYo2ET4h2pXQJ2WO4P+StFtWUaWo5KNYAvCQ5mSDMa1Hf61EqUjN/G+/ValgUPZSxz0ohuZ4TGLOK3YfjY3wV78V+FXjN6uy/HCY7p+M90eCkZGUze6Tk9rFmwK8lgHst6rxNVD0RetGPA3YiJVIj8M92RDfZNm2FZ5oBjjWzQzPv9ceFqwaG/0fLLG9EOtkEr6i5mtJEt/hfuW2WIvWo/hAnjx3tU/yvcaXpi5MaJ32IF4GXwsx4Ee64mXVDcE3oF/FvuHfAKCTjJcl55vXEpIG67/Hsf0Vi3/Z6ViZkfbYH4Fte5zwuYmvWY8q2Khd4j/O4hpvw8uwhJf4f0pmAUL0QyrqPwsl1khk2XDn8kKx4WSePn/VaH2SWivGptAf3Smadt+QKSt03kQapBptZXGGX2o7v851X8UAZwE4Wdd4Wr94IlQqnhsVheJVVzQGMeiJk3t8CkqDLSmZWrIeQI0eOLiIn3b0YijUJLoq2E4VCK+AlWFcAZ3W3r3ajoVg7A2eHxestql30qKcjlFA/S5oVOd7MDq7TsSfECfVcmX8zUS7TV4jfKCTXrwJvd0dZnVRgKzMCWNfMbi27vffhfoVnlf8Axi3lp9wsSFoYz3zNlln9P2BXM7uzaFvh5LIcGS63XO69cUhV3Yfi1lPJeyPX9YP2ZIyJh3hGxq+4c0g7WxNMjBfeTpNZNwIn2o+QdiPnqB0CDsCvzCF4/tPwYvqFM9vdhzdNlMdQKpDyCu9V+3/b6yzBl7Q6HhDPVge9iVe2VB5xlZB0BKkWyHZmdlFYX+zB/SYepPyiDufcEq9wSbC7mZ3Z1eO2HT/Wkng5PHhmfuZqNBQajWZYg1ULSRuStm28hCvf5wQhR446IifdvQyBKCyKZ7XXpX2f3Xs4Ib3Moq5FyFsVQfTqU1xMZQQuAvdhUwfVBHS1zDyUYv+H9tnrycvuVIj/kRLr5N+nzXiQS9qdwj7arc3s0g73i3UNnp0FWNCixpTph+zwmHgf+1jhdTVkeHRgXry8ONsf+Rvedz1KZtu+ZqM3nMJsakf/irOv2X/j4n2o4NoDD5XYbzhQeG1vz8ZMjveVfsITXNZWog4TMjqrszJTshDKZNp/4gMe4Fbe4et2xytER+9NCqxDmr1K1j+F9zdnKyI2Ig2iPE3aogNOEJKKgWzlwAC8DzgJ7N2Ol8oWb9OV1yPT1SqE9Ukt1s7Hw2jg1QeLZ7Z7GHd4bj6GAn/jnz0rhDkCr5V4Cyfolcj/n/jv/zfSe8FvwB8lRCUXJtWvuNbMNpa0Bd5qltwzHsU9uH+p14eUtDdu4ZhgUzO7um7Hd02ELcJi04PvoT3gcfxeDHCUmXXFrq+uCM/7l/FnPHhQ+uYmDilHjl6HnHT3EijW6LitzK6kN80EI3ABnjOBhyzq/V+6Yh1Cqsp5nkW2UzPH0yxUW2Ye+iZno5Bcz4mTuo4wjLQ8PPn3upn91JWx1wtBtCtb1LuPmZ1abvuCfWPthOcnAQ6wyE4qeN8zyKPhRHnszP9jl1hX6f9ifYWehp9wQbq/aE8IZqUwG/8AhaS1s0Q4+29CvOx4VJy0zGRmn9Trw4Ve1KQN4QQzO6jDfWItRJo//QmY3iL7SbFGxu/TEYVigR8D+wC31+seHa7PNfEe9Gkzb/2KV32cZWbDJE2E902PhRPz+arRCJB0Ei5qCLCEWce+4zWMfSY8u9ofDxDMQWVSX5rAb8TqzBRaGj7keq7k7rZtNmR1ZiZtG3mDl7mJNygMbGX/L17XE/EHhYT8N1x0dAD+m30crwVI8Bju+f1DZvs/KimWVwtJxwCHhMV/gTXN6mPnplgT4B7hSWn86hYVVgB1F0pYg12DBxlaai4WLByTv9E7wOzNbK3IkaO3ISfdPRyKNR3eI7k1XvKZxQ/ABTjp/Iw+BMUaB8+0jon37g5qhfKy7kapMnPcumguCgn2jFTnZvAL7bPX75jZ0LoMuM4Ik4jbSDM2x5jZYeG9kemIEI/NIKZne/4BfuE7Pue9Etu1egZ5CPAJXgJeTIhLLVf73hz4tQVws5mtmz1pyJycQWEP917VKh7XCknHAkkLxbVmtnEdj70cqdJz2zVUdnv31n4Gt7AD2M0iO0uxVsb7OWfMbP4H3rN7ukW1i8BVA0mjAHsBh1EY4HkXD0LdI2kfnJyDeykv0REpKPqbL2tmD9dxzLfhKv0Ah5tZp+yMFGtaXB0a4BGLbJmi9/fFldwTnA7s3VHgIwQ0RqE8Qa/1/4nwPuTs92N4EGkUWguGK5EXZ9JLLZd7/Rt+7Z8D7BiOOwS3bnyyHoNUrM3wNjrwfvRZLLLfK+xSdwSxuifx+yV4pclyTVIqr4hwTT9F2nyxhZldUWGXHDly1ICcdPdAKFZ/3LpjNwoj0gmew/vAbmhhT+2GQ3FBFuY4i+yQStv3NoSS5elxa5njqd0i8BMKyfVrwP9aITofMvPj4YGmctnlmYG1SEnx93jQIHm/2R7myaT11xL//4GXiHaGEI+Bd69umznXvzihOtLM/qIOCNfXN3gm6XdggiT4Et67gEJP353M7Px6nLvMeMbCy28TUbWFzOy5Oh17ZVLLqQ6FnxRrcyDp1XwL2BD3mc6K8Rne13pIdwUEJU2KVwBtXfTW3bhy+U2k5egbmdl1HRwvxrOgUEfxJUlL4BlW8ILw6bty3SrWx3jX/FBcm+Gvovd3wZ+ZCc4DdukO1etwL4twj+1sAO9C4EAz+6kTBH8M/B6X/Bu7zHKzK2xG4PeORG8C/F71EB40Lybrv+JVIz8m/yq5FYR2u3tI50lnWmS7l9u+3ggCZbeRKvx/hLd5FSs7tAyKqno+wauGWjKoniNHT0NOunsQFGt8YBs8czSo6O1/8JKlsyxqb3/UF6FYk+EPjZHxh/VUFtlvzR1VYyBpHLyMd3bSDPYcpCI4lTAUL+N8lZRcv17P/r1yCJPJsYDxw78JqnzdTML8D6WJckf/F5DqRpftBeJyHi5yl+ATYOc6kqMrSO3XljGzR0J1xeWkvfAjgK26I2MiFZCnqrK1VR53DXzyDHComR1bdttYY+DWWUkp6U14iXfW6/tpYM9m3aslzYdndBfJrP4Xb0NaOyx/jk+4y5JdSYcDR4bF1YsF/Do5tn54BcX8YdW2Zl2z9VKs84AdwuJKFrW//hVra9w2KekhvxzYtpHiiZJWxDO9WRm9d4EdzazhHeYhODYuLpi2dOatS/FrtBJhzy5X04bUKPxJhoRn/v0A/MjEiGU5gdEZhYEYf7ECF/JQo4PH4dl2Bt5KAt4asXDwLG9pSHoAWC4s7mxm5zZzPDly9BbkpLsHQLHmw2/cG9GebHyKP7Qvtqi+Fku9AYp1IWnGr11Pbk9DINez4AR71szrYnX6jpBUQ7wKvGvWdau4zASuFgI9PoVkpJEYQe1E+TfWYgWm4iBGAfpzoB1nJ5Y6eCsilBUfCBxKoar4NcDeZvZtF4+/MW75BV6iexiugLtWWPcvsImZ3dCV89QwnpHwAFKSrV27kkJ9DcddByfP4NnHsteA4oI+1aEU/t2/wL2tr2u2tkYgBRvhVRFTZN7KjrliVl/SQbh9HdTvb529pt4A5u5qgEqx1seJJcB/LbL9ymy3MV6OnGScrwc2q7eVpqSJ8TaDbAvEUFx/48TOeM13chyj49d1tmJuGDBWLeXPIaM7BtUR9ErvdVef/L8UZcxJSHr5fz/V8pyUtCfeygX+N13BzB6tz/Abi/9n76zDo7i+N/45CVAoUKCUFmpQp07dS6m7u7u7/2rDfOvubtTdS12oUhcqlNIipaUUdwvJ+f1x7mRmN7ub9d0k+z5PnmRnZ+7cJLMz95zznvcVkQ2xNQIY02SFcqTDV1BBU0Ml6C5TiC9tMd3VU4CNEuzyFhY0valeRegiGcSXVTBBEAH+BZYrVN9kPuG8mOMD60yD6z+IteeaC/UiQnUY/fbrJOdvQ2xgHB8oJwqiu5Cr0nBq1NBwgTSV2EBZsCAzoBh/j32O/gNmZVPdEF9WxwI5gNfU091T7V+OEJFVgHswT+sAUzFDpQezFUUSka7AeKx1YSgwGjPAAgsi9slH9TPDOe0B9Srhw4HVc00qxdnpJBXiE1+Wwxwi4l0jAsOq6+KpzaWGC7zOwz438UndecDKqvpXkmPPw34vgH1V9YVE+2Uwl4WwSm8vtykvlHXHEpuA3R9+VE/7pNh3b+x/HfwPXwX2z8dzw1Xxj8H+Zp0jb32ItV/8nus5MpjLophoVtC/W0uYbMhrf34Gc+qGtRWs6jaNwDQDqrHAvDPWVtSVhs+jRSl8Anc66QXoq2FJleB5eKSqPlLgueUVcZoKp6jqXan2r6CCChpHJeguM4gvy2K+2scRqm4GmAo8DNytng4v8tSaLMSXFzDrHIDj1NMHSjmfKFxwHQ2qgyA7XVsusIz9L+4roIkPUTXBGNczGATGpwNHuuMmYJWcRNXpjtn/VmlhNokXLxOT/DwJmJEqaHYB4MfY3w+sStZXVafkMlHXFzge+9tMA7o2xUSXq2wegfV2Lxp561OMzvprluN+RixNGSzI3ENV301wSEHhfs9BwJZu06mqemfyI9IaM6qAf7qq3t5gHwu4P6HhZ/dp4AL1Egeu5QIRWRa4lrAtIMAYjKY/KsEx52K96pCfoDsqavauqm6fy3gxY/vyDTj7NuiuXnKWh/iyM/AioYDZO8BeuSRMRGQ1rN1j88jmyVgv9yPF1MoQkSUxd/LAVWA6VpUN+vOvVi2NBoqb22eEiZfBwHaqOquR4+JblWK/OtGbpdmPOQizUcbzL3VFocbXYknfVEH6JLfPOOC/YjEdUsFZnAXtL38DK5bDvCqooCmjEnSXAdyifhtMGG03Ggpe/YhVtZ9UL/WDp4KGED+GKjUcWLXYQVOC4Dr4Odvg+jescj8Fo4L2ALon+Sr0omIajQfMMa9VdU4+J+AUYt8jVIseAWyuqv/mZXxfnsd87wHWVU+/z8e4pYCrJt0IHBbZXIMFXFdmSiMUkf8Bl0Y2zQR2zqd9VKYQkQ2AwFN9IrZgnJbDeNGg+zRVvaP+Pevh/j+sWhytcP8AnKZefpSYiwUR2QLrRY1aT87HgutrVHVmZN+8Bd2u8vonVs1UjFb+Y7bjNRjfl2uwaj7AwerpU43svw1W5Q4oz4OA3TNVvxaRtlh7xwXEXh+PAucWW1RLRFbEkghBH/l4jF7+Lxb0AXyjqhskOLwocHP8DFN0B0sQ7J6roFfcNfAJsBX9aU1qVleir0UpLKtrKva/aOxrYiG1QUTkNWBX9/JEVb23UOeqoIKWgErQXUKIL52wytPJxFrIgPUcPY95a39e6v6/pg7x5QNCoZh91cutIpP0PGFwHV+9ziS4noYpt47HlF3nY4mYzoSBdDwLIh+oI/RbTrf6nFGfWyHgKKkDscQV2GJkM1Udkbdz+HIqFogAnK1eej7f5QwR2QajnK8Y2TwcW1ylRS1NwC6owZIdXyU/qjgQkScJe2avUdX/S7V/I2M1CLqdLdihmDNAj7hDHgaOLYb6dSHg9BkexJ5PUYwFLgSeUNW6PAfdNwFnuZcDVDVeYT0nuCD6PffyIfX0mFT7u2M2x1pyAubPYGAn9dJL4CT5jP2BfcbeT3fu+YKIrI0FsEu4TaOxKvJw9/6PmACnYm4Ek4s9xwAi0gejmi/iNj2DeVtnHWSKL+0wBtQKbtMJ6mXuqOA+H52JDcSXw1Tou7rdJgC/EkuHz7f1W507TzoB+rRM2RRxycu/MBeBipJ5BRVkiUrQXQKIL2tgvdqH0bAKORajoN2vXn6qdBWA+LID1gcPRpnaMJdEhrMnSlS5XjrVcXGYhymv1mK9aB3Jb0/aFOxhOx4LlqMB86aElds/MMrjhGx7e0sFt/h5hvB3mYpRYX/K63l8WRMY4l6+op7umc/xSwURaYdV4c6nYRXuHNXk4oxODOo9QooqmG7AovlmMmQDEemF9Ve3wea1SrLe5DTGigm66c83mPr3hgl2/x5Yv6kG3AHcZ+t7zBEhHl8CZwBbkIegW0SWx9g7rbHWhJVV9e9sxkp6DtNJmYL1rY8BeqbzDBBfNsAC1S5u07fADurppKTHiCyGsUkOj2zOmk2SD4jI5lgPdye36RdgB1X9J7LPjcDZ7uV+qvp8cWcZC8e6eIdQa+BurL84+2d3bPJlGsZ8y2mtJSIdsL789d2mn4Etog4gjv6+MIkr54thVf0oQ60H+RWWm0cYgP9HigA9ev8WkTcIrQ6PUy2f9rwKKmhqqATdRYL40hpT9D2VsNcwikEYhfyVfCulVlBP4f8Os9IC2Ea9xqt5ccF1NMjOJLjOJ+YR0gCDr/jXjfaFOZXnL4B13aaS9fBlC7eIuZ9QnX42sK2qDs77uayqOR5bIE0BFmvqQVUUIrI6luzbLLJ5EtZv+mj8IldElsa8dAOV8DmE9nQ7qepblAFE5HogUKp+TFUPT7V/inEs6O4IHMzX9CCeehtV/N6iqVHKk0FE+mLPJrB7T3yl7lvCPulcgu5ngP3dy6tU9eJsxmn0PL68A2znXq6iXnrCZeLL2ligFjCMfgK2i+8Lj+gm3EBY8QSjSh+frW5CrhCRnTHmXPAZ/RJrAZkct1/Uj/5eVT2xeLNMDBHZBbPrC0TeLlfVy1Ic0viYvjxMqG3ygnq6bw7za+3mFwSmf2PWYDknjVwwn6hlbIkE2/KZsJ9OuJaoIWSRTcRsa/9x741XLZylXgUVNDdUgu4CQ3zpgfmDHk9D5elZWEXpLvX05/hjK8gvxJcDMaskgHfVC0V6XHC9KpapXg+r3i1P7MKpUFAsoIsPnBMF09PzJbgjImtii+ZG1czLESJyLVahBVsY7JYPpeOk5/PlRUIP4z7q5a/ftBzglJWPxZSVO0XeilFWFpHlsIA76Akdg1Xwgj7n21X19KJMuhGISBeMyREIx62nqt9lPE4HOZL1eJjNiTUAC/UVAqbF0+rpQTQjiMizmAMAwHOECch4HKKqTybY3tj4G2EJQDCq7IqqOj2buTZ6Ll/Ox65VgFPVS19gT3xZDbvuu7tNw7Dk7T8AIrIyRiWP+l1PJUeHgFzhEkYDCIOyd4G9o735kX3bY0nF1sAIVV0hfp9SII5pAnCmqt6a9XimZj+U0OViL/Uyt7tzSZYHgaAVYirWXvNLtnPLBu7e3YXkui7RQL1bkmGygWKBeKKKeVBN/xcYEwi7VlBBS0Yl6C4AXFV1c4xCvg8NM5DDsKr2o+n2hlWQG0RE6EIPDuYbZtCDScBHDGVmvQVJvnutIDZbnCqQnliqbLGIXAJc7l7+CqzbFBRKRWIWzwocpKrPFPScvpyOUYoBzlQv+0VfOUNEumN2N1EV63nAlZii81uETI8RwNbYQn0Sdq8bgQVOZfFwEZEzsd8HLIGwTbpzc/fyfZjH3SwUo6MwGVN6HoQJprXCqv29y12lPFM4mv5QjOJbgwmsbQP8j5ByDZY4PAV4Ie2/rwUtHxMqehfUmkh8WQdjPAG8rJ7ulWr/BMevhAXey7hNI5jATtzJgVibRjQl8zRwlqqOo0QQidGiAEuaHNYIC2oQ0Ne9XCGf2hi5QEROA26LbDpCVR/NerzYJPxYYLVM12NxIpLzsf74j7OdUzHgKvPdSB2gB1/5dDGZhiVo/3bfx8S/Vi0vO8UKKsg3KkF3HiG+tAcOwRYea8W9XYcpod4BfFARRssf3MJtUSwQWAarWK+JidcshVWrFyY/aqM1JM7qxgfT/zWFB0hTpJmLyHFAVPymKKqqjmL6g3v5knq6d4rdmzwc1fQuQuseiPXy/Q2j8weVvqhY4SpaRM/hVBDznP+VUDxpV1Ud2OhxvvTBkixhO1Ad8Bcf0Yu91dPJ4stAYGf3rq+e9s/j1MsGccHF66q6mxPRe5lYCyww8aszVfWHNMbdE3jJvfwdWKOQwoxxbSLTMfu/jBKe4ksvLPBeHoAZLOBhWhEStUcCJ5eyxcI9Ey8D+kc234slNVIKkYnIxcAV7uUJqpkLjRUKItIfEysDuxftpaqvZTWWJdReJ/z83q2enpzBXE7AmA1gid8DVPW5bOZSrnB2o0GF/G5CR4NB2OcnGqC3STBEpphCkoDcff1TDnohFVSQLSpBdx7gst8nYxSjTnFvTwAeAO5pbhWQYsEpgi/jvoLAenlgJffzYsSKQGWDBZhS+Hjs5j4co6XGB9dTyqWCly80JZq5iOyLCacFtnoXq+pVRTm3LdgnYtW9ScDizamvOxEc3fQyrLe7OvLWZOw6GR7ZN6pkfZaq3lKseTYGd90EC+KhwFrJ2CXiSzcs6DiOaKLuT6zGP8F8usWP6X/9G+sRLvtEWzZw18EwQheGnVT1rThf7SgU01u4JJkllkv4/YLdx8ECqJfzOvFE5/Vj+sc3UU+/SLV/wjH2ktVZgc/o6J73M4BHqWUCNwJ+KROujmp8K6YfE+Aq7H/RuHBcLN3/OVXdP9X+xYRLJtxG+LvNxcTgsqouiy/LYgm5QNB2c/X0szTmsTuWLAqeQ2eo6m0pDmnycKJ2wd/5D2DV4B7q/i+dadhv3gNrq4yu33INzieSPCj/GwvMy56tV0HLRCXozhIuS7o9puC6U4JdvsAo5M+pV7kBJINbzC0T9xUE1su6r3z4TCsmtDWRnsBa9GRRoJpXeIhDVFu2/3kczfwXrPe1rK5bEdkOswYLEiw3YT63RbuJiS8vA3u4l2upl1+V9HKEiGyCqTfHUw3HA2cCT6uqishq2LUD8J6qbkeZwC0KPwM2cZsaVPDEl2pMe+MqbAEZ4A8+52XeqRdkO53+3IOJaQVWj436Pjd1iMjBwBPu5W8Ym+t0wqD7WqydKmqPNQW4CLg/vsIqIqcQ6gB8AvQtxmdZfDkWSwgAXKqeXpFq/5hj7To6CLiZ9izO4YTmW7VMoZqt1Wu8wl8ouETGAODgyOZzVPWmDMaoxpKKnbDkWrdycrVwSYXHCe0ApwNbqer3WY3nyxnALe7lUGCdVGs2dz98n1CU7npVPT/Z/s0JcWymw1T18VT7JzheMGp7/Fov+vNS5F5E+Y8UNHZgbCEZNRVUkAyVoDtDOAr5YdhiY9W4t+diPUJ3qqffFntu5QYRaUvsTTVRYN0l6QDZYSqmrPknZtvxDfAj8Fd9VtaXzpjnZEesV7WXeqXruysHJKCZF0xBOBu46sv7hAmYAcDRxWYdiC9nYcE+wGnq6R2p9m/qEJGtMApm8Hf/E7O2iQbgb2NMn5HuqyfWhrFoIrGmUkFENsUCb7BF2UqBuI/4siFGpV8vcsgMrG/5dvqzD2HAeTr9qSbsE/8MUyxv1g9Tt2D+FLMbBEu4tCIMuvcDXsOejZcSe418i1Guv3JjdcKqZUGf/EZaJG93Rw8f6V5+rJ72TbF7eJzICtg1Ui/AycLM5CQm05Fl3ZapmJ1Y0X3qHRX4OUK6dC1wrKoOyGKsqGjk+qrltZ5JoBg+ARMwy7ilxSXbPie0/0vaJiIiq2Cf90Bg9Uks+CybpEQhEedmMAxYvbF2hSzOUYWlsuLXjtHXSxLLvMoUijEXU1HZx1WU2SvIN8o66HZ2CX2whdAymNjVfEz04lvgu0KpnDaYiy/LYL3ax9MwUByNVbUfSuXd2Zzg+iSjtKFEQXU+VTKjmIyJNf2KBda/Y3TwEZqm/6n4MVZC16vXMjLVqSAia2FJitbYgm1jVf2mtLMisLP6hPBz9zLmIVv0B2KcEFNOVjPlDhHZAftbBx65HwC7Y1Xg24BoT/scwMcUzU9w2/ZU1VeKMdd0ISLPAcH/7HL6cxtW2T6WWM2HR4ELgmRcTJV3cS7iZC7AKoEKbNBSkqwisj4QtJ5MwxJQvntd7+vsxPiuJdanWrFWq4swL+j/c9ufUdWoaF/BIb4MxyrylhzykieHXIB3DtZL3Dby1gvAGfRnFtZmELAoZgA7F9M2TkQ6YwmPoL9+HtZjnNXnT0ROwhIMABeq6rWp9i8FXJLhHUKbw9FY4J2xVZf4sha2pmyFXRN91Iu1dxORHlhw3stteh+zXZuf1S/QRCEiHxHqXGTlWJCHOVRj9PVEAXnwugch/T8b1OKU10lcNf8L0+5pEQmXcoJzG1oXiw2XxFoW5mH/m2+BH8op4R9F2QXdItIK2BXkVNB+QBVU1VVXd6gVaYVqLbW1M6uh1n2Y5HPQ24EX833zcxTyjbGM/j40zKx9gtGSXs1UjKXc4YLqZbHe6eXc9+WxKtYyWCYyH8JkyTAVy6QGAfXv7uuPfFhPOCu3kVgiZzZW7U7Ye9iSICKXYtU9KAOauVNO/ozQbu9DbKGTVnIl7/PxY6iXE7G+7vK6ieYBIrIH8Cxh/90bmA/znMg+u2PJxqhn/SjCRel9qnoCZQQRWRH4FaE16zGfnZlNVQyV/CfgFPX0k7jjwqD7aD5l2frg5mH19OgiTL1sICIPEVokDSYMNvePF5JyfaB3YsKWAaZizInWWBK9t6qOpIgQX+4GAg/qXdTTNxLuZ1Ti+zALyQBjMEGyegEv8aUDFvRu5TbNBnZXT9/P89QTzbE7xjYJxFtnALur6qAcxlwJe94CvK+q2+Y0yQLBJRs+IvzdfwW2VM28+CG+XIklhMCC6y0CzQ63yP8IKwKBsee2LFbRp5wgIltjCQcwOv6a+a525wMuWdaD5DT2fKxj52LPvBHua2Tk+8iWeH0UCi4m2RvkNFDHtqp2sWE1qgtcbFhXBdSBfAB6BzCwnBgLZRV020Kv6i6oW7J16yVq27VbvbpNmx60arUoltgyqNaxYMFkamr+Y86cX2vnz/+nGmQi6FnAE7lSTsWXNlg15Exgg7i3azAK+a3qZe73Wi5wVMHFaRhUBz8vTW5ZwnQwm9iAuv7nbB6amUJ8uZ1QkOUa9fT/Uu3fElBONHMRWQxb/ARCS98AW+cj6ZILxJdXgd3cyzXUK64na6EhIgdgPZOB1eELwMGJkpoi0hFL0pxOw/vFP8Ay5SY8KKvKU2zBgfWSYIbpmGDcnYkSqPVB9xLAiSiCADOBlVpaa4oL8oYDHbDqdbBobRB0u/1bYSyxy2moC/CEqh5awOkmhPiyN3ZdA9ysnp4d874Fc1dhgXnw+9VhDI9LE1VRxJeFMUu9HdymecDeyQL6fEBElsN8twNl/onAjrnSwd36YBSWeJ8HdC5VorMxuAr0pwRq8vAl5qqQUaVLfGkLDCF83pysnt7tFvsDgSDxMBrYVFXH5jz5JogENn8HaoHtOguFJIzN+AB98RxOMYnEAfkIzCKt0lfeCNz1dgjILaBd27RZqrZdu9WqW7fuTqtWXbBuBINqLQsWTGL+/HHMmfNLbU3Nf9VQNRbqTi4X1l1ZBN0isijmJXnwQgv1quvYcdOq1q3Tv85raiYxc+aXOnfu7wLyGugJqvpvxvPwZTGMGnkyYWUtwHjMMuGeprLIciJly5E4qF4Os9EqNGqwPtBEwfXYUi7IxZel3dzaYAvoXi2lPSAVyoFm7qiDHwAbuU3DMOrgxGLOIxHEj1FsPkW9wvkKFxsicgTwEGEA/QRwZGOZYkc7vg9YJ+6tc4CbyyHwFl+6AleiHO+CZsNMXqcDx6uX/JlRH3Qfgd05DReqV36022JARM7H6ONRJAy6I8f0wATMdolsVszK6mJVnZzwwAJAfOmCBahVwM/q6ZpujoIl3G/D6KsBvgOObyyYFV8WwtwVArHFGuAA9fSl5EdlBxFZA6NX93Cb/gK2V9VheRo/ymjYSlU/yse4hYCILI8F3sHf4l3MGjAj9qP4shXGpgKYQQ2rciXXAEFiaDKwmar+lvOkmzCcqOk77uUvmBtEs6RZO22ipWgYkPckXF+3TTpActRirJlEAflIYEI5PDfTgYgsjn3mFmBK/nlprbFnhtwLulvbtitrhw4bSevWXRs/0KGmZjwzZnxeN2/eqCpMf+G0Yj5nEqHkQbeILAtVH4q06rnIIv2q27XrjT33MsfcuX8wdep7C1TnTQTtl+6NUXxZA1MhP5T4D4/yA0MYzEA6MZ87VHVwVpMrAFxfy9LEBtLR4HqJ5EfnFYplfxMF1qPLidoRD/HlLuAk9/IK9fTSVPu3FJSSZu4qYy8SVpP/BTZR1dHFOH9jEF/Ww5ISYO4EZWOpkwvi+jjB+m9PTJc66P5vpwHXEGsL8zb2sBue8MACw1m9He3mFT6xx2P1q9G8rao7phxD5CBW5UkOqN/0J7B6S3WmEJGFsPvCCpHNjQXdgi3UE1GVJwEXAA8Xa/EuvnxJKJ7Vg/4sggXbO0R2m4WJwt2e7nNMfGmNMUWC+0ItcFg+1e0d7X0goc7Fb1jAPSaP5zgCE6wE8FT1fyl2LznErC8/JnQeeAw4ItPARXx5ADgGgJcZzg/1le+5WAW9UUux5o4EbhD1eg4tDe5v0Z3k6/ClyY7CPoswCE9EXS8be0oRORu40b2sA67GrBOzruSLSG+QD0UWWqxz521btW27YuMHJYCqMmfOb0yf/kGtau1oqOunWjr75pIG3SKyJFQNrqpqv2TXrvu0atWqc85j1tbOZNKkFxbU1k6dCrqxqv6Z8Ny2ENsFC7a3iXtbgVf4k6d4jCMJFTKHqOraOU8yA4hIFxpWqYOfe5K7tUK6UIwuOpIwsA6C6z/LlXrWGJxP5x/Y33E6Vu2eUtpZlR6OZv4lYeWyKDRz9wC7F/NIBvufbKmqPxb63OnC9XVPBhbBQrfuTb2vO+6hCcY8OjObAEhEtsT6H6OYj3l4X1XMxYJLkNxJyJgAmEkN/+NqTqGOnm7bjqr6dtJx2svhHMcjEQnNPdUrD7paqeB6+qN/g0NV9YkU++8IvOlejsSYY5dhNPUAX2Iq5wVv3Yrp4f2YV/mAHYlNFr0GnJrNAs3dIx4iFJJT4Fj19KGcJg2BwOGLhEy1rzGdi7yygJyeRtBr/6Gqbp3P8QsBEdkMeI+weHK1ql6U4pCGYxgLYihfskT91WqBxD5aBB/5poK4z/NPQJ/mWu3OBS5BGegjxbNNlyfWnjIT/Edy6vo/xeyzF5H7MTHSKL7BngkZM29Me0UGV1d37ty16z6tqqs7NH5QI1iwYCqTJr2woK5u1lio2zgbNnQ+ULKg26oi8kVVVbu1F1vswFbV1Yvkbeza2tlMmvTMgtraGaOgbs1oQCi+dASOxHoQ41Mn04EHmc1dXMdOWLYm6hE9D2iXT8qH+0D2JHlvdad8nSsNjCe0/RkV9/NfpRTUKiTEl/sIg7ykdiEtDaWgmcdV2GuwYOiDQp4zG4gvrxPSZFdVr+nSDSXWox2MNvx/udznRGQYsHKCt0ZjWhmvFJI6J74sClxBbE8uGMXsPPV0rIgc5F6DLRrXSbZQkcPkKVbEFLYn8zuL0rupJ1pyhUuQ/Ub4f35aVQ9Ksm818AOhINlBqvq0Jd65gdBzGSxAvRu4RLVwCVDxpB9V2L3lB0yn3zAGu0ZfyukzYIn9uwjV/AFOVU/vzHpM01t4jDDZ/j6wV6F0LkRkNBYwzMX6ust+DSAie2H9+sHn/hTVzFqAZAO5nm/q3U1gYc7RWel7nbcEuM//F4Rskb1V899G0dzhCmvxgXjwvRfZFdZqsGdtMur6lDzHMVFF+yjmYE4V96Z7PqPzV/1UXd2xV9euB7Sqrs5fF+yCBdOZNOnpBXV1c350RdniO+CUMOi+ALi6a9cDpE2bHo3unylqaiYxceITdVB3g6peIL4sh1Efj8EqVFH8gdHKBtCfZTBa5SYkRrdMMsoR6kmyoHopsqOeZIMpJA6oRwKjyomuUkw439bhmHDUNKCnejqtpJMqExSTZi4iRwMPRjYdrJo/SmY+Ib6cB1znXp6knt5TyvlkA3dvupLQugms8nhFzmKUIjdjgQvAS8CuxC4e3gBOT8ZEyvq8FugciSUOFou89SvWfz8oMscqrLK6vtt0tKo+nGDMJallBNUsRB3wHNforxXRRQARuRYI7BbnASuo6j8J9jsGe66CVWY3il5jItIPYySsGjlsohv7kXxX0ERkRVpxBxewQz3H6SZqsATAlao6Ky/nMQeUmzFGXYBz1dMbkxySas4nYkF8sF54EbtHFiwQFpFHgcPcyy3y1atZaIjIKcAd7qViVeq0AkIR2Ryrli8EwBbANtynXnk5MZQDRGRnrM0BLHW1blPpQ24KcMnKJUkckC9HqGGQKaaRnLo+KtN7ioiMI3U760DgGFX9L42xroOqcxZb7JCqTPq308X8+WOZNOlZxawQr2v0gDyjJEG3iKwM/NK+/XqtFllki4KdZ+bMr5kx4zPlMAaxAn1pqK77Pmb59Qb9aYUtPi8mdWZpHVX9IbrB9TL2xDL+K2EV9CC47gW0y/mXSQ9BD0jCarVqJZBMBvHlQazvE+BS9fSKUs6nXFAsmrl7eL9KaMt3rmrmC9NiQXzZAPjKvXxavcQVvnKFC7jjg4HzVPWGJIdkOn5UaOcRjDV0B7H9vPOw4PgajViRZX1O81C/k9iE6SygP+Y20aC/TET6AoPcy7HAyvEBl/jyCAFN+CvgDc5Q1dtynW9zQIK2hMdV9bC4fTpgrUjBArGvqn6cYKw2GAOtP7EMs8EY5fyHPMx3YeBCrH+8DYcS8t0Gs7O+pW8mPTjbc/opkltpsCXcZ/UijLkR4EHghEJTSOOSJZeo6pWFPF8+ISJXY/9rsEr9Nqr6eSPHrIYJslkjyZosYG9auTTHVuqVr5hcKeCuza8IE5d7apmoRLcEuPtZL5JXyrPhZSvG9hlOqM0U/DwyXpxQRDphNpCNYQIWeL+WbAcnyPpVx46bSYcO8cZR+cP06Z8wa9Z3NaCrF1trplRB951VVe2OX3zxY1pZvFoYqNYxYdIAaleeDvvVb56LiZzcpp7+5OazMfZgWT2NYS/B+jmDAHsl7OIu3C8SYh5JqtTu+6RKljE7iC8rYArZ1RgjoKd6pbWmKhcUmmYuIhtggU/AI7oFOLucr2XxpRV2H+gIjAOWbCp0Y1fhvRs4PrL5VNXsaa8JzrEQ9vdZGGtb6YE9zPfFgv2oYdcorOqd9GGc8ly+dMbo8ScTm1h9Bqsq/t3IXF8mVJu+TFXrqfbiy4ZY0smIcrcBczhTVW/NZq7NDSJyFhBPu91UI4KjInI59twEayvYs5Exl8YqzgdENtdhVd5LVXVqlnPdHbiV0EcetmAa29S3cJ2unt6ezdhpnd9v0MZxNXBxqvuG+6zeAJwV2XwdVqUp+P1GRFbAmIAA76rq9oU+Z77gAsJHCCv1KZXHRWQpLMGzjNv0NhfxBm0IPuu/A2ur1zT1awoFEdkNS5iDqfyvX87P7pYCd/0vRvKAfFnCIke6qMVo69FAXIBMnof3AuckYhOJyDPV1Z327tbtiFZRK7B8Q3UB48c/uKCubs69qnpq40fkD0UPukVkEZBxHTps2K5jx2QM7vxh1qzvmT7zIziTcSzC7cB96hk93GXgr8Ro58WieKfCAsz2IxkF/L+KUEXhEFPRgovU06tLOZ9yQqFo5iaYwedAN7fpWazfs+yvc/HlTSBQvV5FPf29lPNJB46V8xDhQtQEnjR3gacE53oF2N293CBI1Lj77qVYr1c0Wfk6ZjcyIq3xjUp+GCbQ1i3y1m9Y7+z7ac5zFeyarsYq46uo6j9u/M8JRNjeIOA2VIJuhyRB99dYYq7OiXH9hlF1a4A1VNP7nIjINhg7ondk83iMcv5oBj2Cy2OLwl0jmxcAN3ISL7MEQYLgNfV09wYD5BFxdoO4eZ2VKPB2n9UHgCMimy8oJiXSLdzHYEmyWUAXbULewpLYY3uTeBElV637GFjLbfoO2Ir+zMYq3xu77RWHkzi4a+RbQjbcbqr6egmnVEEacPeXZWgYkK+AFRM7F/D0w4FDVPXryHx6AGMWWaRvdfv28c6j+ceMGYOZOfOr2aDdC6WJkQiFSyUkx76gbRdeeI3G9wQOP3xT3nvvPIYNu5phw67m1VfPoF+/3o0f6NCu3aqg1XXcyi3q6VX0Z5KILO5ocaMwOluxAu6AtvEJ8CjgYz6YW2H09HaquoKqbquqx6rqlar6pKp+rqr/NoVApInjSqyiAnCO+JK7ZGLzwTXA9+7n1QkrV1lDRJbA7KSCgOkjzOKlqVzngyI/b1WiOaQNtwB9ijDgrsUefHkPuB2iVN36CpmqzlTVC7AFblQkb1fgVxHxRCRlS474sja2SB5AeP3MxmjDa6cbcLv5DAOCnvz2WAUS4GCCgHsO/5A3bkezRWBXtQHhNXYdQW8s3JpuwA2gqu8Da2MU4UBvZHHsf/6xY+AkhYi0ExEP6+ePBtwfYL7CF7IEX2GBPMBWzu6rYHC93NHKyhnAPU7tvB7u+n+BMOCuw5JjRe1BdImNgFLdHlivmOfPFY4Kuw/Wbwy2znrDij8Gx8p5iTDgHgnsoqoz1NNaTJU5SDRc6CxmK3Bw10jUTu4yF4hXUMZQ1QWqOlJV31fVB1T1IlU9SFU3BBbFnqubYvegK7GCyPfAzPpB2mAs4sOxBoP03cpXAgaLyDUS0p0PhWpp127VVMfFoH37hfD9Pfnqq0v5889refXV01l77WUaPxCwGFTbYey7oqEUQfcmrVotWltd3TGtnf/9dxpXXfU6O+10EzvtdBOffTachx8+hpVX7p7W8VVVbWndqjvUcoqIfIMJCPyH9aHlu0t/HkbF+hALqq/CKJzbYRdZW1VdVlW3VNUjVLW/qg5Q1Y9U9S8tYz/rlgBXqQyEu7oS+ne3eLjqxpFEFx+S/eLDVTtfx7KrYJXGPbVpWc9F+/v6lmwWaSCyiA8eMDWYt2ohhereify8XfybqjoUq0AdiPVTgwVo/YGfRWSX+GPEl07iy61YJWqzyFvPA73V0+vUi+05SxMe1lYCcJh0l35Yv7nhGx6lqaSCSocBkZ+vEbMUChq7JhDbk5wWVHW+ql6LVbujPsCbA9+JyC2uShkDd+38jF1LQdA/FqOsb+uuPdTTOkzbBaxVZEMKDKdefgyWhAdbIzwhvrRxc++EJayCqvt87LP6YPxYRUL0PrdVieaQNVR1OrAzVuUG6AO8ICJtHH1/ANDPvTcJc8wYV3+8p79gSWcwZs4D8UmSCngFCGw9NyBkgFXQBKGGiao6WFUfVdVLVPUAVV0XE6LuAfRlC25ndWwVtytwLnbHX5l0ostqLEn+u0vSbNKmTXeqqtKP3G+88QC23HIVTjvtCbbZ5no++mgYzzxzEt27N276VF3dkVatFl1ActHsgqAEQXfVRq1b90i7//ndd3/hgw+GMmLEBEaMmMC1177BrFnzWG+9no0f7NCmTfcqqFoGy9KmF+2nxudYBv80YE837uJYpXolVd3aBdUXq+r9qvqeqv4RL0BQQVniSsLF0HniS/78Cpo4VHUIYSDSCrjfqWtmBCfO9iyh+Mrf2EJnaj7mWUR8i1EuAfo6waSyQ2QRH1T75gK7a4HtXRxNPPD53UxE2ifYR1X1GSyougGj/YI9xl8XkZdFpJf4IuLLYZjuwumEz67fgR3U0/3U0zHx42cw10mYuJVhXR7HVGMBXud9hmQ7dgvCz4TGW92JDcIv0hyEPFV1jKruB+yA/c/BFm1nAMNE5FAxLOfaGqIJvQVYC0JvVX02AS393cjP21IEOL/uQwiv9wOAV2UN6YUl7YMk3kzMg/vFYswrCZpMcjEZHJ18R6yvG+z//AC2jjvQbZsD7JqEjXEVdu8BY7+cXLjZNj0kqHZ7lWp384R7Zo9T1Y/Zgtg2glYYD/JgrHlse1JrmhuWAwSqNm7dunvaMWnbtq3Zeee1uOKK1/jyyxGMGjWRG298mzFjJnP44ZumNUbr1t1bQ9VG6Z4zHyhq0G0fwrpVW7derPGdE6CqSthjj3VYeOGF+OabUWkf17p1NxxrWAkDqlzwmKpeoKp3qOorqvqdqk6oiEc0fainQ7GAEIxec2IJp1OOuJJw8bExGf593IP4XmAnt2kasJNqarGrcoRTw/7MvVwK64UqK4jI4iRexL9VpCkEAU1rzHwnIVR1hqqeh1WhBkXe2oMl+I3JjMTYQ8EjfA6m6LyWehqtqOeCe4Bf6AysVx9w1wDn5Gn8loBzscoshP+r74EGVmzZQFXfwWjAF2HXQHCex7AEz1DCCjHYtbS2qp6fom8v2orQgJFRKKinT2FJ+4DdswObMZS29b2xk4CtHc2+lPgdYwcCbC6FVL8tINQE1HYn/HsfRvjZrgMOUNUvEh5r4mnHRTZdJb6kx2NtOXgZS7yBJSaK9lmqoESoJfm6rQNGTj8JOAFbLTZIuzMDS7Z3gLoeFqulh+rqKlq1qmbevFiJiTlzathww+WTHBULFxuuWswEUbEr3a2BViLp0wcAevfuwfDh1zBq1PVcc81+HHPMQwwf3qjdWz2sZQewzPd6WE/XzKQHNI5hje9SQRNGVGH2fPFT95e2JDj6d9Sv9GqnNpwuAh0DsMX5Hqr6c4r9yx2DIj+XVRVIRHpiIkDxi/gPiziNaBWx0UWYqv4CbA0czEKMYwfgBBZiUaLUphcxKvnV6uXPo9i195zJdoTybvO5qykI5JUJRM13PV4F/wzNo7WVqs5T1asxT+8oW6MnIZV8HFZv2VpVf005nqd/EVbPNxY/7PctNNTTgcD21Ln1yJK05SigI2MxX+yvUx1fDLhiwiD3sgPh/aTJQVU/w66L+ALJSdqIe4J6+glwn3vZAbirXNlNpYDTYqlUu1sSXia9+3oPjGdyNnA4M9iSZ+jCukAnl2zvADGxWqOYNWse33wzkjPP3J4llliEqiph773XY911l2WJJdK7hbvztSa1TXReUYqe7ozx55/j2W67G9h111t59NHPuPXWg1lppcY5CwkwX1W/x6hFfbGKZjaqdf9kc/IKmgZcD1fQP7gEsRnuFg9V/YjQu7UjcGc6D1cROQFTrQZb9BzmxmrKKMt+R+c3+xmmJQFG4S/FIv4DwgVuepWP/kB/hAsRNiF8Sk3CzB77I/QvkPhlf2rqjSNnAbcnXFRUFpIhErG74ltO0l9JZY5k/wtJ8V4iBMmhamDLnGaUKfozj/uprS8DLAGcyQL6U07taE2eYh7BFGjwuZ6Q5rEXAIHy+a5EzWgrANMNCZJcmwLblHAuFRQaP7EUmaS9q4Hl6cjWHMAZfEx/3hdf1iXLZ8Rppz2BCHz/vc+oUddzzDFb8NJL31FbW74CLMUOumuABZlqJdXU1DJq1ESGDBnD1VcP5Ndfx3Lssek/FyPORjNF5HpgOtaPuT/Z9XhXRDSaP6KiPxeInyE9o/njfELK4e6YQmxSOI/cuyKbzlLVZ5Pt34TwDaGycln0dYvIhphDQuCF/TvmTzu02HNR1cnYvRZgTRFJqYApvqyO0eGfQBw9WZnL54ziLgLH4L2AoSJykWSSGm8EThzplvoN7wMzONVZTlVah9KAs1+L73e9JZ+UZBFZSEQuwqjke0beGgX1S8AlgCeAD0RkdRrHe5Gfi0aLFZGtgQ/4l048BEx3gXY1ywKfii9rFmsujaBZBN0isiZGg46/Hp8Ukc0aHhEL9XQqserzt4svi+Ztgk0crtodZQpWqt3NGyszPetjOwD9mM83wJ8QE6ulhdGjJ7HPPneywgoXsP76/2OXXW6hdetq/vprcuMHh+erIRQILjiKGnQbTalqaE3NxJzHatMm/Wd4Tc0EoGosRik/F0dlyAGZ0GkraIJQT38kFAVaElObrcBBVadgQoIBbheRzon2FZFNgKcJ7zc3aDPxOXZK2Z+7l8tgoiAlg4hsi1WXg4Xgd8DmqvpX6WYVQzFPWPkQXzqKLzdg1j7RRf3LCKvyDstTy2GEiZ52mL7ATyKyPfnB0VhPOUzjP2eQ14ZYX+UKUuNGwoAmUKRfndiWlKwhIjsAP2H/+6Dt5z/gUKx9rDempBxgK+AHEbleRFIl2D8ktIssipiaiOyMub9bp+NkBvEPaxFWCrsDH4sv6akCFRZDCavBW2QjoFlqiMgymKBkIG38BsadATM7ek1EGvWjVU9fJFwbLI6J9FUQ4jngN/fz5pQRA6yC7OCETBcXX9YTX/YUX04TX67jFA7LOZpaELCSqlysljnmzJnP+PHT6dSpHX379ubtt9PrWHSx4dBi6nGVgF5e92VNzb9pW2NdeOHObLjh8iy9dBd69+7BBRfszKabrshLL33b+MEO8+ePq4O6r7FqxcjG9k8Du4lIXxHpUcniNWtEM7YXip+/qlozwfNA0AfXnajFkoOrfL1GuEB+EqPoNScMivxcsiqQiOwDDCSUKxkE9FPV7J5k+UPSvm73MD8QW6SdQxiwjQB2VU/3Uk9HOcXUx4FVgFsJA6SVgLdF5Hm3qM4K4ksnLJAz1HI4SmAbtBdQ8eZtHGsDgc3bP1ggHOByEcnaolNElhWR54G3CFsmajFmwiqq+oS7Rkap6p4Y9XeE268Vlmz/TUQOSPTMVk+nAV+5l6sVWiRLRPbGArfgmfIasJM+rcMwenswl87Ae+JLSS2Y3KL0Y/eyE/a/bjIQkS5YwB2wf77GmI7HEN6fugBviUiPNIY8FeprfEeLL/1S7dyS4PQbokxBr1RzqSA9iC8LiS8riS/biS/Hiy9Xii+Pii8fii9/YKKV/2HMvpeA24Dz6Mam5KJ4NAq4i+nA10jdPzU14zIKfvv2XYWtturNMsssypZbrszzz5/Cn3+O55lnvkzr+JqacTVQl97OeUIperoHL1gwubq2Nr1W6m7dOnL77YfwyScX8eyzJ7Huuj055JB7+fjj9LRt6urmUlMzrgpr478fE3G6loY9PZngNGxBOxaYLiLfi8izInKFiBwhIpuKSLdKQN60oZ5+RxhULo35VFfg4BZipxCKEh4vIvV9H45K/BbmeQ5G2D3KUdCaE0re1y0ix2EaFW3cplcwVfjsyV/5w+eEStPbBfdF8WU17Jp4itCeay62SFvdiUzFQFWnqeqZwLqEyvFg7Q2/icgFItIm/rg0cCnmVgDwrN6q7wD/F3n/iCzGbGk4PPLzBU6wL6gkdsG69TOC81K+EKu0RltYPgXWVdWzElmRqepArMLuEapVL4kxbt4TkVUTnO7NyM87JXg/LxCRg7HPaiDe8xywjxOpRD2dhDFCAtXydsCr4ssBhZpTmmiSFHMx5d6XoV6t4U/MGmyWs3HdB2PYgInxvSGSWkxPPf0HuDCy6b6KvWgMniYUJ+wrIk3memmOEF9aiS+9xJetxJejxJf/uaD6E/FlDPZ8/h14B3OXuQhT998Kc2XJb8FpHhP5kbN5gsU5m13ozxC2YrH5NeOkri799uNFFmnHVVftw8cf/x+33noIX301goMOuocFCxpfYtbWzmDBgsmtgME5/CYZQ4rtcmU3MxnXocOG7Tp2LLwn+axZ3zN9egOtpj+xHq7tKSwddBow3J1vJJZ5D76PUdWi9RFUkB3Elw0Iqw5/ASs5SnEFDiJyGpb5BFP2XxsL/j4iVLr9EdiyTILAvMIxIKZiFMXR6mmvop5f5ALgmsimAcBxTo27LCAib2Eey7As63M0BwBnEdtb+Rpwpno6ouEICccUbGFwPUbzDDAMOCVdqyXxZRXM6qYVFqD1Vk9Hi0gV8CWhn3yAs1T1lnTGbu4QkTOBm+M2D8Y0BFRElsIWcwtjie7VVTUt9w/XKnEHxm4IMB44D7PtTGvx4nrybyX0qQfzx74JuFxVZ0KDe/0r6ume6YyfCUTkGCz5HyTkHwWOSfRZdfeVJwiTDQqcrJ7ek+95pQMRWQu7jwO84hgFZQ33GX4G2NdtmgBs4lT2o/v1wK7bwCXhPWAXF5QnHtuXKqz6H/SC36yenp3H6TdpiMhh2PUN8IGqVkTVCgR3LXbH4pnlgF5xPy9DQx2D9DAXi2Smu69pcd9XJJMUpWL34vuwz+QRzGIFvsGetLNhkUX60r594Q0SZswYzMyZX80G7Z7CTjLvKHrQDSAid1ZVtTt+8cWPaVVIy0fVOiZMeGRBbe20v7AqRqKerrGEVZZ0EPSxrgSs7L73InNxtVpgDLGBePB9BDCx4vtdHhBf3iC8rRynnj6Qav+WBtff9xnmzQlGLdsQS2qBJSs2UdWxCQ5vFhBf3sesrgCWU09HFfycFnReiwUhAW4Czis3NoGInAPcwOrA7kxjofq+SrD73hnqpbbsSTF2Z8yq5hRi2VvPAuc05gEvvrxC6O18uXp6WWTsTQh79gNUgm6HJEH3hlGVfBG5DLMKBHhZVfdqZMylsd7w/SOb6zArsstUdWqWc90NSw72imz+B0v+PO8U8cdha4WZwGL5tKQTkVOB2yOb7gVOTvVZdeJ+9xKrKXIxcLV6xV0fuAB2AqYXMRnoVm73mSjc/fEW4HS3aRawlap+k2T/3thzLNDDeBw4PNU6zCXsfsQqgQpsqZ5+mpdfoInDiScOxcIyMPeMyt8mCziB1sVIHFAvR6xdYmaYhen5T3VfU7CAOviKTTvVYPHJcCyZOpw96Mo6Me0EyfAr1pK4BdCP/4AvgCHE8I6rqzvRrdsR2O2mMFBdwPjxDy6oq5tzr6qe2vgR+UOpgu6VQX5u337d1ossskXBzjNz5tfMmPGZYgHAUKw37wiMuhVP/dYE2xKhU3y1ztEZexEbiAdfy6Y5bjxmkTwgH6Wqs1McW0EeIb5sTEhBGQmsol6FpRCFU4X9Dsum1hEGP1MokXJ2MSF+TGBxpHr6SEHPZwuaezHxrwAXAdeUY7JO+snuLMMrrBCzeR5Wob9WPZ2T8MBMziHSB1PIj1KoZmH/l1sTVa3El76EPfljgZXV01lx4z4OHBLZdLaqxgeaLRIicgZRxXd4RFWPjNunPbZIC3pl+6rqx8TBPUfPwCjh7SNvfY4xF37Iw3zbYbTgC4hdpL4HnEp/LiKkyW+rXnpsiTTOex5wXWTTLdh11Ohn1S24r8EcIwJYcs0rbtArIi8RKsavrapDinn+TCAi5xKKnNUCu6nqmykOwSmYv4exlsDup/+X4hDEjznPH8Da6lXWZwAiciTwsHv5rqrmS/Sy2UF86UzigDr4uX3iIxvBXMKgOlFw3ZDLMYfYuGM4YZD9VzwrR3xZB1v7JUMNxiRbmTraMxwLthuqa9XhdGg6dtxMOnTYIM1fMHNMn/4Js2Z9VwO6uqoOL9iJEqAkQTfUUyKv7tr1AGnTJh3disxQUzOJiROfqIO6G1Q1RrjJCe4chvXorpTo+CQYp6oZTdZZ2vTEPjjLu6/oz52SH516LiQOyEcC/zgxiwryBPHlbcLK7VHq6YASTqcsISJXYoFfgLnAtqr6WZJDmg3Ely0Jex4fVk+PTrV/TueyHsUnsSQiWMLwRFW9r1DnzBbiS3vgEpRzkPoeVqjjTao4Tb1YmmfO57P0+BFYgLNY5K2hWOD2YWRu8fTxY9TThxKMuTS2mA6CtOvinyktFSJyDaEw4lxgeVX9N8F+RwMPupdfAxtHq6TOOusOINprPQELNB/Nd0VVRFbEqt5RYmQNfXmDfuzhXt+knp6T43kEuIzYfvYrgUszTY6JL+cTK1Y5AGNeFa2NJI7ZcLqq3p5i95LB9c0/Edl0tKo+nGz/uGP3xPymg8Txqap6Z9L9jY3wCWGy7xb19KyMJ90MISKtMZHM5d2mTVW1qD205QL3LOxF8mp156wGnk/igDr4uWGLtAJ/ExszRL//l8m9SXzphrX9JMI8YCHmYqoJX7q5xWI68ABwh6qOFJHroOqcxRY7pKp166y1N5Ni/vyxTJr0LJjuyHWN7Z9vlDLobgUyuKqqXZ+uXQ9s1apVSt2KjFBbO5tJk55ZUFs7YxTUralJjMHdA3ETbJF2INDYJD5S1a3yNlHqVTWDIDw+MO8FkYVq+qgBRpM4IB/h7J4qyADiy2aYeA9Yj37vYi52mgISVL3uVdUTSzSdosL5uE/FArOR6unyqY/I8jxme/QyIZW9BjhEVZ8rxPmyhavO7Y0t0EMl6KmYXNVwttDawlEN3X31CuBEYinnTwHnqupY8eUgLHkBZkO1jnqJk5Ui8jQQCFkNA1YtR0ZBMeGen8MIE9dPqerBSfatBr4HAt/pg1T1adfzfQP2/A1QB9yNBaYFe1a5+e+O9RhaL29bLMyvApTftL8mElzLZPz4CvUlqnplkkMaH9OXYzGGS3BNvwwcpF7iNU6+IRJT1XpBVfdNtX8pICLbYHeZYO10qaqmQ3+NjnEy1s4AFqTso6ovJd3faOY/YFeQAn3V008ynHqzhNMxCFry3lLVgokUlhJOg6EnyavV3ZIdmxILCAPoqTQMrhNzKqaSPKj+SzM1xE4B96yfSyjiGmIyppLxHYkq6sOxxOcj0Z5qKypU/VRd3bFX164HtKquzp8+4YIF05k06ekFdXVzfgDdpBS6NyULugFEZEmoGlxVtfCSXbvu26pVq845j1lbO5NJk15YUFs7dSroxvTnGkzA53tsgfUpMDSeluVoZ3tg1e/tSKzsPhw4CfiwGL1MbqGyJIkD8uUx4YRsMI0kATkwOp8fyOaEuL7dw9XTx0o5n3KCiOyFVQeirRQzsODkn9LMqrgQXz4kVC/vqV5+vbFFpBvmLRtUZmcDe6nqO/k8T64QX3piC9ZdIpvnM4K3eIrdscaM/6lqwa1kRGRdjHK+UWTzTBbif1zIyUh9f++O6unbKcY5hFCJG2B31ex60JsLXEUwGogcrpr8nijmsf2WezkaC6wvgRin1y8wRkIqumJeISILYwyd84A2HI01hQEMZnN9K3OmjmNc3IpZSwXIixaA+LIvVsUNFrkfAnuqV3iRSrcmmYQx9CYCi5dT8sm1mHxMqN9zL3BSNnMUkasIHQwaZW2J73QrDBWauYOrdv9OqKWwkap+lfyI8oX40g5T8w5aSYN20uWxtXrmraR12Ip8Komr1TOxNE4sajDDrURB9chiFdYcW6wf5sDQBdxcx2DqCIklM9/DijNBq8eqmJ/7wZjw7tvA/4EMrq7u3Llr131aVVfnagYOCxZMZdKk5xfU1c0eC3UbJ2JkFQMlDboBRGRZqPpQpLrnIotsXd2uXW+yddqaO/cPpk59b4Hq/AlQ14/+/E7o5xrFZOyS+BSjBX0bVaR22ffDMd/YRPyGv4DHsAxNUfsBonCLhV4kDsiXg6xs6xUTl0n4YcYo9mUrnlJIxPV//g6slqwy1pIgIptjN9KAfvsjoY9ro8JJzQXiS39CT9K8JmVcS8y7hErOU4CdVfWLfJ0jV4gvrTDRossxteoAbwOn0Z/ZGK0NYLCqblqUeVkAFFhF2v18EwItdYB31Uvdaygi+2MqyAH+ANZoqQlK1+LwCyFtFFz1upHjom06UUzEaOoDSvV8EZGVgNvZgh0IdJbfYB5fcRFwW7pVEReYxoufnaiq9+Ztrr5si1W5gz7Pb4Gd1NMJ+TpH0nOLvEaoBL+Gqv5S6HOmAxHphWmvBMWIV7EKdVbVLMdUeARrRYRG9EkczfxjILiv3aqenpnNuZsbxCwtg/anN1R1l1T7lxLuOdaLMKCOBteZazQpVn5IRv+eTuIoJbaFNL5INraULaTiy0oYQ/hwAiZbHZZKfQtz9I7FXCxmuhuzQNzcfW1GKFwYQDFh6lVAPhRZaLHOnbdt1bbtimQDVWXOnKFMn/5hrWrtKKjrp6pjshosDyh50A0gIotiNINDFlqoV13HjptWtW69eGOH1aOmZhIzZ36pc+f+LiCvgZ4QZDHEl5HEqpUmwlyMBPEJFogPVk+nuZvuMcBV2IWRSKH8M4w685xqrABPKeHmHqgdJqqUL0vmiutgf6tROJoKltMagy2mxwB/J6PzNweIL4MIPUoPVk+fKuF0Sg4xv9vPCLKcZhFyFtZDG3yI91HVF0swvaJCfNkKqzoBPKieHpuXcU1V9x1CmvZYYPtyWewCiC/rY4uqqNfHv1gQ/kKgtCwiv2KZ7VqgqybwWC7YHO05cyXtOIHTEdphj/dHGchIjkuV+U4QdAOcr6rXJ9q/uUPMO/vquM0Hqya/HzpbpvuJZUAocA9Gu56c94lmCBER1uccdnXCWL8TNCB8Bxyvqt82cnxrrNc6oNnXAUep6qNJD8p2rr5shFWLgnvvMGA79Qq7oIwTKDtFVe8q5PnSgWMBfUKYlPwC2CZXwVkn7vc6xn6ERpw4xJeVsaRzhWYegfs7DifkkGyQTEW+KPOxCu2SxAbUwc/Lk6m9ViIF8KmRr8Th8SwSB9UjMbHksoknoL4nfT/gWEKbPEsofA18gzK7QULiXywMnwqsh4latyU1RqnqchA8M+Re0N3atl1ZO3TYSDLp866p+Y8ZMwbXzZs3qgpjB51e6udMWQTdAURkd6i6G+qWbN16idp27VavbtOmO61adcWSxwbVOhYsmExNzThmz/61tqZmbDXIRNAzgSejVCLxZVfM/zUT1GFC9p9imcuX6E8rYDcsu7MjDQPW6djj+QHgu3KiXCWCUz9ehuTU9cWSH90oJhAG4fFB+RhM6K1Jel2LL1sDgaLtUGDNllrttvYQBhM+SN8BdlXVGhE5AAiqXv9iNPOiBVilgKOeTcVon3+qp9mlZqNjiqyPLayDz+MfwHaqhbckSwfiS0essn0aYUuOYhnti9SL/Z+LyG2Etot7quorxZpr/RzOkCdY1AVF3wM2gxmY4NUdiSpjcUF34HQxA1hZVccVftblAxc8/44xqaKuHwmDbvesORWzdYu37XxSVQ+JP6aUEF8EZSxCd2owfoRdEXWY5delmsDX1QUWTxMKHC7A/iYF01sQX1bH7ruB7ekYLPBOyws9q3PaPSmwhHtWVQ9ItX+hISKLAB9gi3qwa3MzVZ2Yp/E7YuvAPm7Tj8CWqonp/OLL2ZjlHZj+y9rxjggtESJyIvZcgCL4vEdstuKr1cH3dhkNOBfj40zGGiyCr8mYXFhD1BHaAidijk4o+zjB/obrAsdhicTw/j0W+ALlZ6CuQbD9H/YXy8a9aVdVHVg/BysgHgxyC+hibdosWduu3WrVrVt3p1WrRWOsxVRrWbBgEvPn/8ucOb/U1tSMr4aqsVB3kqq+muE8CoKyCrqh/gG9C8ipoFsDVVBVV13dodbi3Dpqa2dWQ637S8tnoLcDLyUK5FxGaxihV2A2GKCeHhWZY3fMQuYoYPUE+/+ABd9PaJaeoqWGe9AEAhCJqOuNZasaw38kDsiD12NVy8+Wy92EPiHM9B2gnj5bwimVBCLSCVuIrOU2fY9ZAc1w7wuW7AqqWveo6klFn2iRIb58BGzpXi6bS9VJRPphFMmgTeRHYAdVbUjeKgHElz0wxemlI5t/Ao5XLzHtXcwrOXj43anF9sj0ZXlMTbc1tcznVmYzPUY19iesehdTnYoLugcTKhU/pKpRGnGzh4g8jGmfgCWmN3c/Nwi6RWQLrL9/zcjmqVj7QRusN3FV1fyq2OcK8eUBAnr4M4xkKMtF3h6DKVrXL+KcJswLhGro84F9i9H3L770wlpPgjXORGAH9QrTF+/WaJOxBfh/QI9SBQ+uzeFNQi2NsVjAPSrP5+mBfe57uk3vAbskWXNWY04WwRrhNvX0jHzOpynCOfn8CSzlNq2WjKqf0biW+I0NrJWVgVWQDN2BaogNpqPBdUPOhGIU8DGEwsXxgmVlt4ZNB+JLFyzIPpYw2WQV+9+Az5jN2JgWsuDdvyDmXpkphgO9E7UYuaTmXiCngbrPVrWLDauAWhcb1lUBdSAfuNjwjVIIpiVD2QXdUYj5e/bBMpjLYD2j87Eb67fA98myjTHj+HIaRl/PFm+o17AHxQUWG2EX5oE09NGbiwkMPAB8Uu5ZrXThfu/u2P9kafd9mbjXS5IdfT2AYhXSVBXzf0vR1yK+bI/1qYL5D65dbL/UUsI9PN/EBDTA2g02ia/4mV4DvxJ+LrZQLZxidTkgrq/7aPXSs6lpMI6JVD1DKJb0KeYzOzXHKeYM8WUprOIX7dWfg9ki3ZzKw94l8yZj9L3fVXWVZPsWAuLLM8D+7uVV9OcmrH3oOGIz8o9h9PFxACKyHxAk1y7D9D46YfepDUtJlSwmRGQDrBULLHi+Dvv7QSTodonp6wj7YcH+VvdjomVnYiJqYK1Z+1NGEF/2AZ4HoI47+R9jsM91tDr2ItY+MQ1LJAX3wznAHqr6bhHnuwT2TAq0NGYAu6ungwpyPpE3CBMMvVULV1lPMYdWWKJjd7dpMvaM+bVA5+uNtVIFPaiPY+KBDdZ1cTRzgK3U04/i92tpEIlhAQxQDYtZKY8zdxATMFNWpoY1qWNVWrE8rerbK9JDLUb/ThRczyAqWjaehuvP6Ne/TZWxmQiuoLQF9izcl2hhbTbwLfP5nPnMaaAVNQXTsLgLaxXaOYdpnKaqdzQ6V2O3rIPFhkti66R52P/lW+CHcqPnByjroDtfcJmwv2ncEiwRpgEbq6e/pTyHLSYPwALwjRLs8jvmU/pIuVSqCgn3QOxO8qB8GaAHmVNPoqjFAvNkQfnfFED4zd2cPgc2dpv2Ua/59ywDgSjV48BBbtMkzHvz9yT7R23EfgP6NGfxqThruSfVy5w6KyJHYYm6gDc1ENg/1/7EXOEqOCdjPsNRmvDbwMnq6Yi0xhH5hLA62lM1vyrvSc9rPbBBBX4CsGKg+CwiG2KLhvUih8zAqPO3YQv7IOg+B6MOBn7FnwObN5ekajK4ZOtnhFX+M7El6q3u9cFYIHoGFlBHr5FvMAbBV26sjlirRKD7UFb+veJLoM7dCvhDPV1JRJbH6LFRIbgZ2LUUCMrNxOiRRQ+wxJfOGLso+GzNA/ZXL/+0ShG5ALNDAzhBVe9LtX8Bzl8FPIS1+4H1x26tBVbFFpFNsfayICC5RlX/L+G+foyn+QhgrZZOM3ef+78wT+oFwPKBqJUTMOvJVPowl/WoYg1aswJtWZK2dM5opajYyj2eBj4JSxXWMZnkTMugBbLZahNF4RJ2R2Cxy0oxb/4DfMoEfqML2qDPfSi2tns8WJs4jZ8vyD7WWlpVZ2ZxbJNBiwi6AcSXG4GzMzysDlMEzciSR0TWwqhph0GDLNwCLCv+APBOKRUISw0nOtODxAF58DpbW7QAC7BbRzIa+xistyajwFx82QmzbwLLaK/bEqrdInI9cK57OQdb6CRV0HZKvp9jAhoA/VXVL+wsSwfxpTX2aO+IZcp7ZHJdiMTYzoAlOI4uNU1NfFkbE0rbMLJ5PBZgPRMIpaU1loiHVcUBjlHVh/I1z6TntETZx4QBySnqxQpAuWv1OKxyG71v/4lV1AK/5XOwSv8QoLfbllJErDlARA7GxGjAEmhrYRaaQdB9I7AnVpEKMAWzXXog/lknIidglREw6u5m5ZS4iLMAXFk9He4SDwdii814tdcZmMBhyRwFxJeFMXZdUG2qxRg3eRVyE5GNsf8ZpPBnLwTc/+BGTLATjP24i6q+V6Tz74ndD4KkaMLqnGtt/IjwnnOHenpa/H4tCdJe2rMwd9KBI+gKLMVYlmAB7elKRxamOsMizExiA+tJwBRmMpm/qEko9BuI/bbs5Icl0LfHnne7ERWOqwF+ZhYfM4MpCdffb2D3v/cSsjxEdsQKBYlsl1PhRlU9t/HdmjZaUtC9HJZZz+RCOF09vT3rc1q/0V5YBmnrBLv8jWVrH1LV0dmepznD9XEsRWoqe7ccTzOfMDAf434eF/f1HzAluMm4RfxXhJ7Je6pXfFGoYkIkJnNfhwlhNdqz6JJQ32I39vlYtTvnXq5yhfjyCiHlsY96+mOjx9hC8irgwsjm2zBv35Ilc5xiqYclLKPtIvcDF6iXuR+oqxYFfrdPq+pBqfbPB8SXvbAqLBjraI1kNHinhHw5cDyJmTjnqOpNbnEReI3+jdFsm+VizrV6/UbYv7+Tqr4lIqcTBt1R1GHXyKWqiW2sHBtqCKZmD9YD/UJ+Z549xJfzMIo8wJnqaf3vKSIrY0Fn1O6mFrgJ8Et5HbjE3wBCBXWAs9TL3SO8/hyWMJ+CtQ6NxSpURVlMisjFwBXuZR3GAirqdSMiJ2NaBWB11X01gUOH+LIido0HbQn9CkX5LxXcs2tRrEBiX0IPurEi3VmRrizDonSjCx1ZjFYZqwHNJVqtrmEaE5jCGMYznNmMIC6oTqfltKXC6T8cBRxNrBaLMQA+ZjQ/sii1DQQvpwIPA3drGjbJKZ4LyVAHrFAuArGFRIsJugHElxeAvdPc/V7gpEwqOCnPLbIidqEfRcPqrWJCKPcDrzanPpFiwCU3gsA8WdU83gswG8zHgm8LxDegDbs4t9/ZjOAGDqPOAvTmtvh2QlJPEwYhGVEKReQqrOIFFnBtWcpgspCI05A4Tz29IeX+VmG9G8s6B7gMuKKUlT/H5riLWMvFocAJudjgxAkxTQSWKOS14IKQXwipc2klyESkD5bR7xv31qdYz+5kEXmdUCzwf6rq0QwhIj52TQIMVNVdRaQr8BLWBxjFIOBM1bSSTVF3kT8xcaWyeP6JL2tgwnoA76inOwCIyFIYxTjQI1hArMXQKOAkVX2rSFNtAFdlvRVTjQ9wBXBZHtc07xBaaa2kqn/kY9xGznkSdk8KcKyqPljo8yaZS/SZNg/YNpFmifgxLVYjMZp52VNoRWRhooG0sRK7N/jqyBJ0ozWLY+WP4CsTbfAaYDLKNGYznUlM52+m8gf/8RPjGYrWB9ZTSvlMbIoQX9oAe2DFv+2IJpIVGM5kPmAi41iRhkXJH7Hk0pOZrGldIuYeLHGdDl5Q1X3THb8po6UF3VtgFMN0cDZwS74eUPVzsAXnztgHYBcaXuQTgUeAB5tzNbDYcA+QaCCeqGreOeOBT8AeRWDEyzAHOINogJ78a3ypqcONQUT6YrY0gahXxsGFU/cdQqiwe5Kq3pPikCYL8aU3FpwCvK2e7ph0XxOlexwTLgF7DJ6mqncmO6bQEF+6Y4vEqBXQPGzRfp16uQdFIjFsgHVV9ftcx0x6Ll9OwVTWwZwH+qZ7X3eLh72xhX6UTjwFC0Lfx67rVlhNpndzYy05QcRhWB/rAkzcdGvAJ5aGPwGjm7+Y7sLY/X3fJxQhO1NVM6mQFAyOzTQaez7MA7rSn27YfIMe7jGYheg+wMWY2GuAZ7DfpySWcm7+HqGwI9h1fFo+WqFE5CJM3wGKEPyKyIGYLWsQNJyvqtenOKSgcNfuAOBwt2kK1iIRs25zCZBBhMmpO9UrrmtD/Vxs/dmNdILpeHu/joQBdTTAziS4nsE8pjOJaUxkBGsyCWEy05hLH+YxuhJQ5w/iy6pYm+sRxFsAz6WOz/iVL+nC/Ho1+QALMBHJO4DPs/mfuM/GWYSieY2h2YvsBmhpQbdggi7rpnnIg5hAUEEy7y5jfiT2wUgks/8ZVv1+vrlVTssRItKBUOCtO7AEiR9G3Qge/L2xDj8wUvr9WZ16IrE09mQB+uRiV4dFZA2sshdYbzyELbCyuRFHPc6nY1ZBY/My0TKCu8/8hSVy5gCLqtdQlMVdby8SVosWYGq4JekNdovD4zBn4qjVygcY6yehWF5W5xI5FeuLhgIunp0g1h+Ei46N1MtcbElEDsGSI/H4BUuwBEmTkvsW5xsi8jRhAuZ5YDX3FY8jVfWRLMZfD3sugzEgVtAyUOkHEF/uwVKrMJITeIRLsGcEmDjWNgEl0lHO7yFMIIDRMi/AetpLwuwRvwHV82ngiFzXNSIxopGPqerhqfbP8Vw7YoyIgFFwrapemOKQosC1v71OeA//C3PyiHmuJaCZb62efpinOQh2v04nkA7XLsmQj+B6PhOZz5/U8gvVfMvCfEMVQ9UL/e1F5DHgUPfyDFXNxWGoAurbwfbDinqbNdjhX/7mbcYyijWggeXXPxjD9/5cEoWukHAXxuxNB98CG7SUhEuLCroBxJfDgGSiItOwB9IJkW2fYurU4ws2J1Pi7IctePcirCgGmI5leB9Q1W8LNY8K0kNMtriaHpzNPbR3C7GX+AgjVQYPucx8IlNjAcmD8vjtM3O9iYnIMljfYpAJfQPr4866Mi8iD2EtFmAVsX1ymWO5QvwYL+Nt1NMPYt43au4bhMJkc4B9VPVNSgDxZXXsgRt9UE/CGD+PFYDxswrWIwzwrqpun2r/rM/jx1BAn1FPD0y1f9JxRPbFBKrAFgnrxe0yn/C+3VdV02VUlTVEYthh0d8xwFeE1/AhqvpklueJLsCvV9XzU+1fLIgvuwPWivAds3m1fqE6DAu4/4nZ3wKgw7EKT9fIW59hLTm/FHzSCeDWPQ8T6jK8CeyrXvaOCC7gnIqFY3+pas/UR2R9nk0xX+wg7Lsf+1uWxeLVKXJ/hFkYgVFyt4zvLY5LfowC1kxFM3dtc/GJ/2TB9EJJhkmODsQG1cHPmQTXxvT4JfL1K/BrNLhOBhFZE0tEgCUrVix31l85wiX518UC7YOJVw6vZT5f8zUf05HZrJVgiEEYhfyVXP/+IrI4JjK4eWTzPQnnFeIwVU2U0G6WaIlB90LYDS++r7oW2Fk9fUd8ORircgeSD6Mxz8shFBgishi2+DgWWD3BLt9jyudPlks1oKVD/JgF+RfApkGQ4mjVySrmwdcS2MM08wdncswmAZUdq6rH631OAmZFFzEi0hlLOAXX4NdAv1wZFyKyKBZsBeJ3e6nqy7mMWY5w95BA6fka9UJbGcdweYewWjgVsxn6jCJDfGmH2TudT2xf6iPAuerpxIKcV2Kou3OBLppnixbxZRlMNK0tFjD2Vk9HZjVWbNB9LvbZuJXE9pBDMMp8k3amcFoD3xJ6P0fxJaZcvyGhfkEuQfey2P9qIex/tUo5iOqILx1QJiO0ZipBZ+5PwHaawvrTPcdvILS0AutcvQ64UlXnFGrOSefky26Y7V2wrvkM2FW97NcRIvI+oUjscvn+nzkRzo8IW7+eBw4st8+WiPTAEtRB4uF9YOdAn0BEqmhPFw7lTRawAbOBsXzAR7yBJWe6YmycroTrhc55mZwF1zX0YCbdqWFxWtGF9rTJaL0RBNe/EgbYQwPLxWwRp4lxuKo+lst4LQnOIvAQLFbo02CHaQzjDUbwO+ugDeKdWVjx8S5V/Tkv8xFZG3NmWtZtmos5rzwlIjtgRYb4dtpxmG1oWeh4FAMtLugGEF8uBf4XtzlGqVx82QDLcAcdu7OAQ9UrToDgFqUbYR+oAzGV0CjmYovAB4BPyiXr2xLhaLlDCAPU7dTLzL7E/b8XIXVwHnwtTuZ2DI1hPrGOlqsRUnInYf2bo4gz58hm8SMiB2HMDTDl21Wbm+Ko+LI4xj4A+EY93QDqKajvEC7OxgE7qBY+oZdgjttiAm4rRjYPx4TS8kJ9THn+WNbDdppnyx/xZQBh0HOTenpO1mPFBd2qeqNjKB2C+RUvGXfII5gdWlkFB+nCBdwPELI1AozF6NJPqmqdSIxoYNZBtzvnNW5s3PgZe9znGyKyEUfwKcu5hNS9/My/9FXVyWkevzVW6Yn63/4BnKiq7yc+qnAQX7bEaNpB1WkIsIN62dFJReQy7NkAcJSqDsh5kuHYK2CJgSXcpneB3VR1Xr7OkQ2ccnvXuK/FsGazkwmTGhOwPu+umPZBvp/ZwTksqb4o0+hFLcuyEEuwCJ3oRluWpSojtt0YYgPrvATXySAim2M6G7hzrdVcBVbzAVfV3gKLC/aDOC14ZRa/8CFv05YZbAUNvLV/w6raj+ZzzSUiewGPEcYpYzFW5NeRfRIpml+qqlfQgtBSg+7FsZtLQJW7B+vd1rj9lgReBjaIbL4MuLKYnsyOvnQg9kHbMMEuv2OV+UdSZd8rKBzElwOw1gSwKtiW+abk1p/LFsRdSS9Aj/eJzycUW1QkqpwHX4kq6/MwH8ed3Dh3qeopBZxnSSC+/IBVCRXoRn+WBd4mrPKPwHx9/yzyvLph1kaHRjbXYMHjVYn6zwsyj9jkS157NMWXPsB3WP/iVGAF9dILlBKOlyDojrzXAbN6O49Y+vWPwKlNTSDGUcpvJ7bCPR+r0l6rGlJi8xx0d8IUzANa9gaq+k2KQwoKEdkSGMjGdGBHt3EOl+g1emWq4xKM0xa4CLtGWkfeegyzn0toqVYoiC/rAm8R3of+xBLFGbNAnMjmIPdygKoelWL3TMZdEnuOBlo3X2Lq4HlV/XZMtKDC3DXFz9HXyWiy+cJMEreQ/YswjtWpYSO60IMlaUVvLNm/Opk96/8mlhL+C0YLL3ryW0Q+JWxr2l3TsCFtaRBflsASyMcSm8AzzONr3uA3hrAOyhpx79ZhBcQ7gQ/yWaBzieeLiS1ifoUxGMfG7StYkj9o350HLFPs+1+p0SKDbgDxxQP6Y0H1/kk9W41++QCxnpcvYUIkjfat5BuObnUMcBgNb7ILMHrHA8A7TbXK0hQhvlQDP2PZbsii2l0IOFGLJSJf8Rn6+EXFEsT6MRcCs7FAqDth9v9F7MGfLHif1tTYHOLLDYBVVz/C40POIVyw/YRVuP8t4nwEq1zeQKyF3idYdbuobgmu/ytIEn6nqvF90tmNa7/nO8C2btM56tohZiQAAQAASURBVOlNOY2ZIuiO7LMcRoVdJu6tZzCxuL9ymUOh4Sje1xGrWg+2QN8iEXU4rnqRU9DtxosK7H2EtbQU/XMvIttja4N2dAVOq3/rA/V0myzHXA3TTYj2O07G2hUGFPP3FF9WxirHARX0X2B79TKjmrqEwlSsLWCkqi6f+oi0xlwU+98HwcOvWI/0pBTHBEyxxgLm+J8z62DODpOwBGuYiN6YPViUXiwM1PAqr+AF76tan734sgiwFkYdXgMLrFcjM/vTILiOp4VPy8cvlg9IrG3gYEwBvkk96wsBt6bcHtN62o2GVesp/MVrvEAV09iNhvpBEzD9g3sL8exxxcBHgT0jm58AjkvWPuNYIs9hFmb9VdVPtF9zRosNuqH+pjajsYqkW8RdAFwF9cqPQzG/17wp+mYC97DbG8t89Uuwy9+Y0vRD2swsbMoVcX28XwEbF6raXQiIyJGY2A5YdvQs7GGdKkgPfs6nYFwi1GIL1GQ96dMwwcHge8zPqrqgwPNrAPFlB+AthgHPUEtdfTLjc6yHe0oR57IKtuCPek5PxaqzDxWTuRMzL5HvsUWlAour5t5DLr7siAlFgfnirqpebpTUuKD7PNXE3usucB1OQ8GxuVhAe12uugj5hoi0x3r6zyeerthIf7WInE1oC3OAqj6b41ziPdX3UNVXcxkziznshvUOB//DN/HojbAcxghZLNuKoKsMHQ1cT2zP7iCMcj4s23lnPBdflsYC7yBRPAXTtfkio3FEBhHeV5ZV1TEZz8WC5g5Y0vc5wh7VCdjnRrGgupP73pmGz6D4oCSfUOz5E8/eSvbzrhhzCOxZuruqDgwGE1+WxxKvgTDfgVgyuk/kK5MExj8kFjQrm+A6GdxnItqet6WqfpLikGYN8aUndo84GnNAiUUtH/Au3/ElfdD6xHIUX2BV7ecK1YrhhFBfAlZ1mxRj81zbWMLEfdY7NreWwnTRooPuTCG+7ITRITu7TdOBQ9TT10s2KUBEVsQ+oEfRUCBOsarPA8CrLUmwoNhwvd0/Embo91CvuAvGbCEi/bDrJFi4nKEZWHg4RfdFSS9Aj34VcqEUxRxiA/KkAXqK1zMyCd7Fl4X5gWm8QivC2+xbwL7FCryccOSF2AMxGgg+CZytXmnbUUTkeqzSByaQ9ExO41l14AfCz+BB6unTyY9Ic1zrWXvRvbxQVa9NsW9/Qm/keMXvv7Hg9ulSV3Pc4ucgLKiJerVG53ylql6SYowLCIOLvVX1pTzMK/q3HgasWSxVYxHZH0ucBvell4CD6M8NQOCtvLd6uf2eIrIE1uIRZdDNx3yvry1W37L4shgmcBS00M3Gignvpj2GyBUYxRTgUiypGA2Q0/2e2soqf6gheftTsiB6aqbMQRG5Grv3gmkCbU5/fsEClT4Y6yhRwSQVguA6WrluEsF1KojEuAoNVNVdSzmfYkN8aQPsjlW1t6PhZ2Eck3max6hhCvsTasIEmIs90+9U1e8KOldLSj5OyNqbChysJXJeaWqoBN0ZwvktvkyssrgHXFGqalEAVyXYGat+70xD4Y4J2I3tHlX9o8jTaxEQX/bEFmpgmew+pb4uGoOI9MZoXZ3dpjtU9bTkR+TtvAJsglkSVWOLof/DFp/JgvSuWEWkVJhNegH6dGBTourFC/Ee8zgY81sveOuH+NIXq26vEtk8EvPcfrvQ508HjsYbzOUBVT0up/F8OQZLMEIe2SZuoREk0FKKv4jIwliwGFQpXqIhPfBzLLFVkp5lEdkA0+LeNLJ5AfZsCzzHx2JV7lS2RhcDwd8iL/2Y7r7wCWGf58mqeneu46Zx3sMxpk/w3HwSOEJVF4gvO2M6FAAPqJfbdRo55w5Yn+Nykc2/YZZYBbWdc9ogHVmFJdmLh2nr9GLqqOULHuId/iC9gDme1VFMzCa9oDn684xiJLzkHOnCW7xIR7aiO7AkNSyOImn9vWZj1d8f3NdPWHA9tVDzLSXc2vUPwnaHtUshLlpsiC8rYT3ORxAK1waoAwbyKYN4n7VRDqChw81IzBP74VTtF3mZqzESLiEUTgRrqdyrEk+kj0rQnQXElw7Yw3nfyOZXgMNLIUSRCM6W6Eis/3u5BLu8jVFQ3qj0fucPrhXhS8LKwcHq6VMlnFJKiEg3jI4UUNkGYqqTRaNjx6kWfwJslUrB1PWpx1fVFyF2MRj/c/zrQijJZoJZNF5hn+b2m4Mtwhr7PldVVXxZFKOvHh053wKsl/vyXLx58w0nZDQFW0yMxmyHsnooiS/tMWp34DixpXr5oSmKxFDWfVXt38j+BwLB534Y9qy4FkuGRjEAuKhYvf3O2ugqGqqSD8Qq8M8RWtk16p8aV9XfSVXfytM8N8LuS2DJ4hULSUcUkRMwQdUAD2KBby041ooFbG2xauMy+WodckmayzDGR1RP40HsfzILoyG3c9/jf071XkeSB8xh8rIVsA+xZNHXMCnCwmEO4X2uC6GwWy2WqBoaeT++fWga1v9cdOu1eLhnfk+ser02IT28V5pDKGFl83KMafGHei1rXRYnyviEqh6aav+mCsfG2gVTut8hwS4jmcMjPMBUJnEIsULOAd7E1u9vFSWBL7IIVrDbI7L5ecyxIK/ihs0dlaA7SyTp8/4N2Es9/a1kE4uDy071w2gre9EwKz0aW2w82NJUBAsF8WU7jKoNFgSspl7xe4obg9MFeJ+w2vUjJphUVIFAt+j8iTDwP0FV7yvg+QSztkgWkKcbuBeTEpke1mI+O9Ca9pF5jWMmr/MLfzOR9AP4tAL8fExZRN4DAnGqlVV1eFbjxFpBvqKe7pmH6dnYItsAgTDiVap6cSP7x1drz1bVm0VkJ+BmYtkHM7Fq8S0F7MFrC5yJ0YCjTJHfgLNU9a04EbMvgU1TJb/cuFdirQtg6tJ5s8ESkacJRd0a/ZvncJ4zsf9JgDswFkLM7y6+vEHguFBDH65kOI0HvZm81xUL1Ioh7tUQVVgn8rqRbR9gPKRY1NIwEF6DUODrDowlkShQjrbqBB7W0WtoAdbH/0b+frH8wbXrrEZscN2HdDRN6rB6+3T+YXluo4ofsGfuvtjfDGw9tmYpRHpLDbcOGI1VfGuBlVQzV9QvVzjXpGOAEwkr+gHmAy8yhNd4kUAsOb7yPRXTabq7mJVlx4R8mfCZpRgj8bpSt0g1RVSC7hzhRHueIqTmzsD8vMuul1dEFsOqXyfRMAs7H6ty3Al8UfkwZQ+XkPmQUFzmWPX0wRJOqQFcMuYJTMAFbJG0kar+XaL5bIuJ+oAtylYtprJ3NnB/wyB474Qtmi8nVqzsLTZkK2poy1xqGMoHNAzqO+Y8mS7YgnmFyLa5WJj4LVCYT/McEgfl6QTuc7F2ghpgR8Lg6h6Mxl2DLcBrIl8Lkv58IF1YhSEI7bEF2+rq5U+UytlHfeReXq+q56dxzHrA11hiZhqWUBjvqJSnYO4Z0cX6CEzt/pU8JjQEU5e9gVhhpqnu/Hepao2IdMUShIEjxsaq+mUa41+LVWPBGCofpdo/E4j5NA/FbLbmAhthYUvrNL5apbnfNhAjRvSTO2fDAHkTurGDe86/hxlaNT3MIHkgPB1hGofSlxXYuv6IKbzAfVzKHKa4fefEX59xgfPBqumxu0TkHOzaBLtLHao5KuDnC44xFB9cr0Z6OiQzsYD6B+BHvmMab3A/C+r7YG9R1bPceaqw5PdW7r171dMT8/JLNDGIxCRO71TVU1PtX+5wa8GNsfv9fjQseo2klnu4lxGM5zDsKR7PwvsBS8o8FSjbFwsisjvWvx2sUaYAB6mWR3taU0Ql6M4DxJcVsExQ1B+vP0blLLt+XtfLtSNGb9mJhtW677E+kafKTWm3qUB82YxwWfYXsHKuCsr5hIhcjvXngAVCWxRagKMxiMgAwh7o51V1vxJOJyOISGfsHhAE3LXAkar6uPjyLPbABdhIPf0q7tgqrPqYqKrennDx3y7u54VpxcJsw+pswEq0ijysf2MOA5nPDNrSsA+s+WFXYH3381fAG8wnVZCe+c9dsL5sMNLte0n2X0BsiuMgTLcArI87KhTXHqMZbkrsPXg4JiT2Lw3vzVE09l53LOCO+roqpt/wNkZbDrAnoZXVt0C8+Jxg1Of4gHYbYB23z0AsmM81EA6+St0CEosuwBnu59GEPg/5Qy1hO8k8LJEf9YSuw/p8v3H7RRNZ8T8Hr6NB9sx0qKguUDgXE9gL8ArWKpVw0S8Sw+66V7XxoFFEjsIqdwFOVdU7Gzsu33BBby9ig+s+NLT+S4a/ob5q/YP7GhG/9nN/ozcJWwhOUdW73ByWwxI+7d17ZWE5Wmw4u7i/sL/DXKCnqo4v7awyh2t1OggLtvvEva3Am4xjAPeyFMpJwMpx+9QQFsEGF7sI5tYklxG2DoFdn3up6p/FnEtzQyXozhNcn/eDwP6Rza8Bh5WzsqSrJpyA0Vni/R+nYUuLu1VLY43WlBFDR4TT1dPbU+1fLMRZgylG58tZAClXuGrbb4S0qj20yHZB2UBElsZUyQNxxdnA/oFFjPhyPCZoBnCJenplXs7ry6Zu3Giy7y/glKijgkuytSVZ4J7d92TvFT/A74Zxd6qwUOU2YsPJCirIDfMIgtjT6caitKYOuIFPmM10kge8yV4nfC+RQrvzML6L2ADwZ+B4VR1cgN81PLcvh2LPiaCyOxjYTb2Ggk3Odm6q2/c3VV01fp+4/ffCekKDxIqnqv9LcUheIL60xe7TfSJfaxGb3EiGWkw1PBpc/6he+jaHInIcELRO1WLWkW+5uZ2MBVlg9/E1y0UjqJgQkZswu1KAK1T10lLOJxOILytjxawjadhyMBl4kFf4kO/ZAziM0DIuwD8Y2+t+1dI4i4hIJ6y6HVWQfxY4ulKEyx2VoDuPcBni84CrCR8mwzALjrLp804EJ2i0P5aZSyTc8C728H+9mCJbTRniy7pY1QhgPLC8eqW9aYnIVlhForXbdKaq3lqyCcVBRA7BbvgAYzCaedne6EVkDax6EShVTwR2UQ2r2a6KMcK9/Eg93Sqnc/rSGbvHnEBY7azD1Kg99UonbOIy5OkE9m0JK5+tsKRfHzfMA8B/xFZGk/98FBvT04kwfcZfvNvg2NTHl1tFtXmjjtiWgWRfURZBd8Jq/QSsdaexY1KNewixlPI7scp+omB4TrQ6LL7cjPXGA+yvnj5HgSEiHTDK7RmE16pii/OLVAunaO30SV4gpJcOA3ZUr6Fvu4gMxqi0AN2TBQ0isjV2zwyotrdiugJ5XYw6O7Q+ka+1Mam46qQHhZhObHD9A6YePjfneYlch60TwZgIm6nqT67i/h6hjdj96unxuZ6vqcElsUdg9+epmPd72fa4iy+tsAD1FEjom/0V87iXm5nHXI4Htkywz4cYhfzVUq6vRWRVjLEXVN7rsP7t6ystp/lBJeguAMSX7bGHeNAfNwNTNn+5ZJPKAM5O5iSMHtM27u0xWHXtgVJl4poSxJfnMV1YgP9TT69JtX9B5yKyClatCK7LO4HTyulm6npQ3wK2d5uuUdX/K+GUkkJE+mK0yyCj/SewYyKRE/HlD6zjugbokk3yxSX19sMWqd0jb30LHK9eadsDckFcBSilJVfMcb5shS1YwKoEK2eqzu4SBY0F5qtg/2swGvX1SfZP1O9ZjVF1g//ZrZhQWTzUjbEzJnoZZQ38AzyC0YvjjwELKI4g1m97LkZTH4hdd4mOW5/QOWA8FlDOTzA3sMpcfGB7LuYvi/s+lBTBcGPCbIng3AqGErpw7KxZeMKKSCuMjXa426TAcarp623EiWQOUE+PynQe2UJE1sU+I+tFNo8DTsfacQpyHxdf+mBBcnD9jgN2Vk+/j5tf1IVif9WGCQm3tviAUMzvMawNJ6c2PPGlK1YsCL7WJfazkAp/ERtc/wCMypc6fTzc/eY5YG+3aQymp/JvApr5DurpOwmGadYQkYeA4LN1rqreWMr5JIL4sgRmz3sCDVsR5gJP8Tmv8g4bY5XvJeL2mYkpgt+lqr8UeLqNQkT2xD6PwWdzCnCgasu7/gqJStBdIIgvy2O2F2tFNl8O9C/HPu9EcHTfo7AAfPm4t2swetidwOflFLiVE8SX1bCHaBV2E1u+FF6bCazB3sR8dcuOtSAiK2EUyjbYdbaWankxRURkf+wBFVRrvsEq3An7z8SXuzHVUrAFa0ZBg/jSC/usRS2nZmJ9+Xc0dXsZEemFeY4CfKyqfVPsbsdYZegrwiDkKPV0QIHmtxIQtNg8rqqHZXj8rli7Edgiv3cquyMRWRJzxjgi7q3XgXOCdh8RWRm4CesNj2IAjViRuWD2F0L5vX1V9YW0fqFwjEcIg9jeqvkTr4s7z/6E/fC/AH0yuXc58brHCdu/aoHDMxXtcurVkzG2xn/AksV8nrvEwamY2n37yFsDsR7h0QU5r91/3iJUMJ4J7K2evlu/jynzB6rjDUSwXBXtE0xwEuzzsE8iWn0jc+mIBdXRIDuRLWo8ajB6+A+RryHq6eRMzp8POKXuQYSswm8wIcJZ4stJGKsQLCBfs5xbFAsBd638gjG5xgLLF8rZIRO4xPdmGIV8X0LGYIA/mct93MNEpnIwoStHFEOxZ/ljWkAbxHThkkD9gSiNfwjWvz0i4UEVZI1K0F1AODGFBwmVecEWTYeVIvDKFu5DuT1Gn9mFhgI+Q7CHxBNa8exrAPFjFqaXq6eXFfX8Da3BhgCblzVlK1bo7QPMjqgsblYichYW6AR4Azgg1bUvvuyDJakAblZPz07rXEZdOwOjl0b7v14FTlVPx2Qy93KGiAwHVsQWx4s2di8RP6YVYQiwbqGSD3FJgWdU9cAUuyc6XrBEV+DLepmqXp7GcRtilfGNI5trCDUCTiS2uj4Ys7v6Oo2xzyMUyxoEbJ3pZ0xEngAOdi9XLJTIjvv7DcYUzMEq1A+keWxrjHkWVBZrsArOi1nNxZdXCKv766un36bavxAQkWUwOurukc2zMfGjWwuRTHXV5FcJnyMLsETX425Oi2B0YAG+V9V68zERWRb4jLAN52OMFZTSZ9slOdYmNsBelYZrkHhMpWH1eqh6mozFUXSISHeM8RLYR70E7Et/wNr5AgX5B9TT44o9v1JDRF7CBB4BjlHVh1LsXti5mGbTIViwvVbc2wq8zve8wiv0xqra8XZfCzDa9t3Ah2W0lumMPUOjSdungWPLua2vKaMSdBcYLjN2DnAtYT/WcKzP+9eSTSxLuMXniRitpmvc29MxCuRd5VaZLCUc62EYtjieiVW7i+KJ7harT2CtAmCKyBtqiazB0oWrBPxCaG13kKrGKyoXFS75dD0QDZgfBE5sbJErvnTB+r2rgJ/V0zUbPZ8va2LqvutHNv8DnKaevpTh9MseIjFsgF0DIbqE+5og0jDCBev20apbAea2FKZSDPCiqu6Tav8kY6yKsV6qsX7hVVQbT5q4z/DB2DMkGWX2H8y666l0FnRuwf871qtbB6yrqj+m83vEjRNV5u+pqn9lOkYG59ocq5SCUZxXajQx0zDgngfsrTn4QIsvJ2KLZ4BL1UuvFSLfiNjB3QEsGXnra0z06Oe8n9OXdphF6h6RzRcC16mnKiJDgDWxa6qTqs4UkcWx/1vQJ/o90E81tnrrEoyrEhtgr0XDamI8ZmOOAl9Hvv4sFD08n3CaIJ8T9szfoKrnOWbBT4RU3x3Va1k2TSKyMZZoA7vXr56O+n5e5+DLqhjT8wgaiu1NZC4P8zB/8x97E2sVGuAP4H7gkXJrxxSR1bBEQKCXUYc9Q24ql6RAc0Ql6C4SXC/Y04QK4TOxPu8muXh21dP9sMzfxgl2+QCj0JRUGKJcEEcvvlE9Pbco5xX5HyFtaDawpWrxKzPZQER2wyorYMmC3qWiYzkq7iPEslZ8wE/3ASW+fAls6F4uqV5i6q/40gYTL7mYcMGp2Ofp4uaqaCsie2OiTRDxsU24rx9TpX1bPd2xwHNbHKMTA7ymqrun2j/FOLcQGk89paoHp9g9/tgdsGswvjdwHHBEJr13IvIopp4LaVo8JRknWo1aMhWdPR8QkRcIA2hfVfun2DdRwL17rj2K4ktPYJR7OVg93TTF7gWHqzBfiTHRggpwDUZBv0Y1v9Vd8aUauB0LRgLcAZxJf+7EelzBqLXfYJoLQdX7d2AL+jMBY7VEA+x1aKjmHI8ajNUSDbCHqtd01xjucz2QUODtBFW9Ly658zewRgukmX9I6F++T7bslIzOacmfPbC17dYJdvmCIbzEKyxNLYfQ0PVnPqalcR8wqBwDWPesfYQwqTMZY+u1OJu6YqMSdBcRTiTjJYwuFeAKrM+7yfZkOoGXk7FqTLu4t/8hFF4r6IKsnCG+LIVlPdtii78V1NN/CnpOkSOw3k6woG1PbQIWXFGIyKuE/sg3q6ZHy87zHDpjn9ut3KZarLqdFr21fhxfrsACabAWk8cT7LM+Vt2OVsKHAkerp19kNvOmBfd3noSxAX5R1TUS7mc01z8xATsF+qin8QJj+Z5bF2xhAvCWqu6Uav9GxhlOyBLqq6ofN3JML4xhsW8jwz8HnK/aUFk6brwtgY/cyylYxT0r5o2IvEZoLbN4tuNkcL6VsL7cVlgSccVEz5VCBdz14/vyM2Y9pcDimdhGFQquMvgQVi0O8BNwVL4TrY7B939YsB/gBa7jTWYT3Bf7Y0rcfVkEWIZJ7MjTdGQVjL3TuZHTKHbviwbYQ/KhIF5uEIkJsGuBnenPuxjNPOgLflA9PbYU8ysVXELiLffya0xwrlCCgT2A44DjacgomsNcnuFpRjCKHbC+7ngMwwLtR1VLfz9IBDH7UJ9wHQLWerG3qo5MeFAFeUUl6C4yxJeFMUucgyKb3wAOaUp93ongFpRHYgH4inFvL8Cyf3cCn5Rj9q/QEF9uJKQm36OenpRq/5zO1dAa7CxVvaVQ5ysURGQ5bJHdFluMrKOqPxXx/EtjvbhBABjjwZ3RWLFK24+qp0dE3msHeJiVTNCGUotZg12hXulFZIoBEfmCsG93KVUd22AfP6Za/LB6enQR5tURa58BeF9VE1nDpDtWdIH9M0btTuTR3AGj7p5LrJL599jvL1i/d5/Ie/OwAP2aRD15Lhj9jvB6PlFV743fL4Pf5S3CPvUuWkD7qsg5bwNOcy8fUI3td3W/4zOYAjzkOeAGED/G9ukQ9TITZCsUHCPnUuy6CSqntcANQH/V/Aas4suRGH3WdAXm8zV3swFdgWWYRXfasyQheTo1RhIbYH+nXvnqjuQbIjHrg+nApvRnJnaPCCqSO6mnbyU6vjnCtVB8R3iP20ZVP8jb+JY82gJjiexNQ/eJP/iVl3iZzsxnPxomiuZhyc77gE/LeV3r1udPANGE8ZOYPkZGjh8VZI9K0F0CuA/6WdjiKFhg/4H1eZfcOiBXuN7XbbHgezca+uD+jAmvPV7OYl75hvjSDfOf7IAlIVZRL//qkNLQGuwu4NRyfiCkgohcgin/A3yKUeQL/rtIGh7cGY0Xq3z8L7CUeqriy+ZYb/jKkd1/wKrb3zcYqBlDJIYNcISqPhrzvi8rYNWv1lhf9EqFZoy4ebV154M01dVTjFWNOQkEvfpnq+rNce8fiV3zPSKHTgAuAh4OehvdvkdjFcdukX3/xYKvAdE+SBE5EwjO9Q2wcS59kiLyPiEFs0MxxHdEZDGM6bAI1oe4dtC/nCDgngvskc+AGxok0J5QTw/N5/i5QkTWwarefSKbh2GCVJ/l7TwmMHUSxthr08juUYwjNsD+phzYAqWE+yy/SCiONxrYiP7siXmyg9HM12zqBZpMICIHYKwVgHdUdYdU+6c1pingH4qtUeMZVXXM5Q1e4neGsSmJ2yd/wQLtx1WLr36fKdxa5mVCp4o6LGl4c1NdFzZVVILuEkJ82QZbIARUw1nAEeplZttSzhCRnhhd5zhiF4Vg/uWBT2GTE5XLBuLH9FjHVDvzMr4tSL8gvLmWrTVYunDVm58IBT+OVNVHCnzOtD24MxrXlzcIM80bYKr2pxL2Ys7H6F/Xq5eZlU5zgPu7D3IvH1PVw2Pe92OEu65QT6M2J4WcVzWWKAOzSExEL8xkvA0w5WLB7oO9sUB5R6xXPboQrMEq2lfEi09FxuuE3VdOJ1Z46idMHOdtzGd5GFZ3VIyq2ajKeSO/x0fAlu5lWy2SrY+IXABc416+qao7FyvgBhBfWmOtEB2xZFz3cmsRc3+P8zFF8yAgVqwf++LGROgajJetkngtM6nmC2KD7H+agtBZsSEi7TFl96AH/ks60I9zeRUrZEAZJnkKCTGbvGGEdqfrqep3WY3ly+pYoH04IXsgwASG8iqv0oY57EFD4bQ52P3lfmBwUwlWRWRfrM0wsBichLH18sYYqCB9VILuEsOpVL5EbEb6akwVtawe4rnABU77YDSeRMIzg7CK7MuJqJbNBeJLJ4xG1wXLNq6hng7Ny9hWjXuPsN9oCLBFqcTH8gkR2R4LHMAqfquo6pQCnSsjD+6MxvZj7MYmEyvC8gVW3c7L9dAUISJtsL9LewI2gHtIiS+bYEq/AOOBFYtJPxWROizA+FpVN2xs/zTGuxdLSIIlx1oTLqwDvIL1af9OGhDz7b6eWCspsPvCfEKf9/tU9QRyhIh8DmziXlarFsezWkTaAb8RqtfvjCV2Cx5w18/BjxF121g9/bJQ58oFTqX4QWIrdqMwW6D3Ex5jYmmrkamSuBKbPvyMd+nHjsX0Mm/qEJElsYRcwLB6ngs4l3b8SJgEPlA9fSbhAM0QcS05z6rqAan2jznWEmR7YsH2Vg12mMMXDOQXfqYPsF6CIYZgukRPFqN9Jl9wieIrsFaTAN9j/tujSzOrCipBdxnA9Xnfh/kABngLOFi9wgQWpYSI9MFugIfQUK30X+xvcV+ifs7mAPHlQiyxAvC8erpfqv3TGtN6nx4n9Mz9F6tkNScf5+cIxaTuUtVTCnCOeA/uN7GscF785+MCxwBzMNrw7c0p0ZYtRORNrOILllz53bXkfEqYsDtJPb0n4QCFm9c8LBHzg6quk4fxumKial0SvP01cG5jImspxt4S6+PdIMHbUzEBsknZjB13nq8xmnydqlY3tn8+IRLj0z6NMCApeMANIL4cA/WiYf9TT71Cni8XuAX46VgbQlTs9AHaci4XshjmrBAE2OvSuJL4AqJK4s+zHCO5mIMIw8U66qjiEPVKa/fY1CAia2P3u6Aaew39+Znwep+K0czL2vozX3AFhVGYc0Md5mQyPOUxJl4bCKP1iHlTmc3vvMVAYDo7EFaBA8zCrPHux5KsTSpQEpFFsX7tKBX/CeD4Sv92aVEJussEblF5BrZQChYvf2J93nn32ywHOLXiI7AAfOW4t2sxBsCdwEdN7aaXCuJLe+x/G1j/rKdednSp+jFFfIxGCE3MGixdOFGz37AHpAIb5Ot3lMQe3A9hQlN5YV6IL7thvXlRT92PgGPU0z/zcY7mAJGYpFRgnxO1E/sNW3AWtWVCRGZi115SZfUMxlqEUCQtWj0chalCP5tr1dhd0/tjf8tekbdqsGv92lxZMCLyPcbSmq+qCzWye17hfr9vMKupAHOxdpqCebbXn9+XJTF3DrCe5EQJjrKCiKxIax6kO1uyDLAMsCx1tG+guxIPxT53UYr4j4GSuIgchC3qhdbAviirxNDOz1FPb6KCtCEiOwOvEWriHEN/tie0rfwA2K6lsAjingsJmTpuHd0XY1TuRbiWNsxhOG/zPT+yKhrjEBLgWyzQfqqpMgRFZE2sfzug49cC5wC3Nad1dFNFJeguM4gv/YBngcXcplnAUerpc6WbVWHhqrTbYMH3HjQUXvsBuAV4ulg9g4WG+HIacJt7+aZ6unOq/VOOJXI45rkItjjaS1VfyXGKZQmRGH/mr4BN8hCcJPLg/h+m9pvzDVJ8WQzryU3kybyVevpRgu0tFs76aLB7+ST9OQoTrgkcEfZQr/jWdyIyBVOv/V1VV8lyjNZY5aU/4T0+iv9T1WsSbM8aInI+cG2CtyZg+gH3ZZtYEqm3zpqlqvE9kgWFa0V4H9g8snk3VX29aHPw65MOYH3d/6XYvSQQX7pjDBH7UtZDGhU9G0VDJfGEQYgLDl8hVH6+miq2Zhc2iiPr3gyc21KCxHxARE7FevABFrAY+3IqdxByCc5WLxRhbM5wuhV/Yb3W84Fe6uwCnd7AgcCZxLZqglLHcD7mTeYyhS1pyOCYgVWF72/qhQrXGvcw4e84EWPqfZj8qAqKiUrQXYYQX3piKpbrRjZfA1zS3OmnIrIMofDaEnFvj8P6vu/RAvvBFhruIfE7YU/i5uplrirrhKfeJayWxSghNze4oOUHrN8QXCU0h/E6E+vBXYdVt+/PfpZubMu67wfcQayI4BCsPxLgcvX0svhjWzLc/3gKVlUei8c1SH2C6iOgXylEmERkPPZ/HKmqyze2f9yxgvUVXkMsq2c+lmQ9BOuGnYVRJ/NCGxWRpbAKZQcsIfckVv2OVtd/By4AXsk0ySQiw7DfZ6qqJqLJFwQu4H4G+5tGcYmqXtnwiALNw5erMGYCmAjqo6n2L8J8qjERvk0jX6mv1TmYJvbfwL9MYxbn8A8PpXMtiMjmmDVlQFm/F1MzvxE4i76YU3eIZ4HDW4oFYj4gIrdirQEA09iZs9iQh9zrecD6zZUNGQ8RuRYTBwS4lv7cCJyIFWy6x+w8m/F8wPd8Ty9qSZQk/QprZXwmX+1jpYJrH7kSu48H+A4rwPxVmllVkAiVoLtM4Xx778NsDQK8AxykXvlbFOQKt6jaF8tcxtP25mK9TbeoNl2LtbiewIyDiQTWYHcDpzR3CpGYB3mQuZ2C9f1mnISRhh7cc7CscM6VMvGlB5Yg2jOyeQrWQvIBtsQF+EI93YQKYiAibwPbsxBwAVOoqr/GN1BPvynRnP7BWgP+VtVlMjhuI6xtaPO4t54BLlLVESJyJ7ZwBHhOVffP05yfwipAYMnKk0RkeeAqYpkdYD2k56qmLwgmIn9iQd1EVY13pygIEgTc87AkQhUwE+tXL0rF2dn9feJePqOeHphq/wKcvxPmax8E2BvTuCv275iuxOfU8jlXsj513EystsBL2LPk36Tntr7jjwh76Z8FDlbVWqeYbOy87RnIpuxISPUdBOzVkmyvcoELqF4GdnWbRnIab9OVE93rIcCGLSGRISI9gFF0ow2bUkMf6hDCthYF/mQobzORCWwAtI0bYjomknq/qv5YtIkXEK5/+ylg+8jmx7CCxJzER1VQKlSC7jKGq5Sdhgk7BQ+sEdgDa0jJJlZEuArRppiv+V40pJ6/g9HW3m5qwab40gr4ldAKa3v10utFTGAN9hZGrWyy1mCZQEQeJxQefEhVj8nw+EQe3LtmEnAkHNc+s0dg12TnyFsvAqeop+Pcfr9g1fo6oGtlARoLEbkIuJJtgC3qNz+lniai6BdrTqOAnsB/qtq9kd1xwe3VWGU5ik+w4ParyL5dMFucIHDdIVchMBHZGqNfg9nErKwRT9l0kgFpnOMvrDP4X1VdsrH9c0WCgHsusBvmjBEEIXer6skNjy7AfOwePgH7rE8FuhVKa8DdW5YnDLA3wxKGqSy75mL08M/d12D1GiYoRaQ7liTcK7J5Kpb0fjT+2eoU0T8ibJF4B3v+zHfvL0WYWBxEf27AgvKA9vozsFNLEQLLFSLSAbtv9LENfMFFdKQ1q7tdrldPz09yeLOA+FIF7MA47qN7/XPbMJs6PuUnvqYTNTH6FQE+x4pYzzUnITERWQtLyCznNtViujS3N7X1cEtBJehuAhBftsIeWMGCbDZmLdRiLCMARGQ5LAlxLA2z+UOxvtnHmtJNVXw5CKN8gi2ONmqs2u16kN8jXCz/BGzeVIU/soFbJA4j9NLcTFXjVcGTHRvvwT0C8+BOqYba6Li+LIs92KOKoeOxYPv5uH1vwareAHurpy/lcu7mBhHZlE58xmkEnaLzgVXU01ElnNNwrK98sqp2TbHfosAlmP96PI37fODVRAsiETkS68cL9l0rWw0LF5z+gPkog9lDPZhgP8F0NK4llvZeg7VFXBEN1BMc/y9G6/xLVXtmM9d04X6nZ7H5ggu4VfU9EVkC+AOj0dcCq6vqsELOp35evjxNyBrYQj39NE/jtsVazIIAe1Ng8UYO+xf4DAsyPgN+UM8C4UbPZ9fCvtj/PXqet7Cq2V9uvxUxL+lAEXowsJ2qzoobbzTWPjUb6ER/1gUGEgbqfwM7qtd02WrFhGNmfUkgxNmetzmHflTRBqvx9muO+iDO3ecwLAHUu/4NBf5A+ZjfGcNy0ECnYArwKFbVbnbXmIgciFkBBomsCcB+qs3vGmhOqATdTQRuQf8isT6C1wMXFVvFt9Rwyr9HYUHLcnFvT8L6yu5sCpZjLnv7A9Qrae6lnr6cdP+G1mDjMGuwFte3IxIjRvcjsH5jlX5J7MG9ay50VPc/PAETeIuKST0OnKleQ2sm8WVXTJkW4C718m9/1pQhIm3Ym9ms5Rg+yg3aX88r8Zx+xYLYGaq6SIL322KB9sXEshwmYMJp96cSLHNq3B9jARbAxap6VZZzjQoOfoElpZIKWLk++uPcPKM08amY1+sdiRIAIjIBC6JGqOoK8e/nC6kC7sg+lwCXu5d5o+g3OjdfjgAGuJfXqKf/l2L3VON0xzzPgwB7PRoGElHUYfe9IMD+HPgrV70DZ2V3C7GtbTOxhNFbWIU7aK/4FthGVaclGCfa2rCeqn4nvqwIvE3YZz4V2F09/ST++AoaQkTWxSreFmitzPsczDbu7b+AtdRr+L9oinDuAKdgz9YwyTkL+JL5fEUb5iY89GMs+f1ic6RXi0grjEF1bmTzN8De2owsYpsrKkF3E4Lr874HODyy+T3gwEQL++YO1+u0O0Y93yLu7RqMhnizam52XIWG+LI7VnkFo931SSaYF2cNNgezBitJj2up4R4+XxOqlZ6hqrel2D/vHtxuEfkgsGVk8z/ACerpwBTHdQQmY3Xc4eppvGVei4b4sibKEAS7ygeyjv6kP5R0TiI/YgJ4c1W1XWR7FVbpvIpYa665mKDUdemyUFyf7HdYG80cYFVVHZ3hPKPWenWYtV5a90CX0LwAoyhG+yFHYV7yz0SDdxGZijFGhqlqbwqAdAJut18HzIoxqNKuXww1YvFlcSz5KcCv6unqjRwSCJ6tThhgNy54Zl7kgwkD7K/UK5wAlIjsiq03lopsnkt4XfwE9NMkfu9xSdHTVPUOAPFlCeB1zN8drCf/0Hg2UAWJISK7Y5RiayvYgd/YpL4C/Lh6eliJppYXiC/rYmu6AwiYQnXYHegzJvAnXQiV8gNMwhxI7lfV34o22SLDJcSeBraNbH4EOKk5JhiaIypBdxOD6+s6FesZDfq8RwP7qadfl2xiJYaIrEd4o46/IX+M/b1eUy0/9Xf3P/0C2NBtOkQ9fbLBfiKHYXQpMHLV3qrJq+ItASKyCbYABRNJ6R0v/iMF8OB2i+Yzscpau8hb9wHnp1NtEF8+JkwW9VIvs+CqOUN8eRXr1bVu0c85WlUfTnlQoeck8i1G961V1VZuW1+sL3r9yK6KLYQuzUaFXCSm9eAlVd07w+OfIewjv1NVT81iDktjFe7Die0Z/hrrR//Y7TcLq7r9rKqJfG9zQpKAe1dVfT/J/lGLpXdUdYdE++Ub4sunhAyFldWLbVURXxbBRM4yETwbThhgfw4MLbbdlrNpuh5jQUQxHujTiNDaelgFDsz3uF6PQXzpgP1fd3KbFDhDPb2dChqFiJyJrWkAajic+SxPe/f6wKbWeuiep7tjz9QwgT0N+JE6vmQ2s2JYZPE4VFWfKOgkSwwR2RATJwwcbxZga947K/3bTQeVoLuJQnzpi30AAypgDfYBvKsUdjrlAifgElCSFo17ewTW9/2wqs4o9txSQXzZFrP+AutNXE29MCAUkS0xVkPQI3qOqt5EBYjIA0AgpPaEqh4aeS/vHtziy+pYdXujyOaRwLHq6QcZjHOpmwvAcerpA6n2bykQXzbFgg1Lo9wGLOBRVT2ipPMS+YLwf74q1ge9e9xu7wLn5aKM6wKd3wgtcHZW1TfTPDZ6H5mAKftPyWEufbCga9u4t17FKuI/YhTo71V1XfKITAPuyDHDCBkHW2sRPGrFj6Hzn4epf0dtu9aE3AXPSgFXXfuahq1cXwLHJOuXdS0LU7GkzGhV7RXzvi+tsVawoyKbrwP+r+LlnRquzewOAseDamZxEu1dt/xUYM2mIFLnGF9HY5ZoxvSowe5+31HDyBhNjADjsXaOnwmLEKaH0wwDGve/PgVj6QV/j/FY//bHJZtYBVmhEnQ3YYgvS2OLkqjl0NPA8eqVV1BZbIgkEd8wTMesum5XLZ0wUxSu2v0BoV90fRAmIitjlfDA0uUe4OTm+IDJBk7JfRhhkqWfqg6SPHtwu0XiBRi9P3j4KRYWXqxerJBQGuNFq/RFtxsqR7jPwYdAXwBeo4ZvaU2CRXuxISKfEIoX1hIyjcCotuep6tt5OtchmCYAGGV6DVVN3MEYHtMGsw8KPGmPUtUBeZiLYOKA1xPa60Hs3+BrVd0w/tgcztkGSyoHSY1GA+7IsVFG0JfAJoW8VzrBsz2wZy9Y2JAoWIgiKnj2OfB9uoJnxYS7h75HqCUzA9OtCBII8zG2z7WJWEMi8iHh/XdpVf0n5n37vPvApZHNT2BCsWX39ygnuPaqVwnYAh2YyUl0cPXu9zE3lLJMXogvvQhFcRdBMVm9H4CfqGN+A5casGTifZgQ5Xx3X/qOsL1sc1X9rMBTLypEpCNwP7FFg8+BA7JhUVVQelSC7iYOFwhci1W5AwwD9qmogtZTi3fA/j7bxb1dh4nT3QwMLnUQG1PhgzHAyvSnA9bHt6Lb/ja2+GxR4nmNQUSOx6omYDZsu2BCZXnx4HZ9Zg8Ba0c2D8MWh2mppicYsxVmVdbJfV+iXBdJxYL4sgMm1gQwnP/xD3X1i/blSpUkc0m8n2jYdzsWCxgeyWfriltQDiKkWnqq+r/kR4CIXIgJ7IAtzLZIJZ6WxZyqMTu8ywkUlEP8hfWf5+wckSDgnoP1cDcacEfm+SPU2yntqaqvpDgks/n50hlrC9kSq2KvT/qCZ4HoWc6CZ4WG65F/hzCp/y/2Oy+BMX1Wiez+A3C0qn4fN8aVmBYAWGUuYd+2+HICZlkWBFvvY64OLcaRIxs4DYZPCYRYl2I+R9HGNdidpZ7eUrLJxcElWDbB1mJ7A1VMw9KEP2Bd2Q0xEqtqP5ro3i8ih2NMNoAXVHXfPE+7ZBCzNX2e2M/ZTcCF2bbFVVB6VILuZgLxZR8sKAhUdWcDJ6qnj5VuVuUFdxM7E1NlXSju7a+w4PuFUt7QxJeBwM4A1HAOV7IXYXXtZ0yFuLIQiYNLrgwm7IufRmgJlrUHt6tiXYYp9wZVvVqMBvk/9VJXH9MY/yVCz+H11Ctv0b9CwqnAf431TQMcSH9WwSphAEeq6iMJDy7UnCyAOxzrb44GmjOxZOfN8VZJeTz3GthytBqr9K6uSbyzRWRZzDZxYSzIW0+1MMJzItIe00c4n1i1/n+wBMSj2SYgcg24I+NExSl/xezXspuTL4tiQXZfrGrbh9RUcbAEzXNYgF1QwbNCwCWZBhJWqScCfVX1V/d+W8DDqPTR++K1wOUBK0NEdsFE08A+K1Fdjdhz+hKwBQKhth8xL++kfeMV1H/2vyRoR1kTC2mFecD66unPpZtdfWFoX2zttWE9ffwHjMPTELMwBucA4NNGXBfaYBJrPbD73oqqOjJfcy8VHFvnXkK9mOkYc+nF0s2qgnygEnQ3I4gvK2GZsbUim+/DBEpyCg6aE0RkceBErB9qibi3/8aEeO7PpRcy67n5sg5GmYK5zOVG2mIpgBZrDZYunHDP18QuiLP24HbMgweJbU8YAhyVr+BYfDkZuNO9vFA9vTYf4zZFiC/7YYstsCXZevRnC6ziCzBAVY9KcGhh5iMSUKoTCYStpqpDizCHG4Bz3MvXVXW3JPs9D+zjXt6uqqcXYW7LYZ+veAzBqPbvZDheXgJuN5ZgAW9QpT1CVR9NcUh4rC9dsYruVligvRapg+zhWAV7LBDYhb2qnu6R/JDyhdPBeAVjiIH1CG+VSKfA3XMfInbN8RtW9R7s+sEnuu1fqurGKc9tLTevEVpEjca8vJutInU+ICLrY4KxFqT1BfoBlrjYSL2Gdn8Fn5MvXYDjgVNRlq6nj/+M6dU3xIdYoP1iJo4iInIxlhSFRhI75Q6XzLqNWOHCH4F9VfWP0syqgnyiEnQ3MzhbsdsJhaUAvgf2VS9xlaSlwi0uDsLoTmvFvT0bewDcqqq/F3VevjwL7AdYN92nLdsaLF2IeXA/RUhRnIJRXjPy4BZf2mMP8TMIF9s1BL2Leew1FF9WxmjqAO+pp/EtEC0Cjmr/CxBYp+2snr7pFiFTMWbKSFVtzFYp97mIrIUF29vHvTWOUNxsyVTKzXmcS0csiAmq7Lur6mtx+0Qp+eMx8bSpRZhbF8z2Ljjv4nG7vIMF30PSGKsNljAOkgpZB9yRMfsSJmxGY3+Xhl7jvnQjNshOpcKuWFLhIzf2Z+rpeDdOFVbt7+7mv5h6udPtiwknfvYcoXjdDMyHO6kzivvfXYCxHKJaF7cCl2AK5r2xe2gnbcTaSHxZBbuee7lNk4Hdsm3jaSkQkT2xdjl7Zu1NsKq5Tj29oGjzsGfaGcCRTGPhXOjjaZ3PNF3GYAyJGZh2QJNjA4rICthnb53I5gcxu72KHVgzQSXobqYQX47CeqQCqtY04Aj18tfb1lzgqiJbYcH3rsRWNRSj2d0MfFiMvm9ZQ85jH66rd+p9mEP1v+Zth5ErnIXKTTSsSO2QScVNfNkaEy6JBndfY73beafpuT63UZgNyDygi3ot7wErvhyL/d0BPgH6Bj2vIjKIQFgNehaK7eFssi7H+paj19E3wLmYgux+hZ5HgnkdQCjSNQqrss9x7y2EUZlXcu+nXdHNw7y6YcE2WHXyJsw+bb3Ibootqi+NF9GKjJMo4N5VNX0ngBRzfIuwYnu6qt7ufKKjQXYqX23FQoZBWKD9iXo6OdnO4st9hFWqPZvS89a1UjxJaDc3G7t/fprm8WtgVe8NIptHYEnFwBpsi3TGE1+6A28QBiBzgYPUa9kWmY1BRM7BPoNG+j8c6IkC/dTTjwp2XnuO9QPOooZd80UfT/v8IvdiVXWAs1X15lT7lxtcwmQAYUvcHEwsd0CJplRBgVAJupsxxJe1sMXMSpHN12NKyxUhhgQQkZWwLO1RWH9kFD8Ct2CeowWhazlrsHfZkzb1mpxwhXp6adKDWjBcL/d1hBRcMJpdIEA1HFizsf+X+NLJjXN8ZPNcrHpzi3qFE64TP8bybHv19N1U+zc3uL754cDSbtPm6oUqtCLSH+sfBThcNb86FU6M6HysTznquT4aows/o6p1IvIEEHgNr6iqiZeUeYZLCr4HbO02Xa6ql7n3LgKudNs/xRgxRXmoi8iSWGUXnJ+4+zweCFwF9IzsPgcLyq/ViF2jSxo8RwECbjf+unTgW3oByzOHPoymqoGbRRR1GDNsEBZkf6pe+m1G4sf0MD+snh6d3cyLC/d/exgL08ASgLtk0UvfCuvdvZww4R/FBap6XYLtDccyO6kXCAVQ64BT1dO7M5lTS4K7V9yNWaba3exYoCt/AWupp9Pyej5fFgIORjmTv1mrEfr4ICywfCET+nha8xBZFdNuAEtMrphPYctCwTFLrsKSugGGA/uo6k+lmVUFhUQl6G7mEF8WwSgqUVXHT4ED1NOxpZlV+cNRJ4/DbC2Wjnv7P4xFcI+qjo8/NodzroRZgy1KZ+B06qiiCssMLx/QGCswuAX7AGyRH+B/QH8s8A4E6C5V1StIArdQvhdYKrL5Y8x3O+Ne8Ewhfkwl83r19PxCn7OcIL6cDdzoXr6uXmzfsoj0w+z0AB5U1WPzcl5b8ByHXS/dIm9NxQLZOzRi0yUiA7AqOFjbQtH6TEWkN0Zrbo3ZNK2O0XWHYkvrWmDddKjceZxTT2yBC/Csqh4Qea8tcCpGL+4UOWw89vd+AGsDyXvALb4shVWwA+GzlVPsXotpaAwiDLKzDkxcAmki0N59765eeS/+GwRqdl3tqapv5DDmSti6Y4u4t75Q1U0SHJJ4HF/aYNfKYZHNVwGXlLv6e6ng7msDCZIVXbGU7sI8rp4eluLQ9M/hy+LASUzjVIawWCP08Ucw+nhBBc5E5E1gR/dyX1V9oZDnyxUishT23N88svk54NimSI+vID1Ugu4WAEf9OQ2jHQU9V+OBg9XLvmeuJcA9wPbBqOfxPrTzMC/dW1Rzox67IP9LQlbCO1zGSKrqF0I3q9d0BULyjcY8uEVkTaxiFSg/rxb/0HeCSTcTu6CbifUn3lMs+y7XU/ofRmn+ST2N1xdotnBJwRHY0lCBPurFBo4i0g4LhNsAf6rqivHjZHROCzJ2x5SWo3YsNcAdwJWq2mAJKSL3Y3UjMDXsolYiROQa7NoE63mdA+zlXt+qqmcWeT4rAIG4zxOqemiCfbpigfcpxHpX/461PAVU5KwDbvFlGWKD7OTXRx2gfEM17xP2ZM9Iun8WED9G1G5L9fSTfI6fT7jPwk1YdRosCbGfqr6Uh7GrMMHS68C5RxseA85UTU7TjxnH1i9XEorUgQVyx1UYe4khIp0wIUFrneiJPeVacYB6+myKQ1OP68uazOUchnMwP9CaEdhdOxazsOBxAPBJPujjac1NZHvMUhXgM1XdPNX+pYSIbIPpzwTJ3hqMrXdHsZhKFZQGlaC7BUF82RjrpVnGbarDaJtXtXR/4HQgIoHH5D6EYl0B3sMCuDczvWk6St4bhDS6X4DN6E97rCuqLRbgr6ie/p39b9A84Hpv36QRD24RuYnQv/41Vd29/j1f9sVUw6PiT+8Ax6unows192QQX74iDECWaSn/Z/FjqONPqqeHJNxP5GPCqtkyqtn9fURkQyz5GF+Bexa4KBVlXETuAk5yL9dTLa69m7PqGkp4/w4wDuitml/qaBrz6e3mA+ZTfmSKfVfAPMT3S/D2PGAnVf0wrfP60pMwwO5LQ+/0KBYAXzGEhfmRPowB5nODqp6XzrmygfhyGBD01d+onp6bav9SIs5HW4FDVPWpPJ+jJ6aLsFhk83/AKZlUI8WXUzFl50Bv4T1MILao131TgYj0whL59oxbG9iTKQhrqpdYXyHhOL4IdezECPozlA1KQR9PBy6B9BOhRsOGqQQASwGXiLoIY+QF1/EYLNGVsaVpBU0P8YFDBc0Y6ukXmAdukA2swnqvXndVvwpSQFUHq+r+2CLvRsw7McC2GKXrRxE51FXI08UNhAH3REy1d5qj/9/hti+E9Re3aIjI2pgfdxBwTwT6xQfcDv2BQGF6NxHZTXzp7ipRzxEG3FOxHv4dSxFwOwyM/LxT0r2aEVyFP+jFX4D5oSdDVASob9K9kp1LZDkReQpbhEYD7s+ATVT1gDR6tKNVtUw+33mBmh/4WQneOrfYAbdD9G+QsuKoqn+6e+eWhIrnARYCjnNBQgzEFxFflhNfjhRfBogvIzFK+yPYZzY+4K7B2qeuxO6pndXTzXiR3fiTeZjvwKkucVcoDMQqxgB7uEpt2UFELiEMuAGOyXfADaCqozEl8yiWAJ4XkedFJN62M/E4nt6BtckFId+2wOfiN7xuKgCnBr47xvQyRZrP6QIMcEr7KSG+tJaj5DTe51/uZCCPswHfEhtwVzEGe84ur6r9VPWRUgTcAK7YERVQS3SvLBmcyvpAbM0d3BPeAtapBNwtB5Wgu4VBPZ0I7IwFcEFFdifge/Flo5JNrAlBVUer6rlYr/cZxHrVronR54aLyGkiEi/GFgMROcaNARZ47BtHg74Ws8EAOMbZqbRIiMjO2II6WDCPADZN9sByfVEhJb8ND/L/7J11lBtlG8V/t4oUd22B4u7u7lDc3V2Kw3RwLc6Hu7s7FHcp7lDcXavP98fzzs4km+xmd2O7zT1nz0lG300yM+995N4RvEta+gnuRzuXRXZljXsEs/2Ta9VsFNXF4UCf8PpSi1okvU9kXpdMuiVNIve6fp/c3v+PcFOdZc3shRIPlxXTqzrpDridtKQb4AtccboW6JF53WqZb9BgOASYNCzKXm9bAB9IOl1baUHF2lGxrsYJ9qe4yNd2pDZSCUbg+gvHAivjJHtZi+woi+xRi+xvgFAZcW7YZxxaDvB0CEHdPCkp7w/MWalztRdB5fq4zKK9zOyKCp4ya/c1LPN6I+BdSVuFTGWLsMhuxwUFE+/vuYAXFSu/9asBIDwb0/apR4APWQVvNywIrabJtJSu4Er+4CrO4WmmyunX7sYIunMtsAJj6GdmcaX7tduA64Afw+tNJeVXBdUEkpbAtSOSnvMxeNvN2oVamRroumiQ7rEQFtkYi+x43Ic2uUHNADytWPvUa2S+3mBmf5rZObhQzwBcBC1BX7wU7nNJx4TexhxIWgYXsEmwl1murUcIkpwW3nYHTi7jv9BpIGkv3JYoIWkv4oS7NaGzm+geJsAjmIJnmCQs/wknYRtaVHm/5RLwKum1uEpQhe2yUKwZgT3D23/JJQCF8DwpsVuh1eNL40o6GG/POAjvBwf/3vcG5jazO9rYClLTTHdAP3LLy6elZaGwSiL7GbSo7h8I9624JSP4d74aYh8m41cWAgbQiwM5iNl4DRfh2ga30stiOB6AGYRbFE1skS1vkUUW2eOt+GKfTFqdtKOkSn5uWauwDSp4njZD0p4ktlKOg8zsggqf9iWcaIB/B5uTEudJcW2UW4MNXYsIft1L4FZk4BVLTyrWRsX3GnthZrfi14vjVuAHTlWsJqs8SdJ0Wk0z6WWe4keeZ3uGMU5OWKwPb9ONHRjDZDbKtjGzJ6vVr10qgvBlMqfqjt/rawY59sUDg8l9+wdgNTM7od4+vwYqjwbpHothkT2K+2Amvpk9caJ4UxA4aqAEmNnoIDyzFJ6FeyCzenIgxsn3mUnkNfS53U46cT3PzC4ucorBeN8mwAaKVbcCIeWGpO6SzsbL7JP71a14Sfn3rR5gEBuwG3M37fks8DX34tntm+pFATdoKiS/mz7kKpp2RUR4WTHAua05KZjZP/jEHWDWYFfVDJJ6StoVz2SfBk1Blv/wnuL+Zna+WbsEmOqBdJ9F+rmBZ5vPKyVLWAGUVF7ejHBPzn9sw/8YxI5EHME+TMJ6wHxA/lNnNCMwhuCZ6eVxkr2iRRZbZE+0xdM+ZJSyAcxjS923HciS7vUreJ42QdIOuJZFgqPNbHClzxtKjt8Ib+fF73Vzkbo2gAeu35F7Frd8PK+KWZK0AmYc4FbFOqSRNCiI4/Br0GtDbqAXf3OjptFMmlgn0Yef+YaHGMYiDCf9/PrwL9NwBd2Z2f60eW20XVmr8vE24AIIjSSwq6Q+LW1cKcitKG/CWyuSe+UzeDl5Q8B4LEWDdI/lCIIaK5Eb+d4EeFmx5q3NqDonzPGUma0FLICXfSa9fePjCrGfSroW7+VJovqP0UL/USiRzJZDnjY2TCzCw/JOYN/M4pOBzcxanmwr1iSKdQ1wO1MyKUuFFaOBS+jFoKYsSz1hrCgxV6w5gO3D29/xFopSULSvW1I3SZvjXq1Z+zfDRa1mM7MjOtj7nCWWPYpuVSFIWgfv0QQPwn0RXq9CriVktdAq6ZbUm0m5j/lZhw3xmoO9GYdZOBAvKZ8mZ4dRjOIT/I54OXAivYiZnkF8xCCesSi1cGsnzsIzTQCbSVqog8crCIvsM9ziDWAxxYWDRNWEpC3wCoIEJ7ZkpVgBJCXmAhY3sx/NbAt8vpHcj6cA7pB0dXCoKIrgn7463t+f4BTgYsVt0lTp8ggZ1e1RCHz8CpzHPHzPp/zOYfzVFJz0q3oWPmVeduQv+tg3tqONqpvy8VYRgvFJy83EpDaPVUNwT3mFXOHI04CVzBpWvWMzGqS7ASyykRbZQNx+JpmUzob3SlX9htUVYGZvmNlWuAXY+SRiJj5Z3wqYI7z/ClfebrE8E+9pfDe8XgLPCnRZBKGjp0nLUUfhQj+Ht1aSpVir4yqmqYXRMtyDSBSvVyO3r7te8DBpCWaXJd141iV59pwaemBLwROZ18tDU/neWnh5/g3k2kXdDcxvZtuZ2ZcdGzJQw0x3sE07J7PoQHKDUWdKmqCaYyI38NB0/1KsCRRrHR2j89ifn9iXldkQV09uPsK/cWHPI4Cl6MH4XMN8PM3dfEESspwV/25flbRmR7L6IUt3QmbRCcW2LQOy2e51i25VBUjaENcaST67s/Ce0moi29edhEGT8ud5yP28tgHeDjZQRWGRjcAF9bL/y87A/YpbJu1jE8I1My9Gam36L7mqCn0Zw/I8yqbMbR/bLPamXdGJy5/PyrzeL6iGVwWStiPX/vV33Pf+kHZWWDXQhdCwDGsgB4o1C67svGBm8aXAvm0p5WsgF5KmxMVLDsZL4bJ4Go/Q399Sj6lirYP3NYOLKc0dJh1dCpIWBO7F+1XBH1obtVaSpVh98Gjy7pnFv+Of+7UMYgO8pB/ga2BOs/J69HYUivU0aWn5LBbZpy1t39mgWAvjGQBw26BZErGrVvd1y6zfcLL3PrALXjKeX4r/BG7/9XwZhpw9/8Gk5cmbBLJQFUiKSPsyn8Crk8DvB2uH16eZ2SFVHNOawP10A+bhUgbwJZ51X5LilQB/4/e7J8Lfa8W8loNF40k0F857GjjczJ5t57h74/3AfcOiFfK1NMqBvN/6gxZZTVwJQlDqTtJA0YXAntX2Aw7q9EnG9GEzWz1vvXCyfS65jQb/Aw5praxZsTbHLauS9ot3gXVC1cFYCUnT4Z/p9kBhEdbZgOW4iOk52iL7seA2nRCSHsXFFQHWM7N7Wtq+DOcbF//t7pRZ/DoujtulnuMNtB+NTHcDOQi9UksB2f7inXFrjllqM6rODzP7AS83zCfc4BZG99K63dh9pCW2/YFdyz7QGkPSuvikOiHcn+GWTq0R7mXxnsEs4X4EmNciuyb0bt9J2jc9HRVUMO4AunqJ+YmZ18eXSrihyTIr8V2dA/+dZAn3q3i56UrlJtwBNcl0S5oZV3oHzyjvHVpZDHc+SEx8DpBScaSKjcdtvGZjC9ZnM1yPfAA749oVy5Il3GOArxjDt1yNk+dJLbI1LbJTLLIXixFucItGXCxtDVz5N8GywDOS7g0Wgm2CmQ0n9YYHOKlCPfGvQVN1zUqKq16JgKSVydUOuQoX7KxFtuVzUgvHJSR1z64MP+mr8az3o5lVe+DPxqzVXzNYZDfSXNn8hbHNlUXSRJJ2DKTzSzxwlRLunuRKMX4M/E6/rkS4A6pmHyapPy72mSXcF+Nirw3C3UATGqS7gWawyP6zyHbDe2GS7PYCwGuKtWHNBtaJEbK32d6zw4Ed8YxdghbtxgJxHJhZFHUVwbtQJrwfTozHD4ufx3v/3iu6X6xxFOt0PBiRePb+gytjr25RWlYcJpr7kJKU/aW6s2DrsqRbsVbAS/vBbYOKCQcW3t8nNhMVWPUB3ju3qJk9XEFCUavy8rNJs3dnmdk7yQpzb/GTwtuKiaop1hSKtbliXYp/dx8wO7sxJ83DiH/wNy/hElmn8g+XsrJdaNtZZE+1tTInELGHgEWBTYEPM6vXBl6XdH34bbQF15K26yxJBcq/w/06KZnuRWoXVBUEd4y7SX87N+EtOjUpGQ7XZRIMmxAnxYW2+xK/T+yJ38vB7+1PSjpdUqHAte9bWNn8CcWqheZB1SBpHEkDJN2GVxBdhmd503tBX1zS7yA+YCd2oA9XAh4Yu4/VtaX2zD9uJ8cDpL+DFSUtUImTSBqAB3yTAOA/wLZmtltQU2+ggSY0yssbaBGKNQ+uepklJ4OBw1rKUjSQQtJUeIYuiS9fA2xnZhZ6jdYDDgPyI/I/4eVK52e9HBXrBlLP4RMssmr35pUVknrgPVh7ZRbfBGzf0kNLsRbBRbKyPrjPANu35PksKSbNct9vZmsX27baCAJ5X+KZ+P+AyVqxQeoUCP9XMiEG2M4iu7qkfV2p/Bg8i5AtW/4LFye8qgRNhA5D0i6kgYKdzeyylrYv0znXxYkTwDfAHPktEaGs8W3SoNOWZnZDh84ba1y8imAVYFVy241y8Q/wO68zBRdyMevyQ5MOwz+4D+0THRlLzrj8XrEdXmo/fWbVKLwN6rhShYqCSvYd4e3bwAJmNrr4Hm2HYq2KazUAXGeRbd3S9mU7r7QYni1Osut34S0RNX1my/3BE9HW3c3sola274+XjC+dWfweTmpeKbgTLqQJ3IZXSiQ4HDilXhwrOopQKbACsCWuUdI8IDkJ7gowPzApL+BCpPdYZGMk9WAiXud35gFgSkazInPaja3acHYaSNoDVzMHuNrMyqZRFCoST8b1NRJ8gLfCvVN4rwbGdjRIdwOtIpTFXQJslln8LLBZUD9voAhC/+AQPJsC7uW9Yj6ZDNmp5YBDgfzev7/xz3+wmX2pWDPjGfKeeCXCrJ31ewi2GjeS+z8fD0TFMjJBmfYo4Ejc+gc8e30kcJZFLU+cQwXBB6ST9rXM7IEWdqkqFOtivF8ZYG2L7P6Wtu8MUKz1SLN+7wDzl/A9TYoHo/ahcFvGe2ZWMFtWCUjaHhc0BNjDzC6s8PnGxbOx/cKizczs5iLbro23qICX8M5hZn8U2rbg/rG64dVMq+JEe1lyrcmyGA48zYf8zBA24zvA2BdYBNg2s83albLGCdnOPXABtskzq/7FA5WnmLUs0Bfuuc+TBju3NbNryjrOWL2AH/HM7m/AlJUOVoeM3hBcuRlcqG79UFZfU4Q+/URQrSQSFMjlAbjoXa+weDT+nDihWCAhfPYXkTolgGeA9+isCYPwm10IF2PdnHz1f/A6sXnwurnpAPEATg6fzg84qLcmoTdf8Cduq9WPH+jLtPZEeYNPtULQAfkSDz+MBPqa2bct71XScafHEwNLZRbfCOxabzoxDdQXGuXlDbQKi+xP3N5lb9ISy6WB1xVrlZoNrM4RHpAXkhLur4EBhbK3oYzyScu1G0tIZ9Zu7EoGMQ6p1+q4VNZvtmKQe5Y/Q0q4R+LZ7aNbINzz4Mqgx5AS7teAhS2yM1ojctDk+ZwVnBrcQh99LdClSswVqzu5vdxHtfQ9Seoj6Ui8n38gKeH+E89wJhmuOYNAYbVQ7fLyw0gJ92O4wGVBmNl9pEGNaUhF14pCsfoq1k6KdSNekvoqPjlfheaE+3VcRG41YBKLbFWu50G+JVFA3oSUcI/E73MV86I1s//M7ExgFvx/TSa64+LX9qeSjlQLHr2h3PnwzKJYUq9i27drnF5On1zPE+OB1YpB0ly4lsXEYdET+HdRc8Id8Bqph/KSLW2YwMxGm9npONlMevu74335LxTTMQif/Y54MDbBTsADnU3ZXNKsko7Bs/yv4EGIlHD3wrPZW+N51zUZzfRcj1jAIlsrtHY0y7DZcPuVKVmF3uEqHsaUfMN9lf+PqoOgA5JUU/TEWxY6BEmr4vfDhHCPxOfGWzYIdwOtoZHpbqBNUKzF8MnfjGGR4ZOe4y3qtPYSFYGkA4Ezwtt/gWXN7NU27D8T7my7E/mZvgl4gANYlm70wcn5AhbZW2UZeBUgaWFceTmZOPyKTw6fKLi9E7eDcLupZGI8Cs92nNjWzEUIiDxD+uDc38zObssxKoVQWfIzPkkYBszcmUsiFWsbvA0APGCyZKH/J1SF7IpXMWTJ9HA8yHSSmf0k6RTSoEnVVMQlbYpnNwAOMrPBFTxXf7zkuTc+qZvPzN5vZZ9+eGZ8XDwTuKBZek8IRGNF0pLxWZsfpQlf4OTtUeCxQiJLeeX2CUbj38kd+dtXEpImxwn0XuQGDH7A7xEXFyOekh7GPw9wkbrzC23X7rG5qnZS7n+uRbZvS9u3+zzSrMBTwNRh0fPAaq2pflcbkp4lve9OaVa6gFcIjh6J3yOSoOuI8H5wsfYAxdoM11RJfhvv4VVEdatsLmlqvLpwK1zTIBfdMGZFzIcrkHsY8D88m39GW/43LaIjeI0TmizE+nKQDavc/a2aCAruw/DWpJ+AGc3a7sQTKi6OwoM9Sa/8F/j97qXyjLaBro4G6W6gzVCsyfBJdDYL9xCwtUX2U+G9xi7I7XTuJa0m2dzMbmphl5aOldiN7U2awfBag2SqaNxvg+qnN7klhF7K64BEKO4TvBT1g4Lbx+qPT5iypVzvAttaVHoQo8A4FiFVw/4dmLUtE8BKQnGO3cmcFrVMuOoVocTzfWCmsGgli2xIzjY+mdkaV7/um1k1Gi/nPtYyPttyC6QkG3O+me1doeHnQO51nFjOHWZmp1ToPML/v6QC5BQzO6zEfY/ESSZ051mO5Ai6NZHsxShe3fYH8DhOsh8BPmot0CNpT9KKG/AA7FYd7SfvCEL1TIR7N2f/12Fh+XX5xCzvPuA2dla6qn6rY4o1EV5i3hOfpPcrdxAtBFyeItUNeRVY2cx+L+d5ygFJp+HWmeBl73e3tH2RYyyMz0Gy7SXP4pVSHxfcJ9ZSeDVI0o7wI7CeRfZCW89fKYR2qwF4n/bKNL9ejWn5g4WZiLnw8JrjV/xaPNci+6Fd515UT/EKrhDfA6M3S9hfXYNMSroWD16Al4Bf0sb9p8DFF7O+8ffhLSkttrE00EAWjfLyBtoMi+xnXO31CNIS6NXxcvMliu44lkDSHHh/T3J9Hd9ewg1uN2ZmR+PVBQfhZeqeM0ymVGItLa8T66xMOgdBofwgnLgkhPsZYIlChFuxuinWXrgVWEK4DS9zXbgjhBsgCPFcGd5ORH2V6XeVEvNdSAn3I1nCHX4PG+JWeleSS7hvBuY2s12yhDvgGdL7Tr6HcyWRFWur5HW2Pinh/oqERLcCxRL7cx/L8CNbAoeyNN14EjgaF7DLPu9H4ZZrEX5tTWaRbWiRnW+RfVgiKVwn7/1OtSTc4MrXZrYzTsay5fj98MDdG5I2yCq8h/tAUi0xFW7DVr4xRfY73mMNfg9vs81ZSwiZvMdICfdbwOr1SLgDnsu8XqroVi0gVIwtjIuyJb/VpfHvd89CCv5B2XxxUseQKYAhirVJe8ZQLkjqHX6Tt+CVGVfgQbL0eh2Pz1me7zgAsSsTsTAJ4f4anxP0tciObi/hBmB5VmdufgNgFGI0jwYR2K6AHPuwQr+PYgg6BK+REu4xeFXNeg3C3UBb0ch0N9AhKNaKeOlccnMehUexz+nMJbHthaRJcDqclG7eAWxcTpuW0He4FXAo8zM7iYnbN8AlfI5xBnBZ6F2uCwTV4fOA3TKLrwd2LFT2qVgzAJfjpbAJPsVVr58p47imwW2IkjL9Bc3szXIdv71QrDnwEkjw8t5Op52gWOPjVQzJvWFRi1xxWNJKuNXVYnm7PQQcYWav0QIkvYwLdwFMYVb5ChtJqwMPhrfHmVnZfd6DyN97pO07LZbPK9Y0eEYsEUCbtti2eHVIksl+Mmh1tHecWRVqgAvNbI/2Hq9SCBnRE/CgcBYv4r+zx8N2s+MCf93xUObM5ZxQK86pCogtskFlOa6ToidJ3UXeB1Yws+/LcfxKIJRNJ2JWT5tZh/rc5dZoV5Gq94P/xncqELBLlM1vxT29ExwBnFytOYvctWR5PKO9MdkKthTD6M8HrMJ8TN1MMO194FRcEb9NNnwtjmt/LcptvMhXoXx6HN7hPxauI02AdkPSU0Di9b6mmT3YyvYC9sXvc4lrxvd41eITlRpnA10bDdLdQIcRJn43kisScyuwi0X2W00GVQMEYnk/adH3W8BSleqpk9SN7qzPHlzL5CFzfFs4axG7sVpA0kR45jJbmhUDseXdgIK11LbAObjib4ILgEMtKv9nKelQXEAKPCO1cv64qo3wOXyCZ4lH4pnITiXSoliHkwqo3WaRbSxp0bAsP4jwPHC4mT1Z0rFzS1Q3MrPbW9q+HJC0LF7CC3C6mQ2swDmOJxV+egTPWDb9FkMgYzn8HrMqBLufQvgLD1P9wqOswPblcjgoUFYOsKqZPVqO41cCkpbHgzz54l2P4uT7ZUmX4voZAKea2aFlO3+s6XEVZYChFllxC7ZSjylNht+v5g2LPgWWM6t/JwtJn+Ak+T9gIrOOEccgmHcqrmif4A+cNF1d4DnTCxc53SGz+HJc2bxsJDZvjMJFUhPl8ekKbPYjvbiLtTDmZwBisrz1L+LPqrsrpaGjPXQc13MUifdBT25gJFvV+pnYUeS1Bz1sZvmBuOy2E+MWhBtlFj8JbFEO9fMGxl40SHcDZYFi9cDLILMTlWHAFvXUM1VJSDqLtDTxJ2BRMxtW8fNGWpVuwQv2N5xqp12LOXZjlR5Ls7FJffHep0RhdgSegbi22baxpsaVRtfLLP4K2Mkiezh/+zKOsTeeBUwyJQOqLQRVCIp1Hql3+QCLaj+mUhGySZ/iGZwxPMt6PMKOeL9iFm/hJPPetkzqJK2DC/EBnGNmZS0JLnLObO9v2XvJJc2Gfx698EDLvAziI7yMdjWcZC9F8dL2f/CgwCO8xZvcxl14G8cYYBEze70MY9wRF2rKx9Jm9lyB5XWDQHrWxTPf+cGK2/BAwgO42NZ/QP9yEljFegX/LsH7uj9v97GcFDyaOd6XuFBnu49ZTUi6BtdxAFi8XEJUklbDyXOW0N4F7Jaf/Q+BzcPIdVZ4HNjYIvu1HOMJY5oFz2hvCcxRYJO/gDuYnofZjkXpyc6k7VcJHgBOAQqqkJcTitWdYTzHtSyWaag5MLgFdFoE7ZAPSZ/z81gBP+1QTn4Due1OJwNHm9mo/O0baKAtaPR0N1AWWGSjLLLDcMKUPLD6Ac8o1mHBB7bLQtJOpIR7FJ59G1aNc1tsj0Ag3RMDq/A6RezG5JYyVYGkxfDIfEK4fwFWKUK4N8bVmrOE+ypg3koSboBQOndQZtEZch/gWqMz93UfQlIy+TGf8Ah3k0u4P8Un3Qua2T3tyKJk+7pX6NBIS0e2XSN/UtwhBEJ4Loky/4zcxyCOAL4DXsIDmsuTS7jHhHUn4qrkk1pka1pkg+1We5RUo6AbcH4oae3IGLfAsz8JsiS+zWrA1YY57sazjdvglnQJNsJJ7Efh/Th4L3w5cWfm9XrFNmoNIat7Pynh/hZYqbMQ7oAO93UXgpk9jAdUrs4sXh94R9LGOdtGZhbZSXjWOSmfXgl4TrGypepthqQpJe0j6XngY/xazBLuUXjQcHN2ZXkGMYaduYKe7Et6bxmDt2Altl9PVqP83SIbTT82YN2mXDf4M7FoZrgzIAgonpNZtH92vaRukg7HtS4Swv0r3rt9eINwN1AONDLdDZQdijUj/rBYOrP4MWAbi7peaU7oKXucdELcZnXMDo8h1vz4JFjAb9zOSrzJzrhPaT6BvBu3X6pYBYKkjYBrSPVVP8IVyj/K2S7WpHiv9xaZxT8Au1lkd1ZqfPkIpOdR0j6/w83s5BZ2qTgUa1w8UDEO3rE/fWfQSVCsaTA+QYzLKJxKppJO3+G2b5eWoaT0Vdy714DJKy1qExSiE6J2k5ltXpbjxhJXcwCfBnvBCXGfgsKO0Z+Q9mU/3lJGLmg/vEE62d/JzC5v1xilAXiLSGLTdBYwKak39xzF3AfqFeHz2Rkn11MX2GQ0MGf+Pavd54s1Ly4aCO3UaQg9//eRBpp+BJY3s/eK7lSHkDQ/MDS8vcXMNq3AOTbALe2myCy+Htgn/16hWEviGfFk2x+B9S2y59twvgmADfGM9iqk10oWT4Ux3MogZiUIcuVt0y7br3JDsdbkce5vaqgRf2Es0tmu8yzCd/QVfpcdDsxgZj8GbZdrSB1DwAO7W5nZF9UfaQNdFV06+9hAbWCRfYFPCo4jVRZdGXhDsdYstl9nRCifvp2UcJ9bbcINYJG9QRrdn5gBbGlme+ER2+MhqJI61gOel/RwCBiUDUGR+hC8pz8h3E8BSxYg3Gvh2e0s4b4dmKeahBs8C4ZHvpPs6VHhQVwzWGT/4sEccIGs+Wo4nJIgaSI+5R4UvvtXSAj3b/gEs7+ZXdBRwh3wRHJacvUkKoWyZboVawLF2kCxLuZfvuKHQLgB1iBLuP/GM6S7437t/S2y3S2y21orgQ2fcbYE/pTQB9y2sbpF242kJOIi4EByP4O6z3Tnw8xGmNkFQH/8t/lb3ibdgTuCJkU58DZp0GaF0IJRMkIbzO2khPtXvJe+UxHugLfxsmqApduiJl0qzOxOvMoqq/ewJfCWlDsPCeR6CZorm7cYDJDUS9J6km7Cg8VX4aJ9WcL9Jt5219fMlmcQ7zCIG3Ediyzh/g1/Vve1yPautYe4RfYAK3BGU8jO6IO4J4jFdkqY2Z94ux14G8nu4bfwBinhHoNXJqzYINwNlBuNTHcDFYVirYB7MmdVdQcDh1dKsKRaCGV+z5KSoUdxVcyalCEFxe+P8IfJCGB2i7zEPUR4dwUOoLmAyxBc1KwkEaui53e7sgvw7FGCa4BdsuqnijUB/hvIbvcb3r98Qy2zuZIuIBXjudLMdmhp+4qPxy3TzgtvjwjlkHUHSeMCezMpR7AXE9MdzyOcwz/8zdnAaWbl65MM51wPz04BnGVmB5Tz+AXONwE0lVw+amartrR9zr7ePzobsDbeKrAcSaDuXjw4QdhiCz5A3I+XED9tUceUgyXdCGwW3l5uZju1tH3evivjmdXeYdHVwA5mNkbSveH/gSopyFcSgUwcgrcJjZtZ9TtOhs43sw4FFxTrTNKy1q0tsutKHFsv3AItIWl/4oKPLxffq74h6VFSotO3UgQnEPot8fvoxJlVlwAHBSLm28aaGO/vzyqbHwmclDyXQpvGsuGYmwCFSOjneEb7ejN7Oxx7BeAYvBUki6/x5+El9SaWqVi9+I/nuZyFSM3IHgLW6azl1iFR8imedPyH3ODh13h2u0NzoQYaKIYG6W6g4lCsyXHvyayv6yu4yNrHtRlVxxAevLeQ9ql+jAvC1NS3UbFOJhWzu84i2zpnvU/etsUtUmbK2/0pPML7eFt7bIOwzy3kqlIfDZyQp768Av5b6JfZ7kFg53KpK3cEkibHAxcTh0WL1XJiG3oLPwlvn7HIlm1p+2ojBFp2wCeT0zGANAT1Bi9zB+uZ2XcVOvckwM94pnuoWccVoVs5Xw9c4AzgOTNbusXtvT1gBZxkr0WupZHjS1JZsm6MYDlWtiHls8QDkDQtbkOWuAGsUMqkMqi1P0g6Kb0Zn5COCusfJyUQfczs73KOu1YIFS43A/lVQF/j98crzGxksx1LObbf/xLP7lssar2sugDh/gdXtS/r76TakHQccFR426I1XpnONx2uSbBGZvEwYPvs9RCUzf+Ht2Y5jCs4g/P5i83wyqzpC5ziJ/x3cz1+f7AQbFsJvz/mV+N8husxXF3PCQjF6s+vvM4l9MnU+pxpZgfWcFgdgqT7gfyqy3twC9NOHTxsoL7RIN0NVAXh4bMPcBpp8eRfwO6lRvvrCZJi/EEKnv1a3Mzeb2GXqiBE6j+GJquRhS1q7nkcyNJWeBS/f97q5/DJ5cOlkG9JM+HZsDnDouF4NuyGzLjGxS17sirTf+NlqpfUU6+ypP3wnlXwEsCla2mXoljv4X25Y4DJy6ms216EoNOmeAuJ/36mxGsEBIzhV7rRzyL7o+hByjOO13FhLAMmK3c2vcD5huP3r4IkX7FmIiXZK9FcTyHBMEbyAKezFsObRHsqphAsaQ+8CgXgA2B+a8F7N4ggPgpMEBbdhROjkZltkpJcgO5mlbEwqgVCKfenFPY9/wi/99/c1v85uHx8j/fD/4Vfzy19D/mE+188y/h4sX06C/IqVcpq0dbCOQXsgmeWx8+sOgu3jvsXMsrmv3Iib+GeAj8WPOQ/ePvHdcAjyfUR9l8N/53kC8V9jFdOXG9R+4I31YZibckwruNq0gasDmhE1BKStsZbZJJgouHzkvNq+ZxvYOxAg3Q3UFUo1oJ4f+BsmcVXAXtXwoO5EpC0CR7RBr9hr21mD9RwSDlQnEMaHwdWKUZqQ/ZuczzjMHve6hdx8v1AsYeRpCVwYbZEgOYnYAMzezYznsXwstTs8Z8CdrDIPi39P6sOQkDiTVIBqq3M7PqajSfWGXhwAmBzi+ymmo3FJ61r4rZLC+Ss3JHvmLFJkOpgi+wMKgzl2vStH9SpK3m+X/EqiA/NbPaQFVsGJ9lrU9gSCFyt+CloKht/n0EcigeiAF7DA3cVKdkMQZJnSH2qYzMbVGTbBfBs7MRh0UP4Zzs8b7uhwPzAcDOrB7X/skLS9nhVDrig4aR5mwzFK4YebMtkXbGuIhWgW9Mie7DI+bss4YamCoykuulxM1u5pe3LfO6ZgSvxMvEEH+Dfy5e4mv0WFFZWH4VfE9cDd2UrPALZXgsn24vl7fcBTrZvtKjzlWYr1uW8wg7c27RoJN73/GzxveoHoR3wfNJrL4uVu8p11UB9oyGk1kBVYZG9jludXJlZvB3waiDkdQ1JC+FBggSH1BPhDvgfnqUBz7YVtfows1HmFl5z4z1qWVGexfEM9stBLCZH7EbSpvjkPCHcHwBLJA9hxeqlWMfj2eKEcA/HCeSK9Ui4AUK2Yv/MolMljV9k82qgLqzDgujeU/hvYoHMqidYg90yhPtr0qxqpfFE5vXyVTjfv0wALMrkinU7Xt7+GG45l0+4v8HLWQcAk1lkK1tkZ1hk7zGImYAobDcGdzyo2EQ8ZGR3hSbn3cMlNQsQyC0FHyEl3E/gvvWFsrFJpuifAuu6Aq4hvR9OCgwEsmX5C+DX5pOSWmw1yMNdmdcbFNogEO5b6aKEG8DMvsGvEYBF1EFLuzae+1O89eNAUruw2fFA8ze450Iu4Z4RD6sN5HcGcaKZXZ8QbsWSYq0HvIyrNGQJ97s4gZ/bIru2MxLugH1YhA9YtOl9T+B2STPWbkilIczbXiOXcD+ReV1RPZAGGkjQyHQ3UDMo1lY4QUxKGEfgQjbn1FO5cQJJU+MP1aSf62q8H6z+xhprM7yiAFwpdgGLbHSr+/nEZyM8Uj9P3uqheOb7LuAwPNuZYAjuTf5rOP98+Oczf2abl4HtLOocart5QlHHmlnU0vYVG0es3ngFQR+8yHFqi6pXyhvsfU4g/SwSvAocwQo8wgoMISW9u1pUHQX/oMad9OC9ZmYLt7R9u87hJcFLAGvxAwcxZREzLyfPz+NBifuBNwvdx0Lw6kG8/BSqIAKXOfeJuFI3uB/tCkmJtKRZ8aBKEjx5HljNrHAFkqQv8XvhN2aWL87YJSBpQ1L167dwor0q3ou7UN7m9wFHmtkbLR4zVh/8N9sb99iePns9Zwj3umFRlyPcCSTdiftoQ5Vt50KP90Y4ESt233gbuI5leIZVuJjcFqrt8Yq3DXD9kgXy9n0Lb7+5rZr360pCsRZgNC9yLb0yLvdDgWXqUdMh3Gv3A04ldZj5E3eDuBnXS0mCBrOb2YdVH2QDYxUapLuBmkKxZsHJ4SKZxffipcd1I2gRevyGkJZnvoCXVv1Xu1EVRyhzexGa4tI7WmRXtLBL7v5OvjfAyff8eat/JVex9QpgdzMbEQjKQCAmfciNCu9P7kxRfkmzAe8APXDv1DnM7POajCXWHaRZscUtspcqfk6pPx5k2SJv1Qd4O8JtQSxodZxEgve7zlXN71nSG7h82xi8r/u3Dh8z1hS44NJaeKVIMZucn4AHcJL9sEWtCylK2hLvAQUvZZ2rGLEtN4LK/FvALGHRLmZ2qdyD/ClghrD8Vbzk8vfmR2k61s94BvhjM5u1cqOuHcKk/QXSzOXWZnZdJjh5PLmtUoY/z44xKy4SqjgnoNd0PY9NhBtA0pH4ZwiwTai6quT5pgM2xlXHW6tOGIWT6dPNbFTQS7mVXC/n74Gp8vYbSghOdxWynYVi7c0/nMsl+EzAcQuwWT0lICRNgc9NssHiV4DNzeyTsM3BuM4QwAXmNqsNNFAxNMrLG6gpLLJP8Idftv9zHdzTO99aoyYIE68LSQn3V8CG9Uq4AUKGbWBm0XGKVbK3sJmNMbPbgQXxTMSrmdVZAnIjPnEfoViz4dmzE0kJ99vAYhbZ8Z2JcAOEqPc54e04wCk1HM59mdcVLTGXNIukK3DP2izh/gq3eZvHzG4NhLsb/n0nOLoG33NS8tuN5orTJUGxuinWoooVKdaL+GT6alzvIJdwf40XJo5hcWAqi2xbi+zGEgn3pKR6CwB7VYtwAwShqN0zi04LlQyPkRLut3B17KKEOyCx1ep0Ht2lIpCIwzOLjpPUK9wfb8HbcnbGrw1wGcEtgPclXRF6hwvhzszr9aEpsJtPuNfuqoQ7IOsMsUjRrToASdNL2l/Ss/j3dBbNCff7eFZ6U/yZBR5sPQl4WtJsFtlvOIEbktkvS7hfxb/LhSyyO7oi4Q44n/G4iy0gU/OzCakSfc0haUXceztLuE/HRVE/ySy7FBd0Bdg+3J8baKBiaGS6G6gbKNaaeL900iNseFlrXEvCJulA0qDAv3gpVTNF8HqEYt1NOolrt8+zpFlwqtHcKkW8zya8xJxsgpom4mPwkq5BHfUZriWCFdqHpL/J5czs6aqPI9Z0pBP7ly2yfJGejp/DVeiPwjUWumdW/YQT6//lB5oUa1MgEXZ7HVik2pNNSQNwb11wP/BDStov1iR4ifdauDjcFEU2/R0XTrqfwezCH00T9vGsjb7Nki4h9ae/3cw2asv+5YKka4DETvAPUjux9/GS8+9b2d816h0vmtkSLW3f2SHpEVI7xL3M7IK89ePg2v1HkjpHAIzGn2nHm1lTQa5iTYWXlgt4l0EshGcL8wl3luB1OeS1h7Rqw9eG485AmtFesshm7+Gf+S3AO0mWNgQ/Yjxo7YmpbvzLatzC4iyOmgmOggtvrlAPzhLVgGJNBgzlA6bnhpxVG4VgfU0QhGEH4QKHiQbND8B2ZkUFC8/BnXUADjezkys9zgbGXjRIdwN1BcWaBs8wZf2enwW2sqj6pb2S1sTL3ZOqkM3M7OYWdqkrKNZceOaqG97LNItFVtj8pNgxXCToTmDysOh34AtgXibCi56zjt/GR4jtLLLnOzb6+oCkXXGLEXBiuahZ6/3xZR9H3KQWDd7X3SIxKvm4Xlp8JN6j2COz6jc82HSOWXPrr9BK8A5peW1RJeZKQtKUeGYa4FkzK5jtDi0X85Jaei1FbnAhizdJlcafT4J+ku4jrTSY3Mx+bsM4l8VLuMGvxTnNauNNH0ovPyA3i/8pHlRqdUyhTD0RUHvCzOqiKqlSkLQokLR0fAf0L9TDKmlCYF9cWG/izKpRuHjoCWY2DECxniMhhBfyGN81lS2PFYQ7gaRPcA/7f4EJ2ysoGAS9EqJdLAj0LoFom9k7rRxvKbpxFfPSn+XIDaU4PgT6keZ7PwDWDtV7XR6KtRwwhGfoxqNNi/8BlmpN16Ai45H64oryWQG8R/G2he9a2G8WvC1KeB3TTGadw8qtgc6HRnl5A3UFi+xbvIfycDxLAF4KNlSxBlRzLEHd90bS6+S4zkS4ASyyd4HLwtsJ8B61kiFpC7z0NCHc7wELsgLzsyVnsBejcwj3i8BJ9GAQcwbrra6Ay/BSNfBy++1rNI6sinlRRfpSIWlGSRfhE46dSQn377iydj8zO74Q4Q7YnpRwP4Vng6sOM/sB974FV0HunaxTrAkUawPFuhjvn34DLxldllzC/TceWNoVmMEim98iO9wiezqvyiar1F1yu0YY08WZRYfXinAHjMQz3AlGA2u1YUzZ/73LlpcnMLOXSasppsaJdaHt/jCz43EyFuHXEvi1tTPwoaSLAkFMVcxnyiHca40thDsgKTEfFy/XLxmS+ko6SNILwOd4kDCfcL+DZz/nNrO5zWxQq4Q7Vk8GMSdH050NySXcXzCaxzidJ5gDF4/8IayZHXhBcZuU7DstLLKngGNZGg9lOsYD7g6B0KpB0kZ4L31CuEfhYq+rt0S4AUK5eWI1OR0etGmggYqgkeluoG6hWEsAN+ATmAQXAgda1LayzjafW5oEp5CJQNAdwMaJ0m9nQqge+Bh/II4C5rSouMgPNJWPHoULwiR4DNiYQfTCe6HWbVrzF8O5jd4ZRVOAYTjBudLMRnT4H6khJC1PajHyAzBrC2S0MmOItQzeMw9wk0W2ebuO46WXRwA7kfbeg5OwM3E17d9aGcs4OFlP2g2Wtsiea894ygEp4328AAPYgBlwu6XlyP0fs/iANJv9dCltEJKuBrYJb0tWu5V0NOm19CLeW1j1aokwlgnwAEl+2e2pZnZoiceYHg9igAvqbVzGIdYlJM2J9/t2w6tAZk7cGlrYZ2Lcjmh/0hJ+gJHMyB3syKaA08Urmgj3E2Ueel0jT8xqZzO7rJXt+5FmtIu12byFZ7RvNSvdLUOxeuHBxCOAvjkrP2c4Q+jNsKYl9wA7M4jxcc2NrLL5DhZZbuF1F4RidQceYyTLcwWpAZw/p1ap9HM/VNycCeyWWTwM2MLMXmjDcbLP9+fNrJA/ewMNdBiNTHcDdQuL7AU8s5jNLu8OvKRYbYqItwWhL+hmUsL9JrBtZyTc0FQ9cHp4m4jDFEXIyl1FLuG+FFiTQSyJT2jWzay7gj5MxWcsB5lCMw+WXAR8LGmPbAays8HMnsRFjgCmpDaiMS/gk32A1UN5d8kIgkLn4wGY3cm1UDkOz2wPKlH9e09Swn1vTQl3LDEfX7A8PvXagNuBs3GV4Szh/g9XGt8H6G+RzWGRHWiRPdoG3YE2Z7qDCv6R4e1o3JO7VoR7PDyrkxDuX/GsN8BBQVStFIxVmW6AQN6uDG8nxu0tW9vnt2A12A9X6f4zrOrJF2za1M08AzATW4xthDsgK6a2aKENJM0kaaCkl4DPcJKeT7jfxCu55jCz+czsuFIJt2L1Vqw98XvjReQS7keA5biCqRhG1gFkXeBNBjEHnmF9LCzvDVwfRBm79Bw72JBuTU9+YXPc1NKxLHB+CN5XBJLmxn87WcJ9E7BAWwh3wFP4vAZgSUkLlmGIDTTQDI1MdwN1j9CLuROuJJ1VzN0fuKTcnt6SziYtH/wJ7+EdVs5zVBuKNQE+oUjKvpYMQY3c7aTJ8TLK5TKLD+EgzmMCTgX2ziz/EdjJIrsn7xhL4ZOfNfIO/zWuAH5JPSu/F0PIsLyPT6pG4uWKH1V1DLFuBDYLb5e1yJ5pdR9pWrxdY1fI8Zj+Cyeng81aV97OjGFCvP93MlzscAGL7M1S9y8HQsBhWVxRYH3ys1IphpH6Zj9hkf1TZLvSzisNxjOX4NnqFoMNYdL5GJD0PJecTS43QtDrblJ/8N+AFfDPLw7LXsJ7MlsMCgRyPjS8vdjMdmth8y6DUBb+EX4d/Y33f5askRHUkQ8BDga6swqp3v5TPMrjbGdm3xQ9QBdEqLz4He+pfc3MFg7LZ8az2ZtQ3Ef7DdIe7TZ7LCvWuHjZ/6F4aXEWDwLH5muTSFoPD0JnhRfPZT6OZABn4nOVBLcC21tUfx7W5YRirQfcxVe4SVd699jXzM4t67n8nrorrkI/Tlj8Lx5Mvby9tmWSdsMrKQEuNbNdOjjUBhpohi4dhWuga8AiM4vsUtxSJIlGjotHpG8K/pllgaSdSQn3SGBAZyfcABbZn3hfW4LTQjCjCZLmxSPHCeH+Dy8nf5gJeIVcwn0/MG8+4QYws+fMbE1gcXKtrqbDAyefBguXknti6wHhd5BUDPTMvK4msn3dLVqHSZomBJA+xb+7hHD/jVc79DOzo9pCuAP2I+1yvKFahFux+ijWAMW6Gi/xfxy/VnMJ97eMxDgK7zSc2SLb2yK7v6OEOyB7jHGLbpViW1LCPYyU3FYVQV/hZlLC/SewWhA8OgUPJoFnD/co4ZBjXaYbwMy+IO3NH59cW8ZS8DcwD4mewAeZNVOyCvCJpLMkTdPBoXYamNmfuFYIwLySjpL0KvAJcDLNCfdQvHJkdjNbwMxOaCvhVqzxFOsA/N54DrmE+17cO33NQmKgZnY3fm95ILN4H97keY7lXDyokhC/jYFnFGvGtoyvs8Eiuxs4h+kJBnhNOFPSKgV3agdC29/NODlOCPebwMJmdll7CXfAdaQ6F1uFczXQQFnRIN0NdBoEUbDFgaxdyya4yFoxW5CSIWmZvGPvWQt7qAriUtJp3jJ4zysAktYHniPtn/+O7qzAIPri2a+5wvL/cAK3Tmvq2Wb2kpmtgwdL7sqsmgbvw/pM0sGSxu/Qf1VdnEzaubaepFWrfP6sOvjahTaQNLWkM/EJ5b54Zh6cMJ6KZ+eOaIvydtOxPcB1YHg7GheLqhgUayrF2lmx7sGrTm7De6qzE6JRwMMM4V0GAxfRk5gbLLK3y10FQy7BbDFoFKpGzsgs2sOsLMS/TQjtMteSXu//4L3DLwOY2XA8c5TgREn5Wb98ZAMOVf+faoyT8L5dgL0kTdXSxglCpcFtpNftP3zLAIaHz28WoCfj4EGtTyUNLvXYnRmS+uPPFfBg5nHAQnmbvY73Wc9qZgua2YntzGyPr1gH4yXqg3FRvAR34ZaH61pkLxU8QECw1Fsbz64mY5+bMbzEIEYxmvVIWwkWAF4eCwTWDgGGMh9p9YYHl26WNGuxnUpFqKAbigcyEpwPLN6Wvv1iMLO/8LY68Pvb9h09ZgMN5KNBuhvoVLDI/rXI9gIG4P2I4JmupxXriCDs0WYEu4nbSXtAzzGzSzs84DqCRTYSV/RMcIr2Vk9JR+LKzUlH1qsszboczfE4aUgypG8AC1tk57eFzJjZq2a2Ad6fn/XwnBLvzRsm6dBQZljXCA/m7Gd4ViA11Tl/ZD+Q9kDOp1hNvumSppJ0Bk629ye39O50nGwf2pZy2ALYj9QK6erWBPnaA8WaTbEGKtazuJfxJcA6pMED8AntTcAWwOQW2eo8yU0ZPe5KCeG0paf7DNKKgBuL+cRWEpK6AZdDEOxysrieWW5bQgguXhLeTgC0VhI6Vma6AUL5d2IhOB4l9HYXJNywto20O+jNdYA/eWYjEZ4aB29j+EzS6dVWg640JM0q6QhJr+Pl+vkkG+A1vC1mVjNbyMxOMmvf/Sa4GByGV5ucRtpmBf69LGiRbWCRvVrqMc1xHh5UTqp9egGDOY79eJt18Ww94XxDFGuH9oy/MyDoYmwO/M1KpL4WHiC9W9JE7TmupO5hjvIUkFQM/ApsaGZ7l7lVLZt02SPcPxtooGxo9HQ30GkRSrauIxtX9ZLTbSwqvS8uZFqfA+YLix7BM0Ht8gutZ4SS8qdxGzZ4klcYwiKZTW7kAO5iIs4HJs0sPx04qg2CU8XH4GXsR+FVCtkS91/w7MN5ZvZ7oX3rAeFB/BxedQGwT5h8Vef8sSLSVoFdGcSd+MR/T5qTof/hfcQd9vQOWe5hwER4dnl2i+zTMhy3Gy6gtAFenDhnkU2/wbNRd+H92Tm/xVDG+Eh4+z8z27OjY2s21ty+vx3N7Ioi261MKir4G+7J3aJ1TbkReh8vJM1ijwQ2MLP7i2w/CV7mm2RXNzCzu4psuwmpwOXBZnZGoe26KkL596c4Of4PVzL/tsi2hQj3WkGcEcVajcRubwR3ciKf4tfyOJnD/INn9U7rYNCsZgiCgkmPdkuCfa8CmwUrp46dM9ZEeGXWgeQ+zwz//Z5gkb1VaN82nce/4xNwf/YEvzAN+7Mb2wMrZZafCRySZ0XYZaBY2wFX8h9wKWP4qSm5dz8e8CtZRDLokVxL2qIDPn/Zysy+LLxXxyDpMdLva3Uze7gS52lg7EQjitNAp4VF9gV+Mz6WtIdqJeANxWqx3zVBmJheTkq4P8If+F3ygRgy1Ac3LViYRZry2L2IifibibiBdILyDbCqRTawHIQbwMzeMrPN8N7G64FEFX5SXOF3mKRjgt1O3SGo2O+XWXSspMmKbV8BOGn6G7iDgTgRPpiUcP+Hi8zMbGYHlYNwBxyAE26AqzpCuINa8JqKdSHwFa7MfhjNCfe7wIl4r/EMFtmeFtlDRX6LL5L+liqV6c5mdQv2dEsah5SYAxxaI8J9JinhHo3f1woSboBgf7V/ZtF5LVSfjLWZboBAsP8X3o6DC3E1QyBjt1OEcAcMwQOO0ItVGcRRwEz4NZxk8cbD+8c/k3RyaF2oe0iaPfRov4G3Nh1Pc8L9Ct6jnTxzx+ko4VasiUNwclg4Z/I8G4M/c+axyDYvB+EGb9Ews4OBVUnbjyblW67meD5jZJMOAPh99N5yatHUGa4GrmMcYEu60bvpe12LVpxTspC0Nl5dlxDuMfhcb6VKEe6A8zOv96rgeRoYC9HIdDfQJaBYK+AR0Wwv4pnA4S2RRUkHkQpi/QksZmbvF9u+K0DSEmzOE8wRynWfZATfcSSbsRvQP7PpbcBuFrW997eN45kdn3RtRW4g8A9Sde3fKjmG9kC5ns3nmdk+VTlvH03O/HzOK4zXVIzqGI6XvZ5cLOvW7nPGmgSfwE6IT45ntahtAoNhkrkWntFek6zBTAoDniVktC1qmzp8KFddAJ+gTWJl9lKXtDGulgww0MyaielJOo7UUu5ZYLlq2g0Gwn0iaRuE4ZmhVn2Dw773kzoPnGNm+xXYbndS0rmDmV3Z0XF3NoR+68/w4MtwPMj1TWZ9QriTAHAhwu3bxroM2DG83cgiuz0cYxr8e9yN3PaKv/AWgDPao81QSUiagzSjPW+RzV4m9dH+LOz3Gt6CNAaYKLTytO3cqebEfuT6oo/B5wcnWmQfFNi1bAgB2IvxFrgEH7MDt9CXgbhtJ3gQYj2L2t6bXu8IbimvAf35FLgGw5qq2rY1s2uK7uvXzUmkLhHgzidbFbp2yo3QLjYMn0uOwa/rzyt93gbGDjQy3Q10CVhkT+CT7aya9gHAc4oLi3hIWgkXlkqwzVhAuLcFnuRhejfZeixHNzbjZFLC/Tc+Adyk0oQbwMw+MLNtgdnJNRyZELce+1TS4XUouHY4aY/vHsE3tGKQNKmk4/mbT3kuh3CPBM4DZjGz/cpNuAMOJJ3EXlEq4VasGRRrb8V6BLeYuw6fjGcJ93/4dbsTMLVFtqxFdnpbCXdAYuHVjbT8v5xosadb0lykWc+RuCd31Qh3wFHk6g7sVArhBu9TxUubk+z1PpLy/ZBhLM90Q5OYVpIV603mMw/VDiUR7oBbMq+bhKLM7NsQ9JgFv8aTq74Pfv/5TNLxwYqsJpBj0TCOt/EWhWNpTrhfxCty+pnZYmZ2WkK4AxKtim4U7vEuPgYXSDscD4IcTXqvGo0/U2a3yLarNOEGCEGQjfH7WWIV1p8rGMg9XImRPFNnB14K7QVdCsEtZXNgJDMDa+a0kV2sIj7YQXDtOXIJ9z3A/NUg3AChyjHRbOhGrg94Aw10CI1MdwNdCqFneR9cLCUpnP4L2NOiNLoq91t9FUjK9I43s6OrOdZqQlJ3XHk7LS0fwPfM19S/meBFYOtKCGSVCrk/6+G4emhWpOx7PIN3UVBcrjmCwMvx4e0jeA9YuX3jJ8EnIbnZm+741HRhLrb/Vc4nWbEmxSP/E+BEclaLCkf+w/U3L96bvQHFJ8+/4JOpu4CHy+VjK2krPKMFMMjMymrRJWkFvBwYvKLg8My6bsCTpBoTVb+nSDoYv/cl2MvMLii2fQvHGUgakHwDWNTMRmbWZ3/365k1tw4cGxAEzj7DgxAjcHKcqOxnCfeaZvZU0ePE6onf3ybBn1dTWmTNghmSpsfvjbuQin6CVwWdBZxZjaogSb1wj/cNcFX8Ymr3L5BmtL9o5Zg7k4r5laQToFjj4KToCHLF0UYBVwInlUN3or0IyuzX4e0xjsl5id2ZiB7MHpaMwYOa51TAbaGmCLZsgzHgLv5laFNLzjBgkWyVhqRtcCGzJCA7Ap+vnFfuZ2prkDQ18AV+jf0IzFAvc44GOjcame4GuhSCp/c5wBJAUrbVB7hasa5WrAkyWYiEcD9Arod1l0JQDb2HLOGehseYu1mm7lJg2VoSbgAz+9TMdsH1T68k7dOdCi83/0jSztVUDW8Bg4GEgK6Kq2yXBZImljSI5tmbkfTkcvZlDGsDUzf5qlcKB+GEG+DyfMKtWD0Ua3nFOhNX630Dz3TlE+7PcGKwAjCVRba9RXZHuQh3wHOZ15Xo627JMmwnUsL9MR4gqhok7UUu4T64PYQ74Cz8ewTvwd0/b/1Yn+kGMLMfSJXee+FVBm0i3NDkLJGI1vUBVi9yvq/MbC+8KukiPAgGfm84BtfDiNqrFN0SJE0oaTNJN+BE5CHc0z1LuA14HieRfc1sSTMb3BrhDngl83qRolvhQQrF2hl/xp9FSrjH4M+M2SyyXWpJuAGC2voyuA2aP8d+YjFOZRp+IVFK74b/D5coVu9Cx+nEOAu4HwHrMC5TkAik9gNuCMrkE0i6Bu8FTwj3B7gV2LnVJtwAQYPjtvB2CnJtyhpooN1oZLob6LJQrD74hGj7poXGx5zF+/zeRI4+xSOuvzY/QudHKNe6B5qi6qNZltdYmUULbP4csEy9RdslzQnEeFlyFh/jE82balDC24S8Pt+PgXk6EhUPE+b98Oz2xJlVo3DRvxPN7HPFepqU5M1SiQmmYk2Ok+U++AS/v0X2hWKND6yGZ7TXIbXGysdruB3dXcBblf5thZ7kr3Ev+D+ASduillvC8ecltQe6NASHkszIe6Tf1ypm9li5zlvCuHYELsssOtrMji+2fYnHXAzPVAon1nNn+m8Hk5aALm1mzxU+StdHEDVLrpExpMmMkgh303Fc/PO+8PY6i2zrEs7dF9fD2IHcqqDf8IDg2R3RNZD7ta+HX+crkZtdTzAceAy/zu9pr2igpJ74NTsO8ImZ9W+2jTsdbI4/D/LX3wIcY1F9tohJWga4BiecflWtzzssQLYt6VlgQLCG7BJQrCnwAN40/A6cx1+MbCLXV+FOKtnv8grcEaScwdg2Q9KyuE0ZwPNmVilxzgbGIjQy3Q10WVhkf1lkO+ACXX8C8Ar9M4T7H9zrsasS7lWBl0gIdzf+YGt+yiPc1+KK7eCZwc2rOsgSYGbvmdmmeOb0vsyq/rgS7VBJ6wfCVQvchpcVJ2Patz0HCZmko/AJfExK4EbhVQizmtluGVGXrBL1mu05Zwk4iDT7cC2wimLdjZfQ3g5sRy7hHoVbZe0D9LXIFrbIjrPI3qxGMCdkRRICOCEwV5lPUaynezBZ//LqEu4t8N9HgpNw+6IOwcxewvuIwcXCLshcY41Md4CZ/UTq75vMqf6mDYQ74FFoygSuF0qnWzv352a2K14VdBmpHsbEeLXJMElHSpqwyCFyEPqz55Z7aL+EOwtcgGfes4T7N/x+sAkwhZmtbWaXdESlP7QvvB7ezpLtU1csKdb6OHm7jlySdh+wkEW2ab0SbgAzewbXnfH2FwPuZG7u5CfGNPXqLw28rFgL1GKMlYBF9iOwNWBMBGzFuKS/0+1Iv8s/gS3NbMdaE+6AZ4BE3X7JYn3oDTTQFjRIdwNdHhbZ9cCCfMK7PJBZsQ7fMqjJkqXLIEyc9sXL5icGoA8/sTd96N/Uw/07sIVFtg259lenKlYzgah6gJm9bmbr4BOTJzKr5sWzLC9IWrXa5DsQvf1JbeuODsrGJSGU1x2Bk+3j8L5O8InJ5cDsZraLWTPxsizpXpsyI2QokgCC4ROky4B1yfUQ/gvPMm2F96KuapGdFyz9aoFKlphnSfe4AJLWALYIy34m16u3ogi2OteQ+t2fBRxZxpLMo/DKAXBF883C66xd2j+MxQjtSvmtFDu0kXBjkY0gLTGfAK8kKW1fs8/MbGecfGfFKCfBe+8/C2KUzSzgQonvMpJOx8u138aDNvnVUF/glWMrA1Oa2TZmdquZ/VnyP9k6Xs68XjiQ7VXxios7cZvJBEOApS2ydSyy1+kEMLPfzWwbYEuSAMtQJudSevAfyec4I/CsYm1Uo2GWHRbZ4yTtNn3oTrNfIW8CC5Yq+FgNhHtotj1nz1qNpYGug0Z5eQNjBYL1yqt42al3fLspzj/4JPmieiurbg+C3cb5eH+pox+/sTkTZ2jSU8A2WVKkWPeTZktji2xQNcbbXgRivTI+OcxXV34CJx5VLXmVdBGpL/JlYRLc0vZ9cB/QgeRmi0fjROp4a8GvNoiWfYn3VP4HTGaRdYgAhWMuggsk7UbxsvHvgLvxifDj5fJwLwckLYH3lQJcE5Txy3XsiYGkMuYh3BbobdxXGaponxXKHx8mDYBcDOxeASG/DYA7wtsfgDnCuZI+x74l9ux2OWT0QfIrTS4JGei2HS/WOqQOHNdY1L7fbhDwOgq3NMwmV37G+/4vA5bEr/N18b7VQniDtD1kaKX7a4OY1tUATMNF7MYcwPJ5m70IHGlR9apJKoHQGnA1BE2OPsA2/M1UZF06IuC4LjE32U09+IT3eZJZmpy7U3yI27X+3nzP2iE8o7/Gq6b+BabrqpWRDVQHDdLdQJdHUFp9HM+Qwji8ykAmpDtZK7H7gJ0tan95XK0RlHRvJ/k/AZZmJCvTM0y7RuGCXKdZlNvnqlhz4KVUPXACN3sNM5UlI5DvdfFsTr5Fzf3AUWbVyYKEz/8j/AFtuFbAawW2Gx+Pmh9CKuYHqZfscUGAp/VzxroYVzIGWMciu6+l7YscI7HX2gQnUjMU2fR90gn4SxbVro++JYTA0++4jVPB3tAOHLsX3sMK8DRO7g8J74cAK1dD+EfSAnhLQ1I2fBPuY1u2/vW8892BEzRwhelpSasrpjSzHytx3npGINx3kHqaJyWx4+P32tks1xKr9WO6kNYP+Pf6B1450hF9iFnxe/5WlFbZOBoPyt4F3FWguqaikHt8vwd4aCe32elNPJBwb1cgodDkKnII3grQgx7Aeoxivpz+/FuAHcosOFlVBM2Ly0gFBr0G41++57+m6ru7gAG11GcpBEnn4O1SAAea2Zm1HE8DnRuN8vIGxgacQUpEv+I/1qI7CwIXZrZZG3hLsTao9uDKgTAJf5nk/+zOGAYAqzYR7g+BJS2yk/MJN0DohUv6N8cBTqn8qDsOc9yN98ptQdqfDv6Af03SLUGMrdJj+QHvxQYv9z0tW+ouaTxJB+HifaeSEu6EbM9pZtuVSrgDsiR7/VJ3UqxuirVUUBz/nNQbtRDhfhaYwyKb0yI73CJ7oV4JN0AQsUvKVGdpS6l/CRhJWro7GWkp+QgqkGUuhECkHiIl3A8C21aKcAfsA03lr7sAU2fWjXXl5UUI95rA6eF9D5wgtgmBYN8d3k6IOyJ0BKPxPulXSNtf8pGUtW8LTGVmK5nZ2VUn3LHm5BiOazL6/Lpp1Uf4vX1Bi+yerkK4AcxstJmdhFcdfMQo4HZ68AjZb2sT4GnFmrE2o+wYQqXMW2QJ9yK47v2uTIxIhP7Wx+3w6g3/y7zeQ24N2UAD7ULjx9NAl4akbYG9w9sRwEZm9oNF9rdFtgeuvPx9WD85cIdiXaa4ee9bvULSRjgx8odyH8awI92Yr2mTi3GhmVcKHiDFsbhAFsDmirVMSxvXE8xsjJndiAtn7YyXXSfYGHhb0lWSZip4gPLhPJxUg6v9ri5pXEkHhOWnk9rbGHADrgq9jZl92OxoreMRUiGr9ULWuiAC0V5Gsc7G+zOfxXvRp89sNgpXIk6Eff4DNrXIPmjH2GqJbGvBkuU6aCDVCcmcCXdLBzihnd9fmyD3aX6E9Df0HLCxmY0ovlfHYWZf4V7ICbICdWOVkFoxwm1mT+M99UmJ7HahzLutuCXzuk1WRUHPYyFJx0p6E7fwG4y34BTTuuiFN1xNTg0CKIo1s2JdBbxNNzZm2rDiT+BLDgTmsshurOdAX0dhZq8AC5L4lD+LPxmGN1HvBXGBtU6joB20Si7Hr5UkwPw9sDbr8D96AZPSm034lTTEcJykSomCtgtm9h5eKQkwK7BKDYfTQCdHg3Q30GUhaSHcyzTBnkGRtwmhHDcR4kqwIzC03h9wkrpJioBbSdSEpwN2pVtwTv0Z2MAi262U0jSL7FdyszNnt0Ti6hFmNsrMLsMfjvuSBlS64ZmcDyRdIGnaYsfo4PlHkButvxwn24OhqYzO8HLgecxsS7P2K+6GHu6Hw9up8DLxJgSivaxinYMHIp7GP5est+5IvBR/B5zMvQlN+aYLLbJv2ju+GqKSYmoJyUzExN6nCpUhkibDM9x9w6K3gHWqqPT7P7yfFtL/fXi9lYNWEq0QbszsN/xaBw/ItDnbjV/PSVXB+orVq6WNJfWUtIqkc/GqlVfxkvL8dpuP8H7upcO6m0jJzlRh3J9K2k/SuFQYijWdYv0P92TelmQ+OhXp7/kyPrbImncAd0GY2d9BB2BD4Gc+BC5F/NK0yZTAEMXavjYjLB2Slsb1AHbILL4TmNfM7scrhFwZfC76slBTZZKA6yXNUr3RloTzM6/3qtkoGuj0aPR0N9AlEbxTXyGdoF5kZrsX3d4FpHYAzia1SBoDnIwLi1U0k9RWhL7gq4BU4XQ+vLvZjV0eBra3yL5t03Fjdce9lZM8+U4W2eUdH3FtED6nffC+uUkyq/7DH6QnB8ufcp/zXZLKg1zcAsRm9k7ZzueTsCvC21Nw396l8bLEjUjEA3MxEv+N3ALcHQIuKNY0eJBgHJxcztwZdQ5Cf30ScHnOzJZuafs2HvsLcsvwl0tIV6UQVKcfJRUN/BRYxqxt13cZxjEffn9IMvx/mNlE1RxDrRAI9524fRbkEe7MdhPhTgST4M+QOcws2/bS+rliXYcrXAOsbZHdn7Pefw9r4H32a5Ha1eXjRbx0/E7g/fz2B0nzAMfg94osvsEJ+iXlDuoo1uTAYTh5ybog/Aqcwql8zT9cE5YdZ2bHlPP8nQEhKHwFsBrjApuSSjU6BgOHFGoVqyWC5kWEf79JwP4vPNB7Zfb3p1hz4XO0cRkDnMNL/NZ0f3sTWKpOrMOQ1AMYhgerxwAzW2rd2UADJaNBuhvocgg3yAdIy4BeAFYIvZ4t7xtrZlw5Opsdew3Y2iJ7r9xjbQ8kzYhPpBZoWrgKTrPEcOBQ4Nz2luMp1oqk5VTfA7NZZH+0sEvdI6hOH4j3LffJrPoLn8AM7qhyaphs7xXOMXne6juBY8zsrfz9Ooowif0en+T8hgcUpi6w6QhyifZvBY51FqmF3GCLrGr2V+WGpI9wD9gRwISlXP8lHvd30n7qS81sl5a2L8P5euO9+yuHRd8BS5vZp8X3quh4TiEVjxsBjFONXvZaolTCndn+SFzcEeDaYBNV+vniHMX4KyyyHYMDx3p47+vKpNUoWYzA7913AveYlValImlenCzl21T9BJwJnN/h+2OsifAMZ/F7cGS/S+qHBy0AHjSzuio3rhZC7/C+wCl0oxdrkO/T8SBu+/lb9UfXHEE35Vpy7fOexfUmCt6rFGtnkpL6//idU/mFMU3hheuBrevl3iLpaLwFD+AkMzuipe0baKAQGqS7gS6HvEnh98DCZvZ1C7vk7u/Z3kNxUaxERfS/cMzzainkEsq27iCxeOmFd/3NBrh10ZYWdZzYKdZtuB0SwKkW2aEdPWY9QNIU+HdbOMsC57U1uh6qKvbHtQOKZf2OCII5ZUP4nS6LZ6l2pvgk/CFSol104qxY0+IZ1N54lnsmi+z7YtvXOyRdiXuLg2dNnm9h81KPuS6p0BXAZGb2S7Hty3C+7ngZcEKGfsMz62UP3rRhTOPh5c9JJqtqNmm1QBHCvYaZPdPCPhPixHFSPDM2l1npugiKNS7wAz/Sh3f5lyG8RXNrxAS/40GZu3CS2u4AqaT5cfK9YYFznAuc3dbKIMUtVhudB5xiUXrMID75Iy5U+BOujj/WTlRDdcl1wDwsjNc1dG9a/QGwnkWV15MohhAc2AsXB02eqaPwCopTWxJ4DBWGNwCbAfAt73IRM5IGZQ4ws7MqM/K2ISiwf4nPCX8EZihXILeBsQcN0t1Al4KkTYCbw9tRwErtLf1UrIXxyO0cmcUP4/YdVe9zlbQjrrjuBeST4JquLql0NnCYRfZfWc7lGf93cQI2EhezaYuqdl1D0nR4GfYukGPP8j3u/X1xaw/UUAJ4ELA7SU+9YwxwY/i7EycnfwKzdNRaKRDt5XCiPYC0TzyLUXiP9i3APS0R7bxjZ61RTrfIBnZkrLWGpF1JNR0ONrMzOni8Pvg1kS0t710pEbNAPi4BdgqL/gVWsSr7zxeCpP/wewPAL3gJdZezDWsP4c7sexiQBNquN7OtStinGy5qtj4TsAd/UkzQ8yvSsvGnyv0bDJnvw3EylNX1+Ad/Bp3RWhY92J/tit9ns/epUfjv+vhiz1FJD5D2zc9UbSX1ekP4HZ4M7Ec/vNw8feL8BmxmkT1caN8Kj2s6XLdktczi9/AMdTO7zILHiDUhXmbuFq7P8zAPNR1vNG7D+GTZBt0BSLqRJEDg/+N1tRxPA50PDdLdQJeBpLnxHrbxw6L9zOycDh0z1nj4w26fzOJfgN0ssls7cuySx+Dl8qeTlv16f9cmwHh8h/duP1T288Y6kVQU7C6LbINyn6PWkDQzntnZmtzJ5Rd4pcPVZrlCPkEB/RBccC+bXR4JXI33iX8ctr0In3gCnGtm+7Z5jLF6kEu0pyyw2YjMWF6yyBYvsE1L55gOVzrujU+sZ7LIfmjrWOsJoV81yQjfbmb5pbNtPd5gvDQ2i0mCeFbZkVexMxJY16z813lbEYIB+a0rbS6hrncUINx/4SXlrRLusH8fPNs9OS5YNo+ZvVtgu/Fwp4P1cVWOYhZ3b4Xx3AW8VkV7ukNxobOemVUjcLJ1Sj4hDver7fBMZ1bXYgzeuhVb1LJ/uaRjcTE4gE3N7JaWth9bIGl14EomYWo2JyvNOQZxIHBOtSrxQoLjInKrF84FDjWzNjkaKNZ8+NzNM+VXcA+fs25Y/QNerfhVhwfdQUhaFvexB3jezOpabLeB+kODdDfQJRB6dl8iiZZ6hnrbck1MFGt1XNgkK0p1DbBPqZnEdp1XmgQvL039WhfDp4HduQvYxaLKZJiCbdoHpP/zqhbZo5U4V60R+tGOpblFz4c4Kb8ZL+I/HNiKbIGfl0leApxmZlmrMkIf5sd4XmIU7sXdasVAmLguT0q0pyiw2X+4dsEtwL24Yvc8+AR/uraI6CnWeaSqrF2inSBkDX/F+6+/B6Zp7/1A0sL4/aUbTh6SAM20lRAzk3QoHuwD/z63MLObyn2e9iAoWyfWUqNIK0VWM7NHajOq8qKjhDtznENIle1vMrPNw/KZgbXxYuEVSasGshjDjMCcdGM2fmMyprTIRrb5nykDgo7IQLyNJduWMxovfT6JQXyIZwFj0udwgluBY0rVRclr4zjVrPPfj8qF0CJ1Kb1YjwHk1uHBZcCelRR+Ddol5+GB6gTf4G0m7c62K9YOeCAHxvAPpzCU4U3aOi/hbTU1LecOAcc3SJ0BFjKz12s4pAY6GRqku4FOjzC5vhOaIqNDcaGhsnqOKtZkeGldlph9DmxrkT1VeK8OnE+aA594+ASmGz5NW5h/8IzbJZWOaivWdsCV4e07wAJd2cIl2Mwdh0+Gs0jEs7Jet38BF+AibEV7nyXFeNYH4BYz27Tgdk60VyAl2vlibOBEOykdv88i+zOz/3GkFkW7WWQXFxtT3nlnwAMDvfDy2X7ZHsvODEkPkhKnWdojPhYqTV4kFQgaSipi2N/MPungMPPPtwuQ/e52N7OLim1fbQTrsuT38RbpBPQT3BKoU/t2h8zzHaQls+0i3OFY4+PZ7inw4Mk1uK3f7EV2+RfXYLgTuI9BnEdazrp6LUqIs5A0FS5IuSdZMbTZMdbgDyZppmlxP3CURW0jJiFYmZSeDzGzldo/6q6HQP52RZzJiozLcpmVxjOIjSpRqSRpebyaK1vBcAt+j+qwtoViXYZXkMFffMTp9CJ1oLkkWKrVFJJ2x+0ToQpCmg10LXQqD94GGiiCo0gJ9y/AgHITbgCL7Ge8m2pbIBGr6Qs8oVinhh62skDSmvhE3wn3eOGsC/MqsJBFdnGVysiugSYPzbmB3apwzprBzF4zs7WBZYDsRHEiUsL9JzAI6Gtmh7ZEuANOJ7Wv2kTSEskKxeqhWKsq1sXAt8AjeDl6lnD/C9wGbA5MYZFtZJHdmCXcAXdlXq/fypiyOJy0NP3crkK4A8rh1703KeF+C/dBTjBe883bD0kb44G9BEfWE+EOyHo4f4h7vwPMQloS3CkRrLjupzyEewa8Kia59oXfxfMJ91d4kGV9YHIz29DMrgqCZdkWpvwqnKrDzL4PWee+iEHMwp/sDGyBcgj3v7wOLGORrd1Wwh3O8y2QiJ8uHALrDQSY4yKMhXic17gNb0ABEMswhtcUa/5ynU9Sb0mnAkNICfcf+O95szKKSe6N24VBH2ZlG97HA80Au4SAZK1xLT4HANgqVCM20EBJaGS6G+jUkLQ2cA8+oRmDT5Aqng1QrL54xDcbY34DtxZ7u93H9Qj2gbhHqpO8qYDNMSbhZGBQtT3DFWtJUvLyCzCrRZVTbK4lwue/Ei7+s2ILmw7BCVFJitg50fHuPMuRHEc3NsZVgicrsMu/uCLxLcD9FtlfrZ7DlWC/xL1ERwCTFyDm+fvMiGe5e+IEo18ILnUJSFoZ97cG+J+Z7dnG/WfExdPGxzOVS+PBj6Q3f3Eze6lMY10V/86T3tnBuABcXT2kJc2Gt52AT0BPxO99PfFy84Vqqa7eXoQWpQdwITPwifWaZvZsifv3BJbEq2TWIq0AyMdo/H56f/h7q9h3HDRFfsSDOz8B09RDpZFiLYULTq6Qs+Ir3LDM60mG4LZpQ9rzG5Z0B+5DDt6W8357x9uVEbyxY6blUDZHTWaGYxhON7a0yG7v4PHnxa/z+TKLnwS2swp4VSvWrLiwmv8n93M1L7FtWD0CLzN/sdznbQsknYsHCAAONLMzazmeBjoPGtHDBjotgsjLdaQZyCOrQbgBLLLPcXJ2CGmMeX7gVcU6UHHbI/OSxqEH1+KZUf+f5gB25CsmYUWL7IhqE24Ai+x5/HMGt8AZVO0xVBpyrAM8j5O0LOH+AheMeSezbEXgOUn3Slqg1ROswFXMwVesBxzE0nTjQbw/Mku4/8FJ9qZ4RnsTi+zmUgg3QKh8SLLdvUjLqlvCEaQk75yuRLgDXiIV/WpTpjsEYM4jFWa8MARZslU0Zcl0S1ocL2lOvosrqUPCHZDNdP9jZu+RqnT3AC7qbJnJYPv3OCnh/hVXTW6RcEuaStJ2km7CyfGTuPBYPuHOXsP3m9lyZnaymb3Z0ndskf2DB2LAq19WKPV/qgQUawHFuhf3X07HYrzNk1zMpXxJ2sCxIvAYfp9cJ1xPbcErmdeLtHvQXRxmNsLMDucbVuJSviGRG+tGb+A2HaETQkC2TZDUTdKB+PeQEO6R+Jxn5UoQbgCL7CNgh6YFa7EFkzQ50vQCbgttDrXEBZnXe3S2+10DtUPjh9JAp0RQhr2d1Bf5dlLBmqrAIhttkZ0GLEpKyHoBZwCPhF7ZkiBpanrzMqPYsmnhcsCm3Ehv5rOo5pYZh5GSjT0Va+5aDqZckNRd0qZ4Kfk9eL9lgo9wu6ZZzWx3fOKxJZ4ZTrA28LqkG4M4UnrsWL0Ua03FupwV+JrNmZ6FyKdp/+AibZsAU1pkm1pkt1jUNq/wDO7MvN6gpQ1DtcaO4e2f+O+2S8HM/iQpV4R55f7JpWJD0raVb0mV/LM9yx0m3cF14QFScn8nsEudEm7I/Z+Tz+IkvNQcPNvbadpQ5P67TwALhkU/Aiua2csFtu0uaXFJsaSXge/wAMmmkNPPbHjAJ8KfD1PhvyGAdUsK1KWoeYm5Ys2iWDfi98m1M6s+ArZEzG+P225Af/yemb1HLoHfW1+XtKnce74UZD//Rds/+rEDZvYEfzAPV3Nr0x0PoDdH8CePBr/0khBaIx7FnwlJ69HbwKJmdpq14L1dDoTs/ODwtid7swTdeCG8nw64KVSW1AQh0Ph4eDsrsEqtxtJA50KDdDfQ6RAi5pfhSs3gvpDb12qSapG9gUfiB2cWrwS8qVhbtLa/xtFi9OYDhof/pwewEf+yEtuE8rBfKzHutsAi+4pUTbk7cGZ7ouf1Akk9JW2Plw7fhFcpJHgLd0Cf08wuTzxwzWyMmd0AzIX7e2eVyjcD3lcvna19tJliXYFPyO/Ho/Zp39cIfPryLBfjGe3NLLJbO0C0s3iSVG9gbcUtTkyOJM2snt1VWwZIWyO6kRtUKYqg0HtuZtG+Zk0uBWXLdEvqBzxM+vsYgiuV17yEuAXkZLoBzOw/Ums8gJPlPvZ1jUAunsL1KsDFu5Y3szcy20wqaXNJ1+DX9Au4MGJ+9vVX4Ea8z3VqM1vczI41s1eCxshJmW0HtWGY95EGNwYEwcWqQLEmU6yz8GfsZplVX+KVOnNZZDdYZGOgKet6OV6jtQV+p0swP36vfUfS9iWQpmymu0G6S4CZ/coINuUOtuVRhpPMiCZgJf7gYx2kfq0dQ9KW+DMwW+01GCfcbxTeqyI4jOTe3Z0Z2Ye/SQNXy1PlJEsBZLPdexXdqoEGMmj0dDfQ6SDpYLznGTxDt6iZfdDCLlWDYq0EXAVMn1l8I27j0Yw8a2rtyU+cy+gQAJsQ2Iih9GVAa16m1YZijQu8Tyqksp5Fdk8Nh9RmBCugHfESub55q1/GexDvNbN8H+Jix9qVbhzFzEzBPLhE0rgFN/8buIf3eIPbOAmnVD/g6tct9l23FYp1PT7hBVjFInuswDYz4ZnJHjhJ71cPwZ1KQNJWeE8iwCAzi0vYJ2uhdh/ukW1h3Z7A+WHdtmZ2TTvHNRXwDJ4dBCcZK5X791BuhDaM5Lo/xsyOy6xL1YfhVjPbpNrjKxWhMuUxoF9Y9AUeLP0UJ4hJb/aSFE9QDCXtzX6xpWBJuF98jGfqABYxs1eLbZ+zb6xbgcRnfmWL7PGWtu8owr1+X7y6I5vB/xG/R15kUev2TaHsdl08wJdPnD/HidMVIWhTaP+PcYG+/4AJzWpjmdYZIWkm5uU+1mHOJkO6fxjJN2xs19jdBbafBCeSm2cWf4X3blf091YMijU9Xl3hwqKvcyF3sRNpsHjLEAiv/tjc1WIYfj2PAWauVMl9A10HjUx3A50KklYiN8K5Tb0QboAwGZoPyD4INsez3isnCyR10wy6ie85v4lwTw9sxan0ZdF6I9wAFtm/uFdrgsGK1avY9vUESX0kHYTb95xPLuF+ElcrXtzM7i6JcMcSg1iAQczK0YitcROpLOEegfEDzzOajfCM9hZ2o53MqKZy0SmBg8rw7+WjFBXzI0n9lc/qqoQ7INuX22pfd1CXTwTX/gH2yqui6XB5eRDteoiUcL+Pi3bVNeEOyP7K8+3BBuLEDGDjQNDrDpJmxzPc/cKiT3FhsMNxovF6eL80ufOkP/FWpp2B6c1sQTM70syeba06IRDL9ma7syXmFQtkKFZ3xdoWF8o7mZRw/4uT7f4W2TmlEG5oqg66C68wWQ2/1yboi5O8TyUdFFrG8pFku8fBK4waKBFm9hlvMR+3ch5JDdN49KQfd2lTnZXdNghOvkUu4b4emK9WhBuaKuy2hJCzX5BdmaUp4AlwmaT5Cu1b8bH59Z44S3SjE7XUNFA7NDLdDXQaBCXhV0ntlI43s7q1qAml5RcAE2cWn8nTnMZ7PM03zNK0dB7+ZlXWtsE1791uEaGk/Elg2bBooEV2eg2H1CICudkH2B8XgcviAeCEUtWJARRrTnwSsCUwc7MNRjKS9+jBO4hPIGS03wAGmtkjYUz98XLNHjip6x8scsoCxZoQVzruiZeB9s3ayynWLPikujvuP97PIvutXOevN4R2lK+BafCs/qTFehJDNvI1YM6w6CAzG5y3zWZ49Qq0Q7lW7gP9ME7owL+jpc3sy+J71Q8kbYf3MYMHJC7IW5+tLPgSmLuegglBjflRPOgFfg32Ig1C5eM90mz2M0m7STvP3RvPdieVUIsV6h1vtl+sPngwYxy8QmZai8rbV6tYqwGnkttqMwa4HIgssm8K7tjW80hL40G/NfNW/QycDZxr5vejEChNni+7mNml5RjD2AbNrDVYkTuZsSnnDe/xGs+wKl9zNP58TPAbsIeZ3UidQLGOAbxCyfiBk3mc4U0Bgk/xqpGqB47lfvJf4PeOH4EZzEoLSDUwdqKR6W6gU0DSuHiGISHcD1DnKtoW2Q141juNFP/KAbzF102EW8DSvMU6zFDvhBuaFLL3g6ZusaMV11xJtBkkTSnpJPyBeCwp4Tbc83phM1urFMKtWNMr1sGK9TreA34UuYR7OJ6JGkBPJuR25uMD7iPNe80PPCzpIUnzm9nHJPZhnikd1JH/NR8W2R+kv7kZ8Bx8FkfhhBvgzK5MuME9bUn7uick7d8thKNJCfdLOAnIR7anu3AzQRGEPtZbSAn3j8CqnYVwB7SU6QbPkCUuEjOQm92tGSSNJ2k/vI1kysyq8cgl3Ild3154yehcZnawmT3eEcINECbkJ2QWtdrqABAcDB4Ib6ckDXp2GEGR/GG88iJLuO8F5rPIdikX4QYIVQFr4T3xWTuryfB79ReSTpI0JQ0xtbLAPrUHeZgZeYe0gm5OFmJlfmS8HML9ODBvPRHugOPx3yeIKTmIGfAEDPiz+Lo2CPSVDSFYflt4OwU1EjpsoPOgQbobqHuETNUFwMJh0afAVpVW0CwHLLIvgVWBA/mEUVwM/BDswHoDK3IBqzK/ndR5ynststdxITtwEnN8DYeTA0nTSzob77U6DJggrBqNZ9/mMbONzey1Fo8TaxLF2kWxhuDE/TRyyesY4BFcJG2qYO91h0X2n5m9bWbr4P2h2Z7N1XAF36vwzy8RPNtZ0pyUF3dmXm+QvFCs/sA24e1vwFllPm+94rnM64Il5pIWxO2ewK1xdixyj2mXkFrob70S7xMGL1Veo57aY0pEVgW5mfhfCHLsQfo57SWpbCSxLZA0i6R9JD2AC52dBZlsX4pPceG8NYHJzGwdM7vArCJtPpfj9xSANUM7Qym4JfO6wyXmijWjYl2FV3asmln1KrCSRbauRfZO4b07DjN71cw2woNg1+L3aPB79mH4PXwz0gBvwzasA7Av7QduYRZe46amT3pmurErMA2jgAPwAOBXxY9SGwShvq0hGKL1Yml25WW8ogv8uo1qM7qccveGoFoDLaJBuhvoDNgd2D68/gfYsBalRO3G34zLfWzBtfRoygtNhutfL8c8NBf06gw4ipQ07qRYC7a0caURJtcX45PnfUmzcSOAi4HZzGwbM3u36DFijatYmyjWncD3Yb8VSH3gwTMv+wPTW2SrWWRXWtSkap0DMxsCLIaXog9LToOrG7+I942C34dPzt+/g8gK5WT7uo8mzXIPLjb2LogWSXfIQF9O+tkcZ1aUcGSzuyXZ8ITA4TnQZAk4HBdnazH4U6fICmsV++1/invAJ7g8lNVXFJJ6S1pF0mBJH+Cl3OcAa5BaH4ETuSHAgbjSdn8z29fMHjSzQtn7siFky7OBykEl7nov/rsBVzFvV2ZPsSZWrFNwIcVtSe9vw3ABxsUssiHtOXZ7YGbvmtk2wGz4PTcRSxuXVFsBYL7Q/tFA+9GXu5mWq0id4ycGdqIHy7Mh3r5Ql7DIfsKDTV5DNi27swzn4AFwgKMlFdMwqSSeIVXpXzIEbxtooCAaPd0N1DUkLYV7qNZcrbI90E5anKd5hI+aMq7Qjz/ZjD6M2zTZ+RPYG7gm23tb71CcoyL/NLB8tccfPI4PxyeL2SDiv7jIyelm9nXR/d1+ZyWcDA2AzPeU4iPgOuB6i+yjdo6zNx4FP4qsfZhPGJJxL29mT7Xn+AXPGetFnPSDl+D1xPtTu+FZv36hFL3LQ1IvPEjUG/jEzPrnrT+SlAi9ifcIFlRKDj3BiRPupWa2Swnnj3GbKfCM3gCz5grCnQGSzsJbTACWMrPni2zXHRcrS4Icp5vZwELbdnA8M+CZrrVwv9zWAiFD8QqD78s9llIRgjwfkgq5LW1mzxXfI+znAcGEWCxvUen3C8XqjVcgHE2uvsWvwHHABaUKpFUSkqYHDsYt6PLbNx7EdRaKBk8baI4Q9NsWr+bwZ9wEGFvyL9NkqnWG8itDWMl+s6G1GGcpUKz9SCu0fudsLuBXDg/va+JmI2l30paxkp4JDYydaGS6G6hbBJGKW0kJ95mdhXArlrSljuZuns8h3DNzJ8OYmHFZkbTEcALcZux2xZq6BsNtL87BCSl4j2HV7IEkLSzpdjzCvBXpvewPvIe0n5kdUIhwK5YUazHFOhsvV3sI2I5cwv0tcCbeRzi7RRa3l3CD93IGQa5Z8EBFMrnN3oMvD5OjciGrYr4ePtlOznfG2EK4oSm7mPSHzhLsugCQNBe5hHjHVqyJsp/bREW3So+/b+b4hON3SsIdMGHmddHfUCjN34n0t36gpJJ80luCpHElrSbpNElv4vfRi3AymiXco3ENhmyLwL3AkrUk3ADh95XNdpfU2007SswVq5tibYYH3M4kJdzD8XvRLBbZmfVAuAHM7Csz2x8PSJyE24UlWAP3+b5N0kI1GF6ng6Sp8d75K0mfcZ/zJyswDZPwdUZzZgEmYWNe1QwaWOZnUTlxDqma/0Tsyxp0a3o/AXCHpELB80riOpzwA2wV7NcaaKAZGpnuBuoSITP1OKng0BN4v1GLtiz1AMWaiFe5j4dZumm62YsxTMde9qldmLOdP0C2zez+C571vrEzZL0Va13SUuYvgDmCtVhlzictgyvfrpG36mc8+n1eonzbbN9Ys5Mqj/cvsMkfuCjKdcAT5VYHzhmL1BefdG+dt+oTYCezjovqKdZcQFIi/SIeQOiG/8b6WVQ/itLVgKRTcH928EzzHSEb+yxuaQRwspkdXvAA6XEmxrODAA+ZWf5vMbvtNsDVmUX7m1khcbZOA0m34VUhADO2JgIn6VDS9ol3gYXaovAbeuEXxPuOV8WfCYX6ssGVvR/AlcYnwMl4UoZ9C7B1R8XQyoWQ7X6fVJRxOTN7usV9/JnxA14q/y3e5lLU4lCxlseJdb4I2TXA0RbVv69wsLN6tMjqB3EHimeqOKROgUCat8Cz29nKhquA/czS1iLtpiOYkuPpEarv/gTu5XE+YEB2u3pBcOh4BZgVgH+4nFNZnFQk8zZgE6siwZF0Lj53g3a4WjQwdqBBuhuoS0g6j1SU4itcbfqHGg6pJOgoLc4QHuS5jE3YBPxCL5a3n+ztgvvE2ggvTZois/hOYA+L7LsKDrfDCBZiD+IiYQDHWGTHlfUcPnlYFSfby+Wt/ha3lLnYzP5qtm+saXHv0S1JhfiyGIFnv64H7rPI/iuwTcUQsjWX0Vxh/B7gsI6UUYbv5kM8wGCkvZuHW2Tl7iGve4R+vzvD29PNbKCkA4EzwrIPgAWCn3JLx+kOTdr0L5jZkkW2Wxe4g9w+8WMKbduZIOkRvIwbYCKzlismJPUAXiC9/lq1epTUj5Rkr4SrYBSC4RUM9+FE+zUzGyNpB/y6Sn7z1+AVBnUVtJW0PXBFeDvEzFZqdZ9YdwPrhrfLWtSccIaA2ylAvk/6Y7jN4+v5+9QrQh/3n7jCfPI8zK8IewpXhX+kmkSrXhGy2/8jI6KJOyXsYWa3FdznIC1NDx5kPNwvfTTwKD/xImvZ6NZt7aoNxZoXDyZ7C8J7HMJNHElafXSYmZ1StfG4GGryvP4ImMOseECsgbETDdLdQN0hzwd2BLCsmb1UuxG1DsXqxi8cwf0cy8cZ4a1JeI5fWb0QIczbfwrgPGDTzOJOkfUOE7w3cXLxD16O3WEF1JDhWg8n2/nKtZ/j2bMr80mSYk0MbIQT7RXJFUIDn6g/jhPt22ttmRWCCq/i2bwsxuDEIbJ2+ngr1ml4f2SCn4CZggXRWIVgQZSUFT+HtxS8iU/aDL/PlOTZLulPoA/wrpk1syCTtDzetpBkZM8H9ukKhEDK0QroXsrEUtJ8+G+8Bx6wWNQs7RsN1QMr4SR7FQpXoiT4HHcOeAR43Mx+yq6UtBd+L01wMU426m4CHAIS75H+vyu0VuWiOKd64hyLbL/MumnwUvWdyG1deQsYCDxcz8+SYpA0FLczG40HYLbEnQbyRUhfxsn3PfX4fVcaLWS3bwb2NrMfW9w/1hT8yeNMwDxNC4diPMTh/Mtp9faZKs6ZK/7LdQzko6Zrfwyu3fBI1cYjPY7POQBWN7OHW9q+gbEPDdLdQF0hZP6eJVXR3NnMLmthl5pDsabgc27jTpZtKjoVMBEn8RtHtmWirVgb4/ZonSrrrVjnAPuEt9dZZPll06UfyzOJm+Lqx/Pkrf4A7/O7Ptt3q1jjAGvj/d1rk6tUnOBVvHT8pnL6zpYD4Xef2ItlxdXAAxmn49nZNpWEK9YyuMhdgkMtslM7MtbODEkf4iWJI/Dsa1I5cY5ZSl5KOM7XwLTA12Y2fd66hfB2mKSv8Aa8rLmuJqzthaT3cMXvP81swta2z+w3iNTWZyhwED5BXZW09aEQfseDZAnR/qTYPVXKEXcE91k/oJ6DHXktCE/hxLvoeENQ8Qdc6+RrYEa8l/3g8JdVif8aF2+8ppLtMpWGpCvxIBm4yOGroTx/S1xIc/a8Xd4GTgRutk5gLVoOtJDd3tPMbi24U6HjxOrBn1zABKRiYN8AtzOEn9g0P8hVayjWJcDO4e2HnMhtjGgSVvsFr5IcVpWxSBuR9pvfaWYbVuO8DXQeNEh3A3UDSZPjxGPGsOgiM9u9hkNqFYq1AkO5nfuYpMnopCf/Ija04fZQO4/Z6bLeijUpXlKVRNeXsqiwqnHRY7il0A64jc/MeavfwDMYtyeTqGCZsyI+8dqIXIGnBJ+QKo/XtR+ypGvxoAHAk8BC5Iq7fY/bC13WitBXesw4R2kbYHKL7OeOj7ZzIm/ynuAzYF4za+Y53cJx3gXmJI94SpoNt5BJgmYPAOuX+n11Bkj6BpgG+MrMZihxH+GZyvvDvi1hJPA8Kcl+tbWy8HD8o8kVJDsJ2hb0rAVCtvsd3DILYGUze7yFXVCse/HgInhAbltgyswmiaDk2ZXU2KgWJB0ADA5vcwLxIUi7ER6knT9v10/x9pErzewfuiA6mt0uetyjtBXduILuQcj2H+B2fuZjNiqH5ki5oFjj4pVLCwAwhps5lvFIWytex90BKn4dhGv5C/weNwqYwax+kyUNVB8N9fIG6gLhZnUjKeF+gdSWpu6gWN11tI7lIYZwZ4Zwj8NHjGTO9hJuAIvsR4tsM1ydNnlgTkooh65HhXOL7BdyFZrPVqyS7i+SpghZsC/wYEOWcD+PPzwXNLNbGMQYxVpEsc7Ee/0fwYl6lnB/j2e4FgdmtciieifcAUfiGVjwsS+LC+0lhGMqPJPxlqQNSlSXPSrvfcH+47EIhWyZdmkL4Q5I+pgnCJP+xLrqEVLC/SywcVci3AHJtdZaL/c0kraRdDWecX2d4oT7HVwIcW1gUjNb3syON7MXSyTcJ5FLuI8ysyPqnXADhP/v2MyiuIRrO6tifjAp4R6F3zP6W2QndwXCHTA083qB7AozG21mN+PtOevic4cEM+OtHZ9LGiQpW0HW6ZFRJr+OlHD/iIuIbdZewg1gx9t1dGdhRuBVYeMBWzIZSzEkfJbt8okvN8JvfGOS+1E3NmVfngY+DpssCFxYDTX2cC1fGd72oHmAt4GxHI1MdwN1gTxl4e/xkqCi/sq1hGJNx+/cwh0sybDMil7cxAh2KGdEtTNlvYPn9VBSBdHtLbKrim4vzYJntXckbSdI8Ajesz3EzEyxZiVVHp+N5viTdPIxxKL6EkwqFVJOD/ZVZra9pP54qWS+RdAzwEAze4ECUKx58Cx3drJxmUW2c6HtxwZImgfvb01wiZnt2o7jPEQqHjgxXur7NF52Df65L29FlPQ7K1oSkZPUBy/XTwTQmvW6F8AneDl1uzQggu7DWaStLeA+zoML71GfCJ/r26S/n9WK9aIq1pJ41neJvFU3A0daZB8336tzQ9KkuEMFwNNmli+omd1WeAXUYfjvMIt/ceG6wWb2SSXGWg1UKrtd8FyxJmEkt9CTlZsWvgPczTMMZ/N6macp1ob4HABgJE+yHUO4lLTdYm8zO7/i4/B5TXINfgzM1hmCfw1UBw3S3UDNIWkT/GEBPqFbyVqxTqkVFGttvuQ6bmGipjyPGIPYlzFcUKmba2fp9VasVXDCDK4sPnu+NZWkxXBRnwHkVtuMxqsdTjezoUEUaDOcaOdb3oBnhe/HKwDu7QpZneDv+QkwCS7utaCZvRHWLY6Xki6Tt9utwBFmuT7iinULngEA/6x64b2g03bm/s6OIE8tegyeVW2zJY6U89nOhffkJmJ/nwDLdMWywjy7tIfx6paEZC8JoRS1Of7GWyYewYMT15MGz9pFkgNRvZC0nxO8f/V/bT1WPUDS5nj/P3iFz9LZ50kIPJ6El1LnYyeL7PLKj7J2kPQFMAOe0Zy4lGetpAXxIOZmpC4C4Nf+bcBpZvWnzN0SytW73aZzxurGGAbRjdR14AfgJn7lZ7Y2s/srcd62QrFOx7UiAL7kLAbxG0krwihgRauCvZykx3BhSChBHLGBsQcN0t1ATSFpDtxvcfywaD8zO6eGQyoIxeoFnMRrHMh9OD0E6M7PjGY9MytUtlruMXSKrLdi3QmsH96eZJEdETJSa+Jke/m8Xf4GLoHwiHQyviX+0MovUTdcpOp64DaL7Fe6GPJsrHJ8oEOGYz3cDigrHjQKn4gdZ2Y/KtZ8eB88eOXIi2E/gGUsKk2luytB0jS4pcvEmcWzmNmn7TjWpbhCNPhnm/h8f4MT7s86MNS6RPjtLYuTZ/De62IkewyuJJ30Zb9gGX9sSUvj5Ft49nE+s9IztKEd6UpSDYQxuCVY0cqaekcIIryJB3HAlZcfCvf9Y4Dd8ZLVBN+SlusPtsgOogtDyrFKm7kt15ikvsD+wC6kc40ETwKnAg/Uc0aymtntomOItR5juJ5u4TP8D88tf8gZeOB3REv7V2F8PYEhwNJh0YMM4m3S6rHv8CrKigqpStoCn6MAXGfWfmHZBroWGqS7gZpB0vj4hDUpQ7wW2LbeHnyKNTMjuYkHWaRJXxqgGy8yhg2tnXZOHRhPXWe9Fas/Tm56Ygzneo7mI7ajebnp98A5zMZlbMlS+AR6HVKbpSxeJ1Ue77AdWT1DUm/gfaBfWNSs1DSQjp3wPtapMqv+BE7maBaje1Pg4wA8O3lleH+6RTawMqOvT4QJ621AvprsFmZ2YzuONxj/XLP4FVjOzN5u3yjrD5ImA1YmzWbnWzRl8TFOsB/F20JaDIhJOhvYN7x9Eq9wKsV+rBc+oU0yvqOBrczsptb2rXfkVH314hUO5w7EYTQXVIxwuvMNTsS/APrVS+C1EpB0HKlGxQAzu6Mdx5gUD17sS+59E7xo+nTcGaOm5DEftchuFx1LrNkZw910y7R5PQE8ycsYm7cniFlOKNZ0+HzB50cjiTiB5Ukzz8/hGe+Kfcdyb/mv8eDIcGCa1u6HDYwdaJDuBmqCMAm+ElddBX/gLd4OQaOKQrE243cu4WYmILdz6Ty8LLImD+d6z3rrCJ1Jb/YH3IU2dzr8IeI0DuRDJmBLvPRv4gKH+RSfXF9vkb1XyfHWGyRtiQcZwDPWCxUiJJImwMvpBpL0rk2NTysBjG8Rs4R1P+CVA95n1oUn6PnIa2H5jfT3Ntis7RlCSRGuJJ/gb2CVYv31nQVhsrg0KcleEJr53Cf4D7ibQLTbassTgq5vATOFRa2Whofx3Uqq3D0C2NTM7mrLuesVkrohhrIA87Ii+X4Mf+N2aGdYZH8BKNaDwOph/eIW2UvVHG81kWfHdKyZRS1t38qxxgG2wTOg+RohX+NCnBe3p/WknKiH7HbBccWaAOMKlGl1+AC4gz/4j12CsF3NoFgr4/clAcZnbMJVnIm3JwCcZ2b7FD1AOcYgnUUqBryPmZ3XwuYNjCVokO4GagJJOwGXhrd/AYua2fs1HFIOFGs84CyGsQu34NMdx3Bgt3opY6y3rLek6YH96M1u7MME9AkrrgU+5llm4TK2Ymq6sR3NvVUh6RRzsv3i2EQMswjl+C/jtmHgFSDXtLD9NHj2a2c2oztzhhWP8S1PsxNeZjeEtLR/bovs3QoNv64QrAjfJb1Gdia997QoylTkeMJ9o1cIi0YDaxYTvqpnhN/ZfDjBXgUXQssXNUwwHA+hLRDex2Y2qIPnXxnPjIM/B+Yxs8+LbDs+cBc0CTr9B2xg1n6niHqCYglYk3/5H+M2uXiA/74uBWKLcquqFOc8R7t0BUueQNVdZrZBGY7ZDW+7GQgslbf6D+Ai4OxaiIXVU3a7EMLv9RCME1FoA/sZf3r/wMXAAVZDmzbFOgo4Lrz9kevYjo+4g7SSbrNKBgekHLvON4EF6q2Ks4Hqo0G6G6g6JM2P23okk7t2lXhWCoo1N8ZNvMjcPIR3ETu+ADY0s9dqNrgCqIesd1CFPhjvxfY+z/nw7myAUfxCD17BJ/b5fdr/4KW/1wGPdVbl8XJD0oo4uQP4Epi9NWV8raX1WBzP+v1B1nDscQbwOvM1icwcYZGdVIlx1xuU639+Oy6A9hleKv03MJFZ6cJykg7Be+oTXGxmu5VpuBVHsDZLSPYq5Abs8jGUtGT8GZygJGJfB5rZmWUYz8V4ry24ONsa+ZNTSRMC95GKCP4NrGNmT3T0/PUAxVoIz2KvlLPifWAY29rzhQNuijUZXm7eHRgGzNxVA5WBIP8O9AE+N7N+ZT7+Ujj5Xp/c6o6ReBD49Gq0jrSQ3b4Jz27/VOkxtAWKtSrGjSiMdQQeGnuHd/AqlJoEd4Nl6X1AoonyLMdxHaO5ILz/E1jEzD6s2BikF0j1PhbrbKJ9DZQfDZ/uBqoKSRPhJWIJ4b6gXgi3YkmxdmYEL3M7c/MgWcL9KC7AUVeEG2rn6y3HCpLuw8tEtyMVVhrOCO5kND8A0INJcYul7D3nSdxje2qLbFuL7KEG4U5hZkNwdXbwsrjWy+EWZ4um16/yOemnuRK3cyB34fnE3OxJl4WkdUgJ96/AXoHQJZOf8aGpLqCU421NLuGGNPtWl5A0o6RtJV0m6RM8eHgZPrHPJ9xfApfjwbOpzGxBMzvEzB4OWatswXOLPt1twEBoat5ZDdg+b/yT4vffhHD/DqzaFQi3Yk2tWJfhYqIp4f6LT7gC93J4gaIiTBbZz6SBuX7AwhUbbI0R2msScci+wemhnMd/zsw2xO8Hl+CVHeDPtO2AtyTdF555FfF8VnHf7Y3NbPN6I9wAFtkjiIUxXgfcI2MTYFXmphuvSNqpUp9XK+Mag7cQfBkWLc1RzEzatjUBcKuk8QrtXyZcknk91lp1NpCiQbobqBrCjfcyoH9Y9Cru01xzKNaEwPX8wiVcxrg5Tr4+yV6jHh94WVhkt+JiZdmSqQ2AdxRri1AO1mFI6h56ZF/ClULXalo5Ib+zAY9zNF+wORvQnSnzdv8aF/+axSJbwSK7Mt9SrIEcHIorMwMcEYStCiJYCiXVDj+yKHPh/fKJsI14Hc9+P8ti2kX9KjPk+kCwt7oos2j/jI1XNuNQyI6u0PFWJbUby2Kidg2wQpDUT9L2kq6Q9BnwOXAVsCMwc97mf+B5qX1wj+i+ZraTmd1gZj8UOHyWdJel3zX0zWYrBQZLmjb8L1Pi95jkO/oZF1x7vhznrhUUq7diHQJ8iH8vyb35E2BTrmMOPidR515NUku/0VsyrzctulXXwBuZ1/NV4gRm9oGZ7YoHMU7ENSASrIX/Hl+UtElQnO8wQgB7S1zbZoPMqpuAuczstnKcp1KwyIYhlgbSioylga0Zl/G4FLguVKtUe1w/4dfESADEwezLfXibDMC8eEVBpXATSZgbtpTUp6WNG+j6aJDuBqqJfUkVZ38DNjGz4cU3rw4UaxHgNT5icy7Gi/Ucf+MR5sPaUn5aS1Qy6y1pPEl74hPFm0l8iXsA8/MT+/AeBzABC7AS3Zk1s2s2e/0m3ptYU4XTzoJQzpgQvYmAI1vY/DDSe/qZdpr9E3rW5sTF1pwkjcALhq/hJUnr1SILUSWcBkwbXj9IdkLYRtIt9/u9ndSy6fbM6qpPJhOEyfosknaUdLWkz/HS+SvwjHG/vF2G4xUmg/Bp8WRmtoGZnRfIRmulydkAQ7ky3ZjZfaTfz8TA/wLxfpKUXH2Pe97WXbVRqQjVVOvj5OoUUlXy3/FrdC6L7Bb7xkYBJ2d2bem6v4P0Hrt5KKvtqhiaeb1AJU9kZt+Z2ZHAjLhTwReZ1Yviz8APJO3ZkWxpZ8xuF4JF9i9eEbAvFn6PMwO7AtOwBfCapKpXYlhkL5B6d8OkXMgiHIC3tQHsKGn7ipzb7C+8XgW8LaKrB8UaaAWNnu4GqgJJS+C+rMmkdX0zu7uGQ0qEQPZjDKfyDD2bivQcH+L9251WbKqFXu99gBtK7f2TNAWwV/ibvGnFdMBi/MTcjEuPZt6n4BPmK4GH8PLJhAANsKjtdi9jKyRNB3wEjItH7OfIt2VRrBnxLFkPfALf16Jc5V1JUzAR/+P3jOKs41Fc9KYrWV2tgocWwHv35jGzLzLrJ8QDfwJeMbOixFtSP+B5XBcePDN8BE6cAK42s+3KOf4WxiK8Umh5XMhteWD6Fnb5Dx/7k7ixz4tm9l8Hzp+1+VqynGrtoYz8XVIrp+8zr78CVq5k/2WloVjzAGfiffQJxuAlqEdblKtELbcO/AS/04J7mefWYKXHvpdU0X15i+ypco69XhAy/olC+xVmtmMVz90TD2YPpDnh/wl/1p5fKknubL3bbYFiLYtXYPj1Owq4B3iDkcAhuDhd1chHmOvdSDoXGspJnMNwLg/v/8XdcwpeXx06t7QYbo0L8LyZ5Qv2NTAWoUG6G6g4Qkns66R2DaeZ2SE1HBKKNTlwBf+xDnfigjUp7sbVomtqF1IutFfhPKjFHoj3XY8LeF5mPmBR/mbigkT7c5xoX53NZivWpqTGYV8Cc1pUX/Zw9QxJx5Nmu240sy1y1sc6FxfOAzjeIju64HFiia/5hoeZmlyN6NHAhUBkZj+XdfBVRijhe4s0y7uHmV1YYLv38JLqkcAEhapuwr3rWVKl/edx0jQR7pEMcGfoBS07wsR8NlKCvQIwTQu7/Iv70CYk+6VyVhNJSjLo4GWvZbXykzQAF1XM4jOccH9WYJe6RxA7i4E9yK0ufALY3yJ7o9B+AJL2x4k6FLjuM+fIWgxeZJHtXmi7zg5J4+Llut2A181soVZ2qcQYhN8DBuKChFn8i1eZDDazT1o4xtT4/Xb9zOIf8XtVXZeSl4rgl30rsETTwpfwEPxo7gF2qOazRrEmwCucknv5pQxiDJ6LB0+0LGJW3na38Ht5Ay9lBw8Av9PCLg10YTRIdwMVRVAcvRdYMyx6Bu/JG1mzMcVaDrieH5mOG/EuQYcBxwAnWgFP5M6MtmS9QzZhIN4K0I0e+GNqAYz+gJr59v6DP1yvAJ4KAib55xf+uE0mKSdbZIeX438bGxAysx+TBk4WNLOh4GJMODEZB2+J6Bd62QofK9a5GHvzHnAnPzIiJxjzK249dmEtr9GOIC8b+wRO2Ap5nF+NC+1AAWXZMMF/DFgyLPoAWNrMfpbbVyW9ekPMLFd1uv1jFx4IWAEn2cuTZtgL4R88KPAETrRfNrMR5RhLkfHdRupJMH25rZQkzYVrfSRCm3/i5P6rcp6nGlCsnsDuOOHOin4Nw50ebm+t2ij8zj7Dr/sxeJXLRwXO1QevDBgPv69PY1Hlfge1hKR38ZaZEUCfms4lvO3kYFw7I9vfPQYPHp2Wva+E63tLPLud/U10+ux2IShWb+As/DpwfIEX5v/F17hzzdNVHM88OPX3JMLf7Mpp7ElauXBTGFNZiZGkfXHvd4AzzawutIwaqD4apLuBikLSEcAJ4e2POFmouuclgGJ1x7OFEe/RjTvwx7bjN2ArM7u/8N5dA0Wz3iPYgxNZCC/9ci/n6fBH0Twkj6h8PIVntW8tRQxNsWbDM5C98OzifBbVjzd7vUPSfvgEBuBeM1sXQLFOxYMkAGdYZAe3eJw44408nJs5iTeBwyGncuFdXHisU3lPS1oab2MRnnWat1jGSdI+uKwcuKr5BZl13fFJc5KJ+g4vpx4W1gv/DXcHXjWzRdo53m7AXKRZ7OWgmfhgFn+RS7JfqSbpkPQoqU/2hOXMCklaAG8JmDxv1YZmdme5zlMNKNZqeIZ6rsziv3FhrsEWlV7iL+nwsB/A5Wa2U5FzXg9N7gXrWWT3tHngnQBSzv9ZtOS+mpDUF9gft77LrwB7AteXeI0unt0uBsXaEZ93uEf2nzjx/pIxuL7EidXSzVGsbXFhSYD/eI7NeJhrSLU59jaz88t6Tm+d+Qb//38GpqsHPaMGqo8G6W6gYpD7DD+Kl4IZsJqZPVqTscSaFriWMazI43i+PcVb+MSuaDlYV0JO1nsU/t8/y2h+ontT+fgCFHPvTZSQr7ao7Z+X4pwy6ceBVbqqr2y5IWkcvLc76eFdkkF8iH8nfXCRrJkssm9bPI5n4H7ABat+B6ZkEFMAJ5FmfhPcAxxUKLtWbwiZ6aF4OTa04iMddCYSFewrzWyHsFzA+Xg5MPgUcbmksiCz/y94tupjM8sKB7Y0xm54GCtLsvNJZhZ/4kGEJ8PfazXO7L2Ei0gZ0KNcFUGh7/Eh/DcJng3uF15/h2e7fy3HuSqJ4CBwBrBu3qqrgcMtsm+a79XKMb3K5XP8sxkF9Dezz5ttF2sd/HoFuNGiwqXonR2SDiUVmdvWrLCHeS0QyNXueKXNVHmrR5ObDe+S2e1iUKxF8UCmtxmOxuUtvQ7gcWBrs5afXWUcy0WkZeVfcA4RvzQJlo7EK5rK6qkt6Tq8ygFgczO7qaXtG+ia6Moqlw3UEJKmAW4g/Y3FNSTcawBD+YcVuY58wn0DnsEaKwg3uMI5g9iVa7iGsxjDfcBUdGcrXKN1VfIJ9z/4pHElYGaLLGoP4Q44EZq6iVfCy/IaKAFBAOvYzKIT8MldYkNyeWuEG8AiGwncF95OBCxvZl+b2bZ4/92Lmc3XBd6RdGotLF/aiIiUcL9AmsUuhqGkqs9ZIbXDSQn3KGBAPuEOSDQfin4ukrpJWkDS/pLuwDNbb4SxDaA54f4Db8cZGMY0qZmtbWanmtmLdVDyn/yvf5SRcC+LB2cnDoueBxbEPwfw8vrB5ThXpaBYEynWabi4XpZwvwAsYZFt1x7CDWBmf5DaGvUgrWrJx0OkzVLrh5Lzroihmdfz12oQhWBmv5jZiXjAaFdcCC9BQrjH4M/TXccWwg1gkb2MO548AfinsTae9+/BSsAbktao0nD2JX3Ozci+bIuaqsh6AjerzD7wwKWZ1w3P7rEUjUx3A2WHpB74JGr5sOgRYM1qlQ81jcMzeicAA/kWjyv/1rR6ND55OauaKpq1RlDC3g/YjemYsJzl4yWPIdZ6uAI0wLfAHBZZ2eyHujKCgu67QH96AYfyZ6hPGA30t8jLn1s9TqxNSP3cz7fI9m5a59nYLXFLo2kzu/2AVylcUe1ruTVIWgQnON3xppEFS3EekPQaTvDG4AGIjcn14t7GzK4tsu8beF3IcDMbJyzrjteJJP3Yy5GSyUL4Db/OEuGzN+rts81C0je4kNuXZjZjGY63Ci5cmdyBngDWNbO/wr3qXVKiv6aZPdjRc5YToWVpB/w5k20L+AZv1bmhkMZFm8/jgn6f46XLXtFSICuoWP8j7Z/d2iK7Ln+bzo4gQpb874+Z2SotbV8LtNC7ncUfwEW4kndNWu5qAcXqgVcqpDZe3+DzMw9jngocVekAYxB6e4VEM2MEZ3Mii5MKv90DbFDG4GI3XKxtlrBo5s4qDtlA+9HIdDdQCcSkhPsbvGyo2oR7JrwscyBvAJeRJdw/AquY2ZljC+GWNI+kK5mAz1iagezFhOyC59IKE25wQZ4Hykm4ASyyu0mzWNPgPV0NlIAwEYkA/+66N/n8Xlsq4Q54kFTRYP0gdJecY0wgmrMDx+OTfHBScQnwcshO1gUk9QIuJ80kHVsK4Q5ISgi74WQlm404tBjhDkgy3b0lHSrpXjzT+ApeYrwezQn3L7hzwAE42Z/czNY3s8Fm9lo9E+6AxKe7w0GyoFR+H+kd6EFgLXNvWwIROSizy8X1VG0RBDlfwa+JhHD/h18zs1tk15WDcAMElef/hbe9cVeJQrg+83rLItt0apjZd7hoHMACgeDWDUJQ4A7gWlLC/QNuM3gn3poBHkwaCHwm6QpJc1d5qDWBRTYq6I5sQeKVPS1eFzAT4MGqp4NVYyXH8TUeZPVqp17sx7ZcT1otsi6595+Onc/Je/b5UlCboYGujUamu4GyQtJapKWro4EVzOyZFnYp/xhibQBcyWgm4mFyi2VduXKjzqiG21aEycjy9ORQZmMNFsBjrM1DbYn6+O34gzBb8t1mX++SxuZBkXdxleLRwIIW1V4QpzNAUjd68ib7MTd9AMMQc1pkH7TpOLHuJ3UVWMQie7XI+frh2YdN8lbdDBxSqL+0mpB0DB7oAy89XazULImknXHSBB6E6BVenwvslx+UC5UGC+FBxYMppnyQ4ic8k/0Ens1+u7M6I4QKpuRzfc7Mlu7AsXbGs3zJ3ehOvM9xeN52wiulEvG2C81sD2oIxeqLC2PlXw+3AIe0MfhV+nm9ZesznHT/DfS1PMslxeqG98PPgN9Xp8n3/+4KkPQgsHp4W3YV/faghez2jcA+SSm5pNlxMrctibBYivvw39ZTY0NCQLHmwwMUMwNeb/QobnroQc3tzOyuIruXawx74CJvAP9xMwfzLufiYpyjgRXLpbAeruEv8QDxN/g1PKrlvRroSmhkuhsoGyTNCGRFTQ6rJuFWrJ6hr+4O/mQiriKfcF+K9692acItqbu6aRP68TZrM4QDWYNNgFnJv+KfxqOtU4eew7ssss3x6G8yUZsU93+9W7FmoEywyD4jVeTtDlyQzbY2UBxmNoZNeK6pk/sj/mAQ7RE6uzPzeoMWzjfMzDbFhb+ynsKbAu9LOjZYG1UdkuYBjgpvRwM7trEsMSuWkxDu24ADzMwkjSdpOUmHh4n+r3gZ+ykUJtw/4gGsvXFf1qnMbCMzO9fM3uyshDtggszrdme6JR2CBzqSu9FVwCaF1HwD8dgFJ5kAu0taob3n7ggUa3zFOhZ4n1zCPRRY3iLbtFKEGyCUkyeZsvHxNqHcbTyznmS7u9M8MNBVkL0PLVCrQSQIc5+7aZ7d3sjMtsj2bpvZB2a2K973fSLZGjzvcn4CeFHSxqFdpcvCInsT7/N+APA7wmr4DKQXEwF3Bj2RHhUcxoV4LSTAOGzKQMZp0pDoDtwoqSVHiZIRruGkym9aoFo97A3UCRqku4GyIJR43oyTNPCe3TOqdn5XJ38MOJgvgYtxP0jHCFy0ZJcgRtUlIWk8Ta/DWZ7v2ZOb2Z65mpWPG18CxwGzWmTLWWSX55ePW2S34VY3WXXNdYB3FWuf0MdYDpyGe08DLINH/htoBYrVi1mbMtTwGBPRvsl11lJog9Y2NrMngYXxQsAkKDMOcDTwgaStqlnqGSZil+PCNwCnmNnrbTzM96TlnuBhutuB04NS9+94hvpEPLNWLLhwEn7NTGVmm5jZ+WbWabPaRTBR5nWbSbccp+IBiwRn4oGSotme0Pd4WGbRZdUM8iiWFGsr3Kf9aFIP8R/xa2ERi+ypKg3nVFLxv32KlNt3+RJz6kRMTVL34MH8Dv6MTHAjMLeZ3V5sXzP7zsyOBGbE202+yKxeFK+c+EDSnpLGK//o6wMW2a/4Z3dc08J58HSAzyYHAo+HLHElzm94kPSlsKgvA1mQRPDNyfH1ZQyANATVxmI0yssbKAsknUUaef8MWLhaFi+KtSJwI8aUvArcj5cpOb7Go80vFtm900MzqD8zczozshYz07NZKG0MI4Cb6cYVwBNt6TNUrAG4fdLUmcUvAruUoxxcsVbHeznBJ7Gzh4dwA0WgWDuRPLg/wPX3XaBl7raWqinWc8CS4e0cpZaoS5oIJyD74YrKCZ7Hy7LLardSZAwDcRIC8B6wUFuCaoGwPItP8UrFt6Sl4gvjWViAlcz+z95Zx0lVfn/8fXaXUEAFMbEbUcHCDuxu/drd2N2Xa3d3d6I/7A5MTEARRRQDE5Rudvf8/jjP3XtnmN2d2Z3a5Xm/XryYufnM7Myde55zzuej7+ZwnBaHiKxBnGG8V1WPamj7tH2rsIxSso/xfOCKbMponQjRQGxyDuAGVa2vrzlvSCi9gZuIxZXASuxvBi7RQCdm3LGQYxK5HxNvAzhXVa9MWW8VQ98AUY/wsoXMwJcCEemOtScBPOMqcYo9htWx63DvxOK/MBuweoPtBo7XBps8PYs5JxLGY6mE21R1dNNGXP5IKLti1ZJWVTMDKz63X6V/gP0KdZ11wmpfElm9jeUObmN34nufUFX7Nfs8di38BeiGVWctmUkU0dM68ZluT7MRkb2IA+5ZWKlgwQMnCaVCQjkPeIvZLEwkzxWHlO9jwX+rC7ilj4hsLYfJvjKSAxjJFuzKCmkB91S+QTmCChbSUA/SQN/JVdhHA30O6I794EesB3wloVwmobTPvGfWx38dK+cFK9e9tDnHa+045dc46/cpUWZ3JZpWKdA/8TjrbLmqTlTVM7Ab+5cSqzYAPhORB0Vk8cx7Nx8RWYnYPk2BIxoLuEWks4jsICKXisi7mF5BYwH3d9iN9eGYsFw3Vd1fVe/Cbpwiykbgq4AkX2PWwaaYv/xTxAG3Aseq6uXZ9q26ioEjsNtwgFNEZIMGdmkWEsriEkrUoJQMuF8EemigZ5Qi4HZcSfwrd1p6FtRl7pLZ7tbo1z2S+LPQq5gnFpF5RORy4CtSA+67MD/5nANuMJFMVX0cE1jcBtMyiOgMnI2Jrj0lIhuUm4BcPtBAn8ey/N8BVlOyH2ZjWsEiwFuu1SfvscscwmoLcRxbcA/xd+0iEdmm2eexifHIIaMSOLS5x/S0HHzQ7WkWIrIiVuIZcYpqZkGmvJ43lC5YD9VljKOC+4DUwtIbMYXyf+bcu+UiB0lX2UfupwdT2Jj76c4KKeXjU5nKv9wNrKhX6xraT+9vrh2XBjpBAz0GE4+KMqFVmBrr167SoDmcStyzeZyEsnYzj9ea2RtYwT1+h1GcmFgXiEi6ME9jNCnojlDVH1R1Z6w37bvEqkOAH9wNUrMmZtJxN1z3EZf53qiqn6RtIyKysogcJiL3iMi3WJD9MpZh3ZxY7TzJKMz+aUdgQVVd1bWlPOBeazJITAZd89P6SQbdWV1TRKQT9p7v4RbNxgTT7sr15Kr6A3BRdGjg/rx/tkJp7yZyfyB1Eus7YDsNdBcNtCn6CXnDvQ+R3d9CxNUWSZ5IPG51JeYucIkqrVYQKY4nuYj0Ab4GziWu8Pke2FRVj1XVCc09hxpvquo2WAD+MLHTRCWmpfExMEhE9nMZ8laDq7Zaj+Rv00bYL0onKrBWnxdEpEvGAzTv3B+S1ErYlDNYmNvcMwEeE5El8nCq5D3zEYWYRPCUJ/4P7WkyIjIPdmGMBHaewEoIC3veUNbBZpl35DtsfvnvutXTgQNU9dQcBZXKFglF5CjZVo6QL1iaMfTgMBYizm7MBkYzlD/Yiw7Mp7foMRroj/UfsWm4vsWeWIYxem9XBN6RUO5zEyFNOe5o4qylYKJq/tqUhntPzkssukxVPyISobHewKxLfgE00N+I5QbXkFBWasrYVPV17LNxMrEwUAfsBmm4iOyRx8zMccRlxqOACxKCZ+eIyAtYq8L32M3NkVi/dSZqSRV/HKaqF6jqK6o6rpFxJAPPuSHTnVNPt4h0Bd4BtnCLpmEe3E/Xv1ej3EAsfrcKcRDeLFzf9p5YcH0Zce/+BOAkoKeryikXLk88Pit9ss0JVX7snq4moaxetJEVj6jVQTDRwoIhIl1cWf87xJOeszHXhF75UrdOR1WHqOohwNLuXGMSq3tjFQ2/iMh57vvWKnA6M/tgvyeWeV4aM3U0nfMdgS9FZJ0CnP4O4qB4Ho5lF6rqqg66YsJqzZrocDoVb7mnyxNb7HpaOf7G1tMcbgHWcI+/x8TKCiYS4G6MjgM+ooaleR0rWow1b38A1nclWi0eCaWzHCuXM5H/WILXWIq1aUMcuPzDNIbyACNZSO/VXnq3PpsvX9j60EBnaqABVtL3cWLV4cB3Esq+TVQhv5E4U9obLzCSiZ2Jy6EHAVFv2wWJbc5vgujOM4nHTVY7duWRN2MTMbcTl+Uti7UQvO36gpuMmH1ZUojrK+x9iATPrsDepwXTdq3GgrW30pYfgJX3RVnrdXMYztyc6W6wtFpElsTcEaKb4vFY5VGzAleX4TyceNLvLBFZqznHlFB6YsFUf0xRGuyzexuwggZ6iwblNYGrqt9gYqVgQk+HZNistQuqDUk87lWIE7iKmX2x36bDEqs+woLtfplU9/ONE13rh02sHkrqa18cmyga7ap6ctGoKFs0UNVAbwY2wWy2bCrsICxEFZYBPhKRY/NZau/aM/oSCatVsDQn045Y6G4jUie9mso9icc5TZZ7Wi4+6PY0CRE5hLhHbzqwl6pOKdj5QumIZaRuZyJteQCTbIp5GlhXVb8u1BiKgYQicqFsIifJ21TzL4txLvMnPD9nAMMZxTscwR101Of0cH0qtiMpFhrocOzH8HggUj9fGKt2eElCWSrH481yx4q4QsLWM3PfXNxERjK4vjTyTVfVr4j74hfFlFhzoVkl5umo6r+q2he7EX4nsaoPMFhE7hCRxvyt6xCRKhFZS0ROwL71SeXqvbBJmnRLmXFYr/l5WCn5/Fg1RbIV4jRVfdL1C3/hli2WQy/63Jbpzqq8XMyH+CMsEw0mLrVpegtAU1HVYcRKx5XAA2LuGTkhoSwkodyJTdxsnlj1NtBLAz1Bg1Qf7DLjssTjc2ROW6VnMKEmgP1bYfXQkMTjvCuYi8jSWGvEE9hvG9jn/jjs8zy8vn0LharOVNWHgLWwz+wAYveF9thk9Tci8qaI7NQaypY10EFYmb1VdAl2FT8Q6EBbLDP9SD4dDTTQGcCeRJUFndiUvfmAeLLvDBHZtZmneR6Iri97ikj6RLGnFdLiv5Ce4uNmUu9ILDpWVb8t2PlC6Y6VwB7ASKyAPXbano0FGfuqNq93uZRIKAvKuXIO0/iTKt5nQbagKvH9/J0a3ud1nqKHPqXL60C9v5BVBdmggdZqoHdgQmsDEqt2wOzFTs7FXkwDfY84O9MFEwzyGFsTZw2HYBr9SS4ivvk6x6mLZ4UG+itxyW5PCWXFZowzPq5l47YCdsfKwMF+c44FRorIKZnK9Jzg2fZO8OwdLKv6JVZZs2j69o7vsD7vI7Bgr6uq7qyqVzirs9Wxibno83i9qt6Q2D+ptp5ttntuznRnvNa6rPOHwJJu0U/ARi5QzidXEpcXr4GJTGWFhNJWQjkVE+M6hvg+6CfMOm/rfDgzFBrnEPCGe7osaYJpGuiYxPqlgA2LN7qikJxg75Wvg4rZgJ2C2YBtn1j1f5hQ2p2ltgJ0fd8DVXV3rNz9BlK/k1thon/fi8gJTluhxeImv3bCJlHtvV8e+/ba9P4BmIDnKpmP0KRz/k5SWK0HB7BKSvXIQyKyXJOPbxUSD7unbbHX4Gnl+KDbkxPu4t2f2P35XlV9uIFdmne+UPYFPqeWVXkHeAzLqxu/Yjd0t5U6AG0Krlx+czlHBlDLP7TnCuZNBBXTgS+ZwFNcwb101rd1Ox1V/Nn1xtBA/9BAd8fEkiLriw5YyfgnrnwzW84gvnk4QsLCKRS3MM5PPL48ynJHuKxL1JvcGcjVTikvJebpuJvDAVhP9dlAVA0zP3aj+I2IHJlB8OwV7DX3ATKVy3/NnIJnR6rq/ao6Ink9cGKPLxFfs57CvF+TNCXontsy3cmJhTnKy0Vkc8xOLapQGQps7PoX84rT6zicOJN7YTZltRLKDthn53ri1zMF+2z20ECfT/9ulTnJbHcmVedWW2KuqpOxiRKA1SUPPsoi0hNr3bmBuKLmT2APVd1DVf9o7jnyjaqOUrPPWwLTH/gpsXpFbLLydxG5TkSWLcUY84Gb5L8C2BKzD7Or7qFE00mrAl+4doB8nfMD4JS6Bf9jH+at6++eH3i6mWKOSc/uo1qjIr0nFe/T7ckad0F4HIguakOADVV1er07NfVcobQDrgP6Mhkrnv0lZZOXgEOyEDsqOySUhVAOYTYn0bYuIxTzKzCcbxnORUxmQKln1XNBQpkf66s9LrG4BrgGuFiDxj8rEsrJWMAO9hlbV4Pc/KdbExLKxlh/LJh6fA8NtGaO7WzWfQRWaj0FWFY1u9YDCWVZ4mz0EA10zWYPPNN5rCf7NiyDlO0Nxmhsgribe/6IqmZljyYii2DaA1FG4j1gu/Q+TNeDHPXsvaGq22Zx7K6YYBvAK6q6YzZjaqmIyIPEvcPdVfX7xLpdscmMSNDrQ0w0bUKBx3Q5piQNNnGyoWbwqpdQVsEC7WTmUjHrnvM10L/T92kpiMgHxMKCe6nqs3XrQumEBSjzYKWsi5Vbf3pzEJH+WBkwwCqqOqKh7Rs4zjxAgE36JoP3OzAv9FLZw+WMm3jZAQsWt0xbXYuVNd8IfNASkxUAEsqiWNn/5nULv8fq7cxI7lbgjHz027vWrvuJrL2m8ytXU4PW/abcoarH17N748cX+Yi4CmV9bYUWt54Yn+n25MJxxAH3JMyPuxAB99KYx3ZffsHUyX+pW12DZSV2bUkBt/MU31ICeYZa/kK4JiXgngZ8QjX3058HWEMH6Wo6SZ9rSQE3gAY6UQM9HrsJjITRKjFv6W8klPSbgEzcRlw62ovUAH5uJJnlviJTwA2W8SCeOe9IDiW3Tu046mvuJaGs0ND22SIi3URkbxG5QUQ+xUp6d6D+gLsWKyW/CfgfVjx4FnHA/Q/JzEPD5+6I9WRGN0ffALvXcyP2O1H2BNbJMuMwt2W6M5aXO32PZ4kD7peBbQsdcDsuxm63wSoUTk2ulFA6SSjXYn/7ZMD9ETaZd0RLDrgdlyYen5/87DoV6Bfc0wWxNpXWxNDE415NOYCIbIV9Ps4mDri/w6o0jm9JATeYp72qvqSqW2GtF/cSy81WYO0+AzH170PSle9bAu47uzVJQbNVsHLzxQBrOXzf9eU391yK3YNYNdQ8LM2hjCH2iT9ORParZ/dsSGa7vYBsK8dnuj1Z4awZPsJ6TyBtRj1v5wlle+BRaunCR5gMU/wR/Qvr3X4/3+ctFG5G9lBqOZYK5vwB+BkYwnhGcCMzuD3bzGRLwFUrnIP1YSWFjh4CTm9IpEhC2RD7vIHd4K/cCm6Oc8Z5lkfB8C/ASg1lqkSkG/AjJqozA1heVf/M8lxnESuDn+dK+bIfq8h8wNpY8LMuJnDWmKDeFCwznyzR+wMLnvpjpcrDiUuW91TV57IYSxss2NjOLRoNbNBQeaiIvIj1DQKsoKo/1bdtYp/pbuzfqGqzlNnLHRF5m9j+q5OqThGR07CKpIjHgMOKadcoIhtg1wrBPvM96cdIrE3ieuIJG7DJlTOBp1pYGXm9uCD7c+y7B7CjqtZpPkgoOxMH3o9roK2md1Qk5bVdoarnNbR92r4LYp/dpPL7LKxk/6piqJIXCydceTSmyr1Y2up/sIz+nar6T/q+5Y5rGXkE04GxDuzXiH41x2EWsq/l4TxLuqOaqN4bvMbHdb8vU4F1ktU/WR/XBOD+wqx3pwKLudYJTyvEZ7o9jSIinbGezyhwuinfAbeEUimhXAK8wjS68ASmIRvfFpmibAsIuF1We1sJ5VmU0cAVKQH3VOwW8Q6+4SEOYCiL6nS9uDUF3FBnLxZiGYgPE6sOwezF9q/PXkwD/Rgr/QTLsF1TyLGWMcmbyKsbKw11QeXt7ml7UrPkjZF1X7eItBeR9UXkRBF5WES+wzyN38EC973IHHAnBc+6Y3/bBbGMZXST2w0TPXsd+wxEAXf/LANuAe4mDrgnANtn0Y/ZnL7uuSnTXQtMFZHLSA24bwEOLmbADeBU0W90T9uzKI+jdYaSUcA9E/M5XlkDfbK1BNxgugmkZrsvSKvUeB2zbAPYTcL8qTyXATlnup0N2P7YtSgZcH+I3WNc3JoCbgBVHauql2GWeAeQeq1bBOgH/CYiD4pIQVqLCoUG+gqmbm5l2VXY1OmeQFu6AK+IyMXN7fnXQEdjv4vWvrI127EQ0f1oB6B/UxTUVXUqsfZCB6zCy9NK8ZluT4O4H+8BwC5u0SBgM1WdlbdzhLIwdtHZkt+xW/+4oEsxe5iLVTOX1ZYLEsriwOEoRyIZsto/AV9Syw88RzXXA4Naak9Vrji7mqOAq0kNUF4DjtNAf8mwz0JYj3JkmdbHKZzPFUgoPYBI9fkvYDlnZdLwfpbVGIWVmFcDK2UrZiWhfEGcMVtBA/3JWRH1IM5gr4upgadbFKUzDfM6/dj9+6ShlhARWR64GSs/T2ccphzcaCZGRC4htlebCWytqh80sEu03/bEqvDXq+rpWezzAyZWNEFVOze2fUtGREYAK2GTGE9hxZwRAXBJqa5nIjIvbRjGJizLRqR25Vq5+0ka6KiMO7cCXB/v19j3FGALVX23bn0od2GZToD9NdAnijzEguDuT/7DfiP+VNVujWy/DJbV3S6xeCLWwnJvS2vnairufVsfa9XZk/RvjLX33Qi8UO73XRESSlvs/uLkuoVjsftJM/56G9hfVcc08zwnYBOMMIvpXM2fVLO8W/0wcGiu10FXSRpNhHyqqus3Z4ye8sUH3Z4GEZEzsQsZ2I3vmqr6WwO75Hb8UDYCnkZZnM+wOfn4Z+9frDTojXp2LznOEms74GiUHZG0H6/JmBTYYCYyjjuB21R1dNEHWia4iYlbMKXziGnAhcDN6YJpEsqxxPZ0wzH/3FYjBNQQEsqjxDYip2ug12e9r8jF2HsK8JCqHprVfhfJOYznCv4EhvARoxAsizBPI7vOxrJOnyf+fZ9J1KqRcQuwK/YZWSKxaixwpKq+kHHHeP/k50WBfVS1fwO7JPdNCqN9oKqbZrFPNElRC1S15kk0EfkLs2ybRqqi/ImqemtpRmVIKLswm7tpwyJ1C2v4g0r6Ai+0psx2fbjs7WPu6duup9fWhbIZJiII8JIGunORh1cwnK1gH/d0kUxBlZs4PBmrqEl+dp/FPr9/pe8ztyAiS2Fl50cRT3BH/IJdi+9rKb3tEspemPCZ2aTNxmR3rSbiD+B/qvpRPbtnc3zBKrCsSuIffucOFsAmucF+p+7L6Zj2uzeY2G9+DdXyty305I4Puj31IiKbAO8Sz4LuoKqv5uXYduE6FbiaGVTyAhZSxXyMXRx/z7B7yXH9PUdgtjWpCuSKddV+CfzA99RyI/CoKyPyABLKbpjCaDIz8SVwlAY6OLFdJVZdEXlUn6WBtvpScwlleeAHrAXoP2BpDbL//Ij5dP+M3UTVAqup6ndp2wgW2MYZbKE3SmOerop9W5MB9tf5Ksl043oRswNL5yXgpEyZe6eg/Rxx29RJqnpLjuf+GSvBnArM31iWJ1Ofcy7na0mIyDRSJ1+qMQeJx+vZpeBIKMthons71S2swdp3PuQjZrFZS8nUNRcXWH6H+TaDaRgMgrpKo1+x73s1pmLeKtqZROQGYnHFbVT1zbT1awL3EFfwgAVffVX1+aIMsgXgSqMPwiYn0v2up2CB5i2qOrLYY8sVJwTanziItbuLV4FqqrHKhhubOkkqobTHHEXsvuRTvuFVVnerZ2Aq5EPr2T3zMUX6YvdEYC2cpzRlbJ7yxgfdnoyIyMLYzNvibtFlqnpBA7tkf2yzlbof2IO/se7N1KLT6zCbjrLKaEooVVggcBTK9kiaJsIk7B0bDEzgVexm8M25pWQtVySU+TD10eOJ1axrMPGjfhroNLfdOliZsmDB0CoalOdkTL6QUO7GMg8AF2qglza0fcZjiJyD2beBFdkdT2qJ+LqQyAzWzyhSA+yvChlcOjXsB93TcViJfTLrPAP73FwdBfpOTOsdYkG2q1U1a/X2xLmfJu5nX11VhzWy/f8Bu7mn3bIVrWtpuN+DZGn/dExM85V6dinseOym90xM8yAW4avhPe5iBcbUVUmcoarXZThEq0REjiBWQ35JNc5oSyhXE/vTH6eB3lns8RWCtOvFmap6rVs+L9bHfypx4kAxzYvzVHUSnjlwrQpbYxMZ26WtVqxd40bgnXKu7JFQ5sHalWJF8NT7zWeBw5v6OXCJly+BhQB4hMH8RNQP/yMmrJZ1dYDTTvoTu56Nw35PGm0n87QsfNDtmQMnOPEaEJWnvYf1RTbbK1lC6Qn0R1mBwVgHZXzUiVjmpKxmnyWUZYiz2ounrKzFTJC+BH5kGrU8BNzcFBXLuRWnVH43cT8iWKB3rAaWtZBQbie2DuuvgTYo9NWSkVCWwF5/G2wqZ2kNcrNfEpFOgLVu0GjmOslfLMwEetCdbkBnQr1Z++Vy7ubg/LKHEff97475yu6DTcYkv38/YtYwv2CVMV3c8scwQa+cJ7vS2mkOV9UHGtn+QWIxplXTqwlaA04R/y3i7Fc10EdVP6x/rwKOJ5RtsYxQ0tbuT+A04Gn6sQn2myVYT//aqvptscdZCkSkLfa9iKqv1lTVIQASSi9sShjgAw0ab59oCYhIT6yJC+AxVT1QRLbGzEaXTWz6LXCUE97zZIGIrAKchF3j5k1bPQxLLDymBbCOzRcSyiFYy5FV6czEVIrsSj0Smzz8uonH3gy7NlZRDVzPKKbVWVT2x9qbsg6yROQR4ED3dH/V1qG94InxQbdnDkSkHyaMAzY3uKZq8+2aJJRDgTuYRXteJlV3FL7CfL/LQuxGQmkD7IyJz2wDab7CE7ERDwYmMRrre7pXVcfjyRkngnI2JoCVtBd7BLuZrsFE1RZyy7fVoHx7/ZuDhHIjsRjMFRo0bIMjIu2xMrpkBnsV0j+zczIes0Cpy2Kr6h+utP1Ht80XGmi2St7NwpWVv0E82fewqh6SWN8JU9k9mVThn2SP8VuYZVKThB5FZHOspQbgDlU9vpHtbwZOdE/rynlbCyKyIvY3WSax+DVV3T7zHgUci2WWbsCEnyJqsBv/fs6T2rYVuQ67boBNiW5QbpVThUIkIfQEz6jqPlDX0vUt5hoANpmXN32WUuEmGqZgk5TfY9eygxKbzMLEWK/OpwDs3ITLwh6JXeuWTFv9H3AncHu5VvpIKKthQfDKdQsHAW8CNcwAjlPVB5t47BOxjDqMYzq3UJ1o0TpZVW/O+liSor3wjqpu2ZQxecoXH3R7UhCRbbAst2B53C1Vm6cY7cp8bgGOSFOTjLgDOK0cSmlcwHEkcBjppbe1WJetZbVB+QgrsxqQjyoAD0goq2BZ700Si//FSgSriG3ERgKra9C6rF2ckv8v2Kz8dOzGeGzdeuvbXJU5lcTbZHmKJzFf28+Bn+qbhZdQvoK6UrnlNMhO/bw5iMjxwG3u6e9YefeEDNutjpWIbpy26k9MgKZe//csxtAJm1IT4AvVhicc0pTSty1n0cdcEZFemLTlwmmr7lbVY+bco0DjsAm5U4CLMEudiA+AvhrMKTgkIvNgV+oowOynqmGBh1oWuNf+M/b7pVgFxvcAEsr5xPZi52igV5VmlPlFRIaQ7N+NeR84WlVHFHdErRP3+7M7NvG5Udrqaqyy6iZV/azYY2sMCaUTdm+xb93C0VgobkXg92I6IDll7d1k1oPAwQAM4x/61907zgY2UdVPszqWTTyPwBwxAFZQ1Z9yGY+nvPE+3Z46RGQJrDQzypBdkIeAewXgE+AIvsHkTOKAeyqmTn58KQNuCaWthLKPhPIWFk6fQzLgHo+ZTdwAPMlsRvIoyrqqurGq9vcBd/7QQL8HNscqDKJ+qK5Yxns/LDML9qN0Zvr+rYBTicrglLvoxwIisr+I3CAiH2LvyVDsBuEYYC3mDLhnYwHHnVhbRJBYtyjwpKr+2EjZW9Kze69mvJ6sEJEVSPViPyJTwA3gVF23xLJ2SRYHPnDZ6iahqpOxbBlATxFp18guyX7A+Zt63nLDiWgOJA64kxVIReuFlVA2x0qHryIOuMdg5a6bZQq4AdyN88FYJhzMu3rtTNu2Ntxrj/rYBTg3sTpZrrp/0QZVQERkOeacGJqAaWL08QF3/lDValV9RlU3Bnpj94vR/U8V9pn6VEQ+FpF9XJBeFrhKmP0xbROreFgS+xW1RpUjgY+ddWUux1XgWOw3F1ZjEXrxi1vdBnhaRBbM6lj2m3xvYtERuYzFU/74TLcHABFpg5VVRrOXrwA7N0cETELZHXiQaubjdWIXQuNbrJy8ZD2QEspK2A/zIcRly0ZUzPwldrup/IsFMXeUawlVa0NCWQwrHU32b8/Ays8r3ONVi5GFLTQiIvRiNXbmUyqZhxqUm5jEpEYDOcW605JCZ0OTSuLuxmc48ez51qr6VoPjscmySKX2cw20dxNeVlY4DYmBxNeeBsu6XTbgYeLetxlAO1LL6R/DRLRybosRkYeIshbQW1U/b2Dbo7HeUWiCVUw5IiI7YZMukUDZJ9j38En3/CJVvaSgY7Dv/rWkBoa1WFXUBdlqHIhIiGXIwb4Da5dDRVWhcRUbv2LuBTXAipHiv4TyCebRDFYt1KBYYLnirmunYmJpSVX9z4Fd8tES52kcEVkc01s5FpsgT/I7pr9wj6qOS9+3VDhx1mdIts28jxV21zIR89oekOMxl8KSAgtRA9zK74yvE3TM+n5aRBbFcvBVwF/AUj6x03rwmW5PxOXEN72/0UQhIrB+aAnlGuA5xjMf95EecD8MrFeKgNuNbS8J5V0srD6DZMA9DuvzuR4rlPqJb1COwC58F/qAu3hooH9poPsAu2A/3mCBQEXi8U2lGFtzEJG2ItJTRA4Wkeudz+x/zMfXVLqbx8FIPQH3z9gn80ysImB+Ve2hqoeq6m2q+pmmWXe5H+xktvsyF7jWiwb6I7E40bpOTLBQnEZ87RmF2bk0xOWkBtxbYmX2yZLGA4ARInJyE7ItyatVY/3srSrTLSIHYjJDUcD9GqZknOyhL5hfr4RSJaGcjFUbJAPuz4B1NdATchQVvIxYPGxVrLe31eMqNqJrYyWp36mkxdt+RRtUHnFVC59hoofzpK0e5APu4qGqf6rqhcBSWLY4WX2yBHAl8LuI3Ckiq5ZijOlooF9gVWIv1C3cFFMC6Mj8wP+JyDUuGZXtMX/DBD9rqAQOZQkqiXQmdsA0axo/jn12X3JPFyPWOPG0AnzQ7Yn8bc9wT2djiotN6ouUUBbHrHvO4HssB/RX3eqZWGb5UC2yZ7WEsqiEchHWL/sMFrAYNZgO50NY5/lHKFN5AbuZ76mq95ezOmdrRwN9EVM2vxXL7CbZWUIpePlzUxGRBURkMxf8PSAigzHRnyHYJ+5UoA9t6VyXe6rFfIZNxPBFLFO3PbCQqi6nqv9T1WtVdaC7uc6Gp4hvhnpjIoGNUfAScxHpQdxjqph7Qb12ZE4k6hz3tBbYT1U/VtUvgQ2wYsEoozIfprnwhbMUy5Zcgu5kADpfvVu1AETkJKyNIwqwnwR2ddfq5GsrSHm5czH4AvubRecbh7WabKCBfpXrMZ1w1sFE5aRwuiudnxu4Bepu+g93KvRgk3ZR2f3+rie1RSAiHZxI3mfEmhOK9epG9Cr2uDzW1uAqfXpi904vEv9ez4Ndm78VkXdFZO9cAtpCoIGOx+wezyL6PiyLjXIZwO6J33aZ/GyP+R5wOmBTsPvRhvg9uNQJpWXDg4nHh2Z7fk/548vL53JEZBksE7CAW5ST2mLKsULZAniCGhbmbczEJ+ZHrJx8SFPH2oTxCJZB64sp3qZe5P/DbvGGYvrHFgzdB9yqqj/iKTsklPUxZYDVEourgf010Gcy71V4XOZ4aeyGL/lv6awOsAmT2NIFGv8ykFs5EPgjF7uRLMa4K5bFBAvAezVUzSKhrIhJBwJ8poGul6+xuPG0wTRk13KLrlXVevv0RWQPTPYmChKOU53Ta1hEumLZlfR+uPuBc1RjYbp6ztMeC1aqgG9VdbUGtt2QaIoEblTVUxs6djniPrv9iMuwwcq4T1TVGrfN2dh7CrCnqj6Xt/OHshDWs31Y2qp7gXM10H+bfY5UK7hR2GRqwbzmywURuZI4w3aDqp4GIKG8Bmzrlm+kgX6caf9yQkR2wVSik9fUYZgN2CAR+Q3r0p0ELJDPa6enaTitjhMxu9WOaav/wn7L71bVP4o9tiQSysbYxLQF2LVY6ugjQBkD7Kuq79Z7gNRjpQqrvcl4PqKzW52VG5BT5P8DK9efCSxan8aJp2Xhg+65GHfT+z5xf1fOvoIAEkoFln26hElU0B8rUI95FhNGKlhZYtp4OmCliX1JVzSNFMg/wwp17ZWOwG4yHyzWGD1Nx6kZn4GViiardV4CTip0j7cT11qV1OC6J9mVF9dgpbNDsOmeISzH9xzMZ5jIGUAPDXR4XgdNXXA1CMt0QxY+oBKmqAIvo4H+msfx9CMue2+w31ZENsLkDCNhs8tU9YJM2yb22QBTOe+VWDweE5a6Nwoo69n3S2wyoBYr4c8YoInIasQVBPeraosSvhGRCiyQ6ZtYfAkQJH8HRORqYuHCzVV1YLPPHUolVvl0OdTdlIJNAh+vQf7s1zLoBtypqsfl6/jlikiKG8I0YBlVHSuhHIxV2gDcpoGeUKIhNoqILIt9RndKLJ4JXAxco84KTkReIK7gWS7qYfeUHhGZH8vYHkfStsuowSaDbwfeLdVkiXMOeYxkOfcPwP8B06kFLgSuzKov2xx7PgTWoha4l//4k0hM7V1MV6Xe3x8AkRTr0GNV9a4GNve0EHx5+dzNpcQB98+YEFCuAXcXrIzoMn6igjtJBtzVmNXL3sUIZiWUFSWU67EZwrtJBtxTMYOZSA5oFDUoz2JlUN1V9SYfcLcMNNBZGujlWMl18gdwJ2C4hHKBhI2qTmeFiCwoIluIyGki8rCIfI1VRHyFZU5PwrrBMgXck7Ef3tuw4GJdoJOqrqaqB6rqNar6JgezM3HA/VwhAm6oU0Y9P7EozKLfuSAl5iKyDrHVVg2mIVFfwL0C8DxxwP0QdgPUIKr6Cfaen0RcEt0ZE0T8pBE166jEvII4E5+JCYnHCzQ2pnLCTbo+SmrAfYqqXpThdyCpvttkS7a6c5uQ0SBssjMKuCdiWbF18xlwA7gb3EOJaprgWBHZtv49WgeqOgbLJoJ52Z/iHg/A9BAA9pGwtKW+mRCR9iJyITYhlwy438GsAS/XVO/1oYnHmezDPCVCVSeq6k2Yhd+WWCImCjorsUrEt4HvROQkEVmg6GMMdAywHVb1Y9e/lbBy825UYPoQL4hIlyyONR2zVvuXCmB/FqQd0cRtH3eOxngo8fjQbF6Dp/zxme65FBHZDnjVPa0GNtIcvRUllHWBZ6hlaQZieYSY0VjWPK83TxnGUIkFXycQl8vF/I5ltYcTGVv8hQXk95S6pMnTfNJ8Z5P8CJyggb6e1XEs47csc2avl8xyKKOJMtfxv58bmxV3N7sjiUsm125K72q2uGz3O8SaBg0qbjuF/8hy51MNdP36ts1hDO2xSYvIQzlU1X71bNsFU89eyS16E9gx7WY7m3MuilmSHZhYrFgAfr6qjk/b/ghi65YzVPU6MiAi82JTegADVXXzXMZVKty4+2PXTrAb4MNU9ZF6th8A7OqeLq6qf2XartHzhtIZu3k9llS1+UeAMzXQf5py3KzPL3IcllED83VfLf1v39oQswIdhbVXTQKWVtUJEsrTxM4Q22ugr5VqjOm4CZFbicycjL8w0cWnMiUHRGQv4knCucaXvaXiNAaOdv8WTVs9Dcs6317MlsQICWVrTHDQ1NhrgDcAc9v+FdhLVb+oZ/fkcfpgv1mV/Ao8QC02katYtvvteve13+ohwBpu0Srq7O/cb+jOWAn72ljl1205vkxPCfBB91yIE4YYQqzafbqqXp/1/tazchxwA1Noy3OkurhaMH9QU8XYshzDgljP5nEkbR/AguthWLAda42/i91sPZ/rDbunfHGl5l8S93hHP2oR/YFTNdDf6/YRmQcTZutFHFz3BDplccpqzKJrSOLf0GYIDx4KPOCevqqB7tCU4+R0ztQ+5N+AlTRN8Txl+1CGEv/wL+1UWptz/muIhRu/AtbP9J10fW2vE08QfItNDja5IsUJ2dyOtQdEjMXEdB6OJklEZA3izNlTqrpvA8echpXvNtj/XS64LNJLxKXWM7AJ0hcb2OcDYGP3tJ0TKMv+nNaCdAjWV520FfoWKyV/P5fjNRV3I/s6psgO8KiqHlSMc5cSEbkbq7YBuFBVL5UwRePhUQ1K/z6IyJLADVjmM6IGKy/vp6r1iviJyCrYtRngaVX9X8EG6skbruJmN8w/e/MMm3yCXbP711cNVZBxhdIN6/PeqG7ht5je+UxmYVUjdzZWHSqhnIJ9puF9ZvEObd2qvzFdlXonGkXkVMxLB+AK4GUs0P4fqdV136lqWSjDexrGB92tDFcyuQbwTKY+RNfb9iZW4gL2Jd4527JyCaUjpkm+P79iIU2sn1yLlYxelU3fS1NwZYl9MauT1BLi8Zgw2mCiIsLJWInOHaqFKdn1lB4nrvYxljmbjv00rgNYDvIvZjCUtxnGRJSewCqkWiDVxyRSg+shwPCGAtQcx12J1WBEWdyNNdCPGtglb4jIy5iNCcBJqnpLvduGcgGx1dLpGmQ/QZfhvJtgNTGC9WWurarfZthOsMmIQ9yiMZjN4C9NPXfi2G2wXrl+QIfEqo+A41X1a1d2PwkLpkep6vINHG80Zo3zt6ou1tzxFRIRWQyzAYsmUSZh1/8Gg14RGY5VJkxR1Wwmp+J9Q+mJtVhslFg8FXv/b9KguJOgLvM7jPimNa/CcOWIiCyPdahWYO0By9CP2diN/wLY32NhDXRavQcp7PjaYkHMRaR+Jz8E+qrq11kcowr75W9DC5kA86QiZil2HHbdT7/O/ItVH92Vj9+BrMZjlWiXE08S27fnacBC5cewfuv6HTcsSfUwcCC1wENM59c6m7s3gO3ru18WkUWwdslKbPKpvvuWQaqai0OHp0T4oLsVISILYqUvHbAf2H1VdXDaNhdiAiRgX+Zeqtmpw0oo3YFnUbrzMfAWSQOnvzH7nvea+TIynbc9VgZ3ArEIVMyPWFZ7ZN14vsFu8h5r6GLoaT1IILcwjhP4G/iZUYxiCrNZjSlZ61b8Slr2GvilkKIuEso+2Ew6wEANileaLCJrYllmsNuH5bUeGz8JZWVM/A1gkAZN+3EXkY7Y+7qcW3Smql5bz7bJQH8GsFmu7S9ZjGcJLIuwd2JxDWa1FACvEAeKXeurZhCpE5ubjWWBy/JHVUSWwyZco/d/DLBd+m/DvwEBAADDaElEQVREPfuOwSqjflXVZbI6XyjzASHWp528WXwam7z5PeOORUBEDsJuhMFu5ldrKOPUGhCRR4jbK05X1esllHswb2WAfTXQpzLvXdBxbY5lMrsnFo/FhPsezuX7JCLfYFVPs4EOvqqtZSIinYjFcFdPW61Ysuh24PVCJXhSxmNVIQ8RTdTNxn4d7Mo5HCs3/66e3ZFQ5sUmkNZkCnAbs5hel/E+V1WvTNneqpH2xrLaG9M4z6jqPtm/Ik+p8EF3KyKtTxvMm/Qs4GZVVRHZFCuzrsCy0n0ay3DUHTuUfYF7mU4HBhB3eRrvYQF3gzYIuSKhLI31/h1Jakmi3YYPxuSOzJV3NpZ3vw34uFxvfD3NR0QWwsrDe2A3WD2xzF2HhvYD7JM/H+OZxhvMYhBxeXhR+zrd7PdgYsGfbTTQN4s6BpFniMXR5vjhT9k2lK+Jb36W0kBHN+F8d2DfZ7Cs8maZFFxFZD+sny5iL1V9Ntfz5TCubbD+0RUTi//CPhtRz/N2qpn1AUTkbWAL93T+hkpgS4WIrI5lVaLeyV+xnsKRWewr2PW1EvhKVRsSoIs+2/sC1wHJzP8PmM5CUT/nmXCv6VlM7AiszHqP1vy74bKIUVXJ38Cy9GMDTOMB4AUNdNeMOxdmPIsB12LBVYRi4noXNOWaLCJPYqW3AKs2FAh5yh/3Pd0IKz3fi3TbV2tsvBNzjihYOyOAhLIcNmEYX/+GYOH/bKZiDj31Tlq5+9kvgK6MIp7ys4neTTFhye2xQHtX0is5G+YGdXaAnvLGq5e3LnqkPW8L3IgpLq6E3chGf/Mwm4BbQmnjFMGf4A86cBfpAfdl2M1bXgJuCUUklK0llAHYBfUckgH331hPzXVYZ944RmOKzEuq6v6q+lFrvnGamxCRhURkcxE5XkRuE5H3RGQslqF7FwuUjgU2IHPAPQF4l848zvb8zLHAecApdOY8tqcftfTjwxIJKe1IHHB/jtWNFJuLiNXfz2pEMbZZKuZOGCkKuKcBh9YTcG9I3OMOcHYhA24AVX0Dm1C4gFjReTHigBtMBb0+kpVCC9a7VYkQs1t7nzjgHo71xjcacDvmJ85UN3hj66qh3sZ+a6KAezp2jV6jHAJuqFPyPxbLqIL1lJa8p7mQuBarqIx+UcwX/X2s4g1ge+dGUlBEpEpETsaqZ5IB92fAuqratxnX5GQbme9xbeGo8aGq7o+Jmp6PiZZGLIfpRPwhIg+KSG8XqOd/LIGOwrLOd9Qt7IUpJXSlA/CkiFxXnyOIs9vcC6hmOWCTulWVwBNYJv0lYB9yC7gh9T3xlDE+092KEJEHqN9aYAbQ3j3OzicwlEWAp1A243MsyI33GAccqKqv1rN7Tkgo82N9PMeT7uNYg/2Ufk7Sjux1rLzo5cZeh6e8cZnrVYmz1z3c84Ua2i+NUcBQ1mElVqAHiwLz87D200Ogrn/6SEyMJOkJPAQTcvqk2S8kS1wm8BNgPbdoNw30+WKdP2UsIg8S901frKpBxu3CFJGiTzTQDXM4R2es5aObW3S8qt6RYbvlsdn+aJLtXuDoYk6iicgymLHgLmmrRgJrZirBF5HbsT5EsKChUVXbYiEiu2MBcHTt/xRTf886K+T+Lj+6p0+q6n5zbBNKB8zG7XQgedP5AnCyBsXpwcwV9/5EgegkrMy81d7AishamPAkmH/3ivTjSuzvBnCMBnp3Ac+/Ifa7nbT0Go9Nrt/b3FJhEdkTq3gD85q/uKHtPS0PF9TugJWeb5Nhky+xz9iTqoXRKJBQ9sdccGyyfyYWLn8DWOXn/9Ts+jLtezRwFzXAgyij61wcJtB028m9VbV/45t5So0PulsRIvIZDWdkoArlcO5kcfpqUP8fX0JZD3iWmXTjRUx2JmYQdlFploqxO89q2MXzINKzlZOwy+eX4BwOx2PeyHflkKXxlAki0pXUoDp6nEtw/TdWIvktNhXzLfCNOkVrCWUxLDiMRJJSyrYllIWAK4HD0457P3COBjqWAiOhbEmc2f4G6KVB4fvSMo5FZFms7LcK80leRlUnZNw2rOuXhBxKzEXkYeIs4pvAtumBtAvMPyGecHsL2KFUPZkishPW271MYvFo4ARVfSFt20uIPcfrLUMvNiJyAqb6HN3UvYmVUOekcyEivYnMcuA2VT0hZb31O95Cqr3ez8BJGuhLTRl7MUn7fL4FbNOaq6VE5FXMjxhgP/rxA3EgXhBtCTexehWWXU9yH3BOtroyWZzHK5jPRYjIiljFymGkTqaDBbEPYArjP+T93DYR3Z9khelgrNd7Nr9jbVGf1rPvzSgn8hKmrBJfbZLJsVzYQAtsz+vJDz7obiWI+QxPIpu+1qWArbhM79ML0le5LNxRwC38RVv6k15QeCNW8pmTZUzaOdpgvXR9sV6WVH7BCs2+Jyp+/RLr1X5SVac39bye4pAIrpOB9arAwjkc5m/ioLouyFbVcY2eP5SjsFlosAz46umqvBLWm3E5F7inkEGwhPImsJV7up8G+mShzpXVeETuxez3AC5S1UsybhfKRZgwFpgN241ZHDuZSZwIrJ6eScxgDTYc2FCbYQ2WD5y13HfEHuoRzwInqvOqdqWyN7p1B6rqY0UbZAbcb8HlwNmJxQ8DRzXlui0i22O3kpDwVJdQFseC+qS90ywsuLpCg5ZxrXZtFcOIKzH6qurt9e/RshGRPsR93F+xOeuwOd9hE16K2QLmJdvv3FLqrzDS/FYYOWeCqVjv7zBVTRfh8rRCRGRerJe/L8me65g3sd/7l1S1Om/ntQqf24irxaxh5RlgDLOwSdp7MuzXnn8ZSxc68gL2bTBmY5/fBXIcyhKq+kfjm3lKjQ+6WwkuYzWq0Q0j2gMr0U+HanQTHamE34pyRIZy8knA4c3pr3RZyKPdv8VTVs7CdI0/xzp2bcbvSeB2Vf28qef0FA4XXKcH1j3ILbj+h7TAGguumyyK4jyB3yPumrpaAz07w3ZVWDvDJcB8iVWfA8dpoF+m79NcJExRDR8FrKRBadsjnKr1D1hv2Xgs2z2HGJiEKUJMH2ugG6Vvk3bchbFgJqpkOERVH07bRrAqg0PdorxZg+UDEbkRsxdLZyImUnkv1pf6iFt+sqreXJzRzYmbwLiPWKUaLAC/oKnZWxE5kPj1nUQ/bsMmZq8i1Sv2DUworcVVITkxvahCYRrQU1V/bGCXFov7zn1OHJxsRT82JHY1OUsDvSYP51kHC3SS1XeTsDaE2/MZ/KSd1yuYz8WIyLrY7/qctrJWrXQX1sqQN7cCCeVg7LNuSa/ZmDGj3UHci03S1nmMyzHyOItjbTozsIameIryVzfuRcmOaqC9b7NsGfigu5XgyiFfzHnHeXmEaRxDPxYCnmU66/A8sUGQ8RVWTp7zTYjLnG+MzUDuSWq/n0kQfYYF3OZ+/BMmVPFgodUoPdnhrOgylYU3JbhOZq+bFVw3hCv9GoqJCdYA62qQ2RrJTQZdAxyQWKyYKur5GuRPaE1CeYxYPKivBuWRUUvTgzhfVS/PuF0o3xILFC1Zn+2Tu7HvD+zhFj0P7J6hrPx84FL3dAaweX0leaVARA4lFnZ7DOshTLZDfIAFpFFlRb198YVGRObDsvBRFUUtlmmZo38+x+PGmfzVOIO92I1UG5ux2MTEkw21LJU7ab35HwObttYbWZEUu8LX6ccJmG4BwFANtFczjt0ZE1g9lri1AeBRzCYwry4nGc7/FCZGBdBdVb9vaHtP68TdtxyGfaeXS1s9G7tW3g58mI92Emet+RTJ6rlh2F35TD4H9lTV0XKwHMByPJryzXgfGEgyyTXAHWfZLE79m6qmV2N5yhQfdLcSROQcrIQrd7ryKiewLqPpSn8shxNzI9ZzNTOn8VjZzQFYsL1GyspaTAH9M6zzzwKcl7AL4BvNFVPxNA33I5VJ0GyRHA4zhjkz19+WYgJFwhRP+i+B9RrKKksom2OlYknV29gvtpkBhbMM+QnLKP+LlXEWROglV1xv3PeYu8E4LNs9eY7tQumHeVgDnKKB3lTP8ZLZ0Yw+yCLyP6yaJaLsxGBEpBeRG6u9nlMxm6NDE5vNJrayuV1V+xZrfBHOfukVTE8XbAJjP1UdkIdjX0wlF7IxsDmzkRTbngeBMzRo+ROkItIBm6hb3i06W1WvLuGQCoYTo/qB+Ka+F/24G+jtnq+hgX6T4zErMLujq0mdmBqOley/16xBZz+OZBtMQe0GPeWP+1xug2W/dyJ1IggsNL4deDTTb15O57Jq0evcuYxx2PTzn/zLMpzA3jxKh7Tk0yws2z0Ty1sbp2IVRY2p8H+s2nDVmad88JZhrYd0u7Ds6cr2fEBX7icZcI8DdlXVU3MJuCWUFSWUGzAbkrtIBtxTsbzQTdh84M+MxSYKllPVXVT1NR9wFx4R6SIim4jIsSJyi4i8LSJ/Y8HR+1ilwQlAH+oPuCPbrtuwH5jNgIVUdRFV3UJVT1TVO1X1/RJWLFxFbCGzNnBSQxtroO8Ba2Jlw5FK9UJYYPG+hLJG5j2z5lRi66VbyyXgBnDChJE3dhfijF86SeuwvTNtICJLYHZuEcdmCLg3xCxSIs4pt4Db8R3xbVAvVf1PVQ/Dssk/ueXJIDTVeaEIOPGoT4gD7nHAlvkIuAHoQQ+Oxa4GccD9E7ClBnpYawi4AZwy/SHEskaXOH/zVocr7b4usegMks7ByR7VLBCRNbDfjgeIA+6p2LW0V7ECboe3DfPUoaq17t5yFyzjfQWxVSBYK8LtmO3YrSLS5HtpDXSGBtoXswazu+kumGLKBnRlI56cI+AGq8fbCOiUsvQyTA+hsTa3Vuu20Brxme5Wgoh8hQUMOewEdMc62H5JWfMhsH+21inOjmlH6rNwGI11kH1LVD7zEXaRezbXDLonO0SkPZaxWRFYyf1bEQsKcs1cp5SEY5nrvKjNFhonmPYh9mmfBvTIxr5IQlkSuJ5UT+oaTKU50GDOnudGjtcFM7zrgHVvLaVBeb2HIrIyFmQKdlOybEaLrFCGY1cOgCU0iAVcXFn5q8C2btFjqnpgyv5zWoPdh4l8leWPkYgMxSYPq4FOUW+eE1oLsIClMrHLHcC5xRCCcx7cL2C3dmD9gNvlo6TW2TheSeyvDkoNwjXAxS1FKC1XRORqrLoFTOJoveYIh5YrTnzqN8xbvoa1WYud+RwLAf7B2kca7Id2LQ0hcCKp34H+wKmqmdtPComIdCcOvJ9S1X2LPQZPeSMi7bDf9uOBTPaXA7F71AFN/e5LKMtglVzrNbKpMRuTpVyUuNHD3E22wia75xQdNq5V1TPrWecpM3zQ3QpwCqFTyMVqoAcWkr1DZMcFNsN/GaZQ26jIiYTSFZvDO450hd/ZWNHOZ8BfgAU8j2Lll0OzHqenXlyJ4NLEAXUyuF6aOcuoGmIsc1pxDVctvIVWoZFQomw8mLzJDtmWikso22JZ2xUSi//CfG2z7mGVMKV3+TYNUm2XygUReRyIfJjPUNXr5tgmlBC4yD09WYNYOExEjsF64QH+xMrKxyfWp1uDvQ1sX85iRyLyEFY2C7C2qn6Vtr4nVoKe/L79iZXUDijguNI9uIdgNmt/NfvYoeyOfe5jwcs/AGEjvUs/bu7xyxk3YfkFcfXYJap6UQO7tFhEUtpFbqAfSxJPNO5cn+Wbm1zbF8uWL5ZYNRLTEXijMCNunDQF829UtbkVSp5WjGshOg4Tn5w3bfXfwD3A3U2ZQHJOPZdiFR+NE7n2TCaZi78Tu9/oD2yfYa9TVDO3eXnKDx90twJcP2Z2PoQrY/Nl32Ol3hEdgN2YwIr01KBh/20JZR2s/Hhf0tUhx2NZ7cFEaozfYzOGD5faAqgl4m5uFic1oI4eL0dqaWs2jMGymemZ6xYfXNeHhDIf9jojS6D9NdAncti/PZb5Oo/Uia13MLXm7zLumLr/L1iFQS2wogaavdNAEXGldd9gAeQ/WOtHut3aam4bgA810E3cvssBXxPbFu6gqq8mjt0Wm/To4xYNBzbSenzBywURORWregA4QlXvz7DN39jfV0kNvv8PC0L+zPOY+mJVF0kP7r0yqc7ndNxQurnj7l63cDa1vEUFn1GN0rZcKxLyiYishXmTV2EVLhu0RhcN55/9G3Zdm8pJHEGXOp2FZzXQvTLs0x1rK+qTWDwDm7C/phyq10RkGDZpMgtTMC+IUrqn9SAi82OTq8cDq6StrsEqim4H3s7lGijdpTs7MoxOWbTz1mDZ7m0xo834U7sPJkb6KHO2de2pqs/haRH4oLsVICK7YTd39bM89hPZCdNs/C1t3e5AR8D6RzZJLx109kp7YCq1c5bjjMRm6X7EShBtPLcD780NN2nNwQXWCzJntjr6P332tTEmYpMwI93/0eORc+vEh4Qp35GxQPdce1EllGWxn8SdEotnY9meSzWYsxTb7Zf0DX9GA90n03blgog8TfzDfqpqqh+3cyQYjt2YKLAE/fgH6/GPbNruVtVjEscUrIz8MLdoLFa2+3OhXke+SPM1vkVV59AGEKlTdZ+OvQ87JFZPwjyz726uZoV7Hy8HzkksfgQ4sjkl0M5m7xisnDxpn/cKN9GL8SwO/KOq2drYtHjSBLm+B9ZSbX0l9SKJSqAqLuQCTsAmkGYDi0XXSSc0dyFwGqmTvS9iVnll811Ou4atoqojSjkeT8vBXWM3x74Tu5PaNgF2PxUlkhp0NpFOMg878Tur1LX/NM5XwM/UsAyVCT+iSZhmx2+YVtIRiT02V9WBWR/fU1J80N0KEJEA6Jdx5dLAFu7/EZgRQXTbIG7dRqRL6j0EHKaBqutFPRLLbC+ZstV0LKP9BSbdY2W3kQfiH3hSEJFOWBCdKbjunOPhZhAH1enB9Vg/0TEnEsqzxBZWD2qghzW0fQPH2RkLvpdJLP4NOAUYkCw5d8HMd9jfGKC3BuWdMXPiUV+7p39j2e70SbiLsRtwMO/mNsTCTD9jPsd1SrAich6WCQP77PZR1UEFegl5RUS6ANEEzQeqOkdvnYgMJO65mxfYFZOMTNrqfQQcrarDaQKuUuBe4KDE4iswi7cmf9+d//rd2C9BxBhMePBp+jEFe03DVbXpgp0tDFem/DGwjlt0g6qeVsIhFQSnsfADdhfwDxfwBFWc4laf6HzZd8ecTJL3AL8AJ6lq7lalBSbtnshnAj1NQkS6YQriR5PaRgH2O/Y0du38OP0aLCLCJnzAlinX1capBW6lloOo4G2sTdP4DJvUno1NdO3oHnfOpL3iKU980F1GOAXQDYG1oWJNkPlABZgMtUOw8HYQMDj5BU8I/cR05m92YlGWw0pW3nJ7RsyPuWYvVe9wzsRy4IcA86SsGeOO9Q32lbfMzu3A8+Xcm1kMnEDH8mTus06/aDdGNTCKzMH1H17pPTcklMWxADjK5G2pgb7TwC4NHWte4FysV6ttYtWrwIka6E9uu92IM+zvaaDJksyyRSRlguJEVb01ZX2YCMz/5AvuZnWs1USxgHpg4ljp1mD7qGpSBb3sEZHfsIBjErBAhhus54hLspdU1d9dsH4NcHhi09lYpvqKnFwh5vTgVqxsvck+7xJKO+wzfB6pmcv7gTM10HGuvzmacMk44dCacaXUg6nns91aSMkMr0bIXq7PezbfcBl/ANslNp+F2YJdkd56Ui6IyF7ETgsXquqlDW3v8TSEm4DbFct+Z/oNH44F34+o6jgA6SGnsRvXpdwdZMvXwFAGsTfrcxfWtmnUiaaJyLrY/eHSwPrAOlDRC+gEoqCToHYwVr36sap+jafk+KC7xDgF3H2h4kSoXRNEq6o617Rps0hVRYW1j9bWzmT27DHV1dX/VVoQXjEMam/BlIGnisgPWFAHMIIFuZgTuBdhHsZhPz1JaZ1VgF3IvWh5BBZsWxHZeMxi5O6mZm5aKk64LpOA2UrYNEauVny/kTlj/cvcPomRbySUYzF1aTDbo9Wbo8IsoayECU5tnVg8EyvTvQoTCtvALd9Bg7jHuZxJ86f+A1g+GSS6EvPvqGFl7sNkw4yUbKCIbIBNykXaD+eq6pWFHX3+EZEXgJ3d0+XSS2lF5B6sIgjMImloYl0f7IYsKcb3PabY/mEW587kwb2/qjbcUtTQMUPZxI0p2bv4I3C0Bvpu4tzdgEhAaICq7s5cRlpP/y/AGtpMP99yw93Af+ae/sBFTKXCuaHcjk20G29gk3DZaciUCBFZFdMsAXhSVfdraHuPJ1vcZ+toLCG1QNrqmcAzVHEPJ9CfBVL86rNHgTuYzoG8wWR25T4sA27sgCky7Q8VJ0FtD4sbFqxp02bhqooK+6mtrZ3B7Nn/VFdXj4/ihsEubniyNbbJtBR80F1CRGQLqHgYaru1a7d07bzz9qxo124pTJR6TlSrmTnzd6ZNG1o7c+bPAhVjoPYwLGi7Gbsxu4F+9AMu5BusCCXq9KvEDL16k72u9Szs1vtTohLyD7CbtWdb8xfXBdZLYGJl6SXhy0HO85djSA2oo8c/teb3sdxw5d4DgY3dois10HObeUzBFH9vIBZrAwtFI/XnYcAa2aqdlwMi8jw2PQdwvKrekbI+lEsYyAXUhWipfa9OWO1TWog1WEOIpJTT75Ee8IrIlVjfNphH9jtp6+dx+58JKT6tdwFn16e14Dy4XyN2hxgH7KzaNAVxCWUBbDLo6MTiaixzeekcWh5WfRVNINyrqkc15bwtGRGpwCaOoiz/Pap6dAO7tEhE5F2slxU2YBLbuoqgj4A3+QNrn3m2JXx/XWZyGvZd8wrmnrzjrul7YloYG6es7Io1ZDaH4cBzXMEFbMcnrMnrdWsmgcwE7dqu3bJqccMSjcQNv7m44dcKqPgdag9J/43yFAcfdJcAV4J8A3Bc27bdauaff6vKqqrcWnqrqycyceLbtbNm/VYBPICVGk6TUDoyi3G8RhuSxjZdsOKx1ALnKcA4lIWRNLux8di892BgBuOwPu97VBtWam4puBupRbG+3GXdv+TjJUm9Oc6GScTBdDK4nmsFzMoRCaU7Zq/UFmu+WEuD5pdeSSidMCutU5jzs3OmBnptc89RTERkbaylBWA0sEJSrEvWk//xBU9Si03iKeup6mdu385YP2yUSX0H849ukZUbIrIHVt4NcLGqBmnrz8BKyQH+p6pP13OcNTALmt6JxX9h1+/n0rbNmwe3mxjaA1MmT/4KfAYcVd/nP01E7ipVPSfTdq0dEVkWK/rs6BbtqKqvlHBIeUdEDsNaC6yhLHKfn8lUnqCb/tyyfsMS4oZewdxTUFz2+0gs+92F6Gq7KnPKsOXCvVSzMT1Ymfd5jEX40Ra3bbuUzj//llJVNX9Oh6uuHs/EiW/VzJr1RyVWw3JaObgNzE34oLvIiMi8IM+DbDHffJtVzDvvGphYYu6oKtOnf8vEie/WQu0noNuzO8fxIVclPP6s23tHqmnHUOwmaxywNsrWSNol4ReshHwEoEwGTsXK2Gc0aZAlIqEInimgXsb9a5d57waJBMzSS8F/wAuYtRgkTBHa+RzYQAOtydOxe2ATYesmFs/ChMau0KDllKaKyEuYYAuYCNg9bnk7rFfMhLU2BbZgMQ30byf49Som0wjWR7+hlrk1WEO4rP1P7ukLqrpr2vo4YMlQFZC2bSXQF+vt7pBYNQALvv/Ipwe3hLIE1gKRHPNUrJf7toY+9yKyNyYWBHCWql5T37atHZEUF4K/MA/6cSUcUl5wAp/nYarkcQXXgUxghbry2Z000JeLP7qm4xXMPcXGaWDsgWW/N6UCmzJdGFgI6MYUujGVeek6x713Jv4DbuEAjuEfXpQ3+atC5p+vD/PM06NZccO0aV8zadLAWtB3QHctV22G1kiumTxPM7CSJ3kOKrbo0mW3inbtlmx8p4aPx7zzrkZVVZeKceP+b33V6s/5P42l0aqoYU2eYjtuoZJvgV1QTkGcGmv0na3GRNE+Bf5mFvEPbydgdrkG3M5XsaGgumM9uzbGRKxz/WdsGiIpZPa7FzBrFVwJ/A/ojgXHJ2Bq081GA/1WQhlKatDdFhOtOkxCOQd4RIMW8Tm6hDjoPk9EHnTZ6pAo4F6UqPB2TxG5HbiTOOAei2UFJxRvyAXhF6ySZT7i3uokSfu5BRs6kKrWADeLyAAs2xC9v7sBW4rIK5gva7M8uF0rxXGYwnmnxKqXgL4a6G8Zd0wl+VpysthrhdyLieVtj1UL3ArsX9IRNQNX7XUw9vmY0wruW0awAuu5Z4cCLSroxgp0I1bFUgkeT8Fw98qPA4+LyCrUchT/cgj/1l1HOwIdqWQWS/AG6/EF3alA6IGyGrA8kmj+bEcN8Cp3yQCRKu3SZXdp23bxOc6bCyJChw49XdwwYAuofU5Edm6pVWgtDZ/pLiLm+yn9unTZTdq1W7rxHXJg1qw/+O+/Z0moLXwD/I9+/AscQy0nUMEiKTtNwXJ8XwBT+R4rqe5AKiVT/nS+oMtQfwn4Ak089DRSg+qUx60gQPBkgYSyMaZRAJb566GB/pqH4y6KlQK3xQK1+7DMZlIH4HPgZA30k+aer9CIyGvAtu7pEVjv9geYYGA1x1Hlriwf0Y+XsQwumKhMH9Xyf43ZICIfEPfudUl6tIrIhlj3K8CNqnpqlscULBt3M6Rdn41HgSM0Rw9uV21xD7GIH8A/mA3YM9lqC4jI+UB0/d9NVZ/PZRytDRFZHNNniPrBWpwSP9R9Xm8itkMDq8a5CTgAWJwK4AL+o4IF3brFNGg5mf20Kg2vYO4pCS77vTumo7F5hk1GYtfqh+jHZKwlawtgbSCkH4dDxRkLLrhnRdu23TLs3nRmzvyVceMGKGg/Vb04rwf3ZMQH3UVCRHoCX3bs2LuyU6cNC3KOKVM+Y/LkjwGe4ySupDPHohxERYodjBXGDQKG8S81/B+wGqk3Z0nuUtVjCzFeV6K6NHEgHf0fPV64nl0bYxYWQP9C5uD6X18G7gGQUO4Aos/3y8DOzRU7k1Aux7LaAFdroGdLKCsA15Ja4gs2K362Bvo7ZUpaQPkz1gcfKXGfSz8OBHowDOifsmu9vc0tERG5hVgep4+qvpdYtzI2GQHwqKoeRA6IyMLAh8QuFGAzqJcBl2dbbSShtMdKhc8h1QbsXuAsDeKJgizHdT3WYgSwSTZq660dEdkP+96CZf9XU9W/SzikrBGRJbEqn/QM/QDgDFX9SUROx65VsDff0IPV3TZ9NWi6RV2xEZEexC7HT6hqi61K8LQO3O/EkVjlSNe01bMxe9G7gXdVtVZE1gc+7tRpI+nYcV0KweTJHzNlymc1wNpJ1w1PYfBBdxGwbEbFp1VVC6zZtesBVdbSl39Ua/n3vydqqzv8O4OTdd4UhfJa7JZwEPAb72Aza0sDAek+3Km8rKo7NWU8YnKKS1B/CfjiZK+jnqQGE3aqL1v9ly8B92SDhDI/1nMciUvtq4E+1YzjdcLcBBbAfkSX0UD/TKzfCriRqDTbmIYpSl+rQXn2VonIm8Qe0RGDgI3px1mM5nIexL6ZxnmqekXxRlh4ROQILHgFOFVVb0ys6wp1ShqvquoOORw33YM7nRFYP/37DR4nlE2xG7aVE4t/wGzAmuQtLSIPYSXIAKu2FiHN5uCqE54i7hd+CdilnCdyTUuGM7DJmOTv/TDgFFV9O7HtfNjv63wswmyOq5u8+VwDTQoAljVOW2Iq1kb5tar2LPGQPB6gLuG0G5b93iLDJj8B90DF4W3adF1+wQX3rbRukPyjWs2//z5eXV09YbBqTYv5frdUfNBdBESkN/Bp58670L79cgU918yZoxk37lnTUFwWk/36Cvic/xjPfdhNYwf3/9pZHHKIqq6ZaYUr/14y7V8yc70kTdNuVMxuKWP5N9ZX7ZVIPXlBwhRl6jFA96aWUUoop2DOBAAPaqCHZdimCvuxvYRYmRosWD8LeLrcrMVEZBMgGfRNB3qq6kjZSDZlCAOJpwvuB44s5yCkKaSpuT+kqocm1lVikywCfKaq6815hIzHzOTBfQgmf3k2qbor92BiZhNSjmE2YFcDSTuvaiyjeZkGTdfkSBPSW0RVxzS0/dyCm2QZRtwScLiqPlDCIWXETRDsgynrJ0VkxmEWdndn+i1NscA7lb+Zv67nezUN9Nv07csVERmO6XbMBDr6+wZPuSEiK2LZ78NgTl/vLl32pLn6T40xY8Yoxo9/AaC3qn5e0JPN5figuwiIyIMVFR0PWHjhw6sKNVsVoaqM/e9BapaaaLfz3/AuM7gDeB4LgC/CvGKzDYYnYn2AycB6Cfd/bj5nqYyh/vLv37yNgaeYSCj/h808A9yngR7ZhGO0wWaoo1/IBm9QJZQuWKVJX1K/jx9i/d5fZdyxBDjRwn+IFf8fUtVDRWQB4BMia7BlgN1YW28on7HnC9ebNwX7Ww1V1V5p6//DrrqjVHX5LI6X7sE9HvPg/sitXx0LtJMB/N/AicCzTnt/L6wfPCmENQizARtGMxGRT4D13dM2PmiJEZGdMUs3gMnA6qrN14TIF26S6EZSPYRrgNuAsCHldde7/gvQhg2YzrZ12fFrNNCzCjPi/CMiz2DfEYCVVfWHUo7H46kPV5mxKzYhvxVAZeUCLLTQIU1WKs8W1VrGjLm/urZ2yqOqcyYKPPnDB90FxkqsZXLHjuu379Qpq+RHCiecsCXnnbcT99wzkCAYkNU+U6Z8xeTJ7yvWazbcjWMz7AZuxQZ3zh/jiQPp6P/o8S+qOrVI4/B4GkVC6YaVmUcqz300iHt2szzGAZjwFcDLGmTXliGhrIplx7dJLFYsY3y+BvpPLuMoBCLyANaHFvE9sCbWB2/lcV0xmbV5rI+9yEMsCiIyDGsNmI1lzmYl1v2AXV8nquoCjRwnkwf39unl2y6DHimQx24MC/IGRyO0Y+vE5lMwLYE78mZ/l8NrmhsRkfuxDBXAu8BWpW5tEpFFMC2Aw0lt33od8+UdnnHHOY9zH3A4VpheQwWV2KTPkhq0jMkXEemHTWwC7K6qA0o3Go8nO5zv97BOnTaVjh3XymqfysoKTj99W/bYY20WWqgTY8ZM5umnP+PGG98kmzhv8uRPmTJl0AzQTn5ytXAUNu3qAegO2r4pqoM9ey7JgQduwLff/pHTfs5SQIBOItLeqe6+R/4C7tlYAP0+8BhWxtgX2AW7Ee+sql1UdS1V3VNVT1fVW1X1ZVX91gfcnnJDA/0D63eMuFtCaUjrIAUJRbAKkois/Yw10OHAdsDOmJIp2Pf3CGCkhHKmhNIUT/m8ICK7EAfcUTC3ClYWHfWj/cv+1Lh82H7Orqo1MsT93wYrW03yr/t/frOHzIyI7Aa8RRxwDwE2yNQvrao1qnorZnn0IgL0Bo5mm7SA+wVgVQ301nwF3I7I6mZutwurj1OxthCAPtjvYEkQkXYiciZ2DTmCOOAeCeyETepkFXA7TExtGvAj0eTSopDyuSt3kq+3R71beTzlxXyA5BI39O27BQcfvCHnn/8cm212JZde+iLHHdeHww/fJKv9LW7Q9kRVa56C0FpvjMqJtQHatJmjVaNB5p23LbfeeiBnnvk0EydOz2nfNm26AqLu3NeQWl7WFG4B9sRu9xYD2qvqcqq6maoeqKrnqurtqvqiqg7xllueFsqdwMfu8YrABTnsuzUQCfV8Rmr/c6NooKqBvoQ5CZyBWY2BZd6vBoZJKDu74L5ouKzZvYlFNyQe93H/zwR2oQuvu+dL0vxrTrkyJPG4V9q6ZGDahQyIyPGYfkB7t+gtYDNV/auhk6rqaC7kfM5gJDsQF/lPBp7nBy7mfA10dHYvITtclj1qIfJBdwZUdSJxphvgKhFZqZhjEGMX4FvsWhFV60wCTscq3l7OVWPBTQK9CMCXKeJrhzZ3zEUk2d7jg25PS2FtEG3TZsHGt4x2WHsZXn99GG+/PZzffx/Pyy8PZeDAEfTsmV0/eJs2dWZB2Wg9eZqID7oLzwoVFfPOrqjILVF1+eV78fbb3/HBB7m3IIlUUVk5XzUWOHzc2PZZMEhVn1PVz1X171KXz3k8hUADrcXEqGa7RWdJKKs3sEuSlCx3U4XQNNBZGuh12Hf3HqzMHMyi6wXgdefBXHCcCNMDxOIuL2JCb+kXpUOcF/fjiWWt1Z5nSOJxr7R1ycA05W7JBUaXY/200e/uo8COqjqJBpBQ2kkol1LJV3RIVCt94Y42mJWoZbCIXOpUcfNFZ+Js6b8NbTg3o6rvYBPTYMrgDzdU6ZBPnC3W65hmS6QjoLhWMlW9PleP9zSsYmckMK2uymU3CaU5ei7FZCQmKghWLeLxtARWrKycr9oMgLLj889/ZuONV2K55eznetVVF6d37+V4553silsqKtpRUTHvbGI7UE8B8EF34Wmf6+/vrruuyeqrd+OKK15q8kndOedR1SewGd6bsJLwppB7bbzH0wJxpd6R1VUVcI+EDXv8SShrEts9/YR5bTZ3HGM00KOxWedk1nxrYKiEcosTYiskfYHt3eN/sJLV9TBngoi/gWfc4+ehTsN8bwmlbYHHVwqSPqa90tYlA9O6oNsJ5DxI7N0O1pJzcGMBkYSyLuY/cT6xkvkIYDNeYnNm1E2AVLltvhSRdbJ6JY2TnDjwme6GOYd4Mmo9cquSyRkR6eJ844eSWu79Pua3e3SelOY/BAZRCwytE3tsC+ybh2MXHPf9ilp2VpFC+bV6PPkl57jh1lvfZsCAr3j//XP49ddreeON07nnnoEMGDA462NEcUNuQ/Xkgg+6C0811Gad9Vp88QW4+OLdOfHEx5g5szlaBrXgMnaqOlxVT8FmsDbDBJom53CwJZoxEI+npXEFFtiA3UAf38j2ySz3dfnsqdVABwObY7Y/Ue9oJXAC1u/d11mQ5RWXQUv2pR+KCXm9ACTvBhbFtBzQQKdggTdYefW2+R5XqVHVsUAkstFLUmVl58h0i0gnzMc58rpW4ATXklPv74LLbl+OKcNHGbrZmM1cLw30fVUdiLU0XEJcndEDGCQil+Uh6+2D7ixR1WnAQcSaBxc4sby8IiJVInIC8CN2DYiCyF8x3/DNVTX7u+xGcJ/Rq4HUGo+WVWIepfraAYX1bPV48kO1u4fPml13XZM991ybvn0fZdttr+Pkk5/g2GP7sPfe62Z9DNVaJf4t8RQAH3QXnv9qaqZXZttOtcYaS7DQQp147bXT+O23a/ntt2vZcMMVOOKITfjtt2upqGi8pVNVqamZKpgXZ3J5raq+r6pHYDfLBwJvEpew1ocPuj1zDc7XOOl5fLmEkrExSkJZGguIwTKdDxZgPKqBPoMJnFxInE3uAtwKDJFQtqpv/1xxwdrjxH3HN2M2VC8Tl5p/ndjlokTw+Vhi+QH5GlOZEWW7FwCWSixPBqZdnQf3QOJM5AxgT1W9raGDJ7Lb5xIHVV8B62igFyV9t1V1hqpeBKwDRMFWJXAezc96+6A7B1T1M2Kl7ArgURGZL1/HF5GtsdD3FuJe+2nYNaG7qvbPtW87S14ARvIPECsP9JZQ0oUEyxXf1+1pafxXUzM1J3epCy/cmVtvfZvnnx/M99//xbPPfsE99wzkxBO3zGp/VaW2dnolaXGDJ7/4oLvwDIbqypqa8Vlt/MEHI+nT5yq23vraun9DhvzGc899xdZbX0ttFknz2topqM6swm7UMqKq01T1MVXdBvOJPY84u5eOLy/3zFVooB8Ad7unHYHb6hExO5U4MLpVA81N9TC3MU3XQC8FVia2JgO7kXxTQnleQslHP9blwBru8bdYqWx/YrXuEVj2Pbq+rImpIwO8QRyg7SKhRKJOrYkhicc9E4+TgekqWJZ6Tfd8PGYnVW/rQQPZ7QuB9TXQr+vbV1W/xqoyLiJ/WW8fdOfOlVhJNphr/a3NPaCIrCAiz2PfrWTQ+CiwkqpeqlrA645qDZGS+ZCUVYcU6px5JtnU6vu6PS2Bwaozq2prp2S9Q/v2beeID2pqarP2+LYYpbqSBuIGT/PxQXfh+Qpg9uzs2qumTp3JiBF/p/ybNm0W48dPZcSIv7M6xuzZdba+X2SzvaqOVtUrsJvq9YE7sJvEiGkZd/R4WjdnYz3LYHZeKX2Mrqc6yohPx2StCo4G+rsGehCwAaaUHrELMFxCuVrCpmXYRGQr4DT3dBYmiHYDEE2X/4uJf40HLk7sepGIiAY6G3jaLZsH2LUp4yhzhiQe90o8TvZ098UmM8HaAjZS1Y/qO2Aj2e1L3fvaIKo6W1UvIX9Zbx9054gLUA8kdh84SET2a8qxRGQ+EbkaCxp3Saz6DLOYO0hVc/MTbToPA2P4hriAHg5qTO+iTPCZbk9L4wtIuZdvlDff/JaTTtqaLbdclSWW6Mx2263OMcdszmuvfZPV/rNm1Z3LB90FxAfdBUZVx0HFsOnTfyia4vf06T8oVPwM/JnLfmp8qqrHY9ZgewOXYQJKHs9chQY6gVTf3VsllEUTz48D5nWP79dAi6rwrIEOwgLvQ4gLP9tgPeYjJZQjcrkpFpEFgYcSi87B+rKj7/9MYFdV/ck9f4G41HodzGscUlXMW2OJ+ZDE416Jx8nANCrNH0o9HtxQl92+Aivfzym7XR+NZL0vzyHr7YPuJqCqv2LXhog7RGTp+rZPR0QqReQITADsTGINhb8wbYANVHVQvsabDao6A7iZaSS9CxanZXh2jySeKvCZbk9L4A+o+Hn69JFZ15dfcMFzvPzyUK64Yk8GDjyHiy7ahUce+Zirr341q/1nzPihFiqGuQl1T4HIqWfA0zRE5BjgjoUXPlwqK/PW4pWRmpqpjBlzr4Kerqo3NL6Hx+NpCAnlKeK+7QHAHpgoz6/AwpjiyYoa6KiSDBCQUDpiWdLTiV2cwWatT9ZAP8y4Y7S/1aA9C+zuFr2J9Y4+T2wbtZ+qPpm23x5uP4BPgQ3ohwCjsExvDbC4BnlRUi4LRKQCy2R2AH5W1eXc8nOIle8B3gb2qM8SzGW3HyQ1EPgKOKwpwXY9Y13DnWPNxOLhwKGq+nkj+94FHO2erpVPga65ARF5lHjS6X1gC5cJb2ifTTCnkeTfayZW3n2lqmZfb5pnRKQL8Bur0CFR8/OUBlr2SuYi8h3W8jED6NjY38HjKTUichrItQsvfJRUVs7b+A7NoLp6EmPH3q/Asap6d6M7eJqMz3QXh8dApk+dWvh7lqlTh4CVhT5Y8JN5PHMHJwBj3ePdsDLzg7GAG6B/KQNuMOVwDfR8rEXk2cSqtYAPJJQnJZSlMu8NwOHEAfd/WF/3Y8QBd7/0gNsxABjmHq8HbO38zp9wyyqJJyxaBapqBkrGsiLSWUSuIDXgHgvskCngLkR2u4GxZsp6rwp8kkXW22e6m0dfbGIOYFPM4z4jIrKUiDyJBefJgPtZTCTtglIG3BBV7XEvI4GpdYtbimd3VGLenlTLQ4+nXHkQmD1t2pCCn2jq1K8AmUZqlZqnAPiguwjYj6VePHXqYJ0166/Gd2gis2ePYerULxT0al8i4vHkBw10LKnloreSegN9DWWCBvqzBroX0IdUhfH/ASMklFBC6ZDcR0RWxLJrEacC9wGRCFp/zJZqzvNZAJpcF7iseVLFfP+mvJYyJ+nX/SxWip/kv0we3Ine7XOIf3+/AtbOtnc7V9J6vaN+vUqsMuIrEanPU6Zr4rEPunNEVSdiNmJRa9nF6e+1iHQQkRATJ/xfYtXXQB9V3UtVfy7KgLPjBmqoIW4TbUfquMuVpJia7+v2lD02yaVXTZnyuc6ePbbxHZrIrFl/MW3aEAW9pNQTe3MDPuguHteBfDVhwuvVtbX5t8FTrWbChNdrQL4DLs37CTyeuRgN9FligbAuwPLu8bsaaFaChcVEA30Py3IfSyzw1R7LeH4voewnoYiItMEC5CgQvw84jNjPdghWityQJsWzQNSzvCHQRwMdBnW35htIKK3NH3dI4nEf938tcXCaDFgbym5fgGW3s1O7aQYu670+llHPJusdZbpn4sU0m4SqfoBVjQBUAY+JSEcx9seC7YuINQD+BY7ByvnfK/Z4G8P1qz/VAj27vZiapyVyKch3Eya8Vq1anfeD19bOZsKE16pBvgKuy/sJPHPgg+4ioarVoAfX1EycPX78i7X5/AKp1jB+/Cu11dXjaqD2wEwZFo/H02ySZeYRZZPlTkcDrdFA7wJWxBTIo4vOElgZ2Yd05Q4gyr5FgkNREDkGE06Li0kzncf6I5PZ7ovc/8lsd5MUnMuYiWnPp2AK01FWsovr/UZC6U392e3LCpHdrg+X9b6U7LLeUdD9b4H8n+cWLiZ2GVgReASzFXuM2I6zGvuOrqiqd5d5z/E1/E3s6wDrSSirlG44WeFtwzwtDruXrz2wunpc7fjxr9Tm87KgWs348S/W1tRMmg16sBYiqvfMgQ+6i4iqDgfdadas0dXjxj1fW1s7o9nHrK2dxfjxL9bOnDmqFnQPL3bj8RQGV2Z+Y2JRDbE1U9migU7QQE8DVgdeqVvxKxvyX50yeTVWRh4JZ80CdlfV37I8zdPEusabichmQLIH/IB6fM5bHCKyNbGHO1jWeGNVfZk4011BdxZ22e103+2iZbfro4Gs9yARucJlvaOg25eWNwNVnY0JqkXVArthFSERrwCrqeppqjqhuKPLHVUdArzZwjy7fyBWMPeZbk+Lwe7pdY+ZM0fVjh//Ym1tbfNzarW1Mxg3bkDtrFmjq0F3tNjEUwx80F1kVPUd0G1mzfp92tixD1fPmNH0dq2ZM39j7NiHqmfO/HUmsJO76fN4PIWjd+JxJXBHSwkmNdDvNdAdgR2YzkieA6L8ZS9AODux+TGq+nHWx7Yp+GRby0Ua6K9YRg9M4K1nkwdfJojIUcCrQNKGQokzaRagdgP25APKILtdH/VkvSuwMQ8B2rplPuhuBiLSCevtrkpb9SOwvaruqKojij+yZnF1ime3cnA5e3ar6kzs/QZYRaR8x+rxpOPu7XeaOfPXmXbPn+1c+JzMmPEzY8c+XD1r1h/TQLdW1XfzN1JPY/iguwSo6kDQ7rW1098ZP/55xo17UWfOHE02FXyqyqxZfzB+/Ms6btxz1NZO+xB0VVV9vQhD93jmWlwJ5a7uadTjvBtQ9pY5STTQV7maz+sKpBcHvqcKdb8HS/MW/VJKw7PlCSDy8N5CRDYmtcS8xXp2i0iFiFyNZbijG/Y/3P9tMTsiaMt4tsSczatYwa0vi+x2fdST9U6WC3tRziYgIm1E5Dgs2LuIeBIj4lfgjaIPLD+8zVSGMNI9ExYHtirlgLLAK5h7Wix2j689amunfTRu3HOMH/+Kzpr1Z9Zxw8yZoxk37gUdP/55amunvw3aXVXfL8LQPQm8T3cJcSq/B0PFBVC7QmXlAtXt2y9b1abNIlRVLURFhWmr1NbOpLp6LLNnj2HmzJ+rq6vHVUHFL1B7BXBvIyJHHo8nD0go9wBHuqcPY7ZhAOOAHhro3xl3LDOcgFMUDE+mA9VMxWx/VsC0xisYgWU8n9cg+x8JETkMuN89fZN+7A/8hWX5/gCWcpZiLQYRmRd4lNhSDaz/dgyxTdjB9GMEU3iJjiyU2O4r4NByDLYzISKrY1Y1ayUWjwe2bczX22O43/XdgCuBlRKrqrHvxs7AYm7Zaap6Q1EHmCdEZD9W4fHElOOTGmjZajeIyCXY5BeYVsULpRyPx9MUnFbIkVBxLtQuU1XVpbpdu2Wr2rRZ2MUNpodZWzvDxQ3/MGPGz9U1NROqoOJHqL0UeNjrdJQGH3SXAe5HenPgCKjYFGqXzLxlxR9Q+wH2w/22D7Y9nuIgoSyKZabaApOAJYF7iD2oBwB75BKglgIRWRqzI4rKo78E1gZgPiZzHJ2YJ2WXD4EzNdBBWR6/DabIHGWSNqAf5wM7ued9nLJ6i0BEFgVeIBabqwFOVNU7RGRb4DWqgD34nFVZm6h6rAYYxbOsyH7lUEqeC+5veBemYh9RC1wNhKrafDGSVoqIbICJK26UtuoZ4DxV/VFEtgTecstnAb1VdSgtDBGpopIfOZ2lmRdQZiEsokF59qWLyL5YNQ7Y3+KKhrb3eMoZF3xvBRwGFZtAbbfMW1aMhtr3gXuBgT7YLi2+vLwMUONdVT1QtWYpTMBmM2BH7GZ1c6Cras0Sqrqfqr7pA26Pp6icRFweeqcGOolUNfPdKPMyc9fH+AhxwP0tUcANE5jEOszDBsR92AAbA59IKM9IKCs2dg4nGnV5YtE5mFJ6RIvx7HZZ30+JA+7JmHbGHe75ELphBk+rsi7R7+mfWMj6GB+3tIAb6v6G6WXPUa/3lyLSe8695m5EZEUR6Q98TGrA/SGwgaruo6o/Aqjq28C1bn1b4HERSZ3qagGoajU1XM/XboHQlngSshzxCuaeVoOq1qrqGxYT1CwBLITFCjthscNmQBfVmqUsttD3fMBdenym2+PxeBpAQukE/AYsgPW8LqOB/unW7YVlsaDMy8xF5DzgMvf0X2Iv6VpM0OkNACcMtwtwFbBy4hDVwJ3AxU7Jvb7ztANGYd3isAhrcxzvY17gE4BFNdCZ+XlVhUFEtsMU2Tu5RaOBHVWtTFxCaQ/0o5az66auldn8zqM8wGGu4/9yVT2/yEPPCyLSF7jVPX0W+zy0cc991tshIgtjvfDHkiqUNgI4G3gh042u+44MwiQMAW5V1RMLO9r8IyIdWZw/ONpN5FXzpV6i65R4WBlx7/lUTJNhsKqu1cguHo/Hk1d8ptvj8Xga5ggs4AZ4NAq4ATTQ/lhwBtCFMlUzd/7LoXtaS6r69mlRwA2ggaoG+jywGnAc1rsMFlScAPwkoZwnocyb6VxOKfj6ugX/cCJWfg/2Pm7XzJdTUJz41UvEAfcXwHqJgDvy3Y4D7j+BYWzPfdxCXIO0IC2XronHD2IVEekK53Nt1ltE5hWR8zGRtBOIA+5/sAB8NVV9vr7MkvuO7A9EkxYniMgOBR523lHVKfzJzfzjFlSxtoSycoM7lYg0BfPuXsHc4/EUGx90ezweTz1IKG2A0xKLrs2wWVmXmYtIR0w4LQoMphKXyt8H3JxpPw20WgO9E5NXC4l9hjthGfOREsrh9VgF3Y1ltQEO4HuS7gplqWIuIpUicj1wO7FC+f8Bm6nqXxJKewnlSsx3uzsAtdTyNtYt9yzzkGqvlQxcWxoLJx7/4yYc1seEqJK+3p84X+/2xR5gKXCfkcOBkZhFXjQxMw37jqyoqnepanVjx1LV74DTE4secJnzlsatDCV+vTM5uoRjaYyoxLw9sHQpB+LxeOY+fNDt8Xg89bMPJpoG8LIGOjx9A1dqfXxi0a1OeK1cuB6I+rGnEgcKHwLHN9bnpYFO1kD7YcH33cR2aYtjQfsQCWX7ZIZfVScDt7mnbXiKtbGSdoCdJZRkpr3kiEgH4Dng1MTia4C9VHWahLIeUXY7/t38khc4mw+I3pFexK8RWnbQnfz8/gN1vt6XMRdmvcXYAfMvv4+odcIk8+4CVlDVfu5znwt3AC+7xwsD9zth1RaDqv7D9zyeqPA4sow9u5N+6CvVu5XH4/EUAB90ezweTwZcEHlmYtHV9W1brmXmIrI7cJR7Wo31VYP1qO+pqrOyPZYG+pcGegxWdp6021kNeAV4S0JZO7H8ZqLyWeVIJtaVmLfHKgLKAhFZHHgf61sGC6SOVtWz6EdbCeUqTCCru1s/Gzgf2IAhvJQ4VC9VnYZNbEBqtrilMUfQHdFI1vvK1pb1FpG1MbXxl7HPesQLwOqqeqyq/tWUY7sJr8OJWzh2xFo6WhbjuLTOs7sd8zG9bFtIfkg8blQY0uPxePKJD7o9Ho8nM1sDPd3jz4APGtm+rMrMXTB5T2JRVF4+DfOpHTPnXo2jgX6nge6KKaUmvZu3AL6QUB6TUJZxx488uzvwBMmMelmUmItIT0yhPBJVmoSJyt2TyG6fRTK7DWtpoJc7ZfKRwHS3LvqsREJ65VTtkCvR2Me7XtgUElnvtbD3BOw9Ohv4qjVkvUVkGRF5DOvp3yKx6jOs5WBXVyLeLNz3JGnPdp2IdK9v+3JEVUcykthWcFKdH3a5MTLx2Ge6PR5PUfFBt8fj8WQmmeW+pjEP7nIqM3ceng+SWczrIFUd0txzaKADgfWA/2Fq5RH7AyMklGtZhXuJiq//Zndm8avbZisJZZHmjqE5uHLhD4El3KJfgQ3pxwcNZLfX10CHRcdQ1RqoM01aQUQ6EQfdnZ1icovClTdHn9sGlfhVdRiwAalZ7+604Ky3iHQRkWuxUuSkxd0o7LO+vqq+n89zquorxGrx7TEbsZb12fmBs+pUHxZkPTlX5i/peDLjM90ej6dk+KDb4/F40pBQegFbuac/YYJajVJGZeYnYZl6ICXDHKjqc/k6iVM6fxorLz6FWEisLXA6+/I2izHULevKm3zvHldgAUxJEJETgBeBjm7Rp8B69KMjDWe3MwlkDUk8XoPUQLWkEwtNpCMQKdM3an/XWrLeItJeRM7Avu+nE4sN/gecDHRX1acL6HV7FrHQVy9MqK3FoBP1A0a6z0sVwmguLPGQMjEWq2YBn+n2eDxFxgfdHo/HMydJQa3rNNCaHPYtaZm5iKyBeWzXLXL/PwNcUohzaqAzNdCbMLG1K4mtkDqzC2vWbfglqxO/k8ksYlFw6tM3A7cQ//71pzfb0o9TySK7nYEhice9SA1UW2KJeXLMWXvOZ5H1LsvMrYhUiMiBWGb7GmJ7wBnYZ3l5Vb05F/2DpqCq07HvRHSeM0Rky0KeM+/8wY11j+fj8NINJDNuwiTKdi9drp9Jj8fTOvFBt8fj8SRwJeH7uafjgIdy2b+UZeYiMg9mD9Y2bdVg4NACZukA0EAnaKDnYlmkhwBlMSwUB6hlcYbUCXOtJ6GskOk4hcBZpw0ATkwsvpLzuIQdeJ90ZfKGs9tJvkk8Xo25NOiGRrPen4nI6vkZYn5wQe0XwCPAUm6xYq0ZK6nquao6sVjjUdWhwLmJRQ+JSMvxex/NdYx1Ey6L0Fm2ka0b2aMUREF3BbBcKQfi8XjmLnzQ7fF4PKkcB7Rxj+/WQKc1tHEmSlhmfiWpCstg6tO7OmXtoqCBjtZADwXWBF5no8TKT1kkUfC+H0VARJbAhPB2couqEY6kH2Npy+dYWThkn91O8m3icQ8gqWQ9VwXdEYms9/nEWe81gC9E5DSnOVAyRGR1EXkVUyVfM7HqdWBNVT1MVUeXZnTciI0LoBtwV0uxEdM/tZo/eb1uwQJcUcLh1IcXU/N4PCXBB90ej8fjkFDaE1v21BB7TTeFopaZi8h2WC93klnA7qUKIDTQoRrodizNNiziZJbGkLztPV1CWaKe3fOCiKyF9Wz3cosmsAwHEXAAcB1xVcAwYJ0ss9t1qOoE4E/3tAepgepizRh6qWh20A11We/LgXWx9xbsvb4OeEtElmz6EJuGiCwhIvcDQyHF1moIsI2qbueyzSVDVWuBQ7AqG4A9SVU3L29mckZdC8nSrCXLll2m3oupeTyekuCDbo/H44nZF1jIPe6vgf7e1APVU2ZeEGEtEVkIK4lN5xhV/aQQ58wFDfVNxnJQ3YKP6h7ND4yUUC6TMP9qxyKyC5bhXtwt+pk9uZRDuRPok9j0emBdDfTr9GNkSZTt7kLckwstM9Od/Iw2OeiOcEHsuth7HNEH+EZEitLXLyLzi8jl2HTPYcQ6B78BBwFrq+qbxRhLNqjqn8CRiUU3i0iLCBD1ZR3Bn87NoCPCclxT4iGl4zPdHo+nJPig2+PxeABX/n1KYtGNzT2mKzN/xj0tSJm5Kz29lzmVsq9X1Qfzea5mUcsATKzKzLni3Ht74DzgRwnlRAklvR89Z8Q4BevhNiXuCj7jFIawOtdiwT5uFFtqoKdroDMyHStLhiced048bolBd14y3UlUdYaqng5sCUQTWfMDj4nIEyLSuf69m46ItBWRE4EfsV7pyMJsIqYWvrKqPuqyy2WFqv4f9r0G6AA8KiJtGtilfJjG5XWPl2RfEaks4WjSSQbdLWIiw+PxtA580O3xeDzGZkBP9/hTDXRQno7bl7jMfHfyX2Z+NLBL2rLXsKCibHCBzdV1Cz4kXdStK3Az8K2EsldTJydEpArzPL6BKKM5P+9yLt1YgN0Tmz4GrKGBvtOU86SR7OtOlpT7oDuBqr6D9XY/nli8L5b1zptSt5t02RubDLkZ+2yB9ZffgCmSX6ParImWYnAqcZDYG7iohGPJnpV5gMlMB2AZ5mFljijxiOpw7SDR9dhnuj0eT9HwQbfH4/EYJyce35SvgxayzFxEVsGCiCQjgP1Uc7I5KxaPAX8AMAJhTN3yZOC7AlYd8LGEsnEuBxeR+YAXSL7fq/EZJ9OHNnRzSyYA+2qgB2qgE3J+BZlJBt2rAP+6xy056K4h9l3PG6o6XlUPwET0JrjF3bA+7xucAn+TEZFNgE8wIcPlE6uewDLbp6lq3l9XIVDVKcABQKQxcJ57fWWNBlrLeJ4CbNprec4v7YjmIOrrXty5Gng8Hk/B8UG3x+OZ65FQlgN2dU//BPrn8/iFKDMXkbZYEJsMUiYAO7tsTtmhqjNJThJ8XPfoZyyTNzCx+frABxLKAAlllcaOLSJLAR8C27tF1ezAH+xF78Qv3dvA6hroU01/FRlJlpcnxdQWbSnK0wmioHtsISduVPVJLOudnHA5BVM475Xr8URkFREZALwPrJdY9R6wrqrur6o/N3W8pUJVPwcC97QCeEQk//oHeWcxzicq2l+FpWReWbek40klWWJeNNtCj8czd+ODbo/H4zHv5ig4ulUDnd3Qxk0k32XmF2N+yBE1wD6qOrKe7cuFu4kynF9j3bWwF+Z33Qez9UoGsbsCwySUu+pTOheRdTCFcvOBrmI6hwC967LbM7GAbpvmiOPVRwMK5u2B+fJ9vkLhrLyiKoy8lpZnwqnqb42VUc90i1fFPL3PzqYX2CmS34UppO+aWDUc+yxtoapf5HfkRecqTBAQYGma56pQFPRS/ZNxmBL8fEAPriztiFLwCuYej6fo+KDb4/HM1Ugo80Fdz+EMLCjMO/ksMxeRzZmzZ/u0clJgrg9VnUwUNNRihcAmqrW9Bqoa6MtYb/1RxJ7XlVjv+o8SyvUSysLR8URkdyy7aRna+ZjBsczDslS5TYYAa2ugN2lQUMGspIL5hMTyllRi3gXq3reCB91gvf6qeiOwDhDZdbXBPOffFZFlMu0nIguLyA2YSNrR2GcE7DNzJNBTVV9W1XTtgBaHqzg4iGiKCg4QkQNKOKTsaMfFdY9XYnMRKZfvglcw93g8RccH3R6PZ27nUKCTe/yIBoXr98xHmblTen6MODMPcB9wS14GWRxuxiY44EtwDt51QYQGWq2B3otloS4CJrtV7bCs6CjpJ5fKPHIB8CxRif2S1HAM7Z1slmIZwvU00GTPdaFIniMZ3JdLoJENBRNRawxVHYaVhV8FdSJ7mwBfi8ghUZm+iHQWkcuAUVj1Qju37WTss7Kiqt6nmr3XektAVX8Fjk0sur2+CYmyoRPPM919d1eggsXKRtwxmen2QbfH4ykKPuj2eDxzLRJKJXBSYlHeBNQaoC+x0FZOZeYu8LiH2HcarI/5+JaU0VPVMcD9gOlJfw7ATule3RroVA30EmA54BqiQL2GDrzE+czgEqLJh9WBQ6ikA2CmZJtpoOdooEnf7EKSDLqTtmc+6M4SVZ2pqucAm2N/Q7AJsQeB50TkEizYPg/cXxqmY5+NZVX1ElWdWtRBFxHXB/+oezof1t9dTnZcKWigNcx2tmcVQHeOFpH2De9VFH5MPPbl5R6Ppyj4oNvj8czN7ECscPxWMTKizSwzPwjYM/H8D2BP1aIFlvnkWqwP3bqxZ9EOUiy96tBA/9VAzwKWZzL38hjKl4kNNgf2ICqMfgizAvtgjgMVlmQfeqfEYx9054iqvo+1GDyUWLwbcAGwgHs+G2tTWF5Vz2opiuR54ATgF/d4Y+Cc0g0lC+bjRtRVLvSkA5XsV+IRoarTiP3ifabb4/EUBR90ezyeuZlTEo9vLNZJNdBnyLHMXESWI7XffAawo8satzickvTTgJWXDwYSJeYZ6UdbrmMDRrnsdiUWbG9OlO/+D/gInEdwcUkG3QsnHi+WvmEZUxZBt2Ma9rfMFEx/D6yhqieo6l8Z1rdaVHUicCBxC0MoIr1LOKQG0UB/Y1pCuWFlLigTRf+oxHxBEelS0pF4PJ65Ah90ezyeuRIJZQ1gC/d0JPBqkYeQdZm5iFQBLxP3rwLsr6pD69mlpXBV3aOPgRq2kFC6ZdpQRNbDcuI9AOviPhgznYpZEJuYGC6h7C+hFO03zimY/+GeLpVY5TPdOSAilU4k7Dvsb7lghs1WAf5PRNYu6uDKBFX9CLjUPa0EHi9rv+kOXF33eHWWAzYt3WDqSIqp+RJzj8dTcHzQ7fF45laSvdw3F1jZeg5yLDO/AQs0Ii5T1f8r2OCKhJs0eA0wXeZvqcCyeCmIyF6Y37JlkBfE9KmXZjpWbrsWNikRsQImNjdUQtmtuZ7oORBlu5O96T7ozgIxdscUzB8lbvsAeAlYE/tbz3DLVgEGicgFblJqbuMSbBIK7L0qhh5FU3mZ2U7Rf2WgM2eXdDSGtw3zeDxFxQfdHo9nrkNCWYg4uJuICTUVnWzKzEVkOyzYiHgHuLA4IywKsX/vh4ByaPQeiEiFiPTD3iMTYFoaM3hbkC+AtTTQ2zTQwRroTsBGWHAesRrwf8CnEso2RQi+k5oAkXp2Swq6k5M+RQm6XbC9LfAZ8BxRJYPxLrChqu6sqkNU9TYs+I46+quw4PN9EUkG6a0ep85+ADDFLTpcRPZsYJeSoYFWU8EdgN11rsZ2rl2mlHjbMI/HU1R80O3xeOZGjiEu1b5XA53S0MYFJr3M/KBohYgsDAxIbPsXsHNLUirPgveJMnZjgJGsAvQWkQ5Yz3dQt2VP4CBqmZdLgQ010O+TB9JAP8ZaBrbGgriIdYHXgfcklI0L9kpSg+7I5qwlBd3RWGcAkwp9MhHZGJskeQ3z6Y74FNhKVbdQ1U+S+6jq98AGWHl1VJ2yATBERI4ok37hoqCqPwEnJhbdIyJLlGo8DVLJPXWP10KQlHGXAp/p9ng8RUVa172bx+PxNIyE0hZT/10Mu2lfXgP9pcRj2os44z0ZWIN+/Ar8BCzrls8GVlIt7VgLgYjshmWkLZO9PY9yN72oZbW6jbYGNuQnhIM0SA3EMh7Tsto7Y5nQNdJWvwpcoIF+lZcXEJ1TZAOsOx1gLLAQ9hlrq6o1+TxXIRCRsUBX4BdVXbax7ZtxnrWxoHm7tFVfYwrlL2UzsSQiGwKPYJZyEc8DR7dUgcFccZMMTwF7u0UDgS3L8fMmF8o7VNEHgEeYxk8spqoFn9zJOBaRtpjgYgXwlarOlfoAHo+nePhMt8fjmdvYm1hRekCpA24ADbQ/FjyA2U09hPAEccANsFdrDLgdLyAu8/Qr8AAH1AXc7YD9gY24F6FXNgE3gAaqGugLWDnyfqSWk24PfCmh9JdQVs3fy+C7xOPIP7kCC77LGhFpgwXcUKDSchFZVUSeBb4gNeD+ARMSXFNVX8y2kkNVPwZ6gfOCNnYFvhGRHfMz6vLGvVfHEltgbYZNXJQfVdxe93gt5gUOLdVQnM3iz+7pinNThYTH4ykNPuj2eDxzDS77eUpi0Y2lGUlGTsRCTviLTYH/JdbdoKovlGJQxUBVa9FEb/dMZwDWGTiccazErhroUU1pA9BAazXQJ4FVsW7w3xKr9wS+kVAelrD5PaZpCuYdEqtaQol50ubsn3weWESWE5GHgWGYyVvEb9jfpIeqPqWau5ihqk5W1aMwH++oTWNh4CURudO1KbRqVHUcNjUVvX8XichmJRxSfbxAjbOAWwXoyKkiUtnwLgUlmojrRKqegcfj8eQdH3R7PJ65iQ2Ie0cHY9JdZYEGOhE4mBkozwBxru8rVT2tZAMrAiJSRWe2T1nYDTic11mEVV3GullooNUa6P2YaNJJxIFlBdZHP0JCuaM+y7IciPq6k/ZuLSHozrtyuYh0E5E7gRHYexxlE//BJplWUtX7nShYs1DV5zHhvKSK/TFYr/d6zT1+uaOqHxDrH1RgNmJdG9il6Gigs6jkPsDqQNZgGaCUFQnJvm4vpubxeAqKD7o9Hs/cxCmJxzdqUGaiFv34lIeYwTj3fCFqWZutSjqmAiNLyEJ0ZQTj63pSja5AJ47QQPOaddVAZ2qgt2A2S+cA492qKqxM90cJ5TqncN8Uvs2wbK4KukVkIRG5HtMkOAZ7b8He63OA5VX1VlWd2ZzzpKOq/2B9/McA09ziFYCPRKSfK6FvzVyBuRsALA48WIZl03ErgHVRn1KicYD36vZ4PEXEB90ej2euQEJZiri09R9MfKjceIW/mAeAtsB+VLBzq7IHS0E2kO2Ywm/864SwBKhyOf5vgN/pW6hza6BTNdCrsL75i4mtl9oDpwGjJJRLJJQFcjz08AzLFsuwrNxodtAtIguIyCVYr+ypxNn+Kdh7vKyqXqWqU5s10gZQ426s1zvysa7EssAfikirzWg68bQDMRE/sCzyqaUb0ZxooCNR3gVgQWAZ+ohIutBhsfCZbo/HUzR80O3xeOYW+hKLW92uQX6zbM1FRM7D7K6MnaimCwCnSihblmhYBUFCEekjtzKYV5no/LfnBXbmPjpwJ2DdqYM5ptDe2hroRA00wBSwr8PssgA6YoJUoySUcyXMujd4rst0i0gHETkXC7YvIO5nnwFciwXbgapOzMtIs0BVRwIbA/2ASMm7NzBYRI4twwxwXlDVv0jYDgJXisi6pRpPRoS76x5btvvkEo3E24Z5PJ6i4YNuj8fT6nEB09Hu6SzgrhIOZw6cX/GliUUDWYOzEs8flFA6F3lYBUHOl0V5k28ZSF+iaY+uzGILdtPn9Ugm0o9KJwj1NV0YVZzyeg10rAZ6BlaOfAcQ9Rl3Bi4HfpJQTpJQ2tV3DEemTHerDLpFpL2InAyMwt6jBdyqauw9XF5Vz1TVf+s5REFR1WpVDYENiUuJ53Vje1FEWsLfJWdU9XXgKve0DfCUiMxfwiGl83+oE1TrDszDASKycMO7FITR2O8B+Ey3x+MpMD7o9ng8cwMHEwcEj+e7T7g5uJvNV4lFpsYDOwA3EfdnLgHcVvzR5Rc5Q/bkRX7hI7rXCcV142dWZkl9UZ8HUNUxLMp7gDmTf81lxRyjBvqHBno8sDLwMLEi9CLY32SkhHKkhFKVcX/L5v6RtrglBHdZB90i0kZEjsQyhTcSK5/XAg9hAmnHq+qfhRhorqjqZ5h13B2JxTti1mK7lGZUBedCYJB7vCxwd7lk9zXQmQgPAdbt35N2WB9+ccdh5fg/uqcriIi/J/Z4PAXDX2A8Hk+rRkKpwNSqI24q1VjSEZEqLLDu6BbVAluo6jQNtBbzsZ3g1u0noexX9EHmAQmlvZwo9/EU/fkmoeq9BI/zByvohzomZYdKTqqbghjBOrJ+8bP8GugoDfQQTBG7f2LVksA9wHcSyn7u85VOeol5Swu6M05KiUiFiOyPZfPvwd6LiGeA1VT1UFX9OdP+pURVp6rq8ViwHb2+rsDzInKziLQv3ejyj6rOxvzpJ7hF+wBHlWxAc3JP3SMrMT9epNEqkkIQVUC0I/Xz7PF4PHnFB90ej6e1sw3mCgswUAMdUsKxpHMH0CPx/GzVeHwa6Gjg+MT62yWUFnVjKKGswq8M5WEO53e3sJIaunCkjtYDMnkz66/6LUtjgdt0hIlcV8wxp4wl0O800L2BtYBXEqtWAB4Hhkgou6b1nrfkoHuiqk5PrhBjV2Ao8Bj22iNeBtZS1X1U9bviDLXpqOorwOrAgMTiE4FBIrJySQZVIFT1F8wHPeImEVm9RMNJQQP9HvgAgIWApVgUmxgoNr6v2+PxFAUfdHs8ntbOKYnHN5ZoDHMgIgcARyYWvQ1zBpca6BPAE+7pAlh/d9lfuyUUkVAO5xuG8AgrMcmtaMt4lN76n97X4AGWT5SVj2bfUts9aaCDNdAdMXGugYlVUQA3SELZ2gXf6UH3fCIyb3FG2mQWcf/XlZa7YHtrrEx5AJb1j3gP2EhVd1LVwcUaZD5Q1bGYk8HxUKcs0BP4SkQOK5cy7Hygqs8Bt7un7bH+7mxFAQtNLKi2FgCnlOC9T9qG+b5uj8dTMMr+xs3j8XiaioTSHdjWPf0ZeLGEw6nDWeQ8kFj0L7Cnar2+4X2hLk+8BaVT+80KCWV+anmct7mPZ2lXJ0nWlqHMorvW6FeNHmQTHmBZLOM6lXnoWvyez0xooB8BfbAKis8Tq3oDbwDvsyuZgppFMiwrC1wQ1sk9/dsF29tgmcg3sNcW8RmwNdYG8XFxR5o/nLXYHcC6QJShnxe4H3hMROYr2eDyz+lYlQKYdNnNJRxLkmdRV/7eA2jPWsBGRR6Dz3R7PJ6i4INuj8fTmkn2ct+igdbUu2WREJHOwGuYqjBYH/cODdkpaaDjsf7uiCsklNXq2bykSCi9mckQnmZfVzxqVPAIs1hPNTsROw20ltUSXurTOb9cMpAaqGqgbwLrAbsBwxKrN2ZNbuIIUouwy7vEPDkhIMDHwOukBkDfALsC66vqWw1MELUoVPUbYB2SPcbWCz1YRHpn3qtloaozgP8BkT/64a43v6RooNMRHgbsamhu3acUeRg+0+3xeIqCD7o9Hk+rRELpAhzink7BMlglxanj9gcWSyw+V1U/r2eXOjTQt4Eb3NN2wKNZ2FcVDQmlQkI5i/F8xH0sw/d1q2qB06jlENUcvdF7cgnd3OOpLIqwXf5G3Hxc8P08Vpq8PyRe9ZLAgZh01UqAlHXQnRzbpsD6ieffYa+tl6q+0FqC7SSqOk1Vj8YC06gRYjngIxE5szWoWqvqCFL1Ie4SkXLI7KYLqu0uIssU8fx/EU9GlMP74fF4Wikt/ofE4/F46uFIYB73+H4N6s8kF5EQKw+PeAe4Jof9zyPuF+4JXJyncTULCWUR4FV+4SruoYpIi1yYjGXxb2hKsKaX6CjWSfRHt6dfXgacZzTQWtd7vxoWuMVj7oaFrKdzk4SyW5rgWklxauS7AY9mWD0Mey2rq+oTmQTvWhuq+jTQi9hqqwq4GnhFRMq2PSBbVPVhcJllc0x4skSK4XVooMOATwCrt+hGBXBC0c5v16Uo271cqbUjPB5P68UH3R6Pp9UhobTBFIkBFLilhMMBwKk/X5BY9C/wv1yCUQ10BnAA5mANcKaEsln+Rpk7Eso2wNd8wTY8DEyrW/UDyrqq+nqzTrA61xEZhk2nt0h5ltUDaKA1GujTwBq8yYspbtcdWRL4P2CwhLJnKcXwXLC9FzDYjWnZxOrRwF5AT1V92nkZzzU4u7NNgSugzk1+W2Co63Nv6fQFRrjHa2GTCqUmPdt9pIh0rG/jAhD1dVeS+l3weDyevOGDbo/H0xrZHVjCPX5JA/2xlINxVkSPJxYpsJeq/pvrsTTQocTBuwAPSyjzN3+UuSGhtJVQrqaG13mZhXkJKyQ3Xsd6f0fUe4BsqeIZ1mVW3fMKTm/2MQuMBlrLRzzPXcCTWAFrTE+sxWCohLKPhFJZrHGJSKWI/A/4GvPVXiPDZseq6rNzQ2a7PlR1tqqeh4nlRVMniwCvi8hVLTkbqqpTsAqGqNXjJDchWEqeJirrXw1ox/zErUHFwIupeTyeguODbo/H0xpJqnvfWKpBAIhIJ+AFTBk5IlTVgfXskg3XAe+7x0tRZDViCWU54AOmcSaPkqrhDdcDO6nq+HycSwOdQk+eISqCVQ4QkYXzcewC8y2KdXnfBQzgM+CLxPrVgKeAbySU/QsZfLtge39MDO1JUr3hP8cmSSJSpwjmYlT1LWyS5LXE4rOAD0VkudKMqvmo6lDgtMSiB0RkqZKNJ9CpmP87tMVM+ODkIvbSezE1j8dTcHzQ7fF4WhUSSm9gQ/d0GPBuycZiatsPkHoj9wFwaXOO61TYDwEmu0UHSyh7NeeY2SKh7AsMZgy9uQczYjNmAYer6umqWl3f/k2iA/c6H19Q2gDH5vX4hWF4yrMhCGa9tQPwaWJNdyzgGC6hHCShVOVrACJSJSIHu7E85s4VMQjYHlNgn5VYniyKn+tR1THAjsAZxG0dvTF1831LNrDmcwfwrHvcGXhcJH+fvSaQ7tm9Ivb5LAY+0+3xeAqOD7o9Hk9rIyXLrUFJ1ZbPAvZMPB8P7JuPPlkN9BdSBYfuklAWb+5x60NC6SCh3Ac8wQjm417s1RhjgD6q+kB9+zeT91mH34kkyIQTSi0A1RiqOonYWx1gUad2/iqwAVa6/FFi/UqYyNX3EsphTpegSYhIGxE5DMuzP0TqpM+HmM/2hqr6mtMUiNTLFRjb1PO2VlS1VlWvwybzfnKL5wOeEJH7nM95i8L93Y8EfnWLNsKEHksznkCHEFWCLE7k73BKkU7vM90ej6fg+KDb4/G0GlzQuY97+i+pfdTFHYvI1sDlaYsPVNU/83iaR7D+YIAuwP2FUMeWUHoCX6AczofAEyRzo4OBdVX143yfN0IDrWVB7qvL0yoLAS0hy/ht4vGikc94wud7E0zNPtlqsDxmb/eDhHKUhNI225OJSFsROQrL3N3vjhXxnjvXphl8tqOge2zeqxRaEar6BZaHfSyx+HDgCxHJ1B9f1qjqBOx7FP3NzxWRrUo3okS22wTVtiqGcKKq/geMc099ptvj8RQEH3R7PJ7WxPGYzQ/AXRro9FIMQkSWxXpnk9fY61T1lXyex2XxjyXuw90WUyfOCxKKSCgnAJ8ym1V4DngrZZNngE1U9bd8nbMBHk5xj4ZToyC2jEkG3W2gTocdqAu+39VANwc2B95OrF4GC0JGSijHNuTJLiLtROQ44Ee3zzKJ1W8Dm6lqH1V9N10t372HUdDtS8sbwVUwHAQcSuzvvArwmYj0bQGfyRRUdRBwvnsqwKMltEd7kug9XR3r74aTinTuKNu9lIjM0+CWHo/H0wR80O3xeFoFEso8xL2+1cDtJRmHyLzAc1jmOeIzzGM772ig/wGHJRZdI6F0r2/7bJFQFsTspG5hEu14AJPhirkIszybmmH3vKOBjmJJBtKtblFPLFAtZ4anPV8041aABjpQA90K2Bh4I7FqKaz/9icJ5QQJpX20QkTai8gJWMnz7cCSif1eBzZW1a1U9X3qpzM2IQA+6M4KNR7C8rFD3OJ2wK3A/4lIl/r2LVOuJRbTWwR4pIgiZnVooJOJqpPaEcn9HSQiXYtw+mRf9/L1buXxeDxNxAfdHo+ntbA/sKB7/JQGeS3jzgqX5boT6JVYPAnYT1VnZdwpD2igr2M3/ADtgUdzKUtOR0LZFAsmduV3LHcav5vTgD1V9ZJcPMbzgvBgera7qOfPnW/TntcbdEdooB9poNtifd/JyohumN/8KDlLzpC2ciYwyi3rltjuFcyubTtVTfaM10cyq+mD7hxwlnjrAzclFu+KeXpvUppR5Y6zhzuYuGJma+DsEg0n3bO7PXB0Ec7r+7o9Hk9B8UG3x+Np8bg+5lMSi26qZ9NCcwJWeprkSFUdVYRzn40JZ4H1nV6U6wEklCoJpR+m+L4EX2Pa61PqNvkVE+B6rrmDbSL9WZWpzFf3fCcRKecezKwz3elooIM00B2BdYEXAeuj/5jFuJ1rmM3V/H979x0nV1X+cfzzbElCGgkQSmihSe8dARGQJr1LR0BBEAuKBfHmAgICFqQX6b0o5SdKlyK9SZEOCRBaek+2zPP749zZuTvZMjM7ZZf9vl8vX8zcufeck3Vndp57znmebLqp4B7C3vpvu/uzCzTYufSYFHQXyd3nu/uPgd2AycnhZYB/m1lkVr067D2RZGk/hJBMD+B0M/t6DYbyAtnVA8uQvSV0vFnpNxELpAzmIlJRCrpF5KtgW0LdY4CnPPLnuzq5EpKZrT/mHb7c3W+vRv8e+RzCl+ZcUqTYtujiknYstmWBR4CIDHU8SFgkn8uz/gSwSVLjtyY88lnUcwebtB0y2mer71WS/b+TU4eW6uzcTtuI/AXGchCX8Bf+QBMPkNtJDLAq89mX8xnLwUmir2Ip6C4Dd/8/wpaHbFK8OmAs8IiZLVOrcRXD3R8hV86wnpCdvapL5ZM8Ffmz3aOBSpdE1Ey3iFSUgm4R+SpoVyas2p2b2dKEpGLpOrevU72SNwB45C8SvuhD+Hy/3mIb1t11FtsehNmlrZgH3ILTfmHyFcD2yWxYrV3DhuR2IcORZjay89NrLr3Koai9omY23Mx+DYzjC05kPrnZvjUIGQy+w0DW4kfAOIvtVxbb8E6a60w66P6iyGslxd0nANsRVplkksNbE5ab71GzgRXnNMINNgg5Av5ag+RwNwIhCeY6ZN/rP67wOBR0i0hFKegWkT7NYlsF2DV5+jEh+Vf1+g/1ou+g/d7YuYQkY7XInv57IFu+a0XgT52daLENstguBO4CFmEKcAXNvNNWEbuVkD34+5Xck16kx1mIcald84OBY2o2mu69nnpc0LJVMxthZqcC44DfkctV4ISCbWuxP2uxJLeQWw68KKFE3TiL7VSLbUSB49NMdxm5e6u7nw58g/B5BCGp4l1mdoFZLhFeb5SUjDuI3AqNPQnbZqo3hsinEzKZhx3dawBhm8XmFevTfSa5m04rVqofEem/FHSLSF/3Q2gLEi/0qOp1hs+HvPRecIK75+/nrYrk338ouZ3YR1lse+afl2Q4f5ZsibEPgEtpZnLbHPJUYCd3v6DqCdO64JFngGvZtN3hH5pZY8dX1NyLqcfLdnoWYGaLmFlMCLZPI1diLAPcAKzh7ge5+xse+Rse+XcIIckN5GZWRybXjrPYxlrc7SqAdBK2zzo9S4ri7k8SEiqmbwKeADxjZqvVZFAFcvdPCCXRss4zsw2qPIz8JeZQxnKInfgw+e/o5GaqiEjZKOgWkT7LYluYXLmsOcCVVe3f7Cjg+3mHbyakH6sZj/wD2i9tv8JiWxLaam8fRUhYtA5OqMJ9HRma2gLuN4FN3b19Ve7e4zoWI70IdBlg75qNpmvpfdaLd3SCmS1qZmcQgu3fAgsnL7UC1wCrufuh7v5W/rUe+Vse+aHA6sC15HbhLwxEwHiL7YykBFxH0jcCPu7kHCmBu08B9gF+AMxPDq8LvGhm3+3NNb2TPerZVTIDgFvMut+qUkbPkF0lshwwCoD9zKzD91CZjEs9Xr6C/YhIP6SgW0T6siOAocnj6zzyKdXq2Mw2ZsFa4O8Dx/aSmeGrCMvGARYDrkxuUtxMuDkxmBbgb0zlnzSS+3twH7C5u79LL5XcVHisj5QPezP1uF3QYmajzOxswpf9U1KvtwB/BVZ19yML+f/CI3/HIz8CWDW5NrviY1jS9jiL7SyLbVTepdmge5q7z0LKKqnpfQlheXT2d2Ew4f+jm8xs4U4vrr1fkrtptApwcbVuFCyQUC3MszcCR1Ww2w9Tj1eoYD8i0g8p6BaRPikpE/aD1KELqtZ3mG35G5AuY9NM2Mc9o1rj6ErypfV75PYpfht4DzgAgOnARXzJa6SXH58D7O7u06s41FJdwwqkd9JvamYV2/NZquT3ITvL2WBmg81sSTM7lxBs/4LcjaNmQlX0Vdz9aHd/v+j+In/fIz+asA7g8qRNkj5+SQi+z7XYljSzOnLLyzXLXUHu/hqwEelAEg4EXjazTTq+qraSPA4HAjOTQ4cAh1dxCDcA84CwUD+swzm2gmXYxqUej6lQHyLSTynoFpG+altyC4wf9ag6e6jNrAG4lbCkOe3n7v5iB5fUjEc+ETg6dWgxAD5gFhcwnalty53nAYe5+y/cvZW+4Q6M2X1ktju9AuNmwpf7nxFmPCFU4L4YWNndv+/u43raoUf+oUf+fWDlpO1sIrzBSd/j+CVXs0jbjaNPetqndM3d57j79wg3vrI3tlYA/mNmJyc3QXqV5MZPOlHhRWa2elX6DiuXbgNgIbJFIZcDdqlQl5rpFpGK6XUf8CIiBUrPcucv866k3wPb5B27F/hLFcdQkGQf94ntDs5kPjewEC1t+4bHAVu4+/VVHl6PeOSzgDtYCxjSdngfM+uNezGnph7vDmSTNM0j/N6s6O7Hu/tH5e7YI//IIz+ekJH5AnKz7gMZxGGcQKiAvDK1yLTfL7n7bYS522eSQw2Ez5V/mtkSnV1XK+5+K7l8GYOBW81soSp1f1Hbo9x6gEolVBuXejymQn2ISD+loFtE+hyLbRkgW/f2M+DuqvRr9h3gp3mHPwGO7CX7uNtYbDsA/wW+BeQKSw1jIFuRXZ75ALCRu79c/RGWxTU0EnbLBnWEbPY1Z8F2ZvYg2aJHOTOBcwnB9o+S+s4V5ZFP8MhPJMzgnUt2yXAdYQbxEPa22B6w2LZLtm5IBSWrGbYGziL37tyBUNN7h1qNqws/At5IHq8N/LEanXrkzwHPA7AU2fVFO5rZyhXo7iNy/19opltEykpBt4j0RcdAW+B4uUfe3NXJ5WBm6xCSH6VlgIPcfXIHl9SExdZgsZ0F3E82W/ZkJnIDE9qKSn0DWJNrgV1609hL8Dgwjo3I/TbAMVXOstyOmdWb2b6EQOEhYPu8U8YDy7n7ye5e9RJdHvlnHvnJwHL8j3tpnzrtW4QxP2ex7WtxxfbOCuDuze7+a0Kwna2RvgRwv5mdmWxl6RXcfQ5hWXx2RcSxZrZflbrvaLb72HJ34u7zgewNMAXdIlJWCrpFpE+x2AYQEoRBKI90RRenl6dPs5GEerv5Syojd3+i0v0XymJbihA0/bLt4Ks8zwUM4H2W5rHkWB2wH19nbNue4j6prWb3UGCdtsPDyZWRqxozG2Rm3yNkqL6ddHXhXEAFgLtPq+LQOuSRT+M23uLPwP8BTe1qdG9E+De8abEdY7FqFldSUppvXeCfqcO/Ah4yC6X+egN3f4P221WuNLNqBKe3AuHm4Jpkt5N8t0JL3Mcl/x1lZkO6OlFEpBgKukWkr9kTyH4Rvcujyi7NTTLl3kjYE5v2CGFpaK9gsW0DvEyYx4YMLdzKP/kbG5Gt+/wEb9PEq8klKwMXVn2g5XcdQF5CtR9VMMNxO2a2sJn9gpCE6TJCaaWslwnZn9MB+GLVGFeBlqWFUBTqL2xHkk079foqhAzo4yy2k5OSc1IB7v4lsCvwc3K11r9ByG7+jZoNbEF/BW5JHg8n1O8e0MX5PeaRzyO7yqiebPmwkWQrMZRXOpnamAq0LyL9lIJuEelrqp1AbSywc96xicAhvSHTt8VWZ7H9CniYbAGtuXzKH3maN9kZyO7PvZsMmzCAfciVADrMYjuk6oMuo7aa3UuQvi2yIiGAqZik7NfZhH2gZ5O7EQThhswOwIZJEqrPyO0VHVytGwIFyGXgn8V4j/xWwg2CHQn/hqwlCYm+Pkpqffea2devEnfPuPt5hESNnyaHlwQeMbNf9obs5knuiu8D2XJ2mwC/q0LXl5B9D21E9ttrJRKqjUs9HlOB9kWkn6r5B7iISKEstjXJzuTCW8CjFe3PbA/gNx28dFgt9uPms9gWAe4BziT7eT6BpziHucxiq+Q0J/wb9nb3GR75e7TfD3mJxZaene2LrgbyZ7srUj7MzFY2s8vI1dgenrzkwJ3AJu6+nbs/mE2ul/x3TrYJoLdkWF82+e+UZM8uHrl75A945NsRAqo7yd0wGE6u1velFlckmVW/5+5PAusTtopAeG+fBdxtZovUbGCJpPb8geRqwP/MzPJvTJa3z8jHETZChHU7oVjkRma2cacXlUZlw0SkIhR0i0hfclzq8cUeVS5juJmtCnRURuscd/9XpfotlMW2MfAS8O3kkPMYt3EF6+CslBybSkiW9jt3z6ZRwyO/CbgmeToUuDnZK99X3QnMZmVgkVy6ODNbv1wdmNmGZnYb8DYhp0B2n3MToZzSau6+r7s/30kT6YR165ZrXKVKZtuXTp5+3NE5HvnzHvm+wOqEf2M2yBpImO1822K71WLboNLj7W+S5eY7AaeRu+mxK/CSmW1Us4El3P0F4OTUoevMbOnOzi+TjhKq/aCjE3tgXOqxgm4RKRsF3SLSJ1hsw4DDkqdzyO7lrURfIfv134H8LNjP0PHMd9VYbGax/QB4kuyMaYbJXMZtPMr+hCAa4FVCObDObhD8kBBAQlhS3Gv2pxcrqdl9O3XA5u3+rvVotjuv7NcLwH7k/m5my36t4O7HuPs73TSXzj1Q86CJsBUhmx27w6A7yyN/2yM/hrDcNlduLPws9gdeVLmx8nP3VnePCNtbsjdtlgf+Y2bHmdX8Z30+cG/yeDHghgpvnXgQeA8IG0hCdoQDzWzRMvahPd0iUhEKukWkrziYXBB8g0c+vRKdJF9kryLM7qVNB77jXvnyZJ2x2IYCNxFmfMLM9Eye5yze4LN2SYVuArZw9w86aysJVA8kzNQC/NTiyi4RrbBrgDCHPKBtRvZAM1uq2Ia6Kfv1JfBrcmW/Pu2ojQ68l3q8VrFjqoBlUo+7DLqzPPJP28qNhZ/Bl6mXVW6sQtz9fsJy82eSQwMI+SxuNLOhnV5Y+XE5oVLAJ8mhbajgTcmkWkFutjssLB8EHFHGbj4hl8hOM90iUjYKukWk10tmz9LLCC+pYHcnAvt2cPwwdx9XwX67lOxnf54QKAdvcyN/YBTNbJ0caQV+TEjyNru7Nj3yVwjZkrOuTcqO9UVPAB8yANikbQa3kSKSLXVT9usDwvaGMe5+Vgllv15LPV6p07OqZ9nU4086PasDHvk0j/wswkzgcYSfTZbKjVWAu39MyGfx59Th7wDPmdkaNRkU4O6TgYOgbVvHb81s2wp2eQ3Z/Ajrkb31eFy5ksy5ewu5m1BjytGmiAgo6BaRvmFLYO3k8VNJsFh2ZrYZcF4HL53j7vdUos9CJBnGnwNWSw7N4G/8hZvZh9wXwy+B7dz9/GwCrwJdQG6J6CjgeotrnyW5WG01uwE2wbC2IODY7ur5JmW/Tqbrsl+ruvul7j63xCG+mXpc6b2vhUgH3QXNdOfzyOd65JcCqxJ+Rq+kXs4vNza8gyakCO7e5O4/IWxzyC7xXx143swOruG4ngCi5GkdcLOZja5IX5FPI5RwDJkFQnaElQjVAsolu8R8pJnK5IlIefS5L1Yi0i9VvExYsi/wNnL7XLMeB06pRJ/dsdgGWWyXEhK6DQaghVc5j7t5lRMJSysBniWUp3qs2D6SZHTfJVeiaDtCVu6+KOzzHw6sRnamf1Hg0I5Oziv79XsWLPu1I0nZr2QGrCfSge0Is5rPAPc46M7yyFuScmMbEH5m6aoCKjdWZu5+B2EVxqvJocGE/dSXmNmgzq+sqDOB+5PHiwO3mlljhfrKX2IO5U2oNi71WEvMRaQsFHSLSK+WfEnfJ3k6Cbij7H2EpYnX0z4QAfgCOLAMAVfxY4ptReA/hCzRwWRu4nfMYla7IPJy4BvuXtQS4TSPfBJhz3x2hvx0i23zUturFY/8Q7JllrZslwTvx+mkU0WU/XqgyFUDXcn//6fWS8yL3tPdnVS5sW2BTYG/kfudWhiVGysbd3+XUCTvqtThYwlJ1qoeKCbVEQ4h97u0JSEQL39fkf+XkEgyhPdjANjVzMaUqQslUxORslPQLSK93VGEvbkAV3rk8yvQxy8JGYLTMoSAu+r1uC223QnlwLKlmObxDL/jAr6Js0VyrAk4xt2/797zn4lH/m/gjORpPaGM2IietlsDlwNhAfcoJiXHVgd2KKDs1+rdlP3qiSlA+uZNrWujp28wTej0rBJ55M955PsQfvZ/ReXGys7d57r7UYSVKvOSwxsQyortXoPxTCJks0/X796rQt3lz3Yb4T1dDuNSjzXTLSJloaBbRHoti62B3EyvA5eWvQ+zbwKnd/DSKe7+73L31+VYYmuw2H4P3E2YGQTnXS7nD/yLk4FskrNPgK3c/coyD+E0sjNIoTTR5X2wBNTdwEQAvsmI1PEb6b7s19tUSDJjPjF16GuV6qtA2aB7orvP6/LMHkjKjR1NrtzYrOQllRsrE3e/mjDrnc2QPwK428x+b2b522UqPZZngJNSh64xq8iqhr8RViKF2zphrcrRZdq2oZluESk7Bd0i0pt9m1xw8H8e+fhyNp6Uk7qZBT8L/w84p5x9dTuW2EYT9hGf3Hawib/xO57lU04hN9v/GGGf8XPlHoNH3kJYZj41ObQfcHS5+6kkj7wJuIYMkKEBayv/k67lW2rZr55KL+OuWdmwJBDL3sApy9Ly7uSVGzsFlRsrK3f/LyFz/J2pwycDD5dSNq+HLgRuTR4PB+7oLplhsZL3eVjVUke2zsAoOq48Uax00K2ZbhEpCwXdItKbVSyBWhJ43AwskffSOEJ5sMwCF1WIxbYtIUv2VsmhFsYzljNZnhYOSZ36J2B7d/9ygUbKxCP/iLCkP+t8i2tXkqhYZjaIS5jBhYTd/046gJtJz8p+9dS7qce1/JkuCW0/l6oE3Vke+VSP/ExUbqzs3H064UbZj8ltZdgaeDlZ0VOtcThwDGEbB4Qc4xdUoKvLyNbU3pDsb3Q5Eqp9RthyAgq6RaRMFHSLSK9ksa1CrgzMB8ADZe4iJtS9TWsC9nX3qR2cX3YWW53FdgrwICElEMAn3M1PuJoTyNWJngsc5O4/rUZSN4/87+RqoS8E3GpxeWeqys3MRpjZL4AP+YLTmdLu5ewNlEbgjh6U/eqpdIC5Yo3GAD2o0V0uRZQb+0UfzS1QEx6cTwi2s//fLgE8ZGa/Llc96wLGMZOQAHNOcugoMzuyrH1EPgH4OwBDCcvMYQszW69H7YYbrtlVVWPSSRhFREqloFtEeqvjUo8vSeowl4WZ7UJYXpzvRHd/sVz9dDmG2BYlLGM/g+xnsXM/53IFL3M+sFhy6gfAZu5+czXGlXIS8FryeC3gj1XuvyBmtoqZXUgIMM4mXfZrBUI+5TV4JzkyiJDhuVbSs8qLmNmwTs+srLKVC+upAsqNnQ18YrFdoIznhXP3p4H1yd2srAN+B9yblEesxhjeIF19AS42s3XL3E0uodombY+O6+jEIo1L/juU9ltTRERKoqBbRHodi20wkJ0VmQ9cXba2zZYjlAfLdwPZPYIVZrFtSshOns2Y7sziDGKmM5uY3GfzP4GN3P3VjtqpJI98LmEGMjsrfKzFtk8Xl1SNBd80s3sIS1iPB4YkL4eyX8PYksOZzMrAt1iR3Gz38TWskZ0/q1yrILLs5cJ6qptyY0OAE4B3LLa7LbZtlHSte0k28V2AiNzPchdCdvNNOr2wvGO4gVwCzEGE/d0Ll7GLx4A3gJAtIGwWOqQMfSiZmoiUlYJuEemNDoS2zNO3eOSTy9GomQ0AbgMWyXvpDeDYMtZk7rj/2MxiOwF4gvAVEWAiL3Ek57EXIZtz1unAbtVa6t4Rj/x/wI9Sh6602Jav1XjMbKCZHU64YfEIsBuhVBCEZawXA6u5+74+w/8DXAfASAaweNus/ZLAAVUdeE5+gFurDOY1X17elVS5sdUI2xyyS5QN2J0wG/6SxXaY9n13zd1b3f00wiqCbAm95YAnzeyEKi2d/gmQXUG0MnBVufr1yJ0FZ7sHA4f3sOlxqcfa1y0iPaagW0R6lWQG6/jUoXImUDuXMIuWNouwj3t2GftZgMU2DLiFkFAom4n8P1zGz7iH84E1k2MzgD3c/bfu3tpBU9V2JSG5FYQbITcmpdyqxsxGmdmphC/C1wDrpV6eQKizvqy7H+/u76Reu6Lt0Y6kZ75+UqN9mr0x6O4VM90d8cjf8ch/QBjvr2hfT3w94FrCvu9TLbZRNRhin+HuDxKWmz+VHGokfBbdXOltDklJuv3IVUXYmxCIl8sNhCSJsDZhPh1+0MP3uDKYi0hZKegWkd5mY8L+ToAXPCpPaSwz2xc4sYOXjnb3t8rRR6d9x7YW8DzpmewMf+A0HuEzroW2gPBNYBN3v6eS4ylGMpP0PXIzP18nLFetODNb08yuAD4i1BBfMvXy88BBhBrbv3f3KfnXe+RvElYVwIqMYSDZ/5/XIySaqqoku3T65s4q1R5DIht0O+0D2V7JI5/ikZ9NCH4OIvx/n7Uk4XfjI4vtCottzY7aEHD3T4BtgD+kDh8APG9mFS1h5+4fAoelDp1jZluWpe3IZxJuwMAAsrfkVgV6krFdy8tFpKwUdItIb1P2MmFmtgpwVQcvXeDut3ZwvGwstsOA5whfAgFm8AWHcBqrkeHU1Kl3Apu6+9sLNFJjHvk04DvQVvP6FIsrU4Io2a+9k5ndD7xOqBM+KHk5Q/g5bUn4Wd3s7s3dNBlmuw3Yql1t6OM7PLvyPko9rtVMd3ZP9xfu3tTlmb2IR97skd9MWK2yJeF3IbtXfxDhd+V1i+1+i20n7ftekLs3u/vPCJnFZySHVwWeM7NDK9z3/wFnJU/rgVvNbPEuLilG7m/FxmQ3nfSkfNi41GPNdItIj1mFtzCKiBQsyeg9ARhIWIq4jEc+p+urumnTbCHgGWCdvJeeBbauVNBhsQ0C/kKoV5v1CvfwK17iAnJJtDKEpbPnVnpPeU9ZbL8k96X5U2Bdj3xSF5cU3rbZYOBQwh7y1fNenkFY5n5hMmNWeLuh1NmnwAhamMcZzARGEeoYL+/un/Z48MWMx+xfhP21ANPcfWSV+28kJCc04AV337ia/ZebxbYC8ENCwJ2/TPpN4M/A9UliQEkxs5UJW0fWSx2+glDFYV6F+mwgZFTP3rR7BNihHFtpLLaHgO2AkCrzfVoJ7/GiV3MkS9NnE0omvuXu+Z9JIiJF0Uy3iPQmRxICboCrexpwJy5gwYB7MrB/BQPulYCnaR9wX8HZ/IGXuJNcwD0F2Mndz+ntAXfiHOCh5PFo4Oqeziaa2Wgz+x1hBvhS2gfcHwI/JuzXPqnYgBvasrCHhGoNDGJlXkpeaqD9/z/Vkt5DPaJa5ZtSRpNLPtdr93MXyiP/0CP/KWH2/ie0Xxa8OnAZ8LHFdobFtlQtxthbuft7wBaEG1pZxwBPmdlKFeqzhbBF4LPk0LbA2DI1n59QrZ6wNaZoyefxuOSpanWLSI8p6BaRXsFiq6N9fdVLOzu34DZDpuuj8g47cIi7f9TBJT1mse1JyNS7XnJoLk0cyVhmMI/rCZl1AV4GNkwSHPUJSa30w4CJyaFd6XiffLfMbAMzu57wxfbXtK+F+wQh2dIq7n6+u8/ooIli5BKq7cLy5JYkfz+Z+a2m/Gzh1V5i3uvKhZWDRz7DI/8zYZ/83mT38geLAqcA4y226y22DTpool9y97nufgxwBLnygOsDL5rZnhXq83NChYrs7PZvzGyXMjR9L9nf6a+RrX/xvR68x7M3cAbRPp+EiEjRFHSLSG+xI7Bi8vgBj/zdnjSWJAa6pIOXTnf3f/Wk7Q77i63RYjsP+Du5xGjv8Do7cSaHAielTr8O+Lq7jyv3OCrNI/+M/IRIsa1fyLVmVm9me5rZY4QbE4eQy+TeAtxIqEu+tbv/vVzZ2z3y1wkrD2ARVmNIW0C2FLBHOfooQq0zmPeJzOWl8shbPfK/e+RbAxsRfqdakpcbCb9zL1psj1lse1ps9bUaa2/i7tcS9spns/8vDPzdzM6txI0pd3+csK0m6waznpUj9MhbCCsbwlqOjYAQLO9ZYpPjUo/HlDouERFQ0C0ivUfZEqglJXDuIOzHS3uIkOm4rCy2pQm1g9OB9a1cxDHcwQ2EJZQQvvyfABzh3nf3mHrk/yKXAXkAcKvFNrSz881smJmdCLxNuCmRzhw+BTgTGOPuh7j7ix21UQaXtz36FumffU+SLZUiP9CtdgbzXl2ju5w88hc98kMIAdNZhN+1rK0Jv4tvW2wnJiX9+jV3f42Qhuy21OGfAY+Y2dIV6PI84K7k8UjgdrMe112/AgjbhjYgbCIp/T2usmEiUjYKukWk5iy2McC3k6cfA/8oua2w9+5yctnCsyYAB5W79rXFtj1hqfjXk0PNZDiBsTzCRB4gF+R8Dmzj7hf1kf3b3fk18ELyeBXgwvwTzGx5MzuPENydD6T3ib4FHEvYr31KKcmOinQ72WzN67A1xnvJ8W+a2RoV7jtNM91V5pFP8Mh/Tfi3H0e4+ZO1EuF382OL7TyLezbb2tclWzkOJCSny1YG2BJ42cy2L3NfTsjj8UFyaGPgjz1qM/IvCe/1sJEnFJDbpsT3uMqGiUjZKOgWkd7g++SSO12WLBMs1XGEL41pLYTEaRM7OL8kFptZbCcD9xOyYQN8xGd8i9PYnLDMMTtr8xRh//Z/ytV/rXnkTYQyYrOSQ4dbbAcnJb+2MLPbCV+mTwKGpy59ENgFWNPdL3MvS7K8QsY7G7gBgDoGs2ZbQjVon0ug0moddH8l93QXwiOf45FfCqxB+B1M51NYmPC7+r7FdpvFtnktxtgbeHAhsBW5EnejgPvN7OflTCrm7tOAfQkZ9QF+YGYH9bDZ/IRqUNp7fFzqsWa6RaRHVDJMRGrKYhtImAldjDCzsqxH/kVJbZltBPyHsOQ57Sfu/ueejLNdP7ENIdT93j91+D6u5wze56+0z8B9IXBSX6qHXAyL7WCywWwr87iMt/mSdfNOm5+c82d3f73KQ2xjsa0LvALAHF7lHFYhbEGYCSzt7jOrMg6zKYTltGEkMLRaqx/M7HnCbtcMMKiAOudfaRbbWoQM+YeQu0mW9Syh5NidHvXPn1OSXf96YOfU4duA77r77DL2cxS5LOqzgU3c/X8ltRUqKrxISAgXFpxPKP49bmaLECpdADzs7mWd6ReR/kUz3SJSa/sSAm6AO3oQcI8kLCvMD7jvJCwfLYtUObB0wD2WmFt4n4fIBdwzgQPc/Ydf1YAbgLHcxyeEfdj1DGIP1iWXmuoL4LfAcu5+dC0DbgCP/L/A8wAMZh2Gc3/y0jDg4CoOJT3DPJhQxqta2rY79PeAG0KSPY/8aGA5ICL8zmZtCtxMmP0+2WKrak313sDdJxOqFMSpw/sDT5vZih1fVZKrgGuSx0OAO8w6zxPRFY/cSW93CZXoS3mPTyV8joOWl4tIDynoFpFa63ECtWS54zUs+MXoXcKMTFlmES22HQlB29rJoZnMZF/GMhrnOnLlwF4jZOG+raN2vgrMbBUzuxD4mOvYkEnJC0sDOzORUIJoeXc/3d2/rNU4O5BLqLY76f39x1exFm9NlpgnSaqW6GQM/ZpH/qVHfhqwPGGf8aupl5cFfk/Y932hxVbt5Hc15e4Zdx9LyAKeDULXBl4wsx3L1IcDx5P7ua8OXNGD9+QthKAZ1iL7yfyDYtpLxpTd172cmTLdi0jpFHSLSM1YbOsBWyRPXyMsDS/Fz4Dd847NBfYtQ43n7P7tXwL/JLcs+C0eZR/+wG+A76VOvwrYzN3fyW+nr0v2a3/TzO4hJKM6HhhCE3AHTmtS/3ojRjGWL919fhfN1cotZPehr8yOGM8mx9ciJIyqhlrV6k7PqCvo7oBHPt8jvwZYD9iOUPs5e9NuCOF3/m2L7R6L7ZvJUuZ+wd3vJuySziaiGwncZ2a/KMcNqyS/w77kAvsDKTHfgkc+h/BZHDKYh8rsa5NLeFmoccl/G6nuihQR+YpR0C0itdRuljtZFlgUM9uKUA4o33Hu/moHx4trP5TCui3pI/vF8m7+wBk8xh2EL+cQgvwj3f2oaiUHqxYzG2hmhxOytD8C7EbuZzEHuIjPWZV6fpq67FqLbakqD7VbHvks4Kbk6VA24rXUy8dXaRi1KhvW7zKXl8ojd4/8EY98d0IlhIsIv+sQfvd3I7wXXrLYDk9yU3zluftbhMD7nuRQHXA2cGupy8Hz2n+XsNIg689mtkln53fjErI3TDYi+4lVbPkwlQ0TkbJQ0C0iNWGxjSC3x24mcGPRbZgtTpi5zF/2d6W7X9ujAQIW28qE/dv7th1s4jTG8iEzuYFcVu53gE3d/Zqe9tmbmNkSZnYqMJ6wfD+dIO1j4GRgGXc/Ifmy/Bfg/5LXRwHXWWy98e9Mbon5DqwHZLPa72NmS1ah/1plMO83NbrLySN/1yM/gZD5/Re0/9mtR3hvjLPYTrXYlliwha+WZPXQXoQ98Fn7EfZ5r9TxVUW1fyfwp+RpI6F+96JFtxP5+8C/ABhB9l22r1lR/x8p6BaRsuiNX4ZEpH84jNwe6Os8Ki5zdLK/7kYWXPL3CnBiTwdnse1M2L+9VnJoBm9zJGfyLUK246xbCfu3X+MrIFlC/nUzu4kQHJ5Gbh8whIzOBwIrufu57j41+0KyUuFI4NPk0PaEwLxX8chfJMzaQyMbsUjbrF0DcEwVhlCroLvflgsrB498qkd+DrAioVzec6mXlyS8Vz622G602L7+VV56nuzzPo2wrSe7hWctwj7vncrQxS8IpRYhJLm73qykG3j5CdUagaOLuH5c6vGYEvoXEQEUdItIDSRfRtPL/C4poZlTCUFd2nTCPu65PRmbxfZr4B+E+RGAN7mOk7iZ84Bs/d4mwnLk71Sr1FQlmdlQM/se4abFk4SgojF5OUPIDL+Fu2/m7rd2lvnaI59EKL+U3SpwhsW2WUUHX5rcbPd+NEKyHx2+b2YNFe47P+BdsQp9gpaXl4VH3uyR3+KRb0rISXE7ud+fRuAgwnvoZYvte0mJwa8kd7+XsNz8reTQCMI+71/1ZJ938vmyP7lVKDsDvy6hqX8BHwCwMhDmy4t5j2umW0TKQkG3iNTCNwn7JAH+7ZG/UczFZrYDoRRVvsPd/f1SB2WxDQPuAH5HdgdgK3dxJv/HB1xB9itbmP34urtfXK36ypViZquZ2fnABOAyYJ3Uy5MI+zVXdPf93f3pQtr0yB8l/AwhLP2/OdlO0JvcRHaP7lLsSR3/TI4vTdivW0n5S7sbCVmzK03Ly8vMI3/aI9+fMPv9e2jL4w9hO8ZlwKcW2/kW22q1GGOlufvbhPJqdyWHDDiTsCy85H3e7j6BcAMj+xl7mpkVVSvbI8+QvqkbZruXBb5dYBPjUo/HFNO3iEiagm4RqYWSy4SZ2TKEZeX5syjnJtl1S5KUAXoG2Ds55HzB2ZzOwjTx89Sp9wIbuPsLpfZVa2bWYGZ7m9nDwJuE5fjDU6c8AxwKLOvuv3L38SV0E5PLRj8GuKI3Lbf1yGcQ8gEADGertozMUOGEau4+j9wMXlY1lphng+5W4LMq9NdveOTjPfJfEn7GhxHeQ1nDCe+xNy22hyy2vS2uysqGqkn2ee9DWIGUDZL3AZ4xK73Emrs/RO4GqwE3mdnSRTZzFTAPCDvww/qdghKqJf+uKclTzXSLSMkUdItIVVlsyxDqvQJ8Tm52pPtrzRoJe6gXy3vpCeCUHoxpF8L+7TWSQ9N5kF9zCUcQZuUhBConA3uk9zH3JWa2VJIYbRxwJ7Bt6uW5wF+BDd19c3e/IQkOS+KRtxBmqbI/q32BH5baXoXklph/g82B95Jn25lVfFYyf6a5GhnMs3u6P3X31i7PlJJ45PM88us98s2BDQnvqfR2l+0I771s4rVqJO6rimSf9xmElSLZfd5rAs+b2c49aPpMaFuJMoqQKb2xi/PbjyvyKWQrFgwiu5ZnBzMr9EbXuOS/yxTTr4hImoJuEam2Y8hlG7/co473BnfiTHJ1vbO+BA7sbI9xVyy2OovtFELG7YUByPA/zudK/sPvCMmRICQG+2aSOKxPLSdPEqNtbWa3AB8Rkj2lZ4reBX4CLO3uR7v7S+Xq2yP/CDgidegPFtvmnZxeC88BoaxcHZuzOH9PvVZSfeAiVDWZmpkNIgQsHfUtFeCRv+SRH014v/2U3E0dkmPZxGu3WGxb9aaVID3h7v8gLOT+X3JoYeAfZnZKKfu83T1DWHnzUXLo64RtL8W4qO1RrgDZsQVem93XXUf7LRoiIgVT0C0iVWOxNQLfS562AlcUfK3ZHsDP8g5nCAH3px1c0t1Ysvu3zyC7VH0G/8cZfMxUTiL3+fgQsL67P1FsH7VkZsPM7DhCUPkYcAAhOzeEn9vdwA7Aau7+50rN3nvk9wDnJE8bgNsstvyVCjWRZFvP/Q4ezHBys5JHmFU0AVa1M5inM5drP3cVJVnP/0TIY7Ej4b2XTbzWQHhvPg68arEdl3w29Wnu/g6wGbTdyDLCZ+0dZsX/+9x9MqEsWfbm6k/NbO8uLml/feQvkV3yvwQhHzocaWaDO7+qjZKpiUiPKegWkWrak9zs8d0eeUFf/s1sRaCjutu/cfdHix2ExfY1QumrvZJDzn+5hD+yDhl2bDsW9iXv5O5fFttHrZjZGmZ2ISEx2sXkSp5B2Ed8JrCCu+/p7g8ms0iVdgohqIAQ/N3Qi+p330B2v+fCHEAdtyXHh5OrI18J+UF3pZeXK3N5jXnkGY/8AY98T0LitTNpv7d/LcJ7doLFdqHFtkYHzfQZSVWHfQnv/+wKob2BZ4tY2p1u7znCqpysq4vcL54/2z2CUP6wO+NSj8cU0Z+ISJve8qVHRPqHohOoJctibye7/DvnH4RswUWx2HYl7N9eHQBnGtdzGX/naLLzHyED8U7uPrYv7H01s0Yz28/MHgXeICQCS88m/YcQQC7r7qe4+0cdtVMpyf7uA4EvkkM70oM9+OXkkU8j5AkAGMEu7ZYAH9+TskfdyA98l09+1ytFNbp7kSTx2imEmyEHk6tJDeG9ezzwhsX2qMW2b7JKqM9J9nmfCexKKOkI4bP3OTMrNIN42sWkEyCGmfNCZqsh/B2Z2DaCkFf9mAKu00y3iPSYgm4RqYpk1mab5OnbwCMFXvonYIO8Y+OBw4qZpU32b/+WkH08ZOqey5v8nqd5n2PJ1aT+D7Ceuz9QaNu1YmajzWws4edxG7mfL4RyWJcTlsZv6e43ufv86o8y8Mg/I9T+zv5/FltcXPmfCsotMd+IHQirICCkXMrPIVAu+YGvAStVqC/QTHev5JHP98hv8si/DqxPeM/OSZ2yDSFYHGexRRbb6BoMs8fc/T5gI8JNQQg3Ue81s1PNCl/1kuTUOIZQdQHCe/TCgq6NfD7Z93o92fJhm5nZOp1fBeT2koP2dItIiRR0i0i1fD/1+JJkP22XzOwgFkx20wTs6+5TOrik43ZiGw78jbBcPPiQBzmHAcwjnVX3PELCtAmFtl1tSWK0bczsdsKXwQhYKnXK28CPCInRvu/ur9RgmB1K6nefmjwN5X/iosv/VMJT5JI+bcUy7RKqFVRaqAQdBb6VXGKuGt29nEf+ikf+fUKStR8D76ReHg2MBcZbbLdZbNv0tcRr7v4esDkhezuEz4DTgDvNbHinFy7YzizCsvXszYkjzeyoAi+/hJBPJNwCCFkuupvtTr9XFXSLSEkUdItIxVlsCxFq10LYP3tdt9eYrU66pFPOj4qpkW2xrUaYudwDAMe5jzu5lq3wtpnFacCe7v7zUrKgV4OZDTez44HXgUcJXzqzWeBbCTcVtgdWd/e/uPu0mgy0e2cD9yWPQ/mfGi+dTW4A5X7XDmE0MDl5tp+ZLVGBbj8lt881q5LJ1JZLPdZMdy/mkU/zyM8HViO8p/9O+8Rr+xE+A1632I5Pbir2Cck+7/2AX5P7/d+TsM971SLa+R/tg+WLzGy9bq8LeURuB2AI2YwXh3a1RN3dpwMzk6cKukWkJAq6RaQa9iUkrQG41aOuM2UnWaPvIHwtSrsRuKzQTi223QlloULN5SamcQEP8xz7ECq2ArwIbODudxfabjWZ2VpmdgkhSLuQXC1xCHukTwfGuPs+7v5wby9p5pFnCDdg0uV/zqrdiNpcD4Tl94M4mHquSY43AoXOohXM3ZvI7XHPqmTQvWLy33nA5xXsR8rEI3eP/GGPfG9CAq8zaP87swbhM2GCxXaxxbZWB830Oh6cBexCuOEJ4TP6OTPbrYh2biKXG2QgYX/3iAIuPb/t0WZAWOq+XzfXZG9ULVPBPA8i8hWmoFtEquF7qccdzV7nu4j2wSWE5b/HFhJUJvu3I0JpnpBQ7HPe4fdMZArpfcQXA1u6+4cdNFMzZjbAzA4ws8eB1whL7NM3IJ4gJCZbzt1/615YFvjewqMFyv+cZLHt1cUlFeeRTyHc6AFYlP35iNxM3LFm1tDxlT1SlbJhyZ7ZMcnTD3v7jRlZkEf+sUd+KmHFwncInwFZQwl15V+z2B6z2A6w2AbUYpzFcPd/ERZ5v54cGg7cY2ZREfu8fwpkVz6tRMho3mVQ7JE/QzZvw5Jk3xnf6/SCIPteHQT0ipKHItK3KOgWkYpKEqhtmTx9A3i6y/PNDgMOzzs8m7CPe1YB/S1MWI45tu3gUzzDpSxNa9ue2dnAQe5+vLvPK+TfUQ1mtoyZnUZIjHYLsFXq5dnApcA67r61u9+azJb2SR75c4QvzFnXWGyVTCRWiNwNoVXZi9wy+GWBUjItd2d83vNKZUZektzKjg8q1IdUgUfe5JHf4pFvDaxL+EyYnTpla8Jnx3iL7TSLbZmO2ukt3P19wj7v21OHxwJ/L2Sfd5Iccj8gu3pqT+CkArr+c9ujMNu9hVmXKwXSNza1xFxEiqagW0QqLb3v7vKuEqgle/o6KiV2lLu/2cHx9tfn9m/vDkALGa7maR5gM3IzxW8AG7n7zQWOv6KSxGjbmdmdhHqwp5KrZQ4hS+8PgdHufpy7v1aDYVbKReTKdYXyP2H/f608QUhEB7ANK3JX6rVKJFTLD4CXNrOBFegnHcwr6P6K8Mhf9ciPIyRZ+yG5jN4QPkNOJWQ9v9Ni27a3Jl5LbqYeAPyC3N713QnLzVcr4PpxwCGpQ2eb2dbdXHYnEBJmrgqMBLqe7VYyNRHpEQXdIlIxFtsgcrPW84AbOj031Ci+jQX3cf/B3W/t4JL8vvYk7N8OyXgmM53zeJ/xbJ467TpgU3d/q9B/Q6WY2QgzO5HwRfkhYG/aJ0a7A9gWWNPdL3T3GbUZaeUkN2COIRforkd6v2VtxpMrH3YIXyMXpO5gZuVe/p0fABvtE56Vy4qpx71qK4X0nEc+wyO/EFiT8JlxB9kM3eEzZW/gYeB/FtuJyWqgXiXZ530OsDO5WetVCYH3HgVcfx/wu+RpPXCrWefl1TzyZsJNv/Cu2wToIKGanWzr23YWkZ0PDxR0i0jRFHSLSCXtQ3YOAW5P9s125g+Emqtp/wZ+2VUHyf7t0whLysP+7VcZx4XUMa9tOfk84GjgCHef3XFL1WFm65rZZYRZlvPJ3iQIPiOUNVve3fdz90e/6vtvPfKZhER7c5NDx1hsh3VxSaVdSyhLB3UcQX27HAT55et6qqMAeEyZ+wDNdPcLSeK1Rz3y/YDlCZ8ln6VOWY3wmfOpxXaZxbZuLcbZFXd/gFBBO7uiZxhwl5nFBezzjgg3FyDM9N9u1uXe9ssJfxtgA2AgI4B9LbZ6O9J+YCfaxwzhJbZmLBuyU+q6Xr1kX0R6JwXdIlJJueV6LakZxDxmtg8LLt/9BDjA3Vs6vS62EYRkaaH2cytwJ2/zN8bgSQAO7wGbuftfaxXAmtkwMzvGzJ4FXiH8XNIzKv8G9icE22N7c53wSvDIX6d9HfdLLba1azSWSdBWp3sUR/Ml2S/moR5wp6WFStBRAFyJfd2a6e5nPPIJHvlYQvC9P/BY6uXBhM+gVyy2Zy22Yyy2YR00UxOpfd63pQ7/FrjbrPNZendvJSSZyy4F3wL4Y6fnh4SO1wMh9/mGwJacywxmMYaLWDQVXC/e7lLNdItI0ewrPokiIjWS7K8OewwnAhcxkVCj+U/p4NfMVgBeJpRtyWoCtnL357pofw3gLkhms6eT4So+Ynq7mcI7CPvBq740O8mguxlhhv0AFlw2P5Ow3P0Sd3+jysPrlSy2y8nlAHgH2CiZCa/2OLYlN2P2EGP5BDgieX60u/+1LP2EWbi5tL8Bfra7/6oc7af6eZxcUr7hSa1k6WcstjUJWc4PJ2Q8T5tNSMB2JfBsV7k3qiX5DP0Z4e9G9j3yDrBnVzk+zGwj4ElCKA1hhdO1HZ4bfiYhe3qGzqeiniD3iQBPuHt3e8ZFRNrRTLeIVEougdqLAIwiLCF/LNm/jZk1AjfTPuAGOKGbgHsvQsK0EHC/y0zOZ2Yq4G4GfgTsX+2A28wWM7MfE5ZHPgV8l/YB9yuEWf2l3f0EBdztnEi4AQOhfNaVNUr+9G/CCgmA7VmTdA3348tVpzfJPp9f7m1MOdrOk509n6SAu//yyN/wyE8gJF77AeGzKGsIoR7904TSYz+22Bat/ihzkn3e5wI7AdmtSV8j7PPes4vrXqD9yqlLzWyD9Dk22IbZpnYW7/F4W2HArr4Rhw0n2RKHmukWkaJppltEyi5JoPYJsCgthFB7brtTJhNm3o4Efp53+ZXufgwdsNjqCeVkfgOEmYkH+IJnWJyQDgfgI0Kw/WwZ/ikFSfYabkuY1d4LyN9HOAO4kfBve6la4+qLkrJhL5K7EfPDJElUtcfxC8IMG8BZjGV7wl5TgM3d/Zmy9GP2KLBN6tCz7r5ZJ6eX0v5AwrvPgOfcfdNytS19n8W2AeEG6UGECgJpTcDfCLPfj3rkGWokWRF1F+3zfpwBRO4dj8vMLiW3bWU8sCGjaWQFbmQNtmHpIiae/gk8y2RgUULwPaizfkVEOqKZbhGphL0JX07gf+QH3CSvvc6CAffzhNI3C7DYhhP2b4eAexZwOZ/zDEuQC7jvAzaoVsBtZkub2SmEWdEHCcvI0wH3k4RlyaPd/QcKuLvnkb9Pbik3wB8ttloEitcA2XwC36WBy1KvHV/GfvL3WJd7T/fy5N4f2s8t7XjkL6XKjh1B+MzKGgAcSKiu8J7FdorFtnT1Rwnu/iFhj3a61ONvgHu6qOf9I8KKKIDlWZ2HOJgP+BbbFhVwA8wHcrPtjcASRV0vIv2egm4RqYRcArUXOz0n//NnIrCPu8/LP9FiWxl4Bvg2AOPJ8Bdm8HlbPesM8CtgN3ef3JOBd8fMGs1sDzO7lzCrfgbtA6WJwHnA6u6+lbtfW+uM6X2NR34X4WcI4Qvu7dVe6uqRfwFty8qX4EfMI/ele38zG1WmrvKTqS1e5mRt6SRqylwuHfLIZ3vk13rkWwGrE95/E1OnrED4rPvIYrvXYtvdYmuo6hjD5+jBhH3e2VnmbwPPmNnKHZw/n1AZ4UsAtmY9hrBQSZ2H5eWfp45oibmIFEVBt4iUlcW2KvANAKYzk/EFXrgBN7n7x/mHk6RWzwGrkwEeYw5XA01tSyE/B7Z197MrudzPzFY2szMJgfZdwK7kPkMduJ/wBW8Zd/95b6gF3sf9mtys27LA9RZ3WzKo3C5pezSMY4CrkmcDCPtfy6GjQHhMmdoGlQuTInnkb3nkPyeUxtqP8NmW3vm8K+GG1EcW25nJlpDqjC34A7AjuXreqwPPmtm2HZz/CSSrVHqSPSME3R+ljijoFpGiKOgWkXJLJ1BbcGF5Z17hR7ay/SZ9yGL7AfAAMJJZwLXM5lEGk/vsehRY390fowLMbJCZHWRmjwDvEmbTl0yd8jGhFu4K7r6Tu9+ZJMeSHvLImwlLW7OzbTsTfv7V9AiQvXnyDbbjEXLBx7FmVl+GPjpa8l3OJeYqFyYl8cibPPI7PPKdCL+TMblyXABLEd6T71lsj1hs30nyeVR+bO4PAZuQrZABiwAPmFm70pNmtglwMhBu4d1Hbo68GOFTPX3TSkG3iBRFQbeIlI3FNpDsflyniRcofElwBnif022g/d22sYUstkuAi4B6PgAuYj7j27KAO2Gp47fc/fNOWiyZma1tZucDnxISoH0z9XILIbnQzoRge6y7FzqfL0XwyCcQEjxlA93TkpUP1erfCb+DwVbsDvwrebY8sEsZuqn0TLeWl0uPeeTjk7rfKxB+7/9GLucBhM/Im4BPLbbzLba1Kz4m9/cI9bzvSw7VAxeZ2SXJNqBlCDPyA9sueg64AZhXZOgdgu63U0cUdItIURR0i0g57UU2gdpsHmYOxc8ENrEnrzKJDMfSSqiNeh0wt+2L0+eEYPtUd28tz7DBzIaZ2TFm9izwKqF81cjUKe8QZkyWcfd93P1f5exfOuaRPwREydM64GaLbXQVh3AdIW0fwKEszDWp136w4OlF+xKYk3esnDPd2bZaaT9LKVI0j7zVI/+nR74PYfn5yYTPxqyRhM/OVy22Zy22Yyy2YRUbj/t0YHfg3NThYwnJ3/5B+5VJwQfAFdQxo+193b0QdKcXqCvoFpGiKOgWkXLKJVB7jhdKbmUqg/kHcA3OE+1eeQBYz90fLrntFAs2N7O/Ap8BlxOWLGbNA64HtgZWc/dz3f2LcvQtRfkdYV8pwOLArRZbYzU69shnEH4HAIbwQ5YCxiXPdzLr2X5WD3U7K5nBPDvT/ZG7t3R5pkgRPPIvPPJzgdUIeTyuJ3xmZm1C+Ez9zGK70mLbzOLy1LhvNw73Vnc/GTicbHgcPrPX6fSiycDFDGUS7xbUSRPzyG01gXDDQUSkYAq6RaQsLLavkVuG/S6PlzDLnfYS8HFbqaNW4JfAzuUIes1sMTP7MfAa8BTwXWhbug7wCqEs1FLufpi7P5EER1IDSX3gQwi13wG2JATi1ZJbYt7AccClqdeOLUP7+cu+x5ShTcxsJLl659rPLRXhkbtH/rhHfhhhn/fxhM/QrCGExINPA69ZbD+uRDUCd7+OUPO+sGoR84CLWYkv+Hu35zbxZVJZI5tjQjPdIlIUBd0iUi5Hpx5fDqzZo9ZyIe5HwFbu/vueZCc3szoz297MbgEmAH/KG+MMQrbqDd19fXe/2N2nldqflJdHPomQSTk7W/tzi22PKvX9BvDv5OmqHMm75GbUDjezAR1eWLj8oLtcM93azy1V5ZFP88gv9sjXBzYk3KCakTplTcJn76cW280W23ZlrkqwAu1voHYtQx2X8A0m8kuc5g7PcaC5rVxYdovGaLPqlkwTkb5NQbeI9FiSQO3I5GkzcC2wVtEN5c+Nr0aGIzjK3Z8ueWxmS5vZKcB7wIPAAYSST1lPEpK/jXb3H7j7S6X2JZXlkT9DqNGbda3FtmJn55dZbrZ7eQ6DttmxUcBuPWw7fxZ6pJkt3OGZxVG5MKkZj/wlj/w4YDThM/bJ1MsDCNUJHiJkPz/FYlu6J/2Z2abkyvoVYxEu4gBmsQvO5AVebQa8bYY7G3TXEWb1RUQKoqBbRMphD2Cx5PHfGMts2s+ydW0RoIGwiBxC8L0LcAB1jOF6i62opXxJ5to9zOxewkz5GbQPQCYC5wGru/tW7n6tuxe2JFFq7S/AHcnjhYHbq1Sm6G7CCgmA3Viee1KvHd3B+cWoVAZzlQuTmvPIZ3vk13rkWwFrAH8AJqVOWYHwGf2RxXaPxba7xcXNIpvZsuRnKi9MdsXK+vyBQ2llYzIdVvReKPlvOhmhlpiLSMEUdItIOXwv9fhyQmKd7hPmrASsAkwht2h4EUIIs0lbC0sCd1ts3S4ZNLOVzexMQqB9F7Aruc85JyTj2o+Qgfzn7v5Whw1Jr5WU8ToK2hIgbQD8uQr9NgOXJU/rOJy1yCVU29HMlu9B85Wq1a3l5dKreORveuQ/A5YmfBbfT24zUR1h1cjdhAD8TIu7T1RoZkOAe4AlShjSAHLJ3w7jDHamjs1xHsg7L3uTQEG3iJTElBtIRDpjZkb4crQRsD6hHFgD4UvKu8CLHMNMlub15JL3gFUZy08IM8kdNAqsDawOPEIuLQ2EXLPfprO5ipM88j92MMZBwN6EUP2bC1wVviRdBVytetpfHRbbOsCzQHaW+1CP/IYK97kk4YZOIzCJM7iIlrZyZrG7jy2p3RA05Jcv+qm7/6nkwYZ27wd2SJ4u7u4TuzpfpBYstjGE7UnfpeOs4I8CVwB/98jn5b9oZj8lzJ6X6iXCzTsIt3+/wViewbmDDLvxKh9zN+sTZsV/BpyWnPsM8CIhF/rLwAvABCXdFJGOKOgWkQWY2SLAEVB3AmRWCMcGttTXD3Gow72Z1tYZDeCG4ayGsQmwPL/w2M8xs5sJ+/VyGghpdTYjzLn9k9zsdiMh2F6vy2F9xyO/JRmfEW4EHA4cRPt62iQt3wNcCTygetpfTRbbEcDVydM5wCZJ0rNK9pn73f6QH3EtfyLM0H0MrFDq75qZfU77mbq/uPuPejRWs3eBlQkB/XAFA9KbWWz1hJtERxNqb+cvMZ8K3ARcA7yYrHrBzA4Ebu5h91cRgn4I5SM3dPfPkr812xAysu8J1INRXz8cs8ZWyGRaW2eb+/xkrHUfQuZC4Bp3n9LDMYnIV4iCbhFpk2Rh/g3YL4DGQYO+xkILrWKNjUtQVzcUS5VYdW+huXkyTU0TmDPvVVqbp0Fd3TtkMocB04HXCbuzW1iX/7IjG1IH3AvtdswtTlhkOGqB4cwklPN6ErjfI3/ezEYTSkcdTtgbmO8dQqB9nepp9w8W21/JfVl+G9jYI59Zwf6+Ti4h1LOMZRLhlhGEknb/Kqlds6cJt6Sy7nX33Usep1k9MJdwS+s1d++8ZrFIL2OxLQEcRgjAv9bBKf8jBN83eOSfmdnGwI6EcoJbAMOK7PLypJ9tkuf/AX4BdVdAZvX6+hEtgwev0zBgwNI0Ni5KOnG5u5PJzKK5+Qvmzn3X5817B6AZ/PfAGe7ehIj0ewq6RQQAM1sf6m4AX33o0I1t8OD1qK8fXNC17k5T0yfMmPFEa0vLl3XAucDvgZ3YjSfZkA+ZQB13EOYqsjYifE1qBOBz4Inkf08Cr3nkLcny8T0IgfaOLJiLYi5wJ2H5oepp9zMW20KEZZ7ZoPIW4KDsLFgF+jPCUtJ1k95O4q22pa13uvu+JbVrdiNh1UbW6+6+dsnjNFsOyG6nuNvd9yy1LZFaSd5vWwHHAPuQS2iWlSHsC78WuNsjn5eU8lo7uW7L5L9LdtNVhnAj92HClioAGhoWbx0+fKv6AQOWaXfTuSutrbOZM+e/zJr1vIO9CZlD3P3lgi4Wka8sBd0igpl9G+xvDQ2L1I0YsVNDY+OC086FcM8we/YLzJz5TAb8CfDd+C178yzX8CDhaw2EPds7M4H1+CchwH4C+DC1XNCATQllZg4ARnTQ3ZOEmY7b3X1GB69LP2GxrULYW5md3TreI7+4gv0dQ5gZgxau5Qx2JHypbyEk6St6lYWZnQ78JnWoR0vCzewb5GqL/8ndf1pKOyK9hcU2nLAu6ghCMJ1vGuGm27XAs3l/T1ZMrskG4at2cP3hhG0iD0OdDRu2OUOGbIiVWEa8uXki06b9q6WlZUoGfG93/0dJDYnIV4KCbpF+zsx2Au4dOHDFupEjd6mz4iq1dKipaQJTptzV6t7yAvhUYKe2FwfzLivxHX/VX+xgLMsAhxK+/HT0pWg8cB1h+fh7PR6ofGVYbPuQKyXWDGzpkT9Xob6GAJ8QbgbN5ywuYT4/Tl4+2d3PLbpNs+8Cf807PMrdJ3V0fgHtHUmuZvGJ7n5BKe2I9EYW28qE5eeHA8t1cMrbhOD7eo/8kwWuNxsFfJ2QLX13QkrPLcD+z6xh80UW2bNuwIAelQ0HwjasqVPvy8yf/0EG2NXd7+9xoyLSJynoFunHzGwFsDcGDlx+4MiRu9WFbaDl0dT0KZMn30mu+DYQMpqfkt7jZmaDCQlqjgC2Z8FSY3MIwdQ1wGPunkGkAxbbH4GfJE8/AjbwyCdXvK/3OYfrOTl56R1gtWJnqM1sG0KW5rRN3P35ksbXfuZ8V82yyVeRxVYHfIPw92NfIH9PlAMPEgLwuzzyOZ22ZXYV1B++6KL71A0YMLpsY3RvZerUezPz54+fD76mu3dUIlBEvuIUdIv0U2ZWB/ZoXd2QLUaNOqyhrm5A2fuYM+d1pk9/CEJite+4+z+Tvo2Q7OYIwvLxjpLe/JvwRelO98olxpKvDoutEXgM2Dw59CCwi0fe0vlVJfe1CiHABhjHWMaRS8K0tbs/UVR77fdgZ+3v7reXND6zG4CDk6druvv/SmlHpK+w2IYR9n0fQQjE880AbiPcwH0qnffBzHYB/rHwwtszePBaZR9bJtPExInXtmQyc/4Dvq1uHov0P6VtVBGRr4KjwbceMWKHigTcAAsttCYDBiznYE3A42a2vJn9hhCsPBnG0C7g/hCIgBXd/Zvufo0CbimUR94M7E+u+vu3gN9VqK93gWym8jGszQupl48uockJhGXxaSuUMrbEiqnH43rQjkif4JHP9Miv8ci3Ifz+jyX8TckaTnhvPgm8Y7H9xmJbzsyGQt1VAwYsn1looTUrMra6ugGMGLFjA/g3KO3zQUT6OM10i/RDYZa77oNBg1ZebuTIXQpLyVqilpbpTJx4NcBbwGodnDKLMPtwLfCkZgCkpyy2bwAPkavze6BHfmsF+tmVUAQPmniQM9mIUDN+LjDa3acV1V6urnbWpe5+XEljM/uMkNztc3dfqpQ2RPq6ZPn5loTZ7/2AoXmnOE/wNg+z2qhRR9LQsHBFxzN16j983rz3x0NmJf2tE+lfNNMt0j9tD5nlhwxZr6IBN0BDw8IMHLgCYOmA2wmlWQ4FlnT3o9z9cX0JkXLwyB8D0tm6r7LYKlGn+p9kZ5EH8C2GJgF4KGt0UCfXdCV/r+eYUgaV5EnIlkj6oJQ2RL4KPPKMR/64R/5dwnviMMLfnjDj5Biv2moDB61Q8YAbIPzNzYwBtqt4ZyLSq/Q8TbGI9EXfbWhYtKWxcamCPgNOOmlHTjppp3bHvvxyBuutFxXU2eDB6zB//ocQyrFcBlzv7h8VN2SRolxIqAR/GCG50t8tto098inl6sAjb7XYLgbOAWAPjBvbXj4aKLZsWX6AXOry8jGpx0raJAJ45LOB64HrLbblgEP5hO8z0ZcdPHLdgtp49tlTWXbZRRY4fs01T/LrX9/Z7fWNjaNpaFikpaVlyncJOSdEpJ9Q0C3SL9VtNXDgmIaQz6wwb731GQcccEnb89bWwielBw5cFjAHP8vdL+n2ApEe8sjdYjsWWBPYkLDH82aLbRePvLXrq4tyFXAaMIhV2B3jRZwNgfXNbAN3f6mItvKD7jFmVlfCCpD0fm7NdIvk8cg/An5nZlPBLhw4cJmC/hjuvPMfqa/PLRJdbbWluPXW47j33lcK6tfMGDhwhYaWlmlblTJuEem7tLxcpJ8xs8UgM7qxcfGirmttzTBx4sy2/02ZMruIPhtoaFiklTDzKFIVHvlcYG9yidV2AM4ocx+TgVuSpwuzLuks4cUmTMqflR4ILFHCsBR0ixRmo4aGRVvNCpuDmjJldru/g9tvvwYffjiRp59+v+AOw9/ezNJmtmiJYxaRPkhBt0j/sxZAY+Oooi5aYYXFeOmlsTzzzG+45JJDWW654r4vNDYu3gB16xV1kUgPJTNa+5MrGP9Li22/MndzYdujnVgPyN6ROjjZX12ojgLkUpaYp6/R8nKRTtWtF/42Fa+xsZ599tmQW255rqjrGhra/vaWvzaZiPRaCrpF+p+hAGYDC77gpZfGc+KJN3HQQZfx85/fxqhRw7nnnhMZObLweCL0Zx3V4xapKI/838BJqUPXWGxrl7H9F4FnARjE2ozg38lLwwkZkwvVUdA9poQhaaZbpDDD6uoK/1uYttNOazN8+ELcdltxQXeqv/xM6iLyFaagW6T/KbpO4KOPvsV9973KW299xhNPvMOhh14BwH77bVzxvkXK5C/ADcnjbGK1kWVs/6K2RzuRLnxf8BJzd58KTM873JOZ7mbg0xKuF+knrOS/Sd/5zqY8+uhbfPHFjFKb0N9DkX5EQbdI/zMTIJOZV3IDc+c28dZbn7HCCoUvUXefD/jMkjsV6QGP3IHvAS8nh1YCbrLY6svUxe1k946vyjep453k+JZm1lF9+s70KIO5heyI2Znuce5lTRon8hXjM0r5W7j00iPZaquvcdNNzxR9baq/WUVfLCJ9loJukf7ndYCWlondndepAQPqWXnlJfjyy8Lv8Dc3f9EMmWIyOYuUVZJYbS9gUnJoJ0Lm8XK0PQ+4EgCjgXXbBc9HFdFUT2t1LwYM6aQtEWkn83Jz8xctxV514IGbMGnSLB566H/dn5wn9bf3taIvFpE+S0G3SD/j7lOg7pPm5i8Lvua3v92dzTZbiWWXXYT111+OK644kmHDBnHbbc8X2GcLLS1TG4AXSxy2SFl45ONpn1jt1xbbPmVq/lIglPfajvWApuT44WY2oJNr8vW0Vrf2c4sU7sWWlqn17oXH3WbGAQdswu23P19U6cys5uYvgLqPk+0kItJPKOgW6Zcyj82b90GLe2FbypZaamEuvvhQnnjiV1x55ZE0NbWw665/ZsKEwr4zzJ8/HnADni59zCLl4ZE/Cvw8dehai23NMrT7EXAvAENZkkXI3pUaBexWYDP5gfJyZkUtgVfQLVK4p8Bt/vyPCr5g662/xjLLLMIttzxbdGfuzrx5H7ZA5vGiLxaRPq2kMgki0udd1do67eCmpgkMHLhMtycfd9z1Peps9uxXM1D3invrqz1qSKR8/gxsCBxMWI59l8W2sUc+rYftXgjsAcD2DOO2tuPHAHcWcH3+kvAGYGmg0KhA5cJECuTur5rVvzxnzn/XHTRoxYImoh577G1Gj/5JSf01NX1Ca+u0BuCvJTUgIn2WZrpF+qdHoe792bNfrnj21JaWKTQ1ja+DzAWV7kukUKnEaq8kh1YGbixDYrWHgbcBWI11qGdCcnwHM1u+gOt7WqtbM90iRclcMH/++LqWlsqv9p49+xWHuvegraygiPQTCrpF+iF3d8icPn/++zZvXuUmw9yd6dMfzkDdJ8CtFetIpAQe+RxCYrXJyaFdgLE9bNOBi4HwF3adtqDbgCMLaGI8C5YSKibo1ky3SHFugbpPpk9/qLXQLVelmDfvQ+bPf98gc4ZXsiMR6ZUUdIv0X9eBPTB9+oMtPSkf1pU5c/5LU9OEOsgc7u5zK9KJSA945OOAA8gmQIPfWGx79bDZa4HZAGzDWqm2v9vd/mwPtfUm5B0eU0Tf2ZnuaUrUJNK98Lcpc3hT04T6OXMqswMqk5nH9OkPtoDdD1xXkU5EpFdT0C3ST4U77X5UJjN33tSp/8gUk721EPPnf8yMGY9ngIvd/ZGyNi5SRh75w8DJqUPXWWxr9KC96UBIhLAwg1mUbF2hZYFvFdBESRnMzawx6QM0yy1SsORv1MUzZjyWmT//4zK33cLUqf+XyWTmzgM/WrPcIv2Tgm6RfszdPwHftanpk5YpU+7JZDLNZWl3/vzxTJlyVwb8EeCnZWlUpLL+CNycPB5KSKy2cA/au6jt0TaMTB0/poBrSy0btiyQnUnXfm6R4vwU/JEpU+7KhIobPZfJNDNlyj2ZpqYJLeDfDn9zRaQ/UtAt0s+5+2PgOzc1fTx/0qQbW5qaPutBWy3MmPEfpky5yyHzAPjuyXJZkV4t2Yt9NPDf5NAqwA0WW0l/Jz3y14HHAFiDpalnSvLS7ma2RDeX589SjymwWyVREylR+Fvle0DmwSlT7vKZM5+iJyvAmpo+Y9KkG1qamj6eD76Tu6tMmEg/pqBbRJKldb5Ra+v0VydPvtWnT/83ra0zirg+w7x5HzBp0k0ts2c/3wIeJQG39nFLn5FKrJYNkHcFoh40GWa764G1mZQcawAO6+a6/IB5GTMbUEB/SqIm0gPuPgd8N/Cxs2Y91zpp0k0t8+Z9gHum+4sTra0zmD7930yefKu3ts74L/iG7v5oBYctIn2AaWuJiGSZWQNwEtip4IMHDlzBBw36Wt2AAUtQXz8SM2s7N5OZT3PzlzQ1fcqcOa+1ZDKzGqDuecgc7e6qxy19lsX2LeBf5G5M7+mR311CO43AOGA0k8lwQVt77wCrdba308y+DjyZd3gVd3+vy/7MzgJ+mTzdyd3vL3bMIhKY2bpQdwVkNq6rG9oyePDaDQMGjKaxcXHq6ga2nefutLZOpanpC+bNeyczf/6HBjYH/HTgD17uhCki0icp6BaRBZjZUOAgqPshZNYKRxta6+oWajWrM/dmMpk5jcnZ88BvISRMe75WYxYpJ4vt58A5ydOZwCYe+VsltPNbIAbgAsYzmWyt7q3d/YkOrzFbCvg07/C33P2hLvsyu4WQiR1gVXd/p9jxikh7ZrYx8AOwA8EHAdTVDW42a8Q945nM3HpoSXIp1L0OmQuAm9x9Vu1GLSK9jYJuEemSmY0ENkj+twjQCMwF3gNeBN7SnXz5qrHYjJBYLRvEvg1smmQmL6adpYCPgAZeYQZ3MTx56Tp3P7zDa8KSkjnAoNTh77n7FV32ZfY8sBGhzvdCyqcgUj7JSrDVgA2BlYGFgGbCdpSXgJdUpk9EOqOgW0REpAMW2xDgKWCd5NC9hKXmhW/wDO2EGehm4Gxm08oQwo2r0e4+rcNrzP4HrJ46dKa7n9JpHyFQnwosDIx39zHFjFFEREQqR4nUREREOuCRzyYkVsvOXu0GnFpCUxcCYY3IWsxMji0EHNTFNQskU+umj8UIATfAu0WOT0RERCpIQbeIiEgnPPIPgAOB7Oz2WItt9yKb+Q8QkgtuzpKp40d3cU1+0L1sN32sknqsoFtERKQXUdAtIiLSBY/8AeDXqUPXW2yrFnG9ky0ftiSwCBOTl9Y3sw06uSw/U7mCbhERkT5KQbeIiEj3zgFuTx4PB+6y2IZ3cX6+G4GQhG0LRqSOdzbbnR84L2Ppmn0L+lrqsbKWi4iI9CIKukVERLqRzFZ/F3gtObQacJ3FVtDf0WR/+NUArE0jdTQlLx1sZkM6uCQ/cB5E2LfdGc10i4iI9FIKukVERArgkc8iJFablhzaA+g0o3gHLgZgILBmW9A9HNi3g3PHA/ml+LpaYp4NuluBD4sYk4iIiFSYgm4REZECeeTvA98h1MIGiC22XQu89l3gnwBswtDUSwssMXf3FgpMppYsO88G3ePcvbmQ8YiIiEh1KOgWEREpgkf+L3KJ1Qy40WL7WheXpP0ZCAXARjAnObalma3cwbn5y8Q7m+leEsguUdd+bhERkV5GQbeIiEjxfg/ckTzOJlYbVsB1DwJvYsDGDE4dP7yDcwsNutMBv/Zzi4iI9DIKukVERIqUJFY7EngjObQ6cG13idWS684HYJ1wKHnpMLMFrs2ftd7SzI41s23NbFUzW8PMdqD9nnAF3SIiIr2Mgm4REZESJInV9iSXWG0v2tfz7sz1wFSGAblF5csB25hZnZktbmbrA4vmXbcFcAnwMPAWIeC/HzghfZJZUaXMREREpMLM3bs/S0RERDpkse0M/IOwvxtgL4/8rm6uORv4Ba+TW6QOUwl7sweUYVifE2bK3wHeBG5w9y/L0K6IiIgUSUG3iIhID1lsvwLOTJ7OBrbwyF/t4vxlgQ9ppp7zcOa3BeyV8qq7r1vhPkRERKQDWl4uIiLSc2cDNyWPhwD3WGyLd3SixbY6cCnwMY3A2hUPuAFURkxERKRGFHSLiIj0UJIg7Wjg+eTQ8sAdFlu7peIW207AM8AuwBgA1qv48DLAjyrei4iIiHRIy8tFRETKxGIbTQi8RyeHrgS+lzw+Efgj7W94f4GzBBcBkyo2rDPc/dSKtS4iIiJdUtAtIiJSRhbbxsDjwKDk0E8IJcW+18Hp44HleYKQk7z8XgC2cHctLxcREakRBd0iIiJlZrEdBNxYwKkZ4AtmsBR/Ilu1ez4wsAzDmAus7+5vl6EtERERKZH2dIuIiJSZR34TcHkBp9YB9zMcWLHt2ECgpQzD+KkCbhERkdpT0C0iIlJmFtuOwIEFnj4FmJeXUO21Hg7hH8BlPWxDREREykBBt4iISJlYbGaxnQjcBwwv8LINgRtYjfSi8lWA/5U4jInAUa79YyIiIr2Cgm4REZEysNgaCfW3z6e4v6+bAhfTCKzZdmwocDvZXd7FOcrdvyjhOhEREakABd0iIiI9ZLEZIUjuKEN5dwYl/3s4b4n5VsAFnVwzs5Pjl7n7vSWMQURERCpEQbeIiEjPDQf26MH1WwJ/ZllgkbZj2xJmzid3cP4/Ozj2LnBSD8YgIiIiFaCgW0REpIc88unAWEK5r1JsCdyH8V7ebPc+wJl5584Cfp93rBU42N1nl9i/iIiIVIiCbhERkTLwyGNgOeC3wOdFXr5l8t+/sE6744cDN+Sd+xzwMiH4zjrP3Z8vsk8RERGpAlNyUxERkfKy2AYC+wM/BjYo8LI1gY+BT7iW4XzYdnxLwnLyYYTEahu6+8tmdi7wM+BD4GvuXo7a3iIiIlJmmukWEREpM498vkd+PbARISHanUCmm8u29MhnAn/NW2J+BPBOtmlgqpmNBk4H6oGVFHCLiIj0XprpFhERqQKLbQxwAnAMHdfwftwj/4bFtgJNvMd51NEEhH3ik6Bu6QXj9rrPIPMM8DRwg7t/Vrl/gYiIiJRCQbeIiEgVWWzDCHu1fwSsnHpppkc+HMAOs0e4l28yDaCeAQOW9MbGJa2xcRRmAwFwn09z80Samz/PNDV9DrQ6YUb9XHd/oYr/JBEREemCgm4REZEasNjqgF0ItbiXB+5kLIcCpwE/q28cbkMWWp+FFlqdurpBXbaVycxj7tw3mT37lZbW1un1wHnAb919XoX/GSIiItINBd0iIiI1ZrEZY1kJ6v4JrDhs2OZ1Q4ZsiFlxqVfcM8ye/SIzZz6dAT6AzM7u/l5FBi0iIiIFUdAtIiJSY2a2GtgT9fXDR4wcuXtDY+OiPWqvuXkyU6fe09LaOmMa+Jbu/nZ5RioiIiLFUtAtIiJSQ2a2FNhL9fUjFlt00f0a6usHl6Xd1tY5TJ58e0tr67RJ4BsoyZqIiEhtqGSYiIhIjZiZgV1hNnCxRRfdp2wBN0B9/WAWXXSfBrOBi4FdFvoSERGRalPQLSIiUjsHg397xIjtG+rrh5a98fr6oYwYsX0D+G7AQWXvQERERLql5eUiIiI1YGYDwD4dNGiVRUaO3KWis9BTp97n8+a9Oxl8aXdvqmRfIiIi0p5mukVERGpjb/BFhw7dtOLLvkMfvhiwV6X7EhERkfYUdIuIiNSE/XDAgKVbi8lUvuSSC3PBBQfz+utn8P77v+fBB3/G2msv0+11jY2L0tg4uhXshz0ZsYiIiBSvodYDEBER6W/MbGFgi4UWWqPgaxZeeCHuvvtEnnrqXQ455HImTZrJmDGLMWPG3IKuHzx4jfrp0z/9upkNd/cZJQ5dREREiqSgW0REpPrWB2hsXLLgC44/fjs+/XQaP/nJLW3HPvlkasHXp/paH3is4AtFRESkR7S8XEREpPo2hPpMQ8PIgi/YYYc1+e9/P+ayyw7n1VdP44EHTuKggzYr+PqGhkWA+kzoW0RERKpFQbeIiEj1ja6vH9pqVvif4eWWW5TDDtuCDz+cyEEHXcZ11z3F6afvxb77blTQ9WZ11NcPbQVGlzhmERERKYGWl4uIiFTfALP6oi6oqzNeffVjzj77PgBef30Cq666JIcd9nXuuOOFQlsBGFBUxyIiItIjmukWERGpvvnuLUVd8OWXM3jnnS/aHXv33S9YeukRRbTSCjC/qI5FRESkRxR0i4iIVN/Hra2z6t1bC77g+ec/ZKWVFm93bMUVF2fChMKSqbm30to6qx74uJiBioiISM8o6BYREam+FyFT19IypeALLr/8MTbYYHl++MPtGTNmMfbaawMOOWQzrr76yYKub2mZDGTqQt8iIiJSLebutR6DiIhIv2JmQ4Hpw4dvWzdkyDoFX7f99mvwq199mxVWGMXHH0/hssv+zU03PVPQtbNn/5cZMx7NAMPdfXZpIxcREZFiKegWERGpAbO6BxsbF//mYot9p7iMaiWaNOmm1ubmiY+6Z75Vjf5EREQk0PJyERGRmvALm5u/qG9u/rLiPTU3f0Fz85f14BdUvDMRERFpR0G3iIhIbfwD6j6dOfOpTCVXnbk7M2c+nYG6T0OfIiIiUk0KukVERGrA3Vsg84P588fVzZ37VsX6mTv3LebPH1cHmeO8mHTpIiIiUhYKukVERGrE3e8Gbpox49HWlpZpZW+/pWUaM2Y80grc6O73lL0DERER6ZYSqYmIiNSQmS0Cdc/X1Q1ZbtFF92toaBhelnZbWmYwefJtLZnMnI8gs7G7F16fTERERMpGQbeIiEiNmdlyUPdEXd2g0SNH7towYMDoHrXX1PQpU6f+X0smM+9TyGzl7h+VaagiIiJSJAXdIiIivYCZjQa7B3yDIUM2tGHDNsesoag23FuYOfNpZs9+0cFeBN/d3T+r0JBFRESkAAq6RUREegkLUfZJwBl1dQsxePA6DYMHr0V9/bAur2ttncmcOa8zZ86rLZnMPAf/DfDHkKxNREREaklBt4iISC9jZl8DfgR2JPighoZFWhobl2xsbByF2UAA3OfT3DyR5ubPm1tapjSAzQW/Gjjf3d+t6T9ARERE2ijoFhER6aXMbBiwL7A51G0KmTWA7JrzFqj7H2SeBZ4G7nD3mbUaq4iIiHRMQbeIiEgfYWYGNCZPm11/xEVERHo9Bd0iIiIiIiIiFVJX6wGIiIiIiIiIfFUp6BYRERERERGpEAXdIiIiIiIiIhWioFtERERERESkQhR0i4iIiIiIiFSIgm4RERERERGRClHQLSIiIiIiIlIhCrpFREREREREKkRBt4iIiIiIiEiFKOgWERERERERqRAF3SIiIiIiIiIVoqBbREREREREpEIUdIuIiIiIiIhUiIJuERERERERkQpR0C0iIiIiIiJSIQq6RURERERERCpEQbeIiIiIiIhIhSjoFhEREREREakQBd0iIiIiIiIiFaKgW0RERERERKRCFHSLiIiIiIiIVIiCbhEREREREZEKUdAtIiIiIiIiUiEKukVEREREREQqREG3iIiIiIiISIUo6BYRERERERGpkP8HiHlNJ1ul0zMAAAAASUVORK5CYII=", - "text/plain": [ - "Graphics object consisting of 60 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g_directed.layout()\n", - "pos = g_directed.get_pos()\n", - "for i, c in enumerate(solution):\n", - " for e in g_directed.edges():\n", - " g_directed.set_edge_label(e[0], e[1], 0)\n", - " if is_in_cycle(e, c):\n", - " g_directed.set_edge_label(e[0], e[1], i + 1)\n", - "\n", - " g_directed.set_pos(pos)\n", - "\n", - " p = g_directed.plot(\n", - " edge_colors=g_directed._color_by_label({\n", - " 0: \"black\", \n", - " 1: \"blue\", \n", - " 2: \"purple\", \n", - " 3: \"red\", \n", - " 4: \"green\", \n", - " 5: \"orange\", \n", - " 6: \"yellow\",\n", - " 7: \"brown\",\n", - " 8: \"pink\",\n", - " 9: \"cyan\",\n", - " 10: \"magenta\",\n", - " 11: \"grey\",\n", - " 12: \"lightblue\",\n", - " 13: \"lightgreen\",\n", - " 14: \"teal\",\n", - " 15: 'salmon',\n", - " 16: 'navy',\n", - " 17: 'gold',\n", - " 18: 'lime',\n", - " 19: 'indigo',\n", - " 20: 'maroon',\n", - " 21: 'olive',\n", - " }), \n", - " vertex_size=70,\n", - " vertex_color=\"midnightblue\",\n", - " transparent=True,\n", - " pos=pos,\n", - " layout='circular',\n", - " )\n", - " for object in p._objects:\n", - " if isinstance(object, sage.plot.text.Text):\n", - " object._options['rgbcolor'] = (1, 1, 1)\n", - " p.show(figsize=(10, 10))" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "39\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "Graphics Array of size 3 x 13" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "G = graphs.CompleteBipartiteGraph(3,3)\n", - "old_labels = G.vertices()\n", - "new_labels = list(range(1, len(old_labels)+1))\n", - "label_map = dict(zip(old_labels, new_labels))\n", - "G = G.relabel(label_map, inplace=False)\n", - "g_directed = G.to_directed()\n", - "g_directed.layout()\n", - "pos = g_directed.get_pos()\n", - "cycles = g_directed.all_simple_cycles()\n", - "print(len(cycles))\n", - "\n", - "def is_in_cycle(e, cycle):\n", - " i_s = [i for i, x in enumerate(cycle) if x == e[0]]\n", - " j_s = [i for i, x in enumerate(cycle) if x == e[1]]\n", - "\n", - " for i in i_s:\n", - " for j in j_s:\n", - " if i + 1 == j or (i == len(cycle) - 2 and j == 0):\n", - " return True\n", - " return False\n", - "\n", - "plots = []\n", - "for i, c in enumerate(cycles):\n", - " for e in g_directed.edges():\n", - " g_directed.set_edge_label(e[0], e[1], 0)\n", - " if is_in_cycle(e, c):\n", - " g_directed.set_edge_label(e[0], e[1], i + 1)\n", - "\n", - " g_directed.set_pos(pos)\n", - "\n", - " p = g_directed.plot(\n", - " edge_colors=g_directed._color_by_label({\n", - " 0: \"black\", \n", - " 1: \"blue\", \n", - " 2: \"purple\", \n", - " 3: \"red\", \n", - " 4: \"green\", \n", - " 5: \"orange\", \n", - " 6: \"yellow\",\n", - " 7: \"brown\",\n", - " 8: \"pink\",\n", - " 9: \"cyan\",\n", - " 10: \"magenta\",\n", - " 11: \"grey\",\n", - " 12: \"lightblue\",\n", - " 13: \"lightgreen\",\n", - " 14: \"teal\",\n", - " 15: 'salmon',\n", - " 16: 'navy',\n", - " 17: 'gold',\n", - " 18: 'lime',\n", - " 19: 'indigo',\n", - " 20: 'maroon',\n", - " 21: 'olive',\n", - " 22: 'khaki',\n", - " 23: 'indianred',\n", - " 24: 'salmon',\n", - " 25: 'deeppink',\n", - " 26: 'orchid',\n", - " 27: 'royalblue',\n", - " 28: 'tomato',\n", - " 29: 'aquamarine',\n", - " 30: 'navajowhite',\n", - " 31: 'floralwhite',\n", - " 32: 'tan',\n", - " 33: 'darkgoldenrod',\n", - " 34: 'paleturquoise',\n", - " 35: 'darkslateblue',\n", - " 36: 'lavenderblush',\n", - " 37: 'hotpink',\n", - " 38: 'crimson',\n", - " 39: 'orangered',\n", - " }), \n", - " vertex_size=70,\n", - " vertex_color=\"midnightblue\",\n", - " transparent=True,\n", - " pos=pos,\n", - " layout='circular',\n", - " )\n", - " for object in p._objects:\n", - " if isinstance(object, sage.plot.text.Text):\n", - " object._options['rgbcolor'] = (1, 1, 1)\n", - " # p.show(figsize=(10, 10))\n", - " plots.append(p)\n", - "\n", - "show(graphics_array([plots[i:i+13] for i in range(0, len(plots), 13)]), figsize=(130, 30), transparent=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0\n", - "0\n", - "36\n", - "0\n", - "48\n", - "0\n", - "84\n", - "0\n", - "186\n", - "0\n", - "330\n" - ] - } - ], - "source": [ - "def find_cycles(g, k, include_non_simple=False):\n", - " adjacency_list = [[] for _ in range(len(g.vertices()))]\n", - " offset = min(g.vertices())\n", - " for e in g.edges():\n", - " adjacency_list[e[0]-offset].append(e[1]-offset)\n", - " adjacency_list[e[1]-offset].append(e[0]-offset)\n", - "\n", - " cycles = []\n", - " queue = []\n", - " for i in range(len(g.vertices())):\n", - " queue.append([i])\n", - " if include_non_simple:\n", - " while len(queue) > 0:\n", - " path = queue.pop(0)\n", - " if len(path) == k:\n", - " if path[0] in adjacency_list[path[-1]] and path[-1] != path[1]:\n", - " repeated_edge = False\n", - " for j in range(len(path)-1):\n", - " if path[j] == path[-1] and path[j + 1] == i:\n", - " repeated_edge = True\n", - " break\n", - " if repeated_edge:\n", - " continue\n", - " cycle = path + [path[0]]\n", - " cycles.append(cycle)\n", - " continue\n", - " for i in adjacency_list[path[-1]]:\n", - " if len(path) > 2 and i == path[-2]:\n", - " continue\n", - " repeated_edge = False\n", - " for j in range(len(path)-1):\n", - " if path[j] == path[-1] and path[j + 1] == i:\n", - " repeated_edge = True\n", - " break\n", - " if repeated_edge:\n", - " continue\n", - " if i >= path[0]:\n", - " queue.append(path + [i])\n", - " else:\n", - " while len(queue) > 0:\n", - " path = queue.pop(0)\n", - " if len(path) == k:\n", - " if path[0] in adjacency_list[path[-1]]:\n", - " cycle = path + [path[0]]\n", - " cycles.append(cycle)\n", - " continue\n", - " for i in adjacency_list[path[-1]]:\n", - " if i not in path and i > path[0]:\n", - " queue.append(path + [i])\n", - " \n", - " return [[v + offset for v in c] for c in cycles]\n", - "\n", - "print(len(find_cycles(G, 2, include_non_simple=True)))\n", - "print(len(find_cycles(G, 3, include_non_simple=True)))\n", - "print(len(find_cycles(G, 4, include_non_simple=True)))\n", - "print(len(find_cycles(G, 5, include_non_simple=True)))\n", - "print(len(find_cycles(G, 6, include_non_simple=True)))\n", - "print(len(find_cycles(G, 7, include_non_simple=True)))\n", - "print(len(find_cycles(G, 8, include_non_simple=True)))\n", - "print(len(find_cycles(G, 9, include_non_simple=True)))\n", - "print(len(find_cycles(G, 10, include_non_simple=True)))\n", - "print(len(find_cycles(G, 11, include_non_simple=True)))\n", - "print(len(find_cycles(G, 12, include_non_simple=True)))" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "36\n", - "8\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics Array of size 2 x 4" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "G = graphs.CompleteBipartiteGraph(3,3)\n", - "old_labels = G.vertices()\n", - "new_labels = list(range(1, len(old_labels)+1))\n", - "label_map = dict(zip(old_labels, new_labels))\n", - "G = G.relabel(label_map, inplace=False)\n", - "g_directed = G.to_directed()\n", - "g_directed.layout()\n", - "pos = g_directed.get_pos()\n", - "cycles = find_cycles(G, 4, include_non_simple=True)\n", - "print(len(cycles))\n", - "\n", - "def is_in_cycle(e, cycle):\n", - " i_s = [i for i, x in enumerate(cycle) if x == e[0]]\n", - " j_s = [i for i, x in enumerate(cycle) if x == e[1]]\n", - "\n", - " for i in i_s:\n", - " for j in j_s:\n", - " if i + 1 == j or (i == len(cycle) - 2 and j == 0):\n", - " return True\n", - " return False\n", - "\n", - "plots = []\n", - "for i, c in enumerate(cycles):\n", - " if not is_in_cycle((6, 2), c):\n", - " continue\n", - "\n", - " for e in g_directed.edges():\n", - " g_directed.set_edge_label(e[0], e[1], 0)\n", - " if is_in_cycle(e, c):\n", - " g_directed.set_edge_label(e[0], e[1], i + 1)\n", - "\n", - " g_directed.set_pos(pos)\n", - "\n", - " p = g_directed.plot(\n", - " edge_colors=g_directed._color_by_label({\n", - " 0: \"black\", \n", - " 1: \"blue\", \n", - " 2: \"purple\", \n", - " 3: \"red\", \n", - " 4: \"green\", \n", - " 5: \"orange\", \n", - " 6: \"yellow\",\n", - " 7: \"brown\",\n", - " 8: \"pink\",\n", - " 9: \"cyan\",\n", - " 10: \"magenta\",\n", - " 11: \"grey\",\n", - " 12: \"lightblue\",\n", - " 13: \"lightgreen\",\n", - " 14: \"teal\",\n", - " 15: 'salmon',\n", - " 16: 'navy',\n", - " 17: 'gold',\n", - " 18: 'lime',\n", - " 19: 'indigo',\n", - " 20: 'maroon',\n", - " 21: 'olive',\n", - " 22: 'khaki',\n", - " 23: 'indianred',\n", - " 24: 'salmon',\n", - " 25: 'deeppink',\n", - " 26: 'orchid',\n", - " 27: 'royalblue',\n", - " 28: 'tomato',\n", - " 29: 'aquamarine',\n", - " 30: 'navajowhite',\n", - " 31: 'floralwhite',\n", - " 32: 'tan',\n", - " 33: 'darkgoldenrod',\n", - " 34: 'paleturquoise',\n", - " 35: 'darkslateblue',\n", - " 36: 'lavenderblush',\n", - " 37: 'hotpink',\n", - " 38: 'crimson',\n", - " 39: 'orangered',\n", - " }), \n", - " vertex_size=70,\n", - " vertex_color=\"midnightblue\",\n", - " transparent=True,\n", - " pos=pos,\n", - " layout='circular',\n", - " )\n", - " for object in p._objects:\n", - " if isinstance(object, sage.plot.text.Text):\n", - " object._options['rgbcolor'] = (1, 1, 1)\n", - " # p.show(figsize=(10, 10))\n", - " plots.append(p)\n", - "print(len(plots))\n", - "show(graphics_array([plots[i:i+4] for i in range(0, len(plots), 4)]), figsize=(40, 20), transparent=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": { - "vscode": { - "languageId": "python" - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Graphics object consisting of 30 graphics primitives" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "def is_in_cycle(e, cycle):\n", - " i_s = [i for i, x in enumerate(cycle) if x == e[0]]\n", - " j_s = [i for i, x in enumerate(cycle) if x == e[1]]\n", - "\n", - " for i in i_s:\n", - " for j in j_s:\n", - " if i + 1 == j or (i == len(cycle) - 2 and j == 0):\n", - " return True\n", - " return False\n", - "\n", - "G = graphs.CompleteBipartiteGraph(3,3)\n", - "old_labels = G.vertices()\n", - "new_labels = list(range(1, len(old_labels)+1))\n", - "label_map = dict(zip(old_labels, new_labels))\n", - "G = G.relabel(label_map, inplace=False)\n", - "g_directed = G.to_directed()\n", - "g_directed.layout()\n", - "pos = g_directed.get_pos()\n", - "solution = [\n", - " [2, 5, 1, 6, 2],\n", - " [6, 1, 4, 3, 6],\n", - " [5, 2, 4, 1, 5, 3, 4, 2, 6, 3, 5]\n", - "]\n", - "for e in g_directed.edges():\n", - " g_directed.set_edge_label(e[0], e[1], 0)\n", - " for i, c in enumerate(solution):\n", - " if is_in_cycle(e, c):\n", - " g_directed.set_edge_label(e[0], e[1], i + 1)\n", - "\n", - "g_directed.set_pos(pos)\n", - "\n", - "p = g_directed.plot(\n", - " edge_colors=g_directed._color_by_label({\n", - " 0: \"black\", \n", - " 1: \"blue\", \n", - " 3: \"red\", \n", - " 2: \"purple\", \n", - " 4: \"green\", \n", - " 5: \"orange\", \n", - " 6: \"yellow\",\n", - " 7: \"brown\",\n", - " 8: \"pink\",\n", - " 9: \"cyan\",\n", - " 10: \"magenta\",\n", - " 11: \"grey\",\n", - " 12: \"lightblue\",\n", - " 13: \"lightgreen\",\n", - " 14: \"teal\",\n", - " 15: 'salmon',\n", - " 16: 'navy',\n", - " 17: 'gold',\n", - " 18: 'lime',\n", - " 19: 'indigo',\n", - " 20: 'maroon',\n", - " 21: 'olive',\n", - " }), \n", - " vertex_size=70,\n", - " vertex_color=\"midnightblue\",\n", - " transparent=True,\n", - " pos=pos,\n", - " layout='circular',\n", - ")\n", - "for object in p._objects:\n", - " if isinstance(object, sage.plot.text.Text):\n", - " object._options['rgbcolor'] = (1, 1, 1)\n", - "p.show(figsize=(10, 10))" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "SageMath 10.3", - "language": "sage", - "name": "SageMath-10.3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "sage", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.8" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/MultiGenus/convert.ipynb b/MultiGenus/convert.ipynb index 851c6f1..d8dafed 100644 --- a/MultiGenus/convert.ipynb +++ b/MultiGenus/convert.ipynb @@ -3,7 +3,11 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "import os" @@ -11,11 +15,15 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": {}, + "execution_count": null, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ - "INPUT_DIR = os.path.join('..', 'CalcGenus', 'adjacency_lists')\n", + "INPUT_DIR = os.path.join('..', 'PAGE', 'adjacency_lists')\n", "OUTPUT_DIR = './graphs'\n", "IGNORE_VERTEX = 65535" ] @@ -23,7 +31,11 @@ { "cell_type": "code", "execution_count": 3, - "metadata": {}, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "def convert(name):\n", @@ -63,7 +75,11 @@ { "cell_type": "code", "execution_count": 4, - "metadata": {}, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [ { "name": "stdout", @@ -599,9 +615,9 @@ ], "metadata": { "kernelspec": { - "display_name": "SageMath 10.7", + "display_name": "SageMath 10.3", "language": "sage", - "name": "SageMath-10.7" + "name": "SageMath-10.3" }, "language_info": { "codemirror_mode": { @@ -610,7 +626,7 @@ }, "file_extension": ".py", "mimetype": "text/x-python", - "name": "python", + "name": "sage", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.3" diff --git a/MultiGenus/planar_cutthroughedges_draw.c b/MultiGenus/planar_cutthroughedges_draw.c index a808513..f4f9d88 100644 --- a/MultiGenus/planar_cutthroughedges_draw.c +++ b/MultiGenus/planar_cutthroughedges_draw.c @@ -16,8 +16,9 @@ #define MAXVAL 50 /* maximale valenz */ #define MAXFACE 50 /* maximale Flaechengroesse 255 */ #define MAXCYC 40 // maximum number of cycles looked for -#define MAXCOLOURGENUS 5 // otherwise the colour list must be updated -- already for genus 5 (10+1 colours) colours are sometimes difficult to distinguish +#define MAXCOLOURGENUS 5 // for larger genus, keep labels and generate additional colours programmatically #define MAXGENUS 20 +#define TEXTURESIZE 2048 #define NOTINGRAPH ((-5)*MAXGENUS) #define RADIUS (100.0) #define MAXEDGES (N<<5) @@ -91,9 +92,13 @@ int nullvertices, numcycles; int available_edges, used_edges; KANTE *edgebuffer; KANTE *edgelist[MAXEDGES]; -int maxcross=0, blackwhite=0, drawvertexnumbers=1, labels=0, straight=0, text=0; +int maxcross=0, blackwhite=0, forceblackwhite=0, drawvertexnumbers=1, labels=0, straight=0, text=0; int chosenvertex=0, chosenedge[2]={0}; int firstpage=1; +char *objprefix=NULL; +int objdrawings=0; +int boundary_side[N+1], boundary_cyc[N+1]; +double boundary_t[N+1]; char allowedcut[SMALLN][SMALLN]; #define CANBECUT(a,b) (((a)>=SMALLN) || (((b)>=SMALLN)) || allowedcut[a][b]) @@ -151,6 +156,37 @@ int dbcycle[100],dbcyclelength; char colours[11][16]={"black","blue","red","green","orange","olive","gray","pink","yellow","lime","cyan"}; +char *cyclecolour(int cyclenumber) +{ + static char generated[8][64]; + static int slot=0; + int n, red, green, blue; + + n=abs(cyclenumber); + if (forceblackwhite) return "gray"; + if (n<11) return colours[n]; + + slot=(slot+1)%8; + red=(53*n+97)%206+50; + green=(97*n+53)%206+50; + blue=(149*n+29)%206+50; + snprintf(generated[slot],64,"color={rgb,255:red,%d;green,%d;blue,%d}",red,green,blue); + return generated[slot]; +} + +char *cyclelabel(int cyclenumber) +{ + static char labels[8][16]; + static int slot=0; + int n; + + n=abs(cyclenumber); + slot=(slot+1)%8; + if (n<=26) snprintf(labels[slot],16,"%c",'A'-1+n); + else snprintf(labels[slot],16,"%d",n); + return labels[slot]; +} + /***************************SCHREIBEEDGE********************************/ void schreibeedge(char st[], KANTE *edge) @@ -286,6 +322,12 @@ void cleargraph() } nv=0; startedge=NULL; + for (i=0;i<=N;i++) + { + boundary_side[i]=(-1); + boundary_cyc[i]=0; + boundary_t[i]=0.0; + } } @@ -1465,6 +1507,1192 @@ void rotate_clockwise_to(double c[2], double coordinates[2], double angle) #define abs(a) ((a)>0?(a):(-(a))) +int uf_find(int parent[], int x) +{ + while (parent[x]!=x) + { + parent[x]=parent[parent[x]]; + x=parent[x]; + } + return x; +} + +void uf_union(int parent[], int a, int b) +{ + int ra, rb; + if ((a<0) || (b<0)) return; + ra=uf_find(parent,a); + rb=uf_find(parent,b); + if (ra!=rb) parent[rb]=ra; +} + +void texture_bounds(double coord[][2], double *minx, double *maxx, double *miny, double *maxy) +{ + int i, first=1; + double padx, pady; + + for (i=1;i<=nv;i++) + if (adj[i]>0) + { + if (first) + { *minx=*maxx=coord[i][0]; *miny=*maxy=coord[i][1]; first=0; } + else + { + if (coord[i][0]<*minx) *minx=coord[i][0]; + if (coord[i][0]>*maxx) *maxx=coord[i][0]; + if (coord[i][1]<*miny) *miny=coord[i][1]; + if (coord[i][1]>*maxy) *maxy=coord[i][1]; + } + } + if (first) { *minx=*miny=-RADIUS; *maxx=*maxy=RADIUS; } + padx=0.08*((*maxx)-(*minx)); + pady=0.08*((*maxy)-(*miny)); + if (padx<1.0) padx=1.0; + if (pady<1.0) pady=1.0; + *minx-=padx; *maxx+=padx; *miny-=pady; *maxy+=pady; +} + +void coord_to_uv(double coord[][2], int v, double minx, double maxx, double miny, double maxy, double *u, double *vv) +{ + *u=(coord[v][0]-minx)/(maxx-minx); + *vv=(coord[v][1]-miny)/(maxy-miny); + if (*u<0.0) *u=0.0; if (*u>1.0) *u=1.0; + if (*vv<0.0) *vv=0.0; if (*vv>1.0) *vv=1.0; +} + +void canonical_point(double x, double y, int genus, double out[3]) +{ + double theta, rho, t, local, major, minor, spacing, u, v, scale, r2; + int handle; + + if (genus<=0) + { + scale=RADIUS; + x/=scale; y/=scale; + r2=x*x+y*y; + out[0]=1.45*(2.0*x/(1.0+r2)); + out[1]=1.45*(2.0*y/(1.0+r2)); + out[2]=1.45*((1.0-r2)/(1.0+r2)); + return; + } + + theta=atan2(y,x); + if (theta<0.0) theta += 2.0*M_PI; + rho=sqrt(x*x+y*y)/RADIUS; + if (rho>1.0) rho=1.0; + t=theta/(2.0*M_PI); + handle=(int)floor(t*((double)genus)); + if (handle>=genus) handle=genus-1; + local=(t*((double)genus))-((double)handle); + u=2.0*M_PI*local; + v=2.0*M_PI*rho; + major=1.25; + minor=0.38; + spacing=3.0; + out[0]=(((double)handle)-(((double)genus)-1.0)/2.0)*spacing + (major+minor*cos(v))*cos(u); + out[1]=(major+minor*cos(v))*sin(u); + out[2]=minor*sin(v); +} + +void texture_set(unsigned char *img, int x, int y, int r, int g, int b) +{ + int p; + if ((x<0) || (x>=TEXTURESIZE) || (y<0) || (y>=TEXTURESIZE)) return; + p=3*((TEXTURESIZE-1-y)*TEXTURESIZE+x); + img[p]=r; img[p+1]=g; img[p+2]=b; +} + +void texture_line(unsigned char *img, int x0, int y0, int x1, int y1, int r, int g, int b, int width) +{ + int dx, dy, sx, sy, err, e2, wx, wy; + + dx=abs(x1-x0); dy=abs(y1-y0); + sx=(x0-dy) { err-=dy; x0+=sx; } + if (e2next) + if ((run->ursprungname) && (run->cyclenumber==0) && (type[run->ursprung]!=3) && (type[run->name]!=3)) + { + coord_to_uv(coord,run->ursprung,minx,maxx,miny,maxy,&u,&vv); + x0=(int)(u*(TEXTURESIZE-1)); y0=(int)(vv*(TEXTURESIZE-1)); + coord_to_uv(coord,run->name,minx,maxx,miny,maxy,&u,&vv); + x1=(int)(u*(TEXTURESIZE-1)); y1=(int)(vv*(TEXTURESIZE-1)); + texture_line(img,x0,y0,x1,y1,20,25,30,4); + } + } + + for (i=1;i<=nv;i++) + if (type[i]==0) + { + coord_to_uv(coord,i,minx,maxx,miny,maxy,&u,&vv); + x0=(int)(u*(TEXTURESIZE-1)); y0=(int)(vv*(TEXTURESIZE-1)); + texture_circle(img,x0,y0,9,10,10,10); + texture_circle(img,x0,y0,5,245,245,245); + } + + file=fopen(filename,"wb"); + if (file==NULL) { fprintf(stderr,"Can't open texture file %s -- exit.\n",filename); exit(1); } + fprintf(file,"P6\n%d %d\n255\n",TEXTURESIZE,TEXTURESIZE); + fwrite(img,3,TEXTURESIZE*TEXTURESIZE,file); + fclose(file); + free(img); +} + +int canonical_mesh_id(int ring, int sector, int sectors) +{ + if (ring==0) return 0; + while (sector<0) sector+=sectors; + sector%=sectors; + return 1+(ring-1)*sectors+sector; +} + +void canonical_mesh_point(int genus, int side_segments, int rings, int ring, int sector, double out[3]) +{ + double rho, theta, local, ub, vb, u, v, major, minor, spacing; + int sectors, side, handle, q; + + if (genus<=0) + { + theta=(2.0*M_PI*((double)sector))/64.0; + rho=((double)ring)/((double)rings); + canonical_point(RADIUS*rho*cos(theta),RADIUS*rho*sin(theta),0,out); + return; + } + + sectors=4*genus*side_segments; + theta=(2.0*M_PI*((double)sector))/((double)sectors); + rho=((double)ring)/((double)rings); + side=sector/side_segments; + handle=side/4; + q=side%4; + local=((double)(sector%side_segments))/((double)side_segments); + + if (q==0) { ub=local; vb=0.0; } + else if (q==1) { ub=1.0; vb=local; } + else if (q==2) { ub=1.0-local; vb=1.0; } + else { ub=0.0; vb=1.0-local; } + + u=0.5*(1.0-rho)+rho*ub; + v=0.5*(1.0-rho)+rho*vb; + major=1.25; + minor=0.38; + spacing=3.0; + + out[0]=(((double)handle)-(((double)genus)-1.0)/2.0)*spacing + (major+minor*cos(2.0*M_PI*v))*cos(2.0*M_PI*u); + out[1]=(major+minor*cos(2.0*M_PI*v))*sin(2.0*M_PI*u); + out[2]=minor*sin(2.0*M_PI*v) + 0.10*(1.0-rho)*sin(theta*((double)genus)); +} + +void clamp_unit(double *x) +{ + if (*x<0.0) *x=0.0; + if (*x>1.0) *x=1.0; +} + +void projected_uv(double x, double y, double minx, double maxx, double miny, double maxy, double *u, double *v) +{ + *u=(x-minx)/(maxx-minx); + *v=(y-miny)/(maxy-miny); + clamp_unit(u); + clamp_unit(v); +} + +typedef struct +{ + long long x; + long long y; + long long z; + long long u; + long long v; + int index; + unsigned char used; +} OBJVERTEXCACHEENTRY; + +typedef struct +{ + OBJVERTEXCACHEENTRY *entries; + unsigned int capacity; +} OBJVERTEXCACHE; + +long long quantize_obj_value(double x) +{ + if (x>=0.0) return (long long)(x*1000000.0+0.5); + return (long long)(x*1000000.0-0.5); +} + +unsigned int obj_vertex_hash(long long x, long long y, long long z, long long u, long long v) +{ + unsigned long long h; + h=1469598103934665603ULL; + h=(h^(unsigned long long)x)*1099511628211ULL; + h=(h^(unsigned long long)y)*1099511628211ULL; + h=(h^(unsigned long long)z)*1099511628211ULL; + h=(h^(unsigned long long)u)*1099511628211ULL; + h=(h^(unsigned long long)v)*1099511628211ULL; + return (unsigned int)(h^(h>>32)); +} + +void obj_cache_init(OBJVERTEXCACHE *cache, unsigned int capacity) +{ + cache->capacity=capacity; + cache->entries=calloc(capacity,sizeof(OBJVERTEXCACHEENTRY)); + if (cache->entries==NULL) { fprintf(stderr,"Can't allocate OBJ vertex cache -- exit.\n"); exit(1); } +} + +void obj_cache_free(OBJVERTEXCACHE *cache) +{ + free(cache->entries); + cache->entries=NULL; + cache->capacity=0; +} + +int obj_emit_vertex(FILE *obj, OBJVERTEXCACHE *cache, double x, double y, double z, double u, double v, int *vcount) +{ + long long qx,qy,qz,qu,qv; + unsigned int slot, start; + + clamp_unit(&u); + clamp_unit(&v); + qx=quantize_obj_value(x); + qy=quantize_obj_value(y); + qz=quantize_obj_value(z); + qu=0; + qv=0; + slot=obj_vertex_hash(qx,qy,qz,qu,qv)&(cache->capacity-1); + start=slot; + while (cache->entries[slot].used) + { + if ((cache->entries[slot].x==qx) && (cache->entries[slot].y==qy) && + (cache->entries[slot].z==qz) && (cache->entries[slot].u==qu) && + (cache->entries[slot].v==qv)) + return cache->entries[slot].index; + slot=(slot+1)&(cache->capacity-1); + if (slot==start) { fprintf(stderr,"OBJ vertex cache is full -- exit.\n"); exit(1); } + } + (*vcount)++; + cache->entries[slot].used=1; + cache->entries[slot].x=qx; + cache->entries[slot].y=qy; + cache->entries[slot].z=qz; + cache->entries[slot].u=qu; + cache->entries[slot].v=qv; + cache->entries[slot].index=*vcount; + fprintf(obj,"v %.8f %.8f %.8f\n",x,y,z); + fprintf(obj,"vt %.8f %.8f\n",u,v); + return *vcount; +} + +void obj_emit_triangle(FILE *obj, OBJVERTEXCACHE *cache, double a[3], double b[3], double c[3], double au, double av, double bu, double bv, double cu, double cv, int *vcount, int *faces) +{ + int ia, ib, ic; + ia=obj_emit_vertex(obj,cache,a[0],a[1],a[2],au,av,vcount); + ib=obj_emit_vertex(obj,cache,b[0],b[1],b[2],bu,bv,vcount); + ic=obj_emit_vertex(obj,cache,c[0],c[1],c[2],cu,cv,vcount); + fprintf(obj,"f %d/%d %d/%d %d/%d\n",ia,ia,ib,ib,ic,ic); + (*faces)++; +} + +void sphere_point(double theta, double phi, double out[3]) +{ + double r; + r=1.45; + out[0]=r*sin(phi)*cos(theta); + out[1]=r*sin(phi)*sin(theta); + out[2]=r*cos(phi); +} + +void sphere_uv(double p[3], double *u, double *v) +{ + *u=0.5 + p[0]/3.2; + *v=0.5 + p[1]/3.2; + clamp_unit(u); + clamp_unit(v); +} + +void write_sphere_mesh(FILE *obj, OBJVERTEXCACHE *cache, int *vcount, int *faces) +{ + int lat, lon, i, j; + double p00[3], p01[3], p10[3], p11[3], u00,v00,u01,v01,u10,v10,u11,v11; + double phi0, phi1, th0, th1; + + lat=56; + lon=112; + for (i=0;i1.0) t=1.0; + px=ax+t*vx; py=ay+t*vy; pz=az+t*vz; + dx=x-px; dy=y-py; dz=z-pz; + return sqrt(dx*dx+dy*dy+dz*dz); +} + +double smooth_min(double a, double b, double k) +{ + double h, m; + if (a>900.0) return b; + m=(a1.0) t=1.0; + out[0]=a[0]+t*(b[0]-a[0]); + out[1]=a[1]+t*(b[1]-a[1]); + out[2]=a[2]+t*(b[2]-a[2]); +} + +void handle_uv(double p[3], double minx, double maxx, double miny, double maxy, double *u, double *v) +{ + projected_uv(p[0],p[1],minx,maxx,miny,maxy,u,v); +} + +void normalize3(double v[3]) +{ + double len; + len=sqrt(v[0]*v[0]+v[1]*v[1]+v[2]*v[2]); + if (len<1e-12) { v[0]=0.0; v[1]=0.0; v[2]=1.0; return; } + v[0]/=len; v[1]/=len; v[2]/=len; +} + +void handle_chain_gradient(double p[3], int genus, double grad[3]) +{ + double eps; + eps=0.0001; + grad[0]=handle_chain_sdf(p[0]+eps,p[1],p[2],genus)-handle_chain_sdf(p[0]-eps,p[1],p[2],genus); + grad[1]=handle_chain_sdf(p[0],p[1]+eps,p[2],genus)-handle_chain_sdf(p[0],p[1]-eps,p[2],genus); + grad[2]=handle_chain_sdf(p[0],p[1],p[2]+eps,genus)-handle_chain_sdf(p[0],p[1],p[2]-eps,genus); + normalize3(grad); +} + +void obj_emit_oriented_handle_triangle(FILE *obj, OBJVERTEXCACHE *cache, int genus, double a[3], double b[3], double c[3], double au, double av, double bu, double bv, double cu, double cv, int *vcount, int *faces) +{ + double ab[3], ac[3], n[3], mid[3], grad[3], dot; + ab[0]=b[0]-a[0]; ab[1]=b[1]-a[1]; ab[2]=b[2]-a[2]; + ac[0]=c[0]-a[0]; ac[1]=c[1]-a[1]; ac[2]=c[2]-a[2]; + n[0]=ab[1]*ac[2]-ab[2]*ac[1]; + n[1]=ab[2]*ac[0]-ab[0]*ac[2]; + n[2]=ab[0]*ac[1]-ab[1]*ac[0]; + mid[0]=(a[0]+b[0]+c[0])/3.0; + mid[1]=(a[1]+b[1]+c[1])/3.0; + mid[2]=(a[2]+b[2]+c[2])/3.0; + handle_chain_gradient(mid,genus,grad); + dot=n[0]*grad[0]+n[1]*grad[1]+n[2]*grad[2]; + if (dot<0.0) obj_emit_triangle(obj,cache,a,c,b,au,av,cu,cv,bu,bv,vcount,faces); + else obj_emit_triangle(obj,cache,a,b,c,au,av,bu,bv,cu,cv,vcount,faces); +} + +void emit_tetra_surface(FILE *obj, OBJVERTEXCACHE *cache, int genus, double p[4][3], double val[4], double minx, double maxx, double miny, double maxy, int *vcount, int *faces) +{ + int inside[4], outside[4], ni, no, i; + double q0[3], q1[3], q2[3], q3[3], u0,v0,u1,v1,u2,v2,u3,v3; + + ni=0; no=0; + for (i=0;i<4;i++) + if (val[i]<0.0) { inside[ni]=i; ni++; } + else { outside[no]=i; no++; } + + if ((ni==0) || (ni==4)) return; + + if (ni==1) + { + interp_zero(p[inside[0]],p[outside[0]],val[inside[0]],val[outside[0]],q0); + interp_zero(p[inside[0]],p[outside[1]],val[inside[0]],val[outside[1]],q1); + interp_zero(p[inside[0]],p[outside[2]],val[inside[0]],val[outside[2]],q2); + handle_uv(q0,minx,maxx,miny,maxy,&u0,&v0); + handle_uv(q1,minx,maxx,miny,maxy,&u1,&v1); + handle_uv(q2,minx,maxx,miny,maxy,&u2,&v2); + obj_emit_oriented_handle_triangle(obj,cache,genus,q0,q1,q2,u0,v0,u1,v1,u2,v2,vcount,faces); + } + else if (ni==3) + { + interp_zero(p[outside[0]],p[inside[0]],val[outside[0]],val[inside[0]],q0); + interp_zero(p[outside[0]],p[inside[1]],val[outside[0]],val[inside[1]],q1); + interp_zero(p[outside[0]],p[inside[2]],val[outside[0]],val[inside[2]],q2); + handle_uv(q0,minx,maxx,miny,maxy,&u0,&v0); + handle_uv(q1,minx,maxx,miny,maxy,&u1,&v1); + handle_uv(q2,minx,maxx,miny,maxy,&u2,&v2); + obj_emit_oriented_handle_triangle(obj,cache,genus,q0,q2,q1,u0,v0,u2,v2,u1,v1,vcount,faces); + } + else + { + interp_zero(p[inside[0]],p[outside[0]],val[inside[0]],val[outside[0]],q0); + interp_zero(p[inside[1]],p[outside[0]],val[inside[1]],val[outside[0]],q1); + interp_zero(p[inside[1]],p[outside[1]],val[inside[1]],val[outside[1]],q2); + interp_zero(p[inside[0]],p[outside[1]],val[inside[0]],val[outside[1]],q3); + handle_uv(q0,minx,maxx,miny,maxy,&u0,&v0); + handle_uv(q1,minx,maxx,miny,maxy,&u1,&v1); + handle_uv(q2,minx,maxx,miny,maxy,&u2,&v2); + handle_uv(q3,minx,maxx,miny,maxy,&u3,&v3); + obj_emit_oriented_handle_triangle(obj,cache,genus,q0,q1,q2,u0,v0,u1,v1,u2,v2,vcount,faces); + obj_emit_oriented_handle_triangle(obj,cache,genus,q0,q2,q3,u0,v0,u2,v2,u3,v3,vcount,faces); + } +} + +void write_handle_chain_mesh(FILE *obj, int genus, OBJVERTEXCACHE *cache, int *vcount, int *faces) +{ + int nx, ny, nz, i, j, k, c, t, m; + int tet[6][4]={{0,5,1,6},{0,1,2,6},{0,2,3,6},{0,3,7,6},{0,7,4,6},{0,4,5,6}}; + int ox[8]={0,1,1,0,0,1,1,0}; + int oy[8]={0,0,1,1,0,0,1,1}; + int oz[8]={0,0,0,0,1,1,1,1}; + double major, minor, spacing, margin, minx, maxx, miny, maxy, minz, maxz, dx, dy, dz; + double cube_p[8][3], cube_val[8], tp[4][3], tv[4]; + + major=1.18; + minor=0.34; + spacing=2.55; + margin=0.22; + minx=-(((double)genus)-1.0)*spacing/2.0 - major - minor - margin; + maxx= (((double)genus)-1.0)*spacing/2.0 + major + minor + margin; + miny=-(major+minor+margin); + maxy= (major+minor+margin); + minz=-(minor+margin); + maxz= (minor+margin); + + nx=56+18*genus; + if (nx>176) nx=176; + ny=44; + nz=28; + dx=(maxx-minx)/((double)nx); + dy=(maxy-miny)/((double)ny); + dz=(maxz-minz)/((double)nz); + + for (i=0;i1.0) rho=1.0; + t=theta/(2.0*M_PI); + handle=(int)floor(t*((double)genus)); + if (handle<0) handle=0; + if (handle>=genus) handle=genus-1; + local=(t*((double)genus))-((double)handle); + u=2.0*M_PI*local; + v=2.0*M_PI*rho; + major=1.18; + minor=0.34; + spacing=2.55; + center=(((double)handle)-(((double)genus)-1.0)/2.0)*spacing; + torus_point(center,major,minor,u,v,out); +} + +void project_handle_chain_point(double start[3], int genus, double lift, double out[3]); + +void graph_chain_surface_point(double x, double y, int genus, double lift, double out[3]) +{ + double theta, rho, major, minor, spacing, bridge, half, s, seg, corner, q, alpha, center; + double spx, spy, nx, ny, v, tube, angle; + int h, placed; + + theta=atan2(y,x); + if (theta<0.0) theta += 2.0*M_PI; + rho=sqrt(x*x+y*y)/RADIUS; + if (rho<0.0) rho=0.0; + if (rho>1.0) rho=1.0; + if (rho>0.985) rho=0.985; + + major=1.18; + minor=0.34; + spacing=2.55; + bridge=spacing-2.0*major; + if (bridge<0.05) bridge=0.05; + seg=M_PI*major; + corner=0.5*M_PI*minor; + half=((double)genus)*seg + ((double)(genus-1))*(bridge+2.0*corner); + s=(theta/(2.0*M_PI))*(2.0*half); + placed=0; + + if (s<=half) + { + for (h=0;h1.0) q=1.0; + alpha=M_PI*(1.0-q); + spx=center+major*cos(alpha); + spy=major*sin(alpha); + nx=cos(alpha); + ny=sin(alpha); + placed=1; + break; + } + s-=seg; + if (h1.0) q=1.0; + angle=0.5*M_PI*q; + spx=center+major; + spy=0.0; + nx=cos(angle); + ny=sin(angle); + placed=1; + break; + } + s-=corner; + if (s<=bridge) + { + q=s/bridge; + if (q<0.0) q=0.0; if (q>1.0) q=1.0; + spx=center+major+q*bridge; + spy=0.0; + nx=0.0; + ny=1.0; + placed=1; + break; + } + s-=bridge; + if (s<=corner) + { + q=s/corner; + if (q<0.0) q=0.0; if (q>1.0) q=1.0; + angle=0.5*M_PI+0.5*M_PI*q; + spx=center+major+bridge; + spy=0.0; + nx=cos(angle); + ny=sin(angle); + placed=1; + break; + } + s-=corner; + } + } + } + else + { + s-=half; + for (h=genus-1;h>=0;h--) + { + center=(((double)h)-(((double)genus)-1.0)/2.0)*spacing; + if ((s<=seg) || (h==0)) + { + q=s/seg; + if (q<0.0) q=0.0; if (q>1.0) q=1.0; + alpha=(-M_PI)*q; + spx=center+major*cos(alpha); + spy=major*sin(alpha); + nx=cos(alpha); + ny=sin(alpha); + placed=1; + break; + } + s-=seg; + if (h>0) + { + if (s<=corner) + { + q=s/corner; + if (q<0.0) q=0.0; if (q>1.0) q=1.0; + angle=M_PI+0.5*M_PI*q; + spx=center-major; + spy=0.0; + nx=cos(angle); + ny=sin(angle); + placed=1; + break; + } + s-=corner; + if (s<=bridge) + { + q=s/bridge; + if (q<0.0) q=0.0; if (q>1.0) q=1.0; + spx=center-major-q*bridge; + spy=0.0; + nx=0.0; + ny=-1.0; + placed=1; + break; + } + s-=bridge; + if (s<=corner) + { + q=s/corner; + if (q<0.0) q=0.0; if (q>1.0) q=1.0; + angle=1.5*M_PI+0.5*M_PI*q; + spx=center-major-bridge; + spy=0.0; + nx=cos(angle); + ny=sin(angle); + placed=1; + break; + } + s-=corner; + } + } + } + + if (!placed) + { + center=-(((double)genus)-1.0)*spacing/2.0; + spx=center-major; + spy=0.0; + nx=-1.0; + ny=0.0; + } + + v=2.0*M_PI*rho; + tube=minor+lift; + out[0]=spx+tube*cos(v)*nx; + out[1]=spy+tube*cos(v)*ny; + out[2]=tube*sin(v); +} + +double positive_angle(double angle) +{ + while (angle<0.0) angle += 2.0*M_PI; + while (angle>=2.0*M_PI) angle -= 2.0*M_PI; + return angle; +} + +double smoothstep01(double edge0, double edge1, double x) +{ + double t; + if (edge0==edge1) return (x>=edge1) ? 1.0 : 0.0; + t=(x-edge0)/(edge1-edge0); + if (t<0.0) t=0.0; + if (t>1.0) t=1.0; + return t*t*(3.0-2.0*t); +} + +void polygon_side_uv(int side, double local, int genus, int *handle, double *u, double *vv) +{ + int q; + + if (genus<1) genus=1; + if (side<0) side=0; + if (side>=4*genus) side=(4*genus)-1; + if (local<0.0) local=0.0; + if (local>1.0) local=1.0; + + *handle=side/4; + q=side%4; + if (q==0) { *u=local; *vv=0.0; } + else if (q==1) { *u=1.0; *vv=local; } + else if (q==2) { *u=1.0-local; *vv=1.0; } + else { *u=0.0; *vv=1.0-local; } +} + +void polygon_params_from_coord(double x, double y, int genus, int *side, double *local, double *rho) +{ + int sides; + double alpha, shifted, angle, rawside; + + sides=numberpaths; + if (sides<=0) sides=4*genus; + if (sides<=0) sides=4; + + alpha=positive_angle(-atan2(y,x)-(M_PI/2.0)); + angle=(2.0*M_PI)/((double)sides); + shifted=positive_angle(alpha-(angle/2.0)); + rawside=shifted/angle; + *side=(int)floor(rawside); + if (*side>=sides) *side=sides-1; + if (*side<0) *side=0; + *local=rawside-((double)(*side)); + if (*local<0.0) *local=0.0; + if (*local>1.0) *local=1.0; + *rho=sqrt(x*x+y*y)/RADIUS; + if (*rho<0.0) *rho=0.0; + if (*rho>1.0) *rho=1.0; +} + +void polygon_params_for_vertex(int vertex, double x, double y, int genus, int *side, double *local, double *rho) +{ + if ((genus>0) && (vertex>0) && (vertex<=N) && (boundary_side[vertex]>=0)) + { + *side=boundary_side[vertex]; + *local=boundary_t[vertex]; + if (*local<0.0) *local=0.0; + if (*local>1.0) *local=1.0; + *rho=1.0; + return; + } + polygon_params_from_coord(x,y,genus,side,local,rho); +} + +void polygon_surface_point(int side, double local, double rho, int genus, double lift, double out[3]) +{ + double ub, vb, u, vv, major, minor, spacing, center, start[3], grad[3]; + double chain[3], centerpoint[3], paired[3], blend[3], alpha, angle, corner, weight, center_weight, radial_weight, corner_weight, x, y; + int sides; + int handle; + + if (rho<0.0) rho=0.0; + if (rho>1.0) rho=1.0; + polygon_side_uv(side,local,genus,&handle,&ub,&vb); + u=0.5*(1.0-rho)+rho*ub; + vv=0.5*(1.0-rho)+rho*vb; + + if (genus<=1) + { + major=1.25; + minor=0.38; + center=0.0; + torus_point(center,major,minor,2.0*M_PI*u,2.0*M_PI*vv,out); + grad[0]=cos(2.0*M_PI*vv)*cos(2.0*M_PI*u); + grad[1]=cos(2.0*M_PI*vv)*sin(2.0*M_PI*u); + grad[2]=sin(2.0*M_PI*vv); + normalize3(grad); + out[0]+=lift*grad[0]; out[1]+=lift*grad[1]; out[2]+=lift*grad[2]; + return; + } + + if (handle<0) handle=0; + if (handle>=genus) handle=genus-1; + major=1.18; + minor=0.34; + spacing=2.55; + center=(((double)handle)-(((double)genus)-1.0)/2.0)*spacing; + torus_point(center,major,minor,2.0*M_PI*u,2.0*M_PI*vv,start); + project_handle_chain_point(start,genus,lift,paired); + + sides=numberpaths; + if (sides<=0) sides=4*genus; + if (sides<=0) sides=4; + angle=(2.0*M_PI)/((double)sides); + alpha=angle/2.0 + (((double)side)+local)*angle; + x=(-RADIUS*rho*sin(alpha)); + y=(-RADIUS*rho*cos(alpha)); + graph_chain_surface_point(x,y,genus,lift,chain); + graph_chain_surface_point(RADIUS*0.001,0.0,genus,lift,centerpoint); + center_weight=1.0-smoothstep01(0.05,0.22,rho); + chain[0]=centerpoint[0]*center_weight+chain[0]*(1.0-center_weight); + chain[1]=centerpoint[1]*center_weight+chain[1]*(1.0-center_weight); + chain[2]=centerpoint[2]*center_weight+chain[2]*(1.0-center_weight); + + corner=local; + if ((1.0-local)=2.0*M_PI) d-=2.0*M_PI; + return d; +} + +int circle_through_points(double ax, double ay, double bx, double by, double cx, double cy, double *ox, double *oy) +{ + double d, aa, bb, cc; + d=2.0*(ax*(by-cy)+bx*(cy-ay)+cx*(ay-by)); + if (fabs(d)<1e-9) return 0; + aa=ax*ax+ay*ay; + bb=bx*bx+by*by; + cc=cx*cx+cy*cy; + *ox=(aa*(by-cy)+bb*(cy-ay)+cc*(ay-by))/d; + *oy=(aa*(cx-bx)+bb*(ax-cx)+cc*(bx-ax))/d; + return 1; +} + +void emit_graph_segment(FILE *obj, double coord[][2], int v, int w, int genus, double lift, int *vcount, int *linecount) +{ + int s, samples, idx, emit_count, lineindices[20000], use_arc; + double x0,y0,x1,y1,dx,dy,length,t,p[3],px,py,mx,my,ox,oy,r,a0,am,a1,delta,dm; + + x0=coord[v][0]; y0=coord[v][1]; + x1=coord[w][0]; y1=coord[w][1]; + dx=x1-x0; dy=y1-y0; + length=sqrt(dx*dx+dy*dy); + samples=(int)(length/1.25)+24; + if (genus>=2) samples*=8; + if (samples<48) samples=48; + if (samples>16384) samples=16384; + + use_arc=0; + if ((type[v]==1) && (type[w]==1) && (length<=(RADIUS/1.5))) + { + mx=(x0+x1)*0.47; + my=(y0+y1)*0.47; + if (circle_through_points(x0,y0,mx,my,x1,y1,&ox,&oy)) + { + r=sqrt((x0-ox)*(x0-ox)+(y0-oy)*(y0-oy)); + a0=atan2(y0-oy,x0-ox); + am=atan2(my-oy,mx-ox); + a1=atan2(y1-oy,x1-ox); + delta=normalized_delta(a0,a1); + dm=normalized_delta(a0,am); + if (dm>delta) delta-=2.0*M_PI; + use_arc=1; + } + } + + emit_count=0; + for (s=0;s<=samples;s++) + { + t=((double)s)/((double)samples); + if (use_arc) + { + px=ox+r*cos(a0+t*delta); + py=oy+r*sin(a0+t*delta); + } + else + { + px=x0+t*dx; + py=y0+t*dy; + } + if (s==0) graph_surface_vertex_point(v,px,py,genus,lift,p); + else if (s==samples) graph_surface_vertex_point(w,px,py,genus,lift,p); + else graph_surface_point(px,py,genus,lift,p); + idx=obj_emit_line_vertex(obj,p,vcount); + if (emit_count>=20000) { fprintf(stderr,"OBJ graph line too long -- exit.\n"); exit(1); } + lineindices[emit_count++]=idx; + } + + fprintf(obj,"l"); + for (s=0;snext) + if ((run->ursprungname) && (run->cyclenumber==0) && + (type[run->ursprung]!=3) && (type[run->name]!=3)) + { + v=run->ursprung; + w=run->name; + fprintf(obj,"# graph_edge %d %d segment %d %d type %d %d coord %.8f %.8f %.8f %.8f\n", + (run->ends)[0],(run->ends)[1],v,w,type[v],type[w],coord[v][0],coord[v][1],coord[w][0],coord[w][1]); + emit_graph_segment(obj,coord,v,w,genus,lift,vcount,linecount); + } + } + + fprintf(obj,"g embedded_graph_vertices\n"); + for (i=1;i<=nv;i++) + if ((i<=nullvertices) && (type[i]!=3)) + { + graph_surface_vertex_point(i,coord[i][0],coord[i][1],genus,lift,p); + graph_surface_vertex_point(i,coord[i][0],coord[i][1],genus,label_lift,labelp); + idx=obj_emit_line_vertex(obj,p,vcount); + fprintf(obj,"# graph_vertex_label %d %d %.8f %.8f %.8f\n",idx,i,labelp[0],labelp[1],labelp[2]); + fprintf(obj,"p %d\n",idx); + (*pointcount)++; + } +} + +void write_obj(double coord[][2]) +{ + FILE *obj, *mtl; + char basename[1024], objname[1100], mtlname[1100], mtlbase[1100]; + char *leaf; + int genus, faces, vcount, linecount, pointcount; + double minx,maxx,miny,maxy; + OBJVERTEXCACHE cache; + + genus=globalgenus; + texture_bounds(coord,&minx,&maxx,&miny,&maxy); + + objdrawings++; + if (objdrawings==1) snprintf(basename,sizeof(basename),"%s",objprefix); + else snprintf(basename,sizeof(basename),"%s_%d",objprefix,objdrawings); + snprintf(objname,sizeof(objname),"%s.obj",basename); + snprintf(mtlname,sizeof(mtlname),"%s.mtl",basename); + leaf=strrchr(basename,'/'); + if (leaf) leaf++; + else leaf=basename; + snprintf(mtlbase,sizeof(mtlbase),"%s.mtl",leaf); + + mtl=fopen(mtlname,"w"); + if (mtl==NULL) { fprintf(stderr,"Can't open material file %s -- exit.\n",mtlname); exit(1); } + fprintf(mtl,"newmtl graph_surface\nKd 0.780 0.790 0.780\nKa 0.180 0.180 0.180\nKs 0.080 0.080 0.080\nNs 20\n"); + fclose(mtl); + + obj=fopen(objname,"w"); + if (obj==NULL) { fprintf(stderr,"Can't open OBJ file %s -- exit.\n",objname); exit(1); } + fprintf(obj,"# canonical handle surface generated by planar_cutthroughedges_draw\n"); + fprintf(obj,"# genus %d; genus 0 is a sphere, genus 1 is a torus, genus >=2 is a thickened canonical loop chain\n",genus); + fprintf(obj,"mtllib %s\n",mtlbase); + fprintf(obj,"o canonical_handles_%d\n",objdrawings); + vcount=0; + faces=0; + obj_cache_init(&cache,(genus>=2) ? 524288U : 131072U); + fprintf(obj,"usemtl graph_surface\ns 1\n"); + if (genus<=0) write_sphere_mesh(obj,&cache,&vcount,&faces); + else if (genus==1) write_torus_mesh(obj,genus,&cache,&vcount,&faces); + else write_handle_chain_mesh(obj,genus,&cache,&vcount,&faces); + write_graph_overlay(obj,coord,genus,&vcount,&linecount,&pointcount); + + fclose(obj); + obj_cache_free(&cache); + fprintf(stderr,"Wrote OBJ surface %s with %d vertices, %d triangular faces, %d graph polylines, and %d graph points.\n",objname,vcount,faces,linecount,pointcount); +} + void output_pl(double coord[][2], KANTE *outer, int writeouterface) // starttop_t0>0 means that a vertex of the original graph is the common point of all cutting cycles { @@ -1473,6 +2701,8 @@ void output_pl(double coord[][2], KANTE *outer, int writeouterface) double scale0, mindistance, length, ve[2]; int realvertices[N], numberrealvertices; + if (objprefix) { write_obj(coord); return; } + if (!writeouterface) for (i=1; i<=nv; i++) if (type[i]==2) type[i]=3; mindistance = RADIUS; @@ -1560,6 +2790,8 @@ void output(double coord[][2]) char *centercolour; double labelmove=1.05, hoekmove=1.0; + if (objprefix) { write_obj(coord); return; } + if (straight) { if (globalgenus==1) { if (starttop_t0) hoekmove=0.95; else hoekmove=0.97; } else hoekmove=0.99; @@ -1727,11 +2959,11 @@ void output(double coord[][2]) fprintf(stdout,"\\tkzDefPoint(%3.5lf,%3.5lf){A}\n",c[0]*hoekmove, c[1]*hoekmove ); rotate_clockwise_to(c,coord[run2->name],-rot_angle); fprintf(stdout,"\\tkzDefPoint(%3.5lf,%3.5lf){B}\n",c[0]*hoekmove, c[1]*hoekmove); - if (straight) fprintf(stdout,"\\draw[->,line width=0.9mm, gray](A) to (B);\n"); + if (straight) fprintf(stdout,"\\draw[->,line width=0.9mm, %s](A) to (B);\n",cyclecolour(run->cyclenumber)); else { fprintf(stdout,"\\tkzDefPoint(0.0,0.0){C}\n"); - fprintf(stdout,"\\tkzDrawArc[->,line width=0.9mm, gray](C,B)(A)\n"); + fprintf(stdout,"\\tkzDrawArc[->,line width=0.9mm, %s](C,B)(A)\n",cyclecolour(run->cyclenumber)); } } else @@ -1741,26 +2973,26 @@ void output(double coord[][2]) fprintf(stdout,"\\tkzDefPoint(%3.5lf,%3.5lf){A}\n",c[0]*hoekmove, c[1]*hoekmove ); rotate_clockwise_to(c,coord[run2->name],-rot_angle); fprintf(stdout,"\\tkzDefPoint(%3.5lf,%3.5lf){B}\n",c[0]*hoekmove, c[1]*hoekmove); - if (straight) fprintf(stdout,"\\draw[<-,line width=0.9mm, gray](A) to (B);\n"); + if (straight) fprintf(stdout,"\\draw[<-,line width=0.9mm, %s](A) to (B);\n",cyclecolour(run->cyclenumber)); else { fprintf(stdout,"\\tkzDefPoint(0.0,0.0){C}\n"); - fprintf(stdout,"\\tkzDrawArc[<-,line width=0.9mm, gray](C,B)(A)\n"); + fprintf(stdout,"\\tkzDrawArc[<-,line width=0.9mm, %s](C,B)(A)\n",cyclecolour(run->cyclenumber)); } } if (straight) { rotate_clockwise_to(c,coord[run->ursprung],(M_PI)/((double)(numcycles))); - if (labels) fprintf(stdout,"\\node [draw=none,fill=none,scale=%1.2lf] () at (%3.5lf,%3.5lf) {%c};\n", - scale3,(c[0]+coord[run->ursprung][0])*0.6,(c[1]+coord[run->ursprung][1])*0.59,'A'-1+abs(run->cyclenumber)); - else fprintf(stdout,"\\node [draw=none,fill=none,scale=%1.2lf] () at (%3.5lf,%3.5lf) {%c};\n", - scale3,(c[0]+coord[run->ursprung][0])*0.56,(c[1]+coord[run->ursprung][1])*0.55,'A'-1+abs(run->cyclenumber)); + if (labels) fprintf(stdout,"\\node [draw=none,fill=none,scale=%1.2lf] () at (%3.5lf,%3.5lf) {%s};\n", + scale3,(c[0]+coord[run->ursprung][0])*0.6,(c[1]+coord[run->ursprung][1])*0.59,cyclelabel(run->cyclenumber)); + else fprintf(stdout,"\\node [draw=none,fill=none,scale=%1.2lf] () at (%3.5lf,%3.5lf) {%s};\n", + scale3,(c[0]+coord[run->ursprung][0])*0.56,(c[1]+coord[run->ursprung][1])*0.55,cyclelabel(run->cyclenumber)); } else { rotate_clockwise_to(c,coord[run->ursprung],(M_PI)/((double)(2*numcycles))); - if (labels) fprintf(stdout,"\\node [draw=none,fill=none,scale=%1.2lf] () at (%3.5lf,%3.5lf) {%c};\n",scale3,c[0]*1.15,c[1]*1.15,'A'-1+abs(run->cyclenumber)); - else fprintf(stdout,"\\node [draw=none,fill=none,scale=%1.2lf] () at (%3.5lf,%3.5lf) {%c};\n",scale3,c[0]*1.06,c[1]*1.06,'A'-1+abs(run->cyclenumber)); + if (labels) fprintf(stdout,"\\node [draw=none,fill=none,scale=%1.2lf] () at (%3.5lf,%3.5lf) {%s};\n",scale3,c[0]*1.15,c[1]*1.15,cyclelabel(run->cyclenumber)); + else fprintf(stdout,"\\node [draw=none,fill=none,scale=%1.2lf] () at (%3.5lf,%3.5lf) {%s};\n",scale3,c[0]*1.06,c[1]*1.06,cyclelabel(run->cyclenumber)); } run=run2->invers->next; } @@ -2300,12 +3532,19 @@ void embed() { KANTE *run, *nextstart; - int i, j, numberpaths, cycn, top, newtop; + int i, j, cycn, top, newtop; int lengthpath[4*MAXGENUS]; KANTE *startsegment[4*MAXGENUS]; double coordinates[N+1][2]={{0.0}}, angle; // angle between two corners double secondcoordinates[2]={0.0}, diff[2]; + for (i=0;i<=N;i++) + { + boundary_side[i]=(-1); + boundary_cyc[i]=0; + boundary_t[i]=0.0; + } + //first look for the boundary if (starttop_t0==0) { @@ -2355,6 +3594,9 @@ void embed() { run=startsegment[i]; top=(run->ursprung); + boundary_side[top]=i; + boundary_cyc[top]=run->cyclenumber; + boundary_t[top]=0.0; rotate_clockwise_to(coordinates[top],coordinates[0],((double)i)*angle+(angle/2.0)); rotate_clockwise_to(secondcoordinates,coordinates[0],((double)(i+1))*angle+(angle/2.0)); diff[0]=secondcoordinates[0]-coordinates[top][0]; @@ -2362,12 +3604,18 @@ void embed() if (straight) for (j=1; jinvers->next) { newtop=run->name; + boundary_side[newtop]=i; + boundary_cyc[newtop]=run->cyclenumber; + boundary_t[newtop]=((double)j)/((double)lengthpath[i]); coordinates[newtop][0]=coordinates[top][0]+((double)j/lengthpath[i])*diff[0]; coordinates[newtop][1]=coordinates[top][1]+((double)j/lengthpath[i])*diff[1]; } else for (j=1; jinvers->next) { newtop=run->name; + boundary_side[newtop]=i; + boundary_cyc[newtop]=run->cyclenumber; + boundary_t[newtop]=((double)j)/((double)lengthpath[i]); coordinates[newtop][0]=coordinates[top][0]+((double)j/lengthpath[i])*diff[0]; coordinates[newtop][1]=coordinates[top][1]+((double)j/lengthpath[i])*diff[1]; rotate_clockwise_to(coordinates[newtop],coordinates[top],((double)j)*(angle/((double)lengthpath[i]))); @@ -2479,7 +3727,7 @@ void embed_planar() void usage(char str[]) { - fprintf(stderr,"\nusage %s (v,f) [b] [mx] [n] [l] [mx] [cv x] [cf x y] [d x col] [N x y] [s] [t]\n",str); + fprintf(stderr,"\nusage %s (v,f) [b] [mx] [n] [l] [mx] [cv x] [cf x y] [d x col] [N x y] [s] [t] [o prefix]\n",str); fprintf(stderr,"Only for connected embedded graphs numbered from 1...|V|.\n"); fprintf(stderr,"The embedded input graph is cut (if genus>0) to form a plane representation and a drawing as tikz in a latex file is written to stdout.\n\n"); fprintf(stderr,"In case of genus>0 at least one of the options v and f must be present. \n"); @@ -2487,7 +3735,7 @@ void usage(char str[]) fprintf(stderr,"Option f: take a point inside a face as the common point of the cutting cycles.\n"); fprintf(stderr,"In case both options are given, two drawings of each input graph are produced -- one with face center, one with vertex center.\n\n"); fprintf(stderr,"Option b: for black and white -- use labels A, B, C for the edges to be identified instead of colours (default).\n"); - fprintf(stderr," \t For genus 6 or larger this is done automatically as colours would be hard to distinguish.\n\n"); + fprintf(stderr," \t For genus 6 or larger labels are added automatically, but colours are still used.\n\n"); fprintf(stderr,"Option n: Do not give vertex numbers, but just draw black dots.\n\n"); fprintf(stderr,"Option l: Write small labels at the boundary -- indicating where edges crossing the boundary will finally go to.\n\n"); fprintf(stderr,"Option: mx: (with x a number) first look only for cuts that never cut the same edge twice -- in the drawing no edge of the graph crosses the boundary twice.\n"); @@ -2500,10 +3748,11 @@ void usage(char str[]) fprintf(stderr,"\t In case of genus 0 the face described is taken as the outer face.\n"); fprintf(stderr,"\t Without this option or if there is no such edge in the graph, the program chooses itself.\n"); fprintf(stderr,"Option d x col: with x a number and col a colour known to tikz, so e.g. blue, red, green. In the output, vertices with degree x get colour col.\n"); - fprintf(stderr,"Option N x y: with x,y numbers. Do not cut through edge {x,y} if present. This option can be used for several edges. If all edges of a face are chosen, it must be made sure\n"); - fprintf(stderr,"\t that this face is not chosen as the outer face by cf or v. Note that even then it is possible that a solution is hard to find or doesn't exist.\n"); - fprintf(stderr,"Option s makes the program use straight line segments for the boundary, so the outer face will be a polygon instead of a circle.\n"); - fprintf(stderr,"Option t makes the program interpret the input not as binary input of planarcode type, but as the ASCII version of it.\n"); + fprintf(stderr,"Option N x y: with x,y numbers. Do not cut through edge {x,y} if present. This option can be used for several edges. If all edges of a face are chosen, it must be made sure\n"); + fprintf(stderr,"\t that this face is not chosen as the outer face by cf or v. Note that even then it is possible that a solution is hard to find or doesn't exist.\n"); + fprintf(stderr,"Option s makes the program use straight line segments for the boundary, so the outer face will be a polygon instead of a circle.\n"); + fprintf(stderr,"Option t makes the program interpret the input not as binary input of planarcode type, but as the ASCII version of it.\n"); + fprintf(stderr,"Option o prefix writes prefix.obj, prefix.mtl, and prefix.ppm as a textured canonical-handle OBJ export instead of writing LaTeX to stdout.\n"); exit(1); } @@ -2554,13 +3803,14 @@ int main(int argc, char *argv[]) { if (argv[i][0]=='m') { maxcross=atoi(argv[i]+1); } else if (argv[i][0]=='n') { drawvertexnumbers=0;} - else if (argv[i][0]=='b') { lblackwhite=1; } + else if (argv[i][0]=='b') { lblackwhite=1; forceblackwhite=1; } else if (argv[i][0]=='f') facestart=1; else if (argv[i][0]=='v') vertexstart=1; else if (argv[i][0]=='p') progress=1; else if (argv[i][0]=='s') straight=1; else if (argv[i][0]=='l') labels=1; else if (argv[i][0]=='t') text=1; + else if (argv[i][0]=='o') { i++; if (i>=argc) usage(argv[0]); objprefix=argv[i]; } else if (argv[i][0]=='c') { if (argv[i][1]=='v') {i++; chosenvertex=atoi(argv[i]); } else if (argv[i][1]=='f') {i++; chosenedge[0]=atoi(argv[i]); i++; chosenedge[1]=atoi(argv[i]); } @@ -2648,12 +3898,10 @@ for (;lesecode(code,&lauf,stdin);) } } } - fprintf(stdout,"\\end{document}\n"); + if (!objprefix) fprintf(stdout,"\\end{document}\n"); - fprintf(stderr,"%s: Wrote %d tikz-drawing(s) of %d graph(s) to stdout.\n",argv[0],drawings,zaehlen); + if (objprefix) fprintf(stderr,"%s: Wrote %d OBJ drawing(s) of %d graph(s).\n",argv[0],drawings,zaehlen); + else fprintf(stderr,"%s: Wrote %d tikz-drawing(s) of %d graph(s) to stdout.\n",argv[0],drawings,zaehlen); return(0); } - - - diff --git a/CalcGenus/adjacency_lists/3-10-cage1.txt b/PAGE/adjacency_lists/3-10-cage1.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-10-cage1.txt rename to PAGE/adjacency_lists/3-10-cage1.txt diff --git a/CalcGenus/adjacency_lists/3-10-cage2.txt b/PAGE/adjacency_lists/3-10-cage2.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-10-cage2.txt rename to PAGE/adjacency_lists/3-10-cage2.txt diff --git a/CalcGenus/adjacency_lists/3-10-cage3.txt b/PAGE/adjacency_lists/3-10-cage3.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-10-cage3.txt rename to PAGE/adjacency_lists/3-10-cage3.txt diff --git a/CalcGenus/adjacency_lists/3-11-cage.txt b/PAGE/adjacency_lists/3-11-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-11-cage.txt rename to PAGE/adjacency_lists/3-11-cage.txt diff --git a/CalcGenus/adjacency_lists/3-12-cage.txt b/PAGE/adjacency_lists/3-12-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-12-cage.txt rename to PAGE/adjacency_lists/3-12-cage.txt diff --git a/CalcGenus/adjacency_lists/3-3-cage.txt b/PAGE/adjacency_lists/3-3-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-3-cage.txt rename to PAGE/adjacency_lists/3-3-cage.txt diff --git a/CalcGenus/adjacency_lists/3-4-cage.txt b/PAGE/adjacency_lists/3-4-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-4-cage.txt rename to PAGE/adjacency_lists/3-4-cage.txt diff --git a/CalcGenus/adjacency_lists/3-5-cage.txt b/PAGE/adjacency_lists/3-5-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-5-cage.txt rename to PAGE/adjacency_lists/3-5-cage.txt diff --git a/CalcGenus/adjacency_lists/3-6-cage.txt b/PAGE/adjacency_lists/3-6-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-6-cage.txt rename to PAGE/adjacency_lists/3-6-cage.txt diff --git a/CalcGenus/adjacency_lists/3-7-cage.txt b/PAGE/adjacency_lists/3-7-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-7-cage.txt rename to PAGE/adjacency_lists/3-7-cage.txt diff --git a/CalcGenus/adjacency_lists/3-8-cage.txt b/PAGE/adjacency_lists/3-8-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-8-cage.txt rename to PAGE/adjacency_lists/3-8-cage.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage1.txt b/PAGE/adjacency_lists/3-9-cage1.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage1.txt rename to PAGE/adjacency_lists/3-9-cage1.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage10.txt b/PAGE/adjacency_lists/3-9-cage10.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage10.txt rename to PAGE/adjacency_lists/3-9-cage10.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage11.txt b/PAGE/adjacency_lists/3-9-cage11.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage11.txt rename to PAGE/adjacency_lists/3-9-cage11.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage12.txt b/PAGE/adjacency_lists/3-9-cage12.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage12.txt rename to PAGE/adjacency_lists/3-9-cage12.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage13.txt b/PAGE/adjacency_lists/3-9-cage13.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage13.txt rename to PAGE/adjacency_lists/3-9-cage13.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage14.txt b/PAGE/adjacency_lists/3-9-cage14.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage14.txt rename to PAGE/adjacency_lists/3-9-cage14.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage15.txt b/PAGE/adjacency_lists/3-9-cage15.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage15.txt rename to PAGE/adjacency_lists/3-9-cage15.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage16.txt b/PAGE/adjacency_lists/3-9-cage16.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage16.txt rename to PAGE/adjacency_lists/3-9-cage16.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage17.txt b/PAGE/adjacency_lists/3-9-cage17.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage17.txt rename to PAGE/adjacency_lists/3-9-cage17.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage18.txt b/PAGE/adjacency_lists/3-9-cage18.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage18.txt rename to PAGE/adjacency_lists/3-9-cage18.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage2.txt b/PAGE/adjacency_lists/3-9-cage2.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage2.txt rename to PAGE/adjacency_lists/3-9-cage2.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage3.txt b/PAGE/adjacency_lists/3-9-cage3.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage3.txt rename to PAGE/adjacency_lists/3-9-cage3.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage4.txt b/PAGE/adjacency_lists/3-9-cage4.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage4.txt rename to PAGE/adjacency_lists/3-9-cage4.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage5.txt b/PAGE/adjacency_lists/3-9-cage5.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage5.txt rename to PAGE/adjacency_lists/3-9-cage5.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage6.txt b/PAGE/adjacency_lists/3-9-cage6.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage6.txt rename to PAGE/adjacency_lists/3-9-cage6.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage7.txt b/PAGE/adjacency_lists/3-9-cage7.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage7.txt rename to PAGE/adjacency_lists/3-9-cage7.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage8.txt b/PAGE/adjacency_lists/3-9-cage8.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage8.txt rename to PAGE/adjacency_lists/3-9-cage8.txt diff --git a/CalcGenus/adjacency_lists/3-9-cage9.txt b/PAGE/adjacency_lists/3-9-cage9.txt similarity index 100% rename from CalcGenus/adjacency_lists/3-9-cage9.txt rename to PAGE/adjacency_lists/3-9-cage9.txt diff --git a/CalcGenus/adjacency_lists/4-12-cage1.txt b/PAGE/adjacency_lists/4-12-cage1.txt similarity index 100% rename from CalcGenus/adjacency_lists/4-12-cage1.txt rename to PAGE/adjacency_lists/4-12-cage1.txt diff --git a/CalcGenus/adjacency_lists/4-5-cage.txt b/PAGE/adjacency_lists/4-5-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/4-5-cage.txt rename to PAGE/adjacency_lists/4-5-cage.txt diff --git a/CalcGenus/adjacency_lists/4-6-cage.txt b/PAGE/adjacency_lists/4-6-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/4-6-cage.txt rename to PAGE/adjacency_lists/4-6-cage.txt diff --git a/CalcGenus/adjacency_lists/4-7-cage1.txt b/PAGE/adjacency_lists/4-7-cage1.txt similarity index 100% rename from CalcGenus/adjacency_lists/4-7-cage1.txt rename to PAGE/adjacency_lists/4-7-cage1.txt diff --git a/CalcGenus/adjacency_lists/4-8-cage.txt b/PAGE/adjacency_lists/4-8-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/4-8-cage.txt rename to PAGE/adjacency_lists/4-8-cage.txt diff --git a/CalcGenus/adjacency_lists/5-12-cage1.txt b/PAGE/adjacency_lists/5-12-cage1.txt similarity index 100% rename from CalcGenus/adjacency_lists/5-12-cage1.txt rename to PAGE/adjacency_lists/5-12-cage1.txt diff --git a/CalcGenus/adjacency_lists/5-5-cage1.txt b/PAGE/adjacency_lists/5-5-cage1.txt similarity index 100% rename from CalcGenus/adjacency_lists/5-5-cage1.txt rename to PAGE/adjacency_lists/5-5-cage1.txt diff --git a/CalcGenus/adjacency_lists/5-5-cage2.txt b/PAGE/adjacency_lists/5-5-cage2.txt similarity index 100% rename from CalcGenus/adjacency_lists/5-5-cage2.txt rename to PAGE/adjacency_lists/5-5-cage2.txt diff --git a/CalcGenus/adjacency_lists/5-5-cage3.txt b/PAGE/adjacency_lists/5-5-cage3.txt similarity index 100% rename from CalcGenus/adjacency_lists/5-5-cage3.txt rename to PAGE/adjacency_lists/5-5-cage3.txt diff --git a/CalcGenus/adjacency_lists/5-5-cage4.txt b/PAGE/adjacency_lists/5-5-cage4.txt similarity index 100% rename from CalcGenus/adjacency_lists/5-5-cage4.txt rename to PAGE/adjacency_lists/5-5-cage4.txt diff --git a/CalcGenus/adjacency_lists/5-6-cage.txt b/PAGE/adjacency_lists/5-6-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/5-6-cage.txt rename to PAGE/adjacency_lists/5-6-cage.txt diff --git a/CalcGenus/adjacency_lists/5-8-cage.txt b/PAGE/adjacency_lists/5-8-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/5-8-cage.txt rename to PAGE/adjacency_lists/5-8-cage.txt diff --git a/CalcGenus/adjacency_lists/6-12-cage1.txt b/PAGE/adjacency_lists/6-12-cage1.txt similarity index 100% rename from CalcGenus/adjacency_lists/6-12-cage1.txt rename to PAGE/adjacency_lists/6-12-cage1.txt diff --git a/CalcGenus/adjacency_lists/6-5-cage.txt b/PAGE/adjacency_lists/6-5-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/6-5-cage.txt rename to PAGE/adjacency_lists/6-5-cage.txt diff --git a/CalcGenus/adjacency_lists/6-6-cage.txt b/PAGE/adjacency_lists/6-6-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/6-6-cage.txt rename to PAGE/adjacency_lists/6-6-cage.txt diff --git a/CalcGenus/adjacency_lists/6-8-cage.txt b/PAGE/adjacency_lists/6-8-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/6-8-cage.txt rename to PAGE/adjacency_lists/6-8-cage.txt diff --git a/CalcGenus/adjacency_lists/7-5-cage.txt b/PAGE/adjacency_lists/7-5-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/7-5-cage.txt rename to PAGE/adjacency_lists/7-5-cage.txt diff --git a/CalcGenus/adjacency_lists/7-6-cage.txt b/PAGE/adjacency_lists/7-6-cage.txt similarity index 100% rename from CalcGenus/adjacency_lists/7-6-cage.txt rename to PAGE/adjacency_lists/7-6-cage.txt diff --git a/CalcGenus/adjacency_lists/Circulant10_1-2-4-5.txt b/PAGE/adjacency_lists/Circulant10_1-2-4-5.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant10_1-2-4-5.txt rename to PAGE/adjacency_lists/Circulant10_1-2-4-5.txt diff --git a/CalcGenus/adjacency_lists/Circulant10_1-2-5.txt b/PAGE/adjacency_lists/Circulant10_1-2-5.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant10_1-2-5.txt rename to PAGE/adjacency_lists/Circulant10_1-2-5.txt diff --git a/CalcGenus/adjacency_lists/Circulant14_1-2-3-6.txt b/PAGE/adjacency_lists/Circulant14_1-2-3-6.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant14_1-2-3-6.txt rename to PAGE/adjacency_lists/Circulant14_1-2-3-6.txt diff --git a/CalcGenus/adjacency_lists/Circulant15_1-5.txt b/PAGE/adjacency_lists/Circulant15_1-5.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant15_1-5.txt rename to PAGE/adjacency_lists/Circulant15_1-5.txt diff --git a/CalcGenus/adjacency_lists/Circulant16_1-7.txt b/PAGE/adjacency_lists/Circulant16_1-7.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant16_1-7.txt rename to PAGE/adjacency_lists/Circulant16_1-7.txt diff --git a/CalcGenus/adjacency_lists/Circulant18_1-3-9.txt b/PAGE/adjacency_lists/Circulant18_1-3-9.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant18_1-3-9.txt rename to PAGE/adjacency_lists/Circulant18_1-3-9.txt diff --git a/CalcGenus/adjacency_lists/Circulant20_1-3-5-7-9-10.txt b/PAGE/adjacency_lists/Circulant20_1-3-5-7-9-10.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant20_1-3-5-7-9-10.txt rename to PAGE/adjacency_lists/Circulant20_1-3-5-7-9-10.txt diff --git a/CalcGenus/adjacency_lists/Circulant20_1-3-5.txt b/PAGE/adjacency_lists/Circulant20_1-3-5.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant20_1-3-5.txt rename to PAGE/adjacency_lists/Circulant20_1-3-5.txt diff --git a/CalcGenus/adjacency_lists/Circulant20_1-6-9.txt b/PAGE/adjacency_lists/Circulant20_1-6-9.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant20_1-6-9.txt rename to PAGE/adjacency_lists/Circulant20_1-6-9.txt diff --git a/CalcGenus/adjacency_lists/Circulant21_1-4-5.txt b/PAGE/adjacency_lists/Circulant21_1-4-5.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant21_1-4-5.txt rename to PAGE/adjacency_lists/Circulant21_1-4-5.txt diff --git a/CalcGenus/adjacency_lists/Circulant26_1-3-9.txt b/PAGE/adjacency_lists/Circulant26_1-3-9.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant26_1-3-9.txt rename to PAGE/adjacency_lists/Circulant26_1-3-9.txt diff --git a/CalcGenus/adjacency_lists/Circulant30_1-4-11-14.txt b/PAGE/adjacency_lists/Circulant30_1-4-11-14.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant30_1-4-11-14.txt rename to PAGE/adjacency_lists/Circulant30_1-4-11-14.txt diff --git a/CalcGenus/adjacency_lists/Circulant30_1-9-11.txt b/PAGE/adjacency_lists/Circulant30_1-9-11.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant30_1-9-11.txt rename to PAGE/adjacency_lists/Circulant30_1-9-11.txt diff --git a/CalcGenus/adjacency_lists/Circulant31_1-5-6.txt b/PAGE/adjacency_lists/Circulant31_1-5-6.txt similarity index 100% rename from CalcGenus/adjacency_lists/Circulant31_1-5-6.txt rename to PAGE/adjacency_lists/Circulant31_1-5-6.txt diff --git a/CalcGenus/adjacency_lists/Cyclotomic16.txt b/PAGE/adjacency_lists/Cyclotomic16.txt similarity index 100% rename from CalcGenus/adjacency_lists/Cyclotomic16.txt rename to PAGE/adjacency_lists/Cyclotomic16.txt diff --git a/CalcGenus/adjacency_lists/Cyclotomic19.txt b/PAGE/adjacency_lists/Cyclotomic19.txt similarity index 100% rename from CalcGenus/adjacency_lists/Cyclotomic19.txt rename to PAGE/adjacency_lists/Cyclotomic19.txt diff --git a/CalcGenus/adjacency_lists/Cyclotomic31.txt b/PAGE/adjacency_lists/Cyclotomic31.txt similarity index 100% rename from CalcGenus/adjacency_lists/Cyclotomic31.txt rename to PAGE/adjacency_lists/Cyclotomic31.txt diff --git a/CalcGenus/adjacency_lists/Cyclotomic37.txt b/PAGE/adjacency_lists/Cyclotomic37.txt similarity 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to PAGE/adjacency_lists/DifferenceSetIncidence11-5-2.txt diff --git a/CalcGenus/adjacency_lists/DifferenceSetIncidence11-6-3.txt b/PAGE/adjacency_lists/DifferenceSetIncidence11-6-3.txt similarity index 100% rename from CalcGenus/adjacency_lists/DifferenceSetIncidence11-6-3.txt rename to PAGE/adjacency_lists/DifferenceSetIncidence11-6-3.txt diff --git a/CalcGenus/adjacency_lists/DifferenceSetIncidence35-17-8.txt b/PAGE/adjacency_lists/DifferenceSetIncidence35-17-8.txt similarity index 100% rename from CalcGenus/adjacency_lists/DifferenceSetIncidence35-17-8.txt rename to PAGE/adjacency_lists/DifferenceSetIncidence35-17-8.txt diff --git a/CalcGenus/adjacency_lists/DifferenceSetIncidence40-13-4.txt b/PAGE/adjacency_lists/DifferenceSetIncidence40-13-4.txt similarity index 100% rename from CalcGenus/adjacency_lists/DifferenceSetIncidence40-13-4.txt rename to PAGE/adjacency_lists/DifferenceSetIncidence40-13-4.txt diff --git a/CalcGenus/adjacency_lists/Fan3-6.txt b/PAGE/adjacency_lists/Fan3-6.txt similarity index 100% rename from CalcGenus/adjacency_lists/Fan3-6.txt rename to PAGE/adjacency_lists/Fan3-6.txt diff --git a/CalcGenus/adjacency_lists/G1-cactus.txt b/PAGE/adjacency_lists/G1-cactus.txt similarity index 100% rename from CalcGenus/adjacency_lists/G1-cactus.txt rename to PAGE/adjacency_lists/G1-cactus.txt diff --git a/CalcGenus/adjacency_lists/HigmanSims.txt b/PAGE/adjacency_lists/HigmanSims.txt similarity index 100% rename from CalcGenus/adjacency_lists/HigmanSims.txt rename to PAGE/adjacency_lists/HigmanSims.txt diff --git a/CalcGenus/adjacency_lists/HoffmanSingleton.txt b/PAGE/adjacency_lists/HoffmanSingleton.txt similarity index 100% rename from CalcGenus/adjacency_lists/HoffmanSingleton.txt rename to PAGE/adjacency_lists/HoffmanSingleton.txt diff --git a/CalcGenus/adjacency_lists/HoffmanSingletonBipartiteDoubleGraph.txt b/PAGE/adjacency_lists/HoffmanSingletonBipartiteDoubleGraph.txt similarity index 100% rename from CalcGenus/adjacency_lists/HoffmanSingletonBipartiteDoubleGraph.txt rename to PAGE/adjacency_lists/HoffmanSingletonBipartiteDoubleGraph.txt diff --git a/CalcGenus/adjacency_lists/Johnson5-2.txt b/PAGE/adjacency_lists/Johnson5-2.txt similarity index 100% rename from CalcGenus/adjacency_lists/Johnson5-2.txt rename to PAGE/adjacency_lists/Johnson5-2.txt diff --git a/CalcGenus/adjacency_lists/Johnson6-2.txt b/PAGE/adjacency_lists/Johnson6-2.txt similarity index 100% rename from CalcGenus/adjacency_lists/Johnson6-2.txt rename to PAGE/adjacency_lists/Johnson6-2.txt diff --git a/CalcGenus/adjacency_lists/Johnson6-3.txt b/PAGE/adjacency_lists/Johnson6-3.txt similarity index 100% rename from CalcGenus/adjacency_lists/Johnson6-3.txt rename to PAGE/adjacency_lists/Johnson6-3.txt diff --git a/CalcGenus/adjacency_lists/Johnson8-4.txt b/PAGE/adjacency_lists/Johnson8-4.txt similarity index 100% rename from CalcGenus/adjacency_lists/Johnson8-4.txt rename to PAGE/adjacency_lists/Johnson8-4.txt diff 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PAGE/adjacency_lists/Pathcomplement10.txt diff --git a/CalcGenus/adjacency_lists/TriangleReplacedCoxeterGraph.txt b/PAGE/adjacency_lists/TriangleReplacedCoxeterGraph.txt similarity index 100% rename from CalcGenus/adjacency_lists/TriangleReplacedCoxeterGraph.txt rename to PAGE/adjacency_lists/TriangleReplacedCoxeterGraph.txt diff --git a/CalcGenus/adjacency_lists/austin_test.txt b/PAGE/adjacency_lists/austin_test.txt similarity index 100% rename from CalcGenus/adjacency_lists/austin_test.txt rename to PAGE/adjacency_lists/austin_test.txt diff --git a/CalcGenus/adjacency_lists/balaban10.txt b/PAGE/adjacency_lists/balaban10.txt similarity index 100% rename from CalcGenus/adjacency_lists/balaban10.txt rename to PAGE/adjacency_lists/balaban10.txt diff --git a/CalcGenus/adjacency_lists/balaban11.txt b/PAGE/adjacency_lists/balaban11.txt similarity index 100% rename from CalcGenus/adjacency_lists/balaban11.txt rename to PAGE/adjacency_lists/balaban11.txt diff --git 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a/CalcGenus/adjacency_lists/issue3_23776.txt b/PAGE/adjacency_lists/issue3_23776.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_23776.txt rename to PAGE/adjacency_lists/issue3_23776.txt diff --git a/CalcGenus/adjacency_lists/issue3_24423.txt b/PAGE/adjacency_lists/issue3_24423.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_24423.txt rename to PAGE/adjacency_lists/issue3_24423.txt diff --git a/CalcGenus/adjacency_lists/issue3_24557.txt b/PAGE/adjacency_lists/issue3_24557.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_24557.txt rename to PAGE/adjacency_lists/issue3_24557.txt diff --git a/CalcGenus/adjacency_lists/issue3_24665.txt b/PAGE/adjacency_lists/issue3_24665.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_24665.txt rename to PAGE/adjacency_lists/issue3_24665.txt diff --git a/CalcGenus/adjacency_lists/issue3_24799.txt b/PAGE/adjacency_lists/issue3_24799.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_24799.txt rename to PAGE/adjacency_lists/issue3_24799.txt diff --git a/CalcGenus/adjacency_lists/issue3_25219.txt b/PAGE/adjacency_lists/issue3_25219.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_25219.txt rename to PAGE/adjacency_lists/issue3_25219.txt diff --git a/CalcGenus/adjacency_lists/issue3_25304.txt b/PAGE/adjacency_lists/issue3_25304.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_25304.txt rename to PAGE/adjacency_lists/issue3_25304.txt diff --git a/CalcGenus/adjacency_lists/issue3_26006.txt b/PAGE/adjacency_lists/issue3_26006.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_26006.txt rename to PAGE/adjacency_lists/issue3_26006.txt diff --git a/CalcGenus/adjacency_lists/issue3_26357.txt b/PAGE/adjacency_lists/issue3_26357.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_26357.txt rename to PAGE/adjacency_lists/issue3_26357.txt diff --git a/CalcGenus/adjacency_lists/issue3_26473.txt b/PAGE/adjacency_lists/issue3_26473.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_26473.txt rename to PAGE/adjacency_lists/issue3_26473.txt diff --git a/CalcGenus/adjacency_lists/issue3_26944.txt b/PAGE/adjacency_lists/issue3_26944.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_26944.txt rename to PAGE/adjacency_lists/issue3_26944.txt diff --git a/CalcGenus/adjacency_lists/issue3_27060.txt b/PAGE/adjacency_lists/issue3_27060.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_27060.txt rename to PAGE/adjacency_lists/issue3_27060.txt diff --git a/CalcGenus/adjacency_lists/issue3_27280.txt b/PAGE/adjacency_lists/issue3_27280.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_27280.txt rename to PAGE/adjacency_lists/issue3_27280.txt diff --git a/CalcGenus/adjacency_lists/issue3_27314.txt b/PAGE/adjacency_lists/issue3_27314.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_27314.txt rename to PAGE/adjacency_lists/issue3_27314.txt diff --git a/CalcGenus/adjacency_lists/issue3_27470.txt b/PAGE/adjacency_lists/issue3_27470.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_27470.txt rename to PAGE/adjacency_lists/issue3_27470.txt diff --git a/CalcGenus/adjacency_lists/issue3_27669.txt b/PAGE/adjacency_lists/issue3_27669.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_27669.txt rename to PAGE/adjacency_lists/issue3_27669.txt diff --git a/CalcGenus/adjacency_lists/issue3_27791.txt b/PAGE/adjacency_lists/issue3_27791.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_27791.txt rename to PAGE/adjacency_lists/issue3_27791.txt diff --git a/CalcGenus/adjacency_lists/issue3_28094.txt b/PAGE/adjacency_lists/issue3_28094.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_28094.txt rename to PAGE/adjacency_lists/issue3_28094.txt diff --git a/CalcGenus/adjacency_lists/issue3_28146.txt b/PAGE/adjacency_lists/issue3_28146.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_28146.txt rename to PAGE/adjacency_lists/issue3_28146.txt diff --git a/CalcGenus/adjacency_lists/issue3_41966.txt b/PAGE/adjacency_lists/issue3_41966.txt similarity index 100% rename from CalcGenus/adjacency_lists/issue3_41966.txt rename to PAGE/adjacency_lists/issue3_41966.txt diff --git a/CalcGenus/adjacency_lists/k1-2-6.txt b/PAGE/adjacency_lists/k1-2-6.txt similarity index 100% rename from CalcGenus/adjacency_lists/k1-2-6.txt rename to PAGE/adjacency_lists/k1-2-6.txt diff --git a/CalcGenus/adjacency_lists/k2-2-2-2-2.txt b/PAGE/adjacency_lists/k2-2-2-2-2.txt similarity index 100% rename from CalcGenus/adjacency_lists/k2-2-2-2-2.txt rename to PAGE/adjacency_lists/k2-2-2-2-2.txt diff --git a/CalcGenus/adjacency_lists/k2-2-2-2.txt b/PAGE/adjacency_lists/k2-2-2-2.txt similarity index 100% rename from CalcGenus/adjacency_lists/k2-2-2-2.txt rename to PAGE/adjacency_lists/k2-2-2-2.txt diff --git a/CalcGenus/adjacency_lists/k2-2-2.txt b/PAGE/adjacency_lists/k2-2-2.txt similarity index 100% rename from CalcGenus/adjacency_lists/k2-2-2.txt rename to PAGE/adjacency_lists/k2-2-2.txt diff --git a/CalcGenus/adjacency_lists/k2-2.txt b/PAGE/adjacency_lists/k2-2.txt similarity index 100% rename from CalcGenus/adjacency_lists/k2-2.txt rename to PAGE/adjacency_lists/k2-2.txt diff --git a/CalcGenus/adjacency_lists/k2.txt b/PAGE/adjacency_lists/k2.txt similarity index 100% rename from CalcGenus/adjacency_lists/k2.txt rename to PAGE/adjacency_lists/k2.txt diff --git a/CalcGenus/adjacency_lists/k3-3.txt b/PAGE/adjacency_lists/k3-3.txt similarity index 100% rename from CalcGenus/adjacency_lists/k3-3.txt rename to PAGE/adjacency_lists/k3-3.txt diff --git a/CalcGenus/adjacency_lists/k3.txt b/PAGE/adjacency_lists/k3.txt similarity index 100% rename from CalcGenus/adjacency_lists/k3.txt rename to PAGE/adjacency_lists/k3.txt diff --git a/CalcGenus/adjacency_lists/k4-4.txt b/PAGE/adjacency_lists/k4-4.txt similarity index 100% rename from CalcGenus/adjacency_lists/k4-4.txt rename to PAGE/adjacency_lists/k4-4.txt diff --git a/CalcGenus/adjacency_lists/k4.txt b/PAGE/adjacency_lists/k4.txt similarity index 100% rename from CalcGenus/adjacency_lists/k4.txt rename to PAGE/adjacency_lists/k4.txt diff --git a/CalcGenus/adjacency_lists/k5-5.txt b/PAGE/adjacency_lists/k5-5.txt similarity index 100% rename from CalcGenus/adjacency_lists/k5-5.txt rename to PAGE/adjacency_lists/k5-5.txt diff --git a/CalcGenus/adjacency_lists/k5.txt b/PAGE/adjacency_lists/k5.txt similarity index 100% rename from CalcGenus/adjacency_lists/k5.txt rename to PAGE/adjacency_lists/k5.txt diff --git a/CalcGenus/adjacency_lists/k6-6.txt b/PAGE/adjacency_lists/k6-6.txt similarity index 100% rename from CalcGenus/adjacency_lists/k6-6.txt rename to PAGE/adjacency_lists/k6-6.txt diff --git a/CalcGenus/adjacency_lists/k6.txt b/PAGE/adjacency_lists/k6.txt similarity index 100% rename from CalcGenus/adjacency_lists/k6.txt rename to PAGE/adjacency_lists/k6.txt diff --git a/CalcGenus/adjacency_lists/k7.txt b/PAGE/adjacency_lists/k7.txt similarity index 100% rename from CalcGenus/adjacency_lists/k7.txt rename to PAGE/adjacency_lists/k7.txt diff --git a/CalcGenus/adjacency_lists/k8.txt b/PAGE/adjacency_lists/k8.txt similarity index 100% rename from CalcGenus/adjacency_lists/k8.txt rename to PAGE/adjacency_lists/k8.txt diff --git a/CalcGenus/adjacency_lists/k9.txt b/PAGE/adjacency_lists/k9.txt similarity index 100% rename from CalcGenus/adjacency_lists/k9.txt rename to PAGE/adjacency_lists/k9.txt diff --git a/CalcGenus/adjacency_lists/nauty_temp.txt b/PAGE/adjacency_lists/nauty_temp.txt similarity index 100% rename from CalcGenus/adjacency_lists/nauty_temp.txt rename to PAGE/adjacency_lists/nauty_temp.txt diff --git a/PAGE/adjacency_lists/rome_temp.txt b/PAGE/adjacency_lists/rome_temp.txt new file mode 100644 index 0000000..4f0dc5a --- /dev/null +++ b/PAGE/adjacency_lists/rome_temp.txt @@ -0,0 +1,27 @@ +26 49 +15 6 2 3 65535 65535 65535 +3 13 65535 65535 65535 65535 65535 +0 4 25 65535 65535 65535 65535 +0 1 4 5 7 11 65535 +2 3 22 65535 65535 65535 65535 +3 19 11 65535 65535 65535 65535 +0 23 11 12 65535 65535 65535 +3 11 20 65535 65535 65535 65535 +14 23 9 21 65535 65535 65535 +8 16 11 12 65535 65535 65535 +17 11 21 65535 65535 65535 65535 +3 5 6 7 9 10 13 +6 9 14 20 65535 65535 65535 +1 11 15 21 65535 65535 65535 +8 12 22 15 24 65535 65535 +0 13 14 22 16 65535 65535 +9 15 18 65535 65535 65535 65535 +10 18 19 65535 65535 65535 65535 +16 17 22 65535 65535 65535 65535 +5 17 23 24 25 65535 65535 +7 12 23 65535 65535 65535 65535 +8 10 13 65535 65535 65535 65535 +4 14 15 18 65535 65535 65535 +6 8 19 20 65535 65535 65535 +14 19 25 65535 65535 65535 65535 +2 19 24 65535 65535 65535 65535 diff --git a/CalcGenus/adjacency_lists/tutte12.txt b/PAGE/adjacency_lists/tutte12.txt similarity index 100% rename from CalcGenus/adjacency_lists/tutte12.txt rename to PAGE/adjacency_lists/tutte12.txt diff --git a/CalcGenus/adjacency_lists/tutte_coxeter_graph.txt b/PAGE/adjacency_lists/tutte_coxeter_graph.txt similarity index 100% rename from CalcGenus/adjacency_lists/tutte_coxeter_graph.txt rename to PAGE/adjacency_lists/tutte_coxeter_graph.txt diff --git a/CalcGenus/graphDatabase.nb b/PAGE/graphDatabase.nb similarity index 99% rename from CalcGenus/graphDatabase.nb rename to PAGE/graphDatabase.nb index 48ba912..9e6c42b 100644 --- a/CalcGenus/graphDatabase.nb +++ b/PAGE/graphDatabase.nb @@ -1500,7 +1500,7 @@ Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Export", "[", RowBox[{ - "\"\\"", ",", " ", RowBox[{"AdjacencyList", "[", RowBox[{"GraphData", "[", "g", "]"}], "]"}], ",", " ", "\"\\""}], @@ -1534,7 +1534,7 @@ bipartite-kneser12-5.txt\>\"", ",", " ", CellLabel-> "In[484]:=",ExpressionUUID->"119fd569-ed61-45aa-91bb-347a41e8bae1"], -Cell[BoxData["\<\"/Users/alex/Desktop/People/Austin/Genus/CalcGenus/adjacency_\ +Cell[BoxData["\<\"/Users/alex/Desktop/People/Austin/Genus/PAGE/adjacency_\ lists/bipartite-kneser12-5.txt\"\>"], "Output", CellChangeTimes->{ 3.93839688180301*^9, 3.9383982569724617`*^9, 3.938399467144957*^9, diff --git a/PAGE/makefile b/PAGE/makefile new file mode 100644 index 0000000..a90ffc6 --- /dev/null +++ b/PAGE/makefile @@ -0,0 +1,24 @@ +CC=gcc +BTYPE=Development +BDIR=. + +all: page + +run: page + $(BDIR)/page + +page: page.c + $(CC) -O3 -ftree-vectorize -funroll-loops -Wall -std=c17 -pedantic -g -pthread -o "$(BDIR)/page" page.c + +run_wine: page.exe +# brew install --cask wine@staging + wine $(BDIR)/page.exe + +page.exe: page.c +# brew install mingw-w64 + x86_64-w64-mingw32-gcc -O3 -ftree-vectorize -funroll-loops -Wall -std=c17 -pedantic -g -o "$(BDIR)/page.exe" page.c + + +clean: + rm -f $(BDIR)/page $(BDIR)/*.o + rm -rf $(BDIR)/*.dSYM diff --git a/PAGE/page.c b/PAGE/page.c new file mode 100644 index 0000000..e7fc93d --- /dev/null +++ b/PAGE/page.c @@ -0,0 +1,3848 @@ +// Narrows down the genus of an arbitrary graph given its adjacency list. +// As evidence, prints the faces from Euler's formula: F - E + V = 2 - 2g. +// Run with `make run`. Works better for regular graphs (preferably of low degree). + +#include +#include +#include +#include +#include +#include +#include +#ifdef _WIN32 +#define WIN32_LEAN_AND_MEAN +#include +#else +#include +#include +#define PAGE_THREAD_LOCAL _Thread_local +#endif + +// configuration options: +#define PRINT_PROGRESS true // whether to print progress messages +// whether to print a newline after each progress bar update: +#define PROGRESS_BAR_NEWLINE progress_bar_newline +#define DEBUG false // whether to print debug messages +// whether to output to stdout instead of file: +#define OUTPUT_TO_STDOUT output_to_stdout +#define ADJACENCY_LIST_FILENAME adj_filename // input file +#define ADJACENCY_LIST_START start_index // vertex numbering starts from +#define OUTPUT_FILENAME "page.out" // output file +#define VERTEX_DEGREE vertex_degree // must be >= 2 +#define PRE_GENUS_LOWER_BOUND pre_genus_lower_bound // pre-computed lower bound on the genus +// true if it should to find the full cycle fitting, otherwise stops early once +// it is clear it exists (doesn't quite work with value false yet): +#define FIND_FULL_CYCLE_FITTING true +// true to branch on a remaining directed edge, otherwise uses the most used vertex +#define CONSTRAINED_BY_TWO true +#ifndef ONLY_SIMPLE_CYCLES +#define ONLY_SIMPLE_CYCLES false // only consider simple cycles +#endif + +// assumptions of the program (don't change these): +#define VERTEX_USE_LIMIT VERTEX_DEGREE +#define MAX_VERTICES 65535 +#define MAX_EDGES 65535 +#define MAX_CYCLE_LENGTH 65535 +#define MAX_CYCLES 4294967295 +#define LENGTH_COMPOSITION_WORK_LIMIT 25000000ULL +#define LENGTH_FEASIBILITY_CACHE_LIMIT 10000000ULL +#define SHORTEST_PACKING_CALL_LIMIT 1000000ULL +#define START_BRANCH_THREAD_CAP 8 +#define START_BRANCH_PARALLEL_MIN_CYCLES 750 +// Symmetry discovery is opportunistic: found automorphisms are used for sound +// pruning, but large graphs skip discovery when it costs more than it saves. +// TODO: find a proper criteria for when/how much symmetry pruning makes sense. +// For now, the VERTEX_LIMIT and LIMIT will need to be tuned based on the graph +#define AUTOMORPHISM_VERTEX_LIMIT 120 +#define AUTOMORPHISM_LIMIT 128 +#define AUTOMORPHISM_SEED_CALL_LIMIT 20000ULL +#define AUTOMORPHISM_TOTAL_CALL_LIMIT 200000ULL +#define DIRECTED_EDGE_LOOKUP_EMPTY UINT32_MAX + +// consequences of assumptions: +#define START_CYCLE_LENGTH 3 +typedef uint8_t degree_t; +#define PRIdegree_t PRIu8 +typedef uint16_t vertex_t; +#define PRIvertex_t PRIu16 +#define SCNvertex_t SCNu16 +typedef uint16_t edge_t; +#define PRIedge_t PRIu16 +#define SCNedge_t SCNu16 +typedef vertex_t cycle_length_t; // max length should always be max vertices +#define PRIcycle_length_t PRIvertex_t +#define SCNcycle_length_t SCNvertex_t +typedef uint32_t cycle_index_t; +#define PRIcycle_index_t PRIu32 +#define SCNcycle_index_t SCNu32 +typedef vertex_t* adj_t; +typedef vertex_t* cycles_t; +typedef cycle_index_t* cbv_t; +typedef cycle_index_t* cbe_t; +#ifdef _WIN32 +typedef SRWLOCK page_mutex_t; +typedef HANDLE page_thread_t; +typedef DWORD (WINAPI *page_thread_start_t)(LPVOID); +#define PAGE_MUTEX_INITIALIZER SRWLOCK_INIT +#define PAGE_THREAD_RETURN DWORD WINAPI +#define PAGE_THREAD_RESULT 0 +#else +typedef pthread_mutex_t page_mutex_t; +typedef pthread_t page_thread_t; +typedef void* (*page_thread_start_t)(void*); +#define PAGE_MUTEX_INITIALIZER PTHREAD_MUTEX_INITIALIZER +#define PAGE_THREAD_RETURN void* +#define PAGE_THREAD_RESULT NULL +#endif +typedef enum { + PACKING_IMPOSSIBLE, + PACKING_FOUND, + PACKING_UNKNOWN +} packing_result_t; +typedef struct { + bool* cycle_length_available; + cycle_length_t max_cycle_length; + cycle_length_t shortest_length; + cycle_length_t required_length; + int8_t* cache_without_required; + int8_t* cache_with_required; + cycle_index_t cache_width; +} length_feasibility_t; +typedef struct { + vertex_t num_vertices; + cycle_index_t count; + cycle_index_t capacity; + vertex_t* maps; +} automorphism_list_t; +typedef struct { + vertex_t num_vertices; + adj_t adjacency_list; + vertex_t* distances; + uint64_t* vertex_signatures; + vertex_t* map; + vertex_t* inverse_map; + vertex_t* result; + uint64_t calls; + uint64_t call_limit; +} automorphism_search_t; +typedef struct { + vertex_t num_vertices; + edge_t num_edges; + adj_t adjacency_list; + cycle_length_t max_cycle_length; + cycle_index_t num_cycles; + cycles_t cycles; + cycle_index_t max_cycles_per_vertex; + cbv_t cycles_by_vertex; + cycle_index_t max_cycles_per_edge; + cbe_t cycles_by_edge; + cycle_index_t* start_cycles; + cycle_index_t num_start_cycles; + cycle_index_t* start_cycle_order; + cycle_index_t initial_cycles_to_use; + cycle_index_t max_used_cycles; + cycle_index_t initial_max_fit; + bool* initial_directed_edge_remaining; + length_feasibility_t length_feasibility_template; + uint64_t length_cache_entries; + bool require_max_cycle_if_start_is_shorter; + page_mutex_t mutex; + cycle_index_t next_start_index; + cycle_index_t completed_start_cycles; + cycle_index_t best_max_fit; + uint64_t total_search_calls; + bool solution_found; + bool* solution_used_cycles; + atomic_bool stop_requested; +} start_branch_search_t; + +// macros +// assert(condition, message, ...fmt_args) +#define assert(condition, ...) \ + if (!(condition)) { \ + fprintf(stderr, __VA_ARGS__); \ + exit(1); \ + } + +int page_mutex_init(page_mutex_t* mutex) { +#ifdef _WIN32 + InitializeSRWLock(mutex); + return 0; +#else + return pthread_mutex_init(mutex, NULL); +#endif +} + +void page_mutex_lock(page_mutex_t* mutex) { +#ifdef _WIN32 + AcquireSRWLockExclusive(mutex); +#else + pthread_mutex_lock(mutex); +#endif +} + +void page_mutex_unlock(page_mutex_t* mutex) { +#ifdef _WIN32 + ReleaseSRWLockExclusive(mutex); +#else + pthread_mutex_unlock(mutex); +#endif +} + +void page_mutex_destroy(page_mutex_t* mutex) { +#ifdef _WIN32 + (void)mutex; +#else + pthread_mutex_destroy(mutex); +#endif +} + +int page_thread_create(page_thread_t* thread, page_thread_start_t start, void* arg) { +#ifdef _WIN32 + *thread = CreateThread(NULL, 0, start, arg, 0, NULL); + return *thread == NULL ? -1 : 0; +#else + return pthread_create(thread, NULL, start, arg); +#endif +} + +int page_thread_join(page_thread_t thread) { +#ifdef _WIN32 + DWORD wait_result = WaitForSingleObject(thread, INFINITE); + CloseHandle(thread); + return wait_result == WAIT_OBJECT_0 ? 0 : -1; +#else + return pthread_join(thread, NULL); +#endif +} + +// static variables +static FILE* output_file = NULL; +static vertex_t start_index = 0; +static degree_t vertex_degree = 3; +static cycle_index_t pre_genus_lower_bound = 0; +static char* adj_filename = NULL; +static cycle_length_t smallest_cycle_length; +static bool output_to_stdout = false; +static bool progress_bar_newline = false; +static bool cubic_exact_cover_mode = false; +static degree_t* vertex_degrees = NULL; +static degree_t* initial_vertex_uses = NULL; +static adj_t full_adjacency_list = NULL; +static cycle_index_t num_directed_edges = 0; +static cycle_index_t* directed_edge_ids = NULL; +#ifdef _WIN32 +typedef struct { + cycle_index_t num_edges_remaining; + bool* directed_edge_remaining; + bool* transitions_used; + size_t transitions_used_size; + cycle_index_t* cycle_edge_conflicts; + vertex_t* rotation_next; + vertex_t* rotation_prev; + degree_t* rotation_pair_count; + size_t rotation_state_size; + atomic_bool* search_stop_requested; +} page_worker_state_t; + +static DWORD page_worker_state_tls = TLS_OUT_OF_INDEXES; +static page_worker_state_t page_main_worker_state = {0}; + +page_worker_state_t* page_worker_state_current(void) { + if (page_worker_state_tls != TLS_OUT_OF_INDEXES) { + page_worker_state_t* state = + (page_worker_state_t*)TlsGetValue(page_worker_state_tls); + if (state != NULL) { + return state; + } + } + return &page_main_worker_state; +} + +#define num_edges_remaining (page_worker_state_current()->num_edges_remaining) +#define directed_edge_remaining (page_worker_state_current()->directed_edge_remaining) +#define transitions_used (page_worker_state_current()->transitions_used) +#define transitions_used_size (page_worker_state_current()->transitions_used_size) +#define cycle_edge_conflicts (page_worker_state_current()->cycle_edge_conflicts) +#define rotation_next (page_worker_state_current()->rotation_next) +#define rotation_prev (page_worker_state_current()->rotation_prev) +#define rotation_pair_count (page_worker_state_current()->rotation_pair_count) +#define rotation_state_size (page_worker_state_current()->rotation_state_size) +#define search_stop_requested (page_worker_state_current()->search_stop_requested) +#else +static PAGE_THREAD_LOCAL cycle_index_t num_edges_remaining = 0; +static PAGE_THREAD_LOCAL bool* directed_edge_remaining = NULL; +static PAGE_THREAD_LOCAL bool* transitions_used = NULL; +static PAGE_THREAD_LOCAL size_t transitions_used_size = 0; +static PAGE_THREAD_LOCAL cycle_index_t* cycle_edge_conflicts = NULL; +static PAGE_THREAD_LOCAL vertex_t* rotation_next = NULL; +static PAGE_THREAD_LOCAL vertex_t* rotation_prev = NULL; +static PAGE_THREAD_LOCAL degree_t* rotation_pair_count = NULL; +static PAGE_THREAD_LOCAL size_t rotation_state_size = 0; +static PAGE_THREAD_LOCAL atomic_bool* search_stop_requested = NULL; +#endif +static uint32_t* directed_edge_lookup_keys = NULL; +static cycle_index_t* directed_edge_lookup_ids = NULL; +static cycle_index_t directed_edge_lookup_capacity = 0; +static automorphism_list_t graph_automorphisms = {0, 0, 0, NULL}; +static page_mutex_t output_file_mutex = PAGE_MUTEX_INITIALIZER; + +// auxiliary data structures +adj_t adj_load(char* filename, vertex_t* num_vertices, edge_t* num_edges); +vertex_t* adj_get_neighbors(adj_t adjacency_list, vertex_t vertex); +void graph_free(adj_t adjacency_list); +bool graph_has_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex); +uint32_t directed_edge_key(vertex_t start_vertex, vertex_t end_vertex); +cycle_index_t directed_edge_lookup_slot(uint32_t key, bool allow_empty); +void directed_edge_lookup_insert(vertex_t start_vertex, vertex_t end_vertex, + cycle_index_t edge_id); +bool adj_try_edge_id(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex, + cycle_index_t* edge_id); +cycle_index_t adj_edge_id(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex); +bool adj_slot_has_edge(vertex_t start_vertex, degree_t neighbor_index); +void adj_remove_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex); +void adj_undo_remove_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex); +bool adj_has_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex); + +cycles_t cycle_generate(adj_t adjacency_list, vertex_t num_vertices, cycle_length_t cycle_length, + cycle_index_t* num_cycles); +vertex_t* cycle_get(cycles_t cycles, cycle_length_t max_cycle_length, cycle_index_t cycle_index, + cycle_length_t* cycle_length); + +cycle_index_t* cbv_generate(vertex_t num_vertices, cycles_t cycles, cycle_index_t num_cycles, + cycle_length_t cycle_length, cycle_index_t* max_cycles_per_vertex); +cycle_index_t* cbv_get_cycle_indices(cbv_t cycles_by_vertex, cycle_index_t max_cycles_per_vertex, + vertex_t vertex, cycle_index_t* num_cycles); +cycle_index_t* cbe_generate(vertex_t num_vertices, cycles_t cycles, cycle_index_t num_cycles, + cycle_length_t max_cycle_length, cycle_index_t* max_cycles_per_edge); +cycle_index_t* cbe_get_cycle_indices(cbe_t cycles_by_edge, cycle_index_t max_cycles_per_edge, + vertex_t start_vertex, vertex_t end_vertex, + cycle_index_t* num_cycles); + +void show_progress(double fraction); +void show_solution(cycle_index_t genus_lower_bound, cycle_index_t genus_lower_bound_implied_fit, + uint64_t num_search_calls, cycle_index_t num_cycles, bool* used_cycles, + cycles_t cycles, cycle_length_t max_cycle_length); + +degree_t adj_neighbor_index(adj_t adjacency_list, vertex_t vertex, vertex_t neighbor); +bool cycle_edges_available(adj_t adjacency_list, vertex_t* cycle, cycle_length_t cycle_length); +bool cycle_vertex_uses_fit(vertex_t* cycle, cycle_length_t cycle_length, + degree_t* vertex_uses); +void automorphism_list_free(automorphism_list_t* automorphisms); +void automorphism_generate(vertex_t num_vertices, adj_t adjacency_list, + automorphism_list_t* automorphisms); +cycle_index_t* start_cycles_prune_by_symmetry(cycles_t cycles, + cycle_length_t max_cycle_length, + cycle_index_t num_cycles, + cbe_t cycles_by_edge, + cycle_index_t max_cycles_per_edge, + cycle_index_t* raw_start_cycles, + cycle_index_t raw_start_count, + cycle_index_t* pruned_start_count); +void cycle_edge_conflicts_init(cycle_index_t num_cycles); +void cycle_edge_conflicts_clear(cycle_index_t num_cycles); +void cycle_edge_conflicts_free(void); +bool candidate_length_possible(cycle_length_t cycle_length, + cycle_index_t cycles_to_use, + length_feasibility_t* length_feasibility, + cycle_index_t required_cycles_to_use); +void cycle_set_edge_conflicts(vertex_t* cycle, cycle_length_t cycle_length, + cycle_index_t max_cycles_per_edge, cbe_t cycles_by_edge, + bool used); +bool cycle_search_candidate_usable(bool* used_cycles, degree_t* vertex_uses, + adj_t adjacency_list, cycles_t cycles, + cycle_length_t max_cycle_length, + cycle_index_t cycle_index, + cycle_index_t* start_cycle_order, + cycle_index_t current_start_cycle_order, + cycle_index_t cycles_to_use, + length_feasibility_t* length_feasibility, + cycle_index_t required_cycles_to_use, + bool check_row_constraints, + bool check_transitions, + cycle_length_t* cycle_length_out, + vertex_t** cycle_out, + cycle_index_t* next_required_cycles_to_use); +bool cycle_transitions_good(vertex_t* cycle, cycle_length_t cycle_length); +void cycle_set_transitions(vertex_t* cycle, cycle_length_t cycle_length, bool used); +unsigned get_start_branch_thread_count(cycle_index_t num_start_cycles, + cycle_index_t num_cycles); +void precompute_start_cycle_order(cycle_index_t* start_cycle_order, + cycle_index_t* start_cycles, + cycle_index_t num_start_cycles); +bool search_start_cycles_parallel(start_branch_search_t* context, + unsigned num_threads); +PAGE_THREAD_RETURN start_branch_worker(void* arg); +void rotation_state_init(vertex_t num_vertices); +void rotation_state_clear(vertex_t num_vertices); +void rotation_state_free(void); +bool rotation_transition_add(vertex_t center, degree_t prev_index, degree_t next_index); +void rotation_transition_remove(vertex_t center, degree_t prev_index, degree_t next_index); +bool cycle_try_add_rotation_system(vertex_t* cycle, cycle_length_t cycle_length); +void cycle_remove_rotation_system(vertex_t* cycle, cycle_length_t cycle_length); +cycle_index_t choose_start_edge(vertex_t num_vertices, adj_t adjacency_list, + cycle_index_t max_cycles_per_edge, cbe_t cycles_by_edge, + vertex_t* start_vertex, vertex_t* end_vertex); +bool path_has_reverse_transition(vertex_t* path, cycle_length_t path_length, vertex_t prev_vertex, + vertex_t center_vertex, vertex_t next_vertex); +cycle_index_t genus_lower_bound_from_fit_upper_bound(cycle_index_t fit_upper_bound, + vertex_t num_vertices, edge_t num_edges); +bool length_composition_possible(cycle_index_t total_length, cycle_index_t cycles_to_use, + bool* cycle_length_available, + cycle_length_t max_cycle_length, + cycle_length_t shortest_length, + cycle_length_t required_length, + cycle_index_t* min_shortest_cycles); +bool cached_length_composition_possible(length_feasibility_t* length_feasibility, + cycle_index_t total_length, + cycle_index_t cycles_to_use, + cycle_index_t required_cycles_to_use); +cycle_index_t max_possible_fit_with_shortest_bound(edge_t num_edges, + cycle_length_t shortest_length, + cycle_length_t second_shortest_length, + cycle_index_t max_shortest_cycles, + cycle_length_t required_length); +packing_result_t can_pack_shortest_cycles(vertex_t num_vertices, edge_t num_edges, + adj_t adjacency_list, cycles_t cycles, + cycle_length_t max_cycle_length, + cycle_length_t shortest_cycle_length, + cycle_index_t num_shortest_cycles, + cycle_index_t target_shortest_cycles, + uint64_t* num_packing_calls); +bool search(cycle_index_t cycles_to_use, // state + cycle_index_t max_used_cycles, // state + bool* used_cycles, // state + degree_t* vertex_uses, cycle_index_t* max_fit, // state + uint64_t* num_search_calls, // state + vertex_t num_vertices, edge_t num_edges, adj_t adjacency_list, + cycle_length_t max_cycle_length, cycle_index_t num_cycles, cycles_t cycles, + cycle_index_t max_cycles_per_vertex, cbv_t cycles_by_vertex, + cycle_index_t max_cycles_per_edge, cbe_t cycles_by_edge, + cycle_index_t* start_cycle_order, cycle_index_t current_start_cycle_order, + length_feasibility_t* length_feasibility, + cycle_index_t required_cycles_to_use); + +cycle_index_t implied_max_fit_for_genus(cycle_index_t genus, vertex_t num_vertices, + edge_t num_edges) { + return num_edges - num_vertices + 2 - 2 * genus; +} + +cycle_index_t implied_max_genus_for_fit(cycle_index_t fit, vertex_t num_vertices, + edge_t num_edges) { + int64_t val = 1 - ((int64_t)fit - num_edges + num_vertices) / 2; + return val < 0 ? 0 : val; +} + +cycle_index_t genus_lower_bound_from_fit_upper_bound(cycle_index_t fit_upper_bound, + vertex_t num_vertices, edge_t num_edges) { + int64_t numerator = (int64_t)num_edges - num_vertices + 2 - fit_upper_bound; + if (numerator <= 0) { + return 0; + } + return (cycle_index_t)((numerator + 1) / 2); +} + +cycle_length_t gcd_cycle_length(cycle_length_t a, cycle_length_t b) { + while (b != 0) { + cycle_length_t r = a % b; + a = b; + b = r; + } + return a; +} + +cycle_index_t ceil_div_u64(uint64_t numerator, uint64_t denominator) { + return (cycle_index_t)((numerator + denominator - 1) / denominator); +} + +bool length_composition_possible(cycle_index_t total_length, cycle_index_t cycles_to_use, + bool* cycle_length_available, + cycle_length_t max_cycle_length, + cycle_length_t shortest_length, + cycle_length_t required_length, + cycle_index_t* min_shortest_cycles) { + *min_shortest_cycles = 0; + if (cycles_to_use == 0) { + return total_length == 0; + } + if (required_length != 0 && + (required_length > max_cycle_length || !cycle_length_available[required_length])) { + return false; + } + + cycle_index_t num_available_lengths = 0; + cycle_length_t min_available_length = 0; + cycle_length_t max_available_length = 0; + cycle_length_t second_available_length = 0; + cycle_length_t length_gcd = 0; + for (cycle_length_t length = START_CYCLE_LENGTH; length <= max_cycle_length; length++) { + if (!cycle_length_available[length]) { + continue; + } + num_available_lengths++; + if (min_available_length == 0) { + min_available_length = length; + } + max_available_length = length; + if (length > shortest_length && second_available_length == 0) { + second_available_length = length; + } + length_gcd = gcd_cycle_length(length_gcd, length - min_available_length); + } + if (num_available_lengths == 0) { + return false; + } + + cycle_index_t start_count = required_length == 0 ? 0 : 1; + cycle_index_t start_sum = required_length; + cycle_index_t start_shortest = required_length == shortest_length ? 1 : 0; + if (start_count > cycles_to_use || start_sum > total_length) { + return false; + } + + uint64_t work = + (uint64_t)(cycles_to_use - start_count) * (total_length + 1) * num_available_lengths; + if (work <= LENGTH_COMPOSITION_WORK_LIMIT) { + cycle_index_t* dp = (cycle_index_t*)malloc((total_length + 1) * sizeof(cycle_index_t)); + cycle_index_t* next = + (cycle_index_t*)malloc((total_length + 1) * sizeof(cycle_index_t)); + assert(dp != NULL && next != NULL, + "Error allocating memory for the length composition DP\n"); + memset(dp, 0xff, (total_length + 1) * sizeof(cycle_index_t)); + dp[start_sum] = start_shortest; + + for (cycle_index_t count = start_count; count < cycles_to_use; count++) { + memset(next, 0xff, (total_length + 1) * sizeof(cycle_index_t)); + for (cycle_index_t sum = 0; sum <= total_length; sum++) { + if (dp[sum] == MAX_CYCLES) { + continue; + } + for (cycle_length_t length = START_CYCLE_LENGTH; length <= max_cycle_length; + length++) { + if (!cycle_length_available[length] || sum + length > total_length) { + continue; + } + cycle_index_t shortest_count = + dp[sum] + (length == shortest_length ? 1 : 0); + if (shortest_count < next[sum + length]) { + next[sum + length] = shortest_count; + } + } + } + cycle_index_t* tmp = dp; + dp = next; + next = tmp; + } + + bool possible = dp[total_length] != MAX_CYCLES; + if (possible) { + *min_shortest_cycles = dp[total_length]; + } + free(dp); + free(next); + return possible; + } + + cycle_index_t remaining_count = cycles_to_use - start_count; + cycle_index_t remaining_sum = total_length - start_sum; + if ((uint64_t)remaining_count * min_available_length > remaining_sum || + (uint64_t)remaining_count * max_available_length < remaining_sum) { + return false; + } + if (length_gcd == 0) { + if (remaining_sum != remaining_count * min_available_length) { + return false; + } + } else if ((remaining_sum - remaining_count * min_available_length) % length_gcd != 0) { + return false; + } + + cycle_index_t lower_shortest_count = start_shortest; + if (remaining_count > 0) { + if (second_available_length == 0) { + if (remaining_sum != remaining_count * shortest_length) { + return false; + } + lower_shortest_count += remaining_count; + } else { + uint64_t sum_without_shortest = (uint64_t)remaining_count * second_available_length; + if (sum_without_shortest > remaining_sum) { + lower_shortest_count += + ceil_div_u64(sum_without_shortest - remaining_sum, + second_available_length - shortest_length); + } + } + } + *min_shortest_cycles = lower_shortest_count; + return true; +} + +bool cached_length_composition_possible(length_feasibility_t* length_feasibility, + cycle_index_t total_length, + cycle_index_t cycles_to_use, + cycle_index_t required_cycles_to_use) { + if (length_feasibility == NULL || length_feasibility->cache_without_required == NULL) { + return true; + } + if (required_cycles_to_use > 1 || total_length >= length_feasibility->cache_width) { + return true; + } + + int8_t* cache = required_cycles_to_use == 0 + ? length_feasibility->cache_without_required + : length_feasibility->cache_with_required; + cycle_index_t cache_index = cycles_to_use * length_feasibility->cache_width + total_length; + if (cache[cache_index] != -1) { + return cache[cache_index] == 1; + } + + cycle_index_t min_shortest_cycles; + bool possible = length_composition_possible( + total_length, cycles_to_use, length_feasibility->cycle_length_available, + length_feasibility->max_cycle_length, length_feasibility->shortest_length, + required_cycles_to_use == 0 ? 0 : length_feasibility->required_length, + &min_shortest_cycles); + cache[cache_index] = possible ? 1 : 0; + return possible; +} + +cycle_index_t max_possible_fit_with_shortest_bound(edge_t num_edges, + cycle_length_t shortest_length, + cycle_length_t second_shortest_length, + cycle_index_t max_shortest_cycles, + cycle_length_t required_length) { + cycle_index_t total_length = 2 * num_edges; + if (shortest_length == 0 || required_length > total_length) { + return 0; + } + + cycle_length_t non_shortest_length = second_shortest_length; + if (non_shortest_length == 0 || required_length < non_shortest_length) { + non_shortest_length = required_length; + } + + cycle_index_t remaining_length = total_length - required_length; + cycle_index_t shortest_cycles_to_use = remaining_length / shortest_length; + if (shortest_cycles_to_use > max_shortest_cycles) { + shortest_cycles_to_use = max_shortest_cycles; + } + remaining_length -= shortest_cycles_to_use * shortest_length; + + return 1 + shortest_cycles_to_use + remaining_length / non_shortest_length; +} + +typedef struct { + vertex_t num_vertices; + edge_t num_edges; + adj_t adjacency_list; + cycles_t cycles; + cycle_length_t max_cycle_length; + cycle_length_t shortest_cycle_length; + cycle_index_t num_shortest_cycles; + cycle_index_t directed_edges; + cycle_index_t edge_cycle_row_width; + cycle_index_t* cycles_by_edge; + cycle_index_t* cycle_edge_ids; + bool* edge_used; + bool* edge_skipped; + degree_t* vertex_uses; + uint64_t calls; + uint64_t call_limit; +} shortest_packing_state_t; + +cycle_index_t directed_edge_id(adj_t adjacency_list, cycle_index_t* edge_slot_to_id, + vertex_t start_vertex, vertex_t end_vertex) { + vertex_t* neighbors = adj_get_neighbors(adjacency_list, start_vertex); + for (degree_t i = 0; i < VERTEX_DEGREE; i++) { + if (neighbors[i] == end_vertex) { + return edge_slot_to_id[start_vertex * VERTEX_DEGREE + i]; + } + } + assert(false, "Error finding directed edge %" PRIvertex_t " -> %" PRIvertex_t "\n", + start_vertex, end_vertex); + return MAX_CYCLES; +} + +bool shortest_packing_cycle_usable(shortest_packing_state_t* state, cycle_index_t cycle_index) { + cycle_index_t edge_offset = cycle_index * state->shortest_cycle_length; + for (cycle_length_t i = 0; i < state->shortest_cycle_length; i++) { + cycle_index_t edge_id = state->cycle_edge_ids[edge_offset + i]; + if (state->edge_used[edge_id] || state->edge_skipped[edge_id]) { + return false; + } + } + + cycle_length_t cycle_length; + vertex_t* cycle = cycle_get(state->cycles, state->max_cycle_length, cycle_index, + &cycle_length); + assert(cycle_length == state->shortest_cycle_length, + "Error: shortest packing got a non-shortest cycle\n"); + for (cycle_length_t i = 0; i < cycle_length; i++) { + if (state->vertex_uses[cycle[i]] >= vertex_degrees[cycle[i]]) { + return false; + } + } + return true; +} + +void shortest_packing_set_cycle(shortest_packing_state_t* state, cycle_index_t cycle_index, + bool used) { + cycle_index_t edge_offset = cycle_index * state->shortest_cycle_length; + for (cycle_length_t i = 0; i < state->shortest_cycle_length; i++) { + state->edge_used[state->cycle_edge_ids[edge_offset + i]] = used; + } + + cycle_length_t cycle_length; + vertex_t* cycle = cycle_get(state->cycles, state->max_cycle_length, cycle_index, + &cycle_length); + for (cycle_length_t i = 0; i < cycle_length; i++) { + if (used) { + state->vertex_uses[cycle[i]]++; + } else { + state->vertex_uses[cycle[i]]--; + } + } +} + +packing_result_t shortest_packing_search(shortest_packing_state_t* state, + cycle_index_t cycles_left, cycle_index_t skips_left, + cycle_index_t used_edges, + cycle_index_t skipped_edges) { + state->calls++; + if (state->calls > state->call_limit) { + return PACKING_UNKNOWN; + } + if (cycles_left == 0) { + return PACKING_FOUND; + } + if ((uint64_t)cycles_left * state->shortest_cycle_length > + (uint64_t)state->directed_edges - used_edges - skipped_edges) { + return PACKING_IMPOSSIBLE; + } + + uint64_t remaining_vertex_capacity = 0; + for (vertex_t i = 0; i < state->num_vertices; i++) { + remaining_vertex_capacity += vertex_degrees[i] - state->vertex_uses[i]; + } + if ((uint64_t)cycles_left * state->shortest_cycle_length > remaining_vertex_capacity) { + return PACKING_IMPOSSIBLE; + } + + cycle_index_t chosen_edge = MAX_CYCLES; + cycle_index_t min_cycle_options = MAX_CYCLES; + for (cycle_index_t edge_id = 0; edge_id < state->directed_edges; edge_id++) { + if (state->edge_used[edge_id] || state->edge_skipped[edge_id]) { + continue; + } + + cycle_index_t usable_cycles = 0; + cycle_index_t* row = + &state->cycles_by_edge[edge_id * (state->edge_cycle_row_width + 1)]; + for (cycle_index_t i = 0; i < row[0]; i++) { + if (shortest_packing_cycle_usable(state, row[i + 1])) { + usable_cycles++; + } + } + + if (usable_cycles < min_cycle_options) { + chosen_edge = edge_id; + min_cycle_options = usable_cycles; + if (min_cycle_options == 0) { + break; + } + } + } + + if (chosen_edge == MAX_CYCLES) { + return PACKING_IMPOSSIBLE; + } + if (min_cycle_options == 0 && skips_left == 0) { + return PACKING_IMPOSSIBLE; + } + + packing_result_t result = PACKING_IMPOSSIBLE; + cycle_index_t* row = + &state->cycles_by_edge[chosen_edge * (state->edge_cycle_row_width + 1)]; + for (cycle_index_t i = 0; i < row[0]; i++) { + cycle_index_t cycle_index = row[i + 1]; + if (!shortest_packing_cycle_usable(state, cycle_index)) { + continue; + } + + shortest_packing_set_cycle(state, cycle_index, true); + packing_result_t child_result = + shortest_packing_search(state, cycles_left - 1, skips_left, + used_edges + state->shortest_cycle_length, skipped_edges); + shortest_packing_set_cycle(state, cycle_index, false); + + if (child_result == PACKING_FOUND) { + return PACKING_FOUND; + } + if (child_result == PACKING_UNKNOWN) { + result = PACKING_UNKNOWN; + } + } + + if (skips_left > 0) { + state->edge_skipped[chosen_edge] = true; + packing_result_t child_result = + shortest_packing_search(state, cycles_left, skips_left - 1, used_edges, + skipped_edges + 1); + state->edge_skipped[chosen_edge] = false; + if (child_result == PACKING_FOUND) { + return PACKING_FOUND; + } + if (child_result == PACKING_UNKNOWN) { + result = PACKING_UNKNOWN; + } + } + + return result; +} + +packing_result_t can_pack_shortest_cycles(vertex_t num_vertices, edge_t num_edges, + adj_t adjacency_list, cycles_t cycles, + cycle_length_t max_cycle_length, + cycle_length_t shortest_cycle_length, + cycle_index_t num_shortest_cycles, + cycle_index_t target_shortest_cycles, + uint64_t* num_packing_calls) { + *num_packing_calls = 0; + if (target_shortest_cycles == 0) { + return PACKING_FOUND; + } + if (target_shortest_cycles > num_shortest_cycles || + (uint64_t)target_shortest_cycles * shortest_cycle_length > 2 * num_edges) { + return PACKING_IMPOSSIBLE; + } + + cycle_index_t edge_slots = num_vertices * VERTEX_DEGREE; + cycle_index_t* edge_slot_to_id = (cycle_index_t*)malloc(edge_slots * sizeof(cycle_index_t)); + assert(edge_slot_to_id != NULL, "Error allocating memory for directed edge ids\n"); + for (cycle_index_t i = 0; i < edge_slots; i++) { + edge_slot_to_id[i] = MAX_CYCLES; + } + + cycle_index_t directed_edges = 0; + for (vertex_t vertex = 0; vertex < num_vertices; vertex++) { + vertex_t* neighbors = adj_get_neighbors(adjacency_list, vertex); + for (degree_t i = 0; i < VERTEX_DEGREE; i++) { + if (neighbors[i] == MAX_VERTICES) { + continue; + } + edge_slot_to_id[vertex * VERTEX_DEGREE + i] = directed_edges++; + } + } + assert(directed_edges == 2 * num_edges, + "Error: found %" PRIcycle_index_t " directed edges but expected %" PRIedge_t "\n", + directed_edges, 2 * num_edges); + + cycle_index_t* edge_cycle_counts = + (cycle_index_t*)calloc(directed_edges, sizeof(cycle_index_t)); + assert(edge_cycle_counts != NULL, + "Error allocating memory for shortest cycles by edge counts\n"); + cycle_index_t* cycle_edge_ids = (cycle_index_t*)malloc( + (uint64_t)num_shortest_cycles * shortest_cycle_length * sizeof(cycle_index_t)); + assert(cycle_edge_ids != NULL, "Error allocating memory for shortest cycle edge ids\n"); + + for (cycle_index_t cycle_index = 0; cycle_index < num_shortest_cycles; cycle_index++) { + cycle_length_t cycle_length; + vertex_t* cycle = cycle_get(cycles, max_cycle_length, cycle_index, &cycle_length); + assert(cycle_length == shortest_cycle_length, + "Error: shortest cycle prefix contains a longer cycle\n"); + for (cycle_length_t i = 0; i < cycle_length; i++) { + cycle_index_t edge_id = + directed_edge_id(adjacency_list, edge_slot_to_id, cycle[i], cycle[i + 1]); + cycle_edge_ids[cycle_index * shortest_cycle_length + i] = edge_id; + edge_cycle_counts[edge_id]++; + } + } + + cycle_index_t edge_cycle_row_width = 0; + for (cycle_index_t edge_id = 0; edge_id < directed_edges; edge_id++) { + if (edge_cycle_counts[edge_id] > edge_cycle_row_width) { + edge_cycle_row_width = edge_cycle_counts[edge_id]; + } + } + + cycle_index_t* cycles_by_edge = (cycle_index_t*)malloc( + directed_edges * (edge_cycle_row_width + 1) * sizeof(cycle_index_t)); + cycle_index_t* edge_cycle_fill = + (cycle_index_t*)calloc(directed_edges, sizeof(cycle_index_t)); + assert(cycles_by_edge != NULL && edge_cycle_fill != NULL, + "Error allocating memory for shortest cycles by edge\n"); + for (cycle_index_t edge_id = 0; edge_id < directed_edges; edge_id++) { + cycles_by_edge[edge_id * (edge_cycle_row_width + 1)] = edge_cycle_counts[edge_id]; + } + for (cycle_index_t cycle_index = 0; cycle_index < num_shortest_cycles; cycle_index++) { + for (cycle_length_t i = 0; i < shortest_cycle_length; i++) { + cycle_index_t edge_id = cycle_edge_ids[cycle_index * shortest_cycle_length + i]; + cycle_index_t fill = edge_cycle_fill[edge_id]++; + cycles_by_edge[edge_id * (edge_cycle_row_width + 1) + fill + 1] = cycle_index; + } + } + + bool* edge_used = (bool*)calloc(directed_edges, sizeof(bool)); + bool* edge_skipped = (bool*)calloc(directed_edges, sizeof(bool)); + degree_t* vertex_uses = (degree_t*)calloc(num_vertices, sizeof(degree_t)); + assert(edge_used != NULL && edge_skipped != NULL && vertex_uses != NULL, + "Error allocating memory for shortest packing state\n"); + + shortest_packing_state_t state = { + .num_vertices = num_vertices, + .num_edges = num_edges, + .adjacency_list = adjacency_list, + .cycles = cycles, + .max_cycle_length = max_cycle_length, + .shortest_cycle_length = shortest_cycle_length, + .num_shortest_cycles = num_shortest_cycles, + .directed_edges = directed_edges, + .edge_cycle_row_width = edge_cycle_row_width, + .cycles_by_edge = cycles_by_edge, + .cycle_edge_ids = cycle_edge_ids, + .edge_used = edge_used, + .edge_skipped = edge_skipped, + .vertex_uses = vertex_uses, + .calls = 0, + .call_limit = SHORTEST_PACKING_CALL_LIMIT, + }; + + cycle_index_t skips_left = + directed_edges - target_shortest_cycles * shortest_cycle_length; + packing_result_t result = + shortest_packing_search(&state, target_shortest_cycles, skips_left, 0, 0); + *num_packing_calls = state.calls; + + free(edge_slot_to_id); + free(edge_cycle_counts); + free(cycle_edge_ids); + free(cycles_by_edge); + free(edge_cycle_fill); + free(edge_used); + free(edge_skipped); + free(vertex_uses); + return result; +} + +int main(void) { + start_index = atoi(getenv("S")); + vertex_degree = atoi(getenv("DEG")); + if (getenv("GLB") != NULL) { + pre_genus_lower_bound = atoi(getenv("GLB")); + } + adj_filename = getenv("ADJ"); + output_to_stdout = getenv("STDOUT") != NULL; + progress_bar_newline = getenv("PBN") != NULL; + + if (PRINT_PROGRESS) { + fprintf(stderr, "Loading adjacency list...\n"); + } + + vertex_t num_vertices; + edge_t num_edges; + adj_t adjacency_list = adj_load(ADJACENCY_LIST_FILENAME, &num_vertices, &num_edges); + initial_vertex_uses = (degree_t*)malloc(num_vertices * sizeof(degree_t)); + assert(initial_vertex_uses != NULL, + "Error allocating memory for the initial vertex use counts\n"); + for (vertex_t i = 0; i < num_vertices; i++) { + initial_vertex_uses[i] = 0; + vertex_t* neighbors = adj_get_neighbors(adjacency_list, i); + for (degree_t j = 0; j < VERTEX_DEGREE; j++) { + if (neighbors[j] == MAX_VERTICES) { + initial_vertex_uses[i]++; + } + } + } + if (OUTPUT_TO_STDOUT) { + output_file = stdout; + } else { + output_file = fopen(OUTPUT_FILENAME, "w"); + assert(output_file != NULL, "Error opening file %s\n", OUTPUT_FILENAME); + fprintf(stderr, "Output file: %s\n", OUTPUT_FILENAME); + } + + cycle_index_t genus_lower_bound = + genus_lower_bound_from_fit_upper_bound(2 * num_edges / START_CYCLE_LENGTH, + num_vertices, num_edges); + cycle_index_t genus_lower_bound_implied_fit = + implied_max_fit_for_genus(genus_lower_bound, num_vertices, num_edges); + if (PRE_GENUS_LOWER_BOUND > genus_lower_bound) { + genus_lower_bound = PRE_GENUS_LOWER_BOUND; + genus_lower_bound_implied_fit = + implied_max_fit_for_genus(genus_lower_bound, num_vertices, num_edges); + } + cycle_index_t max_fit = (2 * num_edges + num_vertices - 1) / num_vertices; + cycle_index_t genus_upper_bound = implied_max_genus_for_fit(max_fit, num_vertices, num_edges); + + if (genus_lower_bound == genus_upper_bound) { + // we've found the genus! + if (PRINT_PROGRESS) { + fprintf(stderr, + "Found the genus! It is %" PRIcycle_index_t + ". No computation needed when the genus is found via the " + "theoretical formula.\n", + genus_lower_bound); + } + fprintf(output_file, "Genus found: %" PRIcycle_index_t " in 0 iterations:\n", + genus_lower_bound); + fclose(output_file); + graph_free(adjacency_list); + return 0; + } + + if (PRINT_PROGRESS) { + fprintf(stderr, + "Beginning to narrow down genus (currently between %" PRIcycle_index_t + " and %" PRIcycle_index_t " with implied fit %" PRIcycle_index_t ")...\n", + genus_lower_bound, genus_upper_bound, genus_lower_bound_implied_fit); + } + + uint64_t num_search_calls = 0; + smallest_cycle_length = num_vertices; + cycle_length_t second_smallest_cycle_length = 0; + cycle_index_t num_shortest_cycles = 0; + cycle_index_t max_shortest_cycles = MAX_CYCLES; + cycle_index_t verified_packable_shortest_cycles = 0; + cycle_length_t max_search_cycle_length = ONLY_SIMPLE_CYCLES ? num_vertices : num_edges; + bool* cycle_length_available = + (bool*)calloc(max_search_cycle_length + 1, sizeof(bool)); + assert(cycle_length_available != NULL, + "Error allocating memory for the cycle length availability flags\n"); + cycles_t cycles = NULL; + cycle_index_t num_cycles = 0; + cycle_length_t cycles_max_cycle_length = 0; + cycle_index_t current_length_cycle_count = 0; + cycle_index_t last_searched_fit = MAX_CYCLES; + for (cycle_length_t cur_max_cycle_length = START_CYCLE_LENGTH; + cur_max_cycle_length <= max_search_cycle_length; cur_max_cycle_length++) { + bool reusing_current_length = + cur_max_cycle_length == cycles_max_cycle_length && + current_length_cycle_count > 0; + cycle_index_t num_new_cycles = current_length_cycle_count; + if (reusing_current_length) { + if (PRINT_PROGRESS) { + fprintf(stderr, + "Rechecking cycles of length up to %" PRIcycle_length_t + " for the new target fit.\n", + cur_max_cycle_length); + } + } else { + if (PRINT_PROGRESS) { + fprintf(stderr, + "Loading auxiliary data structures for cycles of length " + "%" PRIcycle_length_t "... ", + cur_max_cycle_length); + } + + cycles_t new_cycles = + cycle_generate(adjacency_list, num_vertices, cur_max_cycle_length, + &num_new_cycles); + current_length_cycle_count = num_new_cycles; + num_cycles += num_new_cycles; + + if (num_new_cycles == 0) { + // no cycles of this length, skip to the next length + free(new_cycles); + if (PRINT_PROGRESS) { + fprintf(stderr, + "No cycles of length %" PRIcycle_length_t " found. Skipping.\n", + cur_max_cycle_length); + } + continue; + } + assert(new_cycles != NULL, "Error: new cycles is NULL but there are new cycles\n"); + if (PRINT_PROGRESS) { + fprintf(stderr, + "Found %" PRIcycle_index_t " cycles of length %" PRIcycle_length_t ".\n", + num_new_cycles, cur_max_cycle_length); + } + + cycle_length_available[cur_max_cycle_length] = true; + + // keep the smallest cycle length up to date + if (cur_max_cycle_length < smallest_cycle_length) { + smallest_cycle_length = cur_max_cycle_length; + num_shortest_cycles = num_new_cycles; + max_shortest_cycles = num_new_cycles < 2 * num_edges / smallest_cycle_length + ? num_new_cycles + : 2 * num_edges / smallest_cycle_length; + } else if (cur_max_cycle_length > smallest_cycle_length && + second_smallest_cycle_length == 0) { + second_smallest_cycle_length = cur_max_cycle_length; + } + + // the smallest cycle length limits how many cycles we can fit and hence the + // genus + cycle_index_t genus_lower_bound_from_smallest_cycle_length = + genus_lower_bound_from_fit_upper_bound(2 * num_edges / smallest_cycle_length, + num_vertices, num_edges); + if (genus_lower_bound_from_smallest_cycle_length > genus_lower_bound) { + genus_lower_bound = genus_lower_bound_from_smallest_cycle_length; + genus_lower_bound_implied_fit = + implied_max_fit_for_genus(genus_lower_bound, num_vertices, num_edges); + } + + // add the new cycles to the old ones + if (cycles == NULL) { + cycles = new_cycles; + cycles_max_cycle_length = cur_max_cycle_length; + } else { + cycles_t combined = + (cycles_t)malloc(num_cycles * (cur_max_cycle_length + 2) * sizeof(vertex_t)); + assert(combined != NULL, "Error allocating memory for the combined cycles\n"); + for (cycle_index_t i = 0; i < num_cycles - num_new_cycles; i++) { + for (cycle_length_t j = 0; j < cycles_max_cycle_length + 2; j++) { + combined[i * (cur_max_cycle_length + 2) + j] = + cycles[i * (cycles_max_cycle_length + 2) + j]; + } + } + for (cycle_index_t i = 0; i < num_new_cycles; i++) { + for (cycle_length_t j = 0; j < cur_max_cycle_length + 2; j++) { + combined[(num_cycles - num_new_cycles + i) * + (cur_max_cycle_length + 2) + + j] = + new_cycles[i * (cur_max_cycle_length + 2) + j]; + } + } + cycles_max_cycle_length = cur_max_cycle_length; + free(cycles); + free(new_cycles); + cycles = combined; + } + } + + if (genus_lower_bound < PRE_GENUS_LOWER_BOUND) { + continue; + } + + cycle_index_t searched_fit = genus_lower_bound_implied_fit; + bool same_target_fit = last_searched_fit == searched_fit; + cycle_length_t required_length = same_target_fit ? cur_max_cycle_length : 0; + cycle_index_t min_shortest_cycles; + bool length_possible = + length_composition_possible(2 * num_edges, searched_fit, cycle_length_available, + cur_max_cycle_length, smallest_cycle_length, + required_length, &min_shortest_cycles); + + if (length_possible && min_shortest_cycles > max_shortest_cycles) { + length_possible = false; + if (PRINT_PROGRESS) { + fprintf(stderr, + "Any such fit needs at least %" PRIcycle_index_t + " shortest cycles, but at most %" PRIcycle_index_t + " can be packed. Skipping search.\n", + min_shortest_cycles, max_shortest_cycles); + } + } + + uint64_t shortest_packing_slack = + 2 * (uint64_t)num_edges - + (uint64_t)min_shortest_cycles * smallest_cycle_length; + if (length_possible && min_shortest_cycles > verified_packable_shortest_cycles && + shortest_packing_slack <= 2 * (uint64_t)smallest_cycle_length) { + uint64_t num_packing_calls = 0; + packing_result_t packing_result = can_pack_shortest_cycles( + num_vertices, num_edges, adjacency_list, cycles, cur_max_cycle_length, + smallest_cycle_length, num_shortest_cycles, min_shortest_cycles, + &num_packing_calls); + if (packing_result == PACKING_IMPOSSIBLE) { + max_shortest_cycles = min_shortest_cycles - 1; + length_possible = false; + if (PRINT_PROGRESS) { + fprintf(stderr, + "Proved at most %" PRIcycle_index_t + " shortest cycles can be packed in %" PRId64 + " packing iterations. Skipping search.\n", + max_shortest_cycles, num_packing_calls); + } + } else if (packing_result == PACKING_FOUND) { + verified_packable_shortest_cycles = min_shortest_cycles; + } else if (PRINT_PROGRESS) { + fprintf(stderr, + "Shortest-cycle packing check inconclusive after %" PRId64 + " iterations; continuing with full search.\n", + num_packing_calls); + } + } + + if (!length_possible) { + last_searched_fit = searched_fit; + cycle_index_t future_fit_upper_bound = max_possible_fit_with_shortest_bound( + num_edges, smallest_cycle_length, second_smallest_cycle_length, + max_shortest_cycles, cur_max_cycle_length + 1); + cycle_index_t genus_lower_bound_from_fit_bound = + genus_lower_bound_from_fit_upper_bound(future_fit_upper_bound, num_vertices, + num_edges); + if (genus_lower_bound_from_fit_bound > genus_lower_bound) { + genus_lower_bound = genus_lower_bound_from_fit_bound; + if (PRINT_PROGRESS) { + fprintf(stderr, "Found proof the implied fit does not exist. "); + } + } else if (PRINT_PROGRESS) { + fprintf(stderr, + "Did not find proof the fit does not exist, cannot increase " + "lowerbound. "); + } + genus_lower_bound_implied_fit = + implied_max_fit_for_genus(genus_lower_bound, num_vertices, num_edges); + genus_upper_bound = implied_max_genus_for_fit(max_fit, num_vertices, num_edges); + bool target_fit_changed = genus_lower_bound_implied_fit != searched_fit; + + if (genus_lower_bound == genus_upper_bound && !FIND_FULL_CYCLE_FITTING) { + fprintf(stderr, "The genus is %" PRIcycle_index_t ".\n", genus_lower_bound); + graph_free(adjacency_list); + free(cycles); + free(cycle_length_available); + fclose(output_file); + return 0; + } + + if (PRINT_PROGRESS) { + fprintf(stderr, + "Narrowing down the genus to " + "between %" PRIcycle_index_t " and %" PRIcycle_index_t ". Used %" PRId64 + " iterations so far.\n", + genus_lower_bound, genus_upper_bound, num_search_calls); + } + if (target_fit_changed) { + cur_max_cycle_length--; + } + continue; + } + + cycle_index_t max_cycles_per_vertex; + cbv_t cycles_by_vertex = cbv_generate(num_vertices, cycles, num_cycles, + cur_max_cycle_length, &max_cycles_per_vertex); + cycle_index_t max_cycles_per_edge; + cbe_t cycles_by_edge = + cbe_generate(num_vertices, cycles, num_cycles, cur_max_cycle_length, + &max_cycles_per_edge); + + if (PRINT_PROGRESS) { + fprintf(stderr, + "Starting search for fit with %" PRIcycle_index_t + " cycles or proof it doesn't exist (genus between %" PRIcycle_index_t + " and %" PRIcycle_index_t ")...\n", + genus_lower_bound_implied_fit, genus_lower_bound, genus_upper_bound); + } + show_progress(0.0); + + // keep track of used cycles and vertices + bool* used_cycles = (bool*)calloc(num_cycles, sizeof(bool)); + assert(used_cycles != NULL, "Error allocating memory for the used cycles\n"); + // vertices should be used exactly VERTEX_USE_LIMIT times + // so we keep track of the number of times each vertex has been used. + // this allows us to fail early if a vertex can't be used enough times + // and to prioritize vertices exploring vertices that have been used more + // since they constrain the number of possible cycles containing them more + degree_t* vertex_uses = (degree_t*)malloc(num_vertices * sizeof(degree_t)); + assert(vertex_uses != NULL, "Error allocating memory for the vertices most used order\n"); + transitions_used_size = (size_t)num_vertices * VERTEX_DEGREE * VERTEX_DEGREE; + transitions_used = (bool*)malloc(transitions_used_size * sizeof(bool)); + assert(transitions_used != NULL, + "Error allocating memory for the used transition table\n"); + cycle_edge_conflicts_init(num_cycles); + rotation_state_init(num_vertices); + + vertex_t start_vertex; + vertex_t end_vertex; + cycle_index_t num_edge_start_cycles = + choose_start_edge(num_vertices, adjacency_list, max_cycles_per_edge, cycles_by_edge, + &start_vertex, &end_vertex); + bool forced_single_new_cycle = + same_target_fit && min_shortest_cycles == searched_fit - 1; + bool use_max_length_start = + same_target_fit && + (forced_single_new_cycle || num_new_cycles <= num_edge_start_cycles); + cycle_index_t num_start_cycles_for_vertex = num_new_cycles; + cycle_index_t* fixed_edge_start_cycles = NULL; + cycle_index_t* start_cycle_order = + (cycle_index_t*)malloc(num_cycles * sizeof(cycle_index_t)); + assert(start_cycle_order != NULL, "Error allocating memory for the start cycle order\n"); + memset(start_cycle_order, 0xff, num_cycles * sizeof(cycle_index_t)); + int8_t* length_cache_without_required = NULL; + int8_t* length_cache_with_required = NULL; + cycle_index_t length_cache_width = 2 * num_edges + 1; + uint64_t length_cache_entries = (uint64_t)(searched_fit + 1) * length_cache_width; + if (length_cache_entries <= LENGTH_FEASIBILITY_CACHE_LIMIT) { + length_cache_without_required = + (int8_t*)malloc(length_cache_entries * sizeof(int8_t)); + length_cache_with_required = + (int8_t*)malloc(length_cache_entries * sizeof(int8_t)); + assert(length_cache_without_required != NULL && length_cache_with_required != NULL, + "Error allocating memory for length feasibility caches\n"); + memset(length_cache_without_required, 0xff, + length_cache_entries * sizeof(int8_t)); + memset(length_cache_with_required, 0xff, length_cache_entries * sizeof(int8_t)); + } + length_feasibility_t length_feasibility = { + .cycle_length_available = cycle_length_available, + .max_cycle_length = cur_max_cycle_length, + .shortest_length = smallest_cycle_length, + .required_length = cur_max_cycle_length, + .cache_without_required = length_cache_without_required, + .cache_with_required = length_cache_with_required, + .cache_width = length_cache_width, + }; + if (!use_max_length_start) { + fixed_edge_start_cycles = cbe_get_cycle_indices(cycles_by_edge, max_cycles_per_edge, + start_vertex, end_vertex, + &num_start_cycles_for_vertex); + } + + // If the same fit was already ruled out with shorter cycles, any new + // solution must contain a cycle of the current max length. Every fitting + // also uses the chosen directed edge exactly once, so use whichever + // valid start set is smaller. + cycle_index_t raw_start_count = + use_max_length_start ? num_new_cycles : num_start_cycles_for_vertex; + cycle_index_t* raw_start_cycles = + (cycle_index_t*)malloc((raw_start_count == 0 ? 1 : raw_start_count) * + sizeof(cycle_index_t)); + assert(raw_start_cycles != NULL, "Error allocating memory for start cycles\n"); + for (cycle_index_t start_i = 0; start_i < raw_start_count; start_i++) { + raw_start_cycles[start_i] = use_max_length_start + ? num_cycles - num_new_cycles + start_i + : fixed_edge_start_cycles[start_i]; + } + if (graph_automorphisms.maps == NULL) { + automorphism_generate(num_vertices, adjacency_list, &graph_automorphisms); + } + cycle_index_t num_start_cycles; + cycle_index_t* start_cycles = start_cycles_prune_by_symmetry( + cycles, cur_max_cycle_length, num_cycles, cycles_by_edge, max_cycles_per_edge, + raw_start_cycles, raw_start_count, &num_start_cycles); + free(raw_start_cycles); + precompute_start_cycle_order(start_cycle_order, start_cycles, num_start_cycles); + + unsigned num_start_threads = + get_start_branch_thread_count(num_start_cycles, num_cycles); + if (num_start_threads > 1) { + if (PRINT_PROGRESS) { + fprintf(stderr, + "\nSearching start-cycle branches with %u worker threads.\n", + num_start_threads); + } + bool* solution_used_cycles = (bool*)calloc(num_cycles, sizeof(bool)); + assert(solution_used_cycles != NULL, + "Error allocating memory for the parallel search solution\n"); + start_branch_search_t context = { + .num_vertices = num_vertices, + .num_edges = num_edges, + .adjacency_list = adjacency_list, + .max_cycle_length = cur_max_cycle_length, + .num_cycles = num_cycles, + .cycles = cycles, + .max_cycles_per_vertex = max_cycles_per_vertex, + .cycles_by_vertex = cycles_by_vertex, + .max_cycles_per_edge = max_cycles_per_edge, + .cycles_by_edge = cycles_by_edge, + .start_cycles = start_cycles, + .num_start_cycles = num_start_cycles, + .start_cycle_order = start_cycle_order, + .initial_cycles_to_use = genus_lower_bound_implied_fit - 1, + .max_used_cycles = genus_lower_bound_implied_fit, + .initial_max_fit = max_fit, + .initial_directed_edge_remaining = directed_edge_remaining, + .length_feasibility_template = length_feasibility, + .length_cache_entries = length_cache_entries, + .require_max_cycle_if_start_is_shorter = same_target_fit, + .solution_used_cycles = solution_used_cycles, + }; + if (search_start_cycles_parallel(&context, num_start_threads)) { + num_search_calls += context.total_search_calls; + max_fit = context.best_max_fit; + memcpy(used_cycles, solution_used_cycles, num_cycles * sizeof(bool)); + free(solution_used_cycles); + show_progress(1.0); + show_solution(genus_lower_bound, genus_lower_bound_implied_fit, num_search_calls, + num_cycles, used_cycles, cycles, cur_max_cycle_length); + graph_free(adjacency_list); + free(vertex_uses); + free(cycles); + free(cycles_by_vertex); + free(cycles_by_edge); + free(used_cycles); + free(start_cycle_order); + free(cycle_length_available); + free(length_cache_without_required); + free(length_cache_with_required); + free(start_cycles); + cycle_edge_conflicts_free(); + rotation_state_free(); + free(transitions_used); + transitions_used = NULL; + fclose(output_file); + return 0; + } + num_search_calls += context.total_search_calls; + if (context.best_max_fit > max_fit) { + max_fit = context.best_max_fit; + } + free(solution_used_cycles); + } else { + cycle_index_t start_cycles_seen = 0; + for (cycle_index_t start_i = 0; start_i < num_start_cycles; start_i++) { + cycle_index_t c = start_cycles[start_i]; + cycle_length_t cycle_length; + cycles_t cycle = cycle_get(cycles, cur_max_cycle_length, c, &cycle_length); + memset(transitions_used, 0, transitions_used_size * sizeof(bool)); + cycle_edge_conflicts_clear(num_cycles); + rotation_state_clear(num_vertices); + start_cycles_seen++; + cycle_index_t current_start_cycle_order = start_cycle_order[c]; + if (VERTEX_DEGREE > 2 && !cycle_transitions_good(cycle, cycle_length)) { + show_progress(start_cycles_seen / (double)num_start_cycles); + continue; + } + if (!cycle_try_add_rotation_system(cycle, cycle_length)) { + show_progress(start_cycles_seen / (double)num_start_cycles); + continue; + } + + memcpy(vertex_uses, initial_vertex_uses, num_vertices * sizeof(degree_t)); + + // mark start cycle as used + used_cycles[c] = true; + cycle_set_transitions(cycle, cycle_length, true); + cycle_set_edge_conflicts(cycle, cycle_length, max_cycles_per_edge, + cycles_by_edge, true); + for (cycle_length_t i = 0; i < cycle_length; i++) { + adj_remove_edge(adjacency_list, cycle[i], cycle[i + 1]); + + // mark cycle vertices as used + vertex_uses[cycle[i]] += 1; + } + + if (search(genus_lower_bound_implied_fit - 1, genus_lower_bound_implied_fit, + used_cycles, vertex_uses, &max_fit, &num_search_calls, num_vertices, + num_edges, adjacency_list, cur_max_cycle_length, num_cycles, cycles, + max_cycles_per_vertex, cycles_by_vertex, max_cycles_per_edge, + cycles_by_edge, start_cycle_order, + current_start_cycle_order, &length_feasibility, + same_target_fit && cycle_length != cur_max_cycle_length ? 1 : 0)) { + // Success! + show_progress(1.0); + show_solution(genus_lower_bound, genus_lower_bound_implied_fit, num_search_calls, + num_cycles, used_cycles, cycles, cur_max_cycle_length); + graph_free(adjacency_list); + free(vertex_uses); + free(cycles); + free(cycles_by_vertex); + free(cycles_by_edge); + free(used_cycles); + free(start_cycle_order); + free(cycle_length_available); + free(length_cache_without_required); + free(length_cache_with_required); + free(start_cycles); + cycle_edge_conflicts_free(); + rotation_state_free(); + free(transitions_used); + transitions_used = NULL; + fclose(output_file); + return 0; + } + + // mark start cycle as unused + used_cycles[c] = false; + cycle_set_transitions(cycle, cycle_length, false); + cycle_set_edge_conflicts(cycle, cycle_length, max_cycles_per_edge, + cycles_by_edge, false); + cycle_remove_rotation_system(cycle, cycle_length); + for (cycle_length_t i = 0; i < cycle_length; i++) { + adj_undo_remove_edge(adjacency_list, cycle[i], cycle[i + 1]); + } + + show_progress(start_cycles_seen / (double)num_start_cycles); + } + } + + show_progress(1.0); + last_searched_fit = searched_fit; + + // we weren't able to find the implied fit, so the bounds need adjusting + cycle_index_t future_fit_upper_bound = max_possible_fit_with_shortest_bound( + num_edges, smallest_cycle_length, second_smallest_cycle_length, + max_shortest_cycles, cur_max_cycle_length + 1); + cycle_index_t genus_lower_bound_from_fit_bound = + genus_lower_bound_from_fit_upper_bound(future_fit_upper_bound, num_vertices, + num_edges); + if (genus_lower_bound_from_fit_bound > genus_lower_bound) { + genus_lower_bound = genus_lower_bound_from_fit_bound; + if (PRINT_PROGRESS) { + fprintf(stderr, "\nFound proof the implied fit does not exist. "); + } + } else if (PRINT_PROGRESS) { + fprintf(stderr, + "\nDid not find proof the fit does not exist, cannot increase " + "lowerbound. "); + } + genus_lower_bound_implied_fit = + implied_max_fit_for_genus(genus_lower_bound, num_vertices, num_edges); + // as a bonus, we might have found a better upper bound + genus_upper_bound = implied_max_genus_for_fit(max_fit, num_vertices, num_edges); + bool target_fit_changed = genus_lower_bound_implied_fit != searched_fit; + + if (genus_lower_bound == genus_upper_bound && + (!FIND_FULL_CYCLE_FITTING || max_fit == genus_lower_bound_implied_fit)) { + // we've found the genus! + show_solution(genus_lower_bound, max_fit, num_search_calls, num_cycles, used_cycles, + cycles, cur_max_cycle_length); + free(used_cycles); + free(start_cycle_order); + free(start_cycles); + free(vertex_uses); + graph_free(adjacency_list); + free(cycles); + free(cycles_by_vertex); + free(cycles_by_edge); + free(cycle_length_available); + free(length_cache_without_required); + free(length_cache_with_required); + cycle_edge_conflicts_free(); + rotation_state_free(); + free(transitions_used); + transitions_used = NULL; + fclose(output_file); + return 0; + } + assert(FIND_FULL_CYCLE_FITTING || (genus_lower_bound < genus_upper_bound), + "Error: genus lower bound (%" PRIcycle_index_t + ") is greater than upper bound (%" PRIcycle_index_t + " from max_fit %" PRIcycle_index_t ")\n", + genus_lower_bound, genus_upper_bound, max_fit); + + if (PRINT_PROGRESS) { + fprintf(stderr, + "Narrowing down the genus to " + "between %" PRIcycle_index_t " and %" PRIcycle_index_t ". Used %" PRId64 + " iterations so far.\n", + genus_lower_bound, genus_upper_bound, num_search_calls); + } + + free(used_cycles); + free(start_cycle_order); + free(start_cycles); + free(vertex_uses); + free(cycles_by_vertex); + free(cycles_by_edge); + free(length_cache_without_required); + free(length_cache_with_required); + cycle_edge_conflicts_free(); + rotation_state_free(); + free(transitions_used); + transitions_used = NULL; + if (target_fit_changed) { + cur_max_cycle_length--; + } + } + + genus_lower_bound_implied_fit--; + genus_lower_bound = + implied_max_genus_for_fit(genus_lower_bound_implied_fit, num_vertices, num_edges); + if (PRE_GENUS_LOWER_BOUND > genus_lower_bound) { + genus_lower_bound = PRE_GENUS_LOWER_BOUND; + genus_lower_bound_implied_fit = + implied_max_fit_for_genus(genus_lower_bound, num_vertices, num_edges); + } + if (max_fit < (2 * num_edges + cycles_max_cycle_length - 1) / cycles_max_cycle_length) { + max_fit = (2 * num_edges + cycles_max_cycle_length - 1) / cycles_max_cycle_length; + genus_upper_bound = implied_max_genus_for_fit(max_fit, num_vertices, num_edges); + } + cycle_index_t max_cycles_per_vertex; + cbv_t cycles_by_vertex = cbv_generate(num_vertices, cycles, num_cycles, cycles_max_cycle_length, + &max_cycles_per_vertex); + cycle_index_t max_cycles_per_edge; + cbe_t cycles_by_edge = + cbe_generate(num_vertices, cycles, num_cycles, cycles_max_cycle_length, + &max_cycles_per_edge); + bool* used_cycles = (bool*)calloc(num_cycles, sizeof(bool)); + assert(used_cycles != NULL, "Error allocating memory for the used cycles\n"); + degree_t* vertex_uses = (degree_t*)malloc(num_vertices * sizeof(degree_t)); + assert(vertex_uses != NULL, "Error allocating memory for the vertices most used order\n"); + transitions_used_size = (size_t)num_vertices * VERTEX_DEGREE * VERTEX_DEGREE; + transitions_used = (bool*)malloc(transitions_used_size * sizeof(bool)); + assert(transitions_used != NULL, + "Error allocating memory for the used transition table\n"); + cycle_edge_conflicts_init(num_cycles); + rotation_state_init(num_vertices); + vertex_t start_vertex; + vertex_t end_vertex; + choose_start_edge(num_vertices, adjacency_list, max_cycles_per_edge, cycles_by_edge, + &start_vertex, &end_vertex); + cycle_index_t num_start_cycles_for_vertex; + cycle_index_t* start_cycle_indices = cbe_get_cycle_indices( + cycles_by_edge, max_cycles_per_edge, start_vertex, end_vertex, + &num_start_cycles_for_vertex); + if (graph_automorphisms.maps == NULL) { + automorphism_generate(num_vertices, adjacency_list, &graph_automorphisms); + } + cycle_index_t num_start_cycles; + cycle_index_t* start_cycles = start_cycles_prune_by_symmetry( + cycles, cycles_max_cycle_length, num_cycles, cycles_by_edge, max_cycles_per_edge, + start_cycle_indices, num_start_cycles_for_vertex, &num_start_cycles); + cycle_index_t* start_cycle_order = (cycle_index_t*)malloc(num_cycles * sizeof(cycle_index_t)); + assert(start_cycle_order != NULL, "Error allocating memory for the start cycle order\n"); + memset(start_cycle_order, 0xff, num_cycles * sizeof(cycle_index_t)); + precompute_start_cycle_order(start_cycle_order, start_cycles, num_start_cycles); + + while (FIND_FULL_CYCLE_FITTING ? genus_lower_bound <= genus_upper_bound + : genus_lower_bound < genus_upper_bound) { + if (PRINT_PROGRESS) { + fprintf(stderr, + "Starting search for fit with %" PRIcycle_index_t + " cycles or proof it doesn't exist (genus between %" PRIcycle_index_t + " and %" PRIcycle_index_t ")...\n", + genus_lower_bound_implied_fit, genus_lower_bound, genus_upper_bound); + } + show_progress(0.0); + + int8_t* length_cache_without_required = NULL; + int8_t* length_cache_with_required = NULL; + cycle_index_t length_cache_width = 2 * num_edges + 1; + uint64_t length_cache_entries = + (uint64_t)(genus_lower_bound_implied_fit + 1) * length_cache_width; + if (length_cache_entries <= LENGTH_FEASIBILITY_CACHE_LIMIT) { + length_cache_without_required = + (int8_t*)malloc(length_cache_entries * sizeof(int8_t)); + length_cache_with_required = + (int8_t*)malloc(length_cache_entries * sizeof(int8_t)); + assert(length_cache_without_required != NULL && length_cache_with_required != NULL, + "Error allocating memory for length feasibility caches\n"); + memset(length_cache_without_required, 0xff, + length_cache_entries * sizeof(int8_t)); + memset(length_cache_with_required, 0xff, length_cache_entries * sizeof(int8_t)); + } + length_feasibility_t length_feasibility = { + .cycle_length_available = cycle_length_available, + .max_cycle_length = cycles_max_cycle_length, + .shortest_length = smallest_cycle_length, + .required_length = 0, + .cache_without_required = length_cache_without_required, + .cache_with_required = length_cache_with_required, + .cache_width = length_cache_width, + }; + + // Every fitting uses the chosen directed edge exactly once, so it is + // enough to try the cycles that contain that edge. + unsigned num_start_threads = + get_start_branch_thread_count(num_start_cycles, num_cycles); + if (num_start_threads > 1) { + if (PRINT_PROGRESS) { + fprintf(stderr, + "\nSearching start-cycle branches with %u worker threads.\n", + num_start_threads); + } + bool* solution_used_cycles = (bool*)calloc(num_cycles, sizeof(bool)); + assert(solution_used_cycles != NULL, + "Error allocating memory for the parallel search solution\n"); + start_branch_search_t context = { + .num_vertices = num_vertices, + .num_edges = num_edges, + .adjacency_list = adjacency_list, + .max_cycle_length = cycles_max_cycle_length, + .num_cycles = num_cycles, + .cycles = cycles, + .max_cycles_per_vertex = max_cycles_per_vertex, + .cycles_by_vertex = cycles_by_vertex, + .max_cycles_per_edge = max_cycles_per_edge, + .cycles_by_edge = cycles_by_edge, + .start_cycles = start_cycles, + .num_start_cycles = num_start_cycles, + .start_cycle_order = start_cycle_order, + .initial_cycles_to_use = genus_lower_bound_implied_fit - 1, + .max_used_cycles = genus_lower_bound_implied_fit, + .initial_max_fit = max_fit, + .initial_directed_edge_remaining = directed_edge_remaining, + .length_feasibility_template = length_feasibility, + .length_cache_entries = length_cache_entries, + .require_max_cycle_if_start_is_shorter = false, + .solution_used_cycles = solution_used_cycles, + }; + if (search_start_cycles_parallel(&context, num_start_threads)) { + num_search_calls += context.total_search_calls; + max_fit = context.best_max_fit; + memcpy(used_cycles, solution_used_cycles, num_cycles * sizeof(bool)); + free(solution_used_cycles); + show_progress(1.0); + show_solution(genus_lower_bound, genus_lower_bound_implied_fit, num_search_calls, + num_cycles, used_cycles, cycles, cycles_max_cycle_length); + graph_free(adjacency_list); + free(vertex_uses); + free(cycles); + free(cycles_by_vertex); + free(cycles_by_edge); + free(used_cycles); + free(start_cycle_order); + free(start_cycles); + free(cycle_length_available); + free(length_cache_without_required); + free(length_cache_with_required); + cycle_edge_conflicts_free(); + rotation_state_free(); + free(transitions_used); + transitions_used = NULL; + fclose(output_file); + return 0; + } + num_search_calls += context.total_search_calls; + if (context.best_max_fit > max_fit) { + max_fit = context.best_max_fit; + } + free(solution_used_cycles); + } else { + cycle_index_t start_cycles_seen = 0; + for (cycle_index_t start_i = 0; start_i < num_start_cycles; start_i++) { + cycle_index_t c = start_cycles[start_i]; + cycle_length_t cycle_length; + cycles_t cycle = cycle_get(cycles, cycles_max_cycle_length, c, &cycle_length); + memset(transitions_used, 0, transitions_used_size * sizeof(bool)); + cycle_edge_conflicts_clear(num_cycles); + rotation_state_clear(num_vertices); + start_cycles_seen++; + cycle_index_t current_start_cycle_order = start_cycle_order[c]; + if (VERTEX_DEGREE > 2 && !cycle_transitions_good(cycle, cycle_length)) { + show_progress(start_cycles_seen / (double)num_start_cycles); + continue; + } + if (!cycle_try_add_rotation_system(cycle, cycle_length)) { + show_progress(start_cycles_seen / (double)num_start_cycles); + continue; + } + + memcpy(vertex_uses, initial_vertex_uses, num_vertices * sizeof(degree_t)); + + // mark start cycle as used + used_cycles[c] = true; + cycle_set_transitions(cycle, cycle_length, true); + cycle_set_edge_conflicts(cycle, cycle_length, max_cycles_per_edge, + cycles_by_edge, true); + for (cycle_length_t i = 0; i < cycle_length; i++) { + adj_remove_edge(adjacency_list, cycle[i], cycle[i + 1]); + + // mark cycle vertices as used + vertex_uses[cycle[i]] += 1; + } + + if (search(genus_lower_bound_implied_fit - 1, genus_lower_bound_implied_fit, + used_cycles, vertex_uses, &max_fit, &num_search_calls, num_vertices, + num_edges, adjacency_list, cycles_max_cycle_length, num_cycles, cycles, + max_cycles_per_vertex, cycles_by_vertex, max_cycles_per_edge, + cycles_by_edge, start_cycle_order, + current_start_cycle_order, &length_feasibility, 0)) { + // Success! + show_progress(1.0); + show_solution(genus_lower_bound, genus_lower_bound_implied_fit, num_search_calls, + num_cycles, used_cycles, cycles, cycles_max_cycle_length); + graph_free(adjacency_list); + free(vertex_uses); + free(cycles); + free(cycles_by_vertex); + free(cycles_by_edge); + free(used_cycles); + free(start_cycle_order); + free(start_cycles); + free(cycle_length_available); + free(length_cache_without_required); + free(length_cache_with_required); + cycle_edge_conflicts_free(); + rotation_state_free(); + free(transitions_used); + transitions_used = NULL; + fclose(output_file); + return 0; + } + + // mark start cycle as unused + used_cycles[c] = false; + cycle_set_transitions(cycle, cycle_length, false); + cycle_set_edge_conflicts(cycle, cycle_length, max_cycles_per_edge, + cycles_by_edge, false); + cycle_remove_rotation_system(cycle, cycle_length); + for (cycle_length_t i = 0; i < cycle_length; i++) { + adj_undo_remove_edge(adjacency_list, cycle[i], cycle[i + 1]); + } + + show_progress(start_cycles_seen / (double)num_start_cycles); + } + } + + free(length_cache_without_required); + free(length_cache_with_required); + show_progress(1.0); + fprintf(stderr, + "\nFit does not exist. Adjusting bounds. Used %" PRId64 " iterations so far.\n", + num_search_calls); + genus_lower_bound_implied_fit--; + genus_lower_bound = + implied_max_genus_for_fit(genus_lower_bound_implied_fit, num_vertices, num_edges); + } + + graph_free(adjacency_list); + free(cycles); + free(cycles_by_vertex); + free(cycles_by_edge); + free(used_cycles); + free(start_cycle_order); + free(start_cycles); + free(vertex_uses); + free(cycle_length_available); + cycle_edge_conflicts_free(); + rotation_state_free(); + free(transitions_used); + transitions_used = NULL; + fclose(output_file); + + if (FIND_FULL_CYCLE_FITTING) { + fprintf(stderr, + "Was not able to fit any cycles. Double check the settings " + "and adjacency list.\n"); + return 1; + } else { + fprintf(stderr, "The genus is %" PRIcycle_index_t ".\n", genus_lower_bound); + return 0; + } +} + +void show_solution(cycle_index_t genus_lower_bound, cycle_index_t genus_lower_bound_implied_fit, + uint64_t num_search_calls, cycle_index_t num_cycles, bool* used_cycles, + cycles_t cycles, cycle_length_t max_cycle_length) { + if (PRINT_PROGRESS) { + fprintf(stderr, + "\nFound a solution! The genus is %" PRIcycle_index_t + ". Check the output for the %" PRIcycle_index_t " cycles. \n", + genus_lower_bound, genus_lower_bound_implied_fit); + } + fprintf(output_file, + "Solution with %" PRIcycle_index_t " cycles (genus %" PRIcycle_index_t + ") found in %" PRId64 " iterations:\n", + genus_lower_bound_implied_fit, genus_lower_bound, num_search_calls); + for (cycle_index_t i = 0; i < num_cycles; i++) { + if (used_cycles[i]) { + cycle_length_t cycle_length; + cycles_t cycle = cycle_get(cycles, max_cycle_length, i, &cycle_length); + for (cycle_length_t j = 0; j < cycle_length + 1; j++) { + fprintf(output_file, "%" PRIvertex_t " ", cycle[j] + ADJACENCY_LIST_START); + } + fprintf(output_file, "\n"); + } + } +} + +static int prev_percent = -1; +void show_progress(double fraction) { + // E.g. [########## ] 50% + + if (!PRINT_PROGRESS || ((int)(fraction * 100) == prev_percent)) { + return; + } + + if (!PROGRESS_BAR_NEWLINE) { + fflush(stderr); + fprintf(stderr, "\r["); + } else { + fprintf(stderr, "["); + } + for (int i = 0; i < 50; i++) { + if (i < fraction * 50) { + fprintf(stderr, "#"); + } else { + fprintf(stderr, " "); + } + } + fprintf(stderr, "] %d%%", (int)(fraction * 100)); + if (PROGRESS_BAR_NEWLINE) { + fprintf(stderr, "\n"); + } + prev_percent = (int)(fraction * 100); +} + +bool search(cycle_index_t cycles_to_use, // state + cycle_index_t max_used_cycles, // state + bool* used_cycles, // state + degree_t* vertex_uses, cycle_index_t* max_fit, // state + uint64_t* num_search_calls, // state + vertex_t num_vertices, edge_t num_edges, adj_t adjacency_list, + cycle_length_t max_cycle_length, cycle_index_t num_cycles, cycles_t cycles, + cycle_index_t max_cycles_per_vertex, cbv_t cycles_by_vertex, + cycle_index_t max_cycles_per_edge, cbe_t cycles_by_edge, + cycle_index_t* start_cycle_order, cycle_index_t current_start_cycle_order, + length_feasibility_t* length_feasibility, + cycle_index_t required_cycles_to_use) { + if (search_stop_requested != NULL && atomic_load(search_stop_requested)) { + return false; + } + (*num_search_calls)++; + + // Pick the tightest uncovered directed-edge column to explore, DLX style. + // Vertex-use limits are secondary row constraints: a candidate row is + // counted only if it still fits all vertex capacities. + vertex_t vertex = 0; + bool found = false; + cycle_index_t* cycle_indices = NULL; + cycle_index_t num_cycles_for_column = 0; + if (CONSTRAINED_BY_TWO) { + degree_t max_column_pressure = 0; + cycle_index_t min_cycle_options = MAX_CYCLES; + // Degree-5 incidence-style graphs have enough symmetric rows that exact + // column lookahead can dominate; row acceptance still checks conflicts. + // TODO: figure out the proper reason and make the optimal fix/tuning for all graphs. + bool exact_column_count = VERTEX_DEGREE != 5; + + for (vertex_t i = 0; i < num_vertices; i++) { + vertex_t* neighbors = adj_get_neighbors(adjacency_list, i); + for (degree_t j = 0; j < VERTEX_DEGREE; j++) { + if (neighbors[j] == MAX_VERTICES || !adj_slot_has_edge(i, j)) { + continue; + } + + cycle_index_t num_cycles_for_constraint; + cycle_index_t* cycle_indices_for_edge = + cbe_get_cycle_indices(cycles_by_edge, max_cycles_per_edge, i, neighbors[j], + &num_cycles_for_constraint); + cycle_index_t cycle_options = 0; + degree_t column_pressure = vertex_uses[i] + vertex_uses[neighbors[j]]; + for (cycle_index_t k = 0; k < num_cycles_for_constraint; k++) { + cycle_index_t cycle_index = cycle_indices_for_edge[k]; + if (cycle_search_candidate_usable( + used_cycles, vertex_uses, adjacency_list, cycles, + max_cycle_length, cycle_index, start_cycle_order, + current_start_cycle_order, cycles_to_use, + length_feasibility, required_cycles_to_use, + exact_column_count, false, NULL, NULL, NULL)) { + cycle_options++; + if (found && + (cycle_options > min_cycle_options || + (cycle_options == min_cycle_options && + column_pressure <= max_column_pressure))) { + break; + } + } + } + + if (!found || cycle_options < min_cycle_options || + (cycle_options == min_cycle_options && + column_pressure > max_column_pressure)) { + found = true; + vertex = i; + cycle_indices = cycle_indices_for_edge; + num_cycles_for_column = num_cycles_for_constraint; + max_column_pressure = column_pressure; + min_cycle_options = cycle_options; + + if (min_cycle_options == 0) { + break; // we can't do better than this + } + } + } + if (min_cycle_options == 0) { + break; // we can't do better than this + } + } + + } else { + // we pick the most used vertex that hasn't reached the limit since it + // constrains the search space of possible cycles more + degree_t max_uses = 0; + for (vertex_t i = 0; i < num_vertices; i++) { + if (vertex_uses[i] < VERTEX_USE_LIMIT && (!found || vertex_uses[i] > max_uses)) { + found = true; + vertex = i; + max_uses = vertex_uses[i]; + + if (max_uses == VERTEX_USE_LIMIT - 1) { + break; // we can't do better than this + } + } + } + + if (found) { + cycle_indices = cbv_get_cycle_indices(cycles_by_vertex, max_cycles_per_vertex, vertex, + &num_cycles_for_column); + } + } + // if we've explored all vertices fully, this cannot be extended further + if (!found) { + return false; + } + if (num_cycles_for_column == 0) { + return false; + } + + // if we've reached a new maximum fit, print it + if (max_used_cycles - cycles_to_use > *max_fit) { + // make sure all vertices are fully used + bool all_used = true; + for (vertex_t i = 0; i < num_vertices; i++) { + if (vertex_uses[i] < VERTEX_USE_LIMIT) { + all_used = false; + break; + } + } + + if (all_used) { + *max_fit = max_used_cycles - cycles_to_use; + page_mutex_lock(&output_file_mutex); + fprintf(output_file, + "New max fit: %" PRIcycle_index_t " (about to try vertex %" PRIvertex_t ")\n", + *max_fit, vertex); + for (cycle_index_t i = 0; i < num_cycles; i++) { + if (used_cycles[i]) { + cycle_length_t cycle_length; + vertex_t* cycle = cycle_get(cycles, max_cycle_length, i, &cycle_length); + for (cycle_length_t j = 0; j < cycle_length + 1; j++) { + fprintf(output_file, "%" PRIvertex_t " ", cycle[j] + ADJACENCY_LIST_START); + } + fprintf(output_file, "\n"); + } + } + fprintf(output_file, "\n"); + fflush(output_file); + page_mutex_unlock(&output_file_mutex); + } + } + + // Look through the possible cycles that satisfy the selected column. + for (cycle_index_t i = 0; i < num_cycles_for_column; i++) { + // skip if the cycle is already used + cycle_index_t cycle_index = cycle_indices[i]; + cycle_length_t cycle_length; + vertex_t* cycle; + cycle_index_t next_required_cycles_to_use; + if (!cycle_search_candidate_usable( + used_cycles, vertex_uses, adjacency_list, cycles, max_cycle_length, + cycle_index, start_cycle_order, current_start_cycle_order, cycles_to_use, + length_feasibility, required_cycles_to_use, true, true, &cycle_length, + &cycle, &next_required_cycles_to_use)) { + continue; + } + if (!cycle_try_add_rotation_system(cycle, cycle_length)) { + continue; + } + + // use the cycle + used_cycles[cycle_index] = true; + cycle_set_transitions(cycle, cycle_length, true); + cycle_set_edge_conflicts(cycle, cycle_length, max_cycles_per_edge, + cycles_by_edge, true); + for (cycle_length_t j = 0; j < cycle_length; j++) { + adj_remove_edge(adjacency_list, cycle[j], cycle[j + 1]); + + // mark cycle vertices as used + vertex_uses[cycle[j]]++; + assert(vertex_uses[cycle[j]] <= VERTEX_USE_LIMIT, + "\nVertex %" PRIvertex_t " used too many times\n", cycle[j]); + } + + // if this is the final cycle needed to cover all edges, we're done + bool is_final_cycle = + FIND_FULL_CYCLE_FITTING + ? cycles_to_use == 1 + : (cycles_to_use == 1 || + implied_max_genus_for_fit(max_used_cycles - cycles_to_use + 1, num_vertices, + num_edges) == + implied_max_genus_for_fit(max_used_cycles, num_vertices, num_edges)); + if (is_final_cycle) { + if (next_required_cycles_to_use > 0) { + used_cycles[cycle_index] = false; + cycle_set_transitions(cycle, cycle_length, false); + cycle_set_edge_conflicts(cycle, cycle_length, max_cycles_per_edge, + cycles_by_edge, false); + cycle_remove_rotation_system(cycle, cycle_length); + for (cycle_length_t j = 0; j < cycle_length; j++) { + adj_undo_remove_edge(adjacency_list, cycle[j], cycle[j + 1]); + + // un-use the cycle vertices + vertex_uses[cycle[j]]--; + } + continue; + } + if (FIND_FULL_CYCLE_FITTING && !cubic_exact_cover_mode) { + // check that all vertices have been used enough times + bool all_vertices_used = true; + for (vertex_t i = 0; i < num_vertices; i++) { + if (vertex_uses[i] < VERTEX_USE_LIMIT) { + all_vertices_used = false; + break; + } + } + if (!all_vertices_used) { + used_cycles[cycle_index] = false; + cycle_set_transitions(cycle, cycle_length, false); + cycle_set_edge_conflicts(cycle, cycle_length, max_cycles_per_edge, + cycles_by_edge, false); + cycle_remove_rotation_system(cycle, cycle_length); + for (cycle_length_t j = 0; j < cycle_length; j++) { + adj_undo_remove_edge(adjacency_list, cycle[j], cycle[j + 1]); + + // un-use the cycle vertices + vertex_uses[cycle[j]]--; + } + continue; + } + } + return true; + } + + // otherwise, continue adding cycles + if (search(cycles_to_use - 1, max_used_cycles, used_cycles, vertex_uses, max_fit, + num_search_calls, num_vertices, num_edges, adjacency_list, max_cycle_length, + num_cycles, cycles, max_cycles_per_vertex, cycles_by_vertex, + max_cycles_per_edge, cycles_by_edge, + start_cycle_order, current_start_cycle_order, length_feasibility, + next_required_cycles_to_use)) { + return true; // as soon as we succeed, we're done + } + + // un-use the cycle + used_cycles[cycle_index] = false; + cycle_set_transitions(cycle, cycle_length, false); + cycle_set_edge_conflicts(cycle, cycle_length, max_cycles_per_edge, + cycles_by_edge, false); + cycle_remove_rotation_system(cycle, cycle_length); + for (cycle_length_t j = 0; j < cycle_length; j++) { + adj_undo_remove_edge(adjacency_list, cycle[j], cycle[j + 1]); + + // un-use the cycle vertices + vertex_uses[cycle[j]]--; + } + } + + // if we haven't returned true by now, we've failed + return false; +} + +degree_t adj_neighbor_index(adj_t adjacency_list, vertex_t vertex, vertex_t neighbor) { + vertex_t* neighbors = adj_get_neighbors(adjacency_list, vertex); + for (degree_t i = 0; i < VERTEX_DEGREE; i++) { + if (neighbors[i] == neighbor) { + return i; + } + } + assert(false, "Error finding neighbor %" PRIvertex_t " of vertex %" PRIvertex_t "\n", + neighbor, vertex); + return 0; +} + +bool cycle_edges_available(adj_t adjacency_list, vertex_t* cycle, cycle_length_t cycle_length) { + for (cycle_length_t i = 0; i < cycle_length; i++) { + if (!adj_has_edge(adjacency_list, cycle[i], cycle[i + 1])) { + return false; + } + } + return true; +} + +bool cycle_vertex_uses_fit(vertex_t* cycle, cycle_length_t cycle_length, + degree_t* vertex_uses) { + for (cycle_length_t i = 0; i < cycle_length; i++) { + degree_t projected_uses = vertex_uses[cycle[i]] + 1; + for (cycle_length_t j = 0; j < i; j++) { + if (cycle[j] == cycle[i]) { + projected_uses++; + } + } + if (projected_uses > VERTEX_USE_LIMIT) { + return false; + } + } + return true; +} + +void cycle_edge_conflicts_init(cycle_index_t num_cycles) { + cycle_index_t slots = num_cycles == 0 ? 1 : num_cycles; + cycle_edge_conflicts = (cycle_index_t*)calloc(slots, sizeof(cycle_index_t)); + assert(cycle_edge_conflicts != NULL, + "Error allocating memory for cycle edge conflicts\n"); +} + +void cycle_edge_conflicts_clear(cycle_index_t num_cycles) { + assert(cycle_edge_conflicts != NULL, + "Error clearing uninitialized cycle edge conflicts\n"); + memset(cycle_edge_conflicts, 0, num_cycles * sizeof(cycle_index_t)); +} + +void cycle_edge_conflicts_free(void) { + free(cycle_edge_conflicts); + cycle_edge_conflicts = NULL; +} + +bool candidate_length_possible(cycle_length_t cycle_length, + cycle_index_t cycles_to_use, + length_feasibility_t* length_feasibility, + cycle_index_t required_cycles_to_use) { + if (cycle_length > num_edges_remaining) { + return false; + } + + if (((cycles_to_use - 1) * smallest_cycle_length > num_edges_remaining - cycle_length) || + ((cycles_to_use - 1) * length_feasibility->max_cycle_length < + num_edges_remaining - cycle_length)) { + return false; + } + + cycle_index_t remaining_required_cycles_to_use = required_cycles_to_use; + if (remaining_required_cycles_to_use > 0 && + cycle_length == length_feasibility->required_length) { + remaining_required_cycles_to_use--; + } + return cached_length_composition_possible(length_feasibility, + num_edges_remaining - cycle_length, + cycles_to_use - 1, + remaining_required_cycles_to_use); +} + +void cycle_set_edge_conflicts(vertex_t* cycle, cycle_length_t cycle_length, + cycle_index_t max_cycles_per_edge, cbe_t cycles_by_edge, + bool used) { + assert(cycle_edge_conflicts != NULL, + "Error updating uninitialized cycle edge conflicts\n"); + for (cycle_length_t i = 0; i < cycle_length; i++) { + cycle_index_t num_cycles_for_edge; + cycle_index_t* cycle_indices = + cbe_get_cycle_indices(cycles_by_edge, max_cycles_per_edge, cycle[i], + cycle[i + 1], &num_cycles_for_edge); + for (cycle_index_t j = 0; j < num_cycles_for_edge; j++) { + cycle_index_t cycle_index = cycle_indices[j]; + if (used) { + cycle_edge_conflicts[cycle_index]++; + } else { + assert(cycle_edge_conflicts[cycle_index] > 0, + "Error removing missing cycle edge conflict\n"); + cycle_edge_conflicts[cycle_index]--; + } + } + } +} + +bool cycle_search_candidate_usable(bool* used_cycles, degree_t* vertex_uses, + adj_t adjacency_list, cycles_t cycles, + cycle_length_t max_cycle_length, + cycle_index_t cycle_index, + cycle_index_t* start_cycle_order, + cycle_index_t current_start_cycle_order, + cycle_index_t cycles_to_use, + length_feasibility_t* length_feasibility, + cycle_index_t required_cycles_to_use, + bool check_row_constraints, + bool check_transitions, + cycle_length_t* cycle_length_out, + vertex_t** cycle_out, + cycle_index_t* next_required_cycles_to_use) { + if (start_cycle_order[cycle_index] < current_start_cycle_order || + used_cycles[cycle_index]) { + return false; + } + + cycle_length_t cycle_length; + vertex_t* cycle = cycle_get(cycles, max_cycle_length, cycle_index, &cycle_length); + cycle_index_t remaining_required_cycles_to_use = required_cycles_to_use; + if (remaining_required_cycles_to_use > 0 && + cycle_length == length_feasibility->required_length) { + remaining_required_cycles_to_use--; + } + if (!candidate_length_possible(cycle_length, cycles_to_use, length_feasibility, + required_cycles_to_use)) { + return false; + } + + if (check_row_constraints) { + (void)adjacency_list; + assert(cycle_edge_conflicts != NULL, "Error: cycle edge conflicts not initialized\n"); + if (cycle_edge_conflicts[cycle_index] != 0 || + (!cubic_exact_cover_mode && + !cycle_vertex_uses_fit(cycle, cycle_length, vertex_uses))) { + return false; + } + } + + if (check_transitions && VERTEX_DEGREE > 2 && + !cycle_transitions_good(cycle, cycle_length)) { + return false; + } + + if (cycle_length_out != NULL) { + *cycle_length_out = cycle_length; + } + if (cycle_out != NULL) { + *cycle_out = cycle; + } + if (next_required_cycles_to_use != NULL) { + *next_required_cycles_to_use = remaining_required_cycles_to_use; + } + return true; +} + +bool cycle_transitions_good(vertex_t* cycle, cycle_length_t cycle_length) { + for (cycle_length_t i = 0; i < cycle_length; i++) { + vertex_t center = cycle[i]; + if (vertex_degrees[center] <= 2) { + continue; + } + + vertex_t prev = i == 0 ? cycle[cycle_length - 1] : cycle[i - 1]; + vertex_t next = i + 1 == cycle_length ? cycle[0] : cycle[i + 1]; + degree_t prev_index = adj_neighbor_index(full_adjacency_list, center, prev); + degree_t next_index = adj_neighbor_index(full_adjacency_list, center, next); + size_t reverse_transition_index = + ((size_t)center * VERTEX_DEGREE + next_index) * VERTEX_DEGREE + prev_index; + if (transitions_used[reverse_transition_index]) { + return false; + } + } + return true; +} + +void cycle_set_transitions(vertex_t* cycle, cycle_length_t cycle_length, bool used) { + for (cycle_length_t i = 0; i < cycle_length; i++) { + vertex_t center = cycle[i]; + if (vertex_degrees[center] <= 2) { + continue; + } + + vertex_t prev = i == 0 ? cycle[cycle_length - 1] : cycle[i - 1]; + vertex_t next = i + 1 == cycle_length ? cycle[0] : cycle[i + 1]; + degree_t prev_index = adj_neighbor_index(full_adjacency_list, center, prev); + degree_t next_index = adj_neighbor_index(full_adjacency_list, center, next); + size_t transition_index = + ((size_t)center * VERTEX_DEGREE + prev_index) * VERTEX_DEGREE + next_index; + transitions_used[transition_index] = used; + } +} + +unsigned get_online_processor_count(void) { +#ifdef _WIN32 + SYSTEM_INFO system_info; + GetSystemInfo(&system_info); + return system_info.dwNumberOfProcessors > 0 ? system_info.dwNumberOfProcessors : 1; +#elif defined(_SC_NPROCESSORS_ONLN) + long online_processors = sysconf(_SC_NPROCESSORS_ONLN); + return online_processors > 0 ? (unsigned)online_processors : 1; +#else + return 1; +#endif +} + +unsigned get_start_branch_thread_count(cycle_index_t num_start_cycles, + cycle_index_t num_cycles) { + if (num_start_cycles < 4) { + return 1; + } + + char* thread_env = getenv("CG_THREADS"); + if (thread_env == NULL || thread_env[0] == '\0') { + thread_env = getenv("THREADS"); + } + bool explicit_thread_count = thread_env != NULL && thread_env[0] != '\0'; + unsigned threads = 0; + if (explicit_thread_count) { + char* end = NULL; + unsigned long parsed = strtoul(thread_env, &end, 10); + if (end != thread_env && parsed > 0) { + threads = parsed > START_BRANCH_THREAD_CAP ? START_BRANCH_THREAD_CAP + : (unsigned)parsed; + } + } else { + if (num_cycles < START_BRANCH_PARALLEL_MIN_CYCLES) { + return 1; + } + threads = get_online_processor_count(); + if (threads > START_BRANCH_THREAD_CAP) { + threads = START_BRANCH_THREAD_CAP; + } + } + + if (threads < 2) { + return 1; + } + if (threads > num_start_cycles) { + threads = num_start_cycles; + } + return threads; +} + +void precompute_start_cycle_order(cycle_index_t* start_cycle_order, + cycle_index_t* start_cycles, + cycle_index_t num_start_cycles) { + for (cycle_index_t i = 0; i < num_start_cycles; i++) { + start_cycle_order[start_cycles[i]] = i; + } +} + +bool search_start_cycles_parallel(start_branch_search_t* context, + unsigned num_threads) { + context->next_start_index = 0; + context->completed_start_cycles = 0; + context->best_max_fit = context->initial_max_fit; + context->total_search_calls = 0; + context->solution_found = false; + atomic_init(&context->stop_requested, false); + assert(page_mutex_init(&context->mutex) == 0, + "Error initializing start branch mutex\n"); +#ifdef _WIN32 + page_worker_state_tls = TlsAlloc(); + assert(page_worker_state_tls != TLS_OUT_OF_INDEXES, + "Error allocating start branch worker TLS\n"); +#endif + + page_thread_t* threads = (page_thread_t*)malloc(num_threads * sizeof(page_thread_t)); + assert(threads != NULL, "Error allocating start branch threads\n"); + for (unsigned i = 0; i < num_threads; i++) { + assert(page_thread_create(&threads[i], start_branch_worker, context) == 0, + "Error creating start branch worker thread\n"); + } + for (unsigned i = 0; i < num_threads; i++) { + assert(page_thread_join(threads[i]) == 0, + "Error joining start branch worker thread\n"); + } + free(threads); +#ifdef _WIN32 + TlsFree(page_worker_state_tls); + page_worker_state_tls = TLS_OUT_OF_INDEXES; +#endif + page_mutex_destroy(&context->mutex); + return context->solution_found; +} + +PAGE_THREAD_RETURN start_branch_worker(void* arg) { +#ifdef _WIN32 + page_worker_state_t worker_state = {0}; + assert(TlsSetValue(page_worker_state_tls, &worker_state) != 0, + "Error setting start branch worker TLS\n"); +#endif + start_branch_search_t* context = (start_branch_search_t*)arg; + bool* used_cycles = (bool*)calloc(context->num_cycles, sizeof(bool)); + degree_t* vertex_uses = + (degree_t*)malloc(context->num_vertices * sizeof(degree_t)); + directed_edge_remaining = + (bool*)malloc((num_directed_edges == 0 ? 1 : num_directed_edges) * sizeof(bool)); + transitions_used_size = + (size_t)context->num_vertices * VERTEX_DEGREE * VERTEX_DEGREE; + transitions_used = (bool*)malloc(transitions_used_size * sizeof(bool)); + assert(used_cycles != NULL && vertex_uses != NULL && + directed_edge_remaining != NULL && transitions_used != NULL, + "Error allocating start branch worker state\n"); + cycle_edge_conflicts_init(context->num_cycles); + rotation_state_init(context->num_vertices); + + int8_t* length_cache_without_required = NULL; + int8_t* length_cache_with_required = NULL; + if (context->length_feasibility_template.cache_without_required != NULL) { + length_cache_without_required = + (int8_t*)malloc(context->length_cache_entries * sizeof(int8_t)); + length_cache_with_required = + (int8_t*)malloc(context->length_cache_entries * sizeof(int8_t)); + assert(length_cache_without_required != NULL && length_cache_with_required != NULL, + "Error allocating worker length feasibility caches\n"); + } + length_feasibility_t length_feasibility = context->length_feasibility_template; + length_feasibility.cache_without_required = length_cache_without_required; + length_feasibility.cache_with_required = length_cache_with_required; + search_stop_requested = &context->stop_requested; + + while (!atomic_load(&context->stop_requested)) { + page_mutex_lock(&context->mutex); + if (context->solution_found || + context->next_start_index >= context->num_start_cycles) { + page_mutex_unlock(&context->mutex); + break; + } + cycle_index_t start_i = context->next_start_index++; + page_mutex_unlock(&context->mutex); + + if (length_cache_without_required != NULL) { + memset(length_cache_without_required, 0xff, + context->length_cache_entries * sizeof(int8_t)); + memset(length_cache_with_required, 0xff, + context->length_cache_entries * sizeof(int8_t)); + } + memset(used_cycles, 0, context->num_cycles * sizeof(bool)); + memcpy(vertex_uses, initial_vertex_uses, + context->num_vertices * sizeof(degree_t)); + memcpy(directed_edge_remaining, context->initial_directed_edge_remaining, + (num_directed_edges == 0 ? 1 : num_directed_edges) * sizeof(bool)); + num_edges_remaining = num_directed_edges; + memset(transitions_used, 0, transitions_used_size * sizeof(bool)); + cycle_edge_conflicts_clear(context->num_cycles); + rotation_state_clear(context->num_vertices); + + cycle_index_t c = context->start_cycles[start_i]; + cycle_length_t cycle_length; + cycles_t cycle = + cycle_get(context->cycles, context->max_cycle_length, c, &cycle_length); + bool branch_found = false; + cycle_index_t local_max_fit = context->initial_max_fit; + uint64_t local_search_calls = 0; + if ((VERTEX_DEGREE <= 2 || cycle_transitions_good(cycle, cycle_length)) && + cycle_try_add_rotation_system(cycle, cycle_length)) { + used_cycles[c] = true; + cycle_set_transitions(cycle, cycle_length, true); + cycle_set_edge_conflicts(cycle, cycle_length, context->max_cycles_per_edge, + context->cycles_by_edge, true); + for (cycle_length_t i = 0; i < cycle_length; i++) { + adj_remove_edge(context->adjacency_list, cycle[i], cycle[i + 1]); + vertex_uses[cycle[i]] += 1; + } + + cycle_index_t required_cycles_to_use = + context->require_max_cycle_if_start_is_shorter && + cycle_length != context->max_cycle_length + ? 1 + : 0; + branch_found = search( + context->initial_cycles_to_use, context->max_used_cycles, + used_cycles, vertex_uses, &local_max_fit, &local_search_calls, + context->num_vertices, context->num_edges, context->adjacency_list, + context->max_cycle_length, context->num_cycles, context->cycles, + context->max_cycles_per_vertex, context->cycles_by_vertex, + context->max_cycles_per_edge, context->cycles_by_edge, + context->start_cycle_order, start_i, &length_feasibility, + required_cycles_to_use); + } + + page_mutex_lock(&context->mutex); + context->total_search_calls += local_search_calls; + if (local_max_fit > context->best_max_fit) { + context->best_max_fit = local_max_fit; + } + if (branch_found && !context->solution_found) { + context->solution_found = true; + memcpy(context->solution_used_cycles, used_cycles, + context->num_cycles * sizeof(bool)); + atomic_store(&context->stop_requested, true); + } + context->completed_start_cycles++; + if (PRINT_PROGRESS) { + show_progress(context->completed_start_cycles / + (double)context->num_start_cycles); + } + page_mutex_unlock(&context->mutex); + } + + search_stop_requested = NULL; + free(length_cache_without_required); + free(length_cache_with_required); + cycle_edge_conflicts_free(); + rotation_state_free(); + free(transitions_used); + transitions_used = NULL; + transitions_used_size = 0; + free(directed_edge_remaining); + directed_edge_remaining = NULL; + num_edges_remaining = 0; + free(vertex_uses); + free(used_cycles); +#ifdef _WIN32 + TlsSetValue(page_worker_state_tls, NULL); +#endif + return PAGE_THREAD_RESULT; +} + +void rotation_state_init(vertex_t num_vertices) { + if (VERTEX_DEGREE <= 5) { + rotation_next = NULL; + rotation_prev = NULL; + rotation_pair_count = NULL; + rotation_state_size = 0; + return; + } + + rotation_state_size = (size_t)num_vertices * VERTEX_DEGREE; + rotation_next = (vertex_t*)malloc(rotation_state_size * sizeof(vertex_t)); + rotation_prev = (vertex_t*)malloc(rotation_state_size * sizeof(vertex_t)); + rotation_pair_count = (degree_t*)malloc(num_vertices * sizeof(degree_t)); + assert(rotation_next != NULL && rotation_prev != NULL && rotation_pair_count != NULL, + "Error allocating memory for the rotation system state\n"); + rotation_state_clear(num_vertices); +} + +void rotation_state_clear(vertex_t num_vertices) { + if (VERTEX_DEGREE <= 5) { + return; + } + + assert(rotation_state_size == (size_t)num_vertices * VERTEX_DEGREE, + "Error clearing rotation system state with unexpected size\n"); + for (size_t i = 0; i < rotation_state_size; i++) { + rotation_next[i] = MAX_VERTICES; + rotation_prev[i] = MAX_VERTICES; + } + for (vertex_t i = 0; i < num_vertices; i++) { + rotation_pair_count[i] = 0; + } +} + +void rotation_state_free(void) { + free(rotation_next); + free(rotation_prev); + free(rotation_pair_count); + rotation_next = NULL; + rotation_prev = NULL; + rotation_pair_count = NULL; + rotation_state_size = 0; +} + +bool rotation_transition_add(vertex_t center, degree_t prev_index, degree_t next_index) { + if (VERTEX_DEGREE <= 5) { + return true; + } + + size_t source = (size_t)center * VERTEX_DEGREE + prev_index; + size_t target = (size_t)center * VERTEX_DEGREE + next_index; + if (prev_index == next_index || rotation_next[source] != MAX_VERTICES || + rotation_prev[target] != MAX_VERTICES) { + return false; + } + + vertex_t component_size = 1; + bool closes_component = false; + vertex_t cursor = next_index; + while (rotation_next[(size_t)center * VERTEX_DEGREE + cursor] != MAX_VERTICES) { + cursor = rotation_next[(size_t)center * VERTEX_DEGREE + cursor]; + component_size++; + if (cursor == prev_index) { + closes_component = true; + break; + } + if (component_size > vertex_degrees[center]) { + return false; + } + } + + if (closes_component && component_size < vertex_degrees[center]) { + return false; + } + if (!closes_component && rotation_pair_count[center] + 1 == vertex_degrees[center]) { + return false; + } + + rotation_next[source] = next_index; + rotation_prev[target] = prev_index; + rotation_pair_count[center]++; + return true; +} + +void rotation_transition_remove(vertex_t center, degree_t prev_index, degree_t next_index) { + if (VERTEX_DEGREE <= 5) { + return; + } + + size_t source = (size_t)center * VERTEX_DEGREE + prev_index; + size_t target = (size_t)center * VERTEX_DEGREE + next_index; + assert(rotation_next[source] == next_index && rotation_prev[target] == prev_index && + rotation_pair_count[center] > 0, + "Error removing missing rotation system transition\n"); + rotation_next[source] = MAX_VERTICES; + rotation_prev[target] = MAX_VERTICES; + rotation_pair_count[center]--; +} + +bool cycle_try_add_rotation_system(vertex_t* cycle, cycle_length_t cycle_length) { + if (VERTEX_DEGREE <= 5) { + return true; + } + + for (cycle_length_t i = 0; i < cycle_length; i++) { + vertex_t center = cycle[i]; + vertex_t prev = i == 0 ? cycle[cycle_length - 1] : cycle[i - 1]; + vertex_t next = i + 1 == cycle_length ? cycle[0] : cycle[i + 1]; + degree_t prev_index = adj_neighbor_index(full_adjacency_list, center, prev); + degree_t next_index = adj_neighbor_index(full_adjacency_list, center, next); + if (!rotation_transition_add(center, prev_index, next_index)) { + for (cycle_length_t j = 0; j < i; j++) { + vertex_t undo_center = cycle[j]; + vertex_t undo_prev = j == 0 ? cycle[cycle_length - 1] : cycle[j - 1]; + vertex_t undo_next = j + 1 == cycle_length ? cycle[0] : cycle[j + 1]; + degree_t undo_prev_index = + adj_neighbor_index(full_adjacency_list, undo_center, undo_prev); + degree_t undo_next_index = + adj_neighbor_index(full_adjacency_list, undo_center, undo_next); + rotation_transition_remove(undo_center, undo_prev_index, undo_next_index); + } + return false; + } + } + + return true; +} + +void cycle_remove_rotation_system(vertex_t* cycle, cycle_length_t cycle_length) { + if (VERTEX_DEGREE <= 5) { + return; + } + + for (cycle_length_t i = 0; i < cycle_length; i++) { + vertex_t center = cycle[i]; + vertex_t prev = i == 0 ? cycle[cycle_length - 1] : cycle[i - 1]; + vertex_t next = i + 1 == cycle_length ? cycle[0] : cycle[i + 1]; + degree_t prev_index = adj_neighbor_index(full_adjacency_list, center, prev); + degree_t next_index = adj_neighbor_index(full_adjacency_list, center, next); + rotation_transition_remove(center, prev_index, next_index); + } +} + +cycle_index_t choose_start_edge(vertex_t num_vertices, adj_t adjacency_list, + cycle_index_t max_cycles_per_edge, cbe_t cycles_by_edge, + vertex_t* start_vertex, vertex_t* end_vertex) { + bool found_edge = false; + cycle_index_t min_cycle_options = MAX_CYCLES; + + for (vertex_t i = 0; i < num_vertices; i++) { + vertex_t* neighbors = adj_get_neighbors(adjacency_list, i); + for (degree_t j = 0; j < VERTEX_DEGREE; j++) { + if (neighbors[j] == MAX_VERTICES) { + continue; + } + + cycle_index_t cycle_options; + cbe_get_cycle_indices(cycles_by_edge, max_cycles_per_edge, i, neighbors[j], + &cycle_options); + + if (!found_edge || cycle_options < min_cycle_options) { + found_edge = true; + *start_vertex = i; + *end_vertex = neighbors[j]; + min_cycle_options = cycle_options; + + if (min_cycle_options == 0) { + break; + } + } + } + if (min_cycle_options == 0) { + break; + } + } + + assert(found_edge, "Error finding a starting edge\n"); + return min_cycle_options; +} + +bool path_has_reverse_transition(vertex_t* path, cycle_length_t path_length, vertex_t prev_vertex, + vertex_t center_vertex, vertex_t next_vertex) { + if (vertex_degrees[center_vertex] <= 2) { + return false; + } + + for (cycle_length_t i = 1; i + 1 < path_length; i++) { + if (path[i - 1] == next_vertex && path[i] == center_vertex && + path[i + 1] == prev_vertex) { + return true; + } + } + return false; +} + +adj_t adj_load(char* filename, vertex_t* num_vertices, edge_t* num_edges) { + FILE* fp = fopen(filename, "r"); + assert(fp != NULL, "Error opening file %s\n", filename); + + // number of vertices and edges are the two first numbers + assert(fscanf(fp, "%" SCNvertex_t " %" SCNedge_t "", num_vertices, num_edges) == 2, + "Error reading the first line of %s\n", filename); + + adj_t adjacency_list = (adj_t)malloc(*num_vertices * VERTEX_DEGREE * sizeof(vertex_t)); + assert(adjacency_list != NULL, "Error allocating memory for the adjacency list\n"); + vertex_degrees = (degree_t*)malloc(*num_vertices * sizeof(degree_t)); + assert(vertex_degrees != NULL, "Error allocating memory for the vertex degrees\n"); + for (vertex_t i = 0; i < *num_vertices; i++) { + vertex_degrees[i] = 0; + } + for (vertex_t i = 0; i < *num_vertices * VERTEX_DEGREE; i++) { + assert(fscanf(fp, "%" SCNvertex_t, &adjacency_list[i]) == 1, + "Error reading the adjacency list from %s\n", filename); + if (adjacency_list[i] != MAX_VERTICES) { + adjacency_list[i] -= ADJACENCY_LIST_START; + vertex_degrees[i / VERTEX_DEGREE]++; + } + } + full_adjacency_list = + (adj_t)malloc(*num_vertices * VERTEX_DEGREE * sizeof(vertex_t)); + assert(full_adjacency_list != NULL, + "Error allocating memory for the full adjacency list\n"); + for (vertex_t i = 0; i < *num_vertices * VERTEX_DEGREE; i++) { + full_adjacency_list[i] = adjacency_list[i]; + } + + cycle_index_t edge_slot_capacity = (cycle_index_t)(*num_vertices) * VERTEX_DEGREE; + num_directed_edges = 2 * (cycle_index_t)(*num_edges); + directed_edge_ids = + (cycle_index_t*)malloc(edge_slot_capacity * sizeof(cycle_index_t)); + directed_edge_remaining = + (bool*)malloc((num_directed_edges == 0 ? 1 : num_directed_edges) * sizeof(bool)); + assert(directed_edge_ids != NULL && directed_edge_remaining != NULL, + "Error allocating memory for the directed edge state\n"); + for (cycle_index_t i = 0; i < edge_slot_capacity; i++) { + directed_edge_ids[i] = MAX_CYCLES; + } + + directed_edge_lookup_capacity = 1; + while (directed_edge_lookup_capacity < 4 * num_directed_edges) { + directed_edge_lookup_capacity <<= 1; + } + directed_edge_lookup_keys = + (uint32_t*)malloc(directed_edge_lookup_capacity * sizeof(uint32_t)); + directed_edge_lookup_ids = + (cycle_index_t*)malloc(directed_edge_lookup_capacity * sizeof(cycle_index_t)); + assert(directed_edge_lookup_keys != NULL && directed_edge_lookup_ids != NULL, + "Error allocating memory for the directed edge lookup\n"); + for (cycle_index_t i = 0; i < directed_edge_lookup_capacity; i++) { + directed_edge_lookup_keys[i] = DIRECTED_EDGE_LOOKUP_EMPTY; + } + + cycle_index_t edge_id = 0; + for (vertex_t vertex = 0; vertex < *num_vertices; vertex++) { + vertex_t* neighbors = adj_get_neighbors(adjacency_list, vertex); + for (degree_t neighbor_index = 0; neighbor_index < VERTEX_DEGREE; neighbor_index++) { + if (neighbors[neighbor_index] == MAX_VERTICES) { + continue; + } + assert(edge_id < num_directed_edges, + "Error: adjacency list contains more than %" PRIcycle_index_t + " directed edges\n", + num_directed_edges); + directed_edge_ids[vertex * VERTEX_DEGREE + neighbor_index] = edge_id; + directed_edge_remaining[edge_id] = true; + directed_edge_lookup_insert(vertex, neighbors[neighbor_index], edge_id); + edge_id++; + } + } + assert(edge_id == num_directed_edges, + "Error: adjacency list contains %" PRIcycle_index_t + " directed edges, expected %" PRIcycle_index_t "\n", + edge_id, num_directed_edges); + + cubic_exact_cover_mode = VERTEX_DEGREE == 3; + for (vertex_t i = 0; i < *num_vertices && cubic_exact_cover_mode; i++) { + cubic_exact_cover_mode = vertex_degrees[i] == 3; + } + + fclose(fp); + + if (PRINT_PROGRESS) { + fprintf(stderr, "Read the adjacency list from %s\n", filename); + fprintf(stderr, "\tNumber of vertices: %" PRIvertex_t " \n", *num_vertices); + fprintf(stderr, "\tNumber of edges: %" PRIedge_t " (%" PRIedge_t " directed)\n", *num_edges, + 2 * *num_edges); + fprintf(stderr, "\tFirst 5 vertices (with neighbors): "); + vertex_t vertices_to_print = *num_vertices < 5 ? *num_vertices : 5; + degree_t neighbors_to_print = VERTEX_DEGREE < 3 ? VERTEX_DEGREE : 3; + for (vertex_t v = 0; v < vertices_to_print; v++) { + fprintf(stderr, "%" PRIvertex_t "(", v); + for (degree_t d = 0; d < neighbors_to_print; d++) { + if (d > 0) { + fprintf(stderr, " "); + } + fprintf(stderr, "%" PRIvertex_t, + adj_get_neighbors(adjacency_list, v)[d] + ADJACENCY_LIST_START); + } + fprintf(stderr, ") "); + } + fprintf(stderr, "\n"); + } + + num_edges_remaining = num_directed_edges; + return adjacency_list; +} + +vertex_t* adj_get_neighbors(adj_t adjacency_list, vertex_t vertex) { + return &adjacency_list[vertex * VERTEX_DEGREE]; +} + +void graph_free(adj_t adjacency_list) { + free(adjacency_list); + free(full_adjacency_list); + full_adjacency_list = NULL; + free(vertex_degrees); + vertex_degrees = NULL; + free(initial_vertex_uses); + initial_vertex_uses = NULL; + free(directed_edge_ids); + directed_edge_ids = NULL; + free(directed_edge_remaining); + directed_edge_remaining = NULL; + free(directed_edge_lookup_keys); + directed_edge_lookup_keys = NULL; + free(directed_edge_lookup_ids); + directed_edge_lookup_ids = NULL; + directed_edge_lookup_capacity = 0; + num_directed_edges = 0; + num_edges_remaining = 0; + cubic_exact_cover_mode = false; + automorphism_list_free(&graph_automorphisms); +} + +bool graph_has_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex) { + vertex_t* neighbors = adj_get_neighbors(adjacency_list, start_vertex); + for (degree_t i = 0; i < VERTEX_DEGREE; i++) { + if (neighbors[i] == end_vertex) { + return true; + } + } + return false; +} + +void automorphism_list_free(automorphism_list_t* automorphisms) { + free(automorphisms->maps); + automorphisms->num_vertices = 0; + automorphisms->count = 0; + automorphisms->capacity = 0; + automorphisms->maps = NULL; +} + +bool automorphism_is_identity(vertex_t* map, vertex_t num_vertices) { + for (vertex_t i = 0; i < num_vertices; i++) { + if (map[i] != i) { + return false; + } + } + return true; +} + +bool automorphism_list_contains(automorphism_list_t* automorphisms, vertex_t* map) { + for (cycle_index_t i = 0; i < automorphisms->count; i++) { + vertex_t* existing = &automorphisms->maps[i * automorphisms->num_vertices]; + if (memcmp(existing, map, automorphisms->num_vertices * sizeof(vertex_t)) == 0) { + return true; + } + } + return false; +} + +void automorphism_list_add_if_new(automorphism_list_t* automorphisms, vertex_t* map) { + if (automorphisms->count >= automorphisms->capacity || + automorphism_is_identity(map, automorphisms->num_vertices) || + automorphism_list_contains(automorphisms, map)) { + return; + } + + memcpy(&automorphisms->maps[automorphisms->count * automorphisms->num_vertices], map, + automorphisms->num_vertices * sizeof(vertex_t)); + automorphisms->count++; +} + +vertex_t* automorphism_distances_generate(vertex_t num_vertices, adj_t adjacency_list) { + vertex_t* distances = + (vertex_t*)malloc((size_t)num_vertices * num_vertices * sizeof(vertex_t)); + vertex_t* queue = (vertex_t*)malloc(num_vertices * sizeof(vertex_t)); + assert(distances != NULL && queue != NULL, + "Error allocating memory for automorphism distances\n"); + + for (vertex_t source = 0; source < num_vertices; source++) { + vertex_t* source_distances = &distances[(size_t)source * num_vertices]; + for (vertex_t i = 0; i < num_vertices; i++) { + source_distances[i] = MAX_VERTICES; + } + + cycle_index_t head = 0; + cycle_index_t tail = 0; + source_distances[source] = 0; + queue[tail++] = source; + while (head < tail) { + vertex_t vertex = queue[head++]; + vertex_t* neighbors = adj_get_neighbors(adjacency_list, vertex); + for (degree_t i = 0; i < VERTEX_DEGREE; i++) { + vertex_t neighbor = neighbors[i]; + if (neighbor == MAX_VERTICES || + source_distances[neighbor] != MAX_VERTICES) { + continue; + } + source_distances[neighbor] = source_distances[vertex] + 1; + queue[tail++] = neighbor; + } + } + } + + free(queue); + return distances; +} + +uint64_t automorphism_mix(uint64_t hash, uint64_t value) { + hash ^= value + 0x9e3779b97f4a7c15ULL + (hash << 6) + (hash >> 2); + return hash; +} + +uint64_t* automorphism_vertex_signatures_generate(vertex_t num_vertices, vertex_t* distances) { + uint64_t* signatures = (uint64_t*)malloc(num_vertices * sizeof(uint64_t)); + vertex_t* distance_counts = (vertex_t*)malloc((num_vertices + 1) * sizeof(vertex_t)); + assert(signatures != NULL && distance_counts != NULL, + "Error allocating memory for automorphism signatures\n"); + + for (vertex_t vertex = 0; vertex < num_vertices; vertex++) { + memset(distance_counts, 0, (num_vertices + 1) * sizeof(vertex_t)); + for (vertex_t other = 0; other < num_vertices; other++) { + vertex_t distance = distances[(size_t)vertex * num_vertices + other]; + if (distance == MAX_VERTICES || distance > num_vertices) { + distance = num_vertices; + } + distance_counts[distance]++; + } + + uint64_t hash = 1469598103934665603ULL; + hash = automorphism_mix(hash, vertex_degrees[vertex]); + for (vertex_t distance = 0; distance <= num_vertices; distance++) { + hash = automorphism_mix(hash, distance_counts[distance]); + } + signatures[vertex] = hash; + } + + free(distance_counts); + return signatures; +} + +bool automorphism_candidate_ok(automorphism_search_t* state, vertex_t domain_vertex, + vertex_t image_vertex) { + if (state->inverse_map[image_vertex] != MAX_VERTICES || + vertex_degrees[domain_vertex] != vertex_degrees[image_vertex] || + state->vertex_signatures[domain_vertex] != state->vertex_signatures[image_vertex]) { + return false; + } + + for (vertex_t other = 0; other < state->num_vertices; other++) { + vertex_t other_image = state->map[other]; + if (other_image == MAX_VERTICES) { + continue; + } + if (state->distances[(size_t)domain_vertex * state->num_vertices + other] != + state->distances[(size_t)image_vertex * state->num_vertices + other_image]) { + return false; + } + if (graph_has_edge(state->adjacency_list, domain_vertex, other) != + graph_has_edge(state->adjacency_list, image_vertex, other_image)) { + return false; + } + } + + return true; +} + +void automorphism_assign(automorphism_search_t* state, vertex_t domain_vertex, + vertex_t image_vertex) { + state->map[domain_vertex] = image_vertex; + state->inverse_map[image_vertex] = domain_vertex; +} + +void automorphism_unassign(automorphism_search_t* state, vertex_t domain_vertex, + vertex_t image_vertex) { + state->map[domain_vertex] = MAX_VERTICES; + state->inverse_map[image_vertex] = MAX_VERTICES; +} + +bool automorphism_assign_fixed(automorphism_search_t* state, vertex_t domain_vertex, + vertex_t image_vertex) { + if (state->map[domain_vertex] != MAX_VERTICES) { + return state->map[domain_vertex] == image_vertex; + } + if (!automorphism_candidate_ok(state, domain_vertex, image_vertex)) { + return false; + } + automorphism_assign(state, domain_vertex, image_vertex); + return true; +} + +bool automorphism_valid(automorphism_search_t* state) { + for (vertex_t vertex = 0; vertex < state->num_vertices; vertex++) { + if (state->map[vertex] == MAX_VERTICES) { + return false; + } + vertex_t* neighbors = adj_get_neighbors(state->adjacency_list, vertex); + for (degree_t i = 0; i < VERTEX_DEGREE; i++) { + vertex_t neighbor = neighbors[i]; + if (neighbor != MAX_VERTICES && + !graph_has_edge(state->adjacency_list, state->map[vertex], + state->map[neighbor])) { + return false; + } + } + } + return true; +} + +vertex_t automorphism_choose_domain(automorphism_search_t* state, + cycle_index_t* num_candidates) { + vertex_t best_vertex = MAX_VERTICES; + cycle_index_t best_candidates = MAX_CYCLES; + + for (vertex_t vertex = 0; vertex < state->num_vertices; vertex++) { + if (state->map[vertex] != MAX_VERTICES) { + continue; + } + + cycle_index_t candidates = 0; + for (vertex_t image = 0; image < state->num_vertices; image++) { + if (automorphism_candidate_ok(state, vertex, image)) { + candidates++; + } + } + + if (candidates < best_candidates) { + best_vertex = vertex; + best_candidates = candidates; + if (best_candidates == 0) { + break; + } + } + } + + *num_candidates = best_candidates; + return best_vertex; +} + +bool automorphism_search_dfs(automorphism_search_t* state) { + if (state->calls >= state->call_limit) { + return false; + } + state->calls++; + + cycle_index_t num_candidates; + vertex_t domain_vertex = automorphism_choose_domain(state, &num_candidates); + if (domain_vertex == MAX_VERTICES) { + if (!automorphism_valid(state)) { + return false; + } + memcpy(state->result, state->map, state->num_vertices * sizeof(vertex_t)); + return true; + } + if (num_candidates == 0) { + return false; + } + + for (vertex_t image_vertex = 0; image_vertex < state->num_vertices; image_vertex++) { + if (!automorphism_candidate_ok(state, domain_vertex, image_vertex)) { + continue; + } + + automorphism_assign(state, domain_vertex, image_vertex); + if (automorphism_search_dfs(state)) { + return true; + } + automorphism_unassign(state, domain_vertex, image_vertex); + } + + return false; +} + +bool automorphism_find_one(vertex_t num_vertices, adj_t adjacency_list, vertex_t* distances, + uint64_t* vertex_signatures, vertex_t* fixed_domain, + vertex_t* fixed_image, vertex_t fixed_count, + uint64_t call_limit, vertex_t* result, uint64_t* calls) { + automorphism_search_t state = { + .num_vertices = num_vertices, + .adjacency_list = adjacency_list, + .distances = distances, + .vertex_signatures = vertex_signatures, + .map = (vertex_t*)malloc(num_vertices * sizeof(vertex_t)), + .inverse_map = (vertex_t*)malloc(num_vertices * sizeof(vertex_t)), + .result = result, + .calls = 0, + .call_limit = call_limit, + }; + assert(state.map != NULL && state.inverse_map != NULL, + "Error allocating memory for automorphism search\n"); + for (vertex_t i = 0; i < num_vertices; i++) { + state.map[i] = MAX_VERTICES; + state.inverse_map[i] = MAX_VERTICES; + } + + bool fixed_ok = true; + for (vertex_t i = 0; i < fixed_count; i++) { + if (!automorphism_assign_fixed(&state, fixed_domain[i], fixed_image[i])) { + fixed_ok = false; + break; + } + } + + bool found = fixed_ok && automorphism_search_dfs(&state); + *calls = state.calls; + free(state.map); + free(state.inverse_map); + return found; +} + +void automorphism_generate(vertex_t num_vertices, adj_t adjacency_list, + automorphism_list_t* automorphisms) { + automorphism_list_free(automorphisms); + automorphisms->num_vertices = num_vertices; + automorphisms->capacity = AUTOMORPHISM_LIMIT; + automorphisms->count = 0; + automorphisms->maps = + (vertex_t*)malloc((size_t)AUTOMORPHISM_LIMIT * + (num_vertices == 0 ? 1 : num_vertices) * sizeof(vertex_t)); + assert(automorphisms->maps != NULL, + "Error allocating memory for graph automorphisms\n"); + + if (num_vertices == 0 || num_vertices > AUTOMORPHISM_VERTEX_LIMIT || + AUTOMORPHISM_LIMIT == 0) { + return; + } + + vertex_t* distances = automorphism_distances_generate(num_vertices, adjacency_list); + uint64_t* vertex_signatures = + automorphism_vertex_signatures_generate(num_vertices, distances); + vertex_t* result = (vertex_t*)malloc(num_vertices * sizeof(vertex_t)); + assert(result != NULL, "Error allocating memory for an automorphism result\n"); + + uint64_t total_calls = 0; + vertex_t root = 0; + vertex_t root_neighbor = MAX_VERTICES; + vertex_t* root_neighbors = adj_get_neighbors(adjacency_list, root); + for (degree_t i = 0; i < VERTEX_DEGREE; i++) { + if (root_neighbors[i] != MAX_VERTICES) { + root_neighbor = root_neighbors[i]; + break; + } + } + + for (vertex_t target = 0; target < num_vertices && + automorphisms->count < automorphisms->capacity && + total_calls < AUTOMORPHISM_TOTAL_CALL_LIMIT; + target++) { + if (vertex_signatures[root] != vertex_signatures[target]) { + continue; + } + vertex_t fixed_domain[1] = {root}; + vertex_t fixed_image[1] = {target}; + uint64_t calls; + uint64_t remaining = AUTOMORPHISM_TOTAL_CALL_LIMIT - total_calls; + uint64_t call_limit = + remaining < AUTOMORPHISM_SEED_CALL_LIMIT ? remaining : AUTOMORPHISM_SEED_CALL_LIMIT; + if (automorphism_find_one(num_vertices, adjacency_list, distances, vertex_signatures, + fixed_domain, fixed_image, 1, call_limit, result, &calls)) { + automorphism_list_add_if_new(automorphisms, result); + } + total_calls += calls; + } + + if (root_neighbor != MAX_VERTICES) { + for (vertex_t target = 0; target < num_vertices && + automorphisms->count < automorphisms->capacity && + total_calls < AUTOMORPHISM_TOTAL_CALL_LIMIT; + target++) { + if (vertex_signatures[root] != vertex_signatures[target]) { + continue; + } + vertex_t* target_neighbors = adj_get_neighbors(adjacency_list, target); + for (degree_t i = 0; i < VERTEX_DEGREE && + automorphisms->count < automorphisms->capacity && + total_calls < AUTOMORPHISM_TOTAL_CALL_LIMIT; + i++) { + vertex_t target_neighbor = target_neighbors[i]; + if (target_neighbor == MAX_VERTICES || + vertex_signatures[root_neighbor] != vertex_signatures[target_neighbor]) { + continue; + } + + vertex_t fixed_domain[2] = {root, root_neighbor}; + vertex_t fixed_image[2] = {target, target_neighbor}; + uint64_t calls; + uint64_t remaining = AUTOMORPHISM_TOTAL_CALL_LIMIT - total_calls; + uint64_t call_limit = remaining < AUTOMORPHISM_SEED_CALL_LIMIT + ? remaining + : AUTOMORPHISM_SEED_CALL_LIMIT; + if (automorphism_find_one(num_vertices, adjacency_list, distances, + vertex_signatures, fixed_domain, fixed_image, 2, + call_limit, result, &calls)) { + automorphism_list_add_if_new(automorphisms, result); + } + total_calls += calls; + } + } + } + + if (PRINT_PROGRESS && automorphisms->count > 0) { + fprintf(stderr, + "\033[2K\rFound %" PRIcycle_index_t + " graph automorphism(s) for symmetry pruning.\n", + automorphisms->count); + } + + free(result); + free(distances); + free(vertex_signatures); +} + +uint32_t directed_edge_key(vertex_t start_vertex, vertex_t end_vertex) { + assert(start_vertex != MAX_VERTICES && end_vertex != MAX_VERTICES, + "Error: invalid directed edge key %" PRIvertex_t " -> %" PRIvertex_t "\n", + start_vertex, end_vertex); + return ((uint32_t)start_vertex << 16) | end_vertex; +} + +cycle_index_t directed_edge_lookup_slot(uint32_t key, bool allow_empty) { + assert(directed_edge_lookup_capacity > 0 && directed_edge_lookup_keys != NULL, + "Error: directed edge lookup has not been initialized\n"); + cycle_index_t slot = + (cycle_index_t)((key * 2654435761u) & (directed_edge_lookup_capacity - 1)); + while (directed_edge_lookup_keys[slot] != key) { + if (directed_edge_lookup_keys[slot] == DIRECTED_EDGE_LOOKUP_EMPTY) { + if (allow_empty) { + return slot; + } + assert(false, "Error finding directed edge key %" PRIu32 "\n", key); + } + slot = (slot + 1) & (directed_edge_lookup_capacity - 1); + } + return slot; +} + +void directed_edge_lookup_insert(vertex_t start_vertex, vertex_t end_vertex, + cycle_index_t edge_id) { + uint32_t key = directed_edge_key(start_vertex, end_vertex); + cycle_index_t slot = directed_edge_lookup_slot(key, true); + assert(directed_edge_lookup_keys[slot] == DIRECTED_EDGE_LOOKUP_EMPTY, + "Error: duplicate directed edge %" PRIvertex_t " -> %" PRIvertex_t "\n", + start_vertex, end_vertex); + directed_edge_lookup_keys[slot] = key; + directed_edge_lookup_ids[slot] = edge_id; +} + +bool adj_try_edge_id(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex, + cycle_index_t* edge_id) { + (void)adjacency_list; + uint32_t key = directed_edge_key(start_vertex, end_vertex); + cycle_index_t slot = directed_edge_lookup_slot(key, true); + if (directed_edge_lookup_keys[slot] == DIRECTED_EDGE_LOOKUP_EMPTY) { + return false; + } + *edge_id = directed_edge_lookup_ids[slot]; + return true; +} + +cycle_index_t adj_edge_id(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex) { + cycle_index_t edge_id; + assert(adj_try_edge_id(adjacency_list, start_vertex, end_vertex, &edge_id), + "Error finding directed edge %" PRIvertex_t " -> %" PRIvertex_t "\n", + start_vertex, end_vertex); + return edge_id; +} + +bool adj_slot_has_edge(vertex_t start_vertex, degree_t neighbor_index) { + cycle_index_t edge_id = directed_edge_ids[start_vertex * VERTEX_DEGREE + neighbor_index]; + return edge_id != MAX_CYCLES && directed_edge_remaining[edge_id]; +} + +void adj_remove_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex) { + cycle_index_t edge_id = adj_edge_id(adjacency_list, start_vertex, end_vertex); + assert(directed_edge_remaining[edge_id], + "Error: directed edge %" PRIvertex_t " -> %" PRIvertex_t + " was removed twice\n", + start_vertex, end_vertex); + num_edges_remaining -= 1; + directed_edge_remaining[edge_id] = false; +} + +// must have been previously removed, otherwise undefined behavior +void adj_undo_remove_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex) { + cycle_index_t edge_id = adj_edge_id(adjacency_list, start_vertex, end_vertex); + assert(!directed_edge_remaining[edge_id], + "Error: directed edge %" PRIvertex_t " -> %" PRIvertex_t + " was restored before being removed\n", + start_vertex, end_vertex); + num_edges_remaining += 1; + directed_edge_remaining[edge_id] = true; +} + +bool adj_has_edge(adj_t adjacency_list, vertex_t start_vertex, vertex_t end_vertex) { + cycle_index_t edge_id; + if (!adj_try_edge_id(adjacency_list, start_vertex, end_vertex, &edge_id)) { + return false; + } + return directed_edge_remaining[edge_id]; +} + +struct fifo { + vertex_t* data; + cycle_index_t head; + cycle_index_t tail; + cycle_index_t capacity; + cycle_length_t path_length; +}; +void fifo_init(struct fifo* fifo, cycle_index_t initial_capacity, cycle_length_t path_length) { + fifo->data = (vertex_t*)malloc(initial_capacity * path_length * sizeof(vertex_t)); + assert(fifo->data != NULL, "Error allocating memory for the fifo\n"); + fifo->head = 0; + fifo->tail = 0; + fifo->capacity = initial_capacity; + fifo->path_length = path_length; +} +bool fifo_empty(struct fifo* fifo) { return fifo->head == fifo->tail; } +void fifo_push(struct fifo* fifo, vertex_t* path) { + if ((fifo->tail + 1) % fifo->capacity == fifo->head) { + // double the capacity + vertex_t* new_data = + (vertex_t*)malloc(2 * fifo->capacity * fifo->path_length * sizeof(vertex_t)); + assert(new_data != NULL, "Error allocating memory for the fifo\n"); + for (cycle_index_t i = 0; i < fifo->capacity; i++) { + for (cycle_length_t j = 0; j < fifo->path_length; j++) { + new_data[i * fifo->path_length + j] = + fifo->data[((fifo->head + i) % fifo->capacity) * fifo->path_length + j]; + } + } + free(fifo->data); + fifo->data = new_data; + fifo->head = 0; + fifo->tail = fifo->capacity - 1; + fifo->capacity *= 2; + } + + for (cycle_length_t i = 0; i < fifo->path_length; i++) { + fifo->data[fifo->tail * fifo->path_length + i] = path[i]; + } + fifo->tail = (fifo->tail + 1) % fifo->capacity; +} +void fifo_pop(struct fifo* fifo, vertex_t* path) { + for (cycle_length_t i = 0; i < fifo->path_length; i++) { + path[i] = fifo->data[fifo->head * fifo->path_length + i]; + } + fifo->head = (fifo->head + 1) % fifo->capacity; +} +cycle_index_t fifo_size(struct fifo* fifo) { + return (fifo->tail - fifo->head + fifo->capacity) % fifo->capacity; +} +void fifo_free(struct fifo* fifo) { + free(fifo->data); + fifo->data = NULL; +} + +cycles_t cycle_generate(adj_t adjacency_list, vertex_t num_vertices, cycle_length_t cycle_length, + cycle_index_t* num_cycles) { + vertex_t* buffer = (vertex_t*)malloc((cycle_length + 2) * sizeof(vertex_t)); + assert(buffer != NULL, "Error allocating memory for the buffer\n"); + + struct fifo cycle_list; + fifo_init(&cycle_list, cycle_length * num_vertices, cycle_length + 2); + struct fifo queue; + fifo_init(&queue, cycle_length * num_vertices, cycle_length + 2); + + for (cycle_length_t i = 2; i < cycle_length + 2; i++) { + buffer[i] = 0; + } + for (vertex_t i = 0; i < num_vertices; i++) { + buffer[0] = 1; + buffer[1] = i; + fifo_push(&queue, buffer); + } + while (!fifo_empty(&queue)) { + fifo_pop(&queue, buffer); + cycle_length_t path_length = buffer[0]; + vertex_t* path = &buffer[1]; + vertex_t* neighbors = adj_get_neighbors(adjacency_list, path[path_length - 1]); + if (path_length == cycle_length) { + for (degree_t i = 0; i < VERTEX_DEGREE; i++) { + if (neighbors[i] != path[0]) { + continue; // if this doesn't complete a cycle, keep looking + } + if (!ONLY_SIMPLE_CYCLES) { + // when not dealing with purely simple cycles, we need some extra + // checks + + // prevent backtracking + if (path[1] == path[path_length - 1] || path[path_length - 2] == path[0]) { + break; + } + + // prevent repeated directed edges + bool repeated_edge = false; + for (cycle_length_t j = 0; j < path_length - 1; j++) { + if (path[j] == path[path_length - 1] && path[j + 1] == path[0]) { + repeated_edge = true; + break; + } + } + if (repeated_edge) { + break; + } + + if (path_has_reverse_transition(path, path_length, path[path_length - 2], + path[path_length - 1], path[0]) || + path_has_reverse_transition(path, path_length, path[path_length - 1], + path[0], path[1])) { + break; + } + } + // we've found a cycle + buffer[cycle_length + 1] = path[0]; + fifo_push(&cycle_list, buffer); + break; + } + } else { + for (degree_t i = 0; i < VERTEX_DEGREE; i++) { + vertex_t neighbor = neighbors[i]; + if (neighbor == MAX_VERTICES) continue; + if (ONLY_SIMPLE_CYCLES ? (neighbor <= path[0]) : (neighbor < path[0])) { + continue; + } + if (ONLY_SIMPLE_CYCLES) { + // don't allow repeated vertices in the path (implicitly also prevents + // backtracking and repeated directed edges) + bool neighbor_in_path = false; + for (cycle_length_t j = 0; j < path_length; j++) { + if (path[j] == neighbor) { + neighbor_in_path = true; + break; + } + } + if (neighbor_in_path) { + continue; + } + } else { + if (path_length >= 2 && neighbor == path[path_length - 2]) { + // Skip the neighbor if it is the previous vertex in the path (no + // backtracking). + continue; + } + + // skip if any directed edge is repeated, i.e. matches the one we are + // currently adding from path[path_length - 1] to neighbor + bool repeated_edge = false; + for (cycle_length_t j = 0; j < path_length - 1; j++) { + if (path[j] == path[path_length - 1] && path[j + 1] == neighbor) { + repeated_edge = true; + break; + } + } + if (repeated_edge) { + continue; + } + + if (path_length >= 2 && + path_has_reverse_transition(path, path_length, path[path_length - 2], + path[path_length - 1], neighbor)) { + continue; + } + } + + buffer[0] = path_length + 1; + path[path_length] = neighbor; + fifo_push(&queue, buffer); + } + } + } + + fifo_free(&queue); + free(buffer); + *num_cycles = fifo_size(&cycle_list); + vertex_t* cycles = NULL; + if (*num_cycles != 0) { + cycles = (vertex_t*)realloc(cycle_list.data, + *num_cycles * (cycle_length + 2) * sizeof(vertex_t)); + assert(cycles != NULL, "Error reallocating memory for the cycles\n"); + } + cycle_list.data = NULL; + fifo_free(&cycle_list); + + if (DEBUG) { + fprintf(stderr, "Generated cycles of length: %" PRIcycle_length_t "\n", cycle_length); + fprintf(stderr, "\tNumber of cycles: %" PRIcycle_index_t "\n", *num_cycles); + fprintf(stderr, "\tFirst 5 cycles:\n"); + for (cycle_index_t i = 0; i < (*num_cycles > 5 ? 5 : *num_cycles); i++) { + fprintf(stderr, "\t\t%d: ", i); + for (cycle_length_t j = 0; j < cycle_length + 1; j++) { + fprintf(stderr, "%02" PRIvertex_t " ", cycle_get(cycles, cycle_length, i, NULL)[j]); + } + fprintf(stderr, "\n"); + } + } + + return cycles; +} + +vertex_t* cycle_get(cycles_t cycles, cycle_length_t max_cycle_length, cycle_index_t cycle_index, + cycle_length_t* cycle_length) { + vertex_t* row = &cycles[cycle_index * (max_cycle_length + 2)]; + if (cycle_length != NULL) { + *cycle_length = row[0]; + } + return &row[1]; +} + +cycle_index_t* cbv_generate(vertex_t num_vertices, cycles_t cycles, cycle_index_t num_cycles, + cycle_length_t max_cycle_length, cycle_index_t* max_cycles_per_vertex) { + // find the number of cycles per vertex + cycle_index_t* cycles_per_vertex = (cycle_index_t*)malloc(num_vertices * sizeof(cycle_index_t)); + assert(cycles_per_vertex != NULL, "Error allocating memory for the cycles per vertex\n"); + for (vertex_t i = 0; i < num_vertices; i++) { + cycles_per_vertex[i] = 0; + } + cycle_length_t cycle_length; + for (cycle_index_t i = 0; i < num_cycles; i++) { + vertex_t* cycle = cycle_get(cycles, max_cycle_length, i, &cycle_length); + for (cycle_length_t j = 0; j < cycle_length; j++) { + cycles_per_vertex[cycle[j]]++; + } + } + + // find the maximum number of cycles per vertex + *max_cycles_per_vertex = 0; + for (vertex_t i = 0; i < num_vertices; i++) { + if (cycles_per_vertex[i] > *max_cycles_per_vertex) { + *max_cycles_per_vertex = cycles_per_vertex[i]; + } + } + + cbv_t cycles_by_vertex = + (cbv_t)malloc(num_vertices * (*max_cycles_per_vertex + 1) * sizeof(cycle_index_t)); + assert(cycles_by_vertex != NULL, "Error allocating memory for the cycles by vertex\n"); + + // fill in the cycles by vertex + for (vertex_t i = 0; i < num_vertices; i++) { + cycles_by_vertex[i * (*max_cycles_per_vertex + 1)] = cycles_per_vertex[i]; + cycle_index_t num_cycles_for_vertex = 0; + for (cycle_index_t j = 0; j < num_cycles && num_cycles_for_vertex < cycles_per_vertex[i]; + j++) { + bool cycle_contains_vertex = false; + vertex_t* cycle = cycle_get(cycles, max_cycle_length, j, &cycle_length); + for (cycle_length_t k = 0; k < cycle_length; k++) { + if (cycle[k] == i) { + cycle_contains_vertex = true; + break; + } + } + if (cycle_contains_vertex) { + cycles_by_vertex[i * (*max_cycles_per_vertex + 1) + num_cycles_for_vertex + 1] = j; + num_cycles_for_vertex++; + } + } + if (ONLY_SIMPLE_CYCLES) { + // For simple cycles, each vertex can only occur once in a cycle so we + // already have the correct number of cycles + assert(num_cycles_for_vertex == cycles_per_vertex[i], + "Error filling in the cycles by vertex %" PRIvertex_t " (%" PRIcycle_index_t + " != %" PRIcycle_index_t ")\n", + i, num_cycles_for_vertex, cycles_per_vertex[i]); + } else { + // otherwise, we overcounted and need to correct + cycles_by_vertex[i * (*max_cycles_per_vertex + 1)] = num_cycles_for_vertex; + } + } + + if (DEBUG) { + fprintf(stderr, "Organized cycles by vertex\n"); + fprintf(stderr, "\tMax cycles per vertex: %" PRIcycle_index_t "\n", *max_cycles_per_vertex); + fprintf(stderr, "\tLast 2 cycles of vertex 0 and 1:\n"); + for (uint8_t i = num_vertices - 2; i < num_vertices; i++) { + cycle_index_t num_cycles; + cycle_index_t* cycle_indices = + cbv_get_cycle_indices(cycles_by_vertex, *max_cycles_per_vertex, i, &num_cycles); + fprintf(stderr, "\t\t%d:\n", i); + for (cycle_index_t j = 0; j < num_cycles && j < 2; j++) { + fprintf(stderr, "\t\t\t%" PRIcycle_index_t " / %" PRIcycle_index_t ": ", j, + num_cycles); + vertex_t* cycle = + cycle_get(cycles, max_cycle_length, cycle_indices[j], &cycle_length); + for (cycle_length_t h = 0; h < cycle_length + 1; h++) { + fprintf(stderr, "%02" PRIvertex_t " ", cycle[h]); + } + fprintf(stderr, "\n"); + } + } + } + + free(cycles_per_vertex); + return cycles_by_vertex; +} + +cycle_index_t* cbv_get_cycle_indices(cbv_t cycles_by_vertex, cycle_index_t max_cycles_per_vertex, + vertex_t vertex, cycle_index_t* num_cycles) { + cycle_index_t* row = &cycles_by_vertex[vertex * (max_cycles_per_vertex + 1)]; + *num_cycles = row[0]; + return &row[1]; +} + +cycle_index_t* cbe_generate(vertex_t num_vertices, cycles_t cycles, cycle_index_t num_cycles, + cycle_length_t max_cycle_length, cycle_index_t* max_cycles_per_edge) { + cycle_index_t edge_slots = num_vertices * VERTEX_DEGREE; + cycle_index_t* cycles_per_edge = (cycle_index_t*)calloc(edge_slots, sizeof(cycle_index_t)); + assert(cycles_per_edge != NULL, "Error allocating memory for cycles per edge\n"); + + cycle_length_t cycle_length; + for (cycle_index_t i = 0; i < num_cycles; i++) { + vertex_t* cycle = cycle_get(cycles, max_cycle_length, i, &cycle_length); + for (cycle_length_t j = 0; j < cycle_length; j++) { + degree_t neighbor_index = + adj_neighbor_index(full_adjacency_list, cycle[j], cycle[j + 1]); + cycles_per_edge[cycle[j] * VERTEX_DEGREE + neighbor_index]++; + } + } + + *max_cycles_per_edge = 0; + for (cycle_index_t i = 0; i < edge_slots; i++) { + if (cycles_per_edge[i] > *max_cycles_per_edge) { + *max_cycles_per_edge = cycles_per_edge[i]; + } + } + + cbe_t cycles_by_edge = + (cbe_t)malloc(edge_slots * (*max_cycles_per_edge + 1) * sizeof(cycle_index_t)); + cycle_index_t* edge_fill = (cycle_index_t*)calloc(edge_slots, sizeof(cycle_index_t)); + assert(cycles_by_edge != NULL && edge_fill != NULL, + "Error allocating memory for cycles by edge\n"); + + for (cycle_index_t i = 0; i < edge_slots; i++) { + cycles_by_edge[i * (*max_cycles_per_edge + 1)] = cycles_per_edge[i]; + } + + for (cycle_index_t i = 0; i < num_cycles; i++) { + vertex_t* cycle = cycle_get(cycles, max_cycle_length, i, &cycle_length); + for (cycle_length_t j = 0; j < cycle_length; j++) { + degree_t neighbor_index = + adj_neighbor_index(full_adjacency_list, cycle[j], cycle[j + 1]); + cycle_index_t edge_index = cycle[j] * VERTEX_DEGREE + neighbor_index; + cycle_index_t fill = edge_fill[edge_index]++; + cycles_by_edge[edge_index * (*max_cycles_per_edge + 1) + fill + 1] = i; + } + } + + free(cycles_per_edge); + free(edge_fill); + return cycles_by_edge; +} + +cycle_index_t* cbe_get_cycle_indices(cbe_t cycles_by_edge, cycle_index_t max_cycles_per_edge, + vertex_t start_vertex, vertex_t end_vertex, + cycle_index_t* num_cycles) { + degree_t neighbor_index = adj_neighbor_index(full_adjacency_list, start_vertex, end_vertex); + cycle_index_t* row = + &cycles_by_edge[(start_vertex * VERTEX_DEGREE + neighbor_index) * + (max_cycles_per_edge + 1)]; + *num_cycles = row[0]; + return &row[1]; +} + +cycle_index_t cycle_image_index(cycles_t cycles, cycle_length_t max_cycle_length, + cbe_t cycles_by_edge, cycle_index_t max_cycles_per_edge, + cycle_index_t cycle_index, vertex_t* automorphism, + vertex_t* image) { + cycle_length_t cycle_length; + vertex_t* cycle = cycle_get(cycles, max_cycle_length, cycle_index, &cycle_length); + vertex_t min_vertex = MAX_VERTICES; + for (cycle_length_t i = 0; i < cycle_length; i++) { + image[i] = automorphism[cycle[i]]; + if (image[i] < min_vertex) { + min_vertex = image[i]; + } + } + + for (cycle_length_t start = 0; start < cycle_length; start++) { + if (image[start] != min_vertex) { + continue; + } + + cycle_index_t num_cycles_for_edge; + cycle_index_t* cycle_indices = cbe_get_cycle_indices( + cycles_by_edge, max_cycles_per_edge, image[start], + image[(start + 1) % cycle_length], &num_cycles_for_edge); + for (cycle_index_t i = 0; i < num_cycles_for_edge; i++) { + cycle_index_t candidate_index = cycle_indices[i]; + cycle_length_t candidate_length; + vertex_t* candidate = + cycle_get(cycles, max_cycle_length, candidate_index, &candidate_length); + if (candidate_length != cycle_length) { + continue; + } + + bool matches = true; + for (cycle_length_t j = 0; j < cycle_length; j++) { + if (candidate[j] != image[(start + j) % cycle_length]) { + matches = false; + break; + } + } + if (matches) { + return candidate_index; + } + } + } + + return MAX_CYCLES; +} + +cycle_index_t* start_cycles_prune_by_symmetry(cycles_t cycles, + cycle_length_t max_cycle_length, + cycle_index_t num_cycles, + cbe_t cycles_by_edge, + cycle_index_t max_cycles_per_edge, + cycle_index_t* raw_start_cycles, + cycle_index_t raw_start_count, + cycle_index_t* pruned_start_count) { + // Every valid fitting contains at least one raw start cycle. If an + // automorphism maps one raw start cycle to another, searching the earlier + // representative also searches an isomorphic fitting. + cycle_index_t* start_cycles = + (cycle_index_t*)malloc((raw_start_count == 0 ? 1 : raw_start_count) * + sizeof(cycle_index_t)); + assert(start_cycles != NULL, "Error allocating memory for pruned start cycles\n"); + *pruned_start_count = 0; + + if (raw_start_count == 0) { + return start_cycles; + } + if (graph_automorphisms.count == 0 || raw_start_count == 1) { + memcpy(start_cycles, raw_start_cycles, raw_start_count * sizeof(cycle_index_t)); + *pruned_start_count = raw_start_count; + return start_cycles; + } + + bool* is_start_cycle = (bool*)calloc((num_cycles == 0 ? 1 : num_cycles), sizeof(bool)); + bool* start_cycle_seen = (bool*)calloc((num_cycles == 0 ? 1 : num_cycles), sizeof(bool)); + cycle_index_t* queue = + (cycle_index_t*)malloc(raw_start_count * sizeof(cycle_index_t)); + vertex_t* image = (vertex_t*)malloc((max_cycle_length == 0 ? 1 : max_cycle_length) * + sizeof(vertex_t)); + assert(is_start_cycle != NULL && start_cycle_seen != NULL && queue != NULL && + image != NULL, + "Error allocating memory for start cycle symmetry pruning\n"); + for (cycle_index_t i = 0; i < raw_start_count; i++) { + is_start_cycle[raw_start_cycles[i]] = true; + } + + for (cycle_index_t i = 0; i < raw_start_count; i++) { + cycle_index_t cycle_index = raw_start_cycles[i]; + if (start_cycle_seen[cycle_index]) { + continue; + } + + start_cycles[*pruned_start_count] = cycle_index; + (*pruned_start_count)++; + + cycle_index_t head = 0; + cycle_index_t tail = 0; + start_cycle_seen[cycle_index] = true; + queue[tail++] = cycle_index; + while (head < tail) { + cycle_index_t current = queue[head++]; + for (cycle_index_t automorphism_index = 0; + automorphism_index < graph_automorphisms.count; automorphism_index++) { + vertex_t* automorphism = + &graph_automorphisms.maps[automorphism_index * + graph_automorphisms.num_vertices]; + cycle_index_t image_index = + cycle_image_index(cycles, max_cycle_length, cycles_by_edge, + max_cycles_per_edge, current, automorphism, image); + if (image_index == MAX_CYCLES || !is_start_cycle[image_index] || + start_cycle_seen[image_index]) { + continue; + } + + start_cycle_seen[image_index] = true; + queue[tail++] = image_index; + } + } + } + + if (PRINT_PROGRESS && *pruned_start_count < raw_start_count) { + fprintf(stderr, + "\033[2K\rSymmetry pruning reduced start cycles from %" PRIcycle_index_t + " to %" PRIcycle_index_t ".\n", + raw_start_count, *pruned_start_count); + show_progress(0.0); + } + + free(is_start_cycle); + free(start_cycle_seen); + free(queue); + free(image); + return start_cycles; +} diff --git a/PAGE/page.py b/PAGE/page.py new file mode 100644 index 0000000..5340a24 --- /dev/null +++ b/PAGE/page.py @@ -0,0 +1,963 @@ +#!/usr/bin/env python3 +"""A compact pure-Python implementation of PAGE. + +The C implementation in page.c is tuned for large searches, parallel start +branches, and several specialized bounds. This file keeps the same central +algorithm but aims to be readable: + +1. Generate candidate facial walks, length by length. +2. Treat an embedding as an exact cover of the directed edges by those walks. +3. Backtrack on the most constrained uncovered directed edge. +4. Enforce orientability by forbidding both directions of a local transition. + +Input defaults match page.c's environment variables: + S=0 DEG=3 ADJ=adjacency_lists/k3-3.txt python3 page.py +""" + +from __future__ import annotations + +import argparse +import math +import multiprocessing as mp +import os +import sys +from collections import Counter, defaultdict +from dataclasses import dataclass, field +from functools import lru_cache +from time import perf_counter + +MAX_VERTEX = 65535 +START_CYCLE_LENGTH = 3 +START_BRANCH_PROCESS_CAP = 8 +PARALLEL_MIN_STARTS = 8 + +_PARALLEL_STATE = None + + +@dataclass +class Graph: + adjacency: list[list[int]] + start_index: int + degree: int + edge_count: int + vertex_degrees: list[int] + directed_edges: list[tuple[int, int]] + directed_edge_id: dict[tuple[int, int], int] + neighbor_index: dict[tuple[int, int], int] + + @property + def vertex_count(self) -> int: + return len(self.adjacency) + + @property + def directed_edge_count(self) -> int: + return len(self.directed_edges) + + +@dataclass(frozen=True) +class Cycle: + vertices: tuple[int, ...] # closed: vertices[-1] == vertices[0] + edges: tuple[int, ...] + edge_mask: int + vertex_counts: tuple[tuple[int, int], ...] + transitions: tuple[tuple[int, int, int], ...] + reverse_transitions: tuple[tuple[int, int, int], ...] + transition_mask: int + reverse_transition_mask: int + + @property + def length(self) -> int: + return len(self.edges) + + +@dataclass +class SearchStats: + calls: int = 0 + best_fit: int = 0 + + +@dataclass +class PageSearch: + graph: Graph + cycles: list[Cycle] + cycles_by_edge: dict[int, list[int]] + available_lengths: set[int] + target_faces: int + shortest_length: int + max_length: int + required_length: int + cubic_exact_cover: bool + used_cycles: list[bool] = field(init=False) + used_edge_mask: int = field(init=False) + vertex_uses: list[int] = field(init=False) + used_transition_mask: int = field(init=False) + rotation_next: list[int] = field(init=False) + rotation_prev: list[int] = field(init=False) + rotation_pair_count: list[int] = field(init=False) + num_edges_remaining: int = field(init=False) + required_remaining: int = field(init=False) + stats: SearchStats = field(default_factory=SearchStats) + solution: list[int] | None = None + _ordered_lengths: tuple[int, ...] = field(init=False, repr=False) + _length_cache: dict[tuple[int, int, int], bool] = field(init=False, repr=False) + + def __post_init__(self) -> None: + self.used_cycles = [False] * len(self.cycles) + self.used_edge_mask = 0 + self.vertex_uses = [0] * self.graph.vertex_count + self.used_transition_mask = 0 + rotation_slots = self.graph.vertex_count * self.graph.degree + self.rotation_next = [MAX_VERTEX] * rotation_slots + self.rotation_prev = [MAX_VERTEX] * rotation_slots + self.rotation_pair_count = [0] * self.graph.vertex_count + self.num_edges_remaining = self.graph.directed_edge_count + self.required_remaining = 1 if self.required_length else 0 + self._ordered_lengths = tuple(sorted(self.available_lengths)) + self._length_cache = {} + + def length_possible( + self, total_length: int, cycles_left: int, required_left: int = 0 + ) -> bool: + key = (total_length, cycles_left, required_left) + cached = self._length_cache.get(key) + if cached is not None: + return cached + if cycles_left == 0: + possible = total_length == 0 and required_left == 0 + elif required_left > cycles_left: + possible = False + elif total_length < cycles_left * self.shortest_length: + possible = False + elif total_length > cycles_left * self.max_length: + possible = False + else: + possible = False + for length in self._ordered_lengths: + if length > total_length: + break + next_required = required_left + if next_required and length == self.required_length: + next_required -= 1 + if self.length_possible( + total_length - length, cycles_left - 1, next_required + ): + possible = True + break + self._length_cache[key] = possible + return possible + + def candidate_length_possible(self, cycle: Cycle, cycles_left: int) -> bool: + remaining = self.num_edges_remaining - cycle.length + if remaining < 0: + return False + required_left = max(0, self.required_remaining) + if required_left and cycle.length == self.required_length: + required_left -= 1 + if cycles_left == 1: + return remaining == 0 and required_left == 0 + return self.length_possible(remaining, cycles_left - 1, required_left) + + def cycle_vertex_uses_fit(self, cycle: Cycle) -> bool: + for vertex, count in cycle.vertex_counts: + if self.vertex_uses[vertex] + count > self.graph.vertex_degrees[vertex]: + return False + return True + + def cycle_transitions_good(self, cycle: Cycle) -> bool: + return (cycle.reverse_transition_mask & self.used_transition_mask) == 0 + + def add_rotation_transition( + self, center: int, prev_index: int, next_index: int + ) -> bool: + if self.graph.degree <= 5: + return True + source = center * self.graph.degree + prev_index + target = center * self.graph.degree + next_index + if ( + prev_index == next_index + or self.rotation_next[source] != MAX_VERTEX + or self.rotation_prev[target] != MAX_VERTEX + ): + return False + + component_size = 1 + closes_component = False + cursor = next_index + while self.rotation_next[center * self.graph.degree + cursor] != MAX_VERTEX: + cursor = self.rotation_next[center * self.graph.degree + cursor] + component_size += 1 + if cursor == prev_index: + closes_component = True + break + if component_size > self.graph.vertex_degrees[center]: + return False + + if closes_component and component_size < self.graph.vertex_degrees[center]: + return False + if ( + not closes_component + and self.rotation_pair_count[center] + 1 + == self.graph.vertex_degrees[center] + ): + return False + + self.rotation_next[source] = next_index + self.rotation_prev[target] = prev_index + self.rotation_pair_count[center] += 1 + return True + + def remove_rotation_transition( + self, center: int, prev_index: int, next_index: int + ) -> None: + if self.graph.degree <= 5: + return + source = center * self.graph.degree + prev_index + target = center * self.graph.degree + next_index + self.rotation_next[source] = MAX_VERTEX + self.rotation_prev[target] = MAX_VERTEX + self.rotation_pair_count[center] -= 1 + + def try_add_rotation_system(self, cycle: Cycle) -> bool: + if self.graph.degree <= 5: + return True + added: list[tuple[int, int, int]] = [] + for transition in cycle.transitions: + if not self.add_rotation_transition(*transition): + for undo in reversed(added): + self.remove_rotation_transition(*undo) + return False + added.append(transition) + return True + + def remove_rotation_system(self, cycle: Cycle) -> None: + if self.graph.degree <= 5: + return + for transition in cycle.transitions: + self.remove_rotation_transition(*transition) + + def candidate_usable(self, cycle_index: int, cycles_left: int) -> bool: + if self.used_cycles[cycle_index]: + return False + cycle = self.cycles[cycle_index] + if cycle.edge_mask & self.used_edge_mask: + return False + if not self.candidate_length_possible(cycle, cycles_left): + return False + if not self.cubic_exact_cover and not self.cycle_vertex_uses_fit(cycle): + return False + return self.cycle_transitions_good(cycle) + + def choose_edge_column(self, cycles_left: int) -> tuple[int, list[int]] | None: + best_edge = -1 + best_options = math.inf + best_pressure = -1 + + for edge_id in range(self.graph.directed_edge_count): + if self.used_edge_mask & (1 << edge_id): + continue + candidates = [] + u, v = self.graph.directed_edges[edge_id] + pressure = self.vertex_uses[u] + self.vertex_uses[v] + for cycle_index in self.cycles_by_edge.get(edge_id, ()): + if self.candidate_usable(cycle_index, cycles_left): + candidates.append(cycle_index) + if len(candidates) > best_options: + break + options = len(candidates) + if options < best_options or ( + options == best_options and pressure > best_pressure + ): + best_edge = edge_id + best_options = options + best_pressure = pressure + if best_options == 0: + break + + if best_edge < 0: + return None + best_candidates = [ + cycle_index + for cycle_index in self.cycles_by_edge.get(best_edge, ()) + if self.candidate_usable(cycle_index, cycles_left) + ] + best_candidates.sort(key=lambda i: self.cycles[i].length, reverse=True) + return best_edge, best_candidates + + def choose_start_cycles(self) -> list[int]: + best: list[int] | None = None + for edge_id in range(self.graph.directed_edge_count): + row = self.cycles_by_edge.get(edge_id, []) + if best is None or len(row) < len(best): + best = row + if not best: + break + if best is None: + return [] + + if self.required_length: + required_starts = [ + index + for index, cycle in enumerate(self.cycles) + if cycle.length == self.required_length + ] + if required_starts and len(required_starts) <= len(best): + best = required_starts + + def cycle_key(cycle_index: int) -> tuple[int, int]: + cycle = self.cycles[cycle_index] + scarcity = sum( + len(self.cycles_by_edge.get(edge_id, ())) for edge_id in cycle.edges + ) + return (scarcity, cycle.length) + + return sorted(best, key=cycle_key) + + def solve(self) -> bool: + for cycle_index in self.choose_start_cycles(): + if self.solve_from_start(cycle_index): + return True + return False + + def solve_from_start(self, cycle_index: int) -> bool: + if not self.candidate_usable(cycle_index, self.target_faces): + return False + if not self.add_cycle(cycle_index): + return False + if self.target_faces == 1: + if self.final_state_valid(): + self.solution = [cycle_index] + return True + elif self.search(self.target_faces - 1): + return True + self.remove_cycle(cycle_index) + return False + + def add_cycle(self, cycle_index: int) -> bool: + cycle = self.cycles[cycle_index] + if not self.try_add_rotation_system(cycle): + return False + self.used_cycles[cycle_index] = True + self.used_edge_mask |= cycle.edge_mask + self.num_edges_remaining -= cycle.length + for vertex, count in cycle.vertex_counts: + self.vertex_uses[vertex] += count + self.used_transition_mask |= cycle.transition_mask + if self.required_length and cycle.length == self.required_length: + self.required_remaining -= 1 + return True + + def remove_cycle(self, cycle_index: int) -> None: + cycle = self.cycles[cycle_index] + if self.required_length and cycle.length == self.required_length: + self.required_remaining += 1 + self.used_transition_mask &= ~cycle.transition_mask + for vertex, count in cycle.vertex_counts: + self.vertex_uses[vertex] -= count + self.used_edge_mask &= ~cycle.edge_mask + self.num_edges_remaining += cycle.length + self.used_cycles[cycle_index] = False + self.remove_rotation_system(cycle) + + def final_state_valid(self) -> bool: + if self.num_edges_remaining != 0: + return False + if self.required_remaining > 0: + return False + if self.cubic_exact_cover: + return True + return all( + self.vertex_uses[v] == self.graph.vertex_degrees[v] + for v in range(self.graph.vertex_count) + ) + + def search(self, cycles_left: int) -> bool: + self.stats.calls += 1 + used_count = self.target_faces - cycles_left + if used_count > self.stats.best_fit and self.final_state_valid(): + self.stats.best_fit = used_count + + column = self.choose_edge_column(cycles_left) + if column is None: + return False + _, candidates = column + if not candidates: + return False + + for cycle_index in candidates: + if not self.add_cycle(cycle_index): + continue + if cycles_left == 1: + if self.final_state_valid(): + self.solution = [ + i for i, used in enumerate(self.used_cycles) if used + ] + return True + elif self.search(cycles_left - 1): + return True + self.remove_cycle(cycle_index) + return False + + +def _new_search( + graph: Graph, + cycles: list[Cycle], + cycles_by_edge: dict[int, list[int]], + available_lengths: set[int], + target_faces: int, + shortest_length: int, + max_length: int, + required_length: int, + cubic_exact_cover: bool, +) -> PageSearch: + return PageSearch( + graph=graph, + cycles=cycles, + cycles_by_edge=cycles_by_edge, + available_lengths=set(available_lengths), + target_faces=target_faces, + shortest_length=shortest_length, + max_length=max_length, + required_length=required_length, + cubic_exact_cover=cubic_exact_cover, + ) + + +def _parallel_init( + graph: Graph, + cycles: list[Cycle], + cycles_by_edge: dict[int, list[int]], + available_lengths: set[int], + target_faces: int, + shortest_length: int, + max_length: int, + required_length: int, + cubic_exact_cover: bool, +) -> None: + global _PARALLEL_STATE + _PARALLEL_STATE = ( + graph, + cycles, + cycles_by_edge, + available_lengths, + target_faces, + shortest_length, + max_length, + required_length, + cubic_exact_cover, + ) + + +def _parallel_solve_start(cycle_index: int) -> tuple[list[int] | None, int]: + if _PARALLEL_STATE is None: + raise RuntimeError("parallel PAGE worker was not initialized") + search = _new_search(*_PARALLEL_STATE) + if search.solve_from_start(cycle_index): + assert search.solution is not None + return search.solution, search.stats.calls + return None, search.stats.calls + + +def solve_search( + graph: Graph, + cycles: list[Cycle], + cycles_by_edge: dict[int, list[int]], + available_lengths: set[int], + target_faces: int, + shortest_length: int, + max_length: int, + required_length: int, + cubic_exact_cover: bool, + jobs: int, +) -> tuple[list[int] | None, int]: + search = _new_search( + graph, + cycles, + cycles_by_edge, + available_lengths, + target_faces, + shortest_length, + max_length, + required_length, + cubic_exact_cover, + ) + start_cycles = search.choose_start_cycles() + if jobs <= 1 or len(start_cycles) < PARALLEL_MIN_STARTS: + return ( + (search.solution, search.stats.calls) + if search.solve() + else (None, search.stats.calls) + ) + + context_name = "fork" if hasattr(os, "fork") else "spawn" + context = mp.get_context(context_name) + total_calls = 0 + with context.Pool( + processes=max(1, min(jobs, len(start_cycles))), + initializer=_parallel_init, + initargs=( + graph, + cycles, + cycles_by_edge, + available_lengths, + target_faces, + shortest_length, + max_length, + required_length, + cubic_exact_cover, + ), + ) as pool: + for solution, calls in pool.imap_unordered( + _parallel_solve_start, start_cycles, chunksize=1 + ): + total_calls += calls + if solution is not None: + pool.terminate() + return solution, total_calls + return None, total_calls + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser(description="Pure-Python PAGE implementation") + parser.add_argument("--adj", default=os.environ.get("ADJ")) + parser.add_argument( + "--degree", "-d", type=int, default=int(os.environ.get("DEG", "3")) + ) + parser.add_argument( + "--start", "-s", type=int, default=int(os.environ.get("S", "0")) + ) + parser.add_argument("--out", default=os.environ.get("OUT", "page_py.out")) + parser.add_argument( + "--jobs", + "-j", + type=int, + default=int( + os.environ.get( + "PAGE_JOBS", str(min(os.cpu_count() or 1, START_BRANCH_PROCESS_CAP)) + ) + ), + help="parallel start branches to try; set PAGE_JOBS=1 for deterministic sequential search", + ) + parser.add_argument("--quiet", action="store_true") + return parser.parse_args() + + +def load_graph(path: str, degree: int, start_index: int) -> Graph: + if not path: + raise SystemExit("No adjacency list supplied. Use --adj or ADJ=...") + with open(path, "r", encoding="utf-8") as handle: + values = [int(x) for x in handle.read().split()] + if len(values) < 2: + raise SystemExit(f"{path}: expected vertex and edge counts") + n, edge_count = values[0], values[1] + raw = values[2:] + expected = n * degree + if len(raw) < expected: + raise SystemExit( + f"{path}: expected {expected} adjacency entries, found {len(raw)}" + ) + + adjacency: list[list[int]] = [] + vertex_degrees: list[int] = [] + for vertex in range(n): + row = [] + for value in raw[vertex * degree : (vertex + 1) * degree]: + neighbor = MAX_VERTEX if value == MAX_VERTEX else value - start_index + row.append(neighbor) + adjacency.append(row) + vertex_degrees.append(sum(1 for neighbor in row if neighbor != MAX_VERTEX)) + + directed_edges: list[tuple[int, int]] = [] + directed_edge_id: dict[tuple[int, int], int] = {} + neighbor_index: dict[tuple[int, int], int] = {} + for u, row in enumerate(adjacency): + for slot, v in enumerate(row): + if v == MAX_VERTEX: + continue + directed_edge_id[(u, v)] = len(directed_edges) + neighbor_index[(u, v)] = slot + directed_edges.append((u, v)) + + if len(directed_edges) != 2 * edge_count: + raise SystemExit( + f"{path}: found {len(directed_edges)} directed edges, expected {2 * edge_count}" + ) + + return Graph( + adjacency=adjacency, + start_index=start_index, + degree=degree, + edge_count=edge_count, + vertex_degrees=vertex_degrees, + directed_edges=directed_edges, + directed_edge_id=directed_edge_id, + neighbor_index=neighbor_index, + ) + + +def path_has_reverse_transition( + graph: Graph, + path: tuple[int, ...], + prev_vertex: int, + center_vertex: int, + next_vertex: int, +) -> bool: + if graph.vertex_degrees[center_vertex] <= 2: + return False + for i in range(1, len(path) - 1): + if ( + path[i - 1] == next_vertex + and path[i] == center_vertex + and path[i + 1] == prev_vertex + ): + return True + return False + + +def make_cycle(graph: Graph, path: tuple[int, ...]) -> Cycle: + closed = path + (path[0],) + edges = tuple( + graph.directed_edge_id[(closed[i], closed[i + 1])] for i in range(len(path)) + ) + edge_mask = 0 + for edge_id in edges: + edge_mask |= 1 << edge_id + counts = tuple(sorted(Counter(path).items())) + transitions = [] + for i, center in enumerate(path): + if graph.vertex_degrees[center] <= 2: + continue + prev_vertex = path[i - 1] + next_vertex = path[(i + 1) % len(path)] + transitions.append( + ( + center, + graph.neighbor_index[(center, prev_vertex)], + graph.neighbor_index[(center, next_vertex)], + ) + ) + reverse_transitions = tuple( + (center, next_index, prev_index) + for center, prev_index, next_index in transitions + ) + transition_mask = 0 + reverse_transition_mask = 0 + for center, prev_index, next_index in transitions: + transition_id = (center * graph.degree + prev_index) * graph.degree + next_index + reverse_id = (center * graph.degree + next_index) * graph.degree + prev_index + transition_mask |= 1 << transition_id + reverse_transition_mask |= 1 << reverse_id + return Cycle( + closed, + edges, + edge_mask, + counts, + tuple(transitions), + reverse_transitions, + transition_mask, + reverse_transition_mask, + ) + + +def generate_cycles(graph: Graph, cycle_length: int) -> list[Cycle]: + cycles: list[Cycle] = [] + queue: list[tuple[int, ...]] = [(v,) for v in range(graph.vertex_count)] + head = 0 + while head < len(queue): + path = queue[head] + head += 1 + last = path[-1] + if len(path) == cycle_length: + if path[0] not in graph.adjacency[last]: + continue + if path[1] == path[-1] or path[-2] == path[0]: + continue + if any( + path[j] == path[-1] and path[j + 1] == path[0] + for j in range(len(path) - 1) + ): + continue + if path_has_reverse_transition(graph, path, path[-2], path[-1], path[0]): + continue + if path_has_reverse_transition(graph, path, path[-1], path[0], path[1]): + continue + cycles.append(make_cycle(graph, path)) + continue + + for neighbor in graph.adjacency[last]: + if neighbor == MAX_VERTEX or neighbor < path[0]: # type: ignore + continue + if len(path) >= 2 and neighbor == path[-2]: + continue + if any( + path[j] == last and path[j + 1] == neighbor + for j in range(len(path) - 1) + ): + continue + if len(path) >= 2 and path_has_reverse_transition( + graph, path, path[-2], last, neighbor + ): + continue + queue.append(path + (neighbor,)) + return cycles + + +def index_cycles(cycles: list[Cycle]) -> dict[int, list[int]]: + by_edge: dict[int, list[int]] = defaultdict(list) + for index, cycle in enumerate(cycles): + for edge_id in cycle.edges: + by_edge[edge_id].append(index) + return by_edge + + +def implied_faces_for_genus(genus: int, graph: Graph) -> int: + return graph.edge_count - graph.vertex_count + 2 - 2 * genus + + +def genus_from_faces(faces: int, graph: Graph) -> int: + return max(0, 1 - (faces - graph.edge_count + graph.vertex_count) // 2) + + +def genus_lower_bound_from_face_upper_bound(face_upper_bound: int, graph: Graph) -> int: + numerator = graph.edge_count - graph.vertex_count + 2 - face_upper_bound + return 0 if numerator <= 0 else (numerator + 1) // 2 + + +def length_composition_info( + total: int, + count: int, + lengths: set[int], + shortest_length: int, + required_length: int = 0, +) -> tuple[bool, int]: + ordered = tuple(sorted(lengths)) + if not ordered: + return False, 0 + if required_length and required_length not in lengths: + return False, 0 + + @lru_cache(maxsize=None) + def dp(remaining_total: int, remaining_count: int, required: int) -> int | None: + if remaining_count == 0: + return 0 if remaining_total == 0 and required == 0 else None + if required > remaining_count: + return None + if remaining_total < remaining_count * ordered[0]: + return None + if remaining_total > remaining_count * ordered[-1]: + return None + best: int | None = None + for length in ordered: + if length > remaining_total: + break + next_required = required + if next_required and length == required_length: + next_required -= 1 + suffix = dp(remaining_total - length, remaining_count - 1, next_required) + if suffix is None: + continue + shortest_count = suffix + (1 if length == shortest_length else 0) + if best is None or shortest_count < best: + best = shortest_count + return best + + result = dp(total, count, 1 if required_length else 0) + return (result is not None, result or 0) + + +def length_composition_possible( + total: int, count: int, lengths: set[int], required_length: int = 0 +) -> bool: + shortest = min(lengths) if lengths else 0 + return length_composition_info(total, count, lengths, shortest, required_length)[0] + + +def max_possible_fit_with_shortest_bound( + edge_count: int, + shortest_length: int, + second_shortest_length: int, + max_shortest_cycles: int, + required_length: int, +) -> int: + total_length = 2 * edge_count + if shortest_length == 0 or required_length > total_length: + return 0 + non_shortest_length = second_shortest_length + if non_shortest_length == 0 or required_length < non_shortest_length: + non_shortest_length = required_length + remaining_length = total_length - required_length + shortest_cycles_to_use = remaining_length // shortest_length + shortest_cycles_to_use = min(shortest_cycles_to_use, max_shortest_cycles) + remaining_length -= shortest_cycles_to_use * shortest_length + return 1 + shortest_cycles_to_use + remaining_length // non_shortest_length + + +def find_embedding( + graph: Graph, quiet: bool = False, jobs: int = 1 +) -> tuple[int, list[Cycle], list[int], int]: + cycles: list[Cycle] = [] + available_lengths: set[int] = set() + shortest_length = 0 + second_shortest_length = 0 + num_shortest_cycles = 0 + max_shortest_cycles = 0 + genus_lower = genus_lower_bound_from_face_upper_bound( + 2 * graph.edge_count // 3, graph + ) + genus_upper = genus_from_faces(1, graph) + max_generated_length = START_CYCLE_LENGTH - 1 + last_searched_faces: int | None = None + + genus = genus_lower + while genus <= genus_upper: + target_faces = implied_faces_for_genus(genus, graph) + if target_faces <= 0: + genus += 1 + continue + if (graph.edge_count - graph.vertex_count + 2 - target_faces) % 2 != 0: + genus += 1 + continue + + while True: + if shortest_length: + max_needed = 2 * graph.edge_count - shortest_length * (target_faces - 1) + else: + max_needed = 2 * graph.edge_count + if available_lengths: + required_length = ( + max_generated_length if last_searched_faces == target_faces else 0 + ) + length_possible, min_shortest_cycles = length_composition_info( + 2 * graph.edge_count, + target_faces, + available_lengths, + shortest_length, + required_length, + ) + if length_possible and min_shortest_cycles > max_shortest_cycles: + length_possible = False + + if length_possible: + cycles_by_edge = index_cycles(cycles) + if not quiet: + print( + f"Starting search for {target_faces} faces " + f"(genus {genus}, max cycle length {max_generated_length})...", + file=sys.stderr, + ) + solution, calls = solve_search( + graph=graph, + cycles=cycles, + cycles_by_edge=cycles_by_edge, + available_lengths=available_lengths, + target_faces=target_faces, + shortest_length=shortest_length, + max_length=max_generated_length, + required_length=required_length, + cubic_exact_cover=all(d == 3 for d in graph.vertex_degrees), + jobs=jobs, + ) + if solution is not None: + return genus, cycles, solution, calls + + last_searched_faces = target_faces + future_fit_upper_bound = max_possible_fit_with_shortest_bound( + graph.edge_count, + shortest_length, + second_shortest_length, + max_shortest_cycles, + max_generated_length + 1, + ) + future_genus_lower = genus_lower_bound_from_face_upper_bound( + future_fit_upper_bound, graph + ) + if future_genus_lower > genus_lower: + genus_lower = future_genus_lower + if genus < genus_lower: + break + + if max_generated_length >= max_needed: + break + max_generated_length += 1 + new_cycles = generate_cycles(graph, max_generated_length) + if not quiet: + if new_cycles: + print( + f"Found {len(new_cycles)} cycles of length {max_generated_length}.", + file=sys.stderr, + ) + else: + print( + f"No cycles of length {max_generated_length} found. Skipping.", + file=sys.stderr, + ) + if not new_cycles: + continue + cycles.extend(new_cycles) + available_lengths.add(max_generated_length) + if shortest_length == 0: + shortest_length = max_generated_length + num_shortest_cycles = len(new_cycles) + max_shortest_cycles = min( + num_shortest_cycles, + 2 * graph.edge_count // shortest_length, + ) + girth_face_bound = 2 * graph.edge_count // shortest_length + genus_lower = max( + genus_lower, + genus_lower_bound_from_face_upper_bound(girth_face_bound, graph), + ) + if genus < genus_lower: + break + elif second_shortest_length == 0: + second_shortest_length = max_generated_length + + if genus < genus_lower: + genus = genus_lower + continue + genus += 1 + raise RuntimeError("No embedding found") + + +def write_solution( + path: str, + graph: Graph, + genus: int, + cycles: list[Cycle], + solution: list[int], + calls: int, +) -> None: + with open(path, "w", encoding="utf-8") as handle: + handle.write( + f"Solution with {len(solution)} cycles (genus {genus}) found in {calls} iterations:\n" + ) + for cycle_index in solution: + handle.write( + " ".join( + str(v + graph.start_index) for v in cycles[cycle_index].vertices + ) + ) + handle.write("\n") + + +def main() -> int: + args = parse_args() + start = perf_counter() + graph = load_graph(args.adj, args.degree, args.start) + if not args.quiet: + print( + f"Read {args.adj}: {graph.vertex_count} vertices, {graph.edge_count} edges.", + file=sys.stderr, + ) + genus, cycles, solution, calls = find_embedding( + graph, quiet=args.quiet, jobs=args.jobs + ) + write_solution(args.out, graph, genus, cycles, solution, calls) + elapsed = perf_counter() - start + print(f"Found a solution! The genus is {genus}.") + print(f"Wrote {len(solution)} cycles to {args.out}.") + print(f"Iterations: {calls}. Runtime: {elapsed:.3f}s.") + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/PAGE/test_docs.py b/PAGE/test_docs.py new file mode 100644 index 0000000..be0ac93 --- /dev/null +++ b/PAGE/test_docs.py @@ -0,0 +1,94 @@ +import os, re, subprocess, sys, time +from pathlib import Path + +TIMEOUT = 90 +# IMPLEMENTATION = "python" +# IMPLEMENTATION = "c" +IMPLEMENTATION = os.environ.get("IMPLEMENTATION", "c") + +# Identify the graphs that finish in finite time in the docs +rows = [] +for line in Path("../docs/practical_performance.md").read_text().splitlines(): + m = re.search(r"\((\.\./PAGE/adjacency_lists/[^)]+)\)", line) + if not m: + continue + cells = [c.strip() for c in line.split("|")] + if len(cells) >= 10: + genus, page_time = cells[-4], cells[-3] + elif len(cells) >= 6: + genus, page_time = cells[-3], cells[-2] + else: + continue + if not re.fullmatch(r"\d+", genus): + continue + if not re.fullmatch(r"\d+(?:\.\d+)?", page_time): + continue + path = m.group(1).replace("../PAGE/", "") + vals = list(map(int, Path(path).read_text().split())) + n = vals[0] + degree = (len(vals) - 2) // n + rows.append((path, degree, int(genus))) + +# Run the graphs +fail = [] +start = time.perf_counter() +for idx, (path, degree, expected) in enumerate(rows, 1): + start = float("Inf") + with open(path, "r") as f: + lines = f.readlines()[1:] + for line in lines: + start = min(start, min(map(int, line.split()))) + + t = time.perf_counter() + env = os.environ.copy() + if IMPLEMENTATION == "python": + cmd = [ + sys.executable, + "page.py", + "--quiet", + "--adj", + path, + "--degree", + str(degree), + "--start", + str(start), + "--out", + "/tmp/page_test_docs.out", + ] + elif IMPLEMENTATION == "c": + cmd = ["make", "run"] + env["S"] = str(start) + env["DEG"] = str(degree) + env["ADJ"] = path + env["STDOUT"] = "1" + else: + raise ValueError("Invalid implementation: must be 'python' or 'c'") + try: + cp = subprocess.run( + cmd, text=True, capture_output=True, timeout=TIMEOUT, env=env + ) + except subprocess.TimeoutExpired: + dt = time.perf_counter() - t + print( + f"{idx:02d}/{len(rows)} TIMEOUT {path} expected={expected} after {dt:.1f}s", + flush=True, + ) + fail.append((path, "timeout", expected, None)) + continue + out = cp.stdout + cp.stderr + m = re.search(r"genus is (\d+)", out) + got = int(m.group(1)) if m else None + if got is None: + m = re.search(r"It is (\d+)", out) + got = int(m.group(1)) if m else None + status = "OK" if cp.returncode == 0 and got == expected else "FAIL" + print( + f"{idx:02d}/{len(rows)} {status} {path} expected={expected} got={got} time={time.perf_counter()-t:.3f}s", + flush=True, + ) + if status != "OK": + fail.append((path, cp.returncode, expected, got, out[-500:])) + +print("TOTAL", time.perf_counter() - start, "failures", len(fail)) +for f in fail: + print("FAILDETAIL", f) diff --git a/CalcGenus/test_issue_graphs.py b/PAGE/test_issue_graphs.py similarity index 90% rename from CalcGenus/test_issue_graphs.py rename to PAGE/test_issue_graphs.py index 600212a..ab755eb 100755 --- a/CalcGenus/test_issue_graphs.py +++ b/PAGE/test_issue_graphs.py @@ -1,5 +1,5 @@ #!/usr/bin/env python3 -"""Run CalcGenus against the GitHub issue regression fixtures.""" +"""Run PAGE against the GitHub issue regression fixtures.""" from __future__ import annotations @@ -13,7 +13,7 @@ ADJ_DIR = ROOT / "adjacency_lists" CASES = [ - ("issue2_quartic_counterexample.txt", 2, 2, "issue #2 quartic counterexample"), + ("issue2_quartic_counterexample.txt", 2, "issue #2 quartic counterexample"), ("issue3_01886.txt", 1, "issue #3 graph6 1886:H??FFz{"), ("issue3_01995.txt", 1, "issue #3 graph6 1995:H??FfZ{"), ("issue3_02060.txt", 1, "issue #3 graph6 2060:H??Fvjk"), @@ -106,11 +106,19 @@ def run_case(case: tuple) -> tuple[bool, str]: filename, expected, glb, label = case path = ADJ_DIR / filename env = os.environ.copy() - env.update({"S": "0", "DEG": str(read_degree(path)), "ADJ": str(path), "STDOUT": "1", "PBN": "1"}) + env.update( + { + "S": "0", + "DEG": str(read_degree(path)), + "ADJ": str(path), + "STDOUT": "1", + "PBN": "1", + } + ) if glb is not None: env["GLB"] = str(glb) result = subprocess.run( - [str(ROOT / "CalcGenus")], + [str(ROOT / "page")], cwd=ROOT, env=env, text=True, @@ -120,9 +128,12 @@ def run_case(case: tuple) -> tuple[bool, str]: output = result.stdout + result.stderr actual = extract_genus(output) if result.returncode != 0: - return False, f"{label}: CalcGenus exited {result.returncode}\n{output[-1200:]}" + return False, f"{label}: PAGE exited {result.returncode}\n{output[-1200:]}" if actual != expected: - return False, f"{label}: expected genus {expected}, got {actual}\n{output[-1200:]}" + return ( + False, + f"{label}: expected genus {expected}, got {actual}\n{output[-1200:]}", + ) return True, f"{label}: genus {actual}" diff --git a/PAGE/test_rome.py b/PAGE/test_rome.py new file mode 100644 index 0000000..825345d --- /dev/null +++ b/PAGE/test_rome.py @@ -0,0 +1,108 @@ +#!/usr/bin/env sage +"""Run PAGE against the ROME dataset (https://visdunneright.github.io/gd_benchmark_sets/#moveToRome-Lib).""" + +import tarfile +import networkx as nx # type: ignore +import os, signal +import subprocess, threading +from sage.all import Graph # type: ignore +from tqdm import tqdm + + +class Command(object): + def __init__(self, cmd): + self.cmd = cmd + self.process: subprocess.Popen | None = None + + self.stdout: str | None = None + self.stderr: str | None = None + + def run(self, timeout, hide_output=True): + def target(): + if hide_output: + self.process = subprocess.Popen( + self.cmd, + shell=True, + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + preexec_fn=os.setsid, + ) + else: + self.process = subprocess.Popen( + self.cmd, + shell=True, + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + preexec_fn=os.setsid, + ) + self.stdout, self.stderr = self.process.communicate() + + thread = threading.Thread(target=target) + thread.start() + + thread.join(timeout) + if thread.is_alive() and self.process: + os.killpg(self.process.pid, signal.SIGTERM) + thread.join() + + return self.process and self.process.returncode + + +# command = Command("echo 'Process started'; sleep 2; echo 'Process finished'") +# print(command.run(timeout=3)) +# print(command.run(timeout=1)) + +valid = 0 +successfull = 0 +try: + with tarfile.open("adjacency_lists/rome-graphml.tgz", "r:gz") as tar: + for name in tqdm(tar.getnames()): + if not name.endswith(".graphml"): + continue + + f = tar.extractfile(name) + + # load as sage graph + g = Graph(nx.read_graphml(f)) + obscure = int(name.split(".")[1]) != g.num_verts() + + # print("Obscure:", obscure) + # print("Connected:", g.is_connected()) + # print("Planar:", g.is_planar()) + # print("Regular:", g.is_regular()) + # print("Max Degree:", max(g.degree())) + + if not obscure and g.is_connected() and not g.is_planar(): + valid += 1 + + while min(g.degree()) <= 1: + g.delete_vertices( + [v for v in g.vertices() if g.degree(v) <= 1] + ) # remove nodes with only one edge + for v in g.vertices(): + if g.degree(v) == 2: + # replace with a single edge + g.add_edge(g.neighbors(v)) + g.delete_vertex(v) + g.relabel() # relabel edges to numbers + adjacency_list = [[] for j in range(len(g.vertices()))] + for e in g.edges(): + adjacency_list[e[0]].append(e[1]) + adjacency_list[e[1]].append(e[0]) + max_degree = max(g.degree()) + for i in range(len(g.vertices())): # pad adjacency list + while len(adjacency_list[i]) < max_degree: + adjacency_list[i].append(65535) + with open("adjacency_lists/rome_temp.txt", "w") as f: + f.write(f"{len(g.vertices())} {len(g.edges())}\n") + for i in range(len(g.vertices())): + f.write(f'{" ".join(map(str, adjacency_list[i]))}\n') + + command = Command( + f'S="0" DEG="{max_degree}" ADJ="adjacency_lists/rome_temp.txt" make run' + ) + terminated = command.run(timeout=10) == -15 + if not terminated: + successfull += 1 +finally: + print(valid, successfull) diff --git a/PAGE/verify_faces.py b/PAGE/verify_faces.py new file mode 100644 index 0000000..988c8ee --- /dev/null +++ b/PAGE/verify_faces.py @@ -0,0 +1,136 @@ +#!/usr/bin/env sage +"""Check whether the faces output by PAGE are a valid embedding.""" + +import os +from sage.all import Graph, matrix # type: ignore + +IGNORE_VERTEX = 65535 +GRAPH = "austin_test.txt" +FACES = [ + [0, 6, 2, 8, 1, 7, 0], + [3, 9, 4, 11, 5, 10, 3], + [0, 8, 2, 11, 4, 10, 5, 9, 3, 7, 1, 6, 0], + [0, 7, 3, 10, 4, 9, 5, 11, 2, 6, 1, 8, 0], +] + +# convert off-indexed to 0-indexed +off = min(min(v for v in f) for f in FACES) +solution = [[x - off for x in y] for y in FACES] + +# load the graph +with open(os.path.join("adjacency_lists", GRAPH), "r") as f: + lines = f.readlines() + num_vertices, num_edges = map(int, lines.pop(0).strip().split(" ")) + adjacency_list = [set() for _ in range(num_vertices)] + min_number = min(map(int, " ".join(lines).split())) + for v, line in enumerate(lines): + neighbors = map(int, line.strip().split(" ")) + for u in neighbors: + if u == IGNORE_VERTEX: + continue + adjacency_list[v].add(u - min_number) + adjacency_list[u - min_number].add(v) + +adjacency_matrix = [[0 for i in range(num_vertices)] for j in range(num_vertices)] +for i in range(num_vertices): + for j in adjacency_list[i]: + adjacency_matrix[i][j] = 1 + adjacency_matrix[j][i] = 1 + +g = Graph(matrix(adjacency_matrix), format="adjacency_matrix") + +# no duplicates edges +edges = set() +for c in solution: + for i in range(len(c) - 1): + assert (c[i], c[i + 1]) not in edges, ( + "Duplicate edge " + str(c[i]) + " " + str(c[i + 1]) + ) + edges.add((c[i], c[i + 1])) + +# no duplicate cycles in the solution +for i, c1 in enumerate(solution): + for j, c2 in enumerate(solution): + if i == j: + continue + if list(reversed(c1)) == c2: + continue + try: + offset = c2.index(c1[0]) + except ValueError: + continue + assert c2[offset:] + c2[:offset] != c1, ( + "Duplicate cycles " + str(c1) + " " + str(c2) + ) + + +def x_in_y(query, base): + try: + l = len(query) + except TypeError: + l = 1 + query = type(base)((query,)) + + for i in range(len(base)): + if base[i : i + l] == query: + return True + return False + + +# make sure if vertices i, j, k occur in the solution, k, j, i don't +for c in solution: + c = c.copy() + [c[1]] + for i in range(len(c) - 2): + for c2 in solution: + c2 = c2.copy() + [c2[1]] + assert not x_in_y([c[i + 2], c[i + 1], c[i]], c2), ( + "Found " + + str(c[i]) + + " " + + str(c[i + 1]) + + " " + + str(c[i + 2]) + + " in " + + str(c2) + ) + +# Make sure all vertices are used +vertex_uses = g.degree_sequence() +for c in solution: + for v in c[:-1]: + vertex_uses[v] -= 1 +assert all([v == 0 for v in vertex_uses]), "All vertices should be used fully" + +# convert edges list to adjacency list +al = [[] for _ in range(g.num_verts())] +for e in g.edges(): + al[e[0]].append(e[1]) + al[e[1]].append(e[0]) + +# check if every edge is used exactly once by removing them from the adjacency list +for c in solution: + for i in range(len(c) - 1): + assert c[i + 1] in al[c[i]], ( + "Edge " + str(c[i]) + " " + str(c[i + 1]) + " not in adjacency list" + ) + al[c[i]].remove(c[i + 1]) +assert all([len(v) == 0 for v in al]), "All edges should be used exactly once" + +# verify the rotation system (sorted adjacency list) +adj = [[] for _ in range(num_vertices)] +pairs = [[] for _ in range(num_vertices)] +for c in solution: + ce = c[:-1] + for i in range(len(c) - 1): + pairs[c[i]].append((ce[i - 1], c[i + 1])) +for i, p in enumerate(pairs): + u, v = p.pop(0) + s = u + adj[i].append(u) + while v != s: + adj[i].append(v) + u, v = list(filter(lambda x: x[0] == v, p))[0] + p.remove((u, v)) + assert len(p) == 0, "Invalid rotation system" + +print("Valid!") diff --git a/PAGE/visualize_faces.py b/PAGE/visualize_faces.py new file mode 100644 index 0000000..916fc68 --- /dev/null +++ b/PAGE/visualize_faces.py @@ -0,0 +1,145 @@ +#!/usr/bin/env sage +"""Visualize the faces output by PAGE.""" + +import os +from sage.all import Graph, matrix # type: ignore +from sage.plot.text import Text # type: ignore + +# Inputs +GRAPH = "austin_test.txt" +FACES = [ + [0, 6, 2, 8, 1, 7, 0], + [3, 9, 4, 11, 5, 10, 3], + [0, 8, 2, 11, 4, 10, 5, 9, 3, 7, 1, 6, 0], + [0, 7, 3, 10, 4, 9, 5, 11, 2, 6, 1, 8, 0], +] + +# Constants +IGNORE_VERTEX = 65535 +COLORS = { + 0: "black", + 1: "blue", + 2: "purple", + 3: "red", + 4: "green", + 5: "orange", + 6: "yellow", + 7: "brown", + 8: "pink", + 9: "cyan", + 10: "magenta", + 11: "grey", + 12: "lightblue", + 13: "lightgreen", + 14: "teal", + 15: "salmon", + 16: "navy", + 17: "gold", + 18: "lime", + 19: "indigo", + 20: "maroon", + 21: "olive", + 22: "khaki", + 23: "indianred", + 24: "salmon", + 25: "deeppink", + 26: "orchid", + 27: "royalblue", + 28: "tomato", + 29: "aquamarine", + 30: "navajowhite", + 31: "floralwhite", + 32: "tan", + 33: "darkgoldenrod", + 34: "paleturquoise", + 35: "darkslateblue", + 36: "lavenderblush", + 37: "hotpink", + 38: "crimson", + 39: "orangered", +} + +# convert off-indexed to 0-indexed +off = min(min(v for v in f) for f in FACES) +solution = [[x - off for x in y] for y in FACES] + +# load the graph +with open(os.path.join("adjacency_lists", GRAPH), "r") as f: + lines = f.readlines() + num_vertices, num_edges = map(int, lines.pop(0).strip().split(" ")) + adjacency_list = [set() for _ in range(num_vertices)] + min_number = min(map(int, " ".join(lines).split())) + for v, line in enumerate(lines): + neighbors = map(int, line.strip().split(" ")) + for u in neighbors: + if u == IGNORE_VERTEX: + continue + adjacency_list[v].add(u - min_number) + adjacency_list[u - min_number].add(v) + +adjacency_matrix = [[0 for i in range(num_vertices)] for j in range(num_vertices)] +for i in range(num_vertices): + for j in adjacency_list[i]: + adjacency_matrix[i][j] = 1 + adjacency_matrix[j][i] = 1 + +g = Graph(matrix(adjacency_matrix), format="adjacency_matrix") +g_directed = g.to_directed() + + +# Show the faces colored +def is_in_cycle(e, cycle): + try: + i = cycle.index(e[0]) + j = cycle.index(e[1]) + + if i + 1 == j or (i == len(cycle) - 2 and j == 0): + return True + else: + return False + except ValueError: + return False + + +for e in g_directed.edges(): + g_directed.set_edge_label(e[0], e[1], 0) + for i, c in enumerate(solution): + if is_in_cycle(e, c): + g_directed.set_edge_label(e[0], e[1], i + 1) + +p = g_directed.plot( + edge_colors=g_directed._color_by_label(COLORS), + vertex_size=70, + vertex_color="midnightblue", + transparent=True, +) +for object in p._objects: + if isinstance(object, Text): + object._options["rgbcolor"] = (1, 1, 1) + +# export as PDF +p.save("faces_all.pdf", figsize=(14, 14)) + +g_directed.layout() +pos = g_directed.get_pos() +for i, c in enumerate(solution): + for e in g_directed.edges(): + g_directed.set_edge_label(e[0], e[1], 0) + if is_in_cycle(e, c): + g_directed.set_edge_label(e[0], e[1], i + 1) + + g_directed.set_pos(pos) + + p = g_directed.plot( + edge_colors=g_directed._color_by_label(COLORS), + vertex_size=70, + vertex_color="midnightblue", + transparent=True, + pos=pos, + layout="circular", + ) + for object in p._objects: + if isinstance(object, Text): + object._options["rgbcolor"] = (1, 1, 1) + + p.save(f"faces_{i}.pdf", figsize=(14, 14)) diff --git a/PAGE/visualize_k33_faces.py b/PAGE/visualize_k33_faces.py new file mode 100644 index 0000000..59519ce --- /dev/null +++ b/PAGE/visualize_k33_faces.py @@ -0,0 +1,211 @@ +#!/usr/bin/env sage +"""Visualize K3,3's faces.""" + +from sage.all import graphics_array, graphs # type: ignore +from sage.plot.text import Text # type: ignore + +COLORS = { + 0: "black", + 1: "blue", + 2: "purple", + 3: "red", + 4: "green", + 5: "orange", + 6: "yellow", + 7: "brown", + 8: "pink", + 9: "cyan", + 10: "magenta", + 11: "grey", + 12: "lightblue", + 13: "lightgreen", + 14: "teal", + 15: "salmon", + 16: "navy", + 17: "gold", + 18: "lime", + 19: "indigo", + 20: "maroon", + 21: "olive", + 22: "khaki", + 23: "indianred", + 24: "salmon", + 25: "deeppink", + 26: "orchid", + 27: "royalblue", + 28: "tomato", + 29: "aquamarine", + 30: "navajowhite", + 31: "floralwhite", + 32: "tan", + 33: "darkgoldenrod", + 34: "paleturquoise", + 35: "darkslateblue", + 36: "lavenderblush", + 37: "hotpink", + 38: "crimson", + 39: "orangered", +} + +G = graphs.CompleteBipartiteGraph(3, 3) +old_labels = G.vertices() +new_labels = list(range(1, len(old_labels) + 1)) +label_map = dict(zip(old_labels, new_labels)) +G = G.relabel(label_map, inplace=False) +g_directed = G.to_directed() +g_directed.layout() +pos = g_directed.get_pos() +cycles = g_directed.all_simple_cycles() + + +def is_in_cycle(e, cycle): + i_s = [i for i, x in enumerate(cycle) if x == e[0]] + j_s = [i for i, x in enumerate(cycle) if x == e[1]] + + for i in i_s: + for j in j_s: + if i + 1 == j or (i == len(cycle) - 2 and j == 0): + return True + return False + + +# Show all simple cycles +plots = [] +for i, c in enumerate(cycles): + for e in g_directed.edges(): + g_directed.set_edge_label(e[0], e[1], 0) + if is_in_cycle(e, c): + g_directed.set_edge_label(e[0], e[1], i + 1) + + g_directed.set_pos(pos) + + p = g_directed.plot( + edge_colors=g_directed._color_by_label(COLORS), + vertex_size=70, + vertex_color="midnightblue", + transparent=True, + pos=pos, + layout="circular", + ) + for object in p._objects: + if isinstance(object, Text): + object._options["rgbcolor"] = (1, 1, 1) + # p.show(figsize=(10, 10)) + plots.append(p) + +graphics_array([plots[i : i + 13] for i in range(0, len(plots), 13)]).save( + "k33_simple_cycles.pdf", figsize=(130, 30) +) + + +def find_cycles(g, k, include_non_simple=False): + """Find cycles of length k (including non-simple ones if enabled).""" + # TODO: fix off-by-one bugs by matching page.c + adjacency_list = [[] for _ in range(len(g.vertices()))] + offset = min(g.vertices()) + for e in g.edges(): + adjacency_list[e[0] - offset].append(e[1] - offset) + adjacency_list[e[1] - offset].append(e[0] - offset) + + cycles = [] + queue = [] + for i in range(len(g.vertices())): + queue.append([i]) + if include_non_simple: + while len(queue) > 0: + path = queue.pop(0) + if len(path) == k: + if path[0] in adjacency_list[path[-1]] and path[-1] != path[1]: + repeated_edge = False + for j in range(len(path) - 1): + if path[j] == path[-1] and path[j + 1] == i: + repeated_edge = True + break + if repeated_edge: + continue + cycle = path + [path[0]] + cycles.append(cycle) + continue + for i in adjacency_list[path[-1]]: + if len(path) > 2 and i == path[-2]: + continue + repeated_edge = False + for j in range(len(path) - 1): + if path[j] == path[-1] and path[j + 1] == i: + repeated_edge = True + break + if repeated_edge: + continue + if i >= path[0]: + queue.append(path + [i]) + else: + while len(queue) > 0: + path = queue.pop(0) + if len(path) == k: + if path[0] in adjacency_list[path[-1]]: + cycle = path + [path[0]] + cycles.append(cycle) + continue + for i in adjacency_list[path[-1]]: + if i not in path and i > path[0]: + queue.append(path + [i]) + + return [[v + offset for v in c] for c in cycles] + + +# Show closed trails of length 4 +cycles = find_cycles(G, 4, include_non_simple=True) +plots = [] +for i, c in enumerate(cycles): + if not is_in_cycle((6, 2), c): + continue + + for e in g_directed.edges(): + g_directed.set_edge_label(e[0], e[1], 0) + if is_in_cycle(e, c): + g_directed.set_edge_label(e[0], e[1], i + 1) + + g_directed.set_pos(pos) + + p = g_directed.plot( + edge_colors=g_directed._color_by_label(COLORS), + vertex_size=70, + vertex_color="midnightblue", + transparent=True, + pos=pos, + layout="circular", + ) + for object in p._objects: + if isinstance(object, Text): + object._options["rgbcolor"] = (1, 1, 1) + # p.show(figsize=(10, 10)) + plots.append(p) + +graphics_array([plots[i : i + 4] for i in range(0, len(plots), 4)]).save( + "k33_length_4_faces.pdf", figsize=(40, 20) +) + + +# Show one solution +solution = [[2, 5, 1, 6, 2], [6, 1, 4, 3, 6], [5, 2, 4, 1, 5, 3, 4, 2, 6, 3, 5]] +for e in g_directed.edges(): + g_directed.set_edge_label(e[0], e[1], 0) + for i, c in enumerate(solution): + if is_in_cycle(e, c): + g_directed.set_edge_label(e[0], e[1], i + 1) + +g_directed.set_pos(pos) + +p = g_directed.plot( + edge_colors=g_directed._color_by_label(COLORS), + vertex_size=70, + vertex_color="midnightblue", + transparent=True, + pos=pos, + layout="circular", +) +for object in p._objects: + if isinstance(object, Text): + object._options["rgbcolor"] = (1, 1, 1) + +p.save("k33_solution.pdf", figsize=(10, 10)) diff --git a/README.md b/README.md index 78620c1..0fcaf50 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,5 @@ # A Practical Algorithm for Graph Embedding (PAGE) +[![DOI](https://zenodo.org/badge/doi/10.1016/j.disc.2026.115308.svg)](http://doi.org/10.1016/j.disc.2026.115308) [![arXiv](https://img.shields.io/badge/arXiv-2411.07347-b31b1b.svg)](https://arxiv.org/abs/2411.07347) [![maintenance-status](https://img.shields.io/badge/maintenance-actively--developed-brightgreen.svg)](https://gist.github.com/taiki-e/ad73eaea17e2e0372efb76ef6b38f17b) @@ -6,327 +7,52 @@ A famous problem at the intersection of topology and combinatorial graph theory [![K3,3 Torus Embedding](images/k3-3torus.png)](images/k3-3torus.png) -The characterizing property of a torus that allows us to embed K3,3 is that it has a hole (unlike surfaces such as a plane or a sphere). This motivates classifying surfaces by their number of holes, that is, their genus g. The genus of a graph G is then simply the genus of the minimum genus surface on which G can be embedded without edges crossing. For genus zero we use the special name _planar_ and for genus one we use _toroidal_. Calculating the genus of a graph has a number of applications, particularly in the design of integrated circuits, study of graph minors, VLSI design, infrastructure planning, and more. +The characterizing property of a torus that allows us to embed K3,3 is that it has a hole (unlike surfaces such as a plane or a sphere). This motivates classifying surfaces by their number of holes, that is, their genus g. The genus of a graph G is then simply the genus of the minimum genus surface on which G can be embedded without edges crossing. For genus zero we use the special name _planar_ and for genus one we use _toroidal_. Calculating the genus of a graph has a number of applications, particularly in the design of integrated circuits, study of graph minors, VLSI design, infrastructure planning, and more. For an interactive visualization of graph embedding [check here](https://genus.sandergi.com/k33_rotation_animation.html). -## Properties of this algorithm +## Properties of PAGE (our algorithm) This repo contains a fast algorithm for calculating the genus of arbitrary graphs. It has a number of properties that make it practical for real-world use: -1) **Verification**: The algorithm outputs not only the genus but also the corresponding rotation system that defines the surface embedding that achieves this minimum genus. This allows for easy verification of the result both via a [Python script](CalcGenus/verifyEmbedding.ipynb) and visually: - +1) **Verification**: The algorithm outputs not only the genus but also the corresponding rotation system that defines the surface embedding that achieves this minimum genus. This allows for easy verification of the result both via a [Python script](PAGE/verify_faces.py) and [visually](PAGE/visualize_faces.py): [![19 cycles](images/19Cycles.png)](images/19Cycles.png) -2) **Progressively Narrowing Bounds**: The algorithm iterates through possible embeddings and progressively narrows the bounds on the genus. This allows for early stopping if only an estimate is needed. +1) **Speed**: The algorithm can handle graphs with high genus much better than existing algorithms. It also takes effective advantage of the girth and cycle distribution of a graph to work very well in practice. PAGE, for instance, completes the (3, 10) Cages in a few seconds whereas SageMath doesn't finish in weeks and `multi_genus` takes hours. See [more benchmarks here](docs/practical_performance.md) and [theoretical worst case performance here](docs/time_complexity.md). -3) **Simplicity of Implementation**: While there exist more efficient algorithms for certain graph families (e.g., `multi_genus` does better on lower genus high degree graphs), this algorithm is much simpler to implement (can be done in a few dozen lines of Python or a few hundred lines of C). +1) **Progressively Narrowing Bounds**: The algorithm can iterate through possible embeddings in heuristic order and progressively narrow the bounds on the genus. This allows for early stopping if only an estimate is needed. -4) **Scales Well With Genus**: The algorithm can handle graphs with high genus much better than existing algorithms. It can for instance complete the (3, 10) Cages in a few minutes whereas SageMath doesn't finish in weeks and `multi_genus` takes hours. It does not, however, scale as well with degree as `multi_genus` for low genus graphs, so there is a tradeoff and the optimal algorithm depends on both the genus and degree of the graph. +1) **Easily Parallelizable**: The algorithm can be easily parallelized since a parallelizable cycle finding algorithm is chosen and the search needs to go through each possible start cycle (which can be done in parallel). This allows for a speedup proportional to the number of cores available. -5) **Easily Parallelizable**: The algorithm can be easily parallelized since a parallelizable cycle finding algorithm is chosen and the search needs to go through each possible start cycle (which can be done in parallel). This allows for a speedup proportional to the number of cores available. +1) **Simplicity of Implementation**: While there exist more efficient algorithms for certain graph families (e.g., `multi_genus` does better on lower genus high degree graphs), this algorithm is much simpler to implement (can be done in [a few hundred lines of code](PAGE/page.py)). ## Usage -The easiest way is to use the [hosted version](https://genus.fly.dev/). This won't be as fast as running it locally and I can't guarantee it will always be up, but it should allow you to explore the algorithm. You can also self-host the web application by [installing docker](https://docs.docker.com/get-docker/) and running `cd WebApp` followed by `. ./run-dev.sh`. This will start the web application on `localhost:8080`. +The easiest way is to use the [hosted version](https://genus.sandergi.com/). This won't be as fast as running it locally and I can't guarantee it will always be up, but it should allow you to explore the algorithm. You can also self-host the web application by [installing docker](https://docs.docker.com/get-docker/) and running `cd WebApp` followed by `. ./run-dev.sh`. This will start the web application on `localhost:8080`. To run the python scripts you must have [SageMath installed](https://doc.sagemath.org/html/en/installation/index.html) and select the SageMath kernel in Jupyter/VS Code/whatever you use. -To run the C program for any graph, `cd CalcGenus` and run `S="0" DEG="3" ADJ="adjacency_lists/3-8-cage.txt" make run`. This will compile the C program and run it. The output will be in `CalcGenus.out`. The format of the adjacency lists is the number of vertices and number of edges on the first line followed by the neighbors of each vertex on the following lines. See the examples in `CalcGenus/adjacency_lists/`. Use `MallocStackLogging=1 S="0" DEG="3" ADJ="adjacency_lists/3-8-cage.txt" leaks -quiet -atExit -- ./CalcGenus` to check for memory leaks on macOS. Use `S=0 DEG=7 ADJ="adjacency_lists/coHerschel.txt" lldb --file ./CalcGenus` and type `r` then `bt` to debug segmentation faults. If you're on Windows, you'll probably have an easier time if you use [WSL](https://learn.microsoft.com/en-us/windows/wsl/install) or [MSYS](https://www.msys2.org/). - -## Time Complexity - -Let `n` be the size of the vertex set `V` and `m` the size of the edge set `E`. Let `G` be the girth of the graph. - -The algorithm in this repository is roughly `O(n(4^m/n)^(n/G))`. It has some optimizations that allows it to stop early not captured in the below analysis. - -- Upper bound on the number of directed trails of length `k`: `2m choose k = (2m)!/k!/(2m-k)!` which is bounded above by `\sqrt{\frac{1}{2\pi}}\frac{\left(2m\right)^{\left(2m+\frac{1}{2}\right)}}{k^{\left(k+\frac{1}{2}\right)}\left(2m-k\right)^{\left(2m-k+\frac{1}{2}\right)}}` as seen in [Bob Gallager's Information Theory and Reliable Communications](https://mathoverflow.net/questions/236508/are-there-good-bounds-on-binomial-coefficients). This is maximized for `k=m` where it simplifies to `4^m/\sqrt{\pi m}`. A simpler but less tight bound is `2m choose k <= (2em/k)^k`. -- The number of directed trails of any length is `O(4^m)` because it is the sum of the values in the `2m`th row of Pascal's triangle. -- This can also be used to upper bound the number of *non-backtracking closed* directed trails which is what our trail finding algorithm enumerates. Let `c` be the number of trails enumerated by our trail finding algorithm. -- Organizing the `c` trails by vertex is `O(2mc) < O(2m4^m)` since each trail has at most `2m` edges. - -- Finding the most used vertex to explore: `O(n)` by iterating through the vertices (overall time complexity is better when write is kept `O(1)`) -- Looking up the cycles that use a vertex: `O(1)` via hashset lookup -- Checking if a cycle is used: `O(1)` via hashset lookup -- Checking if the edges of a cycle are used: `O(m)` by storing the edges used in a hashset -- Checking if adding cycle breaks rotation system: `O(m)` by storing the current rotation with the adjacency list -- Search iteration (f = implied fit, b = cycles by vertex >= u = unused >= a = w/ edges available >= d = rotation valid): `T(f) = O(n) + O(1) + b O(1) + u O(m) + a O(m) + d T(f-1); T(0) = 0` => `O(d^f * (n + b + um + am)) = O(d^f * (n + b + m(u + a))) < O(b^(f + 2))` -- All search iterations (h = number of start cycles to try out < `4^m`): `O(b^(f + 2) * h) < O((4^m / n)^(n/G) * 4^m) = O(n(4^m/n)^(n/G))`. - -The algorithm is particularly advantageous for high girth graphs such as the cage family of graphs. - -## Practical Performance - -The genus for various cage graphs using the adjacency lists from [win.tue.nl](https://www.win.tue.nl/~aeb/graphs/cages/cages.html). Number (\# links to adjacency list), valency (k), girth (g), vertices (v), edges (e), size of the automorphism group (\|G\|), genus, computation time for the genus (time), computation time for the genus using SageMath (SM time), and computation time using multi_genus.c (MG time). -\# | k | g | v | e | \|G\| | genus | time (s) | SM time (s) | MG time (s) -------------------------------------------------- | --- | --- | ---- | ----- | ---------- | ---------- | -------- | ----------- | ----------- -[1/1](CalcGenus/adjacency_lists/3-3-cage.txt) | 3 | 3 | 4 | 6 | 24 | 0 | 0.005 | 0.004 | 0.006 -[1/1](CalcGenus/adjacency_lists/3-4-cage.txt) | 3 | 4 | 6 | 9 | 72 | 1 | 0.005 | 0.039 | 0.006 -[1/1](CalcGenus/adjacency_lists/3-5-cage.txt) | 3 | 5 | 10 | 15 | 120 | 1 | 0.008 | 0.027 | 0.006 -[1/1](CalcGenus/adjacency_lists/3-6-cage.txt) | 3 | 6 | 14 | 21 | 336 | 1 | 0.005 | 0.010 | 0.006 -[1/1](CalcGenus/adjacency_lists/3-7-cage.txt) | 3 | 7 | 24 | 36 | 32 | 2 | 0.006 | 1.737 | 0.006 -[1/1](CalcGenus/adjacency_lists/3-8-cage.txt) | 3 | 8 | 30 | 45 | 1440 | 4 | 0.066 | 118.958 | 0.012 -[1/18](CalcGenus/adjacency_lists/3-9-cage1.txt) | 3 | 9 | 58 | 87 | 4 | 7 | 2.684 | days | 29.084 -[2/18](CalcGenus/adjacency_lists/3-9-cage2.txt) | 3 | 9 | 58 | 87 | 2 | 7 | 19.587 | days | 30.909 -[3/18](CalcGenus/adjacency_lists/3-9-cage3.txt) | 3 | 9 | 58 | 87 | 24 | 7 | 14.388 | days | 25.993 -[4/18](CalcGenus/adjacency_lists/3-9-cage4.txt) | 3 | 9 | 58 | 87 | 4 | 7 | 3.053 | days | 54.396 -[5/18](CalcGenus/adjacency_lists/3-9-cage5.txt) | 3 | 9 | 58 | 87 | 4 | 7 | 2.644 | days | 67.89 -[6/18](CalcGenus/adjacency_lists/3-9-cage6.txt) | 3 | 9 | 58 | 87 | 2 | 7 | 0.457 | days | 45.310 -[7/18](CalcGenus/adjacency_lists/3-9-cage7.txt) | 3 | 9 | 58 | 87 | 1 | 7 | 1.794 | days | 37.257 -[8/18](CalcGenus/adjacency_lists/3-9-cage8.txt) | 3 | 9 | 58 | 87 | 2 | 7 | 1.240 | days | 42.843 -[9/18](CalcGenus/adjacency_lists/3-9-cage9.txt) | 3 | 9 | 58 | 87 | 1 | 7 | 2.940 | days | 34.437 -[10/18](CalcGenus/adjacency_lists/3-9-cage10.txt) | 3 | 9 | 58 | 87 | 2 | 7 | 1.678 | days | 86.54 -[11/18](CalcGenus/adjacency_lists/3-9-cage11.txt) | 3 | 9 | 58 | 87 | 1 | 7 | 1.076 | days | 54.990 -[12/18](CalcGenus/adjacency_lists/3-9-cage12.txt) | 3 | 9 | 58 | 87 | 2 | 7 | 10.113 | days | 51.589 -[13/18](CalcGenus/adjacency_lists/3-9-cage13.txt) | 3 | 9 | 58 | 87 | 1 | 7 | 11.859 | days | 32.340 -[14/18](CalcGenus/adjacency_lists/3-9-cage14.txt) | 3 | 9 | 58 | 87 | 12 | 7 | 2.498 | days | 30.824 -[15/18](CalcGenus/adjacency_lists/3-9-cage15.txt) | 3 | 9 | 58 | 87 | 8 | 7 | 2.853 | days | 44.888 -[16/18](CalcGenus/adjacency_lists/3-9-cage16.txt) | 3 | 9 | 58 | 87 | 2 | 7 | 2.571 | days | 57.890 -[17/18](CalcGenus/adjacency_lists/3-9-cage17.txt) | 3 | 9 | 58 | 87 | 6 | 7 | 130.47 | days | 140.50 -[18/18](CalcGenus/adjacency_lists/3-9-cage18.txt) | 3 | 9 | 58 | 87 | 6 | 7 | 0.801 | days | 47.737 -[1/3](CalcGenus/adjacency_lists/3-10-cage1.txt) | 3 | 10 | 70 | 105 | 120 | 9 | 51.258 | DNF | 9354.14 -[2/3](CalcGenus/adjacency_lists/3-10-cage2.txt) | 3 | 10 | 70 | 105 | 24 | 9 | 60.66 | DNF | 9556.13 -[3/3](CalcGenus/adjacency_lists/3-10-cage3.txt) | 3 | 10 | 70 | 105 | 80 | 9 | 49.850 | DNF | 10680.89 -[1/1](CalcGenus/adjacency_lists/3-11-cage.txt) | 3 | 11 | 112 | 168 | 64 | [14, 17] | days | DNF | days -[1/1](CalcGenus/adjacency_lists/3-12-cage.txt) | 3 | 12 | 126 | 189 | 12096 | 17 | 1757.92 | DNF | days -[1/1](CalcGenus/adjacency_lists/4-5-cage.txt) | 4 | 5 | 19 | 38 | 24 | 4 | 0.020 | days | 0.019 -[1/1](CalcGenus/adjacency_lists/4-6-cage.txt) | 4 | 6 | 26 | 52 | 11232 | 6 | 0.011 | DNF | 0.013 -[1/?](CalcGenus/adjacency_lists/4-7-cage1.txt) | 4 | 7 | 67 | 134 | 4 | [16, 21] | days | DNF | days -[1/1](CalcGenus/adjacency_lists/4-8-cage.txt) | 4 | 8 | 80 | 160 | 51840 | [21, 27] | days | DNF | days -[1/?](CalcGenus/adjacency_lists/4-12-cage1.txt) | 4 | 12 | 728 | 1456 | 8491392 | [244, 363] | DNF | DNF | too big for bit operations -[1/4](CalcGenus/adjacency_lists/5-5-cage1.txt) | 5 | 5 | 30 | 75 | 120 | [9, 10] | days | DNF | days -[2/4](CalcGenus/adjacency_lists/5-5-cage2.txt) | 5 | 5 | 30 | 75 | 20 | [9, 13] | days | DNF | days -[3/4](CalcGenus/adjacency_lists/5-5-cage3.txt) | 5 | 5 | 30 | 75 | 30 | [9, 14] | days | DNF | days -[4/4](CalcGenus/adjacency_lists/5-5-cage4.txt) | 5 | 5 | 30 | 75 | 96 | [9, 14] | days | DNF | days -[1/1](CalcGenus/adjacency_lists/5-6-cage.txt) | 5 | 6 | 42 | 105 | 241920 | [15, 17] | days | DNF | days -[1/1](CalcGenus/adjacency_lists/5-8-cage.txt) | 5 | 8 | 170 | 425 | 3916800 | [76, 126] | DNF | DNF | too big for bit operations -[1/?](CalcGenus/adjacency_lists/5-12-cage1.txt) | 5 | 12 | 2730 | 6825 | 503193600 |[1480, 2048]| OOM | DNF | too big for bit operations -[1/1](CalcGenus/adjacency_lists/6-5-cage.txt) | 6 | 5 | 40 | 120 | 480 | [17, 22] | days | DNF | days -[1/1](CalcGenus/adjacency_lists/6-6-cage.txt) | 6 | 6 | 62 | 186 | 744000 | [32, 60] | DNF | DNF | DNF -[1/1](CalcGenus/adjacency_lists/6-8-cage.txt) | 6 | 8 | 312 | 936 | 9360000 | [196, 310] | DNF | DNF | too big for bit operations -[1/?](CalcGenus/adjacency_lists/6-12-cage1.txt) | 6 | 12 | 7812 | 23436 | 5859000000 |[5860, 7810]| OOM | DNF | too big for bit operations -[1/1](CalcGenus/adjacency_lists/7-5-cage.txt) | 7 | 5 | 50 | 175 | 252000 | [29, 39] | DNF | DNF | DNF -[1/1](CalcGenus/adjacency_lists/7-6-cage.txt) | 7 | 6 | 90 | 315 | 15120 | [61, 110] | DNF | DNF | DNF - -The genus for various complete graphs generated using the `CompleteGraph` function in SageMath follows. -\# | k | g | v | e | \|G\| | genus | time (s) | SM time (s) | MG time (s) ----------------------------------------- | --- | --- | ---- | ----- | ------------------ | -------- | -------- | ----------- | ----------- -[k2](CalcGenus/adjacency_lists/k2.txt) | 1 | Inf | 2 | 1 | 2 | 0 | --- | 0.004 | --- -[k3](CalcGenus/adjacency_lists/k3.txt) | 2 | 3 | 3 | 3 | 6 | 0 | 0.005 | 0.004 | 0.008 -[k4](CalcGenus/adjacency_lists/k4.txt) | 3 | 3 | 4 | 6 | 24 | 0 | 0.005 | 0.003 | 0.008 -[k5](CalcGenus/adjacency_lists/k5.txt) | 4 | 3 | 5 | 10 | 120 | 1 | 0.005 | 0.005 | 0.008 -[k6](CalcGenus/adjacency_lists/k6.txt) | 5 | 3 | 6 | 15 | 720 | 1 | 0.005 | 0.023 | 0.008 -[k7](CalcGenus/adjacency_lists/k7.txt) | 6 | 3 | 7 | 21 | 5040 | 1 | 0.005 | days | 0.009 -[k8](CalcGenus/adjacency_lists/k8.txt) | 7 | 3 | 8 | 28 | 40320 | 2 | 0.008 | DNF | 0.008 -[k9](CalcGenus/adjacency_lists/k9.txt) | 8 | 3 | 9 | 36 | 362880 | 3 | 0.008 | DNF | 0.008 - -The genus for various complete bipartite graphs generated using the `CompleteBipartiteGraph` function in SageMath follows. Number (\# links to adjacency list), valency (k), girth (g), vertices (v), edges (e), size of the automorphism group (\|G\|), genus, computation time for the genus (time), and computation time for the genus using SageMath (SM time). -\# | k | g | v | e | \|G\| | genus | time (s) | SM time (s) | MG time (s) ------------------------------------------- | --- | --- | ---- | ----- | ------------ | -------- | -------- | ----------- | ----------- -[k3-3](CalcGenus/adjacency_lists/k3-3.txt) | 3 | 4 | 6 | 9 | 72 | 1 | 0.005 | 0.047 | 0.006 -[k4-4](CalcGenus/adjacency_lists/k4-4.txt) | 4 | 4 | 8 | 16 | 1152 | 1 | 0.005 | 0.010 | 0.010 -[k5-5](CalcGenus/adjacency_lists/k5-5.txt) | 5 | 4 | 10 | 25 | 28800 | 3 | 0.014 | DNF | 0.008 -[k6-6](CalcGenus/adjacency_lists/k6-6.txt) | 6 | 4 | 12 | 36 | 1036800 | 4 | 0.005 | DNF | 0.009 - -The genus for various complete n-partite graphs generated using the `CompleteMultipartiteGraph` function in SageMath follows. -\# | v | e | genus | time (s) | MG time (s) --------------------------------------------------------------------------------- | ---- | ----- | -------- | -------- | ----------- -[k2-2](CalcGenus/adjacency_lists/k2-2.txt) | 4 | 4 | 0 | 0.005 | 0.008 -[k2-2-2](CalcGenus/adjacency_lists/k2-2-2.txt) | 6 | 12 | 0 | 0.005 | 0.009 -[k2-2-2-2](CalcGenus/adjacency_lists/k2-2-2-2.txt) | 8 | 24 | 1 | 0.005 | 0.009 -[k2-2-2-2-2](CalcGenus/adjacency_lists/k2-2-2-2-2.txt) | 10 | 40 | 3 | 0.009 | 0.009 - -The genus for various Johnson graphs generated using Mathematica follows. -\# | v | e | genus | time (s) | MG time (s) --------------------------------------------------------------------------------- | ---- | ----- | ---------- | -------- | ----------- -[Johnson (5, 2)](CalcGenus/adjacency_lists/Johnson5-2.txt) | 10 | 30 | 2 | 0.006 | 0.009 -[Johnson (6, 2)](CalcGenus/adjacency_lists/Johnson6-2.txt) | 15 | 60 | [4, 5] | hours | hours -[Johnson (6, 3)](CalcGenus/adjacency_lists/Johnson6-3.txt) | 20 | 90 | [7, 9] | hours | hours -[Johnson (8, 4)](CalcGenus/adjacency_lists/Johnson8-4.txt) | 70 | 560 | [60,238] | days | too big for bit operations -[Johnson (9, 4)](CalcGenus/adjacency_lists/Johnson9-4.txt) | 70 | 560 | [148,558] | days | too big for bit operations - -The genus for various Circulant graphs generated using Mathematica follows. -\# | v | e | genus | time (s) | MG time (s) -----------------------------------------------------------------------| ---- | ----- | -------- | -------- | ----------- -[C10_1,2,5](CalcGenus/adjacency_lists/Circulant10_1-2-5.txt) | 10 | 25 | 1 | 0.006 | 0.007 -[C10_1,2,4,5](CalcGenus/adjacency_lists/Circulant10_1-2-4-5.txt) | 10 | 35 | 3 | 0.976 | 0.023 -[C14_1,2,3,6](CalcGenus/adjacency_lists/Circulant14_1-2-3-6.txt) | 14 | 48 | 4 | hours | 0.896 -[C15_1,5](CalcGenus/adjacency_lists/Circulant15_1-5.txt) | 15 | 30 | 1 | hours | 0.006 -[C16_1,7](CalcGenus/adjacency_lists/Circulant16_1-7.txt) | 16 | 32 | 1 | 0.005 | 0.014 -[C18_1,3,9](CalcGenus/adjacency_lists/Circulant18_1-3-9.txt) | 18 | 45 | 4 | hours | 0.021 -[C20_1,3,5](CalcGenus/adjacency_lists/Circulant20_1-3-5.txt) | 20 | 60 | 6 | 0.317 | 13.698 -[C20_1,6,9](CalcGenus/adjacency_lists/Circulant20_1-6-9.txt) | 20 | 60 | 6 | 0.022 | 20.637 -[C21_1,4,5](CalcGenus/adjacency_lists/Circulant21_1-4-5.txt) | 21 | 63 | 1 | 0.005 | 0.008 -[C26_1,3,9](CalcGenus/adjacency_lists/Circulant26_1-3-9.txt) | 26 | 78 | [8, 27] | hours | hours -[C30_1,9,11](CalcGenus/adjacency_lists/Circulant30_1-9-11.txt) | 30 | 90 | [9, 31] | hours | hours -[C30_1,4,11,14](CalcGenus/adjacency_lists/Circulant30_1-4-11-14.txt) | 30 | 120 | [16, 20] | hours | hours -[C31_1,5,6](CalcGenus/adjacency_lists/Circulant31_1-5-6.txt) | 31 | 93 | 1 | 0.005 | 0.006 -[C20_*](CalcGenus/adjacency_lists/Circulant20_1-3-5-7-9-10.txt) | 20 | 110 | [10, 17] | hours | hours - -The genus for various Cyclotomic graphs generated using Mathematica follows. -\# | v | e | genus | time (s) | MG time (s) -----------------------------------------------------------------------| ---- | ----- | -------- | -------- | ----------- -[16](CalcGenus/adjacency_lists/Cyclotomic16.txt) | 16 | 40 | 4 | 0.085 | 0.042 -[19](CalcGenus/adjacency_lists/Cyclotomic19.txt) | 19 | 57 | 1 | 0.005 | 0.010 -[31](CalcGenus/adjacency_lists/Cyclotomic31.txt) | 31 | 155 | [12,58] | hours | hours -[61](CalcGenus/adjacency_lists/Cyclotomic61.txt) | 61 | 610 | [73,265] | days | too big for bit operations -[67](CalcGenus/adjacency_lists/Cyclotomic67.txt) | 67 | 737 | [91,325] | days | too big for bit operations - -The genus for various DifferenceSetIncidence graphs generated using Mathematica follows. -\# | v | e | genus | time (s) | MG time (s) --------------------------------------------------------------------------------- | ---- | ----- | -------- | -------- | ----------- -[11,5,2](CalcGenus/adjacency_lists/DifferenceSetIncidence11-5-2.txt) | 22 | 55 | 5 | hours | 1.770 -[40,13,4](CalcGenus/adjacency_lists/DifferenceSetIncidence40-13-4.txt) | 80 | 520 | [91,214] | hours | too big for bit operations - -The genus for various Bipartite Kneser graphs generated using Mathematica follows. -\# | v | e | genus | time (s) | MG time (s) --------------------------------------------------------------------------------- | ---- | ----- | --------- | -------------------------------- | ----------- -[Bipartite Kneser (6, 2)](CalcGenus/adjacency_lists/bipartite-kneser6-2.txt) | 30 | 90 | [9,28] | days | days -[Bipartite Kneser (7, 2)](CalcGenus/adjacency_lists/bipartite-kneser7-2.txt) | 42 | 210 | [33,80] | days | days -[Bipartite Kneser (8, 2)](CalcGenus/adjacency_lists/bipartite-kneser8-2.txt) | 56 | 420 | [78,175] | days | days -[Bipartite Kneser (8, 3)](CalcGenus/adjacency_lists/bipartite-kneser8-3.txt) | 112 | 560 | [85,143] | days | too big for bit operations -[Bipartite Kneser (9, 2)](CalcGenus/adjacency_lists/bipartite-kneser9-2.txt) | 72 | 756 | [154,332] | days | too big for bit operations -[Bipartite Kneser (9, 3)](CalcGenus/adjacency_lists/bipartite-kneser9-3.txt) | 168 | 1680 | [337,338] | days | too big for bit operations -[Bipartite Kneser (10, 2)](CalcGenus/adjacency_lists/bipartite-kneser10-2.txt) | 90 | 1260 | [271,572] | days | too big for bit operations -[Bipartite Kneser (10, 3)](CalcGenus/adjacency_lists/bipartite-kneser10-3.txt) | 240 | 4200 | [931,1963]| days | too big for bit operations -[Bipartite Kneser (10, 4)](CalcGenus/adjacency_lists/bipartite-kneser10-4.txt) | 420 | 3150 | [579,1358]| days | too big for bit operations -[Bipartite Kneser (11, 2)](CalcGenus/adjacency_lists/bipartite-kneser11-2.txt) | 110 | 1980 | [441,918] | days | too big for bit operations -[Bipartite Kneser (11, 3)](CalcGenus/adjacency_lists/bipartite-kneser11-3.txt) | 330 | 9240 |[2146,4428]| days | too big for bit operations -[Bipartite Kneser (11, 4)](CalcGenus/adjacency_lists/bipartite-kneser11-4.txt) | 660 | 11550 |[2558,5428]| days | too big for bit operations -[Bipartite Kneser (12, 2)](CalcGenus/adjacency_lists/bipartite-kneser12-2.txt) | 132 | 2970 | [677,1397]| days | too big for bit operations -[Bipartite Kneser (12, 3)](CalcGenus/adjacency_lists/bipartite-kneser12-3.txt) | 440 | 18480 |[4401,8979]| days | too big for bit operations -[Bipartite Kneser (12, 4)](CalcGenus/adjacency_lists/bipartite-kneser12-4.txt) | 990 | 34650 | ? | adjacency list too large to load | too big for bit operations - -The genus for various miscellaneous graphs generated using Mathematica follows. -\# | v | e | genus | time (s) | MG time (s) --------------------------------------------------------------------------------- | ---- | ----- | -------- | -------- | ----------- -[Klein Bottle](CalcGenus/adjacency_lists/KleinBottleTriangulation9-1.txt) | 9 | 27 | 2 | 0.007 | 0.006 -[TRC](CalcGenus/adjacency_lists/TriangleReplacedCoxeterGraph.txt) | 84 | 126 | 3 | hours | 0.006 -[Fan (3, 6)](CalcGenus/adjacency_lists/Fan3-6.txt) | 9 | 23 | 1 | 0.005 | 0.006 -[Co-Herschel](CalcGenus/adjacency_lists/coHerschel.txt) | 11 | 37 | 2 | 0.012 | 0.006 +To run the C program for any graph, `cd PAGE` and run `S="0" DEG="3" ADJ="adjacency_lists/3-8-cage.txt" make run`. This will compile the C program and run it. The output will be in `page.out`. The format of the adjacency lists is the number of vertices and number of edges on the first line followed by the neighbors of each vertex on the following lines. See the examples in `PAGE/adjacency_lists/`. Use `MallocStackLogging=1 S="0" DEG="3" ADJ="adjacency_lists/3-8-cage.txt" leaks -quiet -atExit -- ./page` to check for memory leaks on macOS. Use `S=0 DEG=7 ADJ="adjacency_lists/coHerschel.txt" lldb --file ./page` and type `r` then `bt` to debug segmentation faults. If you're on Windows, you'll probably have an easier time if you use [WSL](https://learn.microsoft.com/en-us/windows/wsl/install) or [MSYS](https://www.msys2.org/). ## Acknowledgements [Austin](https://austinulrigg.github.io/) did the main work in deciphering the math and checking the solutions manually. He also contributed intellectually to the ideas behind the algorithm. -The CalcCycles programs were written by [Sam King](https://www.linkedin.com/in/samkingwa/) and used to check the results of the algorithm for the Balaban 10 Cage. - -Credit to the rest of the recreational math group at the University of Washington for input on the programs/math and for providing computational resources for experimentation. - Thanks to [Professor Steinerberger](https://faculty.washington.edu/steinerb/) for guidance on the project, and thanks to [Professor Brinkmann](https://scholar.google.be/citations?user=yaEBOB4AAAAJ&hl=nl) for providing a fast SoTA algorithm `multi_genus` to compare against and recommendations for visualizing results. -## References -- Adjacency Lists - - [Win.tue.nl](https://www.win.tue.nl/~aeb/graphs/cages/cages.html) - - [SageMath Generators](https://doc.sagemath.org/html/en/reference/graphs/sage/graphs/graph_generators.html) - - [Mathematica](https://www.wolfram.com/mathematica/) - - [ROME and other practical graph datasets](http://graphdrawing.org/data.html) - -- Genus problem is NP-Hard - - [The graph genus problem is NP-complete](https://www.sciencedirect.com/science/article/abs/pii/0196677489900060?via%3Dihub) - - The general problem of determining the genus of a graph is NP-hard - - [Triangulating a Surface with a Prescribed Graph](https://www.sciencedirect.com/science/article/pii/S0095895683710166) - - Determining the non-orientable genus of a graph is NP-hard - -- Background Information - - [Rotation Systems](https://sites.math.washington.edu/~morrow/papers/tom-thesis.pdf) - - [Pearls in Graph Theory - A Comprehensive Introduction - By Nora Hartsfield and Gerhard Ringel](https://proofits.wordpress.com/wp-content/uploads/2012/09/nora_hartsfield_gerhard_ringel_pearls_in_graph.pdf) (particularly Chapter 10) - - [Topological Graph Theory - A Survey](http://www.math.u-szeged.hu/~hajnal/courses/PhD_Specialis/Archdeacon.pdf) - -- Existing Graph Embedding Algorithms - - Planarity Testing (genus = 0) - - [Efficient Planarity Testing](https://dl.acm.org/doi/10.1145/321850.321852) - - O(V) linear time, successfully implemented in ALGOL and can handle 900+ vertices in less than 12 seconds on 1974 hardware - - [An Implementation of the Hopcroft and Tarjan Planarity Test and Embedding Algorithm](https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=6a2fa11f47e315f108698feaabb287ab9751b921) - - Lists flaws and corrections to the original algorithm needed to actually implement it - - [Testing for the consecutive ones property, interval graphs, and graph planarity using PQ-tree algorithms](https://www.sciencedirect.com/science/article/pii/S0022000076800451) - - Also linear but introduces a cool datastructure called a PQ-tree that is good for handling permutations - - [Depth-First Search and Planarity](https://arxiv.org/pdf/math/0610935) - - Linear time, good explanation - - [A Simple Test for Planar Graphs](https://iasl.iis.sinica.edu.tw/webpdf/paper-1993-A_simple_test_for_planar_graphs.pdf) - - O(V + E), good diagrams/explanation - - [Depth-First Search and Kuratowski Subgraphs](https://dl.acm.org/doi/10.1145/1634.322451) - - Extracts the Kuratowski subgraph in O(V) linear time - - [Graphes Planaires: Reconnaissance et Construction de Representations Planaires Topologiques](https://www.mathe2.uni-bayreuth.de/EWS/demoucron.pdf) - - O(V^2) quadratic time but simple and practical to implement - - Torus Embedding (genus = 1) - - [Embedding graphs in the torus in linear time](https://link.springer.com/chapter/10.1007/3-540-59408-6_64) - - Linear time but near impossible to implement - - Has complicated substeps that require entire papers to prove: [Obstructions for simple embeddings](https://www.sfu.ca/~mohar/Papers/Corner.pdf) - - [An algorithm for embedding graphs in the torus](https://www.sfu.ca/~mohar/Papers/Torus.pdf) - - Cubic time but hard to implement - - [A Practical Algorithm for Embedding Graphs on Torus](http://www.ijnc.org/index.php/ijnc/article/view/122/124) - - Exponential but has actually been implemented - - [Practical Toroidality Testing](https://dl.acm.org/doi/pdf/10.5555/314161.314392) - - Exponential but has actually been implemented in C and C++ - - Scales ok up to 10 vertices (11 with up to 24 edges) - - Used to find a set of 2K forbidden minors for the torus (biggest at the time of publication) - - [A large set of torus obstructions and how they were discovered](https://www.combinatorics.org/ojs/index.php/eljc/article/download/v25i1p16/pdf) - - Exponential but actually implemented in C. The best practical algorithm for torus embedding so far - - Projective Plane Embedding (genus = 1, non-orientable) - - [Projective Planarity in Linear Time](https://www.sciencedirect.com/science/article/abs/pii/S0196677483710503) - - Linear time but hard to implement - - [Simpler Projective Plane Embedding](https://www.sciencedirect.com/science/article/abs/pii/S1571065305801751) - - O(n^2) but much easier to implement - - Flawed Algorithms - - [Errors in graph embedding algorithms](https://www.sciencedirect.com/science/article/pii/S0022000010000863?ref=pdf_download&fr=RR-2&rr=8ae048cc8db8c71d) - - Explains errors in many existing algorithms and how fixing them would make them exponential time - - Only currently practical algorithms are exponential time - - Less Efficient Algorithms for Arbitrary Surfaces/Genus - - [SageMath](https://github.com/sagemath/sage/blob/develop/src/sage/graphs/genus.pyx) - - Johnson Trotter to check all rotation systems (exhaustive search with a few optimizations) - - O(V \prod_{v \in V(G)} (deg(v)-1)!) - - SAT/ILP - - [A Practical Method for the Minimum Genus of a Graph: Models and Experiments](https://tcs.informatik.uos.de/_media/pubs/sea16_preprint_mingenus.pdf) - - First SAT and ILP implementation - - Cannot handle genus > 1 - - [Stronger ILPs for the Graph Genus Problem](https://drops.dagstuhl.de/storage/00lipics/lipics-vol144-esa2019/LIPIcs.ESA.2019.30/LIPIcs.ESA.2019.30.pdf) - - Solves most of ROME and NORTH graph datasets - - 42 hours for the Gray graph (genus 7) - - Similar Efficiency with Different Trade-Offs - - [A Practical Algorithm for the Computation of the Genus](https://www.researchgate.net/publication/361684162_A_practical_algorithm_for_the_computation_of_the_genus) - - Scales worse with Genus but better with Vertices - - Theoretically more efficient but Nearly Impossible to Implement - - [A Linear Time Algorithm for Embedding Graphs in an Arbitrary Surface](https://www.sfu.ca/~mohar/Papers/General.pdf) - - Linear for fixed genus - - Has not been implemented correctly in multiple decades - - [A Simpler Linear Time Algorithm for Embedding Graphs into an Arbitrary Surface and the Genus of Graphs of Bounded Tree-Width](https://www.researchgate.net/publication/221499244_A_Simpler_Linear_Time_Algorithm_for_Embedding_Graphs_into_an_Arbitrary_Surface_and_the_Genus_of_Graphs_of_Bounded_Tree-Width) - - Linear for bounded tree-width - - Simpler than the general for fixed genus - - Has not been implemented correctly in multiple decades - - [Graph Minors .XIII. The Disjoint Paths Problem](https://www.sciencedirect.com/science/article/pii/S0095895685710064) - - Cubic time for fixed genus since checking if one of finitely many obstructions is a minor is cubic time - - The complete lists of forbidden minors is only known for the plane (genus 0) and projective plane (non-orientable genus 1) - -- Obstructions and Forbiddden Minors - - [Graph Minor Theorem](https://en.wikipedia.org/wiki/Robertson%E2%80%93Seymour_theorem) - - The minors can be used to determine if a graph contains an obstruction - - [Kuratowski's theorem](https://onlinelibrary.wiley.com/doi/10.1002/jgt.3190050304) - - 3 short proofs of Kuratowski's theorem - - A graph is planar if and only if it has no subdivision of K5 or K3,3 - - [Graph minors. VIII. A kuratowski theorem for general surfaces](https://www.sciencedirect.com/science/article/pii/009589569090121F) - - Every surface has a finite list of forbidden minors - - A graph is embeddable in the surface if and only if it has none of these minors - - [A Kuatowsky Theorem for the Projective Plane](https://onlinelibrary.wiley.com/doi/10.1002/jgt.3190050305) and [103 Graphs that are irreducible for the projective plan](https://www.sciencedirect.com/science/article/pii/0095895679900224) - - The complete list of 103 forbidden minors for the projective plane - - A graph is embeddable in the projective plane if and only if it has none of these minors - - [A Kuratowski theorem for nonorientable surfaces](https://www.sciencedirect.com/science/article/pii/0095895689900439) - - Even nonorientable surfaces have a finite list of forbidden minors - - A graph is embeddable in the nonorientable surface if and only if it has none of these minors - - [Hunting for torus obstructions](https://dspace.library.uvic.ca/items/760d538c-023d-45ff-8d85-57fabd1cd858) - - Largest set at the time ~16K minor order obstructions - - Split delete method to non-exhaustively search for obstructions - - [A large set of torus obstructions and how they were discovered](https://www.combinatorics.org/ojs/index.php/eljc/article/download/v25i1p16/pdf) - - Exponential but simple torus embedding algorithm based on DMP quardratic time planarity testing algorithm - - Growing database of torus obstructions: https://webhome.cs.uvic.ca/~wendym/torus/torus_obstructions.html - - 250,815 torus obstructions, 17,523 of which are minors - - Possibly complete set for all 3 regular graphs, but likely not complete for all graphs - - Overview of current progress (split delete, only 11 obstructions that don't have K3,3 as a subgraph) - - [On Computing Graph Minor Obstruction Sets](https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=7ed5e446f2a1b487a7d9a28fddb83de8772c2402) - - Stopping time of an obstruction algorithm is nonconstructive and other theoretical results - -- Cycle Finding Algorithms - - [Finding All the Elementary Circuits of a Directed Graph](https://www.cs.tufts.edu/comp/150GA/homeworks/hw1/Johnson%2075.PDF) - - O((c + 1)(V + E)) = O(cV + cE) time to find all c elementary cycles of a graph - - [A new way to enumerate cycles in graph](https://ieeexplore.ieee.org/document/1602189) - -- Visualization of Embedding - - [Non-Euclidean Spring Embedders](https://www2.cs.arizona.edu/~kobourov/riemann_embedders.pdf) +## Citation +If you use the PAGE algorithm or other code/visualizations from this repository, please cite: +```bibtex +@article{Metzger_2026, + title={An efficient genus algorithm based on graph rotations}, + volume={349}, + ISSN={0012-365X}, + url={http://doi.org/10.1016/j.disc.2026.115308}, + DOI={10.1016/j.disc.2026.115308}, + number={12}, + journal={Discrete Mathematics}, + publisher={Elsevier BV}, + author={Metzger, Alexander and Ulrigg, Austin}, + year={2026}, + month=Dec, pages={115308} +} +``` +You may also want to check out [the literature](docs/references.md) this work is based on. diff --git a/ReverseCycle/ReverseCycle.java b/ReverseCycle/ReverseCycle.java deleted file mode 100644 index ba26dad..0000000 --- a/ReverseCycle/ReverseCycle.java +++ /dev/null @@ -1,101 +0,0 @@ -package ReverseCycle; - -import java.io.File; -import java.io.FileNotFoundException; -import java.util.ArrayList; -import java.util.LinkedHashSet; -import java.util.List; -import java.util.Scanner; -import java.util.Set; -import java.io.PrintWriter; - -/** - * ReverseCycle - */ -public class ReverseCycle { - private static final String FILENAME = "output1.txt"; // change this to the input with cycles - private static final String OUTPUT_FILENAME = "adjacencylist.txt"; // change this to the output file - private static final int STARTS_AT = 0; // change this if the vertices start at a different number - - private static final int NUM_VERTICES = 70; // this is fixed - - public static void main(String[] args) { - List> adjacencyList = new ArrayList<>(NUM_VERTICES); - for (int i = 0; i < NUM_VERTICES; i++) { - adjacencyList.add(new LinkedHashSet<>()); - } - - File file = new File(FILENAME); - try { - Scanner scanner = new Scanner(file); - - // first line has the number of cycles as the first integer - String line = scanner.nextLine(); - int cycles = Integer.parseInt(line.split(" ")[0]); - System.out.println("Number of cycles: " + cycles); - - for (int cycle = 0; cycle < cycles; cycle++) { - // first line is just the cycle number - scanner.nextLine(); - - // read the number of elements in the cycle - line = scanner.nextLine(); - int n = Integer.parseInt(line.split(": ")[1]); - System.out.println("Number of elements in cycle " + (cycle + 1) + ": " + n); - - // read the cycle - int[][] cycleEdges = new int[n][2]; - for (int i = 0; i < n; i++) { - line = scanner.nextLine(); - String[] vertices = line.split(", "); - cycleEdges[i][0] = Integer.parseInt(vertices[0]) + 1 - STARTS_AT; - cycleEdges[i][1] = Integer.parseInt(vertices[1]) + 1 - STARTS_AT; - } - int u = cycleEdges[n - 1][0]; - int v = cycleEdges[n - 1][1]; - adjacencyList.get(v - 1).add(u); - for (int i = 0; i < n; i++) { - u = cycleEdges[i][0]; - v = cycleEdges[i][1]; - adjacencyList.get(u - 1).add(v); - adjacencyList.get(v - 1).add(u); - } - - // skip 2 blank lines - if (scanner.hasNextLine()) scanner.nextLine(); - if (scanner.hasNextLine()) scanner.nextLine(); - } - - scanner.close(); - } catch (FileNotFoundException e) { - System.err.println("Could not find file " + FILENAME); - } - - // print the adjacency list - for (int i = 0; i < NUM_VERTICES; i++) { - List row = new ArrayList<>(adjacencyList.get(i)); - for (int j = 0; j < adjacencyList.get(i).size(); j++) { - System.out.print(row.get(j) - 1 + STARTS_AT + " "); - } - System.out.println(); - } - - // save the adjacency list to a file - try { - File output = new File(OUTPUT_FILENAME); - PrintWriter writer = new PrintWriter(output); - - for (int i = 0; i < NUM_VERTICES; i++) { - List row = new ArrayList<>(adjacencyList.get(i)); - for (int j = 0; j < adjacencyList.get(i).size(); j++) { - writer.print(row.get(j) - 1 + STARTS_AT + " "); - } - writer.println(); - } - - writer.close(); - } catch (FileNotFoundException e) { - System.err.println("Could not write to file " + OUTPUT_FILENAME); - } - } -} diff --git a/ReverseCycle/adjacencylist.txt b/ReverseCycle/adjacencylist.txt deleted file mode 100644 index fa49214..0000000 --- a/ReverseCycle/adjacencylist.txt +++ /dev/null @@ -1,70 +0,0 @@ -61 69 1 -0 2 46 -3 53 1 -4 2 32 -17 3 5 -40 4 6 -7 5 63 -48 6 8 -9 7 27 -34 10 8 -9 19 11 -52 10 12 -41 13 11 -12 14 30 -47 15 13 -14 36 -25 17 -16 4 18 -19 57 17 -10 18 20 -19 21 45 -20 38 22 -23 21 -62 22 24 -51 25 23 -24 16 26 -27 25 -8 26 28 -29 69 27 -30 28 56 -31 29 13 -32 30 -3 31 33 -66 32 34 -35 9 33 -60 34 36 -37 35 15 -38 36 54 -39 37 21 -68 38 40 -39 5 41 -40 12 42 -41 43 -42 44 -43 45 -44 20 46 -1 47 45 -46 14 48 -47 7 49 -48 50 -49 51 -52 24 50 -53 51 11 -2 52 54 -37 53 55 -54 56 -55 29 -18 58 -57 59 -58 60 -59 35 61 -60 0 62 -61 23 63 -6 64 62 -63 65 -64 66 -65 33 67 -66 68 -69 39 67 -0 68 28 diff --git a/ReverseCycle/output1.txt b/ReverseCycle/output1.txt deleted file mode 100644 index e6cf463..0000000 --- a/ReverseCycle/output1.txt +++ /dev/null @@ -1,196 +0,0 @@ -14 Cycles -Cycle 1: -Length: 10 -9, 10 -10, 19 -19, 18 -18, 57 -57, 58 -58, 59 -59, 60 -60, 35 -35, 34 -34, 9 - - -Cycle 2: -Length: 10 -0, 69 -69, 68 -68, 39 -39, 38 -38, 37 -37, 36 -36, 35 -35, 60 -60, 61 -61, 0 - - -Cycle 3: -Length: 10 -2, 53 -53, 52 -52, 51 -51, 24 -24, 25 -25, 16 -16, 17 -17, 4 -4, 3 -3, 2 - - -Cycle 4: -Length: 10 -0, 1 -1, 2 -2, 3 -3, 32 -32, 31 -31, 30 -30, 29 -29, 28 -28, 69 -69, 0 - - -Cycle 5: -Length: 10 -4, 17 -17, 18 -18, 19 -19, 20 -20, 21 -21, 38 -38, 39 -39, 40 -40, 5 -5, 4 - - -Cycle 6: -Length: 10 -1, 46 -46, 47 -47, 14 -14, 15 -15, 36 -36, 37 -37, 54 -54, 53 -53, 2 -2, 1 - - -Cycle 7: -Length: 10 -5, 40 -40, 41 -41, 12 -12, 13 -13, 14 -14, 47 -47, 48 -48, 7 -7, 6 -6, 5 - - -Cycle 8: -Length: 10 -7, 48 -48, 49 -49, 50 -50, 51 -51, 52 -52, 11 -11, 10 -10, 9 -9, 8 -8, 7 - - -Cycle 9: -Length: 10 -11, 52 -52, 53 -53, 54 -54, 55 -55, 56 -56, 29 -29, 30 -30, 13 -13, 12 -12, 11 - - -Cycle 10: -Length: 10 -10, 11 -11, 12 -12, 41 -41, 42 -42, 43 -43, 44 -44, 45 -45, 20 -20, 19 -19, 10 - - -Cycle 11: -Length: 10 -0, 61 -61, 62 -62, 23 -23, 22 -22, 21 -21, 20 -20, 45 -45, 46 -46, 1 -1, 0 - - -Cycle 12: -Length: 10 -3, 4 -4, 5 -5, 6 -6, 63 -63, 64 -64, 65 -65, 66 -66, 33 -33, 32 -32, 3 - - -Cycle 13: -Length: 10 -6, 7 -7, 8 -8, 27 -27, 26 -26, 25 -25, 24 -24, 23 -23, 62 -62, 63 -63, 6 - - -Cycle 14: -Length: 10 -8, 9 -9, 34 -34, 33 -33, 66 -66, 67 -67, 68 -68, 69 -69, 28 -28, 27 -27, 8 - diff --git a/Visualize/.gitignore b/Visualize/.gitignore deleted file mode 100644 index 4668e94..0000000 --- a/Visualize/.gitignore 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red](C,B)(A) -\tkzDefPoint(-57.17815,-82.04060){A} -\tkzDefPoint(-82.04060,-57.17815){B} -\tkzDefPoint(0.0,0.0){C} -\tkzDrawArc[->,line width=0.9mm, blue](C,B)(A) -\node [black,circle,draw,fill=white,scale=0.49,line width=1mm] (32) at (-19.50903,-98.07853) {}; -\node [black,circle,draw,fill=white,scale=0.49,line width=1mm] (66) at (-83.14696,-55.55702) {}; -\node [black,circle,draw,fill=white,scale=0.49,line width=1mm] (67) at (98.07853,19.50903) {}; -\node [black,circle,draw,fill=white,scale=0.49,line width=1mm] (68) at (-83.14696,55.55702) {}; -\node [black,circle,draw,fill=white,scale=0.49,line width=1mm] (69) at (-55.55702,83.14696) {}; -\node [black,circle,draw,fill=white,scale=0.49,line width=1mm] (70) at (83.14696,55.55702) {}; -\node [black,circle,draw,fill=white,scale=0.49,line width=1mm] (71) at (55.55702,-83.14696) {}; -\node [black,circle,draw,fill=white,scale=0.49,line width=1mm] (72) at (-19.50903,98.07853) {}; -\node [black,circle,draw,fill=white,scale=0.49,line 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deleted file mode 100644 index 4574a6d..0000000 Binary files a/Visualize/k3-3.synctex.gz and /dev/null differ diff --git a/Visualize/k3-3.tex b/Visualize/k3-3.tex deleted file mode 100644 index 762e154..0000000 --- a/Visualize/k3-3.tex +++ /dev/null @@ -1,63 +0,0 @@ -\documentclass{article} -\usepackage{tikz} -\usepackage{tkz-euclide} -\addtolength{\textwidth}{3cm} -\addtolength{\oddsidemargin}{-1.5cm} -\addtolength{\evensidemargin}{-1.5cm} -\begin{document} -\begin{center} -\begin{tikzpicture}[scale=0.065] -\def\vertexscale{1.00} -\def\labelscale{1.00} -\node [circle,black,draw,scale=\vertexscale] (1) at (17.61547,17.61547) {1}; -\node [circle,black,draw,scale=\vertexscale] (2) at (-50.93993,5.15207) {2}; -\node [circle,black,draw,scale=\vertexscale] (3) at (5.15207,-50.93993) {3}; -\node [circle,black,draw,scale=\vertexscale] (4) at (50.93993,-5.15207) {4}; -\node [circle,black,draw,scale=\vertexscale] (5) at (-5.15207,50.93993) {5}; -\node [circle,black,draw,scale=\vertexscale] (6) at (-17.61547,-17.61547) {6}; -\tkzDefPoint(-100.00000,-0.00000){7} -\tkzDefPoint(-70.71068,-70.71068){8} -\tkzDefPoint(0.00000,-100.00000){9} -\tkzDefPoint(100.00000,0.00000){10} -\tkzDefPoint(-0.00000,100.00000){11} -\tkzDefPoint(-70.71068,70.71068){12} -\tkzDefPoint(70.71068,70.71068){13} -\tkzDefPoint(70.71068,-70.71068){14} -\draw [black] (1) to (4); -\draw [black] (1) to (6); -\draw [black] (1) to (5); -\draw [black] (2) to (7); -\node [draw=none,fill=none,scale=\labelscale] () at (-105.00000,-0.00000) {4}; -\draw [black] (2) to (5); -\draw [black] (2) to (6); -\draw [black] (3) to (6); -\draw [black] (3) to (4); -\draw [black] (3) to (9); -\node [draw=none,fill=none,scale=\labelscale] () at (0.00000,-105.00000) {5}; -\draw [black] (4) to (10); -\node [draw=none,fill=none,scale=\labelscale] () at (105.00000,0.00000) {2}; -\draw [black] (5) to (11); -\node [draw=none,fill=none,scale=\labelscale] () at (-0.00000,105.00000) {3}; -\tkzDefPoint(-68.55786,72.79986){A} -\tkzDefPoint(68.55786,72.79986){B} -\tkzDefPoint(0.0,0.0){C} -\tkzDrawArc[<-,line width=0.9mm, red](C,B)(A) -\tkzDefPoint(72.79986,68.55786){A} -\tkzDefPoint(72.79986,-68.55786){B} -\tkzDefPoint(0.0,0.0){C} -\tkzDrawArc[<-,line width=0.9mm, blue](C,B)(A) -\tkzDefPoint(68.55786,-72.79986){A} -\tkzDefPoint(-68.55786,-72.79986){B} -\tkzDefPoint(0.0,0.0){C} -\tkzDrawArc[->,line width=0.9mm, red](C,B)(A) -\tkzDefPoint(-72.79986,-68.55786){A} -\tkzDefPoint(-72.79986,68.55786){B} -\tkzDefPoint(0.0,0.0){C} -\tkzDrawArc[->,line width=0.9mm, blue](C,B)(A) -\node [black,circle,draw,fill=white,scale=0.75,line width=1mm] (8) at (-70.71068,-70.71068) {}; -\node [black,circle,draw,fill=white,scale=0.75,line width=1mm] (12) at (-70.71068,70.71068) {}; -\node [black,circle,draw,fill=white,scale=0.75,line width=1mm] (13) at (70.71068,70.71068) {}; -\node [black,circle,draw,fill=white,scale=0.75,line width=1mm] (14) at (70.71068,-70.71068) {}; -\end{tikzpicture} -\end{center} -\end{document} diff --git a/Visualize/parse_tikz.py b/Visualize/parse_tikz.py deleted file mode 100644 index 0ea1d56..0000000 --- a/Visualize/parse_tikz.py +++ /dev/null @@ -1,290 +0,0 @@ -import sys -import re -import json -from math import dist as calculate_distance # Requires Python 3.8+ -from collections import defaultdict - -# Helper for distance calculation if using older Python -# def calculate_distance(p1, p2): -# return ((p1[0] - p2[0])**2 + (p1[1] - p2[1])**2)**0.5 - - -def parse_tikz_graph(tikz_content): - """ - Parses TikZ content generated by planar_cutthroughedges_draw.c. - - Args: - tikz_content: A string containing the TikZ code. - - Returns: - A dictionary containing nodes, edges, and boundary identification pairs, - or None if parsing fails. - """ - - nodes = ( - {} - ) # Stores {node_id_str: {"x": float, "y": float, "type": "original|boundary", "label": "str"}} - edges = [] # Stores {"u": node_id_str, "v": node_id_str} - boundary_segments = [] # Temp storage for parsed boundary arc info - temp_tkz_points = {} # Stores coords for A, B, C used by tkzDrawArc - - # --- Regex Patterns (Adjusted for the example format) --- - - # Matches \node [...] (id) at (x,y) {label}; or \node [...] (id) at (x,y) {}; - # Captures: style_content, node_id, x, y, label (optional) - node_pattern = re.compile( - r"\\node.*?\[(.*?)\]\s*\((\d+)\)\s*at\s*\(\s*([-\d.]+)\s*,\s*([-\d.]+)\s*\)\s*\{(.*?)\};" - ) - - # Matches \tkzDefPoint(x,y){id} - Captures x, y, node_id (A, B, C, or number) - tkzdefpoint_pattern = re.compile( - r"\\tkzDefPoint\(\s*([-\d.]+)\s*,\s*([-\d.]+)\s*\)\s*\{(\w+)\}" - ) - - # Matches \draw [black] (u) to (v); - Captures u, v - edge_pattern = re.compile(r"\\draw\s*\[black\]\s*\((\d+)\)\s*to\s*\((\d+)\);") - - # Matches \tkzDrawArc[style](Center,End)(Start) - Captures style, center_id, end_id, start_id - boundary_arc_pattern = re.compile( - r"\\tkzDrawArc\[(.*?)\]\s*\(\s*(\w+)\s*,\s*(\w+)\s*\)\s*\(\s*(\w+)\s*\)" - ) - - # Matches \node [draw=none,fill=none,scale=\labelscale] () at (x,y) {label}; - Captures x, y, label - boundary_label_pattern = re.compile( - r"\\node.*?\[draw=none,fill=none,scale=\\labelscale\]\s*\(\)\s*at\s*\(\s*([-\d.]+)\s*,\s*([-\d.]+)\s*\)\s*\{(\d+)\};" - ) - - # --- Parsing Logic --- - lines = tikz_content.splitlines() - - for line in lines: - line = line.strip() - if not line or line.startswith("%"): - continue - - # Match tkzDefPoint (stores A, B, C for arcs AND defines numbered boundary nodes) - tkz_match = tkzdefpoint_pattern.search(line) - if tkz_match: - x, y, point_id = tkz_match.groups() - coords = (float(x), float(y)) - temp_tkz_points[point_id] = coords - # If the ID is numeric, it's a boundary node definition - if point_id.isdigit(): - nodes[point_id] = { - "x": coords[0], - "y": coords[1], - "type": "boundary", - "label": point_id, # Label is the ID itself - } - continue # Process next line - - # Match \node [scale=\labelscale] (labels which vertex each connected boundary node stands for) - bnd_label_match = boundary_label_pattern.search(line) - if bnd_label_match: - x, y, label = bnd_label_match.groups() - coord = (float(x), float(y)) - boundary_node_ids = [ - nid for nid, data in nodes.items() if data["type"] == "boundary" - ] - bnd_id = min( - boundary_node_ids, - key=lambda nid: calculate_distance( - coord, (nodes[nid]["x"], nodes[nid]["y"]) - ), - ) - nodes[bnd_id]["for"] = label - - # Match \node (defines original nodes AND styles boundary nodes) - node_match = node_pattern.search(line) - if node_match: - style, node_id, x, y, label = node_match.groups() - node_type = "original" if label.strip() else "boundary_styled" - # Only add if not already defined by tkzDefPoint, or update type/label - if node_id not in nodes: - nodes[node_id] = { - "x": float(x), - "y": float(y), - "type": node_type, - "label": label.strip() or node_id, - } - elif node_type == "original": # Update if this is the main definition - nodes[node_id]["type"] = "original" - nodes[node_id]["label"] = label.strip() or node_id - # We prioritize tkzDefPoint for boundary node coordinates/ID. - continue - - # Match \draw [black] (original edges) - edge_match = edge_pattern.search(line) - if edge_match: - u, v = edge_match.groups() - # Ensure nodes exist before adding edge (might parse nodes after edges) - # If robustness needed, store edges and add after all nodes parsed. - if u in nodes and v in nodes: - edges.append({"u": u, "v": v}) - else: - print(f"Warning: Nodes for edge ({u},{v}) not defined yet.") - continue - - # Match \tkzDrawArc (boundary segments) - boundary_match = boundary_arc_pattern.search(line) - if boundary_match: - style, center_id, end_id, start_id = boundary_match.groups() - - # Extract color and direction - color_match = re.search( - r"\b(red|blue|green|orange|olive|gray|pink|yellow|lime|cyan)\b", style - ) - color = color_match.group(1) if color_match else None - arrow_match = re.search(r"(<-|->)", style) - direction = arrow_match.group(1) if arrow_match else None - - # Get endpoint coordinates from stored A, B points - start_coords = temp_tkz_points.get(start_id) - end_coords = temp_tkz_points.get(end_id) - - if not start_coords or not end_coords: - print( - f"Warning: Could not find coordinates for boundary arc points {start_id}/{end_id} in line: {line}" - ) - continue - - if not color or not direction: - print( - f"Warning: Could not parse color/direction for boundary arc: {line}" - ) - continue - - # Find the two *numbered boundary node IDs* closest to start_coords and end_coords - boundary_node_ids = [ - nid for nid, data in nodes.items() if data["type"] == "boundary" - ] - if not boundary_node_ids: - print( - f"Warning: No boundary nodes found to map arc endpoints for line: {line}" - ) - continue - - start_node_id = min( - boundary_node_ids, - key=lambda nid: calculate_distance( - start_coords, (nodes[nid]["x"], nodes[nid]["y"]) - ), - ) - end_node_id = min( - boundary_node_ids, - key=lambda nid: calculate_distance( - end_coords, (nodes[nid]["x"], nodes[nid]["y"]) - ), - ) - - boundary_segments.append( - { - "start_node": start_node_id, - "end_node": end_node_id, - "color": color, - "direction": direction, - "line": line, # Keep original line for debugging - } - ) - # Clear A, B, C points as they are usually redefined for the next arc - temp_tkz_points.pop("A", None) - temp_tkz_points.pop("B", None) - temp_tkz_points.pop("C", None) - continue - - # --- Post-processing: Identify Boundary Pairs --- - boundary_pairs_dict = defaultdict(lambda: {"->": None, "<-": None}) - unmatched_segments = [] - - for seg in boundary_segments: - key = seg["color"] # Group by color - direction = seg["direction"] - if ( - direction in boundary_pairs_dict[key] - and boundary_pairs_dict[key][direction] is None - ): - boundary_pairs_dict[key][direction] = seg - else: - # Handle cases where a color might have >2 segments or multiple of same direction - print( - f"Warning: Unexpected segment for color {key}, direction {direction}. Storing as unmatched: {seg['line']}" - ) - unmatched_segments.append(seg) - - final_boundary_pairs = [] - for color, pair in boundary_pairs_dict.items(): - seg1 = pair.get("->") - seg2 = pair.get("<-") - if seg1 and seg2: - # Store the pair of node segments that should be identified - # The exact order (u1,v1 vs v1,u1) matters for orientation - final_boundary_pairs.append( - { - "id": color, - "segment1": { - "u": seg1["start_node"], - "v": seg1["end_node"], - }, # Following -> direction - "segment2": { - "u": seg2["end_node"], - "v": seg2["start_node"], - }, # Following <- direction (reversed nodes) - } - ) - else: - print(f"Warning: Incomplete pair found for color {color}.") - if seg1: - unmatched_segments.append(seg1) - if seg2: - unmatched_segments.append(seg2) - - if unmatched_segments: - print("\nUnmatched boundary segments:") - for seg in unmatched_segments: - print(f" - {seg['line']}") - - # --- Final Output --- - if not nodes: - print("Warning: No nodes found in TikZ input.") - return None - - # Filter out temporary styled boundary nodes if needed - final_nodes = { - nid: data for nid, data in nodes.items() if data["type"] != "boundary_styled" - } - - return { - "nodes": final_nodes, - "edges": edges, - "boundary_pairs": final_boundary_pairs, - } - - -# --- Example Usage --- -if __name__ == "__main__": - tikz = sys.stdin.read() - - # For demonstration, parse the example string - parsed_data = parse_tikz_graph(tikz) - - if parsed_data: - print("\n--- Parsed TikZ Data ---") - print(json.dumps(parsed_data, indent=2)) - - # Example: Verify the extracted data - print( - f"\nNumber of original nodes found: {len([n for n, d in parsed_data['nodes'].items() if d['type'] == 'original'])}" - ) - print( - f"Number of boundary nodes found: {len([n for n, d in parsed_data['nodes'].items() if d['type'] == 'boundary'])}" - ) - print(f"Number of original edges found: {len(parsed_data['edges'])}") - print(f"Number of boundary pairs found: {len(parsed_data['boundary_pairs'])}") - if parsed_data["boundary_pairs"]: - print("Example Boundary Pair:") - print(f" ID: {parsed_data['boundary_pairs'][0]['id']}") - print(f" Segment 1: {parsed_data['boundary_pairs'][0]['segment1']}") - print(f" Segment 2: {parsed_data['boundary_pairs'][0]['segment2']}") - - else: - print("\nParsing Failed.") diff --git a/Visualize/plot_parsed_tikz.py b/Visualize/plot_parsed_tikz.py deleted file mode 100644 index 8babe65..0000000 --- a/Visualize/plot_parsed_tikz.py +++ /dev/null @@ -1,178 +0,0 @@ -import sys -from parse_tikz import parse_tikz_graph -from collections import defaultdict -import networkx as nx -import matplotlib.pyplot as plt - - -def plot_parsed_graph(parsed_data): - """ - Plots the parsed graph data using NetworkX and Matplotlib. - - Args: - parsed_data: The dictionary returned by parse_tikz_graph. - """ - if not parsed_data: - print("No data to plot.") - return - - G = nx.Graph() - pos = {} - node_colors = {} - node_types = {} - node_labels = {} - original_nodes = [] - boundary_nodes = [] - boundary_nodes_for = [] - - # Add nodes and prepare plotting data - for node_id, data in parsed_data["nodes"].items(): - G.add_node(node_id) - pos[node_id] = (data["x"], data["y"]) - if data["type"] == "original": - node_types[node_id] = "original" - node_labels[node_id] = data["label"] - node_colors[node_id] = "skyblue" - original_nodes.append(node_id) - elif data["type"] == "boundary": - if "for" in data: - node_types[node_id] = "boundary_for" - node_labels[node_id] = data["for"] - node_colors[node_id] = "white" - boundary_nodes_for.append(node_id) - else: - node_types[node_id] = "boundary" - node_labels[node_id] = data["label"] - node_colors[node_id] = "lightcoral" - boundary_nodes.append(node_id) - else: - node_colors[node_id] = "grey" # Should not happen with filtering - - # Add original edges - original_edges = [] - for edge in parsed_data["edges"]: - u, v = edge["u"], edge["v"] - if G.has_node(u) and G.has_node(v): - G.add_edge(u, v, type="original", color="black") - original_edges.append((u, v)) - else: - print( - f"Warning: Skipping original edge ({u},{v}) - one or both nodes not found." - ) - - # Add boundary edges and group by color - boundary_edges_by_color = defaultdict(list) - for pair in parsed_data["boundary_pairs"]: - color = pair["id"] - seg1 = pair["segment1"] - seg2 = pair["segment2"] - # Add both segments as edges, tagged with color - if G.has_node(seg1["u"]) and G.has_node(seg1["v"]): - G.add_edge(seg1["u"], seg1["v"], type="boundary", color=color) - boundary_edges_by_color[color].append((seg1["u"], seg1["v"])) - else: - print( - f"Warning: Skipping boundary edge ({seg1['u']},{seg1['v']}) for color {color} - nodes not found." - ) - - if G.has_node(seg2["u"]) and G.has_node(seg2["v"]): - G.add_edge(seg2["u"], seg2["v"], type="boundary", color=color) - boundary_edges_by_color[color].append((seg2["u"], seg2["v"])) - else: - print( - f"Warning: Skipping boundary edge ({seg2['u']},{seg2['v']}) for color {color} - nodes not found." - ) - - # --- Plotting --- - plt.figure(figsize=(12, 12)) - - # Draw original nodes - nx.draw_networkx_nodes( - G, - pos, - nodelist=original_nodes, - node_color="skyblue", - node_size=300, - label="Original Nodes", - ) - # Draw boundary nodes - nx.draw_networkx_nodes( - G, - pos, - nodelist=boundary_nodes, - node_color="lightcoral", - node_size=400, - node_shape="s", - label="Boundary Nodes", - ) - # Draw boundary nodes representing an edge crossing through the boundary - nx.draw_networkx_nodes( - G, - pos, - nodelist=boundary_nodes_for, - node_color="white", - edgecolors="black", - node_size=400, - label="Boundary Cross Through Nodes", - ) - - # Draw original edges - nx.draw_networkx_edges( - G, - pos, - edgelist=original_edges, - edge_color="black", - width=1.0, - label="Original Edges", - ) - - # Draw boundary edges with colors - # Define a mapping from color names to matplotlib colors if needed - color_map = { - "red": "red", - "blue": "blue", - "green": "green", - "orange": "orange", - "olive": "olive", - "gray": "gray", - "pink": "pink", - "yellow": "yellow", - "lime": "lime", - "cyan": "cyan", - # Add more colors if used by the C code - } - for color, edges_list in boundary_edges_by_color.items(): - nx.draw_networkx_edges( - G, - pos, - edgelist=edges_list, - edge_color=color_map.get( - color, "purple" - ), # Default to purple if color unknown - width=2.5, # Make boundary edges thicker - style="dashed", # Use dashed style - label=f"Boundary ({color})", - ) - - # Draw labels - nx.draw_networkx_labels(G, pos, labels=node_labels, font_size=8) - - plt.title("Parsed Graph Visualization") - plt.xlabel("X Coordinate") - plt.ylabel("Y Coordinate") - # plt.legend() # Legend can get crowded, optional - plt.axis("equal") # Ensure aspect ratio is equal - plt.grid(True) - plt.show() - - -# --- Main Execution --- -if __name__ == "__main__": - tikz = sys.stdin.read() - parsed_data = parse_tikz_graph(tikz) - - if parsed_data: - print("\n--- Plotting Parsed Graph ---") - plot_parsed_graph(parsed_data) - else: - print("\nParsing Failed, cannot plot.") diff --git a/Visualize/test.pdf b/Visualize/test.pdf deleted file mode 100644 index e8f0232..0000000 Binary files a/Visualize/test.pdf and /dev/null differ diff --git a/Visualize/test.synctex.gz b/Visualize/test.synctex.gz deleted file mode 100644 index 3985295..0000000 Binary files a/Visualize/test.synctex.gz and /dev/null differ diff --git a/Visualize/test.tex b/Visualize/test.tex deleted file mode 100644 index 32585a8..0000000 --- a/Visualize/test.tex +++ /dev/null @@ -1,78 +0,0 @@ -\documentclass{article} -\usepackage{tikz} -\usepackage{tkz-euclide} -\addtolength{\textwidth}{3cm} -\addtolength{\oddsidemargin}{-1.5cm} -\addtolength{\evensidemargin}{-1.5cm} -\begin{document} -\begin{center} -\begin{tikzpicture}[scale=0.065] -\def\vertexscale{0.65} -\def\labelscale{0.75} -\node [circle,black,draw,scale=\vertexscale] (1) at (23.31846,36.49750) {1}; -\node [circle,black,draw,scale=\vertexscale] (2) at (4.81416,13.57126) {2}; -\node [circle,black,draw,scale=\vertexscale] (3) at (-7.35861,33.88780) {3}; -\node [circle,black,draw,scale=\vertexscale] (4) at (-18.36921,-20.27140) {4}; -\node [circle,black,draw,scale=\vertexscale] (5) at (52.71830,-6.06224) {5}; -\node [circle,black,draw,scale=\vertexscale] (6) at (-8.73972,54.31764) {6}; -\node [circle,black,draw,scale=\vertexscale] (7) at (-9.58977,17.40783) {7}; -\node [circle,black,draw,scale=\vertexscale] (8) at (-1.82652,23.26209) {8}; -\node [circle,black,draw,scale=\vertexscale] (9) at (9.59057,30.14151) {9}; -\node [circle,black,draw,scale=\vertexscale] (10) at (21.31105,5.35430) {10}; -\node [circle,black,draw,scale=\vertexscale] (11) at (-51.93409,5.14831) {11}; -\node [circle,black,draw,scale=\vertexscale] (12) at (5.25192,-52.62787) {12}; -\tkzDefPoint(-100.00000,-0.00000){13} -\tkzDefPoint(-70.71068,-70.71068){14} -\tkzDefPoint(0.00000,-100.00000){15} -\tkzDefPoint(100.00000,0.00000){16} -\tkzDefPoint(-0.00000,100.00000){17} -\tkzDefPoint(-70.71068,70.71068){18} -\tkzDefPoint(70.71068,70.71068){19} -\tkzDefPoint(70.71068,-70.71068){20} -\draw [black] (1) to (9); -\draw [black] (1) to (6); -\draw [black] (1) to (10); -\draw [black] (2) to (9); -\draw [black] (2) to (7); -\draw [black] (2) to (8); -\draw [black] (3) to (7); -\draw [black] (3) to (9); -\draw [black] (3) to (8); -\draw [black] (4) to (11); -\draw [black] (4) to (10); -\draw [black] (4) to (12); -\draw [black] (5) to (12); -\draw [black] (5) to (10); -\draw [black] (5) to (16); -\node [draw=none,fill=none,scale=\labelscale] () at (105.00000,0.00000) {11}; -\draw [black] (6) to (11); -\draw [black] (6) to (17); -\node [draw=none,fill=none,scale=\labelscale] () at (-0.00000,105.00000) {12}; -\draw [black] (7) to (8); -\draw [black] (11) to (13); -\node [draw=none,fill=none,scale=\labelscale] () at (-105.00000,-0.00000) {5}; -\draw [black] (12) to (15); -\node [draw=none,fill=none,scale=\labelscale] () at (0.00000,-105.00000) {6}; -\tkzDefPoint(-69.32233,72.07229){A} -\tkzDefPoint(69.32233,72.07229){B} -\tkzDefPoint(0.0,0.0){C} -\tkzDrawArc[<-,line width=0.9mm, red](C,B)(A) -\tkzDefPoint(72.07229,69.32233){A} -\tkzDefPoint(72.07229,-69.32233){B} -\tkzDefPoint(0.0,0.0){C} -\tkzDrawArc[<-,line width=0.9mm, blue](C,B)(A) -\tkzDefPoint(69.32233,-72.07229){A} -\tkzDefPoint(-69.32233,-72.07229){B} -\tkzDefPoint(0.0,0.0){C} -\tkzDrawArc[->,line width=0.9mm, red](C,B)(A) -\tkzDefPoint(-72.07229,-69.32233){A} -\tkzDefPoint(-72.07229,69.32233){B} -\tkzDefPoint(0.0,0.0){C} -\tkzDrawArc[->,line width=0.9mm, blue](C,B)(A) -\node [black,circle,draw,fill=white,scale=0.49,line width=1mm] (14) at (-70.71068,-70.71068) {}; -\node [black,circle,draw,fill=white,scale=0.49,line width=1mm] (18) at (-70.71068,70.71068) {}; -\node [black,circle,draw,fill=white,scale=0.49,line width=1mm] (19) at (70.71068,70.71068) {}; -\node [black,circle,draw,fill=white,scale=0.49,line width=1mm] (20) at (70.71068,-70.71068) {}; -\end{tikzpicture} -\end{center} -\end{document} diff --git a/WebApp/Dockerfile b/WebApp/Dockerfile index d0f08f3..66cb8ab 100644 --- a/WebApp/Dockerfile +++ b/WebApp/Dockerfile @@ -1,33 +1,46 @@ # Compile C code first so we don't need to keep the C compiler in the final image -FROM gcc as builder +FROM gcc AS builder WORKDIR /app # Copy the C code and compile it -COPY CalcGenus/CalcGenus.c CalcGenus.c -RUN gcc -O3 -ftree-vectorize -funroll-loops -Wall -std=c17 -pedantic -g -o CalcGenus CalcGenus.c -RUN gcc -DONLY_SIMPLE_CYCLES=1 -O3 -ftree-vectorize -funroll-loops -Wall -std=c17 -pedantic -g -o CalcGenusSC CalcGenus.c +COPY PAGE/page.c page.c +RUN gcc -O3 -ftree-vectorize -funroll-loops -Wall -std=c17 -pedantic -g -o page page.c +RUN gcc -DONLY_SIMPLE_CYCLES=1 -O3 -ftree-vectorize -funroll-loops -Wall -std=c17 -pedantic -g -o pageSC page.c COPY MultiGenus/multi_genus_longtype.c multi_genus_longtype.c RUN gcc -O3 -DLONG -march=native -o multi_genus_128 multi_genus_longtype.c -lm +COPY MultiGenus/planar_cutthroughedges_draw.c planar_cutthroughedges_draw.c +RUN gcc -std=gnu89 -O3 -o planar_cutthroughedges_draw planar_cutthroughedges_draw.c -lm # Now we take a minimal python image and copy the compiled C binary to it FROM python:3.9-slim WORKDIR /app -COPY --from=builder /app/CalcGenus /app/CalcGenusSC /app/multi_genus_128 /app/ +RUN --mount=type=cache,target=/var/cache/apt \ + --mount=type=cache,target=/var/lib/apt \ + apt-get update \ + && apt-get install -y --no-install-recommends \ + poppler-utils \ + texlive-latex-base \ + texlive-latex-extra \ + texlive-latex-recommended \ + texlive-pictures \ + && rm -rf /var/lib/apt/lists/* # Python dependencies COPY WebApp/requirements.txt requirements.txt RUN pip install --no-cache-dir -r requirements.txt +# Copy compiled C binaries +COPY --from=builder /app/page /app/pageSC /app/multi_genus_128 /app/planar_cutthroughedges_draw /app/ + # Copy the rest of the files -COPY CalcGenus/adjacency_lists/* adjacency_lists/ +COPY PAGE/adjacency_lists/* adjacency_lists/ COPY WebApp/main.py main.py -COPY WebApp/static/* static/ +COPY WebApp/static/ static/ EXPOSE 8080 CMD gunicorn --workers=$((2 * $(python -c 'import os; print(os.cpu_count())') + 1)) --threads=1 --bind=0.0.0.0:8080 --timeout 600 main:app - diff --git a/WebApp/main.py b/WebApp/main.py index eaa3e48..cb8e5b3 100644 --- a/WebApp/main.py +++ b/WebApp/main.py @@ -1,8 +1,15 @@ import os import subprocess +import threading import tempfile import time +import base64 +import binascii +import re +import struct +import zlib from io import StringIO, BytesIO +from pathlib import Path from flask import Flask, send_from_directory from flask_sock import Sock @@ -11,6 +18,8 @@ # Initialize Flask app app = Flask(__name__) sock = Sock(app) +APP_DIR = Path(__file__).resolve().parent +REPO_DIR = APP_DIR.parent @app.route("/") @@ -33,6 +42,188 @@ def send_adjlist(path): return send_from_directory("adjacency_lists", path) +PAGE_GENUS_RE = re.compile(r"genus\s+(\d+)", re.IGNORECASE) +PAGE_GENUS_FOUND_RE = re.compile(r"Genus found:\s*(\d+)", re.IGNORECASE) +MULTIGENUS_RE = re.compile(r"graphs with genus\s+(\d+):", re.IGNORECASE) + + +def find_executable(*candidates): + for candidate in candidates: + paths = [Path(candidate)] + if not Path(candidate).is_absolute(): + paths.extend([APP_DIR / candidate, REPO_DIR / candidate]) + for path in paths: + path = path.resolve() + if path.is_file() and os.access(path, os.X_OK): + return str(path) + return candidates[0] + + +def graph_label_start(adj_list): + labels = [neighbor for neighbors in adj_list for neighbor in neighbors] + if not labels: + return 0 + return min(labels) + + +def normalize_rotation(adj_list): + start = graph_label_start(adj_list) + n = len(adj_list) + rotation = [] + for vertex, neighbors in enumerate(adj_list): + normalized = [] + for neighbor in neighbors: + converted = neighbor - start + if converted < 0 or converted >= n: + raise ValueError( + f"Neighbor {neighbor} on line {vertex + 1} is outside the vertex range" + ) + normalized.append(converted) + rotation.append(normalized) + return rotation, start + + +def rotation_to_multicode(adj_list): + rotation, start = normalize_rotation(adj_list) + n = len(rotation) + if n > 255: + raise ValueError("Drawing currently supports at most 255 vertices") + + out = BytesIO() + out.write(bytes([n])) + for neighbors in rotation: + for neighbor in neighbors: + out.write(bytes([neighbor + 1])) + out.write(b"\0") + return out.getvalue(), start + + +def decode_multicode_rotation(data, label_start=1): + if not data: + raise ValueError("No embedding was written") + if data[0] == 0: + raise ValueError("Two-byte multicode output is not supported yet") + + n = data[0] + pos = 1 + rotation = [] + for _ in range(n): + neighbors = [] + while True: + if pos >= len(data): + raise ValueError("Truncated embedding code") + value = data[pos] + pos += 1 + if value == 0: + break + neighbors.append(value - 1 + label_start) + rotation.append(neighbors) + return rotation + + +def genus_from_rotation(adj_list): + rotation, _ = normalize_rotation(adj_list) + n = len(rotation) + directed_edges = set() + next_dart = {} + + for vertex, neighbors in enumerate(rotation): + if not neighbors: + continue + seen = set() + for neighbor in neighbors: + if neighbor in seen: + raise ValueError(f"Duplicate neighbor at vertex {vertex}") + seen.add(neighbor) + directed_edges.add((vertex, neighbor)) + for i, incoming in enumerate(neighbors): + outgoing = neighbors[(i + 1) % len(neighbors)] + next_dart[(incoming, vertex)] = (vertex, outgoing) + + for u, v in directed_edges: + if (v, u) not in directed_edges: + raise ValueError(f"Rotation contains edge {u}-{v} only once") + if (u, v) not in next_dart: + raise ValueError(f"Rotation is missing a successor for dart {u}->{v}") + + visited = set() + faces = 0 + for dart in directed_edges: + if dart in visited: + continue + faces += 1 + current = dart + while current not in visited: + visited.add(current) + current = next_dart[current] + + edges = len(directed_edges) // 2 + two_g = 2 - (n - edges + faces) + if two_g < 0 or two_g % 2 != 0: + raise ValueError("Rotation system does not define an orientable embedding") + return two_g // 2 + + +def parse_page_solution(stdout_text, stderr_text, adj_list): + genus_match = PAGE_GENUS_RE.search(stdout_text) or PAGE_GENUS_FOUND_RE.search( + stdout_text + ) + if not genus_match: + genus_match = PAGE_GENUS_RE.search(stderr_text) + if not genus_match: + raise ValueError("PAGE did not report a genus") + genus = int(genus_match.group(1)) + + start = graph_label_start(adj_list) + n = len(adj_list) + next_neighbor = [dict() for _ in range(n)] + cycle_count = 0 + + for line in stdout_text.splitlines(): + if not re.fullmatch(r"\s*\d+(?:\s+\d+)*\s*", line): + continue + cycle = [int(value) - start for value in line.split()] + if len(cycle) < 4 or cycle[0] != cycle[-1]: + continue + cycle = cycle[:-1] + cycle_count += 1 + for i, vertex in enumerate(cycle): + incoming = cycle[i - 1] + outgoing = cycle[(i + 1) % len(cycle)] + if vertex < 0 or vertex >= n or incoming < 0 or outgoing < 0: + raise ValueError("PAGE output contains an unexpected vertex label") + next_neighbor[vertex][incoming] = outgoing + + if cycle_count == 0: + raise ValueError("PAGE did not write a rotation system for this graph") + + rotation = [] + for vertex, input_neighbors in enumerate(adj_list): + normalized_neighbors = [neighbor - start for neighbor in input_neighbors] + if not normalized_neighbors: + rotation.append([]) + continue + first = normalized_neighbors[0] + ordered = [first] + current = first + for _ in range(1, len(normalized_neighbors)): + if current not in next_neighbor[vertex]: + raise ValueError( + f"Could not reconstruct rotation at vertex {vertex + start}" + ) + current = next_neighbor[vertex][current] + ordered.append(current) + if next_neighbor[vertex].get(current) != first: + raise ValueError(f"Rotation at vertex {vertex + start} is not cyclic") + if set(ordered) != set(normalized_neighbors): + raise ValueError( + f"Rotation at vertex {vertex + start} does not match input" + ) + rotation.append([neighbor + start for neighbor in ordered]) + + return genus, rotation + + def setup_page(adj_list, file_name): file = StringIO() @@ -79,13 +270,26 @@ def calc_genus(algorithm, adj_list: list[list[int]]): with tempfile.NamedTemporaryFile(mode="w") as f: if algorithm == "page": env, adj_file, inp_type = setup_page(adj_list, f.name) - cmd = ["./CalcGenus"] + cmd = [find_executable("./page", "../PAGE/page")] elif algorithm == "page_sc": env, adj_file, inp_type = setup_page(adj_list, f.name) - cmd = ["./CalcGenusSC"] + cmd = [find_executable("./pageSC", "../PAGE/page")] elif algorithm == "multi_genus": env, adj_file, inp_type = setup_multi_genus(adj_list) - cmd = ["./multi_genus_128"] + cmd = [ + find_executable( + "./multi_genus_128", + "./multi_genus_longtype_128", + "../MultiGenus/multi_genus_longtype_128", + ) + ] + elif algorithm == "none": + genus = genus_from_rotation(adj_list) + yield f"Genus found: {genus}\n", "STDOUT" + yield "Rotation system:\n", "STDOUT" + for neighbors in adj_list: + yield " ".join(str(n) for n in neighbors) + "\n", "STDOUT" + return else: raise ValueError("Invalid algorithm") @@ -121,6 +325,445 @@ def calc_genus(algorithm, adj_list: list[list[int]]): yield f"{end_time - start_time} seconds", "TIME" +def run_algorithm_capture(algorithm, adj_list, status_callback=None): + if algorithm == "none": + start_time = time.perf_counter() + genus = genus_from_rotation(adj_list) + return ( + { + "genus": genus, + "rotation_system": adj_list, + }, + rotation_to_multicode(adj_list)[0], + "", + "", + time.perf_counter() - start_time, + ) + + with tempfile.NamedTemporaryFile(mode="w") as f: + if algorithm == "page": + env, adj_file, inp_type = setup_page(adj_list, f.name) + cmd = [find_executable("./page", "../PAGE/page")] + elif algorithm == "page_sc": + env, adj_file, inp_type = setup_page(adj_list, f.name) + cmd = [find_executable("./pageSC", "../PAGE/page")] + elif algorithm == "multi_genus": + env, adj_file, inp_type = setup_multi_genus(adj_list) + cmd = [ + find_executable( + "./multi_genus_128", + "./multi_genus_longtype_128", + "../MultiGenus/multi_genus_longtype_128", + ) + ] + cmd.append("w") + else: + raise ValueError("Invalid algorithm") + + if inp_type == "FILE": + assert isinstance(adj_file, StringIO) + adj_file.seek(0) + f.write(adj_file.read()) + f.flush() + + input_bytes = None + if inp_type == "STDIN": + assert isinstance(adj_file, BytesIO) + adj_file.seek(0) + input_bytes = adj_file.read() + + start_time = time.perf_counter() + proc = subprocess.Popen( + cmd, + stdin=subprocess.PIPE if input_bytes is not None else None, + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + env=env, + ) + assert proc.stdout is not None + assert proc.stderr is not None + + if input_bytes is not None: + assert proc.stdin is not None + proc.stdin.write(input_bytes) + proc.stdin.close() + + stdout_chunks = [] + + def read_stdout(): + while True: + chunk = proc.stdout.read(8192) # type: ignore + if not chunk: + break + stdout_chunks.append(chunk) + + stdout_thread = threading.Thread(target=read_stdout) + stdout_thread.start() + + stderr_chunks = [] + for raw_line in proc.stderr: + stderr_chunks.append(raw_line) + if status_callback is not None: + status_callback(raw_line.decode("utf-8", errors="replace")) + + returncode = proc.wait() + stdout_thread.join() + runtime = time.perf_counter() - start_time + + stdout_bytes = b"".join(stdout_chunks) + stderr_text = b"".join(stderr_chunks).decode("utf-8", errors="replace") + stdout_text = stdout_bytes.decode("utf-8", errors="replace") + if returncode != 0: + return ( + { + "error": f"{algorithm} exited with status {returncode}", + "stderr": stderr_text, + }, + None, + stdout_text, + stderr_text, + runtime, + ) + + if algorithm == "multi_genus": + genus_match = MULTIGENUS_RE.search(stderr_text) + if not genus_match: + return ( + { + "error": "MULTI_GENUS did not report a genus", + "stderr": stderr_text, + }, + None, + stdout_text, + stderr_text, + runtime, + ) + start = graph_label_start(adj_list) + rotation = decode_multicode_rotation(stdout_bytes, label_start=start) + result = { + "genus": int(genus_match.group(1)), + "rotation_system": rotation, + } + return result, stdout_bytes, stdout_text, stderr_text, runtime + + try: + genus, rotation = parse_page_solution(stdout_text, stderr_text, adj_list) + except ValueError as exc: + return ( + { + "error": str(exc), + "stdout": stdout_text, + "stderr": stderr_text, + }, + None, + stdout_text, + stderr_text, + runtime, + ) + + multicode, _ = rotation_to_multicode(rotation) + return ( + { + "genus": genus, + "rotation_system": rotation, + }, + multicode, + stdout_text, + stderr_text, + runtime, + ) + + +def render_multicode_png(multicode): + draw_cmd = find_executable( + "./planar_cutthroughedges_draw", + "../MultiGenus/planar_cutthroughedges_draw", + ) + with tempfile.TemporaryDirectory() as tmpdir: + tmpdir = Path(tmpdir) + draw = subprocess.run( + [draw_cmd, "f", "l"], + input=multicode, + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + check=False, + ) + if draw.returncode != 0: + raise RuntimeError(draw.stderr.decode("utf-8", errors="replace")) + + tex_path = tmpdir / "embedding.tex" + tex_path.write_text(suppress_latex_page_numbers(draw.stdout), encoding="utf-8") + latex = subprocess.run( + [ + "pdflatex", + "-interaction=nonstopmode", + "-halt-on-error", + tex_path.name, + ], + cwd=tmpdir, + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + check=False, + ) + if latex.returncode != 0: + raise RuntimeError(summarize_latex_error(latex.stdout)) + + pdf_path = tmpdir / "embedding.pdf" + png_base = tmpdir / "embedding" + convert = subprocess.run( + [ + "pdftoppm", + "-png", + "-singlefile", + "-r", + "180", + str(pdf_path), + str(png_base), + ], + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + check=False, + ) + if convert.returncode != 0: + raise RuntimeError(convert.stderr.decode("utf-8", errors="replace")) + return crop_png((tmpdir / "embedding.png").read_bytes()) + + +def render_multicode_obj(multicode): + draw_cmd = find_executable( + "./planar_cutthroughedges_draw", + "../MultiGenus/planar_cutthroughedges_draw", + ) + with tempfile.TemporaryDirectory() as tmpdir: + tmpdir = Path(tmpdir) + prefix = tmpdir / "surface" + draw = subprocess.run( + [draw_cmd, "f", "l", "o", str(prefix)], + input=multicode, + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + check=False, + ) + if draw.returncode != 0: + raise RuntimeError(draw.stderr.decode("utf-8", errors="replace")) + + obj_path = tmpdir / "surface.obj" + mtl_path = tmpdir / "surface.mtl" + if not obj_path.exists(): + raise RuntimeError("3D exporter did not write the expected OBJ file") + + return { + "obj": obj_path.read_text(encoding="utf-8", errors="replace"), + "mtl": ( + mtl_path.read_text(encoding="utf-8", errors="replace") + if mtl_path.exists() + else "" + ), + } + + +def suppress_latex_page_numbers(output): + text = output.decode("utf-8", errors="replace") + if "\\pagestyle{empty}" in text: + return text + return text.replace("\\begin{document}", "\\pagestyle{empty}\n\\begin{document}", 1) + + +def crop_png(png, background_threshold=250, margin=24): + signature = b"\x89PNG\r\n\x1a\n" + if not png.startswith(signature): + return png + + pos = len(signature) + chunks = [] + ihdr = None + idat = [] + palette = None + transparency = None + + while pos + 8 <= len(png): + length = struct.unpack(">I", png[pos : pos + 4])[0] + chunk_type = png[pos + 4 : pos + 8] + data = png[pos + 8 : pos + 8 + length] + pos += 12 + length + chunks.append((chunk_type, data)) + if chunk_type == b"IHDR": + ihdr = data + elif chunk_type == b"IDAT": + idat.append(data) + elif chunk_type == b"PLTE": + palette = data + elif chunk_type == b"tRNS": + transparency = data + elif chunk_type == b"IEND": + break + + if ihdr is None or not idat: + return png + + width, height, bit_depth, color_type, compression, filter_method, interlace = ( + struct.unpack(">IIBBBBB", ihdr) + ) + if compression != 0 or filter_method != 0 or interlace != 0 or bit_depth != 8: + return png + + try: + raw = zlib.decompress(b"".join(idat)) + rgba_rows = decode_png_rows( + raw, width, height, color_type, palette, transparency + ) + except (IndexError, ValueError, zlib.error): + return png + + left, top, right, bottom = width, height, -1, -1 + for y, row in enumerate(rgba_rows): + for x in range(width): + r, g, b, a = row[x * 4 : x * 4 + 4] + if a > 0 and ( + r < background_threshold + or g < background_threshold + or b < background_threshold + ): + left = min(left, x) + top = min(top, y) + right = max(right, x) + bottom = max(bottom, y) + + if right < left or bottom < top: + return png + + left = max(0, left - margin) + top = max(0, top - margin) + right = min(width - 1, right + margin) + bottom = min(height - 1, bottom + margin) + cropped_width = right - left + 1 + cropped_height = bottom - top + 1 + + scanlines = [] + for y in range(top, bottom + 1): + row = rgba_rows[y] + scanlines.append(b"\0" + row[left * 4 : (right + 1) * 4]) + + return encode_rgba_png(cropped_width, cropped_height, b"".join(scanlines)) + + +def decode_png_rows(raw, width, height, color_type, palette, transparency): + channels_by_type = {0: 1, 2: 3, 3: 1, 4: 2, 6: 4} + if color_type not in channels_by_type: + raise ValueError("Unsupported PNG color type") + + channels = channels_by_type[color_type] + stride = width * channels + rows = [] + previous = bytearray(stride) + pos = 0 + + for _ in range(height): + filter_type = raw[pos] + pos += 1 + current = bytearray(raw[pos : pos + stride]) + pos += stride + unfilter_row(current, previous, channels, filter_type) + rows.append(row_to_rgba(current, width, color_type, palette, transparency)) + previous = current + + return rows + + +def unfilter_row(current, previous, bpp, filter_type): + for i in range(len(current)): + left = current[i - bpp] if i >= bpp else 0 + up = previous[i] + upper_left = previous[i - bpp] if i >= bpp else 0 + if filter_type == 0: + prediction = 0 + elif filter_type == 1: + prediction = left + elif filter_type == 2: + prediction = up + elif filter_type == 3: + prediction = (left + up) // 2 + elif filter_type == 4: + prediction = paeth(left, up, upper_left) + else: + raise ValueError("Unsupported PNG filter") + current[i] = (current[i] + prediction) & 0xFF + + +def paeth(left, up, upper_left): + p = left + up - upper_left + pa = abs(p - left) + pb = abs(p - up) + pc = abs(p - upper_left) + if pa <= pb and pa <= pc: + return left + if pb <= pc: + return up + return upper_left + + +def row_to_rgba(row, width, color_type, palette, transparency): + out = bytearray(width * 4) + for x in range(width): + if color_type == 0: + gray = row[x] + rgba = (gray, gray, gray, 255) + elif color_type == 2: + i = x * 3 + rgba = (row[i], row[i + 1], row[i + 2], 255) + elif color_type == 3: + if palette is None: + raise ValueError("Palette PNG is missing PLTE") + index = row[x] + p = index * 3 + alpha = ( + transparency[index] + if transparency and index < len(transparency) + else 255 + ) + rgba = (palette[p], palette[p + 1], palette[p + 2], alpha) + elif color_type == 4: + i = x * 2 + gray = row[i] + rgba = (gray, gray, gray, row[i + 1]) + else: + i = x * 4 + rgba = (row[i], row[i + 1], row[i + 2], row[i + 3]) + out[x * 4 : x * 4 + 4] = bytes(rgba) + return bytes(out) + + +def encode_rgba_png(width, height, scanlines): + def chunk(chunk_type, data): + checksum = binascii.crc32(chunk_type + data) & 0xFFFFFFFF + return ( + struct.pack(">I", len(data)) + + chunk_type + + data + + struct.pack(">I", checksum) + ) + + ihdr = struct.pack(">IIBBBBB", width, height, 8, 6, 0, 0, 0) + return b"".join( + [ + b"\x89PNG\r\n\x1a\n", + chunk(b"IHDR", ihdr), + chunk(b"IDAT", zlib.compress(scanlines)), + chunk(b"IEND", b""), + ] + ) + + +def summarize_latex_error(output): + text = output.decode("utf-8", errors="replace") + lines = text.splitlines() + for i, line in enumerate(lines): + if line.startswith("! "): + context = lines[i : i + 6] + return "\n".join(context) + return text[-2000:] + + @sock.route("/stream_calc_genus") def stream(ws): data = ws.receive() @@ -129,9 +772,95 @@ def stream(ws): inp = json.loads(data) algorithm = inp["alg"] adj_list = inp["adj"] - - for out, msg_type in calc_genus(algorithm, adj_list): - ws.send(msg_type + ":" + out) + output_format = inp.get("outputFormat", "text") + + if output_format == "text": + for out, msg_type in calc_genus(algorithm, adj_list): + ws.send(msg_type + ":" + out) + elif output_format == "json": + runtime = None + + def send_status(line): + ws.send("STDERR:" + line) + + try: + result, _, _, _, runtime = run_algorithm_capture( + algorithm, adj_list, status_callback=send_status + ) + except Exception as exc: + result = {"error": str(exc)} + ws.send("JSON:" + json.dumps(result, sort_keys=True)) + if runtime is not None: + ws.send("TIME:" + f"{runtime} seconds") + elif output_format == "drawing": + runtime = None + + def send_status(line): + ws.send("STDERR:" + line) + + try: + result, multicode, _, _, runtime = run_algorithm_capture( + algorithm, adj_list, status_callback=send_status + ) + except Exception as exc: + result = {"error": str(exc)} + multicode = None + if multicode is None: + ws.send("JSON:" + json.dumps(result, sort_keys=True)) + else: + try: + png = render_multicode_png(multicode) + except Exception as exc: + ws.send("JSON:" + json.dumps({"error": str(exc)}, sort_keys=True)) + else: + ws.send( + "IMAGE:data:image/png;base64," + + base64.b64encode(png).decode("ascii") + ) + if runtime is not None: + ws.send("TIME:" + f"{runtime} seconds") + elif output_format in ("3d", "3d_raw"): + runtime = None + + def send_status(line): + ws.send("STDERR:" + line) + + try: + result, multicode, _, _, runtime = run_algorithm_capture( + algorithm, adj_list, status_callback=send_status + ) + except Exception as exc: + result = {"error": str(exc)} + multicode = None + if multicode is None: + ws.send("JSON:" + json.dumps(result, sort_keys=True)) + elif output_format == "3d" and result.get("genus", 0) > 1: + ws.send( + "JSON:" + + json.dumps( + { + "error": ( + "3D output is currently supported only for genus 0 " + "and genus 1 embeddings." + ), + "genus": result["genus"], + }, + sort_keys=True, + ) + ) + else: + try: + model = render_multicode_obj(multicode) + except Exception as exc: + ws.send("JSON:" + json.dumps({"error": str(exc)}, sort_keys=True)) + else: + if "genus" in result: + model["genus"] = result["genus"] + ws.send("MODEL:" + json.dumps(model)) + if runtime is not None: + ws.send("TIME:" + f"{runtime} seconds") + else: + ws.send("JSON:" + json.dumps({"error": "Invalid output format"})) time.sleep(1) diff --git a/WebApp/run-dev.sh b/WebApp/run-dev.sh index 8a64e49..d335d3a 100644 --- a/WebApp/run-dev.sh +++ b/WebApp/run-dev.sh @@ -1,6 +1,6 @@ #!/bin/bash -docker build --tag 'genus' -f ./Dockerfile .. +DOCKER_BUILDKIT=1 docker build --tag 'genus' -f ./Dockerfile .. -open http://localhost:8080 || start chrome \"http://localhost:8080\" || google-chrome 'http://localhost:8080' || echo 'Could not open browser automatically. Please open http://localhost:8080 manually' +# open http://localhost:8080 || start chrome \"http://localhost:8080\" || google-chrome 'http://localhost:8080' || echo 'Could not open browser automatically. Please open http://localhost:8080 manually' docker run -t -i -p 8080:8080 -v ./static:/app/static -v ./main.py:/app/main.py 'genus' python main.py diff --git a/WebApp/run-prod.sh b/WebApp/run-prod.sh index a667034..f512a71 100644 --- a/WebApp/run-prod.sh +++ b/WebApp/run-prod.sh @@ -1,6 +1,6 @@ #!/bin/bash -docker build --tag 'genus' -f ./Dockerfile .. +DOCKER_BUILDKIT=1 docker build --tag 'genus' -f ./Dockerfile .. -open http://localhost:8080 || start chrome \"http://localhost:8080\" || google-chrome 'http://localhost:8080' || echo 'Could not open browser automatically. Please open http://localhost:8080 manually' +# open http://localhost:8080 || start chrome \"http://localhost:8080\" || google-chrome 'http://localhost:8080' || echo 'Could not open browser automatically. Please open http://localhost:8080 manually' docker run -t -i -p 8080:8080 'genus' diff --git a/WebApp/static/apple-touch-icon.png b/WebApp/static/apple-touch-icon.png new file mode 100644 index 0000000..ab12302 Binary files /dev/null and b/WebApp/static/apple-touch-icon.png differ diff --git a/WebApp/static/favicon-16x16.png b/WebApp/static/favicon-16x16.png new file mode 100644 index 0000000..91f72d0 Binary files /dev/null and b/WebApp/static/favicon-16x16.png differ diff --git a/WebApp/static/favicon-32x32.png b/WebApp/static/favicon-32x32.png new file mode 100644 index 0000000..eaf1a71 Binary files /dev/null and b/WebApp/static/favicon-32x32.png differ diff --git a/WebApp/static/favicon.ico b/WebApp/static/favicon.ico new file mode 100644 index 0000000..85433bd Binary files /dev/null and b/WebApp/static/favicon.ico differ diff --git a/WebApp/static/index.html b/WebApp/static/index.html index d77f96e..724b591 100644 --- a/WebApp/static/index.html +++ b/WebApp/static/index.html @@ -3,36 +3,92 @@ - CalcGenus + Genus Calculator + + + + -

Practical Algorithm for Graph Embedding (PAGE)

- -

Enter your adjacency list below to calculate the genus of the graph.

-

Each vertex gets its own line. Each line is a list of space separated vertex numbers for the line-vertex's neighbors.

- - -
- -
- - -

Status:

-

+
+
+
+
+

PAGE

+

Graph Genus Calculator

+

Enter an adjacency list, choose an algorithm, and compute text, JSON, drawing, or 3D output.

+
-

Output:

-

+
+ + +
-

Runtime:

-

+
+ + +
- + + +
+

One vertex per line. Use space-separated vertex numbers for each vertex's neighbors.

+ +
+
+ +
+
+
+

Output

+
+
Results will appear here.
+
+
+
+

Status

+
+
Idle.
+
+
+
+

Runtime

+
+
Not run yet.
+
+
+
+
+ + + diff --git a/WebApp/static/k33_genus2_manual.css b/WebApp/static/k33_genus2_manual.css new file mode 100644 index 0000000..7aaad01 --- /dev/null +++ b/WebApp/static/k33_genus2_manual.css @@ -0,0 +1,213 @@ +:root { + color-scheme: light; + --ink: #171a1f; + --muted: #626975; + --panel: rgba(255, 255, 252, 0.94); + --border: rgba(32, 38, 46, 0.16); + --blue: #0867d8; + --surface: #f6f6f1; +} + +* { + box-sizing: border-box; +} + +html, +body { + margin: 0; + height: 100%; + overflow: hidden; + font-family: Inter, ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif; + color: var(--ink); + background: var(--surface); +} + +button, +select, +textarea { + font: inherit; +} + +.manual-shell, +.manual-stage, +.viewer { + width: 100%; + height: 100%; +} + +.manual-stage { + position: relative; + overflow: hidden; +} + +.viewer canvas { + display: block; + width: 100%; + height: 100%; +} + +.tool-panel { + position: absolute; + top: 16px; + right: 16px; + bottom: 16px; + z-index: 5; + width: min(370px, calc(100vw - 32px)); + display: grid; + align-content: start; + gap: 12px; + overflow: auto; + padding: 16px; + border: 1px solid var(--border); + border-radius: 8px; + background: var(--panel); + box-shadow: 0 18px 46px rgba(29, 35, 43, 0.18); + backdrop-filter: blur(16px); +} + +.panel-header h1, +.tool-section h2 { + margin: 0; + line-height: 1.15; +} + +.panel-header h1 { + font-size: 18px; +} + +.panel-header p, +.tool-section p { + margin: 6px 0 0; + color: var(--muted); + font-size: 13px; + line-height: 1.4; +} + +.field { + display: grid; + gap: 6px; + color: var(--muted); + font-size: 12px; + font-weight: 750; +} + +select, +textarea { + width: 100%; + border: 1px solid var(--border); + border-radius: 8px; + background: #fff; + color: var(--ink); +} + +select { + min-height: 38px; + padding: 0 9px; +} + +textarea { + min-height: 130px; + resize: vertical; + padding: 9px; + font-family: ui-monospace, SFMono-Regular, Menlo, Consolas, monospace; + font-size: 12px; +} + +button { + min-height: 38px; + border: 1px solid var(--border); + border-radius: 8px; + background: #fff; + color: var(--ink); + font-weight: 750; + cursor: pointer; +} + +button.primary { + border-color: rgba(5, 73, 154, 0.18); + background: var(--blue); + color: #fff; +} + +button.active { + border-color: rgba(8, 103, 216, 0.52); + background: rgba(8, 103, 216, 0.12); +} + +.button-row { + display: grid; + grid-template-columns: repeat(2, minmax(0, 1fr)); + gap: 8px; +} + +.status { + min-height: 20px; + color: var(--muted); + font-size: 13px; + line-height: 1.35; +} + +.tool-section { + display: grid; + gap: 9px; + padding-top: 10px; + border-top: 1px solid rgba(32, 38, 46, 0.10); +} + +.rotation-system { + display: grid; + gap: 5px; + padding: 8px; + border: 1px solid rgba(32, 38, 46, 0.10); + border-radius: 8px; + background: rgba(255, 255, 255, 0.72); + font-family: ui-monospace, SFMono-Regular, Menlo, Consolas, monospace; + font-size: 12px; +} + +.rotation-row { + white-space: nowrap; +} + +.verify-result { + min-height: 18px; + color: var(--muted); + font-size: 12px; + line-height: 1.35; +} + +.verify-result.ok { + color: #116c38; +} + +.verify-result.warn { + color: #9a4c00; +} + +.vertex-grid { + display: grid; + grid-template-columns: repeat(6, minmax(0, 1fr)); + gap: 6px; +} + +@media (max-width: 760px) { + .manual-stage { + display: grid; + grid-template-rows: 52dvh 48dvh; + } + + .viewer { + min-height: 0; + } + + .tool-panel { + position: static; + width: auto; + height: auto; + min-height: 0; + border-width: 1px 0 0; + border-radius: 0; + box-shadow: none; + backdrop-filter: none; + } +} diff --git a/WebApp/static/k33_genus2_manual.html b/WebApp/static/k33_genus2_manual.html new file mode 100644 index 0000000..2e076d1 --- /dev/null +++ b/WebApp/static/k33_genus2_manual.html @@ -0,0 +1,83 @@ + + + + + + K3,3 Genus 2 Manual Routing + + + + + + +
+
+
+ +
+
+ + + + + diff --git a/WebApp/static/k33_genus2_manual.js b/WebApp/static/k33_genus2_manual.js new file mode 100644 index 0000000..cfc86fe --- /dev/null +++ b/WebApp/static/k33_genus2_manual.js @@ -0,0 +1,787 @@ +import * as THREE from "three"; +import { OrbitControls } from "/vendor/OrbitControls.js"; + +const K33_BASE = [ + [3, 4, 5], + [3, 4, 5], + [3, 4, 5], + [0, 1, 2], + [0, 1, 2], + [0, 1, 2], +]; +const EDGES = []; +for (let left = 0; left < 3; left++) { + for (let right = 3; right < 6; right++) EDGES.push([left, right]); +} +const REPRESENTATIVES = [ + { + mask: 1, + orbit: [ + 1, 2, 3, 4, 5, 6, 8, 15, 16, 23, 24, 31, + 32, 39, 40, 47, 48, 55, 57, 58, 59, 60, 61, 62, + ], + }, +]; + +const el = { + viewer: document.getElementById("viewer"), + representative: document.getElementById("representative_select"), + orbitSummary: document.getElementById("orbit_summary"), + rotationSystem: document.getElementById("rotation_system"), + loadSurface: document.getElementById("load_surface"), + toggleOriginal: document.getElementById("toggle_original"), + status: document.getElementById("status"), + verifyOrientation: document.getElementById("verify_orientation"), + verifyResult: document.getElementById("verify_result"), + vertexButtons: document.getElementById("vertex_buttons"), + edgeSelect: document.getElementById("edge_select"), + undoPoint: document.getElementById("undo_point"), + clearEdge: document.getElementById("clear_edge"), + smoothEdge: document.getElementById("smooth_edge"), + saveLayout: document.getElementById("save_layout"), + copyLayout: document.getElementById("copy_layout"), + layoutJson: document.getElementById("layout_json"), + applyLayout: document.getElementById("apply_layout"), +}; + +const state = { + mode: "vertex", + selectedVertex: 0, + selectedEdge: edgeKey(0, 3), + surfaceMesh: null, + surfaceGroup: new THREE.Group(), + originalGroup: new THREE.Group(), + manualGroup: new THREE.Group(), + vertexPositions: new Map(), + edgeRoutes: new Map(), + surfaceTriangles: [], + center: new THREE.Vector3(), + radius: 1, + showOriginal: false, +}; + +const renderer = new THREE.WebGLRenderer({ antialias: true }); +renderer.setPixelRatio(Math.min(window.devicePixelRatio, 2)); +renderer.outputColorSpace = THREE.SRGBColorSpace; +el.viewer.appendChild(renderer.domElement); + +const scene = new THREE.Scene(); +scene.background = new THREE.Color(0xf7f7f3); +const camera = new THREE.PerspectiveCamera(45, 1, 0.01, 1000); +camera.position.set(0, -5, 2.8); +const controls = new OrbitControls(camera, renderer.domElement); +controls.enableDamping = true; +scene.add(new THREE.HemisphereLight(0xffffff, 0x777777, 2.25)); +const key = new THREE.DirectionalLight(0xffffff, 1.75); +key.position.set(4, -5, 7); +scene.add(key); +scene.add(state.surfaceGroup, state.originalGroup, state.manualGroup); + +const raycaster = new THREE.Raycaster(); +const pointer = new THREE.Vector2(); +const triangleScratch = { + ab: new THREE.Vector3(), + ac: new THREE.Vector3(), + ap: new THREE.Vector3(), + bp: new THREE.Vector3(), + cp: new THREE.Vector3(), + bc: new THREE.Vector3(), +}; +const resizeObserver = new ResizeObserver(resize); +resizeObserver.observe(el.viewer); +resize(); +initControls(); +animate(); +loadSurface(); + +function initControls() { + el.orbitSummary.textContent = "Verified: all 24 genus-2 systems are one symmetry class."; + REPRESENTATIVES.forEach((rep, index) => { + const option = document.createElement("option"); + option.value = String(index); + option.textContent = `Representative mask ${rep.mask}, orbit size ${rep.orbit.length}`; + el.representative.appendChild(option); + }); + el.representative.addEventListener("change", renderRotationSystem); + renderRotationSystem(); + for (let vertex = 0; vertex < 6; vertex++) { + const button = document.createElement("button"); + button.type = "button"; + button.textContent = String(vertex); + button.addEventListener("click", () => selectVertex(vertex)); + el.vertexButtons.appendChild(button); + } + for (const [a, b] of EDGES) { + const option = document.createElement("option"); + option.value = edgeKey(a, b); + option.textContent = `${a}-${b}`; + el.edgeSelect.appendChild(option); + } + el.edgeSelect.addEventListener("change", () => { + state.selectedEdge = el.edgeSelect.value; + state.mode = "edge"; + updateActiveControls(); + }); + el.loadSurface.addEventListener("click", loadSurface); + el.toggleOriginal.addEventListener("click", () => { + state.showOriginal = !state.showOriginal; + state.originalGroup.visible = state.showOriginal; + el.toggleOriginal.classList.toggle("active", state.showOriginal); + }); + el.undoPoint.addEventListener("click", () => { + const route = state.edgeRoutes.get(state.selectedEdge) || []; + route.pop(); + state.edgeRoutes.set(state.selectedEdge, route); + drawManualOverlay(); + }); + el.clearEdge.addEventListener("click", () => { + state.edgeRoutes.set(state.selectedEdge, []); + drawManualOverlay(); + }); + el.smoothEdge.addEventListener("click", smoothSelectedEdge); + el.verifyOrientation.addEventListener("click", verifyOrientations); + el.saveLayout.addEventListener("click", saveLayout); + el.copyLayout.addEventListener("click", copyLayout); + el.applyLayout.addEventListener("click", applyLayout); + renderer.domElement.addEventListener("pointerdown", onPointerDown); + selectVertex(0); +} + +function selectVertex(vertex) { + state.mode = "vertex"; + state.selectedVertex = vertex; + updateActiveControls(); +} + +function updateActiveControls() { + [...el.vertexButtons.children].forEach((button, index) => { + button.classList.toggle("active", state.mode === "vertex" && index === state.selectedVertex); + }); +} + +function renderRotationSystem() { + const rotation = currentRotation(); + el.rotationSystem.replaceChildren(); + rotation.forEach((neighbors, vertex) => { + const row = document.createElement("div"); + row.className = "rotation-row"; + row.textContent = `${vertex}: (${neighbors.join(", ")})`; + el.rotationSystem.appendChild(row); + }); + el.verifyResult.textContent = ""; + el.verifyResult.className = "verify-result"; +} + +async function loadSurface() { + const rep = REPRESENTATIVES[Number(el.representative.value || 0)]; + setStatus(`Loading genus-2 surface for mask ${rep.mask}...`); + clearGroup(state.surfaceGroup); + clearGroup(state.originalGroup); + clearGroup(state.manualGroup); + state.surfaceMesh = null; + state.vertexPositions = new Map(); + state.edgeRoutes = new Map(); + state.surfaceTriangles = []; + try { + const model = await requestModel(rotationFromMask(rep.mask)); + buildSceneFromObj(model.obj); + loadSavedLayout(); + drawManualOverlay(); + setStatus("Loaded the genus-2 representative. Click a vertex or route point onto the surface."); + } catch (error) { + setStatus(error.message); + } +} + +function requestModel(rotation) { + return new Promise((resolve, reject) => { + const socket = new WebSocket(`${location.protocol === "https:" ? "wss:" : "ws:"}//${location.host}/stream_calc_genus`); + let done = false; + socket.onopen = () => { + socket.send(JSON.stringify({ alg: "none", outputFormat: "3d_raw", adj: rotation })); + }; + socket.onmessage = (event) => { + const separator = event.data.indexOf(":"); + const type = separator === -1 ? event.data : event.data.slice(0, separator); + const data = separator === -1 ? "" : event.data.slice(separator + 1); + if (type === "MODEL") { + done = true; + resolve(JSON.parse(data)); + socket.close(); + } else if (type === "JSON") { + const parsed = JSON.parse(data); + if (parsed.error) { + done = true; + reject(new Error(parsed.error)); + socket.close(); + } + } else if (type === "STDERR") { + setStatus(data); + } + }; + socket.onerror = () => { + if (!done) reject(new Error("Could not load the genus-2 model")); + }; + socket.onclose = () => { + if (!done) reject(new Error("3D model request closed before a model was returned")); + }; + }); +} + +function buildSceneFromObj(objText) { + const parsed = parseObj(objText); + parsed.geometry.computeBoundingBox(); + parsed.geometry.boundingBox.getCenter(state.center); + parsed.geometry.translate(-state.center.x, -state.center.y, -state.center.z); + parsed.geometry.computeBoundingSphere(); + state.radius = parsed.geometry.boundingSphere?.radius || 1; + state.surfaceTriangles = buildSurfaceTriangles(parsed.geometry); + + const surface = new THREE.Mesh( + parsed.geometry, + new THREE.MeshStandardMaterial({ + color: 0xc8cac7, + roughness: 0.66, + metalness: 0.02, + side: THREE.DoubleSide, + }), + ); + state.surfaceMesh = surface; + state.surfaceGroup.add(surface); + + const originalMaterial = new THREE.MeshBasicMaterial({ + color: 0x111111, + transparent: true, + opacity: 0.22, + depthTest: true, + depthWrite: false, + }); + const originalRadius = Math.max(state.radius * 0.0016, 0.0025); + for (const line of parsed.graphLines) { + const points = line.points.map((point) => point.clone().sub(state.center)); + state.originalGroup.add(makeTube(points, originalRadius, originalMaterial, Math.max(6, points.length - 1))); + } + state.originalGroup.visible = state.showOriginal; + + camera.position.set(0, -state.radius * 2.7, state.radius * 1.35); + camera.near = Math.max(0.01, state.radius / 100); + camera.far = state.radius * 20; + camera.updateProjectionMatrix(); + controls.target.set(0, 0, 0); + controls.update(); +} + +function onPointerDown(event) { + if (!state.surfaceMesh) return; + const rect = renderer.domElement.getBoundingClientRect(); + pointer.x = ((event.clientX - rect.left) / rect.width) * 2 - 1; + pointer.y = -((event.clientY - rect.top) / rect.height) * 2 + 1; + raycaster.setFromCamera(pointer, camera); + const hit = raycaster.intersectObject(state.surfaceMesh, false)[0]; + if (!hit) return; + const point = hit.point.clone(); + if (state.mode === "vertex") { + state.vertexPositions.set(state.selectedVertex, point); + setStatus(`Placed vertex ${state.selectedVertex}.`); + } else { + const route = state.edgeRoutes.get(state.selectedEdge) || []; + route.push(point); + state.edgeRoutes.set(state.selectedEdge, route); + setStatus(`Added route point ${route.length} for edge ${state.selectedEdge}.`); + } + drawManualOverlay(); +} + +function drawManualOverlay() { + clearGroup(state.manualGroup); + const vertexMaterial = new THREE.MeshBasicMaterial({ + color: 0xf5f5f0, + depthTest: true, + depthWrite: true, + }); + const vertexRingMaterial = new THREE.MeshBasicMaterial({ + color: 0x111111, + depthTest: true, + depthWrite: true, + }); + const routeMaterial = new THREE.MeshBasicMaterial({ + color: 0x0867d8, + depthTest: true, + depthWrite: true, + }); + const vertexRadius = Math.max(state.radius * 0.018, 0.03); + const routeRadius = Math.max(state.radius * 0.006, 0.01); + + for (const [vertex, position] of state.vertexPositions.entries()) { + const dot = new THREE.Mesh(new THREE.SphereGeometry(vertexRadius, 18, 12), vertexMaterial); + dot.position.copy(position); + state.manualGroup.add(dot); + const ring = new THREE.Mesh(new THREE.SphereGeometry(vertexRadius * 1.08, 18, 12), vertexRingMaterial); + ring.material.side = THREE.BackSide; + ring.position.copy(position); + state.manualGroup.add(ring); + const label = makeTextSprite(String(vertex), vertexRadius * 4.2); + label.position.copy(position).addScaledVector(normalAtPoint(position), vertexRadius * 2.4); + state.manualGroup.add(label); + } + + for (const [a, b] of EDGES) { + const start = state.vertexPositions.get(a); + const end = state.vertexPositions.get(b); + const controls = state.edgeRoutes.get(edgeKey(a, b)) || []; + if (!start || !end) continue; + const points = [start, ...controls, end].map((point) => point.clone()); + state.manualGroup.add(makeTube(points, routeRadius, routeMaterial, Math.max(8, points.length * 16))); + } + + state.manualGroup.userData.dispose = () => { + vertexMaterial.dispose(); + vertexRingMaterial.dispose(); + routeMaterial.dispose(); + }; +} + +function smoothSelectedEdge() { + const [a, b] = state.selectedEdge.split("-").map(Number); + const start = state.vertexPositions.get(a); + const end = state.vertexPositions.get(b); + if (!start || !end) { + setStatus(`Place both endpoints for edge ${state.selectedEdge} before smoothing.`); + return; + } + if (state.surfaceTriangles.length === 0) { + setStatus("Load the surface before smoothing an edge."); + return; + } + + const controls = state.edgeRoutes.get(state.selectedEdge) || []; + const basePoints = [start, ...controls, end].map((point) => point.clone()); + const controlLength = polylineLength(basePoints); + if (controlLength < 1e-8) { + setStatus(`Edge ${state.selectedEdge} is too short to smooth.`); + return; + } + + const curve = new THREE.CatmullRomCurve3(basePoints, false, "centripetal", 0.35); + const sampleCount = Math.min(80, Math.max(18, Math.ceil(controlLength / Math.max(state.radius * 0.08, 0.04)))); + const projected = []; + for (let i = 1; i < sampleCount; i++) { + const sample = curve.getPoint(i / sampleCount); + projected.push(projectToSurface(sample).point); + } + state.edgeRoutes.set(state.selectedEdge, projected); + drawManualOverlay(); + setStatus(`Smoothed and projected ${state.selectedEdge} into ${projected.length + 2} surface samples.`); +} + +function verifyOrientations() { + const rotation = currentRotation(); + const missing = []; + const reversed = []; + const mismatches = []; + for (let vertex = 0; vertex < rotation.length; vertex++) { + const placed = state.vertexPositions.get(vertex); + if (!placed) { + missing.push(`vertex ${vertex}`); + continue; + } + const exits = []; + for (const neighbor of rotation[vertex]) { + const exit = exitPointFor(vertex, neighbor); + if (!exit) { + missing.push(`edge ${edgeKey(vertex, neighbor)} near ${vertex}`); + continue; + } + exits.push({ neighbor, point: exit }); + } + if (exits.length !== rotation[vertex].length) continue; + + const normal = normalAtPoint(placed); + const frame = tangentFrame(normal); + const actual = exits + .map(({ neighbor, point }) => { + const tangentVector = point.clone().sub(placed); + tangentVector.addScaledVector(normal, -tangentVector.dot(normal)); + return { + neighbor, + angle: Math.atan2(tangentVector.dot(frame.bitangent), tangentVector.dot(frame.tangent)), + lengthSq: tangentVector.lengthSq(), + }; + }) + .filter((item) => item.lengthSq > 1e-10) + .sort((a, b) => a.angle - b.angle) + .map((item) => item.neighbor); + + if (actual.length !== rotation[vertex].length) { + missing.push(`distinct exits at ${vertex}`); + } else if (cyclicOrderEqual(actual, rotation[vertex])) { + continue; + } else if (cyclicOrderEqual([...actual].reverse(), rotation[vertex])) { + reversed.push(`${vertex}: (${actual.join(", ")})`); + } else { + mismatches.push(`${vertex}: got (${actual.join(", ")}), expected (${rotation[vertex].join(", ")})`); + } + } + + const problems = []; + if (missing.length) problems.push(`Missing: ${missing.join("; ")}.`); + if (reversed.length) problems.push(`Reversed orientation: ${reversed.join("; ")}.`); + if (mismatches.length) problems.push(`Mismatched order: ${mismatches.join("; ")}.`); + if (problems.length === 0) { + el.verifyResult.textContent = "All placed edge exits match the representative cyclic order."; + el.verifyResult.className = "verify-result ok"; + } else { + el.verifyResult.textContent = problems.join(" "); + el.verifyResult.className = "verify-result warn"; + } +} + +function exitPointFor(vertex, neighbor) { + const start = state.vertexPositions.get(vertex); + const end = state.vertexPositions.get(neighbor); + if (!start || !end) return null; + const key = edgeKey(vertex, neighbor); + const controls = state.edgeRoutes.get(key) || []; + const path = vertex < neighbor ? [start, ...controls, end] : [end, ...controls, start]; + const oriented = vertex < neighbor ? path : [...path].reverse(); + for (let i = 1; i < oriented.length; i++) { + if (oriented[i].distanceToSquared(start) > 1e-10) return oriented[i]; + } + return null; +} + +function cyclicOrderEqual(actual, expected) { + if (actual.length !== expected.length) return false; + return expected.some((_, shift) => actual.every((value, index) => value === expected[(index + shift) % expected.length])); +} + +function tangentFrame(normal) { + const reference = Math.abs(normal.z) < 0.85 ? new THREE.Vector3(0, 0, 1) : new THREE.Vector3(1, 0, 0); + const tangent = reference.cross(normal).normalize(); + const bitangent = normal.clone().cross(tangent).normalize(); + return { tangent, bitangent }; +} + +function normalAtPoint(point) { + return projectToSurface(point).normal; +} + +function saveLayout() { + const payload = exportLayout(); + localStorage.setItem(storageKey(), JSON.stringify(payload)); + el.layoutJson.value = JSON.stringify(payload, null, 2); + setStatus("Saved this layout locally."); +} + +async function copyLayout() { + const payload = JSON.stringify(exportLayout(), null, 2); + el.layoutJson.value = payload; + try { + await navigator.clipboard.writeText(payload); + setStatus("Copied layout JSON."); + } catch { + setStatus("Layout JSON is ready in the text box."); + } +} + +function applyLayout() { + try { + importLayout(JSON.parse(el.layoutJson.value)); + localStorage.setItem(storageKey(), JSON.stringify(exportLayout())); + drawManualOverlay(); + setStatus("Applied layout JSON."); + } catch (error) { + setStatus(`Could not apply JSON: ${error.message}`); + } +} + +function loadSavedLayout() { + const saved = localStorage.getItem(storageKey()); + if (!saved) return; + try { + importLayout(JSON.parse(saved)); + el.layoutJson.value = JSON.stringify(exportLayout(), null, 2); + } catch { + localStorage.removeItem(storageKey()); + } +} + +function exportLayout() { + return { + representative: Number(el.representative.value || 0), + mask: REPRESENTATIVES[Number(el.representative.value || 0)].mask, + vertices: Object.fromEntries([...state.vertexPositions.entries()].map(([vertex, point]) => [vertex, vectorToArray(point)])), + edges: Object.fromEntries([...state.edgeRoutes.entries()].map(([edge, points]) => [edge, points.map(vectorToArray)])), + }; +} + +function importLayout(layout) { + state.vertexPositions = new Map(); + state.edgeRoutes = new Map(); + Object.entries(layout.vertices || {}).forEach(([vertex, value]) => { + state.vertexPositions.set(Number(vertex), arrayToVector(value)); + }); + Object.entries(layout.edges || {}).forEach(([edge, points]) => { + state.edgeRoutes.set(edge, points.map(arrayToVector)); + }); +} + +function storageKey() { + return `k33-genus2-manual-${el.representative.value || 0}`; +} + +function currentRotation() { + return rotationFromMask(REPRESENTATIVES[Number(el.representative.value || 0)].mask); +} + +function rotationFromMask(mask) { + return K33_BASE.map((neighbors, vertex) => { + const ordered = [neighbors[0], neighbors[1], neighbors[2]]; + return ((mask >> vertex) & 1) ? [ordered[0], ordered[2], ordered[1]] : ordered; + }); +} + +function parseObj(objText) { + const vertices = [new THREE.Vector3()]; + const positions = []; + const texcoords = []; + const indices = []; + const graphLines = []; + const cornerIndices = new Map(); + const uvs = [[0, 0]]; + + const addCorner = (token) => { + const [vertexToken, textureToken] = token.split("/"); + const vertexIndex = Number(vertexToken); + const textureIndex = textureToken ? Number(textureToken) : 0; + const key = `${vertexIndex}/${textureIndex}`; + if (cornerIndices.has(key)) return cornerIndices.get(key); + const vertex = vertices[vertexIndex]; + const uv = uvs[textureIndex] || [0, 0]; + const index = positions.length / 3; + positions.push(vertex.x, vertex.y, vertex.z); + texcoords.push(uv[0], uv[1]); + cornerIndices.set(key, index); + return index; + }; + + for (const rawLine of objText.split(/\r?\n/)) { + const line = rawLine.trim(); + if (line === "" || line.startsWith("#")) continue; + const parts = line.split(/\s+/); + if (parts[0] === "v") { + vertices.push(new THREE.Vector3(Number(parts[1]), Number(parts[2]), Number(parts[3]))); + } else if (parts[0] === "vt") { + uvs.push([Number(parts[1]), Number(parts[2])]); + } else if (parts[0] === "f") { + const face = parts.slice(1).map(addCorner); + for (let i = 1; i < face.length - 1; i++) indices.push(face[0], face[i], face[i + 1]); + } else if (parts[0] === "l") { + const points = parts.slice(1).map((token) => vertices[Number(token.split("/")[0])]).filter(Boolean); + if (points.length >= 2) graphLines.push({ points }); + } + } + + const geometry = new THREE.BufferGeometry(); + geometry.setAttribute("position", new THREE.Float32BufferAttribute(positions, 3)); + geometry.setAttribute("uv", new THREE.Float32BufferAttribute(texcoords, 2)); + geometry.setIndex(indices); + geometry.computeVertexNormals(); + geometry.normalizeNormals(); + return { geometry, graphLines }; +} + +function buildSurfaceTriangles(geometry) { + const positions = geometry.getAttribute("position"); + const index = geometry.index; + const triangles = []; + const a = new THREE.Vector3(); + const b = new THREE.Vector3(); + const c = new THREE.Vector3(); + const normal = new THREE.Vector3(); + const ab = new THREE.Vector3(); + const ac = new THREE.Vector3(); + const faceCount = index ? index.count / 3 : positions.count / 3; + + for (let face = 0; face < faceCount; face++) { + const i0 = index ? index.getX(face * 3) : face * 3; + const i1 = index ? index.getX(face * 3 + 1) : face * 3 + 1; + const i2 = index ? index.getX(face * 3 + 2) : face * 3 + 2; + a.fromBufferAttribute(positions, i0); + b.fromBufferAttribute(positions, i1); + c.fromBufferAttribute(positions, i2); + ab.subVectors(b, a); + ac.subVectors(c, a); + normal.crossVectors(ab, ac); + if (normal.lengthSq() < 1e-14) continue; + triangles.push({ + a: a.clone(), + b: b.clone(), + c: c.clone(), + normal: normal.normalize().clone(), + }); + } + return triangles; +} + +function projectToSurface(point) { + const closest = new THREE.Vector3(); + const candidate = new THREE.Vector3(); + let bestDistanceSq = Infinity; + let bestNormal = new THREE.Vector3(0, 0, 1); + for (const triangle of state.surfaceTriangles) { + closestPointOnTriangle(point, triangle.a, triangle.b, triangle.c, candidate); + const distanceSq = point.distanceToSquared(candidate); + if (distanceSq < bestDistanceSq) { + bestDistanceSq = distanceSq; + closest.copy(candidate); + bestNormal = triangle.normal; + } + } + if (!Number.isFinite(bestDistanceSq)) return { point: point.clone(), normal: bestNormal.clone(), distanceSq: Infinity }; + return { point: closest, normal: bestNormal.clone(), distanceSq: bestDistanceSq }; +} + +function closestPointOnTriangle(point, a, b, c, target) { + const { ab, ac, ap, bp, cp, bc } = triangleScratch; + ab.subVectors(b, a); + ac.subVectors(c, a); + ap.subVectors(point, a); + const d1 = ab.dot(ap); + const d2 = ac.dot(ap); + if (d1 <= 0 && d2 <= 0) return target.copy(a); + + bp.subVectors(point, b); + const d3 = ab.dot(bp); + const d4 = ac.dot(bp); + if (d3 >= 0 && d4 <= d3) return target.copy(b); + + const vc = d1 * d4 - d3 * d2; + if (vc <= 0 && d1 >= 0 && d3 <= 0) { + const v = d1 / (d1 - d3); + return target.copy(a).addScaledVector(ab, v); + } + + cp.subVectors(point, c); + const d5 = ab.dot(cp); + const d6 = ac.dot(cp); + if (d6 >= 0 && d5 <= d6) return target.copy(c); + + const vb = d5 * d2 - d1 * d6; + if (vb <= 0 && d2 >= 0 && d6 <= 0) { + const w = d2 / (d2 - d6); + return target.copy(a).addScaledVector(ac, w); + } + + const va = d3 * d6 - d5 * d4; + if (va <= 0 && d4 - d3 >= 0 && d5 - d6 >= 0) { + const w = (d4 - d3) / (d4 - d3 + d5 - d6); + bc.subVectors(c, b); + return target.copy(b).addScaledVector(bc, w); + } + + const denom = 1 / (va + vb + vc); + const v = vb * denom; + const w = vc * denom; + return target.copy(a).addScaledVector(ab, v).addScaledVector(ac, w); +} + +function makeTube(points, radius, material, segments = 32) { + const clean = points.filter(Boolean).map((point) => point.clone()); + if (clean.length < 2) return new THREE.Mesh(new THREE.SphereGeometry(radius, 8, 6), material); + const path = new THREE.CurvePath(); + for (let i = 0; i < clean.length - 1; i++) { + if (clean[i].distanceToSquared(clean[i + 1]) > 1e-10) path.add(new THREE.LineCurve3(clean[i], clean[i + 1])); + } + if (path.curves.length === 0) return new THREE.Mesh(new THREE.SphereGeometry(radius, 8, 6), material); + return new THREE.Mesh(new THREE.TubeGeometry(path, Math.max(1, segments), radius, 6, false), material); +} + +function polylineLength(points) { + let total = 0; + for (let i = 0; i < points.length - 1; i++) total += points[i].distanceTo(points[i + 1]); + return total; +} + +function makeTextSprite(text, size) { + const canvas = document.createElement("canvas"); + const context = canvas.getContext("2d"); + const fontSize = 44; + const padding = 14; + context.font = `800 ${fontSize}px system-ui, sans-serif`; + const metrics = context.measureText(text); + canvas.width = Math.ceil(metrics.width + padding * 2); + canvas.height = fontSize + padding * 2; + context.font = `800 ${fontSize}px system-ui, sans-serif`; + context.textBaseline = "middle"; + context.lineWidth = 8; + context.strokeStyle = "rgba(247, 247, 244, 0.96)"; + context.fillStyle = "#111"; + context.strokeText(text, padding, canvas.height / 2); + context.fillText(text, padding, canvas.height / 2); + const texture = new THREE.CanvasTexture(canvas); + texture.colorSpace = THREE.SRGBColorSpace; + const material = new THREE.SpriteMaterial({ map: texture, transparent: true, depthTest: true, depthWrite: false }); + const sprite = new THREE.Sprite(material); + sprite.scale.set(size * (canvas.width / canvas.height), size, 1); + sprite.userData.dispose = () => { + texture.dispose(); + material.dispose(); + }; + return sprite; +} + +function clearGroup(group) { + group.userData.dispose?.(); + delete group.userData.dispose; + while (group.children.length) disposeObject(group.children.pop()); +} + +function disposeObject(object) { + object.traverse?.((child) => { + if (child.geometry) child.geometry.dispose(); + if (child.material) { + const materials = Array.isArray(child.material) ? child.material : [child.material]; + materials.forEach((material) => { + if (material.map) material.map.dispose(); + material.dispose(); + }); + } + if (child.userData?.dispose && child !== 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rgba(251, 251, 248, 0.88); + --panel-strong: rgba(255, 255, 252, 0.95); + --border: rgba(32, 38, 46, 0.16); + --blue: #0867d8; + --blue-soft: rgba(8, 103, 216, 0.13); + --amber: #b46a00; + --green: #237052; + --surface: #f5f5f0; +} + +* { + box-sizing: border-box; +} + +html, +body { + margin: 0; + min-height: 100%; + font-family: Inter, ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif; + color: var(--ink); + background: var(--surface); +} + +button, +input { + font: inherit; +} + +.app-shell { + min-height: 100vh; +} + +.stage { + position: relative; + min-height: 100vh; + overflow: hidden; + background: + linear-gradient(180deg, rgba(255, 255, 255, 0.74), rgba(244, 245, 241, 0.92)), + radial-gradient(circle at 18% 14%, rgba(8, 103, 216, 0.10), transparent 34%), + radial-gradient(circle at 72% 78%, rgba(35, 112, 82, 0.09), transparent 30%), + #f7f7f3; +} + +.viewer { + position: absolute; + inset: 0; +} + +.viewer canvas { + display: block; + width: 100%; + height: 100%; +} + +.mobile-panel { + display: contents; +} + +.topbar { + position: absolute; + top: 18px; + left: 18px; + display: flex; + align-items: flex-start; + gap: 12px; + z-index: 5; + max-width: min(58vw, 760px); +} + +.action-stack { + display: grid; + gap: 8px; +} + +.primary-action { + border: 1px solid rgba(5, 73, 154, 0.18); + border-radius: 8px; + background: #095fc4; + color: #fff; + min-height: 42px; + padding: 0 18px; + box-shadow: 0 8px 28px rgba(17, 68, 125, 0.19); + cursor: pointer; +} + +.primary-action:disabled { + cursor: default; + background: #7b8490; + box-shadow: none; +} + +.playback-controls { + display: flex; + gap: 7px; +} + +.playback-button { + width: 34px; + height: 34px; + display: inline-flex; + align-items: center; + justify-content: center; + border: 2px solid rgba(95, 102, 113, 0.55); + border-radius: 999px; + background: transparent; + color: #646b75; + cursor: pointer; +} + +.playback-button svg { + width: 18px; + height: 18px; + display: block; + fill: none; + stroke: currentColor; + stroke-width: 2; + stroke-linecap: round; + stroke-linejoin: round; +} + +.playback-button:hover, +.playback-button:focus-visible { + outline: none; + color: var(--ink); + border-color: rgba(95, 102, 113, 0.86); + background: rgba(255, 255, 255, 0.44); +} + +.playback-button:disabled { + cursor: default; + opacity: 0.42; +} + +.status { + min-height: 42px; + display: flex; + align-items: center; + padding: 8px 12px; + border: 1px solid var(--border); + border-radius: 8px; + color: var(--muted); + background: var(--panel); + backdrop-filter: blur(14px); +} + +.status:empty { + display: none; +} + +.side-stack { + position: absolute; + top: 18px; + right: 18px; + z-index: 5; + width: 230px; + max-width: calc(100vw - 36px); + display: grid; + gap: 10px; +} + +.rotation-panel, +.explanation-card { + padding: 14px; + border: 1px solid var(--border); + border-radius: 8px; + background: var(--panel-strong); + box-shadow: 0 12px 34px rgba(30, 36, 43, 0.14); + backdrop-filter: blur(16px); +} + +.explanation-card { + color: var(--muted); + font-size: 13px; + line-height: 1.45; +} + +.explanation-card p { + margin: 0; +} + +.panel-title { + display: flex; + align-items: center; + justify-content: space-between; + gap: 10px; + margin-bottom: 10px; + font-size: 14px; + font-weight: 700; +} + +.genus-badge { + flex: 0 0 auto; + border-radius: 999px; + padding: 4px 8px; + color: #0f5138; + background: rgba(35, 112, 82, 0.12); + font-size: 12px; +} + +.rotation-list { + display: grid; + gap: 6px; +} + +.rotation-row { + width: 100%; + display: grid; + grid-template-columns: 34px 1fr; + align-items: center; + gap: 8px; + border: 1px solid rgba(32, 38, 46, 0.10); + border-radius: 8px; + padding: 7px 8px; + background: rgba(255, 255, 255, 0.74); + text-align: left; + color: var(--ink); + cursor: pointer; +} + +.rotation-row:hover, +.rotation-row:focus-visible { + outline: none; + border-color: rgba(8, 103, 216, 0.42); + background: rgba(255, 255, 255, 0.95); +} + +.rotation-row.active { + border-color: rgba(8, 103, 216, 0.54); + background: var(--blue-soft); +} + +.vertex-id { + display: inline-flex; + align-items: center; + justify-content: center; + width: 28px; + height: 28px; + border-radius: 50%; + background: #eef0ed; + font-weight: 800; +} + +.rotation-row.active .vertex-id { + color: #fff; + background: var(--blue); +} + +.neighbor-list { + display: flex; + align-items: center; + flex-wrap: wrap; + gap: 4px; + min-width: 0; + font-variant-numeric: tabular-nums; +} + +.neighbor-chip { + min-width: 26px; + border-radius: 999px; + padding: 3px 8px; + text-align: center; + background: #f2f3f0; + border: 1px solid rgba(32, 38, 46, 0.10); + font-weight: 700; +} + +.neighbor-chip.active { + color: #fff; + background: var(--blue); + border-color: var(--blue); +} + +.cycle-mark { + color: var(--muted); + font-weight: 650; +} + +.slider-panel { + position: absolute; + left: 50%; + bottom: 22px; + transform: translateX(-50%); + z-index: 5; + width: min(760px, calc(100vw - 36px)); + padding: 13px 16px 15px; + border: 1px solid var(--border); + border-radius: 8px; + background: var(--panel-strong); + box-shadow: 0 12px 34px rgba(30, 36, 43, 0.13); + backdrop-filter: blur(16px); +} + +.slider-label { + display: flex; + justify-content: space-between; + color: var(--muted); + font-size: 13px; + font-weight: 700; + margin-bottom: 8px; +} + +.slider-controls { + display: grid; + grid-template-columns: minmax(0, 1fr) 88px; + gap: 12px; + align-items: center; +} + +#rotation_slider { + width: 100%; + accent-color: var(--blue); +} + +.rotation-number { + width: 88px; + min-height: 34px; + border: 1px solid rgba(32, 38, 46, 0.18); + border-radius: 8px; + padding: 0 8px; + color: var(--ink); + background: #fff; + font-weight: 750; + font-variant-numeric: tabular-nums; +} + +.rotation-number:focus { + outline: 2px solid rgba(8, 103, 216, 0.28); + outline-offset: 2px; +} + +.next-rotation-button { + display: none; +} + +@media (max-width: 760px) { + html, + body, + .app-shell { + height: 100%; + overflow: hidden; + } + + .stage { + height: 100dvh; + min-height: 100dvh; + overflow: hidden; + background: #f7f7f3; + } + + .viewer { + inset: 0 0 auto; + height: 50dvh; + } + + .mobile-panel { + position: absolute; + left: 0; + right: 0; + bottom: 0; + top: 50dvh; + z-index: 5; + display: block; + overflow-y: auto; + padding: 12px 12px calc(14px + env(safe-area-inset-bottom)); + background: rgba(245, 245, 240, 0.98); + -webkit-overflow-scrolling: touch; + } + + .topbar { + position: static; + max-width: none; + display: block; + margin: 0 0 10px; + } + + .action-stack { + display: grid; + grid-template-columns: minmax(0, 1fr) minmax(0, 1fr); + gap: 10px; + } + + .primary-action { + order: 2; + width: 100%; + min-height: 44px; + padding: 0 12px; + } + + .playback-controls { + order: 1; + display: grid; + grid-template-columns: repeat(2, minmax(0, 1fr)); + gap: 8px; + } + + #playback_start, + #playback_end { + display: none; + } + + .playback-button { + width: 100%; + height: 44px; + border-radius: 8px; + } + + .status { + display: none; + } + + .side-stack { + position: static; + width: auto; + max-width: none; + display: grid; + gap: 10px; + } + + .explanation-card { + order: 1; + } + + .rotation-panel { + order: 2; + } + + .rotation-panel, + .explanation-card, + .slider-panel { + box-shadow: none; + backdrop-filter: none; + } + + .slider-panel { + position: static; + transform: none; + width: auto; + margin-top: 10px; + padding: 0; + border: 0; + background: transparent; + } + + .slider-label, + .slider-controls { + display: none; + } + + .next-rotation-button { + width: 100%; + min-height: 44px; + display: inline-flex; + align-items: center; + justify-content: center; + border: 1px solid rgba(32, 38, 46, 0.16); + border-radius: 8px; + background: rgba(255, 255, 252, 0.95); + color: var(--ink); + font-weight: 800; + cursor: pointer; + } +} diff --git a/WebApp/static/k33_rotation_animation.html b/WebApp/static/k33_rotation_animation.html new file mode 100644 index 0000000..f891237 --- /dev/null +++ b/WebApp/static/k33_rotation_animation.html @@ -0,0 +1,88 @@ + + + + + + K3,3 Rotation Systems + + + + + + +
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+ + + + + diff --git a/WebApp/static/k33_rotation_animation.js b/WebApp/static/k33_rotation_animation.js new file mode 100644 index 0000000..60e9a8a --- /dev/null +++ b/WebApp/static/k33_rotation_animation.js @@ -0,0 +1,2078 @@ +import * as THREE from "three"; +import { OrbitControls } from "/vendor/OrbitControls.js"; + +const BLUE = 0x0867d8; +const BLACK = 0x151719; +const SURFACE = 0xc7cbc6; +const FACE_COLORS = [0x0a67c5, 0xb46a00, 0x237052, 0x7d4ac7, 0xbb3f4a, 0x47606f]; +const TRACED_FACES_CAMERA_POSITION = new THREE.Vector3(0, -5.85, 3.15); +const TRACED_FACES_CAMERA_TARGET = new THREE.Vector3(0, 0, 0.2); +const SURFACE_CAMERA_POSITION = new THREE.Vector3(0, -6.15, 2.95); +const SURFACE_CAMERA_TARGET = new THREE.Vector3(0, 0, 0); +const TORUS_GLUE_DURATION = 1280; +const TORUS_GLUE_HOLD = 620; +const GENUS2_REPRESENTATIVE_MASK = 1; +const GENUS2_MANUAL_LAYOUT_URL = "k33_genus2_manual_layout.json"; +const K33_BASE = [ + [3, 4, 5], + [3, 4, 5], + [3, 4, 5], + [0, 1, 2], + [0, 1, 2], + [0, 1, 2], +]; +const EDGES = []; +for (let left = 0; left < 3; left++) { + for (let right = 3; right < 6; right++) EDGES.push([left, right]); +} +const INTRO_EXPLANATION = "A rotation system defines a cyclic ordering of the incident edges (darts) for each vertex. Click each line to view."; +const START_TRACE_EXPLANATION = "We start by choosing an arbitrary dart."; +const FINISHED_FACE_EXPLANATION = "We have finished a face, so we choose an arbitrary unused dart."; +const ALL_DARTS_EXPLANATION = "We have used all the darts. Now we have the faces of a 3D surface which is formed by gluing the faces at matching edges."; +const FINAL_EXPLANATION = "In the final embedding, the cyclic ordering of the rotation system is oriented following the right-hand rule (counter-clockwise). Click each line to see."; + +const el = { + viewer: document.getElementById("viewer"), + showEmbedding: document.getElementById("show_embedding"), + status: document.getElementById("status"), + playbackStart: document.getElementById("playback_start"), + playbackBack: document.getElementById("playback_back"), + playbackForward: document.getElementById("playback_forward"), + playbackEnd: document.getElementById("playback_end"), + rotationTitle: document.getElementById("rotation_title"), + genusBadge: document.getElementById("genus_badge"), + rotationList: document.getElementById("rotation_list"), + explanationText: document.getElementById("explanation_text"), + slider: document.getElementById("rotation_slider"), + rotationNumber: document.getElementById("rotation_number"), + sliderLabel: document.getElementById("slider_label"), + nextRotation: document.getElementById("next_rotation"), +}; + +const systems = makeRotationSystems(); +const modelCache = new Map(); +const k33Automorphisms = makeK33Automorphisms(); +let genusTwoManualLayoutPromise = null; +let genusTwoRawModelPromise = null; +let genusTwoBaseRenderDataPromise = null; +const mobileQuery = window.matchMedia("(max-width: 760px)"); +const state = { + index: 0, + phase: "flat", + sequenceToken: 0, + animationToken: 0, + manualMode: false, + manualStep: -1, + cameraToken: 0, + modelGroup: null, + flatGroup: null, + faceGroup: new THREE.Group(), + traceGroup: new THREE.Group(), + highlightGroup: new THREE.Group(), + vertexHighlightGroup: new THREE.Group(), + arrowGroup: new THREE.Group(), + surfacePaths: new Map(), + surfaceVertices: new Map(), + surfaceCenter: new THREE.Vector3(), + surfaceNormalAt: null, + surfaceStrokeRadius: 0.006, + finalOpacity: null, +}; + +const renderer = new THREE.WebGLRenderer({ antialias: true }); +renderer.setPixelRatio(Math.min(window.devicePixelRatio, 2)); +renderer.outputColorSpace = THREE.SRGBColorSpace; +el.viewer.appendChild(renderer.domElement); + +const scene = new THREE.Scene(); +scene.background = new THREE.Color(0xf7f7f3); +const camera = new THREE.PerspectiveCamera(42, 1, 0.01, 100); +camera.position.set(0, 0, 6.8); +const controls = new OrbitControls(camera, renderer.domElement); +controls.enableDamping = true; +controls.enableRotate = false; +controls.enablePan = false; +controls.target.set(0, 0, 0); + +scene.add(new THREE.HemisphereLight(0xffffff, 0x8b8d88, 2.15)); +const key = new THREE.DirectionalLight(0xffffff, 1.8); +key.position.set(4, -5, 7); +scene.add(key); +scene.add(state.faceGroup); +scene.add(state.traceGroup); +scene.add(state.highlightGroup); +scene.add(state.vertexHighlightGroup); +scene.add(state.arrowGroup); + +const resizeObserver = new ResizeObserver(resize); +resizeObserver.observe(el.viewer); +resize(); +setRotation(0); +animate(); +prefetchGenusTwo(); +setTimeout(prefetchNearby, 750); + +el.slider.addEventListener("input", () => setRotation(Number(el.slider.value))); +el.rotationNumber.addEventListener("input", () => { + const value = Number(el.rotationNumber.value); + if (Number.isInteger(value) && value >= 1 && value <= systems.length) { + setRotation(value - 1); + } +}); +el.rotationNumber.addEventListener("change", () => { + const value = clampRotationNumber(el.rotationNumber.value); + el.rotationNumber.value = String(value); + if (value !== state.index + 1) setRotation(value - 1); +}); +el.showEmbedding.addEventListener("click", showEmbedding); +el.playbackStart.addEventListener("click", () => usePlayback("start")); +el.playbackBack.addEventListener("click", () => usePlayback("back")); +el.playbackForward.addEventListener("click", () => usePlayback("forward")); +el.playbackEnd.addEventListener("click", () => usePlayback("end")); +el.nextRotation.addEventListener("click", () => setRotation((state.index + 1) % systems.length)); +mobileQuery.addEventListener("change", () => setShowEmbeddingLabel(currentSystem())); + +function makeRotationSystems() { + const all = []; + for (let mask = 0; mask < 64; mask++) { + const rotation = rotationFromMask(mask); + const faces = computeFaces(rotation); + all.push({ index: mask, rotation, faces, genus: genusFromFaces(rotation, faces) }); + } + return all; +} + +function rotationFromMask(mask) { + return K33_BASE.map((neighbors, vertex) => { + const ordered = [neighbors[0], neighbors[1], neighbors[2]]; + if ((mask >> vertex) & 1) return [ordered[0], ordered[2], ordered[1]]; + return ordered; + }); +} + +function computeFaces(rotation) { + const darts = []; + const next = new Map(); + rotation.forEach((neighbors, vertex) => { + neighbors.forEach((neighbor) => darts.push(dartKey(vertex, neighbor))); + neighbors.forEach((incoming, index) => { + const outgoing = neighbors[(index + 1) % neighbors.length]; + next.set(dartKey(incoming, vertex), [vertex, outgoing]); + }); + }); + + const visited = new Set(); + const faces = []; + for (const startKey of darts) { + if (visited.has(startKey)) continue; + const face = []; + let [from, to] = startKey.split("-").map(Number); + while (!visited.has(dartKey(from, to))) { + visited.add(dartKey(from, to)); + face.push({ from, to }); + [from, to] = next.get(dartKey(from, to)); + } + faces.push(face); + } + return faces; +} + +function genusFromFaces(rotation, faces) { + const vertices = rotation.length; + const edges = rotation.reduce((sum, neighbors) => sum + neighbors.length, 0) / 2; + return (2 - (vertices - edges + faces.length)) / 2; +} + +function setRotation(index) { + state.animationToken++; + state.sequenceToken++; + state.index = index; + state.manualMode = false; + state.manualStep = -1; + + const system = currentSystem(); + el.slider.value = String(index); + el.rotationTitle.textContent = `Rotation ${index + 1} / 64`; + el.genusBadge.textContent = `genus ${system.genus}`; + el.sliderLabel.textContent = `Rotation ${index + 1} of 64`; + el.rotationNumber.value = String(index + 1); + setShowEmbeddingLabel(system); + el.showEmbedding.disabled = false; + el.status.textContent = ""; + setExplanation(INTRO_EXPLANATION); + buildRotationList(system); + resetToFlatScene(); +} + +function currentSystem() { + return systems[state.index]; +} + +function setExplanation(text) { + el.explanationText.textContent = text; +} + +function setShowEmbeddingLabel(system) { + el.showEmbedding.textContent = mobileQuery.matches ? "Embed" : `Show Genus ${system.genus} Embedding`; +} + +function rotationOrderText(order) { + return `(${order.join(", ")})`; +} + +function vertexRotationExplanation(system, vertex) { + return `The local rotation at vertex ${vertex} has cyclic ordering ${rotationOrderText(system.rotation[vertex])}.`; +} + +function nextAfterIncoming(system, vertex, incoming) { + const rotation = system.rotation[vertex]; + const index = rotation.indexOf(incoming); + if (index === -1) return rotation[0]; + return rotation[(index + 1) % rotation.length]; +} + +function traceStepExplanation(system, step) { + if (step <= 0) return START_TRACE_EXPLANATION; + step -= 1; + const timeline = traceTimeline(system); + const current = timeline[step]; + if (!current) return ALL_DARTS_EXPLANATION; + const face = system.faces[current.faceIndex]; + const isLastDartInFace = current.dartIndex === face.length - 1; + const isLastDartOverall = step === timeline.length - 1; + if (isLastDartInFace && !isLastDartOverall) return FINISHED_FACE_EXPLANATION; + const x = current.dart.to; + const y = current.dart.from; + const z = nextAfterIncoming(system, x, y); + return `We entered ${x} from ${y} so the next vertex after ${y} in ${x}'s local rotation is ${z}.`; +} + +function buildRotationList(system) { + el.rotationList.replaceChildren(); + system.rotation.forEach((neighbors, vertex) => { + const row = document.createElement("button"); + row.type = "button"; + row.className = "rotation-row"; + row.dataset.vertex = String(vertex); + row.innerHTML = ` + ${vertex} + + ( + ${neighbors.map((neighbor) => `${neighbor}`).join("")} + ) + + `; + row.addEventListener("click", () => playVertexRotation(vertex)); + el.rotationList.appendChild(row); + }); +} + +function flatPosition(vertex) { + const y = [1.35, 0, -1.35][vertex % 3]; + const x = vertex < 3 ? -1.72 : 1.72; + return new THREE.Vector3(x, y, 0); +} + +function buildFlatGraph() { + if (state.flatGroup) { + disposeGroup(state.flatGroup); + scene.remove(state.flatGroup); + } + const group = new THREE.Group(); + const edgeMaterial = makeBasicMaterial(BLACK, 0.88); + const pointMaterial = makeBasicMaterial(0xf4f4ef, 1); + const pointRingMaterial = makeBasicMaterial(BLACK, 1); + + for (const [a, b] of EDGES) { + const points = [flatPosition(a), flatPosition(b)]; + const tube = makeTube(points, 0.014, edgeMaterial, 24); + tube.userData.edge = edgeKey(a, b); + group.add(tube); + } + + for (let vertex = 0; vertex < 6; vertex++) { + const p = flatPosition(vertex); + const dot = new THREE.Mesh(new THREE.SphereGeometry(0.075, 24, 16), pointMaterial); + dot.position.copy(p); + group.add(dot); + const ring = new THREE.Mesh(new THREE.SphereGeometry(0.082, 24, 12), pointRingMaterial); + ring.position.copy(p); + ring.scale.setScalar(1.02); + ring.material.side = THREE.BackSide; + group.add(ring); + const label = makeTextSprite(String(vertex), 0.22, { depthTest: false }); + label.position.copy(p).add(new THREE.Vector3(vertex < 3 ? -0.2 : 0.2, 0.12, 0.04)); + group.add(label); + } + + group.userData.dispose = () => { + edgeMaterial.dispose(); + pointMaterial.dispose(); + pointRingMaterial.dispose(); + disposeGroupChildren(group); + }; + state.flatGroup = group; + scene.add(group); +} + +function setCameraFlat() { + controls.enableRotate = false; + controls.enablePan = false; + animateCamera(new THREE.Vector3(0, 0, 6.8), new THREE.Vector3(0, 0, 0), 360); +} + +function resetToFlatScene() { + state.phase = "flat"; + clearGroup(state.highlightGroup); + clearGroup(state.traceGroup); + clearGroup(state.vertexHighlightGroup); + clearGroup(state.arrowGroup); + clearGroup(state.faceGroup); + disposeModelGroup(); + clearActiveList(); + buildFlatGraph(); + setGroupOpacity(state.flatGroup, 1); + setCameraFlat(); +} + +async function playVertexRotation(vertex) { + const token = ++state.sequenceToken; + clearActiveList(); + clearGroup(state.vertexHighlightGroup); + highlightVertex(vertex); + const system = currentSystem(); + setExplanation(vertexRotationExplanation(system, vertex)); + const darts = system.rotation[vertex].map((to) => ({ from: vertex, to })); + if (state.phase === "surface") animateCounterclockwiseArrow(vertex, token); + + for (const dart of darts) { + if (token !== state.sequenceToken) return; + highlightDart(dart); + await delay(520); + } +} + +async function showEmbedding() { + const system = currentSystem(); + const token = ++state.animationToken; + state.sequenceToken++; + state.manualMode = false; + state.manualStep = -1; + resetToFlatScene(); + setExplanation(INTRO_EXPLANATION); + el.showEmbedding.disabled = true; + el.slider.disabled = true; + el.rotationNumber.disabled = true; + el.status.textContent = "Resetting view"; + await delay(360); + if (token !== state.animationToken) return; + state.phase = "tracing"; + el.status.textContent = "Tracing faces"; + clearGroup(state.highlightGroup); + clearGroup(state.traceGroup); + clearGroup(state.vertexHighlightGroup); + clearGroup(state.arrowGroup); + clearGroup(state.faceGroup); + if (state.modelGroup) disposeModelGroup(); + + let modelPromise = getModel(system); + await traceFaces(system, token); + if (token !== state.animationToken) return; + + setExplanation(ALL_DARTS_EXPLANATION); + el.status.textContent = "Showing traced faces"; + await Promise.all([ + animateCamera(TRACED_FACES_CAMERA_POSITION, TRACED_FACES_CAMERA_TARGET, 980), + morphTraceDartsToFaceCycles(system, token), + ]); + if (token !== state.animationToken) return; + + el.status.textContent = "Showing traced faces"; + await delay(1120); + if (token !== state.animationToken) return; + + el.status.textContent = "Gluing to the torus"; + const model = await modelPromise; + if (token !== state.animationToken) return; + const modelGroup = buildModelGroup(model); + state.modelGroup = modelGroup.group; + state.surfacePaths = modelGroup.pathsByEdge; + state.surfaceVertices = modelGroup.vertexPositions; + state.surfaceNormalAt = modelGroup.normalAt || torusNormal; + state.finalOpacity = modelGroup.setOpacity; + modelGroup.setOpacity(0); + scene.add(modelGroup.group); + + controls.enableRotate = true; + controls.enablePan = true; + await Promise.all([ + animateCamera(SURFACE_CAMERA_POSITION, SURFACE_CAMERA_TARGET, TORUS_GLUE_DURATION), + morphFaceCyclesToSurface(system, modelGroup, token), + ]); + if (token !== state.animationToken) return; + await delay(TORUS_GLUE_HOLD); + if (token !== state.animationToken) return; + await crossFadeToSurface(modelGroup.setOpacity, token); + if (token !== state.animationToken) return; + + state.phase = "surface"; + state.manualMode = false; + state.manualStep = traceTimeline(system).length + 1; + setExplanation(FINAL_EXPLANATION); + clearGroup(state.highlightGroup); + clearGroup(state.traceGroup); + clearGroup(state.vertexHighlightGroup); + clearActiveList(); + el.status.textContent = ""; + el.showEmbedding.disabled = false; + el.slider.disabled = false; + el.rotationNumber.disabled = false; +} + +async function usePlayback(action) { + const system = currentSystem(); + state.manualMode = true; + const token = ++state.animationToken; + state.sequenceToken++; + + const timeline = traceTimeline(system); + const finalStep = timeline.length + 1; + const current = state.phase === "surface" ? finalStep : state.manualStep; + let next = current; + + if (action === "start") next = -1; + else if (action === "back") next = Math.max(-1, current - 1); + else if (action === "forward") next = Math.min(finalStep, current + 1); + else if (action === "end") next = finalStep; + + await renderManualStep(system, next, token, { animateBoundary: action === "forward" }); +} + +async function renderManualStep(system, step, token, options = {}) { + const timeline = traceTimeline(system); + const facesStep = timeline.length; + const finalStep = timeline.length + 1; + const previousStep = state.phase === "surface" ? finalStep : state.manualStep; + state.manualStep = Math.max(-1, Math.min(finalStep, step)); + const animateBoundary = options.animateBoundary === true; + el.showEmbedding.disabled = false; + el.slider.disabled = state.manualStep > -1; + el.rotationNumber.disabled = state.manualStep > -1; + + if (state.manualStep === -1) { + state.manualMode = false; + resetToFlatScene(); + setExplanation(INTRO_EXPLANATION); + el.status.textContent = ""; + return; + } + + if (state.manualStep < facesStep) { + resetManualTraceScene(); + renderTracePrefix(system, state.manualStep); + const current = timeline[state.manualStep]; + setExplanation(traceStepExplanation(system, state.manualStep)); + el.status.textContent = `Tracing face ${current.faceIndex + 1} / ${system.faces.length}`; + return; + } + + if (state.manualStep === facesStep) { + resetManualTraceScene(); + if (animateBoundary && previousStep === facesStep - 1) { + renderTracePrefix(system, timeline.length - 1, { highlightCurrent: false }); + setExplanation(ALL_DARTS_EXPLANATION); + el.status.textContent = "Showing traced faces"; + await Promise.all([ + animateCamera(TRACED_FACES_CAMERA_POSITION, TRACED_FACES_CAMERA_TARGET, 980), + morphTraceDartsToFaceCycles(system, token), + ]); + return; + } + renderLiftedFaces(system); + setGroupOpacity(state.flatGroup, 0.18); + setCameraPose(TRACED_FACES_CAMERA_POSITION, TRACED_FACES_CAMERA_TARGET); + setExplanation(ALL_DARTS_EXPLANATION); + el.status.textContent = "Showing traced faces"; + return; + } + + if (animateBoundary && previousStep === facesStep) { + el.status.textContent = "Gluing to the torus"; + resetManualTraceScene(); + renderLiftedFaces(system); + setGroupOpacity(state.flatGroup, 0.18); + setCameraPose(TRACED_FACES_CAMERA_POSITION, TRACED_FACES_CAMERA_TARGET); + const model = await getModel(system); + if (token !== state.animationToken || !state.manualMode) return; + disposeModelGroup(); + const modelGroup = buildModelGroup(model); + state.modelGroup = modelGroup.group; + state.surfacePaths = modelGroup.pathsByEdge; + state.surfaceVertices = modelGroup.vertexPositions; + state.surfaceNormalAt = modelGroup.normalAt || torusNormal; + state.finalOpacity = modelGroup.setOpacity; + modelGroup.setOpacity(0); + scene.add(modelGroup.group); + state.phase = "surface"; + controls.enableRotate = true; + controls.enablePan = true; + await Promise.all([ + animateCamera(SURFACE_CAMERA_POSITION, SURFACE_CAMERA_TARGET, TORUS_GLUE_DURATION), + morphFaceCyclesToSurface(system, modelGroup, token), + ]); + if (token !== state.animationToken || !state.manualMode) return; + await delay(TORUS_GLUE_HOLD); + if (token !== state.animationToken || !state.manualMode) return; + await crossFadeToSurface(modelGroup.setOpacity, token); + if (token !== state.animationToken || !state.manualMode) return; + state.manualMode = false; + state.manualStep = finalStep; + setExplanation(FINAL_EXPLANATION); + clearActiveList(); + clearGroup(state.highlightGroup); + clearGroup(state.traceGroup); + clearGroup(state.vertexHighlightGroup); + el.status.textContent = ""; + el.showEmbedding.disabled = false; + el.slider.disabled = false; + el.rotationNumber.disabled = false; + return; + } + + el.status.textContent = "Loading final surface"; + resetManualTraceScene(); + setGroupOpacity(state.flatGroup, 0); + clearGroup(state.traceGroup); + clearGroup(state.faceGroup); + const model = await getModel(system); + if (token !== state.animationToken || !state.manualMode) return; + disposeModelGroup(); + const modelGroup = buildModelGroup(model); + state.modelGroup = modelGroup.group; + state.surfacePaths = modelGroup.pathsByEdge; + state.surfaceVertices = modelGroup.vertexPositions; + state.surfaceNormalAt = modelGroup.normalAt || torusNormal; + state.finalOpacity = modelGroup.setOpacity; + modelGroup.setOpacity(1, true); + scene.add(modelGroup.group); + state.phase = "surface"; + controls.enableRotate = true; + controls.enablePan = true; + setCameraPose(SURFACE_CAMERA_POSITION, SURFACE_CAMERA_TARGET); + clearActiveList(); + clearGroup(state.highlightGroup); + clearGroup(state.vertexHighlightGroup); + el.status.textContent = ""; + state.manualMode = false; + state.manualStep = finalStep; + setExplanation(FINAL_EXPLANATION); + el.showEmbedding.disabled = false; + el.slider.disabled = false; + el.rotationNumber.disabled = false; +} + +function resetManualTraceScene() { + state.phase = "tracing"; + clearGroup(state.highlightGroup); + clearGroup(state.traceGroup); + clearGroup(state.vertexHighlightGroup); + clearGroup(state.arrowGroup); + clearGroup(state.faceGroup); + disposeModelGroup(); + clearActiveList(); + buildFlatGraph(); + setGroupOpacity(state.flatGroup, 1); + controls.enableRotate = false; + controls.enablePan = false; + setCameraPose(new THREE.Vector3(0, 0, 6.8), new THREE.Vector3(0, 0, 0)); +} + +function clearTraceSelection() { + clearGroup(state.highlightGroup); + clearGroup(state.vertexHighlightGroup); + clearActiveList(); +} + +function renderTracePrefix(system, step, options = {}) { + const highlightCurrent = options.highlightCurrent ?? true; + const timeline = traceTimeline(system); + for (let i = 0; i <= step && i < timeline.length; i++) { + const item = timeline[i]; + addTraceDart(item.dart, FACE_COLORS[item.faceIndex % FACE_COLORS.length]); + } + const current = timeline[step]; + if (highlightCurrent && current) { + highlightDart(current.dart, FACE_COLORS[current.faceIndex % FACE_COLORS.length]); + } +} + +function renderLiftedFaces(system) { + addAllFaceCycles(system); + const faces = [...state.faceGroup.children]; + faces.forEach((face, index) => { + face.userData.setOpacity?.(1); + applyLiftedFacePose(face, index, system.faces.length, 1); + }); + clearTraceSelection(); +} + +function addAllFaceCycles(system) { + for (let faceIndex = 0; faceIndex < system.faces.length; faceIndex++) { + addFaceCycle(system.faces[faceIndex], faceIndex, system.faces.length); + } +} + +function traceTimeline(system) { + const timeline = []; + system.faces.forEach((face, faceIndex) => { + face.forEach((dart, dartIndex) => { + timeline.push({ dart, faceIndex, dartIndex }); + }); + }); + return timeline; +} + +async function traceFaces(system, token) { + let step = -1; + for (let faceIndex = 0; faceIndex < system.faces.length; faceIndex++) { + const face = system.faces[faceIndex]; + if (token !== state.animationToken) return; + if (faceIndex === 0) setExplanation(START_TRACE_EXPLANATION); + el.status.textContent = `Tracing face ${faceIndex + 1} / ${system.faces.length}`; + for (const dart of face) { + step += 1; + if (token !== state.animationToken) return; + state.manualStep = step; + if (step > 0) setExplanation(traceStepExplanation(system, step)); + addTraceDart(dart, FACE_COLORS[faceIndex % FACE_COLORS.length]); + highlightDart(dart, FACE_COLORS[faceIndex % FACE_COLORS.length]); + await delay(620); + } + addFaceCycle(face, faceIndex, system.faces.length); + if (faceIndex < system.faces.length - 1) { + setExplanation(FINISHED_FACE_EXPLANATION); + } else { + setExplanation(ALL_DARTS_EXPLANATION); + } + await delay(290); + } +} + +function addFaceCycle(face, faceIndex, totalFaces) { + const group = new THREE.Group(); + group.userData.baseOpacity = 0; + const color = FACE_COLORS[faceIndex % FACE_COLORS.length]; + const material = makeBasicMaterial(color, 0); + const pointMaterial = makeBasicMaterial(0xffffff, 0); + const layout = faceCycleLayout(face, faceIndex, totalFaces); + const points = layout.points; + const tube = makeTube(points, 0.013, material, face.length * 12); + tube.renderOrder = 20; + group.add(tube); + + for (let i = 0; i < face.length; i++) { + const arrowFrom = new THREE.Vector3().lerpVectors(points[i], points[i + 1], 0.80); + const arrowTo = new THREE.Vector3().lerpVectors(points[i], points[i + 1], 0.96); + group.add(makeArrowHead(arrowFrom, arrowTo, color, 0.03, 0.074, { + depthTest: true, + renderOrder: 22, + opacity: 0, + tipAtTarget: true, + })); + } + + for (let i = 0; i < face.length; i++) { + const pos = points[i].clone(); + const dot = new THREE.Mesh(new THREE.SphereGeometry(0.035, 16, 10), pointMaterial); + dot.position.copy(pos); + dot.renderOrder = 30; + group.add(dot); + const label = makeTextSprite(`${face[i].from}`, 0.13, { depthTest: false, opacity: 0 }); + label.position.copy(pos).add(new THREE.Vector3(0.06, -0.05, 0.05)); + group.add(label); + } + + group.userData.setOpacity = (opacity) => { + group.traverse((child) => { + if (child.material) { + const materials = Array.isArray(child.material) ? child.material : [child.material]; + materials.forEach((mat) => { + mat.opacity = opacity; + mat.transparent = true; + }); + } + }); + }; + group.userData.dispose = () => { + material.dispose(); + pointMaterial.dispose(); + disposeGroupChildren(group); + }; + state.faceGroup.add(group); +} + +function faceCycleLayout(face, faceIndex, totalFaces) { + const radius = Math.max(0.42, Math.min(0.82, 0.28 + face.length * 0.035)); + const slotWidth = Math.max(1.18, Math.min(2.15, 5.4 / Math.max(1, totalFaces))); + const slotX = (faceIndex - (totalFaces - 1) / 2) * slotWidth; + const zLift = 1.42 + (faceIndex % 2) * 0.16; + const center = new THREE.Vector3(slotX, -0.22, zLift); + const points = []; + for (let i = 0; i <= face.length; i++) { + const angle = Math.PI / 2 - (i / face.length) * Math.PI * 2; + points.push(new THREE.Vector3( + center.x + Math.cos(angle) * radius, + center.y, + center.z + Math.sin(angle) * radius, + )); + } + return { points }; +} + +function applyLiftedFacePose(face, faceIndex, totalFaces, amount) { + face.position.y = -0.26 * amount; + face.rotation.x = -0.22 * amount; + face.rotation.z = (faceIndex - (totalFaces - 1) / 2) * 0.04 * amount; + face.scale.setScalar(1); +} + +function liftedFaceMatrix(faceIndex, totalFaces) { + const rotation = new THREE.Euler( + -0.22, + 0, + (faceIndex - (totalFaces - 1) / 2) * 0.04, + ); + return new THREE.Matrix4().compose( + new THREE.Vector3(0, -0.26, 0), + new THREE.Quaternion().setFromEuler(rotation), + new THREE.Vector3(1, 1, 1), + ); +} + +function ensureFaceCycles(system) { + if (state.faceGroup.children.length === system.faces.length) return; + clearGroup(state.faceGroup); + addAllFaceCycles(system); +} + +function faceDartMorphs(system) { + const morphs = []; + system.faces.forEach((face, faceIndex) => { + const layout = faceCycleLayout(face, faceIndex, system.faces.length); + const matrix = liftedFaceMatrix(faceIndex, system.faces.length); + face.forEach((dart, dartIndex) => { + morphs.push({ + dart, + color: FACE_COLORS[faceIndex % FACE_COLORS.length], + fromStart: flatPosition(dart.from), + toStart: flatPosition(dart.to), + fromEnd: layout.points[dartIndex].clone().applyMatrix4(matrix), + toEnd: layout.points[dartIndex + 1].clone().applyMatrix4(matrix), + }); + }); + }); + return morphs; +} + +async function morphTraceDartsToFaceCycles(system, token) { + const duration = 980; + const start = performance.now(); + clearTraceSelection(); + ensureFaceCycles(system); + const faces = [...state.faceGroup.children]; + const morphs = faceDartMorphs(system); + while (performance.now() - start < duration) { + if (token !== state.animationToken) return; + const t = easeInOut((performance.now() - start) / duration); + const cycleOpacity = Math.max(0, (t - 0.74) / 0.26); + setGroupOpacity(state.flatGroup, 1 - t * 0.82); + faces.forEach((face, index) => { + face.userData.setOpacity?.(cycleOpacity); + applyLiftedFacePose(face, index, system.faces.length, t); + }); + drawMorphDarts(morphs, t); + await nextFrame(); + } + setGroupOpacity(state.flatGroup, 0.18); + faces.forEach((face, index) => { + face.userData.setOpacity?.(1); + applyLiftedFacePose(face, index, system.faces.length, 1); + }); + clearGroup(state.traceGroup); + clearTraceSelection(); +} + +function drawMorphDarts(morphs, amount) { + clearGroup(state.traceGroup); + for (const morph of morphs) { + const from = new THREE.Vector3().lerpVectors(morph.fromStart, morph.fromEnd, amount); + const to = new THREE.Vector3().lerpVectors(morph.toStart, morph.toEnd, amount); + addDartVisualBetween(from, to, morph.color, state.traceGroup, 0.018, true); + } +} + +async function morphFaceCyclesToSurface(system, modelGroup, token) { + const morph = surfaceGlueMorphData(system, modelGroup.pathsByEdge, modelGroup.vertexPositions); + const start = performance.now(); + while (performance.now() - start < TORUS_GLUE_DURATION) { + if (token !== state.animationToken) return; + const t = easeInOut((performance.now() - start) / TORUS_GLUE_DURATION); + setGroupOpacity(state.flatGroup, 0.18 * (1 - t)); + state.faceGroup.children.forEach((face) => { + face.userData.setOpacity?.(1 - t); + }); + drawSurfaceGlueMorph(morph, t); + await nextFrame(); + } + setGroupOpacity(state.flatGroup, 0); + state.faceGroup.children.forEach((face) => face.userData.setOpacity?.(0)); + drawSurfaceGlueMorph(morph, 1); +} + +function surfaceGlueMorphData(system, pathsByEdge, vertexPositions) { + const darts = []; + const vertices = []; + system.faces.forEach((face, faceIndex) => { + const layout = faceCycleLayout(face, faceIndex, system.faces.length); + const matrix = liftedFaceMatrix(faceIndex, system.faces.length); + face.forEach((dart, dartIndex) => { + const color = FACE_COLORS[faceIndex % FACE_COLORS.length]; + const startFrom = layout.points[dartIndex].clone().applyMatrix4(matrix); + const startTo = layout.points[dartIndex + 1].clone().applyMatrix4(matrix); + const targetPath = directedSurfacePath(dart, pathsByEdge, vertexPositions); + const samples = Math.max(24, Math.min(96, targetPath.length || 2)); + darts.push({ + color, + startPath: resamplePolyline([startFrom, startTo], samples), + targetPath: resamplePolyline(targetPath, samples), + }); + vertices.push({ + start: startFrom, + target: (vertexPositions.get(dart.from) || startFrom).clone(), + }); + }); + }); + return { + darts, + vertices, + edgeRadiusStart: 0.018, + edgeRadiusEnd: Math.max(state.surfaceStrokeRadius * 1.75, 0.010), + pointRadiusStart: 0.035, + pointRadiusEnd: Math.max(state.surfaceStrokeRadius * 2.05, 0.018), + }; +} + +function directedSurfacePath(dart, pathsByEdge, vertexPositions) { + const start = vertexPositions.get(dart.from); + const end = vertexPositions.get(dart.to); + const segments = pathsByEdge.get(edgeKey(dart.from, dart.to)) || []; + const pieces = segments + .map((segment) => segment.points.map((point) => point.clone())) + .filter((points) => points.length >= 2); + if (pieces.length === 0) { + if (start && end) return [start.clone(), end.clone()]; + return [new THREE.Vector3(), new THREE.Vector3()]; + } + return stitchSurfacePieces(pieces, start, end); +} + +function stitchSurfacePieces(pieces, start, end) { + const remaining = pieces.map((points) => points.map((point) => point.clone())); + const path = []; + let current = start ? start.clone() : null; + while (remaining.length) { + let bestIndex = 0; + let bestReverse = false; + let bestDistance = Infinity; + for (let i = 0; i < remaining.length; i++) { + const piece = remaining[i]; + const first = piece[0]; + const last = piece[piece.length - 1]; + const firstDistance = current ? current.distanceToSquared(first) : 0; + const lastDistance = current ? current.distanceToSquared(last) : 0; + if (firstDistance < bestDistance) { + bestDistance = firstDistance; + bestIndex = i; + bestReverse = false; + } + if (lastDistance < bestDistance) { + bestDistance = lastDistance; + bestIndex = i; + bestReverse = true; + } + } + const piece = remaining.splice(bestIndex, 1)[0]; + if (bestReverse) piece.reverse(); + if (path.length === 0) { + if (current && current.distanceToSquared(piece[0]) > 1e-8) path.push(current.clone()); + path.push(...piece); + } else { + const last = path[path.length - 1]; + if (last.distanceToSquared(piece[0]) > 1e-8) path.push(piece[0].clone()); + path.push(...piece.slice(1)); + } + current = path[path.length - 1].clone(); + } + if (end && path[path.length - 1]?.distanceToSquared(end) > 1e-8) path.push(end.clone()); + return path; +} + +function resamplePolyline(points, count) { + const clean = points.filter(Boolean).map((point) => point.clone()); + if (clean.length === 0) return Array.from({ length: count }, () => new THREE.Vector3()); + if (clean.length === 1) return Array.from({ length: count }, () => clean[0].clone()); + const lengths = [0]; + for (let i = 1; i < clean.length; i++) { + lengths.push(lengths[i - 1] + clean[i - 1].distanceTo(clean[i])); + } + const total = lengths[lengths.length - 1]; + if (total < 1e-8) return Array.from({ length: count }, () => clean[0].clone()); + const samples = []; + let segment = 1; + for (let i = 0; i < count; i++) { + const d = total * (i / Math.max(1, count - 1)); + while (segment < lengths.length - 1 && lengths[segment] < d) segment++; + const prev = clean[segment - 1]; + const next = clean[segment]; + const span = lengths[segment] - lengths[segment - 1]; + const t = span > 1e-8 ? (d - lengths[segment - 1]) / span : 0; + samples.push(new THREE.Vector3().lerpVectors(prev, next, t)); + } + return samples; +} + +function drawSurfaceGlueMorph(morph, amount) { + clearGroup(state.traceGroup); + const edgeRadius = lerpScalar(morph.edgeRadiusStart, morph.edgeRadiusEnd, amount); + const pointRadius = lerpScalar(morph.pointRadiusStart, morph.pointRadiusEnd, amount); + for (const dart of morph.darts) { + const points = dart.startPath.map((point, index) => ( + new THREE.Vector3().lerpVectors(point, dart.targetPath[index], amount) + )); + addCurveDartVisual(points, dart.color, state.traceGroup, edgeRadius); + } + for (const vertex of morph.vertices) { + const position = new THREE.Vector3().lerpVectors(vertex.start, vertex.target, amount); + addMorphVertexVisual(position, pointRadius, state.traceGroup); + } +} + +function addCurveDartVisual(points, color, group, radius) { + if (points.length < 2) return; + const material = makeBasicMaterial(color, 1, { depthTest: false }); + const tube = makeTube(points, radius, material, Math.max(8, points.length - 1)); + tube.renderOrder = 24; + group.add(tube); + const headIndex = Math.max(0, points.length - 8); + group.add(makeArrowHead(points[headIndex], points[points.length - 1], color, radius * 3.8, radius * 8.0)); +} + +function addMorphVertexVisual(position, radius, group) { + const dot = new THREE.Mesh( + new THREE.SphereGeometry(radius, 18, 12), + makeBasicMaterial(0xf4f4ef, 1, { depthTest: false }), + ); + dot.position.copy(position); + dot.renderOrder = 32; + group.add(dot); +} + +async function crossFadeToSurface(setOpacity, token) { + const modelFadeDuration = 820; + const colorFadeDuration = 620; + const start = performance.now(); + while (performance.now() - start < modelFadeDuration) { + if (token !== state.animationToken) return; + const t = easeInOut((performance.now() - start) / modelFadeDuration); + setOpacity(t); + setGroupOpacity(state.flatGroup, 0); + setGroupOpacity(state.traceGroup, 1); + state.faceGroup.children.forEach((face) => { + face.userData.setOpacity?.(0); + }); + await nextFrame(); + } + setOpacity(1, true); + setGroupOpacity(state.flatGroup, 0); + setGroupOpacity(state.traceGroup, 1); + state.faceGroup.children.forEach((face) => face.userData.setOpacity?.(0)); + await nextFrame(); + await nextFrame(); + + const fadeStart = performance.now(); + while (performance.now() - fadeStart < colorFadeDuration) { + if (token !== state.animationToken) return; + const t = easeInOut((performance.now() - fadeStart) / colorFadeDuration); + setOpacity(1, true); + setGroupOpacity(state.traceGroup, 1 - t); + await nextFrame(); + } + setOpacity(1, true); + setGroupOpacity(state.traceGroup, 0); + state.faceGroup.children.forEach((face) => face.userData.setOpacity?.(0)); +} + +async function getModel(system) { + if (system.genus === 2) return getGenusTwoManualModel(system); + const key = rotationKey(system.rotation); + if (modelCache.has(key)) return modelCache.get(key); + const model = await requestModel(system.rotation); + modelCache.set(key, model); + return model; +} + +async function getGenusTwoManualModel(system) { + const key = `manual-genus2:${system.index}`; + if (modelCache.has(key)) return modelCache.get(key); + const baseRenderData = await loadGenusTwoBaseRenderData(); + const automorphism = findAutomorphism(rotationFromMask(GENUS2_REPRESENTATIVE_MASK), system.rotation); + if (!automorphism) throw new Error("Could not map the genus-2 representative to this rotation system."); + const model = { + genus: 2, + manualSurfaceData: baseRenderData, + manualLayout: mapPreparedManualLayout(baseRenderData, automorphism), + }; + modelCache.set(key, model); + return model; +} + +function prefetchGenusTwo() { + loadGenusTwoBaseRenderData() + .then((baseRenderData) => { + for (const system of systems) { + if (system.genus !== 2) continue; + const automorphism = findAutomorphism(rotationFromMask(GENUS2_REPRESENTATIVE_MASK), system.rotation); + if (!automorphism) continue; + const key = `manual-genus2:${system.index}`; + if (!modelCache.has(key)) { + modelCache.set(key, { + genus: 2, + manualSurfaceData: baseRenderData, + manualLayout: mapPreparedManualLayout(baseRenderData, automorphism), + }); + } + } + }) + .catch(() => {}); +} + +function loadGenusTwoManualLayout() { + if (!genusTwoManualLayoutPromise) { + genusTwoManualLayoutPromise = fetch(GENUS2_MANUAL_LAYOUT_URL).then((response) => { + if (!response.ok) throw new Error("Could not load the saved genus-2 manual layout."); + return response.json(); + }); + } + return genusTwoManualLayoutPromise; +} + +function requestGenusTwoRawModel() { + if (!genusTwoRawModelPromise) { + genusTwoRawModelPromise = requestModel(rotationFromMask(GENUS2_REPRESENTATIVE_MASK), "3d_raw") + .catch((error) => { + genusTwoRawModelPromise = null; + throw error; + }); + } + return genusTwoRawModelPromise; +} + +function loadGenusTwoBaseRenderData() { + if (!genusTwoBaseRenderDataPromise) { + genusTwoBaseRenderDataPromise = Promise.all([ + loadGenusTwoManualLayout(), + requestGenusTwoRawModel(), + ]) + .then(([layout, rawModel]) => prepareGenusTwoBaseRenderData(layout, rawModel)) + .catch((error) => { + genusTwoBaseRenderDataPromise = null; + throw error; + }); + } + return genusTwoBaseRenderDataPromise; +} + +function prepareGenusTwoBaseRenderData(layout, rawModel) { + const parsed = parseObj(rawModel.obj); + parsed.geometry.computeBoundingBox(); + const center = new THREE.Vector3(); + parsed.geometry.boundingBox.getCenter(center); + parsed.geometry.translate(-center.x, -center.y, -center.z); + parsed.geometry.computeBoundingSphere(); + const surfaceTriangles = buildSurfaceTriangles(parsed.geometry); + const radius = parsed.geometry.boundingSphere?.radius || 1; + const strokeRadius = Math.max(radius * 0.0032, 0.0048); + const graphLift = strokeRadius * 0.18; + const normalAt = (point) => orientedProjectToSurface(point, surfaceTriangles).normal; + const vertices = new Map(); + Object.entries(layout.vertices || {}).forEach(([vertex, point]) => { + vertices.set(Number(vertex), liftPointToSurface(arrayToVector(point), surfaceTriangles, graphLift, null, strokeRadius * 3.0)); + }); + const edges = []; + Object.entries(layout.edges || {}).forEach(([key, route]) => { + const [from, to] = key.split("-").map(Number); + const points = [ + arrayToVector(layout.vertices[String(from)]), + ...route.map(arrayToVector), + arrayToVector(layout.vertices[String(to)]), + ]; + const displayPoints = refineManualSurfacePath(points, surfaceTriangles, graphLift, radius, strokeRadius); + const start = vertices.get(from); + const end = vertices.get(to); + if (start && displayPoints.length) displayPoints[0] = start.clone(); + if (end && displayPoints.length) displayPoints[displayPoints.length - 1] = end.clone(); + edges.push({ + key, + ends: [from, to], + segment: [from, to], + points: displayPoints, + }); + }); + return { + geometry: parsed.geometry, + center, + radius, + strokeRadius, + normalAt, + vertices, + edges, + }; +} + +function mapPreparedManualLayout(baseRenderData, automorphism) { + const vertices = new Map(); + const edges = []; + for (const [vertex, point] of baseRenderData.vertices.entries()) { + vertices.set(automorphism[vertex], point.clone()); + } + for (const edge of baseRenderData.edges) { + const mappedFrom = automorphism[edge.ends[0]]; + const mappedTo = automorphism[edge.ends[1]]; + edges.push({ + key: edgeKey(mappedFrom, mappedTo), + ends: [mappedFrom, mappedTo], + segment: [mappedFrom, mappedTo], + points: edge.points.map((point) => point.clone()), + }); + } + return { vertices, edges }; +} + +function findAutomorphism(sourceRotation, targetRotation) { + for (const permutation of k33Automorphisms) { + if (rotationsMatch(applyAutomorphism(sourceRotation, permutation), targetRotation)) return permutation; + } + return null; +} + +function applyAutomorphism(rotation, permutation) { + const mapped = Array.from({ length: rotation.length }, () => []); + rotation.forEach((neighbors, vertex) => { + mapped[permutation[vertex]] = neighbors.map((neighbor) => permutation[neighbor]); + }); + return mapped; +} + +function rotationsMatch(actual, expected) { + return actual.every((neighbors, vertex) => cyclicOrderEqual(neighbors, expected[vertex])); +} + +function cyclicOrderEqual(actual, expected) { + if (actual.length !== expected.length) return false; + return expected.some((_, shift) => actual.every((value, index) => value === expected[(index + shift) % expected.length])); +} + +function makeK33Automorphisms() { + const permutations = [ + [0, 1, 2], + [0, 2, 1], + [1, 0, 2], + [1, 2, 0], + [2, 0, 1], + [2, 1, 0], + ]; + const automorphisms = []; + for (const left of permutations) { + for (const right of permutations) { + automorphisms.push([left[0], left[1], left[2], 3 + right[0], 3 + right[1], 3 + right[2]]); + automorphisms.push([3 + left[0], 3 + left[1], 3 + left[2], right[0], right[1], right[2]]); + } + } + return automorphisms; +} + +function requestModel(rotation, outputFormat = "3d") { + return new Promise((resolve, reject) => { + const socket = new WebSocket(`${location.protocol === "https:" ? "wss:" : "ws:"}//${location.host}/stream_calc_genus`); + let done = false; + socket.onopen = () => { + socket.send(JSON.stringify({ alg: "none", outputFormat, adj: rotation })); + }; + socket.onmessage = (event) => { + const separator = event.data.indexOf(":"); + const type = separator === -1 ? event.data : event.data.slice(0, separator); + const data = separator === -1 ? "" : event.data.slice(separator + 1); + if (type === "MODEL") { + done = true; + resolve(JSON.parse(data)); + socket.close(); + } else if (type === "JSON") { + const parsed = JSON.parse(data); + if (parsed.error) { + done = true; + reject(new Error(parsed.error)); + socket.close(); + } + } + }; + socket.onerror = () => { + if (!done) reject(new Error("Could not load the 3D model")); + }; + socket.onclose = () => { + if (!done) reject(new Error("3D model request closed before a model was returned")); + }; + }); +} + +function prefetchNearby() { + const genusOne = systems.filter((system) => system.genus === 1); + let cursor = 0; + const pump = async () => { + if (cursor >= genusOne.length) return; + const system = genusOne[cursor++]; + const key = rotationKey(system.rotation); + if (!modelCache.has(key)) { + try { + await getModel(system); + } catch { + return; + } + } + setTimeout(pump, 80); + }; + pump(); +} + +function buildModelGroup(model) { + if (model.manualLayout) return buildManualLayoutModelGroup(model); + + const parsed = parseObj(model.obj); + parsed.geometry.computeBoundingBox(); + const center = new THREE.Vector3(); + parsed.geometry.boundingBox.getCenter(center); + parsed.geometry.translate(-center.x, -center.y, -center.z); + parsed.geometry.computeBoundingSphere(); + state.surfaceCenter.copy(center); + + const group = new THREE.Group(); + const surfaceMaterial = new THREE.MeshStandardMaterial({ + color: SURFACE, + roughness: 0.68, + metalness: 0.02, + side: THREE.DoubleSide, + transparent: true, + opacity: 1, + }); + const surface = new THREE.Mesh(parsed.geometry, surfaceMaterial); + group.add(surface); + + const graphMaterial = makeBasicMaterial(BLACK, 1, { + depthTest: true, + polygonOffset: true, + polygonOffsetFactor: -2, + polygonOffsetUnits: -2, + transparent: false, + }); + const pointMaterial = makeBasicMaterial(0xf4f4ef, 1, { + depthTest: true, + polygonOffset: true, + polygonOffsetFactor: -2, + polygonOffsetUnits: -2, + transparent: false, + }); + const pathsByEdge = new Map(); + const vertexPositions = new Map(); + const radius = parsed.geometry.boundingSphere?.radius || 1; + const strokeRadius = Math.max(radius * 0.003, 0.0046); + state.surfaceStrokeRadius = strokeRadius; + + for (const line of parsed.graphLines) { + const centered = line.points.map((p) => p.clone().sub(center)); + const displayPoints = centered; + const tube = makeTube(displayPoints, strokeRadius, graphMaterial, Math.max(8, displayPoints.length - 1)); + tube.userData.edge = edgeKey(line.ends[0], line.ends[1]); + group.add(tube); + addTubeCaps(displayPoints, strokeRadius, graphMaterial, group); + const key = edgeKey(line.ends[0], line.ends[1]); + if (!pathsByEdge.has(key)) pathsByEdge.set(key, []); + pathsByEdge.get(key).push({ + ends: line.ends, + segment: line.segment, + points: displayPoints, + }); + } + + const pointGeometry = new THREE.SphereGeometry(strokeRadius * 1.9, 18, 12); + for (const point of parsed.graphPoints) { + const pos = point.position.clone().sub(center); + vertexPositions.set(point.label, pos); + const dot = new THREE.Mesh(pointGeometry, pointMaterial); + dot.position.copy(pos); + group.add(dot); + const label = makeTextSprite(String(point.label), Math.max(radius * 0.085, 0.13), { depthTest: true }); + const labelPos = point.labelPosition ? point.labelPosition.clone().sub(center) : pos.clone().multiplyScalar(1.035); + label.position.copy(labelPos); + group.add(label); + } + + const setOpacity = (opacity, solid = false) => { + const clamped = Math.max(0, Math.min(1, opacity)); + const materialOpacity = solid ? 1 : clamped; + surfaceMaterial.transparent = !solid; + surfaceMaterial.opacity = materialOpacity; + graphMaterial.transparent = !solid; + graphMaterial.opacity = materialOpacity; + pointMaterial.transparent = !solid; + pointMaterial.opacity = materialOpacity; + surfaceMaterial.needsUpdate = true; + graphMaterial.needsUpdate = true; + pointMaterial.needsUpdate = true; + group.traverse((child) => { + if (child.isSprite && child.material) { + child.material.transparent = true; + child.material.opacity = materialOpacity; + } + }); + }; + group.userData.dispose = () => { + parsed.geometry.dispose(); + surfaceMaterial.dispose(); + graphMaterial.dispose(); + pointMaterial.dispose(); + pointGeometry.dispose(); + disposeGroupChildren(group); + }; + return { group, pathsByEdge, vertexPositions, setOpacity, normalAt: torusNormal }; +} + +function buildManualLayoutModelGroup(model) { + const data = model.manualSurfaceData; + const surfaceGeometry = data.geometry.clone(); + const normalAt = data.normalAt; + state.surfaceCenter.copy(data.center); + const group = new THREE.Group(); + const surfaceMaterial = new THREE.MeshStandardMaterial({ + color: SURFACE, + roughness: 0.68, + metalness: 0.02, + side: THREE.DoubleSide, + transparent: true, + opacity: 1, + }); + const surface = new THREE.Mesh(surfaceGeometry, surfaceMaterial); + group.add(surface); + + const graphMaterial = makeBasicMaterial(BLACK, 1, { + depthTest: true, + polygonOffset: true, + polygonOffsetFactor: -2, + polygonOffsetUnits: -2, + transparent: false, + }); + const pointMaterial = makeBasicMaterial(0xf4f4ef, 1, { + depthTest: true, + polygonOffset: true, + polygonOffsetFactor: -2, + polygonOffsetUnits: -2, + transparent: false, + }); + const pathsByEdge = new Map(); + const vertexPositions = new Map(model.manualLayout.vertices); + const radius = data.radius; + const strokeRadius = data.strokeRadius; + state.surfaceStrokeRadius = strokeRadius; + + for (const edge of model.manualLayout.edges) { + const displayPoints = edge.points.map((point) => point.clone()); + const tube = makeTube(displayPoints, strokeRadius, graphMaterial, Math.max(16, displayPoints.length - 1)); + tube.userData.edge = edge.key; + group.add(tube); + addTubeCaps(displayPoints, strokeRadius, graphMaterial, group); + if (!pathsByEdge.has(edge.key)) pathsByEdge.set(edge.key, []); + pathsByEdge.get(edge.key).push({ + ends: edge.ends, + segment: edge.segment, + points: displayPoints, + }); + } + + const pointGeometry = new THREE.SphereGeometry(strokeRadius * 2.25, 18, 12); + for (const [vertexLabel, pos] of vertexPositions.entries()) { + const dot = new THREE.Mesh(pointGeometry, pointMaterial); + dot.position.copy(pos); + group.add(dot); + const labelSprite = makeTextSprite(String(vertexLabel), Math.max(radius * 0.085, 0.13), { depthTest: true }); + labelSprite.position.copy(pos).addScaledVector(normalAt(pos), strokeRadius * 8.0); + group.add(labelSprite); + } + + const setOpacity = (opacity, solid = false) => { + const clamped = Math.max(0, Math.min(1, opacity)); + const materialOpacity = solid ? 1 : clamped; + surfaceMaterial.transparent = !solid; + surfaceMaterial.opacity = materialOpacity; + graphMaterial.transparent = !solid; + graphMaterial.opacity = materialOpacity; + pointMaterial.transparent = !solid; + pointMaterial.opacity = materialOpacity; + surfaceMaterial.needsUpdate = true; + graphMaterial.needsUpdate = true; + pointMaterial.needsUpdate = true; + group.traverse((child) => { + if (child.isSprite && child.material) { + child.material.transparent = true; + child.material.opacity = materialOpacity; + } + }); + }; + group.userData.dispose = () => { + surfaceGeometry.dispose(); + surfaceMaterial.dispose(); + graphMaterial.dispose(); + pointMaterial.dispose(); + pointGeometry.dispose(); + disposeGroupChildren(group); + }; + return { group, pathsByEdge, vertexPositions, setOpacity, normalAt }; +} + +function parseObj(objText) { + const vertices = [new THREE.Vector3()]; + const uvs = [[0, 0]]; + const positions = []; + const texcoords = []; + const indices = []; + const graphLines = []; + const graphPoints = []; + const graphPointLabels = new Map(); + const cornerIndices = new Map(); + let pendingEdge = null; + + const addCorner = (token) => { + const [vertexToken, textureToken] = token.split("/"); + const vertexIndex = Number(vertexToken); + const textureIndex = textureToken ? Number(textureToken) : 0; + const key = `${vertexIndex}/${textureIndex}`; + if (cornerIndices.has(key)) return cornerIndices.get(key); + const vertex = vertices[vertexIndex]; + const uv = uvs[textureIndex] || [0, 0]; + const index = positions.length / 3; + positions.push(vertex.x, vertex.y, vertex.z); + texcoords.push(uv[0], uv[1]); + cornerIndices.set(key, index); + return index; + }; + + for (const rawLine of objText.split(/\r?\n/)) { + const line = rawLine.trim(); + if (line.startsWith("# graph_edge ")) { + const parts = line.split(/\s+/); + pendingEdge = { + ends: [Number(parts[2]) - 1, Number(parts[3]) - 1], + segment: [Number(parts[5]) - 1, Number(parts[6]) - 1], + }; + continue; + } + if (line.startsWith("# graph_vertex_label ")) { + const parts = line.split(/\s+/); + const vertexIndex = Number(parts[2]); + const label = Number(parts[3]) - 1; + const labelPosition = parts.length >= 7 + ? new THREE.Vector3(Number(parts[4]), Number(parts[5]), Number(parts[6])) + : null; + graphPointLabels.set(vertexIndex, { label, labelPosition }); + continue; + } + if (line === "" || line.startsWith("#")) continue; + const parts = line.split(/\s+/); + if (parts[0] === "v") { + vertices.push(new THREE.Vector3(Number(parts[1]), Number(parts[2]), Number(parts[3]))); + } else if (parts[0] === "vt") { + uvs.push([Number(parts[1]), Number(parts[2])]); + } else if (parts[0] === "f") { + const face = parts.slice(1).map(addCorner); + for (let i = 1; i < face.length - 1; i++) indices.push(face[0], face[i], face[i + 1]); + } else if (parts[0] === "l") { + const points = parts.slice(1).map((token) => vertices[Number(token.split("/")[0])]).filter(Boolean); + if (points.length >= 2) graphLines.push({ ...(pendingEdge || {}), points }); + pendingEdge = null; + } else if (parts[0] === "p") { + for (const token of parts.slice(1)) { + const vertexIndex = Number(token.split("/")[0]); + const position = vertices[vertexIndex]; + const labelInfo = graphPointLabels.get(vertexIndex); + if (position && labelInfo) { + graphPoints.push({ + position, + label: labelInfo.label, + labelPosition: labelInfo.labelPosition, + }); + } + } + } + } + + const geometry = new THREE.BufferGeometry(); + geometry.setAttribute("position", new THREE.Float32BufferAttribute(positions, 3)); + geometry.setAttribute("uv", new THREE.Float32BufferAttribute(texcoords, 2)); + geometry.setIndex(indices); + geometry.computeVertexNormals(); + geometry.normalizeNormals(); + return { geometry, graphLines, graphPoints }; +} + +function buildSurfaceTriangles(geometry) { + const positions = geometry.getAttribute("position"); + const index = geometry.index; + const triangles = []; + const a = new THREE.Vector3(); + const b = new THREE.Vector3(); + const c = new THREE.Vector3(); + const ab = new THREE.Vector3(); + const ac = new THREE.Vector3(); + const normal = new THREE.Vector3(); + const faceCount = index ? index.count / 3 : positions.count / 3; + for (let face = 0; face < faceCount; face++) { + const i0 = index ? index.getX(face * 3) : face * 3; + const i1 = index ? index.getX(face * 3 + 1) : face * 3 + 1; + const i2 = index ? index.getX(face * 3 + 2) : face * 3 + 2; + a.fromBufferAttribute(positions, i0); + b.fromBufferAttribute(positions, i1); + c.fromBufferAttribute(positions, i2); + ab.subVectors(b, a); + ac.subVectors(c, a); + normal.crossVectors(ab, ac); + if (normal.lengthSq() < 1e-14) continue; + triangles.push({ + a: a.clone(), + b: b.clone(), + c: c.clone(), + normal: normal.normalize().clone(), + }); + } + return triangles; +} + +function projectToSurface(point, triangles) { + const closest = new THREE.Vector3(); + const candidate = new THREE.Vector3(); + let bestDistanceSq = Infinity; + let bestNormal = new THREE.Vector3(0, 0, 1); + for (const triangle of triangles) { + closestPointOnTriangle(point, triangle.a, triangle.b, triangle.c, candidate); + const distanceSq = point.distanceToSquared(candidate); + if (distanceSq < bestDistanceSq) { + bestDistanceSq = distanceSq; + closest.copy(candidate); + bestNormal = triangle.normal; + } + } + if (!Number.isFinite(bestDistanceSq)) return { point: point.clone(), normal: bestNormal.clone() }; + return { point: closest, normal: bestNormal.clone() }; +} + +function orientedProjectToSurface(point, triangles, previousNormal = null, maxSnap = Infinity) { + const projection = projectToSurface(point, triangles); + const normal = projection.normal.clone(); + if (Number.isFinite(maxSnap) && point.distanceToSquared(projection.point) > maxSnap * maxSnap) { + return { + point: point.clone(), + normal: previousNormal ? previousNormal.clone() : normal, + }; + } + const offset = point.clone().sub(projection.point); + if (offset.lengthSq() > 1e-12) { + if (normal.dot(offset) < 0) normal.negate(); + } else if (previousNormal && normal.dot(previousNormal) < 0) { + normal.negate(); + } + if (previousNormal && normal.dot(previousNormal) < -0.35) normal.negate(); + return { point: projection.point, normal }; +} + +function liftPointToSurface(point, triangles, lift, previousNormal = null, maxSnap = Infinity) { + const projection = orientedProjectToSurface(point, triangles, previousNormal, maxSnap); + return projection.point.clone().addScaledVector(projection.normal, lift); +} + +function refineManualSurfacePath(points, triangles, lift, surfaceRadius, strokeRadius) { + const clean = points.filter(Boolean).map((point) => point.clone()); + if (clean.length < 2) return clean.map((point) => liftPointToSurface(point, triangles, lift)); + + const length = polylineLength(clean); + const spacing = Math.max(strokeRadius * 3.5, surfaceRadius * 0.0065, 0.012); + const sampleCount = Math.max(32, Math.min(220, Math.ceil(length / spacing))); + const refined = []; + let previousNormal = null; + const maxSnap = Math.max(strokeRadius * 4.0, surfaceRadius * 0.006, 0.018); + for (let i = 0; i <= sampleCount; i++) { + const t = i / sampleCount; + const sample = samplePolyline(clean, t); + const projection = orientedProjectToSurface(sample, triangles, previousNormal, maxSnap); + previousNormal = projection.normal.clone(); + refined.push(projection.point.clone().addScaledVector(projection.normal, lift)); + } + return removeNearDuplicatePoints(refined, strokeRadius * 0.16); +} + +function samplePolyline(points, t) { + if (points.length === 1) return points[0].clone(); + const total = polylineLength(points); + if (total < 1e-8) return points[0].clone(); + const target = total * Math.max(0, Math.min(1, t)); + let covered = 0; + for (let i = 0; i < points.length - 1; i++) { + const span = points[i].distanceTo(points[i + 1]); + if (covered + span >= target) { + const local = span > 1e-8 ? (target - covered) / span : 0; + return new THREE.Vector3().lerpVectors(points[i], points[i + 1], local); + } + covered += span; + } + return points[points.length - 1].clone(); +} + +function removeNearDuplicatePoints(points, epsilon) { + if (points.length < 2) return points; + const kept = [points[0]]; + const thresholdSq = epsilon * epsilon; + for (let i = 1; i < points.length; i++) { + if (points[i].distanceToSquared(kept[kept.length - 1]) > thresholdSq) kept.push(points[i]); + } + if (kept.length === 1 && points.length > 1) kept.push(points[points.length - 1]); + return kept; +} + +function polylineLength(points) { + let total = 0; + for (let i = 0; i < points.length - 1; i++) total += points[i].distanceTo(points[i + 1]); + return total; +} + +function closestPointOnTriangle(point, a, b, c, target) { + const ab = b.clone().sub(a); + const ac = c.clone().sub(a); + const ap = point.clone().sub(a); + const d1 = ab.dot(ap); + const d2 = ac.dot(ap); + if (d1 <= 0 && d2 <= 0) return target.copy(a); + + const bp = point.clone().sub(b); + const d3 = ab.dot(bp); + const d4 = ac.dot(bp); + if (d3 >= 0 && d4 <= d3) return target.copy(b); + + const vc = d1 * d4 - d3 * d2; + if (vc <= 0 && d1 >= 0 && d3 <= 0) { + const v = d1 / (d1 - d3); + return target.copy(a).addScaledVector(ab, v); + } + + const cp = point.clone().sub(c); + const d5 = ab.dot(cp); + const d6 = ac.dot(cp); + if (d6 >= 0 && d5 <= d6) return target.copy(c); + + const vb = d5 * d2 - d1 * d6; + if (vb <= 0 && d2 >= 0 && d6 <= 0) { + const w = d2 / (d2 - d6); + return target.copy(a).addScaledVector(ac, w); + } + + const va = d3 * d6 - d5 * d4; + if (va <= 0 && d4 - d3 >= 0 && d5 - d6 >= 0) { + const w = (d4 - d3) / (d4 - d3 + d5 - d6); + return target.copy(b).addScaledVector(c.clone().sub(b), w); + } + + const denom = 1 / (va + vb + vc); + const v = vb * denom; + const w = vc * denom; + return target.copy(a).addScaledVector(ab, v).addScaledVector(ac, w); +} + +function highlightDart(dart, color = BLUE) { + clearGroup(state.highlightGroup); + clearActiveList(); + const chip = el.rotationList.querySelector(`[data-dart="${dart.from}-${dart.to}"]`); + chip?.classList.add("active"); + chip?.closest(".rotation-row")?.classList.add("active"); + highlightVertex(dart.from, color); + if (state.phase === "surface") highlightSurfaceDart(dart, color); + else highlightFlatDart(dart, color); +} + +function highlightFlatDart(dart, color) { + addFlatDartVisual(dart, color, state.highlightGroup, 0.026, true); +} + +function addTraceDart(dart, color) { + addFlatDartVisual(dart, color, state.traceGroup, 0.018, true); +} + +function addFlatDartVisual(dart, color, group, radius, arrow) { + const from = flatPosition(dart.from); + const to = flatPosition(dart.to); + addDartVisualBetween(from, to, color, group, radius, arrow); +} + +function addDartVisualBetween(from, to, color, group, radius, arrow) { + const material = makeBasicMaterial(color, 1, { depthTest: false }); + const tube = makeTube([from, to], radius, material, 40); + tube.renderOrder = 20; + group.add(tube); + if (arrow) group.add(makeArrowHead(from, to, color, radius * 4.0, radius * 8.2)); +} + +function highlightSurfaceDart(dart, color) { + const segments = state.surfacePaths.get(edgeKey(dart.from, dart.to)) || []; + if (segments.length === 0) return; + const material = makeBasicMaterial(color, 1, { depthTest: false }); + let arrowPoints = null; + + for (const segment of segments) { + const points = segment.points.map((point) => point.clone()); + if (points.length < 2) continue; + const tube = makeTube(points, state.surfaceStrokeRadius * 1.8, material, Math.max(8, points.length - 1)); + tube.renderOrder = 30; + state.highlightGroup.add(tube); + + if (segment.segment?.[1] === dart.to) { + arrowPoints = points; + } else if (segment.segment?.[0] === dart.to) { + arrowPoints = [...points].reverse(); + } + } + + if (arrowPoints && arrowPoints.length >= 2) { + const headFrom = arrowPoints[Math.max(0, arrowPoints.length - 8)]; + const headTo = arrowPoints[arrowPoints.length - 1]; + state.highlightGroup.add(makeArrowHead(headFrom, headTo, color, state.surfaceStrokeRadius * 5.4, state.surfaceStrokeRadius * 11.0)); + } +} + +function animateCounterclockwiseArrow(vertex, token) { + const started = performance.now(); + const duration = 900; + const update = () => { + if (token !== state.sequenceToken || state.phase !== "surface") return; + const progress = Math.min(1, (performance.now() - started) / duration); + drawCounterclockwiseArrow(vertex, easeOut(progress)); + if (progress < 1) requestAnimationFrame(update); + }; + update(); +} + +function drawCounterclockwiseArrow(vertex, progress) { + clearGroup(state.arrowGroup); + const center = state.surfaceVertices.get(vertex); + if (!center) return; + const normal = (state.surfaceNormalAt || torusNormal)(center).clone().normalize(); + if (normal.lengthSq() < 1e-8) normal.set(0, 0, 1); + const basisA = new THREE.Vector3(0, 0, 1).cross(normal); + if (basisA.lengthSq() < 1e-5) basisA.set(1, 0, 0); + basisA.normalize(); + const basisB = normal.clone().cross(basisA).normalize(); + const radius = 0.22; + const points = []; + const total = Math.max(0.08, progress) * Math.PI * 1.65; + const steps = Math.max(5, Math.round(42 * progress)); + for (let i = 0; i <= steps; i++) { + const theta = Math.PI * 0.72 + (i / steps) * total; + const p = center.clone() + .addScaledVector(normal, state.surfaceStrokeRadius * 9.5) + .addScaledVector(basisA, Math.cos(theta) * radius) + .addScaledVector(basisB, Math.sin(theta) * radius); + points.push(p); + } + const material = makeBasicMaterial(BLUE, 0.95, { depthTest: false }); + state.arrowGroup.add(makeTube(points, 0.009, material, Math.max(8, steps))); + if (points.length >= 2) { + state.arrowGroup.add(makeArrowHead(points[points.length - 2], points[points.length - 1], BLUE, 0.045, 0.095)); + } +} + +function highlightVertex(vertex, color = BLUE) { + clearGroup(state.vertexHighlightGroup); + const position = state.phase === "surface" + ? state.surfaceVertices.get(vertex) + : flatPosition(vertex); + if (!position) return; + const radius = state.phase === "surface" ? state.surfaceStrokeRadius * 4.0 : 0.115; + const material = makeBasicMaterial(color, 1, { depthTest: false }); + const dot = new THREE.Mesh(new THREE.SphereGeometry(radius, 24, 16), material); + dot.position.copy(position); + dot.renderOrder = 40; + state.vertexHighlightGroup.add(dot); +} + +function addTubeCaps(points, radius, material, group) { + if (points.length === 0) return; + const geometry = new THREE.SphereGeometry(radius * 1.08, 10, 8); + const first = new THREE.Mesh(geometry, material); + first.position.copy(points[0]); + group.add(first); + if (points.length > 1) { + const last = new THREE.Mesh(geometry, material); + last.position.copy(points[points.length - 1]); + group.add(last); + } +} + +function torusNormal(point) { + const major = 1.25; + const u = Math.atan2(point.y, point.x); + const tubeCenter = new THREE.Vector3(major * Math.cos(u), major * Math.sin(u), 0); + return point.clone().sub(tubeCenter).normalize(); +} + +function clearActiveList() { + el.rotationList.querySelectorAll(".active").forEach((node) => node.classList.remove("active")); +} + +function makeTextSprite(text, size, options = {}) { + const canvas = document.createElement("canvas"); + const context = canvas.getContext("2d"); + const fontSize = 52; + const padding = 16; + const label = String(text); + context.font = `800 ${fontSize}px system-ui, -apple-system, sans-serif`; + const metrics = context.measureText(label); + canvas.width = Math.ceil(metrics.width + padding * 2); + canvas.height = fontSize + padding * 2; + context.font = `800 ${fontSize}px system-ui, -apple-system, sans-serif`; + context.textBaseline = "middle"; + context.lineWidth = 9; + context.lineJoin = "round"; + context.strokeStyle = "rgba(247, 247, 242, 0.98)"; + context.fillStyle = options.color || "#171a1f"; + context.strokeText(label, padding, canvas.height / 2); + context.fillText(label, padding, canvas.height / 2); + const texture = new THREE.CanvasTexture(canvas); + texture.colorSpace = THREE.SRGBColorSpace; + const material = new THREE.SpriteMaterial({ + map: texture, + transparent: true, + opacity: options.opacity ?? 1, + depthTest: options.depthTest ?? false, + depthWrite: false, + }); + const sprite = new THREE.Sprite(material); + sprite.scale.set(size * (canvas.width / canvas.height), size, 1); + sprite.renderOrder = 50; + sprite.userData.dispose = () => { + texture.dispose(); + material.dispose(); + }; + return sprite; +} + +function makeTube(points, radius, material, segments = 32) { + const clean = points.filter(Boolean).map((point) => point.clone()); + if (clean.length < 2) { + const mesh = new THREE.Mesh(new THREE.SphereGeometry(radius, 8, 6), material); + if (clean[0]) mesh.position.copy(clean[0]); + return mesh; + } + const path = new THREE.CurvePath(); + for (let i = 0; i < clean.length - 1; i++) { + if (clean[i].distanceToSquared(clean[i + 1]) > 1e-10) { + path.add(new THREE.LineCurve3(clean[i], clean[i + 1])); + } + } + if (path.curves.length === 0) { + const mesh = new THREE.Mesh(new THREE.SphereGeometry(radius, 8, 6), material); + mesh.position.copy(clean[0]); + return mesh; + } + const geometry = new THREE.TubeGeometry(path, Math.max(1, segments), radius, 6, false); + return new THREE.Mesh(geometry, material); +} + +function makeArrowHead(from, to, color, radius, height, options = {}) { + const direction = to.clone().sub(from); + if (direction.lengthSq() < 1e-8) direction.set(1, 0, 0); + direction.normalize(); + const cone = new THREE.Mesh( + new THREE.ConeGeometry(radius, height, 24), + makeBasicMaterial(color, options.opacity ?? 1, { depthTest: options.depthTest ?? false }), + ); + const backoff = options.tipAtTarget ? 0.5 : 0.18; + cone.position.copy(to.clone().addScaledVector(direction, -height * backoff)); + cone.quaternion.setFromUnitVectors(new THREE.Vector3(0, 1, 0), direction); + cone.renderOrder = options.renderOrder ?? 35; + return cone; +} + +function makeBasicMaterial(color, opacity = 1, options = {}) { + return new THREE.MeshBasicMaterial({ + color, + transparent: opacity < 1 || options.transparent !== false, + opacity, + depthTest: options.depthTest ?? true, + depthWrite: false, + polygonOffset: options.polygonOffset ?? false, + polygonOffsetFactor: options.polygonOffsetFactor ?? 0, + polygonOffsetUnits: options.polygonOffsetUnits ?? 0, + }); +} + +function setCameraPose(position, target) { + state.cameraToken++; + camera.position.copy(position); + controls.target.copy(target); + camera.near = 0.01; + camera.far = 100; + camera.updateProjectionMatrix(); + controls.update(); +} + +function animateCamera(position, target, duration) { + const token = ++state.cameraToken; + const startPosition = camera.position.clone(); + const startTarget = controls.target.clone(); + const started = performance.now(); + return new Promise((resolve) => { + const tick = () => { + if (token !== state.cameraToken) { + resolve(false); + return; + } + const t = Math.min(1, (performance.now() - started) / duration); + const eased = easeInOut(t); + camera.position.lerpVectors(startPosition, position, eased); + controls.target.lerpVectors(startTarget, target, eased); + camera.near = 0.01; + camera.far = 100; + camera.updateProjectionMatrix(); + controls.update(); + if (t < 1) { + requestAnimationFrame(tick); + } else { + resolve(true); + } + }; + tick(); + }); +} + +function resize() { + const width = el.viewer.clientWidth || window.innerWidth; + const height = el.viewer.clientHeight || window.innerHeight; + renderer.setSize(width, height, false); + camera.aspect = width / height; + camera.updateProjectionMatrix(); +} + +function animate() { + controls.update(); + renderer.render(scene, camera); + requestAnimationFrame(animate); +} + +function disposeModelGroup() { + if (!state.modelGroup) return; + scene.remove(state.modelGroup); + disposeGroup(state.modelGroup); + state.modelGroup = null; + state.surfacePaths = new Map(); + state.surfaceVertices = new Map(); + state.surfaceNormalAt = null; + state.finalOpacity = null; +} + +function clearGroup(group) { + while (group.children.length) { + const child = group.children.pop(); + disposeObject(child); + } +} + +function disposeGroup(group) { + group.userData.dispose?.(); + disposeObject(group); +} + +function disposeGroupChildren(group) { + for (const child of group.children) disposeObject(child); +} + +function disposeObject(object) { + object.traverse?.((child) => { + if (child.geometry) child.geometry.dispose(); + if (child.material) { + const materials = Array.isArray(child.material) ? child.material : [child.material]; + materials.forEach((material) => { + if (material.map) material.map.dispose(); + material.dispose(); + }); + } + if (child.userData?.dispose && child !== object) child.userData.dispose(); + }); +} + +function setGroupOpacity(group, opacity) { + if (!group) return; + group.traverse((child) => { + if (!child.material) return; + const materials = Array.isArray(child.material) ? child.material : [child.material]; + materials.forEach((material) => { + material.opacity = opacity; + material.transparent = true; + }); + }); +} + +function dartKey(from, to) { + return `${from}-${to}`; +} + +function edgeKey(a, b) { + return a < b ? `${a}-${b}` : `${b}-${a}`; +} + +function rotationKey(rotation) { + return rotation.map((neighbors) => neighbors.join(",")).join("|"); +} + +function clampRotationNumber(value) { + const parsed = Number(value); + if (!Number.isFinite(parsed)) return state.index + 1; + return Math.min(systems.length, Math.max(1, Math.round(parsed))); +} + +function delay(ms) { + return new Promise((resolve) => setTimeout(resolve, ms)); +} + +function nextFrame() { + return new Promise((resolve) => requestAnimationFrame(resolve)); +} + +function easeInOut(t) { + const clamped = Math.max(0, Math.min(1, t)); + return clamped * clamped * (3 - 2 * clamped); +} + +function lerpScalar(a, b, t) { + return a + (b - a) * t; +} + +function arrayToVector(value) { + return new THREE.Vector3(Number(value[0]), Number(value[1]), Number(value[2])); +} + +function easeOut(t) { + const clamped = Math.max(0, Math.min(1, t)); + return 1 - Math.pow(1 - clamped, 3); +} diff --git a/WebApp/static/script.js b/WebApp/static/script.js index 0e66151..eb03511 100644 --- a/WebApp/static/script.js +++ b/WebApp/static/script.js @@ -1,4 +1,8 @@ +import * as THREE from "three"; +import { OrbitControls } from "/vendor/OrbitControls.js"; + const algorithm = document.getElementById("algorithm"); +const outputFormat = document.getElementById("output_format"); const adjlist = document.getElementById("adjlist"); const calculate = document.getElementById("calculate"); const stderr = document.getElementById("stderr"); @@ -12,9 +16,29 @@ const serverhost = location.host; // regex to match `[ ] 0%` `[# ] 1%` `[## ] 2%` etc. const progressRegex = /\[\s*#*\s*\]\s*\d+%/g; +let activeViewer = null; + +function setPanelContent(panel, content, isEmpty = false) { + panel.innerHTML = content; + panel.classList.toggle("empty-state", isEmpty); +} + +function markPanelActive(panel) { + panel.classList.remove("empty-state"); +} + +function clearOutput() { + if (activeViewer) { + activeViewer.dispose(); + activeViewer = null; + } + stdout.innerHTML = ""; + stdout.classList.remove("empty-state"); +} calculate.onclick = () => { const alg = algorithm.value; + const format = outputFormat.value; const adj = []; for (const line of adjlist.value.trim().split("\n")) { const neighbors = line @@ -29,20 +53,22 @@ calculate.onclick = () => { } calculate.disabled = true; - stderr.innerHTML = ""; - stdout.innerHTML = ""; - runtime.innerHTML = ""; + setPanelContent(stderr, "Waiting for status...", true); + clearOutput(); + setPanelContent(runtime, "Running...", true); const socket = new WebSocket( `${ location.protocol === "https:" ? "wss:" : "ws:" - }//${serverhost}/stream_calc_genus` + }//${serverhost}/stream_calc_genus`, ); let laststderr = ""; let progress = ""; socket.onmessage = async (event) => { - const [type, data] = event.data.split(":", 2); + const separator = event.data.indexOf(":"); + const type = separator === -1 ? event.data : event.data.slice(0, separator); + const data = separator === -1 ? "" : event.data.slice(separator + 1); if (type === "STDERR") { const line = data + "
"; @@ -56,16 +82,48 @@ calculate.onclick = () => { } } console.log(line, progressRegex.test(line)); // magic line that makes it work + markPanelActive(stderr); stderr.innerHTML = laststderr + "
" + progress; } else if (type === "STDOUT") { + markPanelActive(stdout); stdout.innerHTML += data + "
"; } else if (type === "TIME") { + markPanelActive(runtime); runtime.innerHTML = data; + } else if (type === "JSON") { + clearOutput(); + const pre = document.createElement("pre"); + try { + pre.textContent = JSON.stringify(JSON.parse(data), null, 2); + } catch { + pre.textContent = data; + } + markPanelActive(stdout); + stdout.appendChild(pre); + } else if (type === "IMAGE") { + clearOutput(); + const image = document.createElement("img"); + image.src = data; + image.alt = "Graph embedding drawing"; + image.className = "embedding-image"; + markPanelActive(stdout); + stdout.appendChild(image); + } else if (type === "MODEL") { + clearOutput(); + try { + markPanelActive(stdout); + renderModel(JSON.parse(data), stdout); + } catch (error) { + const pre = document.createElement("pre"); + pre.textContent = error.stack || error.message || String(error); + markPanelActive(stdout); + stdout.appendChild(pre); + } } }; socket.onopen = () => { - socket.send(JSON.stringify({ adj, alg })); + socket.send(JSON.stringify({ adj, alg, outputFormat: format })); }; socket.onclose = () => { @@ -84,7 +142,7 @@ fetch(`${serverorigin}/adjacency_lists`).then(async (response) => { }); loadExample.onclick = async () => { const response = await fetch( - `${serverorigin}/adjacency_lists/${exampleSelect.value}` + `${serverorigin}/adjacency_lists/${exampleSelect.value}`, ); adjlist.value = await response.text(); // remove the first line @@ -94,3 +152,352 @@ loadExample.onclick = async () => { // remove whitespace at the end of each line adjlist.value = adjlist.value.replace(/\s+$/gm, ""); }; + +function parseObj(objText) { + const vertices = [[0, 0, 0]]; + const uvs = [[0, 0]]; + const positions = []; + const texcoords = []; + const indices = []; + const graphLines = []; + const graphPoints = []; + const graphPointLabels = new Map(); + const cornerIndices = new Map(); + + const addCorner = (token) => { + const [vertexToken, textureToken] = token.split("/"); + const vertexIndex = parseInt(vertexToken, 10); + const textureIndex = textureToken ? parseInt(textureToken, 10) : 0; + const key = `${vertexIndex}/${textureIndex}`; + let index = cornerIndices.get(key); + if (index !== undefined) return index; + + const vertex = vertices[vertexIndex]; + const uv = uvs[textureIndex] || [0, 0]; + index = positions.length / 3; + positions.push(vertex[0], vertex[1], vertex[2]); + texcoords.push(uv[0], uv[1]); + cornerIndices.set(key, index); + return index; + }; + + for (const rawLine of objText.split(/\r?\n/)) { + const line = rawLine.trim(); + if (line.startsWith("# graph_vertex_label ")) { + const parts = line.split(/\s+/); + const vertexIndex = parseInt(parts[2], 10); + const label = parts[3]; + const labelPosition = + parts.length >= 7 ? parts.slice(4, 7).map(Number) : null; + if (!Number.isNaN(vertexIndex) && label) { + graphPointLabels.set(vertexIndex, { + label, + labelPosition: + labelPosition && labelPosition.every(Number.isFinite) + ? labelPosition + : null, + }); + } + continue; + } + if (line === "" || line.startsWith("#")) continue; + const parts = line.split(/\s+/); + + if (parts[0] === "v") { + vertices.push(parts.slice(1, 4).map(Number)); + } else if (parts[0] === "vt") { + uvs.push(parts.slice(1, 3).map(Number)); + } else if (parts[0] === "f") { + const face = parts.slice(1).map(addCorner); + for (let i = 1; i < face.length - 1; i++) { + indices.push(face[0], face[i], face[i + 1]); + } + } else if (parts[0] === "l") { + const line = parts + .slice(1) + .map((token) => vertices[parseInt(token.split("/")[0], 10)]) + .filter(Boolean); + if (line.length >= 2) graphLines.push(line); + } else if (parts[0] === "p") { + for (const token of parts.slice(1)) { + const vertexIndex = parseInt(token.split("/")[0], 10); + const point = vertices[vertexIndex]; + const labelInfo = graphPointLabels.get(vertexIndex); + if (point) { + graphPoints.push({ + position: point, + label: labelInfo?.label || String(graphPoints.length + 1), + labelPosition: labelInfo?.labelPosition || null, + }); + } + } + } + } + + const geometry = new THREE.BufferGeometry(); + geometry.setAttribute( + "position", + new THREE.Float32BufferAttribute(positions, 3), + ); + geometry.setAttribute("uv", new THREE.Float32BufferAttribute(texcoords, 2)); + geometry.setIndex(indices); + geometry.computeVertexNormals(); + geometry.normalizeNormals(); + geometry.computeBoundingSphere(); + return { geometry, graphLines, graphPoints }; +} + +function makeTextSprite(text, size) { + const canvas = document.createElement("canvas"); + const context = canvas.getContext("2d"); + const fontSize = 44; + const padding = 14; + const label = String(text); + context.font = `700 ${fontSize}px system-ui, -apple-system, sans-serif`; + const metrics = context.measureText(label); + canvas.width = Math.ceil(metrics.width + padding * 2); + canvas.height = fontSize + padding * 2; + + context.font = `700 ${fontSize}px system-ui, -apple-system, sans-serif`; + context.textBaseline = "middle"; + context.lineJoin = "round"; + context.lineWidth = 8; + context.strokeStyle = "rgba(247, 247, 244, 0.96)"; + context.fillStyle = "#111111"; + context.strokeText(label, padding, canvas.height / 2); + context.fillText(label, padding, canvas.height / 2); + + const texture = new THREE.CanvasTexture(canvas); + texture.colorSpace = THREE.SRGBColorSpace; + const material = new THREE.SpriteMaterial({ + map: texture, + transparent: true, + depthTest: true, + depthWrite: false, + }); + const sprite = new THREE.Sprite(material); + const aspect = canvas.width / canvas.height; + sprite.scale.set(size * aspect, size, 1); + sprite.renderOrder = 10; + sprite.userData.dispose = () => { + texture.dispose(); + material.dispose(); + }; + return sprite; +} + +function makeGraphOverlay(graphLines, graphPoints, center, radius) { + const group = new THREE.Group(); + const strokeRadius = Math.max(radius * 0.0016, 0.0025); + const labelScale = Math.max(radius * 0.075, 0.1); + const labelOffset = Math.max(radius * 0.012, strokeRadius * 3); + const strokeMaterial = new THREE.MeshBasicMaterial({ + color: 0x111111, + depthTest: true, + depthWrite: false, + polygonOffset: true, + polygonOffsetFactor: -2, + polygonOffsetUnits: -2, + }); + const pointMaterial = new THREE.MeshBasicMaterial({ + color: 0xf3f3f0, + depthTest: true, + depthWrite: false, + polygonOffset: true, + polygonOffsetFactor: -2, + polygonOffsetUnits: -2, + }); + + const capPoints = []; + for (const line of graphLines) { + const points = line.map( + ([x, y, z]) => new THREE.Vector3(x - center.x, y - center.y, z - center.z), + ); + if (points.length > 0) { + capPoints.push(points[0], points[points.length - 1]); + } + const path = new THREE.CurvePath(); + for (let i = 0; i < points.length - 1; i++) { + path.add(new THREE.LineCurve3(points[i], points[i + 1])); + } + const tube = new THREE.TubeGeometry( + path, + Math.max(6, Math.min(2048, points.length - 1)), + strokeRadius, + 5, + false, + ); + group.add(new THREE.Mesh(tube, strokeMaterial)); + } + + if (capPoints.length > 0) { + const capGeometry = new THREE.SphereGeometry(strokeRadius * 1.08, 8, 6); + const capMesh = new THREE.InstancedMesh( + capGeometry, + strokeMaterial, + capPoints.length, + ); + const matrix = new THREE.Matrix4(); + capPoints.forEach((point, index) => { + matrix.setPosition(point); + capMesh.setMatrixAt(index, matrix); + }); + capMesh.instanceMatrix.needsUpdate = true; + group.add(capMesh); + } + + if (graphPoints.length > 0) { + const pointGeometry = new THREE.SphereGeometry(strokeRadius * 1.25, 12, 8); + const pointMesh = new THREE.InstancedMesh( + pointGeometry, + pointMaterial, + graphPoints.length, + ); + const matrix = new THREE.Matrix4(); + graphPoints.forEach(({ position: [x, y, z] }, index) => { + matrix.setPosition(x - center.x, y - center.y, z - center.z); + pointMesh.setMatrixAt(index, matrix); + }); + pointMesh.instanceMatrix.needsUpdate = true; + group.add(pointMesh); + + graphPoints.forEach(({ position: [x, y, z], label, labelPosition }) => { + const position = labelPosition + ? new THREE.Vector3( + labelPosition[0] - center.x, + labelPosition[1] - center.y, + labelPosition[2] - center.z, + ) + : new THREE.Vector3(x - center.x, y - center.y, z - center.z); + const sprite = makeTextSprite(label, labelScale); + if (labelPosition) { + sprite.position.copy(position); + } else { + const normal = position.lengthSq() > 1e-10 + ? position.clone().normalize() + : new THREE.Vector3(0, 0, 1); + sprite.position.copy(position.addScaledVector(normal, labelOffset)); + } + group.add(sprite); + }); + } + + group.userData.dispose = () => { + group.traverse((child) => { + if (child.geometry) child.geometry.dispose(); + if (child !== group && child.userData?.dispose) child.userData.dispose(); + }); + strokeMaterial.dispose(); + pointMaterial.dispose(); + }; + return group; +} + +function renderModel(model, container) { + if (activeViewer) { + activeViewer.dispose(); + activeViewer = null; + } + + const viewer = document.createElement("div"); + viewer.className = "model-viewer"; + container.appendChild(viewer); + + const renderer = new THREE.WebGLRenderer({ antialias: true }); + renderer.setPixelRatio(Math.min(window.devicePixelRatio, 2)); + renderer.setSize(viewer.clientWidth, viewer.clientHeight); + renderer.outputColorSpace = THREE.SRGBColorSpace; + viewer.appendChild(renderer.domElement); + + const scene = new THREE.Scene(); + scene.background = new THREE.Color(0xf7f7f4); + + const camera = new THREE.PerspectiveCamera( + 45, + viewer.clientWidth / viewer.clientHeight, + 0.01, + 1000, + ); + camera.position.set(0, -7, 4); + + const controls = new OrbitControls(camera, renderer.domElement); + controls.enableDamping = true; + + const parsedObj = parseObj(model.obj); + const { geometry, graphLines, graphPoints } = parsedObj; + geometry.computeBoundingBox(); + const center = new THREE.Vector3(); + geometry.boundingBox.getCenter(center); + geometry.translate(-center.x, -center.y, -center.z); + geometry.computeBoundingSphere(); + + const radius = geometry.boundingSphere?.radius || 1; + if (model.genus === 0 && graphPoints.length > 0) { + const graphCenter = new THREE.Vector3(); + graphPoints.forEach(({ position: [x, y, z] }) => { + graphCenter.add(new THREE.Vector3(x - center.x, y - center.y, z - center.z)); + }); + graphCenter.multiplyScalar(1 / graphPoints.length); + if (graphCenter.lengthSq() > 1e-10) { + graphCenter.normalize(); + camera.position.copy(graphCenter.multiplyScalar(radius * 3.2)); + } else { + camera.position.set(0, -radius * 2.6, radius * 1.3); + } + } else { + camera.position.set(0, -radius * 2.6, radius * 1.3); + } + camera.near = Math.max(0.01, radius / 100); + camera.far = radius * 20; + camera.updateProjectionMatrix(); + controls.target.set(0, 0, 0); + controls.update(); + + const material = new THREE.MeshStandardMaterial({ + color: 0xc8cac7, + side: THREE.DoubleSide, + roughness: 0.66, + metalness: 0.02, + }); + const mesh = new THREE.Mesh(geometry, material); + scene.add(mesh); + const graphOverlay = makeGraphOverlay(graphLines, graphPoints, center, radius); + scene.add(graphOverlay); + + scene.add(new THREE.HemisphereLight(0xffffff, 0x777777, 2.2)); + const key = new THREE.DirectionalLight(0xffffff, 1.8); + key.position.set(4, -5, 7); + scene.add(key); + + const resizeObserver = new ResizeObserver(() => { + const width = viewer.clientWidth; + const height = viewer.clientHeight; + if (!width || !height) return; + renderer.setSize(width, height); + camera.aspect = width / height; + camera.updateProjectionMatrix(); + }); + resizeObserver.observe(viewer); + + let running = true; + const animate = () => { + if (!running) return; + controls.update(); + renderer.render(scene, camera); + requestAnimationFrame(animate); + }; + animate(); + + activeViewer = { + dispose() { + running = false; + resizeObserver.disconnect(); + controls.dispose(); + geometry.dispose(); + material.dispose(); + graphOverlay.userData.dispose(); + renderer.dispose(); + viewer.remove(); + }, + }; +} diff --git a/WebApp/static/style.css b/WebApp/static/style.css new file mode 100644 index 0000000..7280c9c --- /dev/null +++ b/WebApp/static/style.css @@ -0,0 +1,357 @@ +:root { + color-scheme: light; + --ink: #171a1f; + --muted: #5f6671; + --panel: rgba(251, 251, 248, 0.88); + --panel-strong: rgba(255, 255, 252, 0.96); + --border: rgba(32, 38, 46, 0.16); + --blue: #0867d8; + --blue-strong: #095fc4; + --blue-soft: rgba(8, 103, 216, 0.13); + --green: #237052; + --surface: #f5f5f0; + --shadow: 0 18px 46px rgba(29, 35, 43, 0.15); +} + +* { + box-sizing: border-box; +} + +html, +body { + margin: 0; + min-height: 100%; + font-family: Inter, ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif; + color: var(--ink); + background: var(--surface); +} + +button, +select, +textarea { + font: inherit; +} + +button, +select { + min-height: 40px; +} + +button { + cursor: pointer; +} + +.app-shell { + min-height: 100vh; + padding: 22px; + background: + linear-gradient(180deg, rgba(255, 255, 255, 0.72), rgba(244, 245, 241, 0.94)), + #f7f7f3; +} + +.calculator-stage { + width: min(1380px, 100%); + min-height: calc(100vh - 44px); + margin: 0 auto; + display: grid; + grid-template-columns: minmax(360px, 0.82fr) minmax(0, 1.18fr); + gap: 16px; +} + +.input-panel, +.result-card { + border: 1px solid var(--border); + border-radius: 8px; + background: var(--panel-strong); + box-shadow: var(--shadow); + backdrop-filter: blur(16px); +} + +.input-panel { + display: grid; + align-content: start; + gap: 16px; + padding: 20px; +} + +.panel-header { + display: grid; + gap: 8px; +} + +.eyebrow { + margin: 0; + color: var(--blue); + font-size: 12px; + font-weight: 850; + letter-spacing: 0.08em; + text-transform: uppercase; +} + +h1, +h2, +p { + margin: 0; +} + +h1 { + font-size: clamp(30px, 4vw, 54px); + line-height: 0.98; + letter-spacing: 0; +} + +.lede { + max-width: 52ch; + color: var(--muted); + font-size: 15px; + line-height: 1.48; +} + +.control-grid, +.example-row { + display: grid; + gap: 10px; +} + +.control-grid { + grid-template-columns: repeat(2, minmax(0, 1fr)); +} + +.example-row { + grid-template-columns: minmax(0, 1fr) 92px; + align-items: end; +} + +.field { + display: grid; + gap: 7px; + color: var(--muted); + font-size: 12px; + font-weight: 780; +} + +select, +textarea { + width: 100%; + border: 1px solid rgba(32, 38, 46, 0.18); + border-radius: 8px; + background: #fff; + color: var(--ink); +} + +select { + padding: 0 10px; +} + +select:focus, +textarea:focus, +button:focus-visible { + outline: 2px solid rgba(8, 103, 216, 0.28); + outline-offset: 2px; +} + +textarea { + min-height: 340px; + max-height: 52vh; + resize: vertical; + padding: 13px 14px; + font-family: ui-monospace, SFMono-Regular, Menlo, Consolas, monospace; + font-size: 13px; + line-height: 1.45; +} + +.secondary-action, +.primary-action { + border-radius: 8px; + font-weight: 800; +} + +.secondary-action { + border: 1px solid rgba(32, 38, 46, 0.16); + background: #fff; + color: var(--ink); +} + +.secondary-action:hover { + border-color: rgba(8, 103, 216, 0.42); + background: rgba(255, 255, 255, 0.95); +} + +.primary-action { + min-height: 44px; + border: 1px solid rgba(5, 73, 154, 0.18); + background: var(--blue-strong); + color: #fff; + padding: 0 20px; + box-shadow: 0 8px 28px rgba(17, 68, 125, 0.19); +} + +.primary-action:disabled { + cursor: default; + background: #7b8490; + box-shadow: none; +} + +.input-footer { + display: grid; + grid-template-columns: minmax(0, 1fr) auto; + gap: 14px; + align-items: center; +} + +.hint { + color: var(--muted); + font-size: 13px; + line-height: 1.4; +} + +.result-panel { + min-width: 0; + display: grid; + grid-template-rows: minmax(360px, 1fr) auto; + gap: 16px; +} + +.result-card { + min-width: 0; + display: grid; + grid-template-rows: auto minmax(0, 1fr); + padding: 14px; +} + +.output-card { + min-height: 0; +} + +.card-title { + display: flex; + align-items: center; + justify-content: space-between; + min-height: 28px; + margin-bottom: 10px; +} + +.card-title h2 { + font-size: 14px; + line-height: 1.2; +} + +.output-box, +.log-box, +.runtime-box { + min-width: 0; + border: 1px solid rgba(32, 38, 46, 0.10); + border-radius: 8px; + background: rgba(255, 255, 255, 0.74); + color: var(--ink); +} + +.output-box { + min-height: 420px; + overflow: auto; + padding: 14px; +} + +.log-box, +.runtime-box { + min-height: 112px; + overflow: auto; + padding: 12px; + color: var(--muted); + font-size: 13px; + line-height: 1.45; +} + +.runtime-box { + display: flex; + align-items: center; + color: var(--green); + font-weight: 850; + font-variant-numeric: tabular-nums; +} + +.empty-state { + color: var(--muted); +} + +#stdout pre { + margin: 0; + white-space: pre-wrap; + overflow-wrap: anywhere; + font-family: ui-monospace, SFMono-Regular, Menlo, Consolas, monospace; + font-size: 13px; + line-height: 1.45; +} + +.embedding-image { + display: block; + width: min(100%, 760px); + max-height: 68vh; + object-fit: contain; + margin: 0 auto; +} + +.model-viewer { + height: calc(100% + 28px); + border: 1px solid rgba(32, 38, 46, 0.14); + border-radius: 8px; + background: #f7f7f4; + overflow: hidden; + margin: -14px; +} + +.model-viewer canvas { + display: block; +} + +@media (max-width: 980px) { + .app-shell { + padding: 12px; + } + + .calculator-stage { + min-height: calc(100vh - 24px); + grid-template-columns: 1fr; + } + + .result-panel { + grid-template-rows: auto auto; + } +} + +@media (max-width: 700px) { + h1 { + font-size: 36px; + } + + .input-panel, + .result-card { + box-shadow: none; + backdrop-filter: none; + } + + .control-grid, + .example-row, + .input-footer { + grid-template-columns: 1fr; + } + + .primary-action, + .secondary-action { + width: 100%; + } + + textarea { + min-height: 260px; + max-height: none; + } + + .output-box { + min-height: 280px; + } + + .model-viewer { + min-height: 340px; + height: 58vh; + } +} diff --git a/WebApp/static/vendor/OrbitControls.js b/WebApp/static/vendor/OrbitControls.js new file mode 100644 index 0000000..d21c1eb --- /dev/null +++ b/WebApp/static/vendor/OrbitControls.js @@ -0,0 +1,1532 @@ +import { + EventDispatcher, + MOUSE, + Quaternion, + Spherical, + TOUCH, + Vector2, + Vector3, + Plane, + Ray, + MathUtils +} from 'three'; + +// OrbitControls performs orbiting, dollying (zooming), and panning. +// Unlike TrackballControls, it maintains the "up" direction object.up (+Y by default). +// +// Orbit - left mouse / touch: one-finger move +// Zoom - middle mouse, or mousewheel / touch: two-finger spread or squish +// Pan - right mouse, or left mouse + ctrl/meta/shiftKey, or arrow keys / touch: two-finger move + +const _changeEvent = { type: 'change' }; +const _startEvent = { type: 'start' }; +const _endEvent = { type: 'end' }; +const _ray = new Ray(); +const _plane = new Plane(); +const TILT_LIMIT = Math.cos( 70 * MathUtils.DEG2RAD ); + +class OrbitControls extends EventDispatcher { + + constructor( object, domElement ) { + + super(); + + this.object = object; + this.domElement = domElement; + this.domElement.style.touchAction = 'none'; // disable touch scroll + + // Set to false to disable this control + this.enabled = true; + + // "target" sets the location of focus, where the object orbits around + this.target = new Vector3(); + + // Sets the 3D cursor (similar to Blender), from which the maxTargetRadius takes effect + this.cursor = new Vector3(); + + // How far you can dolly in and out ( PerspectiveCamera only ) + this.minDistance = 0; + this.maxDistance = Infinity; + + // How far you can zoom in and out ( OrthographicCamera only ) + this.minZoom = 0; + this.maxZoom = Infinity; + + // Limit camera target within a spherical area around the cursor + this.minTargetRadius = 0; + this.maxTargetRadius = Infinity; + + // How far you can orbit vertically, upper and lower limits. + // Range is 0 to Math.PI radians. + this.minPolarAngle = 0; // radians + this.maxPolarAngle = Math.PI; // radians + + // How far you can orbit horizontally, upper and lower limits. + // If set, the interval [ min, max ] must be a sub-interval of [ - 2 PI, 2 PI ], with ( max - min < 2 PI ) + this.minAzimuthAngle = - Infinity; // radians + this.maxAzimuthAngle = Infinity; // radians + + // Set to true to enable damping (inertia) + // If damping is enabled, you must call controls.update() in your animation loop + this.enableDamping = false; + this.dampingFactor = 0.05; + + // This option actually enables dollying in and out; left as "zoom" for backwards compatibility. + // Set to false to disable zooming + this.enableZoom = true; + this.zoomSpeed = 1.0; + + // Set to false to disable rotating + this.enableRotate = true; + this.rotateSpeed = 1.0; + + // Set to false to disable panning + this.enablePan = true; + this.panSpeed = 1.0; + this.screenSpacePanning = true; // if false, pan orthogonal to world-space direction camera.up + this.keyPanSpeed = 7.0; // pixels moved per arrow key push + this.zoomToCursor = false; + + // Set to true to automatically rotate around the target + // If auto-rotate is enabled, you must call controls.update() in your animation loop + this.autoRotate = false; + this.autoRotateSpeed = 2.0; // 30 seconds per orbit when fps is 60 + + // The four arrow keys + this.keys = { LEFT: 'ArrowLeft', UP: 'ArrowUp', RIGHT: 'ArrowRight', BOTTOM: 'ArrowDown' }; + + // Mouse buttons + this.mouseButtons = { LEFT: MOUSE.ROTATE, MIDDLE: MOUSE.DOLLY, RIGHT: MOUSE.PAN }; + + // Touch fingers + this.touches = { ONE: TOUCH.ROTATE, TWO: TOUCH.DOLLY_PAN }; + + // for reset + this.target0 = this.target.clone(); + this.position0 = this.object.position.clone(); + this.zoom0 = this.object.zoom; + + // the target DOM element for key events + this._domElementKeyEvents = null; + + // + // public methods + // + + this.getPolarAngle = function () { + + return spherical.phi; + + }; + + this.getAzimuthalAngle = function () { + + return spherical.theta; + + }; + + this.getDistance = function () { + + return this.object.position.distanceTo( this.target ); + + }; + + this.listenToKeyEvents = function ( domElement ) { + + domElement.addEventListener( 'keydown', onKeyDown ); + this._domElementKeyEvents = domElement; + + }; + + this.stopListenToKeyEvents = function () { + + this._domElementKeyEvents.removeEventListener( 'keydown', onKeyDown ); + this._domElementKeyEvents = null; + + }; + + this.saveState = function () { + + scope.target0.copy( scope.target ); + scope.position0.copy( scope.object.position ); + scope.zoom0 = scope.object.zoom; + + }; + + this.reset = function () { + + scope.target.copy( scope.target0 ); + scope.object.position.copy( scope.position0 ); + scope.object.zoom = scope.zoom0; + + scope.object.updateProjectionMatrix(); + scope.dispatchEvent( _changeEvent ); + + scope.update(); + + state = STATE.NONE; + + }; + + // this method is exposed, but perhaps it would be better if we can make it private... + this.update = function () { + + const offset = new Vector3(); + + // so camera.up is the orbit axis + const quat = new Quaternion().setFromUnitVectors( object.up, new Vector3( 0, 1, 0 ) ); + const quatInverse = quat.clone().invert(); + + const lastPosition = new Vector3(); + const lastQuaternion = new Quaternion(); + const lastTargetPosition = new Vector3(); + + const twoPI = 2 * Math.PI; + + return function update( deltaTime = null ) { + + const position = scope.object.position; + + offset.copy( position ).sub( scope.target ); + + // rotate offset to "y-axis-is-up" space + offset.applyQuaternion( quat ); + + // angle from z-axis around y-axis + spherical.setFromVector3( offset ); + + if ( scope.autoRotate && state === STATE.NONE ) { + + rotateLeft( getAutoRotationAngle( deltaTime ) ); + + } + + if ( scope.enableDamping ) { + + spherical.theta += sphericalDelta.theta * scope.dampingFactor; + spherical.phi += sphericalDelta.phi * scope.dampingFactor; + + } else { + + spherical.theta += sphericalDelta.theta; + spherical.phi += sphericalDelta.phi; + + } + + // restrict theta to be between desired limits + + let min = scope.minAzimuthAngle; + let max = scope.maxAzimuthAngle; + + if ( isFinite( min ) && isFinite( max ) ) { + + if ( min < - Math.PI ) min += twoPI; else if ( min > Math.PI ) min -= twoPI; + + if ( max < - Math.PI ) max += twoPI; else if ( max > Math.PI ) max -= twoPI; + + if ( min <= max ) { + + spherical.theta = Math.max( min, Math.min( max, spherical.theta ) ); + + } else { + + spherical.theta = ( spherical.theta > ( min + max ) / 2 ) ? + Math.max( min, spherical.theta ) : + Math.min( max, spherical.theta ); + + } + + } + + // restrict phi to be between desired limits + spherical.phi = Math.max( scope.minPolarAngle, Math.min( scope.maxPolarAngle, spherical.phi ) ); + + spherical.makeSafe(); + + + // move target to panned location + + if ( scope.enableDamping === true ) { + + scope.target.addScaledVector( panOffset, scope.dampingFactor ); + + } else { + + scope.target.add( panOffset ); + + } + + // Limit the target distance from the cursor to create a sphere around the center of interest + scope.target.sub( scope.cursor ); + scope.target.clampLength( scope.minTargetRadius, scope.maxTargetRadius ); + scope.target.add( scope.cursor ); + + let zoomChanged = false; + // adjust the camera position based on zoom only if we're not zooming to the cursor or if it's an ortho camera + // we adjust zoom later in these cases + if ( scope.zoomToCursor && performCursorZoom || scope.object.isOrthographicCamera ) { + + spherical.radius = clampDistance( spherical.radius ); + + } else { + + const prevRadius = spherical.radius; + spherical.radius = clampDistance( spherical.radius * scale ); + zoomChanged = prevRadius != spherical.radius; + + } + + offset.setFromSpherical( spherical ); + + // rotate offset back to "camera-up-vector-is-up" space + offset.applyQuaternion( quatInverse ); + + position.copy( scope.target ).add( offset ); + + scope.object.lookAt( scope.target ); + + if ( scope.enableDamping === true ) { + + sphericalDelta.theta *= ( 1 - scope.dampingFactor ); + sphericalDelta.phi *= ( 1 - scope.dampingFactor ); + + panOffset.multiplyScalar( 1 - scope.dampingFactor ); + + } else { + + sphericalDelta.set( 0, 0, 0 ); + + panOffset.set( 0, 0, 0 ); + + } + + // adjust camera position + if ( scope.zoomToCursor && performCursorZoom ) { + + let newRadius = null; + if ( scope.object.isPerspectiveCamera ) { + + // move the camera down the pointer ray + // this method avoids floating point error + const prevRadius = offset.length(); + newRadius = clampDistance( prevRadius * scale ); + + const radiusDelta = prevRadius - newRadius; + scope.object.position.addScaledVector( dollyDirection, radiusDelta ); + scope.object.updateMatrixWorld(); + + zoomChanged = !! radiusDelta; + + } else if ( scope.object.isOrthographicCamera ) { + + // adjust the ortho camera position based on zoom changes + const mouseBefore = new Vector3( mouse.x, mouse.y, 0 ); + mouseBefore.unproject( scope.object ); + + const prevZoom = scope.object.zoom; + scope.object.zoom = Math.max( scope.minZoom, Math.min( scope.maxZoom, scope.object.zoom / scale ) ); + scope.object.updateProjectionMatrix(); + + zoomChanged = prevZoom !== scope.object.zoom; + + const mouseAfter = new Vector3( mouse.x, mouse.y, 0 ); + mouseAfter.unproject( scope.object ); + + scope.object.position.sub( mouseAfter ).add( mouseBefore ); + scope.object.updateMatrixWorld(); + + newRadius = offset.length(); + + } else { + + console.warn( 'WARNING: OrbitControls.js encountered an unknown camera type - zoom to cursor disabled.' ); + scope.zoomToCursor = false; + + } + + // handle the placement of the target + if ( newRadius !== null ) { + + if ( this.screenSpacePanning ) { + + // position the orbit target in front of the new camera position + scope.target.set( 0, 0, - 1 ) + .transformDirection( scope.object.matrix ) + .multiplyScalar( newRadius ) + .add( scope.object.position ); + + } else { + + // get the ray and translation plane to compute target + _ray.origin.copy( scope.object.position ); + _ray.direction.set( 0, 0, - 1 ).transformDirection( scope.object.matrix ); + + // if the camera is 20 degrees above the horizon then don't adjust the focus target to avoid + // extremely large values + if ( Math.abs( scope.object.up.dot( _ray.direction ) ) < TILT_LIMIT ) { + + object.lookAt( scope.target ); + + } else { + + _plane.setFromNormalAndCoplanarPoint( scope.object.up, scope.target ); + _ray.intersectPlane( _plane, scope.target ); + + } + + } + + } + + } else if ( scope.object.isOrthographicCamera ) { + + const prevZoom = scope.object.zoom; + scope.object.zoom = Math.max( scope.minZoom, Math.min( scope.maxZoom, scope.object.zoom / scale ) ); + + if ( prevZoom !== scope.object.zoom ) { + + scope.object.updateProjectionMatrix(); + zoomChanged = true; + + } + + } + + scale = 1; + performCursorZoom = false; + + // update condition is: + // min(camera displacement, camera rotation in radians)^2 > EPS + // using small-angle approximation cos(x/2) = 1 - x^2 / 8 + + if ( zoomChanged || + lastPosition.distanceToSquared( scope.object.position ) > EPS || + 8 * ( 1 - lastQuaternion.dot( scope.object.quaternion ) ) > EPS || + lastTargetPosition.distanceToSquared( scope.target ) > EPS ) { + + scope.dispatchEvent( _changeEvent ); + + lastPosition.copy( scope.object.position ); + lastQuaternion.copy( scope.object.quaternion ); + lastTargetPosition.copy( scope.target ); + + return true; + + } + + return false; + + }; + + }(); + + this.dispose = function () { + + scope.domElement.removeEventListener( 'contextmenu', onContextMenu ); + + scope.domElement.removeEventListener( 'pointerdown', onPointerDown ); + scope.domElement.removeEventListener( 'pointercancel', onPointerUp ); + scope.domElement.removeEventListener( 'wheel', onMouseWheel ); + + scope.domElement.removeEventListener( 'pointermove', onPointerMove ); + scope.domElement.removeEventListener( 'pointerup', onPointerUp ); + + const document = scope.domElement.getRootNode(); // offscreen canvas compatibility + + document.removeEventListener( 'keydown', interceptControlDown, { capture: true } ); + + if ( scope._domElementKeyEvents !== null ) { + + scope._domElementKeyEvents.removeEventListener( 'keydown', onKeyDown ); + scope._domElementKeyEvents = null; + + } + + //scope.dispatchEvent( { type: 'dispose' } ); // should this be added here? + + }; + + // + // internals + // + + const scope = this; + + const STATE = { + NONE: - 1, + ROTATE: 0, + DOLLY: 1, + PAN: 2, + TOUCH_ROTATE: 3, + TOUCH_PAN: 4, + TOUCH_DOLLY_PAN: 5, + TOUCH_DOLLY_ROTATE: 6 + }; + + let state = STATE.NONE; + + const EPS = 0.000001; + + // current position in spherical coordinates + const spherical = new Spherical(); + const sphericalDelta = new Spherical(); + + let scale = 1; + const panOffset = new Vector3(); + + const rotateStart = new Vector2(); + const rotateEnd = new Vector2(); + const rotateDelta = new Vector2(); + + const panStart = new Vector2(); + const panEnd = new Vector2(); + const panDelta = new Vector2(); + + const dollyStart = new Vector2(); + const dollyEnd = new Vector2(); + const dollyDelta = new Vector2(); + + const dollyDirection = new Vector3(); + const mouse = new Vector2(); + let performCursorZoom = false; + + const pointers = []; + const pointerPositions = {}; + + let controlActive = false; + + function getAutoRotationAngle( deltaTime ) { + + if ( deltaTime !== null ) { + + return ( 2 * Math.PI / 60 * scope.autoRotateSpeed ) * deltaTime; + + } else { + + return 2 * Math.PI / 60 / 60 * scope.autoRotateSpeed; + + } + + } + + function getZoomScale( delta ) { + + const normalizedDelta = Math.abs( delta * 0.01 ); + return Math.pow( 0.95, scope.zoomSpeed * normalizedDelta ); + + } + + function rotateLeft( angle ) { + + sphericalDelta.theta -= angle; + + } + + function rotateUp( angle ) { + + sphericalDelta.phi -= angle; + + } + + const panLeft = function () { + + const v = new Vector3(); + + return function panLeft( distance, objectMatrix ) { + + v.setFromMatrixColumn( objectMatrix, 0 ); // get X column of objectMatrix + v.multiplyScalar( - distance ); + + panOffset.add( v ); + + }; + + }(); + + const panUp = function () { + + const v = new Vector3(); + + return function panUp( distance, objectMatrix ) { + + if ( scope.screenSpacePanning === true ) { + + v.setFromMatrixColumn( objectMatrix, 1 ); + + } else { + + v.setFromMatrixColumn( objectMatrix, 0 ); + v.crossVectors( scope.object.up, v ); + + } + + v.multiplyScalar( distance ); + + panOffset.add( v ); + + }; + + }(); + + // deltaX and deltaY are in pixels; right and down are positive + const pan = function () { + + const offset = new Vector3(); + + return function pan( deltaX, deltaY ) { + + const element = scope.domElement; + + if ( scope.object.isPerspectiveCamera ) { + + // perspective + const position = scope.object.position; + offset.copy( position ).sub( scope.target ); + let targetDistance = offset.length(); + + // half of the fov is center to top of screen + targetDistance *= Math.tan( ( scope.object.fov / 2 ) * Math.PI / 180.0 ); + + // we use only clientHeight here so aspect ratio does not distort speed + panLeft( 2 * deltaX * targetDistance / element.clientHeight, scope.object.matrix ); + panUp( 2 * deltaY * targetDistance / element.clientHeight, scope.object.matrix ); + + } else if ( scope.object.isOrthographicCamera ) { + + // orthographic + panLeft( deltaX * ( scope.object.right - scope.object.left ) / scope.object.zoom / element.clientWidth, scope.object.matrix ); + panUp( deltaY * ( scope.object.top - scope.object.bottom ) / scope.object.zoom / element.clientHeight, scope.object.matrix ); + + } else { + + // camera neither orthographic nor perspective + console.warn( 'WARNING: OrbitControls.js encountered an unknown camera type - pan disabled.' ); + scope.enablePan = false; + + } + + }; + + }(); + + function dollyOut( dollyScale ) { + + if ( scope.object.isPerspectiveCamera || scope.object.isOrthographicCamera ) { + + scale /= dollyScale; + + } else { + + console.warn( 'WARNING: OrbitControls.js encountered an unknown camera type - dolly/zoom disabled.' ); + scope.enableZoom = false; + + } + + } + + function dollyIn( dollyScale ) { + + if ( scope.object.isPerspectiveCamera || scope.object.isOrthographicCamera ) { + + scale *= dollyScale; + + } else { + + console.warn( 'WARNING: OrbitControls.js encountered an unknown camera type - dolly/zoom disabled.' ); + scope.enableZoom = false; + + } + + } + + function updateZoomParameters( x, y ) { + + if ( ! scope.zoomToCursor ) { + + return; + + } + + performCursorZoom = true; + + const rect = scope.domElement.getBoundingClientRect(); + const dx = x - rect.left; + const dy = y - rect.top; + const w = rect.width; + const h = rect.height; + + mouse.x = ( dx / w ) * 2 - 1; + mouse.y = - ( dy / h ) * 2 + 1; + + dollyDirection.set( mouse.x, mouse.y, 1 ).unproject( scope.object ).sub( scope.object.position ).normalize(); + + } + + function clampDistance( dist ) { + + return Math.max( scope.minDistance, Math.min( scope.maxDistance, dist ) ); + + } + + // + // event callbacks - update the object state + // + + function handleMouseDownRotate( event ) { + + rotateStart.set( event.clientX, event.clientY ); + + } + + function handleMouseDownDolly( event ) { + + updateZoomParameters( event.clientX, event.clientX ); + dollyStart.set( event.clientX, event.clientY ); + + } + + function handleMouseDownPan( event ) { + + panStart.set( event.clientX, event.clientY ); + + } + + function handleMouseMoveRotate( event ) { + + rotateEnd.set( event.clientX, event.clientY ); + + rotateDelta.subVectors( rotateEnd, rotateStart ).multiplyScalar( scope.rotateSpeed ); + + const element = scope.domElement; + + rotateLeft( 2 * Math.PI * rotateDelta.x / element.clientHeight ); // yes, height + + rotateUp( 2 * Math.PI * rotateDelta.y / element.clientHeight ); + + rotateStart.copy( rotateEnd ); + + scope.update(); + + } + + function handleMouseMoveDolly( event ) { + + dollyEnd.set( event.clientX, event.clientY ); + + dollyDelta.subVectors( dollyEnd, dollyStart ); + + if ( dollyDelta.y > 0 ) { + + dollyOut( getZoomScale( dollyDelta.y ) ); + + } else if ( dollyDelta.y < 0 ) { + + dollyIn( getZoomScale( dollyDelta.y ) ); + + } + + dollyStart.copy( dollyEnd ); + + scope.update(); + + } + + function handleMouseMovePan( event ) { + + panEnd.set( event.clientX, event.clientY ); + + panDelta.subVectors( panEnd, panStart ).multiplyScalar( scope.panSpeed ); + + pan( panDelta.x, panDelta.y ); + + panStart.copy( panEnd ); + + scope.update(); + + } + + function handleMouseWheel( event ) { + + updateZoomParameters( event.clientX, event.clientY ); + + if ( event.deltaY < 0 ) { + + dollyIn( getZoomScale( event.deltaY ) ); + + } else if ( event.deltaY > 0 ) { + + dollyOut( getZoomScale( event.deltaY ) ); + + } + + scope.update(); + + } + + function handleKeyDown( event ) { + + let needsUpdate = false; + + switch ( event.code ) { + + case scope.keys.UP: + + if ( event.ctrlKey || event.metaKey || event.shiftKey ) { + + rotateUp( 2 * Math.PI * scope.rotateSpeed / scope.domElement.clientHeight ); + + } else { + + pan( 0, scope.keyPanSpeed ); + + } + + needsUpdate = true; + break; + + case scope.keys.BOTTOM: + + if ( event.ctrlKey || event.metaKey || event.shiftKey ) { + + rotateUp( - 2 * Math.PI * scope.rotateSpeed / scope.domElement.clientHeight ); + + } else { + + pan( 0, - scope.keyPanSpeed ); + + } + + needsUpdate = true; + break; + + case scope.keys.LEFT: + + if ( event.ctrlKey || event.metaKey || event.shiftKey ) { + + rotateLeft( 2 * Math.PI * scope.rotateSpeed / scope.domElement.clientHeight ); + + } else { + + pan( scope.keyPanSpeed, 0 ); + + } + + needsUpdate = true; + break; + + case scope.keys.RIGHT: + + if ( event.ctrlKey || event.metaKey || event.shiftKey ) { + + rotateLeft( - 2 * Math.PI * scope.rotateSpeed / scope.domElement.clientHeight ); + + } else { + + pan( - scope.keyPanSpeed, 0 ); + + } + + needsUpdate = true; + break; + + } + + if ( needsUpdate ) { + + // prevent the browser from scrolling on cursor keys + event.preventDefault(); + + scope.update(); + + } + + + } + + function handleTouchStartRotate( event ) { + + if ( pointers.length === 1 ) { + + rotateStart.set( event.pageX, event.pageY ); + + } else { + + const position = getSecondPointerPosition( event ); + + const x = 0.5 * ( event.pageX + position.x ); + const y = 0.5 * ( event.pageY + position.y ); + + rotateStart.set( x, y ); + + } + + } + + function handleTouchStartPan( event ) { + + if ( pointers.length === 1 ) { + + panStart.set( event.pageX, event.pageY ); + + } else { + + const position = getSecondPointerPosition( event ); + + const x = 0.5 * ( event.pageX + position.x ); + const y = 0.5 * ( event.pageY + position.y ); + + panStart.set( x, y ); + + } + + } + + function handleTouchStartDolly( event ) { + + const position = getSecondPointerPosition( event ); + + const dx = event.pageX - position.x; + const dy = event.pageY - position.y; + + const distance = Math.sqrt( dx * dx + dy * dy ); + + dollyStart.set( 0, distance ); + + } + + function handleTouchStartDollyPan( event ) { + + if ( scope.enableZoom ) handleTouchStartDolly( event ); + + if ( scope.enablePan ) handleTouchStartPan( event ); + + } + + function handleTouchStartDollyRotate( event ) { + + if ( scope.enableZoom ) handleTouchStartDolly( event ); + + if ( scope.enableRotate ) handleTouchStartRotate( event ); + + } + + function handleTouchMoveRotate( event ) { + + if ( pointers.length == 1 ) { + + rotateEnd.set( event.pageX, event.pageY ); + + } else { + + const position = getSecondPointerPosition( event ); + + const x = 0.5 * ( event.pageX + position.x ); + const y = 0.5 * ( event.pageY + position.y ); + + rotateEnd.set( x, y ); + + } + + rotateDelta.subVectors( rotateEnd, rotateStart ).multiplyScalar( scope.rotateSpeed ); + + const element = scope.domElement; + + rotateLeft( 2 * Math.PI * rotateDelta.x / element.clientHeight ); // yes, height + + rotateUp( 2 * Math.PI * rotateDelta.y / element.clientHeight ); + + rotateStart.copy( rotateEnd ); + + } + + function handleTouchMovePan( event ) { + + if ( pointers.length === 1 ) { + + panEnd.set( event.pageX, event.pageY ); + + } else { + + const position = getSecondPointerPosition( event ); + + const x = 0.5 * ( event.pageX + position.x ); + const y = 0.5 * ( event.pageY + position.y ); + + panEnd.set( x, y ); + + } + + panDelta.subVectors( panEnd, panStart ).multiplyScalar( scope.panSpeed ); + + pan( panDelta.x, panDelta.y ); + + panStart.copy( panEnd ); + + } + + function handleTouchMoveDolly( event ) { + + const position = getSecondPointerPosition( event ); + + const dx = event.pageX - position.x; + const dy = event.pageY - position.y; + + const distance = Math.sqrt( dx * dx + dy * dy ); + + dollyEnd.set( 0, distance ); + + dollyDelta.set( 0, Math.pow( dollyEnd.y / dollyStart.y, scope.zoomSpeed ) ); + + dollyOut( dollyDelta.y ); + + dollyStart.copy( dollyEnd ); + + const centerX = ( event.pageX + position.x ) * 0.5; + const centerY = ( event.pageY + position.y ) * 0.5; + + updateZoomParameters( centerX, centerY ); + + } + + function handleTouchMoveDollyPan( event ) { + + if ( scope.enableZoom ) handleTouchMoveDolly( event ); + + if ( scope.enablePan ) handleTouchMovePan( event ); + + } + + function handleTouchMoveDollyRotate( event ) { + + if ( scope.enableZoom ) handleTouchMoveDolly( event ); + + if ( scope.enableRotate ) handleTouchMoveRotate( event ); + + } + + // + // event handlers - FSM: listen for events and reset state + // + + function onPointerDown( event ) { + + if ( scope.enabled === false ) return; + + if ( pointers.length === 0 ) { + + scope.domElement.setPointerCapture( event.pointerId ); + + scope.domElement.addEventListener( 'pointermove', onPointerMove ); + scope.domElement.addEventListener( 'pointerup', onPointerUp ); + + } + + // + + if ( isTrackingPointer( event ) ) return; + + // + + addPointer( event ); + + if ( event.pointerType === 'touch' ) { + + onTouchStart( event ); + + } else { + + onMouseDown( event ); + + } + + } + + function onPointerMove( event ) { + + if ( scope.enabled === false ) return; + + if ( event.pointerType === 'touch' ) { + + onTouchMove( event ); + + } else { + + onMouseMove( event ); + + } + + } + + function onPointerUp( event ) { + + removePointer( event ); + + switch ( pointers.length ) { + + case 0: + + scope.domElement.releasePointerCapture( event.pointerId ); + + scope.domElement.removeEventListener( 'pointermove', onPointerMove ); + scope.domElement.removeEventListener( 'pointerup', onPointerUp ); + + scope.dispatchEvent( _endEvent ); + + state = STATE.NONE; + + break; + + case 1: + + const pointerId = pointers[ 0 ]; + const position = pointerPositions[ pointerId ]; + + // minimal placeholder event - allows state correction on pointer-up + onTouchStart( { pointerId: pointerId, pageX: position.x, pageY: position.y } ); + + break; + + } + + } + + function onMouseDown( event ) { + + let mouseAction; + + switch ( event.button ) { + + case 0: + + mouseAction = scope.mouseButtons.LEFT; + break; + + case 1: + + mouseAction = scope.mouseButtons.MIDDLE; + break; + + case 2: + + mouseAction = scope.mouseButtons.RIGHT; + break; + + default: + + mouseAction = - 1; + + } + + switch ( mouseAction ) { + + case MOUSE.DOLLY: + + if ( scope.enableZoom === false ) return; + + handleMouseDownDolly( event ); + + state = STATE.DOLLY; + + break; + + case MOUSE.ROTATE: + + if ( event.ctrlKey || event.metaKey || event.shiftKey ) { + + if ( scope.enablePan === false ) return; + + handleMouseDownPan( event ); + + state = STATE.PAN; + + } else { + + if ( scope.enableRotate === false ) return; + + handleMouseDownRotate( event ); + + state = STATE.ROTATE; + + } + + break; + + case MOUSE.PAN: + + if ( event.ctrlKey || event.metaKey || event.shiftKey ) { + + if ( scope.enableRotate === false ) return; + + handleMouseDownRotate( event ); + + state = STATE.ROTATE; + + } else { + + if ( scope.enablePan === false ) return; + + handleMouseDownPan( event ); + + state = STATE.PAN; + + } + + break; + + default: + + state = STATE.NONE; + + } + + if ( state !== STATE.NONE ) { + + scope.dispatchEvent( _startEvent ); + + } + + } + + function onMouseMove( event ) { + + switch ( state ) { + + case STATE.ROTATE: + + if ( scope.enableRotate === false ) return; + + handleMouseMoveRotate( event ); + + break; + + case STATE.DOLLY: + + if ( scope.enableZoom === false ) return; + + handleMouseMoveDolly( event ); + + break; + + case STATE.PAN: + + if ( scope.enablePan === false ) return; + + handleMouseMovePan( event ); + + break; + + } + + } + + function onMouseWheel( event ) { + + if ( scope.enabled === false || scope.enableZoom === false || state !== STATE.NONE ) return; + + event.preventDefault(); + + scope.dispatchEvent( _startEvent ); + + handleMouseWheel( customWheelEvent( event ) ); + + scope.dispatchEvent( _endEvent ); + + } + + function customWheelEvent( event ) { + + const mode = event.deltaMode; + + // minimal wheel event altered to meet delta-zoom demand + const newEvent = { + clientX: event.clientX, + clientY: event.clientY, + deltaY: event.deltaY, + }; + + switch ( mode ) { + + case 1: // LINE_MODE + newEvent.deltaY *= 16; + break; + + case 2: // PAGE_MODE + newEvent.deltaY *= 100; + break; + + } + + // detect if event was triggered by pinching + if ( event.ctrlKey && ! controlActive ) { + + newEvent.deltaY *= 10; + + } + + return newEvent; + + } + + function interceptControlDown( event ) { + + if ( event.key === 'Control' ) { + + controlActive = true; + + + const document = scope.domElement.getRootNode(); // offscreen canvas compatibility + + document.addEventListener( 'keyup', interceptControlUp, { passive: true, capture: true } ); + + } + + } + + function interceptControlUp( event ) { + + if ( event.key === 'Control' ) { + + controlActive = false; + + + const document = scope.domElement.getRootNode(); // offscreen canvas compatibility + + document.removeEventListener( 'keyup', interceptControlUp, { passive: true, capture: true } ); + + } + + } + + function onKeyDown( event ) { + + if ( scope.enabled === false || scope.enablePan === false ) return; + + handleKeyDown( event ); + + } + + function onTouchStart( event ) { + + trackPointer( event ); + + switch ( pointers.length ) { + + case 1: + + switch ( scope.touches.ONE ) { + + case TOUCH.ROTATE: + + if ( scope.enableRotate === false ) return; + + handleTouchStartRotate( event ); + + state = STATE.TOUCH_ROTATE; + + break; + + case TOUCH.PAN: + + if ( scope.enablePan === false ) return; + + handleTouchStartPan( event ); + + state = STATE.TOUCH_PAN; + + break; + + default: + + state = STATE.NONE; + + } + + break; + + case 2: + + switch ( scope.touches.TWO ) { + + case TOUCH.DOLLY_PAN: + + if ( scope.enableZoom === false && scope.enablePan === false ) return; + + handleTouchStartDollyPan( event ); + + state = STATE.TOUCH_DOLLY_PAN; + + break; + + case TOUCH.DOLLY_ROTATE: + + if ( scope.enableZoom === false && scope.enableRotate === false ) return; + + handleTouchStartDollyRotate( event ); + + state = STATE.TOUCH_DOLLY_ROTATE; + + break; + + default: + + state = STATE.NONE; + + } + + break; + + default: + + state = STATE.NONE; + + } + + if ( state !== STATE.NONE ) { + + scope.dispatchEvent( _startEvent ); + + } + + } + + function onTouchMove( event ) { + + trackPointer( event ); + + switch ( state ) { + + case STATE.TOUCH_ROTATE: + + if ( scope.enableRotate === false ) return; + + handleTouchMoveRotate( event ); + + scope.update(); + + break; + + case STATE.TOUCH_PAN: + + if ( scope.enablePan === false ) return; + + handleTouchMovePan( event ); + + scope.update(); + + break; + + case STATE.TOUCH_DOLLY_PAN: + + if ( scope.enableZoom === false && scope.enablePan === false ) return; + + handleTouchMoveDollyPan( event ); + + scope.update(); + + break; + + case STATE.TOUCH_DOLLY_ROTATE: + + if ( scope.enableZoom === false && scope.enableRotate === false ) return; + + handleTouchMoveDollyRotate( event ); + + scope.update(); + + break; + + default: + + state = STATE.NONE; + + } + + } + + function onContextMenu( event ) { + + if ( scope.enabled === false ) return; + + event.preventDefault(); + + } + + function addPointer( event ) { + + pointers.push( event.pointerId ); + + } + + function removePointer( event ) { + + delete pointerPositions[ event.pointerId ]; + + for ( let i = 0; i < pointers.length; i ++ ) { + + if ( pointers[ i ] == event.pointerId ) { + + pointers.splice( i, 1 ); + return; + + } + + } + + } + + function isTrackingPointer( event ) { + + for ( let i = 0; i < pointers.length; i ++ ) { + + if ( pointers[ i ] == event.pointerId ) return true; + + } + + return false; + + } + + function trackPointer( event ) { + + let position = pointerPositions[ event.pointerId ]; + + if ( position === undefined ) { + + position = new Vector2(); + pointerPositions[ event.pointerId ] = position; + + } + + position.set( event.pageX, event.pageY ); + + } + + function getSecondPointerPosition( event ) { + + const pointerId = ( event.pointerId === pointers[ 0 ] ) ? pointers[ 1 ] : pointers[ 0 ]; + + return pointerPositions[ pointerId ]; + + } + + // + + scope.domElement.addEventListener( 'contextmenu', onContextMenu ); + + scope.domElement.addEventListener( 'pointerdown', onPointerDown ); + scope.domElement.addEventListener( 'pointercancel', onPointerUp ); + scope.domElement.addEventListener( 'wheel', onMouseWheel, { passive: false } ); + + const document = scope.domElement.getRootNode(); // offscreen canvas compatibility + + document.addEventListener( 'keydown', interceptControlDown, { passive: true, capture: true } ); + + // force an update at start + + this.update(); + + } + +} + +export { OrbitControls }; diff --git a/WebApp/static/vendor/three.js b/WebApp/static/vendor/three.js new file mode 100644 index 0000000..fcf5e09 --- /dev/null +++ b/WebApp/static/vendor/three.js @@ -0,0 +1,53479 @@ +/** + * @license + * Copyright 2010-2024 Three.js Authors + * SPDX-License-Identifier: MIT + */ +const REVISION = '165'; + +const MOUSE = { LEFT: 0, MIDDLE: 1, RIGHT: 2, ROTATE: 0, DOLLY: 1, PAN: 2 }; +const TOUCH = { ROTATE: 0, PAN: 1, DOLLY_PAN: 2, DOLLY_ROTATE: 3 }; +const CullFaceNone = 0; +const CullFaceBack = 1; +const CullFaceFront = 2; +const CullFaceFrontBack = 3; +const BasicShadowMap = 0; +const PCFShadowMap = 1; +const PCFSoftShadowMap = 2; +const VSMShadowMap = 3; +const FrontSide = 0; +const BackSide = 1; +const DoubleSide = 2; +const NoBlending = 0; +const NormalBlending = 1; +const AdditiveBlending = 2; +const SubtractiveBlending = 3; +const MultiplyBlending = 4; +const CustomBlending = 5; +const AddEquation = 100; +const SubtractEquation = 101; +const ReverseSubtractEquation = 102; +const MinEquation = 103; +const MaxEquation = 104; +const ZeroFactor = 200; +const OneFactor = 201; +const SrcColorFactor = 202; +const OneMinusSrcColorFactor = 203; +const SrcAlphaFactor = 204; +const OneMinusSrcAlphaFactor = 205; +const DstAlphaFactor = 206; +const OneMinusDstAlphaFactor = 207; +const DstColorFactor = 208; +const OneMinusDstColorFactor = 209; +const SrcAlphaSaturateFactor = 210; +const ConstantColorFactor = 211; +const OneMinusConstantColorFactor = 212; +const ConstantAlphaFactor = 213; +const OneMinusConstantAlphaFactor = 214; +const NeverDepth = 0; +const AlwaysDepth = 1; +const LessDepth = 2; +const LessEqualDepth = 3; +const EqualDepth = 4; +const GreaterEqualDepth = 5; +const GreaterDepth = 6; +const NotEqualDepth = 7; +const MultiplyOperation = 0; +const MixOperation = 1; +const AddOperation = 2; +const NoToneMapping = 0; +const LinearToneMapping = 1; +const ReinhardToneMapping = 2; +const CineonToneMapping = 3; +const ACESFilmicToneMapping = 4; +const CustomToneMapping = 5; +const AgXToneMapping = 6; +const NeutralToneMapping = 7; +const AttachedBindMode = 'attached'; +const DetachedBindMode = 'detached'; + +const UVMapping = 300; +const CubeReflectionMapping = 301; +const CubeRefractionMapping = 302; +const EquirectangularReflectionMapping = 303; +const EquirectangularRefractionMapping = 304; +const CubeUVReflectionMapping = 306; +const RepeatWrapping = 1000; +const ClampToEdgeWrapping = 1001; +const MirroredRepeatWrapping = 1002; +const NearestFilter = 1003; +const NearestMipmapNearestFilter = 1004; +const NearestMipMapNearestFilter = 1004; +const NearestMipmapLinearFilter = 1005; +const NearestMipMapLinearFilter = 1005; +const LinearFilter = 1006; +const LinearMipmapNearestFilter = 1007; +const LinearMipMapNearestFilter = 1007; +const LinearMipmapLinearFilter = 1008; +const LinearMipMapLinearFilter = 1008; +const UnsignedByteType = 1009; +const ByteType = 1010; +const ShortType = 1011; +const UnsignedShortType = 1012; +const IntType = 1013; +const UnsignedIntType = 1014; +const FloatType = 1015; +const HalfFloatType = 1016; +const UnsignedShort4444Type = 1017; +const UnsignedShort5551Type = 1018; +const UnsignedInt248Type = 1020; +const UnsignedInt5999Type = 35902; +const AlphaFormat = 1021; +const RGBFormat = 1022; +const RGBAFormat = 1023; +const LuminanceFormat = 1024; +const LuminanceAlphaFormat = 1025; +const DepthFormat = 1026; +const DepthStencilFormat = 1027; +const RedFormat = 1028; +const RedIntegerFormat = 1029; +const RGFormat = 1030; +const RGIntegerFormat = 1031; +const RGBAIntegerFormat = 1033; + +const RGB_S3TC_DXT1_Format = 33776; +const RGBA_S3TC_DXT1_Format = 33777; +const RGBA_S3TC_DXT3_Format = 33778; +const RGBA_S3TC_DXT5_Format = 33779; +const RGB_PVRTC_4BPPV1_Format = 35840; +const RGB_PVRTC_2BPPV1_Format = 35841; +const RGBA_PVRTC_4BPPV1_Format = 35842; +const RGBA_PVRTC_2BPPV1_Format = 35843; +const RGB_ETC1_Format = 36196; +const RGB_ETC2_Format = 37492; +const RGBA_ETC2_EAC_Format = 37496; +const RGBA_ASTC_4x4_Format = 37808; +const RGBA_ASTC_5x4_Format = 37809; +const RGBA_ASTC_5x5_Format = 37810; +const RGBA_ASTC_6x5_Format = 37811; +const RGBA_ASTC_6x6_Format = 37812; +const RGBA_ASTC_8x5_Format = 37813; +const RGBA_ASTC_8x6_Format = 37814; +const RGBA_ASTC_8x8_Format = 37815; +const RGBA_ASTC_10x5_Format = 37816; +const RGBA_ASTC_10x6_Format = 37817; +const RGBA_ASTC_10x8_Format = 37818; +const RGBA_ASTC_10x10_Format = 37819; +const RGBA_ASTC_12x10_Format = 37820; +const RGBA_ASTC_12x12_Format = 37821; +const RGBA_BPTC_Format = 36492; +const RGB_BPTC_SIGNED_Format = 36494; +const RGB_BPTC_UNSIGNED_Format = 36495; +const RED_RGTC1_Format = 36283; +const SIGNED_RED_RGTC1_Format = 36284; +const RED_GREEN_RGTC2_Format = 36285; +const SIGNED_RED_GREEN_RGTC2_Format = 36286; +const LoopOnce = 2200; +const LoopRepeat = 2201; +const LoopPingPong = 2202; +const InterpolateDiscrete = 2300; +const InterpolateLinear = 2301; +const InterpolateSmooth = 2302; +const ZeroCurvatureEnding = 2400; +const ZeroSlopeEnding = 2401; +const WrapAroundEnding = 2402; +const NormalAnimationBlendMode = 2500; +const AdditiveAnimationBlendMode = 2501; +const TrianglesDrawMode = 0; +const TriangleStripDrawMode = 1; +const TriangleFanDrawMode = 2; +const BasicDepthPacking = 3200; +const RGBADepthPacking = 3201; +const TangentSpaceNormalMap = 0; +const ObjectSpaceNormalMap = 1; + +// Color space string identifiers, matching CSS Color Module Level 4 and WebGPU names where available. +const NoColorSpace = ''; +const SRGBColorSpace = 'srgb'; +const LinearSRGBColorSpace = 'srgb-linear'; +const DisplayP3ColorSpace = 'display-p3'; +const LinearDisplayP3ColorSpace = 'display-p3-linear'; + +const LinearTransfer = 'linear'; +const SRGBTransfer = 'srgb'; + +const Rec709Primaries = 'rec709'; +const P3Primaries = 'p3'; + +const ZeroStencilOp = 0; +const KeepStencilOp = 7680; +const ReplaceStencilOp = 7681; +const IncrementStencilOp = 7682; +const DecrementStencilOp = 7683; +const IncrementWrapStencilOp = 34055; +const DecrementWrapStencilOp = 34056; +const InvertStencilOp = 5386; + +const NeverStencilFunc = 512; +const LessStencilFunc = 513; +const EqualStencilFunc = 514; +const LessEqualStencilFunc = 515; +const GreaterStencilFunc = 516; +const NotEqualStencilFunc = 517; +const GreaterEqualStencilFunc = 518; +const AlwaysStencilFunc = 519; + +const NeverCompare = 512; +const LessCompare = 513; +const EqualCompare = 514; +const LessEqualCompare = 515; +const GreaterCompare = 516; +const NotEqualCompare = 517; +const GreaterEqualCompare = 518; +const AlwaysCompare = 519; + +const StaticDrawUsage = 35044; +const DynamicDrawUsage = 35048; +const StreamDrawUsage = 35040; +const StaticReadUsage = 35045; +const DynamicReadUsage = 35049; +const StreamReadUsage = 35041; +const StaticCopyUsage = 35046; +const DynamicCopyUsage = 35050; +const StreamCopyUsage = 35042; + +const GLSL1 = '100'; +const GLSL3 = '300 es'; + +const WebGLCoordinateSystem = 2000; +const WebGPUCoordinateSystem = 2001; + +/** + * https://github.com/mrdoob/eventdispatcher.js/ + */ + +class EventDispatcher { + + addEventListener( type, listener ) { + + if ( this._listeners === undefined ) this._listeners = {}; + + const listeners = this._listeners; + + if ( listeners[ type ] === undefined ) { + + listeners[ type ] = []; + + } + + if ( listeners[ type ].indexOf( listener ) === - 1 ) { + + listeners[ type ].push( listener ); + + } + + } + + hasEventListener( type, listener ) { + + if ( this._listeners === undefined ) return false; + + const listeners = this._listeners; + + return listeners[ type ] !== undefined && listeners[ type ].indexOf( listener ) !== - 1; + + } + + removeEventListener( type, listener ) { + + if ( this._listeners === undefined ) return; + + const listeners = this._listeners; + const listenerArray = listeners[ type ]; + + if ( listenerArray !== undefined ) { + + const index = listenerArray.indexOf( listener ); + + if ( index !== - 1 ) { + + listenerArray.splice( index, 1 ); + + } + + } + + } + + dispatchEvent( event ) { + + if ( this._listeners === undefined ) return; + + const listeners = this._listeners; + const listenerArray = listeners[ event.type ]; + + if ( listenerArray !== undefined ) { + + event.target = this; + + // Make a copy, in case listeners are removed while iterating. + const array = listenerArray.slice( 0 ); + + for ( let i = 0, l = array.length; i < l; i ++ ) { + + array[ i ].call( this, event ); + + } + + event.target = null; + + } + + } + +} + +const _lut = [ '00', '01', '02', '03', '04', '05', '06', '07', '08', '09', '0a', '0b', '0c', '0d', '0e', '0f', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '1a', '1b', '1c', '1d', '1e', '1f', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '2a', '2b', '2c', '2d', '2e', '2f', '30', '31', '32', '33', '34', '35', '36', '37', '38', '39', '3a', '3b', '3c', '3d', '3e', '3f', '40', '41', '42', '43', '44', '45', '46', '47', '48', '49', '4a', '4b', '4c', '4d', '4e', '4f', '50', '51', '52', '53', '54', '55', '56', '57', '58', '59', '5a', '5b', '5c', '5d', '5e', '5f', '60', '61', '62', '63', '64', '65', '66', '67', '68', '69', '6a', '6b', '6c', '6d', '6e', '6f', '70', '71', '72', '73', '74', '75', '76', '77', '78', '79', '7a', '7b', '7c', '7d', '7e', '7f', '80', '81', '82', '83', '84', '85', '86', '87', '88', '89', '8a', '8b', '8c', '8d', '8e', '8f', '90', '91', '92', '93', '94', '95', '96', '97', '98', '99', '9a', '9b', '9c', '9d', '9e', '9f', 'a0', 'a1', 'a2', 'a3', 'a4', 'a5', 'a6', 'a7', 'a8', 'a9', 'aa', 'ab', 'ac', 'ad', 'ae', 'af', 'b0', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'b7', 'b8', 'b9', 'ba', 'bb', 'bc', 'bd', 'be', 'bf', 'c0', 'c1', 'c2', 'c3', 'c4', 'c5', 'c6', 'c7', 'c8', 'c9', 'ca', 'cb', 'cc', 'cd', 'ce', 'cf', 'd0', 'd1', 'd2', 'd3', 'd4', 'd5', 'd6', 'd7', 'd8', 'd9', 'da', 'db', 'dc', 'dd', 'de', 'df', 'e0', 'e1', 'e2', 'e3', 'e4', 'e5', 'e6', 'e7', 'e8', 'e9', 'ea', 'eb', 'ec', 'ed', 'ee', 'ef', 'f0', 'f1', 'f2', 'f3', 'f4', 'f5', 'f6', 'f7', 'f8', 'f9', 'fa', 'fb', 'fc', 'fd', 'fe', 'ff' ]; + +let _seed = 1234567; + + +const DEG2RAD = Math.PI / 180; +const RAD2DEG = 180 / Math.PI; + +// http://stackoverflow.com/questions/105034/how-to-create-a-guid-uuid-in-javascript/21963136#21963136 +function generateUUID() { + + const d0 = Math.random() * 0xffffffff | 0; + const d1 = Math.random() * 0xffffffff | 0; + const d2 = Math.random() * 0xffffffff | 0; + const d3 = Math.random() * 0xffffffff | 0; + const uuid = _lut[ d0 & 0xff ] + _lut[ d0 >> 8 & 0xff ] + _lut[ d0 >> 16 & 0xff ] + _lut[ d0 >> 24 & 0xff ] + '-' + + _lut[ d1 & 0xff ] + _lut[ d1 >> 8 & 0xff ] + '-' + _lut[ d1 >> 16 & 0x0f | 0x40 ] + _lut[ d1 >> 24 & 0xff ] + '-' + + _lut[ d2 & 0x3f | 0x80 ] + _lut[ d2 >> 8 & 0xff ] + '-' + _lut[ d2 >> 16 & 0xff ] + _lut[ d2 >> 24 & 0xff ] + + _lut[ d3 & 0xff ] + _lut[ d3 >> 8 & 0xff ] + _lut[ d3 >> 16 & 0xff ] + _lut[ d3 >> 24 & 0xff ]; + + // .toLowerCase() here flattens concatenated strings to save heap memory space. + return uuid.toLowerCase(); + +} + +function clamp( value, min, max ) { + + return Math.max( min, Math.min( max, value ) ); + +} + +// compute euclidean modulo of m % n +// https://en.wikipedia.org/wiki/Modulo_operation +function euclideanModulo( n, m ) { + + return ( ( n % m ) + m ) % m; + +} + +// Linear mapping from range to range +function mapLinear( x, a1, a2, b1, b2 ) { + + return b1 + ( x - a1 ) * ( b2 - b1 ) / ( a2 - a1 ); + +} + +// https://www.gamedev.net/tutorials/programming/general-and-gameplay-programming/inverse-lerp-a-super-useful-yet-often-overlooked-function-r5230/ +function inverseLerp( x, y, value ) { + + if ( x !== y ) { + + return ( value - x ) / ( y - x ); + + } else { + + return 0; + + } + +} + +// https://en.wikipedia.org/wiki/Linear_interpolation +function lerp( x, y, t ) { + + return ( 1 - t ) * x + t * y; + +} + +// http://www.rorydriscoll.com/2016/03/07/frame-rate-independent-damping-using-lerp/ +function damp( x, y, lambda, dt ) { + + return lerp( x, y, 1 - Math.exp( - lambda * dt ) ); + +} + +// https://www.desmos.com/calculator/vcsjnyz7x4 +function pingpong( x, length = 1 ) { + + return length - Math.abs( euclideanModulo( x, length * 2 ) - length ); + +} + +// http://en.wikipedia.org/wiki/Smoothstep +function smoothstep( x, min, max ) { + + if ( x <= min ) return 0; + if ( x >= max ) return 1; + + x = ( x - min ) / ( max - min ); + + return x * x * ( 3 - 2 * x ); + +} + +function smootherstep( x, min, max ) { + + if ( x <= min ) return 0; + if ( x >= max ) return 1; + + x = ( x - min ) / ( max - min ); + + return x * x * x * ( x * ( x * 6 - 15 ) + 10 ); + +} + +// Random integer from interval +function randInt( low, high ) { + + return low + Math.floor( Math.random() * ( high - low + 1 ) ); + +} + +// Random float from interval +function randFloat( low, high ) { + + return low + Math.random() * ( high - low ); + +} + +// Random float from <-range/2, range/2> interval +function randFloatSpread( range ) { + + return range * ( 0.5 - Math.random() ); + +} + +// Deterministic pseudo-random float in the interval [ 0, 1 ] +function seededRandom( s ) { + + if ( s !== undefined ) _seed = s; + + // Mulberry32 generator + + let t = _seed += 0x6D2B79F5; + + t = Math.imul( t ^ t >>> 15, t | 1 ); + + t ^= t + Math.imul( t ^ t >>> 7, t | 61 ); + + return ( ( t ^ t >>> 14 ) >>> 0 ) / 4294967296; + +} + +function degToRad( degrees ) { + + return degrees * DEG2RAD; + +} + +function radToDeg( radians ) { + + return radians * RAD2DEG; + +} + +function isPowerOfTwo( value ) { + + return ( value & ( value - 1 ) ) === 0 && value !== 0; + +} + +function ceilPowerOfTwo( value ) { + + return Math.pow( 2, Math.ceil( Math.log( value ) / Math.LN2 ) ); + +} + +function floorPowerOfTwo( value ) { + + return Math.pow( 2, Math.floor( Math.log( value ) / Math.LN2 ) ); + +} + +function setQuaternionFromProperEuler( q, a, b, c, order ) { + + // Intrinsic Proper Euler Angles - see https://en.wikipedia.org/wiki/Euler_angles + + // rotations are applied to the axes in the order specified by 'order' + // rotation by angle 'a' is applied first, then by angle 'b', then by angle 'c' + // angles are in radians + + const cos = Math.cos; + const sin = Math.sin; + + const c2 = cos( b / 2 ); + const s2 = sin( b / 2 ); + + const c13 = cos( ( a + c ) / 2 ); + const s13 = sin( ( a + c ) / 2 ); + + const c1_3 = cos( ( a - c ) / 2 ); + const s1_3 = sin( ( a - c ) / 2 ); + + const c3_1 = cos( ( c - a ) / 2 ); + const s3_1 = sin( ( c - a ) / 2 ); + + switch ( order ) { + + case 'XYX': + q.set( c2 * s13, s2 * c1_3, s2 * s1_3, c2 * c13 ); + break; + + case 'YZY': + q.set( s2 * s1_3, c2 * s13, s2 * c1_3, c2 * c13 ); + break; + + case 'ZXZ': + q.set( s2 * c1_3, s2 * s1_3, c2 * s13, c2 * c13 ); + break; + + case 'XZX': + q.set( c2 * s13, s2 * s3_1, s2 * c3_1, c2 * c13 ); + break; + + case 'YXY': + q.set( s2 * c3_1, c2 * s13, s2 * s3_1, c2 * c13 ); + break; + + case 'ZYZ': + q.set( s2 * s3_1, s2 * c3_1, c2 * s13, c2 * c13 ); + break; + + default: + console.warn( 'THREE.MathUtils: .setQuaternionFromProperEuler() encountered an unknown order: ' + order ); + + } + +} + +function denormalize( value, array ) { + + switch ( array.constructor ) { + + case Float32Array: + + return value; + + case Uint32Array: + + return value / 4294967295.0; + + case Uint16Array: + + return value / 65535.0; + + case Uint8Array: + + return value / 255.0; + + case Int32Array: + + return Math.max( value / 2147483647.0, - 1.0 ); + + case Int16Array: + + return Math.max( value / 32767.0, - 1.0 ); + + case Int8Array: + + return Math.max( value / 127.0, - 1.0 ); + + default: + + throw new Error( 'Invalid component type.' ); + + } + +} + +function normalize( value, array ) { + + switch ( array.constructor ) { + + case Float32Array: + + return value; + + case Uint32Array: + + return Math.round( value * 4294967295.0 ); + + case Uint16Array: + + return Math.round( value * 65535.0 ); + + case Uint8Array: + + return Math.round( value * 255.0 ); + + case Int32Array: + + return Math.round( value * 2147483647.0 ); + + case Int16Array: + + return Math.round( value * 32767.0 ); + + case Int8Array: + + return Math.round( value * 127.0 ); + + default: + + throw new Error( 'Invalid component type.' ); + + } + +} + +const MathUtils = { + DEG2RAD: DEG2RAD, + RAD2DEG: RAD2DEG, + generateUUID: generateUUID, + clamp: clamp, + euclideanModulo: euclideanModulo, + mapLinear: mapLinear, + inverseLerp: inverseLerp, + lerp: lerp, + damp: damp, + pingpong: pingpong, + smoothstep: smoothstep, + smootherstep: smootherstep, + randInt: randInt, + randFloat: randFloat, + randFloatSpread: randFloatSpread, + seededRandom: seededRandom, + degToRad: degToRad, + radToDeg: radToDeg, + isPowerOfTwo: isPowerOfTwo, + ceilPowerOfTwo: ceilPowerOfTwo, + floorPowerOfTwo: floorPowerOfTwo, + setQuaternionFromProperEuler: setQuaternionFromProperEuler, + normalize: normalize, + denormalize: denormalize +}; + +class Vector2 { + + constructor( x = 0, y = 0 ) { + + Vector2.prototype.isVector2 = true; + + this.x = x; + this.y = y; + + } + + get width() { + + return this.x; + + } + + set width( value ) { + + this.x = value; + + } + + get height() { + + return this.y; + + } + + set height( value ) { + + this.y = value; + + } + + set( x, y ) { + + this.x = x; + this.y = y; + + return this; + + } + + setScalar( scalar ) { + + this.x = scalar; + this.y = scalar; + + return this; + + } + + setX( x ) { + + this.x = x; + + return this; + + } + + setY( y ) { + + this.y = y; + + return this; + + } + + setComponent( index, value ) { + + switch ( index ) { + + case 0: this.x = value; break; + case 1: this.y = value; break; + default: throw new Error( 'index is out of range: ' + index ); + + } + + return this; + + } + + getComponent( index ) { + + switch ( index ) { + + case 0: return this.x; + case 1: return this.y; + default: throw new Error( 'index is out of range: ' + index ); + + } + + } + + clone() { + + return new this.constructor( this.x, this.y ); + + } + + copy( v ) { + + this.x = v.x; + this.y = v.y; + + return this; + + } + + add( v ) { + + this.x += v.x; + this.y += v.y; + + return this; + + } + + addScalar( s ) { + + this.x += s; + this.y += s; + + return this; + + } + + addVectors( a, b ) { + + this.x = a.x + b.x; + this.y = a.y + b.y; + + return this; + + } + + addScaledVector( v, s ) { + + this.x += v.x * s; + this.y += v.y * s; + + return this; + + } + + sub( v ) { + + this.x -= v.x; + this.y -= v.y; + + return this; + + } + + subScalar( s ) { + + this.x -= s; + this.y -= s; + + return this; + + } + + subVectors( a, b ) { + + this.x = a.x - b.x; + this.y = a.y - b.y; + + return this; + + } + + multiply( v ) { + + this.x *= v.x; + this.y *= v.y; + + return this; + + } + + multiplyScalar( scalar ) { + + this.x *= scalar; + this.y *= scalar; + + return this; + + } + + divide( v ) { + + this.x /= v.x; + this.y /= v.y; + + return this; + + } + + divideScalar( scalar ) { + + return this.multiplyScalar( 1 / scalar ); + + } + + applyMatrix3( m ) { + + const x = this.x, y = this.y; + const e = m.elements; + + this.x = e[ 0 ] * x + e[ 3 ] * y + e[ 6 ]; + this.y = e[ 1 ] * x + e[ 4 ] * y + e[ 7 ]; + + return this; + + } + + min( v ) { + + this.x = Math.min( this.x, v.x ); + this.y = Math.min( this.y, v.y ); + + return this; + + } + + max( v ) { + + this.x = Math.max( this.x, v.x ); + this.y = Math.max( this.y, v.y ); + + return this; + + } + + clamp( min, max ) { + + // assumes min < max, componentwise + + this.x = Math.max( min.x, Math.min( max.x, this.x ) ); + this.y = Math.max( min.y, Math.min( max.y, this.y ) ); + + return this; + + } + + clampScalar( minVal, maxVal ) { + + this.x = Math.max( minVal, Math.min( maxVal, this.x ) ); + this.y = Math.max( minVal, Math.min( maxVal, this.y ) ); + + return this; + + } + + clampLength( min, max ) { + + const length = this.length(); + + return this.divideScalar( length || 1 ).multiplyScalar( Math.max( min, Math.min( max, length ) ) ); + + } + + floor() { + + this.x = Math.floor( this.x ); + this.y = Math.floor( this.y ); + + return this; + + } + + ceil() { + + this.x = Math.ceil( this.x ); + this.y = Math.ceil( this.y ); + + return this; + + } + + round() { + + this.x = Math.round( this.x ); + this.y = Math.round( this.y ); + + return this; + + } + + roundToZero() { + + this.x = Math.trunc( this.x ); + this.y = Math.trunc( this.y ); + + return this; + + } + + negate() { + + this.x = - this.x; + this.y = - this.y; + + return this; + + } + + dot( v ) { + + return this.x * v.x + this.y * v.y; + + } + + cross( v ) { + + return this.x * v.y - this.y * v.x; + + } + + lengthSq() { + + return this.x * this.x + this.y * this.y; + + } + + length() { + + return Math.sqrt( this.x * this.x + this.y * this.y ); + + } + + manhattanLength() { + + return Math.abs( this.x ) + Math.abs( this.y ); + + } + + normalize() { + + return this.divideScalar( this.length() || 1 ); + + } + + angle() { + + // computes the angle in radians with respect to the positive x-axis + + const angle = Math.atan2( - this.y, - this.x ) + Math.PI; + + return angle; + + } + + angleTo( v ) { + + const denominator = Math.sqrt( this.lengthSq() * v.lengthSq() ); + + if ( denominator === 0 ) return Math.PI / 2; + + const theta = this.dot( v ) / denominator; + + // clamp, to handle numerical problems + + return Math.acos( clamp( theta, - 1, 1 ) ); + + } + + distanceTo( v ) { + + return Math.sqrt( this.distanceToSquared( v ) ); + + } + + distanceToSquared( v ) { + + const dx = this.x - v.x, dy = this.y - v.y; + return dx * dx + dy * dy; + + } + + manhattanDistanceTo( v ) { + + return Math.abs( this.x - v.x ) + Math.abs( this.y - v.y ); + + } + + setLength( length ) { + + return this.normalize().multiplyScalar( length ); + + } + + lerp( v, alpha ) { + + this.x += ( v.x - this.x ) * alpha; + this.y += ( v.y - this.y ) * alpha; + + return this; + + } + + lerpVectors( v1, v2, alpha ) { + + this.x = v1.x + ( v2.x - v1.x ) * alpha; + this.y = v1.y + ( v2.y - v1.y ) * alpha; + + return this; + + } + + equals( v ) { + + return ( ( v.x === this.x ) && ( v.y === this.y ) ); + + } + + fromArray( array, offset = 0 ) { + + this.x = array[ offset ]; + this.y = array[ offset + 1 ]; + + return this; + + } + + toArray( array = [], offset = 0 ) { + + array[ offset ] = this.x; + array[ offset + 1 ] = this.y; + + return array; + + } + + fromBufferAttribute( attribute, index ) { + + this.x = attribute.getX( index ); + this.y = attribute.getY( index ); + + return this; + + } + + rotateAround( center, angle ) { + + const c = Math.cos( angle ), s = Math.sin( angle ); + + const x = this.x - center.x; + const y = this.y - center.y; + + this.x = x * c - y * s + center.x; + this.y = x * s + y * c + center.y; + + return this; + + } + + random() { + + this.x = Math.random(); + this.y = Math.random(); + + return this; + + } + + *[ Symbol.iterator ]() { + + yield this.x; + yield this.y; + + } + +} + +class Matrix3 { + + constructor( n11, n12, n13, n21, n22, n23, n31, n32, n33 ) { + + Matrix3.prototype.isMatrix3 = true; + + this.elements = [ + + 1, 0, 0, + 0, 1, 0, + 0, 0, 1 + + ]; + + if ( n11 !== undefined ) { + + this.set( n11, n12, n13, n21, n22, n23, n31, n32, n33 ); + + } + + } + + set( n11, n12, n13, n21, n22, n23, n31, n32, n33 ) { + + const te = this.elements; + + te[ 0 ] = n11; te[ 1 ] = n21; te[ 2 ] = n31; + te[ 3 ] = n12; te[ 4 ] = n22; te[ 5 ] = n32; + te[ 6 ] = n13; te[ 7 ] = n23; te[ 8 ] = n33; + + return this; + + } + + identity() { + + this.set( + + 1, 0, 0, + 0, 1, 0, + 0, 0, 1 + + ); + + return this; + + } + + copy( m ) { + + const te = this.elements; + const me = m.elements; + + te[ 0 ] = me[ 0 ]; te[ 1 ] = me[ 1 ]; te[ 2 ] = me[ 2 ]; + te[ 3 ] = me[ 3 ]; te[ 4 ] = me[ 4 ]; te[ 5 ] = me[ 5 ]; + te[ 6 ] = me[ 6 ]; te[ 7 ] = me[ 7 ]; te[ 8 ] = me[ 8 ]; + + return this; + + } + + extractBasis( xAxis, yAxis, zAxis ) { + + xAxis.setFromMatrix3Column( this, 0 ); + yAxis.setFromMatrix3Column( this, 1 ); + zAxis.setFromMatrix3Column( this, 2 ); + + return this; + + } + + setFromMatrix4( m ) { + + const me = m.elements; + + this.set( + + me[ 0 ], me[ 4 ], me[ 8 ], + me[ 1 ], me[ 5 ], me[ 9 ], + me[ 2 ], me[ 6 ], me[ 10 ] + + ); + + return this; + + } + + multiply( m ) { + + return this.multiplyMatrices( this, m ); + + } + + premultiply( m ) { + + return this.multiplyMatrices( m, this ); + + } + + multiplyMatrices( a, b ) { + + const ae = a.elements; + const be = b.elements; + const te = this.elements; + + const a11 = ae[ 0 ], a12 = ae[ 3 ], a13 = ae[ 6 ]; + const a21 = ae[ 1 ], a22 = ae[ 4 ], a23 = ae[ 7 ]; + const a31 = ae[ 2 ], a32 = ae[ 5 ], a33 = ae[ 8 ]; + + const b11 = be[ 0 ], b12 = be[ 3 ], b13 = be[ 6 ]; + const b21 = be[ 1 ], b22 = be[ 4 ], b23 = be[ 7 ]; + const b31 = be[ 2 ], b32 = be[ 5 ], b33 = be[ 8 ]; + + te[ 0 ] = a11 * b11 + a12 * b21 + a13 * b31; + te[ 3 ] = a11 * b12 + a12 * b22 + a13 * b32; + te[ 6 ] = a11 * b13 + a12 * b23 + a13 * b33; + + te[ 1 ] = a21 * b11 + a22 * b21 + a23 * b31; + te[ 4 ] = a21 * b12 + a22 * b22 + a23 * b32; + te[ 7 ] = a21 * b13 + a22 * b23 + a23 * b33; + + te[ 2 ] = a31 * b11 + a32 * b21 + a33 * b31; + te[ 5 ] = a31 * b12 + a32 * b22 + a33 * b32; + te[ 8 ] = a31 * b13 + a32 * b23 + a33 * b33; + + return this; + + } + + multiplyScalar( s ) { + + const te = this.elements; + + te[ 0 ] *= s; te[ 3 ] *= s; te[ 6 ] *= s; + te[ 1 ] *= s; te[ 4 ] *= s; te[ 7 ] *= s; + te[ 2 ] *= s; te[ 5 ] *= s; te[ 8 ] *= s; + + return this; + + } + + determinant() { + + const te = this.elements; + + const a = te[ 0 ], b = te[ 1 ], c = te[ 2 ], + d = te[ 3 ], e = te[ 4 ], f = te[ 5 ], + g = te[ 6 ], h = te[ 7 ], i = te[ 8 ]; + + return a * e * i - a * f * h - b * d * i + b * f * g + c * d * h - c * e * g; + + } + + invert() { + + const te = this.elements, + + n11 = te[ 0 ], n21 = te[ 1 ], n31 = te[ 2 ], + n12 = te[ 3 ], n22 = te[ 4 ], n32 = te[ 5 ], + n13 = te[ 6 ], n23 = te[ 7 ], n33 = te[ 8 ], + + t11 = n33 * n22 - n32 * n23, + t12 = n32 * n13 - n33 * n12, + t13 = n23 * n12 - n22 * n13, + + det = n11 * t11 + n21 * t12 + n31 * t13; + + if ( det === 0 ) return this.set( 0, 0, 0, 0, 0, 0, 0, 0, 0 ); + + const detInv = 1 / det; + + te[ 0 ] = t11 * detInv; + te[ 1 ] = ( n31 * n23 - n33 * n21 ) * detInv; + te[ 2 ] = ( n32 * n21 - n31 * n22 ) * detInv; + + te[ 3 ] = t12 * detInv; + te[ 4 ] = ( n33 * n11 - n31 * n13 ) * detInv; + te[ 5 ] = ( n31 * n12 - n32 * n11 ) * detInv; + + te[ 6 ] = t13 * detInv; + te[ 7 ] = ( n21 * n13 - n23 * n11 ) * detInv; + te[ 8 ] = ( n22 * n11 - n21 * n12 ) * detInv; + + return this; + + } + + transpose() { + + let tmp; + const m = this.elements; + + tmp = m[ 1 ]; m[ 1 ] = m[ 3 ]; m[ 3 ] = tmp; + tmp = m[ 2 ]; m[ 2 ] = m[ 6 ]; m[ 6 ] = tmp; + tmp = m[ 5 ]; m[ 5 ] = m[ 7 ]; m[ 7 ] = tmp; + + return this; + + } + + getNormalMatrix( matrix4 ) { + + return this.setFromMatrix4( matrix4 ).invert().transpose(); + + } + + transposeIntoArray( r ) { + + const m = this.elements; + + r[ 0 ] = m[ 0 ]; + r[ 1 ] = m[ 3 ]; + r[ 2 ] = m[ 6 ]; + r[ 3 ] = m[ 1 ]; + r[ 4 ] = m[ 4 ]; + r[ 5 ] = m[ 7 ]; + r[ 6 ] = m[ 2 ]; + r[ 7 ] = m[ 5 ]; + r[ 8 ] = m[ 8 ]; + + return this; + + } + + setUvTransform( tx, ty, sx, sy, rotation, cx, cy ) { + + const c = Math.cos( rotation ); + const s = Math.sin( rotation ); + + this.set( + sx * c, sx * s, - sx * ( c * cx + s * cy ) + cx + tx, + - sy * s, sy * c, - sy * ( - s * cx + c * cy ) + cy + ty, + 0, 0, 1 + ); + + return this; + + } + + // + + scale( sx, sy ) { + + this.premultiply( _m3.makeScale( sx, sy ) ); + + return this; + + } + + rotate( theta ) { + + this.premultiply( _m3.makeRotation( - theta ) ); + + return this; + + } + + translate( tx, ty ) { + + this.premultiply( _m3.makeTranslation( tx, ty ) ); + + return this; + + } + + // for 2D Transforms + + makeTranslation( x, y ) { + + if ( x.isVector2 ) { + + this.set( + + 1, 0, x.x, + 0, 1, x.y, + 0, 0, 1 + + ); + + } else { + + this.set( + + 1, 0, x, + 0, 1, y, + 0, 0, 1 + + ); + + } + + return this; + + } + + makeRotation( theta ) { + + // counterclockwise + + const c = Math.cos( theta ); + const s = Math.sin( theta ); + + this.set( + + c, - s, 0, + s, c, 0, + 0, 0, 1 + + ); + + return this; + + } + + makeScale( x, y ) { + + this.set( + + x, 0, 0, + 0, y, 0, + 0, 0, 1 + + ); + + return this; + + } + + // + + equals( matrix ) { + + const te = this.elements; + const me = matrix.elements; + + for ( let i = 0; i < 9; i ++ ) { + + if ( te[ i ] !== me[ i ] ) return false; + + } + + return true; + + } + + fromArray( array, offset = 0 ) { + + for ( let i = 0; i < 9; i ++ ) { + + this.elements[ i ] = array[ i + offset ]; + + } + + return this; + + } + + toArray( array = [], offset = 0 ) { + + const te = this.elements; + + array[ offset ] = te[ 0 ]; + array[ offset + 1 ] = te[ 1 ]; + array[ offset + 2 ] = te[ 2 ]; + + array[ offset + 3 ] = te[ 3 ]; + array[ offset + 4 ] = te[ 4 ]; + array[ offset + 5 ] = te[ 5 ]; + + array[ offset + 6 ] = te[ 6 ]; + array[ offset + 7 ] = te[ 7 ]; + array[ offset + 8 ] = te[ 8 ]; + + return array; + + } + + clone() { + + return new this.constructor().fromArray( this.elements ); + + } + +} + +const _m3 = /*@__PURE__*/ new Matrix3(); + +function arrayNeedsUint32( array ) { + + // assumes larger values usually on last + + for ( let i = array.length - 1; i >= 0; -- i ) { + + if ( array[ i ] >= 65535 ) return true; // account for PRIMITIVE_RESTART_FIXED_INDEX, #24565 + + } + + return false; + +} + +const TYPED_ARRAYS = { + Int8Array: Int8Array, + Uint8Array: Uint8Array, + Uint8ClampedArray: Uint8ClampedArray, + Int16Array: Int16Array, + Uint16Array: Uint16Array, + Int32Array: Int32Array, + Uint32Array: Uint32Array, + Float32Array: Float32Array, + Float64Array: Float64Array +}; + +function getTypedArray( type, buffer ) { + + return new TYPED_ARRAYS[ type ]( buffer ); + +} + +function createElementNS( name ) { + + return document.createElementNS( 'http://www.w3.org/1999/xhtml', name ); + +} + +function createCanvasElement() { + + const canvas = createElementNS( 'canvas' ); + canvas.style.display = 'block'; + return canvas; + +} + +const _cache = {}; + +function warnOnce( message ) { + + if ( message in _cache ) return; + + _cache[ message ] = true; + + console.warn( message ); + +} + +function probeAsync( gl, sync, interval ) { + + return new Promise( function ( resolve, reject ) { + + function probe() { + + switch ( gl.clientWaitSync( sync, gl.SYNC_FLUSH_COMMANDS_BIT, 0 ) ) { + + case gl.WAIT_FAILED: + reject(); + break; + + case gl.TIMEOUT_EXPIRED: + setTimeout( probe, interval ); + break; + + default: + resolve(); + + } + + } + + setTimeout( probe, interval ); + + } ); + +} + +/** + * Matrices converting P3 <-> Rec. 709 primaries, without gamut mapping + * or clipping. Based on W3C specifications for sRGB and Display P3, + * and ICC specifications for the D50 connection space. Values in/out + * are _linear_ sRGB and _linear_ Display P3. + * + * Note that both sRGB and Display P3 use the sRGB transfer functions. + * + * Reference: + * - http://www.russellcottrell.com/photo/matrixCalculator.htm + */ + +const LINEAR_SRGB_TO_LINEAR_DISPLAY_P3 = /*@__PURE__*/ new Matrix3().set( + 0.8224621, 0.177538, 0.0, + 0.0331941, 0.9668058, 0.0, + 0.0170827, 0.0723974, 0.9105199, +); + +const LINEAR_DISPLAY_P3_TO_LINEAR_SRGB = /*@__PURE__*/ new Matrix3().set( + 1.2249401, - 0.2249404, 0.0, + - 0.0420569, 1.0420571, 0.0, + - 0.0196376, - 0.0786361, 1.0982735 +); + +/** + * Defines supported color spaces by transfer function and primaries, + * and provides conversions to/from the Linear-sRGB reference space. + */ +const COLOR_SPACES = { + [ LinearSRGBColorSpace ]: { + transfer: LinearTransfer, + primaries: Rec709Primaries, + toReference: ( color ) => color, + fromReference: ( color ) => color, + }, + [ SRGBColorSpace ]: { + transfer: SRGBTransfer, + primaries: Rec709Primaries, + toReference: ( color ) => color.convertSRGBToLinear(), + fromReference: ( color ) => color.convertLinearToSRGB(), + }, + [ LinearDisplayP3ColorSpace ]: { + transfer: LinearTransfer, + primaries: P3Primaries, + toReference: ( color ) => color.applyMatrix3( LINEAR_DISPLAY_P3_TO_LINEAR_SRGB ), + fromReference: ( color ) => color.applyMatrix3( LINEAR_SRGB_TO_LINEAR_DISPLAY_P3 ), + }, + [ DisplayP3ColorSpace ]: { + transfer: SRGBTransfer, + primaries: P3Primaries, + toReference: ( color ) => color.convertSRGBToLinear().applyMatrix3( LINEAR_DISPLAY_P3_TO_LINEAR_SRGB ), + fromReference: ( color ) => color.applyMatrix3( LINEAR_SRGB_TO_LINEAR_DISPLAY_P3 ).convertLinearToSRGB(), + }, +}; + +const SUPPORTED_WORKING_COLOR_SPACES = new Set( [ LinearSRGBColorSpace, LinearDisplayP3ColorSpace ] ); + +const ColorManagement = { + + enabled: true, + + _workingColorSpace: LinearSRGBColorSpace, + + get workingColorSpace() { + + return this._workingColorSpace; + + }, + + set workingColorSpace( colorSpace ) { + + if ( ! SUPPORTED_WORKING_COLOR_SPACES.has( colorSpace ) ) { + + throw new Error( `Unsupported working color space, "${ colorSpace }".` ); + + } + + this._workingColorSpace = colorSpace; + + }, + + convert: function ( color, sourceColorSpace, targetColorSpace ) { + + if ( this.enabled === false || sourceColorSpace === targetColorSpace || ! sourceColorSpace || ! targetColorSpace ) { + + return color; + + } + + const sourceToReference = COLOR_SPACES[ sourceColorSpace ].toReference; + const targetFromReference = COLOR_SPACES[ targetColorSpace ].fromReference; + + return targetFromReference( sourceToReference( color ) ); + + }, + + fromWorkingColorSpace: function ( color, targetColorSpace ) { + + return this.convert( color, this._workingColorSpace, targetColorSpace ); + + }, + + toWorkingColorSpace: function ( color, sourceColorSpace ) { + + return this.convert( color, sourceColorSpace, this._workingColorSpace ); + + }, + + getPrimaries: function ( colorSpace ) { + + return COLOR_SPACES[ colorSpace ].primaries; + + }, + + getTransfer: function ( colorSpace ) { + + if ( colorSpace === NoColorSpace ) return LinearTransfer; + + return COLOR_SPACES[ colorSpace ].transfer; + + }, + +}; + + +function SRGBToLinear( c ) { + + return ( c < 0.04045 ) ? c * 0.0773993808 : Math.pow( c * 0.9478672986 + 0.0521327014, 2.4 ); + +} + +function LinearToSRGB( c ) { + + return ( c < 0.0031308 ) ? c * 12.92 : 1.055 * ( Math.pow( c, 0.41666 ) ) - 0.055; + +} + +let _canvas; + +class ImageUtils { + + static getDataURL( image ) { + + if ( /^data:/i.test( image.src ) ) { + + return image.src; + + } + + if ( typeof HTMLCanvasElement === 'undefined' ) { + + return image.src; + + } + + let canvas; + + if ( image instanceof HTMLCanvasElement ) { + + canvas = image; + + } else { + + if ( _canvas === undefined ) _canvas = createElementNS( 'canvas' ); + + _canvas.width = image.width; + _canvas.height = image.height; + + const context = _canvas.getContext( '2d' ); + + if ( image instanceof ImageData ) { + + context.putImageData( image, 0, 0 ); + + } else { + + context.drawImage( image, 0, 0, image.width, image.height ); + + } + + canvas = _canvas; + + } + + if ( canvas.width > 2048 || canvas.height > 2048 ) { + + console.warn( 'THREE.ImageUtils.getDataURL: Image converted to jpg for performance reasons', image ); + + return canvas.toDataURL( 'image/jpeg', 0.6 ); + + } else { + + return canvas.toDataURL( 'image/png' ); + + } + + } + + static sRGBToLinear( image ) { + + if ( ( typeof HTMLImageElement !== 'undefined' && image instanceof HTMLImageElement ) || + ( typeof HTMLCanvasElement !== 'undefined' && image instanceof HTMLCanvasElement ) || + ( typeof ImageBitmap !== 'undefined' && image instanceof ImageBitmap ) ) { + + const canvas = createElementNS( 'canvas' ); + + canvas.width = image.width; + canvas.height = image.height; + + const context = canvas.getContext( '2d' ); + context.drawImage( image, 0, 0, image.width, image.height ); + + const imageData = context.getImageData( 0, 0, image.width, image.height ); + const data = imageData.data; + + for ( let i = 0; i < data.length; i ++ ) { + + data[ i ] = SRGBToLinear( data[ i ] / 255 ) * 255; + + } + + context.putImageData( imageData, 0, 0 ); + + return canvas; + + } else if ( image.data ) { + + const data = image.data.slice( 0 ); + + for ( let i = 0; i < data.length; i ++ ) { + + if ( data instanceof Uint8Array || data instanceof Uint8ClampedArray ) { + + data[ i ] = Math.floor( SRGBToLinear( data[ i ] / 255 ) * 255 ); + + } else { + + // assuming float + + data[ i ] = SRGBToLinear( data[ i ] ); + + } + + } + + return { + data: data, + width: image.width, + height: image.height + }; + + } else { + + console.warn( 'THREE.ImageUtils.sRGBToLinear(): Unsupported image type. No color space conversion applied.' ); + return image; + + } + + } + +} + +let _sourceId = 0; + +class Source { + + constructor( data = null ) { + + this.isSource = true; + + Object.defineProperty( this, 'id', { value: _sourceId ++ } ); + + this.uuid = generateUUID(); + + this.data = data; + this.dataReady = true; + + this.version = 0; + + } + + set needsUpdate( value ) { + + if ( value === true ) this.version ++; + + } + + toJSON( meta ) { + + const isRootObject = ( meta === undefined || typeof meta === 'string' ); + + if ( ! isRootObject && meta.images[ this.uuid ] !== undefined ) { + + return meta.images[ this.uuid ]; + + } + + const output = { + uuid: this.uuid, + url: '' + }; + + const data = this.data; + + if ( data !== null ) { + + let url; + + if ( Array.isArray( data ) ) { + + // cube texture + + url = []; + + for ( let i = 0, l = data.length; i < l; i ++ ) { + + if ( data[ i ].isDataTexture ) { + + url.push( serializeImage( data[ i ].image ) ); + + } else { + + url.push( serializeImage( data[ i ] ) ); + + } + + } + + } else { + + // texture + + url = serializeImage( data ); + + } + + output.url = url; + + } + + if ( ! isRootObject ) { + + meta.images[ this.uuid ] = output; + + } + + return output; + + } + +} + +function serializeImage( image ) { + + if ( ( typeof HTMLImageElement !== 'undefined' && image instanceof HTMLImageElement ) || + ( typeof HTMLCanvasElement !== 'undefined' && image instanceof HTMLCanvasElement ) || + ( typeof ImageBitmap !== 'undefined' && image instanceof ImageBitmap ) ) { + + // default images + + return ImageUtils.getDataURL( image ); + + } else { + + if ( image.data ) { + + // images of DataTexture + + return { + data: Array.from( image.data ), + width: image.width, + height: image.height, + type: image.data.constructor.name + }; + + } else { + + console.warn( 'THREE.Texture: Unable to serialize Texture.' ); + return {}; + + } + + } + +} + +let _textureId = 0; + +class Texture extends EventDispatcher { + + constructor( image = Texture.DEFAULT_IMAGE, mapping = Texture.DEFAULT_MAPPING, wrapS = ClampToEdgeWrapping, wrapT = ClampToEdgeWrapping, magFilter = LinearFilter, minFilter = LinearMipmapLinearFilter, format = RGBAFormat, type = UnsignedByteType, anisotropy = Texture.DEFAULT_ANISOTROPY, colorSpace = NoColorSpace ) { + + super(); + + this.isTexture = true; + + Object.defineProperty( this, 'id', { value: _textureId ++ } ); + + this.uuid = generateUUID(); + + this.name = ''; + + this.source = new Source( image ); + this.mipmaps = []; + + this.mapping = mapping; + this.channel = 0; + + this.wrapS = wrapS; + this.wrapT = wrapT; + + this.magFilter = magFilter; + this.minFilter = minFilter; + + this.anisotropy = anisotropy; + + this.format = format; + this.internalFormat = null; + this.type = type; + + this.offset = new Vector2( 0, 0 ); + this.repeat = new Vector2( 1, 1 ); + this.center = new Vector2( 0, 0 ); + this.rotation = 0; + + this.matrixAutoUpdate = true; + this.matrix = new Matrix3(); + + this.generateMipmaps = true; + this.premultiplyAlpha = false; + this.flipY = true; + this.unpackAlignment = 4; // valid values: 1, 2, 4, 8 (see http://www.khronos.org/opengles/sdk/docs/man/xhtml/glPixelStorei.xml) + + this.colorSpace = colorSpace; + + this.userData = {}; + + this.version = 0; + this.onUpdate = null; + + this.isRenderTargetTexture = false; // indicates whether a texture belongs to a render target or not + this.pmremVersion = 0; // indicates whether this texture should be processed by PMREMGenerator or not (only relevant for render target textures) + + } + + get image() { + + return this.source.data; + + } + + set image( value = null ) { + + this.source.data = value; + + } + + updateMatrix() { + + this.matrix.setUvTransform( this.offset.x, this.offset.y, this.repeat.x, this.repeat.y, this.rotation, this.center.x, this.center.y ); + + } + + clone() { + + return new this.constructor().copy( this ); + + } + + copy( source ) { + + this.name = source.name; + + this.source = source.source; + this.mipmaps = source.mipmaps.slice( 0 ); + + this.mapping = source.mapping; + this.channel = source.channel; + + this.wrapS = source.wrapS; + this.wrapT = source.wrapT; + + this.magFilter = source.magFilter; + this.minFilter = source.minFilter; + + this.anisotropy = source.anisotropy; + + this.format = source.format; + this.internalFormat = source.internalFormat; + this.type = source.type; + + this.offset.copy( source.offset ); + this.repeat.copy( source.repeat ); + this.center.copy( source.center ); + this.rotation = source.rotation; + + this.matrixAutoUpdate = source.matrixAutoUpdate; + this.matrix.copy( source.matrix ); + + this.generateMipmaps = source.generateMipmaps; + this.premultiplyAlpha = source.premultiplyAlpha; + this.flipY = source.flipY; + this.unpackAlignment = source.unpackAlignment; + this.colorSpace = source.colorSpace; + + this.userData = JSON.parse( JSON.stringify( source.userData ) ); + + this.needsUpdate = true; + + return this; + + } + + toJSON( meta ) { + + const isRootObject = ( meta === undefined || typeof meta === 'string' ); + + if ( ! isRootObject && meta.textures[ this.uuid ] !== undefined ) { + + return meta.textures[ this.uuid ]; + + } + + const output = { + + metadata: { + version: 4.6, + type: 'Texture', + generator: 'Texture.toJSON' + }, + + uuid: this.uuid, + name: this.name, + + image: this.source.toJSON( meta ).uuid, + + mapping: this.mapping, + channel: this.channel, + + repeat: [ this.repeat.x, this.repeat.y ], + offset: [ this.offset.x, this.offset.y ], + center: [ this.center.x, this.center.y ], + rotation: this.rotation, + + wrap: [ this.wrapS, this.wrapT ], + + format: this.format, + internalFormat: this.internalFormat, + type: this.type, + colorSpace: this.colorSpace, + + minFilter: this.minFilter, + magFilter: this.magFilter, + anisotropy: this.anisotropy, + + flipY: this.flipY, + + generateMipmaps: this.generateMipmaps, + premultiplyAlpha: this.premultiplyAlpha, + unpackAlignment: this.unpackAlignment + + }; + + if ( Object.keys( this.userData ).length > 0 ) output.userData = this.userData; + + if ( ! isRootObject ) { + + meta.textures[ this.uuid ] = output; + + } + + return output; + + } + + dispose() { + + this.dispatchEvent( { type: 'dispose' } ); + + } + + transformUv( uv ) { + + if ( this.mapping !== UVMapping ) return uv; + + uv.applyMatrix3( this.matrix ); + + if ( uv.x < 0 || uv.x > 1 ) { + + switch ( this.wrapS ) { + + case RepeatWrapping: + + uv.x = uv.x - Math.floor( uv.x ); + break; + + case ClampToEdgeWrapping: + + uv.x = uv.x < 0 ? 0 : 1; + break; + + case MirroredRepeatWrapping: + + if ( Math.abs( Math.floor( uv.x ) % 2 ) === 1 ) { + + uv.x = Math.ceil( uv.x ) - uv.x; + + } else { + + uv.x = uv.x - Math.floor( uv.x ); + + } + + break; + + } + + } + + if ( uv.y < 0 || uv.y > 1 ) { + + switch ( this.wrapT ) { + + case RepeatWrapping: + + uv.y = uv.y - Math.floor( uv.y ); + break; + + case ClampToEdgeWrapping: + + uv.y = uv.y < 0 ? 0 : 1; + break; + + case MirroredRepeatWrapping: + + if ( Math.abs( Math.floor( uv.y ) % 2 ) === 1 ) { + + uv.y = Math.ceil( uv.y ) - uv.y; + + } else { + + uv.y = uv.y - Math.floor( uv.y ); + + } + + break; + + } + + } + + if ( this.flipY ) { + + uv.y = 1 - uv.y; + + } + + return uv; + + } + + set needsUpdate( value ) { + + if ( value === true ) { + + this.version ++; + this.source.needsUpdate = true; + + } + + } + + set needsPMREMUpdate( value ) { + + if ( value === true ) { + + this.pmremVersion ++; + + } + + } + +} + +Texture.DEFAULT_IMAGE = null; +Texture.DEFAULT_MAPPING = UVMapping; +Texture.DEFAULT_ANISOTROPY = 1; + +class Vector4 { + + constructor( x = 0, y = 0, z = 0, w = 1 ) { + + Vector4.prototype.isVector4 = true; + + this.x = x; + this.y = y; + this.z = z; + this.w = w; + + } + + get width() { + + return this.z; + + } + + set width( value ) { + + this.z = value; + + } + + get height() { + + return this.w; + + } + + set height( value ) { + + this.w = value; + + } + + set( x, y, z, w ) { + + this.x = x; + this.y = y; + this.z = z; + this.w = w; + + return this; + + } + + setScalar( scalar ) { + + this.x = scalar; + this.y = scalar; + this.z = scalar; + this.w = scalar; + + return this; + + } + + setX( x ) { + + this.x = x; + + return this; + + } + + setY( y ) { + + this.y = y; + + return this; + + } + + setZ( z ) { + + this.z = z; + + return this; + + } + + setW( w ) { + + this.w = w; + + return this; + + } + + setComponent( index, value ) { + + switch ( index ) { + + case 0: this.x = value; break; + case 1: this.y = value; break; + case 2: this.z = value; break; + case 3: this.w = value; break; + default: throw new Error( 'index is out of range: ' + index ); + + } + + return this; + + } + + getComponent( index ) { + + switch ( index ) { + + case 0: return this.x; + case 1: return this.y; + case 2: return this.z; + case 3: return this.w; + default: throw new Error( 'index is out of range: ' + index ); + + } + + } + + clone() { + + return new this.constructor( this.x, this.y, this.z, this.w ); + + } + + copy( v ) { + + this.x = v.x; + this.y = v.y; + this.z = v.z; + this.w = ( v.w !== undefined ) ? v.w : 1; + + return this; + + } + + add( v ) { + + this.x += v.x; + this.y += v.y; + this.z += v.z; + this.w += v.w; + + return this; + + } + + addScalar( s ) { + + this.x += s; + this.y += s; + this.z += s; + this.w += s; + + return this; + + } + + addVectors( a, b ) { + + this.x = a.x + b.x; + this.y = a.y + b.y; + this.z = a.z + b.z; + this.w = a.w + b.w; + + return this; + + } + + addScaledVector( v, s ) { + + this.x += v.x * s; + this.y += v.y * s; + this.z += v.z * s; + this.w += v.w * s; + + return this; + + } + + sub( v ) { + + this.x -= v.x; + this.y -= v.y; + this.z -= v.z; + this.w -= v.w; + + return this; + + } + + subScalar( s ) { + + this.x -= s; + this.y -= s; + this.z -= s; + this.w -= s; + + return this; + + } + + subVectors( a, b ) { + + this.x = a.x - b.x; + this.y = a.y - b.y; + this.z = a.z - b.z; + this.w = a.w - b.w; + + return this; + + } + + multiply( v ) { + + this.x *= v.x; + this.y *= v.y; + this.z *= v.z; + this.w *= v.w; + + return this; + + } + + multiplyScalar( scalar ) { + + this.x *= scalar; + this.y *= scalar; + this.z *= scalar; + this.w *= scalar; + + return this; + + } + + applyMatrix4( m ) { + + const x = this.x, y = this.y, z = this.z, w = this.w; + const e = m.elements; + + this.x = e[ 0 ] * x + e[ 4 ] * y + e[ 8 ] * z + e[ 12 ] * w; + this.y = e[ 1 ] * x + e[ 5 ] * y + e[ 9 ] * z + e[ 13 ] * w; + this.z = e[ 2 ] * x + e[ 6 ] * y + e[ 10 ] * z + e[ 14 ] * w; + this.w = e[ 3 ] * x + e[ 7 ] * y + e[ 11 ] * z + e[ 15 ] * w; + + return this; + + } + + divideScalar( scalar ) { + + return this.multiplyScalar( 1 / scalar ); + + } + + setAxisAngleFromQuaternion( q ) { + + // http://www.euclideanspace.com/maths/geometry/rotations/conversions/quaternionToAngle/index.htm + + // q is assumed to be normalized + + this.w = 2 * Math.acos( q.w ); + + const s = Math.sqrt( 1 - q.w * q.w ); + + if ( s < 0.0001 ) { + + this.x = 1; + this.y = 0; + this.z = 0; + + } else { + + this.x = q.x / s; + this.y = q.y / s; + this.z = q.z / s; + + } + + return this; + + } + + setAxisAngleFromRotationMatrix( m ) { + + // http://www.euclideanspace.com/maths/geometry/rotations/conversions/matrixToAngle/index.htm + + // assumes the upper 3x3 of m is a pure rotation matrix (i.e, unscaled) + + let angle, x, y, z; // variables for result + const epsilon = 0.01, // margin to allow for rounding errors + epsilon2 = 0.1, // margin to distinguish between 0 and 180 degrees + + te = m.elements, + + m11 = te[ 0 ], m12 = te[ 4 ], m13 = te[ 8 ], + m21 = te[ 1 ], m22 = te[ 5 ], m23 = te[ 9 ], + m31 = te[ 2 ], m32 = te[ 6 ], m33 = te[ 10 ]; + + if ( ( Math.abs( m12 - m21 ) < epsilon ) && + ( Math.abs( m13 - m31 ) < epsilon ) && + ( Math.abs( m23 - m32 ) < epsilon ) ) { + + // singularity found + // first check for identity matrix which must have +1 for all terms + // in leading diagonal and zero in other terms + + if ( ( Math.abs( m12 + m21 ) < epsilon2 ) && + ( Math.abs( m13 + m31 ) < epsilon2 ) && + ( Math.abs( m23 + m32 ) < epsilon2 ) && + ( Math.abs( m11 + m22 + m33 - 3 ) < epsilon2 ) ) { + + // this singularity is identity matrix so angle = 0 + + this.set( 1, 0, 0, 0 ); + + return this; // zero angle, arbitrary axis + + } + + // otherwise this singularity is angle = 180 + + angle = Math.PI; + + const xx = ( m11 + 1 ) / 2; + const yy = ( m22 + 1 ) / 2; + const zz = ( m33 + 1 ) / 2; + const xy = ( m12 + m21 ) / 4; + const xz = ( m13 + m31 ) / 4; + const yz = ( m23 + m32 ) / 4; + + if ( ( xx > yy ) && ( xx > zz ) ) { + + // m11 is the largest diagonal term + + if ( xx < epsilon ) { + + x = 0; + y = 0.707106781; + z = 0.707106781; + + } else { + + x = Math.sqrt( xx ); + y = xy / x; + z = xz / x; + + } + + } else if ( yy > zz ) { + + // m22 is the largest diagonal term + + if ( yy < epsilon ) { + + x = 0.707106781; + y = 0; + z = 0.707106781; + + } else { + + y = Math.sqrt( yy ); + x = xy / y; + z = yz / y; + + } + + } else { + + // m33 is the largest diagonal term so base result on this + + if ( zz < epsilon ) { + + x = 0.707106781; + y = 0.707106781; + z = 0; + + } else { + + z = Math.sqrt( zz ); + x = xz / z; + y = yz / z; + + } + + } + + this.set( x, y, z, angle ); + + return this; // return 180 deg rotation + + } + + // as we have reached here there are no singularities so we can handle normally + + let s = Math.sqrt( ( m32 - m23 ) * ( m32 - m23 ) + + ( m13 - m31 ) * ( m13 - m31 ) + + ( m21 - m12 ) * ( m21 - m12 ) ); // used to normalize + + if ( Math.abs( s ) < 0.001 ) s = 1; + + // prevent divide by zero, should not happen if matrix is orthogonal and should be + // caught by singularity test above, but I've left it in just in case + + this.x = ( m32 - m23 ) / s; + this.y = ( m13 - m31 ) / s; + this.z = ( m21 - m12 ) / s; + this.w = Math.acos( ( m11 + m22 + m33 - 1 ) / 2 ); + + return this; + + } + + min( v ) { + + this.x = Math.min( this.x, v.x ); + this.y = Math.min( this.y, v.y ); + this.z = Math.min( this.z, v.z ); + this.w = Math.min( this.w, v.w ); + + return this; + + } + + max( v ) { + + this.x = Math.max( this.x, v.x ); + this.y = Math.max( this.y, v.y ); + this.z = Math.max( this.z, v.z ); + this.w = Math.max( this.w, v.w ); + + return this; + + } + + clamp( min, max ) { + + // assumes min < max, componentwise + + this.x = Math.max( min.x, Math.min( max.x, this.x ) ); + this.y = Math.max( min.y, Math.min( max.y, this.y ) ); + this.z = Math.max( min.z, Math.min( max.z, this.z ) ); + this.w = Math.max( min.w, Math.min( max.w, this.w ) ); + + return this; + + } + + clampScalar( minVal, maxVal ) { + + this.x = Math.max( minVal, Math.min( maxVal, this.x ) ); + this.y = Math.max( minVal, Math.min( maxVal, this.y ) ); + this.z = Math.max( minVal, Math.min( maxVal, this.z ) ); + this.w = Math.max( minVal, Math.min( maxVal, this.w ) ); + + return this; + + } + + clampLength( min, max ) { + + const length = this.length(); + + return this.divideScalar( length || 1 ).multiplyScalar( Math.max( min, Math.min( max, length ) ) ); + + } + + floor() { + + this.x = Math.floor( this.x ); + this.y = Math.floor( this.y ); + this.z = Math.floor( this.z ); + this.w = Math.floor( this.w ); + + return this; + + } + + ceil() { + + this.x = Math.ceil( this.x ); + this.y = Math.ceil( this.y ); + this.z = Math.ceil( this.z ); + this.w = Math.ceil( this.w ); + + return this; + + } + + round() { + + this.x = Math.round( this.x ); + this.y = Math.round( this.y ); + this.z = Math.round( this.z ); + this.w = Math.round( this.w ); + + return this; + + } + + roundToZero() { + + this.x = Math.trunc( this.x ); + this.y = Math.trunc( this.y ); + this.z = Math.trunc( this.z ); + this.w = Math.trunc( this.w ); + + return this; + + } + + negate() { + + this.x = - this.x; + this.y = - this.y; + this.z = - this.z; + this.w = - this.w; + + return this; + + } + + dot( v ) { + + return this.x * v.x + this.y * v.y + this.z * v.z + this.w * v.w; + + } + + lengthSq() { + + return this.x * this.x + this.y * this.y + this.z * this.z + this.w * this.w; + + } + + length() { + + return Math.sqrt( this.x * this.x + this.y * this.y + this.z * this.z + this.w * this.w ); + + } + + manhattanLength() { + + return Math.abs( this.x ) + Math.abs( this.y ) + Math.abs( this.z ) + Math.abs( this.w ); + + } + + normalize() { + + return this.divideScalar( this.length() || 1 ); + + } + + setLength( length ) { + + return this.normalize().multiplyScalar( length ); + + } + + lerp( v, alpha ) { + + this.x += ( v.x - this.x ) * alpha; + this.y += ( v.y - this.y ) * alpha; + this.z += ( v.z - this.z ) * alpha; + this.w += ( v.w - this.w ) * alpha; + + return this; + + } + + lerpVectors( v1, v2, alpha ) { + + this.x = v1.x + ( v2.x - v1.x ) * alpha; + this.y = v1.y + ( v2.y - v1.y ) * alpha; + this.z = v1.z + ( v2.z - v1.z ) * alpha; + this.w = v1.w + ( v2.w - v1.w ) * alpha; + + return this; + + } + + equals( v ) { + + return ( ( v.x === this.x ) && ( v.y === this.y ) && ( v.z === this.z ) && ( v.w === this.w ) ); + + } + + fromArray( array, offset = 0 ) { + + this.x = array[ offset ]; + this.y = array[ offset + 1 ]; + this.z = array[ offset + 2 ]; + this.w = array[ offset + 3 ]; + + return this; + + } + + toArray( array = [], offset = 0 ) { + + array[ offset ] = this.x; + array[ offset + 1 ] = this.y; + array[ offset + 2 ] = this.z; + array[ offset + 3 ] = this.w; + + return array; + + } + + fromBufferAttribute( attribute, index ) { + + this.x = attribute.getX( index ); + this.y = attribute.getY( index ); + this.z = attribute.getZ( index ); + this.w = attribute.getW( index ); + + return this; + + } + + random() { + + this.x = Math.random(); + this.y = Math.random(); + this.z = Math.random(); + this.w = Math.random(); + + return this; + + } + + *[ Symbol.iterator ]() { + + yield this.x; + yield this.y; + yield this.z; + yield this.w; + + } + +} + +/* + In options, we can specify: + * Texture parameters for an auto-generated target texture + * depthBuffer/stencilBuffer: Booleans to indicate if we should generate these buffers +*/ +class RenderTarget extends EventDispatcher { + + constructor( width = 1, height = 1, options = {} ) { + + super(); + + this.isRenderTarget = true; + + this.width = width; + this.height = height; + this.depth = 1; + + this.scissor = new Vector4( 0, 0, width, height ); + this.scissorTest = false; + + this.viewport = new Vector4( 0, 0, width, height ); + + const image = { width: width, height: height, depth: 1 }; + + options = Object.assign( { + generateMipmaps: false, + internalFormat: null, + minFilter: LinearFilter, + depthBuffer: true, + stencilBuffer: false, + resolveDepthBuffer: true, + resolveStencilBuffer: true, + depthTexture: null, + samples: 0, + count: 1 + }, options ); + + const texture = new Texture( image, options.mapping, options.wrapS, options.wrapT, options.magFilter, options.minFilter, options.format, options.type, options.anisotropy, options.colorSpace ); + + texture.flipY = false; + texture.generateMipmaps = options.generateMipmaps; + texture.internalFormat = options.internalFormat; + + this.textures = []; + + const count = options.count; + for ( let i = 0; i < count; i ++ ) { + + this.textures[ i ] = texture.clone(); + this.textures[ i ].isRenderTargetTexture = true; + + } + + this.depthBuffer = options.depthBuffer; + this.stencilBuffer = options.stencilBuffer; + + this.resolveDepthBuffer = options.resolveDepthBuffer; + this.resolveStencilBuffer = options.resolveStencilBuffer; + + this.depthTexture = options.depthTexture; + + this.samples = options.samples; + + } + + get texture() { + + return this.textures[ 0 ]; + + } + + set texture( value ) { + + this.textures[ 0 ] = value; + + } + + setSize( width, height, depth = 1 ) { + + if ( this.width !== width || this.height !== height || this.depth !== depth ) { + + this.width = width; + this.height = height; + this.depth = depth; + + for ( let i = 0, il = this.textures.length; i < il; i ++ ) { + + this.textures[ i ].image.width = width; + this.textures[ i ].image.height = height; + this.textures[ i ].image.depth = depth; + + } + + this.dispose(); + + } + + this.viewport.set( 0, 0, width, height ); + this.scissor.set( 0, 0, width, height ); + + } + + clone() { + + return new this.constructor().copy( this ); + + } + + copy( source ) { + + this.width = source.width; + this.height = source.height; + this.depth = source.depth; + + this.scissor.copy( source.scissor ); + this.scissorTest = source.scissorTest; + + this.viewport.copy( source.viewport ); + + this.textures.length = 0; + + for ( let i = 0, il = source.textures.length; i < il; i ++ ) { + + this.textures[ i ] = source.textures[ i ].clone(); + this.textures[ i ].isRenderTargetTexture = true; + + } + + // ensure image object is not shared, see #20328 + + const image = Object.assign( {}, source.texture.image ); + this.texture.source = new Source( image ); + + this.depthBuffer = source.depthBuffer; + this.stencilBuffer = source.stencilBuffer; + + this.resolveDepthBuffer = source.resolveDepthBuffer; + this.resolveStencilBuffer = source.resolveStencilBuffer; + + if ( source.depthTexture !== null ) this.depthTexture = source.depthTexture.clone(); + + this.samples = source.samples; + + return this; + + } + + dispose() { + + this.dispatchEvent( { type: 'dispose' } ); + + } + +} + +class WebGLRenderTarget extends RenderTarget { + + constructor( width = 1, height = 1, options = {} ) { + + super( width, height, options ); + + this.isWebGLRenderTarget = true; + + } + +} + +class DataArrayTexture extends Texture { + + constructor( data = null, width = 1, height = 1, depth = 1 ) { + + super( null ); + + this.isDataArrayTexture = true; + + this.image = { data, width, height, depth }; + + this.magFilter = NearestFilter; + this.minFilter = NearestFilter; + + this.wrapR = ClampToEdgeWrapping; + + this.generateMipmaps = false; + this.flipY = false; + this.unpackAlignment = 1; + + this.layerUpdates = new Set(); + + } + + addLayerUpdate( layerIndex ) { + + this.layerUpdates.add( layerIndex ); + + } + + clearLayerUpdates() { + + this.layerUpdates.clear(); + + } + +} + +class WebGLArrayRenderTarget extends WebGLRenderTarget { + + constructor( width = 1, height = 1, depth = 1, options = {} ) { + + super( width, height, options ); + + this.isWebGLArrayRenderTarget = true; + + this.depth = depth; + + this.texture = new DataArrayTexture( null, width, height, depth ); + + this.texture.isRenderTargetTexture = true; + + } + +} + +class Data3DTexture extends Texture { + + constructor( data = null, width = 1, height = 1, depth = 1 ) { + + // We're going to add .setXXX() methods for setting properties later. + // Users can still set in DataTexture3D directly. + // + // const texture = new THREE.DataTexture3D( data, width, height, depth ); + // texture.anisotropy = 16; + // + // See #14839 + + super( null ); + + this.isData3DTexture = true; + + this.image = { data, width, height, depth }; + + this.magFilter = NearestFilter; + this.minFilter = NearestFilter; + + this.wrapR = ClampToEdgeWrapping; + + this.generateMipmaps = false; + this.flipY = false; + this.unpackAlignment = 1; + + } + +} + +class WebGL3DRenderTarget extends WebGLRenderTarget { + + constructor( width = 1, height = 1, depth = 1, options = {} ) { + + super( width, height, options ); + + this.isWebGL3DRenderTarget = true; + + this.depth = depth; + + this.texture = new Data3DTexture( null, width, height, depth ); + + this.texture.isRenderTargetTexture = true; + + } + +} + +class Quaternion { + + constructor( x = 0, y = 0, z = 0, w = 1 ) { + + this.isQuaternion = true; + + this._x = x; + this._y = y; + this._z = z; + this._w = w; + + } + + static slerpFlat( dst, dstOffset, src0, srcOffset0, src1, srcOffset1, t ) { + + // fuzz-free, array-based Quaternion SLERP operation + + let x0 = src0[ srcOffset0 + 0 ], + y0 = src0[ srcOffset0 + 1 ], + z0 = src0[ srcOffset0 + 2 ], + w0 = src0[ srcOffset0 + 3 ]; + + const x1 = src1[ srcOffset1 + 0 ], + y1 = src1[ srcOffset1 + 1 ], + z1 = src1[ srcOffset1 + 2 ], + w1 = src1[ srcOffset1 + 3 ]; + + if ( t === 0 ) { + + dst[ dstOffset + 0 ] = x0; + dst[ dstOffset + 1 ] = y0; + dst[ dstOffset + 2 ] = z0; + dst[ dstOffset + 3 ] = w0; + return; + + } + + if ( t === 1 ) { + + dst[ dstOffset + 0 ] = x1; + dst[ dstOffset + 1 ] = y1; + dst[ dstOffset + 2 ] = z1; + dst[ dstOffset + 3 ] = w1; + return; + + } + + if ( w0 !== w1 || x0 !== x1 || y0 !== y1 || z0 !== z1 ) { + + let s = 1 - t; + const cos = x0 * x1 + y0 * y1 + z0 * z1 + w0 * w1, + dir = ( cos >= 0 ? 1 : - 1 ), + sqrSin = 1 - cos * cos; + + // Skip the Slerp for tiny steps to avoid numeric problems: + if ( sqrSin > Number.EPSILON ) { + + const sin = Math.sqrt( sqrSin ), + len = Math.atan2( sin, cos * dir ); + + s = Math.sin( s * len ) / sin; + t = Math.sin( t * len ) / sin; + + } + + const tDir = t * dir; + + x0 = x0 * s + x1 * tDir; + y0 = y0 * s + y1 * tDir; + z0 = z0 * s + z1 * tDir; + w0 = w0 * s + w1 * tDir; + + // Normalize in case we just did a lerp: + if ( s === 1 - t ) { + + const f = 1 / Math.sqrt( x0 * x0 + y0 * y0 + z0 * z0 + w0 * w0 ); + + x0 *= f; + y0 *= f; + z0 *= f; + w0 *= f; + + } + + } + + dst[ dstOffset ] = x0; + dst[ dstOffset + 1 ] = y0; + dst[ dstOffset + 2 ] = z0; + dst[ dstOffset + 3 ] = w0; + + } + + static multiplyQuaternionsFlat( dst, dstOffset, src0, srcOffset0, src1, srcOffset1 ) { + + const x0 = src0[ srcOffset0 ]; + const y0 = src0[ srcOffset0 + 1 ]; + const z0 = src0[ srcOffset0 + 2 ]; + const w0 = src0[ srcOffset0 + 3 ]; + + const x1 = src1[ srcOffset1 ]; + const y1 = src1[ srcOffset1 + 1 ]; + const z1 = src1[ srcOffset1 + 2 ]; + const w1 = src1[ srcOffset1 + 3 ]; + + dst[ dstOffset ] = x0 * w1 + w0 * x1 + y0 * z1 - z0 * y1; + dst[ dstOffset + 1 ] = y0 * w1 + w0 * y1 + z0 * x1 - x0 * z1; + dst[ dstOffset + 2 ] = z0 * w1 + w0 * z1 + x0 * y1 - y0 * x1; + dst[ dstOffset + 3 ] = w0 * w1 - x0 * x1 - y0 * y1 - z0 * z1; + + return dst; + + } + + get x() { + + return this._x; + + } + + set x( value ) { + + this._x = value; + this._onChangeCallback(); + + } + + get y() { + + return this._y; + + } + + set y( value ) { + + this._y = value; + this._onChangeCallback(); + + } + + get z() { + + return this._z; + + } + + set z( value ) { + + this._z = value; + this._onChangeCallback(); + + } + + get w() { + + return this._w; + + } + + set w( value ) { + + this._w = value; + this._onChangeCallback(); + + } + + set( x, y, z, w ) { + + this._x = x; + this._y = y; + this._z = z; + this._w = w; + + this._onChangeCallback(); + + return this; + + } + + clone() { + + return new this.constructor( this._x, this._y, this._z, this._w ); + + } + + copy( quaternion ) { + + this._x = quaternion.x; + this._y = quaternion.y; + this._z = quaternion.z; + this._w = quaternion.w; + + this._onChangeCallback(); + + return this; + + } + + setFromEuler( euler, update = true ) { + + const x = euler._x, y = euler._y, z = euler._z, order = euler._order; + + // http://www.mathworks.com/matlabcentral/fileexchange/ + // 20696-function-to-convert-between-dcm-euler-angles-quaternions-and-euler-vectors/ + // content/SpinCalc.m + + const cos = Math.cos; + const sin = Math.sin; + + const c1 = cos( x / 2 ); + const c2 = cos( y / 2 ); + const c3 = cos( z / 2 ); + + const s1 = sin( x / 2 ); + const s2 = sin( y / 2 ); + const s3 = sin( z / 2 ); + + switch ( order ) { + + case 'XYZ': + this._x = s1 * c2 * c3 + c1 * s2 * s3; + this._y = c1 * s2 * c3 - s1 * c2 * s3; + this._z = c1 * c2 * s3 + s1 * s2 * c3; + this._w = c1 * c2 * c3 - s1 * s2 * s3; + break; + + case 'YXZ': + this._x = s1 * c2 * c3 + c1 * s2 * s3; + this._y = c1 * s2 * c3 - s1 * c2 * s3; + this._z = c1 * c2 * s3 - s1 * s2 * c3; + this._w = c1 * c2 * c3 + s1 * s2 * s3; + break; + + case 'ZXY': + this._x = s1 * c2 * c3 - c1 * s2 * s3; + this._y = c1 * s2 * c3 + s1 * c2 * s3; + this._z = c1 * c2 * s3 + s1 * s2 * c3; + this._w = c1 * c2 * c3 - s1 * s2 * s3; + break; + + case 'ZYX': + this._x = s1 * c2 * c3 - c1 * s2 * s3; + this._y = c1 * s2 * c3 + s1 * c2 * s3; + this._z = c1 * c2 * s3 - s1 * s2 * c3; + this._w = c1 * c2 * c3 + s1 * s2 * s3; + break; + + case 'YZX': + this._x = s1 * c2 * c3 + c1 * s2 * s3; + this._y = c1 * s2 * c3 + s1 * c2 * s3; + this._z = c1 * c2 * s3 - s1 * s2 * c3; + this._w = c1 * c2 * c3 - s1 * s2 * s3; + break; + + case 'XZY': + this._x = s1 * c2 * c3 - c1 * s2 * s3; + this._y = c1 * s2 * c3 - s1 * c2 * s3; + this._z = c1 * c2 * s3 + s1 * s2 * c3; + this._w = c1 * c2 * c3 + s1 * s2 * s3; + break; + + default: + console.warn( 'THREE.Quaternion: .setFromEuler() encountered an unknown order: ' + order ); + + } + + if ( update === true ) this._onChangeCallback(); + + return this; + + } + + setFromAxisAngle( axis, angle ) { + + // http://www.euclideanspace.com/maths/geometry/rotations/conversions/angleToQuaternion/index.htm + + // assumes axis is normalized + + const halfAngle = angle / 2, s = Math.sin( halfAngle ); + + this._x = axis.x * s; + this._y = axis.y * s; + this._z = axis.z * s; + this._w = Math.cos( halfAngle ); + + this._onChangeCallback(); + + return this; + + } + + setFromRotationMatrix( m ) { + + // http://www.euclideanspace.com/maths/geometry/rotations/conversions/matrixToQuaternion/index.htm + + // assumes the upper 3x3 of m is a pure rotation matrix (i.e, unscaled) + + const te = m.elements, + + m11 = te[ 0 ], m12 = te[ 4 ], m13 = te[ 8 ], + m21 = te[ 1 ], m22 = te[ 5 ], m23 = te[ 9 ], + m31 = te[ 2 ], m32 = te[ 6 ], m33 = te[ 10 ], + + trace = m11 + m22 + m33; + + if ( trace > 0 ) { + + const s = 0.5 / Math.sqrt( trace + 1.0 ); + + this._w = 0.25 / s; + this._x = ( m32 - m23 ) * s; + this._y = ( m13 - m31 ) * s; + this._z = ( m21 - m12 ) * s; + + } else if ( m11 > m22 && m11 > m33 ) { + + const s = 2.0 * Math.sqrt( 1.0 + m11 - m22 - m33 ); + + this._w = ( m32 - m23 ) / s; + this._x = 0.25 * s; + this._y = ( m12 + m21 ) / s; + this._z = ( m13 + m31 ) / s; + + } else if ( m22 > m33 ) { + + const s = 2.0 * Math.sqrt( 1.0 + m22 - m11 - m33 ); + + this._w = ( m13 - m31 ) / s; + this._x = ( m12 + m21 ) / s; + this._y = 0.25 * s; + this._z = ( m23 + m32 ) / s; + + } else { + + const s = 2.0 * Math.sqrt( 1.0 + m33 - m11 - m22 ); + + this._w = ( m21 - m12 ) / s; + this._x = ( m13 + m31 ) / s; + this._y = ( m23 + m32 ) / s; + this._z = 0.25 * s; + + } + + this._onChangeCallback(); + + return this; + + } + + setFromUnitVectors( vFrom, vTo ) { + + // assumes direction vectors vFrom and vTo are normalized + + let r = vFrom.dot( vTo ) + 1; + + if ( r < Number.EPSILON ) { + + // vFrom and vTo point in opposite directions + + r = 0; + + if ( Math.abs( vFrom.x ) > Math.abs( vFrom.z ) ) { + + this._x = - vFrom.y; + this._y = vFrom.x; + this._z = 0; + this._w = r; + + } else { + + this._x = 0; + this._y = - vFrom.z; + this._z = vFrom.y; + this._w = r; + + } + + } else { + + // crossVectors( vFrom, vTo ); // inlined to avoid cyclic dependency on Vector3 + + this._x = vFrom.y * vTo.z - vFrom.z * vTo.y; + this._y = vFrom.z * vTo.x - vFrom.x * vTo.z; + this._z = vFrom.x * vTo.y - vFrom.y * vTo.x; + this._w = r; + + } + + return this.normalize(); + + } + + angleTo( q ) { + + return 2 * Math.acos( Math.abs( clamp( this.dot( q ), - 1, 1 ) ) ); + + } + + rotateTowards( q, step ) { + + const angle = this.angleTo( q ); + + if ( angle === 0 ) return this; + + const t = Math.min( 1, step / angle ); + + this.slerp( q, t ); + + return this; + + } + + identity() { + + return this.set( 0, 0, 0, 1 ); + + } + + invert() { + + // quaternion is assumed to have unit length + + return this.conjugate(); + + } + + conjugate() { + + this._x *= - 1; + this._y *= - 1; + this._z *= - 1; + + this._onChangeCallback(); + + return this; + + } + + dot( v ) { + + return this._x * v._x + this._y * v._y + this._z * v._z + this._w * v._w; + + } + + lengthSq() { + + return this._x * this._x + this._y * this._y + this._z * this._z + this._w * this._w; + + } + + length() { + + return Math.sqrt( this._x * this._x + this._y * this._y + this._z * this._z + this._w * this._w ); + + } + + normalize() { + + let l = this.length(); + + if ( l === 0 ) { + + this._x = 0; + this._y = 0; + this._z = 0; + this._w = 1; + + } else { + + l = 1 / l; + + this._x = this._x * l; + this._y = this._y * l; + this._z = this._z * l; + this._w = this._w * l; + + } + + this._onChangeCallback(); + + return this; + + } + + multiply( q ) { + + return this.multiplyQuaternions( this, q ); + + } + + premultiply( q ) { + + return this.multiplyQuaternions( q, this ); + + } + + multiplyQuaternions( a, b ) { + + // from http://www.euclideanspace.com/maths/algebra/realNormedAlgebra/quaternions/code/index.htm + + const qax = a._x, qay = a._y, qaz = a._z, qaw = a._w; + const qbx = b._x, qby = b._y, qbz = b._z, qbw = b._w; + + this._x = qax * qbw + qaw * qbx + qay * qbz - qaz * qby; + this._y = qay * qbw + qaw * qby + qaz * qbx - qax * qbz; + this._z = qaz * qbw + qaw * qbz + qax * qby - qay * qbx; + this._w = qaw * qbw - qax * qbx - qay * qby - qaz * qbz; + + this._onChangeCallback(); + + return this; + + } + + slerp( qb, t ) { + + if ( t === 0 ) return this; + if ( t === 1 ) return this.copy( qb ); + + const x = this._x, y = this._y, z = this._z, w = this._w; + + // http://www.euclideanspace.com/maths/algebra/realNormedAlgebra/quaternions/slerp/ + + let cosHalfTheta = w * qb._w + x * qb._x + y * qb._y + z * qb._z; + + if ( cosHalfTheta < 0 ) { + + this._w = - qb._w; + this._x = - qb._x; + this._y = - qb._y; + this._z = - qb._z; + + cosHalfTheta = - cosHalfTheta; + + } else { + + this.copy( qb ); + + } + + if ( cosHalfTheta >= 1.0 ) { + + this._w = w; + this._x = x; + this._y = y; + this._z = z; + + return this; + + } + + const sqrSinHalfTheta = 1.0 - cosHalfTheta * cosHalfTheta; + + if ( sqrSinHalfTheta <= Number.EPSILON ) { + + const s = 1 - t; + this._w = s * w + t * this._w; + this._x = s * x + t * this._x; + this._y = s * y + t * this._y; + this._z = s * z + t * this._z; + + this.normalize(); // normalize calls _onChangeCallback() + + return this; + + } + + const sinHalfTheta = Math.sqrt( sqrSinHalfTheta ); + const halfTheta = Math.atan2( sinHalfTheta, cosHalfTheta ); + const ratioA = Math.sin( ( 1 - t ) * halfTheta ) / sinHalfTheta, + ratioB = Math.sin( t * halfTheta ) / sinHalfTheta; + + this._w = ( w * ratioA + this._w * ratioB ); + this._x = ( x * ratioA + this._x * ratioB ); + this._y = ( y * ratioA + this._y * ratioB ); + this._z = ( z * ratioA + this._z * ratioB ); + + this._onChangeCallback(); + + return this; + + } + + slerpQuaternions( qa, qb, t ) { + + return this.copy( qa ).slerp( qb, t ); + + } + + random() { + + // sets this quaternion to a uniform random unit quaternnion + + // Ken Shoemake + // Uniform random rotations + // D. Kirk, editor, Graphics Gems III, pages 124-132. Academic Press, New York, 1992. + + const theta1 = 2 * Math.PI * Math.random(); + const theta2 = 2 * Math.PI * Math.random(); + + const x0 = Math.random(); + const r1 = Math.sqrt( 1 - x0 ); + const r2 = Math.sqrt( x0 ); + + return this.set( + r1 * Math.sin( theta1 ), + r1 * Math.cos( theta1 ), + r2 * Math.sin( theta2 ), + r2 * Math.cos( theta2 ), + ); + + } + + equals( quaternion ) { + + return ( quaternion._x === this._x ) && ( quaternion._y === this._y ) && ( quaternion._z === this._z ) && ( quaternion._w === this._w ); + + } + + fromArray( array, offset = 0 ) { + + this._x = array[ offset ]; + this._y = array[ offset + 1 ]; + this._z = array[ offset + 2 ]; + this._w = array[ offset + 3 ]; + + this._onChangeCallback(); + + return this; + + } + + toArray( array = [], offset = 0 ) { + + array[ offset ] = this._x; + array[ offset + 1 ] = this._y; + array[ offset + 2 ] = this._z; + array[ offset + 3 ] = this._w; + + return array; + + } + + fromBufferAttribute( attribute, index ) { + + this._x = attribute.getX( index ); + this._y = attribute.getY( index ); + this._z = attribute.getZ( index ); + this._w = attribute.getW( index ); + + this._onChangeCallback(); + + return this; + + } + + toJSON() { + + return this.toArray(); + + } + + _onChange( callback ) { + + this._onChangeCallback = callback; + + return this; + + } + + _onChangeCallback() {} + + *[ Symbol.iterator ]() { + + yield this._x; + yield this._y; + yield this._z; + yield this._w; + + } + +} + +class Vector3 { + + constructor( x = 0, y = 0, z = 0 ) { + + Vector3.prototype.isVector3 = true; + + this.x = x; + this.y = y; + this.z = z; + + } + + set( x, y, z ) { + + if ( z === undefined ) z = this.z; // sprite.scale.set(x,y) + + this.x = x; + this.y = y; + this.z = z; + + return this; + + } + + setScalar( scalar ) { + + this.x = scalar; + this.y = scalar; + this.z = scalar; + + return this; + + } + + setX( x ) { + + this.x = x; + + return this; + + } + + setY( y ) { + + this.y = y; + + return this; + + } + + setZ( z ) { + + this.z = z; + + return this; + + } + + setComponent( index, value ) { + + switch ( index ) { + + case 0: this.x = value; break; + case 1: this.y = value; break; + case 2: this.z = value; break; + default: throw new Error( 'index is out of range: ' + index ); + + } + + return this; + + } + + getComponent( index ) { + + switch ( index ) { + + case 0: return this.x; + case 1: return this.y; + case 2: return this.z; + default: throw new Error( 'index is out of range: ' + index ); + + } + + } + + clone() { + + return new this.constructor( this.x, this.y, this.z ); + + } + + copy( v ) { + + this.x = v.x; + this.y = v.y; + this.z = v.z; + + return this; + + } + + add( v ) { + + this.x += v.x; + this.y += v.y; + this.z += v.z; + + return this; + + } + + addScalar( s ) { + + this.x += s; + this.y += s; + this.z += s; + + return this; + + } + + addVectors( a, b ) { + + this.x = a.x + b.x; + this.y = a.y + b.y; + this.z = a.z + b.z; + + return this; + + } + + addScaledVector( v, s ) { + + this.x += v.x * s; + this.y += v.y * s; + this.z += v.z * s; + + return this; + + } + + sub( v ) { + + this.x -= v.x; + this.y -= v.y; + this.z -= v.z; + + return this; + + } + + subScalar( s ) { + + this.x -= s; + this.y -= s; + this.z -= s; + + return this; + + } + + subVectors( a, b ) { + + this.x = a.x - b.x; + this.y = a.y - b.y; + this.z = a.z - b.z; + + return this; + + } + + multiply( v ) { + + this.x *= v.x; + this.y *= v.y; + this.z *= v.z; + + return this; + + } + + multiplyScalar( scalar ) { + + this.x *= scalar; + this.y *= scalar; + this.z *= scalar; + + return this; + + } + + multiplyVectors( a, b ) { + + this.x = a.x * b.x; + this.y = a.y * b.y; + this.z = a.z * b.z; + + return this; + + } + + applyEuler( euler ) { + + return this.applyQuaternion( _quaternion$4.setFromEuler( euler ) ); + + } + + applyAxisAngle( axis, angle ) { + + return this.applyQuaternion( _quaternion$4.setFromAxisAngle( axis, angle ) ); + + } + + applyMatrix3( m ) { + + const x = this.x, y = this.y, z = this.z; + const e = m.elements; + + this.x = e[ 0 ] * x + e[ 3 ] * y + e[ 6 ] * z; + this.y = e[ 1 ] * x + e[ 4 ] * y + e[ 7 ] * z; + this.z = e[ 2 ] * x + e[ 5 ] * y + e[ 8 ] * z; + + return this; + + } + + applyNormalMatrix( m ) { + + return this.applyMatrix3( m ).normalize(); + + } + + applyMatrix4( m ) { + + const x = this.x, y = this.y, z = this.z; + const e = m.elements; + + const w = 1 / ( e[ 3 ] * x + e[ 7 ] * y + e[ 11 ] * z + e[ 15 ] ); + + this.x = ( e[ 0 ] * x + e[ 4 ] * y + e[ 8 ] * z + e[ 12 ] ) * w; + this.y = ( e[ 1 ] * x + e[ 5 ] * y + e[ 9 ] * z + e[ 13 ] ) * w; + this.z = ( e[ 2 ] * x + e[ 6 ] * y + e[ 10 ] * z + e[ 14 ] ) * w; + + return this; + + } + + applyQuaternion( q ) { + + // quaternion q is assumed to have unit length + + const vx = this.x, vy = this.y, vz = this.z; + const qx = q.x, qy = q.y, qz = q.z, qw = q.w; + + // t = 2 * cross( q.xyz, v ); + const tx = 2 * ( qy * vz - qz * vy ); + const ty = 2 * ( qz * vx - qx * vz ); + const tz = 2 * ( qx * vy - qy * vx ); + + // v + q.w * t + cross( q.xyz, t ); + this.x = vx + qw * tx + qy * tz - qz * ty; + this.y = vy + qw * ty + qz * tx - qx * tz; + this.z = vz + qw * tz + qx * ty - qy * tx; + + return this; + + } + + project( camera ) { + + return this.applyMatrix4( camera.matrixWorldInverse ).applyMatrix4( camera.projectionMatrix ); + + } + + unproject( camera ) { + + return this.applyMatrix4( camera.projectionMatrixInverse ).applyMatrix4( camera.matrixWorld ); + + } + + transformDirection( m ) { + + // input: THREE.Matrix4 affine matrix + // vector interpreted as a direction + + const x = this.x, y = this.y, z = this.z; + const e = m.elements; + + this.x = e[ 0 ] * x + e[ 4 ] * y + e[ 8 ] * z; + this.y = e[ 1 ] * x + e[ 5 ] * y + e[ 9 ] * z; + this.z = e[ 2 ] * x + e[ 6 ] * y + e[ 10 ] * z; + + return this.normalize(); + + } + + divide( v ) { + + this.x /= v.x; + this.y /= v.y; + this.z /= v.z; + + return this; + + } + + divideScalar( scalar ) { + + return this.multiplyScalar( 1 / scalar ); + + } + + min( v ) { + + this.x = Math.min( this.x, v.x ); + this.y = Math.min( this.y, v.y ); + this.z = Math.min( this.z, v.z ); + + return this; + + } + + max( v ) { + + this.x = Math.max( this.x, v.x ); + this.y = Math.max( this.y, v.y ); + this.z = Math.max( this.z, v.z ); + + return this; + + } + + clamp( min, max ) { + + // assumes min < max, componentwise + + this.x = Math.max( min.x, Math.min( max.x, this.x ) ); + this.y = Math.max( min.y, Math.min( max.y, this.y ) ); + this.z = Math.max( min.z, Math.min( max.z, this.z ) ); + + return this; + + } + + clampScalar( minVal, maxVal ) { + + this.x = Math.max( minVal, Math.min( maxVal, this.x ) ); + this.y = Math.max( minVal, Math.min( maxVal, this.y ) ); + this.z = Math.max( minVal, Math.min( maxVal, this.z ) ); + + return this; + + } + + clampLength( min, max ) { + + const length = this.length(); + + return this.divideScalar( length || 1 ).multiplyScalar( Math.max( min, Math.min( max, length ) ) ); + + } + + floor() { + + this.x = Math.floor( this.x ); + this.y = Math.floor( this.y ); + this.z = Math.floor( this.z ); + + return this; + + } + + ceil() { + + this.x = Math.ceil( this.x ); + this.y = Math.ceil( this.y ); + this.z = Math.ceil( this.z ); + + return this; + + } + + round() { + + this.x = Math.round( this.x ); + this.y = Math.round( this.y ); + this.z = Math.round( this.z ); + + return this; + + } + + roundToZero() { + + this.x = Math.trunc( this.x ); + this.y = Math.trunc( this.y ); + this.z = Math.trunc( this.z ); + + return this; + + } + + negate() { + + this.x = - this.x; + this.y = - this.y; + this.z = - this.z; + + return this; + + } + + dot( v ) { + + return this.x * v.x + this.y * v.y + this.z * v.z; + + } + + // TODO lengthSquared? + + lengthSq() { + + return this.x * this.x + this.y * this.y + this.z * this.z; + + } + + length() { + + return Math.sqrt( this.x * this.x + this.y * this.y + this.z * this.z ); + + } + + manhattanLength() { + + return Math.abs( this.x ) + Math.abs( this.y ) + Math.abs( this.z ); + + } + + normalize() { + + return this.divideScalar( this.length() || 1 ); + + } + + setLength( length ) { + + return this.normalize().multiplyScalar( length ); + + } + + lerp( v, alpha ) { + + this.x += ( v.x - this.x ) * alpha; + this.y += ( v.y - this.y ) * alpha; + this.z += ( v.z - this.z ) * alpha; + + return this; + + } + + lerpVectors( v1, v2, alpha ) { + + this.x = v1.x + ( v2.x - v1.x ) * alpha; + this.y = v1.y + ( v2.y - v1.y ) * alpha; + this.z = v1.z + ( v2.z - v1.z ) * alpha; + + return this; + + } + + cross( v ) { + + return this.crossVectors( this, v ); + + } + + crossVectors( a, b ) { + + const ax = a.x, ay = a.y, az = a.z; + const bx = b.x, by = b.y, bz = b.z; + + this.x = ay * bz - az * by; + this.y = az * bx - ax * bz; + this.z = ax * by - ay * bx; + + return this; + + } + + projectOnVector( v ) { + + const denominator = v.lengthSq(); + + if ( denominator === 0 ) return this.set( 0, 0, 0 ); + + const scalar = v.dot( this ) / denominator; + + return this.copy( v ).multiplyScalar( scalar ); + + } + + projectOnPlane( planeNormal ) { + + _vector$c.copy( this ).projectOnVector( planeNormal ); + + return this.sub( _vector$c ); + + } + + reflect( normal ) { + + // reflect incident vector off plane orthogonal to normal + // normal is assumed to have unit length + + return this.sub( _vector$c.copy( normal ).multiplyScalar( 2 * this.dot( normal ) ) ); + + } + + angleTo( v ) { + + const denominator = Math.sqrt( this.lengthSq() * v.lengthSq() ); + + if ( denominator === 0 ) return Math.PI / 2; + + const theta = this.dot( v ) / denominator; + + // clamp, to handle numerical problems + + return Math.acos( clamp( theta, - 1, 1 ) ); + + } + + distanceTo( v ) { + + return Math.sqrt( this.distanceToSquared( v ) ); + + } + + distanceToSquared( v ) { + + const dx = this.x - v.x, dy = this.y - v.y, dz = this.z - v.z; + + return dx * dx + dy * dy + dz * dz; + + } + + manhattanDistanceTo( v ) { + + return Math.abs( this.x - v.x ) + Math.abs( this.y - v.y ) + Math.abs( this.z - v.z ); + + } + + setFromSpherical( s ) { + + return this.setFromSphericalCoords( s.radius, s.phi, s.theta ); + + } + + setFromSphericalCoords( radius, phi, theta ) { + + const sinPhiRadius = Math.sin( phi ) * radius; + + this.x = sinPhiRadius * Math.sin( theta ); + this.y = Math.cos( phi ) * radius; + this.z = sinPhiRadius * Math.cos( theta ); + + return this; + + } + + setFromCylindrical( c ) { + + return this.setFromCylindricalCoords( c.radius, c.theta, c.y ); + + } + + setFromCylindricalCoords( radius, theta, y ) { + + this.x = radius * Math.sin( theta ); + this.y = y; + this.z = radius * Math.cos( theta ); + + return this; + + } + + setFromMatrixPosition( m ) { + + const e = m.elements; + + this.x = e[ 12 ]; + this.y = e[ 13 ]; + this.z = e[ 14 ]; + + return this; + + } + + setFromMatrixScale( m ) { + + const sx = this.setFromMatrixColumn( m, 0 ).length(); + const sy = this.setFromMatrixColumn( m, 1 ).length(); + const sz = this.setFromMatrixColumn( m, 2 ).length(); + + this.x = sx; + this.y = sy; + this.z = sz; + + return this; + + } + + setFromMatrixColumn( m, index ) { + + return this.fromArray( m.elements, index * 4 ); + + } + + setFromMatrix3Column( m, index ) { + + return this.fromArray( m.elements, index * 3 ); + + } + + setFromEuler( e ) { + + this.x = e._x; + this.y = e._y; + this.z = e._z; + + return this; + + } + + setFromColor( c ) { + + this.x = c.r; + this.y = c.g; + this.z = c.b; + + return this; + + } + + equals( v ) { + + return ( ( v.x === this.x ) && ( v.y === this.y ) && ( v.z === this.z ) ); + + } + + fromArray( array, offset = 0 ) { + + this.x = array[ offset ]; + this.y = array[ offset + 1 ]; + this.z = array[ offset + 2 ]; + + return this; + + } + + toArray( array = [], offset = 0 ) { + + array[ offset ] = this.x; + array[ offset + 1 ] = this.y; + array[ offset + 2 ] = this.z; + + return array; + + } + + fromBufferAttribute( attribute, index ) { + + this.x = attribute.getX( index ); + this.y = attribute.getY( index ); + this.z = attribute.getZ( index ); + + return this; + + } + + random() { + + this.x = Math.random(); + this.y = Math.random(); + this.z = Math.random(); + + return this; + + } + + randomDirection() { + + // https://mathworld.wolfram.com/SpherePointPicking.html + + const theta = Math.random() * Math.PI * 2; + const u = Math.random() * 2 - 1; + const c = Math.sqrt( 1 - u * u ); + + this.x = c * Math.cos( theta ); + this.y = u; + this.z = c * Math.sin( theta ); + + return this; + + } + + *[ Symbol.iterator ]() { + + yield this.x; + yield this.y; + yield this.z; + + } + +} + +const _vector$c = /*@__PURE__*/ new Vector3(); +const _quaternion$4 = /*@__PURE__*/ new Quaternion(); + +class Box3 { + + constructor( min = new Vector3( + Infinity, + Infinity, + Infinity ), max = new Vector3( - Infinity, - Infinity, - Infinity ) ) { + + this.isBox3 = true; + + this.min = min; + this.max = max; + + } + + set( min, max ) { + + this.min.copy( min ); + this.max.copy( max ); + + return this; + + } + + setFromArray( array ) { + + this.makeEmpty(); + + for ( let i = 0, il = array.length; i < il; i += 3 ) { + + this.expandByPoint( _vector$b.fromArray( array, i ) ); + + } + + return this; + + } + + setFromBufferAttribute( attribute ) { + + this.makeEmpty(); + + for ( let i = 0, il = attribute.count; i < il; i ++ ) { + + this.expandByPoint( _vector$b.fromBufferAttribute( attribute, i ) ); + + } + + return this; + + } + + setFromPoints( points ) { + + this.makeEmpty(); + + for ( let i = 0, il = points.length; i < il; i ++ ) { + + this.expandByPoint( points[ i ] ); + + } + + return this; + + } + + setFromCenterAndSize( center, size ) { + + const halfSize = _vector$b.copy( size ).multiplyScalar( 0.5 ); + + this.min.copy( center ).sub( halfSize ); + this.max.copy( center ).add( halfSize ); + + return this; + + } + + setFromObject( object, precise = false ) { + + this.makeEmpty(); + + return this.expandByObject( object, precise ); + + } + + clone() { + + return new this.constructor().copy( this ); + + } + + copy( box ) { + + this.min.copy( box.min ); + this.max.copy( box.max ); + + return this; + + } + + makeEmpty() { + + this.min.x = this.min.y = this.min.z = + Infinity; + this.max.x = this.max.y = this.max.z = - Infinity; + + return this; + + } + + isEmpty() { + + // this is a more robust check for empty than ( volume <= 0 ) because volume can get positive with two negative axes + + return ( this.max.x < this.min.x ) || ( this.max.y < this.min.y ) || ( this.max.z < this.min.z ); + + } + + getCenter( target ) { + + return this.isEmpty() ? target.set( 0, 0, 0 ) : target.addVectors( this.min, this.max ).multiplyScalar( 0.5 ); + + } + + getSize( target ) { + + return this.isEmpty() ? target.set( 0, 0, 0 ) : target.subVectors( this.max, this.min ); + + } + + expandByPoint( point ) { + + this.min.min( point ); + this.max.max( point ); + + return this; + + } + + expandByVector( vector ) { + + this.min.sub( vector ); + this.max.add( vector ); + + return this; + + } + + expandByScalar( scalar ) { + + this.min.addScalar( - scalar ); + this.max.addScalar( scalar ); + + return this; + + } + + expandByObject( object, precise = false ) { + + // Computes the world-axis-aligned bounding box of an object (including its children), + // accounting for both the object's, and children's, world transforms + + object.updateWorldMatrix( false, false ); + + const geometry = object.geometry; + + if ( geometry !== undefined ) { + + const positionAttribute = geometry.getAttribute( 'position' ); + + // precise AABB computation based on vertex data requires at least a position attribute. + // instancing isn't supported so far and uses the normal (conservative) code path. + + if ( precise === true && positionAttribute !== undefined && object.isInstancedMesh !== true ) { + + for ( let i = 0, l = positionAttribute.count; i < l; i ++ ) { + + if ( object.isMesh === true ) { + + object.getVertexPosition( i, _vector$b ); + + } else { + + _vector$b.fromBufferAttribute( positionAttribute, i ); + + } + + _vector$b.applyMatrix4( object.matrixWorld ); + this.expandByPoint( _vector$b ); + + } + + } else { + + if ( object.boundingBox !== undefined ) { + + // object-level bounding box + + if ( object.boundingBox === null ) { + + object.computeBoundingBox(); + + } + + _box$4.copy( object.boundingBox ); + + + } else { + + // geometry-level bounding box + + if ( geometry.boundingBox === null ) { + + geometry.computeBoundingBox(); + + } + + _box$4.copy( geometry.boundingBox ); + + } + + _box$4.applyMatrix4( object.matrixWorld ); + + this.union( _box$4 ); + + } + + } + + const children = object.children; + + for ( let i = 0, l = children.length; i < l; i ++ ) { + + this.expandByObject( children[ i ], precise ); + + } + + return this; + + } + + containsPoint( point ) { + + return point.x < this.min.x || point.x > this.max.x || + point.y < this.min.y || point.y > this.max.y || + point.z < this.min.z || point.z > this.max.z ? false : true; + + } + + containsBox( box ) { + + return this.min.x <= box.min.x && box.max.x <= this.max.x && + this.min.y <= box.min.y && box.max.y <= this.max.y && + this.min.z <= box.min.z && box.max.z <= this.max.z; + + } + + getParameter( point, target ) { + + // This can potentially have a divide by zero if the box + // has a size dimension of 0. + + return target.set( + ( point.x - this.min.x ) / ( this.max.x - this.min.x ), + ( point.y - this.min.y ) / ( this.max.y - this.min.y ), + ( point.z - this.min.z ) / ( this.max.z - this.min.z ) + ); + + } + + intersectsBox( box ) { + + // using 6 splitting planes to rule out intersections. + return box.max.x < this.min.x || box.min.x > this.max.x || + box.max.y < this.min.y || box.min.y > this.max.y || + box.max.z < this.min.z || box.min.z > this.max.z ? false : true; + + } + + intersectsSphere( sphere ) { + + // Find the point on the AABB closest to the sphere center. + this.clampPoint( sphere.center, _vector$b ); + + // If that point is inside the sphere, the AABB and sphere intersect. + return _vector$b.distanceToSquared( sphere.center ) <= ( sphere.radius * sphere.radius ); + + } + + intersectsPlane( plane ) { + + // We compute the minimum and maximum dot product values. If those values + // are on the same side (back or front) of the plane, then there is no intersection. + + let min, max; + + if ( plane.normal.x > 0 ) { + + min = plane.normal.x * this.min.x; + max = plane.normal.x * this.max.x; + + } else { + + min = plane.normal.x * this.max.x; + max = plane.normal.x * this.min.x; + + } + + if ( plane.normal.y > 0 ) { + + min += plane.normal.y * this.min.y; + max += plane.normal.y * this.max.y; + + } else { + + min += plane.normal.y * this.max.y; + max += plane.normal.y * this.min.y; + + } + + if ( plane.normal.z > 0 ) { + + min += plane.normal.z * this.min.z; + max += plane.normal.z * this.max.z; + + } else { + + min += plane.normal.z * this.max.z; + max += plane.normal.z * this.min.z; + + } + + return ( min <= - plane.constant && max >= - plane.constant ); + + } + + intersectsTriangle( triangle ) { + + if ( this.isEmpty() ) { + + return false; + + } + + // compute box center and extents + this.getCenter( _center ); + _extents.subVectors( this.max, _center ); + + // translate triangle to aabb origin + _v0$2.subVectors( triangle.a, _center ); + _v1$7.subVectors( triangle.b, _center ); + _v2$4.subVectors( triangle.c, _center ); + + // compute edge vectors for triangle + _f0.subVectors( _v1$7, _v0$2 ); + _f1.subVectors( _v2$4, _v1$7 ); + _f2.subVectors( _v0$2, _v2$4 ); + + // test against axes that are given by cross product combinations of the edges of the triangle and the edges of the aabb + // make an axis testing of each of the 3 sides of the aabb against each of the 3 sides of the triangle = 9 axis of separation + // axis_ij = u_i x f_j (u0, u1, u2 = face normals of aabb = x,y,z axes vectors since aabb is axis aligned) + let axes = [ + 0, - _f0.z, _f0.y, 0, - _f1.z, _f1.y, 0, - _f2.z, _f2.y, + _f0.z, 0, - _f0.x, _f1.z, 0, - _f1.x, _f2.z, 0, - _f2.x, + - _f0.y, _f0.x, 0, - _f1.y, _f1.x, 0, - _f2.y, _f2.x, 0 + ]; + if ( ! satForAxes( axes, _v0$2, _v1$7, _v2$4, _extents ) ) { + + return false; + + } + + // test 3 face normals from the aabb + axes = [ 1, 0, 0, 0, 1, 0, 0, 0, 1 ]; + if ( ! satForAxes( axes, _v0$2, _v1$7, _v2$4, _extents ) ) { + + return false; + + } + + // finally testing the face normal of the triangle + // use already existing triangle edge vectors here + _triangleNormal.crossVectors( _f0, _f1 ); + axes = [ _triangleNormal.x, _triangleNormal.y, _triangleNormal.z ]; + + return satForAxes( axes, _v0$2, _v1$7, _v2$4, _extents ); + + } + + clampPoint( point, target ) { + + return target.copy( point ).clamp( this.min, this.max ); + + } + + distanceToPoint( point ) { + + return this.clampPoint( point, _vector$b ).distanceTo( point ); + + } + + getBoundingSphere( target ) { + + if ( this.isEmpty() ) { + + target.makeEmpty(); + + } else { + + this.getCenter( target.center ); + + target.radius = this.getSize( _vector$b ).length() * 0.5; + + } + + return target; + + } + + intersect( box ) { + + this.min.max( box.min ); + this.max.min( box.max ); + + // ensure that if there is no overlap, the result is fully empty, not slightly empty with non-inf/+inf values that will cause subsequence intersects to erroneously return valid values. + if ( this.isEmpty() ) this.makeEmpty(); + + return this; + + } + + union( box ) { + + this.min.min( box.min ); + this.max.max( box.max ); + + return this; + + } + + applyMatrix4( matrix ) { + + // transform of empty box is an empty box. + if ( this.isEmpty() ) return this; + + // NOTE: I am using a binary pattern to specify all 2^3 combinations below + _points[ 0 ].set( this.min.x, this.min.y, this.min.z ).applyMatrix4( matrix ); // 000 + _points[ 1 ].set( this.min.x, this.min.y, this.max.z ).applyMatrix4( matrix ); // 001 + _points[ 2 ].set( this.min.x, this.max.y, this.min.z ).applyMatrix4( matrix ); // 010 + _points[ 3 ].set( this.min.x, this.max.y, this.max.z ).applyMatrix4( matrix ); // 011 + _points[ 4 ].set( this.max.x, this.min.y, this.min.z ).applyMatrix4( matrix ); // 100 + _points[ 5 ].set( this.max.x, this.min.y, this.max.z ).applyMatrix4( matrix ); // 101 + _points[ 6 ].set( this.max.x, this.max.y, this.min.z ).applyMatrix4( matrix ); // 110 + _points[ 7 ].set( this.max.x, this.max.y, this.max.z ).applyMatrix4( matrix ); // 111 + + this.setFromPoints( _points ); + + return this; + + } + + translate( offset ) { + + this.min.add( offset ); + this.max.add( offset ); + + return this; + + } + + equals( box ) { + + return box.min.equals( this.min ) && box.max.equals( this.max ); + + } + +} + +const _points = [ + /*@__PURE__*/ new Vector3(), + /*@__PURE__*/ new Vector3(), + /*@__PURE__*/ new Vector3(), + /*@__PURE__*/ new Vector3(), + /*@__PURE__*/ new Vector3(), + /*@__PURE__*/ new Vector3(), + /*@__PURE__*/ new Vector3(), + /*@__PURE__*/ new Vector3() +]; + +const _vector$b = /*@__PURE__*/ new Vector3(); + +const _box$4 = /*@__PURE__*/ new Box3(); + +// triangle centered vertices + +const _v0$2 = /*@__PURE__*/ new Vector3(); +const _v1$7 = /*@__PURE__*/ new Vector3(); +const _v2$4 = /*@__PURE__*/ new Vector3(); + +// triangle edge vectors + +const _f0 = /*@__PURE__*/ new Vector3(); +const _f1 = /*@__PURE__*/ new Vector3(); +const _f2 = /*@__PURE__*/ new Vector3(); + +const _center = /*@__PURE__*/ new Vector3(); +const _extents = /*@__PURE__*/ new Vector3(); +const _triangleNormal = /*@__PURE__*/ new Vector3(); +const _testAxis = /*@__PURE__*/ new Vector3(); + +function satForAxes( axes, v0, v1, v2, extents ) { + + for ( let i = 0, j = axes.length - 3; i <= j; i += 3 ) { + + _testAxis.fromArray( axes, i ); + // project the aabb onto the separating axis + const r = extents.x * Math.abs( _testAxis.x ) + extents.y * Math.abs( _testAxis.y ) + extents.z * Math.abs( _testAxis.z ); + // project all 3 vertices of the triangle onto the separating axis + const p0 = v0.dot( _testAxis ); + const p1 = v1.dot( _testAxis ); + const p2 = v2.dot( _testAxis ); + // actual test, basically see if either of the most extreme of the triangle points intersects r + if ( Math.max( - Math.max( p0, p1, p2 ), Math.min( p0, p1, p2 ) ) > r ) { + + // points of the projected triangle are outside the projected half-length of the aabb + // the axis is separating and we can exit + return false; + + } + + } + + return true; + +} + +const _box$3 = /*@__PURE__*/ new Box3(); +const _v1$6 = /*@__PURE__*/ new Vector3(); +const _v2$3 = /*@__PURE__*/ new Vector3(); + +class Sphere { + + constructor( center = new Vector3(), radius = - 1 ) { + + this.isSphere = true; + + this.center = center; + this.radius = radius; + + } + + set( center, radius ) { + + this.center.copy( center ); + this.radius = radius; + + return this; + + } + + setFromPoints( points, optionalCenter ) { + + const center = this.center; + + if ( optionalCenter !== undefined ) { + + center.copy( optionalCenter ); + + } else { + + _box$3.setFromPoints( points ).getCenter( center ); + + } + + let maxRadiusSq = 0; + + for ( let i = 0, il = points.length; i < il; i ++ ) { + + maxRadiusSq = Math.max( maxRadiusSq, center.distanceToSquared( points[ i ] ) ); + + } + + this.radius = Math.sqrt( maxRadiusSq ); + + return this; + + } + + copy( sphere ) { + + this.center.copy( sphere.center ); + this.radius = sphere.radius; + + return this; + + } + + isEmpty() { + + return ( this.radius < 0 ); + + } + + makeEmpty() { + + this.center.set( 0, 0, 0 ); + this.radius = - 1; + + return this; + + } + + containsPoint( point ) { + + return ( point.distanceToSquared( this.center ) <= ( this.radius * this.radius ) ); + + } + + distanceToPoint( point ) { + + return ( point.distanceTo( this.center ) - this.radius ); + + } + + intersectsSphere( sphere ) { + + const radiusSum = this.radius + sphere.radius; + + return sphere.center.distanceToSquared( this.center ) <= ( radiusSum * radiusSum ); + + } + + intersectsBox( box ) { + + return box.intersectsSphere( this ); + + } + + intersectsPlane( plane ) { + + return Math.abs( plane.distanceToPoint( this.center ) ) <= this.radius; + + } + + clampPoint( point, target ) { + + const deltaLengthSq = this.center.distanceToSquared( point ); + + target.copy( point ); + + if ( deltaLengthSq > ( this.radius * this.radius ) ) { + + target.sub( this.center ).normalize(); + target.multiplyScalar( this.radius ).add( this.center ); + + } + + return target; + + } + + getBoundingBox( target ) { + + if ( this.isEmpty() ) { + + // Empty sphere produces empty bounding box + target.makeEmpty(); + return target; + + } + + target.set( this.center, this.center ); + target.expandByScalar( this.radius ); + + return target; + + } + + applyMatrix4( matrix ) { + + this.center.applyMatrix4( matrix ); + this.radius = this.radius * matrix.getMaxScaleOnAxis(); + + return this; + + } + + translate( offset ) { + + this.center.add( offset ); + + return this; + + } + + expandByPoint( point ) { + + if ( this.isEmpty() ) { + + this.center.copy( point ); + + this.radius = 0; + + return this; + + } + + _v1$6.subVectors( point, this.center ); + + const lengthSq = _v1$6.lengthSq(); + + if ( lengthSq > ( this.radius * this.radius ) ) { + + // calculate the minimal sphere + + const length = Math.sqrt( lengthSq ); + + const delta = ( length - this.radius ) * 0.5; + + this.center.addScaledVector( _v1$6, delta / length ); + + this.radius += delta; + + } + + return this; + + } + + union( sphere ) { + + if ( sphere.isEmpty() ) { + + return this; + + } + + if ( this.isEmpty() ) { + + this.copy( sphere ); + + return this; + + } + + if ( this.center.equals( sphere.center ) === true ) { + + this.radius = Math.max( this.radius, sphere.radius ); + + } else { + + _v2$3.subVectors( sphere.center, this.center ).setLength( sphere.radius ); + + this.expandByPoint( _v1$6.copy( sphere.center ).add( _v2$3 ) ); + + this.expandByPoint( _v1$6.copy( sphere.center ).sub( _v2$3 ) ); + + } + + return this; + + } + + equals( sphere ) { + + return sphere.center.equals( this.center ) && ( sphere.radius === this.radius ); + + } + + clone() { + + return new this.constructor().copy( this ); + + } + +} + +const _vector$a = /*@__PURE__*/ new Vector3(); +const _segCenter = /*@__PURE__*/ new Vector3(); +const _segDir = /*@__PURE__*/ new Vector3(); +const _diff = /*@__PURE__*/ new Vector3(); + +const _edge1 = /*@__PURE__*/ new Vector3(); +const _edge2 = /*@__PURE__*/ new Vector3(); +const _normal$1 = /*@__PURE__*/ new Vector3(); + +class Ray { + + constructor( origin = new Vector3(), direction = new Vector3( 0, 0, - 1 ) ) { + + this.origin = origin; + this.direction = direction; + + } + + set( origin, direction ) { + + this.origin.copy( origin ); + this.direction.copy( direction ); + + return this; + + } + + copy( ray ) { + + this.origin.copy( ray.origin ); + this.direction.copy( ray.direction ); + + return this; + + } + + at( t, target ) { + + return target.copy( this.origin ).addScaledVector( this.direction, t ); + + } + + lookAt( v ) { + + this.direction.copy( v ).sub( this.origin ).normalize(); + + return this; + + } + + recast( t ) { + + this.origin.copy( this.at( t, _vector$a ) ); + + return this; + + } + + closestPointToPoint( point, target ) { + + target.subVectors( point, this.origin ); + + const directionDistance = target.dot( this.direction ); + + if ( directionDistance < 0 ) { + + return target.copy( this.origin ); + + } + + return target.copy( this.origin ).addScaledVector( this.direction, directionDistance ); + + } + + distanceToPoint( point ) { + + return Math.sqrt( this.distanceSqToPoint( point ) ); + + } + + distanceSqToPoint( point ) { + + const directionDistance = _vector$a.subVectors( point, this.origin ).dot( this.direction ); + + // point behind the ray + + if ( directionDistance < 0 ) { + + return this.origin.distanceToSquared( point ); + + } + + _vector$a.copy( this.origin ).addScaledVector( this.direction, directionDistance ); + + return _vector$a.distanceToSquared( point ); + + } + + distanceSqToSegment( v0, v1, optionalPointOnRay, optionalPointOnSegment ) { + + // from https://github.com/pmjoniak/GeometricTools/blob/master/GTEngine/Include/Mathematics/GteDistRaySegment.h + // It returns the min distance between the ray and the segment + // defined by v0 and v1 + // It can also set two optional targets : + // - The closest point on the ray + // - The closest point on the segment + + _segCenter.copy( v0 ).add( v1 ).multiplyScalar( 0.5 ); + _segDir.copy( v1 ).sub( v0 ).normalize(); + _diff.copy( this.origin ).sub( _segCenter ); + + const segExtent = v0.distanceTo( v1 ) * 0.5; + const a01 = - this.direction.dot( _segDir ); + const b0 = _diff.dot( this.direction ); + const b1 = - _diff.dot( _segDir ); + const c = _diff.lengthSq(); + const det = Math.abs( 1 - a01 * a01 ); + let s0, s1, sqrDist, extDet; + + if ( det > 0 ) { + + // The ray and segment are not parallel. + + s0 = a01 * b1 - b0; + s1 = a01 * b0 - b1; + extDet = segExtent * det; + + if ( s0 >= 0 ) { + + if ( s1 >= - extDet ) { + + if ( s1 <= extDet ) { + + // region 0 + // Minimum at interior points of ray and segment. + + const invDet = 1 / det; + s0 *= invDet; + s1 *= invDet; + sqrDist = s0 * ( s0 + a01 * s1 + 2 * b0 ) + s1 * ( a01 * s0 + s1 + 2 * b1 ) + c; + + } else { + + // region 1 + + s1 = segExtent; + s0 = Math.max( 0, - ( a01 * s1 + b0 ) ); + sqrDist = - s0 * s0 + s1 * ( s1 + 2 * b1 ) + c; + + } + + } else { + + // region 5 + + s1 = - segExtent; + s0 = Math.max( 0, - ( a01 * s1 + b0 ) ); + sqrDist = - s0 * s0 + s1 * ( s1 + 2 * b1 ) + c; + + } + + } else { + + if ( s1 <= - extDet ) { + + // region 4 + + s0 = Math.max( 0, - ( - a01 * segExtent + b0 ) ); + s1 = ( s0 > 0 ) ? - segExtent : Math.min( Math.max( - segExtent, - b1 ), segExtent ); + sqrDist = - s0 * s0 + s1 * ( s1 + 2 * b1 ) + c; + + } else if ( s1 <= extDet ) { + + // region 3 + + s0 = 0; + s1 = Math.min( Math.max( - segExtent, - b1 ), segExtent ); + sqrDist = s1 * ( s1 + 2 * b1 ) + c; + + } else { + + // region 2 + + s0 = Math.max( 0, - ( a01 * segExtent + b0 ) ); + s1 = ( s0 > 0 ) ? segExtent : Math.min( Math.max( - segExtent, - b1 ), segExtent ); + sqrDist = - s0 * s0 + s1 * ( s1 + 2 * b1 ) + c; + + } + + } + + } else { + + // Ray and segment are parallel. + + s1 = ( a01 > 0 ) ? - segExtent : segExtent; + s0 = Math.max( 0, - ( a01 * s1 + b0 ) ); + sqrDist = - s0 * s0 + s1 * ( s1 + 2 * b1 ) + c; + + } + + if ( optionalPointOnRay ) { + + optionalPointOnRay.copy( this.origin ).addScaledVector( this.direction, s0 ); + + } + + if ( optionalPointOnSegment ) { + + optionalPointOnSegment.copy( _segCenter ).addScaledVector( _segDir, s1 ); + + } + + return sqrDist; + + } + + intersectSphere( sphere, target ) { + + _vector$a.subVectors( sphere.center, this.origin ); + const tca = _vector$a.dot( this.direction ); + const d2 = _vector$a.dot( _vector$a ) - tca * tca; + const radius2 = sphere.radius * sphere.radius; + + if ( d2 > radius2 ) return null; + + const thc = Math.sqrt( radius2 - d2 ); + + // t0 = first intersect point - entrance on front of sphere + const t0 = tca - thc; + + // t1 = second intersect point - exit point on back of sphere + const t1 = tca + thc; + + // test to see if t1 is behind the ray - if so, return null + if ( t1 < 0 ) return null; + + // test to see if t0 is behind the ray: + // if it is, the ray is inside the sphere, so return the second exit point scaled by t1, + // in order to always return an intersect point that is in front of the ray. + if ( t0 < 0 ) return this.at( t1, target ); + + // else t0 is in front of the ray, so return the first collision point scaled by t0 + return this.at( t0, target ); + + } + + intersectsSphere( sphere ) { + + return this.distanceSqToPoint( sphere.center ) <= ( sphere.radius * sphere.radius ); + + } + + distanceToPlane( plane ) { + + const denominator = plane.normal.dot( this.direction ); + + if ( denominator === 0 ) { + + // line is coplanar, return origin + if ( plane.distanceToPoint( this.origin ) === 0 ) { + + return 0; + + } + + // Null is preferable to undefined since undefined means.... it is undefined + + return null; + + } + + const t = - ( this.origin.dot( plane.normal ) + plane.constant ) / denominator; + + // Return if the ray never intersects the plane + + return t >= 0 ? t : null; + + } + + intersectPlane( plane, target ) { + + const t = this.distanceToPlane( plane ); + + if ( t === null ) { + + return null; + + } + + return this.at( t, target ); + + } + + intersectsPlane( plane ) { + + // check if the ray lies on the plane first + + const distToPoint = plane.distanceToPoint( this.origin ); + + if ( distToPoint === 0 ) { + + return true; + + } + + const denominator = plane.normal.dot( this.direction ); + + if ( denominator * distToPoint < 0 ) { + + return true; + + } + + // ray origin is behind the plane (and is pointing behind it) + + return false; + + } + + intersectBox( box, target ) { + + let tmin, tmax, tymin, tymax, tzmin, tzmax; + + const invdirx = 1 / this.direction.x, + invdiry = 1 / this.direction.y, + invdirz = 1 / this.direction.z; + + const origin = this.origin; + + if ( invdirx >= 0 ) { + + tmin = ( box.min.x - origin.x ) * invdirx; + tmax = ( box.max.x - origin.x ) * invdirx; + + } else { + + tmin = ( box.max.x - origin.x ) * invdirx; + tmax = ( box.min.x - origin.x ) * invdirx; + + } + + if ( invdiry >= 0 ) { + + tymin = ( box.min.y - origin.y ) * invdiry; + tymax = ( box.max.y - origin.y ) * invdiry; + + } else { + + tymin = ( box.max.y - origin.y ) * invdiry; + tymax = ( box.min.y - origin.y ) * invdiry; + + } + + if ( ( tmin > tymax ) || ( tymin > tmax ) ) return null; + + if ( tymin > tmin || isNaN( tmin ) ) tmin = tymin; + + if ( tymax < tmax || isNaN( tmax ) ) tmax = tymax; + + if ( invdirz >= 0 ) { + + tzmin = ( box.min.z - origin.z ) * invdirz; + tzmax = ( box.max.z - origin.z ) * invdirz; + + } else { + + tzmin = ( box.max.z - origin.z ) * invdirz; + tzmax = ( box.min.z - origin.z ) * invdirz; + + } + + if ( ( tmin > tzmax ) || ( tzmin > tmax ) ) return null; + + if ( tzmin > tmin || tmin !== tmin ) tmin = tzmin; + + if ( tzmax < tmax || tmax !== tmax ) tmax = tzmax; + + //return point closest to the ray (positive side) + + if ( tmax < 0 ) return null; + + return this.at( tmin >= 0 ? tmin : tmax, target ); + + } + + intersectsBox( box ) { + + return this.intersectBox( box, _vector$a ) !== null; + + } + + intersectTriangle( a, b, c, backfaceCulling, target ) { + + // Compute the offset origin, edges, and normal. + + // from https://github.com/pmjoniak/GeometricTools/blob/master/GTEngine/Include/Mathematics/GteIntrRay3Triangle3.h + + _edge1.subVectors( b, a ); + _edge2.subVectors( c, a ); + _normal$1.crossVectors( _edge1, _edge2 ); + + // Solve Q + t*D = b1*E1 + b2*E2 (Q = kDiff, D = ray direction, + // E1 = kEdge1, E2 = kEdge2, N = Cross(E1,E2)) by + // |Dot(D,N)|*b1 = sign(Dot(D,N))*Dot(D,Cross(Q,E2)) + // |Dot(D,N)|*b2 = sign(Dot(D,N))*Dot(D,Cross(E1,Q)) + // |Dot(D,N)|*t = -sign(Dot(D,N))*Dot(Q,N) + let DdN = this.direction.dot( _normal$1 ); + let sign; + + if ( DdN > 0 ) { + + if ( backfaceCulling ) return null; + sign = 1; + + } else if ( DdN < 0 ) { + + sign = - 1; + DdN = - DdN; + + } else { + + return null; + + } + + _diff.subVectors( this.origin, a ); + const DdQxE2 = sign * this.direction.dot( _edge2.crossVectors( _diff, _edge2 ) ); + + // b1 < 0, no intersection + if ( DdQxE2 < 0 ) { + + return null; + + } + + const DdE1xQ = sign * this.direction.dot( _edge1.cross( _diff ) ); + + // b2 < 0, no intersection + if ( DdE1xQ < 0 ) { + + return null; + + } + + // b1+b2 > 1, no intersection + if ( DdQxE2 + DdE1xQ > DdN ) { + + return null; + + } + + // Line intersects triangle, check if ray does. + const QdN = - sign * _diff.dot( _normal$1 ); + + // t < 0, no intersection + if ( QdN < 0 ) { + + return null; + + } + + // Ray intersects triangle. + return this.at( QdN / DdN, target ); + + } + + applyMatrix4( matrix4 ) { + + this.origin.applyMatrix4( matrix4 ); + this.direction.transformDirection( matrix4 ); + + return this; + + } + + equals( ray ) { + + return ray.origin.equals( this.origin ) && ray.direction.equals( this.direction ); + + } + + clone() { + + return new this.constructor().copy( this ); + + } + +} + +class Matrix4 { + + constructor( n11, n12, n13, n14, n21, n22, n23, n24, n31, n32, n33, n34, n41, n42, n43, n44 ) { + + Matrix4.prototype.isMatrix4 = true; + + this.elements = [ + + 1, 0, 0, 0, + 0, 1, 0, 0, + 0, 0, 1, 0, + 0, 0, 0, 1 + + ]; + + if ( n11 !== undefined ) { + + this.set( n11, n12, n13, n14, n21, n22, n23, n24, n31, n32, n33, n34, n41, n42, n43, n44 ); + + } + + } + + set( n11, n12, n13, n14, n21, n22, n23, n24, n31, n32, n33, n34, n41, n42, n43, n44 ) { + + const te = this.elements; + + te[ 0 ] = n11; te[ 4 ] = n12; te[ 8 ] = n13; te[ 12 ] = n14; + te[ 1 ] = n21; te[ 5 ] = n22; te[ 9 ] = n23; te[ 13 ] = n24; + te[ 2 ] = n31; te[ 6 ] = n32; te[ 10 ] = n33; te[ 14 ] = n34; + te[ 3 ] = n41; te[ 7 ] = n42; te[ 11 ] = n43; te[ 15 ] = n44; + + return this; + + } + + identity() { + + this.set( + + 1, 0, 0, 0, + 0, 1, 0, 0, + 0, 0, 1, 0, + 0, 0, 0, 1 + + ); + + return this; + + } + + clone() { + + return new Matrix4().fromArray( this.elements ); + + } + + copy( m ) { + + const te = this.elements; + const me = m.elements; + + te[ 0 ] = me[ 0 ]; te[ 1 ] = me[ 1 ]; te[ 2 ] = me[ 2 ]; te[ 3 ] = me[ 3 ]; + te[ 4 ] = me[ 4 ]; te[ 5 ] = me[ 5 ]; te[ 6 ] = me[ 6 ]; te[ 7 ] = me[ 7 ]; + te[ 8 ] = me[ 8 ]; te[ 9 ] = me[ 9 ]; te[ 10 ] = me[ 10 ]; te[ 11 ] = me[ 11 ]; + te[ 12 ] = me[ 12 ]; te[ 13 ] = me[ 13 ]; te[ 14 ] = me[ 14 ]; te[ 15 ] = me[ 15 ]; + + return this; + + } + + copyPosition( m ) { + + const te = this.elements, me = m.elements; + + te[ 12 ] = me[ 12 ]; + te[ 13 ] = me[ 13 ]; + te[ 14 ] = me[ 14 ]; + + return this; + + } + + setFromMatrix3( m ) { + + const me = m.elements; + + this.set( + + me[ 0 ], me[ 3 ], me[ 6 ], 0, + me[ 1 ], me[ 4 ], me[ 7 ], 0, + me[ 2 ], me[ 5 ], me[ 8 ], 0, + 0, 0, 0, 1 + + ); + + return this; + + } + + extractBasis( xAxis, yAxis, zAxis ) { + + xAxis.setFromMatrixColumn( this, 0 ); + yAxis.setFromMatrixColumn( this, 1 ); + zAxis.setFromMatrixColumn( this, 2 ); + + return this; + + } + + makeBasis( xAxis, yAxis, zAxis ) { + + this.set( + xAxis.x, yAxis.x, zAxis.x, 0, + xAxis.y, yAxis.y, zAxis.y, 0, + xAxis.z, yAxis.z, zAxis.z, 0, + 0, 0, 0, 1 + ); + + return this; + + } + + extractRotation( m ) { + + // this method does not support reflection matrices + + const te = this.elements; + const me = m.elements; + + const scaleX = 1 / _v1$5.setFromMatrixColumn( m, 0 ).length(); + const scaleY = 1 / _v1$5.setFromMatrixColumn( m, 1 ).length(); + const scaleZ = 1 / _v1$5.setFromMatrixColumn( m, 2 ).length(); + + te[ 0 ] = me[ 0 ] * scaleX; + te[ 1 ] = me[ 1 ] * scaleX; + te[ 2 ] = me[ 2 ] * scaleX; + te[ 3 ] = 0; + + te[ 4 ] = me[ 4 ] * scaleY; + te[ 5 ] = me[ 5 ] * scaleY; + te[ 6 ] = me[ 6 ] * scaleY; + te[ 7 ] = 0; + + te[ 8 ] = me[ 8 ] * scaleZ; + te[ 9 ] = me[ 9 ] * scaleZ; + te[ 10 ] = me[ 10 ] * scaleZ; + te[ 11 ] = 0; + + te[ 12 ] = 0; + te[ 13 ] = 0; + te[ 14 ] = 0; + te[ 15 ] = 1; + + return this; + + } + + makeRotationFromEuler( euler ) { + + const te = this.elements; + + const x = euler.x, y = euler.y, z = euler.z; + const a = Math.cos( x ), b = Math.sin( x ); + const c = Math.cos( y ), d = Math.sin( y ); + const e = Math.cos( z ), f = Math.sin( z ); + + if ( euler.order === 'XYZ' ) { + + const ae = a * e, af = a * f, be = b * e, bf = b * f; + + te[ 0 ] = c * e; + te[ 4 ] = - c * f; + te[ 8 ] = d; + + te[ 1 ] = af + be * d; + te[ 5 ] = ae - bf * d; + te[ 9 ] = - b * c; + + te[ 2 ] = bf - ae * d; + te[ 6 ] = be + af * d; + te[ 10 ] = a * c; + + } else if ( euler.order === 'YXZ' ) { + + const ce = c * e, cf = c * f, de = d * e, df = d * f; + + te[ 0 ] = ce + df * b; + te[ 4 ] = de * b - cf; + te[ 8 ] = a * d; + + te[ 1 ] = a * f; + te[ 5 ] = a * e; + te[ 9 ] = - b; + + te[ 2 ] = cf * b - de; + te[ 6 ] = df + ce * b; + te[ 10 ] = a * c; + + } else if ( euler.order === 'ZXY' ) { + + const ce = c * e, cf = c * f, de = d * e, df = d * f; + + te[ 0 ] = ce - df * b; + te[ 4 ] = - a * f; + te[ 8 ] = de + cf * b; + + te[ 1 ] = cf + de * b; + te[ 5 ] = a * e; + te[ 9 ] = df - ce * b; + + te[ 2 ] = - a * d; + te[ 6 ] = b; + te[ 10 ] = a * c; + + } else if ( euler.order === 'ZYX' ) { + + const ae = a * e, af = a * f, be = b * e, bf = b * f; + + te[ 0 ] = c * e; + te[ 4 ] = be * d - af; + te[ 8 ] = ae * d + bf; + + te[ 1 ] = c * f; + te[ 5 ] = bf * d + ae; + te[ 9 ] = af * d - be; + + te[ 2 ] = - d; + te[ 6 ] = b * c; + te[ 10 ] = a * c; + + } else if ( euler.order === 'YZX' ) { + + const ac = a * c, ad = a * d, bc = b * c, bd = b * d; + + te[ 0 ] = c * e; + te[ 4 ] = bd - ac * f; + te[ 8 ] = bc * f + ad; + + te[ 1 ] = f; + te[ 5 ] = a * e; + te[ 9 ] = - b * e; + + te[ 2 ] = - d * e; + te[ 6 ] = ad * f + bc; + te[ 10 ] = ac - bd * f; + + } else if ( euler.order === 'XZY' ) { + + const ac = a * c, ad = a * d, bc = b * c, bd = b * d; + + te[ 0 ] = c * e; + te[ 4 ] = - f; + te[ 8 ] = d * e; + + te[ 1 ] = ac * f + bd; + te[ 5 ] = a * e; + te[ 9 ] = ad * f - bc; + + te[ 2 ] = bc * f - ad; + te[ 6 ] = b * e; + te[ 10 ] = bd * f + ac; + + } + + // bottom row + te[ 3 ] = 0; + te[ 7 ] = 0; + te[ 11 ] = 0; + + // last column + te[ 12 ] = 0; + te[ 13 ] = 0; + te[ 14 ] = 0; + te[ 15 ] = 1; + + return this; + + } + + makeRotationFromQuaternion( q ) { + + return this.compose( _zero, q, _one ); + + } + + lookAt( eye, target, up ) { + + const te = this.elements; + + _z.subVectors( eye, target ); + + if ( _z.lengthSq() === 0 ) { + + // eye and target are in the same position + + _z.z = 1; + + } + + _z.normalize(); + _x.crossVectors( up, _z ); + + if ( _x.lengthSq() === 0 ) { + + // up and z are parallel + + if ( Math.abs( up.z ) === 1 ) { + + _z.x += 0.0001; + + } else { + + _z.z += 0.0001; + + } + + _z.normalize(); + _x.crossVectors( up, _z ); + + } + + _x.normalize(); + _y.crossVectors( _z, _x ); + + te[ 0 ] = _x.x; te[ 4 ] = _y.x; te[ 8 ] = _z.x; + te[ 1 ] = _x.y; te[ 5 ] = _y.y; te[ 9 ] = _z.y; + te[ 2 ] = _x.z; te[ 6 ] = _y.z; te[ 10 ] = _z.z; + + return this; + + } + + multiply( m ) { + + return this.multiplyMatrices( this, m ); + + } + + premultiply( m ) { + + return this.multiplyMatrices( m, this ); + + } + + multiplyMatrices( a, b ) { + + const ae = a.elements; + const be = b.elements; + const te = this.elements; + + const a11 = ae[ 0 ], a12 = ae[ 4 ], a13 = ae[ 8 ], a14 = ae[ 12 ]; + const a21 = ae[ 1 ], a22 = ae[ 5 ], a23 = ae[ 9 ], a24 = ae[ 13 ]; + const a31 = ae[ 2 ], a32 = ae[ 6 ], a33 = ae[ 10 ], a34 = ae[ 14 ]; + const a41 = ae[ 3 ], a42 = ae[ 7 ], a43 = ae[ 11 ], a44 = ae[ 15 ]; + + const b11 = be[ 0 ], b12 = be[ 4 ], b13 = be[ 8 ], b14 = be[ 12 ]; + const b21 = be[ 1 ], b22 = be[ 5 ], b23 = be[ 9 ], b24 = be[ 13 ]; + const b31 = be[ 2 ], b32 = be[ 6 ], b33 = be[ 10 ], b34 = be[ 14 ]; + const b41 = be[ 3 ], b42 = be[ 7 ], b43 = be[ 11 ], b44 = be[ 15 ]; + + te[ 0 ] = a11 * b11 + a12 * b21 + a13 * b31 + a14 * b41; + te[ 4 ] = a11 * b12 + a12 * b22 + a13 * b32 + a14 * b42; + te[ 8 ] = a11 * b13 + a12 * b23 + a13 * b33 + a14 * b43; + te[ 12 ] = a11 * b14 + a12 * b24 + a13 * b34 + a14 * b44; + + te[ 1 ] = a21 * b11 + a22 * b21 + a23 * b31 + a24 * b41; + te[ 5 ] = a21 * b12 + a22 * b22 + a23 * b32 + a24 * b42; + te[ 9 ] = a21 * b13 + a22 * b23 + a23 * b33 + a24 * b43; + te[ 13 ] = a21 * b14 + a22 * b24 + a23 * b34 + a24 * b44; + + te[ 2 ] = a31 * b11 + a32 * b21 + a33 * b31 + a34 * b41; + te[ 6 ] = a31 * b12 + a32 * b22 + a33 * b32 + a34 * b42; + te[ 10 ] = a31 * b13 + a32 * b23 + a33 * b33 + a34 * b43; + te[ 14 ] = a31 * b14 + a32 * b24 + a33 * b34 + a34 * b44; + + te[ 3 ] = a41 * b11 + a42 * b21 + a43 * b31 + a44 * b41; + te[ 7 ] = a41 * b12 + a42 * b22 + a43 * b32 + a44 * b42; + te[ 11 ] = a41 * b13 + a42 * b23 + a43 * b33 + a44 * b43; + te[ 15 ] = a41 * b14 + a42 * b24 + a43 * b34 + a44 * b44; + + return this; + + } + + multiplyScalar( s ) { + + const te = this.elements; + + te[ 0 ] *= s; te[ 4 ] *= s; te[ 8 ] *= s; te[ 12 ] *= s; + te[ 1 ] *= s; te[ 5 ] *= s; te[ 9 ] *= s; te[ 13 ] *= s; + te[ 2 ] *= s; te[ 6 ] *= s; te[ 10 ] *= s; te[ 14 ] *= s; + te[ 3 ] *= s; te[ 7 ] *= s; te[ 11 ] *= s; te[ 15 ] *= s; + + return this; + + } + + determinant() { + + const te = this.elements; + + const n11 = te[ 0 ], n12 = te[ 4 ], n13 = te[ 8 ], n14 = te[ 12 ]; + const n21 = te[ 1 ], n22 = te[ 5 ], n23 = te[ 9 ], n24 = te[ 13 ]; + const n31 = te[ 2 ], n32 = te[ 6 ], n33 = te[ 10 ], n34 = te[ 14 ]; + const n41 = te[ 3 ], n42 = te[ 7 ], n43 = te[ 11 ], n44 = te[ 15 ]; + + //TODO: make this more efficient + //( based on http://www.euclideanspace.com/maths/algebra/matrix/functions/inverse/fourD/index.htm ) + + return ( + n41 * ( + + n14 * n23 * n32 + - n13 * n24 * n32 + - n14 * n22 * n33 + + n12 * n24 * n33 + + n13 * n22 * n34 + - n12 * n23 * n34 + ) + + n42 * ( + + n11 * n23 * n34 + - n11 * n24 * n33 + + n14 * n21 * n33 + - n13 * n21 * n34 + + n13 * n24 * n31 + - n14 * n23 * n31 + ) + + n43 * ( + + n11 * n24 * n32 + - n11 * n22 * n34 + - n14 * n21 * n32 + + n12 * n21 * n34 + + n14 * n22 * n31 + - n12 * n24 * n31 + ) + + n44 * ( + - n13 * n22 * n31 + - n11 * n23 * n32 + + n11 * n22 * n33 + + n13 * n21 * n32 + - n12 * n21 * n33 + + n12 * n23 * n31 + ) + + ); + + } + + transpose() { + + const te = this.elements; + let tmp; + + tmp = te[ 1 ]; te[ 1 ] = te[ 4 ]; te[ 4 ] = tmp; + tmp = te[ 2 ]; te[ 2 ] = te[ 8 ]; te[ 8 ] = tmp; + tmp = te[ 6 ]; te[ 6 ] = te[ 9 ]; te[ 9 ] = tmp; + + tmp = te[ 3 ]; te[ 3 ] = te[ 12 ]; te[ 12 ] = tmp; + tmp = te[ 7 ]; te[ 7 ] = te[ 13 ]; te[ 13 ] = tmp; + tmp = te[ 11 ]; te[ 11 ] = te[ 14 ]; te[ 14 ] = tmp; + + return this; + + } + + setPosition( x, y, z ) { + + const te = this.elements; + + if ( x.isVector3 ) { + + te[ 12 ] = x.x; + te[ 13 ] = x.y; + te[ 14 ] = x.z; + + } else { + + te[ 12 ] = x; + te[ 13 ] = y; + te[ 14 ] = z; + + } + + return this; + + } + + invert() { + + // based on http://www.euclideanspace.com/maths/algebra/matrix/functions/inverse/fourD/index.htm + const te = this.elements, + + n11 = te[ 0 ], n21 = te[ 1 ], n31 = te[ 2 ], n41 = te[ 3 ], + n12 = te[ 4 ], n22 = te[ 5 ], n32 = te[ 6 ], n42 = te[ 7 ], + n13 = te[ 8 ], n23 = te[ 9 ], n33 = te[ 10 ], n43 = te[ 11 ], + n14 = te[ 12 ], n24 = te[ 13 ], n34 = te[ 14 ], n44 = te[ 15 ], + + t11 = n23 * n34 * n42 - n24 * n33 * n42 + n24 * n32 * n43 - n22 * n34 * n43 - n23 * n32 * n44 + n22 * n33 * n44, + t12 = n14 * n33 * n42 - n13 * n34 * n42 - n14 * n32 * n43 + n12 * n34 * n43 + n13 * n32 * n44 - n12 * n33 * n44, + t13 = n13 * n24 * n42 - n14 * n23 * n42 + n14 * n22 * n43 - n12 * n24 * n43 - n13 * n22 * n44 + n12 * n23 * n44, + t14 = n14 * n23 * n32 - n13 * n24 * n32 - n14 * n22 * n33 + n12 * n24 * n33 + n13 * n22 * n34 - n12 * n23 * n34; + + const det = n11 * t11 + n21 * t12 + n31 * t13 + n41 * t14; + + if ( det === 0 ) return this.set( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ); + + const detInv = 1 / det; + + te[ 0 ] = t11 * detInv; + te[ 1 ] = ( n24 * n33 * n41 - n23 * n34 * n41 - n24 * n31 * n43 + n21 * n34 * n43 + n23 * n31 * n44 - n21 * n33 * n44 ) * detInv; + te[ 2 ] = ( n22 * n34 * n41 - n24 * n32 * n41 + n24 * n31 * n42 - n21 * n34 * n42 - n22 * n31 * n44 + n21 * n32 * n44 ) * detInv; + te[ 3 ] = ( n23 * n32 * n41 - n22 * n33 * n41 - n23 * n31 * n42 + n21 * n33 * n42 + n22 * n31 * n43 - n21 * n32 * n43 ) * detInv; + + te[ 4 ] = t12 * detInv; + te[ 5 ] = ( n13 * n34 * n41 - n14 * n33 * n41 + n14 * n31 * n43 - n11 * n34 * n43 - n13 * n31 * n44 + n11 * n33 * n44 ) * detInv; + te[ 6 ] = ( n14 * n32 * n41 - n12 * n34 * n41 - n14 * n31 * n42 + n11 * n34 * n42 + n12 * n31 * n44 - n11 * n32 * n44 ) * detInv; + te[ 7 ] = ( n12 * n33 * n41 - n13 * n32 * n41 + n13 * n31 * n42 - n11 * n33 * n42 - n12 * n31 * n43 + n11 * n32 * n43 ) * detInv; + + te[ 8 ] = t13 * detInv; + te[ 9 ] = ( n14 * n23 * n41 - n13 * n24 * n41 - n14 * n21 * n43 + n11 * n24 * n43 + n13 * n21 * n44 - n11 * n23 * n44 ) * detInv; + te[ 10 ] = ( n12 * n24 * n41 - n14 * n22 * n41 + n14 * n21 * n42 - n11 * n24 * n42 - n12 * n21 * n44 + n11 * n22 * n44 ) * detInv; + te[ 11 ] = ( n13 * n22 * n41 - n12 * n23 * n41 - n13 * n21 * n42 + n11 * n23 * n42 + n12 * n21 * n43 - n11 * n22 * n43 ) * detInv; + + te[ 12 ] = t14 * detInv; + te[ 13 ] = ( n13 * n24 * n31 - n14 * n23 * n31 + n14 * n21 * n33 - n11 * n24 * n33 - n13 * n21 * n34 + n11 * n23 * n34 ) * detInv; + te[ 14 ] = ( n14 * n22 * n31 - n12 * n24 * n31 - n14 * n21 * n32 + n11 * n24 * n32 + n12 * n21 * n34 - n11 * n22 * n34 ) * detInv; + te[ 15 ] = ( n12 * n23 * n31 - n13 * n22 * n31 + n13 * n21 * n32 - n11 * n23 * n32 - n12 * n21 * n33 + n11 * n22 * n33 ) * detInv; + + return this; + + } + + scale( v ) { + + const te = this.elements; + const x = v.x, y = v.y, z = v.z; + + te[ 0 ] *= x; te[ 4 ] *= y; te[ 8 ] *= z; + te[ 1 ] *= x; te[ 5 ] *= y; te[ 9 ] *= z; + te[ 2 ] *= x; te[ 6 ] *= y; te[ 10 ] *= z; + te[ 3 ] *= x; te[ 7 ] *= y; te[ 11 ] *= z; + + return this; + + } + + getMaxScaleOnAxis() { + + const te = this.elements; + + const scaleXSq = te[ 0 ] * te[ 0 ] + te[ 1 ] * te[ 1 ] + te[ 2 ] * te[ 2 ]; + const scaleYSq = te[ 4 ] * te[ 4 ] + te[ 5 ] * te[ 5 ] + te[ 6 ] * te[ 6 ]; + const scaleZSq = te[ 8 ] * te[ 8 ] + te[ 9 ] * te[ 9 ] + te[ 10 ] * te[ 10 ]; + + return Math.sqrt( Math.max( scaleXSq, scaleYSq, scaleZSq ) ); + + } + + makeTranslation( x, y, z ) { + + if ( x.isVector3 ) { + + this.set( + + 1, 0, 0, x.x, + 0, 1, 0, x.y, + 0, 0, 1, x.z, + 0, 0, 0, 1 + + ); + + } else { + + this.set( + + 1, 0, 0, x, + 0, 1, 0, y, + 0, 0, 1, z, + 0, 0, 0, 1 + + ); + + } + + return this; + + } + + makeRotationX( theta ) { + + const c = Math.cos( theta ), s = Math.sin( theta ); + + this.set( + + 1, 0, 0, 0, + 0, c, - s, 0, + 0, s, c, 0, + 0, 0, 0, 1 + + ); + + return this; + + } + + makeRotationY( theta ) { + + const c = Math.cos( theta ), s = Math.sin( theta ); + + this.set( + + c, 0, s, 0, + 0, 1, 0, 0, + - s, 0, c, 0, + 0, 0, 0, 1 + + ); + + return this; + + } + + makeRotationZ( theta ) { + + const c = Math.cos( theta ), s = Math.sin( theta ); + + this.set( + + c, - s, 0, 0, + s, c, 0, 0, + 0, 0, 1, 0, + 0, 0, 0, 1 + + ); + + return this; + + } + + makeRotationAxis( axis, angle ) { + + // Based on http://www.gamedev.net/reference/articles/article1199.asp + + const c = Math.cos( angle ); + const s = Math.sin( angle ); + const t = 1 - c; + const x = axis.x, y = axis.y, z = axis.z; + const tx = t * x, ty = t * y; + + this.set( + + tx * x + c, tx * y - s * z, tx * z + s * y, 0, + tx * y + s * z, ty * y + c, ty * z - s * x, 0, + tx * z - s * y, ty * z + s * x, t * z * z + c, 0, + 0, 0, 0, 1 + + ); + + return this; + + } + + makeScale( x, y, z ) { + + this.set( + + x, 0, 0, 0, + 0, y, 0, 0, + 0, 0, z, 0, + 0, 0, 0, 1 + + ); + + return this; + + } + + makeShear( xy, xz, yx, yz, zx, zy ) { + + this.set( + + 1, yx, zx, 0, + xy, 1, zy, 0, + xz, yz, 1, 0, + 0, 0, 0, 1 + + ); + + return this; + + } + + compose( position, quaternion, scale ) { + + const te = this.elements; + + const x = quaternion._x, y = quaternion._y, z = quaternion._z, w = quaternion._w; + const x2 = x + x, y2 = y + y, z2 = z + z; + const xx = x * x2, xy = x * y2, xz = x * z2; + const yy = y * y2, yz = y * z2, zz = z * z2; + const wx = w * x2, wy = w * y2, wz = w * z2; + + const sx = scale.x, sy = scale.y, sz = scale.z; + + te[ 0 ] = ( 1 - ( yy + zz ) ) * sx; + te[ 1 ] = ( xy + wz ) * sx; + te[ 2 ] = ( xz - wy ) * sx; + te[ 3 ] = 0; + + te[ 4 ] = ( xy - wz ) * sy; + te[ 5 ] = ( 1 - ( xx + zz ) ) * sy; + te[ 6 ] = ( yz + wx ) * sy; + te[ 7 ] = 0; + + te[ 8 ] = ( xz + wy ) * sz; + te[ 9 ] = ( yz - wx ) * sz; + te[ 10 ] = ( 1 - ( xx + yy ) ) * sz; + te[ 11 ] = 0; + + te[ 12 ] = position.x; + te[ 13 ] = position.y; + te[ 14 ] = position.z; + te[ 15 ] = 1; + + return this; + + } + + decompose( position, quaternion, scale ) { + + const te = this.elements; + + let sx = _v1$5.set( te[ 0 ], te[ 1 ], te[ 2 ] ).length(); + const sy = _v1$5.set( te[ 4 ], te[ 5 ], te[ 6 ] ).length(); + const sz = _v1$5.set( te[ 8 ], te[ 9 ], te[ 10 ] ).length(); + + // if determine is negative, we need to invert one scale + const det = this.determinant(); + if ( det < 0 ) sx = - sx; + + position.x = te[ 12 ]; + position.y = te[ 13 ]; + position.z = te[ 14 ]; + + // scale the rotation part + _m1$4.copy( this ); + + const invSX = 1 / sx; + const invSY = 1 / sy; + const invSZ = 1 / sz; + + _m1$4.elements[ 0 ] *= invSX; + _m1$4.elements[ 1 ] *= invSX; + _m1$4.elements[ 2 ] *= invSX; + + _m1$4.elements[ 4 ] *= invSY; + _m1$4.elements[ 5 ] *= invSY; + _m1$4.elements[ 6 ] *= invSY; + + _m1$4.elements[ 8 ] *= invSZ; + _m1$4.elements[ 9 ] *= invSZ; + _m1$4.elements[ 10 ] *= invSZ; + + quaternion.setFromRotationMatrix( _m1$4 ); + + scale.x = sx; + scale.y = sy; + scale.z = sz; + + return this; + + } + + makePerspective( left, right, top, bottom, near, far, coordinateSystem = WebGLCoordinateSystem ) { + + const te = this.elements; + const x = 2 * near / ( right - left ); + const y = 2 * near / ( top - bottom ); + + const a = ( right + left ) / ( right - left ); + const b = ( top + bottom ) / ( top - bottom ); + + let c, d; + + if ( coordinateSystem === WebGLCoordinateSystem ) { + + c = - ( far + near ) / ( far - near ); + d = ( - 2 * far * near ) / ( far - near ); + + } else if ( coordinateSystem === WebGPUCoordinateSystem ) { + + c = - far / ( far - near ); + d = ( - far * near ) / ( far - near ); + + } else { + + throw new Error( 'THREE.Matrix4.makePerspective(): Invalid coordinate system: ' + coordinateSystem ); + + } + + te[ 0 ] = x; te[ 4 ] = 0; te[ 8 ] = a; te[ 12 ] = 0; + te[ 1 ] = 0; te[ 5 ] = y; te[ 9 ] = b; te[ 13 ] = 0; + te[ 2 ] = 0; te[ 6 ] = 0; te[ 10 ] = c; te[ 14 ] = d; + te[ 3 ] = 0; te[ 7 ] = 0; te[ 11 ] = - 1; te[ 15 ] = 0; + + return this; + + } + + makeOrthographic( left, right, top, bottom, near, far, coordinateSystem = WebGLCoordinateSystem ) { + + const te = this.elements; + const w = 1.0 / ( right - left ); + const h = 1.0 / ( top - bottom ); + const p = 1.0 / ( far - near ); + + const x = ( right + left ) * w; + const y = ( top + bottom ) * h; + + let z, zInv; + + if ( coordinateSystem === WebGLCoordinateSystem ) { + + z = ( far + near ) * p; + zInv = - 2 * p; + + } else if ( coordinateSystem === WebGPUCoordinateSystem ) { + + z = near * p; + zInv = - 1 * p; + + } else { + + throw new Error( 'THREE.Matrix4.makeOrthographic(): Invalid coordinate system: ' + coordinateSystem ); + + } + + te[ 0 ] = 2 * w; te[ 4 ] = 0; te[ 8 ] = 0; te[ 12 ] = - x; + te[ 1 ] = 0; te[ 5 ] = 2 * h; te[ 9 ] = 0; te[ 13 ] = - y; + te[ 2 ] = 0; te[ 6 ] = 0; te[ 10 ] = zInv; te[ 14 ] = - z; + te[ 3 ] = 0; te[ 7 ] = 0; te[ 11 ] = 0; te[ 15 ] = 1; + + return this; + + } + + equals( matrix ) { + + const te = this.elements; + const me = matrix.elements; + + for ( let i = 0; i < 16; i ++ ) { + + if ( te[ i ] !== me[ i ] ) return false; + + } + + return true; + + } + + fromArray( array, offset = 0 ) { + + for ( let i = 0; i < 16; i ++ ) { + + this.elements[ i ] = array[ i + offset ]; + + } + + return this; + + } + + toArray( array = [], offset = 0 ) { + + const te = this.elements; + + array[ offset ] = te[ 0 ]; + array[ offset + 1 ] = te[ 1 ]; + array[ offset + 2 ] = te[ 2 ]; + array[ offset + 3 ] = te[ 3 ]; + + array[ offset + 4 ] = te[ 4 ]; + array[ offset + 5 ] = te[ 5 ]; + array[ offset + 6 ] = te[ 6 ]; + array[ offset + 7 ] = te[ 7 ]; + + array[ offset + 8 ] = te[ 8 ]; + array[ offset + 9 ] = te[ 9 ]; + array[ offset + 10 ] = te[ 10 ]; + array[ offset + 11 ] = te[ 11 ]; + + array[ offset + 12 ] = te[ 12 ]; + array[ offset + 13 ] = te[ 13 ]; + array[ offset + 14 ] = te[ 14 ]; + array[ offset + 15 ] = te[ 15 ]; + + return array; + + } + +} + +const _v1$5 = /*@__PURE__*/ new Vector3(); +const _m1$4 = /*@__PURE__*/ new Matrix4(); +const _zero = /*@__PURE__*/ new Vector3( 0, 0, 0 ); +const _one = /*@__PURE__*/ new Vector3( 1, 1, 1 ); +const _x = /*@__PURE__*/ new Vector3(); +const _y = /*@__PURE__*/ new Vector3(); +const _z = /*@__PURE__*/ new Vector3(); + +const _matrix$2 = /*@__PURE__*/ new Matrix4(); +const _quaternion$3 = /*@__PURE__*/ new Quaternion(); + +class Euler { + + constructor( x = 0, y = 0, z = 0, order = Euler.DEFAULT_ORDER ) { + + this.isEuler = true; + + this._x = x; + this._y = y; + this._z = z; + this._order = order; + + } + + get x() { + + return this._x; + + } + + set x( value ) { + + this._x = value; + this._onChangeCallback(); + + } + + get y() { + + return this._y; + + } + + set y( value ) { + + this._y = value; + this._onChangeCallback(); + + } + + get z() { + + return this._z; + + } + + set z( value ) { + + this._z = value; + this._onChangeCallback(); + + } + + get order() { + + return this._order; + + } + + set order( value ) { + + this._order = value; + this._onChangeCallback(); + + } + + set( x, y, z, order = this._order ) { + + this._x = x; + this._y = y; + this._z = z; + this._order = order; + + this._onChangeCallback(); + + return this; + + } + + clone() { + + return new this.constructor( this._x, this._y, this._z, this._order ); + + } + + copy( euler ) { + + this._x = euler._x; + this._y = euler._y; + this._z = euler._z; + this._order = euler._order; + + this._onChangeCallback(); + + return this; + + } + + setFromRotationMatrix( m, order = this._order, update = true ) { + + // assumes the upper 3x3 of m is a pure rotation matrix (i.e, unscaled) + + const te = m.elements; + const m11 = te[ 0 ], m12 = te[ 4 ], m13 = te[ 8 ]; + const m21 = te[ 1 ], m22 = te[ 5 ], m23 = te[ 9 ]; + const m31 = te[ 2 ], m32 = te[ 6 ], m33 = te[ 10 ]; + + switch ( order ) { + + case 'XYZ': + + this._y = Math.asin( clamp( m13, - 1, 1 ) ); + + if ( Math.abs( m13 ) < 0.9999999 ) { + + this._x = Math.atan2( - m23, m33 ); + this._z = Math.atan2( - m12, m11 ); + + } else { + + this._x = Math.atan2( m32, m22 ); + this._z = 0; + + } + + break; + + case 'YXZ': + + this._x = Math.asin( - clamp( m23, - 1, 1 ) ); + + if ( Math.abs( m23 ) < 0.9999999 ) { + + this._y = Math.atan2( m13, m33 ); + this._z = Math.atan2( m21, m22 ); + + } else { + + this._y = Math.atan2( - m31, m11 ); + this._z = 0; + + } + + break; + + case 'ZXY': + + this._x = Math.asin( clamp( m32, - 1, 1 ) ); + + if ( Math.abs( m32 ) < 0.9999999 ) { + + this._y = Math.atan2( - m31, m33 ); + this._z = Math.atan2( - m12, m22 ); + + } else { + + this._y = 0; + this._z = Math.atan2( m21, m11 ); + + } + + break; + + case 'ZYX': + + this._y = Math.asin( - clamp( m31, - 1, 1 ) ); + + if ( Math.abs( m31 ) < 0.9999999 ) { + + this._x = Math.atan2( m32, m33 ); + this._z = Math.atan2( m21, m11 ); + + } else { + + this._x = 0; + this._z = Math.atan2( - m12, m22 ); + + } + + break; + + case 'YZX': + + this._z = Math.asin( clamp( m21, - 1, 1 ) ); + + if ( Math.abs( m21 ) < 0.9999999 ) { + + this._x = Math.atan2( - m23, m22 ); + this._y = Math.atan2( - m31, m11 ); + + } else { + + this._x = 0; + this._y = Math.atan2( m13, m33 ); + + } + + break; + + case 'XZY': + + this._z = Math.asin( - clamp( m12, - 1, 1 ) ); + + if ( Math.abs( m12 ) < 0.9999999 ) { + + this._x = Math.atan2( m32, m22 ); + this._y = Math.atan2( m13, m11 ); + + } else { + + this._x = Math.atan2( - m23, m33 ); + this._y = 0; + + } + + break; + + default: + + console.warn( 'THREE.Euler: .setFromRotationMatrix() encountered an unknown order: ' + order ); + + } + + this._order = order; + + if ( update === true ) this._onChangeCallback(); + + return this; + + } + + setFromQuaternion( q, order, update ) { + + _matrix$2.makeRotationFromQuaternion( q ); + + return this.setFromRotationMatrix( _matrix$2, order, update ); + + } + + setFromVector3( v, order = this._order ) { + + return this.set( v.x, v.y, v.z, order ); + + } + + reorder( newOrder ) { + + // WARNING: this discards revolution information -bhouston + + _quaternion$3.setFromEuler( this ); + + return this.setFromQuaternion( _quaternion$3, newOrder ); + + } + + equals( euler ) { + + return ( euler._x === this._x ) && ( euler._y === this._y ) && ( euler._z === this._z ) && ( euler._order === this._order ); + + } + + fromArray( array ) { + + this._x = array[ 0 ]; + this._y = array[ 1 ]; + this._z = array[ 2 ]; + if ( array[ 3 ] !== undefined ) this._order = array[ 3 ]; + + this._onChangeCallback(); + + return this; + + } + + toArray( array = [], offset = 0 ) { + + array[ offset ] = this._x; + array[ offset + 1 ] = this._y; + array[ offset + 2 ] = this._z; + array[ offset + 3 ] = this._order; + + return array; + + } + + _onChange( callback ) { + + this._onChangeCallback = callback; + + return this; + + } + + _onChangeCallback() {} + + *[ Symbol.iterator ]() { + + yield this._x; + yield this._y; + yield this._z; + yield this._order; + + } + +} + +Euler.DEFAULT_ORDER = 'XYZ'; + +class Layers { + + constructor() { + + this.mask = 1 | 0; + + } + + set( channel ) { + + this.mask = ( 1 << channel | 0 ) >>> 0; + + } + + enable( channel ) { + + this.mask |= 1 << channel | 0; + + } + + enableAll() { + + this.mask = 0xffffffff | 0; + + } + + toggle( channel ) { + + this.mask ^= 1 << channel | 0; + + } + + disable( channel ) { + + this.mask &= ~ ( 1 << channel | 0 ); + + } + + disableAll() { + + this.mask = 0; + + } + + test( layers ) { + + return ( this.mask & layers.mask ) !== 0; + + } + + isEnabled( channel ) { + + return ( this.mask & ( 1 << channel | 0 ) ) !== 0; + + } + +} + +let _object3DId = 0; + +const _v1$4 = /*@__PURE__*/ new Vector3(); +const _q1 = /*@__PURE__*/ new Quaternion(); +const _m1$3 = /*@__PURE__*/ new Matrix4(); +const _target = /*@__PURE__*/ new Vector3(); + +const _position$3 = /*@__PURE__*/ new Vector3(); +const _scale$2 = /*@__PURE__*/ new Vector3(); +const _quaternion$2 = /*@__PURE__*/ new Quaternion(); + +const _xAxis = /*@__PURE__*/ new Vector3( 1, 0, 0 ); +const _yAxis = /*@__PURE__*/ new Vector3( 0, 1, 0 ); +const _zAxis = /*@__PURE__*/ new Vector3( 0, 0, 1 ); + +const _addedEvent = { type: 'added' }; +const _removedEvent = { type: 'removed' }; + +const _childaddedEvent = { type: 'childadded', child: null }; +const _childremovedEvent = { type: 'childremoved', child: null }; + +class Object3D extends EventDispatcher { + + constructor() { + + super(); + + this.isObject3D = true; + + Object.defineProperty( this, 'id', { value: _object3DId ++ } ); + + this.uuid = generateUUID(); + + this.name = ''; + this.type = 'Object3D'; + + this.parent = null; + this.children = []; + + this.up = Object3D.DEFAULT_UP.clone(); + + const position = new Vector3(); + const rotation = new Euler(); + const quaternion = new Quaternion(); + const scale = new Vector3( 1, 1, 1 ); + + function onRotationChange() { + + quaternion.setFromEuler( rotation, false ); + + } + + function onQuaternionChange() { + + rotation.setFromQuaternion( quaternion, undefined, false ); + + } + + rotation._onChange( onRotationChange ); + quaternion._onChange( onQuaternionChange ); + + Object.defineProperties( this, { + position: { + configurable: true, + enumerable: true, + value: position + }, + rotation: { + configurable: true, + enumerable: true, + value: rotation + }, + quaternion: { + configurable: true, + enumerable: true, + value: quaternion + }, + scale: { + configurable: true, + enumerable: true, + value: scale + }, + modelViewMatrix: { + value: new Matrix4() + }, + normalMatrix: { + value: new Matrix3() + } + } ); + + this.matrix = new Matrix4(); + this.matrixWorld = new Matrix4(); + + this.matrixAutoUpdate = Object3D.DEFAULT_MATRIX_AUTO_UPDATE; + + this.matrixWorldAutoUpdate = Object3D.DEFAULT_MATRIX_WORLD_AUTO_UPDATE; // checked by the renderer + this.matrixWorldNeedsUpdate = false; + + this.layers = new Layers(); + this.visible = true; + + this.castShadow = false; + this.receiveShadow = false; + + this.frustumCulled = true; + this.renderOrder = 0; + + this.animations = []; + + this.userData = {}; + + } + + onBeforeShadow( /* renderer, object, camera, shadowCamera, geometry, depthMaterial, group */ ) {} + + onAfterShadow( /* renderer, object, camera, shadowCamera, geometry, depthMaterial, group */ ) {} + + onBeforeRender( /* renderer, scene, camera, geometry, material, group */ ) {} + + onAfterRender( /* renderer, scene, camera, geometry, material, group */ ) {} + + applyMatrix4( matrix ) { + + if ( this.matrixAutoUpdate ) this.updateMatrix(); + + this.matrix.premultiply( matrix ); + + this.matrix.decompose( this.position, this.quaternion, this.scale ); + + } + + applyQuaternion( q ) { + + this.quaternion.premultiply( q ); + + return this; + + } + + setRotationFromAxisAngle( axis, angle ) { + + // assumes axis is normalized + + this.quaternion.setFromAxisAngle( axis, angle ); + + } + + setRotationFromEuler( euler ) { + + this.quaternion.setFromEuler( euler, true ); + + } + + setRotationFromMatrix( m ) { + + // assumes the upper 3x3 of m is a pure rotation matrix (i.e, unscaled) + + this.quaternion.setFromRotationMatrix( m ); + + } + + setRotationFromQuaternion( q ) { + + // assumes q is normalized + + this.quaternion.copy( q ); + + } + + rotateOnAxis( axis, angle ) { + + // rotate object on axis in object space + // axis is assumed to be normalized + + _q1.setFromAxisAngle( axis, angle ); + + this.quaternion.multiply( _q1 ); + + return this; + + } + + rotateOnWorldAxis( axis, angle ) { + + // rotate object on axis in world space + // axis is assumed to be normalized + // method assumes no rotated parent + + _q1.setFromAxisAngle( axis, angle ); + + this.quaternion.premultiply( _q1 ); + + return this; + + } + + rotateX( angle ) { + + return this.rotateOnAxis( _xAxis, angle ); + + } + + rotateY( angle ) { + + return this.rotateOnAxis( _yAxis, angle ); + + } + + rotateZ( angle ) { + + return this.rotateOnAxis( _zAxis, angle ); + + } + + translateOnAxis( axis, distance ) { + + // translate object by distance along axis in object space + // axis is assumed to be normalized + + _v1$4.copy( axis ).applyQuaternion( this.quaternion ); + + this.position.add( _v1$4.multiplyScalar( distance ) ); + + return this; + + } + + translateX( distance ) { + + return this.translateOnAxis( _xAxis, distance ); + + } + + translateY( distance ) { + + return this.translateOnAxis( _yAxis, distance ); + + } + + translateZ( distance ) { + + return this.translateOnAxis( _zAxis, distance ); + + } + + localToWorld( vector ) { + + this.updateWorldMatrix( true, false ); + + return vector.applyMatrix4( this.matrixWorld ); + + } + + worldToLocal( vector ) { + + this.updateWorldMatrix( true, false ); + + return vector.applyMatrix4( _m1$3.copy( this.matrixWorld ).invert() ); + + } + + lookAt( x, y, z ) { + + // This method does not support objects having non-uniformly-scaled parent(s) + + if ( x.isVector3 ) { + + _target.copy( x ); + + } else { + + _target.set( x, y, z ); + + } + + const parent = this.parent; + + this.updateWorldMatrix( true, false ); + + _position$3.setFromMatrixPosition( this.matrixWorld ); + + if ( this.isCamera || this.isLight ) { + + _m1$3.lookAt( _position$3, _target, this.up ); + + } else { + + _m1$3.lookAt( _target, _position$3, this.up ); + + } + + this.quaternion.setFromRotationMatrix( _m1$3 ); + + if ( parent ) { + + _m1$3.extractRotation( parent.matrixWorld ); + _q1.setFromRotationMatrix( _m1$3 ); + this.quaternion.premultiply( _q1.invert() ); + + } + + } + + add( object ) { + + if ( arguments.length > 1 ) { + + for ( let i = 0; i < arguments.length; i ++ ) { + + this.add( arguments[ i ] ); + + } + + return this; + + } + + if ( object === this ) { + + console.error( 'THREE.Object3D.add: object can\'t be added as a child of itself.', object ); + return this; + + } + + if ( object && object.isObject3D ) { + + object.removeFromParent(); + object.parent = this; + this.children.push( object ); + + object.dispatchEvent( _addedEvent ); + + _childaddedEvent.child = object; + this.dispatchEvent( _childaddedEvent ); + _childaddedEvent.child = null; + + } else { + + console.error( 'THREE.Object3D.add: object not an instance of THREE.Object3D.', object ); + + } + + return this; + + } + + remove( object ) { + + if ( arguments.length > 1 ) { + + for ( let i = 0; i < arguments.length; i ++ ) { + + this.remove( arguments[ i ] ); + + } + + return this; + + } + + const index = this.children.indexOf( object ); + + if ( index !== - 1 ) { + + object.parent = null; + this.children.splice( index, 1 ); + + object.dispatchEvent( _removedEvent ); + + _childremovedEvent.child = object; + this.dispatchEvent( _childremovedEvent ); + _childremovedEvent.child = null; + + } + + return this; + + } + + removeFromParent() { + + const parent = this.parent; + + if ( parent !== null ) { + + parent.remove( this ); + + } + + return this; + + } + + clear() { + + return this.remove( ... this.children ); + + } + + attach( object ) { + + // adds object as a child of this, while maintaining the object's world transform + + // Note: This method does not support scene graphs having non-uniformly-scaled nodes(s) + + this.updateWorldMatrix( true, false ); + + _m1$3.copy( this.matrixWorld ).invert(); + + if ( object.parent !== null ) { + + object.parent.updateWorldMatrix( true, false ); + + _m1$3.multiply( object.parent.matrixWorld ); + + } + + object.applyMatrix4( _m1$3 ); + + object.removeFromParent(); + object.parent = this; + this.children.push( object ); + + object.updateWorldMatrix( false, true ); + + object.dispatchEvent( _addedEvent ); + + _childaddedEvent.child = object; + this.dispatchEvent( _childaddedEvent ); + _childaddedEvent.child = null; + + return this; + + } + + getObjectById( id ) { + + return this.getObjectByProperty( 'id', id ); + + } + + getObjectByName( name ) { + + return this.getObjectByProperty( 'name', name ); + + } + + getObjectByProperty( name, value ) { + + if ( this[ name ] === value ) return this; + + for ( let i = 0, l = this.children.length; i < l; i ++ ) { + + const child = this.children[ i ]; + const object = child.getObjectByProperty( name, value ); + + if ( object !== undefined ) { + + return object; + + } + + } + + return undefined; + + } + + getObjectsByProperty( name, value, result = [] ) { + + if ( this[ name ] === value ) result.push( this ); + + const children = this.children; + + for ( let i = 0, l = children.length; i < l; i ++ ) { + + children[ i ].getObjectsByProperty( name, value, result ); + + } + + return result; + + } + + getWorldPosition( target ) { + + this.updateWorldMatrix( true, false ); + + return target.setFromMatrixPosition( this.matrixWorld ); + + } + + getWorldQuaternion( target ) { + + this.updateWorldMatrix( true, false ); + + this.matrixWorld.decompose( _position$3, target, _scale$2 ); + + return target; + + } + + getWorldScale( target ) { + + this.updateWorldMatrix( true, false ); + + this.matrixWorld.decompose( _position$3, _quaternion$2, target ); + + return target; + + } + + getWorldDirection( target ) { + + this.updateWorldMatrix( true, false ); + + const e = this.matrixWorld.elements; + + return target.set( e[ 8 ], e[ 9 ], e[ 10 ] ).normalize(); + + } + + raycast( /* raycaster, intersects */ ) {} + + traverse( callback ) { + + callback( this ); + + const children = this.children; + + for ( let i = 0, l = children.length; i < l; i ++ ) { + + children[ i ].traverse( callback ); + + } + + } + + traverseVisible( callback ) { + + if ( this.visible === false ) return; + + callback( this ); + + const children = this.children; + + for ( let i = 0, l = children.length; i < l; i ++ ) { + + children[ i ].traverseVisible( callback ); + + } + + } + + traverseAncestors( callback ) { + + const parent = this.parent; + + if ( parent !== null ) { + + callback( parent ); + + parent.traverseAncestors( callback ); + + } + + } + + updateMatrix() { + + this.matrix.compose( this.position, this.quaternion, this.scale ); + + this.matrixWorldNeedsUpdate = true; + + } + + updateMatrixWorld( force ) { + + if ( this.matrixAutoUpdate ) this.updateMatrix(); + + if ( this.matrixWorldNeedsUpdate || force ) { + + if ( this.parent === null ) { + + this.matrixWorld.copy( this.matrix ); + + } else { + + this.matrixWorld.multiplyMatrices( this.parent.matrixWorld, this.matrix ); + + } + + this.matrixWorldNeedsUpdate = false; + + force = true; + + } + + // update children + + const children = this.children; + + for ( let i = 0, l = children.length; i < l; i ++ ) { + + const child = children[ i ]; + + if ( child.matrixWorldAutoUpdate === true || force === true ) { + + child.updateMatrixWorld( force ); + + } + + } + + } + + updateWorldMatrix( updateParents, updateChildren ) { + + const parent = this.parent; + + if ( updateParents === true && parent !== null && parent.matrixWorldAutoUpdate === true ) { + + parent.updateWorldMatrix( true, false ); + + } + + if ( this.matrixAutoUpdate ) this.updateMatrix(); + + if ( this.parent === null ) { + + this.matrixWorld.copy( this.matrix ); + + } else { + + this.matrixWorld.multiplyMatrices( this.parent.matrixWorld, this.matrix ); + + } + + // update children + + if ( updateChildren === true ) { + + const children = this.children; + + for ( let i = 0, l = children.length; i < l; i ++ ) { + + const child = children[ i ]; + + if ( child.matrixWorldAutoUpdate === true ) { + + child.updateWorldMatrix( false, true ); + + } + + } + + } + + } + + toJSON( meta ) { + + // meta is a string when called from JSON.stringify + const isRootObject = ( meta === undefined || typeof meta === 'string' ); + + const output = {}; + + // meta is a hash used to collect geometries, materials. + // not providing it implies that this is the root object + // being serialized. + if ( isRootObject ) { + + // initialize meta obj + meta = { + geometries: {}, + materials: {}, + textures: {}, + images: {}, + shapes: {}, + skeletons: {}, + animations: {}, + nodes: {} + }; + + output.metadata = { + version: 4.6, + type: 'Object', + generator: 'Object3D.toJSON' + }; + + } + + // standard Object3D serialization + + const object = {}; + + object.uuid = this.uuid; + object.type = this.type; + + if ( this.name !== '' ) object.name = this.name; + if ( this.castShadow === true ) object.castShadow = true; + if ( this.receiveShadow === true ) object.receiveShadow = true; + if ( this.visible === false ) object.visible = false; + if ( this.frustumCulled === false ) object.frustumCulled = false; + if ( this.renderOrder !== 0 ) object.renderOrder = this.renderOrder; + if ( Object.keys( this.userData ).length > 0 ) object.userData = this.userData; + + object.layers = this.layers.mask; + object.matrix = this.matrix.toArray(); + object.up = this.up.toArray(); + + if ( this.matrixAutoUpdate === false ) object.matrixAutoUpdate = false; + + // object specific properties + + if ( this.isInstancedMesh ) { + + object.type = 'InstancedMesh'; + object.count = this.count; + object.instanceMatrix = this.instanceMatrix.toJSON(); + if ( this.instanceColor !== null ) object.instanceColor = this.instanceColor.toJSON(); + + } + + if ( this.isBatchedMesh ) { + + object.type = 'BatchedMesh'; + object.perObjectFrustumCulled = this.perObjectFrustumCulled; + object.sortObjects = this.sortObjects; + + object.drawRanges = this._drawRanges; + object.reservedRanges = this._reservedRanges; + + object.visibility = this._visibility; + object.active = this._active; + object.bounds = this._bounds.map( bound => ( { + boxInitialized: bound.boxInitialized, + boxMin: bound.box.min.toArray(), + boxMax: bound.box.max.toArray(), + + sphereInitialized: bound.sphereInitialized, + sphereRadius: bound.sphere.radius, + sphereCenter: bound.sphere.center.toArray() + } ) ); + + object.maxGeometryCount = this._maxGeometryCount; + object.maxVertexCount = this._maxVertexCount; + object.maxIndexCount = this._maxIndexCount; + + object.geometryInitialized = this._geometryInitialized; + object.geometryCount = this._geometryCount; + + object.matricesTexture = this._matricesTexture.toJSON( meta ); + + if ( this._colorsTexture !== null ) object.colorsTexture = this._colorsTexture.toJSON( meta ); + + if ( this.boundingSphere !== null ) { + + object.boundingSphere = { + center: object.boundingSphere.center.toArray(), + radius: object.boundingSphere.radius + }; + + } + + if ( this.boundingBox !== null ) { + + object.boundingBox = { + min: object.boundingBox.min.toArray(), + max: object.boundingBox.max.toArray() + }; + + } + + } + + // + + function serialize( library, element ) { + + if ( library[ element.uuid ] === undefined ) { + + library[ element.uuid ] = element.toJSON( meta ); + + } + + return element.uuid; + + } + + if ( this.isScene ) { + + if ( this.background ) { + + if ( this.background.isColor ) { + + object.background = this.background.toJSON(); + + } else if ( this.background.isTexture ) { + + object.background = this.background.toJSON( meta ).uuid; + + } + + } + + if ( this.environment && this.environment.isTexture && this.environment.isRenderTargetTexture !== true ) { + + object.environment = this.environment.toJSON( meta ).uuid; + + } + + } else if ( this.isMesh || this.isLine || this.isPoints ) { + + object.geometry = serialize( meta.geometries, this.geometry ); + + const parameters = this.geometry.parameters; + + if ( parameters !== undefined && parameters.shapes !== undefined ) { + + const shapes = parameters.shapes; + + if ( Array.isArray( shapes ) ) { + + for ( let i = 0, l = shapes.length; i < l; i ++ ) { + + const shape = shapes[ i ]; + + serialize( meta.shapes, shape ); + + } + + } else { + + serialize( meta.shapes, shapes ); + + } + + } + + } + + if ( this.isSkinnedMesh ) { + + object.bindMode = this.bindMode; + object.bindMatrix = this.bindMatrix.toArray(); + + if ( this.skeleton !== undefined ) { + + serialize( meta.skeletons, this.skeleton ); + + object.skeleton = this.skeleton.uuid; + + } + + } + + if ( this.material !== undefined ) { + + if ( Array.isArray( this.material ) ) { + + const uuids = []; + + for ( let i = 0, l = this.material.length; i < l; i ++ ) { + + uuids.push( serialize( meta.materials, this.material[ i ] ) ); + + } + + object.material = uuids; + + } else { + + object.material = serialize( meta.materials, this.material ); + + } + + } + + // + + if ( this.children.length > 0 ) { + + object.children = []; + + for ( let i = 0; i < this.children.length; i ++ ) { + + object.children.push( this.children[ i ].toJSON( meta ).object ); + + } + + } + + // + + if ( this.animations.length > 0 ) { + + object.animations = []; + + for ( let i = 0; i < this.animations.length; i ++ ) { + + const animation = this.animations[ i ]; + + object.animations.push( serialize( meta.animations, animation ) ); + + } + + } + + if ( isRootObject ) { + + const geometries = extractFromCache( meta.geometries ); + const materials = extractFromCache( meta.materials ); + const textures = extractFromCache( meta.textures ); + const images = extractFromCache( meta.images ); + const shapes = extractFromCache( meta.shapes ); + const skeletons = extractFromCache( meta.skeletons ); + const animations = extractFromCache( meta.animations ); + const nodes = extractFromCache( meta.nodes ); + + if ( geometries.length > 0 ) output.geometries = geometries; + if ( materials.length > 0 ) output.materials = materials; + if ( textures.length > 0 ) output.textures = textures; + if ( images.length > 0 ) output.images = images; + if ( shapes.length > 0 ) output.shapes = shapes; + if ( skeletons.length > 0 ) output.skeletons = skeletons; + if ( animations.length > 0 ) output.animations = animations; + if ( nodes.length > 0 ) output.nodes = nodes; + + } + + output.object = object; + + return output; + + // extract data from the cache hash + // remove metadata on each item + // and return as array + function extractFromCache( cache ) { + + const values = []; + for ( const key in cache ) { + + const data = cache[ key ]; + delete data.metadata; + values.push( data ); + + } + + return values; + + } + + } + + clone( recursive ) { + + return new this.constructor().copy( this, recursive ); + + } + + copy( source, recursive = true ) { + + this.name = source.name; + + this.up.copy( source.up ); + + this.position.copy( source.position ); + this.rotation.order = source.rotation.order; + this.quaternion.copy( source.quaternion ); + this.scale.copy( source.scale ); + + this.matrix.copy( source.matrix ); + this.matrixWorld.copy( source.matrixWorld ); + + this.matrixAutoUpdate = source.matrixAutoUpdate; + + this.matrixWorldAutoUpdate = source.matrixWorldAutoUpdate; + this.matrixWorldNeedsUpdate = source.matrixWorldNeedsUpdate; + + this.layers.mask = source.layers.mask; + this.visible = source.visible; + + this.castShadow = source.castShadow; + this.receiveShadow = source.receiveShadow; + + this.frustumCulled = source.frustumCulled; + this.renderOrder = source.renderOrder; + + this.animations = source.animations.slice(); + + this.userData = JSON.parse( JSON.stringify( source.userData ) ); + + if ( recursive === true ) { + + for ( let i = 0; i < source.children.length; i ++ ) { + + const child = source.children[ i ]; + this.add( child.clone() ); + + } + + } + + return this; + + } + +} + +Object3D.DEFAULT_UP = /*@__PURE__*/ new Vector3( 0, 1, 0 ); +Object3D.DEFAULT_MATRIX_AUTO_UPDATE = true; +Object3D.DEFAULT_MATRIX_WORLD_AUTO_UPDATE = true; + +const _v0$1 = /*@__PURE__*/ new Vector3(); +const _v1$3 = /*@__PURE__*/ new Vector3(); +const _v2$2 = /*@__PURE__*/ new Vector3(); +const _v3$2 = /*@__PURE__*/ new Vector3(); + +const _vab = /*@__PURE__*/ new Vector3(); +const _vac = /*@__PURE__*/ new Vector3(); +const _vbc = /*@__PURE__*/ new Vector3(); +const _vap = /*@__PURE__*/ new Vector3(); +const _vbp = /*@__PURE__*/ new Vector3(); +const _vcp = /*@__PURE__*/ new Vector3(); + +class Triangle { + + constructor( a = new Vector3(), b = new Vector3(), c = new Vector3() ) { + + this.a = a; + this.b = b; + this.c = c; + + } + + static getNormal( a, b, c, target ) { + + target.subVectors( c, b ); + _v0$1.subVectors( a, b ); + target.cross( _v0$1 ); + + const targetLengthSq = target.lengthSq(); + if ( targetLengthSq > 0 ) { + + return target.multiplyScalar( 1 / Math.sqrt( targetLengthSq ) ); + + } + + return target.set( 0, 0, 0 ); + + } + + // static/instance method to calculate barycentric coordinates + // based on: http://www.blackpawn.com/texts/pointinpoly/default.html + static getBarycoord( point, a, b, c, target ) { + + _v0$1.subVectors( c, a ); + _v1$3.subVectors( b, a ); + _v2$2.subVectors( point, a ); + + const dot00 = _v0$1.dot( _v0$1 ); + const dot01 = _v0$1.dot( _v1$3 ); + const dot02 = _v0$1.dot( _v2$2 ); + const dot11 = _v1$3.dot( _v1$3 ); + const dot12 = _v1$3.dot( _v2$2 ); + + const denom = ( dot00 * dot11 - dot01 * dot01 ); + + // collinear or singular triangle + if ( denom === 0 ) { + + target.set( 0, 0, 0 ); + return null; + + } + + const invDenom = 1 / denom; + const u = ( dot11 * dot02 - dot01 * dot12 ) * invDenom; + const v = ( dot00 * dot12 - dot01 * dot02 ) * invDenom; + + // barycentric coordinates must always sum to 1 + return target.set( 1 - u - v, v, u ); + + } + + static containsPoint( point, a, b, c ) { + + // if the triangle is degenerate then we can't contain a point + if ( this.getBarycoord( point, a, b, c, _v3$2 ) === null ) { + + return false; + + } + + return ( _v3$2.x >= 0 ) && ( _v3$2.y >= 0 ) && ( ( _v3$2.x + _v3$2.y ) <= 1 ); + + } + + static getInterpolation( point, p1, p2, p3, v1, v2, v3, target ) { + + if ( this.getBarycoord( point, p1, p2, p3, _v3$2 ) === null ) { + + target.x = 0; + target.y = 0; + if ( 'z' in target ) target.z = 0; + if ( 'w' in target ) target.w = 0; + return null; + + } + + target.setScalar( 0 ); + target.addScaledVector( v1, _v3$2.x ); + target.addScaledVector( v2, _v3$2.y ); + target.addScaledVector( v3, _v3$2.z ); + + return target; + + } + + static isFrontFacing( a, b, c, direction ) { + + _v0$1.subVectors( c, b ); + _v1$3.subVectors( a, b ); + + // strictly front facing + return ( _v0$1.cross( _v1$3 ).dot( direction ) < 0 ) ? true : false; + + } + + set( a, b, c ) { + + this.a.copy( a ); + this.b.copy( b ); + this.c.copy( c ); + + return this; + + } + + setFromPointsAndIndices( points, i0, i1, i2 ) { + + this.a.copy( points[ i0 ] ); + this.b.copy( points[ i1 ] ); + this.c.copy( points[ i2 ] ); + + return this; + + } + + setFromAttributeAndIndices( attribute, i0, i1, i2 ) { + + this.a.fromBufferAttribute( attribute, i0 ); + this.b.fromBufferAttribute( attribute, i1 ); + this.c.fromBufferAttribute( attribute, i2 ); + + return this; + + } + + clone() { + + return new this.constructor().copy( this ); + + } + + copy( triangle ) { + + this.a.copy( triangle.a ); + this.b.copy( triangle.b ); + this.c.copy( triangle.c ); + + return this; + + } + + getArea() { + + _v0$1.subVectors( this.c, this.b ); + _v1$3.subVectors( this.a, this.b ); + + return _v0$1.cross( _v1$3 ).length() * 0.5; + + } + + getMidpoint( target ) { + + return target.addVectors( this.a, this.b ).add( this.c ).multiplyScalar( 1 / 3 ); + + } + + getNormal( target ) { + + return Triangle.getNormal( this.a, this.b, this.c, target ); + + } + + getPlane( target ) { + + return target.setFromCoplanarPoints( this.a, this.b, this.c ); + + } + + getBarycoord( point, target ) { + + return Triangle.getBarycoord( point, this.a, this.b, this.c, target ); + + } + + getInterpolation( point, v1, v2, v3, target ) { + + return Triangle.getInterpolation( point, this.a, this.b, this.c, v1, v2, v3, target ); + + } + + containsPoint( point ) { + + return Triangle.containsPoint( point, this.a, this.b, this.c ); + + } + + isFrontFacing( direction ) { + + return Triangle.isFrontFacing( this.a, this.b, this.c, direction ); + + } + + intersectsBox( box ) { + + return box.intersectsTriangle( this ); + + } + + closestPointToPoint( p, target ) { + + const a = this.a, b = this.b, c = this.c; + let v, w; + + // algorithm thanks to Real-Time Collision Detection by Christer Ericson, + // published by Morgan Kaufmann Publishers, (c) 2005 Elsevier Inc., + // under the accompanying license; see chapter 5.1.5 for detailed explanation. + // basically, we're distinguishing which of the voronoi regions of the triangle + // the point lies in with the minimum amount of redundant computation. + + _vab.subVectors( b, a ); + _vac.subVectors( c, a ); + _vap.subVectors( p, a ); + const d1 = _vab.dot( _vap ); + const d2 = _vac.dot( _vap ); + if ( d1 <= 0 && d2 <= 0 ) { + + // vertex region of A; barycentric coords (1, 0, 0) + return target.copy( a ); + + } + + _vbp.subVectors( p, b ); + const d3 = _vab.dot( _vbp ); + const d4 = _vac.dot( _vbp ); + if ( d3 >= 0 && d4 <= d3 ) { + + // vertex region of B; barycentric coords (0, 1, 0) + return target.copy( b ); + + } + + const vc = d1 * d4 - d3 * d2; + if ( vc <= 0 && d1 >= 0 && d3 <= 0 ) { + + v = d1 / ( d1 - d3 ); + // edge region of AB; barycentric coords (1-v, v, 0) + return target.copy( a ).addScaledVector( _vab, v ); + + } + + _vcp.subVectors( p, c ); + const d5 = _vab.dot( _vcp ); + const d6 = _vac.dot( _vcp ); + if ( d6 >= 0 && d5 <= d6 ) { + + // vertex region of C; barycentric coords (0, 0, 1) + return target.copy( c ); + + } + + const vb = d5 * d2 - d1 * d6; + if ( vb <= 0 && d2 >= 0 && d6 <= 0 ) { + + w = d2 / ( d2 - d6 ); + // edge region of AC; barycentric coords (1-w, 0, w) + return target.copy( a ).addScaledVector( _vac, w ); + + } + + const va = d3 * d6 - d5 * d4; + if ( va <= 0 && ( d4 - d3 ) >= 0 && ( d5 - d6 ) >= 0 ) { + + _vbc.subVectors( c, b ); + w = ( d4 - d3 ) / ( ( d4 - d3 ) + ( d5 - d6 ) ); + // edge region of BC; barycentric coords (0, 1-w, w) + return target.copy( b ).addScaledVector( _vbc, w ); // edge region of BC + + } + + // face region + const denom = 1 / ( va + vb + vc ); + // u = va * denom + v = vb * denom; + w = vc * denom; + + return target.copy( a ).addScaledVector( _vab, v ).addScaledVector( _vac, w ); + + } + + equals( triangle ) { + + return triangle.a.equals( this.a ) && triangle.b.equals( this.b ) && triangle.c.equals( this.c ); + + } + +} + +const _colorKeywords = { 'aliceblue': 0xF0F8FF, 'antiquewhite': 0xFAEBD7, 'aqua': 0x00FFFF, 'aquamarine': 0x7FFFD4, 'azure': 0xF0FFFF, + 'beige': 0xF5F5DC, 'bisque': 0xFFE4C4, 'black': 0x000000, 'blanchedalmond': 0xFFEBCD, 'blue': 0x0000FF, 'blueviolet': 0x8A2BE2, + 'brown': 0xA52A2A, 'burlywood': 0xDEB887, 'cadetblue': 0x5F9EA0, 'chartreuse': 0x7FFF00, 'chocolate': 0xD2691E, 'coral': 0xFF7F50, + 'cornflowerblue': 0x6495ED, 'cornsilk': 0xFFF8DC, 'crimson': 0xDC143C, 'cyan': 0x00FFFF, 'darkblue': 0x00008B, 'darkcyan': 0x008B8B, + 'darkgoldenrod': 0xB8860B, 'darkgray': 0xA9A9A9, 'darkgreen': 0x006400, 'darkgrey': 0xA9A9A9, 'darkkhaki': 0xBDB76B, 'darkmagenta': 0x8B008B, + 'darkolivegreen': 0x556B2F, 'darkorange': 0xFF8C00, 'darkorchid': 0x9932CC, 'darkred': 0x8B0000, 'darksalmon': 0xE9967A, 'darkseagreen': 0x8FBC8F, + 'darkslateblue': 0x483D8B, 'darkslategray': 0x2F4F4F, 'darkslategrey': 0x2F4F4F, 'darkturquoise': 0x00CED1, 'darkviolet': 0x9400D3, + 'deeppink': 0xFF1493, 'deepskyblue': 0x00BFFF, 'dimgray': 0x696969, 'dimgrey': 0x696969, 'dodgerblue': 0x1E90FF, 'firebrick': 0xB22222, + 'floralwhite': 0xFFFAF0, 'forestgreen': 0x228B22, 'fuchsia': 0xFF00FF, 'gainsboro': 0xDCDCDC, 'ghostwhite': 0xF8F8FF, 'gold': 0xFFD700, + 'goldenrod': 0xDAA520, 'gray': 0x808080, 'green': 0x008000, 'greenyellow': 0xADFF2F, 'grey': 0x808080, 'honeydew': 0xF0FFF0, 'hotpink': 0xFF69B4, + 'indianred': 0xCD5C5C, 'indigo': 0x4B0082, 'ivory': 0xFFFFF0, 'khaki': 0xF0E68C, 'lavender': 0xE6E6FA, 'lavenderblush': 0xFFF0F5, 'lawngreen': 0x7CFC00, + 'lemonchiffon': 0xFFFACD, 'lightblue': 0xADD8E6, 'lightcoral': 0xF08080, 'lightcyan': 0xE0FFFF, 'lightgoldenrodyellow': 0xFAFAD2, 'lightgray': 0xD3D3D3, + 'lightgreen': 0x90EE90, 'lightgrey': 0xD3D3D3, 'lightpink': 0xFFB6C1, 'lightsalmon': 0xFFA07A, 'lightseagreen': 0x20B2AA, 'lightskyblue': 0x87CEFA, + 'lightslategray': 0x778899, 'lightslategrey': 0x778899, 'lightsteelblue': 0xB0C4DE, 'lightyellow': 0xFFFFE0, 'lime': 0x00FF00, 'limegreen': 0x32CD32, + 'linen': 0xFAF0E6, 'magenta': 0xFF00FF, 'maroon': 0x800000, 'mediumaquamarine': 0x66CDAA, 'mediumblue': 0x0000CD, 'mediumorchid': 0xBA55D3, + 'mediumpurple': 0x9370DB, 'mediumseagreen': 0x3CB371, 'mediumslateblue': 0x7B68EE, 'mediumspringgreen': 0x00FA9A, 'mediumturquoise': 0x48D1CC, + 'mediumvioletred': 0xC71585, 'midnightblue': 0x191970, 'mintcream': 0xF5FFFA, 'mistyrose': 0xFFE4E1, 'moccasin': 0xFFE4B5, 'navajowhite': 0xFFDEAD, + 'navy': 0x000080, 'oldlace': 0xFDF5E6, 'olive': 0x808000, 'olivedrab': 0x6B8E23, 'orange': 0xFFA500, 'orangered': 0xFF4500, 'orchid': 0xDA70D6, + 'palegoldenrod': 0xEEE8AA, 'palegreen': 0x98FB98, 'paleturquoise': 0xAFEEEE, 'palevioletred': 0xDB7093, 'papayawhip': 0xFFEFD5, 'peachpuff': 0xFFDAB9, + 'peru': 0xCD853F, 'pink': 0xFFC0CB, 'plum': 0xDDA0DD, 'powderblue': 0xB0E0E6, 'purple': 0x800080, 'rebeccapurple': 0x663399, 'red': 0xFF0000, 'rosybrown': 0xBC8F8F, + 'royalblue': 0x4169E1, 'saddlebrown': 0x8B4513, 'salmon': 0xFA8072, 'sandybrown': 0xF4A460, 'seagreen': 0x2E8B57, 'seashell': 0xFFF5EE, + 'sienna': 0xA0522D, 'silver': 0xC0C0C0, 'skyblue': 0x87CEEB, 'slateblue': 0x6A5ACD, 'slategray': 0x708090, 'slategrey': 0x708090, 'snow': 0xFFFAFA, + 'springgreen': 0x00FF7F, 'steelblue': 0x4682B4, 'tan': 0xD2B48C, 'teal': 0x008080, 'thistle': 0xD8BFD8, 'tomato': 0xFF6347, 'turquoise': 0x40E0D0, + 'violet': 0xEE82EE, 'wheat': 0xF5DEB3, 'white': 0xFFFFFF, 'whitesmoke': 0xF5F5F5, 'yellow': 0xFFFF00, 'yellowgreen': 0x9ACD32 }; + +const _hslA = { h: 0, s: 0, l: 0 }; +const _hslB = { h: 0, s: 0, l: 0 }; + +function hue2rgb( p, q, t ) { + + if ( t < 0 ) t += 1; + if ( t > 1 ) t -= 1; + if ( t < 1 / 6 ) return p + ( q - p ) * 6 * t; + if ( t < 1 / 2 ) return q; + if ( t < 2 / 3 ) return p + ( q - p ) * 6 * ( 2 / 3 - t ); + return p; + +} + +class Color { + + constructor( r, g, b ) { + + this.isColor = true; + + this.r = 1; + this.g = 1; + this.b = 1; + + return this.set( r, g, b ); + + } + + set( r, g, b ) { + + if ( g === undefined && b === undefined ) { + + // r is THREE.Color, hex or string + + const value = r; + + if ( value && value.isColor ) { + + this.copy( value ); + + } else if ( typeof value === 'number' ) { + + this.setHex( value ); + + } else if ( typeof value === 'string' ) { + + this.setStyle( value ); + + } + + } else { + + this.setRGB( r, g, b ); + + } + + return this; + + } + + setScalar( scalar ) { + + this.r = scalar; + this.g = scalar; + this.b = scalar; + + return this; + + } + + setHex( hex, colorSpace = SRGBColorSpace ) { + + hex = Math.floor( hex ); + + this.r = ( hex >> 16 & 255 ) / 255; + this.g = ( hex >> 8 & 255 ) / 255; + this.b = ( hex & 255 ) / 255; + + ColorManagement.toWorkingColorSpace( this, colorSpace ); + + return this; + + } + + setRGB( r, g, b, colorSpace = ColorManagement.workingColorSpace ) { + + this.r = r; + this.g = g; + this.b = b; + + ColorManagement.toWorkingColorSpace( this, colorSpace ); + + return this; + + } + + setHSL( h, s, l, colorSpace = ColorManagement.workingColorSpace ) { + + // h,s,l ranges are in 0.0 - 1.0 + h = euclideanModulo( h, 1 ); + s = clamp( s, 0, 1 ); + l = clamp( l, 0, 1 ); + + if ( s === 0 ) { + + this.r = this.g = this.b = l; + + } else { + + const p = l <= 0.5 ? l * ( 1 + s ) : l + s - ( l * s ); + const q = ( 2 * l ) - p; + + this.r = hue2rgb( q, p, h + 1 / 3 ); + this.g = hue2rgb( q, p, h ); + this.b = hue2rgb( q, p, h - 1 / 3 ); + + } + + ColorManagement.toWorkingColorSpace( this, colorSpace ); + + return this; + + } + + setStyle( style, colorSpace = SRGBColorSpace ) { + + function handleAlpha( string ) { + + if ( string === undefined ) return; + + if ( parseFloat( string ) < 1 ) { + + console.warn( 'THREE.Color: Alpha component of ' + style + ' will be ignored.' ); + + } + + } + + + let m; + + if ( m = /^(\w+)\(([^\)]*)\)/.exec( style ) ) { + + // rgb / hsl + + let color; + const name = m[ 1 ]; + const components = m[ 2 ]; + + switch ( name ) { + + case 'rgb': + case 'rgba': + + if ( color = /^\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec( components ) ) { + + // rgb(255,0,0) rgba(255,0,0,0.5) + + handleAlpha( color[ 4 ] ); + + return this.setRGB( + Math.min( 255, parseInt( color[ 1 ], 10 ) ) / 255, + Math.min( 255, parseInt( color[ 2 ], 10 ) ) / 255, + Math.min( 255, parseInt( color[ 3 ], 10 ) ) / 255, + colorSpace + ); + + } + + if ( color = /^\s*(\d+)\%\s*,\s*(\d+)\%\s*,\s*(\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec( components ) ) { + + // rgb(100%,0%,0%) rgba(100%,0%,0%,0.5) + + handleAlpha( color[ 4 ] ); + + return this.setRGB( + Math.min( 100, parseInt( color[ 1 ], 10 ) ) / 100, + Math.min( 100, parseInt( color[ 2 ], 10 ) ) / 100, + Math.min( 100, parseInt( color[ 3 ], 10 ) ) / 100, + colorSpace + ); + + } + + break; + + case 'hsl': + case 'hsla': + + if ( color = /^\s*(\d*\.?\d+)\s*,\s*(\d*\.?\d+)\%\s*,\s*(\d*\.?\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec( components ) ) { + + // hsl(120,50%,50%) hsla(120,50%,50%,0.5) + + handleAlpha( color[ 4 ] ); + + return this.setHSL( + parseFloat( color[ 1 ] ) / 360, + parseFloat( color[ 2 ] ) / 100, + parseFloat( color[ 3 ] ) / 100, + colorSpace + ); + + } + + break; + + default: + + console.warn( 'THREE.Color: Unknown color model ' + style ); + + } + + } else if ( m = /^\#([A-Fa-f\d]+)$/.exec( style ) ) { + + // hex color + + const hex = m[ 1 ]; + const size = hex.length; + + if ( size === 3 ) { + + // #ff0 + return this.setRGB( + parseInt( hex.charAt( 0 ), 16 ) / 15, + parseInt( hex.charAt( 1 ), 16 ) / 15, + parseInt( hex.charAt( 2 ), 16 ) / 15, + colorSpace + ); + + } else if ( size === 6 ) { + + // #ff0000 + return this.setHex( parseInt( hex, 16 ), colorSpace ); + + } else { + + console.warn( 'THREE.Color: Invalid hex color ' + style ); + + } + + } else if ( style && style.length > 0 ) { + + return this.setColorName( style, colorSpace ); + + } + + return this; + + } + + setColorName( style, colorSpace = SRGBColorSpace ) { + + // color keywords + const hex = _colorKeywords[ style.toLowerCase() ]; + + if ( hex !== undefined ) { + + // red + this.setHex( hex, colorSpace ); + + } else { + + // unknown color + console.warn( 'THREE.Color: Unknown color ' + style ); + + } + + return this; + + } + + clone() { + + return new this.constructor( this.r, this.g, this.b ); + + } + + copy( color ) { + + this.r = color.r; + this.g = color.g; + this.b = color.b; + + return this; + + } + + copySRGBToLinear( color ) { + + this.r = SRGBToLinear( color.r ); + this.g = SRGBToLinear( color.g ); + this.b = SRGBToLinear( color.b ); + + return this; + + } + + copyLinearToSRGB( color ) { + + this.r = LinearToSRGB( color.r ); + this.g = LinearToSRGB( color.g ); + this.b = LinearToSRGB( color.b ); + + return this; + + } + + convertSRGBToLinear() { + + this.copySRGBToLinear( this ); + + return this; + + } + + convertLinearToSRGB() { + + this.copyLinearToSRGB( this ); + + return this; + + } + + getHex( colorSpace = SRGBColorSpace ) { + + ColorManagement.fromWorkingColorSpace( _color.copy( this ), colorSpace ); + + return Math.round( clamp( _color.r * 255, 0, 255 ) ) * 65536 + Math.round( clamp( _color.g * 255, 0, 255 ) ) * 256 + Math.round( clamp( _color.b * 255, 0, 255 ) ); + + } + + getHexString( colorSpace = SRGBColorSpace ) { + + return ( '000000' + this.getHex( colorSpace ).toString( 16 ) ).slice( - 6 ); + + } + + getHSL( target, colorSpace = ColorManagement.workingColorSpace ) { + + // h,s,l ranges are in 0.0 - 1.0 + + ColorManagement.fromWorkingColorSpace( _color.copy( this ), colorSpace ); + + const r = _color.r, g = _color.g, b = _color.b; + + const max = Math.max( r, g, b ); + const min = Math.min( r, g, b ); + + let hue, saturation; + const lightness = ( min + max ) / 2.0; + + if ( min === max ) { + + hue = 0; + saturation = 0; + + } else { + + const delta = max - min; + + saturation = lightness <= 0.5 ? delta / ( max + min ) : delta / ( 2 - max - min ); + + switch ( max ) { + + case r: hue = ( g - b ) / delta + ( g < b ? 6 : 0 ); break; + case g: hue = ( b - r ) / delta + 2; break; + case b: hue = ( r - g ) / delta + 4; break; + + } + + hue /= 6; + + } + + target.h = hue; + target.s = saturation; + target.l = lightness; + + return target; + + } + + getRGB( target, colorSpace = ColorManagement.workingColorSpace ) { + + ColorManagement.fromWorkingColorSpace( _color.copy( this ), colorSpace ); + + target.r = _color.r; + target.g = _color.g; + target.b = _color.b; + + return target; + + } + + getStyle( colorSpace = SRGBColorSpace ) { + + ColorManagement.fromWorkingColorSpace( _color.copy( this ), colorSpace ); + + const r = _color.r, g = _color.g, b = _color.b; + + if ( colorSpace !== SRGBColorSpace ) { + + // Requires CSS Color Module Level 4 (https://www.w3.org/TR/css-color-4/). + return `color(${ colorSpace } ${ r.toFixed( 3 ) } ${ g.toFixed( 3 ) } ${ b.toFixed( 3 ) })`; + + } + + return `rgb(${ Math.round( r * 255 ) },${ Math.round( g * 255 ) },${ Math.round( b * 255 ) })`; + + } + + offsetHSL( h, s, l ) { + + this.getHSL( _hslA ); + + return this.setHSL( _hslA.h + h, _hslA.s + s, _hslA.l + l ); + + } + + add( color ) { + + this.r += color.r; + this.g += color.g; + this.b += color.b; + + return this; + + } + + addColors( color1, color2 ) { + + this.r = color1.r + color2.r; + this.g = color1.g + color2.g; + this.b = color1.b + color2.b; + + return this; + + } + + addScalar( s ) { + + this.r += s; + this.g += s; + this.b += s; + + return this; + + } + + sub( color ) { + + this.r = Math.max( 0, this.r - color.r ); + this.g = Math.max( 0, this.g - color.g ); + this.b = Math.max( 0, this.b - color.b ); + + return this; + + } + + multiply( color ) { + + this.r *= color.r; + this.g *= color.g; + this.b *= color.b; + + return this; + + } + + multiplyScalar( s ) { + + this.r *= s; + this.g *= s; + this.b *= s; + + return this; + + } + + lerp( color, alpha ) { + + this.r += ( color.r - this.r ) * alpha; + this.g += ( color.g - this.g ) * alpha; + this.b += ( color.b - this.b ) * alpha; + + return this; + + } + + lerpColors( color1, color2, alpha ) { + + this.r = color1.r + ( color2.r - color1.r ) * alpha; + this.g = color1.g + ( color2.g - color1.g ) * alpha; + this.b = color1.b + ( color2.b - color1.b ) * alpha; + + return this; + + } + + lerpHSL( color, alpha ) { + + this.getHSL( _hslA ); + color.getHSL( _hslB ); + + const h = lerp( _hslA.h, _hslB.h, alpha ); + const s = lerp( _hslA.s, _hslB.s, alpha ); + const l = lerp( _hslA.l, _hslB.l, alpha ); + + this.setHSL( h, s, l ); + + return this; + + } + + setFromVector3( v ) { + + this.r = v.x; + this.g = v.y; + this.b = v.z; + + return this; + + } + + applyMatrix3( m ) { + + const r = this.r, g = this.g, b = this.b; + const e = m.elements; + + this.r = e[ 0 ] * r + e[ 3 ] * g + e[ 6 ] * b; + this.g = e[ 1 ] * r + e[ 4 ] * g + e[ 7 ] * b; + this.b = e[ 2 ] * r + e[ 5 ] * g + e[ 8 ] * b; + + return this; + + } + + equals( c ) { + + return ( c.r === this.r ) && ( c.g === this.g ) && ( c.b === this.b ); + + } + + fromArray( array, offset = 0 ) { + + this.r = array[ offset ]; + this.g = array[ offset + 1 ]; + this.b = array[ offset + 2 ]; + + return this; + + } + + toArray( array = [], offset = 0 ) { + + array[ offset ] = this.r; + array[ offset + 1 ] = this.g; + array[ offset + 2 ] = this.b; + + return array; + + } + + fromBufferAttribute( attribute, index ) { + + this.r = attribute.getX( index ); + this.g = attribute.getY( index ); + this.b = attribute.getZ( index ); + + return this; + + } + + toJSON() { + + return this.getHex(); + + } + + *[ Symbol.iterator ]() { + + yield this.r; + yield this.g; + yield this.b; + + } + +} + +const _color = /*@__PURE__*/ new Color(); + +Color.NAMES = _colorKeywords; + +let _materialId = 0; + +class Material extends EventDispatcher { + + constructor() { + + super(); + + this.isMaterial = true; + + Object.defineProperty( this, 'id', { value: _materialId ++ } ); + + this.uuid = generateUUID(); + + this.name = ''; + this.type = 'Material'; + + this.blending = NormalBlending; + this.side = FrontSide; + this.vertexColors = false; + + this.opacity = 1; + this.transparent = false; + this.alphaHash = false; + + this.blendSrc = SrcAlphaFactor; + this.blendDst = OneMinusSrcAlphaFactor; + this.blendEquation = AddEquation; + this.blendSrcAlpha = null; + this.blendDstAlpha = null; + this.blendEquationAlpha = null; + this.blendColor = new Color( 0, 0, 0 ); + this.blendAlpha = 0; + + this.depthFunc = LessEqualDepth; + this.depthTest = true; + this.depthWrite = true; + + this.stencilWriteMask = 0xff; + this.stencilFunc = AlwaysStencilFunc; + this.stencilRef = 0; + this.stencilFuncMask = 0xff; + this.stencilFail = KeepStencilOp; + this.stencilZFail = KeepStencilOp; + this.stencilZPass = KeepStencilOp; + this.stencilWrite = false; + + this.clippingPlanes = null; + this.clipIntersection = false; + this.clipShadows = false; + + this.shadowSide = null; + + this.colorWrite = true; + + this.precision = null; // override the renderer's default precision for this material + + this.polygonOffset = false; + this.polygonOffsetFactor = 0; + this.polygonOffsetUnits = 0; + + this.dithering = false; + + this.alphaToCoverage = false; + this.premultipliedAlpha = false; + this.forceSinglePass = false; + + this.visible = true; + + this.toneMapped = true; + + this.userData = {}; + + this.version = 0; + + this._alphaTest = 0; + + } + + get alphaTest() { + + return this._alphaTest; + + } + + set alphaTest( value ) { + + if ( this._alphaTest > 0 !== value > 0 ) { + + this.version ++; + + } + + this._alphaTest = value; + + } + + onBuild( /* shaderobject, renderer */ ) {} + + onBeforeRender( /* renderer, scene, camera, geometry, object, group */ ) {} + + onBeforeCompile( /* shaderobject, renderer */ ) {} + + customProgramCacheKey() { + + return this.onBeforeCompile.toString(); + + } + + setValues( values ) { + + if ( values === undefined ) return; + + for ( const key in values ) { + + const newValue = values[ key ]; + + if ( newValue === undefined ) { + + console.warn( `THREE.Material: parameter '${ key }' has value of undefined.` ); + continue; + + } + + const currentValue = this[ key ]; + + if ( currentValue === undefined ) { + + console.warn( `THREE.Material: '${ key }' is not a property of THREE.${ this.type }.` ); + continue; + + } + + if ( currentValue && currentValue.isColor ) { + + currentValue.set( newValue ); + + } else if ( ( currentValue && currentValue.isVector3 ) && ( newValue && newValue.isVector3 ) ) { + + currentValue.copy( newValue ); + + } else { + + this[ key ] = newValue; + + } + + } + + } + + toJSON( meta ) { + + const isRootObject = ( meta === undefined || typeof meta === 'string' ); + + if ( isRootObject ) { + + meta = { + textures: {}, + images: {} + }; + + } + + const data = { + metadata: { + version: 4.6, + type: 'Material', + generator: 'Material.toJSON' + } + }; + + // standard Material serialization + data.uuid = this.uuid; + data.type = this.type; + + if ( this.name !== '' ) data.name = this.name; + + if ( this.color && this.color.isColor ) data.color = this.color.getHex(); + + if ( this.roughness !== undefined ) data.roughness = this.roughness; + if ( this.metalness !== undefined ) data.metalness = this.metalness; + + if ( this.sheen !== undefined ) data.sheen = this.sheen; + if ( this.sheenColor && this.sheenColor.isColor ) data.sheenColor = this.sheenColor.getHex(); + if ( this.sheenRoughness !== undefined ) data.sheenRoughness = this.sheenRoughness; + if ( this.emissive && this.emissive.isColor ) data.emissive = this.emissive.getHex(); + if ( this.emissiveIntensity !== undefined && this.emissiveIntensity !== 1 ) data.emissiveIntensity = this.emissiveIntensity; + + if ( this.specular && this.specular.isColor ) data.specular = this.specular.getHex(); + if ( this.specularIntensity !== undefined ) data.specularIntensity = this.specularIntensity; + if ( this.specularColor && this.specularColor.isColor ) data.specularColor = this.specularColor.getHex(); + if ( this.shininess !== undefined ) data.shininess = this.shininess; + if ( this.clearcoat !== undefined ) data.clearcoat = this.clearcoat; + if ( this.clearcoatRoughness !== undefined ) data.clearcoatRoughness = this.clearcoatRoughness; + + if ( this.clearcoatMap && this.clearcoatMap.isTexture ) { + + data.clearcoatMap = this.clearcoatMap.toJSON( meta ).uuid; + + } + + if ( this.clearcoatRoughnessMap && this.clearcoatRoughnessMap.isTexture ) { + + data.clearcoatRoughnessMap = this.clearcoatRoughnessMap.toJSON( meta ).uuid; + + } + + if ( this.clearcoatNormalMap && this.clearcoatNormalMap.isTexture ) { + + data.clearcoatNormalMap = this.clearcoatNormalMap.toJSON( meta ).uuid; + data.clearcoatNormalScale = this.clearcoatNormalScale.toArray(); + + } + + if ( this.dispersion !== undefined ) data.dispersion = this.dispersion; + + if ( this.iridescence !== undefined ) data.iridescence = this.iridescence; + if ( this.iridescenceIOR !== undefined ) data.iridescenceIOR = this.iridescenceIOR; + if ( this.iridescenceThicknessRange !== undefined ) data.iridescenceThicknessRange = this.iridescenceThicknessRange; + + if ( this.iridescenceMap && this.iridescenceMap.isTexture ) { + + data.iridescenceMap = this.iridescenceMap.toJSON( meta ).uuid; + + } + + if ( this.iridescenceThicknessMap && this.iridescenceThicknessMap.isTexture ) { + + data.iridescenceThicknessMap = this.iridescenceThicknessMap.toJSON( meta ).uuid; + + } + + if ( this.anisotropy !== undefined ) data.anisotropy = this.anisotropy; + if ( this.anisotropyRotation !== undefined ) data.anisotropyRotation = this.anisotropyRotation; + + if ( this.anisotropyMap && this.anisotropyMap.isTexture ) { + + data.anisotropyMap = this.anisotropyMap.toJSON( meta ).uuid; + + } + + if ( this.map && this.map.isTexture ) data.map = this.map.toJSON( meta ).uuid; + if ( this.matcap && this.matcap.isTexture ) data.matcap = this.matcap.toJSON( meta ).uuid; + if ( this.alphaMap && this.alphaMap.isTexture ) data.alphaMap = this.alphaMap.toJSON( meta ).uuid; + + if ( this.lightMap && this.lightMap.isTexture ) { + + data.lightMap = this.lightMap.toJSON( meta ).uuid; + data.lightMapIntensity = this.lightMapIntensity; + + } + + if ( this.aoMap && this.aoMap.isTexture ) { + + data.aoMap = this.aoMap.toJSON( meta ).uuid; + data.aoMapIntensity = this.aoMapIntensity; + + } + + if ( this.bumpMap && this.bumpMap.isTexture ) { + + data.bumpMap = this.bumpMap.toJSON( meta ).uuid; + data.bumpScale = this.bumpScale; + + } + + if ( this.normalMap && this.normalMap.isTexture ) { + + data.normalMap = this.normalMap.toJSON( meta ).uuid; + data.normalMapType = this.normalMapType; + data.normalScale = this.normalScale.toArray(); + + } + + if ( this.displacementMap && this.displacementMap.isTexture ) { + + data.displacementMap = this.displacementMap.toJSON( meta ).uuid; + data.displacementScale = this.displacementScale; + data.displacementBias = this.displacementBias; + + } + + if ( this.roughnessMap && this.roughnessMap.isTexture ) data.roughnessMap = this.roughnessMap.toJSON( meta ).uuid; + if ( this.metalnessMap && this.metalnessMap.isTexture ) data.metalnessMap = this.metalnessMap.toJSON( meta ).uuid; + + if ( this.emissiveMap && this.emissiveMap.isTexture ) data.emissiveMap = this.emissiveMap.toJSON( meta ).uuid; + if ( this.specularMap && this.specularMap.isTexture ) data.specularMap = this.specularMap.toJSON( meta ).uuid; + if ( this.specularIntensityMap && this.specularIntensityMap.isTexture ) data.specularIntensityMap = this.specularIntensityMap.toJSON( meta ).uuid; + if ( this.specularColorMap && this.specularColorMap.isTexture ) data.specularColorMap = this.specularColorMap.toJSON( meta ).uuid; + + if ( this.envMap && this.envMap.isTexture ) { + + data.envMap = this.envMap.toJSON( meta ).uuid; + + if ( this.combine !== undefined ) data.combine = this.combine; + + } + + if ( this.envMapRotation !== undefined ) data.envMapRotation = this.envMapRotation.toArray(); + if ( this.envMapIntensity !== undefined ) data.envMapIntensity = this.envMapIntensity; + if ( this.reflectivity !== undefined ) data.reflectivity = this.reflectivity; + if ( this.refractionRatio !== undefined ) data.refractionRatio = this.refractionRatio; + + if ( this.gradientMap && this.gradientMap.isTexture ) { + + data.gradientMap = this.gradientMap.toJSON( meta ).uuid; + + } + + if ( this.transmission !== undefined ) data.transmission = this.transmission; + if ( this.transmissionMap && this.transmissionMap.isTexture ) data.transmissionMap = this.transmissionMap.toJSON( meta ).uuid; + if ( this.thickness !== undefined ) data.thickness = this.thickness; + if ( this.thicknessMap && this.thicknessMap.isTexture ) data.thicknessMap = this.thicknessMap.toJSON( meta ).uuid; + if ( this.attenuationDistance !== undefined && this.attenuationDistance !== Infinity ) data.attenuationDistance = this.attenuationDistance; + if ( this.attenuationColor !== undefined ) data.attenuationColor = this.attenuationColor.getHex(); + + if ( this.size !== undefined ) data.size = this.size; + if ( this.shadowSide !== null ) data.shadowSide = this.shadowSide; + if ( this.sizeAttenuation !== undefined ) data.sizeAttenuation = this.sizeAttenuation; + + if ( this.blending !== NormalBlending ) data.blending = this.blending; + if ( this.side !== FrontSide ) data.side = this.side; + if ( this.vertexColors === true ) data.vertexColors = true; + + if ( this.opacity < 1 ) data.opacity = this.opacity; + if ( this.transparent === true ) data.transparent = true; + + if ( this.blendSrc !== SrcAlphaFactor ) data.blendSrc = this.blendSrc; + if ( this.blendDst !== OneMinusSrcAlphaFactor ) data.blendDst = this.blendDst; + if ( this.blendEquation !== AddEquation ) data.blendEquation = this.blendEquation; + if ( this.blendSrcAlpha !== null ) data.blendSrcAlpha = this.blendSrcAlpha; + if ( this.blendDstAlpha !== null ) data.blendDstAlpha = this.blendDstAlpha; + if ( this.blendEquationAlpha !== null ) data.blendEquationAlpha = this.blendEquationAlpha; + if ( this.blendColor && this.blendColor.isColor ) data.blendColor = this.blendColor.getHex(); + if ( this.blendAlpha !== 0 ) data.blendAlpha = this.blendAlpha; + + if ( this.depthFunc !== LessEqualDepth ) data.depthFunc = this.depthFunc; + if ( this.depthTest === false ) data.depthTest = this.depthTest; + if ( this.depthWrite === false ) data.depthWrite = this.depthWrite; + if ( this.colorWrite === false ) data.colorWrite = this.colorWrite; + + if ( this.stencilWriteMask !== 0xff ) data.stencilWriteMask = this.stencilWriteMask; + if ( this.stencilFunc !== AlwaysStencilFunc ) data.stencilFunc = this.stencilFunc; + if ( this.stencilRef !== 0 ) data.stencilRef = this.stencilRef; + if ( this.stencilFuncMask !== 0xff ) data.stencilFuncMask = this.stencilFuncMask; + if ( this.stencilFail !== KeepStencilOp ) data.stencilFail = this.stencilFail; + if ( this.stencilZFail !== KeepStencilOp ) data.stencilZFail = this.stencilZFail; + if ( this.stencilZPass !== KeepStencilOp ) data.stencilZPass = this.stencilZPass; + if ( this.stencilWrite === true ) data.stencilWrite = this.stencilWrite; + + // rotation (SpriteMaterial) + if ( this.rotation !== undefined && this.rotation !== 0 ) data.rotation = this.rotation; + + if ( this.polygonOffset === true ) data.polygonOffset = true; + if ( this.polygonOffsetFactor !== 0 ) data.polygonOffsetFactor = this.polygonOffsetFactor; + if ( this.polygonOffsetUnits !== 0 ) data.polygonOffsetUnits = this.polygonOffsetUnits; + + if ( this.linewidth !== undefined && this.linewidth !== 1 ) data.linewidth = this.linewidth; + if ( this.dashSize !== undefined ) data.dashSize = this.dashSize; + if ( this.gapSize !== undefined ) data.gapSize = this.gapSize; + if ( this.scale !== undefined ) data.scale = this.scale; + + if ( this.dithering === true ) data.dithering = true; + + if ( this.alphaTest > 0 ) data.alphaTest = this.alphaTest; + if ( this.alphaHash === true ) data.alphaHash = true; + if ( this.alphaToCoverage === true ) data.alphaToCoverage = true; + if ( this.premultipliedAlpha === true ) data.premultipliedAlpha = true; + if ( this.forceSinglePass === true ) data.forceSinglePass = true; + + if ( this.wireframe === true ) data.wireframe = true; + if ( this.wireframeLinewidth > 1 ) data.wireframeLinewidth = this.wireframeLinewidth; + if ( this.wireframeLinecap !== 'round' ) data.wireframeLinecap = this.wireframeLinecap; + if ( this.wireframeLinejoin !== 'round' ) data.wireframeLinejoin = this.wireframeLinejoin; + + if ( this.flatShading === true ) data.flatShading = true; + + if ( this.visible === false ) data.visible = false; + + if ( this.toneMapped === false ) data.toneMapped = false; + + if ( this.fog === false ) data.fog = false; + + if ( Object.keys( this.userData ).length > 0 ) data.userData = this.userData; + + // TODO: Copied from Object3D.toJSON + + function extractFromCache( cache ) { + + const values = []; + + for ( const key in cache ) { + + const data = cache[ key ]; + delete data.metadata; + values.push( data ); + + } + + return values; + + } + + if ( isRootObject ) { + + const textures = extractFromCache( meta.textures ); + const images = extractFromCache( meta.images ); + + if ( textures.length > 0 ) data.textures = textures; + if ( images.length > 0 ) data.images = images; + + } + + return data; + + } + + clone() { + + return new this.constructor().copy( this ); + + } + + copy( source ) { + + this.name = source.name; + + this.blending = source.blending; + this.side = source.side; + this.vertexColors = source.vertexColors; + + this.opacity = source.opacity; + this.transparent = source.transparent; + + this.blendSrc = source.blendSrc; + this.blendDst = source.blendDst; + this.blendEquation = source.blendEquation; + this.blendSrcAlpha = source.blendSrcAlpha; + this.blendDstAlpha = source.blendDstAlpha; + this.blendEquationAlpha = source.blendEquationAlpha; + this.blendColor.copy( source.blendColor ); + this.blendAlpha = source.blendAlpha; + + this.depthFunc = source.depthFunc; + this.depthTest = source.depthTest; + this.depthWrite = source.depthWrite; + + this.stencilWriteMask = source.stencilWriteMask; + this.stencilFunc = source.stencilFunc; + this.stencilRef = source.stencilRef; + this.stencilFuncMask = source.stencilFuncMask; + this.stencilFail = source.stencilFail; + this.stencilZFail = source.stencilZFail; + this.stencilZPass = source.stencilZPass; + this.stencilWrite = source.stencilWrite; + + const srcPlanes = source.clippingPlanes; + let dstPlanes = null; + + if ( srcPlanes !== null ) { + + const n = srcPlanes.length; + dstPlanes = new Array( n ); + + for ( let i = 0; i !== n; ++ i ) { + + dstPlanes[ i ] = srcPlanes[ i ].clone(); + + } + + } + + this.clippingPlanes = dstPlanes; + this.clipIntersection = source.clipIntersection; + this.clipShadows = source.clipShadows; + + this.shadowSide = source.shadowSide; + + this.colorWrite = source.colorWrite; + + this.precision = source.precision; + + this.polygonOffset = source.polygonOffset; + this.polygonOffsetFactor = source.polygonOffsetFactor; + this.polygonOffsetUnits = source.polygonOffsetUnits; + + this.dithering = source.dithering; + + this.alphaTest = source.alphaTest; + this.alphaHash = source.alphaHash; + this.alphaToCoverage = source.alphaToCoverage; + this.premultipliedAlpha = source.premultipliedAlpha; + this.forceSinglePass = source.forceSinglePass; + + this.visible = source.visible; + + this.toneMapped = source.toneMapped; + + this.userData = JSON.parse( JSON.stringify( source.userData ) ); + + return this; + + } + + dispose() { + + this.dispatchEvent( { type: 'dispose' } ); + + } + + set needsUpdate( value ) { + + if ( value === true ) this.version ++; + + } + +} + +class MeshBasicMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isMeshBasicMaterial = true; + + this.type = 'MeshBasicMaterial'; + + this.color = new Color( 0xffffff ); // emissive + + this.map = null; + + this.lightMap = null; + this.lightMapIntensity = 1.0; + + this.aoMap = null; + this.aoMapIntensity = 1.0; + + this.specularMap = null; + + this.alphaMap = null; + + this.envMap = null; + this.envMapRotation = new Euler(); + this.combine = MultiplyOperation; + this.reflectivity = 1; + this.refractionRatio = 0.98; + + this.wireframe = false; + this.wireframeLinewidth = 1; + this.wireframeLinecap = 'round'; + this.wireframeLinejoin = 'round'; + + this.fog = true; + + this.setValues( parameters ); + + } + + copy( source ) { + + super.copy( source ); + + this.color.copy( source.color ); + + this.map = source.map; + + this.lightMap = source.lightMap; + this.lightMapIntensity = source.lightMapIntensity; + + this.aoMap = source.aoMap; + this.aoMapIntensity = source.aoMapIntensity; + + this.specularMap = source.specularMap; + + this.alphaMap = source.alphaMap; + + this.envMap = source.envMap; + this.envMapRotation.copy( source.envMapRotation ); + this.combine = source.combine; + this.reflectivity = source.reflectivity; + this.refractionRatio = source.refractionRatio; + + this.wireframe = source.wireframe; + this.wireframeLinewidth = source.wireframeLinewidth; + this.wireframeLinecap = source.wireframeLinecap; + this.wireframeLinejoin = source.wireframeLinejoin; + + this.fog = source.fog; + + return this; + + } + +} + +// Fast Half Float Conversions, http://www.fox-toolkit.org/ftp/fasthalffloatconversion.pdf + +const _tables = /*@__PURE__*/ _generateTables(); + +function _generateTables() { + + // float32 to float16 helpers + + const buffer = new ArrayBuffer( 4 ); + const floatView = new Float32Array( buffer ); + const uint32View = new Uint32Array( buffer ); + + const baseTable = new Uint32Array( 512 ); + const shiftTable = new Uint32Array( 512 ); + + for ( let i = 0; i < 256; ++ i ) { + + const e = i - 127; + + // very small number (0, -0) + + if ( e < - 27 ) { + + baseTable[ i ] = 0x0000; + baseTable[ i | 0x100 ] = 0x8000; + shiftTable[ i ] = 24; + shiftTable[ i | 0x100 ] = 24; + + // small number (denorm) + + } else if ( e < - 14 ) { + + baseTable[ i ] = 0x0400 >> ( - e - 14 ); + baseTable[ i | 0x100 ] = ( 0x0400 >> ( - e - 14 ) ) | 0x8000; + shiftTable[ i ] = - e - 1; + shiftTable[ i | 0x100 ] = - e - 1; + + // normal number + + } else if ( e <= 15 ) { + + baseTable[ i ] = ( e + 15 ) << 10; + baseTable[ i | 0x100 ] = ( ( e + 15 ) << 10 ) | 0x8000; + shiftTable[ i ] = 13; + shiftTable[ i | 0x100 ] = 13; + + // large number (Infinity, -Infinity) + + } else if ( e < 128 ) { + + baseTable[ i ] = 0x7c00; + baseTable[ i | 0x100 ] = 0xfc00; + shiftTable[ i ] = 24; + shiftTable[ i | 0x100 ] = 24; + + // stay (NaN, Infinity, -Infinity) + + } else { + + baseTable[ i ] = 0x7c00; + baseTable[ i | 0x100 ] = 0xfc00; + shiftTable[ i ] = 13; + shiftTable[ i | 0x100 ] = 13; + + } + + } + + // float16 to float32 helpers + + const mantissaTable = new Uint32Array( 2048 ); + const exponentTable = new Uint32Array( 64 ); + const offsetTable = new Uint32Array( 64 ); + + for ( let i = 1; i < 1024; ++ i ) { + + let m = i << 13; // zero pad mantissa bits + let e = 0; // zero exponent + + // normalized + while ( ( m & 0x00800000 ) === 0 ) { + + m <<= 1; + e -= 0x00800000; // decrement exponent + + } + + m &= ~ 0x00800000; // clear leading 1 bit + e += 0x38800000; // adjust bias + + mantissaTable[ i ] = m | e; + + } + + for ( let i = 1024; i < 2048; ++ i ) { + + mantissaTable[ i ] = 0x38000000 + ( ( i - 1024 ) << 13 ); + + } + + for ( let i = 1; i < 31; ++ i ) { + + exponentTable[ i ] = i << 23; + + } + + exponentTable[ 31 ] = 0x47800000; + exponentTable[ 32 ] = 0x80000000; + + for ( let i = 33; i < 63; ++ i ) { + + exponentTable[ i ] = 0x80000000 + ( ( i - 32 ) << 23 ); + + } + + exponentTable[ 63 ] = 0xc7800000; + + for ( let i = 1; i < 64; ++ i ) { + + if ( i !== 32 ) { + + offsetTable[ i ] = 1024; + + } + + } + + return { + floatView: floatView, + uint32View: uint32View, + baseTable: baseTable, + shiftTable: shiftTable, + mantissaTable: mantissaTable, + exponentTable: exponentTable, + offsetTable: offsetTable + }; + +} + +// float32 to float16 + +function toHalfFloat( val ) { + + if ( Math.abs( val ) > 65504 ) console.warn( 'THREE.DataUtils.toHalfFloat(): Value out of range.' ); + + val = clamp( val, - 65504, 65504 ); + + _tables.floatView[ 0 ] = val; + const f = _tables.uint32View[ 0 ]; + const e = ( f >> 23 ) & 0x1ff; + return _tables.baseTable[ e ] + ( ( f & 0x007fffff ) >> _tables.shiftTable[ e ] ); + +} + +// float16 to float32 + +function fromHalfFloat( val ) { + + const m = val >> 10; + _tables.uint32View[ 0 ] = _tables.mantissaTable[ _tables.offsetTable[ m ] + ( val & 0x3ff ) ] + _tables.exponentTable[ m ]; + return _tables.floatView[ 0 ]; + +} + +const DataUtils = { + toHalfFloat: toHalfFloat, + fromHalfFloat: fromHalfFloat, +}; + +const _vector$9 = /*@__PURE__*/ new Vector3(); +const _vector2$1 = /*@__PURE__*/ new Vector2(); + +class BufferAttribute { + + constructor( array, itemSize, normalized = false ) { + + if ( Array.isArray( array ) ) { + + throw new TypeError( 'THREE.BufferAttribute: array should be a Typed Array.' ); + + } + + this.isBufferAttribute = true; + + this.name = ''; + + this.array = array; + this.itemSize = itemSize; + this.count = array !== undefined ? array.length / itemSize : 0; + this.normalized = normalized; + + this.usage = StaticDrawUsage; + this._updateRange = { offset: 0, count: - 1 }; + this.updateRanges = []; + this.gpuType = FloatType; + + this.version = 0; + + } + + onUploadCallback() {} + + set needsUpdate( value ) { + + if ( value === true ) this.version ++; + + } + + get updateRange() { + + warnOnce( 'THREE.BufferAttribute: updateRange() is deprecated and will be removed in r169. Use addUpdateRange() instead.' ); // @deprecated, r159 + return this._updateRange; + + } + + setUsage( value ) { + + this.usage = value; + + return this; + + } + + addUpdateRange( start, count ) { + + this.updateRanges.push( { start, count } ); + + } + + clearUpdateRanges() { + + this.updateRanges.length = 0; + + } + + copy( source ) { + + this.name = source.name; + this.array = new source.array.constructor( source.array ); + this.itemSize = source.itemSize; + this.count = source.count; + this.normalized = source.normalized; + + this.usage = source.usage; + this.gpuType = source.gpuType; + + return this; + + } + + copyAt( index1, attribute, index2 ) { + + index1 *= this.itemSize; + index2 *= attribute.itemSize; + + for ( let i = 0, l = this.itemSize; i < l; i ++ ) { + + this.array[ index1 + i ] = attribute.array[ index2 + i ]; + + } + + return this; + + } + + copyArray( array ) { + + this.array.set( array ); + + return this; + + } + + applyMatrix3( m ) { + + if ( this.itemSize === 2 ) { + + for ( let i = 0, l = this.count; i < l; i ++ ) { + + _vector2$1.fromBufferAttribute( this, i ); + _vector2$1.applyMatrix3( m ); + + this.setXY( i, _vector2$1.x, _vector2$1.y ); + + } + + } else if ( this.itemSize === 3 ) { + + for ( let i = 0, l = this.count; i < l; i ++ ) { + + _vector$9.fromBufferAttribute( this, i ); + _vector$9.applyMatrix3( m ); + + this.setXYZ( i, _vector$9.x, _vector$9.y, _vector$9.z ); + + } + + } + + return this; + + } + + applyMatrix4( m ) { + + for ( let i = 0, l = this.count; i < l; i ++ ) { + + _vector$9.fromBufferAttribute( this, i ); + + _vector$9.applyMatrix4( m ); + + this.setXYZ( i, _vector$9.x, _vector$9.y, _vector$9.z ); + + } + + return this; + + } + + applyNormalMatrix( m ) { + + for ( let i = 0, l = this.count; i < l; i ++ ) { + + _vector$9.fromBufferAttribute( this, i ); + + _vector$9.applyNormalMatrix( m ); + + this.setXYZ( i, _vector$9.x, _vector$9.y, _vector$9.z ); + + } + + return this; + + } + + transformDirection( m ) { + + for ( let i = 0, l = this.count; i < l; i ++ ) { + + _vector$9.fromBufferAttribute( this, i ); + + _vector$9.transformDirection( m ); + + this.setXYZ( i, _vector$9.x, _vector$9.y, _vector$9.z ); + + } + + return this; + + } + + set( value, offset = 0 ) { + + // Matching BufferAttribute constructor, do not normalize the array. + this.array.set( value, offset ); + + return this; + + } + + getComponent( index, component ) { + + let value = this.array[ index * this.itemSize + component ]; + + if ( this.normalized ) value = denormalize( value, this.array ); + + return value; + + } + + setComponent( index, component, value ) { + + if ( this.normalized ) value = normalize( value, this.array ); + + this.array[ index * this.itemSize + component ] = value; + + return this; + + } + + getX( index ) { + + let x = this.array[ index * this.itemSize ]; + + if ( this.normalized ) x = denormalize( x, this.array ); + + return x; + + } + + setX( index, x ) { + + if ( this.normalized ) x = normalize( x, this.array ); + + this.array[ index * this.itemSize ] = x; + + return this; + + } + + getY( index ) { + + let y = this.array[ index * this.itemSize + 1 ]; + + if ( this.normalized ) y = denormalize( y, this.array ); + + return y; + + } + + setY( index, y ) { + + if ( this.normalized ) y = normalize( y, this.array ); + + this.array[ index * this.itemSize + 1 ] = y; + + return this; + + } + + getZ( index ) { + + let z = this.array[ index * this.itemSize + 2 ]; + + if ( this.normalized ) z = denormalize( z, this.array ); + + return z; + + } + + setZ( index, z ) { + + if ( this.normalized ) z = normalize( z, this.array ); + + this.array[ index * this.itemSize + 2 ] = z; + + return this; + + } + + getW( index ) { + + let w = this.array[ index * this.itemSize + 3 ]; + + if ( this.normalized ) w = denormalize( w, this.array ); + + return w; + + } + + setW( index, w ) { + + if ( this.normalized ) w = normalize( w, this.array ); + + this.array[ index * this.itemSize + 3 ] = w; + + return this; + + } + + setXY( index, x, y ) { + + index *= this.itemSize; + + if ( this.normalized ) { + + x = normalize( x, this.array ); + y = normalize( y, this.array ); + + } + + this.array[ index + 0 ] = x; + this.array[ index + 1 ] = y; + + return this; + + } + + setXYZ( index, x, y, z ) { + + index *= this.itemSize; + + if ( this.normalized ) { + + x = normalize( x, this.array ); + y = normalize( y, this.array ); + z = normalize( z, this.array ); + + } + + this.array[ index + 0 ] = x; + this.array[ index + 1 ] = y; + this.array[ index + 2 ] = z; + + return this; + + } + + setXYZW( index, x, y, z, w ) { + + index *= this.itemSize; + + if ( this.normalized ) { + + x = normalize( x, this.array ); + y = normalize( y, this.array ); + z = normalize( z, this.array ); + w = normalize( w, this.array ); + + } + + this.array[ index + 0 ] = x; + this.array[ index + 1 ] = y; + this.array[ index + 2 ] = z; + this.array[ index + 3 ] = w; + + return this; + + } + + onUpload( callback ) { + + this.onUploadCallback = callback; + + return this; + + } + + clone() { + + return new this.constructor( this.array, this.itemSize ).copy( this ); + + } + + toJSON() { + + const data = { + itemSize: this.itemSize, + type: this.array.constructor.name, + array: Array.from( this.array ), + normalized: this.normalized + }; + + if ( this.name !== '' ) data.name = this.name; + if ( this.usage !== StaticDrawUsage ) data.usage = this.usage; + + return data; + + } + +} + +// + +class Int8BufferAttribute extends BufferAttribute { + + constructor( array, itemSize, normalized ) { + + super( new Int8Array( array ), itemSize, normalized ); + + } + +} + +class Uint8BufferAttribute extends BufferAttribute { + + constructor( array, itemSize, normalized ) { + + super( new Uint8Array( array ), itemSize, normalized ); + + } + +} + +class Uint8ClampedBufferAttribute extends BufferAttribute { + + constructor( array, itemSize, normalized ) { + + super( new Uint8ClampedArray( array ), itemSize, normalized ); + + } + +} + +class Int16BufferAttribute extends BufferAttribute { + + constructor( array, itemSize, normalized ) { + + super( new Int16Array( array ), itemSize, normalized ); + + } + +} + +class Uint16BufferAttribute extends BufferAttribute { + + constructor( array, itemSize, normalized ) { + + super( new Uint16Array( array ), itemSize, normalized ); + + } + +} + +class Int32BufferAttribute extends BufferAttribute { + + constructor( array, itemSize, normalized ) { + + super( new Int32Array( array ), itemSize, normalized ); + + } + +} + +class Uint32BufferAttribute extends BufferAttribute { + + constructor( array, itemSize, normalized ) { + + super( new Uint32Array( array ), itemSize, normalized ); + + } + +} + +class Float16BufferAttribute extends BufferAttribute { + + constructor( array, itemSize, normalized ) { + + super( new Uint16Array( array ), itemSize, normalized ); + + this.isFloat16BufferAttribute = true; + + } + + getX( index ) { + + let x = fromHalfFloat( this.array[ index * this.itemSize ] ); + + if ( this.normalized ) x = denormalize( x, this.array ); + + return x; + + } + + setX( index, x ) { + + if ( this.normalized ) x = normalize( x, this.array ); + + this.array[ index * this.itemSize ] = toHalfFloat( x ); + + return this; + + } + + getY( index ) { + + let y = fromHalfFloat( this.array[ index * this.itemSize + 1 ] ); + + if ( this.normalized ) y = denormalize( y, this.array ); + + return y; + + } + + setY( index, y ) { + + if ( this.normalized ) y = normalize( y, this.array ); + + this.array[ index * this.itemSize + 1 ] = toHalfFloat( y ); + + return this; + + } + + getZ( index ) { + + let z = fromHalfFloat( this.array[ index * this.itemSize + 2 ] ); + + if ( this.normalized ) z = denormalize( z, this.array ); + + return z; + + } + + setZ( index, z ) { + + if ( this.normalized ) z = normalize( z, this.array ); + + this.array[ index * this.itemSize + 2 ] = toHalfFloat( z ); + + return this; + + } + + getW( index ) { + + let w = fromHalfFloat( this.array[ index * this.itemSize + 3 ] ); + + if ( this.normalized ) w = denormalize( w, this.array ); + + return w; + + } + + setW( index, w ) { + + if ( this.normalized ) w = normalize( w, this.array ); + + this.array[ index * this.itemSize + 3 ] = toHalfFloat( w ); + + return this; + + } + + setXY( index, x, y ) { + + index *= this.itemSize; + + if ( this.normalized ) { + + x = normalize( x, this.array ); + y = normalize( y, this.array ); + + } + + this.array[ index + 0 ] = toHalfFloat( x ); + this.array[ index + 1 ] = toHalfFloat( y ); + + return this; + + } + + setXYZ( index, x, y, z ) { + + index *= this.itemSize; + + if ( this.normalized ) { + + x = normalize( x, this.array ); + y = normalize( y, this.array ); + z = normalize( z, this.array ); + + } + + this.array[ index + 0 ] = toHalfFloat( x ); + this.array[ index + 1 ] = toHalfFloat( y ); + this.array[ index + 2 ] = toHalfFloat( z ); + + return this; + + } + + setXYZW( index, x, y, z, w ) { + + index *= this.itemSize; + + if ( this.normalized ) { + + x = normalize( x, this.array ); + y = normalize( y, this.array ); + z = normalize( z, this.array ); + w = normalize( w, this.array ); + + } + + this.array[ index + 0 ] = toHalfFloat( x ); + this.array[ index + 1 ] = toHalfFloat( y ); + this.array[ index + 2 ] = toHalfFloat( z ); + this.array[ index + 3 ] = toHalfFloat( w ); + + return this; + + } + +} + + +class Float32BufferAttribute extends BufferAttribute { + + constructor( array, itemSize, normalized ) { + + super( new Float32Array( array ), itemSize, normalized ); + + } + +} + +let _id$2 = 0; + +const _m1$2 = /*@__PURE__*/ new Matrix4(); +const _obj = /*@__PURE__*/ new Object3D(); +const _offset = /*@__PURE__*/ new Vector3(); +const _box$2 = /*@__PURE__*/ new Box3(); +const _boxMorphTargets = /*@__PURE__*/ new Box3(); +const _vector$8 = /*@__PURE__*/ new Vector3(); + +class BufferGeometry extends EventDispatcher { + + constructor() { + + super(); + + this.isBufferGeometry = true; + + Object.defineProperty( this, 'id', { value: _id$2 ++ } ); + + this.uuid = generateUUID(); + + this.name = ''; + this.type = 'BufferGeometry'; + + this.index = null; + this.attributes = {}; + + this.morphAttributes = {}; + this.morphTargetsRelative = false; + + this.groups = []; + + this.boundingBox = null; + this.boundingSphere = null; + + this.drawRange = { start: 0, count: Infinity }; + + this.userData = {}; + + } + + getIndex() { + + return this.index; + + } + + setIndex( index ) { + + if ( Array.isArray( index ) ) { + + this.index = new ( arrayNeedsUint32( index ) ? Uint32BufferAttribute : Uint16BufferAttribute )( index, 1 ); + + } else { + + this.index = index; + + } + + return this; + + } + + getAttribute( name ) { + + return this.attributes[ name ]; + + } + + setAttribute( name, attribute ) { + + this.attributes[ name ] = attribute; + + return this; + + } + + deleteAttribute( name ) { + + delete this.attributes[ name ]; + + return this; + + } + + hasAttribute( name ) { + + return this.attributes[ name ] !== undefined; + + } + + addGroup( start, count, materialIndex = 0 ) { + + this.groups.push( { + + start: start, + count: count, + materialIndex: materialIndex + + } ); + + } + + clearGroups() { + + this.groups = []; + + } + + setDrawRange( start, count ) { + + this.drawRange.start = start; + this.drawRange.count = count; + + } + + applyMatrix4( matrix ) { + + const position = this.attributes.position; + + if ( position !== undefined ) { + + position.applyMatrix4( matrix ); + + position.needsUpdate = true; + + } + + const normal = this.attributes.normal; + + if ( normal !== undefined ) { + + const normalMatrix = new Matrix3().getNormalMatrix( matrix ); + + normal.applyNormalMatrix( normalMatrix ); + + normal.needsUpdate = true; + + } + + const tangent = this.attributes.tangent; + + if ( tangent !== undefined ) { + + tangent.transformDirection( matrix ); + + tangent.needsUpdate = true; + + } + + if ( this.boundingBox !== null ) { + + this.computeBoundingBox(); + + } + + if ( this.boundingSphere !== null ) { + + this.computeBoundingSphere(); + + } + + return this; + + } + + applyQuaternion( q ) { + + _m1$2.makeRotationFromQuaternion( q ); + + this.applyMatrix4( _m1$2 ); + + return this; + + } + + rotateX( angle ) { + + // rotate geometry around world x-axis + + _m1$2.makeRotationX( angle ); + + this.applyMatrix4( _m1$2 ); + + return this; + + } + + rotateY( angle ) { + + // rotate geometry around world y-axis + + _m1$2.makeRotationY( angle ); + + this.applyMatrix4( _m1$2 ); + + return this; + + } + + rotateZ( angle ) { + + // rotate geometry around world z-axis + + _m1$2.makeRotationZ( angle ); + + this.applyMatrix4( _m1$2 ); + + return this; + + } + + translate( x, y, z ) { + + // translate geometry + + _m1$2.makeTranslation( x, y, z ); + + this.applyMatrix4( _m1$2 ); + + return this; + + } + + scale( x, y, z ) { + + // scale geometry + + _m1$2.makeScale( x, y, z ); + + this.applyMatrix4( _m1$2 ); + + return this; + + } + + lookAt( vector ) { + + _obj.lookAt( vector ); + + _obj.updateMatrix(); + + this.applyMatrix4( _obj.matrix ); + + return this; + + } + + center() { + + this.computeBoundingBox(); + + this.boundingBox.getCenter( _offset ).negate(); + + this.translate( _offset.x, _offset.y, _offset.z ); + + return this; + + } + + setFromPoints( points ) { + + const position = []; + + for ( let i = 0, l = points.length; i < l; i ++ ) { + + const point = points[ i ]; + position.push( point.x, point.y, point.z || 0 ); + + } + + this.setAttribute( 'position', new Float32BufferAttribute( position, 3 ) ); + + return this; + + } + + computeBoundingBox() { + + if ( this.boundingBox === null ) { + + this.boundingBox = new Box3(); + + } + + const position = this.attributes.position; + const morphAttributesPosition = this.morphAttributes.position; + + if ( position && position.isGLBufferAttribute ) { + + console.error( 'THREE.BufferGeometry.computeBoundingBox(): GLBufferAttribute requires a manual bounding box.', this ); + + this.boundingBox.set( + new Vector3( - Infinity, - Infinity, - Infinity ), + new Vector3( + Infinity, + Infinity, + Infinity ) + ); + + return; + + } + + if ( position !== undefined ) { + + this.boundingBox.setFromBufferAttribute( position ); + + // process morph attributes if present + + if ( morphAttributesPosition ) { + + for ( let i = 0, il = morphAttributesPosition.length; i < il; i ++ ) { + + const morphAttribute = morphAttributesPosition[ i ]; + _box$2.setFromBufferAttribute( morphAttribute ); + + if ( this.morphTargetsRelative ) { + + _vector$8.addVectors( this.boundingBox.min, _box$2.min ); + this.boundingBox.expandByPoint( _vector$8 ); + + _vector$8.addVectors( this.boundingBox.max, _box$2.max ); + this.boundingBox.expandByPoint( _vector$8 ); + + } else { + + this.boundingBox.expandByPoint( _box$2.min ); + this.boundingBox.expandByPoint( _box$2.max ); + + } + + } + + } + + } else { + + this.boundingBox.makeEmpty(); + + } + + if ( isNaN( this.boundingBox.min.x ) || isNaN( this.boundingBox.min.y ) || isNaN( this.boundingBox.min.z ) ) { + + console.error( 'THREE.BufferGeometry.computeBoundingBox(): Computed min/max have NaN values. The "position" attribute is likely to have NaN values.', this ); + + } + + } + + computeBoundingSphere() { + + if ( this.boundingSphere === null ) { + + this.boundingSphere = new Sphere(); + + } + + const position = this.attributes.position; + const morphAttributesPosition = this.morphAttributes.position; + + if ( position && position.isGLBufferAttribute ) { + + console.error( 'THREE.BufferGeometry.computeBoundingSphere(): GLBufferAttribute requires a manual bounding sphere.', this ); + + this.boundingSphere.set( new Vector3(), Infinity ); + + return; + + } + + if ( position ) { + + // first, find the center of the bounding sphere + + const center = this.boundingSphere.center; + + _box$2.setFromBufferAttribute( position ); + + // process morph attributes if present + + if ( morphAttributesPosition ) { + + for ( let i = 0, il = morphAttributesPosition.length; i < il; i ++ ) { + + const morphAttribute = morphAttributesPosition[ i ]; + _boxMorphTargets.setFromBufferAttribute( morphAttribute ); + + if ( this.morphTargetsRelative ) { + + _vector$8.addVectors( _box$2.min, _boxMorphTargets.min ); + _box$2.expandByPoint( _vector$8 ); + + _vector$8.addVectors( _box$2.max, _boxMorphTargets.max ); + _box$2.expandByPoint( _vector$8 ); + + } else { + + _box$2.expandByPoint( _boxMorphTargets.min ); + _box$2.expandByPoint( _boxMorphTargets.max ); + + } + + } + + } + + _box$2.getCenter( center ); + + // second, try to find a boundingSphere with a radius smaller than the + // boundingSphere of the boundingBox: sqrt(3) smaller in the best case + + let maxRadiusSq = 0; + + for ( let i = 0, il = position.count; i < il; i ++ ) { + + _vector$8.fromBufferAttribute( position, i ); + + maxRadiusSq = Math.max( maxRadiusSq, center.distanceToSquared( _vector$8 ) ); + + } + + // process morph attributes if present + + if ( morphAttributesPosition ) { + + for ( let i = 0, il = morphAttributesPosition.length; i < il; i ++ ) { + + const morphAttribute = morphAttributesPosition[ i ]; + const morphTargetsRelative = this.morphTargetsRelative; + + for ( let j = 0, jl = morphAttribute.count; j < jl; j ++ ) { + + _vector$8.fromBufferAttribute( morphAttribute, j ); + + if ( morphTargetsRelative ) { + + _offset.fromBufferAttribute( position, j ); + _vector$8.add( _offset ); + + } + + maxRadiusSq = Math.max( maxRadiusSq, center.distanceToSquared( _vector$8 ) ); + + } + + } + + } + + this.boundingSphere.radius = Math.sqrt( maxRadiusSq ); + + if ( isNaN( this.boundingSphere.radius ) ) { + + console.error( 'THREE.BufferGeometry.computeBoundingSphere(): Computed radius is NaN. The "position" attribute is likely to have NaN values.', this ); + + } + + } + + } + + computeTangents() { + + const index = this.index; + const attributes = this.attributes; + + // based on http://www.terathon.com/code/tangent.html + // (per vertex tangents) + + if ( index === null || + attributes.position === undefined || + attributes.normal === undefined || + attributes.uv === undefined ) { + + console.error( 'THREE.BufferGeometry: .computeTangents() failed. Missing required attributes (index, position, normal or uv)' ); + return; + + } + + const positionAttribute = attributes.position; + const normalAttribute = attributes.normal; + const uvAttribute = attributes.uv; + + if ( this.hasAttribute( 'tangent' ) === false ) { + + this.setAttribute( 'tangent', new BufferAttribute( new Float32Array( 4 * positionAttribute.count ), 4 ) ); + + } + + const tangentAttribute = this.getAttribute( 'tangent' ); + + const tan1 = [], tan2 = []; + + for ( let i = 0; i < positionAttribute.count; i ++ ) { + + tan1[ i ] = new Vector3(); + tan2[ i ] = new Vector3(); + + } + + const vA = new Vector3(), + vB = new Vector3(), + vC = new Vector3(), + + uvA = new Vector2(), + uvB = new Vector2(), + uvC = new Vector2(), + + sdir = new Vector3(), + tdir = new Vector3(); + + function handleTriangle( a, b, c ) { + + vA.fromBufferAttribute( positionAttribute, a ); + vB.fromBufferAttribute( positionAttribute, b ); + vC.fromBufferAttribute( positionAttribute, c ); + + uvA.fromBufferAttribute( uvAttribute, a ); + uvB.fromBufferAttribute( uvAttribute, b ); + uvC.fromBufferAttribute( uvAttribute, c ); + + vB.sub( vA ); + vC.sub( vA ); + + uvB.sub( uvA ); + uvC.sub( uvA ); + + const r = 1.0 / ( uvB.x * uvC.y - uvC.x * uvB.y ); + + // silently ignore degenerate uv triangles having coincident or colinear vertices + + if ( ! isFinite( r ) ) return; + + sdir.copy( vB ).multiplyScalar( uvC.y ).addScaledVector( vC, - uvB.y ).multiplyScalar( r ); + tdir.copy( vC ).multiplyScalar( uvB.x ).addScaledVector( vB, - uvC.x ).multiplyScalar( r ); + + tan1[ a ].add( sdir ); + tan1[ b ].add( sdir ); + tan1[ c ].add( sdir ); + + tan2[ a ].add( tdir ); + tan2[ b ].add( tdir ); + tan2[ c ].add( tdir ); + + } + + let groups = this.groups; + + if ( groups.length === 0 ) { + + groups = [ { + start: 0, + count: index.count + } ]; + + } + + for ( let i = 0, il = groups.length; i < il; ++ i ) { + + const group = groups[ i ]; + + const start = group.start; + const count = group.count; + + for ( let j = start, jl = start + count; j < jl; j += 3 ) { + + handleTriangle( + index.getX( j + 0 ), + index.getX( j + 1 ), + index.getX( j + 2 ) + ); + + } + + } + + const tmp = new Vector3(), tmp2 = new Vector3(); + const n = new Vector3(), n2 = new Vector3(); + + function handleVertex( v ) { + + n.fromBufferAttribute( normalAttribute, v ); + n2.copy( n ); + + const t = tan1[ v ]; + + // Gram-Schmidt orthogonalize + + tmp.copy( t ); + tmp.sub( n.multiplyScalar( n.dot( t ) ) ).normalize(); + + // Calculate handedness + + tmp2.crossVectors( n2, t ); + const test = tmp2.dot( tan2[ v ] ); + const w = ( test < 0.0 ) ? - 1.0 : 1.0; + + tangentAttribute.setXYZW( v, tmp.x, tmp.y, tmp.z, w ); + + } + + for ( let i = 0, il = groups.length; i < il; ++ i ) { + + const group = groups[ i ]; + + const start = group.start; + const count = group.count; + + for ( let j = start, jl = start + count; j < jl; j += 3 ) { + + handleVertex( index.getX( j + 0 ) ); + handleVertex( index.getX( j + 1 ) ); + handleVertex( index.getX( j + 2 ) ); + + } + + } + + } + + computeVertexNormals() { + + const index = this.index; + const positionAttribute = this.getAttribute( 'position' ); + + if ( positionAttribute !== undefined ) { + + let normalAttribute = this.getAttribute( 'normal' ); + + if ( normalAttribute === undefined ) { + + normalAttribute = new BufferAttribute( new Float32Array( positionAttribute.count * 3 ), 3 ); + this.setAttribute( 'normal', normalAttribute ); + + } else { + + // reset existing normals to zero + + for ( let i = 0, il = normalAttribute.count; i < il; i ++ ) { + + normalAttribute.setXYZ( i, 0, 0, 0 ); + + } + + } + + const pA = new Vector3(), pB = new Vector3(), pC = new Vector3(); + const nA = new Vector3(), nB = new Vector3(), nC = new Vector3(); + const cb = new Vector3(), ab = new Vector3(); + + // indexed elements + + if ( index ) { + + for ( let i = 0, il = index.count; i < il; i += 3 ) { + + const vA = index.getX( i + 0 ); + const vB = index.getX( i + 1 ); + const vC = index.getX( i + 2 ); + + pA.fromBufferAttribute( positionAttribute, vA ); + pB.fromBufferAttribute( positionAttribute, vB ); + pC.fromBufferAttribute( positionAttribute, vC ); + + cb.subVectors( pC, pB ); + ab.subVectors( pA, pB ); + cb.cross( ab ); + + nA.fromBufferAttribute( normalAttribute, vA ); + nB.fromBufferAttribute( normalAttribute, vB ); + nC.fromBufferAttribute( normalAttribute, vC ); + + nA.add( cb ); + nB.add( cb ); + nC.add( cb ); + + normalAttribute.setXYZ( vA, nA.x, nA.y, nA.z ); + normalAttribute.setXYZ( vB, nB.x, nB.y, nB.z ); + normalAttribute.setXYZ( vC, nC.x, nC.y, nC.z ); + + } + + } else { + + // non-indexed elements (unconnected triangle soup) + + for ( let i = 0, il = positionAttribute.count; i < il; i += 3 ) { + + pA.fromBufferAttribute( positionAttribute, i + 0 ); + pB.fromBufferAttribute( positionAttribute, i + 1 ); + pC.fromBufferAttribute( positionAttribute, i + 2 ); + + cb.subVectors( pC, pB ); + ab.subVectors( pA, pB ); + cb.cross( ab ); + + normalAttribute.setXYZ( i + 0, cb.x, cb.y, cb.z ); + normalAttribute.setXYZ( i + 1, cb.x, cb.y, cb.z ); + normalAttribute.setXYZ( i + 2, cb.x, cb.y, cb.z ); + + } + + } + + this.normalizeNormals(); + + normalAttribute.needsUpdate = true; + + } + + } + + normalizeNormals() { + + const normals = this.attributes.normal; + + for ( let i = 0, il = normals.count; i < il; i ++ ) { + + _vector$8.fromBufferAttribute( normals, i ); + + _vector$8.normalize(); + + normals.setXYZ( i, _vector$8.x, _vector$8.y, _vector$8.z ); + + } + + } + + toNonIndexed() { + + function convertBufferAttribute( attribute, indices ) { + + const array = attribute.array; + const itemSize = attribute.itemSize; + const normalized = attribute.normalized; + + const array2 = new array.constructor( indices.length * itemSize ); + + let index = 0, index2 = 0; + + for ( let i = 0, l = indices.length; i < l; i ++ ) { + + if ( attribute.isInterleavedBufferAttribute ) { + + index = indices[ i ] * attribute.data.stride + attribute.offset; + + } else { + + index = indices[ i ] * itemSize; + + } + + for ( let j = 0; j < itemSize; j ++ ) { + + array2[ index2 ++ ] = array[ index ++ ]; + + } + + } + + return new BufferAttribute( array2, itemSize, normalized ); + + } + + // + + if ( this.index === null ) { + + console.warn( 'THREE.BufferGeometry.toNonIndexed(): BufferGeometry is already non-indexed.' ); + return this; + + } + + const geometry2 = new BufferGeometry(); + + const indices = this.index.array; + const attributes = this.attributes; + + // attributes + + for ( const name in attributes ) { + + const attribute = attributes[ name ]; + + const newAttribute = convertBufferAttribute( attribute, indices ); + + geometry2.setAttribute( name, newAttribute ); + + } + + // morph attributes + + const morphAttributes = this.morphAttributes; + + for ( const name in morphAttributes ) { + + const morphArray = []; + const morphAttribute = morphAttributes[ name ]; // morphAttribute: array of Float32BufferAttributes + + for ( let i = 0, il = morphAttribute.length; i < il; i ++ ) { + + const attribute = morphAttribute[ i ]; + + const newAttribute = convertBufferAttribute( attribute, indices ); + + morphArray.push( newAttribute ); + + } + + geometry2.morphAttributes[ name ] = morphArray; + + } + + geometry2.morphTargetsRelative = this.morphTargetsRelative; + + // groups + + const groups = this.groups; + + for ( let i = 0, l = groups.length; i < l; i ++ ) { + + const group = groups[ i ]; + geometry2.addGroup( group.start, group.count, group.materialIndex ); + + } + + return geometry2; + + } + + toJSON() { + + const data = { + metadata: { + version: 4.6, + type: 'BufferGeometry', + generator: 'BufferGeometry.toJSON' + } + }; + + // standard BufferGeometry serialization + + data.uuid = this.uuid; + data.type = this.type; + if ( this.name !== '' ) data.name = this.name; + if ( Object.keys( this.userData ).length > 0 ) data.userData = this.userData; + + if ( this.parameters !== undefined ) { + + const parameters = this.parameters; + + for ( const key in parameters ) { + + if ( parameters[ key ] !== undefined ) data[ key ] = parameters[ key ]; + + } + + return data; + + } + + // for simplicity the code assumes attributes are not shared across geometries, see #15811 + + data.data = { attributes: {} }; + + const index = this.index; + + if ( index !== null ) { + + data.data.index = { + type: index.array.constructor.name, + array: Array.prototype.slice.call( index.array ) + }; + + } + + const attributes = this.attributes; + + for ( const key in attributes ) { + + const attribute = attributes[ key ]; + + data.data.attributes[ key ] = attribute.toJSON( data.data ); + + } + + const morphAttributes = {}; + let hasMorphAttributes = false; + + for ( const key in this.morphAttributes ) { + + const attributeArray = this.morphAttributes[ key ]; + + const array = []; + + for ( let i = 0, il = attributeArray.length; i < il; i ++ ) { + + const attribute = attributeArray[ i ]; + + array.push( attribute.toJSON( data.data ) ); + + } + + if ( array.length > 0 ) { + + morphAttributes[ key ] = array; + + hasMorphAttributes = true; + + } + + } + + if ( hasMorphAttributes ) { + + data.data.morphAttributes = morphAttributes; + data.data.morphTargetsRelative = this.morphTargetsRelative; + + } + + const groups = this.groups; + + if ( groups.length > 0 ) { + + data.data.groups = JSON.parse( JSON.stringify( groups ) ); + + } + + const boundingSphere = this.boundingSphere; + + if ( boundingSphere !== null ) { + + data.data.boundingSphere = { + center: boundingSphere.center.toArray(), + radius: boundingSphere.radius + }; + + } + + return data; + + } + + clone() { + + return new this.constructor().copy( this ); + + } + + copy( source ) { + + // reset + + this.index = null; + this.attributes = {}; + this.morphAttributes = {}; + this.groups = []; + this.boundingBox = null; + this.boundingSphere = null; + + // used for storing cloned, shared data + + const data = {}; + + // name + + this.name = source.name; + + // index + + const index = source.index; + + if ( index !== null ) { + + this.setIndex( index.clone( data ) ); + + } + + // attributes + + const attributes = source.attributes; + + for ( const name in attributes ) { + + const attribute = attributes[ name ]; + this.setAttribute( name, attribute.clone( data ) ); + + } + + // morph attributes + + const morphAttributes = source.morphAttributes; + + for ( const name in morphAttributes ) { + + const array = []; + const morphAttribute = morphAttributes[ name ]; // morphAttribute: array of Float32BufferAttributes + + for ( let i = 0, l = morphAttribute.length; i < l; i ++ ) { + + array.push( morphAttribute[ i ].clone( data ) ); + + } + + this.morphAttributes[ name ] = array; + + } + + this.morphTargetsRelative = source.morphTargetsRelative; + + // groups + + const groups = source.groups; + + for ( let i = 0, l = groups.length; i < l; i ++ ) { + + const group = groups[ i ]; + this.addGroup( group.start, group.count, group.materialIndex ); + + } + + // bounding box + + const boundingBox = source.boundingBox; + + if ( boundingBox !== null ) { + + this.boundingBox = boundingBox.clone(); + + } + + // bounding sphere + + const boundingSphere = source.boundingSphere; + + if ( boundingSphere !== null ) { + + this.boundingSphere = boundingSphere.clone(); + + } + + // draw range + + this.drawRange.start = source.drawRange.start; + this.drawRange.count = source.drawRange.count; + + // user data + + this.userData = source.userData; + + return this; + + } + + dispose() { + + this.dispatchEvent( { type: 'dispose' } ); + + } + +} + +const _inverseMatrix$3 = /*@__PURE__*/ new Matrix4(); +const _ray$3 = /*@__PURE__*/ new Ray(); +const _sphere$6 = /*@__PURE__*/ new Sphere(); +const _sphereHitAt = /*@__PURE__*/ new Vector3(); + +const _vA$1 = /*@__PURE__*/ new Vector3(); +const _vB$1 = /*@__PURE__*/ new Vector3(); +const _vC$1 = /*@__PURE__*/ new Vector3(); + +const _tempA = /*@__PURE__*/ new Vector3(); +const _morphA = /*@__PURE__*/ new Vector3(); + +const _uvA$1 = /*@__PURE__*/ new Vector2(); +const _uvB$1 = /*@__PURE__*/ new Vector2(); +const _uvC$1 = /*@__PURE__*/ new Vector2(); + +const _normalA = /*@__PURE__*/ new Vector3(); +const _normalB = /*@__PURE__*/ new Vector3(); +const _normalC = /*@__PURE__*/ new Vector3(); + +const _intersectionPoint = /*@__PURE__*/ new Vector3(); +const _intersectionPointWorld = /*@__PURE__*/ new Vector3(); + +class Mesh extends Object3D { + + constructor( geometry = new BufferGeometry(), material = new MeshBasicMaterial() ) { + + super(); + + this.isMesh = true; + + this.type = 'Mesh'; + + this.geometry = geometry; + this.material = material; + + this.updateMorphTargets(); + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + if ( source.morphTargetInfluences !== undefined ) { + + this.morphTargetInfluences = source.morphTargetInfluences.slice(); + + } + + if ( source.morphTargetDictionary !== undefined ) { + + this.morphTargetDictionary = Object.assign( {}, source.morphTargetDictionary ); + + } + + this.material = Array.isArray( source.material ) ? source.material.slice() : source.material; + this.geometry = source.geometry; + + return this; + + } + + updateMorphTargets() { + + const geometry = this.geometry; + + const morphAttributes = geometry.morphAttributes; + const keys = Object.keys( morphAttributes ); + + if ( keys.length > 0 ) { + + const morphAttribute = morphAttributes[ keys[ 0 ] ]; + + if ( morphAttribute !== undefined ) { + + this.morphTargetInfluences = []; + this.morphTargetDictionary = {}; + + for ( let m = 0, ml = morphAttribute.length; m < ml; m ++ ) { + + const name = morphAttribute[ m ].name || String( m ); + + this.morphTargetInfluences.push( 0 ); + this.morphTargetDictionary[ name ] = m; + + } + + } + + } + + } + + getVertexPosition( index, target ) { + + const geometry = this.geometry; + const position = geometry.attributes.position; + const morphPosition = geometry.morphAttributes.position; + const morphTargetsRelative = geometry.morphTargetsRelative; + + target.fromBufferAttribute( position, index ); + + const morphInfluences = this.morphTargetInfluences; + + if ( morphPosition && morphInfluences ) { + + _morphA.set( 0, 0, 0 ); + + for ( let i = 0, il = morphPosition.length; i < il; i ++ ) { + + const influence = morphInfluences[ i ]; + const morphAttribute = morphPosition[ i ]; + + if ( influence === 0 ) continue; + + _tempA.fromBufferAttribute( morphAttribute, index ); + + if ( morphTargetsRelative ) { + + _morphA.addScaledVector( _tempA, influence ); + + } else { + + _morphA.addScaledVector( _tempA.sub( target ), influence ); + + } + + } + + target.add( _morphA ); + + } + + return target; + + } + + raycast( raycaster, intersects ) { + + const geometry = this.geometry; + const material = this.material; + const matrixWorld = this.matrixWorld; + + if ( material === undefined ) return; + + // test with bounding sphere in world space + + if ( geometry.boundingSphere === null ) geometry.computeBoundingSphere(); + + _sphere$6.copy( geometry.boundingSphere ); + _sphere$6.applyMatrix4( matrixWorld ); + + // check distance from ray origin to bounding sphere + + _ray$3.copy( raycaster.ray ).recast( raycaster.near ); + + if ( _sphere$6.containsPoint( _ray$3.origin ) === false ) { + + if ( _ray$3.intersectSphere( _sphere$6, _sphereHitAt ) === null ) return; + + if ( _ray$3.origin.distanceToSquared( _sphereHitAt ) > ( raycaster.far - raycaster.near ) ** 2 ) return; + + } + + // convert ray to local space of mesh + + _inverseMatrix$3.copy( matrixWorld ).invert(); + _ray$3.copy( raycaster.ray ).applyMatrix4( _inverseMatrix$3 ); + + // test with bounding box in local space + + if ( geometry.boundingBox !== null ) { + + if ( _ray$3.intersectsBox( geometry.boundingBox ) === false ) return; + + } + + // test for intersections with geometry + + this._computeIntersections( raycaster, intersects, _ray$3 ); + + } + + _computeIntersections( raycaster, intersects, rayLocalSpace ) { + + let intersection; + + const geometry = this.geometry; + const material = this.material; + + const index = geometry.index; + const position = geometry.attributes.position; + const uv = geometry.attributes.uv; + const uv1 = geometry.attributes.uv1; + const normal = geometry.attributes.normal; + const groups = geometry.groups; + const drawRange = geometry.drawRange; + + if ( index !== null ) { + + // indexed buffer geometry + + if ( Array.isArray( material ) ) { + + for ( let i = 0, il = groups.length; i < il; i ++ ) { + + const group = groups[ i ]; + const groupMaterial = material[ group.materialIndex ]; + + const start = Math.max( group.start, drawRange.start ); + const end = Math.min( index.count, Math.min( ( group.start + group.count ), ( drawRange.start + drawRange.count ) ) ); + + for ( let j = start, jl = end; j < jl; j += 3 ) { + + const a = index.getX( j ); + const b = index.getX( j + 1 ); + const c = index.getX( j + 2 ); + + intersection = checkGeometryIntersection( this, groupMaterial, raycaster, rayLocalSpace, uv, uv1, normal, a, b, c ); + + if ( intersection ) { + + intersection.faceIndex = Math.floor( j / 3 ); // triangle number in indexed buffer semantics + intersection.face.materialIndex = group.materialIndex; + intersects.push( intersection ); + + } + + } + + } + + } else { + + const start = Math.max( 0, drawRange.start ); + const end = Math.min( index.count, ( drawRange.start + drawRange.count ) ); + + for ( let i = start, il = end; i < il; i += 3 ) { + + const a = index.getX( i ); + const b = index.getX( i + 1 ); + const c = index.getX( i + 2 ); + + intersection = checkGeometryIntersection( this, material, raycaster, rayLocalSpace, uv, uv1, normal, a, b, c ); + + if ( intersection ) { + + intersection.faceIndex = Math.floor( i / 3 ); // triangle number in indexed buffer semantics + intersects.push( intersection ); + + } + + } + + } + + } else if ( position !== undefined ) { + + // non-indexed buffer geometry + + if ( Array.isArray( material ) ) { + + for ( let i = 0, il = groups.length; i < il; i ++ ) { + + const group = groups[ i ]; + const groupMaterial = material[ group.materialIndex ]; + + const start = Math.max( group.start, drawRange.start ); + const end = Math.min( position.count, Math.min( ( group.start + group.count ), ( drawRange.start + drawRange.count ) ) ); + + for ( let j = start, jl = end; j < jl; j += 3 ) { + + const a = j; + const b = j + 1; + const c = j + 2; + + intersection = checkGeometryIntersection( this, groupMaterial, raycaster, rayLocalSpace, uv, uv1, normal, a, b, c ); + + if ( intersection ) { + + intersection.faceIndex = Math.floor( j / 3 ); // triangle number in non-indexed buffer semantics + intersection.face.materialIndex = group.materialIndex; + intersects.push( intersection ); + + } + + } + + } + + } else { + + const start = Math.max( 0, drawRange.start ); + const end = Math.min( position.count, ( drawRange.start + drawRange.count ) ); + + for ( let i = start, il = end; i < il; i += 3 ) { + + const a = i; + const b = i + 1; + const c = i + 2; + + intersection = checkGeometryIntersection( this, material, raycaster, rayLocalSpace, uv, uv1, normal, a, b, c ); + + if ( intersection ) { + + intersection.faceIndex = Math.floor( i / 3 ); // triangle number in non-indexed buffer semantics + intersects.push( intersection ); + + } + + } + + } + + } + + } + +} + +function checkIntersection$1( object, material, raycaster, ray, pA, pB, pC, point ) { + + let intersect; + + if ( material.side === BackSide ) { + + intersect = ray.intersectTriangle( pC, pB, pA, true, point ); + + } else { + + intersect = ray.intersectTriangle( pA, pB, pC, ( material.side === FrontSide ), point ); + + } + + if ( intersect === null ) return null; + + _intersectionPointWorld.copy( point ); + _intersectionPointWorld.applyMatrix4( object.matrixWorld ); + + const distance = raycaster.ray.origin.distanceTo( _intersectionPointWorld ); + + if ( distance < raycaster.near || distance > raycaster.far ) return null; + + return { + distance: distance, + point: _intersectionPointWorld.clone(), + object: object + }; + +} + +function checkGeometryIntersection( object, material, raycaster, ray, uv, uv1, normal, a, b, c ) { + + object.getVertexPosition( a, _vA$1 ); + object.getVertexPosition( b, _vB$1 ); + object.getVertexPosition( c, _vC$1 ); + + const intersection = checkIntersection$1( object, material, raycaster, ray, _vA$1, _vB$1, _vC$1, _intersectionPoint ); + + if ( intersection ) { + + if ( uv ) { + + _uvA$1.fromBufferAttribute( uv, a ); + _uvB$1.fromBufferAttribute( uv, b ); + _uvC$1.fromBufferAttribute( uv, c ); + + intersection.uv = Triangle.getInterpolation( _intersectionPoint, _vA$1, _vB$1, _vC$1, _uvA$1, _uvB$1, _uvC$1, new Vector2() ); + + } + + if ( uv1 ) { + + _uvA$1.fromBufferAttribute( uv1, a ); + _uvB$1.fromBufferAttribute( uv1, b ); + _uvC$1.fromBufferAttribute( uv1, c ); + + intersection.uv1 = Triangle.getInterpolation( _intersectionPoint, _vA$1, _vB$1, _vC$1, _uvA$1, _uvB$1, _uvC$1, new Vector2() ); + + } + + if ( normal ) { + + _normalA.fromBufferAttribute( normal, a ); + _normalB.fromBufferAttribute( normal, b ); + _normalC.fromBufferAttribute( normal, c ); + + intersection.normal = Triangle.getInterpolation( _intersectionPoint, _vA$1, _vB$1, _vC$1, _normalA, _normalB, _normalC, new Vector3() ); + + if ( intersection.normal.dot( ray.direction ) > 0 ) { + + intersection.normal.multiplyScalar( - 1 ); + + } + + } + + const face = { + a: a, + b: b, + c: c, + normal: new Vector3(), + materialIndex: 0 + }; + + Triangle.getNormal( _vA$1, _vB$1, _vC$1, face.normal ); + + intersection.face = face; + + } + + return intersection; + +} + +class BoxGeometry extends BufferGeometry { + + constructor( width = 1, height = 1, depth = 1, widthSegments = 1, heightSegments = 1, depthSegments = 1 ) { + + super(); + + this.type = 'BoxGeometry'; + + this.parameters = { + width: width, + height: height, + depth: depth, + widthSegments: widthSegments, + heightSegments: heightSegments, + depthSegments: depthSegments + }; + + const scope = this; + + // segments + + widthSegments = Math.floor( widthSegments ); + heightSegments = Math.floor( heightSegments ); + depthSegments = Math.floor( depthSegments ); + + // buffers + + const indices = []; + const vertices = []; + const normals = []; + const uvs = []; + + // helper variables + + let numberOfVertices = 0; + let groupStart = 0; + + // build each side of the box geometry + + buildPlane( 'z', 'y', 'x', - 1, - 1, depth, height, width, depthSegments, heightSegments, 0 ); // px + buildPlane( 'z', 'y', 'x', 1, - 1, depth, height, - width, depthSegments, heightSegments, 1 ); // nx + buildPlane( 'x', 'z', 'y', 1, 1, width, depth, height, widthSegments, depthSegments, 2 ); // py + buildPlane( 'x', 'z', 'y', 1, - 1, width, depth, - height, widthSegments, depthSegments, 3 ); // ny + buildPlane( 'x', 'y', 'z', 1, - 1, width, height, depth, widthSegments, heightSegments, 4 ); // pz + buildPlane( 'x', 'y', 'z', - 1, - 1, width, height, - depth, widthSegments, heightSegments, 5 ); // nz + + // build geometry + + this.setIndex( indices ); + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + this.setAttribute( 'normal', new Float32BufferAttribute( normals, 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvs, 2 ) ); + + function buildPlane( u, v, w, udir, vdir, width, height, depth, gridX, gridY, materialIndex ) { + + const segmentWidth = width / gridX; + const segmentHeight = height / gridY; + + const widthHalf = width / 2; + const heightHalf = height / 2; + const depthHalf = depth / 2; + + const gridX1 = gridX + 1; + const gridY1 = gridY + 1; + + let vertexCounter = 0; + let groupCount = 0; + + const vector = new Vector3(); + + // generate vertices, normals and uvs + + for ( let iy = 0; iy < gridY1; iy ++ ) { + + const y = iy * segmentHeight - heightHalf; + + for ( let ix = 0; ix < gridX1; ix ++ ) { + + const x = ix * segmentWidth - widthHalf; + + // set values to correct vector component + + vector[ u ] = x * udir; + vector[ v ] = y * vdir; + vector[ w ] = depthHalf; + + // now apply vector to vertex buffer + + vertices.push( vector.x, vector.y, vector.z ); + + // set values to correct vector component + + vector[ u ] = 0; + vector[ v ] = 0; + vector[ w ] = depth > 0 ? 1 : - 1; + + // now apply vector to normal buffer + + normals.push( vector.x, vector.y, vector.z ); + + // uvs + + uvs.push( ix / gridX ); + uvs.push( 1 - ( iy / gridY ) ); + + // counters + + vertexCounter += 1; + + } + + } + + // indices + + // 1. you need three indices to draw a single face + // 2. a single segment consists of two faces + // 3. so we need to generate six (2*3) indices per segment + + for ( let iy = 0; iy < gridY; iy ++ ) { + + for ( let ix = 0; ix < gridX; ix ++ ) { + + const a = numberOfVertices + ix + gridX1 * iy; + const b = numberOfVertices + ix + gridX1 * ( iy + 1 ); + const c = numberOfVertices + ( ix + 1 ) + gridX1 * ( iy + 1 ); + const d = numberOfVertices + ( ix + 1 ) + gridX1 * iy; + + // faces + + indices.push( a, b, d ); + indices.push( b, c, d ); + + // increase counter + + groupCount += 6; + + } + + } + + // add a group to the geometry. this will ensure multi material support + + scope.addGroup( groupStart, groupCount, materialIndex ); + + // calculate new start value for groups + + groupStart += groupCount; + + // update total number of vertices + + numberOfVertices += vertexCounter; + + } + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + static fromJSON( data ) { + + return new BoxGeometry( data.width, data.height, data.depth, data.widthSegments, data.heightSegments, data.depthSegments ); + + } + +} + +/** + * Uniform Utilities + */ + +function cloneUniforms( src ) { + + const dst = {}; + + for ( const u in src ) { + + dst[ u ] = {}; + + for ( const p in src[ u ] ) { + + const property = src[ u ][ p ]; + + if ( property && ( property.isColor || + property.isMatrix3 || property.isMatrix4 || + property.isVector2 || property.isVector3 || property.isVector4 || + property.isTexture || property.isQuaternion ) ) { + + if ( property.isRenderTargetTexture ) { + + console.warn( 'UniformsUtils: Textures of render targets cannot be cloned via cloneUniforms() or mergeUniforms().' ); + dst[ u ][ p ] = null; + + } else { + + dst[ u ][ p ] = property.clone(); + + } + + } else if ( Array.isArray( property ) ) { + + dst[ u ][ p ] = property.slice(); + + } else { + + dst[ u ][ p ] = property; + + } + + } + + } + + return dst; + +} + +function mergeUniforms( uniforms ) { + + const merged = {}; + + for ( let u = 0; u < uniforms.length; u ++ ) { + + const tmp = cloneUniforms( uniforms[ u ] ); + + for ( const p in tmp ) { + + merged[ p ] = tmp[ p ]; + + } + + } + + return merged; + +} + +function cloneUniformsGroups( src ) { + + const dst = []; + + for ( let u = 0; u < src.length; u ++ ) { + + dst.push( src[ u ].clone() ); + + } + + return dst; + +} + +function getUnlitUniformColorSpace( renderer ) { + + const currentRenderTarget = renderer.getRenderTarget(); + + if ( currentRenderTarget === null ) { + + // https://github.com/mrdoob/three.js/pull/23937#issuecomment-1111067398 + return renderer.outputColorSpace; + + } + + // https://github.com/mrdoob/three.js/issues/27868 + if ( currentRenderTarget.isXRRenderTarget === true ) { + + return currentRenderTarget.texture.colorSpace; + + } + + return ColorManagement.workingColorSpace; + +} + +// Legacy + +const UniformsUtils = { clone: cloneUniforms, merge: mergeUniforms }; + +var default_vertex = "void main() {\n\tgl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );\n}"; + +var default_fragment = "void main() {\n\tgl_FragColor = vec4( 1.0, 0.0, 0.0, 1.0 );\n}"; + +class ShaderMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isShaderMaterial = true; + + this.type = 'ShaderMaterial'; + + this.defines = {}; + this.uniforms = {}; + this.uniformsGroups = []; + + this.vertexShader = default_vertex; + this.fragmentShader = default_fragment; + + this.linewidth = 1; + + this.wireframe = false; + this.wireframeLinewidth = 1; + + this.fog = false; // set to use scene fog + this.lights = false; // set to use scene lights + this.clipping = false; // set to use user-defined clipping planes + + this.forceSinglePass = true; + + this.extensions = { + clipCullDistance: false, // set to use vertex shader clipping + multiDraw: false // set to use vertex shader multi_draw / enable gl_DrawID + }; + + // When rendered geometry doesn't include these attributes but the material does, + // use these default values in WebGL. This avoids errors when buffer data is missing. + this.defaultAttributeValues = { + 'color': [ 1, 1, 1 ], + 'uv': [ 0, 0 ], + 'uv1': [ 0, 0 ] + }; + + this.index0AttributeName = undefined; + this.uniformsNeedUpdate = false; + + this.glslVersion = null; + + if ( parameters !== undefined ) { + + this.setValues( parameters ); + + } + + } + + copy( source ) { + + super.copy( source ); + + this.fragmentShader = source.fragmentShader; + this.vertexShader = source.vertexShader; + + this.uniforms = cloneUniforms( source.uniforms ); + this.uniformsGroups = cloneUniformsGroups( source.uniformsGroups ); + + this.defines = Object.assign( {}, source.defines ); + + this.wireframe = source.wireframe; + this.wireframeLinewidth = source.wireframeLinewidth; + + this.fog = source.fog; + this.lights = source.lights; + this.clipping = source.clipping; + + this.extensions = Object.assign( {}, source.extensions ); + + this.glslVersion = source.glslVersion; + + return this; + + } + + toJSON( meta ) { + + const data = super.toJSON( meta ); + + data.glslVersion = this.glslVersion; + data.uniforms = {}; + + for ( const name in this.uniforms ) { + + const uniform = this.uniforms[ name ]; + const value = uniform.value; + + if ( value && value.isTexture ) { + + data.uniforms[ name ] = { + type: 't', + value: value.toJSON( meta ).uuid + }; + + } else if ( value && value.isColor ) { + + data.uniforms[ name ] = { + type: 'c', + value: value.getHex() + }; + + } else if ( value && value.isVector2 ) { + + data.uniforms[ name ] = { + type: 'v2', + value: value.toArray() + }; + + } else if ( value && value.isVector3 ) { + + data.uniforms[ name ] = { + type: 'v3', + value: value.toArray() + }; + + } else if ( value && value.isVector4 ) { + + data.uniforms[ name ] = { + type: 'v4', + value: value.toArray() + }; + + } else if ( value && value.isMatrix3 ) { + + data.uniforms[ name ] = { + type: 'm3', + value: value.toArray() + }; + + } else if ( value && value.isMatrix4 ) { + + data.uniforms[ name ] = { + type: 'm4', + value: value.toArray() + }; + + } else { + + data.uniforms[ name ] = { + value: value + }; + + // note: the array variants v2v, v3v, v4v, m4v and tv are not supported so far + + } + + } + + if ( Object.keys( this.defines ).length > 0 ) data.defines = this.defines; + + data.vertexShader = this.vertexShader; + data.fragmentShader = this.fragmentShader; + + data.lights = this.lights; + data.clipping = this.clipping; + + const extensions = {}; + + for ( const key in this.extensions ) { + + if ( this.extensions[ key ] === true ) extensions[ key ] = true; + + } + + if ( Object.keys( extensions ).length > 0 ) data.extensions = extensions; + + return data; + + } + +} + +class Camera extends Object3D { + + constructor() { + + super(); + + this.isCamera = true; + + this.type = 'Camera'; + + this.matrixWorldInverse = new Matrix4(); + + this.projectionMatrix = new Matrix4(); + this.projectionMatrixInverse = new Matrix4(); + + this.coordinateSystem = WebGLCoordinateSystem; + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + this.matrixWorldInverse.copy( source.matrixWorldInverse ); + + this.projectionMatrix.copy( source.projectionMatrix ); + this.projectionMatrixInverse.copy( source.projectionMatrixInverse ); + + this.coordinateSystem = source.coordinateSystem; + + return this; + + } + + getWorldDirection( target ) { + + return super.getWorldDirection( target ).negate(); + + } + + updateMatrixWorld( force ) { + + super.updateMatrixWorld( force ); + + this.matrixWorldInverse.copy( this.matrixWorld ).invert(); + + } + + updateWorldMatrix( updateParents, updateChildren ) { + + super.updateWorldMatrix( updateParents, updateChildren ); + + this.matrixWorldInverse.copy( this.matrixWorld ).invert(); + + } + + clone() { + + return new this.constructor().copy( this ); + + } + +} + +const _v3$1 = /*@__PURE__*/ new Vector3(); +const _minTarget = /*@__PURE__*/ new Vector2(); +const _maxTarget = /*@__PURE__*/ new Vector2(); + + +class PerspectiveCamera extends Camera { + + constructor( fov = 50, aspect = 1, near = 0.1, far = 2000 ) { + + super(); + + this.isPerspectiveCamera = true; + + this.type = 'PerspectiveCamera'; + + this.fov = fov; + this.zoom = 1; + + this.near = near; + this.far = far; + this.focus = 10; + + this.aspect = aspect; + this.view = null; + + this.filmGauge = 35; // width of the film (default in millimeters) + this.filmOffset = 0; // horizontal film offset (same unit as gauge) + + this.updateProjectionMatrix(); + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + this.fov = source.fov; + this.zoom = source.zoom; + + this.near = source.near; + this.far = source.far; + this.focus = source.focus; + + this.aspect = source.aspect; + this.view = source.view === null ? null : Object.assign( {}, source.view ); + + this.filmGauge = source.filmGauge; + this.filmOffset = source.filmOffset; + + return this; + + } + + /** + * Sets the FOV by focal length in respect to the current .filmGauge. + * + * The default film gauge is 35, so that the focal length can be specified for + * a 35mm (full frame) camera. + * + * Values for focal length and film gauge must have the same unit. + */ + setFocalLength( focalLength ) { + + /** see {@link http://www.bobatkins.com/photography/technical/field_of_view.html} */ + const vExtentSlope = 0.5 * this.getFilmHeight() / focalLength; + + this.fov = RAD2DEG * 2 * Math.atan( vExtentSlope ); + this.updateProjectionMatrix(); + + } + + /** + * Calculates the focal length from the current .fov and .filmGauge. + */ + getFocalLength() { + + const vExtentSlope = Math.tan( DEG2RAD * 0.5 * this.fov ); + + return 0.5 * this.getFilmHeight() / vExtentSlope; + + } + + getEffectiveFOV() { + + return RAD2DEG * 2 * Math.atan( + Math.tan( DEG2RAD * 0.5 * this.fov ) / this.zoom ); + + } + + getFilmWidth() { + + // film not completely covered in portrait format (aspect < 1) + return this.filmGauge * Math.min( this.aspect, 1 ); + + } + + getFilmHeight() { + + // film not completely covered in landscape format (aspect > 1) + return this.filmGauge / Math.max( this.aspect, 1 ); + + } + + /** + * Computes the 2D bounds of the camera's viewable rectangle at a given distance along the viewing direction. + * Sets minTarget and maxTarget to the coordinates of the lower-left and upper-right corners of the view rectangle. + */ + getViewBounds( distance, minTarget, maxTarget ) { + + _v3$1.set( - 1, - 1, 0.5 ).applyMatrix4( this.projectionMatrixInverse ); + + minTarget.set( _v3$1.x, _v3$1.y ).multiplyScalar( - distance / _v3$1.z ); + + _v3$1.set( 1, 1, 0.5 ).applyMatrix4( this.projectionMatrixInverse ); + + maxTarget.set( _v3$1.x, _v3$1.y ).multiplyScalar( - distance / _v3$1.z ); + + } + + /** + * Computes the width and height of the camera's viewable rectangle at a given distance along the viewing direction. + * Copies the result into the target Vector2, where x is width and y is height. + */ + getViewSize( distance, target ) { + + this.getViewBounds( distance, _minTarget, _maxTarget ); + + return target.subVectors( _maxTarget, _minTarget ); + + } + + /** + * Sets an offset in a larger frustum. This is useful for multi-window or + * multi-monitor/multi-machine setups. + * + * For example, if you have 3x2 monitors and each monitor is 1920x1080 and + * the monitors are in grid like this + * + * +---+---+---+ + * | A | B | C | + * +---+---+---+ + * | D | E | F | + * +---+---+---+ + * + * then for each monitor you would call it like this + * + * const w = 1920; + * const h = 1080; + * const fullWidth = w * 3; + * const fullHeight = h * 2; + * + * --A-- + * camera.setViewOffset( fullWidth, fullHeight, w * 0, h * 0, w, h ); + * --B-- + * camera.setViewOffset( fullWidth, fullHeight, w * 1, h * 0, w, h ); + * --C-- + * camera.setViewOffset( fullWidth, fullHeight, w * 2, h * 0, w, h ); + * --D-- + * camera.setViewOffset( fullWidth, fullHeight, w * 0, h * 1, w, h ); + * --E-- + * camera.setViewOffset( fullWidth, fullHeight, w * 1, h * 1, w, h ); + * --F-- + * camera.setViewOffset( fullWidth, fullHeight, w * 2, h * 1, w, h ); + * + * Note there is no reason monitors have to be the same size or in a grid. + */ + setViewOffset( fullWidth, fullHeight, x, y, width, height ) { + + this.aspect = fullWidth / fullHeight; + + if ( this.view === null ) { + + this.view = { + enabled: true, + fullWidth: 1, + fullHeight: 1, + offsetX: 0, + offsetY: 0, + width: 1, + height: 1 + }; + + } + + this.view.enabled = true; + this.view.fullWidth = fullWidth; + this.view.fullHeight = fullHeight; + this.view.offsetX = x; + this.view.offsetY = y; + this.view.width = width; + this.view.height = height; + + this.updateProjectionMatrix(); + + } + + clearViewOffset() { + + if ( this.view !== null ) { + + this.view.enabled = false; + + } + + this.updateProjectionMatrix(); + + } + + updateProjectionMatrix() { + + const near = this.near; + let top = near * Math.tan( DEG2RAD * 0.5 * this.fov ) / this.zoom; + let height = 2 * top; + let width = this.aspect * height; + let left = - 0.5 * width; + const view = this.view; + + if ( this.view !== null && this.view.enabled ) { + + const fullWidth = view.fullWidth, + fullHeight = view.fullHeight; + + left += view.offsetX * width / fullWidth; + top -= view.offsetY * height / fullHeight; + width *= view.width / fullWidth; + height *= view.height / fullHeight; + + } + + const skew = this.filmOffset; + if ( skew !== 0 ) left += near * skew / this.getFilmWidth(); + + this.projectionMatrix.makePerspective( left, left + width, top, top - height, near, this.far, this.coordinateSystem ); + + this.projectionMatrixInverse.copy( this.projectionMatrix ).invert(); + + } + + toJSON( meta ) { + + const data = super.toJSON( meta ); + + data.object.fov = this.fov; + data.object.zoom = this.zoom; + + data.object.near = this.near; + data.object.far = this.far; + data.object.focus = this.focus; + + data.object.aspect = this.aspect; + + if ( this.view !== null ) data.object.view = Object.assign( {}, this.view ); + + data.object.filmGauge = this.filmGauge; + data.object.filmOffset = this.filmOffset; + + return data; + + } + +} + +const fov = - 90; // negative fov is not an error +const aspect = 1; + +class CubeCamera extends Object3D { + + constructor( near, far, renderTarget ) { + + super(); + + this.type = 'CubeCamera'; + + this.renderTarget = renderTarget; + this.coordinateSystem = null; + this.activeMipmapLevel = 0; + + const cameraPX = new PerspectiveCamera( fov, aspect, near, far ); + cameraPX.layers = this.layers; + this.add( cameraPX ); + + const cameraNX = new PerspectiveCamera( fov, aspect, near, far ); + cameraNX.layers = this.layers; + this.add( cameraNX ); + + const cameraPY = new PerspectiveCamera( fov, aspect, near, far ); + cameraPY.layers = this.layers; + this.add( cameraPY ); + + const cameraNY = new PerspectiveCamera( fov, aspect, near, far ); + cameraNY.layers = this.layers; + this.add( cameraNY ); + + const cameraPZ = new PerspectiveCamera( fov, aspect, near, far ); + cameraPZ.layers = this.layers; + this.add( cameraPZ ); + + const cameraNZ = new PerspectiveCamera( fov, aspect, near, far ); + cameraNZ.layers = this.layers; + this.add( cameraNZ ); + + } + + updateCoordinateSystem() { + + const coordinateSystem = this.coordinateSystem; + + const cameras = this.children.concat(); + + const [ cameraPX, cameraNX, cameraPY, cameraNY, cameraPZ, cameraNZ ] = cameras; + + for ( const camera of cameras ) this.remove( camera ); + + if ( coordinateSystem === WebGLCoordinateSystem ) { + + cameraPX.up.set( 0, 1, 0 ); + cameraPX.lookAt( 1, 0, 0 ); + + cameraNX.up.set( 0, 1, 0 ); + cameraNX.lookAt( - 1, 0, 0 ); + + cameraPY.up.set( 0, 0, - 1 ); + cameraPY.lookAt( 0, 1, 0 ); + + cameraNY.up.set( 0, 0, 1 ); + cameraNY.lookAt( 0, - 1, 0 ); + + cameraPZ.up.set( 0, 1, 0 ); + cameraPZ.lookAt( 0, 0, 1 ); + + cameraNZ.up.set( 0, 1, 0 ); + cameraNZ.lookAt( 0, 0, - 1 ); + + } else if ( coordinateSystem === WebGPUCoordinateSystem ) { + + cameraPX.up.set( 0, - 1, 0 ); + cameraPX.lookAt( - 1, 0, 0 ); + + cameraNX.up.set( 0, - 1, 0 ); + cameraNX.lookAt( 1, 0, 0 ); + + cameraPY.up.set( 0, 0, 1 ); + cameraPY.lookAt( 0, 1, 0 ); + + cameraNY.up.set( 0, 0, - 1 ); + cameraNY.lookAt( 0, - 1, 0 ); + + cameraPZ.up.set( 0, - 1, 0 ); + cameraPZ.lookAt( 0, 0, 1 ); + + cameraNZ.up.set( 0, - 1, 0 ); + cameraNZ.lookAt( 0, 0, - 1 ); + + } else { + + throw new Error( 'THREE.CubeCamera.updateCoordinateSystem(): Invalid coordinate system: ' + coordinateSystem ); + + } + + for ( const camera of cameras ) { + + this.add( camera ); + + camera.updateMatrixWorld(); + + } + + } + + update( renderer, scene ) { + + if ( this.parent === null ) this.updateMatrixWorld(); + + const { renderTarget, activeMipmapLevel } = this; + + if ( this.coordinateSystem !== renderer.coordinateSystem ) { + + this.coordinateSystem = renderer.coordinateSystem; + + this.updateCoordinateSystem(); + + } + + const [ cameraPX, cameraNX, cameraPY, cameraNY, cameraPZ, cameraNZ ] = this.children; + + const currentRenderTarget = renderer.getRenderTarget(); + const currentActiveCubeFace = renderer.getActiveCubeFace(); + const currentActiveMipmapLevel = renderer.getActiveMipmapLevel(); + + const currentXrEnabled = renderer.xr.enabled; + + renderer.xr.enabled = false; + + const generateMipmaps = renderTarget.texture.generateMipmaps; + + renderTarget.texture.generateMipmaps = false; + + renderer.setRenderTarget( renderTarget, 0, activeMipmapLevel ); + renderer.render( scene, cameraPX ); + + renderer.setRenderTarget( renderTarget, 1, activeMipmapLevel ); + renderer.render( scene, cameraNX ); + + renderer.setRenderTarget( renderTarget, 2, activeMipmapLevel ); + renderer.render( scene, cameraPY ); + + renderer.setRenderTarget( renderTarget, 3, activeMipmapLevel ); + renderer.render( scene, cameraNY ); + + renderer.setRenderTarget( renderTarget, 4, activeMipmapLevel ); + renderer.render( scene, cameraPZ ); + + // mipmaps are generated during the last call of render() + // at this point, all sides of the cube render target are defined + + renderTarget.texture.generateMipmaps = generateMipmaps; + + renderer.setRenderTarget( renderTarget, 5, activeMipmapLevel ); + renderer.render( scene, cameraNZ ); + + renderer.setRenderTarget( currentRenderTarget, currentActiveCubeFace, currentActiveMipmapLevel ); + + renderer.xr.enabled = currentXrEnabled; + + renderTarget.texture.needsPMREMUpdate = true; + + } + +} + +class CubeTexture extends Texture { + + constructor( images, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy, colorSpace ) { + + images = images !== undefined ? images : []; + mapping = mapping !== undefined ? mapping : CubeReflectionMapping; + + super( images, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy, colorSpace ); + + this.isCubeTexture = true; + + this.flipY = false; + + } + + get images() { + + return this.image; + + } + + set images( value ) { + + this.image = value; + + } + +} + +class WebGLCubeRenderTarget extends WebGLRenderTarget { + + constructor( size = 1, options = {} ) { + + super( size, size, options ); + + this.isWebGLCubeRenderTarget = true; + + const image = { width: size, height: size, depth: 1 }; + const images = [ image, image, image, image, image, image ]; + + this.texture = new CubeTexture( images, options.mapping, options.wrapS, options.wrapT, options.magFilter, options.minFilter, options.format, options.type, options.anisotropy, options.colorSpace ); + + // By convention -- likely based on the RenderMan spec from the 1990's -- cube maps are specified by WebGL (and three.js) + // in a coordinate system in which positive-x is to the right when looking up the positive-z axis -- in other words, + // in a left-handed coordinate system. By continuing this convention, preexisting cube maps continued to render correctly. + + // three.js uses a right-handed coordinate system. So environment maps used in three.js appear to have px and nx swapped + // and the flag isRenderTargetTexture controls this conversion. The flip is not required when using WebGLCubeRenderTarget.texture + // as a cube texture (this is detected when isRenderTargetTexture is set to true for cube textures). + + this.texture.isRenderTargetTexture = true; + + this.texture.generateMipmaps = options.generateMipmaps !== undefined ? options.generateMipmaps : false; + this.texture.minFilter = options.minFilter !== undefined ? options.minFilter : LinearFilter; + + } + + fromEquirectangularTexture( renderer, texture ) { + + this.texture.type = texture.type; + this.texture.colorSpace = texture.colorSpace; + + this.texture.generateMipmaps = texture.generateMipmaps; + this.texture.minFilter = texture.minFilter; + this.texture.magFilter = texture.magFilter; + + const shader = { + + uniforms: { + tEquirect: { value: null }, + }, + + vertexShader: /* glsl */` + + varying vec3 vWorldDirection; + + vec3 transformDirection( in vec3 dir, in mat4 matrix ) { + + return normalize( ( matrix * vec4( dir, 0.0 ) ).xyz ); + + } + + void main() { + + vWorldDirection = transformDirection( position, modelMatrix ); + + #include + #include + + } + `, + + fragmentShader: /* glsl */` + + uniform sampler2D tEquirect; + + varying vec3 vWorldDirection; + + #include + + void main() { + + vec3 direction = normalize( vWorldDirection ); + + vec2 sampleUV = equirectUv( direction ); + + gl_FragColor = texture2D( tEquirect, sampleUV ); + + } + ` + }; + + const geometry = new BoxGeometry( 5, 5, 5 ); + + const material = new ShaderMaterial( { + + name: 'CubemapFromEquirect', + + uniforms: cloneUniforms( shader.uniforms ), + vertexShader: shader.vertexShader, + fragmentShader: shader.fragmentShader, + side: BackSide, + blending: NoBlending + + } ); + + material.uniforms.tEquirect.value = texture; + + const mesh = new Mesh( geometry, material ); + + const currentMinFilter = texture.minFilter; + + // Avoid blurred poles + if ( texture.minFilter === LinearMipmapLinearFilter ) texture.minFilter = LinearFilter; + + const camera = new CubeCamera( 1, 10, this ); + camera.update( renderer, mesh ); + + texture.minFilter = currentMinFilter; + + mesh.geometry.dispose(); + mesh.material.dispose(); + + return this; + + } + + clear( renderer, color, depth, stencil ) { + + const currentRenderTarget = renderer.getRenderTarget(); + + for ( let i = 0; i < 6; i ++ ) { + + renderer.setRenderTarget( this, i ); + + renderer.clear( color, depth, stencil ); + + } + + renderer.setRenderTarget( currentRenderTarget ); + + } + +} + +const _vector1 = /*@__PURE__*/ new Vector3(); +const _vector2 = /*@__PURE__*/ new Vector3(); +const _normalMatrix = /*@__PURE__*/ new Matrix3(); + +class Plane { + + constructor( normal = new Vector3( 1, 0, 0 ), constant = 0 ) { + + this.isPlane = true; + + // normal is assumed to be normalized + + this.normal = normal; + this.constant = constant; + + } + + set( normal, constant ) { + + this.normal.copy( normal ); + this.constant = constant; + + return this; + + } + + setComponents( x, y, z, w ) { + + this.normal.set( x, y, z ); + this.constant = w; + + return this; + + } + + setFromNormalAndCoplanarPoint( normal, point ) { + + this.normal.copy( normal ); + this.constant = - point.dot( this.normal ); + + return this; + + } + + setFromCoplanarPoints( a, b, c ) { + + const normal = _vector1.subVectors( c, b ).cross( _vector2.subVectors( a, b ) ).normalize(); + + // Q: should an error be thrown if normal is zero (e.g. degenerate plane)? + + this.setFromNormalAndCoplanarPoint( normal, a ); + + return this; + + } + + copy( plane ) { + + this.normal.copy( plane.normal ); + this.constant = plane.constant; + + return this; + + } + + normalize() { + + // Note: will lead to a divide by zero if the plane is invalid. + + const inverseNormalLength = 1.0 / this.normal.length(); + this.normal.multiplyScalar( inverseNormalLength ); + this.constant *= inverseNormalLength; + + return this; + + } + + negate() { + + this.constant *= - 1; + this.normal.negate(); + + return this; + + } + + distanceToPoint( point ) { + + return this.normal.dot( point ) + this.constant; + + } + + distanceToSphere( sphere ) { + + return this.distanceToPoint( sphere.center ) - sphere.radius; + + } + + projectPoint( point, target ) { + + return target.copy( point ).addScaledVector( this.normal, - this.distanceToPoint( point ) ); + + } + + intersectLine( line, target ) { + + const direction = line.delta( _vector1 ); + + const denominator = this.normal.dot( direction ); + + if ( denominator === 0 ) { + + // line is coplanar, return origin + if ( this.distanceToPoint( line.start ) === 0 ) { + + return target.copy( line.start ); + + } + + // Unsure if this is the correct method to handle this case. + return null; + + } + + const t = - ( line.start.dot( this.normal ) + this.constant ) / denominator; + + if ( t < 0 || t > 1 ) { + + return null; + + } + + return target.copy( line.start ).addScaledVector( direction, t ); + + } + + intersectsLine( line ) { + + // Note: this tests if a line intersects the plane, not whether it (or its end-points) are coplanar with it. + + const startSign = this.distanceToPoint( line.start ); + const endSign = this.distanceToPoint( line.end ); + + return ( startSign < 0 && endSign > 0 ) || ( endSign < 0 && startSign > 0 ); + + } + + intersectsBox( box ) { + + return box.intersectsPlane( this ); + + } + + intersectsSphere( sphere ) { + + return sphere.intersectsPlane( this ); + + } + + coplanarPoint( target ) { + + return target.copy( this.normal ).multiplyScalar( - this.constant ); + + } + + applyMatrix4( matrix, optionalNormalMatrix ) { + + const normalMatrix = optionalNormalMatrix || _normalMatrix.getNormalMatrix( matrix ); + + const referencePoint = this.coplanarPoint( _vector1 ).applyMatrix4( matrix ); + + const normal = this.normal.applyMatrix3( normalMatrix ).normalize(); + + this.constant = - referencePoint.dot( normal ); + + return this; + + } + + translate( offset ) { + + this.constant -= offset.dot( this.normal ); + + return this; + + } + + equals( plane ) { + + return plane.normal.equals( this.normal ) && ( plane.constant === this.constant ); + + } + + clone() { + + return new this.constructor().copy( this ); + + } + +} + +const _sphere$5 = /*@__PURE__*/ new Sphere(); +const _vector$7 = /*@__PURE__*/ new Vector3(); + +class Frustum { + + constructor( p0 = new Plane(), p1 = new Plane(), p2 = new Plane(), p3 = new Plane(), p4 = new Plane(), p5 = new Plane() ) { + + this.planes = [ p0, p1, p2, p3, p4, p5 ]; + + } + + set( p0, p1, p2, p3, p4, p5 ) { + + const planes = this.planes; + + planes[ 0 ].copy( p0 ); + planes[ 1 ].copy( p1 ); + planes[ 2 ].copy( p2 ); + planes[ 3 ].copy( p3 ); + planes[ 4 ].copy( p4 ); + planes[ 5 ].copy( p5 ); + + return this; + + } + + copy( frustum ) { + + const planes = this.planes; + + for ( let i = 0; i < 6; i ++ ) { + + planes[ i ].copy( frustum.planes[ i ] ); + + } + + return this; + + } + + setFromProjectionMatrix( m, coordinateSystem = WebGLCoordinateSystem ) { + + const planes = this.planes; + const me = m.elements; + const me0 = me[ 0 ], me1 = me[ 1 ], me2 = me[ 2 ], me3 = me[ 3 ]; + const me4 = me[ 4 ], me5 = me[ 5 ], me6 = me[ 6 ], me7 = me[ 7 ]; + const me8 = me[ 8 ], me9 = me[ 9 ], me10 = me[ 10 ], me11 = me[ 11 ]; + const me12 = me[ 12 ], me13 = me[ 13 ], me14 = me[ 14 ], me15 = me[ 15 ]; + + planes[ 0 ].setComponents( me3 - me0, me7 - me4, me11 - me8, me15 - me12 ).normalize(); + planes[ 1 ].setComponents( me3 + me0, me7 + me4, me11 + me8, me15 + me12 ).normalize(); + planes[ 2 ].setComponents( me3 + me1, me7 + me5, me11 + me9, me15 + me13 ).normalize(); + planes[ 3 ].setComponents( me3 - me1, me7 - me5, me11 - me9, me15 - me13 ).normalize(); + planes[ 4 ].setComponents( me3 - me2, me7 - me6, me11 - me10, me15 - me14 ).normalize(); + + if ( coordinateSystem === WebGLCoordinateSystem ) { + + planes[ 5 ].setComponents( me3 + me2, me7 + me6, me11 + me10, me15 + me14 ).normalize(); + + } else if ( coordinateSystem === WebGPUCoordinateSystem ) { + + planes[ 5 ].setComponents( me2, me6, me10, me14 ).normalize(); + + } else { + + throw new Error( 'THREE.Frustum.setFromProjectionMatrix(): Invalid coordinate system: ' + coordinateSystem ); + + } + + return this; + + } + + intersectsObject( object ) { + + if ( object.boundingSphere !== undefined ) { + + if ( object.boundingSphere === null ) object.computeBoundingSphere(); + + _sphere$5.copy( object.boundingSphere ).applyMatrix4( object.matrixWorld ); + + } else { + + const geometry = object.geometry; + + if ( geometry.boundingSphere === null ) geometry.computeBoundingSphere(); + + _sphere$5.copy( geometry.boundingSphere ).applyMatrix4( object.matrixWorld ); + + } + + return this.intersectsSphere( _sphere$5 ); + + } + + intersectsSprite( sprite ) { + + _sphere$5.center.set( 0, 0, 0 ); + _sphere$5.radius = 0.7071067811865476; + _sphere$5.applyMatrix4( sprite.matrixWorld ); + + return this.intersectsSphere( _sphere$5 ); + + } + + intersectsSphere( sphere ) { + + const planes = this.planes; + const center = sphere.center; + const negRadius = - sphere.radius; + + for ( let i = 0; i < 6; i ++ ) { + + const distance = planes[ i ].distanceToPoint( center ); + + if ( distance < negRadius ) { + + return false; + + } + + } + + return true; + + } + + intersectsBox( box ) { + + const planes = this.planes; + + for ( let i = 0; i < 6; i ++ ) { + + const plane = planes[ i ]; + + // corner at max distance + + _vector$7.x = plane.normal.x > 0 ? box.max.x : box.min.x; + _vector$7.y = plane.normal.y > 0 ? box.max.y : box.min.y; + _vector$7.z = plane.normal.z > 0 ? box.max.z : box.min.z; + + if ( plane.distanceToPoint( _vector$7 ) < 0 ) { + + return false; + + } + + } + + return true; + + } + + containsPoint( point ) { + + const planes = this.planes; + + for ( let i = 0; i < 6; i ++ ) { + + if ( planes[ i ].distanceToPoint( point ) < 0 ) { + + return false; + + } + + } + + return true; + + } + + clone() { + + return new this.constructor().copy( this ); + + } + +} + +function WebGLAnimation() { + + let context = null; + let isAnimating = false; + let animationLoop = null; + let requestId = null; + + function onAnimationFrame( time, frame ) { + + animationLoop( time, frame ); + + requestId = context.requestAnimationFrame( onAnimationFrame ); + + } + + return { + + start: function () { + + if ( isAnimating === true ) return; + if ( animationLoop === null ) return; + + requestId = context.requestAnimationFrame( onAnimationFrame ); + + isAnimating = true; + + }, + + stop: function () { + + context.cancelAnimationFrame( requestId ); + + isAnimating = false; + + }, + + setAnimationLoop: function ( callback ) { + + animationLoop = callback; + + }, + + setContext: function ( value ) { + + context = value; + + } + + }; + +} + +function WebGLAttributes( gl ) { + + const buffers = new WeakMap(); + + function createBuffer( attribute, bufferType ) { + + const array = attribute.array; + const usage = attribute.usage; + const size = array.byteLength; + + const buffer = gl.createBuffer(); + + gl.bindBuffer( bufferType, buffer ); + gl.bufferData( bufferType, array, usage ); + + attribute.onUploadCallback(); + + let type; + + if ( array instanceof Float32Array ) { + + type = gl.FLOAT; + + } else if ( array instanceof Uint16Array ) { + + if ( attribute.isFloat16BufferAttribute ) { + + type = gl.HALF_FLOAT; + + } else { + + type = gl.UNSIGNED_SHORT; + + } + + } else if ( array instanceof Int16Array ) { + + type = gl.SHORT; + + } else if ( array instanceof Uint32Array ) { + + type = gl.UNSIGNED_INT; + + } else if ( array instanceof Int32Array ) { + + type = gl.INT; + + } else if ( array instanceof Int8Array ) { + + type = gl.BYTE; + + } else if ( array instanceof Uint8Array ) { + + type = gl.UNSIGNED_BYTE; + + } else if ( array instanceof Uint8ClampedArray ) { + + type = gl.UNSIGNED_BYTE; + + } else { + + throw new Error( 'THREE.WebGLAttributes: Unsupported buffer data format: ' + array ); + + } + + return { + buffer: buffer, + type: type, + bytesPerElement: array.BYTES_PER_ELEMENT, + version: attribute.version, + size: size + }; + + } + + function updateBuffer( buffer, attribute, bufferType ) { + + const array = attribute.array; + const updateRange = attribute._updateRange; // @deprecated, r159 + const updateRanges = attribute.updateRanges; + + gl.bindBuffer( bufferType, buffer ); + + if ( updateRange.count === - 1 && updateRanges.length === 0 ) { + + // Not using update ranges + gl.bufferSubData( bufferType, 0, array ); + + } + + if ( updateRanges.length !== 0 ) { + + for ( let i = 0, l = updateRanges.length; i < l; i ++ ) { + + const range = updateRanges[ i ]; + + gl.bufferSubData( bufferType, range.start * array.BYTES_PER_ELEMENT, + array, range.start, range.count ); + + } + + attribute.clearUpdateRanges(); + + } + + // @deprecated, r159 + if ( updateRange.count !== - 1 ) { + + gl.bufferSubData( bufferType, updateRange.offset * array.BYTES_PER_ELEMENT, + array, updateRange.offset, updateRange.count ); + + updateRange.count = - 1; // reset range + + } + + attribute.onUploadCallback(); + + } + + // + + function get( attribute ) { + + if ( attribute.isInterleavedBufferAttribute ) attribute = attribute.data; + + return buffers.get( attribute ); + + } + + function remove( attribute ) { + + if ( attribute.isInterleavedBufferAttribute ) attribute = attribute.data; + + const data = buffers.get( attribute ); + + if ( data ) { + + gl.deleteBuffer( data.buffer ); + + buffers.delete( attribute ); + + } + + } + + function update( attribute, bufferType ) { + + if ( attribute.isGLBufferAttribute ) { + + const cached = buffers.get( attribute ); + + if ( ! cached || cached.version < attribute.version ) { + + buffers.set( attribute, { + buffer: attribute.buffer, + type: attribute.type, + bytesPerElement: attribute.elementSize, + version: attribute.version + } ); + + } + + return; + + } + + if ( attribute.isInterleavedBufferAttribute ) attribute = attribute.data; + + const data = buffers.get( attribute ); + + if ( data === undefined ) { + + buffers.set( attribute, createBuffer( attribute, bufferType ) ); + + } else if ( data.version < attribute.version ) { + + if ( data.size !== attribute.array.byteLength ) { + + throw new Error( 'THREE.WebGLAttributes: The size of the buffer attribute\'s array buffer does not match the original size. Resizing buffer attributes is not supported.' ); + + } + + updateBuffer( data.buffer, attribute, bufferType ); + + data.version = attribute.version; + + } + + } + + return { + + get: get, + remove: remove, + update: update + + }; + +} + +class PlaneGeometry extends BufferGeometry { + + constructor( width = 1, height = 1, widthSegments = 1, heightSegments = 1 ) { + + super(); + + this.type = 'PlaneGeometry'; + + this.parameters = { + width: width, + height: height, + widthSegments: widthSegments, + heightSegments: heightSegments + }; + + const width_half = width / 2; + const height_half = height / 2; + + const gridX = Math.floor( widthSegments ); + const gridY = Math.floor( heightSegments ); + + const gridX1 = gridX + 1; + const gridY1 = gridY + 1; + + const segment_width = width / gridX; + const segment_height = height / gridY; + + // + + const indices = []; + const vertices = []; + const normals = []; + const uvs = []; + + for ( let iy = 0; iy < gridY1; iy ++ ) { + + const y = iy * segment_height - height_half; + + for ( let ix = 0; ix < gridX1; ix ++ ) { + + const x = ix * segment_width - width_half; + + vertices.push( x, - y, 0 ); + + normals.push( 0, 0, 1 ); + + uvs.push( ix / gridX ); + uvs.push( 1 - ( iy / gridY ) ); + + } + + } + + for ( let iy = 0; iy < gridY; iy ++ ) { + + for ( let ix = 0; ix < gridX; ix ++ ) { + + const a = ix + gridX1 * iy; + const b = ix + gridX1 * ( iy + 1 ); + const c = ( ix + 1 ) + gridX1 * ( iy + 1 ); + const d = ( ix + 1 ) + gridX1 * iy; + + indices.push( a, b, d ); + indices.push( b, c, d ); + + } + + } + + this.setIndex( indices ); + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + this.setAttribute( 'normal', new Float32BufferAttribute( normals, 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvs, 2 ) ); + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + static fromJSON( data ) { + + return new PlaneGeometry( data.width, data.height, data.widthSegments, data.heightSegments ); + + } + +} + +var alphahash_fragment = "#ifdef USE_ALPHAHASH\n\tif ( diffuseColor.a < getAlphaHashThreshold( vPosition ) ) discard;\n#endif"; + +var alphahash_pars_fragment = "#ifdef USE_ALPHAHASH\n\tconst float ALPHA_HASH_SCALE = 0.05;\n\tfloat hash2D( vec2 value ) {\n\t\treturn fract( 1.0e4 * sin( 17.0 * value.x + 0.1 * value.y ) * ( 0.1 + abs( sin( 13.0 * value.y + value.x ) ) ) );\n\t}\n\tfloat hash3D( vec3 value ) {\n\t\treturn hash2D( vec2( hash2D( value.xy ), value.z ) );\n\t}\n\tfloat getAlphaHashThreshold( vec3 position ) {\n\t\tfloat maxDeriv = max(\n\t\t\tlength( dFdx( position.xyz ) ),\n\t\t\tlength( dFdy( position.xyz ) )\n\t\t);\n\t\tfloat pixScale = 1.0 / ( ALPHA_HASH_SCALE * maxDeriv );\n\t\tvec2 pixScales = vec2(\n\t\t\texp2( floor( log2( pixScale ) ) ),\n\t\t\texp2( ceil( log2( pixScale ) ) )\n\t\t);\n\t\tvec2 alpha = vec2(\n\t\t\thash3D( floor( pixScales.x * position.xyz ) ),\n\t\t\thash3D( floor( pixScales.y * position.xyz ) )\n\t\t);\n\t\tfloat lerpFactor = fract( log2( pixScale ) );\n\t\tfloat x = ( 1.0 - lerpFactor ) * alpha.x + lerpFactor * alpha.y;\n\t\tfloat a = min( lerpFactor, 1.0 - lerpFactor );\n\t\tvec3 cases = vec3(\n\t\t\tx * x / ( 2.0 * a * ( 1.0 - a ) ),\n\t\t\t( x - 0.5 * a ) / ( 1.0 - a ),\n\t\t\t1.0 - ( ( 1.0 - x ) * ( 1.0 - x ) / ( 2.0 * a * ( 1.0 - a ) ) )\n\t\t);\n\t\tfloat threshold = ( x < ( 1.0 - a ) )\n\t\t\t? ( ( x < a ) ? cases.x : cases.y )\n\t\t\t: cases.z;\n\t\treturn clamp( threshold , 1.0e-6, 1.0 );\n\t}\n#endif"; + +var alphamap_fragment = "#ifdef USE_ALPHAMAP\n\tdiffuseColor.a *= texture2D( alphaMap, vAlphaMapUv ).g;\n#endif"; + +var alphamap_pars_fragment = "#ifdef USE_ALPHAMAP\n\tuniform sampler2D alphaMap;\n#endif"; + +var alphatest_fragment = "#ifdef USE_ALPHATEST\n\t#ifdef ALPHA_TO_COVERAGE\n\tdiffuseColor.a = smoothstep( alphaTest, alphaTest + fwidth( diffuseColor.a ), diffuseColor.a );\n\tif ( diffuseColor.a == 0.0 ) discard;\n\t#else\n\tif ( diffuseColor.a < alphaTest ) discard;\n\t#endif\n#endif"; + +var alphatest_pars_fragment = "#ifdef USE_ALPHATEST\n\tuniform float alphaTest;\n#endif"; + +var aomap_fragment = "#ifdef USE_AOMAP\n\tfloat ambientOcclusion = ( texture2D( aoMap, vAoMapUv ).r - 1.0 ) * aoMapIntensity + 1.0;\n\treflectedLight.indirectDiffuse *= ambientOcclusion;\n\t#if defined( USE_CLEARCOAT ) \n\t\tclearcoatSpecularIndirect *= ambientOcclusion;\n\t#endif\n\t#if defined( USE_SHEEN ) \n\t\tsheenSpecularIndirect *= ambientOcclusion;\n\t#endif\n\t#if defined( USE_ENVMAP ) && defined( STANDARD )\n\t\tfloat dotNV = saturate( dot( geometryNormal, geometryViewDir ) );\n\t\treflectedLight.indirectSpecular *= computeSpecularOcclusion( dotNV, ambientOcclusion, material.roughness );\n\t#endif\n#endif"; + +var aomap_pars_fragment = "#ifdef USE_AOMAP\n\tuniform sampler2D aoMap;\n\tuniform float aoMapIntensity;\n#endif"; + +var batching_pars_vertex = "#ifdef USE_BATCHING\n\tattribute float batchId;\n\tuniform highp sampler2D batchingTexture;\n\tmat4 getBatchingMatrix( const in float i ) {\n\t\tint size = textureSize( batchingTexture, 0 ).x;\n\t\tint j = int( i ) * 4;\n\t\tint x = j % size;\n\t\tint y = j / size;\n\t\tvec4 v1 = texelFetch( batchingTexture, ivec2( x, y ), 0 );\n\t\tvec4 v2 = texelFetch( batchingTexture, ivec2( x + 1, y ), 0 );\n\t\tvec4 v3 = texelFetch( batchingTexture, ivec2( x + 2, y ), 0 );\n\t\tvec4 v4 = texelFetch( batchingTexture, ivec2( x + 3, y ), 0 );\n\t\treturn mat4( v1, v2, v3, v4 );\n\t}\n#endif\n#ifdef USE_BATCHING_COLOR\n\tuniform sampler2D batchingColorTexture;\n\tvec3 getBatchingColor( const in float i ) {\n\t\tint size = textureSize( batchingColorTexture, 0 ).x;\n\t\tint j = int( i );\n\t\tint x = j % size;\n\t\tint y = j / size;\n\t\treturn texelFetch( batchingColorTexture, ivec2( x, y ), 0 ).rgb;\n\t}\n#endif"; + +var batching_vertex = "#ifdef USE_BATCHING\n\tmat4 batchingMatrix = getBatchingMatrix( batchId );\n#endif"; + +var begin_vertex = "vec3 transformed = vec3( position );\n#ifdef USE_ALPHAHASH\n\tvPosition = vec3( position );\n#endif"; + +var beginnormal_vertex = "vec3 objectNormal = vec3( normal );\n#ifdef USE_TANGENT\n\tvec3 objectTangent = vec3( tangent.xyz );\n#endif"; + +var bsdfs = "float G_BlinnPhong_Implicit( ) {\n\treturn 0.25;\n}\nfloat D_BlinnPhong( const in float shininess, const in float dotNH ) {\n\treturn RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );\n}\nvec3 BRDF_BlinnPhong( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float shininess ) {\n\tvec3 halfDir = normalize( lightDir + viewDir );\n\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\n\tvec3 F = F_Schlick( specularColor, 1.0, dotVH );\n\tfloat G = G_BlinnPhong_Implicit( );\n\tfloat D = D_BlinnPhong( shininess, dotNH );\n\treturn F * ( G * D );\n} // validated"; + +var iridescence_fragment = "#ifdef USE_IRIDESCENCE\n\tconst mat3 XYZ_TO_REC709 = mat3(\n\t\t 3.2404542, -0.9692660, 0.0556434,\n\t\t-1.5371385, 1.8760108, -0.2040259,\n\t\t-0.4985314, 0.0415560, 1.0572252\n\t);\n\tvec3 Fresnel0ToIor( vec3 fresnel0 ) {\n\t\tvec3 sqrtF0 = sqrt( fresnel0 );\n\t\treturn ( vec3( 1.0 ) + sqrtF0 ) / ( vec3( 1.0 ) - sqrtF0 );\n\t}\n\tvec3 IorToFresnel0( vec3 transmittedIor, float incidentIor ) {\n\t\treturn pow2( ( transmittedIor - vec3( incidentIor ) ) / ( transmittedIor + vec3( incidentIor ) ) );\n\t}\n\tfloat IorToFresnel0( float transmittedIor, float incidentIor ) {\n\t\treturn pow2( ( transmittedIor - incidentIor ) / ( transmittedIor + incidentIor ));\n\t}\n\tvec3 evalSensitivity( float OPD, vec3 shift ) {\n\t\tfloat phase = 2.0 * PI * OPD * 1.0e-9;\n\t\tvec3 val = vec3( 5.4856e-13, 4.4201e-13, 5.2481e-13 );\n\t\tvec3 pos = vec3( 1.6810e+06, 1.7953e+06, 2.2084e+06 );\n\t\tvec3 var = vec3( 4.3278e+09, 9.3046e+09, 6.6121e+09 );\n\t\tvec3 xyz = val * sqrt( 2.0 * PI * var ) * cos( pos * phase + shift ) * exp( - pow2( phase ) * var );\n\t\txyz.x += 9.7470e-14 * sqrt( 2.0 * PI * 4.5282e+09 ) * cos( 2.2399e+06 * phase + shift[ 0 ] ) * exp( - 4.5282e+09 * pow2( phase ) );\n\t\txyz /= 1.0685e-7;\n\t\tvec3 rgb = XYZ_TO_REC709 * xyz;\n\t\treturn rgb;\n\t}\n\tvec3 evalIridescence( float outsideIOR, float eta2, float cosTheta1, float thinFilmThickness, vec3 baseF0 ) {\n\t\tvec3 I;\n\t\tfloat iridescenceIOR = mix( outsideIOR, eta2, smoothstep( 0.0, 0.03, thinFilmThickness ) );\n\t\tfloat sinTheta2Sq = pow2( outsideIOR / iridescenceIOR ) * ( 1.0 - pow2( cosTheta1 ) );\n\t\tfloat cosTheta2Sq = 1.0 - sinTheta2Sq;\n\t\tif ( cosTheta2Sq < 0.0 ) {\n\t\t\treturn vec3( 1.0 );\n\t\t}\n\t\tfloat cosTheta2 = sqrt( cosTheta2Sq );\n\t\tfloat R0 = IorToFresnel0( iridescenceIOR, outsideIOR );\n\t\tfloat R12 = F_Schlick( R0, 1.0, cosTheta1 );\n\t\tfloat T121 = 1.0 - R12;\n\t\tfloat phi12 = 0.0;\n\t\tif ( iridescenceIOR < outsideIOR ) phi12 = PI;\n\t\tfloat phi21 = PI - phi12;\n\t\tvec3 baseIOR = Fresnel0ToIor( clamp( baseF0, 0.0, 0.9999 ) );\t\tvec3 R1 = IorToFresnel0( baseIOR, iridescenceIOR );\n\t\tvec3 R23 = F_Schlick( R1, 1.0, cosTheta2 );\n\t\tvec3 phi23 = vec3( 0.0 );\n\t\tif ( baseIOR[ 0 ] < iridescenceIOR ) phi23[ 0 ] = PI;\n\t\tif ( baseIOR[ 1 ] < iridescenceIOR ) phi23[ 1 ] = PI;\n\t\tif ( baseIOR[ 2 ] < iridescenceIOR ) phi23[ 2 ] = PI;\n\t\tfloat OPD = 2.0 * iridescenceIOR * thinFilmThickness * cosTheta2;\n\t\tvec3 phi = vec3( phi21 ) + phi23;\n\t\tvec3 R123 = clamp( R12 * R23, 1e-5, 0.9999 );\n\t\tvec3 r123 = sqrt( R123 );\n\t\tvec3 Rs = pow2( T121 ) * R23 / ( vec3( 1.0 ) - R123 );\n\t\tvec3 C0 = R12 + Rs;\n\t\tI = C0;\n\t\tvec3 Cm = Rs - T121;\n\t\tfor ( int m = 1; m <= 2; ++ m ) {\n\t\t\tCm *= r123;\n\t\t\tvec3 Sm = 2.0 * evalSensitivity( float( m ) * OPD, float( m ) * phi );\n\t\t\tI += Cm * Sm;\n\t\t}\n\t\treturn max( I, vec3( 0.0 ) );\n\t}\n#endif"; + +var bumpmap_pars_fragment = "#ifdef USE_BUMPMAP\n\tuniform sampler2D bumpMap;\n\tuniform float bumpScale;\n\tvec2 dHdxy_fwd() {\n\t\tvec2 dSTdx = dFdx( vBumpMapUv );\n\t\tvec2 dSTdy = dFdy( vBumpMapUv );\n\t\tfloat Hll = bumpScale * texture2D( bumpMap, vBumpMapUv ).x;\n\t\tfloat dBx = bumpScale * texture2D( bumpMap, vBumpMapUv + dSTdx ).x - Hll;\n\t\tfloat dBy = bumpScale * texture2D( bumpMap, vBumpMapUv + dSTdy ).x - Hll;\n\t\treturn vec2( dBx, dBy );\n\t}\n\tvec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {\n\t\tvec3 vSigmaX = normalize( dFdx( surf_pos.xyz ) );\n\t\tvec3 vSigmaY = normalize( dFdy( surf_pos.xyz ) );\n\t\tvec3 vN = surf_norm;\n\t\tvec3 R1 = cross( vSigmaY, vN );\n\t\tvec3 R2 = cross( vN, vSigmaX );\n\t\tfloat fDet = dot( vSigmaX, R1 ) * faceDirection;\n\t\tvec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );\n\t\treturn normalize( abs( fDet ) * surf_norm - vGrad );\n\t}\n#endif"; + +var clipping_planes_fragment = "#if NUM_CLIPPING_PLANES > 0\n\tvec4 plane;\n\t#ifdef ALPHA_TO_COVERAGE\n\t\tfloat distanceToPlane, distanceGradient;\n\t\tfloat clipOpacity = 1.0;\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\n\t\t\tplane = clippingPlanes[ i ];\n\t\t\tdistanceToPlane = - dot( vClipPosition, plane.xyz ) + plane.w;\n\t\t\tdistanceGradient = fwidth( distanceToPlane ) / 2.0;\n\t\t\tclipOpacity *= smoothstep( - distanceGradient, distanceGradient, distanceToPlane );\n\t\t\tif ( clipOpacity == 0.0 ) discard;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\n\t\t\tfloat unionClipOpacity = 1.0;\n\t\t\t#pragma unroll_loop_start\n\t\t\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\n\t\t\t\tplane = clippingPlanes[ i ];\n\t\t\t\tdistanceToPlane = - dot( vClipPosition, plane.xyz ) + plane.w;\n\t\t\t\tdistanceGradient = fwidth( distanceToPlane ) / 2.0;\n\t\t\t\tunionClipOpacity *= 1.0 - smoothstep( - distanceGradient, distanceGradient, distanceToPlane );\n\t\t\t}\n\t\t\t#pragma unroll_loop_end\n\t\t\tclipOpacity *= 1.0 - unionClipOpacity;\n\t\t#endif\n\t\tdiffuseColor.a *= clipOpacity;\n\t\tif ( diffuseColor.a == 0.0 ) discard;\n\t#else\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {\n\t\t\tplane = clippingPlanes[ i ];\n\t\t\tif ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t\t#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES\n\t\t\tbool clipped = true;\n\t\t\t#pragma unroll_loop_start\n\t\t\tfor ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {\n\t\t\t\tplane = clippingPlanes[ i ];\n\t\t\t\tclipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;\n\t\t\t}\n\t\t\t#pragma unroll_loop_end\n\t\t\tif ( clipped ) discard;\n\t\t#endif\n\t#endif\n#endif"; + +var clipping_planes_pars_fragment = "#if NUM_CLIPPING_PLANES > 0\n\tvarying vec3 vClipPosition;\n\tuniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];\n#endif"; + +var clipping_planes_pars_vertex = "#if NUM_CLIPPING_PLANES > 0\n\tvarying vec3 vClipPosition;\n#endif"; + +var clipping_planes_vertex = "#if NUM_CLIPPING_PLANES > 0\n\tvClipPosition = - mvPosition.xyz;\n#endif"; + +var color_fragment = "#if defined( USE_COLOR_ALPHA )\n\tdiffuseColor *= vColor;\n#elif defined( USE_COLOR )\n\tdiffuseColor.rgb *= vColor;\n#endif"; + +var color_pars_fragment = "#if defined( USE_COLOR_ALPHA )\n\tvarying vec4 vColor;\n#elif defined( USE_COLOR )\n\tvarying vec3 vColor;\n#endif"; + +var color_pars_vertex = "#if defined( USE_COLOR_ALPHA )\n\tvarying vec4 vColor;\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR ) || defined( USE_BATCHING_COLOR )\n\tvarying vec3 vColor;\n#endif"; + +var color_vertex = "#if defined( USE_COLOR_ALPHA )\n\tvColor = vec4( 1.0 );\n#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR ) || defined( USE_BATCHING_COLOR )\n\tvColor = vec3( 1.0 );\n#endif\n#ifdef USE_COLOR\n\tvColor *= color;\n#endif\n#ifdef USE_INSTANCING_COLOR\n\tvColor.xyz *= instanceColor.xyz;\n#endif\n#ifdef USE_BATCHING_COLOR\n\tvec3 batchingColor = getBatchingColor( batchId );\n\tvColor.xyz *= batchingColor.xyz;\n#endif"; + +var common = "#define PI 3.141592653589793\n#define PI2 6.283185307179586\n#define PI_HALF 1.5707963267948966\n#define RECIPROCAL_PI 0.3183098861837907\n#define RECIPROCAL_PI2 0.15915494309189535\n#define EPSILON 1e-6\n#ifndef saturate\n#define saturate( a ) clamp( a, 0.0, 1.0 )\n#endif\n#define whiteComplement( a ) ( 1.0 - saturate( a ) )\nfloat pow2( const in float x ) { return x*x; }\nvec3 pow2( const in vec3 x ) { return x*x; }\nfloat pow3( const in float x ) { return x*x*x; }\nfloat pow4( const in float x ) { float x2 = x*x; return x2*x2; }\nfloat max3( const in vec3 v ) { return max( max( v.x, v.y ), v.z ); }\nfloat average( const in vec3 v ) { return dot( v, vec3( 0.3333333 ) ); }\nhighp float rand( const in vec2 uv ) {\n\tconst highp float a = 12.9898, b = 78.233, c = 43758.5453;\n\thighp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );\n\treturn fract( sin( sn ) * c );\n}\n#ifdef HIGH_PRECISION\n\tfloat precisionSafeLength( vec3 v ) { return length( v ); }\n#else\n\tfloat precisionSafeLength( vec3 v ) {\n\t\tfloat maxComponent = max3( abs( v ) );\n\t\treturn length( v / maxComponent ) * maxComponent;\n\t}\n#endif\nstruct IncidentLight {\n\tvec3 color;\n\tvec3 direction;\n\tbool visible;\n};\nstruct ReflectedLight {\n\tvec3 directDiffuse;\n\tvec3 directSpecular;\n\tvec3 indirectDiffuse;\n\tvec3 indirectSpecular;\n};\n#ifdef USE_ALPHAHASH\n\tvarying vec3 vPosition;\n#endif\nvec3 transformDirection( in vec3 dir, in mat4 matrix ) {\n\treturn normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );\n}\nvec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {\n\treturn normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );\n}\nmat3 transposeMat3( const in mat3 m ) {\n\tmat3 tmp;\n\ttmp[ 0 ] = vec3( m[ 0 ].x, m[ 1 ].x, m[ 2 ].x );\n\ttmp[ 1 ] = vec3( m[ 0 ].y, m[ 1 ].y, m[ 2 ].y );\n\ttmp[ 2 ] = vec3( m[ 0 ].z, m[ 1 ].z, m[ 2 ].z );\n\treturn tmp;\n}\nfloat luminance( const in vec3 rgb ) {\n\tconst vec3 weights = vec3( 0.2126729, 0.7151522, 0.0721750 );\n\treturn dot( weights, rgb );\n}\nbool isPerspectiveMatrix( mat4 m ) {\n\treturn m[ 2 ][ 3 ] == - 1.0;\n}\nvec2 equirectUv( in vec3 dir ) {\n\tfloat u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;\n\tfloat v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;\n\treturn vec2( u, v );\n}\nvec3 BRDF_Lambert( const in vec3 diffuseColor ) {\n\treturn RECIPROCAL_PI * diffuseColor;\n}\nvec3 F_Schlick( const in vec3 f0, const in float f90, const in float dotVH ) {\n\tfloat fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );\n\treturn f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );\n}\nfloat F_Schlick( const in float f0, const in float f90, const in float dotVH ) {\n\tfloat fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );\n\treturn f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );\n} // validated"; + +var cube_uv_reflection_fragment = "#ifdef ENVMAP_TYPE_CUBE_UV\n\t#define cubeUV_minMipLevel 4.0\n\t#define cubeUV_minTileSize 16.0\n\tfloat getFace( vec3 direction ) {\n\t\tvec3 absDirection = abs( direction );\n\t\tfloat face = - 1.0;\n\t\tif ( absDirection.x > absDirection.z ) {\n\t\t\tif ( absDirection.x > absDirection.y )\n\t\t\t\tface = direction.x > 0.0 ? 0.0 : 3.0;\n\t\t\telse\n\t\t\t\tface = direction.y > 0.0 ? 1.0 : 4.0;\n\t\t} else {\n\t\t\tif ( absDirection.z > absDirection.y )\n\t\t\t\tface = direction.z > 0.0 ? 2.0 : 5.0;\n\t\t\telse\n\t\t\t\tface = direction.y > 0.0 ? 1.0 : 4.0;\n\t\t}\n\t\treturn face;\n\t}\n\tvec2 getUV( vec3 direction, float face ) {\n\t\tvec2 uv;\n\t\tif ( face == 0.0 ) {\n\t\t\tuv = vec2( direction.z, direction.y ) / abs( direction.x );\n\t\t} else if ( face == 1.0 ) {\n\t\t\tuv = vec2( - direction.x, - direction.z ) / abs( direction.y );\n\t\t} else if ( face == 2.0 ) {\n\t\t\tuv = vec2( - direction.x, direction.y ) / abs( direction.z );\n\t\t} else if ( face == 3.0 ) {\n\t\t\tuv = vec2( - direction.z, direction.y ) / abs( direction.x );\n\t\t} else if ( face == 4.0 ) {\n\t\t\tuv = vec2( - direction.x, direction.z ) / abs( direction.y );\n\t\t} else {\n\t\t\tuv = vec2( direction.x, direction.y ) / abs( direction.z );\n\t\t}\n\t\treturn 0.5 * ( uv + 1.0 );\n\t}\n\tvec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {\n\t\tfloat face = getFace( direction );\n\t\tfloat filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );\n\t\tmipInt = max( mipInt, cubeUV_minMipLevel );\n\t\tfloat faceSize = exp2( mipInt );\n\t\thighp vec2 uv = getUV( direction, face ) * ( faceSize - 2.0 ) + 1.0;\n\t\tif ( face > 2.0 ) {\n\t\t\tuv.y += faceSize;\n\t\t\tface -= 3.0;\n\t\t}\n\t\tuv.x += face * faceSize;\n\t\tuv.x += filterInt * 3.0 * cubeUV_minTileSize;\n\t\tuv.y += 4.0 * ( exp2( CUBEUV_MAX_MIP ) - faceSize );\n\t\tuv.x *= CUBEUV_TEXEL_WIDTH;\n\t\tuv.y *= CUBEUV_TEXEL_HEIGHT;\n\t\t#ifdef texture2DGradEXT\n\t\t\treturn texture2DGradEXT( envMap, uv, vec2( 0.0 ), vec2( 0.0 ) ).rgb;\n\t\t#else\n\t\t\treturn texture2D( envMap, uv ).rgb;\n\t\t#endif\n\t}\n\t#define cubeUV_r0 1.0\n\t#define cubeUV_m0 - 2.0\n\t#define cubeUV_r1 0.8\n\t#define cubeUV_m1 - 1.0\n\t#define cubeUV_r4 0.4\n\t#define cubeUV_m4 2.0\n\t#define cubeUV_r5 0.305\n\t#define cubeUV_m5 3.0\n\t#define cubeUV_r6 0.21\n\t#define cubeUV_m6 4.0\n\tfloat roughnessToMip( float roughness ) {\n\t\tfloat mip = 0.0;\n\t\tif ( roughness >= cubeUV_r1 ) {\n\t\t\tmip = ( cubeUV_r0 - roughness ) * ( cubeUV_m1 - cubeUV_m0 ) / ( cubeUV_r0 - cubeUV_r1 ) + cubeUV_m0;\n\t\t} else if ( roughness >= cubeUV_r4 ) {\n\t\t\tmip = ( cubeUV_r1 - roughness ) * ( cubeUV_m4 - cubeUV_m1 ) / ( cubeUV_r1 - cubeUV_r4 ) + cubeUV_m1;\n\t\t} else if ( roughness >= cubeUV_r5 ) {\n\t\t\tmip = ( cubeUV_r4 - roughness ) * ( cubeUV_m5 - cubeUV_m4 ) / ( cubeUV_r4 - cubeUV_r5 ) + cubeUV_m4;\n\t\t} else if ( roughness >= cubeUV_r6 ) {\n\t\t\tmip = ( cubeUV_r5 - roughness ) * ( cubeUV_m6 - cubeUV_m5 ) / ( cubeUV_r5 - cubeUV_r6 ) + cubeUV_m5;\n\t\t} else {\n\t\t\tmip = - 2.0 * log2( 1.16 * roughness );\t\t}\n\t\treturn mip;\n\t}\n\tvec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {\n\t\tfloat mip = clamp( roughnessToMip( roughness ), cubeUV_m0, CUBEUV_MAX_MIP );\n\t\tfloat mipF = fract( mip );\n\t\tfloat mipInt = floor( mip );\n\t\tvec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );\n\t\tif ( mipF == 0.0 ) {\n\t\t\treturn vec4( color0, 1.0 );\n\t\t} else {\n\t\t\tvec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );\n\t\t\treturn vec4( mix( color0, color1, mipF ), 1.0 );\n\t\t}\n\t}\n#endif"; + +var defaultnormal_vertex = "vec3 transformedNormal = objectNormal;\n#ifdef USE_TANGENT\n\tvec3 transformedTangent = objectTangent;\n#endif\n#ifdef USE_BATCHING\n\tmat3 bm = mat3( batchingMatrix );\n\ttransformedNormal /= vec3( dot( bm[ 0 ], bm[ 0 ] ), dot( bm[ 1 ], bm[ 1 ] ), dot( bm[ 2 ], bm[ 2 ] ) );\n\ttransformedNormal = bm * transformedNormal;\n\t#ifdef USE_TANGENT\n\t\ttransformedTangent = bm * transformedTangent;\n\t#endif\n#endif\n#ifdef USE_INSTANCING\n\tmat3 im = mat3( instanceMatrix );\n\ttransformedNormal /= vec3( dot( im[ 0 ], im[ 0 ] ), dot( im[ 1 ], im[ 1 ] ), dot( im[ 2 ], im[ 2 ] ) );\n\ttransformedNormal = im * transformedNormal;\n\t#ifdef USE_TANGENT\n\t\ttransformedTangent = im * transformedTangent;\n\t#endif\n#endif\ntransformedNormal = normalMatrix * transformedNormal;\n#ifdef FLIP_SIDED\n\ttransformedNormal = - transformedNormal;\n#endif\n#ifdef USE_TANGENT\n\ttransformedTangent = ( modelViewMatrix * vec4( transformedTangent, 0.0 ) ).xyz;\n\t#ifdef FLIP_SIDED\n\t\ttransformedTangent = - transformedTangent;\n\t#endif\n#endif"; + +var displacementmap_pars_vertex = "#ifdef USE_DISPLACEMENTMAP\n\tuniform sampler2D displacementMap;\n\tuniform float displacementScale;\n\tuniform float displacementBias;\n#endif"; + +var displacementmap_vertex = "#ifdef USE_DISPLACEMENTMAP\n\ttransformed += normalize( objectNormal ) * ( texture2D( displacementMap, vDisplacementMapUv ).x * displacementScale + displacementBias );\n#endif"; + +var emissivemap_fragment = "#ifdef USE_EMISSIVEMAP\n\tvec4 emissiveColor = texture2D( emissiveMap, vEmissiveMapUv );\n\ttotalEmissiveRadiance *= emissiveColor.rgb;\n#endif"; + +var emissivemap_pars_fragment = "#ifdef USE_EMISSIVEMAP\n\tuniform sampler2D emissiveMap;\n#endif"; + +var colorspace_fragment = "gl_FragColor = linearToOutputTexel( gl_FragColor );"; + +var colorspace_pars_fragment = "\nconst mat3 LINEAR_SRGB_TO_LINEAR_DISPLAY_P3 = mat3(\n\tvec3( 0.8224621, 0.177538, 0.0 ),\n\tvec3( 0.0331941, 0.9668058, 0.0 ),\n\tvec3( 0.0170827, 0.0723974, 0.9105199 )\n);\nconst mat3 LINEAR_DISPLAY_P3_TO_LINEAR_SRGB = mat3(\n\tvec3( 1.2249401, - 0.2249404, 0.0 ),\n\tvec3( - 0.0420569, 1.0420571, 0.0 ),\n\tvec3( - 0.0196376, - 0.0786361, 1.0982735 )\n);\nvec4 LinearSRGBToLinearDisplayP3( in vec4 value ) {\n\treturn vec4( value.rgb * LINEAR_SRGB_TO_LINEAR_DISPLAY_P3, value.a );\n}\nvec4 LinearDisplayP3ToLinearSRGB( in vec4 value ) {\n\treturn vec4( value.rgb * LINEAR_DISPLAY_P3_TO_LINEAR_SRGB, value.a );\n}\nvec4 LinearTransferOETF( in vec4 value ) {\n\treturn value;\n}\nvec4 sRGBTransferOETF( in vec4 value ) {\n\treturn vec4( mix( pow( value.rgb, vec3( 0.41666 ) ) * 1.055 - vec3( 0.055 ), value.rgb * 12.92, vec3( lessThanEqual( value.rgb, vec3( 0.0031308 ) ) ) ), value.a );\n}\nvec4 LinearToLinear( in vec4 value ) {\n\treturn value;\n}\nvec4 LinearTosRGB( in vec4 value ) {\n\treturn sRGBTransferOETF( value );\n}"; + +var envmap_fragment = "#ifdef USE_ENVMAP\n\t#ifdef ENV_WORLDPOS\n\t\tvec3 cameraToFrag;\n\t\tif ( isOrthographic ) {\n\t\t\tcameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\n\t\t} else {\n\t\t\tcameraToFrag = normalize( vWorldPosition - cameraPosition );\n\t\t}\n\t\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\t\t#ifdef ENVMAP_MODE_REFLECTION\n\t\t\tvec3 reflectVec = reflect( cameraToFrag, worldNormal );\n\t\t#else\n\t\t\tvec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );\n\t\t#endif\n\t#else\n\t\tvec3 reflectVec = vReflect;\n\t#endif\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tvec4 envColor = textureCube( envMap, envMapRotation * vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );\n\t#else\n\t\tvec4 envColor = vec4( 0.0 );\n\t#endif\n\t#ifdef ENVMAP_BLENDING_MULTIPLY\n\t\toutgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );\n\t#elif defined( ENVMAP_BLENDING_MIX )\n\t\toutgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );\n\t#elif defined( ENVMAP_BLENDING_ADD )\n\t\toutgoingLight += envColor.xyz * specularStrength * reflectivity;\n\t#endif\n#endif"; + +var envmap_common_pars_fragment = "#ifdef USE_ENVMAP\n\tuniform float envMapIntensity;\n\tuniform float flipEnvMap;\n\tuniform mat3 envMapRotation;\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tuniform samplerCube envMap;\n\t#else\n\t\tuniform sampler2D envMap;\n\t#endif\n\t\n#endif"; + +var envmap_pars_fragment = "#ifdef USE_ENVMAP\n\tuniform float reflectivity;\n\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG ) || defined( LAMBERT )\n\t\t#define ENV_WORLDPOS\n\t#endif\n\t#ifdef ENV_WORLDPOS\n\t\tvarying vec3 vWorldPosition;\n\t\tuniform float refractionRatio;\n\t#else\n\t\tvarying vec3 vReflect;\n\t#endif\n#endif"; + +var envmap_pars_vertex = "#ifdef USE_ENVMAP\n\t#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG ) || defined( LAMBERT )\n\t\t#define ENV_WORLDPOS\n\t#endif\n\t#ifdef ENV_WORLDPOS\n\t\t\n\t\tvarying vec3 vWorldPosition;\n\t#else\n\t\tvarying vec3 vReflect;\n\t\tuniform float refractionRatio;\n\t#endif\n#endif"; + +var envmap_vertex = "#ifdef USE_ENVMAP\n\t#ifdef ENV_WORLDPOS\n\t\tvWorldPosition = worldPosition.xyz;\n\t#else\n\t\tvec3 cameraToVertex;\n\t\tif ( isOrthographic ) {\n\t\t\tcameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );\n\t\t} else {\n\t\t\tcameraToVertex = normalize( worldPosition.xyz - cameraPosition );\n\t\t}\n\t\tvec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\n\t\t#ifdef ENVMAP_MODE_REFLECTION\n\t\t\tvReflect = reflect( cameraToVertex, worldNormal );\n\t\t#else\n\t\t\tvReflect = refract( cameraToVertex, worldNormal, refractionRatio );\n\t\t#endif\n\t#endif\n#endif"; + +var fog_vertex = "#ifdef USE_FOG\n\tvFogDepth = - mvPosition.z;\n#endif"; + +var fog_pars_vertex = "#ifdef USE_FOG\n\tvarying float vFogDepth;\n#endif"; + +var fog_fragment = "#ifdef USE_FOG\n\t#ifdef FOG_EXP2\n\t\tfloat fogFactor = 1.0 - exp( - fogDensity * fogDensity * vFogDepth * vFogDepth );\n\t#else\n\t\tfloat fogFactor = smoothstep( fogNear, fogFar, vFogDepth );\n\t#endif\n\tgl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );\n#endif"; + +var fog_pars_fragment = "#ifdef USE_FOG\n\tuniform vec3 fogColor;\n\tvarying float vFogDepth;\n\t#ifdef FOG_EXP2\n\t\tuniform float fogDensity;\n\t#else\n\t\tuniform float fogNear;\n\t\tuniform float fogFar;\n\t#endif\n#endif"; + +var gradientmap_pars_fragment = "#ifdef USE_GRADIENTMAP\n\tuniform sampler2D gradientMap;\n#endif\nvec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {\n\tfloat dotNL = dot( normal, lightDirection );\n\tvec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );\n\t#ifdef USE_GRADIENTMAP\n\t\treturn vec3( texture2D( gradientMap, coord ).r );\n\t#else\n\t\tvec2 fw = fwidth( coord ) * 0.5;\n\t\treturn mix( vec3( 0.7 ), vec3( 1.0 ), smoothstep( 0.7 - fw.x, 0.7 + fw.x, coord.x ) );\n\t#endif\n}"; + +var lightmap_pars_fragment = "#ifdef USE_LIGHTMAP\n\tuniform sampler2D lightMap;\n\tuniform float lightMapIntensity;\n#endif"; + +var lights_lambert_fragment = "LambertMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;\nmaterial.specularStrength = specularStrength;"; + +var lights_lambert_pars_fragment = "varying vec3 vViewPosition;\nstruct LambertMaterial {\n\tvec3 diffuseColor;\n\tfloat specularStrength;\n};\nvoid RE_Direct_Lambert( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in LambertMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometryNormal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Lambert( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in LambertMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_Lambert\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Lambert"; + +var lights_pars_begin = "uniform bool receiveShadow;\nuniform vec3 ambientLightColor;\n#if defined( USE_LIGHT_PROBES )\n\tuniform vec3 lightProbe[ 9 ];\n#endif\nvec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {\n\tfloat x = normal.x, y = normal.y, z = normal.z;\n\tvec3 result = shCoefficients[ 0 ] * 0.886227;\n\tresult += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;\n\tresult += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;\n\tresult += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;\n\tresult += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;\n\tresult += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;\n\tresult += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );\n\tresult += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;\n\tresult += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );\n\treturn result;\n}\nvec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in vec3 normal ) {\n\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\tvec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );\n\treturn irradiance;\n}\nvec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {\n\tvec3 irradiance = ambientLightColor;\n\treturn irradiance;\n}\nfloat getDistanceAttenuation( const in float lightDistance, const in float cutoffDistance, const in float decayExponent ) {\n\tfloat distanceFalloff = 1.0 / max( pow( lightDistance, decayExponent ), 0.01 );\n\tif ( cutoffDistance > 0.0 ) {\n\t\tdistanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );\n\t}\n\treturn distanceFalloff;\n}\nfloat getSpotAttenuation( const in float coneCosine, const in float penumbraCosine, const in float angleCosine ) {\n\treturn smoothstep( coneCosine, penumbraCosine, angleCosine );\n}\n#if NUM_DIR_LIGHTS > 0\n\tstruct DirectionalLight {\n\t\tvec3 direction;\n\t\tvec3 color;\n\t};\n\tuniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];\n\tvoid getDirectionalLightInfo( const in DirectionalLight directionalLight, out IncidentLight light ) {\n\t\tlight.color = directionalLight.color;\n\t\tlight.direction = directionalLight.direction;\n\t\tlight.visible = true;\n\t}\n#endif\n#if NUM_POINT_LIGHTS > 0\n\tstruct PointLight {\n\t\tvec3 position;\n\t\tvec3 color;\n\t\tfloat distance;\n\t\tfloat decay;\n\t};\n\tuniform PointLight pointLights[ NUM_POINT_LIGHTS ];\n\tvoid getPointLightInfo( const in PointLight pointLight, const in vec3 geometryPosition, out IncidentLight light ) {\n\t\tvec3 lVector = pointLight.position - geometryPosition;\n\t\tlight.direction = normalize( lVector );\n\t\tfloat lightDistance = length( lVector );\n\t\tlight.color = pointLight.color;\n\t\tlight.color *= getDistanceAttenuation( lightDistance, pointLight.distance, pointLight.decay );\n\t\tlight.visible = ( light.color != vec3( 0.0 ) );\n\t}\n#endif\n#if NUM_SPOT_LIGHTS > 0\n\tstruct SpotLight {\n\t\tvec3 position;\n\t\tvec3 direction;\n\t\tvec3 color;\n\t\tfloat distance;\n\t\tfloat decay;\n\t\tfloat coneCos;\n\t\tfloat penumbraCos;\n\t};\n\tuniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];\n\tvoid getSpotLightInfo( const in SpotLight spotLight, const in vec3 geometryPosition, out IncidentLight light ) {\n\t\tvec3 lVector = spotLight.position - geometryPosition;\n\t\tlight.direction = normalize( lVector );\n\t\tfloat angleCos = dot( light.direction, spotLight.direction );\n\t\tfloat spotAttenuation = getSpotAttenuation( spotLight.coneCos, spotLight.penumbraCos, angleCos );\n\t\tif ( spotAttenuation > 0.0 ) {\n\t\t\tfloat lightDistance = length( lVector );\n\t\t\tlight.color = spotLight.color * spotAttenuation;\n\t\t\tlight.color *= getDistanceAttenuation( lightDistance, spotLight.distance, spotLight.decay );\n\t\t\tlight.visible = ( light.color != vec3( 0.0 ) );\n\t\t} else {\n\t\t\tlight.color = vec3( 0.0 );\n\t\t\tlight.visible = false;\n\t\t}\n\t}\n#endif\n#if NUM_RECT_AREA_LIGHTS > 0\n\tstruct RectAreaLight {\n\t\tvec3 color;\n\t\tvec3 position;\n\t\tvec3 halfWidth;\n\t\tvec3 halfHeight;\n\t};\n\tuniform sampler2D ltc_1;\tuniform sampler2D ltc_2;\n\tuniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];\n#endif\n#if NUM_HEMI_LIGHTS > 0\n\tstruct HemisphereLight {\n\t\tvec3 direction;\n\t\tvec3 skyColor;\n\t\tvec3 groundColor;\n\t};\n\tuniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];\n\tvec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in vec3 normal ) {\n\t\tfloat dotNL = dot( normal, hemiLight.direction );\n\t\tfloat hemiDiffuseWeight = 0.5 * dotNL + 0.5;\n\t\tvec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );\n\t\treturn irradiance;\n\t}\n#endif"; + +var envmap_physical_pars_fragment = "#ifdef USE_ENVMAP\n\tvec3 getIBLIrradiance( const in vec3 normal ) {\n\t\t#ifdef ENVMAP_TYPE_CUBE_UV\n\t\t\tvec3 worldNormal = inverseTransformDirection( normal, viewMatrix );\n\t\t\tvec4 envMapColor = textureCubeUV( envMap, envMapRotation * worldNormal, 1.0 );\n\t\t\treturn PI * envMapColor.rgb * envMapIntensity;\n\t\t#else\n\t\t\treturn vec3( 0.0 );\n\t\t#endif\n\t}\n\tvec3 getIBLRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness ) {\n\t\t#ifdef ENVMAP_TYPE_CUBE_UV\n\t\t\tvec3 reflectVec = reflect( - viewDir, normal );\n\t\t\treflectVec = normalize( mix( reflectVec, normal, roughness * roughness) );\n\t\t\treflectVec = inverseTransformDirection( reflectVec, viewMatrix );\n\t\t\tvec4 envMapColor = textureCubeUV( envMap, envMapRotation * reflectVec, roughness );\n\t\t\treturn envMapColor.rgb * envMapIntensity;\n\t\t#else\n\t\t\treturn vec3( 0.0 );\n\t\t#endif\n\t}\n\t#ifdef USE_ANISOTROPY\n\t\tvec3 getIBLAnisotropyRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness, const in vec3 bitangent, const in float anisotropy ) {\n\t\t\t#ifdef ENVMAP_TYPE_CUBE_UV\n\t\t\t\tvec3 bentNormal = cross( bitangent, viewDir );\n\t\t\t\tbentNormal = normalize( cross( bentNormal, bitangent ) );\n\t\t\t\tbentNormal = normalize( mix( bentNormal, normal, pow2( pow2( 1.0 - anisotropy * ( 1.0 - roughness ) ) ) ) );\n\t\t\t\treturn getIBLRadiance( viewDir, bentNormal, roughness );\n\t\t\t#else\n\t\t\t\treturn vec3( 0.0 );\n\t\t\t#endif\n\t\t}\n\t#endif\n#endif"; + +var lights_toon_fragment = "ToonMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;"; + +var lights_toon_pars_fragment = "varying vec3 vViewPosition;\nstruct ToonMaterial {\n\tvec3 diffuseColor;\n};\nvoid RE_Direct_Toon( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\n\tvec3 irradiance = getGradientIrradiance( geometryNormal, directLight.direction ) * directLight.color;\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Toon( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_Toon\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Toon"; + +var lights_phong_fragment = "BlinnPhongMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb;\nmaterial.specularColor = specular;\nmaterial.specularShininess = shininess;\nmaterial.specularStrength = specularStrength;"; + +var lights_phong_pars_fragment = "varying vec3 vViewPosition;\nstruct BlinnPhongMaterial {\n\tvec3 diffuseColor;\n\tvec3 specularColor;\n\tfloat specularShininess;\n\tfloat specularStrength;\n};\nvoid RE_Direct_BlinnPhong( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometryNormal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n\treflectedLight.directSpecular += irradiance * BRDF_BlinnPhong( directLight.direction, geometryViewDir, geometryNormal, material.specularColor, material.specularShininess ) * material.specularStrength;\n}\nvoid RE_IndirectDiffuse_BlinnPhong( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\n#define RE_Direct\t\t\t\tRE_Direct_BlinnPhong\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_BlinnPhong"; + +var lights_physical_fragment = "PhysicalMaterial material;\nmaterial.diffuseColor = diffuseColor.rgb * ( 1.0 - metalnessFactor );\nvec3 dxy = max( abs( dFdx( nonPerturbedNormal ) ), abs( dFdy( nonPerturbedNormal ) ) );\nfloat geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );\nmaterial.roughness = max( roughnessFactor, 0.0525 );material.roughness += geometryRoughness;\nmaterial.roughness = min( material.roughness, 1.0 );\n#ifdef IOR\n\tmaterial.ior = ior;\n\t#ifdef USE_SPECULAR\n\t\tfloat specularIntensityFactor = specularIntensity;\n\t\tvec3 specularColorFactor = specularColor;\n\t\t#ifdef USE_SPECULAR_COLORMAP\n\t\t\tspecularColorFactor *= texture2D( specularColorMap, vSpecularColorMapUv ).rgb;\n\t\t#endif\n\t\t#ifdef USE_SPECULAR_INTENSITYMAP\n\t\t\tspecularIntensityFactor *= texture2D( specularIntensityMap, vSpecularIntensityMapUv ).a;\n\t\t#endif\n\t\tmaterial.specularF90 = mix( specularIntensityFactor, 1.0, metalnessFactor );\n\t#else\n\t\tfloat specularIntensityFactor = 1.0;\n\t\tvec3 specularColorFactor = vec3( 1.0 );\n\t\tmaterial.specularF90 = 1.0;\n\t#endif\n\tmaterial.specularColor = mix( min( pow2( ( material.ior - 1.0 ) / ( material.ior + 1.0 ) ) * specularColorFactor, vec3( 1.0 ) ) * specularIntensityFactor, diffuseColor.rgb, metalnessFactor );\n#else\n\tmaterial.specularColor = mix( vec3( 0.04 ), diffuseColor.rgb, metalnessFactor );\n\tmaterial.specularF90 = 1.0;\n#endif\n#ifdef USE_CLEARCOAT\n\tmaterial.clearcoat = clearcoat;\n\tmaterial.clearcoatRoughness = clearcoatRoughness;\n\tmaterial.clearcoatF0 = vec3( 0.04 );\n\tmaterial.clearcoatF90 = 1.0;\n\t#ifdef USE_CLEARCOATMAP\n\t\tmaterial.clearcoat *= texture2D( clearcoatMap, vClearcoatMapUv ).x;\n\t#endif\n\t#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\t\tmaterial.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vClearcoatRoughnessMapUv ).y;\n\t#endif\n\tmaterial.clearcoat = saturate( material.clearcoat );\tmaterial.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );\n\tmaterial.clearcoatRoughness += geometryRoughness;\n\tmaterial.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );\n#endif\n#ifdef USE_DISPERSION\n\tmaterial.dispersion = dispersion;\n#endif\n#ifdef USE_IRIDESCENCE\n\tmaterial.iridescence = iridescence;\n\tmaterial.iridescenceIOR = iridescenceIOR;\n\t#ifdef USE_IRIDESCENCEMAP\n\t\tmaterial.iridescence *= texture2D( iridescenceMap, vIridescenceMapUv ).r;\n\t#endif\n\t#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\t\tmaterial.iridescenceThickness = (iridescenceThicknessMaximum - iridescenceThicknessMinimum) * texture2D( iridescenceThicknessMap, vIridescenceThicknessMapUv ).g + iridescenceThicknessMinimum;\n\t#else\n\t\tmaterial.iridescenceThickness = iridescenceThicknessMaximum;\n\t#endif\n#endif\n#ifdef USE_SHEEN\n\tmaterial.sheenColor = sheenColor;\n\t#ifdef USE_SHEEN_COLORMAP\n\t\tmaterial.sheenColor *= texture2D( sheenColorMap, vSheenColorMapUv ).rgb;\n\t#endif\n\tmaterial.sheenRoughness = clamp( sheenRoughness, 0.07, 1.0 );\n\t#ifdef USE_SHEEN_ROUGHNESSMAP\n\t\tmaterial.sheenRoughness *= texture2D( sheenRoughnessMap, vSheenRoughnessMapUv ).a;\n\t#endif\n#endif\n#ifdef USE_ANISOTROPY\n\t#ifdef USE_ANISOTROPYMAP\n\t\tmat2 anisotropyMat = mat2( anisotropyVector.x, anisotropyVector.y, - anisotropyVector.y, anisotropyVector.x );\n\t\tvec3 anisotropyPolar = texture2D( anisotropyMap, vAnisotropyMapUv ).rgb;\n\t\tvec2 anisotropyV = anisotropyMat * normalize( 2.0 * anisotropyPolar.rg - vec2( 1.0 ) ) * anisotropyPolar.b;\n\t#else\n\t\tvec2 anisotropyV = anisotropyVector;\n\t#endif\n\tmaterial.anisotropy = length( anisotropyV );\n\tif( material.anisotropy == 0.0 ) {\n\t\tanisotropyV = vec2( 1.0, 0.0 );\n\t} else {\n\t\tanisotropyV /= material.anisotropy;\n\t\tmaterial.anisotropy = saturate( material.anisotropy );\n\t}\n\tmaterial.alphaT = mix( pow2( material.roughness ), 1.0, pow2( material.anisotropy ) );\n\tmaterial.anisotropyT = tbn[ 0 ] * anisotropyV.x + tbn[ 1 ] * anisotropyV.y;\n\tmaterial.anisotropyB = tbn[ 1 ] * anisotropyV.x - tbn[ 0 ] * anisotropyV.y;\n#endif"; + +var lights_physical_pars_fragment = "struct PhysicalMaterial {\n\tvec3 diffuseColor;\n\tfloat roughness;\n\tvec3 specularColor;\n\tfloat specularF90;\n\tfloat dispersion;\n\t#ifdef USE_CLEARCOAT\n\t\tfloat clearcoat;\n\t\tfloat clearcoatRoughness;\n\t\tvec3 clearcoatF0;\n\t\tfloat clearcoatF90;\n\t#endif\n\t#ifdef USE_IRIDESCENCE\n\t\tfloat iridescence;\n\t\tfloat iridescenceIOR;\n\t\tfloat iridescenceThickness;\n\t\tvec3 iridescenceFresnel;\n\t\tvec3 iridescenceF0;\n\t#endif\n\t#ifdef USE_SHEEN\n\t\tvec3 sheenColor;\n\t\tfloat sheenRoughness;\n\t#endif\n\t#ifdef IOR\n\t\tfloat ior;\n\t#endif\n\t#ifdef USE_TRANSMISSION\n\t\tfloat transmission;\n\t\tfloat transmissionAlpha;\n\t\tfloat thickness;\n\t\tfloat attenuationDistance;\n\t\tvec3 attenuationColor;\n\t#endif\n\t#ifdef USE_ANISOTROPY\n\t\tfloat anisotropy;\n\t\tfloat alphaT;\n\t\tvec3 anisotropyT;\n\t\tvec3 anisotropyB;\n\t#endif\n};\nvec3 clearcoatSpecularDirect = vec3( 0.0 );\nvec3 clearcoatSpecularIndirect = vec3( 0.0 );\nvec3 sheenSpecularDirect = vec3( 0.0 );\nvec3 sheenSpecularIndirect = vec3(0.0 );\nvec3 Schlick_to_F0( const in vec3 f, const in float f90, const in float dotVH ) {\n float x = clamp( 1.0 - dotVH, 0.0, 1.0 );\n float x2 = x * x;\n float x5 = clamp( x * x2 * x2, 0.0, 0.9999 );\n return ( f - vec3( f90 ) * x5 ) / ( 1.0 - x5 );\n}\nfloat V_GGX_SmithCorrelated( const in float alpha, const in float dotNL, const in float dotNV ) {\n\tfloat a2 = pow2( alpha );\n\tfloat gv = dotNL * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNV ) );\n\tfloat gl = dotNV * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNL ) );\n\treturn 0.5 / max( gv + gl, EPSILON );\n}\nfloat D_GGX( const in float alpha, const in float dotNH ) {\n\tfloat a2 = pow2( alpha );\n\tfloat denom = pow2( dotNH ) * ( a2 - 1.0 ) + 1.0;\n\treturn RECIPROCAL_PI * a2 / pow2( denom );\n}\n#ifdef USE_ANISOTROPY\n\tfloat V_GGX_SmithCorrelated_Anisotropic( const in float alphaT, const in float alphaB, const in float dotTV, const in float dotBV, const in float dotTL, const in float dotBL, const in float dotNV, const in float dotNL ) {\n\t\tfloat gv = dotNL * length( vec3( alphaT * dotTV, alphaB * dotBV, dotNV ) );\n\t\tfloat gl = dotNV * length( vec3( alphaT * dotTL, alphaB * dotBL, dotNL ) );\n\t\tfloat v = 0.5 / ( gv + gl );\n\t\treturn saturate(v);\n\t}\n\tfloat D_GGX_Anisotropic( const in float alphaT, const in float alphaB, const in float dotNH, const in float dotTH, const in float dotBH ) {\n\t\tfloat a2 = alphaT * alphaB;\n\t\thighp vec3 v = vec3( alphaB * dotTH, alphaT * dotBH, a2 * dotNH );\n\t\thighp float v2 = dot( v, v );\n\t\tfloat w2 = a2 / v2;\n\t\treturn RECIPROCAL_PI * a2 * pow2 ( w2 );\n\t}\n#endif\n#ifdef USE_CLEARCOAT\n\tvec3 BRDF_GGX_Clearcoat( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in PhysicalMaterial material) {\n\t\tvec3 f0 = material.clearcoatF0;\n\t\tfloat f90 = material.clearcoatF90;\n\t\tfloat roughness = material.clearcoatRoughness;\n\t\tfloat alpha = pow2( roughness );\n\t\tvec3 halfDir = normalize( lightDir + viewDir );\n\t\tfloat dotNL = saturate( dot( normal, lightDir ) );\n\t\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\t\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\t\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\n\t\tvec3 F = F_Schlick( f0, f90, dotVH );\n\t\tfloat V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );\n\t\tfloat D = D_GGX( alpha, dotNH );\n\t\treturn F * ( V * D );\n\t}\n#endif\nvec3 BRDF_GGX( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in PhysicalMaterial material ) {\n\tvec3 f0 = material.specularColor;\n\tfloat f90 = material.specularF90;\n\tfloat roughness = material.roughness;\n\tfloat alpha = pow2( roughness );\n\tvec3 halfDir = normalize( lightDir + viewDir );\n\tfloat dotNL = saturate( dot( normal, lightDir ) );\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\tfloat dotVH = saturate( dot( viewDir, halfDir ) );\n\tvec3 F = F_Schlick( f0, f90, dotVH );\n\t#ifdef USE_IRIDESCENCE\n\t\tF = mix( F, material.iridescenceFresnel, material.iridescence );\n\t#endif\n\t#ifdef USE_ANISOTROPY\n\t\tfloat dotTL = dot( material.anisotropyT, lightDir );\n\t\tfloat dotTV = dot( material.anisotropyT, viewDir );\n\t\tfloat dotTH = dot( material.anisotropyT, halfDir );\n\t\tfloat dotBL = dot( material.anisotropyB, lightDir );\n\t\tfloat dotBV = dot( material.anisotropyB, viewDir );\n\t\tfloat dotBH = dot( material.anisotropyB, halfDir );\n\t\tfloat V = V_GGX_SmithCorrelated_Anisotropic( material.alphaT, alpha, dotTV, dotBV, dotTL, dotBL, dotNV, dotNL );\n\t\tfloat D = D_GGX_Anisotropic( material.alphaT, alpha, dotNH, dotTH, dotBH );\n\t#else\n\t\tfloat V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );\n\t\tfloat D = D_GGX( alpha, dotNH );\n\t#endif\n\treturn F * ( V * D );\n}\nvec2 LTC_Uv( const in vec3 N, const in vec3 V, const in float roughness ) {\n\tconst float LUT_SIZE = 64.0;\n\tconst float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;\n\tconst float LUT_BIAS = 0.5 / LUT_SIZE;\n\tfloat dotNV = saturate( dot( N, V ) );\n\tvec2 uv = vec2( roughness, sqrt( 1.0 - dotNV ) );\n\tuv = uv * LUT_SCALE + LUT_BIAS;\n\treturn uv;\n}\nfloat LTC_ClippedSphereFormFactor( const in vec3 f ) {\n\tfloat l = length( f );\n\treturn max( ( l * l + f.z ) / ( l + 1.0 ), 0.0 );\n}\nvec3 LTC_EdgeVectorFormFactor( const in vec3 v1, const in vec3 v2 ) {\n\tfloat x = dot( v1, v2 );\n\tfloat y = abs( x );\n\tfloat a = 0.8543985 + ( 0.4965155 + 0.0145206 * y ) * y;\n\tfloat b = 3.4175940 + ( 4.1616724 + y ) * y;\n\tfloat v = a / b;\n\tfloat theta_sintheta = ( x > 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;\n\treturn cross( v1, v2 ) * theta_sintheta;\n}\nvec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {\n\tvec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];\n\tvec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];\n\tvec3 lightNormal = cross( v1, v2 );\n\tif( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );\n\tvec3 T1, T2;\n\tT1 = normalize( V - N * dot( V, N ) );\n\tT2 = - cross( N, T1 );\n\tmat3 mat = mInv * transposeMat3( mat3( T1, T2, N ) );\n\tvec3 coords[ 4 ];\n\tcoords[ 0 ] = mat * ( rectCoords[ 0 ] - P );\n\tcoords[ 1 ] = mat * ( rectCoords[ 1 ] - P );\n\tcoords[ 2 ] = mat * ( rectCoords[ 2 ] - P );\n\tcoords[ 3 ] = mat * ( rectCoords[ 3 ] - P );\n\tcoords[ 0 ] = normalize( coords[ 0 ] );\n\tcoords[ 1 ] = normalize( coords[ 1 ] );\n\tcoords[ 2 ] = normalize( coords[ 2 ] );\n\tcoords[ 3 ] = normalize( coords[ 3 ] );\n\tvec3 vectorFormFactor = vec3( 0.0 );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );\n\tvectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );\n\tfloat result = LTC_ClippedSphereFormFactor( vectorFormFactor );\n\treturn vec3( result );\n}\n#if defined( USE_SHEEN )\nfloat D_Charlie( float roughness, float dotNH ) {\n\tfloat alpha = pow2( roughness );\n\tfloat invAlpha = 1.0 / alpha;\n\tfloat cos2h = dotNH * dotNH;\n\tfloat sin2h = max( 1.0 - cos2h, 0.0078125 );\n\treturn ( 2.0 + invAlpha ) * pow( sin2h, invAlpha * 0.5 ) / ( 2.0 * PI );\n}\nfloat V_Neubelt( float dotNV, float dotNL ) {\n\treturn saturate( 1.0 / ( 4.0 * ( dotNL + dotNV - dotNL * dotNV ) ) );\n}\nvec3 BRDF_Sheen( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, vec3 sheenColor, const in float sheenRoughness ) {\n\tvec3 halfDir = normalize( lightDir + viewDir );\n\tfloat dotNL = saturate( dot( normal, lightDir ) );\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tfloat dotNH = saturate( dot( normal, halfDir ) );\n\tfloat D = D_Charlie( sheenRoughness, dotNH );\n\tfloat V = V_Neubelt( dotNV, dotNL );\n\treturn sheenColor * ( D * V );\n}\n#endif\nfloat IBLSheenBRDF( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tfloat r2 = roughness * roughness;\n\tfloat a = roughness < 0.25 ? -339.2 * r2 + 161.4 * roughness - 25.9 : -8.48 * r2 + 14.3 * roughness - 9.95;\n\tfloat b = roughness < 0.25 ? 44.0 * r2 - 23.7 * roughness + 3.26 : 1.97 * r2 - 3.27 * roughness + 0.72;\n\tfloat DG = exp( a * dotNV + b ) + ( roughness < 0.25 ? 0.0 : 0.1 * ( roughness - 0.25 ) );\n\treturn saturate( DG * RECIPROCAL_PI );\n}\nvec2 DFGApprox( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {\n\tfloat dotNV = saturate( dot( normal, viewDir ) );\n\tconst vec4 c0 = vec4( - 1, - 0.0275, - 0.572, 0.022 );\n\tconst vec4 c1 = vec4( 1, 0.0425, 1.04, - 0.04 );\n\tvec4 r = roughness * c0 + c1;\n\tfloat a004 = min( r.x * r.x, exp2( - 9.28 * dotNV ) ) * r.x + r.y;\n\tvec2 fab = vec2( - 1.04, 1.04 ) * a004 + r.zw;\n\treturn fab;\n}\nvec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness ) {\n\tvec2 fab = DFGApprox( normal, viewDir, roughness );\n\treturn specularColor * fab.x + specularF90 * fab.y;\n}\n#ifdef USE_IRIDESCENCE\nvoid computeMultiscatteringIridescence( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float iridescence, const in vec3 iridescenceF0, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\n#else\nvoid computeMultiscattering( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) {\n#endif\n\tvec2 fab = DFGApprox( normal, viewDir, roughness );\n\t#ifdef USE_IRIDESCENCE\n\t\tvec3 Fr = mix( specularColor, iridescenceF0, iridescence );\n\t#else\n\t\tvec3 Fr = specularColor;\n\t#endif\n\tvec3 FssEss = Fr * fab.x + specularF90 * fab.y;\n\tfloat Ess = fab.x + fab.y;\n\tfloat Ems = 1.0 - Ess;\n\tvec3 Favg = Fr + ( 1.0 - Fr ) * 0.047619;\tvec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );\n\tsingleScatter += FssEss;\n\tmultiScatter += Fms * Ems;\n}\n#if NUM_RECT_AREA_LIGHTS > 0\n\tvoid RE_Direct_RectArea_Physical( const in RectAreaLight rectAreaLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\t\tvec3 normal = geometryNormal;\n\t\tvec3 viewDir = geometryViewDir;\n\t\tvec3 position = geometryPosition;\n\t\tvec3 lightPos = rectAreaLight.position;\n\t\tvec3 halfWidth = rectAreaLight.halfWidth;\n\t\tvec3 halfHeight = rectAreaLight.halfHeight;\n\t\tvec3 lightColor = rectAreaLight.color;\n\t\tfloat roughness = material.roughness;\n\t\tvec3 rectCoords[ 4 ];\n\t\trectCoords[ 0 ] = lightPos + halfWidth - halfHeight;\t\trectCoords[ 1 ] = lightPos - halfWidth - halfHeight;\n\t\trectCoords[ 2 ] = lightPos - halfWidth + halfHeight;\n\t\trectCoords[ 3 ] = lightPos + halfWidth + halfHeight;\n\t\tvec2 uv = LTC_Uv( normal, viewDir, roughness );\n\t\tvec4 t1 = texture2D( ltc_1, uv );\n\t\tvec4 t2 = texture2D( ltc_2, uv );\n\t\tmat3 mInv = mat3(\n\t\t\tvec3( t1.x, 0, t1.y ),\n\t\t\tvec3( 0, 1, 0 ),\n\t\t\tvec3( t1.z, 0, t1.w )\n\t\t);\n\t\tvec3 fresnel = ( material.specularColor * t2.x + ( vec3( 1.0 ) - material.specularColor ) * t2.y );\n\t\treflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );\n\t\treflectedLight.directDiffuse += lightColor * material.diffuseColor * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );\n\t}\n#endif\nvoid RE_Direct_Physical( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\tfloat dotNL = saturate( dot( geometryNormal, directLight.direction ) );\n\tvec3 irradiance = dotNL * directLight.color;\n\t#ifdef USE_CLEARCOAT\n\t\tfloat dotNLcc = saturate( dot( geometryClearcoatNormal, directLight.direction ) );\n\t\tvec3 ccIrradiance = dotNLcc * directLight.color;\n\t\tclearcoatSpecularDirect += ccIrradiance * BRDF_GGX_Clearcoat( directLight.direction, geometryViewDir, geometryClearcoatNormal, material );\n\t#endif\n\t#ifdef USE_SHEEN\n\t\tsheenSpecularDirect += irradiance * BRDF_Sheen( directLight.direction, geometryViewDir, geometryNormal, material.sheenColor, material.sheenRoughness );\n\t#endif\n\treflectedLight.directSpecular += irradiance * BRDF_GGX( directLight.direction, geometryViewDir, geometryNormal, material );\n\treflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectDiffuse_Physical( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {\n\treflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );\n}\nvoid RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradiance, const in vec3 clearcoatRadiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight) {\n\t#ifdef USE_CLEARCOAT\n\t\tclearcoatSpecularIndirect += clearcoatRadiance * EnvironmentBRDF( geometryClearcoatNormal, geometryViewDir, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );\n\t#endif\n\t#ifdef USE_SHEEN\n\t\tsheenSpecularIndirect += irradiance * material.sheenColor * IBLSheenBRDF( geometryNormal, geometryViewDir, material.sheenRoughness );\n\t#endif\n\tvec3 singleScattering = vec3( 0.0 );\n\tvec3 multiScattering = vec3( 0.0 );\n\tvec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;\n\t#ifdef USE_IRIDESCENCE\n\t\tcomputeMultiscatteringIridescence( geometryNormal, geometryViewDir, material.specularColor, material.specularF90, material.iridescence, material.iridescenceFresnel, material.roughness, singleScattering, multiScattering );\n\t#else\n\t\tcomputeMultiscattering( geometryNormal, geometryViewDir, material.specularColor, material.specularF90, material.roughness, singleScattering, multiScattering );\n\t#endif\n\tvec3 totalScattering = singleScattering + multiScattering;\n\tvec3 diffuse = material.diffuseColor * ( 1.0 - max( max( totalScattering.r, totalScattering.g ), totalScattering.b ) );\n\treflectedLight.indirectSpecular += radiance * singleScattering;\n\treflectedLight.indirectSpecular += multiScattering * cosineWeightedIrradiance;\n\treflectedLight.indirectDiffuse += diffuse * cosineWeightedIrradiance;\n}\n#define RE_Direct\t\t\t\tRE_Direct_Physical\n#define RE_Direct_RectArea\t\tRE_Direct_RectArea_Physical\n#define RE_IndirectDiffuse\t\tRE_IndirectDiffuse_Physical\n#define RE_IndirectSpecular\t\tRE_IndirectSpecular_Physical\nfloat computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {\n\treturn saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );\n}"; + +var lights_fragment_begin = "\nvec3 geometryPosition = - vViewPosition;\nvec3 geometryNormal = normal;\nvec3 geometryViewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );\nvec3 geometryClearcoatNormal = vec3( 0.0 );\n#ifdef USE_CLEARCOAT\n\tgeometryClearcoatNormal = clearcoatNormal;\n#endif\n#ifdef USE_IRIDESCENCE\n\tfloat dotNVi = saturate( dot( normal, geometryViewDir ) );\n\tif ( material.iridescenceThickness == 0.0 ) {\n\t\tmaterial.iridescence = 0.0;\n\t} else {\n\t\tmaterial.iridescence = saturate( material.iridescence );\n\t}\n\tif ( material.iridescence > 0.0 ) {\n\t\tmaterial.iridescenceFresnel = evalIridescence( 1.0, material.iridescenceIOR, dotNVi, material.iridescenceThickness, material.specularColor );\n\t\tmaterial.iridescenceF0 = Schlick_to_F0( material.iridescenceFresnel, 1.0, dotNVi );\n\t}\n#endif\nIncidentLight directLight;\n#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )\n\tPointLight pointLight;\n\t#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0\n\tPointLightShadow pointLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {\n\t\tpointLight = pointLights[ i ];\n\t\tgetPointLightInfo( pointLight, geometryPosition, directLight );\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS )\n\t\tpointLightShadow = pointLightShadows[ i ];\n\t\tdirectLight.color *= ( directLight.visible && receiveShadow ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )\n\tSpotLight spotLight;\n\tvec4 spotColor;\n\tvec3 spotLightCoord;\n\tbool inSpotLightMap;\n\t#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0\n\tSpotLightShadow spotLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {\n\t\tspotLight = spotLights[ i ];\n\t\tgetSpotLightInfo( spotLight, geometryPosition, directLight );\n\t\t#if ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS )\n\t\t#define SPOT_LIGHT_MAP_INDEX UNROLLED_LOOP_INDEX\n\t\t#elif ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\t#define SPOT_LIGHT_MAP_INDEX NUM_SPOT_LIGHT_MAPS\n\t\t#else\n\t\t#define SPOT_LIGHT_MAP_INDEX ( UNROLLED_LOOP_INDEX - NUM_SPOT_LIGHT_SHADOWS + NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS )\n\t\t#endif\n\t\t#if ( SPOT_LIGHT_MAP_INDEX < NUM_SPOT_LIGHT_MAPS )\n\t\t\tspotLightCoord = vSpotLightCoord[ i ].xyz / vSpotLightCoord[ i ].w;\n\t\t\tinSpotLightMap = all( lessThan( abs( spotLightCoord * 2. - 1. ), vec3( 1.0 ) ) );\n\t\t\tspotColor = texture2D( spotLightMap[ SPOT_LIGHT_MAP_INDEX ], spotLightCoord.xy );\n\t\t\tdirectLight.color = inSpotLightMap ? directLight.color * spotColor.rgb : directLight.color;\n\t\t#endif\n\t\t#undef SPOT_LIGHT_MAP_INDEX\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\tspotLightShadow = spotLightShadows[ i ];\n\t\tdirectLight.color *= ( directLight.visible && receiveShadow ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotLightCoord[ i ] ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct )\n\tDirectionalLight directionalLight;\n\t#if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0\n\tDirectionalLightShadow directionalLightShadow;\n\t#endif\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {\n\t\tdirectionalLight = directionalLights[ i ];\n\t\tgetDirectionalLightInfo( directionalLight, directLight );\n\t\t#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )\n\t\tdirectionalLightShadow = directionalLightShadows[ i ];\n\t\tdirectLight.color *= ( directLight.visible && receiveShadow ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\n\t\t#endif\n\t\tRE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )\n\tRectAreaLight rectAreaLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {\n\t\trectAreaLight = rectAreaLights[ i ];\n\t\tRE_Direct_RectArea( rectAreaLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n\t}\n\t#pragma unroll_loop_end\n#endif\n#if defined( RE_IndirectDiffuse )\n\tvec3 iblIrradiance = vec3( 0.0 );\n\tvec3 irradiance = getAmbientLightIrradiance( ambientLightColor );\n\t#if defined( USE_LIGHT_PROBES )\n\t\tirradiance += getLightProbeIrradiance( lightProbe, geometryNormal );\n\t#endif\n\t#if ( NUM_HEMI_LIGHTS > 0 )\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {\n\t\t\tirradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometryNormal );\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n#endif\n#if defined( RE_IndirectSpecular )\n\tvec3 radiance = vec3( 0.0 );\n\tvec3 clearcoatRadiance = vec3( 0.0 );\n#endif"; + +var lights_fragment_maps = "#if defined( RE_IndirectDiffuse )\n\t#ifdef USE_LIGHTMAP\n\t\tvec4 lightMapTexel = texture2D( lightMap, vLightMapUv );\n\t\tvec3 lightMapIrradiance = lightMapTexel.rgb * lightMapIntensity;\n\t\tirradiance += lightMapIrradiance;\n\t#endif\n\t#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )\n\t\tiblIrradiance += getIBLIrradiance( geometryNormal );\n\t#endif\n#endif\n#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )\n\t#ifdef USE_ANISOTROPY\n\t\tradiance += getIBLAnisotropyRadiance( geometryViewDir, geometryNormal, material.roughness, material.anisotropyB, material.anisotropy );\n\t#else\n\t\tradiance += getIBLRadiance( geometryViewDir, geometryNormal, material.roughness );\n\t#endif\n\t#ifdef USE_CLEARCOAT\n\t\tclearcoatRadiance += getIBLRadiance( geometryViewDir, geometryClearcoatNormal, material.clearcoatRoughness );\n\t#endif\n#endif"; + +var lights_fragment_end = "#if defined( RE_IndirectDiffuse )\n\tRE_IndirectDiffuse( irradiance, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n#endif\n#if defined( RE_IndirectSpecular )\n\tRE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );\n#endif"; + +var logdepthbuf_fragment = "#if defined( USE_LOGDEPTHBUF )\n\tgl_FragDepth = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;\n#endif"; + +var logdepthbuf_pars_fragment = "#if defined( USE_LOGDEPTHBUF )\n\tuniform float logDepthBufFC;\n\tvarying float vFragDepth;\n\tvarying float vIsPerspective;\n#endif"; + +var logdepthbuf_pars_vertex = "#ifdef USE_LOGDEPTHBUF\n\tvarying float vFragDepth;\n\tvarying float vIsPerspective;\n#endif"; + +var logdepthbuf_vertex = "#ifdef USE_LOGDEPTHBUF\n\tvFragDepth = 1.0 + gl_Position.w;\n\tvIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );\n#endif"; + +var map_fragment = "#ifdef USE_MAP\n\tvec4 sampledDiffuseColor = texture2D( map, vMapUv );\n\t#ifdef DECODE_VIDEO_TEXTURE\n\t\tsampledDiffuseColor = vec4( mix( pow( sampledDiffuseColor.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), sampledDiffuseColor.rgb * 0.0773993808, vec3( lessThanEqual( sampledDiffuseColor.rgb, vec3( 0.04045 ) ) ) ), sampledDiffuseColor.w );\n\t\n\t#endif\n\tdiffuseColor *= sampledDiffuseColor;\n#endif"; + +var map_pars_fragment = "#ifdef USE_MAP\n\tuniform sampler2D map;\n#endif"; + +var map_particle_fragment = "#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\n\t#if defined( USE_POINTS_UV )\n\t\tvec2 uv = vUv;\n\t#else\n\t\tvec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;\n\t#endif\n#endif\n#ifdef USE_MAP\n\tdiffuseColor *= texture2D( map, uv );\n#endif\n#ifdef USE_ALPHAMAP\n\tdiffuseColor.a *= texture2D( alphaMap, uv ).g;\n#endif"; + +var map_particle_pars_fragment = "#if defined( USE_POINTS_UV )\n\tvarying vec2 vUv;\n#else\n\t#if defined( USE_MAP ) || defined( USE_ALPHAMAP )\n\t\tuniform mat3 uvTransform;\n\t#endif\n#endif\n#ifdef USE_MAP\n\tuniform sampler2D map;\n#endif\n#ifdef USE_ALPHAMAP\n\tuniform sampler2D alphaMap;\n#endif"; + +var metalnessmap_fragment = "float metalnessFactor = metalness;\n#ifdef USE_METALNESSMAP\n\tvec4 texelMetalness = texture2D( metalnessMap, vMetalnessMapUv );\n\tmetalnessFactor *= texelMetalness.b;\n#endif"; + +var metalnessmap_pars_fragment = "#ifdef USE_METALNESSMAP\n\tuniform sampler2D metalnessMap;\n#endif"; + +var morphinstance_vertex = "#ifdef USE_INSTANCING_MORPH\n\tfloat morphTargetInfluences[ MORPHTARGETS_COUNT ];\n\tfloat morphTargetBaseInfluence = texelFetch( morphTexture, ivec2( 0, gl_InstanceID ), 0 ).r;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\tmorphTargetInfluences[i] = texelFetch( morphTexture, ivec2( i + 1, gl_InstanceID ), 0 ).r;\n\t}\n#endif"; + +var morphcolor_vertex = "#if defined( USE_MORPHCOLORS )\n\tvColor *= morphTargetBaseInfluence;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\t#if defined( USE_COLOR_ALPHA )\n\t\t\tif ( morphTargetInfluences[ i ] != 0.0 ) vColor += getMorph( gl_VertexID, i, 2 ) * morphTargetInfluences[ i ];\n\t\t#elif defined( USE_COLOR )\n\t\t\tif ( morphTargetInfluences[ i ] != 0.0 ) vColor += getMorph( gl_VertexID, i, 2 ).rgb * morphTargetInfluences[ i ];\n\t\t#endif\n\t}\n#endif"; + +var morphnormal_vertex = "#ifdef USE_MORPHNORMALS\n\tobjectNormal *= morphTargetBaseInfluence;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\tif ( morphTargetInfluences[ i ] != 0.0 ) objectNormal += getMorph( gl_VertexID, i, 1 ).xyz * morphTargetInfluences[ i ];\n\t}\n#endif"; + +var morphtarget_pars_vertex = "#ifdef USE_MORPHTARGETS\n\t#ifndef USE_INSTANCING_MORPH\n\t\tuniform float morphTargetBaseInfluence;\n\t\tuniform float morphTargetInfluences[ MORPHTARGETS_COUNT ];\n\t#endif\n\tuniform sampler2DArray morphTargetsTexture;\n\tuniform ivec2 morphTargetsTextureSize;\n\tvec4 getMorph( const in int vertexIndex, const in int morphTargetIndex, const in int offset ) {\n\t\tint texelIndex = vertexIndex * MORPHTARGETS_TEXTURE_STRIDE + offset;\n\t\tint y = texelIndex / morphTargetsTextureSize.x;\n\t\tint x = texelIndex - y * morphTargetsTextureSize.x;\n\t\tivec3 morphUV = ivec3( x, y, morphTargetIndex );\n\t\treturn texelFetch( morphTargetsTexture, morphUV, 0 );\n\t}\n#endif"; + +var morphtarget_vertex = "#ifdef USE_MORPHTARGETS\n\ttransformed *= morphTargetBaseInfluence;\n\tfor ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {\n\t\tif ( morphTargetInfluences[ i ] != 0.0 ) transformed += getMorph( gl_VertexID, i, 0 ).xyz * morphTargetInfluences[ i ];\n\t}\n#endif"; + +var normal_fragment_begin = "float faceDirection = gl_FrontFacing ? 1.0 : - 1.0;\n#ifdef FLAT_SHADED\n\tvec3 fdx = dFdx( vViewPosition );\n\tvec3 fdy = dFdy( vViewPosition );\n\tvec3 normal = normalize( cross( fdx, fdy ) );\n#else\n\tvec3 normal = normalize( vNormal );\n\t#ifdef DOUBLE_SIDED\n\t\tnormal *= faceDirection;\n\t#endif\n#endif\n#if defined( USE_NORMALMAP_TANGENTSPACE ) || defined( USE_CLEARCOAT_NORMALMAP ) || defined( USE_ANISOTROPY )\n\t#ifdef USE_TANGENT\n\t\tmat3 tbn = mat3( normalize( vTangent ), normalize( vBitangent ), normal );\n\t#else\n\t\tmat3 tbn = getTangentFrame( - vViewPosition, normal,\n\t\t#if defined( USE_NORMALMAP )\n\t\t\tvNormalMapUv\n\t\t#elif defined( USE_CLEARCOAT_NORMALMAP )\n\t\t\tvClearcoatNormalMapUv\n\t\t#else\n\t\t\tvUv\n\t\t#endif\n\t\t);\n\t#endif\n\t#if defined( DOUBLE_SIDED ) && ! defined( FLAT_SHADED )\n\t\ttbn[0] *= faceDirection;\n\t\ttbn[1] *= faceDirection;\n\t#endif\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\t#ifdef USE_TANGENT\n\t\tmat3 tbn2 = mat3( normalize( vTangent ), normalize( vBitangent ), normal );\n\t#else\n\t\tmat3 tbn2 = getTangentFrame( - vViewPosition, normal, vClearcoatNormalMapUv );\n\t#endif\n\t#if defined( DOUBLE_SIDED ) && ! defined( FLAT_SHADED )\n\t\ttbn2[0] *= faceDirection;\n\t\ttbn2[1] *= faceDirection;\n\t#endif\n#endif\nvec3 nonPerturbedNormal = normal;"; + +var normal_fragment_maps = "#ifdef USE_NORMALMAP_OBJECTSPACE\n\tnormal = texture2D( normalMap, vNormalMapUv ).xyz * 2.0 - 1.0;\n\t#ifdef FLIP_SIDED\n\t\tnormal = - normal;\n\t#endif\n\t#ifdef DOUBLE_SIDED\n\t\tnormal = normal * faceDirection;\n\t#endif\n\tnormal = normalize( normalMatrix * normal );\n#elif defined( USE_NORMALMAP_TANGENTSPACE )\n\tvec3 mapN = texture2D( normalMap, vNormalMapUv ).xyz * 2.0 - 1.0;\n\tmapN.xy *= normalScale;\n\tnormal = normalize( tbn * mapN );\n#elif defined( USE_BUMPMAP )\n\tnormal = perturbNormalArb( - vViewPosition, normal, dHdxy_fwd(), faceDirection );\n#endif"; + +var normal_pars_fragment = "#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n\t#ifdef USE_TANGENT\n\t\tvarying vec3 vTangent;\n\t\tvarying vec3 vBitangent;\n\t#endif\n#endif"; + +var normal_pars_vertex = "#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n\t#ifdef USE_TANGENT\n\t\tvarying vec3 vTangent;\n\t\tvarying vec3 vBitangent;\n\t#endif\n#endif"; + +var normal_vertex = "#ifndef FLAT_SHADED\n\tvNormal = normalize( transformedNormal );\n\t#ifdef USE_TANGENT\n\t\tvTangent = normalize( transformedTangent );\n\t\tvBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );\n\t#endif\n#endif"; + +var normalmap_pars_fragment = "#ifdef USE_NORMALMAP\n\tuniform sampler2D normalMap;\n\tuniform vec2 normalScale;\n#endif\n#ifdef USE_NORMALMAP_OBJECTSPACE\n\tuniform mat3 normalMatrix;\n#endif\n#if ! defined ( USE_TANGENT ) && ( defined ( USE_NORMALMAP_TANGENTSPACE ) || defined ( USE_CLEARCOAT_NORMALMAP ) || defined( USE_ANISOTROPY ) )\n\tmat3 getTangentFrame( vec3 eye_pos, vec3 surf_norm, vec2 uv ) {\n\t\tvec3 q0 = dFdx( eye_pos.xyz );\n\t\tvec3 q1 = dFdy( eye_pos.xyz );\n\t\tvec2 st0 = dFdx( uv.st );\n\t\tvec2 st1 = dFdy( uv.st );\n\t\tvec3 N = surf_norm;\n\t\tvec3 q1perp = cross( q1, N );\n\t\tvec3 q0perp = cross( N, q0 );\n\t\tvec3 T = q1perp * st0.x + q0perp * st1.x;\n\t\tvec3 B = q1perp * st0.y + q0perp * st1.y;\n\t\tfloat det = max( dot( T, T ), dot( B, B ) );\n\t\tfloat scale = ( det == 0.0 ) ? 0.0 : inversesqrt( det );\n\t\treturn mat3( T * scale, B * scale, N );\n\t}\n#endif"; + +var clearcoat_normal_fragment_begin = "#ifdef USE_CLEARCOAT\n\tvec3 clearcoatNormal = nonPerturbedNormal;\n#endif"; + +var clearcoat_normal_fragment_maps = "#ifdef USE_CLEARCOAT_NORMALMAP\n\tvec3 clearcoatMapN = texture2D( clearcoatNormalMap, vClearcoatNormalMapUv ).xyz * 2.0 - 1.0;\n\tclearcoatMapN.xy *= clearcoatNormalScale;\n\tclearcoatNormal = normalize( tbn2 * clearcoatMapN );\n#endif"; + +var clearcoat_pars_fragment = "#ifdef USE_CLEARCOATMAP\n\tuniform sampler2D clearcoatMap;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tuniform sampler2D clearcoatNormalMap;\n\tuniform vec2 clearcoatNormalScale;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tuniform sampler2D clearcoatRoughnessMap;\n#endif"; + +var iridescence_pars_fragment = "#ifdef USE_IRIDESCENCEMAP\n\tuniform sampler2D iridescenceMap;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tuniform sampler2D iridescenceThicknessMap;\n#endif"; + +var opaque_fragment = "#ifdef OPAQUE\ndiffuseColor.a = 1.0;\n#endif\n#ifdef USE_TRANSMISSION\ndiffuseColor.a *= material.transmissionAlpha;\n#endif\ngl_FragColor = vec4( outgoingLight, diffuseColor.a );"; + +var packing = "vec3 packNormalToRGB( const in vec3 normal ) {\n\treturn normalize( normal ) * 0.5 + 0.5;\n}\nvec3 unpackRGBToNormal( const in vec3 rgb ) {\n\treturn 2.0 * rgb.xyz - 1.0;\n}\nconst float PackUpscale = 256. / 255.;const float UnpackDownscale = 255. / 256.;\nconst vec3 PackFactors = vec3( 256. * 256. * 256., 256. * 256., 256. );\nconst vec4 UnpackFactors = UnpackDownscale / vec4( PackFactors, 1. );\nconst float ShiftRight8 = 1. / 256.;\nvec4 packDepthToRGBA( const in float v ) {\n\tvec4 r = vec4( fract( v * PackFactors ), v );\n\tr.yzw -= r.xyz * ShiftRight8;\treturn r * PackUpscale;\n}\nfloat unpackRGBAToDepth( const in vec4 v ) {\n\treturn dot( v, UnpackFactors );\n}\nvec2 packDepthToRG( in highp float v ) {\n\treturn packDepthToRGBA( v ).yx;\n}\nfloat unpackRGToDepth( const in highp vec2 v ) {\n\treturn unpackRGBAToDepth( vec4( v.xy, 0.0, 0.0 ) );\n}\nvec4 pack2HalfToRGBA( vec2 v ) {\n\tvec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ) );\n\treturn vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w );\n}\nvec2 unpackRGBATo2Half( vec4 v ) {\n\treturn vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );\n}\nfloat viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {\n\treturn ( viewZ + near ) / ( near - far );\n}\nfloat orthographicDepthToViewZ( const in float depth, const in float near, const in float far ) {\n\treturn depth * ( near - far ) - near;\n}\nfloat viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {\n\treturn ( ( near + viewZ ) * far ) / ( ( far - near ) * viewZ );\n}\nfloat perspectiveDepthToViewZ( const in float depth, const in float near, const in float far ) {\n\treturn ( near * far ) / ( ( far - near ) * depth - far );\n}"; + +var premultiplied_alpha_fragment = "#ifdef PREMULTIPLIED_ALPHA\n\tgl_FragColor.rgb *= gl_FragColor.a;\n#endif"; + +var project_vertex = "vec4 mvPosition = vec4( transformed, 1.0 );\n#ifdef USE_BATCHING\n\tmvPosition = batchingMatrix * mvPosition;\n#endif\n#ifdef USE_INSTANCING\n\tmvPosition = instanceMatrix * mvPosition;\n#endif\nmvPosition = modelViewMatrix * mvPosition;\ngl_Position = projectionMatrix * mvPosition;"; + +var dithering_fragment = "#ifdef DITHERING\n\tgl_FragColor.rgb = dithering( gl_FragColor.rgb );\n#endif"; + +var dithering_pars_fragment = "#ifdef DITHERING\n\tvec3 dithering( vec3 color ) {\n\t\tfloat grid_position = rand( gl_FragCoord.xy );\n\t\tvec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );\n\t\tdither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );\n\t\treturn color + dither_shift_RGB;\n\t}\n#endif"; + +var roughnessmap_fragment = "float roughnessFactor = roughness;\n#ifdef USE_ROUGHNESSMAP\n\tvec4 texelRoughness = texture2D( roughnessMap, vRoughnessMapUv );\n\troughnessFactor *= texelRoughness.g;\n#endif"; + +var roughnessmap_pars_fragment = "#ifdef USE_ROUGHNESSMAP\n\tuniform sampler2D roughnessMap;\n#endif"; + +var shadowmap_pars_fragment = "#if NUM_SPOT_LIGHT_COORDS > 0\n\tvarying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ];\n#endif\n#if NUM_SPOT_LIGHT_MAPS > 0\n\tuniform sampler2D spotLightMap[ NUM_SPOT_LIGHT_MAPS ];\n#endif\n#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tstruct DirectionalLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];\n\t\tstruct SpotLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\tuniform sampler2D pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tstruct PointLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t\tfloat shadowCameraNear;\n\t\t\tfloat shadowCameraFar;\n\t\t};\n\t\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\n\t#endif\n\tfloat texture2DCompare( sampler2D depths, vec2 uv, float compare ) {\n\t\treturn step( compare, unpackRGBAToDepth( texture2D( depths, uv ) ) );\n\t}\n\tvec2 texture2DDistribution( sampler2D shadow, vec2 uv ) {\n\t\treturn unpackRGBATo2Half( texture2D( shadow, uv ) );\n\t}\n\tfloat VSMShadow (sampler2D shadow, vec2 uv, float compare ){\n\t\tfloat occlusion = 1.0;\n\t\tvec2 distribution = texture2DDistribution( shadow, uv );\n\t\tfloat hard_shadow = step( compare , distribution.x );\n\t\tif (hard_shadow != 1.0 ) {\n\t\t\tfloat distance = compare - distribution.x ;\n\t\t\tfloat variance = max( 0.00000, distribution.y * distribution.y );\n\t\t\tfloat softness_probability = variance / (variance + distance * distance );\t\t\tsoftness_probability = clamp( ( softness_probability - 0.3 ) / ( 0.95 - 0.3 ), 0.0, 1.0 );\t\t\tocclusion = clamp( max( hard_shadow, softness_probability ), 0.0, 1.0 );\n\t\t}\n\t\treturn occlusion;\n\t}\n\tfloat getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord ) {\n\t\tfloat shadow = 1.0;\n\t\tshadowCoord.xyz /= shadowCoord.w;\n\t\tshadowCoord.z += shadowBias;\n\t\tbool inFrustum = shadowCoord.x >= 0.0 && shadowCoord.x <= 1.0 && shadowCoord.y >= 0.0 && shadowCoord.y <= 1.0;\n\t\tbool frustumTest = inFrustum && shadowCoord.z <= 1.0;\n\t\tif ( frustumTest ) {\n\t\t#if defined( SHADOWMAP_TYPE_PCF )\n\t\t\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\n\t\t\tfloat dx0 = - texelSize.x * shadowRadius;\n\t\t\tfloat dy0 = - texelSize.y * shadowRadius;\n\t\t\tfloat dx1 = + texelSize.x * shadowRadius;\n\t\t\tfloat dy1 = + texelSize.y * shadowRadius;\n\t\t\tfloat dx2 = dx0 / 2.0;\n\t\t\tfloat dy2 = dy0 / 2.0;\n\t\t\tfloat dx3 = dx1 / 2.0;\n\t\t\tfloat dy3 = dy1 / 2.0;\n\t\t\tshadow = (\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy2 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy3 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy1 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy1 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy1 ), shadowCoord.z )\n\t\t\t) * ( 1.0 / 17.0 );\n\t\t#elif defined( SHADOWMAP_TYPE_PCF_SOFT )\n\t\t\tvec2 texelSize = vec2( 1.0 ) / shadowMapSize;\n\t\t\tfloat dx = texelSize.x;\n\t\t\tfloat dy = texelSize.y;\n\t\t\tvec2 uv = shadowCoord.xy;\n\t\t\tvec2 f = fract( uv * shadowMapSize + 0.5 );\n\t\t\tuv -= f * texelSize;\n\t\t\tshadow = (\n\t\t\t\ttexture2DCompare( shadowMap, uv, shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + vec2( dx, 0.0 ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + vec2( 0.0, dy ), shadowCoord.z ) +\n\t\t\t\ttexture2DCompare( shadowMap, uv + texelSize, shadowCoord.z ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, 0.0 ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 0.0 ), shadowCoord.z ),\n\t\t\t\t\t f.x ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( -dx, dy ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, dy ), shadowCoord.z ),\n\t\t\t\t\t f.x ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( 0.0, -dy ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 0.0, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t f.y ) +\n\t\t\t\tmix( texture2DCompare( shadowMap, uv + vec2( dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t f.y ) +\n\t\t\t\tmix( mix( texture2DCompare( shadowMap, uv + vec2( -dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, -dy ), shadowCoord.z ),\n\t\t\t\t\t\t f.x ),\n\t\t\t\t\t mix( texture2DCompare( shadowMap, uv + vec2( -dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t\t texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 2.0 * dy ), shadowCoord.z ),\n\t\t\t\t\t\t f.x ),\n\t\t\t\t\t f.y )\n\t\t\t) * ( 1.0 / 9.0 );\n\t\t#elif defined( SHADOWMAP_TYPE_VSM )\n\t\t\tshadow = VSMShadow( shadowMap, shadowCoord.xy, shadowCoord.z );\n\t\t#else\n\t\t\tshadow = texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z );\n\t\t#endif\n\t\t}\n\t\treturn shadow;\n\t}\n\tvec2 cubeToUV( vec3 v, float texelSizeY ) {\n\t\tvec3 absV = abs( v );\n\t\tfloat scaleToCube = 1.0 / max( absV.x, max( absV.y, absV.z ) );\n\t\tabsV *= scaleToCube;\n\t\tv *= scaleToCube * ( 1.0 - 2.0 * texelSizeY );\n\t\tvec2 planar = v.xy;\n\t\tfloat almostATexel = 1.5 * texelSizeY;\n\t\tfloat almostOne = 1.0 - almostATexel;\n\t\tif ( absV.z >= almostOne ) {\n\t\t\tif ( v.z > 0.0 )\n\t\t\t\tplanar.x = 4.0 - v.x;\n\t\t} else if ( absV.x >= almostOne ) {\n\t\t\tfloat signX = sign( v.x );\n\t\t\tplanar.x = v.z * signX + 2.0 * signX;\n\t\t} else if ( absV.y >= almostOne ) {\n\t\t\tfloat signY = sign( v.y );\n\t\t\tplanar.x = v.x + 2.0 * signY + 2.0;\n\t\t\tplanar.y = v.z * signY - 2.0;\n\t\t}\n\t\treturn vec2( 0.125, 0.25 ) * planar + vec2( 0.375, 0.75 );\n\t}\n\tfloat getPointShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {\n\t\tfloat shadow = 1.0;\n\t\tvec3 lightToPosition = shadowCoord.xyz;\n\t\t\n\t\tfloat lightToPositionLength = length( lightToPosition );\n\t\tif ( lightToPositionLength - shadowCameraFar <= 0.0 && lightToPositionLength - shadowCameraNear >= 0.0 ) {\n\t\t\tfloat dp = ( lightToPositionLength - shadowCameraNear ) / ( shadowCameraFar - shadowCameraNear );\t\t\tdp += shadowBias;\n\t\t\tvec3 bd3D = normalize( lightToPosition );\n\t\t\tvec2 texelSize = vec2( 1.0 ) / ( shadowMapSize * vec2( 4.0, 2.0 ) );\n\t\t\t#if defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_PCF_SOFT ) || defined( SHADOWMAP_TYPE_VSM )\n\t\t\t\tvec2 offset = vec2( - 1, 1 ) * shadowRadius * texelSize.y;\n\t\t\t\tshadow = (\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyy, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyy, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyx, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyx, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxy, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxy, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxx, texelSize.y ), dp ) +\n\t\t\t\t\ttexture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxx, texelSize.y ), dp )\n\t\t\t\t) * ( 1.0 / 9.0 );\n\t\t\t#else\n\t\t\t\tshadow = texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp );\n\t\t\t#endif\n\t\t}\n\t\treturn shadow;\n\t}\n#endif"; + +var shadowmap_pars_vertex = "#if NUM_SPOT_LIGHT_COORDS > 0\n\tuniform mat4 spotLightMatrix[ NUM_SPOT_LIGHT_COORDS ];\n\tvarying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ];\n#endif\n#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\tuniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tvarying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];\n\t\tstruct DirectionalLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\t\tstruct SpotLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t};\n\t\tuniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\tuniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tvarying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];\n\t\tstruct PointLightShadow {\n\t\t\tfloat shadowBias;\n\t\t\tfloat shadowNormalBias;\n\t\t\tfloat shadowRadius;\n\t\t\tvec2 shadowMapSize;\n\t\t\tfloat shadowCameraNear;\n\t\t\tfloat shadowCameraFar;\n\t\t};\n\t\tuniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];\n\t#endif\n#endif"; + +var shadowmap_vertex = "#if ( defined( USE_SHADOWMAP ) && ( NUM_DIR_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0 ) ) || ( NUM_SPOT_LIGHT_COORDS > 0 )\n\tvec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );\n\tvec4 shadowWorldPosition;\n#endif\n#if defined( USE_SHADOWMAP )\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\n\t\t\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );\n\t\t\tvDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\t\t#pragma unroll_loop_start\n\t\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\n\t\t\tshadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );\n\t\t\tvPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;\n\t\t}\n\t\t#pragma unroll_loop_end\n\t#endif\n#endif\n#if NUM_SPOT_LIGHT_COORDS > 0\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHT_COORDS; i ++ ) {\n\t\tshadowWorldPosition = worldPosition;\n\t\t#if ( defined( USE_SHADOWMAP ) && UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )\n\t\t\tshadowWorldPosition.xyz += shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias;\n\t\t#endif\n\t\tvSpotLightCoord[ i ] = spotLightMatrix[ i ] * shadowWorldPosition;\n\t}\n\t#pragma unroll_loop_end\n#endif"; + +var shadowmask_pars_fragment = "float getShadowMask() {\n\tfloat shadow = 1.0;\n\t#ifdef USE_SHADOWMAP\n\t#if NUM_DIR_LIGHT_SHADOWS > 0\n\tDirectionalLightShadow directionalLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {\n\t\tdirectionalLight = directionalLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_SPOT_LIGHT_SHADOWS > 0\n\tSpotLightShadow spotLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {\n\t\tspotLight = spotLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowBias, spotLight.shadowRadius, vSpotLightCoord[ i ] ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#if NUM_POINT_LIGHT_SHADOWS > 0\n\tPointLightShadow pointLight;\n\t#pragma unroll_loop_start\n\tfor ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {\n\t\tpointLight = pointLightShadows[ i ];\n\t\tshadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;\n\t}\n\t#pragma unroll_loop_end\n\t#endif\n\t#endif\n\treturn shadow;\n}"; + +var skinbase_vertex = "#ifdef USE_SKINNING\n\tmat4 boneMatX = getBoneMatrix( skinIndex.x );\n\tmat4 boneMatY = getBoneMatrix( skinIndex.y );\n\tmat4 boneMatZ = getBoneMatrix( skinIndex.z );\n\tmat4 boneMatW = getBoneMatrix( skinIndex.w );\n#endif"; + +var skinning_pars_vertex = "#ifdef USE_SKINNING\n\tuniform mat4 bindMatrix;\n\tuniform mat4 bindMatrixInverse;\n\tuniform highp sampler2D boneTexture;\n\tmat4 getBoneMatrix( const in float i ) {\n\t\tint size = textureSize( boneTexture, 0 ).x;\n\t\tint j = int( i ) * 4;\n\t\tint x = j % size;\n\t\tint y = j / size;\n\t\tvec4 v1 = texelFetch( boneTexture, ivec2( x, y ), 0 );\n\t\tvec4 v2 = texelFetch( boneTexture, ivec2( x + 1, y ), 0 );\n\t\tvec4 v3 = texelFetch( boneTexture, ivec2( x + 2, y ), 0 );\n\t\tvec4 v4 = texelFetch( boneTexture, ivec2( x + 3, y ), 0 );\n\t\treturn mat4( v1, v2, v3, v4 );\n\t}\n#endif"; + +var skinning_vertex = "#ifdef USE_SKINNING\n\tvec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );\n\tvec4 skinned = vec4( 0.0 );\n\tskinned += boneMatX * skinVertex * skinWeight.x;\n\tskinned += boneMatY * skinVertex * skinWeight.y;\n\tskinned += boneMatZ * skinVertex * skinWeight.z;\n\tskinned += boneMatW * skinVertex * skinWeight.w;\n\ttransformed = ( bindMatrixInverse * skinned ).xyz;\n#endif"; + +var skinnormal_vertex = "#ifdef USE_SKINNING\n\tmat4 skinMatrix = mat4( 0.0 );\n\tskinMatrix += skinWeight.x * boneMatX;\n\tskinMatrix += skinWeight.y * boneMatY;\n\tskinMatrix += skinWeight.z * boneMatZ;\n\tskinMatrix += skinWeight.w * boneMatW;\n\tskinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;\n\tobjectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;\n\t#ifdef USE_TANGENT\n\t\tobjectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;\n\t#endif\n#endif"; + +var specularmap_fragment = "float specularStrength;\n#ifdef USE_SPECULARMAP\n\tvec4 texelSpecular = texture2D( specularMap, vSpecularMapUv );\n\tspecularStrength = texelSpecular.r;\n#else\n\tspecularStrength = 1.0;\n#endif"; + +var specularmap_pars_fragment = "#ifdef USE_SPECULARMAP\n\tuniform sampler2D specularMap;\n#endif"; + +var tonemapping_fragment = "#if defined( TONE_MAPPING )\n\tgl_FragColor.rgb = toneMapping( gl_FragColor.rgb );\n#endif"; + +var tonemapping_pars_fragment = "#ifndef saturate\n#define saturate( a ) clamp( a, 0.0, 1.0 )\n#endif\nuniform float toneMappingExposure;\nvec3 LinearToneMapping( vec3 color ) {\n\treturn saturate( toneMappingExposure * color );\n}\nvec3 ReinhardToneMapping( vec3 color ) {\n\tcolor *= toneMappingExposure;\n\treturn saturate( color / ( vec3( 1.0 ) + color ) );\n}\nvec3 OptimizedCineonToneMapping( vec3 color ) {\n\tcolor *= toneMappingExposure;\n\tcolor = max( vec3( 0.0 ), color - 0.004 );\n\treturn pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );\n}\nvec3 RRTAndODTFit( vec3 v ) {\n\tvec3 a = v * ( v + 0.0245786 ) - 0.000090537;\n\tvec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;\n\treturn a / b;\n}\nvec3 ACESFilmicToneMapping( vec3 color ) {\n\tconst mat3 ACESInputMat = mat3(\n\t\tvec3( 0.59719, 0.07600, 0.02840 ),\t\tvec3( 0.35458, 0.90834, 0.13383 ),\n\t\tvec3( 0.04823, 0.01566, 0.83777 )\n\t);\n\tconst mat3 ACESOutputMat = mat3(\n\t\tvec3( 1.60475, -0.10208, -0.00327 ),\t\tvec3( -0.53108, 1.10813, -0.07276 ),\n\t\tvec3( -0.07367, -0.00605, 1.07602 )\n\t);\n\tcolor *= toneMappingExposure / 0.6;\n\tcolor = ACESInputMat * color;\n\tcolor = RRTAndODTFit( color );\n\tcolor = ACESOutputMat * color;\n\treturn saturate( color );\n}\nconst mat3 LINEAR_REC2020_TO_LINEAR_SRGB = mat3(\n\tvec3( 1.6605, - 0.1246, - 0.0182 ),\n\tvec3( - 0.5876, 1.1329, - 0.1006 ),\n\tvec3( - 0.0728, - 0.0083, 1.1187 )\n);\nconst mat3 LINEAR_SRGB_TO_LINEAR_REC2020 = mat3(\n\tvec3( 0.6274, 0.0691, 0.0164 ),\n\tvec3( 0.3293, 0.9195, 0.0880 ),\n\tvec3( 0.0433, 0.0113, 0.8956 )\n);\nvec3 agxDefaultContrastApprox( vec3 x ) {\n\tvec3 x2 = x * x;\n\tvec3 x4 = x2 * x2;\n\treturn + 15.5 * x4 * x2\n\t\t- 40.14 * x4 * x\n\t\t+ 31.96 * x4\n\t\t- 6.868 * x2 * x\n\t\t+ 0.4298 * x2\n\t\t+ 0.1191 * x\n\t\t- 0.00232;\n}\nvec3 AgXToneMapping( vec3 color ) {\n\tconst mat3 AgXInsetMatrix = mat3(\n\t\tvec3( 0.856627153315983, 0.137318972929847, 0.11189821299995 ),\n\t\tvec3( 0.0951212405381588, 0.761241990602591, 0.0767994186031903 ),\n\t\tvec3( 0.0482516061458583, 0.101439036467562, 0.811302368396859 )\n\t);\n\tconst mat3 AgXOutsetMatrix = mat3(\n\t\tvec3( 1.1271005818144368, - 0.1413297634984383, - 0.14132976349843826 ),\n\t\tvec3( - 0.11060664309660323, 1.157823702216272, - 0.11060664309660294 ),\n\t\tvec3( - 0.016493938717834573, - 0.016493938717834257, 1.2519364065950405 )\n\t);\n\tconst float AgxMinEv = - 12.47393;\tconst float AgxMaxEv = 4.026069;\n\tcolor *= toneMappingExposure;\n\tcolor = LINEAR_SRGB_TO_LINEAR_REC2020 * color;\n\tcolor = AgXInsetMatrix * color;\n\tcolor = max( color, 1e-10 );\tcolor = log2( color );\n\tcolor = ( color - AgxMinEv ) / ( AgxMaxEv - AgxMinEv );\n\tcolor = clamp( color, 0.0, 1.0 );\n\tcolor = agxDefaultContrastApprox( color );\n\tcolor = AgXOutsetMatrix * color;\n\tcolor = pow( max( vec3( 0.0 ), color ), vec3( 2.2 ) );\n\tcolor = LINEAR_REC2020_TO_LINEAR_SRGB * color;\n\tcolor = clamp( color, 0.0, 1.0 );\n\treturn color;\n}\nvec3 NeutralToneMapping( vec3 color ) {\n\tconst float StartCompression = 0.8 - 0.04;\n\tconst float Desaturation = 0.15;\n\tcolor *= toneMappingExposure;\n\tfloat x = min( color.r, min( color.g, color.b ) );\n\tfloat offset = x < 0.08 ? x - 6.25 * x * x : 0.04;\n\tcolor -= offset;\n\tfloat peak = max( color.r, max( color.g, color.b ) );\n\tif ( peak < StartCompression ) return color;\n\tfloat d = 1. - StartCompression;\n\tfloat newPeak = 1. - d * d / ( peak + d - StartCompression );\n\tcolor *= newPeak / peak;\n\tfloat g = 1. - 1. / ( Desaturation * ( peak - newPeak ) + 1. );\n\treturn mix( color, vec3( newPeak ), g );\n}\nvec3 CustomToneMapping( vec3 color ) { return color; }"; + +var transmission_fragment = "#ifdef USE_TRANSMISSION\n\tmaterial.transmission = transmission;\n\tmaterial.transmissionAlpha = 1.0;\n\tmaterial.thickness = thickness;\n\tmaterial.attenuationDistance = attenuationDistance;\n\tmaterial.attenuationColor = attenuationColor;\n\t#ifdef USE_TRANSMISSIONMAP\n\t\tmaterial.transmission *= texture2D( transmissionMap, vTransmissionMapUv ).r;\n\t#endif\n\t#ifdef USE_THICKNESSMAP\n\t\tmaterial.thickness *= texture2D( thicknessMap, vThicknessMapUv ).g;\n\t#endif\n\tvec3 pos = vWorldPosition;\n\tvec3 v = normalize( cameraPosition - pos );\n\tvec3 n = inverseTransformDirection( normal, viewMatrix );\n\tvec4 transmitted = getIBLVolumeRefraction(\n\t\tn, v, material.roughness, material.diffuseColor, material.specularColor, material.specularF90,\n\t\tpos, modelMatrix, viewMatrix, projectionMatrix, material.dispersion, material.ior, material.thickness,\n\t\tmaterial.attenuationColor, material.attenuationDistance );\n\tmaterial.transmissionAlpha = mix( material.transmissionAlpha, transmitted.a, material.transmission );\n\ttotalDiffuse = mix( totalDiffuse, transmitted.rgb, material.transmission );\n#endif"; + +var transmission_pars_fragment = "#ifdef USE_TRANSMISSION\n\tuniform float transmission;\n\tuniform float thickness;\n\tuniform float attenuationDistance;\n\tuniform vec3 attenuationColor;\n\t#ifdef USE_TRANSMISSIONMAP\n\t\tuniform sampler2D transmissionMap;\n\t#endif\n\t#ifdef USE_THICKNESSMAP\n\t\tuniform sampler2D thicknessMap;\n\t#endif\n\tuniform vec2 transmissionSamplerSize;\n\tuniform sampler2D transmissionSamplerMap;\n\tuniform mat4 modelMatrix;\n\tuniform mat4 projectionMatrix;\n\tvarying vec3 vWorldPosition;\n\tfloat w0( float a ) {\n\t\treturn ( 1.0 / 6.0 ) * ( a * ( a * ( - a + 3.0 ) - 3.0 ) + 1.0 );\n\t}\n\tfloat w1( float a ) {\n\t\treturn ( 1.0 / 6.0 ) * ( a * a * ( 3.0 * a - 6.0 ) + 4.0 );\n\t}\n\tfloat w2( float a ){\n\t\treturn ( 1.0 / 6.0 ) * ( a * ( a * ( - 3.0 * a + 3.0 ) + 3.0 ) + 1.0 );\n\t}\n\tfloat w3( float a ) {\n\t\treturn ( 1.0 / 6.0 ) * ( a * a * a );\n\t}\n\tfloat g0( float a ) {\n\t\treturn w0( a ) + w1( a );\n\t}\n\tfloat g1( float a ) {\n\t\treturn w2( a ) + w3( a );\n\t}\n\tfloat h0( float a ) {\n\t\treturn - 1.0 + w1( a ) / ( w0( a ) + w1( a ) );\n\t}\n\tfloat h1( float a ) {\n\t\treturn 1.0 + w3( a ) / ( w2( a ) + w3( a ) );\n\t}\n\tvec4 bicubic( sampler2D tex, vec2 uv, vec4 texelSize, float lod ) {\n\t\tuv = uv * texelSize.zw + 0.5;\n\t\tvec2 iuv = floor( uv );\n\t\tvec2 fuv = fract( uv );\n\t\tfloat g0x = g0( fuv.x );\n\t\tfloat g1x = g1( fuv.x );\n\t\tfloat h0x = h0( fuv.x );\n\t\tfloat h1x = h1( fuv.x );\n\t\tfloat h0y = h0( fuv.y );\n\t\tfloat h1y = h1( fuv.y );\n\t\tvec2 p0 = ( vec2( iuv.x + h0x, iuv.y + h0y ) - 0.5 ) * texelSize.xy;\n\t\tvec2 p1 = ( vec2( iuv.x + h1x, iuv.y + h0y ) - 0.5 ) * texelSize.xy;\n\t\tvec2 p2 = ( vec2( iuv.x + h0x, iuv.y + h1y ) - 0.5 ) * texelSize.xy;\n\t\tvec2 p3 = ( vec2( iuv.x + h1x, iuv.y + h1y ) - 0.5 ) * texelSize.xy;\n\t\treturn g0( fuv.y ) * ( g0x * textureLod( tex, p0, lod ) + g1x * textureLod( tex, p1, lod ) ) +\n\t\t\tg1( fuv.y ) * ( g0x * textureLod( tex, p2, lod ) + g1x * textureLod( tex, p3, lod ) );\n\t}\n\tvec4 textureBicubic( sampler2D sampler, vec2 uv, float lod ) {\n\t\tvec2 fLodSize = vec2( textureSize( sampler, int( lod ) ) );\n\t\tvec2 cLodSize = vec2( textureSize( sampler, int( lod + 1.0 ) ) );\n\t\tvec2 fLodSizeInv = 1.0 / fLodSize;\n\t\tvec2 cLodSizeInv = 1.0 / cLodSize;\n\t\tvec4 fSample = bicubic( sampler, uv, vec4( fLodSizeInv, fLodSize ), floor( lod ) );\n\t\tvec4 cSample = bicubic( sampler, uv, vec4( cLodSizeInv, cLodSize ), ceil( lod ) );\n\t\treturn mix( fSample, cSample, fract( lod ) );\n\t}\n\tvec3 getVolumeTransmissionRay( const in vec3 n, const in vec3 v, const in float thickness, const in float ior, const in mat4 modelMatrix ) {\n\t\tvec3 refractionVector = refract( - v, normalize( n ), 1.0 / ior );\n\t\tvec3 modelScale;\n\t\tmodelScale.x = length( vec3( modelMatrix[ 0 ].xyz ) );\n\t\tmodelScale.y = length( vec3( modelMatrix[ 1 ].xyz ) );\n\t\tmodelScale.z = length( vec3( modelMatrix[ 2 ].xyz ) );\n\t\treturn normalize( refractionVector ) * thickness * modelScale;\n\t}\n\tfloat applyIorToRoughness( const in float roughness, const in float ior ) {\n\t\treturn roughness * clamp( ior * 2.0 - 2.0, 0.0, 1.0 );\n\t}\n\tvec4 getTransmissionSample( const in vec2 fragCoord, const in float roughness, const in float ior ) {\n\t\tfloat lod = log2( transmissionSamplerSize.x ) * applyIorToRoughness( roughness, ior );\n\t\treturn textureBicubic( transmissionSamplerMap, fragCoord.xy, lod );\n\t}\n\tvec3 volumeAttenuation( const in float transmissionDistance, const in vec3 attenuationColor, const in float attenuationDistance ) {\n\t\tif ( isinf( attenuationDistance ) ) {\n\t\t\treturn vec3( 1.0 );\n\t\t} else {\n\t\t\tvec3 attenuationCoefficient = -log( attenuationColor ) / attenuationDistance;\n\t\t\tvec3 transmittance = exp( - attenuationCoefficient * transmissionDistance );\t\t\treturn transmittance;\n\t\t}\n\t}\n\tvec4 getIBLVolumeRefraction( const in vec3 n, const in vec3 v, const in float roughness, const in vec3 diffuseColor,\n\t\tconst in vec3 specularColor, const in float specularF90, const in vec3 position, const in mat4 modelMatrix,\n\t\tconst in mat4 viewMatrix, const in mat4 projMatrix, const in float dispersion, const in float ior, const in float thickness,\n\t\tconst in vec3 attenuationColor, const in float attenuationDistance ) {\n\t\tvec4 transmittedLight;\n\t\tvec3 transmittance;\n\t\t#ifdef USE_DISPERSION\n\t\t\tfloat halfSpread = ( ior - 1.0 ) * 0.025 * dispersion;\n\t\t\tvec3 iors = vec3( ior - halfSpread, ior, ior + halfSpread );\n\t\t\tfor ( int i = 0; i < 3; i ++ ) {\n\t\t\t\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, iors[ i ], modelMatrix );\n\t\t\t\tvec3 refractedRayExit = position + transmissionRay;\n\t\t\n\t\t\t\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\n\t\t\t\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\n\t\t\t\trefractionCoords += 1.0;\n\t\t\t\trefractionCoords /= 2.0;\n\t\t\n\t\t\t\tvec4 transmissionSample = getTransmissionSample( refractionCoords, roughness, iors[ i ] );\n\t\t\t\ttransmittedLight[ i ] = transmissionSample[ i ];\n\t\t\t\ttransmittedLight.a += transmissionSample.a;\n\t\t\t\ttransmittance[ i ] = diffuseColor[ i ] * volumeAttenuation( length( transmissionRay ), attenuationColor, attenuationDistance )[ i ];\n\t\t\t}\n\t\t\ttransmittedLight.a /= 3.0;\n\t\t\n\t\t#else\n\t\t\n\t\t\tvec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, ior, modelMatrix );\n\t\t\tvec3 refractedRayExit = position + transmissionRay;\n\t\t\tvec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );\n\t\t\tvec2 refractionCoords = ndcPos.xy / ndcPos.w;\n\t\t\trefractionCoords += 1.0;\n\t\t\trefractionCoords /= 2.0;\n\t\t\ttransmittedLight = getTransmissionSample( refractionCoords, roughness, ior );\n\t\t\ttransmittance = diffuseColor * volumeAttenuation( length( transmissionRay ), attenuationColor, attenuationDistance );\n\t\t\n\t\t#endif\n\t\tvec3 attenuatedColor = transmittance * transmittedLight.rgb;\n\t\tvec3 F = EnvironmentBRDF( n, v, specularColor, specularF90, roughness );\n\t\tfloat transmittanceFactor = ( transmittance.r + transmittance.g + transmittance.b ) / 3.0;\n\t\treturn vec4( ( 1.0 - F ) * attenuatedColor, 1.0 - ( 1.0 - transmittedLight.a ) * transmittanceFactor );\n\t}\n#endif"; + +var uv_pars_fragment = "#if defined( USE_UV ) || defined( USE_ANISOTROPY )\n\tvarying vec2 vUv;\n#endif\n#ifdef USE_MAP\n\tvarying vec2 vMapUv;\n#endif\n#ifdef USE_ALPHAMAP\n\tvarying vec2 vAlphaMapUv;\n#endif\n#ifdef USE_LIGHTMAP\n\tvarying vec2 vLightMapUv;\n#endif\n#ifdef USE_AOMAP\n\tvarying vec2 vAoMapUv;\n#endif\n#ifdef USE_BUMPMAP\n\tvarying vec2 vBumpMapUv;\n#endif\n#ifdef USE_NORMALMAP\n\tvarying vec2 vNormalMapUv;\n#endif\n#ifdef USE_EMISSIVEMAP\n\tvarying vec2 vEmissiveMapUv;\n#endif\n#ifdef USE_METALNESSMAP\n\tvarying vec2 vMetalnessMapUv;\n#endif\n#ifdef USE_ROUGHNESSMAP\n\tvarying vec2 vRoughnessMapUv;\n#endif\n#ifdef USE_ANISOTROPYMAP\n\tvarying vec2 vAnisotropyMapUv;\n#endif\n#ifdef USE_CLEARCOATMAP\n\tvarying vec2 vClearcoatMapUv;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tvarying vec2 vClearcoatNormalMapUv;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tvarying vec2 vClearcoatRoughnessMapUv;\n#endif\n#ifdef USE_IRIDESCENCEMAP\n\tvarying vec2 vIridescenceMapUv;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tvarying vec2 vIridescenceThicknessMapUv;\n#endif\n#ifdef USE_SHEEN_COLORMAP\n\tvarying vec2 vSheenColorMapUv;\n#endif\n#ifdef USE_SHEEN_ROUGHNESSMAP\n\tvarying vec2 vSheenRoughnessMapUv;\n#endif\n#ifdef USE_SPECULARMAP\n\tvarying vec2 vSpecularMapUv;\n#endif\n#ifdef USE_SPECULAR_COLORMAP\n\tvarying vec2 vSpecularColorMapUv;\n#endif\n#ifdef USE_SPECULAR_INTENSITYMAP\n\tvarying vec2 vSpecularIntensityMapUv;\n#endif\n#ifdef USE_TRANSMISSIONMAP\n\tuniform mat3 transmissionMapTransform;\n\tvarying vec2 vTransmissionMapUv;\n#endif\n#ifdef USE_THICKNESSMAP\n\tuniform mat3 thicknessMapTransform;\n\tvarying vec2 vThicknessMapUv;\n#endif"; + +var uv_pars_vertex = "#if defined( USE_UV ) || defined( USE_ANISOTROPY )\n\tvarying vec2 vUv;\n#endif\n#ifdef USE_MAP\n\tuniform mat3 mapTransform;\n\tvarying vec2 vMapUv;\n#endif\n#ifdef USE_ALPHAMAP\n\tuniform mat3 alphaMapTransform;\n\tvarying vec2 vAlphaMapUv;\n#endif\n#ifdef USE_LIGHTMAP\n\tuniform mat3 lightMapTransform;\n\tvarying vec2 vLightMapUv;\n#endif\n#ifdef USE_AOMAP\n\tuniform mat3 aoMapTransform;\n\tvarying vec2 vAoMapUv;\n#endif\n#ifdef USE_BUMPMAP\n\tuniform mat3 bumpMapTransform;\n\tvarying vec2 vBumpMapUv;\n#endif\n#ifdef USE_NORMALMAP\n\tuniform mat3 normalMapTransform;\n\tvarying vec2 vNormalMapUv;\n#endif\n#ifdef USE_DISPLACEMENTMAP\n\tuniform mat3 displacementMapTransform;\n\tvarying vec2 vDisplacementMapUv;\n#endif\n#ifdef USE_EMISSIVEMAP\n\tuniform mat3 emissiveMapTransform;\n\tvarying vec2 vEmissiveMapUv;\n#endif\n#ifdef USE_METALNESSMAP\n\tuniform mat3 metalnessMapTransform;\n\tvarying vec2 vMetalnessMapUv;\n#endif\n#ifdef USE_ROUGHNESSMAP\n\tuniform mat3 roughnessMapTransform;\n\tvarying vec2 vRoughnessMapUv;\n#endif\n#ifdef USE_ANISOTROPYMAP\n\tuniform mat3 anisotropyMapTransform;\n\tvarying vec2 vAnisotropyMapUv;\n#endif\n#ifdef USE_CLEARCOATMAP\n\tuniform mat3 clearcoatMapTransform;\n\tvarying vec2 vClearcoatMapUv;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tuniform mat3 clearcoatNormalMapTransform;\n\tvarying vec2 vClearcoatNormalMapUv;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tuniform mat3 clearcoatRoughnessMapTransform;\n\tvarying vec2 vClearcoatRoughnessMapUv;\n#endif\n#ifdef USE_SHEEN_COLORMAP\n\tuniform mat3 sheenColorMapTransform;\n\tvarying vec2 vSheenColorMapUv;\n#endif\n#ifdef USE_SHEEN_ROUGHNESSMAP\n\tuniform mat3 sheenRoughnessMapTransform;\n\tvarying vec2 vSheenRoughnessMapUv;\n#endif\n#ifdef USE_IRIDESCENCEMAP\n\tuniform mat3 iridescenceMapTransform;\n\tvarying vec2 vIridescenceMapUv;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tuniform mat3 iridescenceThicknessMapTransform;\n\tvarying vec2 vIridescenceThicknessMapUv;\n#endif\n#ifdef USE_SPECULARMAP\n\tuniform mat3 specularMapTransform;\n\tvarying vec2 vSpecularMapUv;\n#endif\n#ifdef USE_SPECULAR_COLORMAP\n\tuniform mat3 specularColorMapTransform;\n\tvarying vec2 vSpecularColorMapUv;\n#endif\n#ifdef USE_SPECULAR_INTENSITYMAP\n\tuniform mat3 specularIntensityMapTransform;\n\tvarying vec2 vSpecularIntensityMapUv;\n#endif\n#ifdef USE_TRANSMISSIONMAP\n\tuniform mat3 transmissionMapTransform;\n\tvarying vec2 vTransmissionMapUv;\n#endif\n#ifdef USE_THICKNESSMAP\n\tuniform mat3 thicknessMapTransform;\n\tvarying vec2 vThicknessMapUv;\n#endif"; + +var uv_vertex = "#if defined( USE_UV ) || defined( USE_ANISOTROPY )\n\tvUv = vec3( uv, 1 ).xy;\n#endif\n#ifdef USE_MAP\n\tvMapUv = ( mapTransform * vec3( MAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_ALPHAMAP\n\tvAlphaMapUv = ( alphaMapTransform * vec3( ALPHAMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_LIGHTMAP\n\tvLightMapUv = ( lightMapTransform * vec3( LIGHTMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_AOMAP\n\tvAoMapUv = ( aoMapTransform * vec3( AOMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_BUMPMAP\n\tvBumpMapUv = ( bumpMapTransform * vec3( BUMPMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_NORMALMAP\n\tvNormalMapUv = ( normalMapTransform * vec3( NORMALMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_DISPLACEMENTMAP\n\tvDisplacementMapUv = ( displacementMapTransform * vec3( DISPLACEMENTMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_EMISSIVEMAP\n\tvEmissiveMapUv = ( emissiveMapTransform * vec3( EMISSIVEMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_METALNESSMAP\n\tvMetalnessMapUv = ( metalnessMapTransform * vec3( METALNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_ROUGHNESSMAP\n\tvRoughnessMapUv = ( roughnessMapTransform * vec3( ROUGHNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_ANISOTROPYMAP\n\tvAnisotropyMapUv = ( anisotropyMapTransform * vec3( ANISOTROPYMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_CLEARCOATMAP\n\tvClearcoatMapUv = ( clearcoatMapTransform * vec3( CLEARCOATMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_CLEARCOAT_NORMALMAP\n\tvClearcoatNormalMapUv = ( clearcoatNormalMapTransform * vec3( CLEARCOAT_NORMALMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_CLEARCOAT_ROUGHNESSMAP\n\tvClearcoatRoughnessMapUv = ( clearcoatRoughnessMapTransform * vec3( CLEARCOAT_ROUGHNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_IRIDESCENCEMAP\n\tvIridescenceMapUv = ( iridescenceMapTransform * vec3( IRIDESCENCEMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_IRIDESCENCE_THICKNESSMAP\n\tvIridescenceThicknessMapUv = ( iridescenceThicknessMapTransform * vec3( IRIDESCENCE_THICKNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SHEEN_COLORMAP\n\tvSheenColorMapUv = ( sheenColorMapTransform * vec3( SHEEN_COLORMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SHEEN_ROUGHNESSMAP\n\tvSheenRoughnessMapUv = ( sheenRoughnessMapTransform * vec3( SHEEN_ROUGHNESSMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SPECULARMAP\n\tvSpecularMapUv = ( specularMapTransform * vec3( SPECULARMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SPECULAR_COLORMAP\n\tvSpecularColorMapUv = ( specularColorMapTransform * vec3( SPECULAR_COLORMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_SPECULAR_INTENSITYMAP\n\tvSpecularIntensityMapUv = ( specularIntensityMapTransform * vec3( SPECULAR_INTENSITYMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_TRANSMISSIONMAP\n\tvTransmissionMapUv = ( transmissionMapTransform * vec3( TRANSMISSIONMAP_UV, 1 ) ).xy;\n#endif\n#ifdef USE_THICKNESSMAP\n\tvThicknessMapUv = ( thicknessMapTransform * vec3( THICKNESSMAP_UV, 1 ) ).xy;\n#endif"; + +var worldpos_vertex = "#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP ) || defined ( USE_TRANSMISSION ) || NUM_SPOT_LIGHT_COORDS > 0\n\tvec4 worldPosition = vec4( transformed, 1.0 );\n\t#ifdef USE_BATCHING\n\t\tworldPosition = batchingMatrix * worldPosition;\n\t#endif\n\t#ifdef USE_INSTANCING\n\t\tworldPosition = instanceMatrix * worldPosition;\n\t#endif\n\tworldPosition = modelMatrix * worldPosition;\n#endif"; + +const vertex$h = "varying vec2 vUv;\nuniform mat3 uvTransform;\nvoid main() {\n\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\n\tgl_Position = vec4( position.xy, 1.0, 1.0 );\n}"; + +const fragment$h = "uniform sampler2D t2D;\nuniform float backgroundIntensity;\nvarying vec2 vUv;\nvoid main() {\n\tvec4 texColor = texture2D( t2D, vUv );\n\t#ifdef DECODE_VIDEO_TEXTURE\n\t\ttexColor = vec4( mix( pow( texColor.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), texColor.rgb * 0.0773993808, vec3( lessThanEqual( texColor.rgb, vec3( 0.04045 ) ) ) ), texColor.w );\n\t#endif\n\ttexColor.rgb *= backgroundIntensity;\n\tgl_FragColor = texColor;\n\t#include \n\t#include \n}"; + +const vertex$g = "varying vec3 vWorldDirection;\n#include \nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include \n\t#include \n\tgl_Position.z = gl_Position.w;\n}"; + +const fragment$g = "#ifdef ENVMAP_TYPE_CUBE\n\tuniform samplerCube envMap;\n#elif defined( ENVMAP_TYPE_CUBE_UV )\n\tuniform sampler2D envMap;\n#endif\nuniform float flipEnvMap;\nuniform float backgroundBlurriness;\nuniform float backgroundIntensity;\nuniform mat3 backgroundRotation;\nvarying vec3 vWorldDirection;\n#include \nvoid main() {\n\t#ifdef ENVMAP_TYPE_CUBE\n\t\tvec4 texColor = textureCube( envMap, backgroundRotation * vec3( flipEnvMap * vWorldDirection.x, vWorldDirection.yz ) );\n\t#elif defined( ENVMAP_TYPE_CUBE_UV )\n\t\tvec4 texColor = textureCubeUV( envMap, backgroundRotation * vWorldDirection, backgroundBlurriness );\n\t#else\n\t\tvec4 texColor = vec4( 0.0, 0.0, 0.0, 1.0 );\n\t#endif\n\ttexColor.rgb *= backgroundIntensity;\n\tgl_FragColor = texColor;\n\t#include \n\t#include \n}"; + +const vertex$f = "varying vec3 vWorldDirection;\n#include \nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include \n\t#include \n\tgl_Position.z = gl_Position.w;\n}"; + +const fragment$f = "uniform samplerCube tCube;\nuniform float tFlip;\nuniform float opacity;\nvarying vec3 vWorldDirection;\nvoid main() {\n\tvec4 texColor = textureCube( tCube, vec3( tFlip * vWorldDirection.x, vWorldDirection.yz ) );\n\tgl_FragColor = texColor;\n\tgl_FragColor.a *= opacity;\n\t#include \n\t#include \n}"; + +const vertex$e = "#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvarying vec2 vHighPrecisionZW;\nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#ifdef USE_DISPLACEMENTMAP\n\t\t#include \n\t\t#include \n\t\t#include \n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvHighPrecisionZW = gl_Position.zw;\n}"; + +const fragment$e = "#if DEPTH_PACKING == 3200\n\tuniform float opacity;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvarying vec2 vHighPrecisionZW;\nvoid main() {\n\tvec4 diffuseColor = vec4( 1.0 );\n\t#include \n\t#if DEPTH_PACKING == 3200\n\t\tdiffuseColor.a = opacity;\n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tfloat fragCoordZ = 0.5 * vHighPrecisionZW[0] / vHighPrecisionZW[1] + 0.5;\n\t#if DEPTH_PACKING == 3200\n\t\tgl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );\n\t#elif DEPTH_PACKING == 3201\n\t\tgl_FragColor = packDepthToRGBA( fragCoordZ );\n\t#endif\n}"; + +const vertex$d = "#define DISTANCE\nvarying vec3 vWorldPosition;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#ifdef USE_DISPLACEMENTMAP\n\t\t#include \n\t\t#include \n\t\t#include \n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvWorldPosition = worldPosition.xyz;\n}"; + +const fragment$d = "#define DISTANCE\nuniform vec3 referencePosition;\nuniform float nearDistance;\nuniform float farDistance;\nvarying vec3 vWorldPosition;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main () {\n\tvec4 diffuseColor = vec4( 1.0 );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tfloat dist = length( vWorldPosition - referencePosition );\n\tdist = ( dist - nearDistance ) / ( farDistance - nearDistance );\n\tdist = saturate( dist );\n\tgl_FragColor = packDepthToRGBA( dist );\n}"; + +const vertex$c = "varying vec3 vWorldDirection;\n#include \nvoid main() {\n\tvWorldDirection = transformDirection( position, modelMatrix );\n\t#include \n\t#include \n}"; + +const fragment$c = "uniform sampler2D tEquirect;\nvarying vec3 vWorldDirection;\n#include \nvoid main() {\n\tvec3 direction = normalize( vWorldDirection );\n\tvec2 sampleUV = equirectUv( direction );\n\tgl_FragColor = texture2D( tEquirect, sampleUV );\n\t#include \n\t#include \n}"; + +const vertex$b = "uniform float scale;\nattribute float lineDistance;\nvarying float vLineDistance;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tvLineDistance = scale * lineDistance;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const fragment$b = "uniform vec3 diffuse;\nuniform float opacity;\nuniform float dashSize;\nuniform float totalSize;\nvarying float vLineDistance;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\tif ( mod( vLineDistance, totalSize ) > dashSize ) {\n\t\tdiscard;\n\t}\n\tvec3 outgoingLight = vec3( 0.0 );\n\t#include \n\t#include \n\t#include \n\toutgoingLight = diffuseColor.rgb;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const vertex$a = "#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#if defined ( USE_ENVMAP ) || defined ( USE_SKINNING )\n\t\t#include \n\t\t#include \n\t\t#include \n\t\t#include \n\t\t#include \n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const fragment$a = "uniform vec3 diffuse;\nuniform float opacity;\n#ifndef FLAT_SHADED\n\tvarying vec3 vNormal;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\t#ifdef USE_LIGHTMAP\n\t\tvec4 lightMapTexel = texture2D( lightMap, vLightMapUv );\n\t\treflectedLight.indirectDiffuse += lightMapTexel.rgb * lightMapIntensity * RECIPROCAL_PI;\n\t#else\n\t\treflectedLight.indirectDiffuse += vec3( 1.0 );\n\t#endif\n\t#include \n\treflectedLight.indirectDiffuse *= diffuseColor.rgb;\n\tvec3 outgoingLight = reflectedLight.indirectDiffuse;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const vertex$9 = "#define LAMBERT\nvarying vec3 vViewPosition;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvViewPosition = - mvPosition.xyz;\n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const fragment$9 = "#define LAMBERT\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform float opacity;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const vertex$8 = "#define MATCAP\nvarying vec3 vViewPosition;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvViewPosition = - mvPosition.xyz;\n}"; + +const fragment$8 = "#define MATCAP\nuniform vec3 diffuse;\nuniform float opacity;\nuniform sampler2D matcap;\nvarying vec3 vViewPosition;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvec3 viewDir = normalize( vViewPosition );\n\tvec3 x = normalize( vec3( viewDir.z, 0.0, - viewDir.x ) );\n\tvec3 y = cross( viewDir, x );\n\tvec2 uv = vec2( dot( x, normal ), dot( y, normal ) ) * 0.495 + 0.5;\n\t#ifdef USE_MATCAP\n\t\tvec4 matcapColor = texture2D( matcap, uv );\n\t#else\n\t\tvec4 matcapColor = vec4( vec3( mix( 0.2, 0.8, uv.y ) ), 1.0 );\n\t#endif\n\tvec3 outgoingLight = diffuseColor.rgb * matcapColor.rgb;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const vertex$7 = "#define NORMAL\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )\n\tvarying vec3 vViewPosition;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )\n\tvViewPosition = - mvPosition.xyz;\n#endif\n}"; + +const fragment$7 = "#define NORMAL\nuniform float opacity;\n#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )\n\tvarying vec3 vViewPosition;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tvec4 diffuseColor = vec4( 0.0, 0.0, 0.0, opacity );\n\t#include \n\t#include \n\t#include \n\t#include \n\tgl_FragColor = vec4( packNormalToRGB( normal ), diffuseColor.a );\n\t#ifdef OPAQUE\n\t\tgl_FragColor.a = 1.0;\n\t#endif\n}"; + +const vertex$6 = "#define PHONG\nvarying vec3 vViewPosition;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvViewPosition = - mvPosition.xyz;\n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const fragment$6 = "#define PHONG\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform vec3 specular;\nuniform float shininess;\nuniform float opacity;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const vertex$5 = "#define STANDARD\nvarying vec3 vViewPosition;\n#ifdef USE_TRANSMISSION\n\tvarying vec3 vWorldPosition;\n#endif\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvViewPosition = - mvPosition.xyz;\n\t#include \n\t#include \n\t#include \n#ifdef USE_TRANSMISSION\n\tvWorldPosition = worldPosition.xyz;\n#endif\n}"; + +const fragment$5 = "#define STANDARD\n#ifdef PHYSICAL\n\t#define IOR\n\t#define USE_SPECULAR\n#endif\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform float roughness;\nuniform float metalness;\nuniform float opacity;\n#ifdef IOR\n\tuniform float ior;\n#endif\n#ifdef USE_SPECULAR\n\tuniform float specularIntensity;\n\tuniform vec3 specularColor;\n\t#ifdef USE_SPECULAR_COLORMAP\n\t\tuniform sampler2D specularColorMap;\n\t#endif\n\t#ifdef USE_SPECULAR_INTENSITYMAP\n\t\tuniform sampler2D specularIntensityMap;\n\t#endif\n#endif\n#ifdef USE_CLEARCOAT\n\tuniform float clearcoat;\n\tuniform float clearcoatRoughness;\n#endif\n#ifdef USE_DISPERSION\n\tuniform float dispersion;\n#endif\n#ifdef USE_IRIDESCENCE\n\tuniform float iridescence;\n\tuniform float iridescenceIOR;\n\tuniform float iridescenceThicknessMinimum;\n\tuniform float iridescenceThicknessMaximum;\n#endif\n#ifdef USE_SHEEN\n\tuniform vec3 sheenColor;\n\tuniform float sheenRoughness;\n\t#ifdef USE_SHEEN_COLORMAP\n\t\tuniform sampler2D sheenColorMap;\n\t#endif\n\t#ifdef USE_SHEEN_ROUGHNESSMAP\n\t\tuniform sampler2D sheenRoughnessMap;\n\t#endif\n#endif\n#ifdef USE_ANISOTROPY\n\tuniform vec2 anisotropyVector;\n\t#ifdef USE_ANISOTROPYMAP\n\t\tuniform sampler2D anisotropyMap;\n\t#endif\n#endif\nvarying vec3 vViewPosition;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvec3 totalDiffuse = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse;\n\tvec3 totalSpecular = reflectedLight.directSpecular + reflectedLight.indirectSpecular;\n\t#include \n\tvec3 outgoingLight = totalDiffuse + totalSpecular + totalEmissiveRadiance;\n\t#ifdef USE_SHEEN\n\t\tfloat sheenEnergyComp = 1.0 - 0.157 * max3( material.sheenColor );\n\t\toutgoingLight = outgoingLight * sheenEnergyComp + sheenSpecularDirect + sheenSpecularIndirect;\n\t#endif\n\t#ifdef USE_CLEARCOAT\n\t\tfloat dotNVcc = saturate( dot( geometryClearcoatNormal, geometryViewDir ) );\n\t\tvec3 Fcc = F_Schlick( material.clearcoatF0, material.clearcoatF90, dotNVcc );\n\t\toutgoingLight = outgoingLight * ( 1.0 - material.clearcoat * Fcc ) + ( clearcoatSpecularDirect + clearcoatSpecularIndirect ) * material.clearcoat;\n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const vertex$4 = "#define TOON\nvarying vec3 vViewPosition;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvViewPosition = - mvPosition.xyz;\n\t#include \n\t#include \n\t#include \n}"; + +const fragment$4 = "#define TOON\nuniform vec3 diffuse;\nuniform vec3 emissive;\nuniform float opacity;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\tReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );\n\tvec3 totalEmissiveRadiance = emissive;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tvec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const vertex$3 = "uniform float size;\nuniform float scale;\n#include \n#include \n#include \n#include \n#include \n#include \n#ifdef USE_POINTS_UV\n\tvarying vec2 vUv;\n\tuniform mat3 uvTransform;\n#endif\nvoid main() {\n\t#ifdef USE_POINTS_UV\n\t\tvUv = ( uvTransform * vec3( uv, 1 ) ).xy;\n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\tgl_PointSize = size;\n\t#ifdef USE_SIZEATTENUATION\n\t\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\n\t\tif ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );\n\t#endif\n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const fragment$3 = "uniform vec3 diffuse;\nuniform float opacity;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\tvec3 outgoingLight = vec3( 0.0 );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\toutgoingLight = diffuseColor.rgb;\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const vertex$2 = "#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const fragment$2 = "uniform vec3 color;\nuniform float opacity;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\tgl_FragColor = vec4( color, opacity * ( 1.0 - getShadowMask() ) );\n\t#include \n\t#include \n\t#include \n}"; + +const vertex$1 = "uniform float rotation;\nuniform vec2 center;\n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\t#include \n\tvec4 mvPosition = modelViewMatrix * vec4( 0.0, 0.0, 0.0, 1.0 );\n\tvec2 scale;\n\tscale.x = length( vec3( modelMatrix[ 0 ].x, modelMatrix[ 0 ].y, modelMatrix[ 0 ].z ) );\n\tscale.y = length( vec3( modelMatrix[ 1 ].x, modelMatrix[ 1 ].y, modelMatrix[ 1 ].z ) );\n\t#ifndef USE_SIZEATTENUATION\n\t\tbool isPerspective = isPerspectiveMatrix( projectionMatrix );\n\t\tif ( isPerspective ) scale *= - mvPosition.z;\n\t#endif\n\tvec2 alignedPosition = ( position.xy - ( center - vec2( 0.5 ) ) ) * scale;\n\tvec2 rotatedPosition;\n\trotatedPosition.x = cos( rotation ) * alignedPosition.x - sin( rotation ) * alignedPosition.y;\n\trotatedPosition.y = sin( rotation ) * alignedPosition.x + cos( rotation ) * alignedPosition.y;\n\tmvPosition.xy += rotatedPosition;\n\tgl_Position = projectionMatrix * mvPosition;\n\t#include \n\t#include \n\t#include \n}"; + +const fragment$1 = "uniform vec3 diffuse;\nuniform float opacity;\n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \n#include \nvoid main() {\n\tvec4 diffuseColor = vec4( diffuse, opacity );\n\t#include \n\tvec3 outgoingLight = vec3( 0.0 );\n\t#include \n\t#include \n\t#include \n\t#include \n\t#include \n\toutgoingLight = diffuseColor.rgb;\n\t#include \n\t#include \n\t#include \n\t#include \n}"; + +const ShaderChunk = { + alphahash_fragment: alphahash_fragment, + alphahash_pars_fragment: alphahash_pars_fragment, + alphamap_fragment: alphamap_fragment, + alphamap_pars_fragment: alphamap_pars_fragment, + alphatest_fragment: alphatest_fragment, + alphatest_pars_fragment: alphatest_pars_fragment, + aomap_fragment: aomap_fragment, + aomap_pars_fragment: aomap_pars_fragment, + batching_pars_vertex: batching_pars_vertex, + batching_vertex: batching_vertex, + begin_vertex: begin_vertex, + beginnormal_vertex: beginnormal_vertex, + bsdfs: bsdfs, + iridescence_fragment: iridescence_fragment, + bumpmap_pars_fragment: bumpmap_pars_fragment, + clipping_planes_fragment: clipping_planes_fragment, + clipping_planes_pars_fragment: clipping_planes_pars_fragment, + clipping_planes_pars_vertex: clipping_planes_pars_vertex, + clipping_planes_vertex: clipping_planes_vertex, + color_fragment: color_fragment, + color_pars_fragment: color_pars_fragment, + color_pars_vertex: color_pars_vertex, + color_vertex: color_vertex, + common: common, + cube_uv_reflection_fragment: cube_uv_reflection_fragment, + defaultnormal_vertex: defaultnormal_vertex, + displacementmap_pars_vertex: displacementmap_pars_vertex, + displacementmap_vertex: displacementmap_vertex, + emissivemap_fragment: emissivemap_fragment, + emissivemap_pars_fragment: emissivemap_pars_fragment, + colorspace_fragment: colorspace_fragment, + colorspace_pars_fragment: colorspace_pars_fragment, + envmap_fragment: envmap_fragment, + envmap_common_pars_fragment: envmap_common_pars_fragment, + envmap_pars_fragment: envmap_pars_fragment, + envmap_pars_vertex: envmap_pars_vertex, + envmap_physical_pars_fragment: envmap_physical_pars_fragment, + envmap_vertex: envmap_vertex, + fog_vertex: fog_vertex, + fog_pars_vertex: fog_pars_vertex, + fog_fragment: fog_fragment, + fog_pars_fragment: fog_pars_fragment, + gradientmap_pars_fragment: gradientmap_pars_fragment, + lightmap_pars_fragment: lightmap_pars_fragment, + lights_lambert_fragment: lights_lambert_fragment, + lights_lambert_pars_fragment: lights_lambert_pars_fragment, + lights_pars_begin: lights_pars_begin, + lights_toon_fragment: lights_toon_fragment, + lights_toon_pars_fragment: lights_toon_pars_fragment, + lights_phong_fragment: lights_phong_fragment, + lights_phong_pars_fragment: lights_phong_pars_fragment, + lights_physical_fragment: lights_physical_fragment, + lights_physical_pars_fragment: lights_physical_pars_fragment, + lights_fragment_begin: lights_fragment_begin, + lights_fragment_maps: lights_fragment_maps, + lights_fragment_end: lights_fragment_end, + logdepthbuf_fragment: logdepthbuf_fragment, + logdepthbuf_pars_fragment: logdepthbuf_pars_fragment, + logdepthbuf_pars_vertex: logdepthbuf_pars_vertex, + logdepthbuf_vertex: logdepthbuf_vertex, + map_fragment: map_fragment, + map_pars_fragment: map_pars_fragment, + map_particle_fragment: map_particle_fragment, + map_particle_pars_fragment: map_particle_pars_fragment, + metalnessmap_fragment: metalnessmap_fragment, + metalnessmap_pars_fragment: metalnessmap_pars_fragment, + morphinstance_vertex: morphinstance_vertex, + morphcolor_vertex: morphcolor_vertex, + morphnormal_vertex: morphnormal_vertex, + morphtarget_pars_vertex: morphtarget_pars_vertex, + morphtarget_vertex: morphtarget_vertex, + normal_fragment_begin: normal_fragment_begin, + normal_fragment_maps: normal_fragment_maps, + normal_pars_fragment: normal_pars_fragment, + normal_pars_vertex: normal_pars_vertex, + normal_vertex: normal_vertex, + normalmap_pars_fragment: normalmap_pars_fragment, + clearcoat_normal_fragment_begin: clearcoat_normal_fragment_begin, + clearcoat_normal_fragment_maps: clearcoat_normal_fragment_maps, + clearcoat_pars_fragment: clearcoat_pars_fragment, + iridescence_pars_fragment: iridescence_pars_fragment, + opaque_fragment: opaque_fragment, + packing: packing, + premultiplied_alpha_fragment: premultiplied_alpha_fragment, + project_vertex: project_vertex, + dithering_fragment: dithering_fragment, + dithering_pars_fragment: dithering_pars_fragment, + roughnessmap_fragment: roughnessmap_fragment, + roughnessmap_pars_fragment: roughnessmap_pars_fragment, + shadowmap_pars_fragment: shadowmap_pars_fragment, + shadowmap_pars_vertex: shadowmap_pars_vertex, + shadowmap_vertex: shadowmap_vertex, + shadowmask_pars_fragment: shadowmask_pars_fragment, + skinbase_vertex: skinbase_vertex, + skinning_pars_vertex: skinning_pars_vertex, + skinning_vertex: skinning_vertex, + skinnormal_vertex: skinnormal_vertex, + specularmap_fragment: specularmap_fragment, + specularmap_pars_fragment: specularmap_pars_fragment, + tonemapping_fragment: tonemapping_fragment, + tonemapping_pars_fragment: tonemapping_pars_fragment, + transmission_fragment: transmission_fragment, + transmission_pars_fragment: transmission_pars_fragment, + uv_pars_fragment: uv_pars_fragment, + uv_pars_vertex: uv_pars_vertex, + uv_vertex: uv_vertex, + worldpos_vertex: worldpos_vertex, + + background_vert: vertex$h, + background_frag: fragment$h, + backgroundCube_vert: vertex$g, + backgroundCube_frag: fragment$g, + cube_vert: vertex$f, + cube_frag: fragment$f, + depth_vert: vertex$e, + depth_frag: fragment$e, + distanceRGBA_vert: vertex$d, + distanceRGBA_frag: fragment$d, + equirect_vert: vertex$c, + equirect_frag: fragment$c, + linedashed_vert: vertex$b, + linedashed_frag: fragment$b, + meshbasic_vert: vertex$a, + meshbasic_frag: fragment$a, + meshlambert_vert: vertex$9, + meshlambert_frag: fragment$9, + meshmatcap_vert: vertex$8, + meshmatcap_frag: fragment$8, + meshnormal_vert: vertex$7, + meshnormal_frag: fragment$7, + meshphong_vert: vertex$6, + meshphong_frag: fragment$6, + meshphysical_vert: vertex$5, + meshphysical_frag: fragment$5, + meshtoon_vert: vertex$4, + meshtoon_frag: fragment$4, + points_vert: vertex$3, + points_frag: fragment$3, + shadow_vert: vertex$2, + shadow_frag: fragment$2, + sprite_vert: vertex$1, + sprite_frag: fragment$1 +}; + +/** + * Uniforms library for shared webgl shaders + */ + +const UniformsLib = { + + common: { + + diffuse: { value: /*@__PURE__*/ new Color( 0xffffff ) }, + opacity: { value: 1.0 }, + + map: { value: null }, + mapTransform: { value: /*@__PURE__*/ new Matrix3() }, + + alphaMap: { value: null }, + alphaMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + + alphaTest: { value: 0 } + + }, + + specularmap: { + + specularMap: { value: null }, + specularMapTransform: { value: /*@__PURE__*/ new Matrix3() } + + }, + + envmap: { + + envMap: { value: null }, + envMapRotation: { value: /*@__PURE__*/ new Matrix3() }, + flipEnvMap: { value: - 1 }, + reflectivity: { value: 1.0 }, // basic, lambert, phong + ior: { value: 1.5 }, // physical + refractionRatio: { value: 0.98 }, // basic, lambert, phong + + }, + + aomap: { + + aoMap: { value: null }, + aoMapIntensity: { value: 1 }, + aoMapTransform: { value: /*@__PURE__*/ new Matrix3() } + + }, + + lightmap: { + + lightMap: { value: null }, + lightMapIntensity: { value: 1 }, + lightMapTransform: { value: /*@__PURE__*/ new Matrix3() } + + }, + + bumpmap: { + + bumpMap: { value: null }, + bumpMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + bumpScale: { value: 1 } + + }, + + normalmap: { + + normalMap: { value: null }, + normalMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + normalScale: { value: /*@__PURE__*/ new Vector2( 1, 1 ) } + + }, + + displacementmap: { + + displacementMap: { value: null }, + displacementMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + displacementScale: { value: 1 }, + displacementBias: { value: 0 } + + }, + + emissivemap: { + + emissiveMap: { value: null }, + emissiveMapTransform: { value: /*@__PURE__*/ new Matrix3() } + + }, + + metalnessmap: { + + metalnessMap: { value: null }, + metalnessMapTransform: { value: /*@__PURE__*/ new Matrix3() } + + }, + + roughnessmap: { + + roughnessMap: { value: null }, + roughnessMapTransform: { value: /*@__PURE__*/ new Matrix3() } + + }, + + gradientmap: { + + gradientMap: { value: null } + + }, + + fog: { + + fogDensity: { value: 0.00025 }, + fogNear: { value: 1 }, + fogFar: { value: 2000 }, + fogColor: { value: /*@__PURE__*/ new Color( 0xffffff ) } + + }, + + lights: { + + ambientLightColor: { value: [] }, + + lightProbe: { value: [] }, + + directionalLights: { value: [], properties: { + direction: {}, + color: {} + } }, + + directionalLightShadows: { value: [], properties: { + shadowBias: {}, + shadowNormalBias: {}, + shadowRadius: {}, + shadowMapSize: {} + } }, + + directionalShadowMap: { value: [] }, + directionalShadowMatrix: { value: [] }, + + spotLights: { value: [], properties: { + color: {}, + position: {}, + direction: {}, + distance: {}, + coneCos: {}, + penumbraCos: {}, + decay: {} + } }, + + spotLightShadows: { value: [], properties: { + shadowBias: {}, + shadowNormalBias: {}, + shadowRadius: {}, + shadowMapSize: {} + } }, + + spotLightMap: { value: [] }, + spotShadowMap: { value: [] }, + spotLightMatrix: { value: [] }, + + pointLights: { value: [], properties: { + color: {}, + position: {}, + decay: {}, + distance: {} + } }, + + pointLightShadows: { value: [], properties: { + shadowBias: {}, + shadowNormalBias: {}, + shadowRadius: {}, + shadowMapSize: {}, + shadowCameraNear: {}, + shadowCameraFar: {} + } }, + + pointShadowMap: { value: [] }, + pointShadowMatrix: { value: [] }, + + hemisphereLights: { value: [], properties: { + direction: {}, + skyColor: {}, + groundColor: {} + } }, + + // TODO (abelnation): RectAreaLight BRDF data needs to be moved from example to main src + rectAreaLights: { value: [], properties: { + color: {}, + position: {}, + width: {}, + height: {} + } }, + + ltc_1: { value: null }, + ltc_2: { value: null } + + }, + + points: { + + diffuse: { value: /*@__PURE__*/ new Color( 0xffffff ) }, + opacity: { value: 1.0 }, + size: { value: 1.0 }, + scale: { value: 1.0 }, + map: { value: null }, + alphaMap: { value: null }, + alphaMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + alphaTest: { value: 0 }, + uvTransform: { value: /*@__PURE__*/ new Matrix3() } + + }, + + sprite: { + + diffuse: { value: /*@__PURE__*/ new Color( 0xffffff ) }, + opacity: { value: 1.0 }, + center: { value: /*@__PURE__*/ new Vector2( 0.5, 0.5 ) }, + rotation: { value: 0.0 }, + map: { value: null }, + mapTransform: { value: /*@__PURE__*/ new Matrix3() }, + alphaMap: { value: null }, + alphaMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + alphaTest: { value: 0 } + + } + +}; + +const ShaderLib = { + + basic: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.common, + UniformsLib.specularmap, + UniformsLib.envmap, + UniformsLib.aomap, + UniformsLib.lightmap, + UniformsLib.fog + ] ), + + vertexShader: ShaderChunk.meshbasic_vert, + fragmentShader: ShaderChunk.meshbasic_frag + + }, + + lambert: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.common, + UniformsLib.specularmap, + UniformsLib.envmap, + UniformsLib.aomap, + UniformsLib.lightmap, + UniformsLib.emissivemap, + UniformsLib.bumpmap, + UniformsLib.normalmap, + UniformsLib.displacementmap, + UniformsLib.fog, + UniformsLib.lights, + { + emissive: { value: /*@__PURE__*/ new Color( 0x000000 ) } + } + ] ), + + vertexShader: ShaderChunk.meshlambert_vert, + fragmentShader: ShaderChunk.meshlambert_frag + + }, + + phong: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.common, + UniformsLib.specularmap, + UniformsLib.envmap, + UniformsLib.aomap, + UniformsLib.lightmap, + UniformsLib.emissivemap, + UniformsLib.bumpmap, + UniformsLib.normalmap, + UniformsLib.displacementmap, + UniformsLib.fog, + UniformsLib.lights, + { + emissive: { value: /*@__PURE__*/ new Color( 0x000000 ) }, + specular: { value: /*@__PURE__*/ new Color( 0x111111 ) }, + shininess: { value: 30 } + } + ] ), + + vertexShader: ShaderChunk.meshphong_vert, + fragmentShader: ShaderChunk.meshphong_frag + + }, + + standard: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.common, + UniformsLib.envmap, + UniformsLib.aomap, + UniformsLib.lightmap, + UniformsLib.emissivemap, + UniformsLib.bumpmap, + UniformsLib.normalmap, + UniformsLib.displacementmap, + UniformsLib.roughnessmap, + UniformsLib.metalnessmap, + UniformsLib.fog, + UniformsLib.lights, + { + emissive: { value: /*@__PURE__*/ new Color( 0x000000 ) }, + roughness: { value: 1.0 }, + metalness: { value: 0.0 }, + envMapIntensity: { value: 1 } + } + ] ), + + vertexShader: ShaderChunk.meshphysical_vert, + fragmentShader: ShaderChunk.meshphysical_frag + + }, + + toon: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.common, + UniformsLib.aomap, + UniformsLib.lightmap, + UniformsLib.emissivemap, + UniformsLib.bumpmap, + UniformsLib.normalmap, + UniformsLib.displacementmap, + UniformsLib.gradientmap, + UniformsLib.fog, + UniformsLib.lights, + { + emissive: { value: /*@__PURE__*/ new Color( 0x000000 ) } + } + ] ), + + vertexShader: ShaderChunk.meshtoon_vert, + fragmentShader: ShaderChunk.meshtoon_frag + + }, + + matcap: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.common, + UniformsLib.bumpmap, + UniformsLib.normalmap, + UniformsLib.displacementmap, + UniformsLib.fog, + { + matcap: { value: null } + } + ] ), + + vertexShader: ShaderChunk.meshmatcap_vert, + fragmentShader: ShaderChunk.meshmatcap_frag + + }, + + points: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.points, + UniformsLib.fog + ] ), + + vertexShader: ShaderChunk.points_vert, + fragmentShader: ShaderChunk.points_frag + + }, + + dashed: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.common, + UniformsLib.fog, + { + scale: { value: 1 }, + dashSize: { value: 1 }, + totalSize: { value: 2 } + } + ] ), + + vertexShader: ShaderChunk.linedashed_vert, + fragmentShader: ShaderChunk.linedashed_frag + + }, + + depth: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.common, + UniformsLib.displacementmap + ] ), + + vertexShader: ShaderChunk.depth_vert, + fragmentShader: ShaderChunk.depth_frag + + }, + + normal: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.common, + UniformsLib.bumpmap, + UniformsLib.normalmap, + UniformsLib.displacementmap, + { + opacity: { value: 1.0 } + } + ] ), + + vertexShader: ShaderChunk.meshnormal_vert, + fragmentShader: ShaderChunk.meshnormal_frag + + }, + + sprite: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.sprite, + UniformsLib.fog + ] ), + + vertexShader: ShaderChunk.sprite_vert, + fragmentShader: ShaderChunk.sprite_frag + + }, + + background: { + + uniforms: { + uvTransform: { value: /*@__PURE__*/ new Matrix3() }, + t2D: { value: null }, + backgroundIntensity: { value: 1 } + }, + + vertexShader: ShaderChunk.background_vert, + fragmentShader: ShaderChunk.background_frag + + }, + + backgroundCube: { + + uniforms: { + envMap: { value: null }, + flipEnvMap: { value: - 1 }, + backgroundBlurriness: { value: 0 }, + backgroundIntensity: { value: 1 }, + backgroundRotation: { value: /*@__PURE__*/ new Matrix3() } + }, + + vertexShader: ShaderChunk.backgroundCube_vert, + fragmentShader: ShaderChunk.backgroundCube_frag + + }, + + cube: { + + uniforms: { + tCube: { value: null }, + tFlip: { value: - 1 }, + opacity: { value: 1.0 } + }, + + vertexShader: ShaderChunk.cube_vert, + fragmentShader: ShaderChunk.cube_frag + + }, + + equirect: { + + uniforms: { + tEquirect: { value: null }, + }, + + vertexShader: ShaderChunk.equirect_vert, + fragmentShader: ShaderChunk.equirect_frag + + }, + + distanceRGBA: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.common, + UniformsLib.displacementmap, + { + referencePosition: { value: /*@__PURE__*/ new Vector3() }, + nearDistance: { value: 1 }, + farDistance: { value: 1000 } + } + ] ), + + vertexShader: ShaderChunk.distanceRGBA_vert, + fragmentShader: ShaderChunk.distanceRGBA_frag + + }, + + shadow: { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + UniformsLib.lights, + UniformsLib.fog, + { + color: { value: /*@__PURE__*/ new Color( 0x00000 ) }, + opacity: { value: 1.0 } + }, + ] ), + + vertexShader: ShaderChunk.shadow_vert, + fragmentShader: ShaderChunk.shadow_frag + + } + +}; + +ShaderLib.physical = { + + uniforms: /*@__PURE__*/ mergeUniforms( [ + ShaderLib.standard.uniforms, + { + clearcoat: { value: 0 }, + clearcoatMap: { value: null }, + clearcoatMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + clearcoatNormalMap: { value: null }, + clearcoatNormalMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + clearcoatNormalScale: { value: /*@__PURE__*/ new Vector2( 1, 1 ) }, + clearcoatRoughness: { value: 0 }, + clearcoatRoughnessMap: { value: null }, + clearcoatRoughnessMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + dispersion: { value: 0 }, + iridescence: { value: 0 }, + iridescenceMap: { value: null }, + iridescenceMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + iridescenceIOR: { value: 1.3 }, + iridescenceThicknessMinimum: { value: 100 }, + iridescenceThicknessMaximum: { value: 400 }, + iridescenceThicknessMap: { value: null }, + iridescenceThicknessMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + sheen: { value: 0 }, + sheenColor: { value: /*@__PURE__*/ new Color( 0x000000 ) }, + sheenColorMap: { value: null }, + sheenColorMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + sheenRoughness: { value: 1 }, + sheenRoughnessMap: { value: null }, + sheenRoughnessMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + transmission: { value: 0 }, + transmissionMap: { value: null }, + transmissionMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + transmissionSamplerSize: { value: /*@__PURE__*/ new Vector2() }, + transmissionSamplerMap: { value: null }, + thickness: { value: 0 }, + thicknessMap: { value: null }, + thicknessMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + attenuationDistance: { value: 0 }, + attenuationColor: { value: /*@__PURE__*/ new Color( 0x000000 ) }, + specularColor: { value: /*@__PURE__*/ new Color( 1, 1, 1 ) }, + specularColorMap: { value: null }, + specularColorMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + specularIntensity: { value: 1 }, + specularIntensityMap: { value: null }, + specularIntensityMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + anisotropyVector: { value: /*@__PURE__*/ new Vector2() }, + anisotropyMap: { value: null }, + anisotropyMapTransform: { value: /*@__PURE__*/ new Matrix3() }, + } + ] ), + + vertexShader: ShaderChunk.meshphysical_vert, + fragmentShader: ShaderChunk.meshphysical_frag + +}; + +const _rgb = { r: 0, b: 0, g: 0 }; +const _e1$1 = /*@__PURE__*/ new Euler(); +const _m1$1 = /*@__PURE__*/ new Matrix4(); + +function WebGLBackground( renderer, cubemaps, cubeuvmaps, state, objects, alpha, premultipliedAlpha ) { + + const clearColor = new Color( 0x000000 ); + let clearAlpha = alpha === true ? 0 : 1; + + let planeMesh; + let boxMesh; + + let currentBackground = null; + let currentBackgroundVersion = 0; + let currentTonemapping = null; + + function getBackground( scene ) { + + let background = scene.isScene === true ? scene.background : null; + + if ( background && background.isTexture ) { + + const usePMREM = scene.backgroundBlurriness > 0; // use PMREM if the user wants to blur the background + background = ( usePMREM ? cubeuvmaps : cubemaps ).get( background ); + + } + + return background; + + } + + function render( scene ) { + + let forceClear = false; + const background = getBackground( scene ); + + if ( background === null ) { + + setClear( clearColor, clearAlpha ); + + } else if ( background && background.isColor ) { + + setClear( background, 1 ); + forceClear = true; + + } + + const environmentBlendMode = renderer.xr.getEnvironmentBlendMode(); + + if ( environmentBlendMode === 'additive' ) { + + state.buffers.color.setClear( 0, 0, 0, 1, premultipliedAlpha ); + + } else if ( environmentBlendMode === 'alpha-blend' ) { + + state.buffers.color.setClear( 0, 0, 0, 0, premultipliedAlpha ); + + } + + if ( renderer.autoClear || forceClear ) { + + // buffers might not be writable which is required to ensure a correct clear + + state.buffers.depth.setTest( true ); + state.buffers.depth.setMask( true ); + state.buffers.color.setMask( true ); + + renderer.clear( renderer.autoClearColor, renderer.autoClearDepth, renderer.autoClearStencil ); + + } + + } + + function addToRenderList( renderList, scene ) { + + const background = getBackground( scene ); + + if ( background && ( background.isCubeTexture || background.mapping === CubeUVReflectionMapping ) ) { + + if ( boxMesh === undefined ) { + + boxMesh = new Mesh( + new BoxGeometry( 1, 1, 1 ), + new ShaderMaterial( { + name: 'BackgroundCubeMaterial', + uniforms: cloneUniforms( ShaderLib.backgroundCube.uniforms ), + vertexShader: ShaderLib.backgroundCube.vertexShader, + fragmentShader: ShaderLib.backgroundCube.fragmentShader, + side: BackSide, + depthTest: false, + depthWrite: false, + fog: false + } ) + ); + + boxMesh.geometry.deleteAttribute( 'normal' ); + boxMesh.geometry.deleteAttribute( 'uv' ); + + boxMesh.onBeforeRender = function ( renderer, scene, camera ) { + + this.matrixWorld.copyPosition( camera.matrixWorld ); + + }; + + // add "envMap" material property so the renderer can evaluate it like for built-in materials + Object.defineProperty( boxMesh.material, 'envMap', { + + get: function () { + + return this.uniforms.envMap.value; + + } + + } ); + + objects.update( boxMesh ); + + } + + _e1$1.copy( scene.backgroundRotation ); + + // accommodate left-handed frame + _e1$1.x *= - 1; _e1$1.y *= - 1; _e1$1.z *= - 1; + + if ( background.isCubeTexture && background.isRenderTargetTexture === false ) { + + // environment maps which are not cube render targets or PMREMs follow a different convention + _e1$1.y *= - 1; + _e1$1.z *= - 1; + + } + + boxMesh.material.uniforms.envMap.value = background; + boxMesh.material.uniforms.flipEnvMap.value = ( background.isCubeTexture && background.isRenderTargetTexture === false ) ? - 1 : 1; + boxMesh.material.uniforms.backgroundBlurriness.value = scene.backgroundBlurriness; + boxMesh.material.uniforms.backgroundIntensity.value = scene.backgroundIntensity; + boxMesh.material.uniforms.backgroundRotation.value.setFromMatrix4( _m1$1.makeRotationFromEuler( _e1$1 ) ); + boxMesh.material.toneMapped = ColorManagement.getTransfer( background.colorSpace ) !== SRGBTransfer; + + if ( currentBackground !== background || + currentBackgroundVersion !== background.version || + currentTonemapping !== renderer.toneMapping ) { + + boxMesh.material.needsUpdate = true; + + currentBackground = background; + currentBackgroundVersion = background.version; + currentTonemapping = renderer.toneMapping; + + } + + boxMesh.layers.enableAll(); + + // push to the pre-sorted opaque render list + renderList.unshift( boxMesh, boxMesh.geometry, boxMesh.material, 0, 0, null ); + + } else if ( background && background.isTexture ) { + + if ( planeMesh === undefined ) { + + planeMesh = new Mesh( + new PlaneGeometry( 2, 2 ), + new ShaderMaterial( { + name: 'BackgroundMaterial', + uniforms: cloneUniforms( ShaderLib.background.uniforms ), + vertexShader: ShaderLib.background.vertexShader, + fragmentShader: ShaderLib.background.fragmentShader, + side: FrontSide, + depthTest: false, + depthWrite: false, + fog: false + } ) + ); + + planeMesh.geometry.deleteAttribute( 'normal' ); + + // add "map" material property so the renderer can evaluate it like for built-in materials + Object.defineProperty( planeMesh.material, 'map', { + + get: function () { + + return this.uniforms.t2D.value; + + } + + } ); + + objects.update( planeMesh ); + + } + + planeMesh.material.uniforms.t2D.value = background; + planeMesh.material.uniforms.backgroundIntensity.value = scene.backgroundIntensity; + planeMesh.material.toneMapped = ColorManagement.getTransfer( background.colorSpace ) !== SRGBTransfer; + + if ( background.matrixAutoUpdate === true ) { + + background.updateMatrix(); + + } + + planeMesh.material.uniforms.uvTransform.value.copy( background.matrix ); + + if ( currentBackground !== background || + currentBackgroundVersion !== background.version || + currentTonemapping !== renderer.toneMapping ) { + + planeMesh.material.needsUpdate = true; + + currentBackground = background; + currentBackgroundVersion = background.version; + currentTonemapping = renderer.toneMapping; + + } + + planeMesh.layers.enableAll(); + + // push to the pre-sorted opaque render list + renderList.unshift( planeMesh, planeMesh.geometry, planeMesh.material, 0, 0, null ); + + } + + } + + function setClear( color, alpha ) { + + color.getRGB( _rgb, getUnlitUniformColorSpace( renderer ) ); + + state.buffers.color.setClear( _rgb.r, _rgb.g, _rgb.b, alpha, premultipliedAlpha ); + + } + + return { + + getClearColor: function () { + + return clearColor; + + }, + setClearColor: function ( color, alpha = 1 ) { + + clearColor.set( color ); + clearAlpha = alpha; + setClear( clearColor, clearAlpha ); + + }, + getClearAlpha: function () { + + return clearAlpha; + + }, + setClearAlpha: function ( alpha ) { + + clearAlpha = alpha; + setClear( clearColor, clearAlpha ); + + }, + render: render, + addToRenderList: addToRenderList + + }; + +} + +function WebGLBindingStates( gl, attributes ) { + + const maxVertexAttributes = gl.getParameter( gl.MAX_VERTEX_ATTRIBS ); + + const bindingStates = {}; + + const defaultState = createBindingState( null ); + let currentState = defaultState; + let forceUpdate = false; + + function setup( object, material, program, geometry, index ) { + + let updateBuffers = false; + + const state = getBindingState( geometry, program, material ); + + if ( currentState !== state ) { + + currentState = state; + bindVertexArrayObject( currentState.object ); + + } + + updateBuffers = needsUpdate( object, geometry, program, index ); + + if ( updateBuffers ) saveCache( object, geometry, program, index ); + + if ( index !== null ) { + + attributes.update( index, gl.ELEMENT_ARRAY_BUFFER ); + + } + + if ( updateBuffers || forceUpdate ) { + + forceUpdate = false; + + setupVertexAttributes( object, material, program, geometry ); + + if ( index !== null ) { + + gl.bindBuffer( gl.ELEMENT_ARRAY_BUFFER, attributes.get( index ).buffer ); + + } + + } + + } + + function createVertexArrayObject() { + + return gl.createVertexArray(); + + } + + function bindVertexArrayObject( vao ) { + + return gl.bindVertexArray( vao ); + + } + + function deleteVertexArrayObject( vao ) { + + return gl.deleteVertexArray( vao ); + + } + + function getBindingState( geometry, program, material ) { + + const wireframe = ( material.wireframe === true ); + + let programMap = bindingStates[ geometry.id ]; + + if ( programMap === undefined ) { + + programMap = {}; + bindingStates[ geometry.id ] = programMap; + + } + + let stateMap = programMap[ program.id ]; + + if ( stateMap === undefined ) { + + stateMap = {}; + programMap[ program.id ] = stateMap; + + } + + let state = stateMap[ wireframe ]; + + if ( state === undefined ) { + + state = createBindingState( createVertexArrayObject() ); + stateMap[ wireframe ] = state; + + } + + return state; + + } + + function createBindingState( vao ) { + + const newAttributes = []; + const enabledAttributes = []; + const attributeDivisors = []; + + for ( let i = 0; i < maxVertexAttributes; i ++ ) { + + newAttributes[ i ] = 0; + enabledAttributes[ i ] = 0; + attributeDivisors[ i ] = 0; + + } + + return { + + // for backward compatibility on non-VAO support browser + geometry: null, + program: null, + wireframe: false, + + newAttributes: newAttributes, + enabledAttributes: enabledAttributes, + attributeDivisors: attributeDivisors, + object: vao, + attributes: {}, + index: null + + }; + + } + + function needsUpdate( object, geometry, program, index ) { + + const cachedAttributes = currentState.attributes; + const geometryAttributes = geometry.attributes; + + let attributesNum = 0; + + const programAttributes = program.getAttributes(); + + for ( const name in programAttributes ) { + + const programAttribute = programAttributes[ name ]; + + if ( programAttribute.location >= 0 ) { + + const cachedAttribute = cachedAttributes[ name ]; + let geometryAttribute = geometryAttributes[ name ]; + + if ( geometryAttribute === undefined ) { + + if ( name === 'instanceMatrix' && object.instanceMatrix ) geometryAttribute = object.instanceMatrix; + if ( name === 'instanceColor' && object.instanceColor ) geometryAttribute = object.instanceColor; + + } + + if ( cachedAttribute === undefined ) return true; + + if ( cachedAttribute.attribute !== geometryAttribute ) return true; + + if ( geometryAttribute && cachedAttribute.data !== geometryAttribute.data ) return true; + + attributesNum ++; + + } + + } + + if ( currentState.attributesNum !== attributesNum ) return true; + + if ( currentState.index !== index ) return true; + + return false; + + } + + function saveCache( object, geometry, program, index ) { + + const cache = {}; + const attributes = geometry.attributes; + let attributesNum = 0; + + const programAttributes = program.getAttributes(); + + for ( const name in programAttributes ) { + + const programAttribute = programAttributes[ name ]; + + if ( programAttribute.location >= 0 ) { + + let attribute = attributes[ name ]; + + if ( attribute === undefined ) { + + if ( name === 'instanceMatrix' && object.instanceMatrix ) attribute = object.instanceMatrix; + if ( name === 'instanceColor' && object.instanceColor ) attribute = object.instanceColor; + + } + + const data = {}; + data.attribute = attribute; + + if ( attribute && attribute.data ) { + + data.data = attribute.data; + + } + + cache[ name ] = data; + + attributesNum ++; + + } + + } + + currentState.attributes = cache; + currentState.attributesNum = attributesNum; + + currentState.index = index; + + } + + function initAttributes() { + + const newAttributes = currentState.newAttributes; + + for ( let i = 0, il = newAttributes.length; i < il; i ++ ) { + + newAttributes[ i ] = 0; + + } + + } + + function enableAttribute( attribute ) { + + enableAttributeAndDivisor( attribute, 0 ); + + } + + function enableAttributeAndDivisor( attribute, meshPerAttribute ) { + + const newAttributes = currentState.newAttributes; + const enabledAttributes = currentState.enabledAttributes; + const attributeDivisors = currentState.attributeDivisors; + + newAttributes[ attribute ] = 1; + + if ( enabledAttributes[ attribute ] === 0 ) { + + gl.enableVertexAttribArray( attribute ); + enabledAttributes[ attribute ] = 1; + + } + + if ( attributeDivisors[ attribute ] !== meshPerAttribute ) { + + gl.vertexAttribDivisor( attribute, meshPerAttribute ); + attributeDivisors[ attribute ] = meshPerAttribute; + + } + + } + + function disableUnusedAttributes() { + + const newAttributes = currentState.newAttributes; + const enabledAttributes = currentState.enabledAttributes; + + for ( let i = 0, il = enabledAttributes.length; i < il; i ++ ) { + + if ( enabledAttributes[ i ] !== newAttributes[ i ] ) { + + gl.disableVertexAttribArray( i ); + enabledAttributes[ i ] = 0; + + } + + } + + } + + function vertexAttribPointer( index, size, type, normalized, stride, offset, integer ) { + + if ( integer === true ) { + + gl.vertexAttribIPointer( index, size, type, stride, offset ); + + } else { + + gl.vertexAttribPointer( index, size, type, normalized, stride, offset ); + + } + + } + + function setupVertexAttributes( object, material, program, geometry ) { + + initAttributes(); + + const geometryAttributes = geometry.attributes; + + const programAttributes = program.getAttributes(); + + const materialDefaultAttributeValues = material.defaultAttributeValues; + + for ( const name in programAttributes ) { + + const programAttribute = programAttributes[ name ]; + + if ( programAttribute.location >= 0 ) { + + let geometryAttribute = geometryAttributes[ name ]; + + if ( geometryAttribute === undefined ) { + + if ( name === 'instanceMatrix' && object.instanceMatrix ) geometryAttribute = object.instanceMatrix; + if ( name === 'instanceColor' && object.instanceColor ) geometryAttribute = object.instanceColor; + + } + + if ( geometryAttribute !== undefined ) { + + const normalized = geometryAttribute.normalized; + const size = geometryAttribute.itemSize; + + const attribute = attributes.get( geometryAttribute ); + + // TODO Attribute may not be available on context restore + + if ( attribute === undefined ) continue; + + const buffer = attribute.buffer; + const type = attribute.type; + const bytesPerElement = attribute.bytesPerElement; + + // check for integer attributes + + const integer = ( type === gl.INT || type === gl.UNSIGNED_INT || geometryAttribute.gpuType === IntType ); + + if ( geometryAttribute.isInterleavedBufferAttribute ) { + + const data = geometryAttribute.data; + const stride = data.stride; + const offset = geometryAttribute.offset; + + if ( data.isInstancedInterleavedBuffer ) { + + for ( let i = 0; i < programAttribute.locationSize; i ++ ) { + + enableAttributeAndDivisor( programAttribute.location + i, data.meshPerAttribute ); + + } + + if ( object.isInstancedMesh !== true && geometry._maxInstanceCount === undefined ) { + + geometry._maxInstanceCount = data.meshPerAttribute * data.count; + + } + + } else { + + for ( let i = 0; i < programAttribute.locationSize; i ++ ) { + + enableAttribute( programAttribute.location + i ); + + } + + } + + gl.bindBuffer( gl.ARRAY_BUFFER, buffer ); + + for ( let i = 0; i < programAttribute.locationSize; i ++ ) { + + vertexAttribPointer( + programAttribute.location + i, + size / programAttribute.locationSize, + type, + normalized, + stride * bytesPerElement, + ( offset + ( size / programAttribute.locationSize ) * i ) * bytesPerElement, + integer + ); + + } + + } else { + + if ( geometryAttribute.isInstancedBufferAttribute ) { + + for ( let i = 0; i < programAttribute.locationSize; i ++ ) { + + enableAttributeAndDivisor( programAttribute.location + i, geometryAttribute.meshPerAttribute ); + + } + + if ( object.isInstancedMesh !== true && geometry._maxInstanceCount === undefined ) { + + geometry._maxInstanceCount = geometryAttribute.meshPerAttribute * geometryAttribute.count; + + } + + } else { + + for ( let i = 0; i < programAttribute.locationSize; i ++ ) { + + enableAttribute( programAttribute.location + i ); + + } + + } + + gl.bindBuffer( gl.ARRAY_BUFFER, buffer ); + + for ( let i = 0; i < programAttribute.locationSize; i ++ ) { + + vertexAttribPointer( + programAttribute.location + i, + size / programAttribute.locationSize, + type, + normalized, + size * bytesPerElement, + ( size / programAttribute.locationSize ) * i * bytesPerElement, + integer + ); + + } + + } + + } else if ( materialDefaultAttributeValues !== undefined ) { + + const value = materialDefaultAttributeValues[ name ]; + + if ( value !== undefined ) { + + switch ( value.length ) { + + case 2: + gl.vertexAttrib2fv( programAttribute.location, value ); + break; + + case 3: + gl.vertexAttrib3fv( programAttribute.location, value ); + break; + + case 4: + gl.vertexAttrib4fv( programAttribute.location, value ); + break; + + default: + gl.vertexAttrib1fv( programAttribute.location, value ); + + } + + } + + } + + } + + } + + disableUnusedAttributes(); + + } + + function dispose() { + + reset(); + + for ( const geometryId in bindingStates ) { + + const programMap = bindingStates[ geometryId ]; + + for ( const programId in programMap ) { + + const stateMap = programMap[ programId ]; + + for ( const wireframe in stateMap ) { + + deleteVertexArrayObject( stateMap[ wireframe ].object ); + + delete stateMap[ wireframe ]; + + } + + delete programMap[ programId ]; + + } + + delete bindingStates[ geometryId ]; + + } + + } + + function releaseStatesOfGeometry( geometry ) { + + if ( bindingStates[ geometry.id ] === undefined ) return; + + const programMap = bindingStates[ geometry.id ]; + + for ( const programId in programMap ) { + + const stateMap = programMap[ programId ]; + + for ( const wireframe in stateMap ) { + + deleteVertexArrayObject( stateMap[ wireframe ].object ); + + delete stateMap[ wireframe ]; + + } + + delete programMap[ programId ]; + + } + + delete bindingStates[ geometry.id ]; + + } + + function releaseStatesOfProgram( program ) { + + for ( const geometryId in bindingStates ) { + + const programMap = bindingStates[ geometryId ]; + + if ( programMap[ program.id ] === undefined ) continue; + + const stateMap = programMap[ program.id ]; + + for ( const wireframe in stateMap ) { + + deleteVertexArrayObject( stateMap[ wireframe ].object ); + + delete stateMap[ wireframe ]; + + } + + delete programMap[ program.id ]; + + } + + } + + function reset() { + + resetDefaultState(); + forceUpdate = true; + + if ( currentState === defaultState ) return; + + currentState = defaultState; + bindVertexArrayObject( currentState.object ); + + } + + // for backward-compatibility + + function resetDefaultState() { + + defaultState.geometry = null; + defaultState.program = null; + defaultState.wireframe = false; + + } + + return { + + setup: setup, + reset: reset, + resetDefaultState: resetDefaultState, + dispose: dispose, + releaseStatesOfGeometry: releaseStatesOfGeometry, + releaseStatesOfProgram: releaseStatesOfProgram, + + initAttributes: initAttributes, + enableAttribute: enableAttribute, + disableUnusedAttributes: disableUnusedAttributes + + }; + +} + +function WebGLBufferRenderer( gl, extensions, info ) { + + let mode; + + function setMode( value ) { + + mode = value; + + } + + function render( start, count ) { + + gl.drawArrays( mode, start, count ); + + info.update( count, mode, 1 ); + + } + + function renderInstances( start, count, primcount ) { + + if ( primcount === 0 ) return; + + gl.drawArraysInstanced( mode, start, count, primcount ); + + info.update( count, mode, primcount ); + + } + + function renderMultiDraw( starts, counts, drawCount ) { + + if ( drawCount === 0 ) return; + + const extension = extensions.get( 'WEBGL_multi_draw' ); + + if ( extension === null ) { + + for ( let i = 0; i < drawCount; i ++ ) { + + this.render( starts[ i ], counts[ i ] ); + + } + + } else { + + extension.multiDrawArraysWEBGL( mode, starts, 0, counts, 0, drawCount ); + + let elementCount = 0; + for ( let i = 0; i < drawCount; i ++ ) { + + elementCount += counts[ i ]; + + } + + info.update( elementCount, mode, 1 ); + + } + + } + + function renderMultiDrawInstances( starts, counts, drawCount, primcount ) { + + if ( drawCount === 0 ) return; + + const extension = extensions.get( 'WEBGL_multi_draw' ); + + if ( extension === null ) { + + for ( let i = 0; i < starts.length; i ++ ) { + + renderInstances( starts[ i ], counts[ i ], primcount[ i ] ); + + } + + } else { + + extension.multiDrawArraysInstancedWEBGL( mode, starts, 0, counts, 0, primcount, 0, drawCount ); + + let elementCount = 0; + for ( let i = 0; i < drawCount; i ++ ) { + + elementCount += counts[ i ]; + + } + + for ( let i = 0; i < primcount.length; i ++ ) { + + info.update( elementCount, mode, primcount[ i ] ); + + } + + } + + } + + // + + this.setMode = setMode; + this.render = render; + this.renderInstances = renderInstances; + this.renderMultiDraw = renderMultiDraw; + this.renderMultiDrawInstances = renderMultiDrawInstances; + +} + +function WebGLCapabilities( gl, extensions, parameters, utils ) { + + let maxAnisotropy; + + function getMaxAnisotropy() { + + if ( maxAnisotropy !== undefined ) return maxAnisotropy; + + if ( extensions.has( 'EXT_texture_filter_anisotropic' ) === true ) { + + const extension = extensions.get( 'EXT_texture_filter_anisotropic' ); + + maxAnisotropy = gl.getParameter( extension.MAX_TEXTURE_MAX_ANISOTROPY_EXT ); + + } else { + + maxAnisotropy = 0; + + } + + return maxAnisotropy; + + } + + function textureFormatReadable( textureFormat ) { + + if ( textureFormat !== RGBAFormat && utils.convert( textureFormat ) !== gl.getParameter( gl.IMPLEMENTATION_COLOR_READ_FORMAT ) ) { + + return false; + + } + + return true; + + } + + function textureTypeReadable( textureType ) { + + const halfFloatSupportedByExt = ( textureType === HalfFloatType ) && ( extensions.has( 'EXT_color_buffer_half_float' ) || extensions.has( 'EXT_color_buffer_float' ) ); + + if ( textureType !== UnsignedByteType && utils.convert( textureType ) !== gl.getParameter( gl.IMPLEMENTATION_COLOR_READ_TYPE ) && // Edge and Chrome Mac < 52 (#9513) + textureType !== FloatType && ! halfFloatSupportedByExt ) { + + return false; + + } + + return true; + + } + + function getMaxPrecision( precision ) { + + if ( precision === 'highp' ) { + + if ( gl.getShaderPrecisionFormat( gl.VERTEX_SHADER, gl.HIGH_FLOAT ).precision > 0 && + gl.getShaderPrecisionFormat( gl.FRAGMENT_SHADER, gl.HIGH_FLOAT ).precision > 0 ) { + + return 'highp'; + + } + + precision = 'mediump'; + + } + + if ( precision === 'mediump' ) { + + if ( gl.getShaderPrecisionFormat( gl.VERTEX_SHADER, gl.MEDIUM_FLOAT ).precision > 0 && + gl.getShaderPrecisionFormat( gl.FRAGMENT_SHADER, gl.MEDIUM_FLOAT ).precision > 0 ) { + + return 'mediump'; + + } + + } + + return 'lowp'; + + } + + let precision = parameters.precision !== undefined ? parameters.precision : 'highp'; + const maxPrecision = getMaxPrecision( precision ); + + if ( maxPrecision !== precision ) { + + console.warn( 'THREE.WebGLRenderer:', precision, 'not supported, using', maxPrecision, 'instead.' ); + precision = maxPrecision; + + } + + const logarithmicDepthBuffer = parameters.logarithmicDepthBuffer === true; + + const maxTextures = gl.getParameter( gl.MAX_TEXTURE_IMAGE_UNITS ); + const maxVertexTextures = gl.getParameter( gl.MAX_VERTEX_TEXTURE_IMAGE_UNITS ); + const maxTextureSize = gl.getParameter( gl.MAX_TEXTURE_SIZE ); + const maxCubemapSize = gl.getParameter( gl.MAX_CUBE_MAP_TEXTURE_SIZE ); + + const maxAttributes = gl.getParameter( gl.MAX_VERTEX_ATTRIBS ); + const maxVertexUniforms = gl.getParameter( gl.MAX_VERTEX_UNIFORM_VECTORS ); + const maxVaryings = gl.getParameter( gl.MAX_VARYING_VECTORS ); + const maxFragmentUniforms = gl.getParameter( gl.MAX_FRAGMENT_UNIFORM_VECTORS ); + + const vertexTextures = maxVertexTextures > 0; + + const maxSamples = gl.getParameter( gl.MAX_SAMPLES ); + + return { + + isWebGL2: true, // keeping this for backwards compatibility + + getMaxAnisotropy: getMaxAnisotropy, + getMaxPrecision: getMaxPrecision, + + textureFormatReadable: textureFormatReadable, + textureTypeReadable: textureTypeReadable, + + precision: precision, + logarithmicDepthBuffer: logarithmicDepthBuffer, + + maxTextures: maxTextures, + maxVertexTextures: maxVertexTextures, + maxTextureSize: maxTextureSize, + maxCubemapSize: maxCubemapSize, + + maxAttributes: maxAttributes, + maxVertexUniforms: maxVertexUniforms, + maxVaryings: maxVaryings, + maxFragmentUniforms: maxFragmentUniforms, + + vertexTextures: vertexTextures, + + maxSamples: maxSamples + + }; + +} + +function WebGLClipping( properties ) { + + const scope = this; + + let globalState = null, + numGlobalPlanes = 0, + localClippingEnabled = false, + renderingShadows = false; + + const plane = new Plane(), + viewNormalMatrix = new Matrix3(), + + uniform = { value: null, needsUpdate: false }; + + this.uniform = uniform; + this.numPlanes = 0; + this.numIntersection = 0; + + this.init = function ( planes, enableLocalClipping ) { + + const enabled = + planes.length !== 0 || + enableLocalClipping || + // enable state of previous frame - the clipping code has to + // run another frame in order to reset the state: + numGlobalPlanes !== 0 || + localClippingEnabled; + + localClippingEnabled = enableLocalClipping; + + numGlobalPlanes = planes.length; + + return enabled; + + }; + + this.beginShadows = function () { + + renderingShadows = true; + projectPlanes( null ); + + }; + + this.endShadows = function () { + + renderingShadows = false; + + }; + + this.setGlobalState = function ( planes, camera ) { + + globalState = projectPlanes( planes, camera, 0 ); + + }; + + this.setState = function ( material, camera, useCache ) { + + const planes = material.clippingPlanes, + clipIntersection = material.clipIntersection, + clipShadows = material.clipShadows; + + const materialProperties = properties.get( material ); + + if ( ! localClippingEnabled || planes === null || planes.length === 0 || renderingShadows && ! clipShadows ) { + + // there's no local clipping + + if ( renderingShadows ) { + + // there's no global clipping + + projectPlanes( null ); + + } else { + + resetGlobalState(); + + } + + } else { + + const nGlobal = renderingShadows ? 0 : numGlobalPlanes, + lGlobal = nGlobal * 4; + + let dstArray = materialProperties.clippingState || null; + + uniform.value = dstArray; // ensure unique state + + dstArray = projectPlanes( planes, camera, lGlobal, useCache ); + + for ( let i = 0; i !== lGlobal; ++ i ) { + + dstArray[ i ] = globalState[ i ]; + + } + + materialProperties.clippingState = dstArray; + this.numIntersection = clipIntersection ? this.numPlanes : 0; + this.numPlanes += nGlobal; + + } + + + }; + + function resetGlobalState() { + + if ( uniform.value !== globalState ) { + + uniform.value = globalState; + uniform.needsUpdate = numGlobalPlanes > 0; + + } + + scope.numPlanes = numGlobalPlanes; + scope.numIntersection = 0; + + } + + function projectPlanes( planes, camera, dstOffset, skipTransform ) { + + const nPlanes = planes !== null ? planes.length : 0; + let dstArray = null; + + if ( nPlanes !== 0 ) { + + dstArray = uniform.value; + + if ( skipTransform !== true || dstArray === null ) { + + const flatSize = dstOffset + nPlanes * 4, + viewMatrix = camera.matrixWorldInverse; + + viewNormalMatrix.getNormalMatrix( viewMatrix ); + + if ( dstArray === null || dstArray.length < flatSize ) { + + dstArray = new Float32Array( flatSize ); + + } + + for ( let i = 0, i4 = dstOffset; i !== nPlanes; ++ i, i4 += 4 ) { + + plane.copy( planes[ i ] ).applyMatrix4( viewMatrix, viewNormalMatrix ); + + plane.normal.toArray( dstArray, i4 ); + dstArray[ i4 + 3 ] = plane.constant; + + } + + } + + uniform.value = dstArray; + uniform.needsUpdate = true; + + } + + scope.numPlanes = nPlanes; + scope.numIntersection = 0; + + return dstArray; + + } + +} + +function WebGLCubeMaps( renderer ) { + + let cubemaps = new WeakMap(); + + function mapTextureMapping( texture, mapping ) { + + if ( mapping === EquirectangularReflectionMapping ) { + + texture.mapping = CubeReflectionMapping; + + } else if ( mapping === EquirectangularRefractionMapping ) { + + texture.mapping = CubeRefractionMapping; + + } + + return texture; + + } + + function get( texture ) { + + if ( texture && texture.isTexture ) { + + const mapping = texture.mapping; + + if ( mapping === EquirectangularReflectionMapping || mapping === EquirectangularRefractionMapping ) { + + if ( cubemaps.has( texture ) ) { + + const cubemap = cubemaps.get( texture ).texture; + return mapTextureMapping( cubemap, texture.mapping ); + + } else { + + const image = texture.image; + + if ( image && image.height > 0 ) { + + const renderTarget = new WebGLCubeRenderTarget( image.height ); + renderTarget.fromEquirectangularTexture( renderer, texture ); + cubemaps.set( texture, renderTarget ); + + texture.addEventListener( 'dispose', onTextureDispose ); + + return mapTextureMapping( renderTarget.texture, texture.mapping ); + + } else { + + // image not yet ready. try the conversion next frame + + return null; + + } + + } + + } + + } + + return texture; + + } + + function onTextureDispose( event ) { + + const texture = event.target; + + texture.removeEventListener( 'dispose', onTextureDispose ); + + const cubemap = cubemaps.get( texture ); + + if ( cubemap !== undefined ) { + + cubemaps.delete( texture ); + cubemap.dispose(); + + } + + } + + function dispose() { + + cubemaps = new WeakMap(); + + } + + return { + get: get, + dispose: dispose + }; + +} + +class OrthographicCamera extends Camera { + + constructor( left = - 1, right = 1, top = 1, bottom = - 1, near = 0.1, far = 2000 ) { + + super(); + + this.isOrthographicCamera = true; + + this.type = 'OrthographicCamera'; + + this.zoom = 1; + this.view = null; + + this.left = left; + this.right = right; + this.top = top; + this.bottom = bottom; + + this.near = near; + this.far = far; + + this.updateProjectionMatrix(); + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + this.left = source.left; + this.right = source.right; + this.top = source.top; + this.bottom = source.bottom; + this.near = source.near; + this.far = source.far; + + this.zoom = source.zoom; + this.view = source.view === null ? null : Object.assign( {}, source.view ); + + return this; + + } + + setViewOffset( fullWidth, fullHeight, x, y, width, height ) { + + if ( this.view === null ) { + + this.view = { + enabled: true, + fullWidth: 1, + fullHeight: 1, + offsetX: 0, + offsetY: 0, + width: 1, + height: 1 + }; + + } + + this.view.enabled = true; + this.view.fullWidth = fullWidth; + this.view.fullHeight = fullHeight; + this.view.offsetX = x; + this.view.offsetY = y; + this.view.width = width; + this.view.height = height; + + this.updateProjectionMatrix(); + + } + + clearViewOffset() { + + if ( this.view !== null ) { + + this.view.enabled = false; + + } + + this.updateProjectionMatrix(); + + } + + updateProjectionMatrix() { + + const dx = ( this.right - this.left ) / ( 2 * this.zoom ); + const dy = ( this.top - this.bottom ) / ( 2 * this.zoom ); + const cx = ( this.right + this.left ) / 2; + const cy = ( this.top + this.bottom ) / 2; + + let left = cx - dx; + let right = cx + dx; + let top = cy + dy; + let bottom = cy - dy; + + if ( this.view !== null && this.view.enabled ) { + + const scaleW = ( this.right - this.left ) / this.view.fullWidth / this.zoom; + const scaleH = ( this.top - this.bottom ) / this.view.fullHeight / this.zoom; + + left += scaleW * this.view.offsetX; + right = left + scaleW * this.view.width; + top -= scaleH * this.view.offsetY; + bottom = top - scaleH * this.view.height; + + } + + this.projectionMatrix.makeOrthographic( left, right, top, bottom, this.near, this.far, this.coordinateSystem ); + + this.projectionMatrixInverse.copy( this.projectionMatrix ).invert(); + + } + + toJSON( meta ) { + + const data = super.toJSON( meta ); + + data.object.zoom = this.zoom; + data.object.left = this.left; + data.object.right = this.right; + data.object.top = this.top; + data.object.bottom = this.bottom; + data.object.near = this.near; + data.object.far = this.far; + + if ( this.view !== null ) data.object.view = Object.assign( {}, this.view ); + + return data; + + } + +} + +const LOD_MIN = 4; + +// The standard deviations (radians) associated with the extra mips. These are +// chosen to approximate a Trowbridge-Reitz distribution function times the +// geometric shadowing function. These sigma values squared must match the +// variance #defines in cube_uv_reflection_fragment.glsl.js. +const EXTRA_LOD_SIGMA = [ 0.125, 0.215, 0.35, 0.446, 0.526, 0.582 ]; + +// The maximum length of the blur for loop. Smaller sigmas will use fewer +// samples and exit early, but not recompile the shader. +const MAX_SAMPLES = 20; + +const _flatCamera = /*@__PURE__*/ new OrthographicCamera(); +const _clearColor = /*@__PURE__*/ new Color(); +let _oldTarget = null; +let _oldActiveCubeFace = 0; +let _oldActiveMipmapLevel = 0; +let _oldXrEnabled = false; + +// Golden Ratio +const PHI = ( 1 + Math.sqrt( 5 ) ) / 2; +const INV_PHI = 1 / PHI; + +// Vertices of a dodecahedron (except the opposites, which represent the +// same axis), used as axis directions evenly spread on a sphere. +const _axisDirections = [ + /*@__PURE__*/ new Vector3( - PHI, INV_PHI, 0 ), + /*@__PURE__*/ new Vector3( PHI, INV_PHI, 0 ), + /*@__PURE__*/ new Vector3( - INV_PHI, 0, PHI ), + /*@__PURE__*/ new Vector3( INV_PHI, 0, PHI ), + /*@__PURE__*/ new Vector3( 0, PHI, - INV_PHI ), + /*@__PURE__*/ new Vector3( 0, PHI, INV_PHI ), + /*@__PURE__*/ new Vector3( - 1, 1, - 1 ), + /*@__PURE__*/ new Vector3( 1, 1, - 1 ), + /*@__PURE__*/ new Vector3( - 1, 1, 1 ), + /*@__PURE__*/ new Vector3( 1, 1, 1 ) ]; + +/** + * This class generates a Prefiltered, Mipmapped Radiance Environment Map + * (PMREM) from a cubeMap environment texture. This allows different levels of + * blur to be quickly accessed based on material roughness. It is packed into a + * special CubeUV format that allows us to perform custom interpolation so that + * we can support nonlinear formats such as RGBE. Unlike a traditional mipmap + * chain, it only goes down to the LOD_MIN level (above), and then creates extra + * even more filtered 'mips' at the same LOD_MIN resolution, associated with + * higher roughness levels. In this way we maintain resolution to smoothly + * interpolate diffuse lighting while limiting sampling computation. + * + * Paper: Fast, Accurate Image-Based Lighting + * https://drive.google.com/file/d/15y8r_UpKlU9SvV4ILb0C3qCPecS8pvLz/view +*/ + +class PMREMGenerator { + + constructor( renderer ) { + + this._renderer = renderer; + this._pingPongRenderTarget = null; + + this._lodMax = 0; + this._cubeSize = 0; + this._lodPlanes = []; + this._sizeLods = []; + this._sigmas = []; + + this._blurMaterial = null; + this._cubemapMaterial = null; + this._equirectMaterial = null; + + this._compileMaterial( this._blurMaterial ); + + } + + /** + * Generates a PMREM from a supplied Scene, which can be faster than using an + * image if networking bandwidth is low. Optional sigma specifies a blur radius + * in radians to be applied to the scene before PMREM generation. Optional near + * and far planes ensure the scene is rendered in its entirety (the cubeCamera + * is placed at the origin). + */ + fromScene( scene, sigma = 0, near = 0.1, far = 100 ) { + + _oldTarget = this._renderer.getRenderTarget(); + _oldActiveCubeFace = this._renderer.getActiveCubeFace(); + _oldActiveMipmapLevel = this._renderer.getActiveMipmapLevel(); + _oldXrEnabled = this._renderer.xr.enabled; + + this._renderer.xr.enabled = false; + + this._setSize( 256 ); + + const cubeUVRenderTarget = this._allocateTargets(); + cubeUVRenderTarget.depthBuffer = true; + + this._sceneToCubeUV( scene, near, far, cubeUVRenderTarget ); + + if ( sigma > 0 ) { + + this._blur( cubeUVRenderTarget, 0, 0, sigma ); + + } + + this._applyPMREM( cubeUVRenderTarget ); + this._cleanup( cubeUVRenderTarget ); + + return cubeUVRenderTarget; + + } + + /** + * Generates a PMREM from an equirectangular texture, which can be either LDR + * or HDR. The ideal input image size is 1k (1024 x 512), + * as this matches best with the 256 x 256 cubemap output. + * The smallest supported equirectangular image size is 64 x 32. + */ + fromEquirectangular( equirectangular, renderTarget = null ) { + + return this._fromTexture( equirectangular, renderTarget ); + + } + + /** + * Generates a PMREM from an cubemap texture, which can be either LDR + * or HDR. The ideal input cube size is 256 x 256, + * as this matches best with the 256 x 256 cubemap output. + * The smallest supported cube size is 16 x 16. + */ + fromCubemap( cubemap, renderTarget = null ) { + + return this._fromTexture( cubemap, renderTarget ); + + } + + /** + * Pre-compiles the cubemap shader. You can get faster start-up by invoking this method during + * your texture's network fetch for increased concurrency. + */ + compileCubemapShader() { + + if ( this._cubemapMaterial === null ) { + + this._cubemapMaterial = _getCubemapMaterial(); + this._compileMaterial( this._cubemapMaterial ); + + } + + } + + /** + * Pre-compiles the equirectangular shader. You can get faster start-up by invoking this method during + * your texture's network fetch for increased concurrency. + */ + compileEquirectangularShader() { + + if ( this._equirectMaterial === null ) { + + this._equirectMaterial = _getEquirectMaterial(); + this._compileMaterial( this._equirectMaterial ); + + } + + } + + /** + * Disposes of the PMREMGenerator's internal memory. Note that PMREMGenerator is a static class, + * so you should not need more than one PMREMGenerator object. If you do, calling dispose() on + * one of them will cause any others to also become unusable. + */ + dispose() { + + this._dispose(); + + if ( this._cubemapMaterial !== null ) this._cubemapMaterial.dispose(); + if ( this._equirectMaterial !== null ) this._equirectMaterial.dispose(); + + } + + // private interface + + _setSize( cubeSize ) { + + this._lodMax = Math.floor( Math.log2( cubeSize ) ); + this._cubeSize = Math.pow( 2, this._lodMax ); + + } + + _dispose() { + + if ( this._blurMaterial !== null ) this._blurMaterial.dispose(); + + if ( this._pingPongRenderTarget !== null ) this._pingPongRenderTarget.dispose(); + + for ( let i = 0; i < this._lodPlanes.length; i ++ ) { + + this._lodPlanes[ i ].dispose(); + + } + + } + + _cleanup( outputTarget ) { + + this._renderer.setRenderTarget( _oldTarget, _oldActiveCubeFace, _oldActiveMipmapLevel ); + this._renderer.xr.enabled = _oldXrEnabled; + + outputTarget.scissorTest = false; + _setViewport( outputTarget, 0, 0, outputTarget.width, outputTarget.height ); + + } + + _fromTexture( texture, renderTarget ) { + + if ( texture.mapping === CubeReflectionMapping || texture.mapping === CubeRefractionMapping ) { + + this._setSize( texture.image.length === 0 ? 16 : ( texture.image[ 0 ].width || texture.image[ 0 ].image.width ) ); + + } else { // Equirectangular + + this._setSize( texture.image.width / 4 ); + + } + + _oldTarget = this._renderer.getRenderTarget(); + _oldActiveCubeFace = this._renderer.getActiveCubeFace(); + _oldActiveMipmapLevel = this._renderer.getActiveMipmapLevel(); + _oldXrEnabled = this._renderer.xr.enabled; + + this._renderer.xr.enabled = false; + + const cubeUVRenderTarget = renderTarget || this._allocateTargets(); + this._textureToCubeUV( texture, cubeUVRenderTarget ); + this._applyPMREM( cubeUVRenderTarget ); + this._cleanup( cubeUVRenderTarget ); + + return cubeUVRenderTarget; + + } + + _allocateTargets() { + + const width = 3 * Math.max( this._cubeSize, 16 * 7 ); + const height = 4 * this._cubeSize; + + const params = { + magFilter: LinearFilter, + minFilter: LinearFilter, + generateMipmaps: false, + type: HalfFloatType, + format: RGBAFormat, + colorSpace: LinearSRGBColorSpace, + depthBuffer: false + }; + + const cubeUVRenderTarget = _createRenderTarget( width, height, params ); + + if ( this._pingPongRenderTarget === null || this._pingPongRenderTarget.width !== width || this._pingPongRenderTarget.height !== height ) { + + if ( this._pingPongRenderTarget !== null ) { + + this._dispose(); + + } + + this._pingPongRenderTarget = _createRenderTarget( width, height, params ); + + const { _lodMax } = this; + ( { sizeLods: this._sizeLods, lodPlanes: this._lodPlanes, sigmas: this._sigmas } = _createPlanes( _lodMax ) ); + + this._blurMaterial = _getBlurShader( _lodMax, width, height ); + + } + + return cubeUVRenderTarget; + + } + + _compileMaterial( material ) { + + const tmpMesh = new Mesh( this._lodPlanes[ 0 ], material ); + this._renderer.compile( tmpMesh, _flatCamera ); + + } + + _sceneToCubeUV( scene, near, far, cubeUVRenderTarget ) { + + const fov = 90; + const aspect = 1; + const cubeCamera = new PerspectiveCamera( fov, aspect, near, far ); + const upSign = [ 1, - 1, 1, 1, 1, 1 ]; + const forwardSign = [ 1, 1, 1, - 1, - 1, - 1 ]; + const renderer = this._renderer; + + const originalAutoClear = renderer.autoClear; + const toneMapping = renderer.toneMapping; + renderer.getClearColor( _clearColor ); + + renderer.toneMapping = NoToneMapping; + renderer.autoClear = false; + + const backgroundMaterial = new MeshBasicMaterial( { + name: 'PMREM.Background', + side: BackSide, + depthWrite: false, + depthTest: false, + } ); + + const backgroundBox = new Mesh( new BoxGeometry(), backgroundMaterial ); + + let useSolidColor = false; + const background = scene.background; + + if ( background ) { + + if ( background.isColor ) { + + backgroundMaterial.color.copy( background ); + scene.background = null; + useSolidColor = true; + + } + + } else { + + backgroundMaterial.color.copy( _clearColor ); + useSolidColor = true; + + } + + for ( let i = 0; i < 6; i ++ ) { + + const col = i % 3; + + if ( col === 0 ) { + + cubeCamera.up.set( 0, upSign[ i ], 0 ); + cubeCamera.lookAt( forwardSign[ i ], 0, 0 ); + + } else if ( col === 1 ) { + + cubeCamera.up.set( 0, 0, upSign[ i ] ); + cubeCamera.lookAt( 0, forwardSign[ i ], 0 ); + + } else { + + cubeCamera.up.set( 0, upSign[ i ], 0 ); + cubeCamera.lookAt( 0, 0, forwardSign[ i ] ); + + } + + const size = this._cubeSize; + + _setViewport( cubeUVRenderTarget, col * size, i > 2 ? size : 0, size, size ); + + renderer.setRenderTarget( cubeUVRenderTarget ); + + if ( useSolidColor ) { + + renderer.render( backgroundBox, cubeCamera ); + + } + + renderer.render( scene, cubeCamera ); + + } + + backgroundBox.geometry.dispose(); + backgroundBox.material.dispose(); + + renderer.toneMapping = toneMapping; + renderer.autoClear = originalAutoClear; + scene.background = background; + + } + + _textureToCubeUV( texture, cubeUVRenderTarget ) { + + const renderer = this._renderer; + + const isCubeTexture = ( texture.mapping === CubeReflectionMapping || texture.mapping === CubeRefractionMapping ); + + if ( isCubeTexture ) { + + if ( this._cubemapMaterial === null ) { + + this._cubemapMaterial = _getCubemapMaterial(); + + } + + this._cubemapMaterial.uniforms.flipEnvMap.value = ( texture.isRenderTargetTexture === false ) ? - 1 : 1; + + } else { + + if ( this._equirectMaterial === null ) { + + this._equirectMaterial = _getEquirectMaterial(); + + } + + } + + const material = isCubeTexture ? this._cubemapMaterial : this._equirectMaterial; + const mesh = new Mesh( this._lodPlanes[ 0 ], material ); + + const uniforms = material.uniforms; + + uniforms[ 'envMap' ].value = texture; + + const size = this._cubeSize; + + _setViewport( cubeUVRenderTarget, 0, 0, 3 * size, 2 * size ); + + renderer.setRenderTarget( cubeUVRenderTarget ); + renderer.render( mesh, _flatCamera ); + + } + + _applyPMREM( cubeUVRenderTarget ) { + + const renderer = this._renderer; + const autoClear = renderer.autoClear; + renderer.autoClear = false; + const n = this._lodPlanes.length; + + for ( let i = 1; i < n; i ++ ) { + + const sigma = Math.sqrt( this._sigmas[ i ] * this._sigmas[ i ] - this._sigmas[ i - 1 ] * this._sigmas[ i - 1 ] ); + + const poleAxis = _axisDirections[ ( n - i - 1 ) % _axisDirections.length ]; + + this._blur( cubeUVRenderTarget, i - 1, i, sigma, poleAxis ); + + } + + renderer.autoClear = autoClear; + + } + + /** + * This is a two-pass Gaussian blur for a cubemap. Normally this is done + * vertically and horizontally, but this breaks down on a cube. Here we apply + * the blur latitudinally (around the poles), and then longitudinally (towards + * the poles) to approximate the orthogonally-separable blur. It is least + * accurate at the poles, but still does a decent job. + */ + _blur( cubeUVRenderTarget, lodIn, lodOut, sigma, poleAxis ) { + + const pingPongRenderTarget = this._pingPongRenderTarget; + + this._halfBlur( + cubeUVRenderTarget, + pingPongRenderTarget, + lodIn, + lodOut, + sigma, + 'latitudinal', + poleAxis ); + + this._halfBlur( + pingPongRenderTarget, + cubeUVRenderTarget, + lodOut, + lodOut, + sigma, + 'longitudinal', + poleAxis ); + + } + + _halfBlur( targetIn, targetOut, lodIn, lodOut, sigmaRadians, direction, poleAxis ) { + + const renderer = this._renderer; + const blurMaterial = this._blurMaterial; + + if ( direction !== 'latitudinal' && direction !== 'longitudinal' ) { + + console.error( + 'blur direction must be either latitudinal or longitudinal!' ); + + } + + // Number of standard deviations at which to cut off the discrete approximation. + const STANDARD_DEVIATIONS = 3; + + const blurMesh = new Mesh( this._lodPlanes[ lodOut ], blurMaterial ); + const blurUniforms = blurMaterial.uniforms; + + const pixels = this._sizeLods[ lodIn ] - 1; + const radiansPerPixel = isFinite( sigmaRadians ) ? Math.PI / ( 2 * pixels ) : 2 * Math.PI / ( 2 * MAX_SAMPLES - 1 ); + const sigmaPixels = sigmaRadians / radiansPerPixel; + const samples = isFinite( sigmaRadians ) ? 1 + Math.floor( STANDARD_DEVIATIONS * sigmaPixels ) : MAX_SAMPLES; + + if ( samples > MAX_SAMPLES ) { + + console.warn( `sigmaRadians, ${ + sigmaRadians}, is too large and will clip, as it requested ${ + samples} samples when the maximum is set to ${MAX_SAMPLES}` ); + + } + + const weights = []; + let sum = 0; + + for ( let i = 0; i < MAX_SAMPLES; ++ i ) { + + const x = i / sigmaPixels; + const weight = Math.exp( - x * x / 2 ); + weights.push( weight ); + + if ( i === 0 ) { + + sum += weight; + + } else if ( i < samples ) { + + sum += 2 * weight; + + } + + } + + for ( let i = 0; i < weights.length; i ++ ) { + + weights[ i ] = weights[ i ] / sum; + + } + + blurUniforms[ 'envMap' ].value = targetIn.texture; + blurUniforms[ 'samples' ].value = samples; + blurUniforms[ 'weights' ].value = weights; + blurUniforms[ 'latitudinal' ].value = direction === 'latitudinal'; + + if ( poleAxis ) { + + blurUniforms[ 'poleAxis' ].value = poleAxis; + + } + + const { _lodMax } = this; + blurUniforms[ 'dTheta' ].value = radiansPerPixel; + blurUniforms[ 'mipInt' ].value = _lodMax - lodIn; + + const outputSize = this._sizeLods[ lodOut ]; + const x = 3 * outputSize * ( lodOut > _lodMax - LOD_MIN ? lodOut - _lodMax + LOD_MIN : 0 ); + const y = 4 * ( this._cubeSize - outputSize ); + + _setViewport( targetOut, x, y, 3 * outputSize, 2 * outputSize ); + renderer.setRenderTarget( targetOut ); + renderer.render( blurMesh, _flatCamera ); + + } + +} + + + +function _createPlanes( lodMax ) { + + const lodPlanes = []; + const sizeLods = []; + const sigmas = []; + + let lod = lodMax; + + const totalLods = lodMax - LOD_MIN + 1 + EXTRA_LOD_SIGMA.length; + + for ( let i = 0; i < totalLods; i ++ ) { + + const sizeLod = Math.pow( 2, lod ); + sizeLods.push( sizeLod ); + let sigma = 1.0 / sizeLod; + + if ( i > lodMax - LOD_MIN ) { + + sigma = EXTRA_LOD_SIGMA[ i - lodMax + LOD_MIN - 1 ]; + + } else if ( i === 0 ) { + + sigma = 0; + + } + + sigmas.push( sigma ); + + const texelSize = 1.0 / ( sizeLod - 2 ); + const min = - texelSize; + const max = 1 + texelSize; + const uv1 = [ min, min, max, min, max, max, min, min, max, max, min, max ]; + + const cubeFaces = 6; + const vertices = 6; + const positionSize = 3; + const uvSize = 2; + const faceIndexSize = 1; + + const position = new Float32Array( positionSize * vertices * cubeFaces ); + const uv = new Float32Array( uvSize * vertices * cubeFaces ); + const faceIndex = new Float32Array( faceIndexSize * vertices * cubeFaces ); + + for ( let face = 0; face < cubeFaces; face ++ ) { + + const x = ( face % 3 ) * 2 / 3 - 1; + const y = face > 2 ? 0 : - 1; + const coordinates = [ + x, y, 0, + x + 2 / 3, y, 0, + x + 2 / 3, y + 1, 0, + x, y, 0, + x + 2 / 3, y + 1, 0, + x, y + 1, 0 + ]; + position.set( coordinates, positionSize * vertices * face ); + uv.set( uv1, uvSize * vertices * face ); + const fill = [ face, face, face, face, face, face ]; + faceIndex.set( fill, faceIndexSize * vertices * face ); + + } + + const planes = new BufferGeometry(); + planes.setAttribute( 'position', new BufferAttribute( position, positionSize ) ); + planes.setAttribute( 'uv', new BufferAttribute( uv, uvSize ) ); + planes.setAttribute( 'faceIndex', new BufferAttribute( faceIndex, faceIndexSize ) ); + lodPlanes.push( planes ); + + if ( lod > LOD_MIN ) { + + lod --; + + } + + } + + return { lodPlanes, sizeLods, sigmas }; + +} + +function _createRenderTarget( width, height, params ) { + + const cubeUVRenderTarget = new WebGLRenderTarget( width, height, params ); + cubeUVRenderTarget.texture.mapping = CubeUVReflectionMapping; + cubeUVRenderTarget.texture.name = 'PMREM.cubeUv'; + cubeUVRenderTarget.scissorTest = true; + return cubeUVRenderTarget; + +} + +function _setViewport( target, x, y, width, height ) { + + target.viewport.set( x, y, width, height ); + target.scissor.set( x, y, width, height ); + +} + +function _getBlurShader( lodMax, width, height ) { + + const weights = new Float32Array( MAX_SAMPLES ); + const poleAxis = new Vector3( 0, 1, 0 ); + const shaderMaterial = new ShaderMaterial( { + + name: 'SphericalGaussianBlur', + + defines: { + 'n': MAX_SAMPLES, + 'CUBEUV_TEXEL_WIDTH': 1.0 / width, + 'CUBEUV_TEXEL_HEIGHT': 1.0 / height, + 'CUBEUV_MAX_MIP': `${lodMax}.0`, + }, + + uniforms: { + 'envMap': { value: null }, + 'samples': { value: 1 }, + 'weights': { value: weights }, + 'latitudinal': { value: false }, + 'dTheta': { value: 0 }, + 'mipInt': { value: 0 }, + 'poleAxis': { value: poleAxis } + }, + + vertexShader: _getCommonVertexShader(), + + fragmentShader: /* glsl */` + + precision mediump float; + precision mediump int; + + varying vec3 vOutputDirection; + + uniform sampler2D envMap; + uniform int samples; + uniform float weights[ n ]; + uniform bool latitudinal; + uniform float dTheta; + uniform float mipInt; + uniform vec3 poleAxis; + + #define ENVMAP_TYPE_CUBE_UV + #include + + vec3 getSample( float theta, vec3 axis ) { + + float cosTheta = cos( theta ); + // Rodrigues' axis-angle rotation + vec3 sampleDirection = vOutputDirection * cosTheta + + cross( axis, vOutputDirection ) * sin( theta ) + + axis * dot( axis, vOutputDirection ) * ( 1.0 - cosTheta ); + + return bilinearCubeUV( envMap, sampleDirection, mipInt ); + + } + + void main() { + + vec3 axis = latitudinal ? poleAxis : cross( poleAxis, vOutputDirection ); + + if ( all( equal( axis, vec3( 0.0 ) ) ) ) { + + axis = vec3( vOutputDirection.z, 0.0, - vOutputDirection.x ); + + } + + axis = normalize( axis ); + + gl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 ); + gl_FragColor.rgb += weights[ 0 ] * getSample( 0.0, axis ); + + for ( int i = 1; i < n; i++ ) { + + if ( i >= samples ) { + + break; + + } + + float theta = dTheta * float( i ); + gl_FragColor.rgb += weights[ i ] * getSample( -1.0 * theta, axis ); + gl_FragColor.rgb += weights[ i ] * getSample( theta, axis ); + + } + + } + `, + + blending: NoBlending, + depthTest: false, + depthWrite: false + + } ); + + return shaderMaterial; + +} + +function _getEquirectMaterial() { + + return new ShaderMaterial( { + + name: 'EquirectangularToCubeUV', + + uniforms: { + 'envMap': { value: null } + }, + + vertexShader: _getCommonVertexShader(), + + fragmentShader: /* glsl */` + + precision mediump float; + precision mediump int; + + varying vec3 vOutputDirection; + + uniform sampler2D envMap; + + #include + + void main() { + + vec3 outputDirection = normalize( vOutputDirection ); + vec2 uv = equirectUv( outputDirection ); + + gl_FragColor = vec4( texture2D ( envMap, uv ).rgb, 1.0 ); + + } + `, + + blending: NoBlending, + depthTest: false, + depthWrite: false + + } ); + +} + +function _getCubemapMaterial() { + + return new ShaderMaterial( { + + name: 'CubemapToCubeUV', + + uniforms: { + 'envMap': { value: null }, + 'flipEnvMap': { value: - 1 } + }, + + vertexShader: _getCommonVertexShader(), + + fragmentShader: /* glsl */` + + precision mediump float; + precision mediump int; + + uniform float flipEnvMap; + + varying vec3 vOutputDirection; + + uniform samplerCube envMap; + + void main() { + + gl_FragColor = textureCube( envMap, vec3( flipEnvMap * vOutputDirection.x, vOutputDirection.yz ) ); + + } + `, + + blending: NoBlending, + depthTest: false, + depthWrite: false + + } ); + +} + +function _getCommonVertexShader() { + + return /* glsl */` + + precision mediump float; + precision mediump int; + + attribute float faceIndex; + + varying vec3 vOutputDirection; + + // RH coordinate system; PMREM face-indexing convention + vec3 getDirection( vec2 uv, float face ) { + + uv = 2.0 * uv - 1.0; + + vec3 direction = vec3( uv, 1.0 ); + + if ( face == 0.0 ) { + + direction = direction.zyx; // ( 1, v, u ) pos x + + } else if ( face == 1.0 ) { + + direction = direction.xzy; + direction.xz *= -1.0; // ( -u, 1, -v ) pos y + + } else if ( face == 2.0 ) { + + direction.x *= -1.0; // ( -u, v, 1 ) pos z + + } else if ( face == 3.0 ) { + + direction = direction.zyx; + direction.xz *= -1.0; // ( -1, v, -u ) neg x + + } else if ( face == 4.0 ) { + + direction = direction.xzy; + direction.xy *= -1.0; // ( -u, -1, v ) neg y + + } else if ( face == 5.0 ) { + + direction.z *= -1.0; // ( u, v, -1 ) neg z + + } + + return direction; + + } + + void main() { + + vOutputDirection = getDirection( uv, faceIndex ); + gl_Position = vec4( position, 1.0 ); + + } + `; + +} + +function WebGLCubeUVMaps( renderer ) { + + let cubeUVmaps = new WeakMap(); + + let pmremGenerator = null; + + function get( texture ) { + + if ( texture && texture.isTexture ) { + + const mapping = texture.mapping; + + const isEquirectMap = ( mapping === EquirectangularReflectionMapping || mapping === EquirectangularRefractionMapping ); + const isCubeMap = ( mapping === CubeReflectionMapping || mapping === CubeRefractionMapping ); + + // equirect/cube map to cubeUV conversion + + if ( isEquirectMap || isCubeMap ) { + + let renderTarget = cubeUVmaps.get( texture ); + + const currentPMREMVersion = renderTarget !== undefined ? renderTarget.texture.pmremVersion : 0; + + if ( texture.isRenderTargetTexture && texture.pmremVersion !== currentPMREMVersion ) { + + if ( pmremGenerator === null ) pmremGenerator = new PMREMGenerator( renderer ); + + renderTarget = isEquirectMap ? pmremGenerator.fromEquirectangular( texture, renderTarget ) : pmremGenerator.fromCubemap( texture, renderTarget ); + renderTarget.texture.pmremVersion = texture.pmremVersion; + + cubeUVmaps.set( texture, renderTarget ); + + return renderTarget.texture; + + } else { + + if ( renderTarget !== undefined ) { + + return renderTarget.texture; + + } else { + + const image = texture.image; + + if ( ( isEquirectMap && image && image.height > 0 ) || ( isCubeMap && image && isCubeTextureComplete( image ) ) ) { + + if ( pmremGenerator === null ) pmremGenerator = new PMREMGenerator( renderer ); + + renderTarget = isEquirectMap ? pmremGenerator.fromEquirectangular( texture ) : pmremGenerator.fromCubemap( texture ); + renderTarget.texture.pmremVersion = texture.pmremVersion; + + cubeUVmaps.set( texture, renderTarget ); + + texture.addEventListener( 'dispose', onTextureDispose ); + + return renderTarget.texture; + + } else { + + // image not yet ready. try the conversion next frame + + return null; + + } + + } + + } + + } + + } + + return texture; + + } + + function isCubeTextureComplete( image ) { + + let count = 0; + const length = 6; + + for ( let i = 0; i < length; i ++ ) { + + if ( image[ i ] !== undefined ) count ++; + + } + + return count === length; + + + } + + function onTextureDispose( event ) { + + const texture = event.target; + + texture.removeEventListener( 'dispose', onTextureDispose ); + + const cubemapUV = cubeUVmaps.get( texture ); + + if ( cubemapUV !== undefined ) { + + cubeUVmaps.delete( texture ); + cubemapUV.dispose(); + + } + + } + + function dispose() { + + cubeUVmaps = new WeakMap(); + + if ( pmremGenerator !== null ) { + + pmremGenerator.dispose(); + pmremGenerator = null; + + } + + } + + return { + get: get, + dispose: dispose + }; + +} + +function WebGLExtensions( gl ) { + + const extensions = {}; + + function getExtension( name ) { + + if ( extensions[ name ] !== undefined ) { + + return extensions[ name ]; + + } + + let extension; + + switch ( name ) { + + case 'WEBGL_depth_texture': + extension = gl.getExtension( 'WEBGL_depth_texture' ) || gl.getExtension( 'MOZ_WEBGL_depth_texture' ) || gl.getExtension( 'WEBKIT_WEBGL_depth_texture' ); + break; + + case 'EXT_texture_filter_anisotropic': + extension = gl.getExtension( 'EXT_texture_filter_anisotropic' ) || gl.getExtension( 'MOZ_EXT_texture_filter_anisotropic' ) || gl.getExtension( 'WEBKIT_EXT_texture_filter_anisotropic' ); + break; + + case 'WEBGL_compressed_texture_s3tc': + extension = gl.getExtension( 'WEBGL_compressed_texture_s3tc' ) || gl.getExtension( 'MOZ_WEBGL_compressed_texture_s3tc' ) || gl.getExtension( 'WEBKIT_WEBGL_compressed_texture_s3tc' ); + break; + + case 'WEBGL_compressed_texture_pvrtc': + extension = gl.getExtension( 'WEBGL_compressed_texture_pvrtc' ) || gl.getExtension( 'WEBKIT_WEBGL_compressed_texture_pvrtc' ); + break; + + default: + extension = gl.getExtension( name ); + + } + + extensions[ name ] = extension; + + return extension; + + } + + return { + + has: function ( name ) { + + return getExtension( name ) !== null; + + }, + + init: function () { + + getExtension( 'EXT_color_buffer_float' ); + getExtension( 'WEBGL_clip_cull_distance' ); + getExtension( 'OES_texture_float_linear' ); + getExtension( 'EXT_color_buffer_half_float' ); + getExtension( 'WEBGL_multisampled_render_to_texture' ); + getExtension( 'WEBGL_render_shared_exponent' ); + + }, + + get: function ( name ) { + + const extension = getExtension( name ); + + if ( extension === null ) { + + warnOnce( 'THREE.WebGLRenderer: ' + name + ' extension not supported.' ); + + } + + return extension; + + } + + }; + +} + +function WebGLGeometries( gl, attributes, info, bindingStates ) { + + const geometries = {}; + const wireframeAttributes = new WeakMap(); + + function onGeometryDispose( event ) { + + const geometry = event.target; + + if ( geometry.index !== null ) { + + attributes.remove( geometry.index ); + + } + + for ( const name in geometry.attributes ) { + + attributes.remove( geometry.attributes[ name ] ); + + } + + for ( const name in geometry.morphAttributes ) { + + const array = geometry.morphAttributes[ name ]; + + for ( let i = 0, l = array.length; i < l; i ++ ) { + + attributes.remove( array[ i ] ); + + } + + } + + geometry.removeEventListener( 'dispose', onGeometryDispose ); + + delete geometries[ geometry.id ]; + + const attribute = wireframeAttributes.get( geometry ); + + if ( attribute ) { + + attributes.remove( attribute ); + wireframeAttributes.delete( geometry ); + + } + + bindingStates.releaseStatesOfGeometry( geometry ); + + if ( geometry.isInstancedBufferGeometry === true ) { + + delete geometry._maxInstanceCount; + + } + + // + + info.memory.geometries --; + + } + + function get( object, geometry ) { + + if ( geometries[ geometry.id ] === true ) return geometry; + + geometry.addEventListener( 'dispose', onGeometryDispose ); + + geometries[ geometry.id ] = true; + + info.memory.geometries ++; + + return geometry; + + } + + function update( geometry ) { + + const geometryAttributes = geometry.attributes; + + // Updating index buffer in VAO now. See WebGLBindingStates. + + for ( const name in geometryAttributes ) { + + attributes.update( geometryAttributes[ name ], gl.ARRAY_BUFFER ); + + } + + // morph targets + + const morphAttributes = geometry.morphAttributes; + + for ( const name in morphAttributes ) { + + const array = morphAttributes[ name ]; + + for ( let i = 0, l = array.length; i < l; i ++ ) { + + attributes.update( array[ i ], gl.ARRAY_BUFFER ); + + } + + } + + } + + function updateWireframeAttribute( geometry ) { + + const indices = []; + + const geometryIndex = geometry.index; + const geometryPosition = geometry.attributes.position; + let version = 0; + + if ( geometryIndex !== null ) { + + const array = geometryIndex.array; + version = geometryIndex.version; + + for ( let i = 0, l = array.length; i < l; i += 3 ) { + + const a = array[ i + 0 ]; + const b = array[ i + 1 ]; + const c = array[ i + 2 ]; + + indices.push( a, b, b, c, c, a ); + + } + + } else if ( geometryPosition !== undefined ) { + + const array = geometryPosition.array; + version = geometryPosition.version; + + for ( let i = 0, l = ( array.length / 3 ) - 1; i < l; i += 3 ) { + + const a = i + 0; + const b = i + 1; + const c = i + 2; + + indices.push( a, b, b, c, c, a ); + + } + + } else { + + return; + + } + + const attribute = new ( arrayNeedsUint32( indices ) ? Uint32BufferAttribute : Uint16BufferAttribute )( indices, 1 ); + attribute.version = version; + + // Updating index buffer in VAO now. See WebGLBindingStates + + // + + const previousAttribute = wireframeAttributes.get( geometry ); + + if ( previousAttribute ) attributes.remove( previousAttribute ); + + // + + wireframeAttributes.set( geometry, attribute ); + + } + + function getWireframeAttribute( geometry ) { + + const currentAttribute = wireframeAttributes.get( geometry ); + + if ( currentAttribute ) { + + const geometryIndex = geometry.index; + + if ( geometryIndex !== null ) { + + // if the attribute is obsolete, create a new one + + if ( currentAttribute.version < geometryIndex.version ) { + + updateWireframeAttribute( geometry ); + + } + + } + + } else { + + updateWireframeAttribute( geometry ); + + } + + return wireframeAttributes.get( geometry ); + + } + + return { + + get: get, + update: update, + + getWireframeAttribute: getWireframeAttribute + + }; + +} + +function WebGLIndexedBufferRenderer( gl, extensions, info ) { + + let mode; + + function setMode( value ) { + + mode = value; + + } + + let type, bytesPerElement; + + function setIndex( value ) { + + type = value.type; + bytesPerElement = value.bytesPerElement; + + } + + function render( start, count ) { + + gl.drawElements( mode, count, type, start * bytesPerElement ); + + info.update( count, mode, 1 ); + + } + + function renderInstances( start, count, primcount ) { + + if ( primcount === 0 ) return; + + gl.drawElementsInstanced( mode, count, type, start * bytesPerElement, primcount ); + + info.update( count, mode, primcount ); + + } + + function renderMultiDraw( starts, counts, drawCount ) { + + if ( drawCount === 0 ) return; + + const extension = extensions.get( 'WEBGL_multi_draw' ); + + if ( extension === null ) { + + for ( let i = 0; i < drawCount; i ++ ) { + + this.render( starts[ i ] / bytesPerElement, counts[ i ] ); + + } + + } else { + + extension.multiDrawElementsWEBGL( mode, counts, 0, type, starts, 0, drawCount ); + + let elementCount = 0; + for ( let i = 0; i < drawCount; i ++ ) { + + elementCount += counts[ i ]; + + } + + info.update( elementCount, mode, 1 ); + + } + + } + + function renderMultiDrawInstances( starts, counts, drawCount, primcount ) { + + if ( drawCount === 0 ) return; + + const extension = extensions.get( 'WEBGL_multi_draw' ); + + if ( extension === null ) { + + for ( let i = 0; i < starts.length; i ++ ) { + + renderInstances( starts[ i ] / bytesPerElement, counts[ i ], primcount[ i ] ); + + } + + } else { + + extension.multiDrawElementsInstancedWEBGL( mode, counts, 0, type, starts, 0, primcount, 0, drawCount ); + + let elementCount = 0; + for ( let i = 0; i < drawCount; i ++ ) { + + elementCount += counts[ i ]; + + } + + for ( let i = 0; i < primcount.length; i ++ ) { + + info.update( elementCount, mode, primcount[ i ] ); + + } + + } + + } + + // + + this.setMode = setMode; + this.setIndex = setIndex; + this.render = render; + this.renderInstances = renderInstances; + this.renderMultiDraw = renderMultiDraw; + this.renderMultiDrawInstances = renderMultiDrawInstances; + +} + +function WebGLInfo( gl ) { + + const memory = { + geometries: 0, + textures: 0 + }; + + const render = { + frame: 0, + calls: 0, + triangles: 0, + points: 0, + lines: 0 + }; + + function update( count, mode, instanceCount ) { + + render.calls ++; + + switch ( mode ) { + + case gl.TRIANGLES: + render.triangles += instanceCount * ( count / 3 ); + break; + + case gl.LINES: + render.lines += instanceCount * ( count / 2 ); + break; + + case gl.LINE_STRIP: + render.lines += instanceCount * ( count - 1 ); + break; + + case gl.LINE_LOOP: + render.lines += instanceCount * count; + break; + + case gl.POINTS: + render.points += instanceCount * count; + break; + + default: + console.error( 'THREE.WebGLInfo: Unknown draw mode:', mode ); + break; + + } + + } + + function reset() { + + render.calls = 0; + render.triangles = 0; + render.points = 0; + render.lines = 0; + + } + + return { + memory: memory, + render: render, + programs: null, + autoReset: true, + reset: reset, + update: update + }; + +} + +function WebGLMorphtargets( gl, capabilities, textures ) { + + const morphTextures = new WeakMap(); + const morph = new Vector4(); + + function update( object, geometry, program ) { + + const objectInfluences = object.morphTargetInfluences; + + // the following encodes morph targets into an array of data textures. Each layer represents a single morph target. + + const morphAttribute = geometry.morphAttributes.position || geometry.morphAttributes.normal || geometry.morphAttributes.color; + const morphTargetsCount = ( morphAttribute !== undefined ) ? morphAttribute.length : 0; + + let entry = morphTextures.get( geometry ); + + if ( entry === undefined || entry.count !== morphTargetsCount ) { + + if ( entry !== undefined ) entry.texture.dispose(); + + const hasMorphPosition = geometry.morphAttributes.position !== undefined; + const hasMorphNormals = geometry.morphAttributes.normal !== undefined; + const hasMorphColors = geometry.morphAttributes.color !== undefined; + + const morphTargets = geometry.morphAttributes.position || []; + const morphNormals = geometry.morphAttributes.normal || []; + const morphColors = geometry.morphAttributes.color || []; + + let vertexDataCount = 0; + + if ( hasMorphPosition === true ) vertexDataCount = 1; + if ( hasMorphNormals === true ) vertexDataCount = 2; + if ( hasMorphColors === true ) vertexDataCount = 3; + + let width = geometry.attributes.position.count * vertexDataCount; + let height = 1; + + if ( width > capabilities.maxTextureSize ) { + + height = Math.ceil( width / capabilities.maxTextureSize ); + width = capabilities.maxTextureSize; + + } + + const buffer = new Float32Array( width * height * 4 * morphTargetsCount ); + + const texture = new DataArrayTexture( buffer, width, height, morphTargetsCount ); + texture.type = FloatType; + texture.needsUpdate = true; + + // fill buffer + + const vertexDataStride = vertexDataCount * 4; + + for ( let i = 0; i < morphTargetsCount; i ++ ) { + + const morphTarget = morphTargets[ i ]; + const morphNormal = morphNormals[ i ]; + const morphColor = morphColors[ i ]; + + const offset = width * height * 4 * i; + + for ( let j = 0; j < morphTarget.count; j ++ ) { + + const stride = j * vertexDataStride; + + if ( hasMorphPosition === true ) { + + morph.fromBufferAttribute( morphTarget, j ); + + buffer[ offset + stride + 0 ] = morph.x; + buffer[ offset + stride + 1 ] = morph.y; + buffer[ offset + stride + 2 ] = morph.z; + buffer[ offset + stride + 3 ] = 0; + + } + + if ( hasMorphNormals === true ) { + + morph.fromBufferAttribute( morphNormal, j ); + + buffer[ offset + stride + 4 ] = morph.x; + buffer[ offset + stride + 5 ] = morph.y; + buffer[ offset + stride + 6 ] = morph.z; + buffer[ offset + stride + 7 ] = 0; + + } + + if ( hasMorphColors === true ) { + + morph.fromBufferAttribute( morphColor, j ); + + buffer[ offset + stride + 8 ] = morph.x; + buffer[ offset + stride + 9 ] = morph.y; + buffer[ offset + stride + 10 ] = morph.z; + buffer[ offset + stride + 11 ] = ( morphColor.itemSize === 4 ) ? morph.w : 1; + + } + + } + + } + + entry = { + count: morphTargetsCount, + texture: texture, + size: new Vector2( width, height ) + }; + + morphTextures.set( geometry, entry ); + + function disposeTexture() { + + texture.dispose(); + + morphTextures.delete( geometry ); + + geometry.removeEventListener( 'dispose', disposeTexture ); + + } + + geometry.addEventListener( 'dispose', disposeTexture ); + + } + + // + if ( object.isInstancedMesh === true && object.morphTexture !== null ) { + + program.getUniforms().setValue( gl, 'morphTexture', object.morphTexture, textures ); + + } else { + + let morphInfluencesSum = 0; + + for ( let i = 0; i < objectInfluences.length; i ++ ) { + + morphInfluencesSum += objectInfluences[ i ]; + + } + + const morphBaseInfluence = geometry.morphTargetsRelative ? 1 : 1 - morphInfluencesSum; + + + program.getUniforms().setValue( gl, 'morphTargetBaseInfluence', morphBaseInfluence ); + program.getUniforms().setValue( gl, 'morphTargetInfluences', objectInfluences ); + + } + + program.getUniforms().setValue( gl, 'morphTargetsTexture', entry.texture, textures ); + program.getUniforms().setValue( gl, 'morphTargetsTextureSize', entry.size ); + + } + + return { + + update: update + + }; + +} + +function WebGLObjects( gl, geometries, attributes, info ) { + + let updateMap = new WeakMap(); + + function update( object ) { + + const frame = info.render.frame; + + const geometry = object.geometry; + const buffergeometry = geometries.get( object, geometry ); + + // Update once per frame + + if ( updateMap.get( buffergeometry ) !== frame ) { + + geometries.update( buffergeometry ); + + updateMap.set( buffergeometry, frame ); + + } + + if ( object.isInstancedMesh ) { + + if ( object.hasEventListener( 'dispose', onInstancedMeshDispose ) === false ) { + + object.addEventListener( 'dispose', onInstancedMeshDispose ); + + } + + if ( updateMap.get( object ) !== frame ) { + + attributes.update( object.instanceMatrix, gl.ARRAY_BUFFER ); + + if ( object.instanceColor !== null ) { + + attributes.update( object.instanceColor, gl.ARRAY_BUFFER ); + + } + + updateMap.set( object, frame ); + + } + + } + + if ( object.isSkinnedMesh ) { + + const skeleton = object.skeleton; + + if ( updateMap.get( skeleton ) !== frame ) { + + skeleton.update(); + + updateMap.set( skeleton, frame ); + + } + + } + + return buffergeometry; + + } + + function dispose() { + + updateMap = new WeakMap(); + + } + + function onInstancedMeshDispose( event ) { + + const instancedMesh = event.target; + + instancedMesh.removeEventListener( 'dispose', onInstancedMeshDispose ); + + attributes.remove( instancedMesh.instanceMatrix ); + + if ( instancedMesh.instanceColor !== null ) attributes.remove( instancedMesh.instanceColor ); + + } + + return { + + update: update, + dispose: dispose + + }; + +} + +class DepthTexture extends Texture { + + constructor( width, height, type, mapping, wrapS, wrapT, magFilter, minFilter, anisotropy, format = DepthFormat ) { + + if ( format !== DepthFormat && format !== DepthStencilFormat ) { + + throw new Error( 'DepthTexture format must be either THREE.DepthFormat or THREE.DepthStencilFormat' ); + + } + + if ( type === undefined && format === DepthFormat ) type = UnsignedIntType; + if ( type === undefined && format === DepthStencilFormat ) type = UnsignedInt248Type; + + super( null, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy ); + + this.isDepthTexture = true; + + this.image = { width: width, height: height }; + + this.magFilter = magFilter !== undefined ? magFilter : NearestFilter; + this.minFilter = minFilter !== undefined ? minFilter : NearestFilter; + + this.flipY = false; + this.generateMipmaps = false; + + this.compareFunction = null; + + } + + + copy( source ) { + + super.copy( source ); + + this.compareFunction = source.compareFunction; + + return this; + + } + + toJSON( meta ) { + + const data = super.toJSON( meta ); + + if ( this.compareFunction !== null ) data.compareFunction = this.compareFunction; + + return data; + + } + +} + +/** + * Uniforms of a program. + * Those form a tree structure with a special top-level container for the root, + * which you get by calling 'new WebGLUniforms( gl, program )'. + * + * + * Properties of inner nodes including the top-level container: + * + * .seq - array of nested uniforms + * .map - nested uniforms by name + * + * + * Methods of all nodes except the top-level container: + * + * .setValue( gl, value, [textures] ) + * + * uploads a uniform value(s) + * the 'textures' parameter is needed for sampler uniforms + * + * + * Static methods of the top-level container (textures factorizations): + * + * .upload( gl, seq, values, textures ) + * + * sets uniforms in 'seq' to 'values[id].value' + * + * .seqWithValue( seq, values ) : filteredSeq + * + * filters 'seq' entries with corresponding entry in values + * + * + * Methods of the top-level container (textures factorizations): + * + * .setValue( gl, name, value, textures ) + * + * sets uniform with name 'name' to 'value' + * + * .setOptional( gl, obj, prop ) + * + * like .set for an optional property of the object + * + */ + + +const emptyTexture = /*@__PURE__*/ new Texture(); + +const emptyShadowTexture = /*@__PURE__*/ new DepthTexture( 1, 1 ); +emptyShadowTexture.compareFunction = LessEqualCompare; + +const emptyArrayTexture = /*@__PURE__*/ new DataArrayTexture(); +const empty3dTexture = /*@__PURE__*/ new Data3DTexture(); +const emptyCubeTexture = /*@__PURE__*/ new CubeTexture(); + +// --- Utilities --- + +// Array Caches (provide typed arrays for temporary by size) + +const arrayCacheF32 = []; +const arrayCacheI32 = []; + +// Float32Array caches used for uploading Matrix uniforms + +const mat4array = new Float32Array( 16 ); +const mat3array = new Float32Array( 9 ); +const mat2array = new Float32Array( 4 ); + +// Flattening for arrays of vectors and matrices + +function flatten( array, nBlocks, blockSize ) { + + const firstElem = array[ 0 ]; + + if ( firstElem <= 0 || firstElem > 0 ) return array; + // unoptimized: ! isNaN( firstElem ) + // see http://jacksondunstan.com/articles/983 + + const n = nBlocks * blockSize; + let r = arrayCacheF32[ n ]; + + if ( r === undefined ) { + + r = new Float32Array( n ); + arrayCacheF32[ n ] = r; + + } + + if ( nBlocks !== 0 ) { + + firstElem.toArray( r, 0 ); + + for ( let i = 1, offset = 0; i !== nBlocks; ++ i ) { + + offset += blockSize; + array[ i ].toArray( r, offset ); + + } + + } + + return r; + +} + +function arraysEqual( a, b ) { + + if ( a.length !== b.length ) return false; + + for ( let i = 0, l = a.length; i < l; i ++ ) { + + if ( a[ i ] !== b[ i ] ) return false; + + } + + return true; + +} + +function copyArray( a, b ) { + + for ( let i = 0, l = b.length; i < l; i ++ ) { + + a[ i ] = b[ i ]; + + } + +} + +// Texture unit allocation + +function allocTexUnits( textures, n ) { + + let r = arrayCacheI32[ n ]; + + if ( r === undefined ) { + + r = new Int32Array( n ); + arrayCacheI32[ n ] = r; + + } + + for ( let i = 0; i !== n; ++ i ) { + + r[ i ] = textures.allocateTextureUnit(); + + } + + return r; + +} + +// --- Setters --- + +// Note: Defining these methods externally, because they come in a bunch +// and this way their names minify. + +// Single scalar + +function setValueV1f( gl, v ) { + + const cache = this.cache; + + if ( cache[ 0 ] === v ) return; + + gl.uniform1f( this.addr, v ); + + cache[ 0 ] = v; + +} + +// Single float vector (from flat array or THREE.VectorN) + +function setValueV2f( gl, v ) { + + const cache = this.cache; + + if ( v.x !== undefined ) { + + if ( cache[ 0 ] !== v.x || cache[ 1 ] !== v.y ) { + + gl.uniform2f( this.addr, v.x, v.y ); + + cache[ 0 ] = v.x; + cache[ 1 ] = v.y; + + } + + } else { + + if ( arraysEqual( cache, v ) ) return; + + gl.uniform2fv( this.addr, v ); + + copyArray( cache, v ); + + } + +} + +function setValueV3f( gl, v ) { + + const cache = this.cache; + + if ( v.x !== undefined ) { + + if ( cache[ 0 ] !== v.x || cache[ 1 ] !== v.y || cache[ 2 ] !== v.z ) { + + gl.uniform3f( this.addr, v.x, v.y, v.z ); + + cache[ 0 ] = v.x; + cache[ 1 ] = v.y; + cache[ 2 ] = v.z; + + } + + } else if ( v.r !== undefined ) { + + if ( cache[ 0 ] !== v.r || cache[ 1 ] !== v.g || cache[ 2 ] !== v.b ) { + + gl.uniform3f( this.addr, v.r, v.g, v.b ); + + cache[ 0 ] = v.r; + cache[ 1 ] = v.g; + cache[ 2 ] = v.b; + + } + + } else { + + if ( arraysEqual( cache, v ) ) return; + + gl.uniform3fv( this.addr, v ); + + copyArray( cache, v ); + + } + +} + +function setValueV4f( gl, v ) { + + const cache = this.cache; + + if ( v.x !== undefined ) { + + if ( cache[ 0 ] !== v.x || cache[ 1 ] !== v.y || cache[ 2 ] !== v.z || cache[ 3 ] !== v.w ) { + + gl.uniform4f( this.addr, v.x, v.y, v.z, v.w ); + + cache[ 0 ] = v.x; + cache[ 1 ] = v.y; + cache[ 2 ] = v.z; + cache[ 3 ] = v.w; + + } + + } else { + + if ( arraysEqual( cache, v ) ) return; + + gl.uniform4fv( this.addr, v ); + + copyArray( cache, v ); + + } + +} + +// Single matrix (from flat array or THREE.MatrixN) + +function setValueM2( gl, v ) { + + const cache = this.cache; + const elements = v.elements; + + if ( elements === undefined ) { + + if ( arraysEqual( cache, v ) ) return; + + gl.uniformMatrix2fv( this.addr, false, v ); + + copyArray( cache, v ); + + } else { + + if ( arraysEqual( cache, elements ) ) return; + + mat2array.set( elements ); + + gl.uniformMatrix2fv( this.addr, false, mat2array ); + + copyArray( cache, elements ); + + } + +} + +function setValueM3( gl, v ) { + + const cache = this.cache; + const elements = v.elements; + + if ( elements === undefined ) { + + if ( arraysEqual( cache, v ) ) return; + + gl.uniformMatrix3fv( this.addr, false, v ); + + copyArray( cache, v ); + + } else { + + if ( arraysEqual( cache, elements ) ) return; + + mat3array.set( elements ); + + gl.uniformMatrix3fv( this.addr, false, mat3array ); + + copyArray( cache, elements ); + + } + +} + +function setValueM4( gl, v ) { + + const cache = this.cache; + const elements = v.elements; + + if ( elements === undefined ) { + + if ( arraysEqual( cache, v ) ) return; + + gl.uniformMatrix4fv( this.addr, false, v ); + + copyArray( cache, v ); + + } else { + + if ( arraysEqual( cache, elements ) ) return; + + mat4array.set( elements ); + + gl.uniformMatrix4fv( this.addr, false, mat4array ); + + copyArray( cache, elements ); + + } + +} + +// Single integer / boolean + +function setValueV1i( gl, v ) { + + const cache = this.cache; + + if ( cache[ 0 ] === v ) return; + + gl.uniform1i( this.addr, v ); + + cache[ 0 ] = v; + +} + +// Single integer / boolean vector (from flat array or THREE.VectorN) + +function setValueV2i( gl, v ) { + + const cache = this.cache; + + if ( v.x !== undefined ) { + + if ( cache[ 0 ] !== v.x || cache[ 1 ] !== v.y ) { + + gl.uniform2i( this.addr, v.x, v.y ); + + cache[ 0 ] = v.x; + cache[ 1 ] = v.y; + + } + + } else { + + if ( arraysEqual( cache, v ) ) return; + + gl.uniform2iv( this.addr, v ); + + copyArray( cache, v ); + + } + +} + +function setValueV3i( gl, v ) { + + const cache = this.cache; + + if ( v.x !== undefined ) { + + if ( cache[ 0 ] !== v.x || cache[ 1 ] !== v.y || cache[ 2 ] !== v.z ) { + + gl.uniform3i( this.addr, v.x, v.y, v.z ); + + cache[ 0 ] = v.x; + cache[ 1 ] = v.y; + cache[ 2 ] = v.z; + + } + + } else { + + if ( arraysEqual( cache, v ) ) return; + + gl.uniform3iv( this.addr, v ); + + copyArray( cache, v ); + + } + +} + +function setValueV4i( gl, v ) { + + const cache = this.cache; + + if ( v.x !== undefined ) { + + if ( cache[ 0 ] !== v.x || cache[ 1 ] !== v.y || cache[ 2 ] !== v.z || cache[ 3 ] !== v.w ) { + + gl.uniform4i( this.addr, v.x, v.y, v.z, v.w ); + + cache[ 0 ] = v.x; + cache[ 1 ] = v.y; + cache[ 2 ] = v.z; + cache[ 3 ] = v.w; + + } + + } else { + + if ( arraysEqual( cache, v ) ) return; + + gl.uniform4iv( this.addr, v ); + + copyArray( cache, v ); + + } + +} + +// Single unsigned integer + +function setValueV1ui( gl, v ) { + + const cache = this.cache; + + if ( cache[ 0 ] === v ) return; + + gl.uniform1ui( this.addr, v ); + + cache[ 0 ] = v; + +} + +// Single unsigned integer vector (from flat array or THREE.VectorN) + +function setValueV2ui( gl, v ) { + + const cache = this.cache; + + if ( v.x !== undefined ) { + + if ( cache[ 0 ] !== v.x || cache[ 1 ] !== v.y ) { + + gl.uniform2ui( this.addr, v.x, v.y ); + + cache[ 0 ] = v.x; + cache[ 1 ] = v.y; + + } + + } else { + + if ( arraysEqual( cache, v ) ) return; + + gl.uniform2uiv( this.addr, v ); + + copyArray( cache, v ); + + } + +} + +function setValueV3ui( gl, v ) { + + const cache = this.cache; + + if ( v.x !== undefined ) { + + if ( cache[ 0 ] !== v.x || cache[ 1 ] !== v.y || cache[ 2 ] !== v.z ) { + + gl.uniform3ui( this.addr, v.x, v.y, v.z ); + + cache[ 0 ] = v.x; + cache[ 1 ] = v.y; + cache[ 2 ] = v.z; + + } + + } else { + + if ( arraysEqual( cache, v ) ) return; + + gl.uniform3uiv( this.addr, v ); + + copyArray( cache, v ); + + } + +} + +function setValueV4ui( gl, v ) { + + const cache = this.cache; + + if ( v.x !== undefined ) { + + if ( cache[ 0 ] !== v.x || cache[ 1 ] !== v.y || cache[ 2 ] !== v.z || cache[ 3 ] !== v.w ) { + + gl.uniform4ui( this.addr, v.x, v.y, v.z, v.w ); + + cache[ 0 ] = v.x; + cache[ 1 ] = v.y; + cache[ 2 ] = v.z; + cache[ 3 ] = v.w; + + } + + } else { + + if ( arraysEqual( cache, v ) ) return; + + gl.uniform4uiv( this.addr, v ); + + copyArray( cache, v ); + + } + +} + + +// Single texture (2D / Cube) + +function setValueT1( gl, v, textures ) { + + const cache = this.cache; + const unit = textures.allocateTextureUnit(); + + if ( cache[ 0 ] !== unit ) { + + gl.uniform1i( this.addr, unit ); + cache[ 0 ] = unit; + + } + + const emptyTexture2D = ( this.type === gl.SAMPLER_2D_SHADOW ) ? emptyShadowTexture : emptyTexture; + + textures.setTexture2D( v || emptyTexture2D, unit ); + +} + +function setValueT3D1( gl, v, textures ) { + + const cache = this.cache; + const unit = textures.allocateTextureUnit(); + + if ( cache[ 0 ] !== unit ) { + + gl.uniform1i( this.addr, unit ); + cache[ 0 ] = unit; + + } + + textures.setTexture3D( v || empty3dTexture, unit ); + +} + +function setValueT6( gl, v, textures ) { + + const cache = this.cache; + const unit = textures.allocateTextureUnit(); + + if ( cache[ 0 ] !== unit ) { + + gl.uniform1i( this.addr, unit ); + cache[ 0 ] = unit; + + } + + textures.setTextureCube( v || emptyCubeTexture, unit ); + +} + +function setValueT2DArray1( gl, v, textures ) { + + const cache = this.cache; + const unit = textures.allocateTextureUnit(); + + if ( cache[ 0 ] !== unit ) { + + gl.uniform1i( this.addr, unit ); + cache[ 0 ] = unit; + + } + + textures.setTexture2DArray( v || emptyArrayTexture, unit ); + +} + +// Helper to pick the right setter for the singular case + +function getSingularSetter( type ) { + + switch ( type ) { + + case 0x1406: return setValueV1f; // FLOAT + case 0x8b50: return setValueV2f; // _VEC2 + case 0x8b51: return setValueV3f; // _VEC3 + case 0x8b52: return setValueV4f; // _VEC4 + + case 0x8b5a: return setValueM2; // _MAT2 + case 0x8b5b: return setValueM3; // _MAT3 + case 0x8b5c: return setValueM4; // _MAT4 + + case 0x1404: case 0x8b56: return setValueV1i; // INT, BOOL + case 0x8b53: case 0x8b57: return setValueV2i; // _VEC2 + case 0x8b54: case 0x8b58: return setValueV3i; // _VEC3 + case 0x8b55: case 0x8b59: return setValueV4i; // _VEC4 + + case 0x1405: return setValueV1ui; // UINT + case 0x8dc6: return setValueV2ui; // _VEC2 + case 0x8dc7: return setValueV3ui; // _VEC3 + case 0x8dc8: return setValueV4ui; // _VEC4 + + case 0x8b5e: // SAMPLER_2D + case 0x8d66: // SAMPLER_EXTERNAL_OES + case 0x8dca: // INT_SAMPLER_2D + case 0x8dd2: // UNSIGNED_INT_SAMPLER_2D + case 0x8b62: // SAMPLER_2D_SHADOW + return setValueT1; + + case 0x8b5f: // SAMPLER_3D + case 0x8dcb: // INT_SAMPLER_3D + case 0x8dd3: // UNSIGNED_INT_SAMPLER_3D + return setValueT3D1; + + case 0x8b60: // SAMPLER_CUBE + case 0x8dcc: // INT_SAMPLER_CUBE + case 0x8dd4: // UNSIGNED_INT_SAMPLER_CUBE + case 0x8dc5: // SAMPLER_CUBE_SHADOW + return setValueT6; + + case 0x8dc1: // SAMPLER_2D_ARRAY + case 0x8dcf: // INT_SAMPLER_2D_ARRAY + case 0x8dd7: // UNSIGNED_INT_SAMPLER_2D_ARRAY + case 0x8dc4: // SAMPLER_2D_ARRAY_SHADOW + return setValueT2DArray1; + + } + +} + + +// Array of scalars + +function setValueV1fArray( gl, v ) { + + gl.uniform1fv( this.addr, v ); + +} + +// Array of vectors (from flat array or array of THREE.VectorN) + +function setValueV2fArray( gl, v ) { + + const data = flatten( v, this.size, 2 ); + + gl.uniform2fv( this.addr, data ); + +} + +function setValueV3fArray( gl, v ) { + + const data = flatten( v, this.size, 3 ); + + gl.uniform3fv( this.addr, data ); + +} + +function setValueV4fArray( gl, v ) { + + const data = flatten( v, this.size, 4 ); + + gl.uniform4fv( this.addr, data ); + +} + +// Array of matrices (from flat array or array of THREE.MatrixN) + +function setValueM2Array( gl, v ) { + + const data = flatten( v, this.size, 4 ); + + gl.uniformMatrix2fv( this.addr, false, data ); + +} + +function setValueM3Array( gl, v ) { + + const data = flatten( v, this.size, 9 ); + + gl.uniformMatrix3fv( this.addr, false, data ); + +} + +function setValueM4Array( gl, v ) { + + const data = flatten( v, this.size, 16 ); + + gl.uniformMatrix4fv( this.addr, false, data ); + +} + +// Array of integer / boolean + +function setValueV1iArray( gl, v ) { + + gl.uniform1iv( this.addr, v ); + +} + +// Array of integer / boolean vectors (from flat array) + +function setValueV2iArray( gl, v ) { + + gl.uniform2iv( this.addr, v ); + +} + +function setValueV3iArray( gl, v ) { + + gl.uniform3iv( this.addr, v ); + +} + +function setValueV4iArray( gl, v ) { + + gl.uniform4iv( this.addr, v ); + +} + +// Array of unsigned integer + +function setValueV1uiArray( gl, v ) { + + gl.uniform1uiv( this.addr, v ); + +} + +// Array of unsigned integer vectors (from flat array) + +function setValueV2uiArray( gl, v ) { + + gl.uniform2uiv( this.addr, v ); + +} + +function setValueV3uiArray( gl, v ) { + + gl.uniform3uiv( this.addr, v ); + +} + +function setValueV4uiArray( gl, v ) { + + gl.uniform4uiv( this.addr, v ); + +} + + +// Array of textures (2D / 3D / Cube / 2DArray) + +function setValueT1Array( gl, v, textures ) { + + const cache = this.cache; + + const n = v.length; + + const units = allocTexUnits( textures, n ); + + if ( ! arraysEqual( cache, units ) ) { + + gl.uniform1iv( this.addr, units ); + + copyArray( cache, units ); + + } + + for ( let i = 0; i !== n; ++ i ) { + + textures.setTexture2D( v[ i ] || emptyTexture, units[ i ] ); + + } + +} + +function setValueT3DArray( gl, v, textures ) { + + const cache = this.cache; + + const n = v.length; + + const units = allocTexUnits( textures, n ); + + if ( ! arraysEqual( cache, units ) ) { + + gl.uniform1iv( this.addr, units ); + + copyArray( cache, units ); + + } + + for ( let i = 0; i !== n; ++ i ) { + + textures.setTexture3D( v[ i ] || empty3dTexture, units[ i ] ); + + } + +} + +function setValueT6Array( gl, v, textures ) { + + const cache = this.cache; + + const n = v.length; + + const units = allocTexUnits( textures, n ); + + if ( ! arraysEqual( cache, units ) ) { + + gl.uniform1iv( this.addr, units ); + + copyArray( cache, units ); + + } + + for ( let i = 0; i !== n; ++ i ) { + + textures.setTextureCube( v[ i ] || emptyCubeTexture, units[ i ] ); + + } + +} + +function setValueT2DArrayArray( gl, v, textures ) { + + const cache = this.cache; + + const n = v.length; + + const units = allocTexUnits( textures, n ); + + if ( ! arraysEqual( cache, units ) ) { + + gl.uniform1iv( this.addr, units ); + + copyArray( cache, units ); + + } + + for ( let i = 0; i !== n; ++ i ) { + + textures.setTexture2DArray( v[ i ] || emptyArrayTexture, units[ i ] ); + + } + +} + + +// Helper to pick the right setter for a pure (bottom-level) array + +function getPureArraySetter( type ) { + + switch ( type ) { + + case 0x1406: return setValueV1fArray; // FLOAT + case 0x8b50: return setValueV2fArray; // _VEC2 + case 0x8b51: return setValueV3fArray; // _VEC3 + case 0x8b52: return setValueV4fArray; // _VEC4 + + case 0x8b5a: return setValueM2Array; // _MAT2 + case 0x8b5b: return setValueM3Array; // _MAT3 + case 0x8b5c: return setValueM4Array; // _MAT4 + + case 0x1404: case 0x8b56: return setValueV1iArray; // INT, BOOL + case 0x8b53: case 0x8b57: return setValueV2iArray; // _VEC2 + case 0x8b54: case 0x8b58: return setValueV3iArray; // _VEC3 + case 0x8b55: case 0x8b59: return setValueV4iArray; // _VEC4 + + case 0x1405: return setValueV1uiArray; // UINT + case 0x8dc6: return setValueV2uiArray; // _VEC2 + case 0x8dc7: return setValueV3uiArray; // _VEC3 + case 0x8dc8: return setValueV4uiArray; // _VEC4 + + case 0x8b5e: // SAMPLER_2D + case 0x8d66: // SAMPLER_EXTERNAL_OES + case 0x8dca: // INT_SAMPLER_2D + case 0x8dd2: // UNSIGNED_INT_SAMPLER_2D + case 0x8b62: // SAMPLER_2D_SHADOW + return setValueT1Array; + + case 0x8b5f: // SAMPLER_3D + case 0x8dcb: // INT_SAMPLER_3D + case 0x8dd3: // UNSIGNED_INT_SAMPLER_3D + return setValueT3DArray; + + case 0x8b60: // SAMPLER_CUBE + case 0x8dcc: // INT_SAMPLER_CUBE + case 0x8dd4: // UNSIGNED_INT_SAMPLER_CUBE + case 0x8dc5: // SAMPLER_CUBE_SHADOW + return setValueT6Array; + + case 0x8dc1: // SAMPLER_2D_ARRAY + case 0x8dcf: // INT_SAMPLER_2D_ARRAY + case 0x8dd7: // UNSIGNED_INT_SAMPLER_2D_ARRAY + case 0x8dc4: // SAMPLER_2D_ARRAY_SHADOW + return setValueT2DArrayArray; + + } + +} + +// --- Uniform Classes --- + +class SingleUniform { + + constructor( id, activeInfo, addr ) { + + this.id = id; + this.addr = addr; + this.cache = []; + this.type = activeInfo.type; + this.setValue = getSingularSetter( activeInfo.type ); + + // this.path = activeInfo.name; // DEBUG + + } + +} + +class PureArrayUniform { + + constructor( id, activeInfo, addr ) { + + this.id = id; + this.addr = addr; + this.cache = []; + this.type = activeInfo.type; + this.size = activeInfo.size; + this.setValue = getPureArraySetter( activeInfo.type ); + + // this.path = activeInfo.name; // DEBUG + + } + +} + +class StructuredUniform { + + constructor( id ) { + + this.id = id; + + this.seq = []; + this.map = {}; + + } + + setValue( gl, value, textures ) { + + const seq = this.seq; + + for ( let i = 0, n = seq.length; i !== n; ++ i ) { + + const u = seq[ i ]; + u.setValue( gl, value[ u.id ], textures ); + + } + + } + +} + +// --- Top-level --- + +// Parser - builds up the property tree from the path strings + +const RePathPart = /(\w+)(\])?(\[|\.)?/g; + +// extracts +// - the identifier (member name or array index) +// - followed by an optional right bracket (found when array index) +// - followed by an optional left bracket or dot (type of subscript) +// +// Note: These portions can be read in a non-overlapping fashion and +// allow straightforward parsing of the hierarchy that WebGL encodes +// in the uniform names. + +function addUniform( container, uniformObject ) { + + container.seq.push( uniformObject ); + container.map[ uniformObject.id ] = uniformObject; + +} + +function parseUniform( activeInfo, addr, container ) { + + const path = activeInfo.name, + pathLength = path.length; + + // reset RegExp object, because of the early exit of a previous run + RePathPart.lastIndex = 0; + + while ( true ) { + + const match = RePathPart.exec( path ), + matchEnd = RePathPart.lastIndex; + + let id = match[ 1 ]; + const idIsIndex = match[ 2 ] === ']', + subscript = match[ 3 ]; + + if ( idIsIndex ) id = id | 0; // convert to integer + + if ( subscript === undefined || subscript === '[' && matchEnd + 2 === pathLength ) { + + // bare name or "pure" bottom-level array "[0]" suffix + + addUniform( container, subscript === undefined ? + new SingleUniform( id, activeInfo, addr ) : + new PureArrayUniform( id, activeInfo, addr ) ); + + break; + + } else { + + // step into inner node / create it in case it doesn't exist + + const map = container.map; + let next = map[ id ]; + + if ( next === undefined ) { + + next = new StructuredUniform( id ); + addUniform( container, next ); + + } + + container = next; + + } + + } + +} + +// Root Container + +class WebGLUniforms { + + constructor( gl, program ) { + + this.seq = []; + this.map = {}; + + const n = gl.getProgramParameter( program, gl.ACTIVE_UNIFORMS ); + + for ( let i = 0; i < n; ++ i ) { + + const info = gl.getActiveUniform( program, i ), + addr = gl.getUniformLocation( program, info.name ); + + parseUniform( info, addr, this ); + + } + + } + + setValue( gl, name, value, textures ) { + + const u = this.map[ name ]; + + if ( u !== undefined ) u.setValue( gl, value, textures ); + + } + + setOptional( gl, object, name ) { + + const v = object[ name ]; + + if ( v !== undefined ) this.setValue( gl, name, v ); + + } + + static upload( gl, seq, values, textures ) { + + for ( let i = 0, n = seq.length; i !== n; ++ i ) { + + const u = seq[ i ], + v = values[ u.id ]; + + if ( v.needsUpdate !== false ) { + + // note: always updating when .needsUpdate is undefined + u.setValue( gl, v.value, textures ); + + } + + } + + } + + static seqWithValue( seq, values ) { + + const r = []; + + for ( let i = 0, n = seq.length; i !== n; ++ i ) { + + const u = seq[ i ]; + if ( u.id in values ) r.push( u ); + + } + + return r; + + } + +} + +function WebGLShader( gl, type, string ) { + + const shader = gl.createShader( type ); + + gl.shaderSource( shader, string ); + gl.compileShader( shader ); + + return shader; + +} + +// From https://www.khronos.org/registry/webgl/extensions/KHR_parallel_shader_compile/ +const COMPLETION_STATUS_KHR = 0x91B1; + +let programIdCount = 0; + +function handleSource( string, errorLine ) { + + const lines = string.split( '\n' ); + const lines2 = []; + + const from = Math.max( errorLine - 6, 0 ); + const to = Math.min( errorLine + 6, lines.length ); + + for ( let i = from; i < to; i ++ ) { + + const line = i + 1; + lines2.push( `${line === errorLine ? '>' : ' '} ${line}: ${lines[ i ]}` ); + + } + + return lines2.join( '\n' ); + +} + +function getEncodingComponents( colorSpace ) { + + const workingPrimaries = ColorManagement.getPrimaries( ColorManagement.workingColorSpace ); + const encodingPrimaries = ColorManagement.getPrimaries( colorSpace ); + + let gamutMapping; + + if ( workingPrimaries === encodingPrimaries ) { + + gamutMapping = ''; + + } else if ( workingPrimaries === P3Primaries && encodingPrimaries === Rec709Primaries ) { + + gamutMapping = 'LinearDisplayP3ToLinearSRGB'; + + } else if ( workingPrimaries === Rec709Primaries && encodingPrimaries === P3Primaries ) { + + gamutMapping = 'LinearSRGBToLinearDisplayP3'; + + } + + switch ( colorSpace ) { + + case LinearSRGBColorSpace: + case LinearDisplayP3ColorSpace: + return [ gamutMapping, 'LinearTransferOETF' ]; + + case SRGBColorSpace: + case DisplayP3ColorSpace: + return [ gamutMapping, 'sRGBTransferOETF' ]; + + default: + console.warn( 'THREE.WebGLProgram: Unsupported color space:', colorSpace ); + return [ gamutMapping, 'LinearTransferOETF' ]; + + } + +} + +function getShaderErrors( gl, shader, type ) { + + const status = gl.getShaderParameter( shader, gl.COMPILE_STATUS ); + const errors = gl.getShaderInfoLog( shader ).trim(); + + if ( status && errors === '' ) return ''; + + const errorMatches = /ERROR: 0:(\d+)/.exec( errors ); + if ( errorMatches ) { + + // --enable-privileged-webgl-extension + // console.log( '**' + type + '**', gl.getExtension( 'WEBGL_debug_shaders' ).getTranslatedShaderSource( shader ) ); + + const errorLine = parseInt( errorMatches[ 1 ] ); + return type.toUpperCase() + '\n\n' + errors + '\n\n' + handleSource( gl.getShaderSource( shader ), errorLine ); + + } else { + + return errors; + + } + +} + +function getTexelEncodingFunction( functionName, colorSpace ) { + + const components = getEncodingComponents( colorSpace ); + return `vec4 ${functionName}( vec4 value ) { return ${components[ 0 ]}( ${components[ 1 ]}( value ) ); }`; + +} + +function getToneMappingFunction( functionName, toneMapping ) { + + let toneMappingName; + + switch ( toneMapping ) { + + case LinearToneMapping: + toneMappingName = 'Linear'; + break; + + case ReinhardToneMapping: + toneMappingName = 'Reinhard'; + break; + + case CineonToneMapping: + toneMappingName = 'OptimizedCineon'; + break; + + case ACESFilmicToneMapping: + toneMappingName = 'ACESFilmic'; + break; + + case AgXToneMapping: + toneMappingName = 'AgX'; + break; + + case NeutralToneMapping: + toneMappingName = 'Neutral'; + break; + + case CustomToneMapping: + toneMappingName = 'Custom'; + break; + + default: + console.warn( 'THREE.WebGLProgram: Unsupported toneMapping:', toneMapping ); + toneMappingName = 'Linear'; + + } + + return 'vec3 ' + functionName + '( vec3 color ) { return ' + toneMappingName + 'ToneMapping( color ); }'; + +} + +function generateVertexExtensions( parameters ) { + + const chunks = [ + parameters.extensionClipCullDistance ? '#extension GL_ANGLE_clip_cull_distance : require' : '', + parameters.extensionMultiDraw ? '#extension GL_ANGLE_multi_draw : require' : '', + ]; + + return chunks.filter( filterEmptyLine ).join( '\n' ); + +} + +function generateDefines( defines ) { + + const chunks = []; + + for ( const name in defines ) { + + const value = defines[ name ]; + + if ( value === false ) continue; + + chunks.push( '#define ' + name + ' ' + value ); + + } + + return chunks.join( '\n' ); + +} + +function fetchAttributeLocations( gl, program ) { + + const attributes = {}; + + const n = gl.getProgramParameter( program, gl.ACTIVE_ATTRIBUTES ); + + for ( let i = 0; i < n; i ++ ) { + + const info = gl.getActiveAttrib( program, i ); + const name = info.name; + + let locationSize = 1; + if ( info.type === gl.FLOAT_MAT2 ) locationSize = 2; + if ( info.type === gl.FLOAT_MAT3 ) locationSize = 3; + if ( info.type === gl.FLOAT_MAT4 ) locationSize = 4; + + // console.log( 'THREE.WebGLProgram: ACTIVE VERTEX ATTRIBUTE:', name, i ); + + attributes[ name ] = { + type: info.type, + location: gl.getAttribLocation( program, name ), + locationSize: locationSize + }; + + } + + return attributes; + +} + +function filterEmptyLine( string ) { + + return string !== ''; + +} + +function replaceLightNums( string, parameters ) { + + const numSpotLightCoords = parameters.numSpotLightShadows + parameters.numSpotLightMaps - parameters.numSpotLightShadowsWithMaps; + + return string + .replace( /NUM_DIR_LIGHTS/g, parameters.numDirLights ) + .replace( /NUM_SPOT_LIGHTS/g, parameters.numSpotLights ) + .replace( /NUM_SPOT_LIGHT_MAPS/g, parameters.numSpotLightMaps ) + .replace( /NUM_SPOT_LIGHT_COORDS/g, numSpotLightCoords ) + .replace( /NUM_RECT_AREA_LIGHTS/g, parameters.numRectAreaLights ) + .replace( /NUM_POINT_LIGHTS/g, parameters.numPointLights ) + .replace( /NUM_HEMI_LIGHTS/g, parameters.numHemiLights ) + .replace( /NUM_DIR_LIGHT_SHADOWS/g, parameters.numDirLightShadows ) + .replace( /NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS/g, parameters.numSpotLightShadowsWithMaps ) + .replace( /NUM_SPOT_LIGHT_SHADOWS/g, parameters.numSpotLightShadows ) + .replace( /NUM_POINT_LIGHT_SHADOWS/g, parameters.numPointLightShadows ); + +} + +function replaceClippingPlaneNums( string, parameters ) { + + return string + .replace( /NUM_CLIPPING_PLANES/g, parameters.numClippingPlanes ) + .replace( /UNION_CLIPPING_PLANES/g, ( parameters.numClippingPlanes - parameters.numClipIntersection ) ); + +} + +// Resolve Includes + +const includePattern = /^[ \t]*#include +<([\w\d./]+)>/gm; + +function resolveIncludes( string ) { + + return string.replace( includePattern, includeReplacer ); + +} + +const shaderChunkMap = new Map(); + +function includeReplacer( match, include ) { + + let string = ShaderChunk[ include ]; + + if ( string === undefined ) { + + const newInclude = shaderChunkMap.get( include ); + + if ( newInclude !== undefined ) { + + string = ShaderChunk[ newInclude ]; + console.warn( 'THREE.WebGLRenderer: Shader chunk "%s" has been deprecated. Use "%s" instead.', include, newInclude ); + + } else { + + throw new Error( 'Can not resolve #include <' + include + '>' ); + + } + + } + + return resolveIncludes( string ); + +} + +// Unroll Loops + +const unrollLoopPattern = /#pragma unroll_loop_start\s+for\s*\(\s*int\s+i\s*=\s*(\d+)\s*;\s*i\s*<\s*(\d+)\s*;\s*i\s*\+\+\s*\)\s*{([\s\S]+?)}\s+#pragma unroll_loop_end/g; + +function unrollLoops( string ) { + + return string.replace( unrollLoopPattern, loopReplacer ); + +} + +function loopReplacer( match, start, end, snippet ) { + + let string = ''; + + for ( let i = parseInt( start ); i < parseInt( end ); i ++ ) { + + string += snippet + .replace( /\[\s*i\s*\]/g, '[ ' + i + ' ]' ) + .replace( /UNROLLED_LOOP_INDEX/g, i ); + + } + + return string; + +} + +// + +function generatePrecision( parameters ) { + + let precisionstring = `precision ${parameters.precision} float; + precision ${parameters.precision} int; + precision ${parameters.precision} sampler2D; + precision ${parameters.precision} samplerCube; + precision ${parameters.precision} sampler3D; + precision ${parameters.precision} sampler2DArray; + precision ${parameters.precision} sampler2DShadow; + precision ${parameters.precision} samplerCubeShadow; + precision ${parameters.precision} sampler2DArrayShadow; + precision ${parameters.precision} isampler2D; + precision ${parameters.precision} isampler3D; + precision ${parameters.precision} isamplerCube; + precision ${parameters.precision} isampler2DArray; + precision ${parameters.precision} usampler2D; + precision ${parameters.precision} usampler3D; + precision ${parameters.precision} usamplerCube; + precision ${parameters.precision} usampler2DArray; + `; + + if ( parameters.precision === 'highp' ) { + + precisionstring += '\n#define HIGH_PRECISION'; + + } else if ( parameters.precision === 'mediump' ) { + + precisionstring += '\n#define MEDIUM_PRECISION'; + + } else if ( parameters.precision === 'lowp' ) { + + precisionstring += '\n#define LOW_PRECISION'; + + } + + return precisionstring; + +} + +function generateShadowMapTypeDefine( parameters ) { + + let shadowMapTypeDefine = 'SHADOWMAP_TYPE_BASIC'; + + if ( parameters.shadowMapType === PCFShadowMap ) { + + shadowMapTypeDefine = 'SHADOWMAP_TYPE_PCF'; + + } else if ( parameters.shadowMapType === PCFSoftShadowMap ) { + + shadowMapTypeDefine = 'SHADOWMAP_TYPE_PCF_SOFT'; + + } else if ( parameters.shadowMapType === VSMShadowMap ) { + + shadowMapTypeDefine = 'SHADOWMAP_TYPE_VSM'; + + } + + return shadowMapTypeDefine; + +} + +function generateEnvMapTypeDefine( parameters ) { + + let envMapTypeDefine = 'ENVMAP_TYPE_CUBE'; + + if ( parameters.envMap ) { + + switch ( parameters.envMapMode ) { + + case CubeReflectionMapping: + case CubeRefractionMapping: + envMapTypeDefine = 'ENVMAP_TYPE_CUBE'; + break; + + case CubeUVReflectionMapping: + envMapTypeDefine = 'ENVMAP_TYPE_CUBE_UV'; + break; + + } + + } + + return envMapTypeDefine; + +} + +function generateEnvMapModeDefine( parameters ) { + + let envMapModeDefine = 'ENVMAP_MODE_REFLECTION'; + + if ( parameters.envMap ) { + + switch ( parameters.envMapMode ) { + + case CubeRefractionMapping: + + envMapModeDefine = 'ENVMAP_MODE_REFRACTION'; + break; + + } + + } + + return envMapModeDefine; + +} + +function generateEnvMapBlendingDefine( parameters ) { + + let envMapBlendingDefine = 'ENVMAP_BLENDING_NONE'; + + if ( parameters.envMap ) { + + switch ( parameters.combine ) { + + case MultiplyOperation: + envMapBlendingDefine = 'ENVMAP_BLENDING_MULTIPLY'; + break; + + case MixOperation: + envMapBlendingDefine = 'ENVMAP_BLENDING_MIX'; + break; + + case AddOperation: + envMapBlendingDefine = 'ENVMAP_BLENDING_ADD'; + break; + + } + + } + + return envMapBlendingDefine; + +} + +function generateCubeUVSize( parameters ) { + + const imageHeight = parameters.envMapCubeUVHeight; + + if ( imageHeight === null ) return null; + + const maxMip = Math.log2( imageHeight ) - 2; + + const texelHeight = 1.0 / imageHeight; + + const texelWidth = 1.0 / ( 3 * Math.max( Math.pow( 2, maxMip ), 7 * 16 ) ); + + return { texelWidth, texelHeight, maxMip }; + +} + +function WebGLProgram( renderer, cacheKey, parameters, bindingStates ) { + + // TODO Send this event to Three.js DevTools + // console.log( 'WebGLProgram', cacheKey ); + + const gl = renderer.getContext(); + + const defines = parameters.defines; + + let vertexShader = parameters.vertexShader; + let fragmentShader = parameters.fragmentShader; + + const shadowMapTypeDefine = generateShadowMapTypeDefine( parameters ); + const envMapTypeDefine = generateEnvMapTypeDefine( parameters ); + const envMapModeDefine = generateEnvMapModeDefine( parameters ); + const envMapBlendingDefine = generateEnvMapBlendingDefine( parameters ); + const envMapCubeUVSize = generateCubeUVSize( parameters ); + + const customVertexExtensions = generateVertexExtensions( parameters ); + + const customDefines = generateDefines( defines ); + + const program = gl.createProgram(); + + let prefixVertex, prefixFragment; + let versionString = parameters.glslVersion ? '#version ' + parameters.glslVersion + '\n' : ''; + + if ( parameters.isRawShaderMaterial ) { + + prefixVertex = [ + + '#define SHADER_TYPE ' + parameters.shaderType, + '#define SHADER_NAME ' + parameters.shaderName, + + customDefines + + ].filter( filterEmptyLine ).join( '\n' ); + + if ( prefixVertex.length > 0 ) { + + prefixVertex += '\n'; + + } + + prefixFragment = [ + + '#define SHADER_TYPE ' + parameters.shaderType, + '#define SHADER_NAME ' + parameters.shaderName, + + customDefines + + ].filter( filterEmptyLine ).join( '\n' ); + + if ( prefixFragment.length > 0 ) { + + prefixFragment += '\n'; + + } + + } else { + + prefixVertex = [ + + generatePrecision( parameters ), + + '#define SHADER_TYPE ' + parameters.shaderType, + '#define SHADER_NAME ' + parameters.shaderName, + + customDefines, + + parameters.extensionClipCullDistance ? '#define USE_CLIP_DISTANCE' : '', + parameters.batching ? '#define USE_BATCHING' : '', + parameters.batchingColor ? '#define USE_BATCHING_COLOR' : '', + parameters.instancing ? '#define USE_INSTANCING' : '', + parameters.instancingColor ? '#define USE_INSTANCING_COLOR' : '', + parameters.instancingMorph ? '#define USE_INSTANCING_MORPH' : '', + + parameters.useFog && parameters.fog ? '#define USE_FOG' : '', + parameters.useFog && parameters.fogExp2 ? '#define FOG_EXP2' : '', + + parameters.map ? '#define USE_MAP' : '', + parameters.envMap ? '#define USE_ENVMAP' : '', + parameters.envMap ? '#define ' + envMapModeDefine : '', + parameters.lightMap ? '#define USE_LIGHTMAP' : '', + parameters.aoMap ? '#define USE_AOMAP' : '', + parameters.bumpMap ? '#define USE_BUMPMAP' : '', + parameters.normalMap ? '#define USE_NORMALMAP' : '', + parameters.normalMapObjectSpace ? '#define USE_NORMALMAP_OBJECTSPACE' : '', + parameters.normalMapTangentSpace ? '#define USE_NORMALMAP_TANGENTSPACE' : '', + parameters.displacementMap ? '#define USE_DISPLACEMENTMAP' : '', + parameters.emissiveMap ? '#define USE_EMISSIVEMAP' : '', + + parameters.anisotropy ? '#define USE_ANISOTROPY' : '', + parameters.anisotropyMap ? '#define USE_ANISOTROPYMAP' : '', + + parameters.clearcoatMap ? '#define USE_CLEARCOATMAP' : '', + parameters.clearcoatRoughnessMap ? '#define USE_CLEARCOAT_ROUGHNESSMAP' : '', + parameters.clearcoatNormalMap ? '#define USE_CLEARCOAT_NORMALMAP' : '', + + parameters.iridescenceMap ? '#define USE_IRIDESCENCEMAP' : '', + parameters.iridescenceThicknessMap ? '#define USE_IRIDESCENCE_THICKNESSMAP' : '', + + parameters.specularMap ? '#define USE_SPECULARMAP' : '', + parameters.specularColorMap ? '#define USE_SPECULAR_COLORMAP' : '', + parameters.specularIntensityMap ? '#define USE_SPECULAR_INTENSITYMAP' : '', + + parameters.roughnessMap ? '#define USE_ROUGHNESSMAP' : '', + parameters.metalnessMap ? '#define USE_METALNESSMAP' : '', + parameters.alphaMap ? '#define USE_ALPHAMAP' : '', + parameters.alphaHash ? '#define USE_ALPHAHASH' : '', + + parameters.transmission ? '#define USE_TRANSMISSION' : '', + parameters.transmissionMap ? '#define USE_TRANSMISSIONMAP' : '', + parameters.thicknessMap ? '#define USE_THICKNESSMAP' : '', + + parameters.sheenColorMap ? '#define USE_SHEEN_COLORMAP' : '', + parameters.sheenRoughnessMap ? '#define USE_SHEEN_ROUGHNESSMAP' : '', + + // + + parameters.mapUv ? '#define MAP_UV ' + parameters.mapUv : '', + parameters.alphaMapUv ? '#define ALPHAMAP_UV ' + parameters.alphaMapUv : '', + parameters.lightMapUv ? '#define LIGHTMAP_UV ' + parameters.lightMapUv : '', + parameters.aoMapUv ? '#define AOMAP_UV ' + parameters.aoMapUv : '', + parameters.emissiveMapUv ? '#define EMISSIVEMAP_UV ' + parameters.emissiveMapUv : '', + parameters.bumpMapUv ? '#define BUMPMAP_UV ' + parameters.bumpMapUv : '', + parameters.normalMapUv ? '#define NORMALMAP_UV ' + parameters.normalMapUv : '', + parameters.displacementMapUv ? '#define DISPLACEMENTMAP_UV ' + parameters.displacementMapUv : '', + + parameters.metalnessMapUv ? '#define METALNESSMAP_UV ' + parameters.metalnessMapUv : '', + parameters.roughnessMapUv ? '#define ROUGHNESSMAP_UV ' + parameters.roughnessMapUv : '', + + parameters.anisotropyMapUv ? '#define ANISOTROPYMAP_UV ' + parameters.anisotropyMapUv : '', + + parameters.clearcoatMapUv ? '#define CLEARCOATMAP_UV ' + parameters.clearcoatMapUv : '', + parameters.clearcoatNormalMapUv ? '#define CLEARCOAT_NORMALMAP_UV ' + parameters.clearcoatNormalMapUv : '', + parameters.clearcoatRoughnessMapUv ? '#define CLEARCOAT_ROUGHNESSMAP_UV ' + parameters.clearcoatRoughnessMapUv : '', + + parameters.iridescenceMapUv ? '#define IRIDESCENCEMAP_UV ' + parameters.iridescenceMapUv : '', + parameters.iridescenceThicknessMapUv ? '#define IRIDESCENCE_THICKNESSMAP_UV ' + parameters.iridescenceThicknessMapUv : '', + + parameters.sheenColorMapUv ? '#define SHEEN_COLORMAP_UV ' + parameters.sheenColorMapUv : '', + parameters.sheenRoughnessMapUv ? '#define SHEEN_ROUGHNESSMAP_UV ' + parameters.sheenRoughnessMapUv : '', + + parameters.specularMapUv ? '#define SPECULARMAP_UV ' + parameters.specularMapUv : '', + parameters.specularColorMapUv ? '#define SPECULAR_COLORMAP_UV ' + parameters.specularColorMapUv : '', + parameters.specularIntensityMapUv ? '#define SPECULAR_INTENSITYMAP_UV ' + parameters.specularIntensityMapUv : '', + + parameters.transmissionMapUv ? '#define TRANSMISSIONMAP_UV ' + parameters.transmissionMapUv : '', + parameters.thicknessMapUv ? '#define THICKNESSMAP_UV ' + parameters.thicknessMapUv : '', + + // + + parameters.vertexTangents && parameters.flatShading === false ? '#define USE_TANGENT' : '', + parameters.vertexColors ? '#define USE_COLOR' : '', + parameters.vertexAlphas ? '#define USE_COLOR_ALPHA' : '', + parameters.vertexUv1s ? '#define USE_UV1' : '', + parameters.vertexUv2s ? '#define USE_UV2' : '', + parameters.vertexUv3s ? '#define USE_UV3' : '', + + parameters.pointsUvs ? '#define USE_POINTS_UV' : '', + + parameters.flatShading ? '#define FLAT_SHADED' : '', + + parameters.skinning ? '#define USE_SKINNING' : '', + + parameters.morphTargets ? '#define USE_MORPHTARGETS' : '', + parameters.morphNormals && parameters.flatShading === false ? '#define USE_MORPHNORMALS' : '', + ( parameters.morphColors ) ? '#define USE_MORPHCOLORS' : '', + ( parameters.morphTargetsCount > 0 ) ? '#define MORPHTARGETS_TEXTURE_STRIDE ' + parameters.morphTextureStride : '', + ( parameters.morphTargetsCount > 0 ) ? '#define MORPHTARGETS_COUNT ' + parameters.morphTargetsCount : '', + parameters.doubleSided ? '#define DOUBLE_SIDED' : '', + parameters.flipSided ? '#define FLIP_SIDED' : '', + + parameters.shadowMapEnabled ? '#define USE_SHADOWMAP' : '', + parameters.shadowMapEnabled ? '#define ' + shadowMapTypeDefine : '', + + parameters.sizeAttenuation ? '#define USE_SIZEATTENUATION' : '', + + parameters.numLightProbes > 0 ? '#define USE_LIGHT_PROBES' : '', + + parameters.logarithmicDepthBuffer ? '#define USE_LOGDEPTHBUF' : '', + + 'uniform mat4 modelMatrix;', + 'uniform mat4 modelViewMatrix;', + 'uniform mat4 projectionMatrix;', + 'uniform mat4 viewMatrix;', + 'uniform mat3 normalMatrix;', + 'uniform vec3 cameraPosition;', + 'uniform bool isOrthographic;', + + '#ifdef USE_INSTANCING', + + ' attribute mat4 instanceMatrix;', + + '#endif', + + '#ifdef USE_INSTANCING_COLOR', + + ' attribute vec3 instanceColor;', + + '#endif', + + '#ifdef USE_INSTANCING_MORPH', + + ' uniform sampler2D morphTexture;', + + '#endif', + + 'attribute vec3 position;', + 'attribute vec3 normal;', + 'attribute vec2 uv;', + + '#ifdef USE_UV1', + + ' attribute vec2 uv1;', + + '#endif', + + '#ifdef USE_UV2', + + ' attribute vec2 uv2;', + + '#endif', + + '#ifdef USE_UV3', + + ' attribute vec2 uv3;', + + '#endif', + + '#ifdef USE_TANGENT', + + ' attribute vec4 tangent;', + + '#endif', + + '#if defined( USE_COLOR_ALPHA )', + + ' attribute vec4 color;', + + '#elif defined( USE_COLOR )', + + ' attribute vec3 color;', + + '#endif', + + '#ifdef USE_SKINNING', + + ' attribute vec4 skinIndex;', + ' attribute vec4 skinWeight;', + + '#endif', + + '\n' + + ].filter( filterEmptyLine ).join( '\n' ); + + prefixFragment = [ + + generatePrecision( parameters ), + + '#define SHADER_TYPE ' + parameters.shaderType, + '#define SHADER_NAME ' + parameters.shaderName, + + customDefines, + + parameters.useFog && parameters.fog ? '#define USE_FOG' : '', + parameters.useFog && parameters.fogExp2 ? '#define FOG_EXP2' : '', + + parameters.alphaToCoverage ? '#define ALPHA_TO_COVERAGE' : '', + parameters.map ? '#define USE_MAP' : '', + parameters.matcap ? '#define USE_MATCAP' : '', + parameters.envMap ? '#define USE_ENVMAP' : '', + parameters.envMap ? '#define ' + envMapTypeDefine : '', + parameters.envMap ? '#define ' + envMapModeDefine : '', + parameters.envMap ? '#define ' + envMapBlendingDefine : '', + envMapCubeUVSize ? '#define CUBEUV_TEXEL_WIDTH ' + envMapCubeUVSize.texelWidth : '', + envMapCubeUVSize ? '#define CUBEUV_TEXEL_HEIGHT ' + envMapCubeUVSize.texelHeight : '', + envMapCubeUVSize ? '#define CUBEUV_MAX_MIP ' + envMapCubeUVSize.maxMip + '.0' : '', + parameters.lightMap ? '#define USE_LIGHTMAP' : '', + parameters.aoMap ? '#define USE_AOMAP' : '', + parameters.bumpMap ? '#define USE_BUMPMAP' : '', + parameters.normalMap ? '#define USE_NORMALMAP' : '', + parameters.normalMapObjectSpace ? '#define USE_NORMALMAP_OBJECTSPACE' : '', + parameters.normalMapTangentSpace ? '#define USE_NORMALMAP_TANGENTSPACE' : '', + parameters.emissiveMap ? '#define USE_EMISSIVEMAP' : '', + + parameters.anisotropy ? '#define USE_ANISOTROPY' : '', + parameters.anisotropyMap ? '#define USE_ANISOTROPYMAP' : '', + + parameters.clearcoat ? '#define USE_CLEARCOAT' : '', + parameters.clearcoatMap ? '#define USE_CLEARCOATMAP' : '', + parameters.clearcoatRoughnessMap ? '#define USE_CLEARCOAT_ROUGHNESSMAP' : '', + parameters.clearcoatNormalMap ? '#define USE_CLEARCOAT_NORMALMAP' : '', + + parameters.dispersion ? '#define USE_DISPERSION' : '', + + parameters.iridescence ? '#define USE_IRIDESCENCE' : '', + parameters.iridescenceMap ? '#define USE_IRIDESCENCEMAP' : '', + parameters.iridescenceThicknessMap ? '#define USE_IRIDESCENCE_THICKNESSMAP' : '', + + parameters.specularMap ? '#define USE_SPECULARMAP' : '', + parameters.specularColorMap ? '#define USE_SPECULAR_COLORMAP' : '', + parameters.specularIntensityMap ? '#define USE_SPECULAR_INTENSITYMAP' : '', + + parameters.roughnessMap ? '#define USE_ROUGHNESSMAP' : '', + parameters.metalnessMap ? '#define USE_METALNESSMAP' : '', + + parameters.alphaMap ? '#define USE_ALPHAMAP' : '', + parameters.alphaTest ? '#define USE_ALPHATEST' : '', + parameters.alphaHash ? '#define USE_ALPHAHASH' : '', + + parameters.sheen ? '#define USE_SHEEN' : '', + parameters.sheenColorMap ? '#define USE_SHEEN_COLORMAP' : '', + parameters.sheenRoughnessMap ? '#define USE_SHEEN_ROUGHNESSMAP' : '', + + parameters.transmission ? '#define USE_TRANSMISSION' : '', + parameters.transmissionMap ? '#define USE_TRANSMISSIONMAP' : '', + parameters.thicknessMap ? '#define USE_THICKNESSMAP' : '', + + parameters.vertexTangents && parameters.flatShading === false ? '#define USE_TANGENT' : '', + parameters.vertexColors || parameters.instancingColor || parameters.batchingColor ? '#define USE_COLOR' : '', + parameters.vertexAlphas ? '#define USE_COLOR_ALPHA' : '', + parameters.vertexUv1s ? '#define USE_UV1' : '', + parameters.vertexUv2s ? '#define USE_UV2' : '', + parameters.vertexUv3s ? '#define USE_UV3' : '', + + parameters.pointsUvs ? '#define USE_POINTS_UV' : '', + + parameters.gradientMap ? '#define USE_GRADIENTMAP' : '', + + parameters.flatShading ? '#define FLAT_SHADED' : '', + + parameters.doubleSided ? '#define DOUBLE_SIDED' : '', + parameters.flipSided ? '#define FLIP_SIDED' : '', + + parameters.shadowMapEnabled ? '#define USE_SHADOWMAP' : '', + parameters.shadowMapEnabled ? '#define ' + shadowMapTypeDefine : '', + + parameters.premultipliedAlpha ? '#define PREMULTIPLIED_ALPHA' : '', + + parameters.numLightProbes > 0 ? '#define USE_LIGHT_PROBES' : '', + + parameters.decodeVideoTexture ? '#define DECODE_VIDEO_TEXTURE' : '', + + parameters.logarithmicDepthBuffer ? '#define USE_LOGDEPTHBUF' : '', + + 'uniform mat4 viewMatrix;', + 'uniform vec3 cameraPosition;', + 'uniform bool isOrthographic;', + + ( parameters.toneMapping !== NoToneMapping ) ? '#define TONE_MAPPING' : '', + ( parameters.toneMapping !== NoToneMapping ) ? ShaderChunk[ 'tonemapping_pars_fragment' ] : '', // this code is required here because it is used by the toneMapping() function defined below + ( parameters.toneMapping !== NoToneMapping ) ? getToneMappingFunction( 'toneMapping', parameters.toneMapping ) : '', + + parameters.dithering ? '#define DITHERING' : '', + parameters.opaque ? '#define OPAQUE' : '', + + ShaderChunk[ 'colorspace_pars_fragment' ], // this code is required here because it is used by the various encoding/decoding function defined below + getTexelEncodingFunction( 'linearToOutputTexel', parameters.outputColorSpace ), + + parameters.useDepthPacking ? '#define DEPTH_PACKING ' + parameters.depthPacking : '', + + '\n' + + ].filter( filterEmptyLine ).join( '\n' ); + + } + + vertexShader = resolveIncludes( vertexShader ); + vertexShader = replaceLightNums( vertexShader, parameters ); + vertexShader = replaceClippingPlaneNums( vertexShader, parameters ); + + fragmentShader = resolveIncludes( fragmentShader ); + fragmentShader = replaceLightNums( fragmentShader, parameters ); + fragmentShader = replaceClippingPlaneNums( fragmentShader, parameters ); + + vertexShader = unrollLoops( vertexShader ); + fragmentShader = unrollLoops( fragmentShader ); + + if ( parameters.isRawShaderMaterial !== true ) { + + // GLSL 3.0 conversion for built-in materials and ShaderMaterial + + versionString = '#version 300 es\n'; + + prefixVertex = [ + customVertexExtensions, + '#define attribute in', + '#define varying out', + '#define texture2D texture' + ].join( '\n' ) + '\n' + prefixVertex; + + prefixFragment = [ + '#define varying in', + ( parameters.glslVersion === GLSL3 ) ? '' : 'layout(location = 0) out highp vec4 pc_fragColor;', + ( parameters.glslVersion === GLSL3 ) ? '' : '#define gl_FragColor pc_fragColor', + '#define gl_FragDepthEXT gl_FragDepth', + '#define texture2D texture', + '#define textureCube texture', + '#define texture2DProj textureProj', + '#define texture2DLodEXT textureLod', + '#define texture2DProjLodEXT textureProjLod', + '#define textureCubeLodEXT textureLod', + '#define texture2DGradEXT textureGrad', + '#define texture2DProjGradEXT textureProjGrad', + '#define textureCubeGradEXT textureGrad' + ].join( '\n' ) + '\n' + prefixFragment; + + } + + const vertexGlsl = versionString + prefixVertex + vertexShader; + const fragmentGlsl = versionString + prefixFragment + fragmentShader; + + // console.log( '*VERTEX*', vertexGlsl ); + // console.log( '*FRAGMENT*', fragmentGlsl ); + + const glVertexShader = WebGLShader( gl, gl.VERTEX_SHADER, vertexGlsl ); + const glFragmentShader = WebGLShader( gl, gl.FRAGMENT_SHADER, fragmentGlsl ); + + gl.attachShader( program, glVertexShader ); + gl.attachShader( program, glFragmentShader ); + + // Force a particular attribute to index 0. + + if ( parameters.index0AttributeName !== undefined ) { + + gl.bindAttribLocation( program, 0, parameters.index0AttributeName ); + + } else if ( parameters.morphTargets === true ) { + + // programs with morphTargets displace position out of attribute 0 + gl.bindAttribLocation( program, 0, 'position' ); + + } + + gl.linkProgram( program ); + + function onFirstUse( self ) { + + // check for link errors + if ( renderer.debug.checkShaderErrors ) { + + const programLog = gl.getProgramInfoLog( program ).trim(); + const vertexLog = gl.getShaderInfoLog( glVertexShader ).trim(); + const fragmentLog = gl.getShaderInfoLog( glFragmentShader ).trim(); + + let runnable = true; + let haveDiagnostics = true; + + if ( gl.getProgramParameter( program, gl.LINK_STATUS ) === false ) { + + runnable = false; + + if ( typeof renderer.debug.onShaderError === 'function' ) { + + renderer.debug.onShaderError( gl, program, glVertexShader, glFragmentShader ); + + } else { + + // default error reporting + + const vertexErrors = getShaderErrors( gl, glVertexShader, 'vertex' ); + const fragmentErrors = getShaderErrors( gl, glFragmentShader, 'fragment' ); + + console.error( + 'THREE.WebGLProgram: Shader Error ' + gl.getError() + ' - ' + + 'VALIDATE_STATUS ' + gl.getProgramParameter( program, gl.VALIDATE_STATUS ) + '\n\n' + + 'Material Name: ' + self.name + '\n' + + 'Material Type: ' + self.type + '\n\n' + + 'Program Info Log: ' + programLog + '\n' + + vertexErrors + '\n' + + fragmentErrors + ); + + } + + } else if ( programLog !== '' ) { + + console.warn( 'THREE.WebGLProgram: Program Info Log:', programLog ); + + } else if ( vertexLog === '' || fragmentLog === '' ) { + + haveDiagnostics = false; + + } + + if ( haveDiagnostics ) { + + self.diagnostics = { + + runnable: runnable, + + programLog: programLog, + + vertexShader: { + + log: vertexLog, + prefix: prefixVertex + + }, + + fragmentShader: { + + log: fragmentLog, + prefix: prefixFragment + + } + + }; + + } + + } + + // Clean up + + // Crashes in iOS9 and iOS10. #18402 + // gl.detachShader( program, glVertexShader ); + // gl.detachShader( program, glFragmentShader ); + + gl.deleteShader( glVertexShader ); + gl.deleteShader( glFragmentShader ); + + cachedUniforms = new WebGLUniforms( gl, program ); + cachedAttributes = fetchAttributeLocations( gl, program ); + + } + + // set up caching for uniform locations + + let cachedUniforms; + + this.getUniforms = function () { + + if ( cachedUniforms === undefined ) { + + // Populates cachedUniforms and cachedAttributes + onFirstUse( this ); + + } + + return cachedUniforms; + + }; + + // set up caching for attribute locations + + let cachedAttributes; + + this.getAttributes = function () { + + if ( cachedAttributes === undefined ) { + + // Populates cachedAttributes and cachedUniforms + onFirstUse( this ); + + } + + return cachedAttributes; + + }; + + // indicate when the program is ready to be used. if the KHR_parallel_shader_compile extension isn't supported, + // flag the program as ready immediately. It may cause a stall when it's first used. + + let programReady = ( parameters.rendererExtensionParallelShaderCompile === false ); + + this.isReady = function () { + + if ( programReady === false ) { + + programReady = gl.getProgramParameter( program, COMPLETION_STATUS_KHR ); + + } + + return programReady; + + }; + + // free resource + + this.destroy = function () { + + bindingStates.releaseStatesOfProgram( this ); + + gl.deleteProgram( program ); + this.program = undefined; + + }; + + // + + this.type = parameters.shaderType; + this.name = parameters.shaderName; + this.id = programIdCount ++; + this.cacheKey = cacheKey; + this.usedTimes = 1; + this.program = program; + this.vertexShader = glVertexShader; + this.fragmentShader = glFragmentShader; + + return this; + +} + +let _id$1 = 0; + +class WebGLShaderCache { + + constructor() { + + this.shaderCache = new Map(); + this.materialCache = new Map(); + + } + + update( material ) { + + const vertexShader = material.vertexShader; + const fragmentShader = material.fragmentShader; + + const vertexShaderStage = this._getShaderStage( vertexShader ); + const fragmentShaderStage = this._getShaderStage( fragmentShader ); + + const materialShaders = this._getShaderCacheForMaterial( material ); + + if ( materialShaders.has( vertexShaderStage ) === false ) { + + materialShaders.add( vertexShaderStage ); + vertexShaderStage.usedTimes ++; + + } + + if ( materialShaders.has( fragmentShaderStage ) === false ) { + + materialShaders.add( fragmentShaderStage ); + fragmentShaderStage.usedTimes ++; + + } + + return this; + + } + + remove( material ) { + + const materialShaders = this.materialCache.get( material ); + + for ( const shaderStage of materialShaders ) { + + shaderStage.usedTimes --; + + if ( shaderStage.usedTimes === 0 ) this.shaderCache.delete( shaderStage.code ); + + } + + this.materialCache.delete( material ); + + return this; + + } + + getVertexShaderID( material ) { + + return this._getShaderStage( material.vertexShader ).id; + + } + + getFragmentShaderID( material ) { + + return this._getShaderStage( material.fragmentShader ).id; + + } + + dispose() { + + this.shaderCache.clear(); + this.materialCache.clear(); + + } + + _getShaderCacheForMaterial( material ) { + + const cache = this.materialCache; + let set = cache.get( material ); + + if ( set === undefined ) { + + set = new Set(); + cache.set( material, set ); + + } + + return set; + + } + + _getShaderStage( code ) { + + const cache = this.shaderCache; + let stage = cache.get( code ); + + if ( stage === undefined ) { + + stage = new WebGLShaderStage( code ); + cache.set( code, stage ); + + } + + return stage; + + } + +} + +class WebGLShaderStage { + + constructor( code ) { + + this.id = _id$1 ++; + + this.code = code; + this.usedTimes = 0; + + } + +} + +function WebGLPrograms( renderer, cubemaps, cubeuvmaps, extensions, capabilities, bindingStates, clipping ) { + + const _programLayers = new Layers(); + const _customShaders = new WebGLShaderCache(); + const _activeChannels = new Set(); + const programs = []; + + const logarithmicDepthBuffer = capabilities.logarithmicDepthBuffer; + const SUPPORTS_VERTEX_TEXTURES = capabilities.vertexTextures; + + let precision = capabilities.precision; + + const shaderIDs = { + MeshDepthMaterial: 'depth', + MeshDistanceMaterial: 'distanceRGBA', + MeshNormalMaterial: 'normal', + MeshBasicMaterial: 'basic', + MeshLambertMaterial: 'lambert', + MeshPhongMaterial: 'phong', + MeshToonMaterial: 'toon', + MeshStandardMaterial: 'physical', + MeshPhysicalMaterial: 'physical', + MeshMatcapMaterial: 'matcap', + LineBasicMaterial: 'basic', + LineDashedMaterial: 'dashed', + PointsMaterial: 'points', + ShadowMaterial: 'shadow', + SpriteMaterial: 'sprite' + }; + + function getChannel( value ) { + + _activeChannels.add( value ); + + if ( value === 0 ) return 'uv'; + + return `uv${ value }`; + + } + + function getParameters( material, lights, shadows, scene, object ) { + + const fog = scene.fog; + const geometry = object.geometry; + const environment = material.isMeshStandardMaterial ? scene.environment : null; + + const envMap = ( material.isMeshStandardMaterial ? cubeuvmaps : cubemaps ).get( material.envMap || environment ); + const envMapCubeUVHeight = ( !! envMap ) && ( envMap.mapping === CubeUVReflectionMapping ) ? envMap.image.height : null; + + const shaderID = shaderIDs[ material.type ]; + + // heuristics to create shader parameters according to lights in the scene + // (not to blow over maxLights budget) + + if ( material.precision !== null ) { + + precision = capabilities.getMaxPrecision( material.precision ); + + if ( precision !== material.precision ) { + + console.warn( 'THREE.WebGLProgram.getParameters:', material.precision, 'not supported, using', precision, 'instead.' ); + + } + + } + + // + + const morphAttribute = geometry.morphAttributes.position || geometry.morphAttributes.normal || geometry.morphAttributes.color; + const morphTargetsCount = ( morphAttribute !== undefined ) ? morphAttribute.length : 0; + + let morphTextureStride = 0; + + if ( geometry.morphAttributes.position !== undefined ) morphTextureStride = 1; + if ( geometry.morphAttributes.normal !== undefined ) morphTextureStride = 2; + if ( geometry.morphAttributes.color !== undefined ) morphTextureStride = 3; + + // + + let vertexShader, fragmentShader; + let customVertexShaderID, customFragmentShaderID; + + if ( shaderID ) { + + const shader = ShaderLib[ shaderID ]; + + vertexShader = shader.vertexShader; + fragmentShader = shader.fragmentShader; + + } else { + + vertexShader = material.vertexShader; + fragmentShader = material.fragmentShader; + + _customShaders.update( material ); + + customVertexShaderID = _customShaders.getVertexShaderID( material ); + customFragmentShaderID = _customShaders.getFragmentShaderID( material ); + + } + + const currentRenderTarget = renderer.getRenderTarget(); + + const IS_INSTANCEDMESH = object.isInstancedMesh === true; + const IS_BATCHEDMESH = object.isBatchedMesh === true; + + const HAS_MAP = !! material.map; + const HAS_MATCAP = !! material.matcap; + const HAS_ENVMAP = !! envMap; + const HAS_AOMAP = !! material.aoMap; + const HAS_LIGHTMAP = !! material.lightMap; + const HAS_BUMPMAP = !! material.bumpMap; + const HAS_NORMALMAP = !! material.normalMap; + const HAS_DISPLACEMENTMAP = !! material.displacementMap; + const HAS_EMISSIVEMAP = !! material.emissiveMap; + + const HAS_METALNESSMAP = !! material.metalnessMap; + const HAS_ROUGHNESSMAP = !! material.roughnessMap; + + const HAS_ANISOTROPY = material.anisotropy > 0; + const HAS_CLEARCOAT = material.clearcoat > 0; + const HAS_DISPERSION = material.dispersion > 0; + const HAS_IRIDESCENCE = material.iridescence > 0; + const HAS_SHEEN = material.sheen > 0; + const HAS_TRANSMISSION = material.transmission > 0; + + const HAS_ANISOTROPYMAP = HAS_ANISOTROPY && !! material.anisotropyMap; + + const HAS_CLEARCOATMAP = HAS_CLEARCOAT && !! material.clearcoatMap; + const HAS_CLEARCOAT_NORMALMAP = HAS_CLEARCOAT && !! material.clearcoatNormalMap; + const HAS_CLEARCOAT_ROUGHNESSMAP = HAS_CLEARCOAT && !! material.clearcoatRoughnessMap; + + const HAS_IRIDESCENCEMAP = HAS_IRIDESCENCE && !! material.iridescenceMap; + const HAS_IRIDESCENCE_THICKNESSMAP = HAS_IRIDESCENCE && !! material.iridescenceThicknessMap; + + const HAS_SHEEN_COLORMAP = HAS_SHEEN && !! material.sheenColorMap; + const HAS_SHEEN_ROUGHNESSMAP = HAS_SHEEN && !! material.sheenRoughnessMap; + + const HAS_SPECULARMAP = !! material.specularMap; + const HAS_SPECULAR_COLORMAP = !! material.specularColorMap; + const HAS_SPECULAR_INTENSITYMAP = !! material.specularIntensityMap; + + const HAS_TRANSMISSIONMAP = HAS_TRANSMISSION && !! material.transmissionMap; + const HAS_THICKNESSMAP = HAS_TRANSMISSION && !! material.thicknessMap; + + const HAS_GRADIENTMAP = !! material.gradientMap; + + const HAS_ALPHAMAP = !! material.alphaMap; + + const HAS_ALPHATEST = material.alphaTest > 0; + + const HAS_ALPHAHASH = !! material.alphaHash; + + const HAS_EXTENSIONS = !! material.extensions; + + let toneMapping = NoToneMapping; + + if ( material.toneMapped ) { + + if ( currentRenderTarget === null || currentRenderTarget.isXRRenderTarget === true ) { + + toneMapping = renderer.toneMapping; + + } + + } + + const parameters = { + + shaderID: shaderID, + shaderType: material.type, + shaderName: material.name, + + vertexShader: vertexShader, + fragmentShader: fragmentShader, + defines: material.defines, + + customVertexShaderID: customVertexShaderID, + customFragmentShaderID: customFragmentShaderID, + + isRawShaderMaterial: material.isRawShaderMaterial === true, + glslVersion: material.glslVersion, + + precision: precision, + + batching: IS_BATCHEDMESH, + batchingColor: IS_BATCHEDMESH && object._colorsTexture !== null, + instancing: IS_INSTANCEDMESH, + instancingColor: IS_INSTANCEDMESH && object.instanceColor !== null, + instancingMorph: IS_INSTANCEDMESH && object.morphTexture !== null, + + supportsVertexTextures: SUPPORTS_VERTEX_TEXTURES, + outputColorSpace: ( currentRenderTarget === null ) ? renderer.outputColorSpace : ( currentRenderTarget.isXRRenderTarget === true ? currentRenderTarget.texture.colorSpace : LinearSRGBColorSpace ), + alphaToCoverage: !! material.alphaToCoverage, + + map: HAS_MAP, + matcap: HAS_MATCAP, + envMap: HAS_ENVMAP, + envMapMode: HAS_ENVMAP && envMap.mapping, + envMapCubeUVHeight: envMapCubeUVHeight, + aoMap: HAS_AOMAP, + lightMap: HAS_LIGHTMAP, + bumpMap: HAS_BUMPMAP, + normalMap: HAS_NORMALMAP, + displacementMap: SUPPORTS_VERTEX_TEXTURES && HAS_DISPLACEMENTMAP, + emissiveMap: HAS_EMISSIVEMAP, + + normalMapObjectSpace: HAS_NORMALMAP && material.normalMapType === ObjectSpaceNormalMap, + normalMapTangentSpace: HAS_NORMALMAP && material.normalMapType === TangentSpaceNormalMap, + + metalnessMap: HAS_METALNESSMAP, + roughnessMap: HAS_ROUGHNESSMAP, + + anisotropy: HAS_ANISOTROPY, + anisotropyMap: HAS_ANISOTROPYMAP, + + clearcoat: HAS_CLEARCOAT, + clearcoatMap: HAS_CLEARCOATMAP, + clearcoatNormalMap: HAS_CLEARCOAT_NORMALMAP, + clearcoatRoughnessMap: HAS_CLEARCOAT_ROUGHNESSMAP, + + dispersion: HAS_DISPERSION, + + iridescence: HAS_IRIDESCENCE, + iridescenceMap: HAS_IRIDESCENCEMAP, + iridescenceThicknessMap: HAS_IRIDESCENCE_THICKNESSMAP, + + sheen: HAS_SHEEN, + sheenColorMap: HAS_SHEEN_COLORMAP, + sheenRoughnessMap: HAS_SHEEN_ROUGHNESSMAP, + + specularMap: HAS_SPECULARMAP, + specularColorMap: HAS_SPECULAR_COLORMAP, + specularIntensityMap: HAS_SPECULAR_INTENSITYMAP, + + transmission: HAS_TRANSMISSION, + transmissionMap: HAS_TRANSMISSIONMAP, + thicknessMap: HAS_THICKNESSMAP, + + gradientMap: HAS_GRADIENTMAP, + + opaque: material.transparent === false && material.blending === NormalBlending && material.alphaToCoverage === false, + + alphaMap: HAS_ALPHAMAP, + alphaTest: HAS_ALPHATEST, + alphaHash: HAS_ALPHAHASH, + + combine: material.combine, + + // + + mapUv: HAS_MAP && getChannel( material.map.channel ), + aoMapUv: HAS_AOMAP && getChannel( material.aoMap.channel ), + lightMapUv: HAS_LIGHTMAP && getChannel( material.lightMap.channel ), + bumpMapUv: HAS_BUMPMAP && getChannel( material.bumpMap.channel ), + normalMapUv: HAS_NORMALMAP && getChannel( material.normalMap.channel ), + displacementMapUv: HAS_DISPLACEMENTMAP && getChannel( material.displacementMap.channel ), + emissiveMapUv: HAS_EMISSIVEMAP && getChannel( material.emissiveMap.channel ), + + metalnessMapUv: HAS_METALNESSMAP && getChannel( material.metalnessMap.channel ), + roughnessMapUv: HAS_ROUGHNESSMAP && getChannel( material.roughnessMap.channel ), + + anisotropyMapUv: HAS_ANISOTROPYMAP && getChannel( material.anisotropyMap.channel ), + + clearcoatMapUv: HAS_CLEARCOATMAP && getChannel( material.clearcoatMap.channel ), + clearcoatNormalMapUv: HAS_CLEARCOAT_NORMALMAP && getChannel( material.clearcoatNormalMap.channel ), + clearcoatRoughnessMapUv: HAS_CLEARCOAT_ROUGHNESSMAP && getChannel( material.clearcoatRoughnessMap.channel ), + + iridescenceMapUv: HAS_IRIDESCENCEMAP && getChannel( material.iridescenceMap.channel ), + iridescenceThicknessMapUv: HAS_IRIDESCENCE_THICKNESSMAP && getChannel( material.iridescenceThicknessMap.channel ), + + sheenColorMapUv: HAS_SHEEN_COLORMAP && getChannel( material.sheenColorMap.channel ), + sheenRoughnessMapUv: HAS_SHEEN_ROUGHNESSMAP && getChannel( material.sheenRoughnessMap.channel ), + + specularMapUv: HAS_SPECULARMAP && getChannel( material.specularMap.channel ), + specularColorMapUv: HAS_SPECULAR_COLORMAP && getChannel( material.specularColorMap.channel ), + specularIntensityMapUv: HAS_SPECULAR_INTENSITYMAP && getChannel( material.specularIntensityMap.channel ), + + transmissionMapUv: HAS_TRANSMISSIONMAP && getChannel( material.transmissionMap.channel ), + thicknessMapUv: HAS_THICKNESSMAP && getChannel( material.thicknessMap.channel ), + + alphaMapUv: HAS_ALPHAMAP && getChannel( material.alphaMap.channel ), + + // + + vertexTangents: !! geometry.attributes.tangent && ( HAS_NORMALMAP || HAS_ANISOTROPY ), + vertexColors: material.vertexColors, + vertexAlphas: material.vertexColors === true && !! geometry.attributes.color && geometry.attributes.color.itemSize === 4, + + pointsUvs: object.isPoints === true && !! geometry.attributes.uv && ( HAS_MAP || HAS_ALPHAMAP ), + + fog: !! fog, + useFog: material.fog === true, + fogExp2: ( !! fog && fog.isFogExp2 ), + + flatShading: material.flatShading === true, + + sizeAttenuation: material.sizeAttenuation === true, + logarithmicDepthBuffer: logarithmicDepthBuffer, + + skinning: object.isSkinnedMesh === true, + + morphTargets: geometry.morphAttributes.position !== undefined, + morphNormals: geometry.morphAttributes.normal !== undefined, + morphColors: geometry.morphAttributes.color !== undefined, + morphTargetsCount: morphTargetsCount, + morphTextureStride: morphTextureStride, + + numDirLights: lights.directional.length, + numPointLights: lights.point.length, + numSpotLights: lights.spot.length, + numSpotLightMaps: lights.spotLightMap.length, + numRectAreaLights: lights.rectArea.length, + numHemiLights: lights.hemi.length, + + numDirLightShadows: lights.directionalShadowMap.length, + numPointLightShadows: lights.pointShadowMap.length, + numSpotLightShadows: lights.spotShadowMap.length, + numSpotLightShadowsWithMaps: lights.numSpotLightShadowsWithMaps, + + numLightProbes: lights.numLightProbes, + + numClippingPlanes: clipping.numPlanes, + numClipIntersection: clipping.numIntersection, + + dithering: material.dithering, + + shadowMapEnabled: renderer.shadowMap.enabled && shadows.length > 0, + shadowMapType: renderer.shadowMap.type, + + toneMapping: toneMapping, + + decodeVideoTexture: HAS_MAP && ( material.map.isVideoTexture === true ) && ( ColorManagement.getTransfer( material.map.colorSpace ) === SRGBTransfer ), + + premultipliedAlpha: material.premultipliedAlpha, + + doubleSided: material.side === DoubleSide, + flipSided: material.side === BackSide, + + useDepthPacking: material.depthPacking >= 0, + depthPacking: material.depthPacking || 0, + + index0AttributeName: material.index0AttributeName, + + extensionClipCullDistance: HAS_EXTENSIONS && material.extensions.clipCullDistance === true && extensions.has( 'WEBGL_clip_cull_distance' ), + extensionMultiDraw: HAS_EXTENSIONS && material.extensions.multiDraw === true && extensions.has( 'WEBGL_multi_draw' ), + + rendererExtensionParallelShaderCompile: extensions.has( 'KHR_parallel_shader_compile' ), + + customProgramCacheKey: material.customProgramCacheKey() + + }; + + // the usage of getChannel() determines the active texture channels for this shader + + parameters.vertexUv1s = _activeChannels.has( 1 ); + parameters.vertexUv2s = _activeChannels.has( 2 ); + parameters.vertexUv3s = _activeChannels.has( 3 ); + + _activeChannels.clear(); + + return parameters; + + } + + function getProgramCacheKey( parameters ) { + + const array = []; + + if ( parameters.shaderID ) { + + array.push( parameters.shaderID ); + + } else { + + array.push( parameters.customVertexShaderID ); + array.push( parameters.customFragmentShaderID ); + + } + + if ( parameters.defines !== undefined ) { + + for ( const name in parameters.defines ) { + + array.push( name ); + array.push( parameters.defines[ name ] ); + + } + + } + + if ( parameters.isRawShaderMaterial === false ) { + + getProgramCacheKeyParameters( array, parameters ); + getProgramCacheKeyBooleans( array, parameters ); + array.push( renderer.outputColorSpace ); + + } + + array.push( parameters.customProgramCacheKey ); + + return array.join(); + + } + + function getProgramCacheKeyParameters( array, parameters ) { + + array.push( parameters.precision ); + array.push( parameters.outputColorSpace ); + array.push( parameters.envMapMode ); + array.push( parameters.envMapCubeUVHeight ); + array.push( parameters.mapUv ); + array.push( parameters.alphaMapUv ); + array.push( parameters.lightMapUv ); + array.push( parameters.aoMapUv ); + array.push( parameters.bumpMapUv ); + array.push( parameters.normalMapUv ); + array.push( parameters.displacementMapUv ); + array.push( parameters.emissiveMapUv ); + array.push( parameters.metalnessMapUv ); + array.push( parameters.roughnessMapUv ); + array.push( parameters.anisotropyMapUv ); + array.push( parameters.clearcoatMapUv ); + array.push( parameters.clearcoatNormalMapUv ); + array.push( parameters.clearcoatRoughnessMapUv ); + array.push( parameters.iridescenceMapUv ); + array.push( parameters.iridescenceThicknessMapUv ); + array.push( parameters.sheenColorMapUv ); + array.push( parameters.sheenRoughnessMapUv ); + array.push( parameters.specularMapUv ); + array.push( parameters.specularColorMapUv ); + array.push( parameters.specularIntensityMapUv ); + array.push( parameters.transmissionMapUv ); + array.push( parameters.thicknessMapUv ); + array.push( parameters.combine ); + array.push( parameters.fogExp2 ); + array.push( parameters.sizeAttenuation ); + array.push( parameters.morphTargetsCount ); + array.push( parameters.morphAttributeCount ); + array.push( parameters.numDirLights ); + array.push( parameters.numPointLights ); + array.push( parameters.numSpotLights ); + array.push( parameters.numSpotLightMaps ); + array.push( parameters.numHemiLights ); + array.push( parameters.numRectAreaLights ); + array.push( parameters.numDirLightShadows ); + array.push( parameters.numPointLightShadows ); + array.push( parameters.numSpotLightShadows ); + array.push( parameters.numSpotLightShadowsWithMaps ); + array.push( parameters.numLightProbes ); + array.push( parameters.shadowMapType ); + array.push( parameters.toneMapping ); + array.push( parameters.numClippingPlanes ); + array.push( parameters.numClipIntersection ); + array.push( parameters.depthPacking ); + + } + + function getProgramCacheKeyBooleans( array, parameters ) { + + _programLayers.disableAll(); + + if ( parameters.supportsVertexTextures ) + _programLayers.enable( 0 ); + if ( parameters.instancing ) + _programLayers.enable( 1 ); + if ( parameters.instancingColor ) + _programLayers.enable( 2 ); + if ( parameters.instancingMorph ) + _programLayers.enable( 3 ); + if ( parameters.matcap ) + _programLayers.enable( 4 ); + if ( parameters.envMap ) + _programLayers.enable( 5 ); + if ( parameters.normalMapObjectSpace ) + _programLayers.enable( 6 ); + if ( parameters.normalMapTangentSpace ) + _programLayers.enable( 7 ); + if ( parameters.clearcoat ) + _programLayers.enable( 8 ); + if ( parameters.iridescence ) + _programLayers.enable( 9 ); + if ( parameters.alphaTest ) + _programLayers.enable( 10 ); + if ( parameters.vertexColors ) + _programLayers.enable( 11 ); + if ( parameters.vertexAlphas ) + _programLayers.enable( 12 ); + if ( parameters.vertexUv1s ) + _programLayers.enable( 13 ); + if ( parameters.vertexUv2s ) + _programLayers.enable( 14 ); + if ( parameters.vertexUv3s ) + _programLayers.enable( 15 ); + if ( parameters.vertexTangents ) + _programLayers.enable( 16 ); + if ( parameters.anisotropy ) + _programLayers.enable( 17 ); + if ( parameters.alphaHash ) + _programLayers.enable( 18 ); + if ( parameters.batching ) + _programLayers.enable( 19 ); + if ( parameters.dispersion ) + _programLayers.enable( 20 ); + if ( parameters.batchingColor ) + _programLayers.enable( 21 ); + + array.push( _programLayers.mask ); + _programLayers.disableAll(); + + if ( parameters.fog ) + _programLayers.enable( 0 ); + if ( parameters.useFog ) + _programLayers.enable( 1 ); + if ( parameters.flatShading ) + _programLayers.enable( 2 ); + if ( parameters.logarithmicDepthBuffer ) + _programLayers.enable( 3 ); + if ( parameters.skinning ) + _programLayers.enable( 4 ); + if ( parameters.morphTargets ) + _programLayers.enable( 5 ); + if ( parameters.morphNormals ) + _programLayers.enable( 6 ); + if ( parameters.morphColors ) + _programLayers.enable( 7 ); + if ( parameters.premultipliedAlpha ) + _programLayers.enable( 8 ); + if ( parameters.shadowMapEnabled ) + _programLayers.enable( 9 ); + if ( parameters.doubleSided ) + _programLayers.enable( 10 ); + if ( parameters.flipSided ) + _programLayers.enable( 11 ); + if ( parameters.useDepthPacking ) + _programLayers.enable( 12 ); + if ( parameters.dithering ) + _programLayers.enable( 13 ); + if ( parameters.transmission ) + _programLayers.enable( 14 ); + if ( parameters.sheen ) + _programLayers.enable( 15 ); + if ( parameters.opaque ) + _programLayers.enable( 16 ); + if ( parameters.pointsUvs ) + _programLayers.enable( 17 ); + if ( parameters.decodeVideoTexture ) + _programLayers.enable( 18 ); + if ( parameters.alphaToCoverage ) + _programLayers.enable( 19 ); + + array.push( _programLayers.mask ); + + } + + function getUniforms( material ) { + + const shaderID = shaderIDs[ material.type ]; + let uniforms; + + if ( shaderID ) { + + const shader = ShaderLib[ shaderID ]; + uniforms = UniformsUtils.clone( shader.uniforms ); + + } else { + + uniforms = material.uniforms; + + } + + return uniforms; + + } + + function acquireProgram( parameters, cacheKey ) { + + let program; + + // Check if code has been already compiled + for ( let p = 0, pl = programs.length; p < pl; p ++ ) { + + const preexistingProgram = programs[ p ]; + + if ( preexistingProgram.cacheKey === cacheKey ) { + + program = preexistingProgram; + ++ program.usedTimes; + + break; + + } + + } + + if ( program === undefined ) { + + program = new WebGLProgram( renderer, cacheKey, parameters, bindingStates ); + programs.push( program ); + + } + + return program; + + } + + function releaseProgram( program ) { + + if ( -- program.usedTimes === 0 ) { + + // Remove from unordered set + const i = programs.indexOf( program ); + programs[ i ] = programs[ programs.length - 1 ]; + programs.pop(); + + // Free WebGL resources + program.destroy(); + + } + + } + + function releaseShaderCache( material ) { + + _customShaders.remove( material ); + + } + + function dispose() { + + _customShaders.dispose(); + + } + + return { + getParameters: getParameters, + getProgramCacheKey: getProgramCacheKey, + getUniforms: getUniforms, + acquireProgram: acquireProgram, + releaseProgram: releaseProgram, + releaseShaderCache: releaseShaderCache, + // Exposed for resource monitoring & error feedback via renderer.info: + programs: programs, + dispose: dispose + }; + +} + +function WebGLProperties() { + + let properties = new WeakMap(); + + function get( object ) { + + let map = properties.get( object ); + + if ( map === undefined ) { + + map = {}; + properties.set( object, map ); + + } + + return map; + + } + + function remove( object ) { + + properties.delete( object ); + + } + + function update( object, key, value ) { + + properties.get( object )[ key ] = value; + + } + + function dispose() { + + properties = new WeakMap(); + + } + + return { + get: get, + remove: remove, + update: update, + dispose: dispose + }; + +} + +function painterSortStable( a, b ) { + + if ( a.groupOrder !== b.groupOrder ) { + + return a.groupOrder - b.groupOrder; + + } else if ( a.renderOrder !== b.renderOrder ) { + + return a.renderOrder - b.renderOrder; + + } else if ( a.material.id !== b.material.id ) { + + return a.material.id - b.material.id; + + } else if ( a.z !== b.z ) { + + return a.z - b.z; + + } else { + + return a.id - b.id; + + } + +} + +function reversePainterSortStable( a, b ) { + + if ( a.groupOrder !== b.groupOrder ) { + + return a.groupOrder - b.groupOrder; + + } else if ( a.renderOrder !== b.renderOrder ) { + + return a.renderOrder - b.renderOrder; + + } else if ( a.z !== b.z ) { + + return b.z - a.z; + + } else { + + return a.id - b.id; + + } + +} + + +function WebGLRenderList() { + + const renderItems = []; + let renderItemsIndex = 0; + + const opaque = []; + const transmissive = []; + const transparent = []; + + function init() { + + renderItemsIndex = 0; + + opaque.length = 0; + transmissive.length = 0; + transparent.length = 0; + + } + + function getNextRenderItem( object, geometry, material, groupOrder, z, group ) { + + let renderItem = renderItems[ renderItemsIndex ]; + + if ( renderItem === undefined ) { + + renderItem = { + id: object.id, + object: object, + geometry: geometry, + material: material, + groupOrder: groupOrder, + renderOrder: object.renderOrder, + z: z, + group: group + }; + + renderItems[ renderItemsIndex ] = renderItem; + + } else { + + renderItem.id = object.id; + renderItem.object = object; + renderItem.geometry = geometry; + renderItem.material = material; + renderItem.groupOrder = groupOrder; + renderItem.renderOrder = object.renderOrder; + renderItem.z = z; + renderItem.group = group; + + } + + renderItemsIndex ++; + + return renderItem; + + } + + function push( object, geometry, material, groupOrder, z, group ) { + + const renderItem = getNextRenderItem( object, geometry, material, groupOrder, z, group ); + + if ( material.transmission > 0.0 ) { + + transmissive.push( renderItem ); + + } else if ( material.transparent === true ) { + + transparent.push( renderItem ); + + } else { + + opaque.push( renderItem ); + + } + + } + + function unshift( object, geometry, material, groupOrder, z, group ) { + + const renderItem = getNextRenderItem( object, geometry, material, groupOrder, z, group ); + + if ( material.transmission > 0.0 ) { + + transmissive.unshift( renderItem ); + + } else if ( material.transparent === true ) { + + transparent.unshift( renderItem ); + + } else { + + opaque.unshift( renderItem ); + + } + + } + + function sort( customOpaqueSort, customTransparentSort ) { + + if ( opaque.length > 1 ) opaque.sort( customOpaqueSort || painterSortStable ); + if ( transmissive.length > 1 ) transmissive.sort( customTransparentSort || reversePainterSortStable ); + if ( transparent.length > 1 ) transparent.sort( customTransparentSort || reversePainterSortStable ); + + } + + function finish() { + + // Clear references from inactive renderItems in the list + + for ( let i = renderItemsIndex, il = renderItems.length; i < il; i ++ ) { + + const renderItem = renderItems[ i ]; + + if ( renderItem.id === null ) break; + + renderItem.id = null; + renderItem.object = null; + renderItem.geometry = null; + renderItem.material = null; + renderItem.group = null; + + } + + } + + return { + + opaque: opaque, + transmissive: transmissive, + transparent: transparent, + + init: init, + push: push, + unshift: unshift, + finish: finish, + + sort: sort + }; + +} + +function WebGLRenderLists() { + + let lists = new WeakMap(); + + function get( scene, renderCallDepth ) { + + const listArray = lists.get( scene ); + let list; + + if ( listArray === undefined ) { + + list = new WebGLRenderList(); + lists.set( scene, [ list ] ); + + } else { + + if ( renderCallDepth >= listArray.length ) { + + list = new WebGLRenderList(); + listArray.push( list ); + + } else { + + list = listArray[ renderCallDepth ]; + + } + + } + + return list; + + } + + function dispose() { + + lists = new WeakMap(); + + } + + return { + get: get, + dispose: dispose + }; + +} + +function UniformsCache() { + + const lights = {}; + + return { + + get: function ( light ) { + + if ( lights[ light.id ] !== undefined ) { + + return lights[ light.id ]; + + } + + let uniforms; + + switch ( light.type ) { + + case 'DirectionalLight': + uniforms = { + direction: new Vector3(), + color: new Color() + }; + break; + + case 'SpotLight': + uniforms = { + position: new Vector3(), + direction: new Vector3(), + color: new Color(), + distance: 0, + coneCos: 0, + penumbraCos: 0, + decay: 0 + }; + break; + + case 'PointLight': + uniforms = { + position: new Vector3(), + color: new Color(), + distance: 0, + decay: 0 + }; + break; + + case 'HemisphereLight': + uniforms = { + direction: new Vector3(), + skyColor: new Color(), + groundColor: new Color() + }; + break; + + case 'RectAreaLight': + uniforms = { + color: new Color(), + position: new Vector3(), + halfWidth: new Vector3(), + halfHeight: new Vector3() + }; + break; + + } + + lights[ light.id ] = uniforms; + + return uniforms; + + } + + }; + +} + +function ShadowUniformsCache() { + + const lights = {}; + + return { + + get: function ( light ) { + + if ( lights[ light.id ] !== undefined ) { + + return lights[ light.id ]; + + } + + let uniforms; + + switch ( light.type ) { + + case 'DirectionalLight': + uniforms = { + shadowBias: 0, + shadowNormalBias: 0, + shadowRadius: 1, + shadowMapSize: new Vector2() + }; + break; + + case 'SpotLight': + uniforms = { + shadowBias: 0, + shadowNormalBias: 0, + shadowRadius: 1, + shadowMapSize: new Vector2() + }; + break; + + case 'PointLight': + uniforms = { + shadowBias: 0, + shadowNormalBias: 0, + shadowRadius: 1, + shadowMapSize: new Vector2(), + shadowCameraNear: 1, + shadowCameraFar: 1000 + }; + break; + + // TODO (abelnation): set RectAreaLight shadow uniforms + + } + + lights[ light.id ] = uniforms; + + return uniforms; + + } + + }; + +} + + + +let nextVersion = 0; + +function shadowCastingAndTexturingLightsFirst( lightA, lightB ) { + + return ( lightB.castShadow ? 2 : 0 ) - ( lightA.castShadow ? 2 : 0 ) + ( lightB.map ? 1 : 0 ) - ( lightA.map ? 1 : 0 ); + +} + +function WebGLLights( extensions ) { + + const cache = new UniformsCache(); + + const shadowCache = ShadowUniformsCache(); + + const state = { + + version: 0, + + hash: { + directionalLength: - 1, + pointLength: - 1, + spotLength: - 1, + rectAreaLength: - 1, + hemiLength: - 1, + + numDirectionalShadows: - 1, + numPointShadows: - 1, + numSpotShadows: - 1, + numSpotMaps: - 1, + + numLightProbes: - 1 + }, + + ambient: [ 0, 0, 0 ], + probe: [], + directional: [], + directionalShadow: [], + directionalShadowMap: [], + directionalShadowMatrix: [], + spot: [], + spotLightMap: [], + spotShadow: [], + spotShadowMap: [], + spotLightMatrix: [], + rectArea: [], + rectAreaLTC1: null, + rectAreaLTC2: null, + point: [], + pointShadow: [], + pointShadowMap: [], + pointShadowMatrix: [], + hemi: [], + numSpotLightShadowsWithMaps: 0, + numLightProbes: 0 + + }; + + for ( let i = 0; i < 9; i ++ ) state.probe.push( new Vector3() ); + + const vector3 = new Vector3(); + const matrix4 = new Matrix4(); + const matrix42 = new Matrix4(); + + function setup( lights ) { + + let r = 0, g = 0, b = 0; + + for ( let i = 0; i < 9; i ++ ) state.probe[ i ].set( 0, 0, 0 ); + + let directionalLength = 0; + let pointLength = 0; + let spotLength = 0; + let rectAreaLength = 0; + let hemiLength = 0; + + let numDirectionalShadows = 0; + let numPointShadows = 0; + let numSpotShadows = 0; + let numSpotMaps = 0; + let numSpotShadowsWithMaps = 0; + + let numLightProbes = 0; + + // ordering : [shadow casting + map texturing, map texturing, shadow casting, none ] + lights.sort( shadowCastingAndTexturingLightsFirst ); + + for ( let i = 0, l = lights.length; i < l; i ++ ) { + + const light = lights[ i ]; + + const color = light.color; + const intensity = light.intensity; + const distance = light.distance; + + const shadowMap = ( light.shadow && light.shadow.map ) ? light.shadow.map.texture : null; + + if ( light.isAmbientLight ) { + + r += color.r * intensity; + g += color.g * intensity; + b += color.b * intensity; + + } else if ( light.isLightProbe ) { + + for ( let j = 0; j < 9; j ++ ) { + + state.probe[ j ].addScaledVector( light.sh.coefficients[ j ], intensity ); + + } + + numLightProbes ++; + + } else if ( light.isDirectionalLight ) { + + const uniforms = cache.get( light ); + + uniforms.color.copy( light.color ).multiplyScalar( light.intensity ); + + if ( light.castShadow ) { + + const shadow = light.shadow; + + const shadowUniforms = shadowCache.get( light ); + + shadowUniforms.shadowBias = shadow.bias; + shadowUniforms.shadowNormalBias = shadow.normalBias; + shadowUniforms.shadowRadius = shadow.radius; + shadowUniforms.shadowMapSize = shadow.mapSize; + + state.directionalShadow[ directionalLength ] = shadowUniforms; + state.directionalShadowMap[ directionalLength ] = shadowMap; + state.directionalShadowMatrix[ directionalLength ] = light.shadow.matrix; + + numDirectionalShadows ++; + + } + + state.directional[ directionalLength ] = uniforms; + + directionalLength ++; + + } else if ( light.isSpotLight ) { + + const uniforms = cache.get( light ); + + uniforms.position.setFromMatrixPosition( light.matrixWorld ); + + uniforms.color.copy( color ).multiplyScalar( intensity ); + uniforms.distance = distance; + + uniforms.coneCos = Math.cos( light.angle ); + uniforms.penumbraCos = Math.cos( light.angle * ( 1 - light.penumbra ) ); + uniforms.decay = light.decay; + + state.spot[ spotLength ] = uniforms; + + const shadow = light.shadow; + + if ( light.map ) { + + state.spotLightMap[ numSpotMaps ] = light.map; + numSpotMaps ++; + + // make sure the lightMatrix is up to date + // TODO : do it if required only + shadow.updateMatrices( light ); + + if ( light.castShadow ) numSpotShadowsWithMaps ++; + + } + + state.spotLightMatrix[ spotLength ] = shadow.matrix; + + if ( light.castShadow ) { + + const shadowUniforms = shadowCache.get( light ); + + shadowUniforms.shadowBias = shadow.bias; + shadowUniforms.shadowNormalBias = shadow.normalBias; + shadowUniforms.shadowRadius = shadow.radius; + shadowUniforms.shadowMapSize = shadow.mapSize; + + state.spotShadow[ spotLength ] = shadowUniforms; + state.spotShadowMap[ spotLength ] = shadowMap; + + numSpotShadows ++; + + } + + spotLength ++; + + } else if ( light.isRectAreaLight ) { + + const uniforms = cache.get( light ); + + uniforms.color.copy( color ).multiplyScalar( intensity ); + + uniforms.halfWidth.set( light.width * 0.5, 0.0, 0.0 ); + uniforms.halfHeight.set( 0.0, light.height * 0.5, 0.0 ); + + state.rectArea[ rectAreaLength ] = uniforms; + + rectAreaLength ++; + + } else if ( light.isPointLight ) { + + const uniforms = cache.get( light ); + + uniforms.color.copy( light.color ).multiplyScalar( light.intensity ); + uniforms.distance = light.distance; + uniforms.decay = light.decay; + + if ( light.castShadow ) { + + const shadow = light.shadow; + + const shadowUniforms = shadowCache.get( light ); + + shadowUniforms.shadowBias = shadow.bias; + shadowUniforms.shadowNormalBias = shadow.normalBias; + shadowUniforms.shadowRadius = shadow.radius; + shadowUniforms.shadowMapSize = shadow.mapSize; + shadowUniforms.shadowCameraNear = shadow.camera.near; + shadowUniforms.shadowCameraFar = shadow.camera.far; + + state.pointShadow[ pointLength ] = shadowUniforms; + state.pointShadowMap[ pointLength ] = shadowMap; + state.pointShadowMatrix[ pointLength ] = light.shadow.matrix; + + numPointShadows ++; + + } + + state.point[ pointLength ] = uniforms; + + pointLength ++; + + } else if ( light.isHemisphereLight ) { + + const uniforms = cache.get( light ); + + uniforms.skyColor.copy( light.color ).multiplyScalar( intensity ); + uniforms.groundColor.copy( light.groundColor ).multiplyScalar( intensity ); + + state.hemi[ hemiLength ] = uniforms; + + hemiLength ++; + + } + + } + + if ( rectAreaLength > 0 ) { + + if ( extensions.has( 'OES_texture_float_linear' ) === true ) { + + state.rectAreaLTC1 = UniformsLib.LTC_FLOAT_1; + state.rectAreaLTC2 = UniformsLib.LTC_FLOAT_2; + + } else { + + state.rectAreaLTC1 = UniformsLib.LTC_HALF_1; + state.rectAreaLTC2 = UniformsLib.LTC_HALF_2; + + } + + } + + state.ambient[ 0 ] = r; + state.ambient[ 1 ] = g; + state.ambient[ 2 ] = b; + + const hash = state.hash; + + if ( hash.directionalLength !== directionalLength || + hash.pointLength !== pointLength || + hash.spotLength !== spotLength || + hash.rectAreaLength !== rectAreaLength || + hash.hemiLength !== hemiLength || + hash.numDirectionalShadows !== numDirectionalShadows || + hash.numPointShadows !== numPointShadows || + hash.numSpotShadows !== numSpotShadows || + hash.numSpotMaps !== numSpotMaps || + hash.numLightProbes !== numLightProbes ) { + + state.directional.length = directionalLength; + state.spot.length = spotLength; + state.rectArea.length = rectAreaLength; + state.point.length = pointLength; + state.hemi.length = hemiLength; + + state.directionalShadow.length = numDirectionalShadows; + state.directionalShadowMap.length = numDirectionalShadows; + state.pointShadow.length = numPointShadows; + state.pointShadowMap.length = numPointShadows; + state.spotShadow.length = numSpotShadows; + state.spotShadowMap.length = numSpotShadows; + state.directionalShadowMatrix.length = numDirectionalShadows; + state.pointShadowMatrix.length = numPointShadows; + state.spotLightMatrix.length = numSpotShadows + numSpotMaps - numSpotShadowsWithMaps; + state.spotLightMap.length = numSpotMaps; + state.numSpotLightShadowsWithMaps = numSpotShadowsWithMaps; + state.numLightProbes = numLightProbes; + + hash.directionalLength = directionalLength; + hash.pointLength = pointLength; + hash.spotLength = spotLength; + hash.rectAreaLength = rectAreaLength; + hash.hemiLength = hemiLength; + + hash.numDirectionalShadows = numDirectionalShadows; + hash.numPointShadows = numPointShadows; + hash.numSpotShadows = numSpotShadows; + hash.numSpotMaps = numSpotMaps; + + hash.numLightProbes = numLightProbes; + + state.version = nextVersion ++; + + } + + } + + function setupView( lights, camera ) { + + let directionalLength = 0; + let pointLength = 0; + let spotLength = 0; + let rectAreaLength = 0; + let hemiLength = 0; + + const viewMatrix = camera.matrixWorldInverse; + + for ( let i = 0, l = lights.length; i < l; i ++ ) { + + const light = lights[ i ]; + + if ( light.isDirectionalLight ) { + + const uniforms = state.directional[ directionalLength ]; + + uniforms.direction.setFromMatrixPosition( light.matrixWorld ); + vector3.setFromMatrixPosition( light.target.matrixWorld ); + uniforms.direction.sub( vector3 ); + uniforms.direction.transformDirection( viewMatrix ); + + directionalLength ++; + + } else if ( light.isSpotLight ) { + + const uniforms = state.spot[ spotLength ]; + + uniforms.position.setFromMatrixPosition( light.matrixWorld ); + uniforms.position.applyMatrix4( viewMatrix ); + + uniforms.direction.setFromMatrixPosition( light.matrixWorld ); + vector3.setFromMatrixPosition( light.target.matrixWorld ); + uniforms.direction.sub( vector3 ); + uniforms.direction.transformDirection( viewMatrix ); + + spotLength ++; + + } else if ( light.isRectAreaLight ) { + + const uniforms = state.rectArea[ rectAreaLength ]; + + uniforms.position.setFromMatrixPosition( light.matrixWorld ); + uniforms.position.applyMatrix4( viewMatrix ); + + // extract local rotation of light to derive width/height half vectors + matrix42.identity(); + matrix4.copy( light.matrixWorld ); + matrix4.premultiply( viewMatrix ); + matrix42.extractRotation( matrix4 ); + + uniforms.halfWidth.set( light.width * 0.5, 0.0, 0.0 ); + uniforms.halfHeight.set( 0.0, light.height * 0.5, 0.0 ); + + uniforms.halfWidth.applyMatrix4( matrix42 ); + uniforms.halfHeight.applyMatrix4( matrix42 ); + + rectAreaLength ++; + + } else if ( light.isPointLight ) { + + const uniforms = state.point[ pointLength ]; + + uniforms.position.setFromMatrixPosition( light.matrixWorld ); + uniforms.position.applyMatrix4( viewMatrix ); + + pointLength ++; + + } else if ( light.isHemisphereLight ) { + + const uniforms = state.hemi[ hemiLength ]; + + uniforms.direction.setFromMatrixPosition( light.matrixWorld ); + uniforms.direction.transformDirection( viewMatrix ); + + hemiLength ++; + + } + + } + + } + + return { + setup: setup, + setupView: setupView, + state: state + }; + +} + +function WebGLRenderState( extensions ) { + + const lights = new WebGLLights( extensions ); + + const lightsArray = []; + const shadowsArray = []; + + function init( camera ) { + + state.camera = camera; + + lightsArray.length = 0; + shadowsArray.length = 0; + + } + + function pushLight( light ) { + + lightsArray.push( light ); + + } + + function pushShadow( shadowLight ) { + + shadowsArray.push( shadowLight ); + + } + + function setupLights() { + + lights.setup( lightsArray ); + + } + + function setupLightsView( camera ) { + + lights.setupView( lightsArray, camera ); + + } + + const state = { + lightsArray: lightsArray, + shadowsArray: shadowsArray, + + camera: null, + + lights: lights, + + transmissionRenderTarget: {} + }; + + return { + init: init, + state: state, + setupLights: setupLights, + setupLightsView: setupLightsView, + + pushLight: pushLight, + pushShadow: pushShadow + }; + +} + +function WebGLRenderStates( extensions ) { + + let renderStates = new WeakMap(); + + function get( scene, renderCallDepth = 0 ) { + + const renderStateArray = renderStates.get( scene ); + let renderState; + + if ( renderStateArray === undefined ) { + + renderState = new WebGLRenderState( extensions ); + renderStates.set( scene, [ renderState ] ); + + } else { + + if ( renderCallDepth >= renderStateArray.length ) { + + renderState = new WebGLRenderState( extensions ); + renderStateArray.push( renderState ); + + } else { + + renderState = renderStateArray[ renderCallDepth ]; + + } + + } + + return renderState; + + } + + function dispose() { + + renderStates = new WeakMap(); + + } + + return { + get: get, + dispose: dispose + }; + +} + +class MeshDepthMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isMeshDepthMaterial = true; + + this.type = 'MeshDepthMaterial'; + + this.depthPacking = BasicDepthPacking; + + this.map = null; + + this.alphaMap = null; + + this.displacementMap = null; + this.displacementScale = 1; + this.displacementBias = 0; + + this.wireframe = false; + this.wireframeLinewidth = 1; + + this.setValues( parameters ); + + } + + copy( source ) { + + super.copy( source ); + + this.depthPacking = source.depthPacking; + + this.map = source.map; + + this.alphaMap = source.alphaMap; + + this.displacementMap = source.displacementMap; + this.displacementScale = source.displacementScale; + this.displacementBias = source.displacementBias; + + this.wireframe = source.wireframe; + this.wireframeLinewidth = source.wireframeLinewidth; + + return this; + + } + +} + +class MeshDistanceMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isMeshDistanceMaterial = true; + + this.type = 'MeshDistanceMaterial'; + + this.map = null; + + this.alphaMap = null; + + this.displacementMap = null; + this.displacementScale = 1; + this.displacementBias = 0; + + this.setValues( parameters ); + + } + + copy( source ) { + + super.copy( source ); + + this.map = source.map; + + this.alphaMap = source.alphaMap; + + this.displacementMap = source.displacementMap; + this.displacementScale = source.displacementScale; + this.displacementBias = source.displacementBias; + + return this; + + } + +} + +const vertex = "void main() {\n\tgl_Position = vec4( position, 1.0 );\n}"; + +const fragment = "uniform sampler2D shadow_pass;\nuniform vec2 resolution;\nuniform float radius;\n#include \nvoid main() {\n\tconst float samples = float( VSM_SAMPLES );\n\tfloat mean = 0.0;\n\tfloat squared_mean = 0.0;\n\tfloat uvStride = samples <= 1.0 ? 0.0 : 2.0 / ( samples - 1.0 );\n\tfloat uvStart = samples <= 1.0 ? 0.0 : - 1.0;\n\tfor ( float i = 0.0; i < samples; i ++ ) {\n\t\tfloat uvOffset = uvStart + i * uvStride;\n\t\t#ifdef HORIZONTAL_PASS\n\t\t\tvec2 distribution = unpackRGBATo2Half( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( uvOffset, 0.0 ) * radius ) / resolution ) );\n\t\t\tmean += distribution.x;\n\t\t\tsquared_mean += distribution.y * distribution.y + distribution.x * distribution.x;\n\t\t#else\n\t\t\tfloat depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( 0.0, uvOffset ) * radius ) / resolution ) );\n\t\t\tmean += depth;\n\t\t\tsquared_mean += depth * depth;\n\t\t#endif\n\t}\n\tmean = mean / samples;\n\tsquared_mean = squared_mean / samples;\n\tfloat std_dev = sqrt( squared_mean - mean * mean );\n\tgl_FragColor = pack2HalfToRGBA( vec2( mean, std_dev ) );\n}"; + +function WebGLShadowMap( renderer, objects, capabilities ) { + + let _frustum = new Frustum(); + + const _shadowMapSize = new Vector2(), + _viewportSize = new Vector2(), + + _viewport = new Vector4(), + + _depthMaterial = new MeshDepthMaterial( { depthPacking: RGBADepthPacking } ), + _distanceMaterial = new MeshDistanceMaterial(), + + _materialCache = {}, + + _maxTextureSize = capabilities.maxTextureSize; + + const shadowSide = { [ FrontSide ]: BackSide, [ BackSide ]: FrontSide, [ DoubleSide ]: DoubleSide }; + + const shadowMaterialVertical = new ShaderMaterial( { + defines: { + VSM_SAMPLES: 8 + }, + uniforms: { + shadow_pass: { value: null }, + resolution: { value: new Vector2() }, + radius: { value: 4.0 } + }, + + vertexShader: vertex, + fragmentShader: fragment + + } ); + + const shadowMaterialHorizontal = shadowMaterialVertical.clone(); + shadowMaterialHorizontal.defines.HORIZONTAL_PASS = 1; + + const fullScreenTri = new BufferGeometry(); + fullScreenTri.setAttribute( + 'position', + new BufferAttribute( + new Float32Array( [ - 1, - 1, 0.5, 3, - 1, 0.5, - 1, 3, 0.5 ] ), + 3 + ) + ); + + const fullScreenMesh = new Mesh( fullScreenTri, shadowMaterialVertical ); + + const scope = this; + + this.enabled = false; + + this.autoUpdate = true; + this.needsUpdate = false; + + this.type = PCFShadowMap; + let _previousType = this.type; + + this.render = function ( lights, scene, camera ) { + + if ( scope.enabled === false ) return; + if ( scope.autoUpdate === false && scope.needsUpdate === false ) return; + + if ( lights.length === 0 ) return; + + const currentRenderTarget = renderer.getRenderTarget(); + const activeCubeFace = renderer.getActiveCubeFace(); + const activeMipmapLevel = renderer.getActiveMipmapLevel(); + + const _state = renderer.state; + + // Set GL state for depth map. + _state.setBlending( NoBlending ); + _state.buffers.color.setClear( 1, 1, 1, 1 ); + _state.buffers.depth.setTest( true ); + _state.setScissorTest( false ); + + // check for shadow map type changes + + const toVSM = ( _previousType !== VSMShadowMap && this.type === VSMShadowMap ); + const fromVSM = ( _previousType === VSMShadowMap && this.type !== VSMShadowMap ); + + // render depth map + + for ( let i = 0, il = lights.length; i < il; i ++ ) { + + const light = lights[ i ]; + const shadow = light.shadow; + + if ( shadow === undefined ) { + + console.warn( 'THREE.WebGLShadowMap:', light, 'has no shadow.' ); + continue; + + } + + if ( shadow.autoUpdate === false && shadow.needsUpdate === false ) continue; + + _shadowMapSize.copy( shadow.mapSize ); + + const shadowFrameExtents = shadow.getFrameExtents(); + + _shadowMapSize.multiply( shadowFrameExtents ); + + _viewportSize.copy( shadow.mapSize ); + + if ( _shadowMapSize.x > _maxTextureSize || _shadowMapSize.y > _maxTextureSize ) { + + if ( _shadowMapSize.x > _maxTextureSize ) { + + _viewportSize.x = Math.floor( _maxTextureSize / shadowFrameExtents.x ); + _shadowMapSize.x = _viewportSize.x * shadowFrameExtents.x; + shadow.mapSize.x = _viewportSize.x; + + } + + if ( _shadowMapSize.y > _maxTextureSize ) { + + _viewportSize.y = Math.floor( _maxTextureSize / shadowFrameExtents.y ); + _shadowMapSize.y = _viewportSize.y * shadowFrameExtents.y; + shadow.mapSize.y = _viewportSize.y; + + } + + } + + if ( shadow.map === null || toVSM === true || fromVSM === true ) { + + const pars = ( this.type !== VSMShadowMap ) ? { minFilter: NearestFilter, magFilter: NearestFilter } : {}; + + if ( shadow.map !== null ) { + + shadow.map.dispose(); + + } + + shadow.map = new WebGLRenderTarget( _shadowMapSize.x, _shadowMapSize.y, pars ); + shadow.map.texture.name = light.name + '.shadowMap'; + + shadow.camera.updateProjectionMatrix(); + + } + + renderer.setRenderTarget( shadow.map ); + renderer.clear(); + + const viewportCount = shadow.getViewportCount(); + + for ( let vp = 0; vp < viewportCount; vp ++ ) { + + const viewport = shadow.getViewport( vp ); + + _viewport.set( + _viewportSize.x * viewport.x, + _viewportSize.y * viewport.y, + _viewportSize.x * viewport.z, + _viewportSize.y * viewport.w + ); + + _state.viewport( _viewport ); + + shadow.updateMatrices( light, vp ); + + _frustum = shadow.getFrustum(); + + renderObject( scene, camera, shadow.camera, light, this.type ); + + } + + // do blur pass for VSM + + if ( shadow.isPointLightShadow !== true && this.type === VSMShadowMap ) { + + VSMPass( shadow, camera ); + + } + + shadow.needsUpdate = false; + + } + + _previousType = this.type; + + scope.needsUpdate = false; + + renderer.setRenderTarget( currentRenderTarget, activeCubeFace, activeMipmapLevel ); + + }; + + function VSMPass( shadow, camera ) { + + const geometry = objects.update( fullScreenMesh ); + + if ( shadowMaterialVertical.defines.VSM_SAMPLES !== shadow.blurSamples ) { + + shadowMaterialVertical.defines.VSM_SAMPLES = shadow.blurSamples; + shadowMaterialHorizontal.defines.VSM_SAMPLES = shadow.blurSamples; + + shadowMaterialVertical.needsUpdate = true; + shadowMaterialHorizontal.needsUpdate = true; + + } + + if ( shadow.mapPass === null ) { + + shadow.mapPass = new WebGLRenderTarget( _shadowMapSize.x, _shadowMapSize.y ); + + } + + // vertical pass + + shadowMaterialVertical.uniforms.shadow_pass.value = shadow.map.texture; + shadowMaterialVertical.uniforms.resolution.value = shadow.mapSize; + shadowMaterialVertical.uniforms.radius.value = shadow.radius; + renderer.setRenderTarget( shadow.mapPass ); + renderer.clear(); + renderer.renderBufferDirect( camera, null, geometry, shadowMaterialVertical, fullScreenMesh, null ); + + // horizontal pass + + shadowMaterialHorizontal.uniforms.shadow_pass.value = shadow.mapPass.texture; + shadowMaterialHorizontal.uniforms.resolution.value = shadow.mapSize; + shadowMaterialHorizontal.uniforms.radius.value = shadow.radius; + renderer.setRenderTarget( shadow.map ); + renderer.clear(); + renderer.renderBufferDirect( camera, null, geometry, shadowMaterialHorizontal, fullScreenMesh, null ); + + } + + function getDepthMaterial( object, material, light, type ) { + + let result = null; + + const customMaterial = ( light.isPointLight === true ) ? object.customDistanceMaterial : object.customDepthMaterial; + + if ( customMaterial !== undefined ) { + + result = customMaterial; + + } else { + + result = ( light.isPointLight === true ) ? _distanceMaterial : _depthMaterial; + + if ( ( renderer.localClippingEnabled && material.clipShadows === true && Array.isArray( material.clippingPlanes ) && material.clippingPlanes.length !== 0 ) || + ( material.displacementMap && material.displacementScale !== 0 ) || + ( material.alphaMap && material.alphaTest > 0 ) || + ( material.map && material.alphaTest > 0 ) ) { + + // in this case we need a unique material instance reflecting the + // appropriate state + + const keyA = result.uuid, keyB = material.uuid; + + let materialsForVariant = _materialCache[ keyA ]; + + if ( materialsForVariant === undefined ) { + + materialsForVariant = {}; + _materialCache[ keyA ] = materialsForVariant; + + } + + let cachedMaterial = materialsForVariant[ keyB ]; + + if ( cachedMaterial === undefined ) { + + cachedMaterial = result.clone(); + materialsForVariant[ keyB ] = cachedMaterial; + material.addEventListener( 'dispose', onMaterialDispose ); + + } + + result = cachedMaterial; + + } + + } + + result.visible = material.visible; + result.wireframe = material.wireframe; + + if ( type === VSMShadowMap ) { + + result.side = ( material.shadowSide !== null ) ? material.shadowSide : material.side; + + } else { + + result.side = ( material.shadowSide !== null ) ? material.shadowSide : shadowSide[ material.side ]; + + } + + result.alphaMap = material.alphaMap; + result.alphaTest = material.alphaTest; + result.map = material.map; + + result.clipShadows = material.clipShadows; + result.clippingPlanes = material.clippingPlanes; + result.clipIntersection = material.clipIntersection; + + result.displacementMap = material.displacementMap; + result.displacementScale = material.displacementScale; + result.displacementBias = material.displacementBias; + + result.wireframeLinewidth = material.wireframeLinewidth; + result.linewidth = material.linewidth; + + if ( light.isPointLight === true && result.isMeshDistanceMaterial === true ) { + + const materialProperties = renderer.properties.get( result ); + materialProperties.light = light; + + } + + return result; + + } + + function renderObject( object, camera, shadowCamera, light, type ) { + + if ( object.visible === false ) return; + + const visible = object.layers.test( camera.layers ); + + if ( visible && ( object.isMesh || object.isLine || object.isPoints ) ) { + + if ( ( object.castShadow || ( object.receiveShadow && type === VSMShadowMap ) ) && ( ! object.frustumCulled || _frustum.intersectsObject( object ) ) ) { + + object.modelViewMatrix.multiplyMatrices( shadowCamera.matrixWorldInverse, object.matrixWorld ); + + const geometry = objects.update( object ); + const material = object.material; + + if ( Array.isArray( material ) ) { + + const groups = geometry.groups; + + for ( let k = 0, kl = groups.length; k < kl; k ++ ) { + + const group = groups[ k ]; + const groupMaterial = material[ group.materialIndex ]; + + if ( groupMaterial && groupMaterial.visible ) { + + const depthMaterial = getDepthMaterial( object, groupMaterial, light, type ); + + object.onBeforeShadow( renderer, object, camera, shadowCamera, geometry, depthMaterial, group ); + + renderer.renderBufferDirect( shadowCamera, null, geometry, depthMaterial, object, group ); + + object.onAfterShadow( renderer, object, camera, shadowCamera, geometry, depthMaterial, group ); + + } + + } + + } else if ( material.visible ) { + + const depthMaterial = getDepthMaterial( object, material, light, type ); + + object.onBeforeShadow( renderer, object, camera, shadowCamera, geometry, depthMaterial, null ); + + renderer.renderBufferDirect( shadowCamera, null, geometry, depthMaterial, object, null ); + + object.onAfterShadow( renderer, object, camera, shadowCamera, geometry, depthMaterial, null ); + + } + + } + + } + + const children = object.children; + + for ( let i = 0, l = children.length; i < l; i ++ ) { + + renderObject( children[ i ], camera, shadowCamera, light, type ); + + } + + } + + function onMaterialDispose( event ) { + + const material = event.target; + + material.removeEventListener( 'dispose', onMaterialDispose ); + + // make sure to remove the unique distance/depth materials used for shadow map rendering + + for ( const id in _materialCache ) { + + const cache = _materialCache[ id ]; + + const uuid = event.target.uuid; + + if ( uuid in cache ) { + + const shadowMaterial = cache[ uuid ]; + shadowMaterial.dispose(); + delete cache[ uuid ]; + + } + + } + + } + +} + +function WebGLState( gl ) { + + function ColorBuffer() { + + let locked = false; + + const color = new Vector4(); + let currentColorMask = null; + const currentColorClear = new Vector4( 0, 0, 0, 0 ); + + return { + + setMask: function ( colorMask ) { + + if ( currentColorMask !== colorMask && ! locked ) { + + gl.colorMask( colorMask, colorMask, colorMask, colorMask ); + currentColorMask = colorMask; + + } + + }, + + setLocked: function ( lock ) { + + locked = lock; + + }, + + setClear: function ( r, g, b, a, premultipliedAlpha ) { + + if ( premultipliedAlpha === true ) { + + r *= a; g *= a; b *= a; + + } + + color.set( r, g, b, a ); + + if ( currentColorClear.equals( color ) === false ) { + + gl.clearColor( r, g, b, a ); + currentColorClear.copy( color ); + + } + + }, + + reset: function () { + + locked = false; + + currentColorMask = null; + currentColorClear.set( - 1, 0, 0, 0 ); // set to invalid state + + } + + }; + + } + + function DepthBuffer() { + + let locked = false; + + let currentDepthMask = null; + let currentDepthFunc = null; + let currentDepthClear = null; + + return { + + setTest: function ( depthTest ) { + + if ( depthTest ) { + + enable( gl.DEPTH_TEST ); + + } else { + + disable( gl.DEPTH_TEST ); + + } + + }, + + setMask: function ( depthMask ) { + + if ( currentDepthMask !== depthMask && ! locked ) { + + gl.depthMask( depthMask ); + currentDepthMask = depthMask; + + } + + }, + + setFunc: function ( depthFunc ) { + + if ( currentDepthFunc !== depthFunc ) { + + switch ( depthFunc ) { + + case NeverDepth: + + gl.depthFunc( gl.NEVER ); + break; + + case AlwaysDepth: + + gl.depthFunc( gl.ALWAYS ); + break; + + case LessDepth: + + gl.depthFunc( gl.LESS ); + break; + + case LessEqualDepth: + + gl.depthFunc( gl.LEQUAL ); + break; + + case EqualDepth: + + gl.depthFunc( gl.EQUAL ); + break; + + case GreaterEqualDepth: + + gl.depthFunc( gl.GEQUAL ); + break; + + case GreaterDepth: + + gl.depthFunc( gl.GREATER ); + break; + + case NotEqualDepth: + + gl.depthFunc( gl.NOTEQUAL ); + break; + + default: + + gl.depthFunc( gl.LEQUAL ); + + } + + currentDepthFunc = depthFunc; + + } + + }, + + setLocked: function ( lock ) { + + locked = lock; + + }, + + setClear: function ( depth ) { + + if ( currentDepthClear !== depth ) { + + gl.clearDepth( depth ); + currentDepthClear = depth; + + } + + }, + + reset: function () { + + locked = false; + + currentDepthMask = null; + currentDepthFunc = null; + currentDepthClear = null; + + } + + }; + + } + + function StencilBuffer() { + + let locked = false; + + let currentStencilMask = null; + let currentStencilFunc = null; + let currentStencilRef = null; + let currentStencilFuncMask = null; + let currentStencilFail = null; + let currentStencilZFail = null; + let currentStencilZPass = null; + let currentStencilClear = null; + + return { + + setTest: function ( stencilTest ) { + + if ( ! locked ) { + + if ( stencilTest ) { + + enable( gl.STENCIL_TEST ); + + } else { + + disable( gl.STENCIL_TEST ); + + } + + } + + }, + + setMask: function ( stencilMask ) { + + if ( currentStencilMask !== stencilMask && ! locked ) { + + gl.stencilMask( stencilMask ); + currentStencilMask = stencilMask; + + } + + }, + + setFunc: function ( stencilFunc, stencilRef, stencilMask ) { + + if ( currentStencilFunc !== stencilFunc || + currentStencilRef !== stencilRef || + currentStencilFuncMask !== stencilMask ) { + + gl.stencilFunc( stencilFunc, stencilRef, stencilMask ); + + currentStencilFunc = stencilFunc; + currentStencilRef = stencilRef; + currentStencilFuncMask = stencilMask; + + } + + }, + + setOp: function ( stencilFail, stencilZFail, stencilZPass ) { + + if ( currentStencilFail !== stencilFail || + currentStencilZFail !== stencilZFail || + currentStencilZPass !== stencilZPass ) { + + gl.stencilOp( stencilFail, stencilZFail, stencilZPass ); + + currentStencilFail = stencilFail; + currentStencilZFail = stencilZFail; + currentStencilZPass = stencilZPass; + + } + + }, + + setLocked: function ( lock ) { + + locked = lock; + + }, + + setClear: function ( stencil ) { + + if ( currentStencilClear !== stencil ) { + + gl.clearStencil( stencil ); + currentStencilClear = stencil; + + } + + }, + + reset: function () { + + locked = false; + + currentStencilMask = null; + currentStencilFunc = null; + currentStencilRef = null; + currentStencilFuncMask = null; + currentStencilFail = null; + currentStencilZFail = null; + currentStencilZPass = null; + currentStencilClear = null; + + } + + }; + + } + + // + + const colorBuffer = new ColorBuffer(); + const depthBuffer = new DepthBuffer(); + const stencilBuffer = new StencilBuffer(); + + const uboBindings = new WeakMap(); + const uboProgramMap = new WeakMap(); + + let enabledCapabilities = {}; + + let currentBoundFramebuffers = {}; + let currentDrawbuffers = new WeakMap(); + let defaultDrawbuffers = []; + + let currentProgram = null; + + let currentBlendingEnabled = false; + let currentBlending = null; + let currentBlendEquation = null; + let currentBlendSrc = null; + let currentBlendDst = null; + let currentBlendEquationAlpha = null; + let currentBlendSrcAlpha = null; + let currentBlendDstAlpha = null; + let currentBlendColor = new Color( 0, 0, 0 ); + let currentBlendAlpha = 0; + let currentPremultipledAlpha = false; + + let currentFlipSided = null; + let currentCullFace = null; + + let currentLineWidth = null; + + let currentPolygonOffsetFactor = null; + let currentPolygonOffsetUnits = null; + + const maxTextures = gl.getParameter( gl.MAX_COMBINED_TEXTURE_IMAGE_UNITS ); + + let lineWidthAvailable = false; + let version = 0; + const glVersion = gl.getParameter( gl.VERSION ); + + if ( glVersion.indexOf( 'WebGL' ) !== - 1 ) { + + version = parseFloat( /^WebGL (\d)/.exec( glVersion )[ 1 ] ); + lineWidthAvailable = ( version >= 1.0 ); + + } else if ( glVersion.indexOf( 'OpenGL ES' ) !== - 1 ) { + + version = parseFloat( /^OpenGL ES (\d)/.exec( glVersion )[ 1 ] ); + lineWidthAvailable = ( version >= 2.0 ); + + } + + let currentTextureSlot = null; + let currentBoundTextures = {}; + + const scissorParam = gl.getParameter( gl.SCISSOR_BOX ); + const viewportParam = gl.getParameter( gl.VIEWPORT ); + + const currentScissor = new Vector4().fromArray( scissorParam ); + const currentViewport = new Vector4().fromArray( viewportParam ); + + function createTexture( type, target, count, dimensions ) { + + const data = new Uint8Array( 4 ); // 4 is required to match default unpack alignment of 4. + const texture = gl.createTexture(); + + gl.bindTexture( type, texture ); + gl.texParameteri( type, gl.TEXTURE_MIN_FILTER, gl.NEAREST ); + gl.texParameteri( type, gl.TEXTURE_MAG_FILTER, gl.NEAREST ); + + for ( let i = 0; i < count; i ++ ) { + + if ( type === gl.TEXTURE_3D || type === gl.TEXTURE_2D_ARRAY ) { + + gl.texImage3D( target, 0, gl.RGBA, 1, 1, dimensions, 0, gl.RGBA, gl.UNSIGNED_BYTE, data ); + + } else { + + gl.texImage2D( target + i, 0, gl.RGBA, 1, 1, 0, gl.RGBA, gl.UNSIGNED_BYTE, data ); + + } + + } + + return texture; + + } + + const emptyTextures = {}; + emptyTextures[ gl.TEXTURE_2D ] = createTexture( gl.TEXTURE_2D, gl.TEXTURE_2D, 1 ); + emptyTextures[ gl.TEXTURE_CUBE_MAP ] = createTexture( gl.TEXTURE_CUBE_MAP, gl.TEXTURE_CUBE_MAP_POSITIVE_X, 6 ); + emptyTextures[ gl.TEXTURE_2D_ARRAY ] = createTexture( gl.TEXTURE_2D_ARRAY, gl.TEXTURE_2D_ARRAY, 1, 1 ); + emptyTextures[ gl.TEXTURE_3D ] = createTexture( gl.TEXTURE_3D, gl.TEXTURE_3D, 1, 1 ); + + // init + + colorBuffer.setClear( 0, 0, 0, 1 ); + depthBuffer.setClear( 1 ); + stencilBuffer.setClear( 0 ); + + enable( gl.DEPTH_TEST ); + depthBuffer.setFunc( LessEqualDepth ); + + setFlipSided( false ); + setCullFace( CullFaceBack ); + enable( gl.CULL_FACE ); + + setBlending( NoBlending ); + + // + + function enable( id ) { + + if ( enabledCapabilities[ id ] !== true ) { + + gl.enable( id ); + enabledCapabilities[ id ] = true; + + } + + } + + function disable( id ) { + + if ( enabledCapabilities[ id ] !== false ) { + + gl.disable( id ); + enabledCapabilities[ id ] = false; + + } + + } + + function bindFramebuffer( target, framebuffer ) { + + if ( currentBoundFramebuffers[ target ] !== framebuffer ) { + + gl.bindFramebuffer( target, framebuffer ); + + currentBoundFramebuffers[ target ] = framebuffer; + + // gl.DRAW_FRAMEBUFFER is equivalent to gl.FRAMEBUFFER + + if ( target === gl.DRAW_FRAMEBUFFER ) { + + currentBoundFramebuffers[ gl.FRAMEBUFFER ] = framebuffer; + + } + + if ( target === gl.FRAMEBUFFER ) { + + currentBoundFramebuffers[ gl.DRAW_FRAMEBUFFER ] = framebuffer; + + } + + return true; + + } + + return false; + + } + + function drawBuffers( renderTarget, framebuffer ) { + + let drawBuffers = defaultDrawbuffers; + + let needsUpdate = false; + + if ( renderTarget ) { + + drawBuffers = currentDrawbuffers.get( framebuffer ); + + if ( drawBuffers === undefined ) { + + drawBuffers = []; + currentDrawbuffers.set( framebuffer, drawBuffers ); + + } + + const textures = renderTarget.textures; + + if ( drawBuffers.length !== textures.length || drawBuffers[ 0 ] !== gl.COLOR_ATTACHMENT0 ) { + + for ( let i = 0, il = textures.length; i < il; i ++ ) { + + drawBuffers[ i ] = gl.COLOR_ATTACHMENT0 + i; + + } + + drawBuffers.length = textures.length; + + needsUpdate = true; + + } + + } else { + + if ( drawBuffers[ 0 ] !== gl.BACK ) { + + drawBuffers[ 0 ] = gl.BACK; + + needsUpdate = true; + + } + + } + + if ( needsUpdate ) { + + gl.drawBuffers( drawBuffers ); + + } + + } + + function useProgram( program ) { + + if ( currentProgram !== program ) { + + gl.useProgram( program ); + + currentProgram = program; + + return true; + + } + + return false; + + } + + const equationToGL = { + [ AddEquation ]: gl.FUNC_ADD, + [ SubtractEquation ]: gl.FUNC_SUBTRACT, + [ ReverseSubtractEquation ]: gl.FUNC_REVERSE_SUBTRACT + }; + + equationToGL[ MinEquation ] = gl.MIN; + equationToGL[ MaxEquation ] = gl.MAX; + + const factorToGL = { + [ ZeroFactor ]: gl.ZERO, + [ OneFactor ]: gl.ONE, + [ SrcColorFactor ]: gl.SRC_COLOR, + [ SrcAlphaFactor ]: gl.SRC_ALPHA, + [ SrcAlphaSaturateFactor ]: gl.SRC_ALPHA_SATURATE, + [ DstColorFactor ]: gl.DST_COLOR, + [ DstAlphaFactor ]: gl.DST_ALPHA, + [ OneMinusSrcColorFactor ]: gl.ONE_MINUS_SRC_COLOR, + [ OneMinusSrcAlphaFactor ]: gl.ONE_MINUS_SRC_ALPHA, + [ OneMinusDstColorFactor ]: gl.ONE_MINUS_DST_COLOR, + [ OneMinusDstAlphaFactor ]: gl.ONE_MINUS_DST_ALPHA, + [ ConstantColorFactor ]: gl.CONSTANT_COLOR, + [ OneMinusConstantColorFactor ]: gl.ONE_MINUS_CONSTANT_COLOR, + [ ConstantAlphaFactor ]: gl.CONSTANT_ALPHA, + [ OneMinusConstantAlphaFactor ]: gl.ONE_MINUS_CONSTANT_ALPHA + }; + + function setBlending( blending, blendEquation, blendSrc, blendDst, blendEquationAlpha, blendSrcAlpha, blendDstAlpha, blendColor, blendAlpha, premultipliedAlpha ) { + + if ( blending === NoBlending ) { + + if ( currentBlendingEnabled === true ) { + + disable( gl.BLEND ); + currentBlendingEnabled = false; + + } + + return; + + } + + if ( currentBlendingEnabled === false ) { + + enable( gl.BLEND ); + currentBlendingEnabled = true; + + } + + if ( blending !== CustomBlending ) { + + if ( blending !== currentBlending || premultipliedAlpha !== currentPremultipledAlpha ) { + + if ( currentBlendEquation !== AddEquation || currentBlendEquationAlpha !== AddEquation ) { + + gl.blendEquation( gl.FUNC_ADD ); + + currentBlendEquation = AddEquation; + currentBlendEquationAlpha = AddEquation; + + } + + if ( premultipliedAlpha ) { + + switch ( blending ) { + + case NormalBlending: + gl.blendFuncSeparate( gl.ONE, gl.ONE_MINUS_SRC_ALPHA, gl.ONE, gl.ONE_MINUS_SRC_ALPHA ); + break; + + case AdditiveBlending: + gl.blendFunc( gl.ONE, gl.ONE ); + break; + + case SubtractiveBlending: + gl.blendFuncSeparate( gl.ZERO, gl.ONE_MINUS_SRC_COLOR, gl.ZERO, gl.ONE ); + break; + + case MultiplyBlending: + gl.blendFuncSeparate( gl.ZERO, gl.SRC_COLOR, gl.ZERO, gl.SRC_ALPHA ); + break; + + default: + console.error( 'THREE.WebGLState: Invalid blending: ', blending ); + break; + + } + + } else { + + switch ( blending ) { + + case NormalBlending: + gl.blendFuncSeparate( gl.SRC_ALPHA, gl.ONE_MINUS_SRC_ALPHA, gl.ONE, gl.ONE_MINUS_SRC_ALPHA ); + break; + + case AdditiveBlending: + gl.blendFunc( gl.SRC_ALPHA, gl.ONE ); + break; + + case SubtractiveBlending: + gl.blendFuncSeparate( gl.ZERO, gl.ONE_MINUS_SRC_COLOR, gl.ZERO, gl.ONE ); + break; + + case MultiplyBlending: + gl.blendFunc( gl.ZERO, gl.SRC_COLOR ); + break; + + default: + console.error( 'THREE.WebGLState: Invalid blending: ', blending ); + break; + + } + + } + + currentBlendSrc = null; + currentBlendDst = null; + currentBlendSrcAlpha = null; + currentBlendDstAlpha = null; + currentBlendColor.set( 0, 0, 0 ); + currentBlendAlpha = 0; + + currentBlending = blending; + currentPremultipledAlpha = premultipliedAlpha; + + } + + return; + + } + + // custom blending + + blendEquationAlpha = blendEquationAlpha || blendEquation; + blendSrcAlpha = blendSrcAlpha || blendSrc; + blendDstAlpha = blendDstAlpha || blendDst; + + if ( blendEquation !== currentBlendEquation || blendEquationAlpha !== currentBlendEquationAlpha ) { + + gl.blendEquationSeparate( equationToGL[ blendEquation ], equationToGL[ blendEquationAlpha ] ); + + currentBlendEquation = blendEquation; + currentBlendEquationAlpha = blendEquationAlpha; + + } + + if ( blendSrc !== currentBlendSrc || blendDst !== currentBlendDst || blendSrcAlpha !== currentBlendSrcAlpha || blendDstAlpha !== currentBlendDstAlpha ) { + + gl.blendFuncSeparate( factorToGL[ blendSrc ], factorToGL[ blendDst ], factorToGL[ blendSrcAlpha ], factorToGL[ blendDstAlpha ] ); + + currentBlendSrc = blendSrc; + currentBlendDst = blendDst; + currentBlendSrcAlpha = blendSrcAlpha; + currentBlendDstAlpha = blendDstAlpha; + + } + + if ( blendColor.equals( currentBlendColor ) === false || blendAlpha !== currentBlendAlpha ) { + + gl.blendColor( blendColor.r, blendColor.g, blendColor.b, blendAlpha ); + + currentBlendColor.copy( blendColor ); + currentBlendAlpha = blendAlpha; + + } + + currentBlending = blending; + currentPremultipledAlpha = false; + + } + + function setMaterial( material, frontFaceCW ) { + + material.side === DoubleSide + ? disable( gl.CULL_FACE ) + : enable( gl.CULL_FACE ); + + let flipSided = ( material.side === BackSide ); + if ( frontFaceCW ) flipSided = ! flipSided; + + setFlipSided( flipSided ); + + ( material.blending === NormalBlending && material.transparent === false ) + ? setBlending( NoBlending ) + : setBlending( material.blending, material.blendEquation, material.blendSrc, material.blendDst, material.blendEquationAlpha, material.blendSrcAlpha, material.blendDstAlpha, material.blendColor, material.blendAlpha, material.premultipliedAlpha ); + + depthBuffer.setFunc( material.depthFunc ); + depthBuffer.setTest( material.depthTest ); + depthBuffer.setMask( material.depthWrite ); + colorBuffer.setMask( material.colorWrite ); + + const stencilWrite = material.stencilWrite; + stencilBuffer.setTest( stencilWrite ); + if ( stencilWrite ) { + + stencilBuffer.setMask( material.stencilWriteMask ); + stencilBuffer.setFunc( material.stencilFunc, material.stencilRef, material.stencilFuncMask ); + stencilBuffer.setOp( material.stencilFail, material.stencilZFail, material.stencilZPass ); + + } + + setPolygonOffset( material.polygonOffset, material.polygonOffsetFactor, material.polygonOffsetUnits ); + + material.alphaToCoverage === true + ? enable( gl.SAMPLE_ALPHA_TO_COVERAGE ) + : disable( gl.SAMPLE_ALPHA_TO_COVERAGE ); + + } + + // + + function setFlipSided( flipSided ) { + + if ( currentFlipSided !== flipSided ) { + + if ( flipSided ) { + + gl.frontFace( gl.CW ); + + } else { + + gl.frontFace( gl.CCW ); + + } + + currentFlipSided = flipSided; + + } + + } + + function setCullFace( cullFace ) { + + if ( cullFace !== CullFaceNone ) { + + enable( gl.CULL_FACE ); + + if ( cullFace !== currentCullFace ) { + + if ( cullFace === CullFaceBack ) { + + gl.cullFace( gl.BACK ); + + } else if ( cullFace === CullFaceFront ) { + + gl.cullFace( gl.FRONT ); + + } else { + + gl.cullFace( gl.FRONT_AND_BACK ); + + } + + } + + } else { + + disable( gl.CULL_FACE ); + + } + + currentCullFace = cullFace; + + } + + function setLineWidth( width ) { + + if ( width !== currentLineWidth ) { + + if ( lineWidthAvailable ) gl.lineWidth( width ); + + currentLineWidth = width; + + } + + } + + function setPolygonOffset( polygonOffset, factor, units ) { + + if ( polygonOffset ) { + + enable( gl.POLYGON_OFFSET_FILL ); + + if ( currentPolygonOffsetFactor !== factor || currentPolygonOffsetUnits !== units ) { + + gl.polygonOffset( factor, units ); + + currentPolygonOffsetFactor = factor; + currentPolygonOffsetUnits = units; + + } + + } else { + + disable( gl.POLYGON_OFFSET_FILL ); + + } + + } + + function setScissorTest( scissorTest ) { + + if ( scissorTest ) { + + enable( gl.SCISSOR_TEST ); + + } else { + + disable( gl.SCISSOR_TEST ); + + } + + } + + // texture + + function activeTexture( webglSlot ) { + + if ( webglSlot === undefined ) webglSlot = gl.TEXTURE0 + maxTextures - 1; + + if ( currentTextureSlot !== webglSlot ) { + + gl.activeTexture( webglSlot ); + currentTextureSlot = webglSlot; + + } + + } + + function bindTexture( webglType, webglTexture, webglSlot ) { + + if ( webglSlot === undefined ) { + + if ( currentTextureSlot === null ) { + + webglSlot = gl.TEXTURE0 + maxTextures - 1; + + } else { + + webglSlot = currentTextureSlot; + + } + + } + + let boundTexture = currentBoundTextures[ webglSlot ]; + + if ( boundTexture === undefined ) { + + boundTexture = { type: undefined, texture: undefined }; + currentBoundTextures[ webglSlot ] = boundTexture; + + } + + if ( boundTexture.type !== webglType || boundTexture.texture !== webglTexture ) { + + if ( currentTextureSlot !== webglSlot ) { + + gl.activeTexture( webglSlot ); + currentTextureSlot = webglSlot; + + } + + gl.bindTexture( webglType, webglTexture || emptyTextures[ webglType ] ); + + boundTexture.type = webglType; + boundTexture.texture = webglTexture; + + } + + } + + function unbindTexture() { + + const boundTexture = currentBoundTextures[ currentTextureSlot ]; + + if ( boundTexture !== undefined && boundTexture.type !== undefined ) { + + gl.bindTexture( boundTexture.type, null ); + + boundTexture.type = undefined; + boundTexture.texture = undefined; + + } + + } + + function compressedTexImage2D() { + + try { + + gl.compressedTexImage2D.apply( gl, arguments ); + + } catch ( error ) { + + console.error( 'THREE.WebGLState:', error ); + + } + + } + + function compressedTexImage3D() { + + try { + + gl.compressedTexImage3D.apply( gl, arguments ); + + } catch ( error ) { + + console.error( 'THREE.WebGLState:', error ); + + } + + } + + function texSubImage2D() { + + try { + + gl.texSubImage2D.apply( gl, arguments ); + + } catch ( error ) { + + console.error( 'THREE.WebGLState:', error ); + + } + + } + + function texSubImage3D() { + + try { + + gl.texSubImage3D.apply( gl, arguments ); + + } catch ( error ) { + + console.error( 'THREE.WebGLState:', error ); + + } + + } + + function compressedTexSubImage2D() { + + try { + + gl.compressedTexSubImage2D.apply( gl, arguments ); + + } catch ( error ) { + + console.error( 'THREE.WebGLState:', error ); + + } + + } + + function compressedTexSubImage3D() { + + try { + + gl.compressedTexSubImage3D.apply( gl, arguments ); + + } catch ( error ) { + + console.error( 'THREE.WebGLState:', error ); + + } + + } + + function texStorage2D() { + + try { + + gl.texStorage2D.apply( gl, arguments ); + + } catch ( error ) { + + console.error( 'THREE.WebGLState:', error ); + + } + + } + + function texStorage3D() { + + try { + + gl.texStorage3D.apply( gl, arguments ); + + } catch ( error ) { + + console.error( 'THREE.WebGLState:', error ); + + } + + } + + function texImage2D() { + + try { + + gl.texImage2D.apply( gl, arguments ); + + } catch ( error ) { + + console.error( 'THREE.WebGLState:', error ); + + } + + } + + function texImage3D() { + + try { + + gl.texImage3D.apply( gl, arguments ); + + } catch ( error ) { + + console.error( 'THREE.WebGLState:', error ); + + } + + } + + // + + function scissor( scissor ) { + + if ( currentScissor.equals( scissor ) === false ) { + + gl.scissor( scissor.x, scissor.y, scissor.z, scissor.w ); + currentScissor.copy( scissor ); + + } + + } + + function viewport( viewport ) { + + if ( currentViewport.equals( viewport ) === false ) { + + gl.viewport( viewport.x, viewport.y, viewport.z, viewport.w ); + currentViewport.copy( viewport ); + + } + + } + + function updateUBOMapping( uniformsGroup, program ) { + + let mapping = uboProgramMap.get( program ); + + if ( mapping === undefined ) { + + mapping = new WeakMap(); + + uboProgramMap.set( program, mapping ); + + } + + let blockIndex = mapping.get( uniformsGroup ); + + if ( blockIndex === undefined ) { + + blockIndex = gl.getUniformBlockIndex( program, uniformsGroup.name ); + + mapping.set( uniformsGroup, blockIndex ); + + } + + } + + function uniformBlockBinding( uniformsGroup, program ) { + + const mapping = uboProgramMap.get( program ); + const blockIndex = mapping.get( uniformsGroup ); + + if ( uboBindings.get( program ) !== blockIndex ) { + + // bind shader specific block index to global block point + gl.uniformBlockBinding( program, blockIndex, uniformsGroup.__bindingPointIndex ); + + uboBindings.set( program, blockIndex ); + + } + + } + + // + + function reset() { + + // reset state + + gl.disable( gl.BLEND ); + gl.disable( gl.CULL_FACE ); + gl.disable( gl.DEPTH_TEST ); + gl.disable( gl.POLYGON_OFFSET_FILL ); + gl.disable( gl.SCISSOR_TEST ); + gl.disable( gl.STENCIL_TEST ); + gl.disable( gl.SAMPLE_ALPHA_TO_COVERAGE ); + + gl.blendEquation( gl.FUNC_ADD ); + gl.blendFunc( gl.ONE, gl.ZERO ); + gl.blendFuncSeparate( gl.ONE, gl.ZERO, gl.ONE, gl.ZERO ); + gl.blendColor( 0, 0, 0, 0 ); + + gl.colorMask( true, true, true, true ); + gl.clearColor( 0, 0, 0, 0 ); + + gl.depthMask( true ); + gl.depthFunc( gl.LESS ); + gl.clearDepth( 1 ); + + gl.stencilMask( 0xffffffff ); + gl.stencilFunc( gl.ALWAYS, 0, 0xffffffff ); + gl.stencilOp( gl.KEEP, gl.KEEP, gl.KEEP ); + gl.clearStencil( 0 ); + + gl.cullFace( gl.BACK ); + gl.frontFace( gl.CCW ); + + gl.polygonOffset( 0, 0 ); + + gl.activeTexture( gl.TEXTURE0 ); + + gl.bindFramebuffer( gl.FRAMEBUFFER, null ); + gl.bindFramebuffer( gl.DRAW_FRAMEBUFFER, null ); + gl.bindFramebuffer( gl.READ_FRAMEBUFFER, null ); + + gl.useProgram( null ); + + gl.lineWidth( 1 ); + + gl.scissor( 0, 0, gl.canvas.width, gl.canvas.height ); + gl.viewport( 0, 0, gl.canvas.width, gl.canvas.height ); + + // reset internals + + enabledCapabilities = {}; + + currentTextureSlot = null; + currentBoundTextures = {}; + + currentBoundFramebuffers = {}; + currentDrawbuffers = new WeakMap(); + defaultDrawbuffers = []; + + currentProgram = null; + + currentBlendingEnabled = false; + currentBlending = null; + currentBlendEquation = null; + currentBlendSrc = null; + currentBlendDst = null; + currentBlendEquationAlpha = null; + currentBlendSrcAlpha = null; + currentBlendDstAlpha = null; + currentBlendColor = new Color( 0, 0, 0 ); + currentBlendAlpha = 0; + currentPremultipledAlpha = false; + + currentFlipSided = null; + currentCullFace = null; + + currentLineWidth = null; + + currentPolygonOffsetFactor = null; + currentPolygonOffsetUnits = null; + + currentScissor.set( 0, 0, gl.canvas.width, gl.canvas.height ); + currentViewport.set( 0, 0, gl.canvas.width, gl.canvas.height ); + + colorBuffer.reset(); + depthBuffer.reset(); + stencilBuffer.reset(); + + } + + return { + + buffers: { + color: colorBuffer, + depth: depthBuffer, + stencil: stencilBuffer + }, + + enable: enable, + disable: disable, + + bindFramebuffer: bindFramebuffer, + drawBuffers: drawBuffers, + + useProgram: useProgram, + + setBlending: setBlending, + setMaterial: setMaterial, + + setFlipSided: setFlipSided, + setCullFace: setCullFace, + + setLineWidth: setLineWidth, + setPolygonOffset: setPolygonOffset, + + setScissorTest: setScissorTest, + + activeTexture: activeTexture, + bindTexture: bindTexture, + unbindTexture: unbindTexture, + compressedTexImage2D: compressedTexImage2D, + compressedTexImage3D: compressedTexImage3D, + texImage2D: texImage2D, + texImage3D: texImage3D, + + updateUBOMapping: updateUBOMapping, + uniformBlockBinding: uniformBlockBinding, + + texStorage2D: texStorage2D, + texStorage3D: texStorage3D, + texSubImage2D: texSubImage2D, + texSubImage3D: texSubImage3D, + compressedTexSubImage2D: compressedTexSubImage2D, + compressedTexSubImage3D: compressedTexSubImage3D, + + scissor: scissor, + viewport: viewport, + + reset: reset + + }; + +} + +function WebGLTextures( _gl, extensions, state, properties, capabilities, utils, info ) { + + const multisampledRTTExt = extensions.has( 'WEBGL_multisampled_render_to_texture' ) ? extensions.get( 'WEBGL_multisampled_render_to_texture' ) : null; + const supportsInvalidateFramebuffer = typeof navigator === 'undefined' ? false : /OculusBrowser/g.test( navigator.userAgent ); + + const _imageDimensions = new Vector2(); + const _videoTextures = new WeakMap(); + let _canvas; + + const _sources = new WeakMap(); // maps WebglTexture objects to instances of Source + + // cordova iOS (as of 5.0) still uses UIWebView, which provides OffscreenCanvas, + // also OffscreenCanvas.getContext("webgl"), but not OffscreenCanvas.getContext("2d")! + // Some implementations may only implement OffscreenCanvas partially (e.g. lacking 2d). + + let useOffscreenCanvas = false; + + try { + + useOffscreenCanvas = typeof OffscreenCanvas !== 'undefined' + // eslint-disable-next-line compat/compat + && ( new OffscreenCanvas( 1, 1 ).getContext( '2d' ) ) !== null; + + } catch ( err ) { + + // Ignore any errors + + } + + function createCanvas( width, height ) { + + // Use OffscreenCanvas when available. Specially needed in web workers + + return useOffscreenCanvas ? + // eslint-disable-next-line compat/compat + new OffscreenCanvas( width, height ) : createElementNS( 'canvas' ); + + } + + function resizeImage( image, needsNewCanvas, maxSize ) { + + let scale = 1; + + const dimensions = getDimensions( image ); + + // handle case if texture exceeds max size + + if ( dimensions.width > maxSize || dimensions.height > maxSize ) { + + scale = maxSize / Math.max( dimensions.width, dimensions.height ); + + } + + // only perform resize if necessary + + if ( scale < 1 ) { + + // only perform resize for certain image types + + if ( ( typeof HTMLImageElement !== 'undefined' && image instanceof HTMLImageElement ) || + ( typeof HTMLCanvasElement !== 'undefined' && image instanceof HTMLCanvasElement ) || + ( typeof ImageBitmap !== 'undefined' && image instanceof ImageBitmap ) || + ( typeof VideoFrame !== 'undefined' && image instanceof VideoFrame ) ) { + + const width = Math.floor( scale * dimensions.width ); + const height = Math.floor( scale * dimensions.height ); + + if ( _canvas === undefined ) _canvas = createCanvas( width, height ); + + // cube textures can't reuse the same canvas + + const canvas = needsNewCanvas ? createCanvas( width, height ) : _canvas; + + canvas.width = width; + canvas.height = height; + + const context = canvas.getContext( '2d' ); + context.drawImage( image, 0, 0, width, height ); + + console.warn( 'THREE.WebGLRenderer: Texture has been resized from (' + dimensions.width + 'x' + dimensions.height + ') to (' + width + 'x' + height + ').' ); + + return canvas; + + } else { + + if ( 'data' in image ) { + + console.warn( 'THREE.WebGLRenderer: Image in DataTexture is too big (' + dimensions.width + 'x' + dimensions.height + ').' ); + + } + + return image; + + } + + } + + return image; + + } + + function textureNeedsGenerateMipmaps( texture ) { + + return texture.generateMipmaps && texture.minFilter !== NearestFilter && texture.minFilter !== LinearFilter; + + } + + function generateMipmap( target ) { + + _gl.generateMipmap( target ); + + } + + function getInternalFormat( internalFormatName, glFormat, glType, colorSpace, forceLinearTransfer = false ) { + + if ( internalFormatName !== null ) { + + if ( _gl[ internalFormatName ] !== undefined ) return _gl[ internalFormatName ]; + + console.warn( 'THREE.WebGLRenderer: Attempt to use non-existing WebGL internal format \'' + internalFormatName + '\'' ); + + } + + let internalFormat = glFormat; + + if ( glFormat === _gl.RED ) { + + if ( glType === _gl.FLOAT ) internalFormat = _gl.R32F; + if ( glType === _gl.HALF_FLOAT ) internalFormat = _gl.R16F; + if ( glType === _gl.UNSIGNED_BYTE ) internalFormat = _gl.R8; + + } + + if ( glFormat === _gl.RED_INTEGER ) { + + if ( glType === _gl.UNSIGNED_BYTE ) internalFormat = _gl.R8UI; + if ( glType === _gl.UNSIGNED_SHORT ) internalFormat = _gl.R16UI; + if ( glType === _gl.UNSIGNED_INT ) internalFormat = _gl.R32UI; + if ( glType === _gl.BYTE ) internalFormat = _gl.R8I; + if ( glType === _gl.SHORT ) internalFormat = _gl.R16I; + if ( glType === _gl.INT ) internalFormat = _gl.R32I; + + } + + if ( glFormat === _gl.RG ) { + + if ( glType === _gl.FLOAT ) internalFormat = _gl.RG32F; + if ( glType === _gl.HALF_FLOAT ) internalFormat = _gl.RG16F; + if ( glType === _gl.UNSIGNED_BYTE ) internalFormat = _gl.RG8; + + } + + if ( glFormat === _gl.RG_INTEGER ) { + + if ( glType === _gl.UNSIGNED_BYTE ) internalFormat = _gl.RG8UI; + if ( glType === _gl.UNSIGNED_SHORT ) internalFormat = _gl.RG16UI; + if ( glType === _gl.UNSIGNED_INT ) internalFormat = _gl.RG32UI; + if ( glType === _gl.BYTE ) internalFormat = _gl.RG8I; + if ( glType === _gl.SHORT ) internalFormat = _gl.RG16I; + if ( glType === _gl.INT ) internalFormat = _gl.RG32I; + + } + + if ( glFormat === _gl.RGB ) { + + if ( glType === _gl.UNSIGNED_INT_5_9_9_9_REV ) internalFormat = _gl.RGB9_E5; + + } + + if ( glFormat === _gl.RGBA ) { + + const transfer = forceLinearTransfer ? LinearTransfer : ColorManagement.getTransfer( colorSpace ); + + if ( glType === _gl.FLOAT ) internalFormat = _gl.RGBA32F; + if ( glType === _gl.HALF_FLOAT ) internalFormat = _gl.RGBA16F; + if ( glType === _gl.UNSIGNED_BYTE ) internalFormat = ( transfer === SRGBTransfer ) ? _gl.SRGB8_ALPHA8 : _gl.RGBA8; + if ( glType === _gl.UNSIGNED_SHORT_4_4_4_4 ) internalFormat = _gl.RGBA4; + if ( glType === _gl.UNSIGNED_SHORT_5_5_5_1 ) internalFormat = _gl.RGB5_A1; + + } + + if ( internalFormat === _gl.R16F || internalFormat === _gl.R32F || + internalFormat === _gl.RG16F || internalFormat === _gl.RG32F || + internalFormat === _gl.RGBA16F || internalFormat === _gl.RGBA32F ) { + + extensions.get( 'EXT_color_buffer_float' ); + + } + + return internalFormat; + + } + + function getInternalDepthFormat( useStencil, depthType ) { + + let glInternalFormat; + if ( useStencil ) { + + if ( depthType === null || depthType === UnsignedIntType || depthType === UnsignedInt248Type ) { + + glInternalFormat = _gl.DEPTH24_STENCIL8; + + } else if ( depthType === FloatType ) { + + glInternalFormat = _gl.DEPTH32F_STENCIL8; + + } else if ( depthType === UnsignedShortType ) { + + glInternalFormat = _gl.DEPTH24_STENCIL8; + console.warn( 'DepthTexture: 16 bit depth attachment is not supported with stencil. Using 24-bit attachment.' ); + + } + + } else { + + if ( depthType === null || depthType === UnsignedIntType || depthType === UnsignedInt248Type ) { + + glInternalFormat = _gl.DEPTH_COMPONENT24; + + } else if ( depthType === FloatType ) { + + glInternalFormat = _gl.DEPTH_COMPONENT32F; + + } else if ( depthType === UnsignedShortType ) { + + glInternalFormat = _gl.DEPTH_COMPONENT16; + + } + + } + + return glInternalFormat; + + } + + function getMipLevels( texture, image ) { + + if ( textureNeedsGenerateMipmaps( texture ) === true || ( texture.isFramebufferTexture && texture.minFilter !== NearestFilter && texture.minFilter !== LinearFilter ) ) { + + return Math.log2( Math.max( image.width, image.height ) ) + 1; + + } else if ( texture.mipmaps !== undefined && texture.mipmaps.length > 0 ) { + + // user-defined mipmaps + + return texture.mipmaps.length; + + } else if ( texture.isCompressedTexture && Array.isArray( texture.image ) ) { + + return image.mipmaps.length; + + } else { + + // texture without mipmaps (only base level) + + return 1; + + } + + } + + // + + function onTextureDispose( event ) { + + const texture = event.target; + + texture.removeEventListener( 'dispose', onTextureDispose ); + + deallocateTexture( texture ); + + if ( texture.isVideoTexture ) { + + _videoTextures.delete( texture ); + + } + + } + + function onRenderTargetDispose( event ) { + + const renderTarget = event.target; + + renderTarget.removeEventListener( 'dispose', onRenderTargetDispose ); + + deallocateRenderTarget( renderTarget ); + + } + + // + + function deallocateTexture( texture ) { + + const textureProperties = properties.get( texture ); + + if ( textureProperties.__webglInit === undefined ) return; + + // check if it's necessary to remove the WebGLTexture object + + const source = texture.source; + const webglTextures = _sources.get( source ); + + if ( webglTextures ) { + + const webglTexture = webglTextures[ textureProperties.__cacheKey ]; + webglTexture.usedTimes --; + + // the WebGLTexture object is not used anymore, remove it + + if ( webglTexture.usedTimes === 0 ) { + + deleteTexture( texture ); + + } + + // remove the weak map entry if no WebGLTexture uses the source anymore + + if ( Object.keys( webglTextures ).length === 0 ) { + + _sources.delete( source ); + + } + + } + + properties.remove( texture ); + + } + + function deleteTexture( texture ) { + + const textureProperties = properties.get( texture ); + _gl.deleteTexture( textureProperties.__webglTexture ); + + const source = texture.source; + const webglTextures = _sources.get( source ); + delete webglTextures[ textureProperties.__cacheKey ]; + + info.memory.textures --; + + } + + function deallocateRenderTarget( renderTarget ) { + + const renderTargetProperties = properties.get( renderTarget ); + + if ( renderTarget.depthTexture ) { + + renderTarget.depthTexture.dispose(); + + } + + if ( renderTarget.isWebGLCubeRenderTarget ) { + + for ( let i = 0; i < 6; i ++ ) { + + if ( Array.isArray( renderTargetProperties.__webglFramebuffer[ i ] ) ) { + + for ( let level = 0; level < renderTargetProperties.__webglFramebuffer[ i ].length; level ++ ) _gl.deleteFramebuffer( renderTargetProperties.__webglFramebuffer[ i ][ level ] ); + + } else { + + _gl.deleteFramebuffer( renderTargetProperties.__webglFramebuffer[ i ] ); + + } + + if ( renderTargetProperties.__webglDepthbuffer ) _gl.deleteRenderbuffer( renderTargetProperties.__webglDepthbuffer[ i ] ); + + } + + } else { + + if ( Array.isArray( renderTargetProperties.__webglFramebuffer ) ) { + + for ( let level = 0; level < renderTargetProperties.__webglFramebuffer.length; level ++ ) _gl.deleteFramebuffer( renderTargetProperties.__webglFramebuffer[ level ] ); + + } else { + + _gl.deleteFramebuffer( renderTargetProperties.__webglFramebuffer ); + + } + + if ( renderTargetProperties.__webglDepthbuffer ) _gl.deleteRenderbuffer( renderTargetProperties.__webglDepthbuffer ); + if ( renderTargetProperties.__webglMultisampledFramebuffer ) _gl.deleteFramebuffer( renderTargetProperties.__webglMultisampledFramebuffer ); + + if ( renderTargetProperties.__webglColorRenderbuffer ) { + + for ( let i = 0; i < renderTargetProperties.__webglColorRenderbuffer.length; i ++ ) { + + if ( renderTargetProperties.__webglColorRenderbuffer[ i ] ) _gl.deleteRenderbuffer( renderTargetProperties.__webglColorRenderbuffer[ i ] ); + + } + + } + + if ( renderTargetProperties.__webglDepthRenderbuffer ) _gl.deleteRenderbuffer( renderTargetProperties.__webglDepthRenderbuffer ); + + } + + const textures = renderTarget.textures; + + for ( let i = 0, il = textures.length; i < il; i ++ ) { + + const attachmentProperties = properties.get( textures[ i ] ); + + if ( attachmentProperties.__webglTexture ) { + + _gl.deleteTexture( attachmentProperties.__webglTexture ); + + info.memory.textures --; + + } + + properties.remove( textures[ i ] ); + + } + + properties.remove( renderTarget ); + + } + + // + + let textureUnits = 0; + + function resetTextureUnits() { + + textureUnits = 0; + + } + + function allocateTextureUnit() { + + const textureUnit = textureUnits; + + if ( textureUnit >= capabilities.maxTextures ) { + + console.warn( 'THREE.WebGLTextures: Trying to use ' + textureUnit + ' texture units while this GPU supports only ' + capabilities.maxTextures ); + + } + + textureUnits += 1; + + return textureUnit; + + } + + function getTextureCacheKey( texture ) { + + const array = []; + + array.push( texture.wrapS ); + array.push( texture.wrapT ); + array.push( texture.wrapR || 0 ); + array.push( texture.magFilter ); + array.push( texture.minFilter ); + array.push( texture.anisotropy ); + array.push( texture.internalFormat ); + array.push( texture.format ); + array.push( texture.type ); + array.push( texture.generateMipmaps ); + array.push( texture.premultiplyAlpha ); + array.push( texture.flipY ); + array.push( texture.unpackAlignment ); + array.push( texture.colorSpace ); + + return array.join(); + + } + + // + + function setTexture2D( texture, slot ) { + + const textureProperties = properties.get( texture ); + + if ( texture.isVideoTexture ) updateVideoTexture( texture ); + + if ( texture.isRenderTargetTexture === false && texture.version > 0 && textureProperties.__version !== texture.version ) { + + const image = texture.image; + + if ( image === null ) { + + console.warn( 'THREE.WebGLRenderer: Texture marked for update but no image data found.' ); + + } else if ( image.complete === false ) { + + console.warn( 'THREE.WebGLRenderer: Texture marked for update but image is incomplete' ); + + } else { + + uploadTexture( textureProperties, texture, slot ); + return; + + } + + } + + state.bindTexture( _gl.TEXTURE_2D, textureProperties.__webglTexture, _gl.TEXTURE0 + slot ); + + } + + function setTexture2DArray( texture, slot ) { + + const textureProperties = properties.get( texture ); + + if ( texture.version > 0 && textureProperties.__version !== texture.version ) { + + uploadTexture( textureProperties, texture, slot ); + return; + + } + + state.bindTexture( _gl.TEXTURE_2D_ARRAY, textureProperties.__webglTexture, _gl.TEXTURE0 + slot ); + + } + + function setTexture3D( texture, slot ) { + + const textureProperties = properties.get( texture ); + + if ( texture.version > 0 && textureProperties.__version !== texture.version ) { + + uploadTexture( textureProperties, texture, slot ); + return; + + } + + state.bindTexture( _gl.TEXTURE_3D, textureProperties.__webglTexture, _gl.TEXTURE0 + slot ); + + } + + function setTextureCube( texture, slot ) { + + const textureProperties = properties.get( texture ); + + if ( texture.version > 0 && textureProperties.__version !== texture.version ) { + + uploadCubeTexture( textureProperties, texture, slot ); + return; + + } + + state.bindTexture( _gl.TEXTURE_CUBE_MAP, textureProperties.__webglTexture, _gl.TEXTURE0 + slot ); + + } + + const wrappingToGL = { + [ RepeatWrapping ]: _gl.REPEAT, + [ ClampToEdgeWrapping ]: _gl.CLAMP_TO_EDGE, + [ MirroredRepeatWrapping ]: _gl.MIRRORED_REPEAT + }; + + const filterToGL = { + [ NearestFilter ]: _gl.NEAREST, + [ NearestMipmapNearestFilter ]: _gl.NEAREST_MIPMAP_NEAREST, + [ NearestMipmapLinearFilter ]: _gl.NEAREST_MIPMAP_LINEAR, + + [ LinearFilter ]: _gl.LINEAR, + [ LinearMipmapNearestFilter ]: _gl.LINEAR_MIPMAP_NEAREST, + [ LinearMipmapLinearFilter ]: _gl.LINEAR_MIPMAP_LINEAR + }; + + const compareToGL = { + [ NeverCompare ]: _gl.NEVER, + [ AlwaysCompare ]: _gl.ALWAYS, + [ LessCompare ]: _gl.LESS, + [ LessEqualCompare ]: _gl.LEQUAL, + [ EqualCompare ]: _gl.EQUAL, + [ GreaterEqualCompare ]: _gl.GEQUAL, + [ GreaterCompare ]: _gl.GREATER, + [ NotEqualCompare ]: _gl.NOTEQUAL + }; + + function setTextureParameters( textureType, texture ) { + + if ( texture.type === FloatType && extensions.has( 'OES_texture_float_linear' ) === false && + ( texture.magFilter === LinearFilter || texture.magFilter === LinearMipmapNearestFilter || texture.magFilter === NearestMipmapLinearFilter || texture.magFilter === LinearMipmapLinearFilter || + texture.minFilter === LinearFilter || texture.minFilter === LinearMipmapNearestFilter || texture.minFilter === NearestMipmapLinearFilter || texture.minFilter === LinearMipmapLinearFilter ) ) { + + console.warn( 'THREE.WebGLRenderer: Unable to use linear filtering with floating point textures. OES_texture_float_linear not supported on this device.' ); + + } + + _gl.texParameteri( textureType, _gl.TEXTURE_WRAP_S, wrappingToGL[ texture.wrapS ] ); + _gl.texParameteri( textureType, _gl.TEXTURE_WRAP_T, wrappingToGL[ texture.wrapT ] ); + + if ( textureType === _gl.TEXTURE_3D || textureType === _gl.TEXTURE_2D_ARRAY ) { + + _gl.texParameteri( textureType, _gl.TEXTURE_WRAP_R, wrappingToGL[ texture.wrapR ] ); + + } + + _gl.texParameteri( textureType, _gl.TEXTURE_MAG_FILTER, filterToGL[ texture.magFilter ] ); + _gl.texParameteri( textureType, _gl.TEXTURE_MIN_FILTER, filterToGL[ texture.minFilter ] ); + + if ( texture.compareFunction ) { + + _gl.texParameteri( textureType, _gl.TEXTURE_COMPARE_MODE, _gl.COMPARE_REF_TO_TEXTURE ); + _gl.texParameteri( textureType, _gl.TEXTURE_COMPARE_FUNC, compareToGL[ texture.compareFunction ] ); + + } + + if ( extensions.has( 'EXT_texture_filter_anisotropic' ) === true ) { + + if ( texture.magFilter === NearestFilter ) return; + if ( texture.minFilter !== NearestMipmapLinearFilter && texture.minFilter !== LinearMipmapLinearFilter ) return; + if ( texture.type === FloatType && extensions.has( 'OES_texture_float_linear' ) === false ) return; // verify extension + + if ( texture.anisotropy > 1 || properties.get( texture ).__currentAnisotropy ) { + + const extension = extensions.get( 'EXT_texture_filter_anisotropic' ); + _gl.texParameterf( textureType, extension.TEXTURE_MAX_ANISOTROPY_EXT, Math.min( texture.anisotropy, capabilities.getMaxAnisotropy() ) ); + properties.get( texture ).__currentAnisotropy = texture.anisotropy; + + } + + } + + } + + function initTexture( textureProperties, texture ) { + + let forceUpload = false; + + if ( textureProperties.__webglInit === undefined ) { + + textureProperties.__webglInit = true; + + texture.addEventListener( 'dispose', onTextureDispose ); + + } + + // create Source <-> WebGLTextures mapping if necessary + + const source = texture.source; + let webglTextures = _sources.get( source ); + + if ( webglTextures === undefined ) { + + webglTextures = {}; + _sources.set( source, webglTextures ); + + } + + // check if there is already a WebGLTexture object for the given texture parameters + + const textureCacheKey = getTextureCacheKey( texture ); + + if ( textureCacheKey !== textureProperties.__cacheKey ) { + + // if not, create a new instance of WebGLTexture + + if ( webglTextures[ textureCacheKey ] === undefined ) { + + // create new entry + + webglTextures[ textureCacheKey ] = { + texture: _gl.createTexture(), + usedTimes: 0 + }; + + info.memory.textures ++; + + // when a new instance of WebGLTexture was created, a texture upload is required + // even if the image contents are identical + + forceUpload = true; + + } + + webglTextures[ textureCacheKey ].usedTimes ++; + + // every time the texture cache key changes, it's necessary to check if an instance of + // WebGLTexture can be deleted in order to avoid a memory leak. + + const webglTexture = webglTextures[ textureProperties.__cacheKey ]; + + if ( webglTexture !== undefined ) { + + webglTextures[ textureProperties.__cacheKey ].usedTimes --; + + if ( webglTexture.usedTimes === 0 ) { + + deleteTexture( texture ); + + } + + } + + // store references to cache key and WebGLTexture object + + textureProperties.__cacheKey = textureCacheKey; + textureProperties.__webglTexture = webglTextures[ textureCacheKey ].texture; + + } + + return forceUpload; + + } + + function uploadTexture( textureProperties, texture, slot ) { + + let textureType = _gl.TEXTURE_2D; + + if ( texture.isDataArrayTexture || texture.isCompressedArrayTexture ) textureType = _gl.TEXTURE_2D_ARRAY; + if ( texture.isData3DTexture ) textureType = _gl.TEXTURE_3D; + + const forceUpload = initTexture( textureProperties, texture ); + const source = texture.source; + + state.bindTexture( textureType, textureProperties.__webglTexture, _gl.TEXTURE0 + slot ); + + const sourceProperties = properties.get( source ); + + if ( source.version !== sourceProperties.__version || forceUpload === true ) { + + state.activeTexture( _gl.TEXTURE0 + slot ); + + const workingPrimaries = ColorManagement.getPrimaries( ColorManagement.workingColorSpace ); + const texturePrimaries = texture.colorSpace === NoColorSpace ? null : ColorManagement.getPrimaries( texture.colorSpace ); + const unpackConversion = texture.colorSpace === NoColorSpace || workingPrimaries === texturePrimaries ? _gl.NONE : _gl.BROWSER_DEFAULT_WEBGL; + + _gl.pixelStorei( _gl.UNPACK_FLIP_Y_WEBGL, texture.flipY ); + _gl.pixelStorei( _gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, texture.premultiplyAlpha ); + _gl.pixelStorei( _gl.UNPACK_ALIGNMENT, texture.unpackAlignment ); + _gl.pixelStorei( _gl.UNPACK_COLORSPACE_CONVERSION_WEBGL, unpackConversion ); + + let image = resizeImage( texture.image, false, capabilities.maxTextureSize ); + image = verifyColorSpace( texture, image ); + + const glFormat = utils.convert( texture.format, texture.colorSpace ); + + const glType = utils.convert( texture.type ); + let glInternalFormat = getInternalFormat( texture.internalFormat, glFormat, glType, texture.colorSpace, texture.isVideoTexture ); + + setTextureParameters( textureType, texture ); + + let mipmap; + const mipmaps = texture.mipmaps; + + const useTexStorage = ( texture.isVideoTexture !== true ); + const allocateMemory = ( sourceProperties.__version === undefined ) || ( forceUpload === true ); + const dataReady = source.dataReady; + const levels = getMipLevels( texture, image ); + + if ( texture.isDepthTexture ) { + + glInternalFormat = getInternalDepthFormat( texture.format === DepthStencilFormat, texture.type ); + + // + + if ( allocateMemory ) { + + if ( useTexStorage ) { + + state.texStorage2D( _gl.TEXTURE_2D, 1, glInternalFormat, image.width, image.height ); + + } else { + + state.texImage2D( _gl.TEXTURE_2D, 0, glInternalFormat, image.width, image.height, 0, glFormat, glType, null ); + + } + + } + + } else if ( texture.isDataTexture ) { + + // use manually created mipmaps if available + // if there are no manual mipmaps + // set 0 level mipmap and then use GL to generate other mipmap levels + + if ( mipmaps.length > 0 ) { + + if ( useTexStorage && allocateMemory ) { + + state.texStorage2D( _gl.TEXTURE_2D, levels, glInternalFormat, mipmaps[ 0 ].width, mipmaps[ 0 ].height ); + + } + + for ( let i = 0, il = mipmaps.length; i < il; i ++ ) { + + mipmap = mipmaps[ i ]; + + if ( useTexStorage ) { + + if ( dataReady ) { + + state.texSubImage2D( _gl.TEXTURE_2D, i, 0, 0, mipmap.width, mipmap.height, glFormat, glType, mipmap.data ); + + } + + } else { + + state.texImage2D( _gl.TEXTURE_2D, i, glInternalFormat, mipmap.width, mipmap.height, 0, glFormat, glType, mipmap.data ); + + } + + } + + texture.generateMipmaps = false; + + } else { + + if ( useTexStorage ) { + + if ( allocateMemory ) { + + state.texStorage2D( _gl.TEXTURE_2D, levels, glInternalFormat, image.width, image.height ); + + } + + if ( dataReady ) { + + state.texSubImage2D( _gl.TEXTURE_2D, 0, 0, 0, image.width, image.height, glFormat, glType, image.data ); + + } + + } else { + + state.texImage2D( _gl.TEXTURE_2D, 0, glInternalFormat, image.width, image.height, 0, glFormat, glType, image.data ); + + } + + } + + } else if ( texture.isCompressedTexture ) { + + if ( texture.isCompressedArrayTexture ) { + + if ( useTexStorage && allocateMemory ) { + + state.texStorage3D( _gl.TEXTURE_2D_ARRAY, levels, glInternalFormat, mipmaps[ 0 ].width, mipmaps[ 0 ].height, image.depth ); + + } + + for ( let i = 0, il = mipmaps.length; i < il; i ++ ) { + + mipmap = mipmaps[ i ]; + + if ( texture.format !== RGBAFormat ) { + + if ( glFormat !== null ) { + + if ( useTexStorage ) { + + if ( dataReady ) { + + if ( texture.layerUpdates.size > 0 ) { + + for ( const layerIndex of texture.layerUpdates ) { + + const layerSize = mipmap.width * mipmap.height; + state.compressedTexSubImage3D( _gl.TEXTURE_2D_ARRAY, i, 0, 0, layerIndex, mipmap.width, mipmap.height, 1, glFormat, mipmap.data.slice( layerSize * layerIndex, layerSize * ( layerIndex + 1 ) ), 0, 0 ); + + } + + texture.clearLayerUpdates(); + + } else { + + state.compressedTexSubImage3D( _gl.TEXTURE_2D_ARRAY, i, 0, 0, 0, mipmap.width, mipmap.height, image.depth, glFormat, mipmap.data, 0, 0 ); + + } + + } + + } else { + + state.compressedTexImage3D( _gl.TEXTURE_2D_ARRAY, i, glInternalFormat, mipmap.width, mipmap.height, image.depth, 0, mipmap.data, 0, 0 ); + + } + + } else { + + console.warn( 'THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .uploadTexture()' ); + + } + + } else { + + if ( useTexStorage ) { + + if ( dataReady ) { + + state.texSubImage3D( _gl.TEXTURE_2D_ARRAY, i, 0, 0, 0, mipmap.width, mipmap.height, image.depth, glFormat, glType, mipmap.data ); + + } + + } else { + + state.texImage3D( _gl.TEXTURE_2D_ARRAY, i, glInternalFormat, mipmap.width, mipmap.height, image.depth, 0, glFormat, glType, mipmap.data ); + + } + + } + + } + + } else { + + if ( useTexStorage && allocateMemory ) { + + state.texStorage2D( _gl.TEXTURE_2D, levels, glInternalFormat, mipmaps[ 0 ].width, mipmaps[ 0 ].height ); + + } + + for ( let i = 0, il = mipmaps.length; i < il; i ++ ) { + + mipmap = mipmaps[ i ]; + + if ( texture.format !== RGBAFormat ) { + + if ( glFormat !== null ) { + + if ( useTexStorage ) { + + if ( dataReady ) { + + state.compressedTexSubImage2D( _gl.TEXTURE_2D, i, 0, 0, mipmap.width, mipmap.height, glFormat, mipmap.data ); + + } + + } else { + + state.compressedTexImage2D( _gl.TEXTURE_2D, i, glInternalFormat, mipmap.width, mipmap.height, 0, mipmap.data ); + + } + + } else { + + console.warn( 'THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .uploadTexture()' ); + + } + + } else { + + if ( useTexStorage ) { + + if ( dataReady ) { + + state.texSubImage2D( _gl.TEXTURE_2D, i, 0, 0, mipmap.width, mipmap.height, glFormat, glType, mipmap.data ); + + } + + } else { + + state.texImage2D( _gl.TEXTURE_2D, i, glInternalFormat, mipmap.width, mipmap.height, 0, glFormat, glType, mipmap.data ); + + } + + } + + } + + } + + } else if ( texture.isDataArrayTexture ) { + + if ( useTexStorage ) { + + if ( allocateMemory ) { + + state.texStorage3D( _gl.TEXTURE_2D_ARRAY, levels, glInternalFormat, image.width, image.height, image.depth ); + + } + + if ( dataReady ) { + + if ( texture.layerUpdates.size > 0 ) { + + // When type is GL_UNSIGNED_BYTE, each of these bytes is + // interpreted as one color component, depending on format. When + // type is one of GL_UNSIGNED_SHORT_5_6_5, + // GL_UNSIGNED_SHORT_4_4_4_4, GL_UNSIGNED_SHORT_5_5_5_1, each + // unsigned value is interpreted as containing all the components + // for a single pixel, with the color components arranged + // according to format. + // + // See https://registry.khronos.org/OpenGL-Refpages/es1.1/xhtml/glTexImage2D.xml + let texelSize; + switch ( glType ) { + + case _gl.UNSIGNED_BYTE: + switch ( glFormat ) { + + case _gl.ALPHA: + texelSize = 1; + break; + case _gl.LUMINANCE: + texelSize = 1; + break; + case _gl.LUMINANCE_ALPHA: + texelSize = 2; + break; + case _gl.RGB: + texelSize = 3; + break; + case _gl.RGBA: + texelSize = 4; + break; + + default: + throw new Error( `Unknown texel size for format ${glFormat}.` ); + + } + + break; + + case _gl.UNSIGNED_SHORT_4_4_4_4: + case _gl.UNSIGNED_SHORT_5_5_5_1: + case _gl.UNSIGNED_SHORT_5_6_5: + texelSize = 1; + break; + + default: + throw new Error( `Unknown texel size for type ${glType}.` ); + + } + + const layerSize = image.width * image.height * texelSize; + + for ( const layerIndex of texture.layerUpdates ) { + + state.texSubImage3D( _gl.TEXTURE_2D_ARRAY, 0, 0, 0, layerIndex, image.width, image.height, 1, glFormat, glType, image.data.slice( layerSize * layerIndex, layerSize * ( layerIndex + 1 ) ) ); + + } + + texture.clearLayerUpdates(); + + } else { + + state.texSubImage3D( _gl.TEXTURE_2D_ARRAY, 0, 0, 0, 0, image.width, image.height, image.depth, glFormat, glType, image.data ); + + } + + } + + } else { + + state.texImage3D( _gl.TEXTURE_2D_ARRAY, 0, glInternalFormat, image.width, image.height, image.depth, 0, glFormat, glType, image.data ); + + } + + } else if ( texture.isData3DTexture ) { + + if ( useTexStorage ) { + + if ( allocateMemory ) { + + state.texStorage3D( _gl.TEXTURE_3D, levels, glInternalFormat, image.width, image.height, image.depth ); + + } + + if ( dataReady ) { + + state.texSubImage3D( _gl.TEXTURE_3D, 0, 0, 0, 0, image.width, image.height, image.depth, glFormat, glType, image.data ); + + } + + } else { + + state.texImage3D( _gl.TEXTURE_3D, 0, glInternalFormat, image.width, image.height, image.depth, 0, glFormat, glType, image.data ); + + } + + } else if ( texture.isFramebufferTexture ) { + + if ( allocateMemory ) { + + if ( useTexStorage ) { + + state.texStorage2D( _gl.TEXTURE_2D, levels, glInternalFormat, image.width, image.height ); + + } else { + + let width = image.width, height = image.height; + + for ( let i = 0; i < levels; i ++ ) { + + state.texImage2D( _gl.TEXTURE_2D, i, glInternalFormat, width, height, 0, glFormat, glType, null ); + + width >>= 1; + height >>= 1; + + } + + } + + } + + } else { + + // regular Texture (image, video, canvas) + + // use manually created mipmaps if available + // if there are no manual mipmaps + // set 0 level mipmap and then use GL to generate other mipmap levels + + if ( mipmaps.length > 0 ) { + + if ( useTexStorage && allocateMemory ) { + + const dimensions = getDimensions( mipmaps[ 0 ] ); + + state.texStorage2D( _gl.TEXTURE_2D, levels, glInternalFormat, dimensions.width, dimensions.height ); + + } + + for ( let i = 0, il = mipmaps.length; i < il; i ++ ) { + + mipmap = mipmaps[ i ]; + + if ( useTexStorage ) { + + if ( dataReady ) { + + state.texSubImage2D( _gl.TEXTURE_2D, i, 0, 0, glFormat, glType, mipmap ); + + } + + } else { + + state.texImage2D( _gl.TEXTURE_2D, i, glInternalFormat, glFormat, glType, mipmap ); + + } + + } + + texture.generateMipmaps = false; + + } else { + + if ( useTexStorage ) { + + if ( allocateMemory ) { + + const dimensions = getDimensions( image ); + + state.texStorage2D( _gl.TEXTURE_2D, levels, glInternalFormat, dimensions.width, dimensions.height ); + + } + + if ( dataReady ) { + + state.texSubImage2D( _gl.TEXTURE_2D, 0, 0, 0, glFormat, glType, image ); + + } + + } else { + + state.texImage2D( _gl.TEXTURE_2D, 0, glInternalFormat, glFormat, glType, image ); + + } + + } + + } + + if ( textureNeedsGenerateMipmaps( texture ) ) { + + generateMipmap( textureType ); + + } + + sourceProperties.__version = source.version; + + if ( texture.onUpdate ) texture.onUpdate( texture ); + + } + + textureProperties.__version = texture.version; + + } + + function uploadCubeTexture( textureProperties, texture, slot ) { + + if ( texture.image.length !== 6 ) return; + + const forceUpload = initTexture( textureProperties, texture ); + const source = texture.source; + + state.bindTexture( _gl.TEXTURE_CUBE_MAP, textureProperties.__webglTexture, _gl.TEXTURE0 + slot ); + + const sourceProperties = properties.get( source ); + + if ( source.version !== sourceProperties.__version || forceUpload === true ) { + + state.activeTexture( _gl.TEXTURE0 + slot ); + + const workingPrimaries = ColorManagement.getPrimaries( ColorManagement.workingColorSpace ); + const texturePrimaries = texture.colorSpace === NoColorSpace ? null : ColorManagement.getPrimaries( texture.colorSpace ); + const unpackConversion = texture.colorSpace === NoColorSpace || workingPrimaries === texturePrimaries ? _gl.NONE : _gl.BROWSER_DEFAULT_WEBGL; + + _gl.pixelStorei( _gl.UNPACK_FLIP_Y_WEBGL, texture.flipY ); + _gl.pixelStorei( _gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, texture.premultiplyAlpha ); + _gl.pixelStorei( _gl.UNPACK_ALIGNMENT, texture.unpackAlignment ); + _gl.pixelStorei( _gl.UNPACK_COLORSPACE_CONVERSION_WEBGL, unpackConversion ); + + const isCompressed = ( texture.isCompressedTexture || texture.image[ 0 ].isCompressedTexture ); + const isDataTexture = ( texture.image[ 0 ] && texture.image[ 0 ].isDataTexture ); + + const cubeImage = []; + + for ( let i = 0; i < 6; i ++ ) { + + if ( ! isCompressed && ! isDataTexture ) { + + cubeImage[ i ] = resizeImage( texture.image[ i ], true, capabilities.maxCubemapSize ); + + } else { + + cubeImage[ i ] = isDataTexture ? texture.image[ i ].image : texture.image[ i ]; + + } + + cubeImage[ i ] = verifyColorSpace( texture, cubeImage[ i ] ); + + } + + const image = cubeImage[ 0 ], + glFormat = utils.convert( texture.format, texture.colorSpace ), + glType = utils.convert( texture.type ), + glInternalFormat = getInternalFormat( texture.internalFormat, glFormat, glType, texture.colorSpace ); + + const useTexStorage = ( texture.isVideoTexture !== true ); + const allocateMemory = ( sourceProperties.__version === undefined ) || ( forceUpload === true ); + const dataReady = source.dataReady; + let levels = getMipLevels( texture, image ); + + setTextureParameters( _gl.TEXTURE_CUBE_MAP, texture ); + + let mipmaps; + + if ( isCompressed ) { + + if ( useTexStorage && allocateMemory ) { + + state.texStorage2D( _gl.TEXTURE_CUBE_MAP, levels, glInternalFormat, image.width, image.height ); + + } + + for ( let i = 0; i < 6; i ++ ) { + + mipmaps = cubeImage[ i ].mipmaps; + + for ( let j = 0; j < mipmaps.length; j ++ ) { + + const mipmap = mipmaps[ j ]; + + if ( texture.format !== RGBAFormat ) { + + if ( glFormat !== null ) { + + if ( useTexStorage ) { + + if ( dataReady ) { + + state.compressedTexSubImage2D( _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j, 0, 0, mipmap.width, mipmap.height, glFormat, mipmap.data ); + + } + + } else { + + state.compressedTexImage2D( _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j, glInternalFormat, mipmap.width, mipmap.height, 0, mipmap.data ); + + } + + } else { + + console.warn( 'THREE.WebGLRenderer: Attempt to load unsupported compressed texture format in .setTextureCube()' ); + + } + + } else { + + if ( useTexStorage ) { + + if ( dataReady ) { + + state.texSubImage2D( _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j, 0, 0, mipmap.width, mipmap.height, glFormat, glType, mipmap.data ); + + } + + } else { + + state.texImage2D( _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j, glInternalFormat, mipmap.width, mipmap.height, 0, glFormat, glType, mipmap.data ); + + } + + } + + } + + } + + } else { + + mipmaps = texture.mipmaps; + + if ( useTexStorage && allocateMemory ) { + + // TODO: Uniformly handle mipmap definitions + // Normal textures and compressed cube textures define base level + mips with their mipmap array + // Uncompressed cube textures use their mipmap array only for mips (no base level) + + if ( mipmaps.length > 0 ) levels ++; + + const dimensions = getDimensions( cubeImage[ 0 ] ); + + state.texStorage2D( _gl.TEXTURE_CUBE_MAP, levels, glInternalFormat, dimensions.width, dimensions.height ); + + } + + for ( let i = 0; i < 6; i ++ ) { + + if ( isDataTexture ) { + + if ( useTexStorage ) { + + if ( dataReady ) { + + state.texSubImage2D( _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, 0, 0, 0, cubeImage[ i ].width, cubeImage[ i ].height, glFormat, glType, cubeImage[ i ].data ); + + } + + } else { + + state.texImage2D( _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, 0, glInternalFormat, cubeImage[ i ].width, cubeImage[ i ].height, 0, glFormat, glType, cubeImage[ i ].data ); + + } + + for ( let j = 0; j < mipmaps.length; j ++ ) { + + const mipmap = mipmaps[ j ]; + const mipmapImage = mipmap.image[ i ].image; + + if ( useTexStorage ) { + + if ( dataReady ) { + + state.texSubImage2D( _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j + 1, 0, 0, mipmapImage.width, mipmapImage.height, glFormat, glType, mipmapImage.data ); + + } + + } else { + + state.texImage2D( _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j + 1, glInternalFormat, mipmapImage.width, mipmapImage.height, 0, glFormat, glType, mipmapImage.data ); + + } + + } + + } else { + + if ( useTexStorage ) { + + if ( dataReady ) { + + state.texSubImage2D( _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, 0, 0, 0, glFormat, glType, cubeImage[ i ] ); + + } + + } else { + + state.texImage2D( _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, 0, glInternalFormat, glFormat, glType, cubeImage[ i ] ); + + } + + for ( let j = 0; j < mipmaps.length; j ++ ) { + + const mipmap = mipmaps[ j ]; + + if ( useTexStorage ) { + + if ( dataReady ) { + + state.texSubImage2D( _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j + 1, 0, 0, glFormat, glType, mipmap.image[ i ] ); + + } + + } else { + + state.texImage2D( _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, j + 1, glInternalFormat, glFormat, glType, mipmap.image[ i ] ); + + } + + } + + } + + } + + } + + if ( textureNeedsGenerateMipmaps( texture ) ) { + + // We assume images for cube map have the same size. + generateMipmap( _gl.TEXTURE_CUBE_MAP ); + + } + + sourceProperties.__version = source.version; + + if ( texture.onUpdate ) texture.onUpdate( texture ); + + } + + textureProperties.__version = texture.version; + + } + + // Render targets + + // Setup storage for target texture and bind it to correct framebuffer + function setupFrameBufferTexture( framebuffer, renderTarget, texture, attachment, textureTarget, level ) { + + const glFormat = utils.convert( texture.format, texture.colorSpace ); + const glType = utils.convert( texture.type ); + const glInternalFormat = getInternalFormat( texture.internalFormat, glFormat, glType, texture.colorSpace ); + const renderTargetProperties = properties.get( renderTarget ); + + if ( ! renderTargetProperties.__hasExternalTextures ) { + + const width = Math.max( 1, renderTarget.width >> level ); + const height = Math.max( 1, renderTarget.height >> level ); + + if ( textureTarget === _gl.TEXTURE_3D || textureTarget === _gl.TEXTURE_2D_ARRAY ) { + + state.texImage3D( textureTarget, level, glInternalFormat, width, height, renderTarget.depth, 0, glFormat, glType, null ); + + } else { + + state.texImage2D( textureTarget, level, glInternalFormat, width, height, 0, glFormat, glType, null ); + + } + + } + + state.bindFramebuffer( _gl.FRAMEBUFFER, framebuffer ); + + if ( useMultisampledRTT( renderTarget ) ) { + + multisampledRTTExt.framebufferTexture2DMultisampleEXT( _gl.FRAMEBUFFER, attachment, textureTarget, properties.get( texture ).__webglTexture, 0, getRenderTargetSamples( renderTarget ) ); + + } else if ( textureTarget === _gl.TEXTURE_2D || ( textureTarget >= _gl.TEXTURE_CUBE_MAP_POSITIVE_X && textureTarget <= _gl.TEXTURE_CUBE_MAP_NEGATIVE_Z ) ) { // see #24753 + + _gl.framebufferTexture2D( _gl.FRAMEBUFFER, attachment, textureTarget, properties.get( texture ).__webglTexture, level ); + + } + + state.bindFramebuffer( _gl.FRAMEBUFFER, null ); + + } + + // Setup storage for internal depth/stencil buffers and bind to correct framebuffer + function setupRenderBufferStorage( renderbuffer, renderTarget, isMultisample ) { + + _gl.bindRenderbuffer( _gl.RENDERBUFFER, renderbuffer ); + + if ( renderTarget.depthBuffer ) { + + // retrieve the depth attachment types + const depthTexture = renderTarget.depthTexture; + const depthType = depthTexture && depthTexture.isDepthTexture ? depthTexture.type : null; + const glInternalFormat = getInternalDepthFormat( renderTarget.stencilBuffer, depthType ); + const glAttachmentType = renderTarget.stencilBuffer ? _gl.DEPTH_STENCIL_ATTACHMENT : _gl.DEPTH_ATTACHMENT; + + // set up the attachment + const samples = getRenderTargetSamples( renderTarget ); + const isUseMultisampledRTT = useMultisampledRTT( renderTarget ); + if ( isUseMultisampledRTT ) { + + multisampledRTTExt.renderbufferStorageMultisampleEXT( _gl.RENDERBUFFER, samples, glInternalFormat, renderTarget.width, renderTarget.height ); + + } else if ( isMultisample ) { + + _gl.renderbufferStorageMultisample( _gl.RENDERBUFFER, samples, glInternalFormat, renderTarget.width, renderTarget.height ); + + } else { + + _gl.renderbufferStorage( _gl.RENDERBUFFER, glInternalFormat, renderTarget.width, renderTarget.height ); + + } + + _gl.framebufferRenderbuffer( _gl.FRAMEBUFFER, glAttachmentType, _gl.RENDERBUFFER, renderbuffer ); + + } else { + + const textures = renderTarget.textures; + + for ( let i = 0; i < textures.length; i ++ ) { + + const texture = textures[ i ]; + + const glFormat = utils.convert( texture.format, texture.colorSpace ); + const glType = utils.convert( texture.type ); + const glInternalFormat = getInternalFormat( texture.internalFormat, glFormat, glType, texture.colorSpace ); + const samples = getRenderTargetSamples( renderTarget ); + + if ( isMultisample && useMultisampledRTT( renderTarget ) === false ) { + + _gl.renderbufferStorageMultisample( _gl.RENDERBUFFER, samples, glInternalFormat, renderTarget.width, renderTarget.height ); + + } else if ( useMultisampledRTT( renderTarget ) ) { + + multisampledRTTExt.renderbufferStorageMultisampleEXT( _gl.RENDERBUFFER, samples, glInternalFormat, renderTarget.width, renderTarget.height ); + + } else { + + _gl.renderbufferStorage( _gl.RENDERBUFFER, glInternalFormat, renderTarget.width, renderTarget.height ); + + } + + } + + } + + _gl.bindRenderbuffer( _gl.RENDERBUFFER, null ); + + } + + // Setup resources for a Depth Texture for a FBO (needs an extension) + function setupDepthTexture( framebuffer, renderTarget ) { + + const isCube = ( renderTarget && renderTarget.isWebGLCubeRenderTarget ); + if ( isCube ) throw new Error( 'Depth Texture with cube render targets is not supported' ); + + state.bindFramebuffer( _gl.FRAMEBUFFER, framebuffer ); + + if ( ! ( renderTarget.depthTexture && renderTarget.depthTexture.isDepthTexture ) ) { + + throw new Error( 'renderTarget.depthTexture must be an instance of THREE.DepthTexture' ); + + } + + // upload an empty depth texture with framebuffer size + if ( ! properties.get( renderTarget.depthTexture ).__webglTexture || + renderTarget.depthTexture.image.width !== renderTarget.width || + renderTarget.depthTexture.image.height !== renderTarget.height ) { + + renderTarget.depthTexture.image.width = renderTarget.width; + renderTarget.depthTexture.image.height = renderTarget.height; + renderTarget.depthTexture.needsUpdate = true; + + } + + setTexture2D( renderTarget.depthTexture, 0 ); + + const webglDepthTexture = properties.get( renderTarget.depthTexture ).__webglTexture; + const samples = getRenderTargetSamples( renderTarget ); + + if ( renderTarget.depthTexture.format === DepthFormat ) { + + if ( useMultisampledRTT( renderTarget ) ) { + + multisampledRTTExt.framebufferTexture2DMultisampleEXT( _gl.FRAMEBUFFER, _gl.DEPTH_ATTACHMENT, _gl.TEXTURE_2D, webglDepthTexture, 0, samples ); + + } else { + + _gl.framebufferTexture2D( _gl.FRAMEBUFFER, _gl.DEPTH_ATTACHMENT, _gl.TEXTURE_2D, webglDepthTexture, 0 ); + + } + + } else if ( renderTarget.depthTexture.format === DepthStencilFormat ) { + + if ( useMultisampledRTT( renderTarget ) ) { + + multisampledRTTExt.framebufferTexture2DMultisampleEXT( _gl.FRAMEBUFFER, _gl.DEPTH_STENCIL_ATTACHMENT, _gl.TEXTURE_2D, webglDepthTexture, 0, samples ); + + } else { + + _gl.framebufferTexture2D( _gl.FRAMEBUFFER, _gl.DEPTH_STENCIL_ATTACHMENT, _gl.TEXTURE_2D, webglDepthTexture, 0 ); + + } + + } else { + + throw new Error( 'Unknown depthTexture format' ); + + } + + } + + // Setup GL resources for a non-texture depth buffer + function setupDepthRenderbuffer( renderTarget ) { + + const renderTargetProperties = properties.get( renderTarget ); + const isCube = ( renderTarget.isWebGLCubeRenderTarget === true ); + + if ( renderTarget.depthTexture && ! renderTargetProperties.__autoAllocateDepthBuffer ) { + + if ( isCube ) throw new Error( 'target.depthTexture not supported in Cube render targets' ); + + setupDepthTexture( renderTargetProperties.__webglFramebuffer, renderTarget ); + + } else { + + if ( isCube ) { + + renderTargetProperties.__webglDepthbuffer = []; + + for ( let i = 0; i < 6; i ++ ) { + + state.bindFramebuffer( _gl.FRAMEBUFFER, renderTargetProperties.__webglFramebuffer[ i ] ); + renderTargetProperties.__webglDepthbuffer[ i ] = _gl.createRenderbuffer(); + setupRenderBufferStorage( renderTargetProperties.__webglDepthbuffer[ i ], renderTarget, false ); + + } + + } else { + + state.bindFramebuffer( _gl.FRAMEBUFFER, renderTargetProperties.__webglFramebuffer ); + renderTargetProperties.__webglDepthbuffer = _gl.createRenderbuffer(); + setupRenderBufferStorage( renderTargetProperties.__webglDepthbuffer, renderTarget, false ); + + } + + } + + state.bindFramebuffer( _gl.FRAMEBUFFER, null ); + + } + + // rebind framebuffer with external textures + function rebindTextures( renderTarget, colorTexture, depthTexture ) { + + const renderTargetProperties = properties.get( renderTarget ); + + if ( colorTexture !== undefined ) { + + setupFrameBufferTexture( renderTargetProperties.__webglFramebuffer, renderTarget, renderTarget.texture, _gl.COLOR_ATTACHMENT0, _gl.TEXTURE_2D, 0 ); + + } + + if ( depthTexture !== undefined ) { + + setupDepthRenderbuffer( renderTarget ); + + } + + } + + // Set up GL resources for the render target + function setupRenderTarget( renderTarget ) { + + const texture = renderTarget.texture; + + const renderTargetProperties = properties.get( renderTarget ); + const textureProperties = properties.get( texture ); + + renderTarget.addEventListener( 'dispose', onRenderTargetDispose ); + + const textures = renderTarget.textures; + + const isCube = ( renderTarget.isWebGLCubeRenderTarget === true ); + const isMultipleRenderTargets = ( textures.length > 1 ); + + if ( ! isMultipleRenderTargets ) { + + if ( textureProperties.__webglTexture === undefined ) { + + textureProperties.__webglTexture = _gl.createTexture(); + + } + + textureProperties.__version = texture.version; + info.memory.textures ++; + + } + + // Setup framebuffer + + if ( isCube ) { + + renderTargetProperties.__webglFramebuffer = []; + + for ( let i = 0; i < 6; i ++ ) { + + if ( texture.mipmaps && texture.mipmaps.length > 0 ) { + + renderTargetProperties.__webglFramebuffer[ i ] = []; + + for ( let level = 0; level < texture.mipmaps.length; level ++ ) { + + renderTargetProperties.__webglFramebuffer[ i ][ level ] = _gl.createFramebuffer(); + + } + + } else { + + renderTargetProperties.__webglFramebuffer[ i ] = _gl.createFramebuffer(); + + } + + } + + } else { + + if ( texture.mipmaps && texture.mipmaps.length > 0 ) { + + renderTargetProperties.__webglFramebuffer = []; + + for ( let level = 0; level < texture.mipmaps.length; level ++ ) { + + renderTargetProperties.__webglFramebuffer[ level ] = _gl.createFramebuffer(); + + } + + } else { + + renderTargetProperties.__webglFramebuffer = _gl.createFramebuffer(); + + } + + if ( isMultipleRenderTargets ) { + + for ( let i = 0, il = textures.length; i < il; i ++ ) { + + const attachmentProperties = properties.get( textures[ i ] ); + + if ( attachmentProperties.__webglTexture === undefined ) { + + attachmentProperties.__webglTexture = _gl.createTexture(); + + info.memory.textures ++; + + } + + } + + } + + if ( ( renderTarget.samples > 0 ) && useMultisampledRTT( renderTarget ) === false ) { + + renderTargetProperties.__webglMultisampledFramebuffer = _gl.createFramebuffer(); + renderTargetProperties.__webglColorRenderbuffer = []; + + state.bindFramebuffer( _gl.FRAMEBUFFER, renderTargetProperties.__webglMultisampledFramebuffer ); + + for ( let i = 0; i < textures.length; i ++ ) { + + const texture = textures[ i ]; + renderTargetProperties.__webglColorRenderbuffer[ i ] = _gl.createRenderbuffer(); + + _gl.bindRenderbuffer( _gl.RENDERBUFFER, renderTargetProperties.__webglColorRenderbuffer[ i ] ); + + const glFormat = utils.convert( texture.format, texture.colorSpace ); + const glType = utils.convert( texture.type ); + const glInternalFormat = getInternalFormat( texture.internalFormat, glFormat, glType, texture.colorSpace, renderTarget.isXRRenderTarget === true ); + const samples = getRenderTargetSamples( renderTarget ); + _gl.renderbufferStorageMultisample( _gl.RENDERBUFFER, samples, glInternalFormat, renderTarget.width, renderTarget.height ); + + _gl.framebufferRenderbuffer( _gl.FRAMEBUFFER, _gl.COLOR_ATTACHMENT0 + i, _gl.RENDERBUFFER, renderTargetProperties.__webglColorRenderbuffer[ i ] ); + + } + + _gl.bindRenderbuffer( _gl.RENDERBUFFER, null ); + + if ( renderTarget.depthBuffer ) { + + renderTargetProperties.__webglDepthRenderbuffer = _gl.createRenderbuffer(); + setupRenderBufferStorage( renderTargetProperties.__webglDepthRenderbuffer, renderTarget, true ); + + } + + state.bindFramebuffer( _gl.FRAMEBUFFER, null ); + + } + + } + + // Setup color buffer + + if ( isCube ) { + + state.bindTexture( _gl.TEXTURE_CUBE_MAP, textureProperties.__webglTexture ); + setTextureParameters( _gl.TEXTURE_CUBE_MAP, texture ); + + for ( let i = 0; i < 6; i ++ ) { + + if ( texture.mipmaps && texture.mipmaps.length > 0 ) { + + for ( let level = 0; level < texture.mipmaps.length; level ++ ) { + + setupFrameBufferTexture( renderTargetProperties.__webglFramebuffer[ i ][ level ], renderTarget, texture, _gl.COLOR_ATTACHMENT0, _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, level ); + + } + + } else { + + setupFrameBufferTexture( renderTargetProperties.__webglFramebuffer[ i ], renderTarget, texture, _gl.COLOR_ATTACHMENT0, _gl.TEXTURE_CUBE_MAP_POSITIVE_X + i, 0 ); + + } + + } + + if ( textureNeedsGenerateMipmaps( texture ) ) { + + generateMipmap( _gl.TEXTURE_CUBE_MAP ); + + } + + state.unbindTexture(); + + } else if ( isMultipleRenderTargets ) { + + for ( let i = 0, il = textures.length; i < il; i ++ ) { + + const attachment = textures[ i ]; + const attachmentProperties = properties.get( attachment ); + + state.bindTexture( _gl.TEXTURE_2D, attachmentProperties.__webglTexture ); + setTextureParameters( _gl.TEXTURE_2D, attachment ); + setupFrameBufferTexture( renderTargetProperties.__webglFramebuffer, renderTarget, attachment, _gl.COLOR_ATTACHMENT0 + i, _gl.TEXTURE_2D, 0 ); + + if ( textureNeedsGenerateMipmaps( attachment ) ) { + + generateMipmap( _gl.TEXTURE_2D ); + + } + + } + + state.unbindTexture(); + + } else { + + let glTextureType = _gl.TEXTURE_2D; + + if ( renderTarget.isWebGL3DRenderTarget || renderTarget.isWebGLArrayRenderTarget ) { + + glTextureType = renderTarget.isWebGL3DRenderTarget ? _gl.TEXTURE_3D : _gl.TEXTURE_2D_ARRAY; + + } + + state.bindTexture( glTextureType, textureProperties.__webglTexture ); + setTextureParameters( glTextureType, texture ); + + if ( texture.mipmaps && texture.mipmaps.length > 0 ) { + + for ( let level = 0; level < texture.mipmaps.length; level ++ ) { + + setupFrameBufferTexture( renderTargetProperties.__webglFramebuffer[ level ], renderTarget, texture, _gl.COLOR_ATTACHMENT0, glTextureType, level ); + + } + + } else { + + setupFrameBufferTexture( renderTargetProperties.__webglFramebuffer, renderTarget, texture, _gl.COLOR_ATTACHMENT0, glTextureType, 0 ); + + } + + if ( textureNeedsGenerateMipmaps( texture ) ) { + + generateMipmap( glTextureType ); + + } + + state.unbindTexture(); + + } + + // Setup depth and stencil buffers + + if ( renderTarget.depthBuffer ) { + + setupDepthRenderbuffer( renderTarget ); + + } + + } + + function updateRenderTargetMipmap( renderTarget ) { + + const textures = renderTarget.textures; + + for ( let i = 0, il = textures.length; i < il; i ++ ) { + + const texture = textures[ i ]; + + if ( textureNeedsGenerateMipmaps( texture ) ) { + + const target = renderTarget.isWebGLCubeRenderTarget ? _gl.TEXTURE_CUBE_MAP : _gl.TEXTURE_2D; + const webglTexture = properties.get( texture ).__webglTexture; + + state.bindTexture( target, webglTexture ); + generateMipmap( target ); + state.unbindTexture(); + + } + + } + + } + + const invalidationArrayRead = []; + const invalidationArrayDraw = []; + + function updateMultisampleRenderTarget( renderTarget ) { + + if ( renderTarget.samples > 0 ) { + + if ( useMultisampledRTT( renderTarget ) === false ) { + + const textures = renderTarget.textures; + const width = renderTarget.width; + const height = renderTarget.height; + let mask = _gl.COLOR_BUFFER_BIT; + const depthStyle = renderTarget.stencilBuffer ? _gl.DEPTH_STENCIL_ATTACHMENT : _gl.DEPTH_ATTACHMENT; + const renderTargetProperties = properties.get( renderTarget ); + const isMultipleRenderTargets = ( textures.length > 1 ); + + // If MRT we need to remove FBO attachments + if ( isMultipleRenderTargets ) { + + for ( let i = 0; i < textures.length; i ++ ) { + + state.bindFramebuffer( _gl.FRAMEBUFFER, renderTargetProperties.__webglMultisampledFramebuffer ); + _gl.framebufferRenderbuffer( _gl.FRAMEBUFFER, _gl.COLOR_ATTACHMENT0 + i, _gl.RENDERBUFFER, null ); + + state.bindFramebuffer( _gl.FRAMEBUFFER, renderTargetProperties.__webglFramebuffer ); + _gl.framebufferTexture2D( _gl.DRAW_FRAMEBUFFER, _gl.COLOR_ATTACHMENT0 + i, _gl.TEXTURE_2D, null, 0 ); + + } + + } + + state.bindFramebuffer( _gl.READ_FRAMEBUFFER, renderTargetProperties.__webglMultisampledFramebuffer ); + state.bindFramebuffer( _gl.DRAW_FRAMEBUFFER, renderTargetProperties.__webglFramebuffer ); + + for ( let i = 0; i < textures.length; i ++ ) { + + if ( renderTarget.resolveDepthBuffer ) { + + if ( renderTarget.depthBuffer ) mask |= _gl.DEPTH_BUFFER_BIT; + + // resolving stencil is slow with a D3D backend. disable it for all transmission render targets (see #27799) + + if ( renderTarget.stencilBuffer && renderTarget.resolveStencilBuffer ) mask |= _gl.STENCIL_BUFFER_BIT; + + } + + if ( isMultipleRenderTargets ) { + + _gl.framebufferRenderbuffer( _gl.READ_FRAMEBUFFER, _gl.COLOR_ATTACHMENT0, _gl.RENDERBUFFER, renderTargetProperties.__webglColorRenderbuffer[ i ] ); + + const webglTexture = properties.get( textures[ i ] ).__webglTexture; + _gl.framebufferTexture2D( _gl.DRAW_FRAMEBUFFER, _gl.COLOR_ATTACHMENT0, _gl.TEXTURE_2D, webglTexture, 0 ); + + } + + _gl.blitFramebuffer( 0, 0, width, height, 0, 0, width, height, mask, _gl.NEAREST ); + + if ( supportsInvalidateFramebuffer === true ) { + + invalidationArrayRead.length = 0; + invalidationArrayDraw.length = 0; + + invalidationArrayRead.push( _gl.COLOR_ATTACHMENT0 + i ); + + if ( renderTarget.depthBuffer && renderTarget.resolveDepthBuffer === false ) { + + invalidationArrayRead.push( depthStyle ); + invalidationArrayDraw.push( depthStyle ); + + _gl.invalidateFramebuffer( _gl.DRAW_FRAMEBUFFER, invalidationArrayDraw ); + + } + + _gl.invalidateFramebuffer( _gl.READ_FRAMEBUFFER, invalidationArrayRead ); + + } + + } + + state.bindFramebuffer( _gl.READ_FRAMEBUFFER, null ); + state.bindFramebuffer( _gl.DRAW_FRAMEBUFFER, null ); + + // If MRT since pre-blit we removed the FBO we need to reconstruct the attachments + if ( isMultipleRenderTargets ) { + + for ( let i = 0; i < textures.length; i ++ ) { + + state.bindFramebuffer( _gl.FRAMEBUFFER, renderTargetProperties.__webglMultisampledFramebuffer ); + _gl.framebufferRenderbuffer( _gl.FRAMEBUFFER, _gl.COLOR_ATTACHMENT0 + i, _gl.RENDERBUFFER, renderTargetProperties.__webglColorRenderbuffer[ i ] ); + + const webglTexture = properties.get( textures[ i ] ).__webglTexture; + + state.bindFramebuffer( _gl.FRAMEBUFFER, renderTargetProperties.__webglFramebuffer ); + _gl.framebufferTexture2D( _gl.DRAW_FRAMEBUFFER, _gl.COLOR_ATTACHMENT0 + i, _gl.TEXTURE_2D, webglTexture, 0 ); + + } + + } + + state.bindFramebuffer( _gl.DRAW_FRAMEBUFFER, renderTargetProperties.__webglMultisampledFramebuffer ); + + } else { + + if ( renderTarget.depthBuffer && renderTarget.resolveDepthBuffer === false && supportsInvalidateFramebuffer ) { + + const depthStyle = renderTarget.stencilBuffer ? _gl.DEPTH_STENCIL_ATTACHMENT : _gl.DEPTH_ATTACHMENT; + + _gl.invalidateFramebuffer( _gl.DRAW_FRAMEBUFFER, [ depthStyle ] ); + + } + + } + + } + + } + + function getRenderTargetSamples( renderTarget ) { + + return Math.min( capabilities.maxSamples, renderTarget.samples ); + + } + + function useMultisampledRTT( renderTarget ) { + + const renderTargetProperties = properties.get( renderTarget ); + + return renderTarget.samples > 0 && extensions.has( 'WEBGL_multisampled_render_to_texture' ) === true && renderTargetProperties.__useRenderToTexture !== false; + + } + + function updateVideoTexture( texture ) { + + const frame = info.render.frame; + + // Check the last frame we updated the VideoTexture + + if ( _videoTextures.get( texture ) !== frame ) { + + _videoTextures.set( texture, frame ); + texture.update(); + + } + + } + + function verifyColorSpace( texture, image ) { + + const colorSpace = texture.colorSpace; + const format = texture.format; + const type = texture.type; + + if ( texture.isCompressedTexture === true || texture.isVideoTexture === true ) return image; + + if ( colorSpace !== LinearSRGBColorSpace && colorSpace !== NoColorSpace ) { + + // sRGB + + if ( ColorManagement.getTransfer( colorSpace ) === SRGBTransfer ) { + + // in WebGL 2 uncompressed textures can only be sRGB encoded if they have the RGBA8 format + + if ( format !== RGBAFormat || type !== UnsignedByteType ) { + + console.warn( 'THREE.WebGLTextures: sRGB encoded textures have to use RGBAFormat and UnsignedByteType.' ); + + } + + } else { + + console.error( 'THREE.WebGLTextures: Unsupported texture color space:', colorSpace ); + + } + + } + + return image; + + } + + function getDimensions( image ) { + + if ( typeof HTMLImageElement !== 'undefined' && image instanceof HTMLImageElement ) { + + // if intrinsic data are not available, fallback to width/height + + _imageDimensions.width = image.naturalWidth || image.width; + _imageDimensions.height = image.naturalHeight || image.height; + + } else if ( typeof VideoFrame !== 'undefined' && image instanceof VideoFrame ) { + + _imageDimensions.width = image.displayWidth; + _imageDimensions.height = image.displayHeight; + + } else { + + _imageDimensions.width = image.width; + _imageDimensions.height = image.height; + + } + + return _imageDimensions; + + } + + // + + this.allocateTextureUnit = allocateTextureUnit; + this.resetTextureUnits = resetTextureUnits; + + this.setTexture2D = setTexture2D; + this.setTexture2DArray = setTexture2DArray; + this.setTexture3D = setTexture3D; + this.setTextureCube = setTextureCube; + this.rebindTextures = rebindTextures; + this.setupRenderTarget = setupRenderTarget; + this.updateRenderTargetMipmap = updateRenderTargetMipmap; + this.updateMultisampleRenderTarget = updateMultisampleRenderTarget; + this.setupDepthRenderbuffer = setupDepthRenderbuffer; + this.setupFrameBufferTexture = setupFrameBufferTexture; + this.useMultisampledRTT = useMultisampledRTT; + +} + +function WebGLUtils( gl, extensions ) { + + function convert( p, colorSpace = NoColorSpace ) { + + let extension; + + const transfer = ColorManagement.getTransfer( colorSpace ); + + if ( p === UnsignedByteType ) return gl.UNSIGNED_BYTE; + if ( p === UnsignedShort4444Type ) return gl.UNSIGNED_SHORT_4_4_4_4; + if ( p === UnsignedShort5551Type ) return gl.UNSIGNED_SHORT_5_5_5_1; + if ( p === UnsignedInt5999Type ) return gl.UNSIGNED_INT_5_9_9_9_REV; + + if ( p === ByteType ) return gl.BYTE; + if ( p === ShortType ) return gl.SHORT; + if ( p === UnsignedShortType ) return gl.UNSIGNED_SHORT; + if ( p === IntType ) return gl.INT; + if ( p === UnsignedIntType ) return gl.UNSIGNED_INT; + if ( p === FloatType ) return gl.FLOAT; + if ( p === HalfFloatType ) return gl.HALF_FLOAT; + + if ( p === AlphaFormat ) return gl.ALPHA; + if ( p === RGBFormat ) return gl.RGB; + if ( p === RGBAFormat ) return gl.RGBA; + if ( p === LuminanceFormat ) return gl.LUMINANCE; + if ( p === LuminanceAlphaFormat ) return gl.LUMINANCE_ALPHA; + if ( p === DepthFormat ) return gl.DEPTH_COMPONENT; + if ( p === DepthStencilFormat ) return gl.DEPTH_STENCIL; + + // WebGL2 formats. + + if ( p === RedFormat ) return gl.RED; + if ( p === RedIntegerFormat ) return gl.RED_INTEGER; + if ( p === RGFormat ) return gl.RG; + if ( p === RGIntegerFormat ) return gl.RG_INTEGER; + if ( p === RGBAIntegerFormat ) return gl.RGBA_INTEGER; + + // S3TC + + if ( p === RGB_S3TC_DXT1_Format || p === RGBA_S3TC_DXT1_Format || p === RGBA_S3TC_DXT3_Format || p === RGBA_S3TC_DXT5_Format ) { + + if ( transfer === SRGBTransfer ) { + + extension = extensions.get( 'WEBGL_compressed_texture_s3tc_srgb' ); + + if ( extension !== null ) { + + if ( p === RGB_S3TC_DXT1_Format ) return extension.COMPRESSED_SRGB_S3TC_DXT1_EXT; + if ( p === RGBA_S3TC_DXT1_Format ) return extension.COMPRESSED_SRGB_ALPHA_S3TC_DXT1_EXT; + if ( p === RGBA_S3TC_DXT3_Format ) return extension.COMPRESSED_SRGB_ALPHA_S3TC_DXT3_EXT; + if ( p === RGBA_S3TC_DXT5_Format ) return extension.COMPRESSED_SRGB_ALPHA_S3TC_DXT5_EXT; + + } else { + + return null; + + } + + } else { + + extension = extensions.get( 'WEBGL_compressed_texture_s3tc' ); + + if ( extension !== null ) { + + if ( p === RGB_S3TC_DXT1_Format ) return extension.COMPRESSED_RGB_S3TC_DXT1_EXT; + if ( p === RGBA_S3TC_DXT1_Format ) return extension.COMPRESSED_RGBA_S3TC_DXT1_EXT; + if ( p === RGBA_S3TC_DXT3_Format ) return extension.COMPRESSED_RGBA_S3TC_DXT3_EXT; + if ( p === RGBA_S3TC_DXT5_Format ) return extension.COMPRESSED_RGBA_S3TC_DXT5_EXT; + + } else { + + return null; + + } + + } + + } + + // PVRTC + + if ( p === RGB_PVRTC_4BPPV1_Format || p === RGB_PVRTC_2BPPV1_Format || p === RGBA_PVRTC_4BPPV1_Format || p === RGBA_PVRTC_2BPPV1_Format ) { + + extension = extensions.get( 'WEBGL_compressed_texture_pvrtc' ); + + if ( extension !== null ) { + + if ( p === RGB_PVRTC_4BPPV1_Format ) return extension.COMPRESSED_RGB_PVRTC_4BPPV1_IMG; + if ( p === RGB_PVRTC_2BPPV1_Format ) return extension.COMPRESSED_RGB_PVRTC_2BPPV1_IMG; + if ( p === RGBA_PVRTC_4BPPV1_Format ) return extension.COMPRESSED_RGBA_PVRTC_4BPPV1_IMG; + if ( p === RGBA_PVRTC_2BPPV1_Format ) return extension.COMPRESSED_RGBA_PVRTC_2BPPV1_IMG; + + } else { + + return null; + + } + + } + + // ETC + + if ( p === RGB_ETC1_Format || p === RGB_ETC2_Format || p === RGBA_ETC2_EAC_Format ) { + + extension = extensions.get( 'WEBGL_compressed_texture_etc' ); + + if ( extension !== null ) { + + if ( p === RGB_ETC1_Format || p === RGB_ETC2_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ETC2 : extension.COMPRESSED_RGB8_ETC2; + if ( p === RGBA_ETC2_EAC_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ETC2_EAC : extension.COMPRESSED_RGBA8_ETC2_EAC; + + } else { + + return null; + + } + + } + + // ASTC + + if ( p === RGBA_ASTC_4x4_Format || p === RGBA_ASTC_5x4_Format || p === RGBA_ASTC_5x5_Format || + p === RGBA_ASTC_6x5_Format || p === RGBA_ASTC_6x6_Format || p === RGBA_ASTC_8x5_Format || + p === RGBA_ASTC_8x6_Format || p === RGBA_ASTC_8x8_Format || p === RGBA_ASTC_10x5_Format || + p === RGBA_ASTC_10x6_Format || p === RGBA_ASTC_10x8_Format || p === RGBA_ASTC_10x10_Format || + p === RGBA_ASTC_12x10_Format || p === RGBA_ASTC_12x12_Format ) { + + extension = extensions.get( 'WEBGL_compressed_texture_astc' ); + + if ( extension !== null ) { + + if ( p === RGBA_ASTC_4x4_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_4x4_KHR : extension.COMPRESSED_RGBA_ASTC_4x4_KHR; + if ( p === RGBA_ASTC_5x4_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_5x4_KHR : extension.COMPRESSED_RGBA_ASTC_5x4_KHR; + if ( p === RGBA_ASTC_5x5_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_5x5_KHR : extension.COMPRESSED_RGBA_ASTC_5x5_KHR; + if ( p === RGBA_ASTC_6x5_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_6x5_KHR : extension.COMPRESSED_RGBA_ASTC_6x5_KHR; + if ( p === RGBA_ASTC_6x6_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_6x6_KHR : extension.COMPRESSED_RGBA_ASTC_6x6_KHR; + if ( p === RGBA_ASTC_8x5_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_8x5_KHR : extension.COMPRESSED_RGBA_ASTC_8x5_KHR; + if ( p === RGBA_ASTC_8x6_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_8x6_KHR : extension.COMPRESSED_RGBA_ASTC_8x6_KHR; + if ( p === RGBA_ASTC_8x8_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_8x8_KHR : extension.COMPRESSED_RGBA_ASTC_8x8_KHR; + if ( p === RGBA_ASTC_10x5_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_10x5_KHR : extension.COMPRESSED_RGBA_ASTC_10x5_KHR; + if ( p === RGBA_ASTC_10x6_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_10x6_KHR : extension.COMPRESSED_RGBA_ASTC_10x6_KHR; + if ( p === RGBA_ASTC_10x8_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_10x8_KHR : extension.COMPRESSED_RGBA_ASTC_10x8_KHR; + if ( p === RGBA_ASTC_10x10_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_10x10_KHR : extension.COMPRESSED_RGBA_ASTC_10x10_KHR; + if ( p === RGBA_ASTC_12x10_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_12x10_KHR : extension.COMPRESSED_RGBA_ASTC_12x10_KHR; + if ( p === RGBA_ASTC_12x12_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB8_ALPHA8_ASTC_12x12_KHR : extension.COMPRESSED_RGBA_ASTC_12x12_KHR; + + } else { + + return null; + + } + + } + + // BPTC + + if ( p === RGBA_BPTC_Format || p === RGB_BPTC_SIGNED_Format || p === RGB_BPTC_UNSIGNED_Format ) { + + extension = extensions.get( 'EXT_texture_compression_bptc' ); + + if ( extension !== null ) { + + if ( p === RGBA_BPTC_Format ) return ( transfer === SRGBTransfer ) ? extension.COMPRESSED_SRGB_ALPHA_BPTC_UNORM_EXT : extension.COMPRESSED_RGBA_BPTC_UNORM_EXT; + if ( p === RGB_BPTC_SIGNED_Format ) return extension.COMPRESSED_RGB_BPTC_SIGNED_FLOAT_EXT; + if ( p === RGB_BPTC_UNSIGNED_Format ) return extension.COMPRESSED_RGB_BPTC_UNSIGNED_FLOAT_EXT; + + } else { + + return null; + + } + + } + + // RGTC + + if ( p === RED_RGTC1_Format || p === SIGNED_RED_RGTC1_Format || p === RED_GREEN_RGTC2_Format || p === SIGNED_RED_GREEN_RGTC2_Format ) { + + extension = extensions.get( 'EXT_texture_compression_rgtc' ); + + if ( extension !== null ) { + + if ( p === RGBA_BPTC_Format ) return extension.COMPRESSED_RED_RGTC1_EXT; + if ( p === SIGNED_RED_RGTC1_Format ) return extension.COMPRESSED_SIGNED_RED_RGTC1_EXT; + if ( p === RED_GREEN_RGTC2_Format ) return extension.COMPRESSED_RED_GREEN_RGTC2_EXT; + if ( p === SIGNED_RED_GREEN_RGTC2_Format ) return extension.COMPRESSED_SIGNED_RED_GREEN_RGTC2_EXT; + + } else { + + return null; + + } + + } + + // + + if ( p === UnsignedInt248Type ) return gl.UNSIGNED_INT_24_8; + + // if "p" can't be resolved, assume the user defines a WebGL constant as a string (fallback/workaround for packed RGB formats) + + return ( gl[ p ] !== undefined ) ? gl[ p ] : null; + + } + + return { convert: convert }; + +} + +class ArrayCamera extends PerspectiveCamera { + + constructor( array = [] ) { + + super(); + + this.isArrayCamera = true; + + this.cameras = array; + + } + +} + +class Group extends Object3D { + + constructor() { + + super(); + + this.isGroup = true; + + this.type = 'Group'; + + } + +} + +const _moveEvent = { type: 'move' }; + +class WebXRController { + + constructor() { + + this._targetRay = null; + this._grip = null; + this._hand = null; + + } + + getHandSpace() { + + if ( this._hand === null ) { + + this._hand = new Group(); + this._hand.matrixAutoUpdate = false; + this._hand.visible = false; + + this._hand.joints = {}; + this._hand.inputState = { pinching: false }; + + } + + return this._hand; + + } + + getTargetRaySpace() { + + if ( this._targetRay === null ) { + + this._targetRay = new Group(); + this._targetRay.matrixAutoUpdate = false; + this._targetRay.visible = false; + this._targetRay.hasLinearVelocity = false; + this._targetRay.linearVelocity = new Vector3(); + this._targetRay.hasAngularVelocity = false; + this._targetRay.angularVelocity = new Vector3(); + + } + + return this._targetRay; + + } + + getGripSpace() { + + if ( this._grip === null ) { + + this._grip = new Group(); + this._grip.matrixAutoUpdate = false; + this._grip.visible = false; + this._grip.hasLinearVelocity = false; + this._grip.linearVelocity = new Vector3(); + this._grip.hasAngularVelocity = false; + this._grip.angularVelocity = new Vector3(); + + } + + return this._grip; + + } + + dispatchEvent( event ) { + + if ( this._targetRay !== null ) { + + this._targetRay.dispatchEvent( event ); + + } + + if ( this._grip !== null ) { + + this._grip.dispatchEvent( event ); + + } + + if ( this._hand !== null ) { + + this._hand.dispatchEvent( event ); + + } + + return this; + + } + + connect( inputSource ) { + + if ( inputSource && inputSource.hand ) { + + const hand = this._hand; + + if ( hand ) { + + for ( const inputjoint of inputSource.hand.values() ) { + + // Initialize hand with joints when connected + this._getHandJoint( hand, inputjoint ); + + } + + } + + } + + this.dispatchEvent( { type: 'connected', data: inputSource } ); + + return this; + + } + + disconnect( inputSource ) { + + this.dispatchEvent( { type: 'disconnected', data: inputSource } ); + + if ( this._targetRay !== null ) { + + this._targetRay.visible = false; + + } + + if ( this._grip !== null ) { + + this._grip.visible = false; + + } + + if ( this._hand !== null ) { + + this._hand.visible = false; + + } + + return this; + + } + + update( inputSource, frame, referenceSpace ) { + + let inputPose = null; + let gripPose = null; + let handPose = null; + + const targetRay = this._targetRay; + const grip = this._grip; + const hand = this._hand; + + if ( inputSource && frame.session.visibilityState !== 'visible-blurred' ) { + + if ( hand && inputSource.hand ) { + + handPose = true; + + for ( const inputjoint of inputSource.hand.values() ) { + + // Update the joints groups with the XRJoint poses + const jointPose = frame.getJointPose( inputjoint, referenceSpace ); + + // The transform of this joint will be updated with the joint pose on each frame + const joint = this._getHandJoint( hand, inputjoint ); + + if ( jointPose !== null ) { + + joint.matrix.fromArray( jointPose.transform.matrix ); + joint.matrix.decompose( joint.position, joint.rotation, joint.scale ); + joint.matrixWorldNeedsUpdate = true; + joint.jointRadius = jointPose.radius; + + } + + joint.visible = jointPose !== null; + + } + + // Custom events + + // Check pinchz + const indexTip = hand.joints[ 'index-finger-tip' ]; + const thumbTip = hand.joints[ 'thumb-tip' ]; + const distance = indexTip.position.distanceTo( thumbTip.position ); + + const distanceToPinch = 0.02; + const threshold = 0.005; + + if ( hand.inputState.pinching && distance > distanceToPinch + threshold ) { + + hand.inputState.pinching = false; + this.dispatchEvent( { + type: 'pinchend', + handedness: inputSource.handedness, + target: this + } ); + + } else if ( ! hand.inputState.pinching && distance <= distanceToPinch - threshold ) { + + hand.inputState.pinching = true; + this.dispatchEvent( { + type: 'pinchstart', + handedness: inputSource.handedness, + target: this + } ); + + } + + } else { + + if ( grip !== null && inputSource.gripSpace ) { + + gripPose = frame.getPose( inputSource.gripSpace, referenceSpace ); + + if ( gripPose !== null ) { + + grip.matrix.fromArray( gripPose.transform.matrix ); + grip.matrix.decompose( grip.position, grip.rotation, grip.scale ); + grip.matrixWorldNeedsUpdate = true; + + if ( gripPose.linearVelocity ) { + + grip.hasLinearVelocity = true; + grip.linearVelocity.copy( gripPose.linearVelocity ); + + } else { + + grip.hasLinearVelocity = false; + + } + + if ( gripPose.angularVelocity ) { + + grip.hasAngularVelocity = true; + grip.angularVelocity.copy( gripPose.angularVelocity ); + + } else { + + grip.hasAngularVelocity = false; + + } + + } + + } + + } + + if ( targetRay !== null ) { + + inputPose = frame.getPose( inputSource.targetRaySpace, referenceSpace ); + + // Some runtimes (namely Vive Cosmos with Vive OpenXR Runtime) have only grip space and ray space is equal to it + if ( inputPose === null && gripPose !== null ) { + + inputPose = gripPose; + + } + + if ( inputPose !== null ) { + + targetRay.matrix.fromArray( inputPose.transform.matrix ); + targetRay.matrix.decompose( targetRay.position, targetRay.rotation, targetRay.scale ); + targetRay.matrixWorldNeedsUpdate = true; + + if ( inputPose.linearVelocity ) { + + targetRay.hasLinearVelocity = true; + targetRay.linearVelocity.copy( inputPose.linearVelocity ); + + } else { + + targetRay.hasLinearVelocity = false; + + } + + if ( inputPose.angularVelocity ) { + + targetRay.hasAngularVelocity = true; + targetRay.angularVelocity.copy( inputPose.angularVelocity ); + + } else { + + targetRay.hasAngularVelocity = false; + + } + + this.dispatchEvent( _moveEvent ); + + } + + } + + + } + + if ( targetRay !== null ) { + + targetRay.visible = ( inputPose !== null ); + + } + + if ( grip !== null ) { + + grip.visible = ( gripPose !== null ); + + } + + if ( hand !== null ) { + + hand.visible = ( handPose !== null ); + + } + + return this; + + } + + // private method + + _getHandJoint( hand, inputjoint ) { + + if ( hand.joints[ inputjoint.jointName ] === undefined ) { + + const joint = new Group(); + joint.matrixAutoUpdate = false; + joint.visible = false; + hand.joints[ inputjoint.jointName ] = joint; + + hand.add( joint ); + + } + + return hand.joints[ inputjoint.jointName ]; + + } + +} + +const _occlusion_vertex = ` +void main() { + + gl_Position = vec4( position, 1.0 ); + +}`; + +const _occlusion_fragment = ` +uniform sampler2DArray depthColor; +uniform float depthWidth; +uniform float depthHeight; + +void main() { + + vec2 coord = vec2( gl_FragCoord.x / depthWidth, gl_FragCoord.y / depthHeight ); + + if ( coord.x >= 1.0 ) { + + gl_FragDepth = texture( depthColor, vec3( coord.x - 1.0, coord.y, 1 ) ).r; + + } else { + + gl_FragDepth = texture( depthColor, vec3( coord.x, coord.y, 0 ) ).r; + + } + +}`; + +class WebXRDepthSensing { + + constructor() { + + this.texture = null; + this.mesh = null; + + this.depthNear = 0; + this.depthFar = 0; + + } + + init( renderer, depthData, renderState ) { + + if ( this.texture === null ) { + + const texture = new Texture(); + + const texProps = renderer.properties.get( texture ); + texProps.__webglTexture = depthData.texture; + + if ( ( depthData.depthNear != renderState.depthNear ) || ( depthData.depthFar != renderState.depthFar ) ) { + + this.depthNear = depthData.depthNear; + this.depthFar = depthData.depthFar; + + } + + this.texture = texture; + + } + + } + + getMesh( cameraXR ) { + + if ( this.texture !== null ) { + + if ( this.mesh === null ) { + + const viewport = cameraXR.cameras[ 0 ].viewport; + const material = new ShaderMaterial( { + vertexShader: _occlusion_vertex, + fragmentShader: _occlusion_fragment, + uniforms: { + depthColor: { value: this.texture }, + depthWidth: { value: viewport.z }, + depthHeight: { value: viewport.w } + } + } ); + + this.mesh = new Mesh( new PlaneGeometry( 20, 20 ), material ); + + } + + } + + return this.mesh; + + } + + reset() { + + this.texture = null; + this.mesh = null; + + } + +} + +class WebXRManager extends EventDispatcher { + + constructor( renderer, gl ) { + + super(); + + const scope = this; + + let session = null; + + let framebufferScaleFactor = 1.0; + + let referenceSpace = null; + let referenceSpaceType = 'local-floor'; + // Set default foveation to maximum. + let foveation = 1.0; + let customReferenceSpace = null; + + let pose = null; + let glBinding = null; + let glProjLayer = null; + let glBaseLayer = null; + let xrFrame = null; + + const depthSensing = new WebXRDepthSensing(); + const attributes = gl.getContextAttributes(); + + let initialRenderTarget = null; + let newRenderTarget = null; + + const controllers = []; + const controllerInputSources = []; + + const currentSize = new Vector2(); + let currentPixelRatio = null; + + // + + const cameraL = new PerspectiveCamera(); + cameraL.layers.enable( 1 ); + cameraL.viewport = new Vector4(); + + const cameraR = new PerspectiveCamera(); + cameraR.layers.enable( 2 ); + cameraR.viewport = new Vector4(); + + const cameras = [ cameraL, cameraR ]; + + const cameraXR = new ArrayCamera(); + cameraXR.layers.enable( 1 ); + cameraXR.layers.enable( 2 ); + + let _currentDepthNear = null; + let _currentDepthFar = null; + + // + + this.cameraAutoUpdate = true; + this.enabled = false; + + this.isPresenting = false; + + this.getController = function ( index ) { + + let controller = controllers[ index ]; + + if ( controller === undefined ) { + + controller = new WebXRController(); + controllers[ index ] = controller; + + } + + return controller.getTargetRaySpace(); + + }; + + this.getControllerGrip = function ( index ) { + + let controller = controllers[ index ]; + + if ( controller === undefined ) { + + controller = new WebXRController(); + controllers[ index ] = controller; + + } + + return controller.getGripSpace(); + + }; + + this.getHand = function ( index ) { + + let controller = controllers[ index ]; + + if ( controller === undefined ) { + + controller = new WebXRController(); + controllers[ index ] = controller; + + } + + return controller.getHandSpace(); + + }; + + // + + function onSessionEvent( event ) { + + const controllerIndex = controllerInputSources.indexOf( event.inputSource ); + + if ( controllerIndex === - 1 ) { + + return; + + } + + const controller = controllers[ controllerIndex ]; + + if ( controller !== undefined ) { + + controller.update( event.inputSource, event.frame, customReferenceSpace || referenceSpace ); + controller.dispatchEvent( { type: event.type, data: event.inputSource } ); + + } + + } + + function onSessionEnd() { + + session.removeEventListener( 'select', onSessionEvent ); + session.removeEventListener( 'selectstart', onSessionEvent ); + session.removeEventListener( 'selectend', onSessionEvent ); + session.removeEventListener( 'squeeze', onSessionEvent ); + session.removeEventListener( 'squeezestart', onSessionEvent ); + session.removeEventListener( 'squeezeend', onSessionEvent ); + session.removeEventListener( 'end', onSessionEnd ); + session.removeEventListener( 'inputsourceschange', onInputSourcesChange ); + + for ( let i = 0; i < controllers.length; i ++ ) { + + const inputSource = controllerInputSources[ i ]; + + if ( inputSource === null ) continue; + + controllerInputSources[ i ] = null; + + controllers[ i ].disconnect( inputSource ); + + } + + _currentDepthNear = null; + _currentDepthFar = null; + + depthSensing.reset(); + + // restore framebuffer/rendering state + + renderer.setRenderTarget( initialRenderTarget ); + + glBaseLayer = null; + glProjLayer = null; + glBinding = null; + session = null; + newRenderTarget = null; + + // + + animation.stop(); + + scope.isPresenting = false; + + renderer.setPixelRatio( currentPixelRatio ); + renderer.setSize( currentSize.width, currentSize.height, false ); + + scope.dispatchEvent( { type: 'sessionend' } ); + + } + + this.setFramebufferScaleFactor = function ( value ) { + + framebufferScaleFactor = value; + + if ( scope.isPresenting === true ) { + + console.warn( 'THREE.WebXRManager: Cannot change framebuffer scale while presenting.' ); + + } + + }; + + this.setReferenceSpaceType = function ( value ) { + + referenceSpaceType = value; + + if ( scope.isPresenting === true ) { + + console.warn( 'THREE.WebXRManager: Cannot change reference space type while presenting.' ); + + } + + }; + + this.getReferenceSpace = function () { + + return customReferenceSpace || referenceSpace; + + }; + + this.setReferenceSpace = function ( space ) { + + customReferenceSpace = space; + + }; + + this.getBaseLayer = function () { + + return glProjLayer !== null ? glProjLayer : glBaseLayer; + + }; + + this.getBinding = function () { + + return glBinding; + + }; + + this.getFrame = function () { + + return xrFrame; + + }; + + this.getSession = function () { + + return session; + + }; + + this.setSession = async function ( value ) { + + session = value; + + if ( session !== null ) { + + initialRenderTarget = renderer.getRenderTarget(); + + session.addEventListener( 'select', onSessionEvent ); + session.addEventListener( 'selectstart', onSessionEvent ); + session.addEventListener( 'selectend', onSessionEvent ); + session.addEventListener( 'squeeze', onSessionEvent ); + session.addEventListener( 'squeezestart', onSessionEvent ); + session.addEventListener( 'squeezeend', onSessionEvent ); + session.addEventListener( 'end', onSessionEnd ); + session.addEventListener( 'inputsourceschange', onInputSourcesChange ); + + if ( attributes.xrCompatible !== true ) { + + await gl.makeXRCompatible(); + + } + + currentPixelRatio = renderer.getPixelRatio(); + renderer.getSize( currentSize ); + + if ( session.renderState.layers === undefined ) { + + const layerInit = { + antialias: attributes.antialias, + alpha: true, + depth: attributes.depth, + stencil: attributes.stencil, + framebufferScaleFactor: framebufferScaleFactor + }; + + glBaseLayer = new XRWebGLLayer( session, gl, layerInit ); + + session.updateRenderState( { baseLayer: glBaseLayer } ); + + renderer.setPixelRatio( 1 ); + renderer.setSize( glBaseLayer.framebufferWidth, glBaseLayer.framebufferHeight, false ); + + newRenderTarget = new WebGLRenderTarget( + glBaseLayer.framebufferWidth, + glBaseLayer.framebufferHeight, + { + format: RGBAFormat, + type: UnsignedByteType, + colorSpace: renderer.outputColorSpace, + stencilBuffer: attributes.stencil + } + ); + + } else { + + let depthFormat = null; + let depthType = null; + let glDepthFormat = null; + + if ( attributes.depth ) { + + glDepthFormat = attributes.stencil ? gl.DEPTH24_STENCIL8 : gl.DEPTH_COMPONENT24; + depthFormat = attributes.stencil ? DepthStencilFormat : DepthFormat; + depthType = attributes.stencil ? UnsignedInt248Type : UnsignedIntType; + + } + + const projectionlayerInit = { + colorFormat: gl.RGBA8, + depthFormat: glDepthFormat, + scaleFactor: framebufferScaleFactor + }; + + glBinding = new XRWebGLBinding( session, gl ); + + glProjLayer = glBinding.createProjectionLayer( projectionlayerInit ); + + session.updateRenderState( { layers: [ glProjLayer ] } ); + + renderer.setPixelRatio( 1 ); + renderer.setSize( glProjLayer.textureWidth, glProjLayer.textureHeight, false ); + + newRenderTarget = new WebGLRenderTarget( + glProjLayer.textureWidth, + glProjLayer.textureHeight, + { + format: RGBAFormat, + type: UnsignedByteType, + depthTexture: new DepthTexture( glProjLayer.textureWidth, glProjLayer.textureHeight, depthType, undefined, undefined, undefined, undefined, undefined, undefined, depthFormat ), + stencilBuffer: attributes.stencil, + colorSpace: renderer.outputColorSpace, + samples: attributes.antialias ? 4 : 0, + resolveDepthBuffer: ( glProjLayer.ignoreDepthValues === false ) + } ); + + } + + newRenderTarget.isXRRenderTarget = true; // TODO Remove this when possible, see #23278 + + this.setFoveation( foveation ); + + customReferenceSpace = null; + referenceSpace = await session.requestReferenceSpace( referenceSpaceType ); + + animation.setContext( session ); + animation.start(); + + scope.isPresenting = true; + + scope.dispatchEvent( { type: 'sessionstart' } ); + + } + + }; + + this.getEnvironmentBlendMode = function () { + + if ( session !== null ) { + + return session.environmentBlendMode; + + } + + }; + + function onInputSourcesChange( event ) { + + // Notify disconnected + + for ( let i = 0; i < event.removed.length; i ++ ) { + + const inputSource = event.removed[ i ]; + const index = controllerInputSources.indexOf( inputSource ); + + if ( index >= 0 ) { + + controllerInputSources[ index ] = null; + controllers[ index ].disconnect( inputSource ); + + } + + } + + // Notify connected + + for ( let i = 0; i < event.added.length; i ++ ) { + + const inputSource = event.added[ i ]; + + let controllerIndex = controllerInputSources.indexOf( inputSource ); + + if ( controllerIndex === - 1 ) { + + // Assign input source a controller that currently has no input source + + for ( let i = 0; i < controllers.length; i ++ ) { + + if ( i >= controllerInputSources.length ) { + + controllerInputSources.push( inputSource ); + controllerIndex = i; + break; + + } else if ( controllerInputSources[ i ] === null ) { + + controllerInputSources[ i ] = inputSource; + controllerIndex = i; + break; + + } + + } + + // If all controllers do currently receive input we ignore new ones + + if ( controllerIndex === - 1 ) break; + + } + + const controller = controllers[ controllerIndex ]; + + if ( controller ) { + + controller.connect( inputSource ); + + } + + } + + } + + // + + const cameraLPos = new Vector3(); + const cameraRPos = new Vector3(); + + /** + * Assumes 2 cameras that are parallel and share an X-axis, and that + * the cameras' projection and world matrices have already been set. + * And that near and far planes are identical for both cameras. + * Visualization of this technique: https://computergraphics.stackexchange.com/a/4765 + */ + function setProjectionFromUnion( camera, cameraL, cameraR ) { + + cameraLPos.setFromMatrixPosition( cameraL.matrixWorld ); + cameraRPos.setFromMatrixPosition( cameraR.matrixWorld ); + + const ipd = cameraLPos.distanceTo( cameraRPos ); + + const projL = cameraL.projectionMatrix.elements; + const projR = cameraR.projectionMatrix.elements; + + // VR systems will have identical far and near planes, and + // most likely identical top and bottom frustum extents. + // Use the left camera for these values. + const near = projL[ 14 ] / ( projL[ 10 ] - 1 ); + const far = projL[ 14 ] / ( projL[ 10 ] + 1 ); + const topFov = ( projL[ 9 ] + 1 ) / projL[ 5 ]; + const bottomFov = ( projL[ 9 ] - 1 ) / projL[ 5 ]; + + const leftFov = ( projL[ 8 ] - 1 ) / projL[ 0 ]; + const rightFov = ( projR[ 8 ] + 1 ) / projR[ 0 ]; + const left = near * leftFov; + const right = near * rightFov; + + // Calculate the new camera's position offset from the + // left camera. xOffset should be roughly half `ipd`. + const zOffset = ipd / ( - leftFov + rightFov ); + const xOffset = zOffset * - leftFov; + + // TODO: Better way to apply this offset? + cameraL.matrixWorld.decompose( camera.position, camera.quaternion, camera.scale ); + camera.translateX( xOffset ); + camera.translateZ( zOffset ); + camera.matrixWorld.compose( camera.position, camera.quaternion, camera.scale ); + camera.matrixWorldInverse.copy( camera.matrixWorld ).invert(); + + // Find the union of the frustum values of the cameras and scale + // the values so that the near plane's position does not change in world space, + // although must now be relative to the new union camera. + const near2 = near + zOffset; + const far2 = far + zOffset; + const left2 = left - xOffset; + const right2 = right + ( ipd - xOffset ); + const top2 = topFov * far / far2 * near2; + const bottom2 = bottomFov * far / far2 * near2; + + camera.projectionMatrix.makePerspective( left2, right2, top2, bottom2, near2, far2 ); + camera.projectionMatrixInverse.copy( camera.projectionMatrix ).invert(); + + } + + function updateCamera( camera, parent ) { + + if ( parent === null ) { + + camera.matrixWorld.copy( camera.matrix ); + + } else { + + camera.matrixWorld.multiplyMatrices( parent.matrixWorld, camera.matrix ); + + } + + camera.matrixWorldInverse.copy( camera.matrixWorld ).invert(); + + } + + this.updateCamera = function ( camera ) { + + if ( session === null ) return; + + if ( depthSensing.texture !== null ) { + + camera.near = depthSensing.depthNear; + camera.far = depthSensing.depthFar; + + } + + cameraXR.near = cameraR.near = cameraL.near = camera.near; + cameraXR.far = cameraR.far = cameraL.far = camera.far; + + if ( _currentDepthNear !== cameraXR.near || _currentDepthFar !== cameraXR.far ) { + + // Note that the new renderState won't apply until the next frame. See #18320 + + session.updateRenderState( { + depthNear: cameraXR.near, + depthFar: cameraXR.far + } ); + + _currentDepthNear = cameraXR.near; + _currentDepthFar = cameraXR.far; + + cameraL.near = _currentDepthNear; + cameraL.far = _currentDepthFar; + cameraR.near = _currentDepthNear; + cameraR.far = _currentDepthFar; + + cameraL.updateProjectionMatrix(); + cameraR.updateProjectionMatrix(); + camera.updateProjectionMatrix(); + + } + + const parent = camera.parent; + const cameras = cameraXR.cameras; + + updateCamera( cameraXR, parent ); + + for ( let i = 0; i < cameras.length; i ++ ) { + + updateCamera( cameras[ i ], parent ); + + } + + // update projection matrix for proper view frustum culling + + if ( cameras.length === 2 ) { + + setProjectionFromUnion( cameraXR, cameraL, cameraR ); + + } else { + + // assume single camera setup (AR) + + cameraXR.projectionMatrix.copy( cameraL.projectionMatrix ); + + } + + // update user camera and its children + + updateUserCamera( camera, cameraXR, parent ); + + }; + + function updateUserCamera( camera, cameraXR, parent ) { + + if ( parent === null ) { + + camera.matrix.copy( cameraXR.matrixWorld ); + + } else { + + camera.matrix.copy( parent.matrixWorld ); + camera.matrix.invert(); + camera.matrix.multiply( cameraXR.matrixWorld ); + + } + + camera.matrix.decompose( camera.position, camera.quaternion, camera.scale ); + camera.updateMatrixWorld( true ); + + camera.projectionMatrix.copy( cameraXR.projectionMatrix ); + camera.projectionMatrixInverse.copy( cameraXR.projectionMatrixInverse ); + + if ( camera.isPerspectiveCamera ) { + + camera.fov = RAD2DEG * 2 * Math.atan( 1 / camera.projectionMatrix.elements[ 5 ] ); + camera.zoom = 1; + + } + + } + + this.getCamera = function () { + + return cameraXR; + + }; + + this.getFoveation = function () { + + if ( glProjLayer === null && glBaseLayer === null ) { + + return undefined; + + } + + return foveation; + + }; + + this.setFoveation = function ( value ) { + + // 0 = no foveation = full resolution + // 1 = maximum foveation = the edges render at lower resolution + + foveation = value; + + if ( glProjLayer !== null ) { + + glProjLayer.fixedFoveation = value; + + } + + if ( glBaseLayer !== null && glBaseLayer.fixedFoveation !== undefined ) { + + glBaseLayer.fixedFoveation = value; + + } + + }; + + this.hasDepthSensing = function () { + + return depthSensing.texture !== null; + + }; + + this.getDepthSensingMesh = function () { + + return depthSensing.getMesh( cameraXR ); + + }; + + // Animation Loop + + let onAnimationFrameCallback = null; + + function onAnimationFrame( time, frame ) { + + pose = frame.getViewerPose( customReferenceSpace || referenceSpace ); + xrFrame = frame; + + if ( pose !== null ) { + + const views = pose.views; + + if ( glBaseLayer !== null ) { + + renderer.setRenderTargetFramebuffer( newRenderTarget, glBaseLayer.framebuffer ); + renderer.setRenderTarget( newRenderTarget ); + + } + + let cameraXRNeedsUpdate = false; + + // check if it's necessary to rebuild cameraXR's camera list + + if ( views.length !== cameraXR.cameras.length ) { + + cameraXR.cameras.length = 0; + cameraXRNeedsUpdate = true; + + } + + for ( let i = 0; i < views.length; i ++ ) { + + const view = views[ i ]; + + let viewport = null; + + if ( glBaseLayer !== null ) { + + viewport = glBaseLayer.getViewport( view ); + + } else { + + const glSubImage = glBinding.getViewSubImage( glProjLayer, view ); + viewport = glSubImage.viewport; + + // For side-by-side projection, we only produce a single texture for both eyes. + if ( i === 0 ) { + + renderer.setRenderTargetTextures( + newRenderTarget, + glSubImage.colorTexture, + glProjLayer.ignoreDepthValues ? undefined : glSubImage.depthStencilTexture ); + + renderer.setRenderTarget( newRenderTarget ); + + } + + } + + let camera = cameras[ i ]; + + if ( camera === undefined ) { + + camera = new PerspectiveCamera(); + camera.layers.enable( i ); + camera.viewport = new Vector4(); + cameras[ i ] = camera; + + } + + camera.matrix.fromArray( view.transform.matrix ); + camera.matrix.decompose( camera.position, camera.quaternion, camera.scale ); + camera.projectionMatrix.fromArray( view.projectionMatrix ); + camera.projectionMatrixInverse.copy( camera.projectionMatrix ).invert(); + camera.viewport.set( viewport.x, viewport.y, viewport.width, viewport.height ); + + if ( i === 0 ) { + + cameraXR.matrix.copy( camera.matrix ); + cameraXR.matrix.decompose( cameraXR.position, cameraXR.quaternion, cameraXR.scale ); + + } + + if ( cameraXRNeedsUpdate === true ) { + + cameraXR.cameras.push( camera ); + + } + + } + + // + + const enabledFeatures = session.enabledFeatures; + + if ( enabledFeatures && enabledFeatures.includes( 'depth-sensing' ) ) { + + const depthData = glBinding.getDepthInformation( views[ 0 ] ); + + if ( depthData && depthData.isValid && depthData.texture ) { + + depthSensing.init( renderer, depthData, session.renderState ); + + } + + } + + } + + // + + for ( let i = 0; i < controllers.length; i ++ ) { + + const inputSource = controllerInputSources[ i ]; + const controller = controllers[ i ]; + + if ( inputSource !== null && controller !== undefined ) { + + controller.update( inputSource, frame, customReferenceSpace || referenceSpace ); + + } + + } + + if ( onAnimationFrameCallback ) onAnimationFrameCallback( time, frame ); + + if ( frame.detectedPlanes ) { + + scope.dispatchEvent( { type: 'planesdetected', data: frame } ); + + } + + xrFrame = null; + + } + + const animation = new WebGLAnimation(); + + animation.setAnimationLoop( onAnimationFrame ); + + this.setAnimationLoop = function ( callback ) { + + onAnimationFrameCallback = callback; + + }; + + this.dispose = function () {}; + + } + +} + +const _e1 = /*@__PURE__*/ new Euler(); +const _m1 = /*@__PURE__*/ new Matrix4(); + +function WebGLMaterials( renderer, properties ) { + + function refreshTransformUniform( map, uniform ) { + + if ( map.matrixAutoUpdate === true ) { + + map.updateMatrix(); + + } + + uniform.value.copy( map.matrix ); + + } + + function refreshFogUniforms( uniforms, fog ) { + + fog.color.getRGB( uniforms.fogColor.value, getUnlitUniformColorSpace( renderer ) ); + + if ( fog.isFog ) { + + uniforms.fogNear.value = fog.near; + uniforms.fogFar.value = fog.far; + + } else if ( fog.isFogExp2 ) { + + uniforms.fogDensity.value = fog.density; + + } + + } + + function refreshMaterialUniforms( uniforms, material, pixelRatio, height, transmissionRenderTarget ) { + + if ( material.isMeshBasicMaterial ) { + + refreshUniformsCommon( uniforms, material ); + + } else if ( material.isMeshLambertMaterial ) { + + refreshUniformsCommon( uniforms, material ); + + } else if ( material.isMeshToonMaterial ) { + + refreshUniformsCommon( uniforms, material ); + refreshUniformsToon( uniforms, material ); + + } else if ( material.isMeshPhongMaterial ) { + + refreshUniformsCommon( uniforms, material ); + refreshUniformsPhong( uniforms, material ); + + } else if ( material.isMeshStandardMaterial ) { + + refreshUniformsCommon( uniforms, material ); + refreshUniformsStandard( uniforms, material ); + + if ( material.isMeshPhysicalMaterial ) { + + refreshUniformsPhysical( uniforms, material, transmissionRenderTarget ); + + } + + } else if ( material.isMeshMatcapMaterial ) { + + refreshUniformsCommon( uniforms, material ); + refreshUniformsMatcap( uniforms, material ); + + } else if ( material.isMeshDepthMaterial ) { + + refreshUniformsCommon( uniforms, material ); + + } else if ( material.isMeshDistanceMaterial ) { + + refreshUniformsCommon( uniforms, material ); + refreshUniformsDistance( uniforms, material ); + + } else if ( material.isMeshNormalMaterial ) { + + refreshUniformsCommon( uniforms, material ); + + } else if ( material.isLineBasicMaterial ) { + + refreshUniformsLine( uniforms, material ); + + if ( material.isLineDashedMaterial ) { + + refreshUniformsDash( uniforms, material ); + + } + + } else if ( material.isPointsMaterial ) { + + refreshUniformsPoints( uniforms, material, pixelRatio, height ); + + } else if ( material.isSpriteMaterial ) { + + refreshUniformsSprites( uniforms, material ); + + } else if ( material.isShadowMaterial ) { + + uniforms.color.value.copy( material.color ); + uniforms.opacity.value = material.opacity; + + } else if ( material.isShaderMaterial ) { + + material.uniformsNeedUpdate = false; // #15581 + + } + + } + + function refreshUniformsCommon( uniforms, material ) { + + uniforms.opacity.value = material.opacity; + + if ( material.color ) { + + uniforms.diffuse.value.copy( material.color ); + + } + + if ( material.emissive ) { + + uniforms.emissive.value.copy( material.emissive ).multiplyScalar( material.emissiveIntensity ); + + } + + if ( material.map ) { + + uniforms.map.value = material.map; + + refreshTransformUniform( material.map, uniforms.mapTransform ); + + } + + if ( material.alphaMap ) { + + uniforms.alphaMap.value = material.alphaMap; + + refreshTransformUniform( material.alphaMap, uniforms.alphaMapTransform ); + + } + + if ( material.bumpMap ) { + + uniforms.bumpMap.value = material.bumpMap; + + refreshTransformUniform( material.bumpMap, uniforms.bumpMapTransform ); + + uniforms.bumpScale.value = material.bumpScale; + + if ( material.side === BackSide ) { + + uniforms.bumpScale.value *= - 1; + + } + + } + + if ( material.normalMap ) { + + uniforms.normalMap.value = material.normalMap; + + refreshTransformUniform( material.normalMap, uniforms.normalMapTransform ); + + uniforms.normalScale.value.copy( material.normalScale ); + + if ( material.side === BackSide ) { + + uniforms.normalScale.value.negate(); + + } + + } + + if ( material.displacementMap ) { + + uniforms.displacementMap.value = material.displacementMap; + + refreshTransformUniform( material.displacementMap, uniforms.displacementMapTransform ); + + uniforms.displacementScale.value = material.displacementScale; + uniforms.displacementBias.value = material.displacementBias; + + } + + if ( material.emissiveMap ) { + + uniforms.emissiveMap.value = material.emissiveMap; + + refreshTransformUniform( material.emissiveMap, uniforms.emissiveMapTransform ); + + } + + if ( material.specularMap ) { + + uniforms.specularMap.value = material.specularMap; + + refreshTransformUniform( material.specularMap, uniforms.specularMapTransform ); + + } + + if ( material.alphaTest > 0 ) { + + uniforms.alphaTest.value = material.alphaTest; + + } + + const materialProperties = properties.get( material ); + + const envMap = materialProperties.envMap; + const envMapRotation = materialProperties.envMapRotation; + + if ( envMap ) { + + uniforms.envMap.value = envMap; + + _e1.copy( envMapRotation ); + + // accommodate left-handed frame + _e1.x *= - 1; _e1.y *= - 1; _e1.z *= - 1; + + if ( envMap.isCubeTexture && envMap.isRenderTargetTexture === false ) { + + // environment maps which are not cube render targets or PMREMs follow a different convention + _e1.y *= - 1; + _e1.z *= - 1; + + } + + uniforms.envMapRotation.value.setFromMatrix4( _m1.makeRotationFromEuler( _e1 ) ); + + uniforms.flipEnvMap.value = ( envMap.isCubeTexture && envMap.isRenderTargetTexture === false ) ? - 1 : 1; + + uniforms.reflectivity.value = material.reflectivity; + uniforms.ior.value = material.ior; + uniforms.refractionRatio.value = material.refractionRatio; + + } + + if ( material.lightMap ) { + + uniforms.lightMap.value = material.lightMap; + uniforms.lightMapIntensity.value = material.lightMapIntensity; + + refreshTransformUniform( material.lightMap, uniforms.lightMapTransform ); + + } + + if ( material.aoMap ) { + + uniforms.aoMap.value = material.aoMap; + uniforms.aoMapIntensity.value = material.aoMapIntensity; + + refreshTransformUniform( material.aoMap, uniforms.aoMapTransform ); + + } + + } + + function refreshUniformsLine( uniforms, material ) { + + uniforms.diffuse.value.copy( material.color ); + uniforms.opacity.value = material.opacity; + + if ( material.map ) { + + uniforms.map.value = material.map; + + refreshTransformUniform( material.map, uniforms.mapTransform ); + + } + + } + + function refreshUniformsDash( uniforms, material ) { + + uniforms.dashSize.value = material.dashSize; + uniforms.totalSize.value = material.dashSize + material.gapSize; + uniforms.scale.value = material.scale; + + } + + function refreshUniformsPoints( uniforms, material, pixelRatio, height ) { + + uniforms.diffuse.value.copy( material.color ); + uniforms.opacity.value = material.opacity; + uniforms.size.value = material.size * pixelRatio; + uniforms.scale.value = height * 0.5; + + if ( material.map ) { + + uniforms.map.value = material.map; + + refreshTransformUniform( material.map, uniforms.uvTransform ); + + } + + if ( material.alphaMap ) { + + uniforms.alphaMap.value = material.alphaMap; + + refreshTransformUniform( material.alphaMap, uniforms.alphaMapTransform ); + + } + + if ( material.alphaTest > 0 ) { + + uniforms.alphaTest.value = material.alphaTest; + + } + + } + + function refreshUniformsSprites( uniforms, material ) { + + uniforms.diffuse.value.copy( material.color ); + uniforms.opacity.value = material.opacity; + uniforms.rotation.value = material.rotation; + + if ( material.map ) { + + uniforms.map.value = material.map; + + refreshTransformUniform( material.map, uniforms.mapTransform ); + + } + + if ( material.alphaMap ) { + + uniforms.alphaMap.value = material.alphaMap; + + refreshTransformUniform( material.alphaMap, uniforms.alphaMapTransform ); + + } + + if ( material.alphaTest > 0 ) { + + uniforms.alphaTest.value = material.alphaTest; + + } + + } + + function refreshUniformsPhong( uniforms, material ) { + + uniforms.specular.value.copy( material.specular ); + uniforms.shininess.value = Math.max( material.shininess, 1e-4 ); // to prevent pow( 0.0, 0.0 ) + + } + + function refreshUniformsToon( uniforms, material ) { + + if ( material.gradientMap ) { + + uniforms.gradientMap.value = material.gradientMap; + + } + + } + + function refreshUniformsStandard( uniforms, material ) { + + uniforms.metalness.value = material.metalness; + + if ( material.metalnessMap ) { + + uniforms.metalnessMap.value = material.metalnessMap; + + refreshTransformUniform( material.metalnessMap, uniforms.metalnessMapTransform ); + + } + + uniforms.roughness.value = material.roughness; + + if ( material.roughnessMap ) { + + uniforms.roughnessMap.value = material.roughnessMap; + + refreshTransformUniform( material.roughnessMap, uniforms.roughnessMapTransform ); + + } + + if ( material.envMap ) { + + //uniforms.envMap.value = material.envMap; // part of uniforms common + + uniforms.envMapIntensity.value = material.envMapIntensity; + + } + + } + + function refreshUniformsPhysical( uniforms, material, transmissionRenderTarget ) { + + uniforms.ior.value = material.ior; // also part of uniforms common + + if ( material.sheen > 0 ) { + + uniforms.sheenColor.value.copy( material.sheenColor ).multiplyScalar( material.sheen ); + + uniforms.sheenRoughness.value = material.sheenRoughness; + + if ( material.sheenColorMap ) { + + uniforms.sheenColorMap.value = material.sheenColorMap; + + refreshTransformUniform( material.sheenColorMap, uniforms.sheenColorMapTransform ); + + } + + if ( material.sheenRoughnessMap ) { + + uniforms.sheenRoughnessMap.value = material.sheenRoughnessMap; + + refreshTransformUniform( material.sheenRoughnessMap, uniforms.sheenRoughnessMapTransform ); + + } + + } + + if ( material.clearcoat > 0 ) { + + uniforms.clearcoat.value = material.clearcoat; + uniforms.clearcoatRoughness.value = material.clearcoatRoughness; + + if ( material.clearcoatMap ) { + + uniforms.clearcoatMap.value = material.clearcoatMap; + + refreshTransformUniform( material.clearcoatMap, uniforms.clearcoatMapTransform ); + + } + + if ( material.clearcoatRoughnessMap ) { + + uniforms.clearcoatRoughnessMap.value = material.clearcoatRoughnessMap; + + refreshTransformUniform( material.clearcoatRoughnessMap, uniforms.clearcoatRoughnessMapTransform ); + + } + + if ( material.clearcoatNormalMap ) { + + uniforms.clearcoatNormalMap.value = material.clearcoatNormalMap; + + refreshTransformUniform( material.clearcoatNormalMap, uniforms.clearcoatNormalMapTransform ); + + uniforms.clearcoatNormalScale.value.copy( material.clearcoatNormalScale ); + + if ( material.side === BackSide ) { + + uniforms.clearcoatNormalScale.value.negate(); + + } + + } + + } + + if ( material.dispersion > 0 ) { + + uniforms.dispersion.value = material.dispersion; + + } + + if ( material.iridescence > 0 ) { + + uniforms.iridescence.value = material.iridescence; + uniforms.iridescenceIOR.value = material.iridescenceIOR; + uniforms.iridescenceThicknessMinimum.value = material.iridescenceThicknessRange[ 0 ]; + uniforms.iridescenceThicknessMaximum.value = material.iridescenceThicknessRange[ 1 ]; + + if ( material.iridescenceMap ) { + + uniforms.iridescenceMap.value = material.iridescenceMap; + + refreshTransformUniform( material.iridescenceMap, uniforms.iridescenceMapTransform ); + + } + + if ( material.iridescenceThicknessMap ) { + + uniforms.iridescenceThicknessMap.value = material.iridescenceThicknessMap; + + refreshTransformUniform( material.iridescenceThicknessMap, uniforms.iridescenceThicknessMapTransform ); + + } + + } + + if ( material.transmission > 0 ) { + + uniforms.transmission.value = material.transmission; + uniforms.transmissionSamplerMap.value = transmissionRenderTarget.texture; + uniforms.transmissionSamplerSize.value.set( transmissionRenderTarget.width, transmissionRenderTarget.height ); + + if ( material.transmissionMap ) { + + uniforms.transmissionMap.value = material.transmissionMap; + + refreshTransformUniform( material.transmissionMap, uniforms.transmissionMapTransform ); + + } + + uniforms.thickness.value = material.thickness; + + if ( material.thicknessMap ) { + + uniforms.thicknessMap.value = material.thicknessMap; + + refreshTransformUniform( material.thicknessMap, uniforms.thicknessMapTransform ); + + } + + uniforms.attenuationDistance.value = material.attenuationDistance; + uniforms.attenuationColor.value.copy( material.attenuationColor ); + + } + + if ( material.anisotropy > 0 ) { + + uniforms.anisotropyVector.value.set( material.anisotropy * Math.cos( material.anisotropyRotation ), material.anisotropy * Math.sin( material.anisotropyRotation ) ); + + if ( material.anisotropyMap ) { + + uniforms.anisotropyMap.value = material.anisotropyMap; + + refreshTransformUniform( material.anisotropyMap, uniforms.anisotropyMapTransform ); + + } + + } + + uniforms.specularIntensity.value = material.specularIntensity; + uniforms.specularColor.value.copy( material.specularColor ); + + if ( material.specularColorMap ) { + + uniforms.specularColorMap.value = material.specularColorMap; + + refreshTransformUniform( material.specularColorMap, uniforms.specularColorMapTransform ); + + } + + if ( material.specularIntensityMap ) { + + uniforms.specularIntensityMap.value = material.specularIntensityMap; + + refreshTransformUniform( material.specularIntensityMap, uniforms.specularIntensityMapTransform ); + + } + + } + + function refreshUniformsMatcap( uniforms, material ) { + + if ( material.matcap ) { + + uniforms.matcap.value = material.matcap; + + } + + } + + function refreshUniformsDistance( uniforms, material ) { + + const light = properties.get( material ).light; + + uniforms.referencePosition.value.setFromMatrixPosition( light.matrixWorld ); + uniforms.nearDistance.value = light.shadow.camera.near; + uniforms.farDistance.value = light.shadow.camera.far; + + } + + return { + refreshFogUniforms: refreshFogUniforms, + refreshMaterialUniforms: refreshMaterialUniforms + }; + +} + +function WebGLUniformsGroups( gl, info, capabilities, state ) { + + let buffers = {}; + let updateList = {}; + let allocatedBindingPoints = []; + + const maxBindingPoints = gl.getParameter( gl.MAX_UNIFORM_BUFFER_BINDINGS ); // binding points are global whereas block indices are per shader program + + function bind( uniformsGroup, program ) { + + const webglProgram = program.program; + state.uniformBlockBinding( uniformsGroup, webglProgram ); + + } + + function update( uniformsGroup, program ) { + + let buffer = buffers[ uniformsGroup.id ]; + + if ( buffer === undefined ) { + + prepareUniformsGroup( uniformsGroup ); + + buffer = createBuffer( uniformsGroup ); + buffers[ uniformsGroup.id ] = buffer; + + uniformsGroup.addEventListener( 'dispose', onUniformsGroupsDispose ); + + } + + // ensure to update the binding points/block indices mapping for this program + + const webglProgram = program.program; + state.updateUBOMapping( uniformsGroup, webglProgram ); + + // update UBO once per frame + + const frame = info.render.frame; + + if ( updateList[ uniformsGroup.id ] !== frame ) { + + updateBufferData( uniformsGroup ); + + updateList[ uniformsGroup.id ] = frame; + + } + + } + + function createBuffer( uniformsGroup ) { + + // the setup of an UBO is independent of a particular shader program but global + + const bindingPointIndex = allocateBindingPointIndex(); + uniformsGroup.__bindingPointIndex = bindingPointIndex; + + const buffer = gl.createBuffer(); + const size = uniformsGroup.__size; + const usage = uniformsGroup.usage; + + gl.bindBuffer( gl.UNIFORM_BUFFER, buffer ); + gl.bufferData( gl.UNIFORM_BUFFER, size, usage ); + gl.bindBuffer( gl.UNIFORM_BUFFER, null ); + gl.bindBufferBase( gl.UNIFORM_BUFFER, bindingPointIndex, buffer ); + + return buffer; + + } + + function allocateBindingPointIndex() { + + for ( let i = 0; i < maxBindingPoints; i ++ ) { + + if ( allocatedBindingPoints.indexOf( i ) === - 1 ) { + + allocatedBindingPoints.push( i ); + return i; + + } + + } + + console.error( 'THREE.WebGLRenderer: Maximum number of simultaneously usable uniforms groups reached.' ); + + return 0; + + } + + function updateBufferData( uniformsGroup ) { + + const buffer = buffers[ uniformsGroup.id ]; + const uniforms = uniformsGroup.uniforms; + const cache = uniformsGroup.__cache; + + gl.bindBuffer( gl.UNIFORM_BUFFER, buffer ); + + for ( let i = 0, il = uniforms.length; i < il; i ++ ) { + + const uniformArray = Array.isArray( uniforms[ i ] ) ? uniforms[ i ] : [ uniforms[ i ] ]; + + for ( let j = 0, jl = uniformArray.length; j < jl; j ++ ) { + + const uniform = uniformArray[ j ]; + + if ( hasUniformChanged( uniform, i, j, cache ) === true ) { + + const offset = uniform.__offset; + + const values = Array.isArray( uniform.value ) ? uniform.value : [ uniform.value ]; + + let arrayOffset = 0; + + for ( let k = 0; k < values.length; k ++ ) { + + const value = values[ k ]; + + const info = getUniformSize( value ); + + // TODO add integer and struct support + if ( typeof value === 'number' || typeof value === 'boolean' ) { + + uniform.__data[ 0 ] = value; + gl.bufferSubData( gl.UNIFORM_BUFFER, offset + arrayOffset, uniform.__data ); + + } else if ( value.isMatrix3 ) { + + // manually converting 3x3 to 3x4 + + uniform.__data[ 0 ] = value.elements[ 0 ]; + uniform.__data[ 1 ] = value.elements[ 1 ]; + uniform.__data[ 2 ] = value.elements[ 2 ]; + uniform.__data[ 3 ] = 0; + uniform.__data[ 4 ] = value.elements[ 3 ]; + uniform.__data[ 5 ] = value.elements[ 4 ]; + uniform.__data[ 6 ] = value.elements[ 5 ]; + uniform.__data[ 7 ] = 0; + uniform.__data[ 8 ] = value.elements[ 6 ]; + uniform.__data[ 9 ] = value.elements[ 7 ]; + uniform.__data[ 10 ] = value.elements[ 8 ]; + uniform.__data[ 11 ] = 0; + + } else { + + value.toArray( uniform.__data, arrayOffset ); + + arrayOffset += info.storage / Float32Array.BYTES_PER_ELEMENT; + + } + + } + + gl.bufferSubData( gl.UNIFORM_BUFFER, offset, uniform.__data ); + + } + + } + + } + + gl.bindBuffer( gl.UNIFORM_BUFFER, null ); + + } + + function hasUniformChanged( uniform, index, indexArray, cache ) { + + const value = uniform.value; + const indexString = index + '_' + indexArray; + + if ( cache[ indexString ] === undefined ) { + + // cache entry does not exist so far + + if ( typeof value === 'number' || typeof value === 'boolean' ) { + + cache[ indexString ] = value; + + } else { + + cache[ indexString ] = value.clone(); + + } + + return true; + + } else { + + const cachedObject = cache[ indexString ]; + + // compare current value with cached entry + + if ( typeof value === 'number' || typeof value === 'boolean' ) { + + if ( cachedObject !== value ) { + + cache[ indexString ] = value; + return true; + + } + + } else { + + if ( cachedObject.equals( value ) === false ) { + + cachedObject.copy( value ); + return true; + + } + + } + + } + + return false; + + } + + function prepareUniformsGroup( uniformsGroup ) { + + // determine total buffer size according to the STD140 layout + // Hint: STD140 is the only supported layout in WebGL 2 + + const uniforms = uniformsGroup.uniforms; + + let offset = 0; // global buffer offset in bytes + const chunkSize = 16; // size of a chunk in bytes + + for ( let i = 0, l = uniforms.length; i < l; i ++ ) { + + const uniformArray = Array.isArray( uniforms[ i ] ) ? uniforms[ i ] : [ uniforms[ i ] ]; + + for ( let j = 0, jl = uniformArray.length; j < jl; j ++ ) { + + const uniform = uniformArray[ j ]; + + const values = Array.isArray( uniform.value ) ? uniform.value : [ uniform.value ]; + + for ( let k = 0, kl = values.length; k < kl; k ++ ) { + + const value = values[ k ]; + + const info = getUniformSize( value ); + + // Calculate the chunk offset + const chunkOffsetUniform = offset % chunkSize; + + // Check for chunk overflow + if ( chunkOffsetUniform !== 0 && ( chunkSize - chunkOffsetUniform ) < info.boundary ) { + + // Add padding and adjust offset + offset += ( chunkSize - chunkOffsetUniform ); + + } + + // the following two properties will be used for partial buffer updates + + uniform.__data = new Float32Array( info.storage / Float32Array.BYTES_PER_ELEMENT ); + uniform.__offset = offset; + + + // Update the global offset + offset += info.storage; + + + } + + } + + } + + // ensure correct final padding + + const chunkOffset = offset % chunkSize; + + if ( chunkOffset > 0 ) offset += ( chunkSize - chunkOffset ); + + // + + uniformsGroup.__size = offset; + uniformsGroup.__cache = {}; + + return this; + + } + + function getUniformSize( value ) { + + const info = { + boundary: 0, // bytes + storage: 0 // bytes + }; + + // determine sizes according to STD140 + + if ( typeof value === 'number' || typeof value === 'boolean' ) { + + // float/int/bool + + info.boundary = 4; + info.storage = 4; + + } else if ( value.isVector2 ) { + + // vec2 + + info.boundary = 8; + info.storage = 8; + + } else if ( value.isVector3 || value.isColor ) { + + // vec3 + + info.boundary = 16; + info.storage = 12; // evil: vec3 must start on a 16-byte boundary but it only consumes 12 bytes + + } else if ( value.isVector4 ) { + + // vec4 + + info.boundary = 16; + info.storage = 16; + + } else if ( value.isMatrix3 ) { + + // mat3 (in STD140 a 3x3 matrix is represented as 3x4) + + info.boundary = 48; + info.storage = 48; + + } else if ( value.isMatrix4 ) { + + // mat4 + + info.boundary = 64; + info.storage = 64; + + } else if ( value.isTexture ) { + + console.warn( 'THREE.WebGLRenderer: Texture samplers can not be part of an uniforms group.' ); + + } else { + + console.warn( 'THREE.WebGLRenderer: Unsupported uniform value type.', value ); + + } + + return info; + + } + + function onUniformsGroupsDispose( event ) { + + const uniformsGroup = event.target; + + uniformsGroup.removeEventListener( 'dispose', onUniformsGroupsDispose ); + + const index = allocatedBindingPoints.indexOf( uniformsGroup.__bindingPointIndex ); + allocatedBindingPoints.splice( index, 1 ); + + gl.deleteBuffer( buffers[ uniformsGroup.id ] ); + + delete buffers[ uniformsGroup.id ]; + delete updateList[ uniformsGroup.id ]; + + } + + function dispose() { + + for ( const id in buffers ) { + + gl.deleteBuffer( buffers[ id ] ); + + } + + allocatedBindingPoints = []; + buffers = {}; + updateList = {}; + + } + + return { + + bind: bind, + update: update, + + dispose: dispose + + }; + +} + +class WebGLRenderer { + + constructor( parameters = {} ) { + + const { + canvas = createCanvasElement(), + context = null, + depth = true, + stencil = false, + alpha = false, + antialias = false, + premultipliedAlpha = true, + preserveDrawingBuffer = false, + powerPreference = 'default', + failIfMajorPerformanceCaveat = false, + } = parameters; + + this.isWebGLRenderer = true; + + let _alpha; + + if ( context !== null ) { + + if ( typeof WebGLRenderingContext !== 'undefined' && context instanceof WebGLRenderingContext ) { + + throw new Error( 'THREE.WebGLRenderer: WebGL 1 is not supported since r163.' ); + + } + + _alpha = context.getContextAttributes().alpha; + + } else { + + _alpha = alpha; + + } + + const uintClearColor = new Uint32Array( 4 ); + const intClearColor = new Int32Array( 4 ); + + let currentRenderList = null; + let currentRenderState = null; + + // render() can be called from within a callback triggered by another render. + // We track this so that the nested render call gets its list and state isolated from the parent render call. + + const renderListStack = []; + const renderStateStack = []; + + // public properties + + this.domElement = canvas; + + // Debug configuration container + this.debug = { + + /** + * Enables error checking and reporting when shader programs are being compiled + * @type {boolean} + */ + checkShaderErrors: true, + /** + * Callback for custom error reporting. + * @type {?Function} + */ + onShaderError: null + }; + + // clearing + + this.autoClear = true; + this.autoClearColor = true; + this.autoClearDepth = true; + this.autoClearStencil = true; + + // scene graph + + this.sortObjects = true; + + // user-defined clipping + + this.clippingPlanes = []; + this.localClippingEnabled = false; + + // physically based shading + + this._outputColorSpace = SRGBColorSpace; + + // tone mapping + + this.toneMapping = NoToneMapping; + this.toneMappingExposure = 1.0; + + // internal properties + + const _this = this; + + let _isContextLost = false; + + // internal state cache + + let _currentActiveCubeFace = 0; + let _currentActiveMipmapLevel = 0; + let _currentRenderTarget = null; + let _currentMaterialId = - 1; + + let _currentCamera = null; + + const _currentViewport = new Vector4(); + const _currentScissor = new Vector4(); + let _currentScissorTest = null; + + const _currentClearColor = new Color( 0x000000 ); + let _currentClearAlpha = 0; + + // + + let _width = canvas.width; + let _height = canvas.height; + + let _pixelRatio = 1; + let _opaqueSort = null; + let _transparentSort = null; + + const _viewport = new Vector4( 0, 0, _width, _height ); + const _scissor = new Vector4( 0, 0, _width, _height ); + let _scissorTest = false; + + // frustum + + const _frustum = new Frustum(); + + // clipping + + let _clippingEnabled = false; + let _localClippingEnabled = false; + + // camera matrices cache + + const _projScreenMatrix = new Matrix4(); + + const _vector3 = new Vector3(); + + const _emptyScene = { background: null, fog: null, environment: null, overrideMaterial: null, isScene: true }; + + let _renderBackground = false; + + function getTargetPixelRatio() { + + return _currentRenderTarget === null ? _pixelRatio : 1; + + } + + // initialize + + let _gl = context; + + function getContext( contextName, contextAttributes ) { + + return canvas.getContext( contextName, contextAttributes ); + + } + + try { + + const contextAttributes = { + alpha: true, + depth, + stencil, + antialias, + premultipliedAlpha, + preserveDrawingBuffer, + powerPreference, + failIfMajorPerformanceCaveat, + }; + + // OffscreenCanvas does not have setAttribute, see #22811 + if ( 'setAttribute' in canvas ) canvas.setAttribute( 'data-engine', `three.js r${REVISION}` ); + + // event listeners must be registered before WebGL context is created, see #12753 + canvas.addEventListener( 'webglcontextlost', onContextLost, false ); + canvas.addEventListener( 'webglcontextrestored', onContextRestore, false ); + canvas.addEventListener( 'webglcontextcreationerror', onContextCreationError, false ); + + if ( _gl === null ) { + + const contextName = 'webgl2'; + + _gl = getContext( contextName, contextAttributes ); + + if ( _gl === null ) { + + if ( getContext( contextName ) ) { + + throw new Error( 'Error creating WebGL context with your selected attributes.' ); + + } else { + + throw new Error( 'Error creating WebGL context.' ); + + } + + } + + } + + } catch ( error ) { + + console.error( 'THREE.WebGLRenderer: ' + error.message ); + throw error; + + } + + let extensions, capabilities, state, info; + let properties, textures, cubemaps, cubeuvmaps, attributes, geometries, objects; + let programCache, materials, renderLists, renderStates, clipping, shadowMap; + + let background, morphtargets, bufferRenderer, indexedBufferRenderer; + + let utils, bindingStates, uniformsGroups; + + function initGLContext() { + + extensions = new WebGLExtensions( _gl ); + extensions.init(); + + utils = new WebGLUtils( _gl, extensions ); + + capabilities = new WebGLCapabilities( _gl, extensions, parameters, utils ); + + state = new WebGLState( _gl ); + + info = new WebGLInfo( _gl ); + properties = new WebGLProperties(); + textures = new WebGLTextures( _gl, extensions, state, properties, capabilities, utils, info ); + cubemaps = new WebGLCubeMaps( _this ); + cubeuvmaps = new WebGLCubeUVMaps( _this ); + attributes = new WebGLAttributes( _gl ); + bindingStates = new WebGLBindingStates( _gl, attributes ); + geometries = new WebGLGeometries( _gl, attributes, info, bindingStates ); + objects = new WebGLObjects( _gl, geometries, attributes, info ); + morphtargets = new WebGLMorphtargets( _gl, capabilities, textures ); + clipping = new WebGLClipping( properties ); + programCache = new WebGLPrograms( _this, cubemaps, cubeuvmaps, extensions, capabilities, bindingStates, clipping ); + materials = new WebGLMaterials( _this, properties ); + renderLists = new WebGLRenderLists(); + renderStates = new WebGLRenderStates( extensions ); + background = new WebGLBackground( _this, cubemaps, cubeuvmaps, state, objects, _alpha, premultipliedAlpha ); + shadowMap = new WebGLShadowMap( _this, objects, capabilities ); + uniformsGroups = new WebGLUniformsGroups( _gl, info, capabilities, state ); + + bufferRenderer = new WebGLBufferRenderer( _gl, extensions, info ); + indexedBufferRenderer = new WebGLIndexedBufferRenderer( _gl, extensions, info ); + + info.programs = programCache.programs; + + _this.capabilities = capabilities; + _this.extensions = extensions; + _this.properties = properties; + _this.renderLists = renderLists; + _this.shadowMap = shadowMap; + _this.state = state; + _this.info = info; + + } + + initGLContext(); + + // xr + + const xr = new WebXRManager( _this, _gl ); + + this.xr = xr; + + // API + + this.getContext = function () { + + return _gl; + + }; + + this.getContextAttributes = function () { + + return _gl.getContextAttributes(); + + }; + + this.forceContextLoss = function () { + + const extension = extensions.get( 'WEBGL_lose_context' ); + if ( extension ) extension.loseContext(); + + }; + + this.forceContextRestore = function () { + + const extension = extensions.get( 'WEBGL_lose_context' ); + if ( extension ) extension.restoreContext(); + + }; + + this.getPixelRatio = function () { + + return _pixelRatio; + + }; + + this.setPixelRatio = function ( value ) { + + if ( value === undefined ) return; + + _pixelRatio = value; + + this.setSize( _width, _height, false ); + + }; + + this.getSize = function ( target ) { + + return target.set( _width, _height ); + + }; + + this.setSize = function ( width, height, updateStyle = true ) { + + if ( xr.isPresenting ) { + + console.warn( 'THREE.WebGLRenderer: Can\'t change size while VR device is presenting.' ); + return; + + } + + _width = width; + _height = height; + + canvas.width = Math.floor( width * _pixelRatio ); + canvas.height = Math.floor( height * _pixelRatio ); + + if ( updateStyle === true ) { + + canvas.style.width = width + 'px'; + canvas.style.height = height + 'px'; + + } + + this.setViewport( 0, 0, width, height ); + + }; + + this.getDrawingBufferSize = function ( target ) { + + return target.set( _width * _pixelRatio, _height * _pixelRatio ).floor(); + + }; + + this.setDrawingBufferSize = function ( width, height, pixelRatio ) { + + _width = width; + _height = height; + + _pixelRatio = pixelRatio; + + canvas.width = Math.floor( width * pixelRatio ); + canvas.height = Math.floor( height * pixelRatio ); + + this.setViewport( 0, 0, width, height ); + + }; + + this.getCurrentViewport = function ( target ) { + + return target.copy( _currentViewport ); + + }; + + this.getViewport = function ( target ) { + + return target.copy( _viewport ); + + }; + + this.setViewport = function ( x, y, width, height ) { + + if ( x.isVector4 ) { + + _viewport.set( x.x, x.y, x.z, x.w ); + + } else { + + _viewport.set( x, y, width, height ); + + } + + state.viewport( _currentViewport.copy( _viewport ).multiplyScalar( _pixelRatio ).round() ); + + }; + + this.getScissor = function ( target ) { + + return target.copy( _scissor ); + + }; + + this.setScissor = function ( x, y, width, height ) { + + if ( x.isVector4 ) { + + _scissor.set( x.x, x.y, x.z, x.w ); + + } else { + + _scissor.set( x, y, width, height ); + + } + + state.scissor( _currentScissor.copy( _scissor ).multiplyScalar( _pixelRatio ).round() ); + + }; + + this.getScissorTest = function () { + + return _scissorTest; + + }; + + this.setScissorTest = function ( boolean ) { + + state.setScissorTest( _scissorTest = boolean ); + + }; + + this.setOpaqueSort = function ( method ) { + + _opaqueSort = method; + + }; + + this.setTransparentSort = function ( method ) { + + _transparentSort = method; + + }; + + // Clearing + + this.getClearColor = function ( target ) { + + return target.copy( background.getClearColor() ); + + }; + + this.setClearColor = function () { + + background.setClearColor.apply( background, arguments ); + + }; + + this.getClearAlpha = function () { + + return background.getClearAlpha(); + + }; + + this.setClearAlpha = function () { + + background.setClearAlpha.apply( background, arguments ); + + }; + + this.clear = function ( color = true, depth = true, stencil = true ) { + + let bits = 0; + + if ( color ) { + + // check if we're trying to clear an integer target + let isIntegerFormat = false; + if ( _currentRenderTarget !== null ) { + + const targetFormat = _currentRenderTarget.texture.format; + isIntegerFormat = targetFormat === RGBAIntegerFormat || + targetFormat === RGIntegerFormat || + targetFormat === RedIntegerFormat; + + } + + // use the appropriate clear functions to clear the target if it's a signed + // or unsigned integer target + if ( isIntegerFormat ) { + + const targetType = _currentRenderTarget.texture.type; + const isUnsignedType = targetType === UnsignedByteType || + targetType === UnsignedIntType || + targetType === UnsignedShortType || + targetType === UnsignedInt248Type || + targetType === UnsignedShort4444Type || + targetType === UnsignedShort5551Type; + + const clearColor = background.getClearColor(); + const a = background.getClearAlpha(); + const r = clearColor.r; + const g = clearColor.g; + const b = clearColor.b; + + if ( isUnsignedType ) { + + uintClearColor[ 0 ] = r; + uintClearColor[ 1 ] = g; + uintClearColor[ 2 ] = b; + uintClearColor[ 3 ] = a; + _gl.clearBufferuiv( _gl.COLOR, 0, uintClearColor ); + + } else { + + intClearColor[ 0 ] = r; + intClearColor[ 1 ] = g; + intClearColor[ 2 ] = b; + intClearColor[ 3 ] = a; + _gl.clearBufferiv( _gl.COLOR, 0, intClearColor ); + + } + + } else { + + bits |= _gl.COLOR_BUFFER_BIT; + + } + + } + + if ( depth ) bits |= _gl.DEPTH_BUFFER_BIT; + if ( stencil ) { + + bits |= _gl.STENCIL_BUFFER_BIT; + this.state.buffers.stencil.setMask( 0xffffffff ); + + } + + _gl.clear( bits ); + + }; + + this.clearColor = function () { + + this.clear( true, false, false ); + + }; + + this.clearDepth = function () { + + this.clear( false, true, false ); + + }; + + this.clearStencil = function () { + + this.clear( false, false, true ); + + }; + + // + + this.dispose = function () { + + canvas.removeEventListener( 'webglcontextlost', onContextLost, false ); + canvas.removeEventListener( 'webglcontextrestored', onContextRestore, false ); + canvas.removeEventListener( 'webglcontextcreationerror', onContextCreationError, false ); + + renderLists.dispose(); + renderStates.dispose(); + properties.dispose(); + cubemaps.dispose(); + cubeuvmaps.dispose(); + objects.dispose(); + bindingStates.dispose(); + uniformsGroups.dispose(); + programCache.dispose(); + + xr.dispose(); + + xr.removeEventListener( 'sessionstart', onXRSessionStart ); + xr.removeEventListener( 'sessionend', onXRSessionEnd ); + + animation.stop(); + + }; + + // Events + + function onContextLost( event ) { + + event.preventDefault(); + + console.log( 'THREE.WebGLRenderer: Context Lost.' ); + + _isContextLost = true; + + } + + function onContextRestore( /* event */ ) { + + console.log( 'THREE.WebGLRenderer: Context Restored.' ); + + _isContextLost = false; + + const infoAutoReset = info.autoReset; + const shadowMapEnabled = shadowMap.enabled; + const shadowMapAutoUpdate = shadowMap.autoUpdate; + const shadowMapNeedsUpdate = shadowMap.needsUpdate; + const shadowMapType = shadowMap.type; + + initGLContext(); + + info.autoReset = infoAutoReset; + shadowMap.enabled = shadowMapEnabled; + shadowMap.autoUpdate = shadowMapAutoUpdate; + shadowMap.needsUpdate = shadowMapNeedsUpdate; + shadowMap.type = shadowMapType; + + } + + function onContextCreationError( event ) { + + console.error( 'THREE.WebGLRenderer: A WebGL context could not be created. Reason: ', event.statusMessage ); + + } + + function onMaterialDispose( event ) { + + const material = event.target; + + material.removeEventListener( 'dispose', onMaterialDispose ); + + deallocateMaterial( material ); + + } + + // Buffer deallocation + + function deallocateMaterial( material ) { + + releaseMaterialProgramReferences( material ); + + properties.remove( material ); + + } + + + function releaseMaterialProgramReferences( material ) { + + const programs = properties.get( material ).programs; + + if ( programs !== undefined ) { + + programs.forEach( function ( program ) { + + programCache.releaseProgram( program ); + + } ); + + if ( material.isShaderMaterial ) { + + programCache.releaseShaderCache( material ); + + } + + } + + } + + // Buffer rendering + + this.renderBufferDirect = function ( camera, scene, geometry, material, object, group ) { + + if ( scene === null ) scene = _emptyScene; // renderBufferDirect second parameter used to be fog (could be null) + + const frontFaceCW = ( object.isMesh && object.matrixWorld.determinant() < 0 ); + + const program = setProgram( camera, scene, geometry, material, object ); + + state.setMaterial( material, frontFaceCW ); + + // + + let index = geometry.index; + let rangeFactor = 1; + + if ( material.wireframe === true ) { + + index = geometries.getWireframeAttribute( geometry ); + + if ( index === undefined ) return; + + rangeFactor = 2; + + } + + // + + const drawRange = geometry.drawRange; + const position = geometry.attributes.position; + + let drawStart = drawRange.start * rangeFactor; + let drawEnd = ( drawRange.start + drawRange.count ) * rangeFactor; + + if ( group !== null ) { + + drawStart = Math.max( drawStart, group.start * rangeFactor ); + drawEnd = Math.min( drawEnd, ( group.start + group.count ) * rangeFactor ); + + } + + if ( index !== null ) { + + drawStart = Math.max( drawStart, 0 ); + drawEnd = Math.min( drawEnd, index.count ); + + } else if ( position !== undefined && position !== null ) { + + drawStart = Math.max( drawStart, 0 ); + drawEnd = Math.min( drawEnd, position.count ); + + } + + const drawCount = drawEnd - drawStart; + + if ( drawCount < 0 || drawCount === Infinity ) return; + + // + + bindingStates.setup( object, material, program, geometry, index ); + + let attribute; + let renderer = bufferRenderer; + + if ( index !== null ) { + + attribute = attributes.get( index ); + + renderer = indexedBufferRenderer; + renderer.setIndex( attribute ); + + } + + // + + if ( object.isMesh ) { + + if ( material.wireframe === true ) { + + state.setLineWidth( material.wireframeLinewidth * getTargetPixelRatio() ); + renderer.setMode( _gl.LINES ); + + } else { + + renderer.setMode( _gl.TRIANGLES ); + + } + + } else if ( object.isLine ) { + + let lineWidth = material.linewidth; + + if ( lineWidth === undefined ) lineWidth = 1; // Not using Line*Material + + state.setLineWidth( lineWidth * getTargetPixelRatio() ); + + if ( object.isLineSegments ) { + + renderer.setMode( _gl.LINES ); + + } else if ( object.isLineLoop ) { + + renderer.setMode( _gl.LINE_LOOP ); + + } else { + + renderer.setMode( _gl.LINE_STRIP ); + + } + + } else if ( object.isPoints ) { + + renderer.setMode( _gl.POINTS ); + + } else if ( object.isSprite ) { + + renderer.setMode( _gl.TRIANGLES ); + + } + + if ( object.isBatchedMesh ) { + + if ( object._multiDrawInstances !== null ) { + + renderer.renderMultiDrawInstances( object._multiDrawStarts, object._multiDrawCounts, object._multiDrawCount, object._multiDrawInstances ); + + } else { + + renderer.renderMultiDraw( object._multiDrawStarts, object._multiDrawCounts, object._multiDrawCount ); + + } + + } else if ( object.isInstancedMesh ) { + + renderer.renderInstances( drawStart, drawCount, object.count ); + + } else if ( geometry.isInstancedBufferGeometry ) { + + const maxInstanceCount = geometry._maxInstanceCount !== undefined ? geometry._maxInstanceCount : Infinity; + const instanceCount = Math.min( geometry.instanceCount, maxInstanceCount ); + + renderer.renderInstances( drawStart, drawCount, instanceCount ); + + } else { + + renderer.render( drawStart, drawCount ); + + } + + }; + + // Compile + + function prepareMaterial( material, scene, object ) { + + if ( material.transparent === true && material.side === DoubleSide && material.forceSinglePass === false ) { + + material.side = BackSide; + material.needsUpdate = true; + getProgram( material, scene, object ); + + material.side = FrontSide; + material.needsUpdate = true; + getProgram( material, scene, object ); + + material.side = DoubleSide; + + } else { + + getProgram( material, scene, object ); + + } + + } + + this.compile = function ( scene, camera, targetScene = null ) { + + if ( targetScene === null ) targetScene = scene; + + currentRenderState = renderStates.get( targetScene ); + currentRenderState.init( camera ); + + renderStateStack.push( currentRenderState ); + + // gather lights from both the target scene and the new object that will be added to the scene. + + targetScene.traverseVisible( function ( object ) { + + if ( object.isLight && object.layers.test( camera.layers ) ) { + + currentRenderState.pushLight( object ); + + if ( object.castShadow ) { + + currentRenderState.pushShadow( object ); + + } + + } + + } ); + + if ( scene !== targetScene ) { + + scene.traverseVisible( function ( object ) { + + if ( object.isLight && object.layers.test( camera.layers ) ) { + + currentRenderState.pushLight( object ); + + if ( object.castShadow ) { + + currentRenderState.pushShadow( object ); + + } + + } + + } ); + + } + + currentRenderState.setupLights(); + + // Only initialize materials in the new scene, not the targetScene. + + const materials = new Set(); + + scene.traverse( function ( object ) { + + const material = object.material; + + if ( material ) { + + if ( Array.isArray( material ) ) { + + for ( let i = 0; i < material.length; i ++ ) { + + const material2 = material[ i ]; + + prepareMaterial( material2, targetScene, object ); + materials.add( material2 ); + + } + + } else { + + prepareMaterial( material, targetScene, object ); + materials.add( material ); + + } + + } + + } ); + + renderStateStack.pop(); + currentRenderState = null; + + return materials; + + }; + + // compileAsync + + this.compileAsync = function ( scene, camera, targetScene = null ) { + + const materials = this.compile( scene, camera, targetScene ); + + // Wait for all the materials in the new object to indicate that they're + // ready to be used before resolving the promise. + + return new Promise( ( resolve ) => { + + function checkMaterialsReady() { + + materials.forEach( function ( material ) { + + const materialProperties = properties.get( material ); + const program = materialProperties.currentProgram; + + if ( program.isReady() ) { + + // remove any programs that report they're ready to use from the list + materials.delete( material ); + + } + + } ); + + // once the list of compiling materials is empty, call the callback + + if ( materials.size === 0 ) { + + resolve( scene ); + return; + + } + + // if some materials are still not ready, wait a bit and check again + + setTimeout( checkMaterialsReady, 10 ); + + } + + if ( extensions.get( 'KHR_parallel_shader_compile' ) !== null ) { + + // If we can check the compilation status of the materials without + // blocking then do so right away. + + checkMaterialsReady(); + + } else { + + // Otherwise start by waiting a bit to give the materials we just + // initialized a chance to finish. + + setTimeout( checkMaterialsReady, 10 ); + + } + + } ); + + }; + + // Animation Loop + + let onAnimationFrameCallback = null; + + function onAnimationFrame( time ) { + + if ( onAnimationFrameCallback ) onAnimationFrameCallback( time ); + + } + + function onXRSessionStart() { + + animation.stop(); + + } + + function onXRSessionEnd() { + + animation.start(); + + } + + const animation = new WebGLAnimation(); + animation.setAnimationLoop( onAnimationFrame ); + + if ( typeof self !== 'undefined' ) animation.setContext( self ); + + this.setAnimationLoop = function ( callback ) { + + onAnimationFrameCallback = callback; + xr.setAnimationLoop( callback ); + + ( callback === null ) ? animation.stop() : animation.start(); + + }; + + xr.addEventListener( 'sessionstart', onXRSessionStart ); + xr.addEventListener( 'sessionend', onXRSessionEnd ); + + // Rendering + + this.render = function ( scene, camera ) { + + if ( camera !== undefined && camera.isCamera !== true ) { + + console.error( 'THREE.WebGLRenderer.render: camera is not an instance of THREE.Camera.' ); + return; + + } + + if ( _isContextLost === true ) return; + + // update scene graph + + if ( scene.matrixWorldAutoUpdate === true ) scene.updateMatrixWorld(); + + // update camera matrices and frustum + + if ( camera.parent === null && camera.matrixWorldAutoUpdate === true ) camera.updateMatrixWorld(); + + if ( xr.enabled === true && xr.isPresenting === true ) { + + if ( xr.cameraAutoUpdate === true ) xr.updateCamera( camera ); + + camera = xr.getCamera(); // use XR camera for rendering + + } + + // + if ( scene.isScene === true ) scene.onBeforeRender( _this, scene, camera, _currentRenderTarget ); + + currentRenderState = renderStates.get( scene, renderStateStack.length ); + currentRenderState.init( camera ); + + renderStateStack.push( currentRenderState ); + + _projScreenMatrix.multiplyMatrices( camera.projectionMatrix, camera.matrixWorldInverse ); + _frustum.setFromProjectionMatrix( _projScreenMatrix ); + + _localClippingEnabled = this.localClippingEnabled; + _clippingEnabled = clipping.init( this.clippingPlanes, _localClippingEnabled ); + + currentRenderList = renderLists.get( scene, renderListStack.length ); + currentRenderList.init(); + + renderListStack.push( currentRenderList ); + + if ( xr.enabled === true && xr.isPresenting === true ) { + + const depthSensingMesh = _this.xr.getDepthSensingMesh(); + + if ( depthSensingMesh !== null ) { + + projectObject( depthSensingMesh, camera, - Infinity, _this.sortObjects ); + + } + + } + + projectObject( scene, camera, 0, _this.sortObjects ); + + currentRenderList.finish(); + + if ( _this.sortObjects === true ) { + + currentRenderList.sort( _opaqueSort, _transparentSort ); + + } + + _renderBackground = xr.enabled === false || xr.isPresenting === false || xr.hasDepthSensing() === false; + if ( _renderBackground ) { + + background.addToRenderList( currentRenderList, scene ); + + } + + // + + this.info.render.frame ++; + + if ( _clippingEnabled === true ) clipping.beginShadows(); + + const shadowsArray = currentRenderState.state.shadowsArray; + + shadowMap.render( shadowsArray, scene, camera ); + + if ( _clippingEnabled === true ) clipping.endShadows(); + + // + + if ( this.info.autoReset === true ) this.info.reset(); + + // render scene + + const opaqueObjects = currentRenderList.opaque; + const transmissiveObjects = currentRenderList.transmissive; + + currentRenderState.setupLights(); + + if ( camera.isArrayCamera ) { + + const cameras = camera.cameras; + + if ( transmissiveObjects.length > 0 ) { + + for ( let i = 0, l = cameras.length; i < l; i ++ ) { + + const camera2 = cameras[ i ]; + + renderTransmissionPass( opaqueObjects, transmissiveObjects, scene, camera2 ); + + } + + } + + if ( _renderBackground ) background.render( scene ); + + for ( let i = 0, l = cameras.length; i < l; i ++ ) { + + const camera2 = cameras[ i ]; + + renderScene( currentRenderList, scene, camera2, camera2.viewport ); + + } + + } else { + + if ( transmissiveObjects.length > 0 ) renderTransmissionPass( opaqueObjects, transmissiveObjects, scene, camera ); + + if ( _renderBackground ) background.render( scene ); + + renderScene( currentRenderList, scene, camera ); + + } + + // + + if ( _currentRenderTarget !== null ) { + + // resolve multisample renderbuffers to a single-sample texture if necessary + + textures.updateMultisampleRenderTarget( _currentRenderTarget ); + + // Generate mipmap if we're using any kind of mipmap filtering + + textures.updateRenderTargetMipmap( _currentRenderTarget ); + + } + + // + + if ( scene.isScene === true ) scene.onAfterRender( _this, scene, camera ); + + // _gl.finish(); + + bindingStates.resetDefaultState(); + _currentMaterialId = - 1; + _currentCamera = null; + + renderStateStack.pop(); + + if ( renderStateStack.length > 0 ) { + + currentRenderState = renderStateStack[ renderStateStack.length - 1 ]; + + if ( _clippingEnabled === true ) clipping.setGlobalState( _this.clippingPlanes, currentRenderState.state.camera ); + + } else { + + currentRenderState = null; + + } + + renderListStack.pop(); + + if ( renderListStack.length > 0 ) { + + currentRenderList = renderListStack[ renderListStack.length - 1 ]; + + } else { + + currentRenderList = null; + + } + + }; + + function projectObject( object, camera, groupOrder, sortObjects ) { + + if ( object.visible === false ) return; + + const visible = object.layers.test( camera.layers ); + + if ( visible ) { + + if ( object.isGroup ) { + + groupOrder = object.renderOrder; + + } else if ( object.isLOD ) { + + if ( object.autoUpdate === true ) object.update( camera ); + + } else if ( object.isLight ) { + + currentRenderState.pushLight( object ); + + if ( object.castShadow ) { + + currentRenderState.pushShadow( object ); + + } + + } else if ( object.isSprite ) { + + if ( ! object.frustumCulled || _frustum.intersectsSprite( object ) ) { + + if ( sortObjects ) { + + _vector3.setFromMatrixPosition( object.matrixWorld ) + .applyMatrix4( _projScreenMatrix ); + + } + + const geometry = objects.update( object ); + const material = object.material; + + if ( material.visible ) { + + currentRenderList.push( object, geometry, material, groupOrder, _vector3.z, null ); + + } + + } + + } else if ( object.isMesh || object.isLine || object.isPoints ) { + + if ( ! object.frustumCulled || _frustum.intersectsObject( object ) ) { + + const geometry = objects.update( object ); + const material = object.material; + + if ( sortObjects ) { + + if ( object.boundingSphere !== undefined ) { + + if ( object.boundingSphere === null ) object.computeBoundingSphere(); + _vector3.copy( object.boundingSphere.center ); + + } else { + + if ( geometry.boundingSphere === null ) geometry.computeBoundingSphere(); + _vector3.copy( geometry.boundingSphere.center ); + + } + + _vector3 + .applyMatrix4( object.matrixWorld ) + .applyMatrix4( _projScreenMatrix ); + + } + + if ( Array.isArray( material ) ) { + + const groups = geometry.groups; + + for ( let i = 0, l = groups.length; i < l; i ++ ) { + + const group = groups[ i ]; + const groupMaterial = material[ group.materialIndex ]; + + if ( groupMaterial && groupMaterial.visible ) { + + currentRenderList.push( object, geometry, groupMaterial, groupOrder, _vector3.z, group ); + + } + + } + + } else if ( material.visible ) { + + currentRenderList.push( object, geometry, material, groupOrder, _vector3.z, null ); + + } + + } + + } + + } + + const children = object.children; + + for ( let i = 0, l = children.length; i < l; i ++ ) { + + projectObject( children[ i ], camera, groupOrder, sortObjects ); + + } + + } + + function renderScene( currentRenderList, scene, camera, viewport ) { + + const opaqueObjects = currentRenderList.opaque; + const transmissiveObjects = currentRenderList.transmissive; + const transparentObjects = currentRenderList.transparent; + + currentRenderState.setupLightsView( camera ); + + if ( _clippingEnabled === true ) clipping.setGlobalState( _this.clippingPlanes, camera ); + + if ( viewport ) state.viewport( _currentViewport.copy( viewport ) ); + + if ( opaqueObjects.length > 0 ) renderObjects( opaqueObjects, scene, camera ); + if ( transmissiveObjects.length > 0 ) renderObjects( transmissiveObjects, scene, camera ); + if ( transparentObjects.length > 0 ) renderObjects( transparentObjects, scene, camera ); + + // Ensure depth buffer writing is enabled so it can be cleared on next render + + state.buffers.depth.setTest( true ); + state.buffers.depth.setMask( true ); + state.buffers.color.setMask( true ); + + state.setPolygonOffset( false ); + + } + + function renderTransmissionPass( opaqueObjects, transmissiveObjects, scene, camera ) { + + const overrideMaterial = scene.isScene === true ? scene.overrideMaterial : null; + + if ( overrideMaterial !== null ) { + + return; + + } + + if ( currentRenderState.state.transmissionRenderTarget[ camera.id ] === undefined ) { + + currentRenderState.state.transmissionRenderTarget[ camera.id ] = new WebGLRenderTarget( 1, 1, { + generateMipmaps: true, + type: ( extensions.has( 'EXT_color_buffer_half_float' ) || extensions.has( 'EXT_color_buffer_float' ) ) ? HalfFloatType : UnsignedByteType, + minFilter: LinearMipmapLinearFilter, + samples: 4, + stencilBuffer: stencil, + resolveDepthBuffer: false, + resolveStencilBuffer: false, + colorSpace: ColorManagement.workingColorSpace, + } ); + + // debug + + /* + const geometry = new PlaneGeometry(); + const material = new MeshBasicMaterial( { map: _transmissionRenderTarget.texture } ); + + const mesh = new Mesh( geometry, material ); + scene.add( mesh ); + */ + + } + + const transmissionRenderTarget = currentRenderState.state.transmissionRenderTarget[ camera.id ]; + + const activeViewport = camera.viewport || _currentViewport; + transmissionRenderTarget.setSize( activeViewport.z, activeViewport.w ); + + // + + const currentRenderTarget = _this.getRenderTarget(); + _this.setRenderTarget( transmissionRenderTarget ); + + _this.getClearColor( _currentClearColor ); + _currentClearAlpha = _this.getClearAlpha(); + if ( _currentClearAlpha < 1 ) _this.setClearColor( 0xffffff, 0.5 ); + + if ( _renderBackground ) { + + background.render( scene ); + + } else { + + _this.clear(); + + } + + // Turn off the features which can affect the frag color for opaque objects pass. + // Otherwise they are applied twice in opaque objects pass and transmission objects pass. + const currentToneMapping = _this.toneMapping; + _this.toneMapping = NoToneMapping; + + // Remove viewport from camera to avoid nested render calls resetting viewport to it (e.g Reflector). + // Transmission render pass requires viewport to match the transmissionRenderTarget. + const currentCameraViewport = camera.viewport; + if ( camera.viewport !== undefined ) camera.viewport = undefined; + + currentRenderState.setupLightsView( camera ); + + if ( _clippingEnabled === true ) clipping.setGlobalState( _this.clippingPlanes, camera ); + + renderObjects( opaqueObjects, scene, camera ); + + textures.updateMultisampleRenderTarget( transmissionRenderTarget ); + textures.updateRenderTargetMipmap( transmissionRenderTarget ); + + if ( extensions.has( 'WEBGL_multisampled_render_to_texture' ) === false ) { // see #28131 + + let renderTargetNeedsUpdate = false; + + for ( let i = 0, l = transmissiveObjects.length; i < l; i ++ ) { + + const renderItem = transmissiveObjects[ i ]; + + const object = renderItem.object; + const geometry = renderItem.geometry; + const material = renderItem.material; + const group = renderItem.group; + + if ( material.side === DoubleSide && object.layers.test( camera.layers ) ) { + + const currentSide = material.side; + + material.side = BackSide; + material.needsUpdate = true; + + renderObject( object, scene, camera, geometry, material, group ); + + material.side = currentSide; + material.needsUpdate = true; + + renderTargetNeedsUpdate = true; + + } + + } + + if ( renderTargetNeedsUpdate === true ) { + + textures.updateMultisampleRenderTarget( transmissionRenderTarget ); + textures.updateRenderTargetMipmap( transmissionRenderTarget ); + + } + + } + + _this.setRenderTarget( currentRenderTarget ); + + _this.setClearColor( _currentClearColor, _currentClearAlpha ); + + if ( currentCameraViewport !== undefined ) camera.viewport = currentCameraViewport; + + _this.toneMapping = currentToneMapping; + + } + + function renderObjects( renderList, scene, camera ) { + + const overrideMaterial = scene.isScene === true ? scene.overrideMaterial : null; + + for ( let i = 0, l = renderList.length; i < l; i ++ ) { + + const renderItem = renderList[ i ]; + + const object = renderItem.object; + const geometry = renderItem.geometry; + const material = overrideMaterial === null ? renderItem.material : overrideMaterial; + const group = renderItem.group; + + if ( object.layers.test( camera.layers ) ) { + + renderObject( object, scene, camera, geometry, material, group ); + + } + + } + + } + + function renderObject( object, scene, camera, geometry, material, group ) { + + object.onBeforeRender( _this, scene, camera, geometry, material, group ); + + object.modelViewMatrix.multiplyMatrices( camera.matrixWorldInverse, object.matrixWorld ); + object.normalMatrix.getNormalMatrix( object.modelViewMatrix ); + + material.onBeforeRender( _this, scene, camera, geometry, object, group ); + + if ( material.transparent === true && material.side === DoubleSide && material.forceSinglePass === false ) { + + material.side = BackSide; + material.needsUpdate = true; + _this.renderBufferDirect( camera, scene, geometry, material, object, group ); + + material.side = FrontSide; + material.needsUpdate = true; + _this.renderBufferDirect( camera, scene, geometry, material, object, group ); + + material.side = DoubleSide; + + } else { + + _this.renderBufferDirect( camera, scene, geometry, material, object, group ); + + } + + object.onAfterRender( _this, scene, camera, geometry, material, group ); + + } + + function getProgram( material, scene, object ) { + + if ( scene.isScene !== true ) scene = _emptyScene; // scene could be a Mesh, Line, Points, ... + + const materialProperties = properties.get( material ); + + const lights = currentRenderState.state.lights; + const shadowsArray = currentRenderState.state.shadowsArray; + + const lightsStateVersion = lights.state.version; + + const parameters = programCache.getParameters( material, lights.state, shadowsArray, scene, object ); + const programCacheKey = programCache.getProgramCacheKey( parameters ); + + let programs = materialProperties.programs; + + // always update environment and fog - changing these trigger an getProgram call, but it's possible that the program doesn't change + + materialProperties.environment = material.isMeshStandardMaterial ? scene.environment : null; + materialProperties.fog = scene.fog; + materialProperties.envMap = ( material.isMeshStandardMaterial ? cubeuvmaps : cubemaps ).get( material.envMap || materialProperties.environment ); + materialProperties.envMapRotation = ( materialProperties.environment !== null && material.envMap === null ) ? scene.environmentRotation : material.envMapRotation; + + if ( programs === undefined ) { + + // new material + + material.addEventListener( 'dispose', onMaterialDispose ); + + programs = new Map(); + materialProperties.programs = programs; + + } + + let program = programs.get( programCacheKey ); + + if ( program !== undefined ) { + + // early out if program and light state is identical + + if ( materialProperties.currentProgram === program && materialProperties.lightsStateVersion === lightsStateVersion ) { + + updateCommonMaterialProperties( material, parameters ); + + return program; + + } + + } else { + + parameters.uniforms = programCache.getUniforms( material ); + + material.onBuild( object, parameters, _this ); + + material.onBeforeCompile( parameters, _this ); + + program = programCache.acquireProgram( parameters, programCacheKey ); + programs.set( programCacheKey, program ); + + materialProperties.uniforms = parameters.uniforms; + + } + + const uniforms = materialProperties.uniforms; + + if ( ( ! material.isShaderMaterial && ! material.isRawShaderMaterial ) || material.clipping === true ) { + + uniforms.clippingPlanes = clipping.uniform; + + } + + updateCommonMaterialProperties( material, parameters ); + + // store the light setup it was created for + + materialProperties.needsLights = materialNeedsLights( material ); + materialProperties.lightsStateVersion = lightsStateVersion; + + if ( materialProperties.needsLights ) { + + // wire up the material to this renderer's lighting state + + uniforms.ambientLightColor.value = lights.state.ambient; + uniforms.lightProbe.value = lights.state.probe; + uniforms.directionalLights.value = lights.state.directional; + uniforms.directionalLightShadows.value = lights.state.directionalShadow; + uniforms.spotLights.value = lights.state.spot; + uniforms.spotLightShadows.value = lights.state.spotShadow; + uniforms.rectAreaLights.value = lights.state.rectArea; + uniforms.ltc_1.value = lights.state.rectAreaLTC1; + uniforms.ltc_2.value = lights.state.rectAreaLTC2; + uniforms.pointLights.value = lights.state.point; + uniforms.pointLightShadows.value = lights.state.pointShadow; + uniforms.hemisphereLights.value = lights.state.hemi; + + uniforms.directionalShadowMap.value = lights.state.directionalShadowMap; + uniforms.directionalShadowMatrix.value = lights.state.directionalShadowMatrix; + uniforms.spotShadowMap.value = lights.state.spotShadowMap; + uniforms.spotLightMatrix.value = lights.state.spotLightMatrix; + uniforms.spotLightMap.value = lights.state.spotLightMap; + uniforms.pointShadowMap.value = lights.state.pointShadowMap; + uniforms.pointShadowMatrix.value = lights.state.pointShadowMatrix; + // TODO (abelnation): add area lights shadow info to uniforms + + } + + materialProperties.currentProgram = program; + materialProperties.uniformsList = null; + + return program; + + } + + function getUniformList( materialProperties ) { + + if ( materialProperties.uniformsList === null ) { + + const progUniforms = materialProperties.currentProgram.getUniforms(); + materialProperties.uniformsList = WebGLUniforms.seqWithValue( progUniforms.seq, materialProperties.uniforms ); + + } + + return materialProperties.uniformsList; + + } + + function updateCommonMaterialProperties( material, parameters ) { + + const materialProperties = properties.get( material ); + + materialProperties.outputColorSpace = parameters.outputColorSpace; + materialProperties.batching = parameters.batching; + materialProperties.batchingColor = parameters.batchingColor; + materialProperties.instancing = parameters.instancing; + materialProperties.instancingColor = parameters.instancingColor; + materialProperties.instancingMorph = parameters.instancingMorph; + materialProperties.skinning = parameters.skinning; + materialProperties.morphTargets = parameters.morphTargets; + materialProperties.morphNormals = parameters.morphNormals; + materialProperties.morphColors = parameters.morphColors; + materialProperties.morphTargetsCount = parameters.morphTargetsCount; + materialProperties.numClippingPlanes = parameters.numClippingPlanes; + materialProperties.numIntersection = parameters.numClipIntersection; + materialProperties.vertexAlphas = parameters.vertexAlphas; + materialProperties.vertexTangents = parameters.vertexTangents; + materialProperties.toneMapping = parameters.toneMapping; + + } + + function setProgram( camera, scene, geometry, material, object ) { + + if ( scene.isScene !== true ) scene = _emptyScene; // scene could be a Mesh, Line, Points, ... + + textures.resetTextureUnits(); + + const fog = scene.fog; + const environment = material.isMeshStandardMaterial ? scene.environment : null; + const colorSpace = ( _currentRenderTarget === null ) ? _this.outputColorSpace : ( _currentRenderTarget.isXRRenderTarget === true ? _currentRenderTarget.texture.colorSpace : LinearSRGBColorSpace ); + const envMap = ( material.isMeshStandardMaterial ? cubeuvmaps : cubemaps ).get( material.envMap || environment ); + const vertexAlphas = material.vertexColors === true && !! geometry.attributes.color && geometry.attributes.color.itemSize === 4; + const vertexTangents = !! geometry.attributes.tangent && ( !! material.normalMap || material.anisotropy > 0 ); + const morphTargets = !! geometry.morphAttributes.position; + const morphNormals = !! geometry.morphAttributes.normal; + const morphColors = !! geometry.morphAttributes.color; + + let toneMapping = NoToneMapping; + + if ( material.toneMapped ) { + + if ( _currentRenderTarget === null || _currentRenderTarget.isXRRenderTarget === true ) { + + toneMapping = _this.toneMapping; + + } + + } + + const morphAttribute = geometry.morphAttributes.position || geometry.morphAttributes.normal || geometry.morphAttributes.color; + const morphTargetsCount = ( morphAttribute !== undefined ) ? morphAttribute.length : 0; + + const materialProperties = properties.get( material ); + const lights = currentRenderState.state.lights; + + if ( _clippingEnabled === true ) { + + if ( _localClippingEnabled === true || camera !== _currentCamera ) { + + const useCache = + camera === _currentCamera && + material.id === _currentMaterialId; + + // we might want to call this function with some ClippingGroup + // object instead of the material, once it becomes feasible + // (#8465, #8379) + clipping.setState( material, camera, useCache ); + + } + + } + + // + + let needsProgramChange = false; + + if ( material.version === materialProperties.__version ) { + + if ( materialProperties.needsLights && ( materialProperties.lightsStateVersion !== lights.state.version ) ) { + + needsProgramChange = true; + + } else if ( materialProperties.outputColorSpace !== colorSpace ) { + + needsProgramChange = true; + + } else if ( object.isBatchedMesh && materialProperties.batching === false ) { + + needsProgramChange = true; + + } else if ( ! object.isBatchedMesh && materialProperties.batching === true ) { + + needsProgramChange = true; + + } else if ( object.isBatchedMesh && materialProperties.batchingColor === true && object.colorTexture === null ) { + + needsProgramChange = true; + + } else if ( object.isBatchedMesh && materialProperties.batchingColor === false && object.colorTexture !== null ) { + + needsProgramChange = true; + + } else if ( object.isInstancedMesh && materialProperties.instancing === false ) { + + needsProgramChange = true; + + } else if ( ! object.isInstancedMesh && materialProperties.instancing === true ) { + + needsProgramChange = true; + + } else if ( object.isSkinnedMesh && materialProperties.skinning === false ) { + + needsProgramChange = true; + + } else if ( ! object.isSkinnedMesh && materialProperties.skinning === true ) { + + needsProgramChange = true; + + } else if ( object.isInstancedMesh && materialProperties.instancingColor === true && object.instanceColor === null ) { + + needsProgramChange = true; + + } else if ( object.isInstancedMesh && materialProperties.instancingColor === false && object.instanceColor !== null ) { + + needsProgramChange = true; + + } else if ( object.isInstancedMesh && materialProperties.instancingMorph === true && object.morphTexture === null ) { + + needsProgramChange = true; + + } else if ( object.isInstancedMesh && materialProperties.instancingMorph === false && object.morphTexture !== null ) { + + needsProgramChange = true; + + } else if ( materialProperties.envMap !== envMap ) { + + needsProgramChange = true; + + } else if ( material.fog === true && materialProperties.fog !== fog ) { + + needsProgramChange = true; + + } else if ( materialProperties.numClippingPlanes !== undefined && + ( materialProperties.numClippingPlanes !== clipping.numPlanes || + materialProperties.numIntersection !== clipping.numIntersection ) ) { + + needsProgramChange = true; + + } else if ( materialProperties.vertexAlphas !== vertexAlphas ) { + + needsProgramChange = true; + + } else if ( materialProperties.vertexTangents !== vertexTangents ) { + + needsProgramChange = true; + + } else if ( materialProperties.morphTargets !== morphTargets ) { + + needsProgramChange = true; + + } else if ( materialProperties.morphNormals !== morphNormals ) { + + needsProgramChange = true; + + } else if ( materialProperties.morphColors !== morphColors ) { + + needsProgramChange = true; + + } else if ( materialProperties.toneMapping !== toneMapping ) { + + needsProgramChange = true; + + } else if ( materialProperties.morphTargetsCount !== morphTargetsCount ) { + + needsProgramChange = true; + + } + + } else { + + needsProgramChange = true; + materialProperties.__version = material.version; + + } + + // + + let program = materialProperties.currentProgram; + + if ( needsProgramChange === true ) { + + program = getProgram( material, scene, object ); + + } + + let refreshProgram = false; + let refreshMaterial = false; + let refreshLights = false; + + const p_uniforms = program.getUniforms(), + m_uniforms = materialProperties.uniforms; + + if ( state.useProgram( program.program ) ) { + + refreshProgram = true; + refreshMaterial = true; + refreshLights = true; + + } + + if ( material.id !== _currentMaterialId ) { + + _currentMaterialId = material.id; + + refreshMaterial = true; + + } + + if ( refreshProgram || _currentCamera !== camera ) { + + // common camera uniforms + + p_uniforms.setValue( _gl, 'projectionMatrix', camera.projectionMatrix ); + p_uniforms.setValue( _gl, 'viewMatrix', camera.matrixWorldInverse ); + + const uCamPos = p_uniforms.map.cameraPosition; + + if ( uCamPos !== undefined ) { + + uCamPos.setValue( _gl, _vector3.setFromMatrixPosition( camera.matrixWorld ) ); + + } + + if ( capabilities.logarithmicDepthBuffer ) { + + p_uniforms.setValue( _gl, 'logDepthBufFC', + 2.0 / ( Math.log( camera.far + 1.0 ) / Math.LN2 ) ); + + } + + // consider moving isOrthographic to UniformLib and WebGLMaterials, see https://github.com/mrdoob/three.js/pull/26467#issuecomment-1645185067 + + if ( material.isMeshPhongMaterial || + material.isMeshToonMaterial || + material.isMeshLambertMaterial || + material.isMeshBasicMaterial || + material.isMeshStandardMaterial || + material.isShaderMaterial ) { + + p_uniforms.setValue( _gl, 'isOrthographic', camera.isOrthographicCamera === true ); + + } + + if ( _currentCamera !== camera ) { + + _currentCamera = camera; + + // lighting uniforms depend on the camera so enforce an update + // now, in case this material supports lights - or later, when + // the next material that does gets activated: + + refreshMaterial = true; // set to true on material change + refreshLights = true; // remains set until update done + + } + + } + + // skinning and morph target uniforms must be set even if material didn't change + // auto-setting of texture unit for bone and morph texture must go before other textures + // otherwise textures used for skinning and morphing can take over texture units reserved for other material textures + + if ( object.isSkinnedMesh ) { + + p_uniforms.setOptional( _gl, object, 'bindMatrix' ); + p_uniforms.setOptional( _gl, object, 'bindMatrixInverse' ); + + const skeleton = object.skeleton; + + if ( skeleton ) { + + if ( skeleton.boneTexture === null ) skeleton.computeBoneTexture(); + + p_uniforms.setValue( _gl, 'boneTexture', skeleton.boneTexture, textures ); + + } + + } + + if ( object.isBatchedMesh ) { + + p_uniforms.setOptional( _gl, object, 'batchingTexture' ); + p_uniforms.setValue( _gl, 'batchingTexture', object._matricesTexture, textures ); + + p_uniforms.setOptional( _gl, object, 'batchingColorTexture' ); + if ( object._colorsTexture !== null ) { + + p_uniforms.setValue( _gl, 'batchingColorTexture', object._colorsTexture, textures ); + + } + + } + + const morphAttributes = geometry.morphAttributes; + + if ( morphAttributes.position !== undefined || morphAttributes.normal !== undefined || ( morphAttributes.color !== undefined ) ) { + + morphtargets.update( object, geometry, program ); + + } + + if ( refreshMaterial || materialProperties.receiveShadow !== object.receiveShadow ) { + + materialProperties.receiveShadow = object.receiveShadow; + p_uniforms.setValue( _gl, 'receiveShadow', object.receiveShadow ); + + } + + // https://github.com/mrdoob/three.js/pull/24467#issuecomment-1209031512 + + if ( material.isMeshGouraudMaterial && material.envMap !== null ) { + + m_uniforms.envMap.value = envMap; + + m_uniforms.flipEnvMap.value = ( envMap.isCubeTexture && envMap.isRenderTargetTexture === false ) ? - 1 : 1; + + } + + if ( material.isMeshStandardMaterial && material.envMap === null && scene.environment !== null ) { + + m_uniforms.envMapIntensity.value = scene.environmentIntensity; + + } + + if ( refreshMaterial ) { + + p_uniforms.setValue( _gl, 'toneMappingExposure', _this.toneMappingExposure ); + + if ( materialProperties.needsLights ) { + + // the current material requires lighting info + + // note: all lighting uniforms are always set correctly + // they simply reference the renderer's state for their + // values + // + // use the current material's .needsUpdate flags to set + // the GL state when required + + markUniformsLightsNeedsUpdate( m_uniforms, refreshLights ); + + } + + // refresh uniforms common to several materials + + if ( fog && material.fog === true ) { + + materials.refreshFogUniforms( m_uniforms, fog ); + + } + + materials.refreshMaterialUniforms( m_uniforms, material, _pixelRatio, _height, currentRenderState.state.transmissionRenderTarget[ camera.id ] ); + + WebGLUniforms.upload( _gl, getUniformList( materialProperties ), m_uniforms, textures ); + + } + + if ( material.isShaderMaterial && material.uniformsNeedUpdate === true ) { + + WebGLUniforms.upload( _gl, getUniformList( materialProperties ), m_uniforms, textures ); + material.uniformsNeedUpdate = false; + + } + + if ( material.isSpriteMaterial ) { + + p_uniforms.setValue( _gl, 'center', object.center ); + + } + + // common matrices + + p_uniforms.setValue( _gl, 'modelViewMatrix', object.modelViewMatrix ); + p_uniforms.setValue( _gl, 'normalMatrix', object.normalMatrix ); + p_uniforms.setValue( _gl, 'modelMatrix', object.matrixWorld ); + + // UBOs + + if ( material.isShaderMaterial || material.isRawShaderMaterial ) { + + const groups = material.uniformsGroups; + + for ( let i = 0, l = groups.length; i < l; i ++ ) { + + const group = groups[ i ]; + + uniformsGroups.update( group, program ); + uniformsGroups.bind( group, program ); + + } + + } + + return program; + + } + + // If uniforms are marked as clean, they don't need to be loaded to the GPU. + + function markUniformsLightsNeedsUpdate( uniforms, value ) { + + uniforms.ambientLightColor.needsUpdate = value; + uniforms.lightProbe.needsUpdate = value; + + uniforms.directionalLights.needsUpdate = value; + uniforms.directionalLightShadows.needsUpdate = value; + uniforms.pointLights.needsUpdate = value; + uniforms.pointLightShadows.needsUpdate = value; + uniforms.spotLights.needsUpdate = value; + uniforms.spotLightShadows.needsUpdate = value; + uniforms.rectAreaLights.needsUpdate = value; + uniforms.hemisphereLights.needsUpdate = value; + + } + + function materialNeedsLights( material ) { + + return material.isMeshLambertMaterial || material.isMeshToonMaterial || material.isMeshPhongMaterial || + material.isMeshStandardMaterial || material.isShadowMaterial || + ( material.isShaderMaterial && material.lights === true ); + + } + + this.getActiveCubeFace = function () { + + return _currentActiveCubeFace; + + }; + + this.getActiveMipmapLevel = function () { + + return _currentActiveMipmapLevel; + + }; + + this.getRenderTarget = function () { + + return _currentRenderTarget; + + }; + + this.setRenderTargetTextures = function ( renderTarget, colorTexture, depthTexture ) { + + properties.get( renderTarget.texture ).__webglTexture = colorTexture; + properties.get( renderTarget.depthTexture ).__webglTexture = depthTexture; + + const renderTargetProperties = properties.get( renderTarget ); + renderTargetProperties.__hasExternalTextures = true; + + renderTargetProperties.__autoAllocateDepthBuffer = depthTexture === undefined; + + if ( ! renderTargetProperties.__autoAllocateDepthBuffer ) { + + // The multisample_render_to_texture extension doesn't work properly if there + // are midframe flushes and an external depth buffer. Disable use of the extension. + if ( extensions.has( 'WEBGL_multisampled_render_to_texture' ) === true ) { + + console.warn( 'THREE.WebGLRenderer: Render-to-texture extension was disabled because an external texture was provided' ); + renderTargetProperties.__useRenderToTexture = false; + + } + + } + + }; + + this.setRenderTargetFramebuffer = function ( renderTarget, defaultFramebuffer ) { + + const renderTargetProperties = properties.get( renderTarget ); + renderTargetProperties.__webglFramebuffer = defaultFramebuffer; + renderTargetProperties.__useDefaultFramebuffer = defaultFramebuffer === undefined; + + }; + + this.setRenderTarget = function ( renderTarget, activeCubeFace = 0, activeMipmapLevel = 0 ) { + + _currentRenderTarget = renderTarget; + _currentActiveCubeFace = activeCubeFace; + _currentActiveMipmapLevel = activeMipmapLevel; + + let useDefaultFramebuffer = true; + let framebuffer = null; + let isCube = false; + let isRenderTarget3D = false; + + if ( renderTarget ) { + + const renderTargetProperties = properties.get( renderTarget ); + + if ( renderTargetProperties.__useDefaultFramebuffer !== undefined ) { + + // We need to make sure to rebind the framebuffer. + state.bindFramebuffer( _gl.FRAMEBUFFER, null ); + useDefaultFramebuffer = false; + + } else if ( renderTargetProperties.__webglFramebuffer === undefined ) { + + textures.setupRenderTarget( renderTarget ); + + } else if ( renderTargetProperties.__hasExternalTextures ) { + + // Color and depth texture must be rebound in order for the swapchain to update. + textures.rebindTextures( renderTarget, properties.get( renderTarget.texture ).__webglTexture, properties.get( renderTarget.depthTexture ).__webglTexture ); + + } + + const texture = renderTarget.texture; + + if ( texture.isData3DTexture || texture.isDataArrayTexture || texture.isCompressedArrayTexture ) { + + isRenderTarget3D = true; + + } + + const __webglFramebuffer = properties.get( renderTarget ).__webglFramebuffer; + + if ( renderTarget.isWebGLCubeRenderTarget ) { + + if ( Array.isArray( __webglFramebuffer[ activeCubeFace ] ) ) { + + framebuffer = __webglFramebuffer[ activeCubeFace ][ activeMipmapLevel ]; + + } else { + + framebuffer = __webglFramebuffer[ activeCubeFace ]; + + } + + isCube = true; + + } else if ( ( renderTarget.samples > 0 ) && textures.useMultisampledRTT( renderTarget ) === false ) { + + framebuffer = properties.get( renderTarget ).__webglMultisampledFramebuffer; + + } else { + + if ( Array.isArray( __webglFramebuffer ) ) { + + framebuffer = __webglFramebuffer[ activeMipmapLevel ]; + + } else { + + framebuffer = __webglFramebuffer; + + } + + } + + _currentViewport.copy( renderTarget.viewport ); + _currentScissor.copy( renderTarget.scissor ); + _currentScissorTest = renderTarget.scissorTest; + + } else { + + _currentViewport.copy( _viewport ).multiplyScalar( _pixelRatio ).floor(); + _currentScissor.copy( _scissor ).multiplyScalar( _pixelRatio ).floor(); + _currentScissorTest = _scissorTest; + + } + + const framebufferBound = state.bindFramebuffer( _gl.FRAMEBUFFER, framebuffer ); + + if ( framebufferBound && useDefaultFramebuffer ) { + + state.drawBuffers( renderTarget, framebuffer ); + + } + + state.viewport( _currentViewport ); + state.scissor( _currentScissor ); + state.setScissorTest( _currentScissorTest ); + + if ( isCube ) { + + const textureProperties = properties.get( renderTarget.texture ); + _gl.framebufferTexture2D( _gl.FRAMEBUFFER, _gl.COLOR_ATTACHMENT0, _gl.TEXTURE_CUBE_MAP_POSITIVE_X + activeCubeFace, textureProperties.__webglTexture, activeMipmapLevel ); + + } else if ( isRenderTarget3D ) { + + const textureProperties = properties.get( renderTarget.texture ); + const layer = activeCubeFace || 0; + _gl.framebufferTextureLayer( _gl.FRAMEBUFFER, _gl.COLOR_ATTACHMENT0, textureProperties.__webglTexture, activeMipmapLevel || 0, layer ); + + } + + _currentMaterialId = - 1; // reset current material to ensure correct uniform bindings + + }; + + this.readRenderTargetPixels = function ( renderTarget, x, y, width, height, buffer, activeCubeFaceIndex ) { + + if ( ! ( renderTarget && renderTarget.isWebGLRenderTarget ) ) { + + console.error( 'THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not THREE.WebGLRenderTarget.' ); + return; + + } + + let framebuffer = properties.get( renderTarget ).__webglFramebuffer; + + if ( renderTarget.isWebGLCubeRenderTarget && activeCubeFaceIndex !== undefined ) { + + framebuffer = framebuffer[ activeCubeFaceIndex ]; + + } + + if ( framebuffer ) { + + state.bindFramebuffer( _gl.FRAMEBUFFER, framebuffer ); + + try { + + const texture = renderTarget.texture; + const textureFormat = texture.format; + const textureType = texture.type; + + if ( ! capabilities.textureFormatReadable( textureFormat ) ) { + + console.error( 'THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not in RGBA or implementation defined format.' ); + return; + + } + + if ( ! capabilities.textureTypeReadable( textureType ) ) { + + console.error( 'THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not in UnsignedByteType or implementation defined type.' ); + return; + + } + + // the following if statement ensures valid read requests (no out-of-bounds pixels, see #8604) + + if ( ( x >= 0 && x <= ( renderTarget.width - width ) ) && ( y >= 0 && y <= ( renderTarget.height - height ) ) ) { + + _gl.readPixels( x, y, width, height, utils.convert( textureFormat ), utils.convert( textureType ), buffer ); + + } + + } finally { + + // restore framebuffer of current render target if necessary + + const framebuffer = ( _currentRenderTarget !== null ) ? properties.get( _currentRenderTarget ).__webglFramebuffer : null; + state.bindFramebuffer( _gl.FRAMEBUFFER, framebuffer ); + + } + + } + + }; + + this.readRenderTargetPixelsAsync = async function ( renderTarget, x, y, width, height, buffer, activeCubeFaceIndex ) { + + if ( ! ( renderTarget && renderTarget.isWebGLRenderTarget ) ) { + + throw new Error( 'THREE.WebGLRenderer.readRenderTargetPixels: renderTarget is not THREE.WebGLRenderTarget.' ); + + } + + let framebuffer = properties.get( renderTarget ).__webglFramebuffer; + if ( renderTarget.isWebGLCubeRenderTarget && activeCubeFaceIndex !== undefined ) { + + framebuffer = framebuffer[ activeCubeFaceIndex ]; + + } + + if ( framebuffer ) { + + state.bindFramebuffer( _gl.FRAMEBUFFER, framebuffer ); + + try { + + const texture = renderTarget.texture; + const textureFormat = texture.format; + const textureType = texture.type; + + if ( ! capabilities.textureFormatReadable( textureFormat ) ) { + + throw new Error( 'THREE.WebGLRenderer.readRenderTargetPixelsAsync: renderTarget is not in RGBA or implementation defined format.' ); + + } + + if ( ! capabilities.textureTypeReadable( textureType ) ) { + + throw new Error( 'THREE.WebGLRenderer.readRenderTargetPixelsAsync: renderTarget is not in UnsignedByteType or implementation defined type.' ); + + } + + // the following if statement ensures valid read requests (no out-of-bounds pixels, see #8604) + if ( ( x >= 0 && x <= ( renderTarget.width - width ) ) && ( y >= 0 && y <= ( renderTarget.height - height ) ) ) { + + const glBuffer = _gl.createBuffer(); + _gl.bindBuffer( _gl.PIXEL_PACK_BUFFER, glBuffer ); + _gl.bufferData( _gl.PIXEL_PACK_BUFFER, buffer.byteLength, _gl.STREAM_READ ); + _gl.readPixels( x, y, width, height, utils.convert( textureFormat ), utils.convert( textureType ), 0 ); + _gl.flush(); + + // check if the commands have finished every 8 ms + const sync = _gl.fenceSync( _gl.SYNC_GPU_COMMANDS_COMPLETE, 0 ); + await probeAsync( _gl, sync, 4 ); + + try { + + _gl.bindBuffer( _gl.PIXEL_PACK_BUFFER, glBuffer ); + _gl.getBufferSubData( _gl.PIXEL_PACK_BUFFER, 0, buffer ); + + } finally { + + _gl.deleteBuffer( glBuffer ); + _gl.deleteSync( sync ); + + } + + return buffer; + + } + + } finally { + + // restore framebuffer of current render target if necessary + + const framebuffer = ( _currentRenderTarget !== null ) ? properties.get( _currentRenderTarget ).__webglFramebuffer : null; + state.bindFramebuffer( _gl.FRAMEBUFFER, framebuffer ); + + } + + } + + }; + + this.copyFramebufferToTexture = function ( texture, position = null, level = 0 ) { + + // support previous signature with position first + if ( texture.isTexture !== true ) { + + // @deprecated, r165 + console.warn( 'WebGLRenderer: copyFramebufferToTexture function signature has changed.' ); + + position = arguments[ 0 ] || null; + texture = arguments[ 1 ]; + + } + + const levelScale = Math.pow( 2, - level ); + const width = Math.floor( texture.image.width * levelScale ); + const height = Math.floor( texture.image.height * levelScale ); + + const x = position !== null ? position.x : 0; + const y = position !== null ? position.y : 0; + + textures.setTexture2D( texture, 0 ); + + _gl.copyTexSubImage2D( _gl.TEXTURE_2D, level, 0, 0, x, y, width, height ); + + state.unbindTexture(); + + }; + + this.copyTextureToTexture = function ( srcTexture, dstTexture, srcRegion = null, dstPosition = null, level = 0 ) { + + // support previous signature with dstPosition first + if ( srcTexture.isTexture !== true ) { + + // @deprecated, r165 + console.warn( 'WebGLRenderer: copyTextureToTexture function signature has changed.' ); + + dstPosition = arguments[ 0 ] || null; + srcTexture = arguments[ 1 ]; + dstTexture = arguments[ 2 ]; + level = arguments[ 3 ] || 0; + srcRegion = null; + + } + + let width, height, minX, minY; + let dstX, dstY; + if ( srcRegion !== null ) { + + width = srcRegion.max.x - srcRegion.min.x; + height = srcRegion.max.y - srcRegion.min.y; + minX = srcRegion.min.x; + minY = srcRegion.min.y; + + } else { + + width = srcTexture.image.width; + height = srcTexture.image.height; + minX = 0; + minY = 0; + + } + + if ( dstPosition !== null ) { + + dstX = dstPosition.x; + dstY = dstPosition.y; + + } else { + + dstX = 0; + dstY = 0; + + } + + const glFormat = utils.convert( dstTexture.format ); + const glType = utils.convert( dstTexture.type ); + + textures.setTexture2D( dstTexture, 0 ); + + // As another texture upload may have changed pixelStorei + // parameters, make sure they are correct for the dstTexture + _gl.pixelStorei( _gl.UNPACK_FLIP_Y_WEBGL, dstTexture.flipY ); + _gl.pixelStorei( _gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, dstTexture.premultiplyAlpha ); + _gl.pixelStorei( _gl.UNPACK_ALIGNMENT, dstTexture.unpackAlignment ); + + const currentUnpackRowLen = _gl.getParameter( _gl.UNPACK_ROW_LENGTH ); + const currentUnpackImageHeight = _gl.getParameter( _gl.UNPACK_IMAGE_HEIGHT ); + const currentUnpackSkipPixels = _gl.getParameter( _gl.UNPACK_SKIP_PIXELS ); + const currentUnpackSkipRows = _gl.getParameter( _gl.UNPACK_SKIP_ROWS ); + const currentUnpackSkipImages = _gl.getParameter( _gl.UNPACK_SKIP_IMAGES ); + + const image = srcTexture.isCompressedTexture ? srcTexture.mipmaps[ level ] : srcTexture.image; + + _gl.pixelStorei( _gl.UNPACK_ROW_LENGTH, image.width ); + _gl.pixelStorei( _gl.UNPACK_IMAGE_HEIGHT, image.height ); + _gl.pixelStorei( _gl.UNPACK_SKIP_PIXELS, minX ); + _gl.pixelStorei( _gl.UNPACK_SKIP_ROWS, minY ); + + if ( srcTexture.isDataTexture ) { + + _gl.texSubImage2D( _gl.TEXTURE_2D, level, dstX, dstY, width, height, glFormat, glType, image.data ); + + } else { + + if ( srcTexture.isCompressedTexture ) { + + _gl.compressedTexSubImage2D( _gl.TEXTURE_2D, level, dstX, dstY, image.width, image.height, glFormat, image.data ); + + } else { + + _gl.texSubImage2D( _gl.TEXTURE_2D, level, dstX, dstY, glFormat, glType, image ); + + } + + } + + _gl.pixelStorei( _gl.UNPACK_ROW_LENGTH, currentUnpackRowLen ); + _gl.pixelStorei( _gl.UNPACK_IMAGE_HEIGHT, currentUnpackImageHeight ); + _gl.pixelStorei( _gl.UNPACK_SKIP_PIXELS, currentUnpackSkipPixels ); + _gl.pixelStorei( _gl.UNPACK_SKIP_ROWS, currentUnpackSkipRows ); + _gl.pixelStorei( _gl.UNPACK_SKIP_IMAGES, currentUnpackSkipImages ); + + // Generate mipmaps only when copying level 0 + if ( level === 0 && dstTexture.generateMipmaps ) _gl.generateMipmap( _gl.TEXTURE_2D ); + + state.unbindTexture(); + + }; + + this.copyTextureToTexture3D = function ( srcTexture, dstTexture, srcRegion = null, dstPosition = null, level = 0 ) { + + // support previous signature with source box first + if ( srcTexture.isTexture !== true ) { + + // @deprecated, r165 + console.warn( 'WebGLRenderer: copyTextureToTexture3D function signature has changed.' ); + + srcRegion = arguments[ 0 ] || null; + dstPosition = arguments[ 1 ] || null; + srcTexture = arguments[ 2 ]; + dstTexture = arguments[ 3 ]; + level = arguments[ 4 ] || 0; + + } + + let width, height, depth, minX, minY, minZ; + let dstX, dstY, dstZ; + const image = srcTexture.isCompressedTexture ? srcTexture.mipmaps[ level ] : srcTexture.image; + if ( srcRegion !== null ) { + + width = srcRegion.max.x - srcRegion.min.x; + height = srcRegion.max.y - srcRegion.min.y; + depth = srcRegion.max.z - srcRegion.min.z; + minX = srcRegion.min.x; + minY = srcRegion.min.y; + minZ = srcRegion.min.z; + + } else { + + width = image.width; + height = image.height; + depth = image.depth; + minX = 0; + minY = 0; + minZ = 0; + + } + + if ( dstPosition !== null ) { + + dstX = dstPosition.x; + dstY = dstPosition.y; + dstZ = dstPosition.z; + + } else { + + dstX = 0; + dstY = 0; + dstZ = 0; + + } + + const glFormat = utils.convert( dstTexture.format ); + const glType = utils.convert( dstTexture.type ); + let glTarget; + + if ( dstTexture.isData3DTexture ) { + + textures.setTexture3D( dstTexture, 0 ); + glTarget = _gl.TEXTURE_3D; + + } else if ( dstTexture.isDataArrayTexture || dstTexture.isCompressedArrayTexture ) { + + textures.setTexture2DArray( dstTexture, 0 ); + glTarget = _gl.TEXTURE_2D_ARRAY; + + } else { + + console.warn( 'THREE.WebGLRenderer.copyTextureToTexture3D: only supports THREE.DataTexture3D and THREE.DataTexture2DArray.' ); + return; + + } + + _gl.pixelStorei( _gl.UNPACK_FLIP_Y_WEBGL, dstTexture.flipY ); + _gl.pixelStorei( _gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, dstTexture.premultiplyAlpha ); + _gl.pixelStorei( _gl.UNPACK_ALIGNMENT, dstTexture.unpackAlignment ); + + const currentUnpackRowLen = _gl.getParameter( _gl.UNPACK_ROW_LENGTH ); + const currentUnpackImageHeight = _gl.getParameter( _gl.UNPACK_IMAGE_HEIGHT ); + const currentUnpackSkipPixels = _gl.getParameter( _gl.UNPACK_SKIP_PIXELS ); + const currentUnpackSkipRows = _gl.getParameter( _gl.UNPACK_SKIP_ROWS ); + const currentUnpackSkipImages = _gl.getParameter( _gl.UNPACK_SKIP_IMAGES ); + + _gl.pixelStorei( _gl.UNPACK_ROW_LENGTH, image.width ); + _gl.pixelStorei( _gl.UNPACK_IMAGE_HEIGHT, image.height ); + _gl.pixelStorei( _gl.UNPACK_SKIP_PIXELS, minX ); + _gl.pixelStorei( _gl.UNPACK_SKIP_ROWS, minY ); + _gl.pixelStorei( _gl.UNPACK_SKIP_IMAGES, minZ ); + + if ( srcTexture.isDataTexture || srcTexture.isData3DTexture ) { + + _gl.texSubImage3D( glTarget, level, dstX, dstY, dstZ, width, height, depth, glFormat, glType, image.data ); + + } else { + + if ( dstTexture.isCompressedArrayTexture ) { + + _gl.compressedTexSubImage3D( glTarget, level, dstX, dstY, dstZ, width, height, depth, glFormat, image.data ); + + } else { + + _gl.texSubImage3D( glTarget, level, dstX, dstY, dstZ, width, height, depth, glFormat, glType, image ); + + } + + } + + _gl.pixelStorei( _gl.UNPACK_ROW_LENGTH, currentUnpackRowLen ); + _gl.pixelStorei( _gl.UNPACK_IMAGE_HEIGHT, currentUnpackImageHeight ); + _gl.pixelStorei( _gl.UNPACK_SKIP_PIXELS, currentUnpackSkipPixels ); + _gl.pixelStorei( _gl.UNPACK_SKIP_ROWS, currentUnpackSkipRows ); + _gl.pixelStorei( _gl.UNPACK_SKIP_IMAGES, currentUnpackSkipImages ); + + // Generate mipmaps only when copying level 0 + if ( level === 0 && dstTexture.generateMipmaps ) _gl.generateMipmap( glTarget ); + + state.unbindTexture(); + + }; + + this.initRenderTarget = function ( target ) { + + if ( properties.get( target ).__webglFramebuffer === undefined ) { + + textures.setupRenderTarget( target ); + + } + + }; + + this.initTexture = function ( texture ) { + + if ( texture.isCubeTexture ) { + + textures.setTextureCube( texture, 0 ); + + } else if ( texture.isData3DTexture ) { + + textures.setTexture3D( texture, 0 ); + + } else if ( texture.isDataArrayTexture || texture.isCompressedArrayTexture ) { + + textures.setTexture2DArray( texture, 0 ); + + } else { + + textures.setTexture2D( texture, 0 ); + + } + + state.unbindTexture(); + + }; + + this.resetState = function () { + + _currentActiveCubeFace = 0; + _currentActiveMipmapLevel = 0; + _currentRenderTarget = null; + + state.reset(); + bindingStates.reset(); + + }; + + if ( typeof __THREE_DEVTOOLS__ !== 'undefined' ) { + + __THREE_DEVTOOLS__.dispatchEvent( new CustomEvent( 'observe', { detail: this } ) ); + + } + + } + + get coordinateSystem() { + + return WebGLCoordinateSystem; + + } + + get outputColorSpace() { + + return this._outputColorSpace; + + } + + set outputColorSpace( colorSpace ) { + + this._outputColorSpace = colorSpace; + + const gl = this.getContext(); + gl.drawingBufferColorSpace = colorSpace === DisplayP3ColorSpace ? 'display-p3' : 'srgb'; + gl.unpackColorSpace = ColorManagement.workingColorSpace === LinearDisplayP3ColorSpace ? 'display-p3' : 'srgb'; + + } + +} + +class FogExp2 { + + constructor( color, density = 0.00025 ) { + + this.isFogExp2 = true; + + this.name = ''; + + this.color = new Color( color ); + this.density = density; + + } + + clone() { + + return new FogExp2( this.color, this.density ); + + } + + toJSON( /* meta */ ) { + + return { + type: 'FogExp2', + name: this.name, + color: this.color.getHex(), + density: this.density + }; + + } + +} + +class Fog { + + constructor( color, near = 1, far = 1000 ) { + + this.isFog = true; + + this.name = ''; + + this.color = new Color( color ); + + this.near = near; + this.far = far; + + } + + clone() { + + return new Fog( this.color, this.near, this.far ); + + } + + toJSON( /* meta */ ) { + + return { + type: 'Fog', + name: this.name, + color: this.color.getHex(), + near: this.near, + far: this.far + }; + + } + +} + +class Scene extends Object3D { + + constructor() { + + super(); + + this.isScene = true; + + this.type = 'Scene'; + + this.background = null; + this.environment = null; + this.fog = null; + + this.backgroundBlurriness = 0; + this.backgroundIntensity = 1; + this.backgroundRotation = new Euler(); + + this.environmentIntensity = 1; + this.environmentRotation = new Euler(); + + this.overrideMaterial = null; + + if ( typeof __THREE_DEVTOOLS__ !== 'undefined' ) { + + __THREE_DEVTOOLS__.dispatchEvent( new CustomEvent( 'observe', { detail: this } ) ); + + } + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + if ( source.background !== null ) this.background = source.background.clone(); + if ( source.environment !== null ) this.environment = source.environment.clone(); + if ( source.fog !== null ) this.fog = source.fog.clone(); + + this.backgroundBlurriness = source.backgroundBlurriness; + this.backgroundIntensity = source.backgroundIntensity; + this.backgroundRotation.copy( source.backgroundRotation ); + + this.environmentIntensity = source.environmentIntensity; + this.environmentRotation.copy( source.environmentRotation ); + + if ( source.overrideMaterial !== null ) this.overrideMaterial = source.overrideMaterial.clone(); + + this.matrixAutoUpdate = source.matrixAutoUpdate; + + return this; + + } + + toJSON( meta ) { + + const data = super.toJSON( meta ); + + if ( this.fog !== null ) data.object.fog = this.fog.toJSON(); + + if ( this.backgroundBlurriness > 0 ) data.object.backgroundBlurriness = this.backgroundBlurriness; + if ( this.backgroundIntensity !== 1 ) data.object.backgroundIntensity = this.backgroundIntensity; + data.object.backgroundRotation = this.backgroundRotation.toArray(); + + if ( this.environmentIntensity !== 1 ) data.object.environmentIntensity = this.environmentIntensity; + data.object.environmentRotation = this.environmentRotation.toArray(); + + return data; + + } + +} + +class InterleavedBuffer { + + constructor( array, stride ) { + + this.isInterleavedBuffer = true; + + this.array = array; + this.stride = stride; + this.count = array !== undefined ? array.length / stride : 0; + + this.usage = StaticDrawUsage; + this._updateRange = { offset: 0, count: - 1 }; + this.updateRanges = []; + + this.version = 0; + + this.uuid = generateUUID(); + + } + + onUploadCallback() {} + + set needsUpdate( value ) { + + if ( value === true ) this.version ++; + + } + + get updateRange() { + + warnOnce( 'THREE.InterleavedBuffer: updateRange() is deprecated and will be removed in r169. Use addUpdateRange() instead.' ); // @deprecated, r159 + return this._updateRange; + + } + + setUsage( value ) { + + this.usage = value; + + return this; + + } + + addUpdateRange( start, count ) { + + this.updateRanges.push( { start, count } ); + + } + + clearUpdateRanges() { + + this.updateRanges.length = 0; + + } + + copy( source ) { + + this.array = new source.array.constructor( source.array ); + this.count = source.count; + this.stride = source.stride; + this.usage = source.usage; + + return this; + + } + + copyAt( index1, attribute, index2 ) { + + index1 *= this.stride; + index2 *= attribute.stride; + + for ( let i = 0, l = this.stride; i < l; i ++ ) { + + this.array[ index1 + i ] = attribute.array[ index2 + i ]; + + } + + return this; + + } + + set( value, offset = 0 ) { + + this.array.set( value, offset ); + + return this; + + } + + clone( data ) { + + if ( data.arrayBuffers === undefined ) { + + data.arrayBuffers = {}; + + } + + if ( this.array.buffer._uuid === undefined ) { + + this.array.buffer._uuid = generateUUID(); + + } + + if ( data.arrayBuffers[ this.array.buffer._uuid ] === undefined ) { + + data.arrayBuffers[ this.array.buffer._uuid ] = this.array.slice( 0 ).buffer; + + } + + const array = new this.array.constructor( data.arrayBuffers[ this.array.buffer._uuid ] ); + + const ib = new this.constructor( array, this.stride ); + ib.setUsage( this.usage ); + + return ib; + + } + + onUpload( callback ) { + + this.onUploadCallback = callback; + + return this; + + } + + toJSON( data ) { + + if ( data.arrayBuffers === undefined ) { + + data.arrayBuffers = {}; + + } + + // generate UUID for array buffer if necessary + + if ( this.array.buffer._uuid === undefined ) { + + this.array.buffer._uuid = generateUUID(); + + } + + if ( data.arrayBuffers[ this.array.buffer._uuid ] === undefined ) { + + data.arrayBuffers[ this.array.buffer._uuid ] = Array.from( new Uint32Array( this.array.buffer ) ); + + } + + // + + return { + uuid: this.uuid, + buffer: this.array.buffer._uuid, + type: this.array.constructor.name, + stride: this.stride + }; + + } + +} + +const _vector$6 = /*@__PURE__*/ new Vector3(); + +class InterleavedBufferAttribute { + + constructor( interleavedBuffer, itemSize, offset, normalized = false ) { + + this.isInterleavedBufferAttribute = true; + + this.name = ''; + + this.data = interleavedBuffer; + this.itemSize = itemSize; + this.offset = offset; + + this.normalized = normalized; + + } + + get count() { + + return this.data.count; + + } + + get array() { + + return this.data.array; + + } + + set needsUpdate( value ) { + + this.data.needsUpdate = value; + + } + + applyMatrix4( m ) { + + for ( let i = 0, l = this.data.count; i < l; i ++ ) { + + _vector$6.fromBufferAttribute( this, i ); + + _vector$6.applyMatrix4( m ); + + this.setXYZ( i, _vector$6.x, _vector$6.y, _vector$6.z ); + + } + + return this; + + } + + applyNormalMatrix( m ) { + + for ( let i = 0, l = this.count; i < l; i ++ ) { + + _vector$6.fromBufferAttribute( this, i ); + + _vector$6.applyNormalMatrix( m ); + + this.setXYZ( i, _vector$6.x, _vector$6.y, _vector$6.z ); + + } + + return this; + + } + + transformDirection( m ) { + + for ( let i = 0, l = this.count; i < l; i ++ ) { + + _vector$6.fromBufferAttribute( this, i ); + + _vector$6.transformDirection( m ); + + this.setXYZ( i, _vector$6.x, _vector$6.y, _vector$6.z ); + + } + + return this; + + } + + getComponent( index, component ) { + + let value = this.array[ index * this.data.stride + this.offset + component ]; + + if ( this.normalized ) value = denormalize( value, this.array ); + + return value; + + } + + setComponent( index, component, value ) { + + if ( this.normalized ) value = normalize( value, this.array ); + + this.data.array[ index * this.data.stride + this.offset + component ] = value; + + return this; + + } + + setX( index, x ) { + + if ( this.normalized ) x = normalize( x, this.array ); + + this.data.array[ index * this.data.stride + this.offset ] = x; + + return this; + + } + + setY( index, y ) { + + if ( this.normalized ) y = normalize( y, this.array ); + + this.data.array[ index * this.data.stride + this.offset + 1 ] = y; + + return this; + + } + + setZ( index, z ) { + + if ( this.normalized ) z = normalize( z, this.array ); + + this.data.array[ index * this.data.stride + this.offset + 2 ] = z; + + return this; + + } + + setW( index, w ) { + + if ( this.normalized ) w = normalize( w, this.array ); + + this.data.array[ index * this.data.stride + this.offset + 3 ] = w; + + return this; + + } + + getX( index ) { + + let x = this.data.array[ index * this.data.stride + this.offset ]; + + if ( this.normalized ) x = denormalize( x, this.array ); + + return x; + + } + + getY( index ) { + + let y = this.data.array[ index * this.data.stride + this.offset + 1 ]; + + if ( this.normalized ) y = denormalize( y, this.array ); + + return y; + + } + + getZ( index ) { + + let z = this.data.array[ index * this.data.stride + this.offset + 2 ]; + + if ( this.normalized ) z = denormalize( z, this.array ); + + return z; + + } + + getW( index ) { + + let w = this.data.array[ index * this.data.stride + this.offset + 3 ]; + + if ( this.normalized ) w = denormalize( w, this.array ); + + return w; + + } + + setXY( index, x, y ) { + + index = index * this.data.stride + this.offset; + + if ( this.normalized ) { + + x = normalize( x, this.array ); + y = normalize( y, this.array ); + + } + + this.data.array[ index + 0 ] = x; + this.data.array[ index + 1 ] = y; + + return this; + + } + + setXYZ( index, x, y, z ) { + + index = index * this.data.stride + this.offset; + + if ( this.normalized ) { + + x = normalize( x, this.array ); + y = normalize( y, this.array ); + z = normalize( z, this.array ); + + } + + this.data.array[ index + 0 ] = x; + this.data.array[ index + 1 ] = y; + this.data.array[ index + 2 ] = z; + + return this; + + } + + setXYZW( index, x, y, z, w ) { + + index = index * this.data.stride + this.offset; + + if ( this.normalized ) { + + x = normalize( x, this.array ); + y = normalize( y, this.array ); + z = normalize( z, this.array ); + w = normalize( w, this.array ); + + } + + this.data.array[ index + 0 ] = x; + this.data.array[ index + 1 ] = y; + this.data.array[ index + 2 ] = z; + this.data.array[ index + 3 ] = w; + + return this; + + } + + clone( data ) { + + if ( data === undefined ) { + + console.log( 'THREE.InterleavedBufferAttribute.clone(): Cloning an interleaved buffer attribute will de-interleave buffer data.' ); + + const array = []; + + for ( let i = 0; i < this.count; i ++ ) { + + const index = i * this.data.stride + this.offset; + + for ( let j = 0; j < this.itemSize; j ++ ) { + + array.push( this.data.array[ index + j ] ); + + } + + } + + return new BufferAttribute( new this.array.constructor( array ), this.itemSize, this.normalized ); + + } else { + + if ( data.interleavedBuffers === undefined ) { + + data.interleavedBuffers = {}; + + } + + if ( data.interleavedBuffers[ this.data.uuid ] === undefined ) { + + data.interleavedBuffers[ this.data.uuid ] = this.data.clone( data ); + + } + + return new InterleavedBufferAttribute( data.interleavedBuffers[ this.data.uuid ], this.itemSize, this.offset, this.normalized ); + + } + + } + + toJSON( data ) { + + if ( data === undefined ) { + + console.log( 'THREE.InterleavedBufferAttribute.toJSON(): Serializing an interleaved buffer attribute will de-interleave buffer data.' ); + + const array = []; + + for ( let i = 0; i < this.count; i ++ ) { + + const index = i * this.data.stride + this.offset; + + for ( let j = 0; j < this.itemSize; j ++ ) { + + array.push( this.data.array[ index + j ] ); + + } + + } + + // de-interleave data and save it as an ordinary buffer attribute for now + + return { + itemSize: this.itemSize, + type: this.array.constructor.name, + array: array, + normalized: this.normalized + }; + + } else { + + // save as true interleaved attribute + + if ( data.interleavedBuffers === undefined ) { + + data.interleavedBuffers = {}; + + } + + if ( data.interleavedBuffers[ this.data.uuid ] === undefined ) { + + data.interleavedBuffers[ this.data.uuid ] = this.data.toJSON( data ); + + } + + return { + isInterleavedBufferAttribute: true, + itemSize: this.itemSize, + data: this.data.uuid, + offset: this.offset, + normalized: this.normalized + }; + + } + + } + +} + +class SpriteMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isSpriteMaterial = true; + + this.type = 'SpriteMaterial'; + + this.color = new Color( 0xffffff ); + + this.map = null; + + this.alphaMap = null; + + this.rotation = 0; + + this.sizeAttenuation = true; + + this.transparent = true; + + this.fog = true; + + this.setValues( parameters ); + + } + + copy( source ) { + + super.copy( source ); + + this.color.copy( source.color ); + + this.map = source.map; + + this.alphaMap = source.alphaMap; + + this.rotation = source.rotation; + + this.sizeAttenuation = source.sizeAttenuation; + + this.fog = source.fog; + + return this; + + } + +} + +let _geometry; + +const _intersectPoint = /*@__PURE__*/ new Vector3(); +const _worldScale = /*@__PURE__*/ new Vector3(); +const _mvPosition = /*@__PURE__*/ new Vector3(); + +const _alignedPosition = /*@__PURE__*/ new Vector2(); +const _rotatedPosition = /*@__PURE__*/ new Vector2(); +const _viewWorldMatrix = /*@__PURE__*/ new Matrix4(); + +const _vA = /*@__PURE__*/ new Vector3(); +const _vB = /*@__PURE__*/ new Vector3(); +const _vC = /*@__PURE__*/ new Vector3(); + +const _uvA = /*@__PURE__*/ new Vector2(); +const _uvB = /*@__PURE__*/ new Vector2(); +const _uvC = /*@__PURE__*/ new Vector2(); + +class Sprite extends Object3D { + + constructor( material = new SpriteMaterial() ) { + + super(); + + this.isSprite = true; + + this.type = 'Sprite'; + + if ( _geometry === undefined ) { + + _geometry = new BufferGeometry(); + + const float32Array = new Float32Array( [ + - 0.5, - 0.5, 0, 0, 0, + 0.5, - 0.5, 0, 1, 0, + 0.5, 0.5, 0, 1, 1, + - 0.5, 0.5, 0, 0, 1 + ] ); + + const interleavedBuffer = new InterleavedBuffer( float32Array, 5 ); + + _geometry.setIndex( [ 0, 1, 2, 0, 2, 3 ] ); + _geometry.setAttribute( 'position', new InterleavedBufferAttribute( interleavedBuffer, 3, 0, false ) ); + _geometry.setAttribute( 'uv', new InterleavedBufferAttribute( interleavedBuffer, 2, 3, false ) ); + + } + + this.geometry = _geometry; + this.material = material; + + this.center = new Vector2( 0.5, 0.5 ); + + } + + raycast( raycaster, intersects ) { + + if ( raycaster.camera === null ) { + + console.error( 'THREE.Sprite: "Raycaster.camera" needs to be set in order to raycast against sprites.' ); + + } + + _worldScale.setFromMatrixScale( this.matrixWorld ); + + _viewWorldMatrix.copy( raycaster.camera.matrixWorld ); + this.modelViewMatrix.multiplyMatrices( raycaster.camera.matrixWorldInverse, this.matrixWorld ); + + _mvPosition.setFromMatrixPosition( this.modelViewMatrix ); + + if ( raycaster.camera.isPerspectiveCamera && this.material.sizeAttenuation === false ) { + + _worldScale.multiplyScalar( - _mvPosition.z ); + + } + + const rotation = this.material.rotation; + let sin, cos; + + if ( rotation !== 0 ) { + + cos = Math.cos( rotation ); + sin = Math.sin( rotation ); + + } + + const center = this.center; + + transformVertex( _vA.set( - 0.5, - 0.5, 0 ), _mvPosition, center, _worldScale, sin, cos ); + transformVertex( _vB.set( 0.5, - 0.5, 0 ), _mvPosition, center, _worldScale, sin, cos ); + transformVertex( _vC.set( 0.5, 0.5, 0 ), _mvPosition, center, _worldScale, sin, cos ); + + _uvA.set( 0, 0 ); + _uvB.set( 1, 0 ); + _uvC.set( 1, 1 ); + + // check first triangle + let intersect = raycaster.ray.intersectTriangle( _vA, _vB, _vC, false, _intersectPoint ); + + if ( intersect === null ) { + + // check second triangle + transformVertex( _vB.set( - 0.5, 0.5, 0 ), _mvPosition, center, _worldScale, sin, cos ); + _uvB.set( 0, 1 ); + + intersect = raycaster.ray.intersectTriangle( _vA, _vC, _vB, false, _intersectPoint ); + if ( intersect === null ) { + + return; + + } + + } + + const distance = raycaster.ray.origin.distanceTo( _intersectPoint ); + + if ( distance < raycaster.near || distance > raycaster.far ) return; + + intersects.push( { + + distance: distance, + point: _intersectPoint.clone(), + uv: Triangle.getInterpolation( _intersectPoint, _vA, _vB, _vC, _uvA, _uvB, _uvC, new Vector2() ), + face: null, + object: this + + } ); + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + if ( source.center !== undefined ) this.center.copy( source.center ); + + this.material = source.material; + + return this; + + } + +} + +function transformVertex( vertexPosition, mvPosition, center, scale, sin, cos ) { + + // compute position in camera space + _alignedPosition.subVectors( vertexPosition, center ).addScalar( 0.5 ).multiply( scale ); + + // to check if rotation is not zero + if ( sin !== undefined ) { + + _rotatedPosition.x = ( cos * _alignedPosition.x ) - ( sin * _alignedPosition.y ); + _rotatedPosition.y = ( sin * _alignedPosition.x ) + ( cos * _alignedPosition.y ); + + } else { + + _rotatedPosition.copy( _alignedPosition ); + + } + + + vertexPosition.copy( mvPosition ); + vertexPosition.x += _rotatedPosition.x; + vertexPosition.y += _rotatedPosition.y; + + // transform to world space + vertexPosition.applyMatrix4( _viewWorldMatrix ); + +} + +const _v1$2 = /*@__PURE__*/ new Vector3(); +const _v2$1 = /*@__PURE__*/ new Vector3(); + +class LOD extends Object3D { + + constructor() { + + super(); + + this._currentLevel = 0; + + this.type = 'LOD'; + + Object.defineProperties( this, { + levels: { + enumerable: true, + value: [] + }, + isLOD: { + value: true, + } + } ); + + this.autoUpdate = true; + + } + + copy( source ) { + + super.copy( source, false ); + + const levels = source.levels; + + for ( let i = 0, l = levels.length; i < l; i ++ ) { + + const level = levels[ i ]; + + this.addLevel( level.object.clone(), level.distance, level.hysteresis ); + + } + + this.autoUpdate = source.autoUpdate; + + return this; + + } + + addLevel( object, distance = 0, hysteresis = 0 ) { + + distance = Math.abs( distance ); + + const levels = this.levels; + + let l; + + for ( l = 0; l < levels.length; l ++ ) { + + if ( distance < levels[ l ].distance ) { + + break; + + } + + } + + levels.splice( l, 0, { distance: distance, hysteresis: hysteresis, object: object } ); + + this.add( object ); + + return this; + + } + + getCurrentLevel() { + + return this._currentLevel; + + } + + + + getObjectForDistance( distance ) { + + const levels = this.levels; + + if ( levels.length > 0 ) { + + let i, l; + + for ( i = 1, l = levels.length; i < l; i ++ ) { + + let levelDistance = levels[ i ].distance; + + if ( levels[ i ].object.visible ) { + + levelDistance -= levelDistance * levels[ i ].hysteresis; + + } + + if ( distance < levelDistance ) { + + break; + + } + + } + + return levels[ i - 1 ].object; + + } + + return null; + + } + + raycast( raycaster, intersects ) { + + const levels = this.levels; + + if ( levels.length > 0 ) { + + _v1$2.setFromMatrixPosition( this.matrixWorld ); + + const distance = raycaster.ray.origin.distanceTo( _v1$2 ); + + this.getObjectForDistance( distance ).raycast( raycaster, intersects ); + + } + + } + + update( camera ) { + + const levels = this.levels; + + if ( levels.length > 1 ) { + + _v1$2.setFromMatrixPosition( camera.matrixWorld ); + _v2$1.setFromMatrixPosition( this.matrixWorld ); + + const distance = _v1$2.distanceTo( _v2$1 ) / camera.zoom; + + levels[ 0 ].object.visible = true; + + let i, l; + + for ( i = 1, l = levels.length; i < l; i ++ ) { + + let levelDistance = levels[ i ].distance; + + if ( levels[ i ].object.visible ) { + + levelDistance -= levelDistance * levels[ i ].hysteresis; + + } + + if ( distance >= levelDistance ) { + + levels[ i - 1 ].object.visible = false; + levels[ i ].object.visible = true; + + } else { + + break; + + } + + } + + this._currentLevel = i - 1; + + for ( ; i < l; i ++ ) { + + levels[ i ].object.visible = false; + + } + + } + + } + + toJSON( meta ) { + + const data = super.toJSON( meta ); + + if ( this.autoUpdate === false ) data.object.autoUpdate = false; + + data.object.levels = []; + + const levels = this.levels; + + for ( let i = 0, l = levels.length; i < l; i ++ ) { + + const level = levels[ i ]; + + data.object.levels.push( { + object: level.object.uuid, + distance: level.distance, + hysteresis: level.hysteresis + } ); + + } + + return data; + + } + +} + +const _basePosition = /*@__PURE__*/ new Vector3(); + +const _skinIndex = /*@__PURE__*/ new Vector4(); +const _skinWeight = /*@__PURE__*/ new Vector4(); + +const _vector3 = /*@__PURE__*/ new Vector3(); +const _matrix4 = /*@__PURE__*/ new Matrix4(); +const _vertex = /*@__PURE__*/ new Vector3(); + +const _sphere$4 = /*@__PURE__*/ new Sphere(); +const _inverseMatrix$2 = /*@__PURE__*/ new Matrix4(); +const _ray$2 = /*@__PURE__*/ new Ray(); + +class SkinnedMesh extends Mesh { + + constructor( geometry, material ) { + + super( geometry, material ); + + this.isSkinnedMesh = true; + + this.type = 'SkinnedMesh'; + + this.bindMode = AttachedBindMode; + this.bindMatrix = new Matrix4(); + this.bindMatrixInverse = new Matrix4(); + + this.boundingBox = null; + this.boundingSphere = null; + + } + + computeBoundingBox() { + + const geometry = this.geometry; + + if ( this.boundingBox === null ) { + + this.boundingBox = new Box3(); + + } + + this.boundingBox.makeEmpty(); + + const positionAttribute = geometry.getAttribute( 'position' ); + + for ( let i = 0; i < positionAttribute.count; i ++ ) { + + this.getVertexPosition( i, _vertex ); + this.boundingBox.expandByPoint( _vertex ); + + } + + } + + computeBoundingSphere() { + + const geometry = this.geometry; + + if ( this.boundingSphere === null ) { + + this.boundingSphere = new Sphere(); + + } + + this.boundingSphere.makeEmpty(); + + const positionAttribute = geometry.getAttribute( 'position' ); + + for ( let i = 0; i < positionAttribute.count; i ++ ) { + + this.getVertexPosition( i, _vertex ); + this.boundingSphere.expandByPoint( _vertex ); + + } + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + this.bindMode = source.bindMode; + this.bindMatrix.copy( source.bindMatrix ); + this.bindMatrixInverse.copy( source.bindMatrixInverse ); + + this.skeleton = source.skeleton; + + if ( source.boundingBox !== null ) this.boundingBox = source.boundingBox.clone(); + if ( source.boundingSphere !== null ) this.boundingSphere = source.boundingSphere.clone(); + + return this; + + } + + raycast( raycaster, intersects ) { + + const material = this.material; + const matrixWorld = this.matrixWorld; + + if ( material === undefined ) return; + + // test with bounding sphere in world space + + if ( this.boundingSphere === null ) this.computeBoundingSphere(); + + _sphere$4.copy( this.boundingSphere ); + _sphere$4.applyMatrix4( matrixWorld ); + + if ( raycaster.ray.intersectsSphere( _sphere$4 ) === false ) return; + + // convert ray to local space of skinned mesh + + _inverseMatrix$2.copy( matrixWorld ).invert(); + _ray$2.copy( raycaster.ray ).applyMatrix4( _inverseMatrix$2 ); + + // test with bounding box in local space + + if ( this.boundingBox !== null ) { + + if ( _ray$2.intersectsBox( this.boundingBox ) === false ) return; + + } + + // test for intersections with geometry + + this._computeIntersections( raycaster, intersects, _ray$2 ); + + } + + getVertexPosition( index, target ) { + + super.getVertexPosition( index, target ); + + this.applyBoneTransform( index, target ); + + return target; + + } + + bind( skeleton, bindMatrix ) { + + this.skeleton = skeleton; + + if ( bindMatrix === undefined ) { + + this.updateMatrixWorld( true ); + + this.skeleton.calculateInverses(); + + bindMatrix = this.matrixWorld; + + } + + this.bindMatrix.copy( bindMatrix ); + this.bindMatrixInverse.copy( bindMatrix ).invert(); + + } + + pose() { + + this.skeleton.pose(); + + } + + normalizeSkinWeights() { + + const vector = new Vector4(); + + const skinWeight = this.geometry.attributes.skinWeight; + + for ( let i = 0, l = skinWeight.count; i < l; i ++ ) { + + vector.fromBufferAttribute( skinWeight, i ); + + const scale = 1.0 / vector.manhattanLength(); + + if ( scale !== Infinity ) { + + vector.multiplyScalar( scale ); + + } else { + + vector.set( 1, 0, 0, 0 ); // do something reasonable + + } + + skinWeight.setXYZW( i, vector.x, vector.y, vector.z, vector.w ); + + } + + } + + updateMatrixWorld( force ) { + + super.updateMatrixWorld( force ); + + if ( this.bindMode === AttachedBindMode ) { + + this.bindMatrixInverse.copy( this.matrixWorld ).invert(); + + } else if ( this.bindMode === DetachedBindMode ) { + + this.bindMatrixInverse.copy( this.bindMatrix ).invert(); + + } else { + + console.warn( 'THREE.SkinnedMesh: Unrecognized bindMode: ' + this.bindMode ); + + } + + } + + applyBoneTransform( index, vector ) { + + const skeleton = this.skeleton; + const geometry = this.geometry; + + _skinIndex.fromBufferAttribute( geometry.attributes.skinIndex, index ); + _skinWeight.fromBufferAttribute( geometry.attributes.skinWeight, index ); + + _basePosition.copy( vector ).applyMatrix4( this.bindMatrix ); + + vector.set( 0, 0, 0 ); + + for ( let i = 0; i < 4; i ++ ) { + + const weight = _skinWeight.getComponent( i ); + + if ( weight !== 0 ) { + + const boneIndex = _skinIndex.getComponent( i ); + + _matrix4.multiplyMatrices( skeleton.bones[ boneIndex ].matrixWorld, skeleton.boneInverses[ boneIndex ] ); + + vector.addScaledVector( _vector3.copy( _basePosition ).applyMatrix4( _matrix4 ), weight ); + + } + + } + + return vector.applyMatrix4( this.bindMatrixInverse ); + + } + +} + +class Bone extends Object3D { + + constructor() { + + super(); + + this.isBone = true; + + this.type = 'Bone'; + + } + +} + +class DataTexture extends Texture { + + constructor( data = null, width = 1, height = 1, format, type, mapping, wrapS, wrapT, magFilter = NearestFilter, minFilter = NearestFilter, anisotropy, colorSpace ) { + + super( null, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy, colorSpace ); + + this.isDataTexture = true; + + this.image = { data: data, width: width, height: height }; + + this.generateMipmaps = false; + this.flipY = false; + this.unpackAlignment = 1; + + } + +} + +const _offsetMatrix = /*@__PURE__*/ new Matrix4(); +const _identityMatrix$1 = /*@__PURE__*/ new Matrix4(); + +class Skeleton { + + constructor( bones = [], boneInverses = [] ) { + + this.uuid = generateUUID(); + + this.bones = bones.slice( 0 ); + this.boneInverses = boneInverses; + this.boneMatrices = null; + + this.boneTexture = null; + + this.init(); + + } + + init() { + + const bones = this.bones; + const boneInverses = this.boneInverses; + + this.boneMatrices = new Float32Array( bones.length * 16 ); + + // calculate inverse bone matrices if necessary + + if ( boneInverses.length === 0 ) { + + this.calculateInverses(); + + } else { + + // handle special case + + if ( bones.length !== boneInverses.length ) { + + console.warn( 'THREE.Skeleton: Number of inverse bone matrices does not match amount of bones.' ); + + this.boneInverses = []; + + for ( let i = 0, il = this.bones.length; i < il; i ++ ) { + + this.boneInverses.push( new Matrix4() ); + + } + + } + + } + + } + + calculateInverses() { + + this.boneInverses.length = 0; + + for ( let i = 0, il = this.bones.length; i < il; i ++ ) { + + const inverse = new Matrix4(); + + if ( this.bones[ i ] ) { + + inverse.copy( this.bones[ i ].matrixWorld ).invert(); + + } + + this.boneInverses.push( inverse ); + + } + + } + + pose() { + + // recover the bind-time world matrices + + for ( let i = 0, il = this.bones.length; i < il; i ++ ) { + + const bone = this.bones[ i ]; + + if ( bone ) { + + bone.matrixWorld.copy( this.boneInverses[ i ] ).invert(); + + } + + } + + // compute the local matrices, positions, rotations and scales + + for ( let i = 0, il = this.bones.length; i < il; i ++ ) { + + const bone = this.bones[ i ]; + + if ( bone ) { + + if ( bone.parent && bone.parent.isBone ) { + + bone.matrix.copy( bone.parent.matrixWorld ).invert(); + bone.matrix.multiply( bone.matrixWorld ); + + } else { + + bone.matrix.copy( bone.matrixWorld ); + + } + + bone.matrix.decompose( bone.position, bone.quaternion, bone.scale ); + + } + + } + + } + + update() { + + const bones = this.bones; + const boneInverses = this.boneInverses; + const boneMatrices = this.boneMatrices; + const boneTexture = this.boneTexture; + + // flatten bone matrices to array + + for ( let i = 0, il = bones.length; i < il; i ++ ) { + + // compute the offset between the current and the original transform + + const matrix = bones[ i ] ? bones[ i ].matrixWorld : _identityMatrix$1; + + _offsetMatrix.multiplyMatrices( matrix, boneInverses[ i ] ); + _offsetMatrix.toArray( boneMatrices, i * 16 ); + + } + + if ( boneTexture !== null ) { + + boneTexture.needsUpdate = true; + + } + + } + + clone() { + + return new Skeleton( this.bones, this.boneInverses ); + + } + + computeBoneTexture() { + + // layout (1 matrix = 4 pixels) + // RGBA RGBA RGBA RGBA (=> column1, column2, column3, column4) + // with 8x8 pixel texture max 16 bones * 4 pixels = (8 * 8) + // 16x16 pixel texture max 64 bones * 4 pixels = (16 * 16) + // 32x32 pixel texture max 256 bones * 4 pixels = (32 * 32) + // 64x64 pixel texture max 1024 bones * 4 pixels = (64 * 64) + + let size = Math.sqrt( this.bones.length * 4 ); // 4 pixels needed for 1 matrix + size = Math.ceil( size / 4 ) * 4; + size = Math.max( size, 4 ); + + const boneMatrices = new Float32Array( size * size * 4 ); // 4 floats per RGBA pixel + boneMatrices.set( this.boneMatrices ); // copy current values + + const boneTexture = new DataTexture( boneMatrices, size, size, RGBAFormat, FloatType ); + boneTexture.needsUpdate = true; + + this.boneMatrices = boneMatrices; + this.boneTexture = boneTexture; + + return this; + + } + + getBoneByName( name ) { + + for ( let i = 0, il = this.bones.length; i < il; i ++ ) { + + const bone = this.bones[ i ]; + + if ( bone.name === name ) { + + return bone; + + } + + } + + return undefined; + + } + + dispose( ) { + + if ( this.boneTexture !== null ) { + + this.boneTexture.dispose(); + + this.boneTexture = null; + + } + + } + + fromJSON( json, bones ) { + + this.uuid = json.uuid; + + for ( let i = 0, l = json.bones.length; i < l; i ++ ) { + + const uuid = json.bones[ i ]; + let bone = bones[ uuid ]; + + if ( bone === undefined ) { + + console.warn( 'THREE.Skeleton: No bone found with UUID:', uuid ); + bone = new Bone(); + + } + + this.bones.push( bone ); + this.boneInverses.push( new Matrix4().fromArray( json.boneInverses[ i ] ) ); + + } + + this.init(); + + return this; + + } + + toJSON() { + + const data = { + metadata: { + version: 4.6, + type: 'Skeleton', + generator: 'Skeleton.toJSON' + }, + bones: [], + boneInverses: [] + }; + + data.uuid = this.uuid; + + const bones = this.bones; + const boneInverses = this.boneInverses; + + for ( let i = 0, l = bones.length; i < l; i ++ ) { + + const bone = bones[ i ]; + data.bones.push( bone.uuid ); + + const boneInverse = boneInverses[ i ]; + data.boneInverses.push( boneInverse.toArray() ); + + } + + return data; + + } + +} + +class InstancedBufferAttribute extends BufferAttribute { + + constructor( array, itemSize, normalized, meshPerAttribute = 1 ) { + + super( array, itemSize, normalized ); + + this.isInstancedBufferAttribute = true; + + this.meshPerAttribute = meshPerAttribute; + + } + + copy( source ) { + + super.copy( source ); + + this.meshPerAttribute = source.meshPerAttribute; + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.meshPerAttribute = this.meshPerAttribute; + + data.isInstancedBufferAttribute = true; + + return data; + + } + +} + +const _instanceLocalMatrix = /*@__PURE__*/ new Matrix4(); +const _instanceWorldMatrix = /*@__PURE__*/ new Matrix4(); + +const _instanceIntersects = []; + +const _box3 = /*@__PURE__*/ new Box3(); +const _identity = /*@__PURE__*/ new Matrix4(); +const _mesh$1 = /*@__PURE__*/ new Mesh(); +const _sphere$3 = /*@__PURE__*/ new Sphere(); + +class InstancedMesh extends Mesh { + + constructor( geometry, material, count ) { + + super( geometry, material ); + + this.isInstancedMesh = true; + + this.instanceMatrix = new InstancedBufferAttribute( new Float32Array( count * 16 ), 16 ); + this.instanceColor = null; + this.morphTexture = null; + + this.count = count; + + this.boundingBox = null; + this.boundingSphere = null; + + for ( let i = 0; i < count; i ++ ) { + + this.setMatrixAt( i, _identity ); + + } + + } + + computeBoundingBox() { + + const geometry = this.geometry; + const count = this.count; + + if ( this.boundingBox === null ) { + + this.boundingBox = new Box3(); + + } + + if ( geometry.boundingBox === null ) { + + geometry.computeBoundingBox(); + + } + + this.boundingBox.makeEmpty(); + + for ( let i = 0; i < count; i ++ ) { + + this.getMatrixAt( i, _instanceLocalMatrix ); + + _box3.copy( geometry.boundingBox ).applyMatrix4( _instanceLocalMatrix ); + + this.boundingBox.union( _box3 ); + + } + + } + + computeBoundingSphere() { + + const geometry = this.geometry; + const count = this.count; + + if ( this.boundingSphere === null ) { + + this.boundingSphere = new Sphere(); + + } + + if ( geometry.boundingSphere === null ) { + + geometry.computeBoundingSphere(); + + } + + this.boundingSphere.makeEmpty(); + + for ( let i = 0; i < count; i ++ ) { + + this.getMatrixAt( i, _instanceLocalMatrix ); + + _sphere$3.copy( geometry.boundingSphere ).applyMatrix4( _instanceLocalMatrix ); + + this.boundingSphere.union( _sphere$3 ); + + } + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + this.instanceMatrix.copy( source.instanceMatrix ); + + if ( source.morphTexture !== null ) this.morphTexture = source.morphTexture.clone(); + if ( source.instanceColor !== null ) this.instanceColor = source.instanceColor.clone(); + + this.count = source.count; + + if ( source.boundingBox !== null ) this.boundingBox = source.boundingBox.clone(); + if ( source.boundingSphere !== null ) this.boundingSphere = source.boundingSphere.clone(); + + return this; + + } + + getColorAt( index, color ) { + + color.fromArray( this.instanceColor.array, index * 3 ); + + } + + getMatrixAt( index, matrix ) { + + matrix.fromArray( this.instanceMatrix.array, index * 16 ); + + } + + getMorphAt( index, object ) { + + const objectInfluences = object.morphTargetInfluences; + + const array = this.morphTexture.source.data.data; + + const len = objectInfluences.length + 1; // All influences + the baseInfluenceSum + + const dataIndex = index * len + 1; // Skip the baseInfluenceSum at the beginning + + for ( let i = 0; i < objectInfluences.length; i ++ ) { + + objectInfluences[ i ] = array[ dataIndex + i ]; + + } + + } + + raycast( raycaster, intersects ) { + + const matrixWorld = this.matrixWorld; + const raycastTimes = this.count; + + _mesh$1.geometry = this.geometry; + _mesh$1.material = this.material; + + if ( _mesh$1.material === undefined ) return; + + // test with bounding sphere first + + if ( this.boundingSphere === null ) this.computeBoundingSphere(); + + _sphere$3.copy( this.boundingSphere ); + _sphere$3.applyMatrix4( matrixWorld ); + + if ( raycaster.ray.intersectsSphere( _sphere$3 ) === false ) return; + + // now test each instance + + for ( let instanceId = 0; instanceId < raycastTimes; instanceId ++ ) { + + // calculate the world matrix for each instance + + this.getMatrixAt( instanceId, _instanceLocalMatrix ); + + _instanceWorldMatrix.multiplyMatrices( matrixWorld, _instanceLocalMatrix ); + + // the mesh represents this single instance + + _mesh$1.matrixWorld = _instanceWorldMatrix; + + _mesh$1.raycast( raycaster, _instanceIntersects ); + + // process the result of raycast + + for ( let i = 0, l = _instanceIntersects.length; i < l; i ++ ) { + + const intersect = _instanceIntersects[ i ]; + intersect.instanceId = instanceId; + intersect.object = this; + intersects.push( intersect ); + + } + + _instanceIntersects.length = 0; + + } + + } + + setColorAt( index, color ) { + + if ( this.instanceColor === null ) { + + this.instanceColor = new InstancedBufferAttribute( new Float32Array( this.instanceMatrix.count * 3 ), 3 ); + + } + + color.toArray( this.instanceColor.array, index * 3 ); + + } + + setMatrixAt( index, matrix ) { + + matrix.toArray( this.instanceMatrix.array, index * 16 ); + + } + + setMorphAt( index, object ) { + + const objectInfluences = object.morphTargetInfluences; + + const len = objectInfluences.length + 1; // morphBaseInfluence + all influences + + if ( this.morphTexture === null ) { + + this.morphTexture = new DataTexture( new Float32Array( len * this.count ), len, this.count, RedFormat, FloatType ); + + } + + const array = this.morphTexture.source.data.data; + + let morphInfluencesSum = 0; + + for ( let i = 0; i < objectInfluences.length; i ++ ) { + + morphInfluencesSum += objectInfluences[ i ]; + + } + + const morphBaseInfluence = this.geometry.morphTargetsRelative ? 1 : 1 - morphInfluencesSum; + + const dataIndex = len * index; + + array[ dataIndex ] = morphBaseInfluence; + + array.set( objectInfluences, dataIndex + 1 ); + + } + + updateMorphTargets() { + + } + + dispose() { + + this.dispatchEvent( { type: 'dispose' } ); + + if ( this.morphTexture !== null ) { + + this.morphTexture.dispose(); + this.morphTexture = null; + + } + + return this; + + } + +} + +function sortOpaque( a, b ) { + + return a.z - b.z; + +} + +function sortTransparent( a, b ) { + + return b.z - a.z; + +} + +class MultiDrawRenderList { + + constructor() { + + this.index = 0; + this.pool = []; + this.list = []; + + } + + push( drawRange, z ) { + + const pool = this.pool; + const list = this.list; + if ( this.index >= pool.length ) { + + pool.push( { + + start: - 1, + count: - 1, + z: - 1, + + } ); + + } + + const item = pool[ this.index ]; + list.push( item ); + this.index ++; + + item.start = drawRange.start; + item.count = drawRange.count; + item.z = z; + + } + + reset() { + + this.list.length = 0; + this.index = 0; + + } + +} + +const ID_ATTR_NAME = 'batchId'; +const _matrix$1 = /*@__PURE__*/ new Matrix4(); +const _invMatrixWorld = /*@__PURE__*/ new Matrix4(); +const _identityMatrix = /*@__PURE__*/ new Matrix4(); +const _whiteColor = /*@__PURE__*/ new Color( 1, 1, 1 ); +const _projScreenMatrix$2 = /*@__PURE__*/ new Matrix4(); +const _frustum = /*@__PURE__*/ new Frustum(); +const _box$1 = /*@__PURE__*/ new Box3(); +const _sphere$2 = /*@__PURE__*/ new Sphere(); +const _vector$5 = /*@__PURE__*/ new Vector3(); +const _forward = /*@__PURE__*/ new Vector3(); +const _temp = /*@__PURE__*/ new Vector3(); +const _renderList = /*@__PURE__*/ new MultiDrawRenderList(); +const _mesh = /*@__PURE__*/ new Mesh(); +const _batchIntersects = []; + +// @TODO: SkinnedMesh support? +// @TODO: geometry.groups support? +// @TODO: geometry.drawRange support? +// @TODO: geometry.morphAttributes support? +// @TODO: Support uniform parameter per geometry +// @TODO: Add an "optimize" function to pack geometry and remove data gaps + +// copies data from attribute "src" into "target" starting at "targetOffset" +function copyAttributeData( src, target, targetOffset = 0 ) { + + const itemSize = target.itemSize; + if ( src.isInterleavedBufferAttribute || src.array.constructor !== target.array.constructor ) { + + // use the component getters and setters if the array data cannot + // be copied directly + const vertexCount = src.count; + for ( let i = 0; i < vertexCount; i ++ ) { + + for ( let c = 0; c < itemSize; c ++ ) { + + target.setComponent( i + targetOffset, c, src.getComponent( i, c ) ); + + } + + } + + } else { + + // faster copy approach using typed array set function + target.array.set( src.array, targetOffset * itemSize ); + + } + + target.needsUpdate = true; + +} + +class BatchedMesh extends Mesh { + + get maxGeometryCount() { + + return this._maxGeometryCount; + + } + + constructor( maxGeometryCount, maxVertexCount, maxIndexCount = maxVertexCount * 2, material ) { + + super( new BufferGeometry(), material ); + + this.isBatchedMesh = true; + this.perObjectFrustumCulled = true; + this.sortObjects = true; + this.boundingBox = null; + this.boundingSphere = null; + this.customSort = null; + + this._drawRanges = []; + this._reservedRanges = []; + + this._visibility = []; + this._active = []; + this._bounds = []; + + this._maxGeometryCount = maxGeometryCount; + this._maxVertexCount = maxVertexCount; + this._maxIndexCount = maxIndexCount; + + this._geometryInitialized = false; + this._geometryCount = 0; + this._multiDrawCounts = new Int32Array( maxGeometryCount ); + this._multiDrawStarts = new Int32Array( maxGeometryCount ); + this._multiDrawCount = 0; + this._multiDrawInstances = null; + this._visibilityChanged = true; + + // Local matrix per geometry by using data texture + this._matricesTexture = null; + + this._initMatricesTexture(); + + // Local color per geometry by using data texture + this._colorsTexture = null; + + } + + _initMatricesTexture() { + + // layout (1 matrix = 4 pixels) + // RGBA RGBA RGBA RGBA (=> column1, column2, column3, column4) + // with 8x8 pixel texture max 16 matrices * 4 pixels = (8 * 8) + // 16x16 pixel texture max 64 matrices * 4 pixels = (16 * 16) + // 32x32 pixel texture max 256 matrices * 4 pixels = (32 * 32) + // 64x64 pixel texture max 1024 matrices * 4 pixels = (64 * 64) + + let size = Math.sqrt( this._maxGeometryCount * 4 ); // 4 pixels needed for 1 matrix + size = Math.ceil( size / 4 ) * 4; + size = Math.max( size, 4 ); + + const matricesArray = new Float32Array( size * size * 4 ); // 4 floats per RGBA pixel + const matricesTexture = new DataTexture( matricesArray, size, size, RGBAFormat, FloatType ); + + this._matricesTexture = matricesTexture; + + } + + _initColorsTexture() { + + let size = Math.sqrt( this._maxGeometryCount ); + size = Math.ceil( size ); + + // 4 floats per RGBA pixel initialized to white + const colorsArray = new Float32Array( size * size * 4 ).fill( 1 ); + const colorsTexture = new DataTexture( colorsArray, size, size, RGBAFormat, FloatType ); + colorsTexture.colorSpace = ColorManagement.workingColorSpace; + + this._colorsTexture = colorsTexture; + + } + + _initializeGeometry( reference ) { + + const geometry = this.geometry; + const maxVertexCount = this._maxVertexCount; + const maxGeometryCount = this._maxGeometryCount; + const maxIndexCount = this._maxIndexCount; + if ( this._geometryInitialized === false ) { + + for ( const attributeName in reference.attributes ) { + + const srcAttribute = reference.getAttribute( attributeName ); + const { array, itemSize, normalized } = srcAttribute; + + const dstArray = new array.constructor( maxVertexCount * itemSize ); + const dstAttribute = new BufferAttribute( dstArray, itemSize, normalized ); + + geometry.setAttribute( attributeName, dstAttribute ); + + } + + if ( reference.getIndex() !== null ) { + + const indexArray = maxVertexCount > 65536 + ? new Uint32Array( maxIndexCount ) + : new Uint16Array( maxIndexCount ); + + geometry.setIndex( new BufferAttribute( indexArray, 1 ) ); + + } + + const idArray = maxGeometryCount > 65536 + ? new Uint32Array( maxVertexCount ) + : new Uint16Array( maxVertexCount ); + geometry.setAttribute( ID_ATTR_NAME, new BufferAttribute( idArray, 1 ) ); + + this._geometryInitialized = true; + + } + + } + + // Make sure the geometry is compatible with the existing combined geometry attributes + _validateGeometry( geometry ) { + + // check that the geometry doesn't have a version of our reserved id attribute + if ( geometry.getAttribute( ID_ATTR_NAME ) ) { + + throw new Error( `BatchedMesh: Geometry cannot use attribute "${ ID_ATTR_NAME }"` ); + + } + + // check to ensure the geometries are using consistent attributes and indices + const batchGeometry = this.geometry; + if ( Boolean( geometry.getIndex() ) !== Boolean( batchGeometry.getIndex() ) ) { + + throw new Error( 'BatchedMesh: All geometries must consistently have "index".' ); + + } + + for ( const attributeName in batchGeometry.attributes ) { + + if ( attributeName === ID_ATTR_NAME ) { + + continue; + + } + + if ( ! geometry.hasAttribute( attributeName ) ) { + + throw new Error( `BatchedMesh: Added geometry missing "${ attributeName }". All geometries must have consistent attributes.` ); + + } + + const srcAttribute = geometry.getAttribute( attributeName ); + const dstAttribute = batchGeometry.getAttribute( attributeName ); + if ( srcAttribute.itemSize !== dstAttribute.itemSize || srcAttribute.normalized !== dstAttribute.normalized ) { + + throw new Error( 'BatchedMesh: All attributes must have a consistent itemSize and normalized value.' ); + + } + + } + + } + + setCustomSort( func ) { + + this.customSort = func; + return this; + + } + + computeBoundingBox() { + + if ( this.boundingBox === null ) { + + this.boundingBox = new Box3(); + + } + + const geometryCount = this._geometryCount; + const boundingBox = this.boundingBox; + const active = this._active; + + boundingBox.makeEmpty(); + for ( let i = 0; i < geometryCount; i ++ ) { + + if ( active[ i ] === false ) continue; + + this.getMatrixAt( i, _matrix$1 ); + this.getBoundingBoxAt( i, _box$1 ).applyMatrix4( _matrix$1 ); + boundingBox.union( _box$1 ); + + } + + } + + computeBoundingSphere() { + + if ( this.boundingSphere === null ) { + + this.boundingSphere = new Sphere(); + + } + + const geometryCount = this._geometryCount; + const boundingSphere = this.boundingSphere; + const active = this._active; + + boundingSphere.makeEmpty(); + for ( let i = 0; i < geometryCount; i ++ ) { + + if ( active[ i ] === false ) continue; + + this.getMatrixAt( i, _matrix$1 ); + this.getBoundingSphereAt( i, _sphere$2 ).applyMatrix4( _matrix$1 ); + boundingSphere.union( _sphere$2 ); + + } + + } + + addGeometry( geometry, vertexCount = - 1, indexCount = - 1 ) { + + this._initializeGeometry( geometry ); + + this._validateGeometry( geometry ); + + // ensure we're not over geometry + if ( this._geometryCount >= this._maxGeometryCount ) { + + throw new Error( 'BatchedMesh: Maximum geometry count reached.' ); + + } + + // get the necessary range fo the geometry + const reservedRange = { + vertexStart: - 1, + vertexCount: - 1, + indexStart: - 1, + indexCount: - 1, + }; + + let lastRange = null; + const reservedRanges = this._reservedRanges; + const drawRanges = this._drawRanges; + const bounds = this._bounds; + if ( this._geometryCount !== 0 ) { + + lastRange = reservedRanges[ reservedRanges.length - 1 ]; + + } + + if ( vertexCount === - 1 ) { + + reservedRange.vertexCount = geometry.getAttribute( 'position' ).count; + + } else { + + reservedRange.vertexCount = vertexCount; + + } + + if ( lastRange === null ) { + + reservedRange.vertexStart = 0; + + } else { + + reservedRange.vertexStart = lastRange.vertexStart + lastRange.vertexCount; + + } + + const index = geometry.getIndex(); + const hasIndex = index !== null; + if ( hasIndex ) { + + if ( indexCount === - 1 ) { + + reservedRange.indexCount = index.count; + + } else { + + reservedRange.indexCount = indexCount; + + } + + if ( lastRange === null ) { + + reservedRange.indexStart = 0; + + } else { + + reservedRange.indexStart = lastRange.indexStart + lastRange.indexCount; + + } + + } + + if ( + reservedRange.indexStart !== - 1 && + reservedRange.indexStart + reservedRange.indexCount > this._maxIndexCount || + reservedRange.vertexStart + reservedRange.vertexCount > this._maxVertexCount + ) { + + throw new Error( 'BatchedMesh: Reserved space request exceeds the maximum buffer size.' ); + + } + + const visibility = this._visibility; + const active = this._active; + const matricesTexture = this._matricesTexture; + const matricesArray = this._matricesTexture.image.data; + const colorsTexture = this._colorsTexture; + + // push new visibility states + visibility.push( true ); + active.push( true ); + + // update id + const geometryId = this._geometryCount; + this._geometryCount ++; + + // initialize matrix information + _identityMatrix.toArray( matricesArray, geometryId * 16 ); + matricesTexture.needsUpdate = true; + + // initialize the color to white + if ( colorsTexture !== null ) { + + _whiteColor.toArray( colorsTexture.image.data, geometryId * 4 ); + colorsTexture.needsUpdate = true; + + } + + // add the reserved range and draw range objects + reservedRanges.push( reservedRange ); + drawRanges.push( { + start: hasIndex ? reservedRange.indexStart : reservedRange.vertexStart, + count: - 1 + } ); + bounds.push( { + boxInitialized: false, + box: new Box3(), + + sphereInitialized: false, + sphere: new Sphere() + } ); + + // set the id for the geometry + const idAttribute = this.geometry.getAttribute( ID_ATTR_NAME ); + for ( let i = 0; i < reservedRange.vertexCount; i ++ ) { + + idAttribute.setX( reservedRange.vertexStart + i, geometryId ); + + } + + idAttribute.needsUpdate = true; + + // update the geometry + this.setGeometryAt( geometryId, geometry ); + + return geometryId; + + } + + setGeometryAt( id, geometry ) { + + if ( id >= this._geometryCount ) { + + throw new Error( 'BatchedMesh: Maximum geometry count reached.' ); + + } + + this._validateGeometry( geometry ); + + const batchGeometry = this.geometry; + const hasIndex = batchGeometry.getIndex() !== null; + const dstIndex = batchGeometry.getIndex(); + const srcIndex = geometry.getIndex(); + const reservedRange = this._reservedRanges[ id ]; + if ( + hasIndex && + srcIndex.count > reservedRange.indexCount || + geometry.attributes.position.count > reservedRange.vertexCount + ) { + + throw new Error( 'BatchedMesh: Reserved space not large enough for provided geometry.' ); + + } + + // copy geometry over + const vertexStart = reservedRange.vertexStart; + const vertexCount = reservedRange.vertexCount; + for ( const attributeName in batchGeometry.attributes ) { + + if ( attributeName === ID_ATTR_NAME ) { + + continue; + + } + + // copy attribute data + const srcAttribute = geometry.getAttribute( attributeName ); + const dstAttribute = batchGeometry.getAttribute( attributeName ); + copyAttributeData( srcAttribute, dstAttribute, vertexStart ); + + // fill the rest in with zeroes + const itemSize = srcAttribute.itemSize; + for ( let i = srcAttribute.count, l = vertexCount; i < l; i ++ ) { + + const index = vertexStart + i; + for ( let c = 0; c < itemSize; c ++ ) { + + dstAttribute.setComponent( index, c, 0 ); + + } + + } + + dstAttribute.needsUpdate = true; + dstAttribute.addUpdateRange( vertexStart * itemSize, vertexCount * itemSize ); + + } + + // copy index + if ( hasIndex ) { + + const indexStart = reservedRange.indexStart; + + // copy index data over + for ( let i = 0; i < srcIndex.count; i ++ ) { + + dstIndex.setX( indexStart + i, vertexStart + srcIndex.getX( i ) ); + + } + + // fill the rest in with zeroes + for ( let i = srcIndex.count, l = reservedRange.indexCount; i < l; i ++ ) { + + dstIndex.setX( indexStart + i, vertexStart ); + + } + + dstIndex.needsUpdate = true; + dstIndex.addUpdateRange( indexStart, reservedRange.indexCount ); + + } + + // store the bounding boxes + const bound = this._bounds[ id ]; + if ( geometry.boundingBox !== null ) { + + bound.box.copy( geometry.boundingBox ); + bound.boxInitialized = true; + + } else { + + bound.boxInitialized = false; + + } + + if ( geometry.boundingSphere !== null ) { + + bound.sphere.copy( geometry.boundingSphere ); + bound.sphereInitialized = true; + + } else { + + bound.sphereInitialized = false; + + } + + // set drawRange count + const drawRange = this._drawRanges[ id ]; + const posAttr = geometry.getAttribute( 'position' ); + drawRange.count = hasIndex ? srcIndex.count : posAttr.count; + this._visibilityChanged = true; + + return id; + + } + + deleteGeometry( geometryId ) { + + // Note: User needs to call optimize() afterward to pack the data. + + const active = this._active; + if ( geometryId >= active.length || active[ geometryId ] === false ) { + + return this; + + } + + active[ geometryId ] = false; + this._visibilityChanged = true; + + return this; + + } + + getInstanceCountAt( id ) { + + if ( this._multiDrawInstances === null ) return null; + + return this._multiDrawInstances[ id ]; + + } + + setInstanceCountAt( id, instanceCount ) { + + if ( this._multiDrawInstances === null ) { + + this._multiDrawInstances = new Int32Array( this._maxGeometryCount ).fill( 1 ); + + } + + this._multiDrawInstances[ id ] = instanceCount; + + return id; + + } + + // get bounding box and compute it if it doesn't exist + getBoundingBoxAt( id, target ) { + + const active = this._active; + if ( active[ id ] === false ) { + + return null; + + } + + // compute bounding box + const bound = this._bounds[ id ]; + const box = bound.box; + const geometry = this.geometry; + if ( bound.boxInitialized === false ) { + + box.makeEmpty(); + + const index = geometry.index; + const position = geometry.attributes.position; + const drawRange = this._drawRanges[ id ]; + for ( let i = drawRange.start, l = drawRange.start + drawRange.count; i < l; i ++ ) { + + let iv = i; + if ( index ) { + + iv = index.getX( iv ); + + } + + box.expandByPoint( _vector$5.fromBufferAttribute( position, iv ) ); + + } + + bound.boxInitialized = true; + + } + + target.copy( box ); + return target; + + } + + // get bounding sphere and compute it if it doesn't exist + getBoundingSphereAt( id, target ) { + + const active = this._active; + if ( active[ id ] === false ) { + + return null; + + } + + // compute bounding sphere + const bound = this._bounds[ id ]; + const sphere = bound.sphere; + const geometry = this.geometry; + if ( bound.sphereInitialized === false ) { + + sphere.makeEmpty(); + + this.getBoundingBoxAt( id, _box$1 ); + _box$1.getCenter( sphere.center ); + + const index = geometry.index; + const position = geometry.attributes.position; + const drawRange = this._drawRanges[ id ]; + + let maxRadiusSq = 0; + for ( let i = drawRange.start, l = drawRange.start + drawRange.count; i < l; i ++ ) { + + let iv = i; + if ( index ) { + + iv = index.getX( iv ); + + } + + _vector$5.fromBufferAttribute( position, iv ); + maxRadiusSq = Math.max( maxRadiusSq, sphere.center.distanceToSquared( _vector$5 ) ); + + } + + sphere.radius = Math.sqrt( maxRadiusSq ); + bound.sphereInitialized = true; + + } + + target.copy( sphere ); + return target; + + } + + setMatrixAt( geometryId, matrix ) { + + // @TODO: Map geometryId to index of the arrays because + // optimize() can make geometryId mismatch the index + + const active = this._active; + const matricesTexture = this._matricesTexture; + const matricesArray = this._matricesTexture.image.data; + const geometryCount = this._geometryCount; + if ( geometryId >= geometryCount || active[ geometryId ] === false ) { + + return this; + + } + + matrix.toArray( matricesArray, geometryId * 16 ); + matricesTexture.needsUpdate = true; + + return this; + + } + + getMatrixAt( geometryId, matrix ) { + + const active = this._active; + const matricesArray = this._matricesTexture.image.data; + const geometryCount = this._geometryCount; + if ( geometryId >= geometryCount || active[ geometryId ] === false ) { + + return null; + + } + + return matrix.fromArray( matricesArray, geometryId * 16 ); + + } + + setColorAt( geometryId, color ) { + + if ( this._colorsTexture === null ) { + + this._initColorsTexture(); + + } + + // @TODO: Map geometryId to index of the arrays because + // optimize() can make geometryId mismatch the index + + const active = this._active; + const colorsTexture = this._colorsTexture; + const colorsArray = this._colorsTexture.image.data; + const geometryCount = this._geometryCount; + if ( geometryId >= geometryCount || active[ geometryId ] === false ) { + + return this; + + } + + color.toArray( colorsArray, geometryId * 4 ); + colorsTexture.needsUpdate = true; + + return this; + + } + + getColorAt( geometryId, color ) { + + const active = this._active; + const colorsArray = this._colorsTexture.image.data; + const geometryCount = this._geometryCount; + if ( geometryId >= geometryCount || active[ geometryId ] === false ) { + + return null; + + } + + return color.fromArray( colorsArray, geometryId * 4 ); + + } + + setVisibleAt( geometryId, value ) { + + const visibility = this._visibility; + const active = this._active; + const geometryCount = this._geometryCount; + + // if the geometry is out of range, not active, or visibility state + // does not change then return early + if ( + geometryId >= geometryCount || + active[ geometryId ] === false || + visibility[ geometryId ] === value + ) { + + return this; + + } + + visibility[ geometryId ] = value; + this._visibilityChanged = true; + + return this; + + } + + getVisibleAt( geometryId ) { + + const visibility = this._visibility; + const active = this._active; + const geometryCount = this._geometryCount; + + // return early if the geometry is out of range or not active + if ( geometryId >= geometryCount || active[ geometryId ] === false ) { + + return false; + + } + + return visibility[ geometryId ]; + + } + + raycast( raycaster, intersects ) { + + const visibility = this._visibility; + const active = this._active; + const drawRanges = this._drawRanges; + const geometryCount = this._geometryCount; + const matrixWorld = this.matrixWorld; + const batchGeometry = this.geometry; + + // iterate over each geometry + _mesh.material = this.material; + _mesh.geometry.index = batchGeometry.index; + _mesh.geometry.attributes = batchGeometry.attributes; + if ( _mesh.geometry.boundingBox === null ) { + + _mesh.geometry.boundingBox = new Box3(); + + } + + if ( _mesh.geometry.boundingSphere === null ) { + + _mesh.geometry.boundingSphere = new Sphere(); + + } + + for ( let i = 0; i < geometryCount; i ++ ) { + + if ( ! visibility[ i ] || ! active[ i ] ) { + + continue; + + } + + const drawRange = drawRanges[ i ]; + _mesh.geometry.setDrawRange( drawRange.start, drawRange.count ); + + // ge the intersects + this.getMatrixAt( i, _mesh.matrixWorld ).premultiply( matrixWorld ); + this.getBoundingBoxAt( i, _mesh.geometry.boundingBox ); + this.getBoundingSphereAt( i, _mesh.geometry.boundingSphere ); + _mesh.raycast( raycaster, _batchIntersects ); + + // add batch id to the intersects + for ( let j = 0, l = _batchIntersects.length; j < l; j ++ ) { + + const intersect = _batchIntersects[ j ]; + intersect.object = this; + intersect.batchId = i; + intersects.push( intersect ); + + } + + _batchIntersects.length = 0; + + } + + _mesh.material = null; + _mesh.geometry.index = null; + _mesh.geometry.attributes = {}; + _mesh.geometry.setDrawRange( 0, Infinity ); + + } + + copy( source ) { + + super.copy( source ); + + this.geometry = source.geometry.clone(); + this.perObjectFrustumCulled = source.perObjectFrustumCulled; + this.sortObjects = source.sortObjects; + this.boundingBox = source.boundingBox !== null ? source.boundingBox.clone() : null; + this.boundingSphere = source.boundingSphere !== null ? source.boundingSphere.clone() : null; + + this._drawRanges = source._drawRanges.map( range => ( { ...range } ) ); + this._reservedRanges = source._reservedRanges.map( range => ( { ...range } ) ); + + this._visibility = source._visibility.slice(); + this._active = source._active.slice(); + this._bounds = source._bounds.map( bound => ( { + boxInitialized: bound.boxInitialized, + box: bound.box.clone(), + + sphereInitialized: bound.sphereInitialized, + sphere: bound.sphere.clone() + } ) ); + + this._maxGeometryCount = source._maxGeometryCount; + this._maxVertexCount = source._maxVertexCount; + this._maxIndexCount = source._maxIndexCount; + + this._geometryInitialized = source._geometryInitialized; + this._geometryCount = source._geometryCount; + this._multiDrawCounts = source._multiDrawCounts.slice(); + this._multiDrawStarts = source._multiDrawStarts.slice(); + + this._matricesTexture = source._matricesTexture.clone(); + this._matricesTexture.image.data = this._matricesTexture.image.slice(); + + if ( this._colorsTexture !== null ) { + + this._colorsTexture = source._colorsTexture.clone(); + this._colorsTexture.image.data = this._colorsTexture.image.slice(); + + } + + return this; + + } + + dispose() { + + // Assuming the geometry is not shared with other meshes + this.geometry.dispose(); + + this._matricesTexture.dispose(); + this._matricesTexture = null; + + if ( this._colorsTexture !== null ) { + + this._colorsTexture.dispose(); + this._colorsTexture = null; + + } + + return this; + + } + + onBeforeRender( renderer, scene, camera, geometry, material/*, _group*/ ) { + + // if visibility has not changed and frustum culling and object sorting is not required + // then skip iterating over all items + if ( ! this._visibilityChanged && ! this.perObjectFrustumCulled && ! this.sortObjects ) { + + return; + + } + + // the indexed version of the multi draw function requires specifying the start + // offset in bytes. + const index = geometry.getIndex(); + const bytesPerElement = index === null ? 1 : index.array.BYTES_PER_ELEMENT; + + const active = this._active; + const visibility = this._visibility; + const multiDrawStarts = this._multiDrawStarts; + const multiDrawCounts = this._multiDrawCounts; + const drawRanges = this._drawRanges; + const perObjectFrustumCulled = this.perObjectFrustumCulled; + + // prepare the frustum in the local frame + if ( perObjectFrustumCulled ) { + + _projScreenMatrix$2 + .multiplyMatrices( camera.projectionMatrix, camera.matrixWorldInverse ) + .multiply( this.matrixWorld ); + _frustum.setFromProjectionMatrix( + _projScreenMatrix$2, + renderer.coordinateSystem + ); + + } + + let count = 0; + if ( this.sortObjects ) { + + // get the camera position in the local frame + _invMatrixWorld.copy( this.matrixWorld ).invert(); + _vector$5.setFromMatrixPosition( camera.matrixWorld ).applyMatrix4( _invMatrixWorld ); + _forward.set( 0, 0, - 1 ).transformDirection( camera.matrixWorld ).transformDirection( _invMatrixWorld ); + + for ( let i = 0, l = visibility.length; i < l; i ++ ) { + + if ( visibility[ i ] && active[ i ] ) { + + // get the bounds in world space + this.getMatrixAt( i, _matrix$1 ); + this.getBoundingSphereAt( i, _sphere$2 ).applyMatrix4( _matrix$1 ); + + // determine whether the batched geometry is within the frustum + let culled = false; + if ( perObjectFrustumCulled ) { + + culled = ! _frustum.intersectsSphere( _sphere$2 ); + + } + + if ( ! culled ) { + + // get the distance from camera used for sorting + const z = _temp.subVectors( _sphere$2.center, _vector$5 ).dot( _forward ); + _renderList.push( drawRanges[ i ], z ); + + } + + } + + } + + // Sort the draw ranges and prep for rendering + const list = _renderList.list; + const customSort = this.customSort; + if ( customSort === null ) { + + list.sort( material.transparent ? sortTransparent : sortOpaque ); + + } else { + + customSort.call( this, list, camera ); + + } + + for ( let i = 0, l = list.length; i < l; i ++ ) { + + const item = list[ i ]; + multiDrawStarts[ count ] = item.start * bytesPerElement; + multiDrawCounts[ count ] = item.count; + count ++; + + } + + _renderList.reset(); + + } else { + + for ( let i = 0, l = visibility.length; i < l; i ++ ) { + + if ( visibility[ i ] && active[ i ] ) { + + // determine whether the batched geometry is within the frustum + let culled = false; + if ( perObjectFrustumCulled ) { + + // get the bounds in world space + this.getMatrixAt( i, _matrix$1 ); + this.getBoundingSphereAt( i, _sphere$2 ).applyMatrix4( _matrix$1 ); + culled = ! _frustum.intersectsSphere( _sphere$2 ); + + } + + if ( ! culled ) { + + const range = drawRanges[ i ]; + multiDrawStarts[ count ] = range.start * bytesPerElement; + multiDrawCounts[ count ] = range.count; + count ++; + + } + + } + + } + + } + + this._multiDrawCount = count; + this._visibilityChanged = false; + + } + + onBeforeShadow( renderer, object, camera, shadowCamera, geometry, depthMaterial/* , group */ ) { + + this.onBeforeRender( renderer, null, shadowCamera, geometry, depthMaterial ); + + } + +} + +class LineBasicMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isLineBasicMaterial = true; + + this.type = 'LineBasicMaterial'; + + this.color = new Color( 0xffffff ); + + this.map = null; + + this.linewidth = 1; + this.linecap = 'round'; + this.linejoin = 'round'; + + this.fog = true; + + this.setValues( parameters ); + + } + + + copy( source ) { + + super.copy( source ); + + this.color.copy( source.color ); + + this.map = source.map; + + this.linewidth = source.linewidth; + this.linecap = source.linecap; + this.linejoin = source.linejoin; + + this.fog = source.fog; + + return this; + + } + +} + +const _vStart = /*@__PURE__*/ new Vector3(); +const _vEnd = /*@__PURE__*/ new Vector3(); + +const _inverseMatrix$1 = /*@__PURE__*/ new Matrix4(); +const _ray$1 = /*@__PURE__*/ new Ray(); +const _sphere$1 = /*@__PURE__*/ new Sphere(); + +const _intersectPointOnRay = /*@__PURE__*/ new Vector3(); +const _intersectPointOnSegment = /*@__PURE__*/ new Vector3(); + +class Line extends Object3D { + + constructor( geometry = new BufferGeometry(), material = new LineBasicMaterial() ) { + + super(); + + this.isLine = true; + + this.type = 'Line'; + + this.geometry = geometry; + this.material = material; + + this.updateMorphTargets(); + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + this.material = Array.isArray( source.material ) ? source.material.slice() : source.material; + this.geometry = source.geometry; + + return this; + + } + + computeLineDistances() { + + const geometry = this.geometry; + + // we assume non-indexed geometry + + if ( geometry.index === null ) { + + const positionAttribute = geometry.attributes.position; + const lineDistances = [ 0 ]; + + for ( let i = 1, l = positionAttribute.count; i < l; i ++ ) { + + _vStart.fromBufferAttribute( positionAttribute, i - 1 ); + _vEnd.fromBufferAttribute( positionAttribute, i ); + + lineDistances[ i ] = lineDistances[ i - 1 ]; + lineDistances[ i ] += _vStart.distanceTo( _vEnd ); + + } + + geometry.setAttribute( 'lineDistance', new Float32BufferAttribute( lineDistances, 1 ) ); + + } else { + + console.warn( 'THREE.Line.computeLineDistances(): Computation only possible with non-indexed BufferGeometry.' ); + + } + + return this; + + } + + raycast( raycaster, intersects ) { + + const geometry = this.geometry; + const matrixWorld = this.matrixWorld; + const threshold = raycaster.params.Line.threshold; + const drawRange = geometry.drawRange; + + // Checking boundingSphere distance to ray + + if ( geometry.boundingSphere === null ) geometry.computeBoundingSphere(); + + _sphere$1.copy( geometry.boundingSphere ); + _sphere$1.applyMatrix4( matrixWorld ); + _sphere$1.radius += threshold; + + if ( raycaster.ray.intersectsSphere( _sphere$1 ) === false ) return; + + // + + _inverseMatrix$1.copy( matrixWorld ).invert(); + _ray$1.copy( raycaster.ray ).applyMatrix4( _inverseMatrix$1 ); + + const localThreshold = threshold / ( ( this.scale.x + this.scale.y + this.scale.z ) / 3 ); + const localThresholdSq = localThreshold * localThreshold; + + const step = this.isLineSegments ? 2 : 1; + + const index = geometry.index; + const attributes = geometry.attributes; + const positionAttribute = attributes.position; + + if ( index !== null ) { + + const start = Math.max( 0, drawRange.start ); + const end = Math.min( index.count, ( drawRange.start + drawRange.count ) ); + + for ( let i = start, l = end - 1; i < l; i += step ) { + + const a = index.getX( i ); + const b = index.getX( i + 1 ); + + const intersect = checkIntersection( this, raycaster, _ray$1, localThresholdSq, a, b ); + + if ( intersect ) { + + intersects.push( intersect ); + + } + + } + + if ( this.isLineLoop ) { + + const a = index.getX( end - 1 ); + const b = index.getX( start ); + + const intersect = checkIntersection( this, raycaster, _ray$1, localThresholdSq, a, b ); + + if ( intersect ) { + + intersects.push( intersect ); + + } + + } + + } else { + + const start = Math.max( 0, drawRange.start ); + const end = Math.min( positionAttribute.count, ( drawRange.start + drawRange.count ) ); + + for ( let i = start, l = end - 1; i < l; i += step ) { + + const intersect = checkIntersection( this, raycaster, _ray$1, localThresholdSq, i, i + 1 ); + + if ( intersect ) { + + intersects.push( intersect ); + + } + + } + + if ( this.isLineLoop ) { + + const intersect = checkIntersection( this, raycaster, _ray$1, localThresholdSq, end - 1, start ); + + if ( intersect ) { + + intersects.push( intersect ); + + } + + } + + } + + } + + updateMorphTargets() { + + const geometry = this.geometry; + + const morphAttributes = geometry.morphAttributes; + const keys = Object.keys( morphAttributes ); + + if ( keys.length > 0 ) { + + const morphAttribute = morphAttributes[ keys[ 0 ] ]; + + if ( morphAttribute !== undefined ) { + + this.morphTargetInfluences = []; + this.morphTargetDictionary = {}; + + for ( let m = 0, ml = morphAttribute.length; m < ml; m ++ ) { + + const name = morphAttribute[ m ].name || String( m ); + + this.morphTargetInfluences.push( 0 ); + this.morphTargetDictionary[ name ] = m; + + } + + } + + } + + } + +} + +function checkIntersection( object, raycaster, ray, thresholdSq, a, b ) { + + const positionAttribute = object.geometry.attributes.position; + + _vStart.fromBufferAttribute( positionAttribute, a ); + _vEnd.fromBufferAttribute( positionAttribute, b ); + + const distSq = ray.distanceSqToSegment( _vStart, _vEnd, _intersectPointOnRay, _intersectPointOnSegment ); + + if ( distSq > thresholdSq ) return; + + _intersectPointOnRay.applyMatrix4( object.matrixWorld ); // Move back to world space for distance calculation + + const distance = raycaster.ray.origin.distanceTo( _intersectPointOnRay ); + + if ( distance < raycaster.near || distance > raycaster.far ) return; + + return { + + distance: distance, + // What do we want? intersection point on the ray or on the segment?? + // point: raycaster.ray.at( distance ), + point: _intersectPointOnSegment.clone().applyMatrix4( object.matrixWorld ), + index: a, + face: null, + faceIndex: null, + object: object + + }; + +} + +const _start = /*@__PURE__*/ new Vector3(); +const _end = /*@__PURE__*/ new Vector3(); + +class LineSegments extends Line { + + constructor( geometry, material ) { + + super( geometry, material ); + + this.isLineSegments = true; + + this.type = 'LineSegments'; + + } + + computeLineDistances() { + + const geometry = this.geometry; + + // we assume non-indexed geometry + + if ( geometry.index === null ) { + + const positionAttribute = geometry.attributes.position; + const lineDistances = []; + + for ( let i = 0, l = positionAttribute.count; i < l; i += 2 ) { + + _start.fromBufferAttribute( positionAttribute, i ); + _end.fromBufferAttribute( positionAttribute, i + 1 ); + + lineDistances[ i ] = ( i === 0 ) ? 0 : lineDistances[ i - 1 ]; + lineDistances[ i + 1 ] = lineDistances[ i ] + _start.distanceTo( _end ); + + } + + geometry.setAttribute( 'lineDistance', new Float32BufferAttribute( lineDistances, 1 ) ); + + } else { + + console.warn( 'THREE.LineSegments.computeLineDistances(): Computation only possible with non-indexed BufferGeometry.' ); + + } + + return this; + + } + +} + +class LineLoop extends Line { + + constructor( geometry, material ) { + + super( geometry, material ); + + this.isLineLoop = true; + + this.type = 'LineLoop'; + + } + +} + +class PointsMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isPointsMaterial = true; + + this.type = 'PointsMaterial'; + + this.color = new Color( 0xffffff ); + + this.map = null; + + this.alphaMap = null; + + this.size = 1; + this.sizeAttenuation = true; + + this.fog = true; + + this.setValues( parameters ); + + } + + copy( source ) { + + super.copy( source ); + + this.color.copy( source.color ); + + this.map = source.map; + + this.alphaMap = source.alphaMap; + + this.size = source.size; + this.sizeAttenuation = source.sizeAttenuation; + + this.fog = source.fog; + + return this; + + } + +} + +const _inverseMatrix = /*@__PURE__*/ new Matrix4(); +const _ray = /*@__PURE__*/ new Ray(); +const _sphere = /*@__PURE__*/ new Sphere(); +const _position$2 = /*@__PURE__*/ new Vector3(); + +class Points extends Object3D { + + constructor( geometry = new BufferGeometry(), material = new PointsMaterial() ) { + + super(); + + this.isPoints = true; + + this.type = 'Points'; + + this.geometry = geometry; + this.material = material; + + this.updateMorphTargets(); + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + this.material = Array.isArray( source.material ) ? source.material.slice() : source.material; + this.geometry = source.geometry; + + return this; + + } + + raycast( raycaster, intersects ) { + + const geometry = this.geometry; + const matrixWorld = this.matrixWorld; + const threshold = raycaster.params.Points.threshold; + const drawRange = geometry.drawRange; + + // Checking boundingSphere distance to ray + + if ( geometry.boundingSphere === null ) geometry.computeBoundingSphere(); + + _sphere.copy( geometry.boundingSphere ); + _sphere.applyMatrix4( matrixWorld ); + _sphere.radius += threshold; + + if ( raycaster.ray.intersectsSphere( _sphere ) === false ) return; + + // + + _inverseMatrix.copy( matrixWorld ).invert(); + _ray.copy( raycaster.ray ).applyMatrix4( _inverseMatrix ); + + const localThreshold = threshold / ( ( this.scale.x + this.scale.y + this.scale.z ) / 3 ); + const localThresholdSq = localThreshold * localThreshold; + + const index = geometry.index; + const attributes = geometry.attributes; + const positionAttribute = attributes.position; + + if ( index !== null ) { + + const start = Math.max( 0, drawRange.start ); + const end = Math.min( index.count, ( drawRange.start + drawRange.count ) ); + + for ( let i = start, il = end; i < il; i ++ ) { + + const a = index.getX( i ); + + _position$2.fromBufferAttribute( positionAttribute, a ); + + testPoint( _position$2, a, localThresholdSq, matrixWorld, raycaster, intersects, this ); + + } + + } else { + + const start = Math.max( 0, drawRange.start ); + const end = Math.min( positionAttribute.count, ( drawRange.start + drawRange.count ) ); + + for ( let i = start, l = end; i < l; i ++ ) { + + _position$2.fromBufferAttribute( positionAttribute, i ); + + testPoint( _position$2, i, localThresholdSq, matrixWorld, raycaster, intersects, this ); + + } + + } + + } + + updateMorphTargets() { + + const geometry = this.geometry; + + const morphAttributes = geometry.morphAttributes; + const keys = Object.keys( morphAttributes ); + + if ( keys.length > 0 ) { + + const morphAttribute = morphAttributes[ keys[ 0 ] ]; + + if ( morphAttribute !== undefined ) { + + this.morphTargetInfluences = []; + this.morphTargetDictionary = {}; + + for ( let m = 0, ml = morphAttribute.length; m < ml; m ++ ) { + + const name = morphAttribute[ m ].name || String( m ); + + this.morphTargetInfluences.push( 0 ); + this.morphTargetDictionary[ name ] = m; + + } + + } + + } + + } + +} + +function testPoint( point, index, localThresholdSq, matrixWorld, raycaster, intersects, object ) { + + const rayPointDistanceSq = _ray.distanceSqToPoint( point ); + + if ( rayPointDistanceSq < localThresholdSq ) { + + const intersectPoint = new Vector3(); + + _ray.closestPointToPoint( point, intersectPoint ); + intersectPoint.applyMatrix4( matrixWorld ); + + const distance = raycaster.ray.origin.distanceTo( intersectPoint ); + + if ( distance < raycaster.near || distance > raycaster.far ) return; + + intersects.push( { + + distance: distance, + distanceToRay: Math.sqrt( rayPointDistanceSq ), + point: intersectPoint, + index: index, + face: null, + object: object + + } ); + + } + +} + +class VideoTexture extends Texture { + + constructor( video, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy ) { + + super( video, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy ); + + this.isVideoTexture = true; + + this.minFilter = minFilter !== undefined ? minFilter : LinearFilter; + this.magFilter = magFilter !== undefined ? magFilter : LinearFilter; + + this.generateMipmaps = false; + + const scope = this; + + function updateVideo() { + + scope.needsUpdate = true; + video.requestVideoFrameCallback( updateVideo ); + + } + + if ( 'requestVideoFrameCallback' in video ) { + + video.requestVideoFrameCallback( updateVideo ); + + } + + } + + clone() { + + return new this.constructor( this.image ).copy( this ); + + } + + update() { + + const video = this.image; + const hasVideoFrameCallback = 'requestVideoFrameCallback' in video; + + if ( hasVideoFrameCallback === false && video.readyState >= video.HAVE_CURRENT_DATA ) { + + this.needsUpdate = true; + + } + + } + +} + +class FramebufferTexture extends Texture { + + constructor( width, height ) { + + super( { width, height } ); + + this.isFramebufferTexture = true; + + this.magFilter = NearestFilter; + this.minFilter = NearestFilter; + + this.generateMipmaps = false; + + this.needsUpdate = true; + + } + +} + +class CompressedTexture extends Texture { + + constructor( mipmaps, width, height, format, type, mapping, wrapS, wrapT, magFilter, minFilter, anisotropy, colorSpace ) { + + super( null, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy, colorSpace ); + + this.isCompressedTexture = true; + + this.image = { width: width, height: height }; + this.mipmaps = mipmaps; + + // no flipping for cube textures + // (also flipping doesn't work for compressed textures ) + + this.flipY = false; + + // can't generate mipmaps for compressed textures + // mips must be embedded in DDS files + + this.generateMipmaps = false; + + } + +} + +class CompressedArrayTexture extends CompressedTexture { + + constructor( mipmaps, width, height, depth, format, type ) { + + super( mipmaps, width, height, format, type ); + + this.isCompressedArrayTexture = true; + this.image.depth = depth; + this.wrapR = ClampToEdgeWrapping; + + this.layerUpdates = new Set(); + + } + + addLayerUpdates( layerIndex ) { + + this.layerUpdates.add( layerIndex ); + + } + + clearLayerUpdates() { + + this.layerUpdates.clear(); + + } + +} + +class CompressedCubeTexture extends CompressedTexture { + + constructor( images, format, type ) { + + super( undefined, images[ 0 ].width, images[ 0 ].height, format, type, CubeReflectionMapping ); + + this.isCompressedCubeTexture = true; + this.isCubeTexture = true; + + this.image = images; + + } + +} + +class CanvasTexture extends Texture { + + constructor( canvas, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy ) { + + super( canvas, mapping, wrapS, wrapT, magFilter, minFilter, format, type, anisotropy ); + + this.isCanvasTexture = true; + + this.needsUpdate = true; + + } + +} + +/** + * Extensible curve object. + * + * Some common of curve methods: + * .getPoint( t, optionalTarget ), .getTangent( t, optionalTarget ) + * .getPointAt( u, optionalTarget ), .getTangentAt( u, optionalTarget ) + * .getPoints(), .getSpacedPoints() + * .getLength() + * .updateArcLengths() + * + * This following curves inherit from THREE.Curve: + * + * -- 2D curves -- + * THREE.ArcCurve + * THREE.CubicBezierCurve + * THREE.EllipseCurve + * THREE.LineCurve + * THREE.QuadraticBezierCurve + * THREE.SplineCurve + * + * -- 3D curves -- + * THREE.CatmullRomCurve3 + * THREE.CubicBezierCurve3 + * THREE.LineCurve3 + * THREE.QuadraticBezierCurve3 + * + * A series of curves can be represented as a THREE.CurvePath. + * + **/ + +class Curve { + + constructor() { + + this.type = 'Curve'; + + this.arcLengthDivisions = 200; + + } + + // Virtual base class method to overwrite and implement in subclasses + // - t [0 .. 1] + + getPoint( /* t, optionalTarget */ ) { + + console.warn( 'THREE.Curve: .getPoint() not implemented.' ); + return null; + + } + + // Get point at relative position in curve according to arc length + // - u [0 .. 1] + + getPointAt( u, optionalTarget ) { + + const t = this.getUtoTmapping( u ); + return this.getPoint( t, optionalTarget ); + + } + + // Get sequence of points using getPoint( t ) + + getPoints( divisions = 5 ) { + + const points = []; + + for ( let d = 0; d <= divisions; d ++ ) { + + points.push( this.getPoint( d / divisions ) ); + + } + + return points; + + } + + // Get sequence of points using getPointAt( u ) + + getSpacedPoints( divisions = 5 ) { + + const points = []; + + for ( let d = 0; d <= divisions; d ++ ) { + + points.push( this.getPointAt( d / divisions ) ); + + } + + return points; + + } + + // Get total curve arc length + + getLength() { + + const lengths = this.getLengths(); + return lengths[ lengths.length - 1 ]; + + } + + // Get list of cumulative segment lengths + + getLengths( divisions = this.arcLengthDivisions ) { + + if ( this.cacheArcLengths && + ( this.cacheArcLengths.length === divisions + 1 ) && + ! this.needsUpdate ) { + + return this.cacheArcLengths; + + } + + this.needsUpdate = false; + + const cache = []; + let current, last = this.getPoint( 0 ); + let sum = 0; + + cache.push( 0 ); + + for ( let p = 1; p <= divisions; p ++ ) { + + current = this.getPoint( p / divisions ); + sum += current.distanceTo( last ); + cache.push( sum ); + last = current; + + } + + this.cacheArcLengths = cache; + + return cache; // { sums: cache, sum: sum }; Sum is in the last element. + + } + + updateArcLengths() { + + this.needsUpdate = true; + this.getLengths(); + + } + + // Given u ( 0 .. 1 ), get a t to find p. This gives you points which are equidistant + + getUtoTmapping( u, distance ) { + + const arcLengths = this.getLengths(); + + let i = 0; + const il = arcLengths.length; + + let targetArcLength; // The targeted u distance value to get + + if ( distance ) { + + targetArcLength = distance; + + } else { + + targetArcLength = u * arcLengths[ il - 1 ]; + + } + + // binary search for the index with largest value smaller than target u distance + + let low = 0, high = il - 1, comparison; + + while ( low <= high ) { + + i = Math.floor( low + ( high - low ) / 2 ); // less likely to overflow, though probably not issue here, JS doesn't really have integers, all numbers are floats + + comparison = arcLengths[ i ] - targetArcLength; + + if ( comparison < 0 ) { + + low = i + 1; + + } else if ( comparison > 0 ) { + + high = i - 1; + + } else { + + high = i; + break; + + // DONE + + } + + } + + i = high; + + if ( arcLengths[ i ] === targetArcLength ) { + + return i / ( il - 1 ); + + } + + // we could get finer grain at lengths, or use simple interpolation between two points + + const lengthBefore = arcLengths[ i ]; + const lengthAfter = arcLengths[ i + 1 ]; + + const segmentLength = lengthAfter - lengthBefore; + + // determine where we are between the 'before' and 'after' points + + const segmentFraction = ( targetArcLength - lengthBefore ) / segmentLength; + + // add that fractional amount to t + + const t = ( i + segmentFraction ) / ( il - 1 ); + + return t; + + } + + // Returns a unit vector tangent at t + // In case any sub curve does not implement its tangent derivation, + // 2 points a small delta apart will be used to find its gradient + // which seems to give a reasonable approximation + + getTangent( t, optionalTarget ) { + + const delta = 0.0001; + let t1 = t - delta; + let t2 = t + delta; + + // Capping in case of danger + + if ( t1 < 0 ) t1 = 0; + if ( t2 > 1 ) t2 = 1; + + const pt1 = this.getPoint( t1 ); + const pt2 = this.getPoint( t2 ); + + const tangent = optionalTarget || ( ( pt1.isVector2 ) ? new Vector2() : new Vector3() ); + + tangent.copy( pt2 ).sub( pt1 ).normalize(); + + return tangent; + + } + + getTangentAt( u, optionalTarget ) { + + const t = this.getUtoTmapping( u ); + return this.getTangent( t, optionalTarget ); + + } + + computeFrenetFrames( segments, closed ) { + + // see http://www.cs.indiana.edu/pub/techreports/TR425.pdf + + const normal = new Vector3(); + + const tangents = []; + const normals = []; + const binormals = []; + + const vec = new Vector3(); + const mat = new Matrix4(); + + // compute the tangent vectors for each segment on the curve + + for ( let i = 0; i <= segments; i ++ ) { + + const u = i / segments; + + tangents[ i ] = this.getTangentAt( u, new Vector3() ); + + } + + // select an initial normal vector perpendicular to the first tangent vector, + // and in the direction of the minimum tangent xyz component + + normals[ 0 ] = new Vector3(); + binormals[ 0 ] = new Vector3(); + let min = Number.MAX_VALUE; + const tx = Math.abs( tangents[ 0 ].x ); + const ty = Math.abs( tangents[ 0 ].y ); + const tz = Math.abs( tangents[ 0 ].z ); + + if ( tx <= min ) { + + min = tx; + normal.set( 1, 0, 0 ); + + } + + if ( ty <= min ) { + + min = ty; + normal.set( 0, 1, 0 ); + + } + + if ( tz <= min ) { + + normal.set( 0, 0, 1 ); + + } + + vec.crossVectors( tangents[ 0 ], normal ).normalize(); + + normals[ 0 ].crossVectors( tangents[ 0 ], vec ); + binormals[ 0 ].crossVectors( tangents[ 0 ], normals[ 0 ] ); + + + // compute the slowly-varying normal and binormal vectors for each segment on the curve + + for ( let i = 1; i <= segments; i ++ ) { + + normals[ i ] = normals[ i - 1 ].clone(); + + binormals[ i ] = binormals[ i - 1 ].clone(); + + vec.crossVectors( tangents[ i - 1 ], tangents[ i ] ); + + if ( vec.length() > Number.EPSILON ) { + + vec.normalize(); + + const theta = Math.acos( clamp( tangents[ i - 1 ].dot( tangents[ i ] ), - 1, 1 ) ); // clamp for floating pt errors + + normals[ i ].applyMatrix4( mat.makeRotationAxis( vec, theta ) ); + + } + + binormals[ i ].crossVectors( tangents[ i ], normals[ i ] ); + + } + + // if the curve is closed, postprocess the vectors so the first and last normal vectors are the same + + if ( closed === true ) { + + let theta = Math.acos( clamp( normals[ 0 ].dot( normals[ segments ] ), - 1, 1 ) ); + theta /= segments; + + if ( tangents[ 0 ].dot( vec.crossVectors( normals[ 0 ], normals[ segments ] ) ) > 0 ) { + + theta = - theta; + + } + + for ( let i = 1; i <= segments; i ++ ) { + + // twist a little... + normals[ i ].applyMatrix4( mat.makeRotationAxis( tangents[ i ], theta * i ) ); + binormals[ i ].crossVectors( tangents[ i ], normals[ i ] ); + + } + + } + + return { + tangents: tangents, + normals: normals, + binormals: binormals + }; + + } + + clone() { + + return new this.constructor().copy( this ); + + } + + copy( source ) { + + this.arcLengthDivisions = source.arcLengthDivisions; + + return this; + + } + + toJSON() { + + const data = { + metadata: { + version: 4.6, + type: 'Curve', + generator: 'Curve.toJSON' + } + }; + + data.arcLengthDivisions = this.arcLengthDivisions; + data.type = this.type; + + return data; + + } + + fromJSON( json ) { + + this.arcLengthDivisions = json.arcLengthDivisions; + + return this; + + } + +} + +class EllipseCurve extends Curve { + + constructor( aX = 0, aY = 0, xRadius = 1, yRadius = 1, aStartAngle = 0, aEndAngle = Math.PI * 2, aClockwise = false, aRotation = 0 ) { + + super(); + + this.isEllipseCurve = true; + + this.type = 'EllipseCurve'; + + this.aX = aX; + this.aY = aY; + + this.xRadius = xRadius; + this.yRadius = yRadius; + + this.aStartAngle = aStartAngle; + this.aEndAngle = aEndAngle; + + this.aClockwise = aClockwise; + + this.aRotation = aRotation; + + } + + getPoint( t, optionalTarget = new Vector2() ) { + + const point = optionalTarget; + + const twoPi = Math.PI * 2; + let deltaAngle = this.aEndAngle - this.aStartAngle; + const samePoints = Math.abs( deltaAngle ) < Number.EPSILON; + + // ensures that deltaAngle is 0 .. 2 PI + while ( deltaAngle < 0 ) deltaAngle += twoPi; + while ( deltaAngle > twoPi ) deltaAngle -= twoPi; + + if ( deltaAngle < Number.EPSILON ) { + + if ( samePoints ) { + + deltaAngle = 0; + + } else { + + deltaAngle = twoPi; + + } + + } + + if ( this.aClockwise === true && ! samePoints ) { + + if ( deltaAngle === twoPi ) { + + deltaAngle = - twoPi; + + } else { + + deltaAngle = deltaAngle - twoPi; + + } + + } + + const angle = this.aStartAngle + t * deltaAngle; + let x = this.aX + this.xRadius * Math.cos( angle ); + let y = this.aY + this.yRadius * Math.sin( angle ); + + if ( this.aRotation !== 0 ) { + + const cos = Math.cos( this.aRotation ); + const sin = Math.sin( this.aRotation ); + + const tx = x - this.aX; + const ty = y - this.aY; + + // Rotate the point about the center of the ellipse. + x = tx * cos - ty * sin + this.aX; + y = tx * sin + ty * cos + this.aY; + + } + + return point.set( x, y ); + + } + + copy( source ) { + + super.copy( source ); + + this.aX = source.aX; + this.aY = source.aY; + + this.xRadius = source.xRadius; + this.yRadius = source.yRadius; + + this.aStartAngle = source.aStartAngle; + this.aEndAngle = source.aEndAngle; + + this.aClockwise = source.aClockwise; + + this.aRotation = source.aRotation; + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.aX = this.aX; + data.aY = this.aY; + + data.xRadius = this.xRadius; + data.yRadius = this.yRadius; + + data.aStartAngle = this.aStartAngle; + data.aEndAngle = this.aEndAngle; + + data.aClockwise = this.aClockwise; + + data.aRotation = this.aRotation; + + return data; + + } + + fromJSON( json ) { + + super.fromJSON( json ); + + this.aX = json.aX; + this.aY = json.aY; + + this.xRadius = json.xRadius; + this.yRadius = json.yRadius; + + this.aStartAngle = json.aStartAngle; + this.aEndAngle = json.aEndAngle; + + this.aClockwise = json.aClockwise; + + this.aRotation = json.aRotation; + + return this; + + } + +} + +class ArcCurve extends EllipseCurve { + + constructor( aX, aY, aRadius, aStartAngle, aEndAngle, aClockwise ) { + + super( aX, aY, aRadius, aRadius, aStartAngle, aEndAngle, aClockwise ); + + this.isArcCurve = true; + + this.type = 'ArcCurve'; + + } + +} + +/** + * Centripetal CatmullRom Curve - which is useful for avoiding + * cusps and self-intersections in non-uniform catmull rom curves. + * http://www.cemyuksel.com/research/catmullrom_param/catmullrom.pdf + * + * curve.type accepts centripetal(default), chordal and catmullrom + * curve.tension is used for catmullrom which defaults to 0.5 + */ + + +/* +Based on an optimized c++ solution in + - http://stackoverflow.com/questions/9489736/catmull-rom-curve-with-no-cusps-and-no-self-intersections/ + - http://ideone.com/NoEbVM + +This CubicPoly class could be used for reusing some variables and calculations, +but for three.js curve use, it could be possible inlined and flatten into a single function call +which can be placed in CurveUtils. +*/ + +function CubicPoly() { + + let c0 = 0, c1 = 0, c2 = 0, c3 = 0; + + /* + * Compute coefficients for a cubic polynomial + * p(s) = c0 + c1*s + c2*s^2 + c3*s^3 + * such that + * p(0) = x0, p(1) = x1 + * and + * p'(0) = t0, p'(1) = t1. + */ + function init( x0, x1, t0, t1 ) { + + c0 = x0; + c1 = t0; + c2 = - 3 * x0 + 3 * x1 - 2 * t0 - t1; + c3 = 2 * x0 - 2 * x1 + t0 + t1; + + } + + return { + + initCatmullRom: function ( x0, x1, x2, x3, tension ) { + + init( x1, x2, tension * ( x2 - x0 ), tension * ( x3 - x1 ) ); + + }, + + initNonuniformCatmullRom: function ( x0, x1, x2, x3, dt0, dt1, dt2 ) { + + // compute tangents when parameterized in [t1,t2] + let t1 = ( x1 - x0 ) / dt0 - ( x2 - x0 ) / ( dt0 + dt1 ) + ( x2 - x1 ) / dt1; + let t2 = ( x2 - x1 ) / dt1 - ( x3 - x1 ) / ( dt1 + dt2 ) + ( x3 - x2 ) / dt2; + + // rescale tangents for parametrization in [0,1] + t1 *= dt1; + t2 *= dt1; + + init( x1, x2, t1, t2 ); + + }, + + calc: function ( t ) { + + const t2 = t * t; + const t3 = t2 * t; + return c0 + c1 * t + c2 * t2 + c3 * t3; + + } + + }; + +} + +// + +const tmp = /*@__PURE__*/ new Vector3(); +const px = /*@__PURE__*/ new CubicPoly(); +const py = /*@__PURE__*/ new CubicPoly(); +const pz = /*@__PURE__*/ new CubicPoly(); + +class CatmullRomCurve3 extends Curve { + + constructor( points = [], closed = false, curveType = 'centripetal', tension = 0.5 ) { + + super(); + + this.isCatmullRomCurve3 = true; + + this.type = 'CatmullRomCurve3'; + + this.points = points; + this.closed = closed; + this.curveType = curveType; + this.tension = tension; + + } + + getPoint( t, optionalTarget = new Vector3() ) { + + const point = optionalTarget; + + const points = this.points; + const l = points.length; + + const p = ( l - ( this.closed ? 0 : 1 ) ) * t; + let intPoint = Math.floor( p ); + let weight = p - intPoint; + + if ( this.closed ) { + + intPoint += intPoint > 0 ? 0 : ( Math.floor( Math.abs( intPoint ) / l ) + 1 ) * l; + + } else if ( weight === 0 && intPoint === l - 1 ) { + + intPoint = l - 2; + weight = 1; + + } + + let p0, p3; // 4 points (p1 & p2 defined below) + + if ( this.closed || intPoint > 0 ) { + + p0 = points[ ( intPoint - 1 ) % l ]; + + } else { + + // extrapolate first point + tmp.subVectors( points[ 0 ], points[ 1 ] ).add( points[ 0 ] ); + p0 = tmp; + + } + + const p1 = points[ intPoint % l ]; + const p2 = points[ ( intPoint + 1 ) % l ]; + + if ( this.closed || intPoint + 2 < l ) { + + p3 = points[ ( intPoint + 2 ) % l ]; + + } else { + + // extrapolate last point + tmp.subVectors( points[ l - 1 ], points[ l - 2 ] ).add( points[ l - 1 ] ); + p3 = tmp; + + } + + if ( this.curveType === 'centripetal' || this.curveType === 'chordal' ) { + + // init Centripetal / Chordal Catmull-Rom + const pow = this.curveType === 'chordal' ? 0.5 : 0.25; + let dt0 = Math.pow( p0.distanceToSquared( p1 ), pow ); + let dt1 = Math.pow( p1.distanceToSquared( p2 ), pow ); + let dt2 = Math.pow( p2.distanceToSquared( p3 ), pow ); + + // safety check for repeated points + if ( dt1 < 1e-4 ) dt1 = 1.0; + if ( dt0 < 1e-4 ) dt0 = dt1; + if ( dt2 < 1e-4 ) dt2 = dt1; + + px.initNonuniformCatmullRom( p0.x, p1.x, p2.x, p3.x, dt0, dt1, dt2 ); + py.initNonuniformCatmullRom( p0.y, p1.y, p2.y, p3.y, dt0, dt1, dt2 ); + pz.initNonuniformCatmullRom( p0.z, p1.z, p2.z, p3.z, dt0, dt1, dt2 ); + + } else if ( this.curveType === 'catmullrom' ) { + + px.initCatmullRom( p0.x, p1.x, p2.x, p3.x, this.tension ); + py.initCatmullRom( p0.y, p1.y, p2.y, p3.y, this.tension ); + pz.initCatmullRom( p0.z, p1.z, p2.z, p3.z, this.tension ); + + } + + point.set( + px.calc( weight ), + py.calc( weight ), + pz.calc( weight ) + ); + + return point; + + } + + copy( source ) { + + super.copy( source ); + + this.points = []; + + for ( let i = 0, l = source.points.length; i < l; i ++ ) { + + const point = source.points[ i ]; + + this.points.push( point.clone() ); + + } + + this.closed = source.closed; + this.curveType = source.curveType; + this.tension = source.tension; + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.points = []; + + for ( let i = 0, l = this.points.length; i < l; i ++ ) { + + const point = this.points[ i ]; + data.points.push( point.toArray() ); + + } + + data.closed = this.closed; + data.curveType = this.curveType; + data.tension = this.tension; + + return data; + + } + + fromJSON( json ) { + + super.fromJSON( json ); + + this.points = []; + + for ( let i = 0, l = json.points.length; i < l; i ++ ) { + + const point = json.points[ i ]; + this.points.push( new Vector3().fromArray( point ) ); + + } + + this.closed = json.closed; + this.curveType = json.curveType; + this.tension = json.tension; + + return this; + + } + +} + +/** + * Bezier Curves formulas obtained from + * https://en.wikipedia.org/wiki/B%C3%A9zier_curve + */ + +function CatmullRom( t, p0, p1, p2, p3 ) { + + const v0 = ( p2 - p0 ) * 0.5; + const v1 = ( p3 - p1 ) * 0.5; + const t2 = t * t; + const t3 = t * t2; + return ( 2 * p1 - 2 * p2 + v0 + v1 ) * t3 + ( - 3 * p1 + 3 * p2 - 2 * v0 - v1 ) * t2 + v0 * t + p1; + +} + +// + +function QuadraticBezierP0( t, p ) { + + const k = 1 - t; + return k * k * p; + +} + +function QuadraticBezierP1( t, p ) { + + return 2 * ( 1 - t ) * t * p; + +} + +function QuadraticBezierP2( t, p ) { + + return t * t * p; + +} + +function QuadraticBezier( t, p0, p1, p2 ) { + + return QuadraticBezierP0( t, p0 ) + QuadraticBezierP1( t, p1 ) + + QuadraticBezierP2( t, p2 ); + +} + +// + +function CubicBezierP0( t, p ) { + + const k = 1 - t; + return k * k * k * p; + +} + +function CubicBezierP1( t, p ) { + + const k = 1 - t; + return 3 * k * k * t * p; + +} + +function CubicBezierP2( t, p ) { + + return 3 * ( 1 - t ) * t * t * p; + +} + +function CubicBezierP3( t, p ) { + + return t * t * t * p; + +} + +function CubicBezier( t, p0, p1, p2, p3 ) { + + return CubicBezierP0( t, p0 ) + CubicBezierP1( t, p1 ) + CubicBezierP2( t, p2 ) + + CubicBezierP3( t, p3 ); + +} + +class CubicBezierCurve extends Curve { + + constructor( v0 = new Vector2(), v1 = new Vector2(), v2 = new Vector2(), v3 = new Vector2() ) { + + super(); + + this.isCubicBezierCurve = true; + + this.type = 'CubicBezierCurve'; + + this.v0 = v0; + this.v1 = v1; + this.v2 = v2; + this.v3 = v3; + + } + + getPoint( t, optionalTarget = new Vector2() ) { + + const point = optionalTarget; + + const v0 = this.v0, v1 = this.v1, v2 = this.v2, v3 = this.v3; + + point.set( + CubicBezier( t, v0.x, v1.x, v2.x, v3.x ), + CubicBezier( t, v0.y, v1.y, v2.y, v3.y ) + ); + + return point; + + } + + copy( source ) { + + super.copy( source ); + + this.v0.copy( source.v0 ); + this.v1.copy( source.v1 ); + this.v2.copy( source.v2 ); + this.v3.copy( source.v3 ); + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.v0 = this.v0.toArray(); + data.v1 = this.v1.toArray(); + data.v2 = this.v2.toArray(); + data.v3 = this.v3.toArray(); + + return data; + + } + + fromJSON( json ) { + + super.fromJSON( json ); + + this.v0.fromArray( json.v0 ); + this.v1.fromArray( json.v1 ); + this.v2.fromArray( json.v2 ); + this.v3.fromArray( json.v3 ); + + return this; + + } + +} + +class CubicBezierCurve3 extends Curve { + + constructor( v0 = new Vector3(), v1 = new Vector3(), v2 = new Vector3(), v3 = new Vector3() ) { + + super(); + + this.isCubicBezierCurve3 = true; + + this.type = 'CubicBezierCurve3'; + + this.v0 = v0; + this.v1 = v1; + this.v2 = v2; + this.v3 = v3; + + } + + getPoint( t, optionalTarget = new Vector3() ) { + + const point = optionalTarget; + + const v0 = this.v0, v1 = this.v1, v2 = this.v2, v3 = this.v3; + + point.set( + CubicBezier( t, v0.x, v1.x, v2.x, v3.x ), + CubicBezier( t, v0.y, v1.y, v2.y, v3.y ), + CubicBezier( t, v0.z, v1.z, v2.z, v3.z ) + ); + + return point; + + } + + copy( source ) { + + super.copy( source ); + + this.v0.copy( source.v0 ); + this.v1.copy( source.v1 ); + this.v2.copy( source.v2 ); + this.v3.copy( source.v3 ); + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.v0 = this.v0.toArray(); + data.v1 = this.v1.toArray(); + data.v2 = this.v2.toArray(); + data.v3 = this.v3.toArray(); + + return data; + + } + + fromJSON( json ) { + + super.fromJSON( json ); + + this.v0.fromArray( json.v0 ); + this.v1.fromArray( json.v1 ); + this.v2.fromArray( json.v2 ); + this.v3.fromArray( json.v3 ); + + return this; + + } + +} + +class LineCurve extends Curve { + + constructor( v1 = new Vector2(), v2 = new Vector2() ) { + + super(); + + this.isLineCurve = true; + + this.type = 'LineCurve'; + + this.v1 = v1; + this.v2 = v2; + + } + + getPoint( t, optionalTarget = new Vector2() ) { + + const point = optionalTarget; + + if ( t === 1 ) { + + point.copy( this.v2 ); + + } else { + + point.copy( this.v2 ).sub( this.v1 ); + point.multiplyScalar( t ).add( this.v1 ); + + } + + return point; + + } + + // Line curve is linear, so we can overwrite default getPointAt + getPointAt( u, optionalTarget ) { + + return this.getPoint( u, optionalTarget ); + + } + + getTangent( t, optionalTarget = new Vector2() ) { + + return optionalTarget.subVectors( this.v2, this.v1 ).normalize(); + + } + + getTangentAt( u, optionalTarget ) { + + return this.getTangent( u, optionalTarget ); + + } + + copy( source ) { + + super.copy( source ); + + this.v1.copy( source.v1 ); + this.v2.copy( source.v2 ); + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.v1 = this.v1.toArray(); + data.v2 = this.v2.toArray(); + + return data; + + } + + fromJSON( json ) { + + super.fromJSON( json ); + + this.v1.fromArray( json.v1 ); + this.v2.fromArray( json.v2 ); + + return this; + + } + +} + +class LineCurve3 extends Curve { + + constructor( v1 = new Vector3(), v2 = new Vector3() ) { + + super(); + + this.isLineCurve3 = true; + + this.type = 'LineCurve3'; + + this.v1 = v1; + this.v2 = v2; + + } + + getPoint( t, optionalTarget = new Vector3() ) { + + const point = optionalTarget; + + if ( t === 1 ) { + + point.copy( this.v2 ); + + } else { + + point.copy( this.v2 ).sub( this.v1 ); + point.multiplyScalar( t ).add( this.v1 ); + + } + + return point; + + } + + // Line curve is linear, so we can overwrite default getPointAt + getPointAt( u, optionalTarget ) { + + return this.getPoint( u, optionalTarget ); + + } + + getTangent( t, optionalTarget = new Vector3() ) { + + return optionalTarget.subVectors( this.v2, this.v1 ).normalize(); + + } + + getTangentAt( u, optionalTarget ) { + + return this.getTangent( u, optionalTarget ); + + } + + copy( source ) { + + super.copy( source ); + + this.v1.copy( source.v1 ); + this.v2.copy( source.v2 ); + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.v1 = this.v1.toArray(); + data.v2 = this.v2.toArray(); + + return data; + + } + + fromJSON( json ) { + + super.fromJSON( json ); + + this.v1.fromArray( json.v1 ); + this.v2.fromArray( json.v2 ); + + return this; + + } + +} + +class QuadraticBezierCurve extends Curve { + + constructor( v0 = new Vector2(), v1 = new Vector2(), v2 = new Vector2() ) { + + super(); + + this.isQuadraticBezierCurve = true; + + this.type = 'QuadraticBezierCurve'; + + this.v0 = v0; + this.v1 = v1; + this.v2 = v2; + + } + + getPoint( t, optionalTarget = new Vector2() ) { + + const point = optionalTarget; + + const v0 = this.v0, v1 = this.v1, v2 = this.v2; + + point.set( + QuadraticBezier( t, v0.x, v1.x, v2.x ), + QuadraticBezier( t, v0.y, v1.y, v2.y ) + ); + + return point; + + } + + copy( source ) { + + super.copy( source ); + + this.v0.copy( source.v0 ); + this.v1.copy( source.v1 ); + this.v2.copy( source.v2 ); + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.v0 = this.v0.toArray(); + data.v1 = this.v1.toArray(); + data.v2 = this.v2.toArray(); + + return data; + + } + + fromJSON( json ) { + + super.fromJSON( json ); + + this.v0.fromArray( json.v0 ); + this.v1.fromArray( json.v1 ); + this.v2.fromArray( json.v2 ); + + return this; + + } + +} + +class QuadraticBezierCurve3 extends Curve { + + constructor( v0 = new Vector3(), v1 = new Vector3(), v2 = new Vector3() ) { + + super(); + + this.isQuadraticBezierCurve3 = true; + + this.type = 'QuadraticBezierCurve3'; + + this.v0 = v0; + this.v1 = v1; + this.v2 = v2; + + } + + getPoint( t, optionalTarget = new Vector3() ) { + + const point = optionalTarget; + + const v0 = this.v0, v1 = this.v1, v2 = this.v2; + + point.set( + QuadraticBezier( t, v0.x, v1.x, v2.x ), + QuadraticBezier( t, v0.y, v1.y, v2.y ), + QuadraticBezier( t, v0.z, v1.z, v2.z ) + ); + + return point; + + } + + copy( source ) { + + super.copy( source ); + + this.v0.copy( source.v0 ); + this.v1.copy( source.v1 ); + this.v2.copy( source.v2 ); + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.v0 = this.v0.toArray(); + data.v1 = this.v1.toArray(); + data.v2 = this.v2.toArray(); + + return data; + + } + + fromJSON( json ) { + + super.fromJSON( json ); + + this.v0.fromArray( json.v0 ); + this.v1.fromArray( json.v1 ); + this.v2.fromArray( json.v2 ); + + return this; + + } + +} + +class SplineCurve extends Curve { + + constructor( points = [] ) { + + super(); + + this.isSplineCurve = true; + + this.type = 'SplineCurve'; + + this.points = points; + + } + + getPoint( t, optionalTarget = new Vector2() ) { + + const point = optionalTarget; + + const points = this.points; + const p = ( points.length - 1 ) * t; + + const intPoint = Math.floor( p ); + const weight = p - intPoint; + + const p0 = points[ intPoint === 0 ? intPoint : intPoint - 1 ]; + const p1 = points[ intPoint ]; + const p2 = points[ intPoint > points.length - 2 ? points.length - 1 : intPoint + 1 ]; + const p3 = points[ intPoint > points.length - 3 ? points.length - 1 : intPoint + 2 ]; + + point.set( + CatmullRom( weight, p0.x, p1.x, p2.x, p3.x ), + CatmullRom( weight, p0.y, p1.y, p2.y, p3.y ) + ); + + return point; + + } + + copy( source ) { + + super.copy( source ); + + this.points = []; + + for ( let i = 0, l = source.points.length; i < l; i ++ ) { + + const point = source.points[ i ]; + + this.points.push( point.clone() ); + + } + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.points = []; + + for ( let i = 0, l = this.points.length; i < l; i ++ ) { + + const point = this.points[ i ]; + data.points.push( point.toArray() ); + + } + + return data; + + } + + fromJSON( json ) { + + super.fromJSON( json ); + + this.points = []; + + for ( let i = 0, l = json.points.length; i < l; i ++ ) { + + const point = json.points[ i ]; + this.points.push( new Vector2().fromArray( point ) ); + + } + + return this; + + } + +} + +var Curves = /*#__PURE__*/Object.freeze({ + __proto__: null, + ArcCurve: ArcCurve, + CatmullRomCurve3: CatmullRomCurve3, + CubicBezierCurve: CubicBezierCurve, + CubicBezierCurve3: CubicBezierCurve3, + EllipseCurve: EllipseCurve, + LineCurve: LineCurve, + LineCurve3: LineCurve3, + QuadraticBezierCurve: QuadraticBezierCurve, + QuadraticBezierCurve3: QuadraticBezierCurve3, + SplineCurve: SplineCurve +}); + +/************************************************************** + * Curved Path - a curve path is simply a array of connected + * curves, but retains the api of a curve + **************************************************************/ + +class CurvePath extends Curve { + + constructor() { + + super(); + + this.type = 'CurvePath'; + + this.curves = []; + this.autoClose = false; // Automatically closes the path + + } + + add( curve ) { + + this.curves.push( curve ); + + } + + closePath() { + + // Add a line curve if start and end of lines are not connected + const startPoint = this.curves[ 0 ].getPoint( 0 ); + const endPoint = this.curves[ this.curves.length - 1 ].getPoint( 1 ); + + if ( ! startPoint.equals( endPoint ) ) { + + const lineType = ( startPoint.isVector2 === true ) ? 'LineCurve' : 'LineCurve3'; + this.curves.push( new Curves[ lineType ]( endPoint, startPoint ) ); + + } + + return this; + + } + + // To get accurate point with reference to + // entire path distance at time t, + // following has to be done: + + // 1. Length of each sub path have to be known + // 2. Locate and identify type of curve + // 3. Get t for the curve + // 4. Return curve.getPointAt(t') + + getPoint( t, optionalTarget ) { + + const d = t * this.getLength(); + const curveLengths = this.getCurveLengths(); + let i = 0; + + // To think about boundaries points. + + while ( i < curveLengths.length ) { + + if ( curveLengths[ i ] >= d ) { + + const diff = curveLengths[ i ] - d; + const curve = this.curves[ i ]; + + const segmentLength = curve.getLength(); + const u = segmentLength === 0 ? 0 : 1 - diff / segmentLength; + + return curve.getPointAt( u, optionalTarget ); + + } + + i ++; + + } + + return null; + + // loop where sum != 0, sum > d , sum+1 1 && ! points[ points.length - 1 ].equals( points[ 0 ] ) ) { + + points.push( points[ 0 ] ); + + } + + return points; + + } + + copy( source ) { + + super.copy( source ); + + this.curves = []; + + for ( let i = 0, l = source.curves.length; i < l; i ++ ) { + + const curve = source.curves[ i ]; + + this.curves.push( curve.clone() ); + + } + + this.autoClose = source.autoClose; + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.autoClose = this.autoClose; + data.curves = []; + + for ( let i = 0, l = this.curves.length; i < l; i ++ ) { + + const curve = this.curves[ i ]; + data.curves.push( curve.toJSON() ); + + } + + return data; + + } + + fromJSON( json ) { + + super.fromJSON( json ); + + this.autoClose = json.autoClose; + this.curves = []; + + for ( let i = 0, l = json.curves.length; i < l; i ++ ) { + + const curve = json.curves[ i ]; + this.curves.push( new Curves[ curve.type ]().fromJSON( curve ) ); + + } + + return this; + + } + +} + +class Path extends CurvePath { + + constructor( points ) { + + super(); + + this.type = 'Path'; + + this.currentPoint = new Vector2(); + + if ( points ) { + + this.setFromPoints( points ); + + } + + } + + setFromPoints( points ) { + + this.moveTo( points[ 0 ].x, points[ 0 ].y ); + + for ( let i = 1, l = points.length; i < l; i ++ ) { + + this.lineTo( points[ i ].x, points[ i ].y ); + + } + + return this; + + } + + moveTo( x, y ) { + + this.currentPoint.set( x, y ); // TODO consider referencing vectors instead of copying? + + return this; + + } + + lineTo( x, y ) { + + const curve = new LineCurve( this.currentPoint.clone(), new Vector2( x, y ) ); + this.curves.push( curve ); + + this.currentPoint.set( x, y ); + + return this; + + } + + quadraticCurveTo( aCPx, aCPy, aX, aY ) { + + const curve = new QuadraticBezierCurve( + this.currentPoint.clone(), + new Vector2( aCPx, aCPy ), + new Vector2( aX, aY ) + ); + + this.curves.push( curve ); + + this.currentPoint.set( aX, aY ); + + return this; + + } + + bezierCurveTo( aCP1x, aCP1y, aCP2x, aCP2y, aX, aY ) { + + const curve = new CubicBezierCurve( + this.currentPoint.clone(), + new Vector2( aCP1x, aCP1y ), + new Vector2( aCP2x, aCP2y ), + new Vector2( aX, aY ) + ); + + this.curves.push( curve ); + + this.currentPoint.set( aX, aY ); + + return this; + + } + + splineThru( pts /*Array of Vector*/ ) { + + const npts = [ this.currentPoint.clone() ].concat( pts ); + + const curve = new SplineCurve( npts ); + this.curves.push( curve ); + + this.currentPoint.copy( pts[ pts.length - 1 ] ); + + return this; + + } + + arc( aX, aY, aRadius, aStartAngle, aEndAngle, aClockwise ) { + + const x0 = this.currentPoint.x; + const y0 = this.currentPoint.y; + + this.absarc( aX + x0, aY + y0, aRadius, + aStartAngle, aEndAngle, aClockwise ); + + return this; + + } + + absarc( aX, aY, aRadius, aStartAngle, aEndAngle, aClockwise ) { + + this.absellipse( aX, aY, aRadius, aRadius, aStartAngle, aEndAngle, aClockwise ); + + return this; + + } + + ellipse( aX, aY, xRadius, yRadius, aStartAngle, aEndAngle, aClockwise, aRotation ) { + + const x0 = this.currentPoint.x; + const y0 = this.currentPoint.y; + + this.absellipse( aX + x0, aY + y0, xRadius, yRadius, aStartAngle, aEndAngle, aClockwise, aRotation ); + + return this; + + } + + absellipse( aX, aY, xRadius, yRadius, aStartAngle, aEndAngle, aClockwise, aRotation ) { + + const curve = new EllipseCurve( aX, aY, xRadius, yRadius, aStartAngle, aEndAngle, aClockwise, aRotation ); + + if ( this.curves.length > 0 ) { + + // if a previous curve is present, attempt to join + const firstPoint = curve.getPoint( 0 ); + + if ( ! firstPoint.equals( this.currentPoint ) ) { + + this.lineTo( firstPoint.x, firstPoint.y ); + + } + + } + + this.curves.push( curve ); + + const lastPoint = curve.getPoint( 1 ); + this.currentPoint.copy( lastPoint ); + + return this; + + } + + copy( source ) { + + super.copy( source ); + + this.currentPoint.copy( source.currentPoint ); + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.currentPoint = this.currentPoint.toArray(); + + return data; + + } + + fromJSON( json ) { + + super.fromJSON( json ); + + this.currentPoint.fromArray( json.currentPoint ); + + return this; + + } + +} + +class LatheGeometry extends BufferGeometry { + + constructor( points = [ new Vector2( 0, - 0.5 ), new Vector2( 0.5, 0 ), new Vector2( 0, 0.5 ) ], segments = 12, phiStart = 0, phiLength = Math.PI * 2 ) { + + super(); + + this.type = 'LatheGeometry'; + + this.parameters = { + points: points, + segments: segments, + phiStart: phiStart, + phiLength: phiLength + }; + + segments = Math.floor( segments ); + + // clamp phiLength so it's in range of [ 0, 2PI ] + + phiLength = clamp( phiLength, 0, Math.PI * 2 ); + + // buffers + + const indices = []; + const vertices = []; + const uvs = []; + const initNormals = []; + const normals = []; + + // helper variables + + const inverseSegments = 1.0 / segments; + const vertex = new Vector3(); + const uv = new Vector2(); + const normal = new Vector3(); + const curNormal = new Vector3(); + const prevNormal = new Vector3(); + let dx = 0; + let dy = 0; + + // pre-compute normals for initial "meridian" + + for ( let j = 0; j <= ( points.length - 1 ); j ++ ) { + + switch ( j ) { + + case 0: // special handling for 1st vertex on path + + dx = points[ j + 1 ].x - points[ j ].x; + dy = points[ j + 1 ].y - points[ j ].y; + + normal.x = dy * 1.0; + normal.y = - dx; + normal.z = dy * 0.0; + + prevNormal.copy( normal ); + + normal.normalize(); + + initNormals.push( normal.x, normal.y, normal.z ); + + break; + + case ( points.length - 1 ): // special handling for last Vertex on path + + initNormals.push( prevNormal.x, prevNormal.y, prevNormal.z ); + + break; + + default: // default handling for all vertices in between + + dx = points[ j + 1 ].x - points[ j ].x; + dy = points[ j + 1 ].y - points[ j ].y; + + normal.x = dy * 1.0; + normal.y = - dx; + normal.z = dy * 0.0; + + curNormal.copy( normal ); + + normal.x += prevNormal.x; + normal.y += prevNormal.y; + normal.z += prevNormal.z; + + normal.normalize(); + + initNormals.push( normal.x, normal.y, normal.z ); + + prevNormal.copy( curNormal ); + + } + + } + + // generate vertices, uvs and normals + + for ( let i = 0; i <= segments; i ++ ) { + + const phi = phiStart + i * inverseSegments * phiLength; + + const sin = Math.sin( phi ); + const cos = Math.cos( phi ); + + for ( let j = 0; j <= ( points.length - 1 ); j ++ ) { + + // vertex + + vertex.x = points[ j ].x * sin; + vertex.y = points[ j ].y; + vertex.z = points[ j ].x * cos; + + vertices.push( vertex.x, vertex.y, vertex.z ); + + // uv + + uv.x = i / segments; + uv.y = j / ( points.length - 1 ); + + uvs.push( uv.x, uv.y ); + + // normal + + const x = initNormals[ 3 * j + 0 ] * sin; + const y = initNormals[ 3 * j + 1 ]; + const z = initNormals[ 3 * j + 0 ] * cos; + + normals.push( x, y, z ); + + } + + } + + // indices + + for ( let i = 0; i < segments; i ++ ) { + + for ( let j = 0; j < ( points.length - 1 ); j ++ ) { + + const base = j + i * points.length; + + const a = base; + const b = base + points.length; + const c = base + points.length + 1; + const d = base + 1; + + // faces + + indices.push( a, b, d ); + indices.push( c, d, b ); + + } + + } + + // build geometry + + this.setIndex( indices ); + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvs, 2 ) ); + this.setAttribute( 'normal', new Float32BufferAttribute( normals, 3 ) ); + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + static fromJSON( data ) { + + return new LatheGeometry( data.points, data.segments, data.phiStart, data.phiLength ); + + } + +} + +class CapsuleGeometry extends LatheGeometry { + + constructor( radius = 1, length = 1, capSegments = 4, radialSegments = 8 ) { + + const path = new Path(); + path.absarc( 0, - length / 2, radius, Math.PI * 1.5, 0 ); + path.absarc( 0, length / 2, radius, 0, Math.PI * 0.5 ); + + super( path.getPoints( capSegments ), radialSegments ); + + this.type = 'CapsuleGeometry'; + + this.parameters = { + radius: radius, + length: length, + capSegments: capSegments, + radialSegments: radialSegments, + }; + + } + + static fromJSON( data ) { + + return new CapsuleGeometry( data.radius, data.length, data.capSegments, data.radialSegments ); + + } + +} + +class CircleGeometry extends BufferGeometry { + + constructor( radius = 1, segments = 32, thetaStart = 0, thetaLength = Math.PI * 2 ) { + + super(); + + this.type = 'CircleGeometry'; + + this.parameters = { + radius: radius, + segments: segments, + thetaStart: thetaStart, + thetaLength: thetaLength + }; + + segments = Math.max( 3, segments ); + + // buffers + + const indices = []; + const vertices = []; + const normals = []; + const uvs = []; + + // helper variables + + const vertex = new Vector3(); + const uv = new Vector2(); + + // center point + + vertices.push( 0, 0, 0 ); + normals.push( 0, 0, 1 ); + uvs.push( 0.5, 0.5 ); + + for ( let s = 0, i = 3; s <= segments; s ++, i += 3 ) { + + const segment = thetaStart + s / segments * thetaLength; + + // vertex + + vertex.x = radius * Math.cos( segment ); + vertex.y = radius * Math.sin( segment ); + + vertices.push( vertex.x, vertex.y, vertex.z ); + + // normal + + normals.push( 0, 0, 1 ); + + // uvs + + uv.x = ( vertices[ i ] / radius + 1 ) / 2; + uv.y = ( vertices[ i + 1 ] / radius + 1 ) / 2; + + uvs.push( uv.x, uv.y ); + + } + + // indices + + for ( let i = 1; i <= segments; i ++ ) { + + indices.push( i, i + 1, 0 ); + + } + + // build geometry + + this.setIndex( indices ); + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + this.setAttribute( 'normal', new Float32BufferAttribute( normals, 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvs, 2 ) ); + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + static fromJSON( data ) { + + return new CircleGeometry( data.radius, data.segments, data.thetaStart, data.thetaLength ); + + } + +} + +class CylinderGeometry extends BufferGeometry { + + constructor( radiusTop = 1, radiusBottom = 1, height = 1, radialSegments = 32, heightSegments = 1, openEnded = false, thetaStart = 0, thetaLength = Math.PI * 2 ) { + + super(); + + this.type = 'CylinderGeometry'; + + this.parameters = { + radiusTop: radiusTop, + radiusBottom: radiusBottom, + height: height, + radialSegments: radialSegments, + heightSegments: heightSegments, + openEnded: openEnded, + thetaStart: thetaStart, + thetaLength: thetaLength + }; + + const scope = this; + + radialSegments = Math.floor( radialSegments ); + heightSegments = Math.floor( heightSegments ); + + // buffers + + const indices = []; + const vertices = []; + const normals = []; + const uvs = []; + + // helper variables + + let index = 0; + const indexArray = []; + const halfHeight = height / 2; + let groupStart = 0; + + // generate geometry + + generateTorso(); + + if ( openEnded === false ) { + + if ( radiusTop > 0 ) generateCap( true ); + if ( radiusBottom > 0 ) generateCap( false ); + + } + + // build geometry + + this.setIndex( indices ); + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + this.setAttribute( 'normal', new Float32BufferAttribute( normals, 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvs, 2 ) ); + + function generateTorso() { + + const normal = new Vector3(); + const vertex = new Vector3(); + + let groupCount = 0; + + // this will be used to calculate the normal + const slope = ( radiusBottom - radiusTop ) / height; + + // generate vertices, normals and uvs + + for ( let y = 0; y <= heightSegments; y ++ ) { + + const indexRow = []; + + const v = y / heightSegments; + + // calculate the radius of the current row + + const radius = v * ( radiusBottom - radiusTop ) + radiusTop; + + for ( let x = 0; x <= radialSegments; x ++ ) { + + const u = x / radialSegments; + + const theta = u * thetaLength + thetaStart; + + const sinTheta = Math.sin( theta ); + const cosTheta = Math.cos( theta ); + + // vertex + + vertex.x = radius * sinTheta; + vertex.y = - v * height + halfHeight; + vertex.z = radius * cosTheta; + vertices.push( vertex.x, vertex.y, vertex.z ); + + // normal + + normal.set( sinTheta, slope, cosTheta ).normalize(); + normals.push( normal.x, normal.y, normal.z ); + + // uv + + uvs.push( u, 1 - v ); + + // save index of vertex in respective row + + indexRow.push( index ++ ); + + } + + // now save vertices of the row in our index array + + indexArray.push( indexRow ); + + } + + // generate indices + + for ( let x = 0; x < radialSegments; x ++ ) { + + for ( let y = 0; y < heightSegments; y ++ ) { + + // we use the index array to access the correct indices + + const a = indexArray[ y ][ x ]; + const b = indexArray[ y + 1 ][ x ]; + const c = indexArray[ y + 1 ][ x + 1 ]; + const d = indexArray[ y ][ x + 1 ]; + + // faces + + indices.push( a, b, d ); + indices.push( b, c, d ); + + // update group counter + + groupCount += 6; + + } + + } + + // add a group to the geometry. this will ensure multi material support + + scope.addGroup( groupStart, groupCount, 0 ); + + // calculate new start value for groups + + groupStart += groupCount; + + } + + function generateCap( top ) { + + // save the index of the first center vertex + const centerIndexStart = index; + + const uv = new Vector2(); + const vertex = new Vector3(); + + let groupCount = 0; + + const radius = ( top === true ) ? radiusTop : radiusBottom; + const sign = ( top === true ) ? 1 : - 1; + + // first we generate the center vertex data of the cap. + // because the geometry needs one set of uvs per face, + // we must generate a center vertex per face/segment + + for ( let x = 1; x <= radialSegments; x ++ ) { + + // vertex + + vertices.push( 0, halfHeight * sign, 0 ); + + // normal + + normals.push( 0, sign, 0 ); + + // uv + + uvs.push( 0.5, 0.5 ); + + // increase index + + index ++; + + } + + // save the index of the last center vertex + const centerIndexEnd = index; + + // now we generate the surrounding vertices, normals and uvs + + for ( let x = 0; x <= radialSegments; x ++ ) { + + const u = x / radialSegments; + const theta = u * thetaLength + thetaStart; + + const cosTheta = Math.cos( theta ); + const sinTheta = Math.sin( theta ); + + // vertex + + vertex.x = radius * sinTheta; + vertex.y = halfHeight * sign; + vertex.z = radius * cosTheta; + vertices.push( vertex.x, vertex.y, vertex.z ); + + // normal + + normals.push( 0, sign, 0 ); + + // uv + + uv.x = ( cosTheta * 0.5 ) + 0.5; + uv.y = ( sinTheta * 0.5 * sign ) + 0.5; + uvs.push( uv.x, uv.y ); + + // increase index + + index ++; + + } + + // generate indices + + for ( let x = 0; x < radialSegments; x ++ ) { + + const c = centerIndexStart + x; + const i = centerIndexEnd + x; + + if ( top === true ) { + + // face top + + indices.push( i, i + 1, c ); + + } else { + + // face bottom + + indices.push( i + 1, i, c ); + + } + + groupCount += 3; + + } + + // add a group to the geometry. this will ensure multi material support + + scope.addGroup( groupStart, groupCount, top === true ? 1 : 2 ); + + // calculate new start value for groups + + groupStart += groupCount; + + } + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + static fromJSON( data ) { + + return new CylinderGeometry( data.radiusTop, data.radiusBottom, data.height, data.radialSegments, data.heightSegments, data.openEnded, data.thetaStart, data.thetaLength ); + + } + +} + +class ConeGeometry extends CylinderGeometry { + + constructor( radius = 1, height = 1, radialSegments = 32, heightSegments = 1, openEnded = false, thetaStart = 0, thetaLength = Math.PI * 2 ) { + + super( 0, radius, height, radialSegments, heightSegments, openEnded, thetaStart, thetaLength ); + + this.type = 'ConeGeometry'; + + this.parameters = { + radius: radius, + height: height, + radialSegments: radialSegments, + heightSegments: heightSegments, + openEnded: openEnded, + thetaStart: thetaStart, + thetaLength: thetaLength + }; + + } + + static fromJSON( data ) { + + return new ConeGeometry( data.radius, data.height, data.radialSegments, data.heightSegments, data.openEnded, data.thetaStart, data.thetaLength ); + + } + +} + +class PolyhedronGeometry extends BufferGeometry { + + constructor( vertices = [], indices = [], radius = 1, detail = 0 ) { + + super(); + + this.type = 'PolyhedronGeometry'; + + this.parameters = { + vertices: vertices, + indices: indices, + radius: radius, + detail: detail + }; + + // default buffer data + + const vertexBuffer = []; + const uvBuffer = []; + + // the subdivision creates the vertex buffer data + + subdivide( detail ); + + // all vertices should lie on a conceptual sphere with a given radius + + applyRadius( radius ); + + // finally, create the uv data + + generateUVs(); + + // build non-indexed geometry + + this.setAttribute( 'position', new Float32BufferAttribute( vertexBuffer, 3 ) ); + this.setAttribute( 'normal', new Float32BufferAttribute( vertexBuffer.slice(), 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvBuffer, 2 ) ); + + if ( detail === 0 ) { + + this.computeVertexNormals(); // flat normals + + } else { + + this.normalizeNormals(); // smooth normals + + } + + // helper functions + + function subdivide( detail ) { + + const a = new Vector3(); + const b = new Vector3(); + const c = new Vector3(); + + // iterate over all faces and apply a subdivision with the given detail value + + for ( let i = 0; i < indices.length; i += 3 ) { + + // get the vertices of the face + + getVertexByIndex( indices[ i + 0 ], a ); + getVertexByIndex( indices[ i + 1 ], b ); + getVertexByIndex( indices[ i + 2 ], c ); + + // perform subdivision + + subdivideFace( a, b, c, detail ); + + } + + } + + function subdivideFace( a, b, c, detail ) { + + const cols = detail + 1; + + // we use this multidimensional array as a data structure for creating the subdivision + + const v = []; + + // construct all of the vertices for this subdivision + + for ( let i = 0; i <= cols; i ++ ) { + + v[ i ] = []; + + const aj = a.clone().lerp( c, i / cols ); + const bj = b.clone().lerp( c, i / cols ); + + const rows = cols - i; + + for ( let j = 0; j <= rows; j ++ ) { + + if ( j === 0 && i === cols ) { + + v[ i ][ j ] = aj; + + } else { + + v[ i ][ j ] = aj.clone().lerp( bj, j / rows ); + + } + + } + + } + + // construct all of the faces + + for ( let i = 0; i < cols; i ++ ) { + + for ( let j = 0; j < 2 * ( cols - i ) - 1; j ++ ) { + + const k = Math.floor( j / 2 ); + + if ( j % 2 === 0 ) { + + pushVertex( v[ i ][ k + 1 ] ); + pushVertex( v[ i + 1 ][ k ] ); + pushVertex( v[ i ][ k ] ); + + } else { + + pushVertex( v[ i ][ k + 1 ] ); + pushVertex( v[ i + 1 ][ k + 1 ] ); + pushVertex( v[ i + 1 ][ k ] ); + + } + + } + + } + + } + + function applyRadius( radius ) { + + const vertex = new Vector3(); + + // iterate over the entire buffer and apply the radius to each vertex + + for ( let i = 0; i < vertexBuffer.length; i += 3 ) { + + vertex.x = vertexBuffer[ i + 0 ]; + vertex.y = vertexBuffer[ i + 1 ]; + vertex.z = vertexBuffer[ i + 2 ]; + + vertex.normalize().multiplyScalar( radius ); + + vertexBuffer[ i + 0 ] = vertex.x; + vertexBuffer[ i + 1 ] = vertex.y; + vertexBuffer[ i + 2 ] = vertex.z; + + } + + } + + function generateUVs() { + + const vertex = new Vector3(); + + for ( let i = 0; i < vertexBuffer.length; i += 3 ) { + + vertex.x = vertexBuffer[ i + 0 ]; + vertex.y = vertexBuffer[ i + 1 ]; + vertex.z = vertexBuffer[ i + 2 ]; + + const u = azimuth( vertex ) / 2 / Math.PI + 0.5; + const v = inclination( vertex ) / Math.PI + 0.5; + uvBuffer.push( u, 1 - v ); + + } + + correctUVs(); + + correctSeam(); + + } + + function correctSeam() { + + // handle case when face straddles the seam, see #3269 + + for ( let i = 0; i < uvBuffer.length; i += 6 ) { + + // uv data of a single face + + const x0 = uvBuffer[ i + 0 ]; + const x1 = uvBuffer[ i + 2 ]; + const x2 = uvBuffer[ i + 4 ]; + + const max = Math.max( x0, x1, x2 ); + const min = Math.min( x0, x1, x2 ); + + // 0.9 is somewhat arbitrary + + if ( max > 0.9 && min < 0.1 ) { + + if ( x0 < 0.2 ) uvBuffer[ i + 0 ] += 1; + if ( x1 < 0.2 ) uvBuffer[ i + 2 ] += 1; + if ( x2 < 0.2 ) uvBuffer[ i + 4 ] += 1; + + } + + } + + } + + function pushVertex( vertex ) { + + vertexBuffer.push( vertex.x, vertex.y, vertex.z ); + + } + + function getVertexByIndex( index, vertex ) { + + const stride = index * 3; + + vertex.x = vertices[ stride + 0 ]; + vertex.y = vertices[ stride + 1 ]; + vertex.z = vertices[ stride + 2 ]; + + } + + function correctUVs() { + + const a = new Vector3(); + const b = new Vector3(); + const c = new Vector3(); + + const centroid = new Vector3(); + + const uvA = new Vector2(); + const uvB = new Vector2(); + const uvC = new Vector2(); + + for ( let i = 0, j = 0; i < vertexBuffer.length; i += 9, j += 6 ) { + + a.set( vertexBuffer[ i + 0 ], vertexBuffer[ i + 1 ], vertexBuffer[ i + 2 ] ); + b.set( vertexBuffer[ i + 3 ], vertexBuffer[ i + 4 ], vertexBuffer[ i + 5 ] ); + c.set( vertexBuffer[ i + 6 ], vertexBuffer[ i + 7 ], vertexBuffer[ i + 8 ] ); + + uvA.set( uvBuffer[ j + 0 ], uvBuffer[ j + 1 ] ); + uvB.set( uvBuffer[ j + 2 ], uvBuffer[ j + 3 ] ); + uvC.set( uvBuffer[ j + 4 ], uvBuffer[ j + 5 ] ); + + centroid.copy( a ).add( b ).add( c ).divideScalar( 3 ); + + const azi = azimuth( centroid ); + + correctUV( uvA, j + 0, a, azi ); + correctUV( uvB, j + 2, b, azi ); + correctUV( uvC, j + 4, c, azi ); + + } + + } + + function correctUV( uv, stride, vector, azimuth ) { + + if ( ( azimuth < 0 ) && ( uv.x === 1 ) ) { + + uvBuffer[ stride ] = uv.x - 1; + + } + + if ( ( vector.x === 0 ) && ( vector.z === 0 ) ) { + + uvBuffer[ stride ] = azimuth / 2 / Math.PI + 0.5; + + } + + } + + // Angle around the Y axis, counter-clockwise when looking from above. + + function azimuth( vector ) { + + return Math.atan2( vector.z, - vector.x ); + + } + + + // Angle above the XZ plane. + + function inclination( vector ) { + + return Math.atan2( - vector.y, Math.sqrt( ( vector.x * vector.x ) + ( vector.z * vector.z ) ) ); + + } + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + static fromJSON( data ) { + + return new PolyhedronGeometry( data.vertices, data.indices, data.radius, data.details ); + + } + +} + +class DodecahedronGeometry extends PolyhedronGeometry { + + constructor( radius = 1, detail = 0 ) { + + const t = ( 1 + Math.sqrt( 5 ) ) / 2; + const r = 1 / t; + + const vertices = [ + + // (±1, ±1, ±1) + - 1, - 1, - 1, - 1, - 1, 1, + - 1, 1, - 1, - 1, 1, 1, + 1, - 1, - 1, 1, - 1, 1, + 1, 1, - 1, 1, 1, 1, + + // (0, ±1/φ, ±φ) + 0, - r, - t, 0, - r, t, + 0, r, - t, 0, r, t, + + // (±1/φ, ±φ, 0) + - r, - t, 0, - r, t, 0, + r, - t, 0, r, t, 0, + + // (±φ, 0, ±1/φ) + - t, 0, - r, t, 0, - r, + - t, 0, r, t, 0, r + ]; + + const indices = [ + 3, 11, 7, 3, 7, 15, 3, 15, 13, + 7, 19, 17, 7, 17, 6, 7, 6, 15, + 17, 4, 8, 17, 8, 10, 17, 10, 6, + 8, 0, 16, 8, 16, 2, 8, 2, 10, + 0, 12, 1, 0, 1, 18, 0, 18, 16, + 6, 10, 2, 6, 2, 13, 6, 13, 15, + 2, 16, 18, 2, 18, 3, 2, 3, 13, + 18, 1, 9, 18, 9, 11, 18, 11, 3, + 4, 14, 12, 4, 12, 0, 4, 0, 8, + 11, 9, 5, 11, 5, 19, 11, 19, 7, + 19, 5, 14, 19, 14, 4, 19, 4, 17, + 1, 12, 14, 1, 14, 5, 1, 5, 9 + ]; + + super( vertices, indices, radius, detail ); + + this.type = 'DodecahedronGeometry'; + + this.parameters = { + radius: radius, + detail: detail + }; + + } + + static fromJSON( data ) { + + return new DodecahedronGeometry( data.radius, data.detail ); + + } + +} + +const _v0 = /*@__PURE__*/ new Vector3(); +const _v1$1 = /*@__PURE__*/ new Vector3(); +const _normal = /*@__PURE__*/ new Vector3(); +const _triangle = /*@__PURE__*/ new Triangle(); + +class EdgesGeometry extends BufferGeometry { + + constructor( geometry = null, thresholdAngle = 1 ) { + + super(); + + this.type = 'EdgesGeometry'; + + this.parameters = { + geometry: geometry, + thresholdAngle: thresholdAngle + }; + + if ( geometry !== null ) { + + const precisionPoints = 4; + const precision = Math.pow( 10, precisionPoints ); + const thresholdDot = Math.cos( DEG2RAD * thresholdAngle ); + + const indexAttr = geometry.getIndex(); + const positionAttr = geometry.getAttribute( 'position' ); + const indexCount = indexAttr ? indexAttr.count : positionAttr.count; + + const indexArr = [ 0, 0, 0 ]; + const vertKeys = [ 'a', 'b', 'c' ]; + const hashes = new Array( 3 ); + + const edgeData = {}; + const vertices = []; + for ( let i = 0; i < indexCount; i += 3 ) { + + if ( indexAttr ) { + + indexArr[ 0 ] = indexAttr.getX( i ); + indexArr[ 1 ] = indexAttr.getX( i + 1 ); + indexArr[ 2 ] = indexAttr.getX( i + 2 ); + + } else { + + indexArr[ 0 ] = i; + indexArr[ 1 ] = i + 1; + indexArr[ 2 ] = i + 2; + + } + + const { a, b, c } = _triangle; + a.fromBufferAttribute( positionAttr, indexArr[ 0 ] ); + b.fromBufferAttribute( positionAttr, indexArr[ 1 ] ); + c.fromBufferAttribute( positionAttr, indexArr[ 2 ] ); + _triangle.getNormal( _normal ); + + // create hashes for the edge from the vertices + hashes[ 0 ] = `${ Math.round( a.x * precision ) },${ Math.round( a.y * precision ) },${ Math.round( a.z * precision ) }`; + hashes[ 1 ] = `${ Math.round( b.x * precision ) },${ Math.round( b.y * precision ) },${ Math.round( b.z * precision ) }`; + hashes[ 2 ] = `${ Math.round( c.x * precision ) },${ Math.round( c.y * precision ) },${ Math.round( c.z * precision ) }`; + + // skip degenerate triangles + if ( hashes[ 0 ] === hashes[ 1 ] || hashes[ 1 ] === hashes[ 2 ] || hashes[ 2 ] === hashes[ 0 ] ) { + + continue; + + } + + // iterate over every edge + for ( let j = 0; j < 3; j ++ ) { + + // get the first and next vertex making up the edge + const jNext = ( j + 1 ) % 3; + const vecHash0 = hashes[ j ]; + const vecHash1 = hashes[ jNext ]; + const v0 = _triangle[ vertKeys[ j ] ]; + const v1 = _triangle[ vertKeys[ jNext ] ]; + + const hash = `${ vecHash0 }_${ vecHash1 }`; + const reverseHash = `${ vecHash1 }_${ vecHash0 }`; + + if ( reverseHash in edgeData && edgeData[ reverseHash ] ) { + + // if we found a sibling edge add it into the vertex array if + // it meets the angle threshold and delete the edge from the map. + if ( _normal.dot( edgeData[ reverseHash ].normal ) <= thresholdDot ) { + + vertices.push( v0.x, v0.y, v0.z ); + vertices.push( v1.x, v1.y, v1.z ); + + } + + edgeData[ reverseHash ] = null; + + } else if ( ! ( hash in edgeData ) ) { + + // if we've already got an edge here then skip adding a new one + edgeData[ hash ] = { + + index0: indexArr[ j ], + index1: indexArr[ jNext ], + normal: _normal.clone(), + + }; + + } + + } + + } + + // iterate over all remaining, unmatched edges and add them to the vertex array + for ( const key in edgeData ) { + + if ( edgeData[ key ] ) { + + const { index0, index1 } = edgeData[ key ]; + _v0.fromBufferAttribute( positionAttr, index0 ); + _v1$1.fromBufferAttribute( positionAttr, index1 ); + + vertices.push( _v0.x, _v0.y, _v0.z ); + vertices.push( _v1$1.x, _v1$1.y, _v1$1.z ); + + } + + } + + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + + } + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + +} + +class Shape extends Path { + + constructor( points ) { + + super( points ); + + this.uuid = generateUUID(); + + this.type = 'Shape'; + + this.holes = []; + + } + + getPointsHoles( divisions ) { + + const holesPts = []; + + for ( let i = 0, l = this.holes.length; i < l; i ++ ) { + + holesPts[ i ] = this.holes[ i ].getPoints( divisions ); + + } + + return holesPts; + + } + + // get points of shape and holes (keypoints based on segments parameter) + + extractPoints( divisions ) { + + return { + + shape: this.getPoints( divisions ), + holes: this.getPointsHoles( divisions ) + + }; + + } + + copy( source ) { + + super.copy( source ); + + this.holes = []; + + for ( let i = 0, l = source.holes.length; i < l; i ++ ) { + + const hole = source.holes[ i ]; + + this.holes.push( hole.clone() ); + + } + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.uuid = this.uuid; + data.holes = []; + + for ( let i = 0, l = this.holes.length; i < l; i ++ ) { + + const hole = this.holes[ i ]; + data.holes.push( hole.toJSON() ); + + } + + return data; + + } + + fromJSON( json ) { + + super.fromJSON( json ); + + this.uuid = json.uuid; + this.holes = []; + + for ( let i = 0, l = json.holes.length; i < l; i ++ ) { + + const hole = json.holes[ i ]; + this.holes.push( new Path().fromJSON( hole ) ); + + } + + return this; + + } + +} + +/** + * Port from https://github.com/mapbox/earcut (v2.2.4) + */ + +const Earcut = { + + triangulate: function ( data, holeIndices, dim = 2 ) { + + const hasHoles = holeIndices && holeIndices.length; + const outerLen = hasHoles ? holeIndices[ 0 ] * dim : data.length; + let outerNode = linkedList( data, 0, outerLen, dim, true ); + const triangles = []; + + if ( ! outerNode || outerNode.next === outerNode.prev ) return triangles; + + let minX, minY, maxX, maxY, x, y, invSize; + + if ( hasHoles ) outerNode = eliminateHoles( data, holeIndices, outerNode, dim ); + + // if the shape is not too simple, we'll use z-order curve hash later; calculate polygon bbox + if ( data.length > 80 * dim ) { + + minX = maxX = data[ 0 ]; + minY = maxY = data[ 1 ]; + + for ( let i = dim; i < outerLen; i += dim ) { + + x = data[ i ]; + y = data[ i + 1 ]; + if ( x < minX ) minX = x; + if ( y < minY ) minY = y; + if ( x > maxX ) maxX = x; + if ( y > maxY ) maxY = y; + + } + + // minX, minY and invSize are later used to transform coords into integers for z-order calculation + invSize = Math.max( maxX - minX, maxY - minY ); + invSize = invSize !== 0 ? 32767 / invSize : 0; + + } + + earcutLinked( outerNode, triangles, dim, minX, minY, invSize, 0 ); + + return triangles; + + } + +}; + +// create a circular doubly linked list from polygon points in the specified winding order +function linkedList( data, start, end, dim, clockwise ) { + + let i, last; + + if ( clockwise === ( signedArea( data, start, end, dim ) > 0 ) ) { + + for ( i = start; i < end; i += dim ) last = insertNode( i, data[ i ], data[ i + 1 ], last ); + + } else { + + for ( i = end - dim; i >= start; i -= dim ) last = insertNode( i, data[ i ], data[ i + 1 ], last ); + + } + + if ( last && equals( last, last.next ) ) { + + removeNode( last ); + last = last.next; + + } + + return last; + +} + +// eliminate colinear or duplicate points +function filterPoints( start, end ) { + + if ( ! start ) return start; + if ( ! end ) end = start; + + let p = start, + again; + do { + + again = false; + + if ( ! p.steiner && ( equals( p, p.next ) || area( p.prev, p, p.next ) === 0 ) ) { + + removeNode( p ); + p = end = p.prev; + if ( p === p.next ) break; + again = true; + + } else { + + p = p.next; + + } + + } while ( again || p !== end ); + + return end; + +} + +// main ear slicing loop which triangulates a polygon (given as a linked list) +function earcutLinked( ear, triangles, dim, minX, minY, invSize, pass ) { + + if ( ! ear ) return; + + // interlink polygon nodes in z-order + if ( ! pass && invSize ) indexCurve( ear, minX, minY, invSize ); + + let stop = ear, + prev, next; + + // iterate through ears, slicing them one by one + while ( ear.prev !== ear.next ) { + + prev = ear.prev; + next = ear.next; + + if ( invSize ? isEarHashed( ear, minX, minY, invSize ) : isEar( ear ) ) { + + // cut off the triangle + triangles.push( prev.i / dim | 0 ); + triangles.push( ear.i / dim | 0 ); + triangles.push( next.i / dim | 0 ); + + removeNode( ear ); + + // skipping the next vertex leads to less sliver triangles + ear = next.next; + stop = next.next; + + continue; + + } + + ear = next; + + // if we looped through the whole remaining polygon and can't find any more ears + if ( ear === stop ) { + + // try filtering points and slicing again + if ( ! pass ) { + + earcutLinked( filterPoints( ear ), triangles, dim, minX, minY, invSize, 1 ); + + // if this didn't work, try curing all small self-intersections locally + + } else if ( pass === 1 ) { + + ear = cureLocalIntersections( filterPoints( ear ), triangles, dim ); + earcutLinked( ear, triangles, dim, minX, minY, invSize, 2 ); + + // as a last resort, try splitting the remaining polygon into two + + } else if ( pass === 2 ) { + + splitEarcut( ear, triangles, dim, minX, minY, invSize ); + + } + + break; + + } + + } + +} + +// check whether a polygon node forms a valid ear with adjacent nodes +function isEar( ear ) { + + const a = ear.prev, + b = ear, + c = ear.next; + + if ( area( a, b, c ) >= 0 ) return false; // reflex, can't be an ear + + // now make sure we don't have other points inside the potential ear + const ax = a.x, bx = b.x, cx = c.x, ay = a.y, by = b.y, cy = c.y; + + // triangle bbox; min & max are calculated like this for speed + const x0 = ax < bx ? ( ax < cx ? ax : cx ) : ( bx < cx ? bx : cx ), + y0 = ay < by ? ( ay < cy ? ay : cy ) : ( by < cy ? by : cy ), + x1 = ax > bx ? ( ax > cx ? ax : cx ) : ( bx > cx ? bx : cx ), + y1 = ay > by ? ( ay > cy ? ay : cy ) : ( by > cy ? by : cy ); + + let p = c.next; + while ( p !== a ) { + + if ( p.x >= x0 && p.x <= x1 && p.y >= y0 && p.y <= y1 && + pointInTriangle( ax, ay, bx, by, cx, cy, p.x, p.y ) && + area( p.prev, p, p.next ) >= 0 ) return false; + p = p.next; + + } + + return true; + +} + +function isEarHashed( ear, minX, minY, invSize ) { + + const a = ear.prev, + b = ear, + c = ear.next; + + if ( area( a, b, c ) >= 0 ) return false; // reflex, can't be an ear + + const ax = a.x, bx = b.x, cx = c.x, ay = a.y, by = b.y, cy = c.y; + + // triangle bbox; min & max are calculated like this for speed + const x0 = ax < bx ? ( ax < cx ? ax : cx ) : ( bx < cx ? bx : cx ), + y0 = ay < by ? ( ay < cy ? ay : cy ) : ( by < cy ? by : cy ), + x1 = ax > bx ? ( ax > cx ? ax : cx ) : ( bx > cx ? bx : cx ), + y1 = ay > by ? ( ay > cy ? ay : cy ) : ( by > cy ? by : cy ); + + // z-order range for the current triangle bbox; + const minZ = zOrder( x0, y0, minX, minY, invSize ), + maxZ = zOrder( x1, y1, minX, minY, invSize ); + + let p = ear.prevZ, + n = ear.nextZ; + + // look for points inside the triangle in both directions + while ( p && p.z >= minZ && n && n.z <= maxZ ) { + + if ( p.x >= x0 && p.x <= x1 && p.y >= y0 && p.y <= y1 && p !== a && p !== c && + pointInTriangle( ax, ay, bx, by, cx, cy, p.x, p.y ) && area( p.prev, p, p.next ) >= 0 ) return false; + p = p.prevZ; + + if ( n.x >= x0 && n.x <= x1 && n.y >= y0 && n.y <= y1 && n !== a && n !== c && + pointInTriangle( ax, ay, bx, by, cx, cy, n.x, n.y ) && area( n.prev, n, n.next ) >= 0 ) return false; + n = n.nextZ; + + } + + // look for remaining points in decreasing z-order + while ( p && p.z >= minZ ) { + + if ( p.x >= x0 && p.x <= x1 && p.y >= y0 && p.y <= y1 && p !== a && p !== c && + pointInTriangle( ax, ay, bx, by, cx, cy, p.x, p.y ) && area( p.prev, p, p.next ) >= 0 ) return false; + p = p.prevZ; + + } + + // look for remaining points in increasing z-order + while ( n && n.z <= maxZ ) { + + if ( n.x >= x0 && n.x <= x1 && n.y >= y0 && n.y <= y1 && n !== a && n !== c && + pointInTriangle( ax, ay, bx, by, cx, cy, n.x, n.y ) && area( n.prev, n, n.next ) >= 0 ) return false; + n = n.nextZ; + + } + + return true; + +} + +// go through all polygon nodes and cure small local self-intersections +function cureLocalIntersections( start, triangles, dim ) { + + let p = start; + do { + + const a = p.prev, + b = p.next.next; + + if ( ! equals( a, b ) && intersects( a, p, p.next, b ) && locallyInside( a, b ) && locallyInside( b, a ) ) { + + triangles.push( a.i / dim | 0 ); + triangles.push( p.i / dim | 0 ); + triangles.push( b.i / dim | 0 ); + + // remove two nodes involved + removeNode( p ); + removeNode( p.next ); + + p = start = b; + + } + + p = p.next; + + } while ( p !== start ); + + return filterPoints( p ); + +} + +// try splitting polygon into two and triangulate them independently +function splitEarcut( start, triangles, dim, minX, minY, invSize ) { + + // look for a valid diagonal that divides the polygon into two + let a = start; + do { + + let b = a.next.next; + while ( b !== a.prev ) { + + if ( a.i !== b.i && isValidDiagonal( a, b ) ) { + + // split the polygon in two by the diagonal + let c = splitPolygon( a, b ); + + // filter colinear points around the cuts + a = filterPoints( a, a.next ); + c = filterPoints( c, c.next ); + + // run earcut on each half + earcutLinked( a, triangles, dim, minX, minY, invSize, 0 ); + earcutLinked( c, triangles, dim, minX, minY, invSize, 0 ); + return; + + } + + b = b.next; + + } + + a = a.next; + + } while ( a !== start ); + +} + +// link every hole into the outer loop, producing a single-ring polygon without holes +function eliminateHoles( data, holeIndices, outerNode, dim ) { + + const queue = []; + let i, len, start, end, list; + + for ( i = 0, len = holeIndices.length; i < len; i ++ ) { + + start = holeIndices[ i ] * dim; + end = i < len - 1 ? holeIndices[ i + 1 ] * dim : data.length; + list = linkedList( data, start, end, dim, false ); + if ( list === list.next ) list.steiner = true; + queue.push( getLeftmost( list ) ); + + } + + queue.sort( compareX ); + + // process holes from left to right + for ( i = 0; i < queue.length; i ++ ) { + + outerNode = eliminateHole( queue[ i ], outerNode ); + + } + + return outerNode; + +} + +function compareX( a, b ) { + + return a.x - b.x; + +} + +// find a bridge between vertices that connects hole with an outer ring and link it +function eliminateHole( hole, outerNode ) { + + const bridge = findHoleBridge( hole, outerNode ); + if ( ! bridge ) { + + return outerNode; + + } + + const bridgeReverse = splitPolygon( bridge, hole ); + + // filter collinear points around the cuts + filterPoints( bridgeReverse, bridgeReverse.next ); + return filterPoints( bridge, bridge.next ); + +} + +// David Eberly's algorithm for finding a bridge between hole and outer polygon +function findHoleBridge( hole, outerNode ) { + + let p = outerNode, + qx = - Infinity, + m; + + const hx = hole.x, hy = hole.y; + + // find a segment intersected by a ray from the hole's leftmost point to the left; + // segment's endpoint with lesser x will be potential connection point + do { + + if ( hy <= p.y && hy >= p.next.y && p.next.y !== p.y ) { + + const x = p.x + ( hy - p.y ) * ( p.next.x - p.x ) / ( p.next.y - p.y ); + if ( x <= hx && x > qx ) { + + qx = x; + m = p.x < p.next.x ? p : p.next; + if ( x === hx ) return m; // hole touches outer segment; pick leftmost endpoint + + } + + } + + p = p.next; + + } while ( p !== outerNode ); + + if ( ! m ) return null; + + // look for points inside the triangle of hole point, segment intersection and endpoint; + // if there are no points found, we have a valid connection; + // otherwise choose the point of the minimum angle with the ray as connection point + + const stop = m, + mx = m.x, + my = m.y; + let tanMin = Infinity, tan; + + p = m; + + do { + + if ( hx >= p.x && p.x >= mx && hx !== p.x && + pointInTriangle( hy < my ? hx : qx, hy, mx, my, hy < my ? qx : hx, hy, p.x, p.y ) ) { + + tan = Math.abs( hy - p.y ) / ( hx - p.x ); // tangential + + if ( locallyInside( p, hole ) && ( tan < tanMin || ( tan === tanMin && ( p.x > m.x || ( p.x === m.x && sectorContainsSector( m, p ) ) ) ) ) ) { + + m = p; + tanMin = tan; + + } + + } + + p = p.next; + + } while ( p !== stop ); + + return m; + +} + +// whether sector in vertex m contains sector in vertex p in the same coordinates +function sectorContainsSector( m, p ) { + + return area( m.prev, m, p.prev ) < 0 && area( p.next, m, m.next ) < 0; + +} + +// interlink polygon nodes in z-order +function indexCurve( start, minX, minY, invSize ) { + + let p = start; + do { + + if ( p.z === 0 ) p.z = zOrder( p.x, p.y, minX, minY, invSize ); + p.prevZ = p.prev; + p.nextZ = p.next; + p = p.next; + + } while ( p !== start ); + + p.prevZ.nextZ = null; + p.prevZ = null; + + sortLinked( p ); + +} + +// Simon Tatham's linked list merge sort algorithm +// http://www.chiark.greenend.org.uk/~sgtatham/algorithms/listsort.html +function sortLinked( list ) { + + let i, p, q, e, tail, numMerges, pSize, qSize, + inSize = 1; + + do { + + p = list; + list = null; + tail = null; + numMerges = 0; + + while ( p ) { + + numMerges ++; + q = p; + pSize = 0; + for ( i = 0; i < inSize; i ++ ) { + + pSize ++; + q = q.nextZ; + if ( ! q ) break; + + } + + qSize = inSize; + + while ( pSize > 0 || ( qSize > 0 && q ) ) { + + if ( pSize !== 0 && ( qSize === 0 || ! q || p.z <= q.z ) ) { + + e = p; + p = p.nextZ; + pSize --; + + } else { + + e = q; + q = q.nextZ; + qSize --; + + } + + if ( tail ) tail.nextZ = e; + else list = e; + + e.prevZ = tail; + tail = e; + + } + + p = q; + + } + + tail.nextZ = null; + inSize *= 2; + + } while ( numMerges > 1 ); + + return list; + +} + +// z-order of a point given coords and inverse of the longer side of data bbox +function zOrder( x, y, minX, minY, invSize ) { + + // coords are transformed into non-negative 15-bit integer range + x = ( x - minX ) * invSize | 0; + y = ( y - minY ) * invSize | 0; + + x = ( x | ( x << 8 ) ) & 0x00FF00FF; + x = ( x | ( x << 4 ) ) & 0x0F0F0F0F; + x = ( x | ( x << 2 ) ) & 0x33333333; + x = ( x | ( x << 1 ) ) & 0x55555555; + + y = ( y | ( y << 8 ) ) & 0x00FF00FF; + y = ( y | ( y << 4 ) ) & 0x0F0F0F0F; + y = ( y | ( y << 2 ) ) & 0x33333333; + y = ( y | ( y << 1 ) ) & 0x55555555; + + return x | ( y << 1 ); + +} + +// find the leftmost node of a polygon ring +function getLeftmost( start ) { + + let p = start, + leftmost = start; + do { + + if ( p.x < leftmost.x || ( p.x === leftmost.x && p.y < leftmost.y ) ) leftmost = p; + p = p.next; + + } while ( p !== start ); + + return leftmost; + +} + +// check if a point lies within a convex triangle +function pointInTriangle( ax, ay, bx, by, cx, cy, px, py ) { + + return ( cx - px ) * ( ay - py ) >= ( ax - px ) * ( cy - py ) && + ( ax - px ) * ( by - py ) >= ( bx - px ) * ( ay - py ) && + ( bx - px ) * ( cy - py ) >= ( cx - px ) * ( by - py ); + +} + +// check if a diagonal between two polygon nodes is valid (lies in polygon interior) +function isValidDiagonal( a, b ) { + + return a.next.i !== b.i && a.prev.i !== b.i && ! intersectsPolygon( a, b ) && // dones't intersect other edges + ( locallyInside( a, b ) && locallyInside( b, a ) && middleInside( a, b ) && // locally visible + ( area( a.prev, a, b.prev ) || area( a, b.prev, b ) ) || // does not create opposite-facing sectors + equals( a, b ) && area( a.prev, a, a.next ) > 0 && area( b.prev, b, b.next ) > 0 ); // special zero-length case + +} + +// signed area of a triangle +function area( p, q, r ) { + + return ( q.y - p.y ) * ( r.x - q.x ) - ( q.x - p.x ) * ( r.y - q.y ); + +} + +// check if two points are equal +function equals( p1, p2 ) { + + return p1.x === p2.x && p1.y === p2.y; + +} + +// check if two segments intersect +function intersects( p1, q1, p2, q2 ) { + + const o1 = sign( area( p1, q1, p2 ) ); + const o2 = sign( area( p1, q1, q2 ) ); + const o3 = sign( area( p2, q2, p1 ) ); + const o4 = sign( area( p2, q2, q1 ) ); + + if ( o1 !== o2 && o3 !== o4 ) return true; // general case + + if ( o1 === 0 && onSegment( p1, p2, q1 ) ) return true; // p1, q1 and p2 are collinear and p2 lies on p1q1 + if ( o2 === 0 && onSegment( p1, q2, q1 ) ) return true; // p1, q1 and q2 are collinear and q2 lies on p1q1 + if ( o3 === 0 && onSegment( p2, p1, q2 ) ) return true; // p2, q2 and p1 are collinear and p1 lies on p2q2 + if ( o4 === 0 && onSegment( p2, q1, q2 ) ) return true; // p2, q2 and q1 are collinear and q1 lies on p2q2 + + return false; + +} + +// for collinear points p, q, r, check if point q lies on segment pr +function onSegment( p, q, r ) { + + return q.x <= Math.max( p.x, r.x ) && q.x >= Math.min( p.x, r.x ) && q.y <= Math.max( p.y, r.y ) && q.y >= Math.min( p.y, r.y ); + +} + +function sign( num ) { + + return num > 0 ? 1 : num < 0 ? - 1 : 0; + +} + +// check if a polygon diagonal intersects any polygon segments +function intersectsPolygon( a, b ) { + + let p = a; + do { + + if ( p.i !== a.i && p.next.i !== a.i && p.i !== b.i && p.next.i !== b.i && + intersects( p, p.next, a, b ) ) return true; + p = p.next; + + } while ( p !== a ); + + return false; + +} + +// check if a polygon diagonal is locally inside the polygon +function locallyInside( a, b ) { + + return area( a.prev, a, a.next ) < 0 ? + area( a, b, a.next ) >= 0 && area( a, a.prev, b ) >= 0 : + area( a, b, a.prev ) < 0 || area( a, a.next, b ) < 0; + +} + +// check if the middle point of a polygon diagonal is inside the polygon +function middleInside( a, b ) { + + let p = a, + inside = false; + const px = ( a.x + b.x ) / 2, + py = ( a.y + b.y ) / 2; + do { + + if ( ( ( p.y > py ) !== ( p.next.y > py ) ) && p.next.y !== p.y && + ( px < ( p.next.x - p.x ) * ( py - p.y ) / ( p.next.y - p.y ) + p.x ) ) + inside = ! inside; + p = p.next; + + } while ( p !== a ); + + return inside; + +} + +// link two polygon vertices with a bridge; if the vertices belong to the same ring, it splits polygon into two; +// if one belongs to the outer ring and another to a hole, it merges it into a single ring +function splitPolygon( a, b ) { + + const a2 = new Node( a.i, a.x, a.y ), + b2 = new Node( b.i, b.x, b.y ), + an = a.next, + bp = b.prev; + + a.next = b; + b.prev = a; + + a2.next = an; + an.prev = a2; + + b2.next = a2; + a2.prev = b2; + + bp.next = b2; + b2.prev = bp; + + return b2; + +} + +// create a node and optionally link it with previous one (in a circular doubly linked list) +function insertNode( i, x, y, last ) { + + const p = new Node( i, x, y ); + + if ( ! last ) { + + p.prev = p; + p.next = p; + + } else { + + p.next = last.next; + p.prev = last; + last.next.prev = p; + last.next = p; + + } + + return p; + +} + +function removeNode( p ) { + + p.next.prev = p.prev; + p.prev.next = p.next; + + if ( p.prevZ ) p.prevZ.nextZ = p.nextZ; + if ( p.nextZ ) p.nextZ.prevZ = p.prevZ; + +} + +function Node( i, x, y ) { + + // vertex index in coordinates array + this.i = i; + + // vertex coordinates + this.x = x; + this.y = y; + + // previous and next vertex nodes in a polygon ring + this.prev = null; + this.next = null; + + // z-order curve value + this.z = 0; + + // previous and next nodes in z-order + this.prevZ = null; + this.nextZ = null; + + // indicates whether this is a steiner point + this.steiner = false; + +} + +function signedArea( data, start, end, dim ) { + + let sum = 0; + for ( let i = start, j = end - dim; i < end; i += dim ) { + + sum += ( data[ j ] - data[ i ] ) * ( data[ i + 1 ] + data[ j + 1 ] ); + j = i; + + } + + return sum; + +} + +class ShapeUtils { + + // calculate area of the contour polygon + + static area( contour ) { + + const n = contour.length; + let a = 0.0; + + for ( let p = n - 1, q = 0; q < n; p = q ++ ) { + + a += contour[ p ].x * contour[ q ].y - contour[ q ].x * contour[ p ].y; + + } + + return a * 0.5; + + } + + static isClockWise( pts ) { + + return ShapeUtils.area( pts ) < 0; + + } + + static triangulateShape( contour, holes ) { + + const vertices = []; // flat array of vertices like [ x0,y0, x1,y1, x2,y2, ... ] + const holeIndices = []; // array of hole indices + const faces = []; // final array of vertex indices like [ [ a,b,d ], [ b,c,d ] ] + + removeDupEndPts( contour ); + addContour( vertices, contour ); + + // + + let holeIndex = contour.length; + + holes.forEach( removeDupEndPts ); + + for ( let i = 0; i < holes.length; i ++ ) { + + holeIndices.push( holeIndex ); + holeIndex += holes[ i ].length; + addContour( vertices, holes[ i ] ); + + } + + // + + const triangles = Earcut.triangulate( vertices, holeIndices ); + + // + + for ( let i = 0; i < triangles.length; i += 3 ) { + + faces.push( triangles.slice( i, i + 3 ) ); + + } + + return faces; + + } + +} + +function removeDupEndPts( points ) { + + const l = points.length; + + if ( l > 2 && points[ l - 1 ].equals( points[ 0 ] ) ) { + + points.pop(); + + } + +} + +function addContour( vertices, contour ) { + + for ( let i = 0; i < contour.length; i ++ ) { + + vertices.push( contour[ i ].x ); + vertices.push( contour[ i ].y ); + + } + +} + +/** + * Creates extruded geometry from a path shape. + * + * parameters = { + * + * curveSegments: , // number of points on the curves + * steps: , // number of points for z-side extrusions / used for subdividing segments of extrude spline too + * depth: , // Depth to extrude the shape + * + * bevelEnabled: , // turn on bevel + * bevelThickness: , // how deep into the original shape bevel goes + * bevelSize: , // how far from shape outline (including bevelOffset) is bevel + * bevelOffset: , // how far from shape outline does bevel start + * bevelSegments: , // number of bevel layers + * + * extrudePath: // curve to extrude shape along + * + * UVGenerator: // object that provides UV generator functions + * + * } + */ + + +class ExtrudeGeometry extends BufferGeometry { + + constructor( shapes = new Shape( [ new Vector2( 0.5, 0.5 ), new Vector2( - 0.5, 0.5 ), new Vector2( - 0.5, - 0.5 ), new Vector2( 0.5, - 0.5 ) ] ), options = {} ) { + + super(); + + this.type = 'ExtrudeGeometry'; + + this.parameters = { + shapes: shapes, + options: options + }; + + shapes = Array.isArray( shapes ) ? shapes : [ shapes ]; + + const scope = this; + + const verticesArray = []; + const uvArray = []; + + for ( let i = 0, l = shapes.length; i < l; i ++ ) { + + const shape = shapes[ i ]; + addShape( shape ); + + } + + // build geometry + + this.setAttribute( 'position', new Float32BufferAttribute( verticesArray, 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvArray, 2 ) ); + + this.computeVertexNormals(); + + // functions + + function addShape( shape ) { + + const placeholder = []; + + // options + + const curveSegments = options.curveSegments !== undefined ? options.curveSegments : 12; + const steps = options.steps !== undefined ? options.steps : 1; + const depth = options.depth !== undefined ? options.depth : 1; + + let bevelEnabled = options.bevelEnabled !== undefined ? options.bevelEnabled : true; + let bevelThickness = options.bevelThickness !== undefined ? options.bevelThickness : 0.2; + let bevelSize = options.bevelSize !== undefined ? options.bevelSize : bevelThickness - 0.1; + let bevelOffset = options.bevelOffset !== undefined ? options.bevelOffset : 0; + let bevelSegments = options.bevelSegments !== undefined ? options.bevelSegments : 3; + + const extrudePath = options.extrudePath; + + const uvgen = options.UVGenerator !== undefined ? options.UVGenerator : WorldUVGenerator; + + // + + let extrudePts, extrudeByPath = false; + let splineTube, binormal, normal, position2; + + if ( extrudePath ) { + + extrudePts = extrudePath.getSpacedPoints( steps ); + + extrudeByPath = true; + bevelEnabled = false; // bevels not supported for path extrusion + + // SETUP TNB variables + + // TODO1 - have a .isClosed in spline? + + splineTube = extrudePath.computeFrenetFrames( steps, false ); + + // console.log(splineTube, 'splineTube', splineTube.normals.length, 'steps', steps, 'extrudePts', extrudePts.length); + + binormal = new Vector3(); + normal = new Vector3(); + position2 = new Vector3(); + + } + + // Safeguards if bevels are not enabled + + if ( ! bevelEnabled ) { + + bevelSegments = 0; + bevelThickness = 0; + bevelSize = 0; + bevelOffset = 0; + + } + + // Variables initialization + + const shapePoints = shape.extractPoints( curveSegments ); + + let vertices = shapePoints.shape; + const holes = shapePoints.holes; + + const reverse = ! ShapeUtils.isClockWise( vertices ); + + if ( reverse ) { + + vertices = vertices.reverse(); + + // Maybe we should also check if holes are in the opposite direction, just to be safe ... + + for ( let h = 0, hl = holes.length; h < hl; h ++ ) { + + const ahole = holes[ h ]; + + if ( ShapeUtils.isClockWise( ahole ) ) { + + holes[ h ] = ahole.reverse(); + + } + + } + + } + + + const faces = ShapeUtils.triangulateShape( vertices, holes ); + + /* Vertices */ + + const contour = vertices; // vertices has all points but contour has only points of circumference + + for ( let h = 0, hl = holes.length; h < hl; h ++ ) { + + const ahole = holes[ h ]; + + vertices = vertices.concat( ahole ); + + } + + + function scalePt2( pt, vec, size ) { + + if ( ! vec ) console.error( 'THREE.ExtrudeGeometry: vec does not exist' ); + + return pt.clone().addScaledVector( vec, size ); + + } + + const vlen = vertices.length, flen = faces.length; + + + // Find directions for point movement + + + function getBevelVec( inPt, inPrev, inNext ) { + + // computes for inPt the corresponding point inPt' on a new contour + // shifted by 1 unit (length of normalized vector) to the left + // if we walk along contour clockwise, this new contour is outside the old one + // + // inPt' is the intersection of the two lines parallel to the two + // adjacent edges of inPt at a distance of 1 unit on the left side. + + let v_trans_x, v_trans_y, shrink_by; // resulting translation vector for inPt + + // good reading for geometry algorithms (here: line-line intersection) + // http://geomalgorithms.com/a05-_intersect-1.html + + const v_prev_x = inPt.x - inPrev.x, + v_prev_y = inPt.y - inPrev.y; + const v_next_x = inNext.x - inPt.x, + v_next_y = inNext.y - inPt.y; + + const v_prev_lensq = ( v_prev_x * v_prev_x + v_prev_y * v_prev_y ); + + // check for collinear edges + const collinear0 = ( v_prev_x * v_next_y - v_prev_y * v_next_x ); + + if ( Math.abs( collinear0 ) > Number.EPSILON ) { + + // not collinear + + // length of vectors for normalizing + + const v_prev_len = Math.sqrt( v_prev_lensq ); + const v_next_len = Math.sqrt( v_next_x * v_next_x + v_next_y * v_next_y ); + + // shift adjacent points by unit vectors to the left + + const ptPrevShift_x = ( inPrev.x - v_prev_y / v_prev_len ); + const ptPrevShift_y = ( inPrev.y + v_prev_x / v_prev_len ); + + const ptNextShift_x = ( inNext.x - v_next_y / v_next_len ); + const ptNextShift_y = ( inNext.y + v_next_x / v_next_len ); + + // scaling factor for v_prev to intersection point + + const sf = ( ( ptNextShift_x - ptPrevShift_x ) * v_next_y - + ( ptNextShift_y - ptPrevShift_y ) * v_next_x ) / + ( v_prev_x * v_next_y - v_prev_y * v_next_x ); + + // vector from inPt to intersection point + + v_trans_x = ( ptPrevShift_x + v_prev_x * sf - inPt.x ); + v_trans_y = ( ptPrevShift_y + v_prev_y * sf - inPt.y ); + + // Don't normalize!, otherwise sharp corners become ugly + // but prevent crazy spikes + const v_trans_lensq = ( v_trans_x * v_trans_x + v_trans_y * v_trans_y ); + if ( v_trans_lensq <= 2 ) { + + return new Vector2( v_trans_x, v_trans_y ); + + } else { + + shrink_by = Math.sqrt( v_trans_lensq / 2 ); + + } + + } else { + + // handle special case of collinear edges + + let direction_eq = false; // assumes: opposite + + if ( v_prev_x > Number.EPSILON ) { + + if ( v_next_x > Number.EPSILON ) { + + direction_eq = true; + + } + + } else { + + if ( v_prev_x < - Number.EPSILON ) { + + if ( v_next_x < - Number.EPSILON ) { + + direction_eq = true; + + } + + } else { + + if ( Math.sign( v_prev_y ) === Math.sign( v_next_y ) ) { + + direction_eq = true; + + } + + } + + } + + if ( direction_eq ) { + + // console.log("Warning: lines are a straight sequence"); + v_trans_x = - v_prev_y; + v_trans_y = v_prev_x; + shrink_by = Math.sqrt( v_prev_lensq ); + + } else { + + // console.log("Warning: lines are a straight spike"); + v_trans_x = v_prev_x; + v_trans_y = v_prev_y; + shrink_by = Math.sqrt( v_prev_lensq / 2 ); + + } + + } + + return new Vector2( v_trans_x / shrink_by, v_trans_y / shrink_by ); + + } + + + const contourMovements = []; + + for ( let i = 0, il = contour.length, j = il - 1, k = i + 1; i < il; i ++, j ++, k ++ ) { + + if ( j === il ) j = 0; + if ( k === il ) k = 0; + + // (j)---(i)---(k) + // console.log('i,j,k', i, j , k) + + contourMovements[ i ] = getBevelVec( contour[ i ], contour[ j ], contour[ k ] ); + + } + + const holesMovements = []; + let oneHoleMovements, verticesMovements = contourMovements.concat(); + + for ( let h = 0, hl = holes.length; h < hl; h ++ ) { + + const ahole = holes[ h ]; + + oneHoleMovements = []; + + for ( let i = 0, il = ahole.length, j = il - 1, k = i + 1; i < il; i ++, j ++, k ++ ) { + + if ( j === il ) j = 0; + if ( k === il ) k = 0; + + // (j)---(i)---(k) + oneHoleMovements[ i ] = getBevelVec( ahole[ i ], ahole[ j ], ahole[ k ] ); + + } + + holesMovements.push( oneHoleMovements ); + verticesMovements = verticesMovements.concat( oneHoleMovements ); + + } + + + // Loop bevelSegments, 1 for the front, 1 for the back + + for ( let b = 0; b < bevelSegments; b ++ ) { + + //for ( b = bevelSegments; b > 0; b -- ) { + + const t = b / bevelSegments; + const z = bevelThickness * Math.cos( t * Math.PI / 2 ); + const bs = bevelSize * Math.sin( t * Math.PI / 2 ) + bevelOffset; + + // contract shape + + for ( let i = 0, il = contour.length; i < il; i ++ ) { + + const vert = scalePt2( contour[ i ], contourMovements[ i ], bs ); + + v( vert.x, vert.y, - z ); + + } + + // expand holes + + for ( let h = 0, hl = holes.length; h < hl; h ++ ) { + + const ahole = holes[ h ]; + oneHoleMovements = holesMovements[ h ]; + + for ( let i = 0, il = ahole.length; i < il; i ++ ) { + + const vert = scalePt2( ahole[ i ], oneHoleMovements[ i ], bs ); + + v( vert.x, vert.y, - z ); + + } + + } + + } + + const bs = bevelSize + bevelOffset; + + // Back facing vertices + + for ( let i = 0; i < vlen; i ++ ) { + + const vert = bevelEnabled ? scalePt2( vertices[ i ], verticesMovements[ i ], bs ) : vertices[ i ]; + + if ( ! extrudeByPath ) { + + v( vert.x, vert.y, 0 ); + + } else { + + // v( vert.x, vert.y + extrudePts[ 0 ].y, extrudePts[ 0 ].x ); + + normal.copy( splineTube.normals[ 0 ] ).multiplyScalar( vert.x ); + binormal.copy( splineTube.binormals[ 0 ] ).multiplyScalar( vert.y ); + + position2.copy( extrudePts[ 0 ] ).add( normal ).add( binormal ); + + v( position2.x, position2.y, position2.z ); + + } + + } + + // Add stepped vertices... + // Including front facing vertices + + for ( let s = 1; s <= steps; s ++ ) { + + for ( let i = 0; i < vlen; i ++ ) { + + const vert = bevelEnabled ? scalePt2( vertices[ i ], verticesMovements[ i ], bs ) : vertices[ i ]; + + if ( ! extrudeByPath ) { + + v( vert.x, vert.y, depth / steps * s ); + + } else { + + // v( vert.x, vert.y + extrudePts[ s - 1 ].y, extrudePts[ s - 1 ].x ); + + normal.copy( splineTube.normals[ s ] ).multiplyScalar( vert.x ); + binormal.copy( splineTube.binormals[ s ] ).multiplyScalar( vert.y ); + + position2.copy( extrudePts[ s ] ).add( normal ).add( binormal ); + + v( position2.x, position2.y, position2.z ); + + } + + } + + } + + + // Add bevel segments planes + + //for ( b = 1; b <= bevelSegments; b ++ ) { + for ( let b = bevelSegments - 1; b >= 0; b -- ) { + + const t = b / bevelSegments; + const z = bevelThickness * Math.cos( t * Math.PI / 2 ); + const bs = bevelSize * Math.sin( t * Math.PI / 2 ) + bevelOffset; + + // contract shape + + for ( let i = 0, il = contour.length; i < il; i ++ ) { + + const vert = scalePt2( contour[ i ], contourMovements[ i ], bs ); + v( vert.x, vert.y, depth + z ); + + } + + // expand holes + + for ( let h = 0, hl = holes.length; h < hl; h ++ ) { + + const ahole = holes[ h ]; + oneHoleMovements = holesMovements[ h ]; + + for ( let i = 0, il = ahole.length; i < il; i ++ ) { + + const vert = scalePt2( ahole[ i ], oneHoleMovements[ i ], bs ); + + if ( ! extrudeByPath ) { + + v( vert.x, vert.y, depth + z ); + + } else { + + v( vert.x, vert.y + extrudePts[ steps - 1 ].y, extrudePts[ steps - 1 ].x + z ); + + } + + } + + } + + } + + /* Faces */ + + // Top and bottom faces + + buildLidFaces(); + + // Sides faces + + buildSideFaces(); + + + ///// Internal functions + + function buildLidFaces() { + + const start = verticesArray.length / 3; + + if ( bevelEnabled ) { + + let layer = 0; // steps + 1 + let offset = vlen * layer; + + // Bottom faces + + for ( let i = 0; i < flen; i ++ ) { + + const face = faces[ i ]; + f3( face[ 2 ] + offset, face[ 1 ] + offset, face[ 0 ] + offset ); + + } + + layer = steps + bevelSegments * 2; + offset = vlen * layer; + + // Top faces + + for ( let i = 0; i < flen; i ++ ) { + + const face = faces[ i ]; + f3( face[ 0 ] + offset, face[ 1 ] + offset, face[ 2 ] + offset ); + + } + + } else { + + // Bottom faces + + for ( let i = 0; i < flen; i ++ ) { + + const face = faces[ i ]; + f3( face[ 2 ], face[ 1 ], face[ 0 ] ); + + } + + // Top faces + + for ( let i = 0; i < flen; i ++ ) { + + const face = faces[ i ]; + f3( face[ 0 ] + vlen * steps, face[ 1 ] + vlen * steps, face[ 2 ] + vlen * steps ); + + } + + } + + scope.addGroup( start, verticesArray.length / 3 - start, 0 ); + + } + + // Create faces for the z-sides of the shape + + function buildSideFaces() { + + const start = verticesArray.length / 3; + let layeroffset = 0; + sidewalls( contour, layeroffset ); + layeroffset += contour.length; + + for ( let h = 0, hl = holes.length; h < hl; h ++ ) { + + const ahole = holes[ h ]; + sidewalls( ahole, layeroffset ); + + //, true + layeroffset += ahole.length; + + } + + + scope.addGroup( start, verticesArray.length / 3 - start, 1 ); + + + } + + function sidewalls( contour, layeroffset ) { + + let i = contour.length; + + while ( -- i >= 0 ) { + + const j = i; + let k = i - 1; + if ( k < 0 ) k = contour.length - 1; + + //console.log('b', i,j, i-1, k,vertices.length); + + for ( let s = 0, sl = ( steps + bevelSegments * 2 ); s < sl; s ++ ) { + + const slen1 = vlen * s; + const slen2 = vlen * ( s + 1 ); + + const a = layeroffset + j + slen1, + b = layeroffset + k + slen1, + c = layeroffset + k + slen2, + d = layeroffset + j + slen2; + + f4( a, b, c, d ); + + } + + } + + } + + function v( x, y, z ) { + + placeholder.push( x ); + placeholder.push( y ); + placeholder.push( z ); + + } + + + function f3( a, b, c ) { + + addVertex( a ); + addVertex( b ); + addVertex( c ); + + const nextIndex = verticesArray.length / 3; + const uvs = uvgen.generateTopUV( scope, verticesArray, nextIndex - 3, nextIndex - 2, nextIndex - 1 ); + + addUV( uvs[ 0 ] ); + addUV( uvs[ 1 ] ); + addUV( uvs[ 2 ] ); + + } + + function f4( a, b, c, d ) { + + addVertex( a ); + addVertex( b ); + addVertex( d ); + + addVertex( b ); + addVertex( c ); + addVertex( d ); + + + const nextIndex = verticesArray.length / 3; + const uvs = uvgen.generateSideWallUV( scope, verticesArray, nextIndex - 6, nextIndex - 3, nextIndex - 2, nextIndex - 1 ); + + addUV( uvs[ 0 ] ); + addUV( uvs[ 1 ] ); + addUV( uvs[ 3 ] ); + + addUV( uvs[ 1 ] ); + addUV( uvs[ 2 ] ); + addUV( uvs[ 3 ] ); + + } + + function addVertex( index ) { + + verticesArray.push( placeholder[ index * 3 + 0 ] ); + verticesArray.push( placeholder[ index * 3 + 1 ] ); + verticesArray.push( placeholder[ index * 3 + 2 ] ); + + } + + + function addUV( vector2 ) { + + uvArray.push( vector2.x ); + uvArray.push( vector2.y ); + + } + + } + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + const shapes = this.parameters.shapes; + const options = this.parameters.options; + + return toJSON$1( shapes, options, data ); + + } + + static fromJSON( data, shapes ) { + + const geometryShapes = []; + + for ( let j = 0, jl = data.shapes.length; j < jl; j ++ ) { + + const shape = shapes[ data.shapes[ j ] ]; + + geometryShapes.push( shape ); + + } + + const extrudePath = data.options.extrudePath; + + if ( extrudePath !== undefined ) { + + data.options.extrudePath = new Curves[ extrudePath.type ]().fromJSON( extrudePath ); + + } + + return new ExtrudeGeometry( geometryShapes, data.options ); + + } + +} + +const WorldUVGenerator = { + + generateTopUV: function ( geometry, vertices, indexA, indexB, indexC ) { + + const a_x = vertices[ indexA * 3 ]; + const a_y = vertices[ indexA * 3 + 1 ]; + const b_x = vertices[ indexB * 3 ]; + const b_y = vertices[ indexB * 3 + 1 ]; + const c_x = vertices[ indexC * 3 ]; + const c_y = vertices[ indexC * 3 + 1 ]; + + return [ + new Vector2( a_x, a_y ), + new Vector2( b_x, b_y ), + new Vector2( c_x, c_y ) + ]; + + }, + + generateSideWallUV: function ( geometry, vertices, indexA, indexB, indexC, indexD ) { + + const a_x = vertices[ indexA * 3 ]; + const a_y = vertices[ indexA * 3 + 1 ]; + const a_z = vertices[ indexA * 3 + 2 ]; + const b_x = vertices[ indexB * 3 ]; + const b_y = vertices[ indexB * 3 + 1 ]; + const b_z = vertices[ indexB * 3 + 2 ]; + const c_x = vertices[ indexC * 3 ]; + const c_y = vertices[ indexC * 3 + 1 ]; + const c_z = vertices[ indexC * 3 + 2 ]; + const d_x = vertices[ indexD * 3 ]; + const d_y = vertices[ indexD * 3 + 1 ]; + const d_z = vertices[ indexD * 3 + 2 ]; + + if ( Math.abs( a_y - b_y ) < Math.abs( a_x - b_x ) ) { + + return [ + new Vector2( a_x, 1 - a_z ), + new Vector2( b_x, 1 - b_z ), + new Vector2( c_x, 1 - c_z ), + new Vector2( d_x, 1 - d_z ) + ]; + + } else { + + return [ + new Vector2( a_y, 1 - a_z ), + new Vector2( b_y, 1 - b_z ), + new Vector2( c_y, 1 - c_z ), + new Vector2( d_y, 1 - d_z ) + ]; + + } + + } + +}; + +function toJSON$1( shapes, options, data ) { + + data.shapes = []; + + if ( Array.isArray( shapes ) ) { + + for ( let i = 0, l = shapes.length; i < l; i ++ ) { + + const shape = shapes[ i ]; + + data.shapes.push( shape.uuid ); + + } + + } else { + + data.shapes.push( shapes.uuid ); + + } + + data.options = Object.assign( {}, options ); + + if ( options.extrudePath !== undefined ) data.options.extrudePath = options.extrudePath.toJSON(); + + return data; + +} + +class IcosahedronGeometry extends PolyhedronGeometry { + + constructor( radius = 1, detail = 0 ) { + + const t = ( 1 + Math.sqrt( 5 ) ) / 2; + + const vertices = [ + - 1, t, 0, 1, t, 0, - 1, - t, 0, 1, - t, 0, + 0, - 1, t, 0, 1, t, 0, - 1, - t, 0, 1, - t, + t, 0, - 1, t, 0, 1, - t, 0, - 1, - t, 0, 1 + ]; + + const indices = [ + 0, 11, 5, 0, 5, 1, 0, 1, 7, 0, 7, 10, 0, 10, 11, + 1, 5, 9, 5, 11, 4, 11, 10, 2, 10, 7, 6, 7, 1, 8, + 3, 9, 4, 3, 4, 2, 3, 2, 6, 3, 6, 8, 3, 8, 9, + 4, 9, 5, 2, 4, 11, 6, 2, 10, 8, 6, 7, 9, 8, 1 + ]; + + super( vertices, indices, radius, detail ); + + this.type = 'IcosahedronGeometry'; + + this.parameters = { + radius: radius, + detail: detail + }; + + } + + static fromJSON( data ) { + + return new IcosahedronGeometry( data.radius, data.detail ); + + } + +} + +class OctahedronGeometry extends PolyhedronGeometry { + + constructor( radius = 1, detail = 0 ) { + + const vertices = [ + 1, 0, 0, - 1, 0, 0, 0, 1, 0, + 0, - 1, 0, 0, 0, 1, 0, 0, - 1 + ]; + + const indices = [ + 0, 2, 4, 0, 4, 3, 0, 3, 5, + 0, 5, 2, 1, 2, 5, 1, 5, 3, + 1, 3, 4, 1, 4, 2 + ]; + + super( vertices, indices, radius, detail ); + + this.type = 'OctahedronGeometry'; + + this.parameters = { + radius: radius, + detail: detail + }; + + } + + static fromJSON( data ) { + + return new OctahedronGeometry( data.radius, data.detail ); + + } + +} + +class RingGeometry extends BufferGeometry { + + constructor( innerRadius = 0.5, outerRadius = 1, thetaSegments = 32, phiSegments = 1, thetaStart = 0, thetaLength = Math.PI * 2 ) { + + super(); + + this.type = 'RingGeometry'; + + this.parameters = { + innerRadius: innerRadius, + outerRadius: outerRadius, + thetaSegments: thetaSegments, + phiSegments: phiSegments, + thetaStart: thetaStart, + thetaLength: thetaLength + }; + + thetaSegments = Math.max( 3, thetaSegments ); + phiSegments = Math.max( 1, phiSegments ); + + // buffers + + const indices = []; + const vertices = []; + const normals = []; + const uvs = []; + + // some helper variables + + let radius = innerRadius; + const radiusStep = ( ( outerRadius - innerRadius ) / phiSegments ); + const vertex = new Vector3(); + const uv = new Vector2(); + + // generate vertices, normals and uvs + + for ( let j = 0; j <= phiSegments; j ++ ) { + + for ( let i = 0; i <= thetaSegments; i ++ ) { + + // values are generate from the inside of the ring to the outside + + const segment = thetaStart + i / thetaSegments * thetaLength; + + // vertex + + vertex.x = radius * Math.cos( segment ); + vertex.y = radius * Math.sin( segment ); + + vertices.push( vertex.x, vertex.y, vertex.z ); + + // normal + + normals.push( 0, 0, 1 ); + + // uv + + uv.x = ( vertex.x / outerRadius + 1 ) / 2; + uv.y = ( vertex.y / outerRadius + 1 ) / 2; + + uvs.push( uv.x, uv.y ); + + } + + // increase the radius for next row of vertices + + radius += radiusStep; + + } + + // indices + + for ( let j = 0; j < phiSegments; j ++ ) { + + const thetaSegmentLevel = j * ( thetaSegments + 1 ); + + for ( let i = 0; i < thetaSegments; i ++ ) { + + const segment = i + thetaSegmentLevel; + + const a = segment; + const b = segment + thetaSegments + 1; + const c = segment + thetaSegments + 2; + const d = segment + 1; + + // faces + + indices.push( a, b, d ); + indices.push( b, c, d ); + + } + + } + + // build geometry + + this.setIndex( indices ); + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + this.setAttribute( 'normal', new Float32BufferAttribute( normals, 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvs, 2 ) ); + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + static fromJSON( data ) { + + return new RingGeometry( data.innerRadius, data.outerRadius, data.thetaSegments, data.phiSegments, data.thetaStart, data.thetaLength ); + + } + +} + +class ShapeGeometry extends BufferGeometry { + + constructor( shapes = new Shape( [ new Vector2( 0, 0.5 ), new Vector2( - 0.5, - 0.5 ), new Vector2( 0.5, - 0.5 ) ] ), curveSegments = 12 ) { + + super(); + + this.type = 'ShapeGeometry'; + + this.parameters = { + shapes: shapes, + curveSegments: curveSegments + }; + + // buffers + + const indices = []; + const vertices = []; + const normals = []; + const uvs = []; + + // helper variables + + let groupStart = 0; + let groupCount = 0; + + // allow single and array values for "shapes" parameter + + if ( Array.isArray( shapes ) === false ) { + + addShape( shapes ); + + } else { + + for ( let i = 0; i < shapes.length; i ++ ) { + + addShape( shapes[ i ] ); + + this.addGroup( groupStart, groupCount, i ); // enables MultiMaterial support + + groupStart += groupCount; + groupCount = 0; + + } + + } + + // build geometry + + this.setIndex( indices ); + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + this.setAttribute( 'normal', new Float32BufferAttribute( normals, 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvs, 2 ) ); + + + // helper functions + + function addShape( shape ) { + + const indexOffset = vertices.length / 3; + const points = shape.extractPoints( curveSegments ); + + let shapeVertices = points.shape; + const shapeHoles = points.holes; + + // check direction of vertices + + if ( ShapeUtils.isClockWise( shapeVertices ) === false ) { + + shapeVertices = shapeVertices.reverse(); + + } + + for ( let i = 0, l = shapeHoles.length; i < l; i ++ ) { + + const shapeHole = shapeHoles[ i ]; + + if ( ShapeUtils.isClockWise( shapeHole ) === true ) { + + shapeHoles[ i ] = shapeHole.reverse(); + + } + + } + + const faces = ShapeUtils.triangulateShape( shapeVertices, shapeHoles ); + + // join vertices of inner and outer paths to a single array + + for ( let i = 0, l = shapeHoles.length; i < l; i ++ ) { + + const shapeHole = shapeHoles[ i ]; + shapeVertices = shapeVertices.concat( shapeHole ); + + } + + // vertices, normals, uvs + + for ( let i = 0, l = shapeVertices.length; i < l; i ++ ) { + + const vertex = shapeVertices[ i ]; + + vertices.push( vertex.x, vertex.y, 0 ); + normals.push( 0, 0, 1 ); + uvs.push( vertex.x, vertex.y ); // world uvs + + } + + // indices + + for ( let i = 0, l = faces.length; i < l; i ++ ) { + + const face = faces[ i ]; + + const a = face[ 0 ] + indexOffset; + const b = face[ 1 ] + indexOffset; + const c = face[ 2 ] + indexOffset; + + indices.push( a, b, c ); + groupCount += 3; + + } + + } + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + const shapes = this.parameters.shapes; + + return toJSON( shapes, data ); + + } + + static fromJSON( data, shapes ) { + + const geometryShapes = []; + + for ( let j = 0, jl = data.shapes.length; j < jl; j ++ ) { + + const shape = shapes[ data.shapes[ j ] ]; + + geometryShapes.push( shape ); + + } + + return new ShapeGeometry( geometryShapes, data.curveSegments ); + + } + +} + +function toJSON( shapes, data ) { + + data.shapes = []; + + if ( Array.isArray( shapes ) ) { + + for ( let i = 0, l = shapes.length; i < l; i ++ ) { + + const shape = shapes[ i ]; + + data.shapes.push( shape.uuid ); + + } + + } else { + + data.shapes.push( shapes.uuid ); + + } + + return data; + +} + +class SphereGeometry extends BufferGeometry { + + constructor( radius = 1, widthSegments = 32, heightSegments = 16, phiStart = 0, phiLength = Math.PI * 2, thetaStart = 0, thetaLength = Math.PI ) { + + super(); + + this.type = 'SphereGeometry'; + + this.parameters = { + radius: radius, + widthSegments: widthSegments, + heightSegments: heightSegments, + phiStart: phiStart, + phiLength: phiLength, + thetaStart: thetaStart, + thetaLength: thetaLength + }; + + widthSegments = Math.max( 3, Math.floor( widthSegments ) ); + heightSegments = Math.max( 2, Math.floor( heightSegments ) ); + + const thetaEnd = Math.min( thetaStart + thetaLength, Math.PI ); + + let index = 0; + const grid = []; + + const vertex = new Vector3(); + const normal = new Vector3(); + + // buffers + + const indices = []; + const vertices = []; + const normals = []; + const uvs = []; + + // generate vertices, normals and uvs + + for ( let iy = 0; iy <= heightSegments; iy ++ ) { + + const verticesRow = []; + + const v = iy / heightSegments; + + // special case for the poles + + let uOffset = 0; + + if ( iy === 0 && thetaStart === 0 ) { + + uOffset = 0.5 / widthSegments; + + } else if ( iy === heightSegments && thetaEnd === Math.PI ) { + + uOffset = - 0.5 / widthSegments; + + } + + for ( let ix = 0; ix <= widthSegments; ix ++ ) { + + const u = ix / widthSegments; + + // vertex + + vertex.x = - radius * Math.cos( phiStart + u * phiLength ) * Math.sin( thetaStart + v * thetaLength ); + vertex.y = radius * Math.cos( thetaStart + v * thetaLength ); + vertex.z = radius * Math.sin( phiStart + u * phiLength ) * Math.sin( thetaStart + v * thetaLength ); + + vertices.push( vertex.x, vertex.y, vertex.z ); + + // normal + + normal.copy( vertex ).normalize(); + normals.push( normal.x, normal.y, normal.z ); + + // uv + + uvs.push( u + uOffset, 1 - v ); + + verticesRow.push( index ++ ); + + } + + grid.push( verticesRow ); + + } + + // indices + + for ( let iy = 0; iy < heightSegments; iy ++ ) { + + for ( let ix = 0; ix < widthSegments; ix ++ ) { + + const a = grid[ iy ][ ix + 1 ]; + const b = grid[ iy ][ ix ]; + const c = grid[ iy + 1 ][ ix ]; + const d = grid[ iy + 1 ][ ix + 1 ]; + + if ( iy !== 0 || thetaStart > 0 ) indices.push( a, b, d ); + if ( iy !== heightSegments - 1 || thetaEnd < Math.PI ) indices.push( b, c, d ); + + } + + } + + // build geometry + + this.setIndex( indices ); + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + this.setAttribute( 'normal', new Float32BufferAttribute( normals, 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvs, 2 ) ); + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + static fromJSON( data ) { + + return new SphereGeometry( data.radius, data.widthSegments, data.heightSegments, data.phiStart, data.phiLength, data.thetaStart, data.thetaLength ); + + } + +} + +class TetrahedronGeometry extends PolyhedronGeometry { + + constructor( radius = 1, detail = 0 ) { + + const vertices = [ + 1, 1, 1, - 1, - 1, 1, - 1, 1, - 1, 1, - 1, - 1 + ]; + + const indices = [ + 2, 1, 0, 0, 3, 2, 1, 3, 0, 2, 3, 1 + ]; + + super( vertices, indices, radius, detail ); + + this.type = 'TetrahedronGeometry'; + + this.parameters = { + radius: radius, + detail: detail + }; + + } + + static fromJSON( data ) { + + return new TetrahedronGeometry( data.radius, data.detail ); + + } + +} + +class TorusGeometry extends BufferGeometry { + + constructor( radius = 1, tube = 0.4, radialSegments = 12, tubularSegments = 48, arc = Math.PI * 2 ) { + + super(); + + this.type = 'TorusGeometry'; + + this.parameters = { + radius: radius, + tube: tube, + radialSegments: radialSegments, + tubularSegments: tubularSegments, + arc: arc + }; + + radialSegments = Math.floor( radialSegments ); + tubularSegments = Math.floor( tubularSegments ); + + // buffers + + const indices = []; + const vertices = []; + const normals = []; + const uvs = []; + + // helper variables + + const center = new Vector3(); + const vertex = new Vector3(); + const normal = new Vector3(); + + // generate vertices, normals and uvs + + for ( let j = 0; j <= radialSegments; j ++ ) { + + for ( let i = 0; i <= tubularSegments; i ++ ) { + + const u = i / tubularSegments * arc; + const v = j / radialSegments * Math.PI * 2; + + // vertex + + vertex.x = ( radius + tube * Math.cos( v ) ) * Math.cos( u ); + vertex.y = ( radius + tube * Math.cos( v ) ) * Math.sin( u ); + vertex.z = tube * Math.sin( v ); + + vertices.push( vertex.x, vertex.y, vertex.z ); + + // normal + + center.x = radius * Math.cos( u ); + center.y = radius * Math.sin( u ); + normal.subVectors( vertex, center ).normalize(); + + normals.push( normal.x, normal.y, normal.z ); + + // uv + + uvs.push( i / tubularSegments ); + uvs.push( j / radialSegments ); + + } + + } + + // generate indices + + for ( let j = 1; j <= radialSegments; j ++ ) { + + for ( let i = 1; i <= tubularSegments; i ++ ) { + + // indices + + const a = ( tubularSegments + 1 ) * j + i - 1; + const b = ( tubularSegments + 1 ) * ( j - 1 ) + i - 1; + const c = ( tubularSegments + 1 ) * ( j - 1 ) + i; + const d = ( tubularSegments + 1 ) * j + i; + + // faces + + indices.push( a, b, d ); + indices.push( b, c, d ); + + } + + } + + // build geometry + + this.setIndex( indices ); + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + this.setAttribute( 'normal', new Float32BufferAttribute( normals, 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvs, 2 ) ); + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + static fromJSON( data ) { + + return new TorusGeometry( data.radius, data.tube, data.radialSegments, data.tubularSegments, data.arc ); + + } + +} + +class TorusKnotGeometry extends BufferGeometry { + + constructor( radius = 1, tube = 0.4, tubularSegments = 64, radialSegments = 8, p = 2, q = 3 ) { + + super(); + + this.type = 'TorusKnotGeometry'; + + this.parameters = { + radius: radius, + tube: tube, + tubularSegments: tubularSegments, + radialSegments: radialSegments, + p: p, + q: q + }; + + tubularSegments = Math.floor( tubularSegments ); + radialSegments = Math.floor( radialSegments ); + + // buffers + + const indices = []; + const vertices = []; + const normals = []; + const uvs = []; + + // helper variables + + const vertex = new Vector3(); + const normal = new Vector3(); + + const P1 = new Vector3(); + const P2 = new Vector3(); + + const B = new Vector3(); + const T = new Vector3(); + const N = new Vector3(); + + // generate vertices, normals and uvs + + for ( let i = 0; i <= tubularSegments; ++ i ) { + + // the radian "u" is used to calculate the position on the torus curve of the current tubular segment + + const u = i / tubularSegments * p * Math.PI * 2; + + // now we calculate two points. P1 is our current position on the curve, P2 is a little farther ahead. + // these points are used to create a special "coordinate space", which is necessary to calculate the correct vertex positions + + calculatePositionOnCurve( u, p, q, radius, P1 ); + calculatePositionOnCurve( u + 0.01, p, q, radius, P2 ); + + // calculate orthonormal basis + + T.subVectors( P2, P1 ); + N.addVectors( P2, P1 ); + B.crossVectors( T, N ); + N.crossVectors( B, T ); + + // normalize B, N. T can be ignored, we don't use it + + B.normalize(); + N.normalize(); + + for ( let j = 0; j <= radialSegments; ++ j ) { + + // now calculate the vertices. they are nothing more than an extrusion of the torus curve. + // because we extrude a shape in the xy-plane, there is no need to calculate a z-value. + + const v = j / radialSegments * Math.PI * 2; + const cx = - tube * Math.cos( v ); + const cy = tube * Math.sin( v ); + + // now calculate the final vertex position. + // first we orient the extrusion with our basis vectors, then we add it to the current position on the curve + + vertex.x = P1.x + ( cx * N.x + cy * B.x ); + vertex.y = P1.y + ( cx * N.y + cy * B.y ); + vertex.z = P1.z + ( cx * N.z + cy * B.z ); + + vertices.push( vertex.x, vertex.y, vertex.z ); + + // normal (P1 is always the center/origin of the extrusion, thus we can use it to calculate the normal) + + normal.subVectors( vertex, P1 ).normalize(); + + normals.push( normal.x, normal.y, normal.z ); + + // uv + + uvs.push( i / tubularSegments ); + uvs.push( j / radialSegments ); + + } + + } + + // generate indices + + for ( let j = 1; j <= tubularSegments; j ++ ) { + + for ( let i = 1; i <= radialSegments; i ++ ) { + + // indices + + const a = ( radialSegments + 1 ) * ( j - 1 ) + ( i - 1 ); + const b = ( radialSegments + 1 ) * j + ( i - 1 ); + const c = ( radialSegments + 1 ) * j + i; + const d = ( radialSegments + 1 ) * ( j - 1 ) + i; + + // faces + + indices.push( a, b, d ); + indices.push( b, c, d ); + + } + + } + + // build geometry + + this.setIndex( indices ); + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + this.setAttribute( 'normal', new Float32BufferAttribute( normals, 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvs, 2 ) ); + + // this function calculates the current position on the torus curve + + function calculatePositionOnCurve( u, p, q, radius, position ) { + + const cu = Math.cos( u ); + const su = Math.sin( u ); + const quOverP = q / p * u; + const cs = Math.cos( quOverP ); + + position.x = radius * ( 2 + cs ) * 0.5 * cu; + position.y = radius * ( 2 + cs ) * su * 0.5; + position.z = radius * Math.sin( quOverP ) * 0.5; + + } + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + static fromJSON( data ) { + + return new TorusKnotGeometry( data.radius, data.tube, data.tubularSegments, data.radialSegments, data.p, data.q ); + + } + +} + +class TubeGeometry extends BufferGeometry { + + constructor( path = new QuadraticBezierCurve3( new Vector3( - 1, - 1, 0 ), new Vector3( - 1, 1, 0 ), new Vector3( 1, 1, 0 ) ), tubularSegments = 64, radius = 1, radialSegments = 8, closed = false ) { + + super(); + + this.type = 'TubeGeometry'; + + this.parameters = { + path: path, + tubularSegments: tubularSegments, + radius: radius, + radialSegments: radialSegments, + closed: closed + }; + + const frames = path.computeFrenetFrames( tubularSegments, closed ); + + // expose internals + + this.tangents = frames.tangents; + this.normals = frames.normals; + this.binormals = frames.binormals; + + // helper variables + + const vertex = new Vector3(); + const normal = new Vector3(); + const uv = new Vector2(); + let P = new Vector3(); + + // buffer + + const vertices = []; + const normals = []; + const uvs = []; + const indices = []; + + // create buffer data + + generateBufferData(); + + // build geometry + + this.setIndex( indices ); + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + this.setAttribute( 'normal', new Float32BufferAttribute( normals, 3 ) ); + this.setAttribute( 'uv', new Float32BufferAttribute( uvs, 2 ) ); + + // functions + + function generateBufferData() { + + for ( let i = 0; i < tubularSegments; i ++ ) { + + generateSegment( i ); + + } + + // if the geometry is not closed, generate the last row of vertices and normals + // at the regular position on the given path + // + // if the geometry is closed, duplicate the first row of vertices and normals (uvs will differ) + + generateSegment( ( closed === false ) ? tubularSegments : 0 ); + + // uvs are generated in a separate function. + // this makes it easy compute correct values for closed geometries + + generateUVs(); + + // finally create faces + + generateIndices(); + + } + + function generateSegment( i ) { + + // we use getPointAt to sample evenly distributed points from the given path + + P = path.getPointAt( i / tubularSegments, P ); + + // retrieve corresponding normal and binormal + + const N = frames.normals[ i ]; + const B = frames.binormals[ i ]; + + // generate normals and vertices for the current segment + + for ( let j = 0; j <= radialSegments; j ++ ) { + + const v = j / radialSegments * Math.PI * 2; + + const sin = Math.sin( v ); + const cos = - Math.cos( v ); + + // normal + + normal.x = ( cos * N.x + sin * B.x ); + normal.y = ( cos * N.y + sin * B.y ); + normal.z = ( cos * N.z + sin * B.z ); + normal.normalize(); + + normals.push( normal.x, normal.y, normal.z ); + + // vertex + + vertex.x = P.x + radius * normal.x; + vertex.y = P.y + radius * normal.y; + vertex.z = P.z + radius * normal.z; + + vertices.push( vertex.x, vertex.y, vertex.z ); + + } + + } + + function generateIndices() { + + for ( let j = 1; j <= tubularSegments; j ++ ) { + + for ( let i = 1; i <= radialSegments; i ++ ) { + + const a = ( radialSegments + 1 ) * ( j - 1 ) + ( i - 1 ); + const b = ( radialSegments + 1 ) * j + ( i - 1 ); + const c = ( radialSegments + 1 ) * j + i; + const d = ( radialSegments + 1 ) * ( j - 1 ) + i; + + // faces + + indices.push( a, b, d ); + indices.push( b, c, d ); + + } + + } + + } + + function generateUVs() { + + for ( let i = 0; i <= tubularSegments; i ++ ) { + + for ( let j = 0; j <= radialSegments; j ++ ) { + + uv.x = i / tubularSegments; + uv.y = j / radialSegments; + + uvs.push( uv.x, uv.y ); + + } + + } + + } + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.path = this.parameters.path.toJSON(); + + return data; + + } + + static fromJSON( data ) { + + // This only works for built-in curves (e.g. CatmullRomCurve3). + // User defined curves or instances of CurvePath will not be deserialized. + return new TubeGeometry( + new Curves[ data.path.type ]().fromJSON( data.path ), + data.tubularSegments, + data.radius, + data.radialSegments, + data.closed + ); + + } + +} + +class WireframeGeometry extends BufferGeometry { + + constructor( geometry = null ) { + + super(); + + this.type = 'WireframeGeometry'; + + this.parameters = { + geometry: geometry + }; + + if ( geometry !== null ) { + + // buffer + + const vertices = []; + const edges = new Set(); + + // helper variables + + const start = new Vector3(); + const end = new Vector3(); + + if ( geometry.index !== null ) { + + // indexed BufferGeometry + + const position = geometry.attributes.position; + const indices = geometry.index; + let groups = geometry.groups; + + if ( groups.length === 0 ) { + + groups = [ { start: 0, count: indices.count, materialIndex: 0 } ]; + + } + + // create a data structure that contains all edges without duplicates + + for ( let o = 0, ol = groups.length; o < ol; ++ o ) { + + const group = groups[ o ]; + + const groupStart = group.start; + const groupCount = group.count; + + for ( let i = groupStart, l = ( groupStart + groupCount ); i < l; i += 3 ) { + + for ( let j = 0; j < 3; j ++ ) { + + const index1 = indices.getX( i + j ); + const index2 = indices.getX( i + ( j + 1 ) % 3 ); + + start.fromBufferAttribute( position, index1 ); + end.fromBufferAttribute( position, index2 ); + + if ( isUniqueEdge( start, end, edges ) === true ) { + + vertices.push( start.x, start.y, start.z ); + vertices.push( end.x, end.y, end.z ); + + } + + } + + } + + } + + } else { + + // non-indexed BufferGeometry + + const position = geometry.attributes.position; + + for ( let i = 0, l = ( position.count / 3 ); i < l; i ++ ) { + + for ( let j = 0; j < 3; j ++ ) { + + // three edges per triangle, an edge is represented as (index1, index2) + // e.g. the first triangle has the following edges: (0,1),(1,2),(2,0) + + const index1 = 3 * i + j; + const index2 = 3 * i + ( ( j + 1 ) % 3 ); + + start.fromBufferAttribute( position, index1 ); + end.fromBufferAttribute( position, index2 ); + + if ( isUniqueEdge( start, end, edges ) === true ) { + + vertices.push( start.x, start.y, start.z ); + vertices.push( end.x, end.y, end.z ); + + } + + } + + } + + } + + // build geometry + + this.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + + } + + } + + copy( source ) { + + super.copy( source ); + + this.parameters = Object.assign( {}, source.parameters ); + + return this; + + } + +} + +function isUniqueEdge( start, end, edges ) { + + const hash1 = `${start.x},${start.y},${start.z}-${end.x},${end.y},${end.z}`; + const hash2 = `${end.x},${end.y},${end.z}-${start.x},${start.y},${start.z}`; // coincident edge + + if ( edges.has( hash1 ) === true || edges.has( hash2 ) === true ) { + + return false; + + } else { + + edges.add( hash1 ); + edges.add( hash2 ); + return true; + + } + +} + +var Geometries = /*#__PURE__*/Object.freeze({ + __proto__: null, + BoxGeometry: BoxGeometry, + CapsuleGeometry: CapsuleGeometry, + CircleGeometry: CircleGeometry, + ConeGeometry: ConeGeometry, + CylinderGeometry: CylinderGeometry, + DodecahedronGeometry: DodecahedronGeometry, + EdgesGeometry: EdgesGeometry, + ExtrudeGeometry: ExtrudeGeometry, + IcosahedronGeometry: IcosahedronGeometry, + LatheGeometry: LatheGeometry, + OctahedronGeometry: OctahedronGeometry, + PlaneGeometry: PlaneGeometry, + PolyhedronGeometry: PolyhedronGeometry, + RingGeometry: RingGeometry, + ShapeGeometry: ShapeGeometry, + SphereGeometry: SphereGeometry, + TetrahedronGeometry: TetrahedronGeometry, + TorusGeometry: TorusGeometry, + TorusKnotGeometry: TorusKnotGeometry, + TubeGeometry: TubeGeometry, + WireframeGeometry: WireframeGeometry +}); + +class ShadowMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isShadowMaterial = true; + + this.type = 'ShadowMaterial'; + + this.color = new Color( 0x000000 ); + this.transparent = true; + + this.fog = true; + + this.setValues( parameters ); + + } + + copy( source ) { + + super.copy( source ); + + this.color.copy( source.color ); + + this.fog = source.fog; + + return this; + + } + +} + +class RawShaderMaterial extends ShaderMaterial { + + constructor( parameters ) { + + super( parameters ); + + this.isRawShaderMaterial = true; + + this.type = 'RawShaderMaterial'; + + } + +} + +class MeshStandardMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isMeshStandardMaterial = true; + + this.defines = { 'STANDARD': '' }; + + this.type = 'MeshStandardMaterial'; + + this.color = new Color( 0xffffff ); // diffuse + this.roughness = 1.0; + this.metalness = 0.0; + + this.map = null; + + this.lightMap = null; + this.lightMapIntensity = 1.0; + + this.aoMap = null; + this.aoMapIntensity = 1.0; + + this.emissive = new Color( 0x000000 ); + this.emissiveIntensity = 1.0; + this.emissiveMap = null; + + this.bumpMap = null; + this.bumpScale = 1; + + this.normalMap = null; + this.normalMapType = TangentSpaceNormalMap; + this.normalScale = new Vector2( 1, 1 ); + + this.displacementMap = null; + this.displacementScale = 1; + this.displacementBias = 0; + + this.roughnessMap = null; + + this.metalnessMap = null; + + this.alphaMap = null; + + this.envMap = null; + this.envMapRotation = new Euler(); + this.envMapIntensity = 1.0; + + this.wireframe = false; + this.wireframeLinewidth = 1; + this.wireframeLinecap = 'round'; + this.wireframeLinejoin = 'round'; + + this.flatShading = false; + + this.fog = true; + + this.setValues( parameters ); + + } + + copy( source ) { + + super.copy( source ); + + this.defines = { 'STANDARD': '' }; + + this.color.copy( source.color ); + this.roughness = source.roughness; + this.metalness = source.metalness; + + this.map = source.map; + + this.lightMap = source.lightMap; + this.lightMapIntensity = source.lightMapIntensity; + + this.aoMap = source.aoMap; + this.aoMapIntensity = source.aoMapIntensity; + + this.emissive.copy( source.emissive ); + this.emissiveMap = source.emissiveMap; + this.emissiveIntensity = source.emissiveIntensity; + + this.bumpMap = source.bumpMap; + this.bumpScale = source.bumpScale; + + this.normalMap = source.normalMap; + this.normalMapType = source.normalMapType; + this.normalScale.copy( source.normalScale ); + + this.displacementMap = source.displacementMap; + this.displacementScale = source.displacementScale; + this.displacementBias = source.displacementBias; + + this.roughnessMap = source.roughnessMap; + + this.metalnessMap = source.metalnessMap; + + this.alphaMap = source.alphaMap; + + this.envMap = source.envMap; + this.envMapRotation.copy( source.envMapRotation ); + this.envMapIntensity = source.envMapIntensity; + + this.wireframe = source.wireframe; + this.wireframeLinewidth = source.wireframeLinewidth; + this.wireframeLinecap = source.wireframeLinecap; + this.wireframeLinejoin = source.wireframeLinejoin; + + this.flatShading = source.flatShading; + + this.fog = source.fog; + + return this; + + } + +} + +class MeshPhysicalMaterial extends MeshStandardMaterial { + + constructor( parameters ) { + + super(); + + this.isMeshPhysicalMaterial = true; + + this.defines = { + + 'STANDARD': '', + 'PHYSICAL': '' + + }; + + this.type = 'MeshPhysicalMaterial'; + + this.anisotropyRotation = 0; + this.anisotropyMap = null; + + this.clearcoatMap = null; + this.clearcoatRoughness = 0.0; + this.clearcoatRoughnessMap = null; + this.clearcoatNormalScale = new Vector2( 1, 1 ); + this.clearcoatNormalMap = null; + + this.ior = 1.5; + + Object.defineProperty( this, 'reflectivity', { + get: function () { + + return ( clamp( 2.5 * ( this.ior - 1 ) / ( this.ior + 1 ), 0, 1 ) ); + + }, + set: function ( reflectivity ) { + + this.ior = ( 1 + 0.4 * reflectivity ) / ( 1 - 0.4 * reflectivity ); + + } + } ); + + this.iridescenceMap = null; + this.iridescenceIOR = 1.3; + this.iridescenceThicknessRange = [ 100, 400 ]; + this.iridescenceThicknessMap = null; + + this.sheenColor = new Color( 0x000000 ); + this.sheenColorMap = null; + this.sheenRoughness = 1.0; + this.sheenRoughnessMap = null; + + this.transmissionMap = null; + + this.thickness = 0; + this.thicknessMap = null; + this.attenuationDistance = Infinity; + this.attenuationColor = new Color( 1, 1, 1 ); + + this.specularIntensity = 1.0; + this.specularIntensityMap = null; + this.specularColor = new Color( 1, 1, 1 ); + this.specularColorMap = null; + + this._anisotropy = 0; + this._clearcoat = 0; + this._dispersion = 0; + this._iridescence = 0; + this._sheen = 0.0; + this._transmission = 0; + + this.setValues( parameters ); + + } + + get anisotropy() { + + return this._anisotropy; + + } + + set anisotropy( value ) { + + if ( this._anisotropy > 0 !== value > 0 ) { + + this.version ++; + + } + + this._anisotropy = value; + + } + + get clearcoat() { + + return this._clearcoat; + + } + + set clearcoat( value ) { + + if ( this._clearcoat > 0 !== value > 0 ) { + + this.version ++; + + } + + this._clearcoat = value; + + } + + get iridescence() { + + return this._iridescence; + + } + + set iridescence( value ) { + + if ( this._iridescence > 0 !== value > 0 ) { + + this.version ++; + + } + + this._iridescence = value; + + } + + get dispersion() { + + return this._dispersion; + + } + + set dispersion( value ) { + + if ( this._dispersion > 0 !== value > 0 ) { + + this.version ++; + + } + + this._dispersion = value; + + } + + get sheen() { + + return this._sheen; + + } + + set sheen( value ) { + + if ( this._sheen > 0 !== value > 0 ) { + + this.version ++; + + } + + this._sheen = value; + + } + + get transmission() { + + return this._transmission; + + } + + set transmission( value ) { + + if ( this._transmission > 0 !== value > 0 ) { + + this.version ++; + + } + + this._transmission = value; + + } + + copy( source ) { + + super.copy( source ); + + this.defines = { + + 'STANDARD': '', + 'PHYSICAL': '' + + }; + + this.anisotropy = source.anisotropy; + this.anisotropyRotation = source.anisotropyRotation; + this.anisotropyMap = source.anisotropyMap; + + this.clearcoat = source.clearcoat; + this.clearcoatMap = source.clearcoatMap; + this.clearcoatRoughness = source.clearcoatRoughness; + this.clearcoatRoughnessMap = source.clearcoatRoughnessMap; + this.clearcoatNormalMap = source.clearcoatNormalMap; + this.clearcoatNormalScale.copy( source.clearcoatNormalScale ); + + this.dispersion = source.dispersion; + this.ior = source.ior; + + this.iridescence = source.iridescence; + this.iridescenceMap = source.iridescenceMap; + this.iridescenceIOR = source.iridescenceIOR; + this.iridescenceThicknessRange = [ ...source.iridescenceThicknessRange ]; + this.iridescenceThicknessMap = source.iridescenceThicknessMap; + + this.sheen = source.sheen; + this.sheenColor.copy( source.sheenColor ); + this.sheenColorMap = source.sheenColorMap; + this.sheenRoughness = source.sheenRoughness; + this.sheenRoughnessMap = source.sheenRoughnessMap; + + this.transmission = source.transmission; + this.transmissionMap = source.transmissionMap; + + this.thickness = source.thickness; + this.thicknessMap = source.thicknessMap; + this.attenuationDistance = source.attenuationDistance; + this.attenuationColor.copy( source.attenuationColor ); + + this.specularIntensity = source.specularIntensity; + this.specularIntensityMap = source.specularIntensityMap; + this.specularColor.copy( source.specularColor ); + this.specularColorMap = source.specularColorMap; + + return this; + + } + +} + +class MeshPhongMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isMeshPhongMaterial = true; + + this.type = 'MeshPhongMaterial'; + + this.color = new Color( 0xffffff ); // diffuse + this.specular = new Color( 0x111111 ); + this.shininess = 30; + + this.map = null; + + this.lightMap = null; + this.lightMapIntensity = 1.0; + + this.aoMap = null; + this.aoMapIntensity = 1.0; + + this.emissive = new Color( 0x000000 ); + this.emissiveIntensity = 1.0; + this.emissiveMap = null; + + this.bumpMap = null; + this.bumpScale = 1; + + this.normalMap = null; + this.normalMapType = TangentSpaceNormalMap; + this.normalScale = new Vector2( 1, 1 ); + + this.displacementMap = null; + this.displacementScale = 1; + this.displacementBias = 0; + + this.specularMap = null; + + this.alphaMap = null; + + this.envMap = null; + this.envMapRotation = new Euler(); + this.combine = MultiplyOperation; + this.reflectivity = 1; + this.refractionRatio = 0.98; + + this.wireframe = false; + this.wireframeLinewidth = 1; + this.wireframeLinecap = 'round'; + this.wireframeLinejoin = 'round'; + + this.flatShading = false; + + this.fog = true; + + this.setValues( parameters ); + + } + + copy( source ) { + + super.copy( source ); + + this.color.copy( source.color ); + this.specular.copy( source.specular ); + this.shininess = source.shininess; + + this.map = source.map; + + this.lightMap = source.lightMap; + this.lightMapIntensity = source.lightMapIntensity; + + this.aoMap = source.aoMap; + this.aoMapIntensity = source.aoMapIntensity; + + this.emissive.copy( source.emissive ); + this.emissiveMap = source.emissiveMap; + this.emissiveIntensity = source.emissiveIntensity; + + this.bumpMap = source.bumpMap; + this.bumpScale = source.bumpScale; + + this.normalMap = source.normalMap; + this.normalMapType = source.normalMapType; + this.normalScale.copy( source.normalScale ); + + this.displacementMap = source.displacementMap; + this.displacementScale = source.displacementScale; + this.displacementBias = source.displacementBias; + + this.specularMap = source.specularMap; + + this.alphaMap = source.alphaMap; + + this.envMap = source.envMap; + this.envMapRotation.copy( source.envMapRotation ); + this.combine = source.combine; + this.reflectivity = source.reflectivity; + this.refractionRatio = source.refractionRatio; + + this.wireframe = source.wireframe; + this.wireframeLinewidth = source.wireframeLinewidth; + this.wireframeLinecap = source.wireframeLinecap; + this.wireframeLinejoin = source.wireframeLinejoin; + + this.flatShading = source.flatShading; + + this.fog = source.fog; + + return this; + + } + +} + +class MeshToonMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isMeshToonMaterial = true; + + this.defines = { 'TOON': '' }; + + this.type = 'MeshToonMaterial'; + + this.color = new Color( 0xffffff ); + + this.map = null; + this.gradientMap = null; + + this.lightMap = null; + this.lightMapIntensity = 1.0; + + this.aoMap = null; + this.aoMapIntensity = 1.0; + + this.emissive = new Color( 0x000000 ); + this.emissiveIntensity = 1.0; + this.emissiveMap = null; + + this.bumpMap = null; + this.bumpScale = 1; + + this.normalMap = null; + this.normalMapType = TangentSpaceNormalMap; + this.normalScale = new Vector2( 1, 1 ); + + this.displacementMap = null; + this.displacementScale = 1; + this.displacementBias = 0; + + this.alphaMap = null; + + this.wireframe = false; + this.wireframeLinewidth = 1; + this.wireframeLinecap = 'round'; + this.wireframeLinejoin = 'round'; + + this.fog = true; + + this.setValues( parameters ); + + } + + copy( source ) { + + super.copy( source ); + + this.color.copy( source.color ); + + this.map = source.map; + this.gradientMap = source.gradientMap; + + this.lightMap = source.lightMap; + this.lightMapIntensity = source.lightMapIntensity; + + this.aoMap = source.aoMap; + this.aoMapIntensity = source.aoMapIntensity; + + this.emissive.copy( source.emissive ); + this.emissiveMap = source.emissiveMap; + this.emissiveIntensity = source.emissiveIntensity; + + this.bumpMap = source.bumpMap; + this.bumpScale = source.bumpScale; + + this.normalMap = source.normalMap; + this.normalMapType = source.normalMapType; + this.normalScale.copy( source.normalScale ); + + this.displacementMap = source.displacementMap; + this.displacementScale = source.displacementScale; + this.displacementBias = source.displacementBias; + + this.alphaMap = source.alphaMap; + + this.wireframe = source.wireframe; + this.wireframeLinewidth = source.wireframeLinewidth; + this.wireframeLinecap = source.wireframeLinecap; + this.wireframeLinejoin = source.wireframeLinejoin; + + this.fog = source.fog; + + return this; + + } + +} + +class MeshNormalMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isMeshNormalMaterial = true; + + this.type = 'MeshNormalMaterial'; + + this.bumpMap = null; + this.bumpScale = 1; + + this.normalMap = null; + this.normalMapType = TangentSpaceNormalMap; + this.normalScale = new Vector2( 1, 1 ); + + this.displacementMap = null; + this.displacementScale = 1; + this.displacementBias = 0; + + this.wireframe = false; + this.wireframeLinewidth = 1; + + this.flatShading = false; + + this.setValues( parameters ); + + } + + copy( source ) { + + super.copy( source ); + + this.bumpMap = source.bumpMap; + this.bumpScale = source.bumpScale; + + this.normalMap = source.normalMap; + this.normalMapType = source.normalMapType; + this.normalScale.copy( source.normalScale ); + + this.displacementMap = source.displacementMap; + this.displacementScale = source.displacementScale; + this.displacementBias = source.displacementBias; + + this.wireframe = source.wireframe; + this.wireframeLinewidth = source.wireframeLinewidth; + + this.flatShading = source.flatShading; + + return this; + + } + +} + +class MeshLambertMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isMeshLambertMaterial = true; + + this.type = 'MeshLambertMaterial'; + + this.color = new Color( 0xffffff ); // diffuse + + this.map = null; + + this.lightMap = null; + this.lightMapIntensity = 1.0; + + this.aoMap = null; + this.aoMapIntensity = 1.0; + + this.emissive = new Color( 0x000000 ); + this.emissiveIntensity = 1.0; + this.emissiveMap = null; + + this.bumpMap = null; + this.bumpScale = 1; + + this.normalMap = null; + this.normalMapType = TangentSpaceNormalMap; + this.normalScale = new Vector2( 1, 1 ); + + this.displacementMap = null; + this.displacementScale = 1; + this.displacementBias = 0; + + this.specularMap = null; + + this.alphaMap = null; + + this.envMap = null; + this.envMapRotation = new Euler(); + this.combine = MultiplyOperation; + this.reflectivity = 1; + this.refractionRatio = 0.98; + + this.wireframe = false; + this.wireframeLinewidth = 1; + this.wireframeLinecap = 'round'; + this.wireframeLinejoin = 'round'; + + this.flatShading = false; + + this.fog = true; + + this.setValues( parameters ); + + } + + copy( source ) { + + super.copy( source ); + + this.color.copy( source.color ); + + this.map = source.map; + + this.lightMap = source.lightMap; + this.lightMapIntensity = source.lightMapIntensity; + + this.aoMap = source.aoMap; + this.aoMapIntensity = source.aoMapIntensity; + + this.emissive.copy( source.emissive ); + this.emissiveMap = source.emissiveMap; + this.emissiveIntensity = source.emissiveIntensity; + + this.bumpMap = source.bumpMap; + this.bumpScale = source.bumpScale; + + this.normalMap = source.normalMap; + this.normalMapType = source.normalMapType; + this.normalScale.copy( source.normalScale ); + + this.displacementMap = source.displacementMap; + this.displacementScale = source.displacementScale; + this.displacementBias = source.displacementBias; + + this.specularMap = source.specularMap; + + this.alphaMap = source.alphaMap; + + this.envMap = source.envMap; + this.envMapRotation.copy( source.envMapRotation ); + this.combine = source.combine; + this.reflectivity = source.reflectivity; + this.refractionRatio = source.refractionRatio; + + this.wireframe = source.wireframe; + this.wireframeLinewidth = source.wireframeLinewidth; + this.wireframeLinecap = source.wireframeLinecap; + this.wireframeLinejoin = source.wireframeLinejoin; + + this.flatShading = source.flatShading; + + this.fog = source.fog; + + return this; + + } + +} + +class MeshMatcapMaterial extends Material { + + constructor( parameters ) { + + super(); + + this.isMeshMatcapMaterial = true; + + this.defines = { 'MATCAP': '' }; + + this.type = 'MeshMatcapMaterial'; + + this.color = new Color( 0xffffff ); // diffuse + + this.matcap = null; + + this.map = null; + + this.bumpMap = null; + this.bumpScale = 1; + + this.normalMap = null; + this.normalMapType = TangentSpaceNormalMap; + this.normalScale = new Vector2( 1, 1 ); + + this.displacementMap = null; + this.displacementScale = 1; + this.displacementBias = 0; + + this.alphaMap = null; + + this.flatShading = false; + + this.fog = true; + + this.setValues( parameters ); + + } + + + copy( source ) { + + super.copy( source ); + + this.defines = { 'MATCAP': '' }; + + this.color.copy( source.color ); + + this.matcap = source.matcap; + + this.map = source.map; + + this.bumpMap = source.bumpMap; + this.bumpScale = source.bumpScale; + + this.normalMap = source.normalMap; + this.normalMapType = source.normalMapType; + this.normalScale.copy( source.normalScale ); + + this.displacementMap = source.displacementMap; + this.displacementScale = source.displacementScale; + this.displacementBias = source.displacementBias; + + this.alphaMap = source.alphaMap; + + this.flatShading = source.flatShading; + + this.fog = source.fog; + + return this; + + } + +} + +class LineDashedMaterial extends LineBasicMaterial { + + constructor( parameters ) { + + super(); + + this.isLineDashedMaterial = true; + + this.type = 'LineDashedMaterial'; + + this.scale = 1; + this.dashSize = 3; + this.gapSize = 1; + + this.setValues( parameters ); + + } + + copy( source ) { + + super.copy( source ); + + this.scale = source.scale; + this.dashSize = source.dashSize; + this.gapSize = source.gapSize; + + return this; + + } + +} + +// converts an array to a specific type +function convertArray( array, type, forceClone ) { + + if ( ! array || // let 'undefined' and 'null' pass + ! forceClone && array.constructor === type ) return array; + + if ( typeof type.BYTES_PER_ELEMENT === 'number' ) { + + return new type( array ); // create typed array + + } + + return Array.prototype.slice.call( array ); // create Array + +} + +function isTypedArray( object ) { + + return ArrayBuffer.isView( object ) && + ! ( object instanceof DataView ); + +} + +// returns an array by which times and values can be sorted +function getKeyframeOrder( times ) { + + function compareTime( i, j ) { + + return times[ i ] - times[ j ]; + + } + + const n = times.length; + const result = new Array( n ); + for ( let i = 0; i !== n; ++ i ) result[ i ] = i; + + result.sort( compareTime ); + + return result; + +} + +// uses the array previously returned by 'getKeyframeOrder' to sort data +function sortedArray( values, stride, order ) { + + const nValues = values.length; + const result = new values.constructor( nValues ); + + for ( let i = 0, dstOffset = 0; dstOffset !== nValues; ++ i ) { + + const srcOffset = order[ i ] * stride; + + for ( let j = 0; j !== stride; ++ j ) { + + result[ dstOffset ++ ] = values[ srcOffset + j ]; + + } + + } + + return result; + +} + +// function for parsing AOS keyframe formats +function flattenJSON( jsonKeys, times, values, valuePropertyName ) { + + let i = 1, key = jsonKeys[ 0 ]; + + while ( key !== undefined && key[ valuePropertyName ] === undefined ) { + + key = jsonKeys[ i ++ ]; + + } + + if ( key === undefined ) return; // no data + + let value = key[ valuePropertyName ]; + if ( value === undefined ) return; // no data + + if ( Array.isArray( value ) ) { + + do { + + value = key[ valuePropertyName ]; + + if ( value !== undefined ) { + + times.push( key.time ); + values.push.apply( values, value ); // push all elements + + } + + key = jsonKeys[ i ++ ]; + + } while ( key !== undefined ); + + } else if ( value.toArray !== undefined ) { + + // ...assume THREE.Math-ish + + do { + + value = key[ valuePropertyName ]; + + if ( value !== undefined ) { + + times.push( key.time ); + value.toArray( values, values.length ); + + } + + key = jsonKeys[ i ++ ]; + + } while ( key !== undefined ); + + } else { + + // otherwise push as-is + + do { + + value = key[ valuePropertyName ]; + + if ( value !== undefined ) { + + times.push( key.time ); + values.push( value ); + + } + + key = jsonKeys[ i ++ ]; + + } while ( key !== undefined ); + + } + +} + +function subclip( sourceClip, name, startFrame, endFrame, fps = 30 ) { + + const clip = sourceClip.clone(); + + clip.name = name; + + const tracks = []; + + for ( let i = 0; i < clip.tracks.length; ++ i ) { + + const track = clip.tracks[ i ]; + const valueSize = track.getValueSize(); + + const times = []; + const values = []; + + for ( let j = 0; j < track.times.length; ++ j ) { + + const frame = track.times[ j ] * fps; + + if ( frame < startFrame || frame >= endFrame ) continue; + + times.push( track.times[ j ] ); + + for ( let k = 0; k < valueSize; ++ k ) { + + values.push( track.values[ j * valueSize + k ] ); + + } + + } + + if ( times.length === 0 ) continue; + + track.times = convertArray( times, track.times.constructor ); + track.values = convertArray( values, track.values.constructor ); + + tracks.push( track ); + + } + + clip.tracks = tracks; + + // find minimum .times value across all tracks in the trimmed clip + + let minStartTime = Infinity; + + for ( let i = 0; i < clip.tracks.length; ++ i ) { + + if ( minStartTime > clip.tracks[ i ].times[ 0 ] ) { + + minStartTime = clip.tracks[ i ].times[ 0 ]; + + } + + } + + // shift all tracks such that clip begins at t=0 + + for ( let i = 0; i < clip.tracks.length; ++ i ) { + + clip.tracks[ i ].shift( - 1 * minStartTime ); + + } + + clip.resetDuration(); + + return clip; + +} + +function makeClipAdditive( targetClip, referenceFrame = 0, referenceClip = targetClip, fps = 30 ) { + + if ( fps <= 0 ) fps = 30; + + const numTracks = referenceClip.tracks.length; + const referenceTime = referenceFrame / fps; + + // Make each track's values relative to the values at the reference frame + for ( let i = 0; i < numTracks; ++ i ) { + + const referenceTrack = referenceClip.tracks[ i ]; + const referenceTrackType = referenceTrack.ValueTypeName; + + // Skip this track if it's non-numeric + if ( referenceTrackType === 'bool' || referenceTrackType === 'string' ) continue; + + // Find the track in the target clip whose name and type matches the reference track + const targetTrack = targetClip.tracks.find( function ( track ) { + + return track.name === referenceTrack.name + && track.ValueTypeName === referenceTrackType; + + } ); + + if ( targetTrack === undefined ) continue; + + let referenceOffset = 0; + const referenceValueSize = referenceTrack.getValueSize(); + + if ( referenceTrack.createInterpolant.isInterpolantFactoryMethodGLTFCubicSpline ) { + + referenceOffset = referenceValueSize / 3; + + } + + let targetOffset = 0; + const targetValueSize = targetTrack.getValueSize(); + + if ( targetTrack.createInterpolant.isInterpolantFactoryMethodGLTFCubicSpline ) { + + targetOffset = targetValueSize / 3; + + } + + const lastIndex = referenceTrack.times.length - 1; + let referenceValue; + + // Find the value to subtract out of the track + if ( referenceTime <= referenceTrack.times[ 0 ] ) { + + // Reference frame is earlier than the first keyframe, so just use the first keyframe + const startIndex = referenceOffset; + const endIndex = referenceValueSize - referenceOffset; + referenceValue = referenceTrack.values.slice( startIndex, endIndex ); + + } else if ( referenceTime >= referenceTrack.times[ lastIndex ] ) { + + // Reference frame is after the last keyframe, so just use the last keyframe + const startIndex = lastIndex * referenceValueSize + referenceOffset; + const endIndex = startIndex + referenceValueSize - referenceOffset; + referenceValue = referenceTrack.values.slice( startIndex, endIndex ); + + } else { + + // Interpolate to the reference value + const interpolant = referenceTrack.createInterpolant(); + const startIndex = referenceOffset; + const endIndex = referenceValueSize - referenceOffset; + interpolant.evaluate( referenceTime ); + referenceValue = interpolant.resultBuffer.slice( startIndex, endIndex ); + + } + + // Conjugate the quaternion + if ( referenceTrackType === 'quaternion' ) { + + const referenceQuat = new Quaternion().fromArray( referenceValue ).normalize().conjugate(); + referenceQuat.toArray( referenceValue ); + + } + + // Subtract the reference value from all of the track values + + const numTimes = targetTrack.times.length; + for ( let j = 0; j < numTimes; ++ j ) { + + const valueStart = j * targetValueSize + targetOffset; + + if ( referenceTrackType === 'quaternion' ) { + + // Multiply the conjugate for quaternion track types + Quaternion.multiplyQuaternionsFlat( + targetTrack.values, + valueStart, + referenceValue, + 0, + targetTrack.values, + valueStart + ); + + } else { + + const valueEnd = targetValueSize - targetOffset * 2; + + // Subtract each value for all other numeric track types + for ( let k = 0; k < valueEnd; ++ k ) { + + targetTrack.values[ valueStart + k ] -= referenceValue[ k ]; + + } + + } + + } + + } + + targetClip.blendMode = AdditiveAnimationBlendMode; + + return targetClip; + +} + +const AnimationUtils = { + convertArray: convertArray, + isTypedArray: isTypedArray, + getKeyframeOrder: getKeyframeOrder, + sortedArray: sortedArray, + flattenJSON: flattenJSON, + subclip: subclip, + makeClipAdditive: makeClipAdditive +}; + +/** + * Abstract base class of interpolants over parametric samples. + * + * The parameter domain is one dimensional, typically the time or a path + * along a curve defined by the data. + * + * The sample values can have any dimensionality and derived classes may + * apply special interpretations to the data. + * + * This class provides the interval seek in a Template Method, deferring + * the actual interpolation to derived classes. + * + * Time complexity is O(1) for linear access crossing at most two points + * and O(log N) for random access, where N is the number of positions. + * + * References: + * + * http://www.oodesign.com/template-method-pattern.html + * + */ + +class Interpolant { + + constructor( parameterPositions, sampleValues, sampleSize, resultBuffer ) { + + this.parameterPositions = parameterPositions; + this._cachedIndex = 0; + + this.resultBuffer = resultBuffer !== undefined ? + resultBuffer : new sampleValues.constructor( sampleSize ); + this.sampleValues = sampleValues; + this.valueSize = sampleSize; + + this.settings = null; + this.DefaultSettings_ = {}; + + } + + evaluate( t ) { + + const pp = this.parameterPositions; + let i1 = this._cachedIndex, + t1 = pp[ i1 ], + t0 = pp[ i1 - 1 ]; + + validate_interval: { + + seek: { + + let right; + + linear_scan: { + + //- See http://jsperf.com/comparison-to-undefined/3 + //- slower code: + //- + //- if ( t >= t1 || t1 === undefined ) { + forward_scan: if ( ! ( t < t1 ) ) { + + for ( let giveUpAt = i1 + 2; ; ) { + + if ( t1 === undefined ) { + + if ( t < t0 ) break forward_scan; + + // after end + + i1 = pp.length; + this._cachedIndex = i1; + return this.copySampleValue_( i1 - 1 ); + + } + + if ( i1 === giveUpAt ) break; // this loop + + t0 = t1; + t1 = pp[ ++ i1 ]; + + if ( t < t1 ) { + + // we have arrived at the sought interval + break seek; + + } + + } + + // prepare binary search on the right side of the index + right = pp.length; + break linear_scan; + + } + + //- slower code: + //- if ( t < t0 || t0 === undefined ) { + if ( ! ( t >= t0 ) ) { + + // looping? + + const t1global = pp[ 1 ]; + + if ( t < t1global ) { + + i1 = 2; // + 1, using the scan for the details + t0 = t1global; + + } + + // linear reverse scan + + for ( let giveUpAt = i1 - 2; ; ) { + + if ( t0 === undefined ) { + + // before start + + this._cachedIndex = 0; + return this.copySampleValue_( 0 ); + + } + + if ( i1 === giveUpAt ) break; // this loop + + t1 = t0; + t0 = pp[ -- i1 - 1 ]; + + if ( t >= t0 ) { + + // we have arrived at the sought interval + break seek; + + } + + } + + // prepare binary search on the left side of the index + right = i1; + i1 = 0; + break linear_scan; + + } + + // the interval is valid + + break validate_interval; + + } // linear scan + + // binary search + + while ( i1 < right ) { + + const mid = ( i1 + right ) >>> 1; + + if ( t < pp[ mid ] ) { + + right = mid; + + } else { + + i1 = mid + 1; + + } + + } + + t1 = pp[ i1 ]; + t0 = pp[ i1 - 1 ]; + + // check boundary cases, again + + if ( t0 === undefined ) { + + this._cachedIndex = 0; + return this.copySampleValue_( 0 ); + + } + + if ( t1 === undefined ) { + + i1 = pp.length; + this._cachedIndex = i1; + return this.copySampleValue_( i1 - 1 ); + + } + + } // seek + + this._cachedIndex = i1; + + this.intervalChanged_( i1, t0, t1 ); + + } // validate_interval + + return this.interpolate_( i1, t0, t, t1 ); + + } + + getSettings_() { + + return this.settings || this.DefaultSettings_; + + } + + copySampleValue_( index ) { + + // copies a sample value to the result buffer + + const result = this.resultBuffer, + values = this.sampleValues, + stride = this.valueSize, + offset = index * stride; + + for ( let i = 0; i !== stride; ++ i ) { + + result[ i ] = values[ offset + i ]; + + } + + return result; + + } + + // Template methods for derived classes: + + interpolate_( /* i1, t0, t, t1 */ ) { + + throw new Error( 'call to abstract method' ); + // implementations shall return this.resultBuffer + + } + + intervalChanged_( /* i1, t0, t1 */ ) { + + // empty + + } + +} + +/** + * Fast and simple cubic spline interpolant. + * + * It was derived from a Hermitian construction setting the first derivative + * at each sample position to the linear slope between neighboring positions + * over their parameter interval. + */ + +class CubicInterpolant extends Interpolant { + + constructor( parameterPositions, sampleValues, sampleSize, resultBuffer ) { + + super( parameterPositions, sampleValues, sampleSize, resultBuffer ); + + this._weightPrev = - 0; + this._offsetPrev = - 0; + this._weightNext = - 0; + this._offsetNext = - 0; + + this.DefaultSettings_ = { + + endingStart: ZeroCurvatureEnding, + endingEnd: ZeroCurvatureEnding + + }; + + } + + intervalChanged_( i1, t0, t1 ) { + + const pp = this.parameterPositions; + let iPrev = i1 - 2, + iNext = i1 + 1, + + tPrev = pp[ iPrev ], + tNext = pp[ iNext ]; + + if ( tPrev === undefined ) { + + switch ( this.getSettings_().endingStart ) { + + case ZeroSlopeEnding: + + // f'(t0) = 0 + iPrev = i1; + tPrev = 2 * t0 - t1; + + break; + + case WrapAroundEnding: + + // use the other end of the curve + iPrev = pp.length - 2; + tPrev = t0 + pp[ iPrev ] - pp[ iPrev + 1 ]; + + break; + + default: // ZeroCurvatureEnding + + // f''(t0) = 0 a.k.a. Natural Spline + iPrev = i1; + tPrev = t1; + + } + + } + + if ( tNext === undefined ) { + + switch ( this.getSettings_().endingEnd ) { + + case ZeroSlopeEnding: + + // f'(tN) = 0 + iNext = i1; + tNext = 2 * t1 - t0; + + break; + + case WrapAroundEnding: + + // use the other end of the curve + iNext = 1; + tNext = t1 + pp[ 1 ] - pp[ 0 ]; + + break; + + default: // ZeroCurvatureEnding + + // f''(tN) = 0, a.k.a. Natural Spline + iNext = i1 - 1; + tNext = t0; + + } + + } + + const halfDt = ( t1 - t0 ) * 0.5, + stride = this.valueSize; + + this._weightPrev = halfDt / ( t0 - tPrev ); + this._weightNext = halfDt / ( tNext - t1 ); + this._offsetPrev = iPrev * stride; + this._offsetNext = iNext * stride; + + } + + interpolate_( i1, t0, t, t1 ) { + + const result = this.resultBuffer, + values = this.sampleValues, + stride = this.valueSize, + + o1 = i1 * stride, o0 = o1 - stride, + oP = this._offsetPrev, oN = this._offsetNext, + wP = this._weightPrev, wN = this._weightNext, + + p = ( t - t0 ) / ( t1 - t0 ), + pp = p * p, + ppp = pp * p; + + // evaluate polynomials + + const sP = - wP * ppp + 2 * wP * pp - wP * p; + const s0 = ( 1 + wP ) * ppp + ( - 1.5 - 2 * wP ) * pp + ( - 0.5 + wP ) * p + 1; + const s1 = ( - 1 - wN ) * ppp + ( 1.5 + wN ) * pp + 0.5 * p; + const sN = wN * ppp - wN * pp; + + // combine data linearly + + for ( let i = 0; i !== stride; ++ i ) { + + result[ i ] = + sP * values[ oP + i ] + + s0 * values[ o0 + i ] + + s1 * values[ o1 + i ] + + sN * values[ oN + i ]; + + } + + return result; + + } + +} + +class LinearInterpolant extends Interpolant { + + constructor( parameterPositions, sampleValues, sampleSize, resultBuffer ) { + + super( parameterPositions, sampleValues, sampleSize, resultBuffer ); + + } + + interpolate_( i1, t0, t, t1 ) { + + const result = this.resultBuffer, + values = this.sampleValues, + stride = this.valueSize, + + offset1 = i1 * stride, + offset0 = offset1 - stride, + + weight1 = ( t - t0 ) / ( t1 - t0 ), + weight0 = 1 - weight1; + + for ( let i = 0; i !== stride; ++ i ) { + + result[ i ] = + values[ offset0 + i ] * weight0 + + values[ offset1 + i ] * weight1; + + } + + return result; + + } + +} + +/** + * + * Interpolant that evaluates to the sample value at the position preceding + * the parameter. + */ + +class DiscreteInterpolant extends Interpolant { + + constructor( parameterPositions, sampleValues, sampleSize, resultBuffer ) { + + super( parameterPositions, sampleValues, sampleSize, resultBuffer ); + + } + + interpolate_( i1 /*, t0, t, t1 */ ) { + + return this.copySampleValue_( i1 - 1 ); + + } + +} + +class KeyframeTrack { + + constructor( name, times, values, interpolation ) { + + if ( name === undefined ) throw new Error( 'THREE.KeyframeTrack: track name is undefined' ); + if ( times === undefined || times.length === 0 ) throw new Error( 'THREE.KeyframeTrack: no keyframes in track named ' + name ); + + this.name = name; + + this.times = convertArray( times, this.TimeBufferType ); + this.values = convertArray( values, this.ValueBufferType ); + + this.setInterpolation( interpolation || this.DefaultInterpolation ); + + } + + // Serialization (in static context, because of constructor invocation + // and automatic invocation of .toJSON): + + static toJSON( track ) { + + const trackType = track.constructor; + + let json; + + // derived classes can define a static toJSON method + if ( trackType.toJSON !== this.toJSON ) { + + json = trackType.toJSON( track ); + + } else { + + // by default, we assume the data can be serialized as-is + json = { + + 'name': track.name, + 'times': convertArray( track.times, Array ), + 'values': convertArray( track.values, Array ) + + }; + + const interpolation = track.getInterpolation(); + + if ( interpolation !== track.DefaultInterpolation ) { + + json.interpolation = interpolation; + + } + + } + + json.type = track.ValueTypeName; // mandatory + + return json; + + } + + InterpolantFactoryMethodDiscrete( result ) { + + return new DiscreteInterpolant( this.times, this.values, this.getValueSize(), result ); + + } + + InterpolantFactoryMethodLinear( result ) { + + return new LinearInterpolant( this.times, this.values, this.getValueSize(), result ); + + } + + InterpolantFactoryMethodSmooth( result ) { + + return new CubicInterpolant( this.times, this.values, this.getValueSize(), result ); + + } + + setInterpolation( interpolation ) { + + let factoryMethod; + + switch ( interpolation ) { + + case InterpolateDiscrete: + + factoryMethod = this.InterpolantFactoryMethodDiscrete; + + break; + + case InterpolateLinear: + + factoryMethod = this.InterpolantFactoryMethodLinear; + + break; + + case InterpolateSmooth: + + factoryMethod = this.InterpolantFactoryMethodSmooth; + + break; + + } + + if ( factoryMethod === undefined ) { + + const message = 'unsupported interpolation for ' + + this.ValueTypeName + ' keyframe track named ' + this.name; + + if ( this.createInterpolant === undefined ) { + + // fall back to default, unless the default itself is messed up + if ( interpolation !== this.DefaultInterpolation ) { + + this.setInterpolation( this.DefaultInterpolation ); + + } else { + + throw new Error( message ); // fatal, in this case + + } + + } + + console.warn( 'THREE.KeyframeTrack:', message ); + return this; + + } + + this.createInterpolant = factoryMethod; + + return this; + + } + + getInterpolation() { + + switch ( this.createInterpolant ) { + + case this.InterpolantFactoryMethodDiscrete: + + return InterpolateDiscrete; + + case this.InterpolantFactoryMethodLinear: + + return InterpolateLinear; + + case this.InterpolantFactoryMethodSmooth: + + return InterpolateSmooth; + + } + + } + + getValueSize() { + + return this.values.length / this.times.length; + + } + + // move all keyframes either forwards or backwards in time + shift( timeOffset ) { + + if ( timeOffset !== 0.0 ) { + + const times = this.times; + + for ( let i = 0, n = times.length; i !== n; ++ i ) { + + times[ i ] += timeOffset; + + } + + } + + return this; + + } + + // scale all keyframe times by a factor (useful for frame <-> seconds conversions) + scale( timeScale ) { + + if ( timeScale !== 1.0 ) { + + const times = this.times; + + for ( let i = 0, n = times.length; i !== n; ++ i ) { + + times[ i ] *= timeScale; + + } + + } + + return this; + + } + + // removes keyframes before and after animation without changing any values within the range [startTime, endTime]. + // IMPORTANT: We do not shift around keys to the start of the track time, because for interpolated keys this will change their values + trim( startTime, endTime ) { + + const times = this.times, + nKeys = times.length; + + let from = 0, + to = nKeys - 1; + + while ( from !== nKeys && times[ from ] < startTime ) { + + ++ from; + + } + + while ( to !== - 1 && times[ to ] > endTime ) { + + -- to; + + } + + ++ to; // inclusive -> exclusive bound + + if ( from !== 0 || to !== nKeys ) { + + // empty tracks are forbidden, so keep at least one keyframe + if ( from >= to ) { + + to = Math.max( to, 1 ); + from = to - 1; + + } + + const stride = this.getValueSize(); + this.times = times.slice( from, to ); + this.values = this.values.slice( from * stride, to * stride ); + + } + + return this; + + } + + // ensure we do not get a GarbageInGarbageOut situation, make sure tracks are at least minimally viable + validate() { + + let valid = true; + + const valueSize = this.getValueSize(); + if ( valueSize - Math.floor( valueSize ) !== 0 ) { + + console.error( 'THREE.KeyframeTrack: Invalid value size in track.', this ); + valid = false; + + } + + const times = this.times, + values = this.values, + + nKeys = times.length; + + if ( nKeys === 0 ) { + + console.error( 'THREE.KeyframeTrack: Track is empty.', this ); + valid = false; + + } + + let prevTime = null; + + for ( let i = 0; i !== nKeys; i ++ ) { + + const currTime = times[ i ]; + + if ( typeof currTime === 'number' && isNaN( currTime ) ) { + + console.error( 'THREE.KeyframeTrack: Time is not a valid number.', this, i, currTime ); + valid = false; + break; + + } + + if ( prevTime !== null && prevTime > currTime ) { + + console.error( 'THREE.KeyframeTrack: Out of order keys.', this, i, currTime, prevTime ); + valid = false; + break; + + } + + prevTime = currTime; + + } + + if ( values !== undefined ) { + + if ( isTypedArray( values ) ) { + + for ( let i = 0, n = values.length; i !== n; ++ i ) { + + const value = values[ i ]; + + if ( isNaN( value ) ) { + + console.error( 'THREE.KeyframeTrack: Value is not a valid number.', this, i, value ); + valid = false; + break; + + } + + } + + } + + } + + return valid; + + } + + // removes equivalent sequential keys as common in morph target sequences + // (0,0,0,0,1,1,1,0,0,0,0,0,0,0) --> (0,0,1,1,0,0) + optimize() { + + // times or values may be shared with other tracks, so overwriting is unsafe + const times = this.times.slice(), + values = this.values.slice(), + stride = this.getValueSize(), + + smoothInterpolation = this.getInterpolation() === InterpolateSmooth, + + lastIndex = times.length - 1; + + let writeIndex = 1; + + for ( let i = 1; i < lastIndex; ++ i ) { + + let keep = false; + + const time = times[ i ]; + const timeNext = times[ i + 1 ]; + + // remove adjacent keyframes scheduled at the same time + + if ( time !== timeNext && ( i !== 1 || time !== times[ 0 ] ) ) { + + if ( ! smoothInterpolation ) { + + // remove unnecessary keyframes same as their neighbors + + const offset = i * stride, + offsetP = offset - stride, + offsetN = offset + stride; + + for ( let j = 0; j !== stride; ++ j ) { + + const value = values[ offset + j ]; + + if ( value !== values[ offsetP + j ] || + value !== values[ offsetN + j ] ) { + + keep = true; + break; + + } + + } + + } else { + + keep = true; + + } + + } + + // in-place compaction + + if ( keep ) { + + if ( i !== writeIndex ) { + + times[ writeIndex ] = times[ i ]; + + const readOffset = i * stride, + writeOffset = writeIndex * stride; + + for ( let j = 0; j !== stride; ++ j ) { + + values[ writeOffset + j ] = values[ readOffset + j ]; + + } + + } + + ++ writeIndex; + + } + + } + + // flush last keyframe (compaction looks ahead) + + if ( lastIndex > 0 ) { + + times[ writeIndex ] = times[ lastIndex ]; + + for ( let readOffset = lastIndex * stride, writeOffset = writeIndex * stride, j = 0; j !== stride; ++ j ) { + + values[ writeOffset + j ] = values[ readOffset + j ]; + + } + + ++ writeIndex; + + } + + if ( writeIndex !== times.length ) { + + this.times = times.slice( 0, writeIndex ); + this.values = values.slice( 0, writeIndex * stride ); + + } else { + + this.times = times; + this.values = values; + + } + + return this; + + } + + clone() { + + const times = this.times.slice(); + const values = this.values.slice(); + + const TypedKeyframeTrack = this.constructor; + const track = new TypedKeyframeTrack( this.name, times, values ); + + // Interpolant argument to constructor is not saved, so copy the factory method directly. + track.createInterpolant = this.createInterpolant; + + return track; + + } + +} + +KeyframeTrack.prototype.TimeBufferType = Float32Array; +KeyframeTrack.prototype.ValueBufferType = Float32Array; +KeyframeTrack.prototype.DefaultInterpolation = InterpolateLinear; + +/** + * A Track of Boolean keyframe values. + */ +class BooleanKeyframeTrack extends KeyframeTrack { + + // No interpolation parameter because only InterpolateDiscrete is valid. + constructor( name, times, values ) { + + super( name, times, values ); + + } + +} + +BooleanKeyframeTrack.prototype.ValueTypeName = 'bool'; +BooleanKeyframeTrack.prototype.ValueBufferType = Array; +BooleanKeyframeTrack.prototype.DefaultInterpolation = InterpolateDiscrete; +BooleanKeyframeTrack.prototype.InterpolantFactoryMethodLinear = undefined; +BooleanKeyframeTrack.prototype.InterpolantFactoryMethodSmooth = undefined; + +/** + * A Track of keyframe values that represent color. + */ +class ColorKeyframeTrack extends KeyframeTrack {} + +ColorKeyframeTrack.prototype.ValueTypeName = 'color'; + +/** + * A Track of numeric keyframe values. + */ +class NumberKeyframeTrack extends KeyframeTrack {} + +NumberKeyframeTrack.prototype.ValueTypeName = 'number'; + +/** + * Spherical linear unit quaternion interpolant. + */ + +class QuaternionLinearInterpolant extends Interpolant { + + constructor( parameterPositions, sampleValues, sampleSize, resultBuffer ) { + + super( parameterPositions, sampleValues, sampleSize, resultBuffer ); + + } + + interpolate_( i1, t0, t, t1 ) { + + const result = this.resultBuffer, + values = this.sampleValues, + stride = this.valueSize, + + alpha = ( t - t0 ) / ( t1 - t0 ); + + let offset = i1 * stride; + + for ( let end = offset + stride; offset !== end; offset += 4 ) { + + Quaternion.slerpFlat( result, 0, values, offset - stride, values, offset, alpha ); + + } + + return result; + + } + +} + +/** + * A Track of quaternion keyframe values. + */ +class QuaternionKeyframeTrack extends KeyframeTrack { + + InterpolantFactoryMethodLinear( result ) { + + return new QuaternionLinearInterpolant( this.times, this.values, this.getValueSize(), result ); + + } + +} + +QuaternionKeyframeTrack.prototype.ValueTypeName = 'quaternion'; +// ValueBufferType is inherited +// DefaultInterpolation is inherited; +QuaternionKeyframeTrack.prototype.InterpolantFactoryMethodSmooth = undefined; + +/** + * A Track that interpolates Strings + */ +class StringKeyframeTrack extends KeyframeTrack { + + // No interpolation parameter because only InterpolateDiscrete is valid. + constructor( name, times, values ) { + + super( name, times, values ); + + } + +} + +StringKeyframeTrack.prototype.ValueTypeName = 'string'; +StringKeyframeTrack.prototype.ValueBufferType = Array; +StringKeyframeTrack.prototype.DefaultInterpolation = InterpolateDiscrete; +StringKeyframeTrack.prototype.InterpolantFactoryMethodLinear = undefined; +StringKeyframeTrack.prototype.InterpolantFactoryMethodSmooth = undefined; + +/** + * A Track of vectored keyframe values. + */ +class VectorKeyframeTrack extends KeyframeTrack {} + +VectorKeyframeTrack.prototype.ValueTypeName = 'vector'; + +class AnimationClip { + + constructor( name = '', duration = - 1, tracks = [], blendMode = NormalAnimationBlendMode ) { + + this.name = name; + this.tracks = tracks; + this.duration = duration; + this.blendMode = blendMode; + + this.uuid = generateUUID(); + + // this means it should figure out its duration by scanning the tracks + if ( this.duration < 0 ) { + + this.resetDuration(); + + } + + } + + + static parse( json ) { + + const tracks = [], + jsonTracks = json.tracks, + frameTime = 1.0 / ( json.fps || 1.0 ); + + for ( let i = 0, n = jsonTracks.length; i !== n; ++ i ) { + + tracks.push( parseKeyframeTrack( jsonTracks[ i ] ).scale( frameTime ) ); + + } + + const clip = new this( json.name, json.duration, tracks, json.blendMode ); + clip.uuid = json.uuid; + + return clip; + + } + + static toJSON( clip ) { + + const tracks = [], + clipTracks = clip.tracks; + + const json = { + + 'name': clip.name, + 'duration': clip.duration, + 'tracks': tracks, + 'uuid': clip.uuid, + 'blendMode': clip.blendMode + + }; + + for ( let i = 0, n = clipTracks.length; i !== n; ++ i ) { + + tracks.push( KeyframeTrack.toJSON( clipTracks[ i ] ) ); + + } + + return json; + + } + + static CreateFromMorphTargetSequence( name, morphTargetSequence, fps, noLoop ) { + + const numMorphTargets = morphTargetSequence.length; + const tracks = []; + + for ( let i = 0; i < numMorphTargets; i ++ ) { + + let times = []; + let values = []; + + times.push( + ( i + numMorphTargets - 1 ) % numMorphTargets, + i, + ( i + 1 ) % numMorphTargets ); + + values.push( 0, 1, 0 ); + + const order = getKeyframeOrder( times ); + times = sortedArray( times, 1, order ); + values = sortedArray( values, 1, order ); + + // if there is a key at the first frame, duplicate it as the + // last frame as well for perfect loop. + if ( ! noLoop && times[ 0 ] === 0 ) { + + times.push( numMorphTargets ); + values.push( values[ 0 ] ); + + } + + tracks.push( + new NumberKeyframeTrack( + '.morphTargetInfluences[' + morphTargetSequence[ i ].name + ']', + times, values + ).scale( 1.0 / fps ) ); + + } + + return new this( name, - 1, tracks ); + + } + + static findByName( objectOrClipArray, name ) { + + let clipArray = objectOrClipArray; + + if ( ! Array.isArray( objectOrClipArray ) ) { + + const o = objectOrClipArray; + clipArray = o.geometry && o.geometry.animations || o.animations; + + } + + for ( let i = 0; i < clipArray.length; i ++ ) { + + if ( clipArray[ i ].name === name ) { + + return clipArray[ i ]; + + } + + } + + return null; + + } + + static CreateClipsFromMorphTargetSequences( morphTargets, fps, noLoop ) { + + const animationToMorphTargets = {}; + + // tested with https://regex101.com/ on trick sequences + // such flamingo_flyA_003, flamingo_run1_003, crdeath0059 + const pattern = /^([\w-]*?)([\d]+)$/; + + // sort morph target names into animation groups based + // patterns like Walk_001, Walk_002, Run_001, Run_002 + for ( let i = 0, il = morphTargets.length; i < il; i ++ ) { + + const morphTarget = morphTargets[ i ]; + const parts = morphTarget.name.match( pattern ); + + if ( parts && parts.length > 1 ) { + + const name = parts[ 1 ]; + + let animationMorphTargets = animationToMorphTargets[ name ]; + + if ( ! animationMorphTargets ) { + + animationToMorphTargets[ name ] = animationMorphTargets = []; + + } + + animationMorphTargets.push( morphTarget ); + + } + + } + + const clips = []; + + for ( const name in animationToMorphTargets ) { + + clips.push( this.CreateFromMorphTargetSequence( name, animationToMorphTargets[ name ], fps, noLoop ) ); + + } + + return clips; + + } + + // parse the animation.hierarchy format + static parseAnimation( animation, bones ) { + + if ( ! animation ) { + + console.error( 'THREE.AnimationClip: No animation in JSONLoader data.' ); + return null; + + } + + const addNonemptyTrack = function ( trackType, trackName, animationKeys, propertyName, destTracks ) { + + // only return track if there are actually keys. + if ( animationKeys.length !== 0 ) { + + const times = []; + const values = []; + + flattenJSON( animationKeys, times, values, propertyName ); + + // empty keys are filtered out, so check again + if ( times.length !== 0 ) { + + destTracks.push( new trackType( trackName, times, values ) ); + + } + + } + + }; + + const tracks = []; + + const clipName = animation.name || 'default'; + const fps = animation.fps || 30; + const blendMode = animation.blendMode; + + // automatic length determination in AnimationClip. + let duration = animation.length || - 1; + + const hierarchyTracks = animation.hierarchy || []; + + for ( let h = 0; h < hierarchyTracks.length; h ++ ) { + + const animationKeys = hierarchyTracks[ h ].keys; + + // skip empty tracks + if ( ! animationKeys || animationKeys.length === 0 ) continue; + + // process morph targets + if ( animationKeys[ 0 ].morphTargets ) { + + // figure out all morph targets used in this track + const morphTargetNames = {}; + + let k; + + for ( k = 0; k < animationKeys.length; k ++ ) { + + if ( animationKeys[ k ].morphTargets ) { + + for ( let m = 0; m < animationKeys[ k ].morphTargets.length; m ++ ) { + + morphTargetNames[ animationKeys[ k ].morphTargets[ m ] ] = - 1; + + } + + } + + } + + // create a track for each morph target with all zero + // morphTargetInfluences except for the keys in which + // the morphTarget is named. + for ( const morphTargetName in morphTargetNames ) { + + const times = []; + const values = []; + + for ( let m = 0; m !== animationKeys[ k ].morphTargets.length; ++ m ) { + + const animationKey = animationKeys[ k ]; + + times.push( animationKey.time ); + values.push( ( animationKey.morphTarget === morphTargetName ) ? 1 : 0 ); + + } + + tracks.push( new NumberKeyframeTrack( '.morphTargetInfluence[' + morphTargetName + ']', times, values ) ); + + } + + duration = morphTargetNames.length * fps; + + } else { + + // ...assume skeletal animation + + const boneName = '.bones[' + bones[ h ].name + ']'; + + addNonemptyTrack( + VectorKeyframeTrack, boneName + '.position', + animationKeys, 'pos', tracks ); + + addNonemptyTrack( + QuaternionKeyframeTrack, boneName + '.quaternion', + animationKeys, 'rot', tracks ); + + addNonemptyTrack( + VectorKeyframeTrack, boneName + '.scale', + animationKeys, 'scl', tracks ); + + } + + } + + if ( tracks.length === 0 ) { + + return null; + + } + + const clip = new this( clipName, duration, tracks, blendMode ); + + return clip; + + } + + resetDuration() { + + const tracks = this.tracks; + let duration = 0; + + for ( let i = 0, n = tracks.length; i !== n; ++ i ) { + + const track = this.tracks[ i ]; + + duration = Math.max( duration, track.times[ track.times.length - 1 ] ); + + } + + this.duration = duration; + + return this; + + } + + trim() { + + for ( let i = 0; i < this.tracks.length; i ++ ) { + + this.tracks[ i ].trim( 0, this.duration ); + + } + + return this; + + } + + validate() { + + let valid = true; + + for ( let i = 0; i < this.tracks.length; i ++ ) { + + valid = valid && this.tracks[ i ].validate(); + + } + + return valid; + + } + + optimize() { + + for ( let i = 0; i < this.tracks.length; i ++ ) { + + this.tracks[ i ].optimize(); + + } + + return this; + + } + + clone() { + + const tracks = []; + + for ( let i = 0; i < this.tracks.length; i ++ ) { + + tracks.push( this.tracks[ i ].clone() ); + + } + + return new this.constructor( this.name, this.duration, tracks, this.blendMode ); + + } + + toJSON() { + + return this.constructor.toJSON( this ); + + } + +} + +function getTrackTypeForValueTypeName( typeName ) { + + switch ( typeName.toLowerCase() ) { + + case 'scalar': + case 'double': + case 'float': + case 'number': + case 'integer': + + return NumberKeyframeTrack; + + case 'vector': + case 'vector2': + case 'vector3': + case 'vector4': + + return VectorKeyframeTrack; + + case 'color': + + return ColorKeyframeTrack; + + case 'quaternion': + + return QuaternionKeyframeTrack; + + case 'bool': + case 'boolean': + + return BooleanKeyframeTrack; + + case 'string': + + return StringKeyframeTrack; + + } + + throw new Error( 'THREE.KeyframeTrack: Unsupported typeName: ' + typeName ); + +} + +function parseKeyframeTrack( json ) { + + if ( json.type === undefined ) { + + throw new Error( 'THREE.KeyframeTrack: track type undefined, can not parse' ); + + } + + const trackType = getTrackTypeForValueTypeName( json.type ); + + if ( json.times === undefined ) { + + const times = [], values = []; + + flattenJSON( json.keys, times, values, 'value' ); + + json.times = times; + json.values = values; + + } + + // derived classes can define a static parse method + if ( trackType.parse !== undefined ) { + + return trackType.parse( json ); + + } else { + + // by default, we assume a constructor compatible with the base + return new trackType( json.name, json.times, json.values, json.interpolation ); + + } + +} + +const Cache = { + + enabled: false, + + files: {}, + + add: function ( key, file ) { + + if ( this.enabled === false ) return; + + // console.log( 'THREE.Cache', 'Adding key:', key ); + + this.files[ key ] = file; + + }, + + get: function ( key ) { + + if ( this.enabled === false ) return; + + // console.log( 'THREE.Cache', 'Checking key:', key ); + + return this.files[ key ]; + + }, + + remove: function ( key ) { + + delete this.files[ key ]; + + }, + + clear: function () { + + this.files = {}; + + } + +}; + +class LoadingManager { + + constructor( onLoad, onProgress, onError ) { + + const scope = this; + + let isLoading = false; + let itemsLoaded = 0; + let itemsTotal = 0; + let urlModifier = undefined; + const handlers = []; + + // Refer to #5689 for the reason why we don't set .onStart + // in the constructor + + this.onStart = undefined; + this.onLoad = onLoad; + this.onProgress = onProgress; + this.onError = onError; + + this.itemStart = function ( url ) { + + itemsTotal ++; + + if ( isLoading === false ) { + + if ( scope.onStart !== undefined ) { + + scope.onStart( url, itemsLoaded, itemsTotal ); + + } + + } + + isLoading = true; + + }; + + this.itemEnd = function ( url ) { + + itemsLoaded ++; + + if ( scope.onProgress !== undefined ) { + + scope.onProgress( url, itemsLoaded, itemsTotal ); + + } + + if ( itemsLoaded === itemsTotal ) { + + isLoading = false; + + if ( scope.onLoad !== undefined ) { + + scope.onLoad(); + + } + + } + + }; + + this.itemError = function ( url ) { + + if ( scope.onError !== undefined ) { + + scope.onError( url ); + + } + + }; + + this.resolveURL = function ( url ) { + + if ( urlModifier ) { + + return urlModifier( url ); + + } + + return url; + + }; + + this.setURLModifier = function ( transform ) { + + urlModifier = transform; + + return this; + + }; + + this.addHandler = function ( regex, loader ) { + + handlers.push( regex, loader ); + + return this; + + }; + + this.removeHandler = function ( regex ) { + + const index = handlers.indexOf( regex ); + + if ( index !== - 1 ) { + + handlers.splice( index, 2 ); + + } + + return this; + + }; + + this.getHandler = function ( file ) { + + for ( let i = 0, l = handlers.length; i < l; i += 2 ) { + + const regex = handlers[ i ]; + const loader = handlers[ i + 1 ]; + + if ( regex.global ) regex.lastIndex = 0; // see #17920 + + if ( regex.test( file ) ) { + + return loader; + + } + + } + + return null; + + }; + + } + +} + +const DefaultLoadingManager = /*@__PURE__*/ new LoadingManager(); + +class Loader { + + constructor( manager ) { + + this.manager = ( manager !== undefined ) ? manager : DefaultLoadingManager; + + this.crossOrigin = 'anonymous'; + this.withCredentials = false; + this.path = ''; + this.resourcePath = ''; + this.requestHeader = {}; + + } + + load( /* url, onLoad, onProgress, onError */ ) {} + + loadAsync( url, onProgress ) { + + const scope = this; + + return new Promise( function ( resolve, reject ) { + + scope.load( url, resolve, onProgress, reject ); + + } ); + + } + + parse( /* data */ ) {} + + setCrossOrigin( crossOrigin ) { + + this.crossOrigin = crossOrigin; + return this; + + } + + setWithCredentials( value ) { + + this.withCredentials = value; + return this; + + } + + setPath( path ) { + + this.path = path; + return this; + + } + + setResourcePath( resourcePath ) { + + this.resourcePath = resourcePath; + return this; + + } + + setRequestHeader( requestHeader ) { + + this.requestHeader = requestHeader; + return this; + + } + +} + +Loader.DEFAULT_MATERIAL_NAME = '__DEFAULT'; + +const loading = {}; + +class HttpError extends Error { + + constructor( message, response ) { + + super( message ); + this.response = response; + + } + +} + +class FileLoader extends Loader { + + constructor( manager ) { + + super( manager ); + + } + + load( url, onLoad, onProgress, onError ) { + + if ( url === undefined ) url = ''; + + if ( this.path !== undefined ) url = this.path + url; + + url = this.manager.resolveURL( url ); + + const cached = Cache.get( url ); + + if ( cached !== undefined ) { + + this.manager.itemStart( url ); + + setTimeout( () => { + + if ( onLoad ) onLoad( cached ); + + this.manager.itemEnd( url ); + + }, 0 ); + + return cached; + + } + + // Check if request is duplicate + + if ( loading[ url ] !== undefined ) { + + loading[ url ].push( { + + onLoad: onLoad, + onProgress: onProgress, + onError: onError + + } ); + + return; + + } + + // Initialise array for duplicate requests + loading[ url ] = []; + + loading[ url ].push( { + onLoad: onLoad, + onProgress: onProgress, + onError: onError, + } ); + + // create request + const req = new Request( url, { + headers: new Headers( this.requestHeader ), + credentials: this.withCredentials ? 'include' : 'same-origin', + // An abort controller could be added within a future PR + } ); + + // record states ( avoid data race ) + const mimeType = this.mimeType; + const responseType = this.responseType; + + // start the fetch + fetch( req ) + .then( response => { + + if ( response.status === 200 || response.status === 0 ) { + + // Some browsers return HTTP Status 0 when using non-http protocol + // e.g. 'file://' or 'data://'. Handle as success. + + if ( response.status === 0 ) { + + console.warn( 'THREE.FileLoader: HTTP Status 0 received.' ); + + } + + // Workaround: Checking if response.body === undefined for Alipay browser #23548 + + if ( typeof ReadableStream === 'undefined' || response.body === undefined || response.body.getReader === undefined ) { + + return response; + + } + + const callbacks = loading[ url ]; + const reader = response.body.getReader(); + + // Nginx needs X-File-Size check + // https://serverfault.com/questions/482875/why-does-nginx-remove-content-length-header-for-chunked-content + const contentLength = response.headers.get( 'X-File-Size' ) || response.headers.get( 'Content-Length' ); + const total = contentLength ? parseInt( contentLength ) : 0; + const lengthComputable = total !== 0; + let loaded = 0; + + // periodically read data into the new stream tracking while download progress + const stream = new ReadableStream( { + start( controller ) { + + readData(); + + function readData() { + + reader.read().then( ( { done, value } ) => { + + if ( done ) { + + controller.close(); + + } else { + + loaded += value.byteLength; + + const event = new ProgressEvent( 'progress', { lengthComputable, loaded, total } ); + for ( let i = 0, il = callbacks.length; i < il; i ++ ) { + + const callback = callbacks[ i ]; + if ( callback.onProgress ) callback.onProgress( event ); + + } + + controller.enqueue( value ); + readData(); + + } + + }, ( e ) => { + + controller.error( e ); + + } ); + + } + + } + + } ); + + return new Response( stream ); + + } else { + + throw new HttpError( `fetch for "${response.url}" responded with ${response.status}: ${response.statusText}`, response ); + + } + + } ) + .then( response => { + + switch ( responseType ) { + + case 'arraybuffer': + + return response.arrayBuffer(); + + case 'blob': + + return response.blob(); + + case 'document': + + return response.text() + .then( text => { + + const parser = new DOMParser(); + return parser.parseFromString( text, mimeType ); + + } ); + + case 'json': + + return response.json(); + + default: + + if ( mimeType === undefined ) { + + return response.text(); + + } else { + + // sniff encoding + const re = /charset="?([^;"\s]*)"?/i; + const exec = re.exec( mimeType ); + const label = exec && exec[ 1 ] ? exec[ 1 ].toLowerCase() : undefined; + const decoder = new TextDecoder( label ); + return response.arrayBuffer().then( ab => decoder.decode( ab ) ); + + } + + } + + } ) + .then( data => { + + // Add to cache only on HTTP success, so that we do not cache + // error response bodies as proper responses to requests. + Cache.add( url, data ); + + const callbacks = loading[ url ]; + delete loading[ url ]; + + for ( let i = 0, il = callbacks.length; i < il; i ++ ) { + + const callback = callbacks[ i ]; + if ( callback.onLoad ) callback.onLoad( data ); + + } + + } ) + .catch( err => { + + // Abort errors and other errors are handled the same + + const callbacks = loading[ url ]; + + if ( callbacks === undefined ) { + + // When onLoad was called and url was deleted in `loading` + this.manager.itemError( url ); + throw err; + + } + + delete loading[ url ]; + + for ( let i = 0, il = callbacks.length; i < il; i ++ ) { + + const callback = callbacks[ i ]; + if ( callback.onError ) callback.onError( err ); + + } + + this.manager.itemError( url ); + + } ) + .finally( () => { + + this.manager.itemEnd( url ); + + } ); + + this.manager.itemStart( url ); + + } + + setResponseType( value ) { + + this.responseType = value; + return this; + + } + + setMimeType( value ) { + + this.mimeType = value; + return this; + + } + +} + +class AnimationLoader extends Loader { + + constructor( manager ) { + + super( manager ); + + } + + load( url, onLoad, onProgress, onError ) { + + const scope = this; + + const loader = new FileLoader( this.manager ); + loader.setPath( this.path ); + loader.setRequestHeader( this.requestHeader ); + loader.setWithCredentials( this.withCredentials ); + loader.load( url, function ( text ) { + + try { + + onLoad( scope.parse( JSON.parse( text ) ) ); + + } catch ( e ) { + + if ( onError ) { + + onError( e ); + + } else { + + console.error( e ); + + } + + scope.manager.itemError( url ); + + } + + }, onProgress, onError ); + + } + + parse( json ) { + + const animations = []; + + for ( let i = 0; i < json.length; i ++ ) { + + const clip = AnimationClip.parse( json[ i ] ); + + animations.push( clip ); + + } + + return animations; + + } + +} + +/** + * Abstract Base class to block based textures loader (dds, pvr, ...) + * + * Sub classes have to implement the parse() method which will be used in load(). + */ + +class CompressedTextureLoader extends Loader { + + constructor( manager ) { + + super( manager ); + + } + + load( url, onLoad, onProgress, onError ) { + + const scope = this; + + const images = []; + + const texture = new CompressedTexture(); + + const loader = new FileLoader( this.manager ); + loader.setPath( this.path ); + loader.setResponseType( 'arraybuffer' ); + loader.setRequestHeader( this.requestHeader ); + loader.setWithCredentials( scope.withCredentials ); + + let loaded = 0; + + function loadTexture( i ) { + + loader.load( url[ i ], function ( buffer ) { + + const texDatas = scope.parse( buffer, true ); + + images[ i ] = { + width: texDatas.width, + height: texDatas.height, + format: texDatas.format, + mipmaps: texDatas.mipmaps + }; + + loaded += 1; + + if ( loaded === 6 ) { + + if ( texDatas.mipmapCount === 1 ) texture.minFilter = LinearFilter; + + texture.image = images; + texture.format = texDatas.format; + texture.needsUpdate = true; + + if ( onLoad ) onLoad( texture ); + + } + + }, onProgress, onError ); + + } + + if ( Array.isArray( url ) ) { + + for ( let i = 0, il = url.length; i < il; ++ i ) { + + loadTexture( i ); + + } + + } else { + + // compressed cubemap texture stored in a single DDS file + + loader.load( url, function ( buffer ) { + + const texDatas = scope.parse( buffer, true ); + + if ( texDatas.isCubemap ) { + + const faces = texDatas.mipmaps.length / texDatas.mipmapCount; + + for ( let f = 0; f < faces; f ++ ) { + + images[ f ] = { mipmaps: [] }; + + for ( let i = 0; i < texDatas.mipmapCount; i ++ ) { + + images[ f ].mipmaps.push( texDatas.mipmaps[ f * texDatas.mipmapCount + i ] ); + images[ f ].format = texDatas.format; + images[ f ].width = texDatas.width; + images[ f ].height = texDatas.height; + + } + + } + + texture.image = images; + + } else { + + texture.image.width = texDatas.width; + texture.image.height = texDatas.height; + texture.mipmaps = texDatas.mipmaps; + + } + + if ( texDatas.mipmapCount === 1 ) { + + texture.minFilter = LinearFilter; + + } + + texture.format = texDatas.format; + texture.needsUpdate = true; + + if ( onLoad ) onLoad( texture ); + + }, onProgress, onError ); + + } + + return texture; + + } + +} + +class ImageLoader extends Loader { + + constructor( manager ) { + + super( manager ); + + } + + load( url, onLoad, onProgress, onError ) { + + if ( this.path !== undefined ) url = this.path + url; + + url = this.manager.resolveURL( url ); + + const scope = this; + + const cached = Cache.get( url ); + + if ( cached !== undefined ) { + + scope.manager.itemStart( url ); + + setTimeout( function () { + + if ( onLoad ) onLoad( cached ); + + scope.manager.itemEnd( url ); + + }, 0 ); + + return cached; + + } + + const image = createElementNS( 'img' ); + + function onImageLoad() { + + removeEventListeners(); + + Cache.add( url, this ); + + if ( onLoad ) onLoad( this ); + + scope.manager.itemEnd( url ); + + } + + function onImageError( event ) { + + removeEventListeners(); + + if ( onError ) onError( event ); + + scope.manager.itemError( url ); + scope.manager.itemEnd( url ); + + } + + function removeEventListeners() { + + image.removeEventListener( 'load', onImageLoad, false ); + image.removeEventListener( 'error', onImageError, false ); + + } + + image.addEventListener( 'load', onImageLoad, false ); + image.addEventListener( 'error', onImageError, false ); + + if ( url.slice( 0, 5 ) !== 'data:' ) { + + if ( this.crossOrigin !== undefined ) image.crossOrigin = this.crossOrigin; + + } + + scope.manager.itemStart( url ); + + image.src = url; + + return image; + + } + +} + +class CubeTextureLoader extends Loader { + + constructor( manager ) { + + super( manager ); + + } + + load( urls, onLoad, onProgress, onError ) { + + const texture = new CubeTexture(); + texture.colorSpace = SRGBColorSpace; + + const loader = new ImageLoader( this.manager ); + loader.setCrossOrigin( this.crossOrigin ); + loader.setPath( this.path ); + + let loaded = 0; + + function loadTexture( i ) { + + loader.load( urls[ i ], function ( image ) { + + texture.images[ i ] = image; + + loaded ++; + + if ( loaded === 6 ) { + + texture.needsUpdate = true; + + if ( onLoad ) onLoad( texture ); + + } + + }, undefined, onError ); + + } + + for ( let i = 0; i < urls.length; ++ i ) { + + loadTexture( i ); + + } + + return texture; + + } + +} + +/** + * Abstract Base class to load generic binary textures formats (rgbe, hdr, ...) + * + * Sub classes have to implement the parse() method which will be used in load(). + */ + +class DataTextureLoader extends Loader { + + constructor( manager ) { + + super( manager ); + + } + + load( url, onLoad, onProgress, onError ) { + + const scope = this; + + const texture = new DataTexture(); + + const loader = new FileLoader( this.manager ); + loader.setResponseType( 'arraybuffer' ); + loader.setRequestHeader( this.requestHeader ); + loader.setPath( this.path ); + loader.setWithCredentials( scope.withCredentials ); + loader.load( url, function ( buffer ) { + + let texData; + + try { + + texData = scope.parse( buffer ); + + } catch ( error ) { + + if ( onError !== undefined ) { + + onError( error ); + + } else { + + console.error( error ); + return; + + } + + } + + if ( texData.image !== undefined ) { + + texture.image = texData.image; + + } else if ( texData.data !== undefined ) { + + texture.image.width = texData.width; + texture.image.height = texData.height; + texture.image.data = texData.data; + + } + + texture.wrapS = texData.wrapS !== undefined ? texData.wrapS : ClampToEdgeWrapping; + texture.wrapT = texData.wrapT !== undefined ? texData.wrapT : ClampToEdgeWrapping; + + texture.magFilter = texData.magFilter !== undefined ? texData.magFilter : LinearFilter; + texture.minFilter = texData.minFilter !== undefined ? texData.minFilter : LinearFilter; + + texture.anisotropy = texData.anisotropy !== undefined ? texData.anisotropy : 1; + + if ( texData.colorSpace !== undefined ) { + + texture.colorSpace = texData.colorSpace; + + } + + if ( texData.flipY !== undefined ) { + + texture.flipY = texData.flipY; + + } + + if ( texData.format !== undefined ) { + + texture.format = texData.format; + + } + + if ( texData.type !== undefined ) { + + texture.type = texData.type; + + } + + if ( texData.mipmaps !== undefined ) { + + texture.mipmaps = texData.mipmaps; + texture.minFilter = LinearMipmapLinearFilter; // presumably... + + } + + if ( texData.mipmapCount === 1 ) { + + texture.minFilter = LinearFilter; + + } + + if ( texData.generateMipmaps !== undefined ) { + + texture.generateMipmaps = texData.generateMipmaps; + + } + + texture.needsUpdate = true; + + if ( onLoad ) onLoad( texture, texData ); + + }, onProgress, onError ); + + + return texture; + + } + +} + +class TextureLoader extends Loader { + + constructor( manager ) { + + super( manager ); + + } + + load( url, onLoad, onProgress, onError ) { + + const texture = new Texture(); + + const loader = new ImageLoader( this.manager ); + loader.setCrossOrigin( this.crossOrigin ); + loader.setPath( this.path ); + + loader.load( url, function ( image ) { + + texture.image = image; + texture.needsUpdate = true; + + if ( onLoad !== undefined ) { + + onLoad( texture ); + + } + + }, onProgress, onError ); + + return texture; + + } + +} + +class Light extends Object3D { + + constructor( color, intensity = 1 ) { + + super(); + + this.isLight = true; + + this.type = 'Light'; + + this.color = new Color( color ); + this.intensity = intensity; + + } + + dispose() { + + // Empty here in base class; some subclasses override. + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + this.color.copy( source.color ); + this.intensity = source.intensity; + + return this; + + } + + toJSON( meta ) { + + const data = super.toJSON( meta ); + + data.object.color = this.color.getHex(); + data.object.intensity = this.intensity; + + if ( this.groundColor !== undefined ) data.object.groundColor = this.groundColor.getHex(); + + if ( this.distance !== undefined ) data.object.distance = this.distance; + if ( this.angle !== undefined ) data.object.angle = this.angle; + if ( this.decay !== undefined ) data.object.decay = this.decay; + if ( this.penumbra !== undefined ) data.object.penumbra = this.penumbra; + + if ( this.shadow !== undefined ) data.object.shadow = this.shadow.toJSON(); + + return data; + + } + +} + +class HemisphereLight extends Light { + + constructor( skyColor, groundColor, intensity ) { + + super( skyColor, intensity ); + + this.isHemisphereLight = true; + + this.type = 'HemisphereLight'; + + this.position.copy( Object3D.DEFAULT_UP ); + this.updateMatrix(); + + this.groundColor = new Color( groundColor ); + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + this.groundColor.copy( source.groundColor ); + + return this; + + } + +} + +const _projScreenMatrix$1 = /*@__PURE__*/ new Matrix4(); +const _lightPositionWorld$1 = /*@__PURE__*/ new Vector3(); +const _lookTarget$1 = /*@__PURE__*/ new Vector3(); + +class LightShadow { + + constructor( camera ) { + + this.camera = camera; + + this.bias = 0; + this.normalBias = 0; + this.radius = 1; + this.blurSamples = 8; + + this.mapSize = new Vector2( 512, 512 ); + + this.map = null; + this.mapPass = null; + this.matrix = new Matrix4(); + + this.autoUpdate = true; + this.needsUpdate = false; + + this._frustum = new Frustum(); + this._frameExtents = new Vector2( 1, 1 ); + + this._viewportCount = 1; + + this._viewports = [ + + new Vector4( 0, 0, 1, 1 ) + + ]; + + } + + getViewportCount() { + + return this._viewportCount; + + } + + getFrustum() { + + return this._frustum; + + } + + updateMatrices( light ) { + + const shadowCamera = this.camera; + const shadowMatrix = this.matrix; + + _lightPositionWorld$1.setFromMatrixPosition( light.matrixWorld ); + shadowCamera.position.copy( _lightPositionWorld$1 ); + + _lookTarget$1.setFromMatrixPosition( light.target.matrixWorld ); + shadowCamera.lookAt( _lookTarget$1 ); + shadowCamera.updateMatrixWorld(); + + _projScreenMatrix$1.multiplyMatrices( shadowCamera.projectionMatrix, shadowCamera.matrixWorldInverse ); + this._frustum.setFromProjectionMatrix( _projScreenMatrix$1 ); + + shadowMatrix.set( + 0.5, 0.0, 0.0, 0.5, + 0.0, 0.5, 0.0, 0.5, + 0.0, 0.0, 0.5, 0.5, + 0.0, 0.0, 0.0, 1.0 + ); + + shadowMatrix.multiply( _projScreenMatrix$1 ); + + } + + getViewport( viewportIndex ) { + + return this._viewports[ viewportIndex ]; + + } + + getFrameExtents() { + + return this._frameExtents; + + } + + dispose() { + + if ( this.map ) { + + this.map.dispose(); + + } + + if ( this.mapPass ) { + + this.mapPass.dispose(); + + } + + } + + copy( source ) { + + this.camera = source.camera.clone(); + + this.bias = source.bias; + this.radius = source.radius; + + this.mapSize.copy( source.mapSize ); + + return this; + + } + + clone() { + + return new this.constructor().copy( this ); + + } + + toJSON() { + + const object = {}; + + if ( this.bias !== 0 ) object.bias = this.bias; + if ( this.normalBias !== 0 ) object.normalBias = this.normalBias; + if ( this.radius !== 1 ) object.radius = this.radius; + if ( this.mapSize.x !== 512 || this.mapSize.y !== 512 ) object.mapSize = this.mapSize.toArray(); + + object.camera = this.camera.toJSON( false ).object; + delete object.camera.matrix; + + return object; + + } + +} + +class SpotLightShadow extends LightShadow { + + constructor() { + + super( new PerspectiveCamera( 50, 1, 0.5, 500 ) ); + + this.isSpotLightShadow = true; + + this.focus = 1; + + } + + updateMatrices( light ) { + + const camera = this.camera; + + const fov = RAD2DEG * 2 * light.angle * this.focus; + const aspect = this.mapSize.width / this.mapSize.height; + const far = light.distance || camera.far; + + if ( fov !== camera.fov || aspect !== camera.aspect || far !== camera.far ) { + + camera.fov = fov; + camera.aspect = aspect; + camera.far = far; + camera.updateProjectionMatrix(); + + } + + super.updateMatrices( light ); + + } + + copy( source ) { + + super.copy( source ); + + this.focus = source.focus; + + return this; + + } + +} + +class SpotLight extends Light { + + constructor( color, intensity, distance = 0, angle = Math.PI / 3, penumbra = 0, decay = 2 ) { + + super( color, intensity ); + + this.isSpotLight = true; + + this.type = 'SpotLight'; + + this.position.copy( Object3D.DEFAULT_UP ); + this.updateMatrix(); + + this.target = new Object3D(); + + this.distance = distance; + this.angle = angle; + this.penumbra = penumbra; + this.decay = decay; + + this.map = null; + + this.shadow = new SpotLightShadow(); + + } + + get power() { + + // compute the light's luminous power (in lumens) from its intensity (in candela) + // by convention for a spotlight, luminous power (lm) = π * luminous intensity (cd) + return this.intensity * Math.PI; + + } + + set power( power ) { + + // set the light's intensity (in candela) from the desired luminous power (in lumens) + this.intensity = power / Math.PI; + + } + + dispose() { + + this.shadow.dispose(); + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + this.distance = source.distance; + this.angle = source.angle; + this.penumbra = source.penumbra; + this.decay = source.decay; + + this.target = source.target.clone(); + + this.shadow = source.shadow.clone(); + + return this; + + } + +} + +const _projScreenMatrix = /*@__PURE__*/ new Matrix4(); +const _lightPositionWorld = /*@__PURE__*/ new Vector3(); +const _lookTarget = /*@__PURE__*/ new Vector3(); + +class PointLightShadow extends LightShadow { + + constructor() { + + super( new PerspectiveCamera( 90, 1, 0.5, 500 ) ); + + this.isPointLightShadow = true; + + this._frameExtents = new Vector2( 4, 2 ); + + this._viewportCount = 6; + + this._viewports = [ + // These viewports map a cube-map onto a 2D texture with the + // following orientation: + // + // xzXZ + // y Y + // + // X - Positive x direction + // x - Negative x direction + // Y - Positive y direction + // y - Negative y direction + // Z - Positive z direction + // z - Negative z direction + + // positive X + new Vector4( 2, 1, 1, 1 ), + // negative X + new Vector4( 0, 1, 1, 1 ), + // positive Z + new Vector4( 3, 1, 1, 1 ), + // negative Z + new Vector4( 1, 1, 1, 1 ), + // positive Y + new Vector4( 3, 0, 1, 1 ), + // negative Y + new Vector4( 1, 0, 1, 1 ) + ]; + + this._cubeDirections = [ + new Vector3( 1, 0, 0 ), new Vector3( - 1, 0, 0 ), new Vector3( 0, 0, 1 ), + new Vector3( 0, 0, - 1 ), new Vector3( 0, 1, 0 ), new Vector3( 0, - 1, 0 ) + ]; + + this._cubeUps = [ + new Vector3( 0, 1, 0 ), new Vector3( 0, 1, 0 ), new Vector3( 0, 1, 0 ), + new Vector3( 0, 1, 0 ), new Vector3( 0, 0, 1 ), new Vector3( 0, 0, - 1 ) + ]; + + } + + updateMatrices( light, viewportIndex = 0 ) { + + const camera = this.camera; + const shadowMatrix = this.matrix; + + const far = light.distance || camera.far; + + if ( far !== camera.far ) { + + camera.far = far; + camera.updateProjectionMatrix(); + + } + + _lightPositionWorld.setFromMatrixPosition( light.matrixWorld ); + camera.position.copy( _lightPositionWorld ); + + _lookTarget.copy( camera.position ); + _lookTarget.add( this._cubeDirections[ viewportIndex ] ); + camera.up.copy( this._cubeUps[ viewportIndex ] ); + camera.lookAt( _lookTarget ); + camera.updateMatrixWorld(); + + shadowMatrix.makeTranslation( - _lightPositionWorld.x, - _lightPositionWorld.y, - _lightPositionWorld.z ); + + _projScreenMatrix.multiplyMatrices( camera.projectionMatrix, camera.matrixWorldInverse ); + this._frustum.setFromProjectionMatrix( _projScreenMatrix ); + + } + +} + +class PointLight extends Light { + + constructor( color, intensity, distance = 0, decay = 2 ) { + + super( color, intensity ); + + this.isPointLight = true; + + this.type = 'PointLight'; + + this.distance = distance; + this.decay = decay; + + this.shadow = new PointLightShadow(); + + } + + get power() { + + // compute the light's luminous power (in lumens) from its intensity (in candela) + // for an isotropic light source, luminous power (lm) = 4 π luminous intensity (cd) + return this.intensity * 4 * Math.PI; + + } + + set power( power ) { + + // set the light's intensity (in candela) from the desired luminous power (in lumens) + this.intensity = power / ( 4 * Math.PI ); + + } + + dispose() { + + this.shadow.dispose(); + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + this.distance = source.distance; + this.decay = source.decay; + + this.shadow = source.shadow.clone(); + + return this; + + } + +} + +class DirectionalLightShadow extends LightShadow { + + constructor() { + + super( new OrthographicCamera( - 5, 5, 5, - 5, 0.5, 500 ) ); + + this.isDirectionalLightShadow = true; + + } + +} + +class DirectionalLight extends Light { + + constructor( color, intensity ) { + + super( color, intensity ); + + this.isDirectionalLight = true; + + this.type = 'DirectionalLight'; + + this.position.copy( Object3D.DEFAULT_UP ); + this.updateMatrix(); + + this.target = new Object3D(); + + this.shadow = new DirectionalLightShadow(); + + } + + dispose() { + + this.shadow.dispose(); + + } + + copy( source ) { + + super.copy( source ); + + this.target = source.target.clone(); + this.shadow = source.shadow.clone(); + + return this; + + } + +} + +class AmbientLight extends Light { + + constructor( color, intensity ) { + + super( color, intensity ); + + this.isAmbientLight = true; + + this.type = 'AmbientLight'; + + } + +} + +class RectAreaLight extends Light { + + constructor( color, intensity, width = 10, height = 10 ) { + + super( color, intensity ); + + this.isRectAreaLight = true; + + this.type = 'RectAreaLight'; + + this.width = width; + this.height = height; + + } + + get power() { + + // compute the light's luminous power (in lumens) from its intensity (in nits) + return this.intensity * this.width * this.height * Math.PI; + + } + + set power( power ) { + + // set the light's intensity (in nits) from the desired luminous power (in lumens) + this.intensity = power / ( this.width * this.height * Math.PI ); + + } + + copy( source ) { + + super.copy( source ); + + this.width = source.width; + this.height = source.height; + + return this; + + } + + toJSON( meta ) { + + const data = super.toJSON( meta ); + + data.object.width = this.width; + data.object.height = this.height; + + return data; + + } + +} + +/** + * Primary reference: + * https://graphics.stanford.edu/papers/envmap/envmap.pdf + * + * Secondary reference: + * https://www.ppsloan.org/publications/StupidSH36.pdf + */ + +// 3-band SH defined by 9 coefficients + +class SphericalHarmonics3 { + + constructor() { + + this.isSphericalHarmonics3 = true; + + this.coefficients = []; + + for ( let i = 0; i < 9; i ++ ) { + + this.coefficients.push( new Vector3() ); + + } + + } + + set( coefficients ) { + + for ( let i = 0; i < 9; i ++ ) { + + this.coefficients[ i ].copy( coefficients[ i ] ); + + } + + return this; + + } + + zero() { + + for ( let i = 0; i < 9; i ++ ) { + + this.coefficients[ i ].set( 0, 0, 0 ); + + } + + return this; + + } + + // get the radiance in the direction of the normal + // target is a Vector3 + getAt( normal, target ) { + + // normal is assumed to be unit length + + const x = normal.x, y = normal.y, z = normal.z; + + const coeff = this.coefficients; + + // band 0 + target.copy( coeff[ 0 ] ).multiplyScalar( 0.282095 ); + + // band 1 + target.addScaledVector( coeff[ 1 ], 0.488603 * y ); + target.addScaledVector( coeff[ 2 ], 0.488603 * z ); + target.addScaledVector( coeff[ 3 ], 0.488603 * x ); + + // band 2 + target.addScaledVector( coeff[ 4 ], 1.092548 * ( x * y ) ); + target.addScaledVector( coeff[ 5 ], 1.092548 * ( y * z ) ); + target.addScaledVector( coeff[ 6 ], 0.315392 * ( 3.0 * z * z - 1.0 ) ); + target.addScaledVector( coeff[ 7 ], 1.092548 * ( x * z ) ); + target.addScaledVector( coeff[ 8 ], 0.546274 * ( x * x - y * y ) ); + + return target; + + } + + // get the irradiance (radiance convolved with cosine lobe) in the direction of the normal + // target is a Vector3 + // https://graphics.stanford.edu/papers/envmap/envmap.pdf + getIrradianceAt( normal, target ) { + + // normal is assumed to be unit length + + const x = normal.x, y = normal.y, z = normal.z; + + const coeff = this.coefficients; + + // band 0 + target.copy( coeff[ 0 ] ).multiplyScalar( 0.886227 ); // π * 0.282095 + + // band 1 + target.addScaledVector( coeff[ 1 ], 2.0 * 0.511664 * y ); // ( 2 * π / 3 ) * 0.488603 + target.addScaledVector( coeff[ 2 ], 2.0 * 0.511664 * z ); + target.addScaledVector( coeff[ 3 ], 2.0 * 0.511664 * x ); + + // band 2 + target.addScaledVector( coeff[ 4 ], 2.0 * 0.429043 * x * y ); // ( π / 4 ) * 1.092548 + target.addScaledVector( coeff[ 5 ], 2.0 * 0.429043 * y * z ); + target.addScaledVector( coeff[ 6 ], 0.743125 * z * z - 0.247708 ); // ( π / 4 ) * 0.315392 * 3 + target.addScaledVector( coeff[ 7 ], 2.0 * 0.429043 * x * z ); + target.addScaledVector( coeff[ 8 ], 0.429043 * ( x * x - y * y ) ); // ( π / 4 ) * 0.546274 + + return target; + + } + + add( sh ) { + + for ( let i = 0; i < 9; i ++ ) { + + this.coefficients[ i ].add( sh.coefficients[ i ] ); + + } + + return this; + + } + + addScaledSH( sh, s ) { + + for ( let i = 0; i < 9; i ++ ) { + + this.coefficients[ i ].addScaledVector( sh.coefficients[ i ], s ); + + } + + return this; + + } + + scale( s ) { + + for ( let i = 0; i < 9; i ++ ) { + + this.coefficients[ i ].multiplyScalar( s ); + + } + + return this; + + } + + lerp( sh, alpha ) { + + for ( let i = 0; i < 9; i ++ ) { + + this.coefficients[ i ].lerp( sh.coefficients[ i ], alpha ); + + } + + return this; + + } + + equals( sh ) { + + for ( let i = 0; i < 9; i ++ ) { + + if ( ! this.coefficients[ i ].equals( sh.coefficients[ i ] ) ) { + + return false; + + } + + } + + return true; + + } + + copy( sh ) { + + return this.set( sh.coefficients ); + + } + + clone() { + + return new this.constructor().copy( this ); + + } + + fromArray( array, offset = 0 ) { + + const coefficients = this.coefficients; + + for ( let i = 0; i < 9; i ++ ) { + + coefficients[ i ].fromArray( array, offset + ( i * 3 ) ); + + } + + return this; + + } + + toArray( array = [], offset = 0 ) { + + const coefficients = this.coefficients; + + for ( let i = 0; i < 9; i ++ ) { + + coefficients[ i ].toArray( array, offset + ( i * 3 ) ); + + } + + return array; + + } + + // evaluate the basis functions + // shBasis is an Array[ 9 ] + static getBasisAt( normal, shBasis ) { + + // normal is assumed to be unit length + + const x = normal.x, y = normal.y, z = normal.z; + + // band 0 + shBasis[ 0 ] = 0.282095; + + // band 1 + shBasis[ 1 ] = 0.488603 * y; + shBasis[ 2 ] = 0.488603 * z; + shBasis[ 3 ] = 0.488603 * x; + + // band 2 + shBasis[ 4 ] = 1.092548 * x * y; + shBasis[ 5 ] = 1.092548 * y * z; + shBasis[ 6 ] = 0.315392 * ( 3 * z * z - 1 ); + shBasis[ 7 ] = 1.092548 * x * z; + shBasis[ 8 ] = 0.546274 * ( x * x - y * y ); + + } + +} + +class LightProbe extends Light { + + constructor( sh = new SphericalHarmonics3(), intensity = 1 ) { + + super( undefined, intensity ); + + this.isLightProbe = true; + + this.sh = sh; + + } + + copy( source ) { + + super.copy( source ); + + this.sh.copy( source.sh ); + + return this; + + } + + fromJSON( json ) { + + this.intensity = json.intensity; // TODO: Move this bit to Light.fromJSON(); + this.sh.fromArray( json.sh ); + + return this; + + } + + toJSON( meta ) { + + const data = super.toJSON( meta ); + + data.object.sh = this.sh.toArray(); + + return data; + + } + +} + +class MaterialLoader extends Loader { + + constructor( manager ) { + + super( manager ); + this.textures = {}; + + } + + load( url, onLoad, onProgress, onError ) { + + const scope = this; + + const loader = new FileLoader( scope.manager ); + loader.setPath( scope.path ); + loader.setRequestHeader( scope.requestHeader ); + loader.setWithCredentials( scope.withCredentials ); + loader.load( url, function ( text ) { + + try { + + onLoad( scope.parse( JSON.parse( text ) ) ); + + } catch ( e ) { + + if ( onError ) { + + onError( e ); + + } else { + + console.error( e ); + + } + + scope.manager.itemError( url ); + + } + + }, onProgress, onError ); + + } + + parse( json ) { + + const textures = this.textures; + + function getTexture( name ) { + + if ( textures[ name ] === undefined ) { + + console.warn( 'THREE.MaterialLoader: Undefined texture', name ); + + } + + return textures[ name ]; + + } + + const material = MaterialLoader.createMaterialFromType( json.type ); + + if ( json.uuid !== undefined ) material.uuid = json.uuid; + if ( json.name !== undefined ) material.name = json.name; + if ( json.color !== undefined && material.color !== undefined ) material.color.setHex( json.color ); + if ( json.roughness !== undefined ) material.roughness = json.roughness; + if ( json.metalness !== undefined ) material.metalness = json.metalness; + if ( json.sheen !== undefined ) material.sheen = json.sheen; + if ( json.sheenColor !== undefined ) material.sheenColor = new Color().setHex( json.sheenColor ); + if ( json.sheenRoughness !== undefined ) material.sheenRoughness = json.sheenRoughness; + if ( json.emissive !== undefined && material.emissive !== undefined ) material.emissive.setHex( json.emissive ); + if ( json.specular !== undefined && material.specular !== undefined ) material.specular.setHex( json.specular ); + if ( json.specularIntensity !== undefined ) material.specularIntensity = json.specularIntensity; + if ( json.specularColor !== undefined && material.specularColor !== undefined ) material.specularColor.setHex( json.specularColor ); + if ( json.shininess !== undefined ) material.shininess = json.shininess; + if ( json.clearcoat !== undefined ) material.clearcoat = json.clearcoat; + if ( json.clearcoatRoughness !== undefined ) material.clearcoatRoughness = json.clearcoatRoughness; + if ( json.dispersion !== undefined ) material.dispersion = json.dispersion; + if ( json.iridescence !== undefined ) material.iridescence = json.iridescence; + if ( json.iridescenceIOR !== undefined ) material.iridescenceIOR = json.iridescenceIOR; + if ( json.iridescenceThicknessRange !== undefined ) material.iridescenceThicknessRange = json.iridescenceThicknessRange; + if ( json.transmission !== undefined ) material.transmission = json.transmission; + if ( json.thickness !== undefined ) material.thickness = json.thickness; + if ( json.attenuationDistance !== undefined ) material.attenuationDistance = json.attenuationDistance; + if ( json.attenuationColor !== undefined && material.attenuationColor !== undefined ) material.attenuationColor.setHex( json.attenuationColor ); + if ( json.anisotropy !== undefined ) material.anisotropy = json.anisotropy; + if ( json.anisotropyRotation !== undefined ) material.anisotropyRotation = json.anisotropyRotation; + if ( json.fog !== undefined ) material.fog = json.fog; + if ( json.flatShading !== undefined ) material.flatShading = json.flatShading; + if ( json.blending !== undefined ) material.blending = json.blending; + if ( json.combine !== undefined ) material.combine = json.combine; + if ( json.side !== undefined ) material.side = json.side; + if ( json.shadowSide !== undefined ) material.shadowSide = json.shadowSide; + if ( json.opacity !== undefined ) material.opacity = json.opacity; + if ( json.transparent !== undefined ) material.transparent = json.transparent; + if ( json.alphaTest !== undefined ) material.alphaTest = json.alphaTest; + if ( json.alphaHash !== undefined ) material.alphaHash = json.alphaHash; + if ( json.depthFunc !== undefined ) material.depthFunc = json.depthFunc; + if ( json.depthTest !== undefined ) material.depthTest = json.depthTest; + if ( json.depthWrite !== undefined ) material.depthWrite = json.depthWrite; + if ( json.colorWrite !== undefined ) material.colorWrite = json.colorWrite; + if ( json.blendSrc !== undefined ) material.blendSrc = json.blendSrc; + if ( json.blendDst !== undefined ) material.blendDst = json.blendDst; + if ( json.blendEquation !== undefined ) material.blendEquation = json.blendEquation; + if ( json.blendSrcAlpha !== undefined ) material.blendSrcAlpha = json.blendSrcAlpha; + if ( json.blendDstAlpha !== undefined ) material.blendDstAlpha = json.blendDstAlpha; + if ( json.blendEquationAlpha !== undefined ) material.blendEquationAlpha = json.blendEquationAlpha; + if ( json.blendColor !== undefined && material.blendColor !== undefined ) material.blendColor.setHex( json.blendColor ); + if ( json.blendAlpha !== undefined ) material.blendAlpha = json.blendAlpha; + if ( json.stencilWriteMask !== undefined ) material.stencilWriteMask = json.stencilWriteMask; + if ( json.stencilFunc !== undefined ) material.stencilFunc = json.stencilFunc; + if ( json.stencilRef !== undefined ) material.stencilRef = json.stencilRef; + if ( json.stencilFuncMask !== undefined ) material.stencilFuncMask = json.stencilFuncMask; + if ( json.stencilFail !== undefined ) material.stencilFail = json.stencilFail; + if ( json.stencilZFail !== undefined ) material.stencilZFail = json.stencilZFail; + if ( json.stencilZPass !== undefined ) material.stencilZPass = json.stencilZPass; + if ( json.stencilWrite !== undefined ) material.stencilWrite = json.stencilWrite; + + if ( json.wireframe !== undefined ) material.wireframe = json.wireframe; + if ( json.wireframeLinewidth !== undefined ) material.wireframeLinewidth = json.wireframeLinewidth; + if ( json.wireframeLinecap !== undefined ) material.wireframeLinecap = json.wireframeLinecap; + if ( json.wireframeLinejoin !== undefined ) material.wireframeLinejoin = json.wireframeLinejoin; + + if ( json.rotation !== undefined ) material.rotation = json.rotation; + + if ( json.linewidth !== undefined ) material.linewidth = json.linewidth; + if ( json.dashSize !== undefined ) material.dashSize = json.dashSize; + if ( json.gapSize !== undefined ) material.gapSize = json.gapSize; + if ( json.scale !== undefined ) material.scale = json.scale; + + if ( json.polygonOffset !== undefined ) material.polygonOffset = json.polygonOffset; + if ( json.polygonOffsetFactor !== undefined ) material.polygonOffsetFactor = json.polygonOffsetFactor; + if ( json.polygonOffsetUnits !== undefined ) material.polygonOffsetUnits = json.polygonOffsetUnits; + + if ( json.dithering !== undefined ) material.dithering = json.dithering; + + if ( json.alphaToCoverage !== undefined ) material.alphaToCoverage = json.alphaToCoverage; + if ( json.premultipliedAlpha !== undefined ) material.premultipliedAlpha = json.premultipliedAlpha; + if ( json.forceSinglePass !== undefined ) material.forceSinglePass = json.forceSinglePass; + + if ( json.visible !== undefined ) material.visible = json.visible; + + if ( json.toneMapped !== undefined ) material.toneMapped = json.toneMapped; + + if ( json.userData !== undefined ) material.userData = json.userData; + + if ( json.vertexColors !== undefined ) { + + if ( typeof json.vertexColors === 'number' ) { + + material.vertexColors = ( json.vertexColors > 0 ) ? true : false; + + } else { + + material.vertexColors = json.vertexColors; + + } + + } + + // Shader Material + + if ( json.uniforms !== undefined ) { + + for ( const name in json.uniforms ) { + + const uniform = json.uniforms[ name ]; + + material.uniforms[ name ] = {}; + + switch ( uniform.type ) { + + case 't': + material.uniforms[ name ].value = getTexture( uniform.value ); + break; + + case 'c': + material.uniforms[ name ].value = new Color().setHex( uniform.value ); + break; + + case 'v2': + material.uniforms[ name ].value = new Vector2().fromArray( uniform.value ); + break; + + case 'v3': + material.uniforms[ name ].value = new Vector3().fromArray( uniform.value ); + break; + + case 'v4': + material.uniforms[ name ].value = new Vector4().fromArray( uniform.value ); + break; + + case 'm3': + material.uniforms[ name ].value = new Matrix3().fromArray( uniform.value ); + break; + + case 'm4': + material.uniforms[ name ].value = new Matrix4().fromArray( uniform.value ); + break; + + default: + material.uniforms[ name ].value = uniform.value; + + } + + } + + } + + if ( json.defines !== undefined ) material.defines = json.defines; + if ( json.vertexShader !== undefined ) material.vertexShader = json.vertexShader; + if ( json.fragmentShader !== undefined ) material.fragmentShader = json.fragmentShader; + if ( json.glslVersion !== undefined ) material.glslVersion = json.glslVersion; + + if ( json.extensions !== undefined ) { + + for ( const key in json.extensions ) { + + material.extensions[ key ] = json.extensions[ key ]; + + } + + } + + if ( json.lights !== undefined ) material.lights = json.lights; + if ( json.clipping !== undefined ) material.clipping = json.clipping; + + // for PointsMaterial + + if ( json.size !== undefined ) material.size = json.size; + if ( json.sizeAttenuation !== undefined ) material.sizeAttenuation = json.sizeAttenuation; + + // maps + + if ( json.map !== undefined ) material.map = getTexture( json.map ); + if ( json.matcap !== undefined ) material.matcap = getTexture( json.matcap ); + + if ( json.alphaMap !== undefined ) material.alphaMap = getTexture( json.alphaMap ); + + if ( json.bumpMap !== undefined ) material.bumpMap = getTexture( json.bumpMap ); + if ( json.bumpScale !== undefined ) material.bumpScale = json.bumpScale; + + if ( json.normalMap !== undefined ) material.normalMap = getTexture( json.normalMap ); + if ( json.normalMapType !== undefined ) material.normalMapType = json.normalMapType; + if ( json.normalScale !== undefined ) { + + let normalScale = json.normalScale; + + if ( Array.isArray( normalScale ) === false ) { + + // Blender exporter used to export a scalar. See #7459 + + normalScale = [ normalScale, normalScale ]; + + } + + material.normalScale = new Vector2().fromArray( normalScale ); + + } + + if ( json.displacementMap !== undefined ) material.displacementMap = getTexture( json.displacementMap ); + if ( json.displacementScale !== undefined ) material.displacementScale = json.displacementScale; + if ( json.displacementBias !== undefined ) material.displacementBias = json.displacementBias; + + if ( json.roughnessMap !== undefined ) material.roughnessMap = getTexture( json.roughnessMap ); + if ( json.metalnessMap !== undefined ) material.metalnessMap = getTexture( json.metalnessMap ); + + if ( json.emissiveMap !== undefined ) material.emissiveMap = getTexture( json.emissiveMap ); + if ( json.emissiveIntensity !== undefined ) material.emissiveIntensity = json.emissiveIntensity; + + if ( json.specularMap !== undefined ) material.specularMap = getTexture( json.specularMap ); + if ( json.specularIntensityMap !== undefined ) material.specularIntensityMap = getTexture( json.specularIntensityMap ); + if ( json.specularColorMap !== undefined ) material.specularColorMap = getTexture( json.specularColorMap ); + + if ( json.envMap !== undefined ) material.envMap = getTexture( json.envMap ); + if ( json.envMapRotation !== undefined ) material.envMapRotation.fromArray( json.envMapRotation ); + if ( json.envMapIntensity !== undefined ) material.envMapIntensity = json.envMapIntensity; + + if ( json.reflectivity !== undefined ) material.reflectivity = json.reflectivity; + if ( json.refractionRatio !== undefined ) material.refractionRatio = json.refractionRatio; + + if ( json.lightMap !== undefined ) material.lightMap = getTexture( json.lightMap ); + if ( json.lightMapIntensity !== undefined ) material.lightMapIntensity = json.lightMapIntensity; + + if ( json.aoMap !== undefined ) material.aoMap = getTexture( json.aoMap ); + if ( json.aoMapIntensity !== undefined ) material.aoMapIntensity = json.aoMapIntensity; + + if ( json.gradientMap !== undefined ) material.gradientMap = getTexture( json.gradientMap ); + + if ( json.clearcoatMap !== undefined ) material.clearcoatMap = getTexture( json.clearcoatMap ); + if ( json.clearcoatRoughnessMap !== undefined ) material.clearcoatRoughnessMap = getTexture( json.clearcoatRoughnessMap ); + if ( json.clearcoatNormalMap !== undefined ) material.clearcoatNormalMap = getTexture( json.clearcoatNormalMap ); + if ( json.clearcoatNormalScale !== undefined ) material.clearcoatNormalScale = new Vector2().fromArray( json.clearcoatNormalScale ); + + if ( json.iridescenceMap !== undefined ) material.iridescenceMap = getTexture( json.iridescenceMap ); + if ( json.iridescenceThicknessMap !== undefined ) material.iridescenceThicknessMap = getTexture( json.iridescenceThicknessMap ); + + if ( json.transmissionMap !== undefined ) material.transmissionMap = getTexture( json.transmissionMap ); + if ( json.thicknessMap !== undefined ) material.thicknessMap = getTexture( json.thicknessMap ); + + if ( json.anisotropyMap !== undefined ) material.anisotropyMap = getTexture( json.anisotropyMap ); + + if ( json.sheenColorMap !== undefined ) material.sheenColorMap = getTexture( json.sheenColorMap ); + if ( json.sheenRoughnessMap !== undefined ) material.sheenRoughnessMap = getTexture( json.sheenRoughnessMap ); + + return material; + + } + + setTextures( value ) { + + this.textures = value; + return this; + + } + + static createMaterialFromType( type ) { + + const materialLib = { + ShadowMaterial, + SpriteMaterial, + RawShaderMaterial, + ShaderMaterial, + PointsMaterial, + MeshPhysicalMaterial, + MeshStandardMaterial, + MeshPhongMaterial, + MeshToonMaterial, + MeshNormalMaterial, + MeshLambertMaterial, + MeshDepthMaterial, + MeshDistanceMaterial, + MeshBasicMaterial, + MeshMatcapMaterial, + LineDashedMaterial, + LineBasicMaterial, + Material + }; + + return new materialLib[ type ](); + + } + +} + +class LoaderUtils { + + static decodeText( array ) { // @deprecated, r165 + + console.warn( 'THREE.LoaderUtils: decodeText() has been deprecated with r165 and will be removed with r175. Use TextDecoder instead.' ); + + if ( typeof TextDecoder !== 'undefined' ) { + + return new TextDecoder().decode( array ); + + } + + // Avoid the String.fromCharCode.apply(null, array) shortcut, which + // throws a "maximum call stack size exceeded" error for large arrays. + + let s = ''; + + for ( let i = 0, il = array.length; i < il; i ++ ) { + + // Implicitly assumes little-endian. + s += String.fromCharCode( array[ i ] ); + + } + + try { + + // merges multi-byte utf-8 characters. + + return decodeURIComponent( escape( s ) ); + + } catch ( e ) { // see #16358 + + return s; + + } + + } + + static extractUrlBase( url ) { + + const index = url.lastIndexOf( '/' ); + + if ( index === - 1 ) return './'; + + return url.slice( 0, index + 1 ); + + } + + static resolveURL( url, path ) { + + // Invalid URL + if ( typeof url !== 'string' || url === '' ) return ''; + + // Host Relative URL + if ( /^https?:\/\//i.test( path ) && /^\//.test( url ) ) { + + path = path.replace( /(^https?:\/\/[^\/]+).*/i, '$1' ); + + } + + // Absolute URL http://,https://,// + if ( /^(https?:)?\/\//i.test( url ) ) return url; + + // Data URI + if ( /^data:.*,.*$/i.test( url ) ) return url; + + // Blob URL + if ( /^blob:.*$/i.test( url ) ) return url; + + // Relative URL + return path + url; + + } + +} + +class InstancedBufferGeometry extends BufferGeometry { + + constructor() { + + super(); + + this.isInstancedBufferGeometry = true; + + this.type = 'InstancedBufferGeometry'; + this.instanceCount = Infinity; + + } + + copy( source ) { + + super.copy( source ); + + this.instanceCount = source.instanceCount; + + return this; + + } + + toJSON() { + + const data = super.toJSON(); + + data.instanceCount = this.instanceCount; + + data.isInstancedBufferGeometry = true; + + return data; + + } + +} + +class BufferGeometryLoader extends Loader { + + constructor( manager ) { + + super( manager ); + + } + + load( url, onLoad, onProgress, onError ) { + + const scope = this; + + const loader = new FileLoader( scope.manager ); + loader.setPath( scope.path ); + loader.setRequestHeader( scope.requestHeader ); + loader.setWithCredentials( scope.withCredentials ); + loader.load( url, function ( text ) { + + try { + + onLoad( scope.parse( JSON.parse( text ) ) ); + + } catch ( e ) { + + if ( onError ) { + + onError( e ); + + } else { + + console.error( e ); + + } + + scope.manager.itemError( url ); + + } + + }, onProgress, onError ); + + } + + parse( json ) { + + const interleavedBufferMap = {}; + const arrayBufferMap = {}; + + function getInterleavedBuffer( json, uuid ) { + + if ( interleavedBufferMap[ uuid ] !== undefined ) return interleavedBufferMap[ uuid ]; + + const interleavedBuffers = json.interleavedBuffers; + const interleavedBuffer = interleavedBuffers[ uuid ]; + + const buffer = getArrayBuffer( json, interleavedBuffer.buffer ); + + const array = getTypedArray( interleavedBuffer.type, buffer ); + const ib = new InterleavedBuffer( array, interleavedBuffer.stride ); + ib.uuid = interleavedBuffer.uuid; + + interleavedBufferMap[ uuid ] = ib; + + return ib; + + } + + function getArrayBuffer( json, uuid ) { + + if ( arrayBufferMap[ uuid ] !== undefined ) return arrayBufferMap[ uuid ]; + + const arrayBuffers = json.arrayBuffers; + const arrayBuffer = arrayBuffers[ uuid ]; + + const ab = new Uint32Array( arrayBuffer ).buffer; + + arrayBufferMap[ uuid ] = ab; + + return ab; + + } + + const geometry = json.isInstancedBufferGeometry ? new InstancedBufferGeometry() : new BufferGeometry(); + + const index = json.data.index; + + if ( index !== undefined ) { + + const typedArray = getTypedArray( index.type, index.array ); + geometry.setIndex( new BufferAttribute( typedArray, 1 ) ); + + } + + const attributes = json.data.attributes; + + for ( const key in attributes ) { + + const attribute = attributes[ key ]; + let bufferAttribute; + + if ( attribute.isInterleavedBufferAttribute ) { + + const interleavedBuffer = getInterleavedBuffer( json.data, attribute.data ); + bufferAttribute = new InterleavedBufferAttribute( interleavedBuffer, attribute.itemSize, attribute.offset, attribute.normalized ); + + } else { + + const typedArray = getTypedArray( attribute.type, attribute.array ); + const bufferAttributeConstr = attribute.isInstancedBufferAttribute ? InstancedBufferAttribute : BufferAttribute; + bufferAttribute = new bufferAttributeConstr( typedArray, attribute.itemSize, attribute.normalized ); + + } + + if ( attribute.name !== undefined ) bufferAttribute.name = attribute.name; + if ( attribute.usage !== undefined ) bufferAttribute.setUsage( attribute.usage ); + + geometry.setAttribute( key, bufferAttribute ); + + } + + const morphAttributes = json.data.morphAttributes; + + if ( morphAttributes ) { + + for ( const key in morphAttributes ) { + + const attributeArray = morphAttributes[ key ]; + + const array = []; + + for ( let i = 0, il = attributeArray.length; i < il; i ++ ) { + + const attribute = attributeArray[ i ]; + let bufferAttribute; + + if ( attribute.isInterleavedBufferAttribute ) { + + const interleavedBuffer = getInterleavedBuffer( json.data, attribute.data ); + bufferAttribute = new InterleavedBufferAttribute( interleavedBuffer, attribute.itemSize, attribute.offset, attribute.normalized ); + + } else { + + const typedArray = getTypedArray( attribute.type, attribute.array ); + bufferAttribute = new BufferAttribute( typedArray, attribute.itemSize, attribute.normalized ); + + } + + if ( attribute.name !== undefined ) bufferAttribute.name = attribute.name; + array.push( bufferAttribute ); + + } + + geometry.morphAttributes[ key ] = array; + + } + + } + + const morphTargetsRelative = json.data.morphTargetsRelative; + + if ( morphTargetsRelative ) { + + geometry.morphTargetsRelative = true; + + } + + const groups = json.data.groups || json.data.drawcalls || json.data.offsets; + + if ( groups !== undefined ) { + + for ( let i = 0, n = groups.length; i !== n; ++ i ) { + + const group = groups[ i ]; + + geometry.addGroup( group.start, group.count, group.materialIndex ); + + } + + } + + const boundingSphere = json.data.boundingSphere; + + if ( boundingSphere !== undefined ) { + + const center = new Vector3(); + + if ( boundingSphere.center !== undefined ) { + + center.fromArray( boundingSphere.center ); + + } + + geometry.boundingSphere = new Sphere( center, boundingSphere.radius ); + + } + + if ( json.name ) geometry.name = json.name; + if ( json.userData ) geometry.userData = json.userData; + + return geometry; + + } + +} + +class ObjectLoader extends Loader { + + constructor( manager ) { + + super( manager ); + + } + + load( url, onLoad, onProgress, onError ) { + + const scope = this; + + const path = ( this.path === '' ) ? LoaderUtils.extractUrlBase( url ) : this.path; + this.resourcePath = this.resourcePath || path; + + const loader = new FileLoader( this.manager ); + loader.setPath( this.path ); + loader.setRequestHeader( this.requestHeader ); + loader.setWithCredentials( this.withCredentials ); + loader.load( url, function ( text ) { + + let json = null; + + try { + + json = JSON.parse( text ); + + } catch ( error ) { + + if ( onError !== undefined ) onError( error ); + + console.error( 'THREE:ObjectLoader: Can\'t parse ' + url + '.', error.message ); + + return; + + } + + const metadata = json.metadata; + + if ( metadata === undefined || metadata.type === undefined || metadata.type.toLowerCase() === 'geometry' ) { + + if ( onError !== undefined ) onError( new Error( 'THREE.ObjectLoader: Can\'t load ' + url ) ); + + console.error( 'THREE.ObjectLoader: Can\'t load ' + url ); + return; + + } + + scope.parse( json, onLoad ); + + }, onProgress, onError ); + + } + + async loadAsync( url, onProgress ) { + + const scope = this; + + const path = ( this.path === '' ) ? LoaderUtils.extractUrlBase( url ) : this.path; + this.resourcePath = this.resourcePath || path; + + const loader = new FileLoader( this.manager ); + loader.setPath( this.path ); + loader.setRequestHeader( this.requestHeader ); + loader.setWithCredentials( this.withCredentials ); + + const text = await loader.loadAsync( url, onProgress ); + + const json = JSON.parse( text ); + + const metadata = json.metadata; + + if ( metadata === undefined || metadata.type === undefined || metadata.type.toLowerCase() === 'geometry' ) { + + throw new Error( 'THREE.ObjectLoader: Can\'t load ' + url ); + + } + + return await scope.parseAsync( json ); + + } + + parse( json, onLoad ) { + + const animations = this.parseAnimations( json.animations ); + const shapes = this.parseShapes( json.shapes ); + const geometries = this.parseGeometries( json.geometries, shapes ); + + const images = this.parseImages( json.images, function () { + + if ( onLoad !== undefined ) onLoad( object ); + + } ); + + const textures = this.parseTextures( json.textures, images ); + const materials = this.parseMaterials( json.materials, textures ); + + const object = this.parseObject( json.object, geometries, materials, textures, animations ); + const skeletons = this.parseSkeletons( json.skeletons, object ); + + this.bindSkeletons( object, skeletons ); + + // + + if ( onLoad !== undefined ) { + + let hasImages = false; + + for ( const uuid in images ) { + + if ( images[ uuid ].data instanceof HTMLImageElement ) { + + hasImages = true; + break; + + } + + } + + if ( hasImages === false ) onLoad( object ); + + } + + return object; + + } + + async parseAsync( json ) { + + const animations = this.parseAnimations( json.animations ); + const shapes = this.parseShapes( json.shapes ); + const geometries = this.parseGeometries( json.geometries, shapes ); + + const images = await this.parseImagesAsync( json.images ); + + const textures = this.parseTextures( json.textures, images ); + const materials = this.parseMaterials( json.materials, textures ); + + const object = this.parseObject( json.object, geometries, materials, textures, animations ); + const skeletons = this.parseSkeletons( json.skeletons, object ); + + this.bindSkeletons( object, skeletons ); + + return object; + + } + + parseShapes( json ) { + + const shapes = {}; + + if ( json !== undefined ) { + + for ( let i = 0, l = json.length; i < l; i ++ ) { + + const shape = new Shape().fromJSON( json[ i ] ); + + shapes[ shape.uuid ] = shape; + + } + + } + + return shapes; + + } + + parseSkeletons( json, object ) { + + const skeletons = {}; + const bones = {}; + + // generate bone lookup table + + object.traverse( function ( child ) { + + if ( child.isBone ) bones[ child.uuid ] = child; + + } ); + + // create skeletons + + if ( json !== undefined ) { + + for ( let i = 0, l = json.length; i < l; i ++ ) { + + const skeleton = new Skeleton().fromJSON( json[ i ], bones ); + + skeletons[ skeleton.uuid ] = skeleton; + + } + + } + + return skeletons; + + } + + parseGeometries( json, shapes ) { + + const geometries = {}; + + if ( json !== undefined ) { + + const bufferGeometryLoader = new BufferGeometryLoader(); + + for ( let i = 0, l = json.length; i < l; i ++ ) { + + let geometry; + const data = json[ i ]; + + switch ( data.type ) { + + case 'BufferGeometry': + case 'InstancedBufferGeometry': + + geometry = bufferGeometryLoader.parse( data ); + break; + + default: + + if ( data.type in Geometries ) { + + geometry = Geometries[ data.type ].fromJSON( data, shapes ); + + } else { + + console.warn( `THREE.ObjectLoader: Unsupported geometry type "${ data.type }"` ); + + } + + } + + geometry.uuid = data.uuid; + + if ( data.name !== undefined ) geometry.name = data.name; + if ( data.userData !== undefined ) geometry.userData = data.userData; + + geometries[ data.uuid ] = geometry; + + } + + } + + return geometries; + + } + + parseMaterials( json, textures ) { + + const cache = {}; // MultiMaterial + const materials = {}; + + if ( json !== undefined ) { + + const loader = new MaterialLoader(); + loader.setTextures( textures ); + + for ( let i = 0, l = json.length; i < l; i ++ ) { + + const data = json[ i ]; + + if ( cache[ data.uuid ] === undefined ) { + + cache[ data.uuid ] = loader.parse( data ); + + } + + materials[ data.uuid ] = cache[ data.uuid ]; + + } + + } + + return materials; + + } + + parseAnimations( json ) { + + const animations = {}; + + if ( json !== undefined ) { + + for ( let i = 0; i < json.length; i ++ ) { + + const data = json[ i ]; + + const clip = AnimationClip.parse( data ); + + animations[ clip.uuid ] = clip; + + } + + } + + return animations; + + } + + parseImages( json, onLoad ) { + + const scope = this; + const images = {}; + + let loader; + + function loadImage( url ) { + + scope.manager.itemStart( url ); + + return loader.load( url, function () { + + scope.manager.itemEnd( url ); + + }, undefined, function () { + + scope.manager.itemError( url ); + scope.manager.itemEnd( url ); + + } ); + + } + + function deserializeImage( image ) { + + if ( typeof image === 'string' ) { + + const url = image; + + const path = /^(\/\/)|([a-z]+:(\/\/)?)/i.test( url ) ? url : scope.resourcePath + url; + + return loadImage( path ); + + } else { + + if ( image.data ) { + + return { + data: getTypedArray( image.type, image.data ), + width: image.width, + height: image.height + }; + + } else { + + return null; + + } + + } + + } + + if ( json !== undefined && json.length > 0 ) { + + const manager = new LoadingManager( onLoad ); + + loader = new ImageLoader( manager ); + loader.setCrossOrigin( this.crossOrigin ); + + for ( let i = 0, il = json.length; i < il; i ++ ) { + + const image = json[ i ]; + const url = image.url; + + if ( Array.isArray( url ) ) { + + // load array of images e.g CubeTexture + + const imageArray = []; + + for ( let j = 0, jl = url.length; j < jl; j ++ ) { + + const currentUrl = url[ j ]; + + const deserializedImage = deserializeImage( currentUrl ); + + if ( deserializedImage !== null ) { + + if ( deserializedImage instanceof HTMLImageElement ) { + + imageArray.push( deserializedImage ); + + } else { + + // special case: handle array of data textures for cube textures + + imageArray.push( new DataTexture( deserializedImage.data, deserializedImage.width, deserializedImage.height ) ); + + } + + } + + } + + images[ image.uuid ] = new Source( imageArray ); + + } else { + + // load single image + + const deserializedImage = deserializeImage( image.url ); + images[ image.uuid ] = new Source( deserializedImage ); + + + } + + } + + } + + return images; + + } + + async parseImagesAsync( json ) { + + const scope = this; + const images = {}; + + let loader; + + async function deserializeImage( image ) { + + if ( typeof image === 'string' ) { + + const url = image; + + const path = /^(\/\/)|([a-z]+:(\/\/)?)/i.test( url ) ? url : scope.resourcePath + url; + + return await loader.loadAsync( path ); + + } else { + + if ( image.data ) { + + return { + data: getTypedArray( image.type, image.data ), + width: image.width, + height: image.height + }; + + } else { + + return null; + + } + + } + + } + + if ( json !== undefined && json.length > 0 ) { + + loader = new ImageLoader( this.manager ); + loader.setCrossOrigin( this.crossOrigin ); + + for ( let i = 0, il = json.length; i < il; i ++ ) { + + const image = json[ i ]; + const url = image.url; + + if ( Array.isArray( url ) ) { + + // load array of images e.g CubeTexture + + const imageArray = []; + + for ( let j = 0, jl = url.length; j < jl; j ++ ) { + + const currentUrl = url[ j ]; + + const deserializedImage = await deserializeImage( currentUrl ); + + if ( deserializedImage !== null ) { + + if ( deserializedImage instanceof HTMLImageElement ) { + + imageArray.push( deserializedImage ); + + } else { + + // special case: handle array of data textures for cube textures + + imageArray.push( new DataTexture( deserializedImage.data, deserializedImage.width, deserializedImage.height ) ); + + } + + } + + } + + images[ image.uuid ] = new Source( imageArray ); + + } else { + + // load single image + + const deserializedImage = await deserializeImage( image.url ); + images[ image.uuid ] = new Source( deserializedImage ); + + } + + } + + } + + return images; + + } + + parseTextures( json, images ) { + + function parseConstant( value, type ) { + + if ( typeof value === 'number' ) return value; + + console.warn( 'THREE.ObjectLoader.parseTexture: Constant should be in numeric form.', value ); + + return type[ value ]; + + } + + const textures = {}; + + if ( json !== undefined ) { + + for ( let i = 0, l = json.length; i < l; i ++ ) { + + const data = json[ i ]; + + if ( data.image === undefined ) { + + console.warn( 'THREE.ObjectLoader: No "image" specified for', data.uuid ); + + } + + if ( images[ data.image ] === undefined ) { + + console.warn( 'THREE.ObjectLoader: Undefined image', data.image ); + + } + + const source = images[ data.image ]; + const image = source.data; + + let texture; + + if ( Array.isArray( image ) ) { + + texture = new CubeTexture(); + + if ( image.length === 6 ) texture.needsUpdate = true; + + } else { + + if ( image && image.data ) { + + texture = new DataTexture(); + + } else { + + texture = new Texture(); + + } + + if ( image ) texture.needsUpdate = true; // textures can have undefined image data + + } + + texture.source = source; + + texture.uuid = data.uuid; + + if ( data.name !== undefined ) texture.name = data.name; + + if ( data.mapping !== undefined ) texture.mapping = parseConstant( data.mapping, TEXTURE_MAPPING ); + if ( data.channel !== undefined ) texture.channel = data.channel; + + if ( data.offset !== undefined ) texture.offset.fromArray( data.offset ); + if ( data.repeat !== undefined ) texture.repeat.fromArray( data.repeat ); + if ( data.center !== undefined ) texture.center.fromArray( data.center ); + if ( data.rotation !== undefined ) texture.rotation = data.rotation; + + if ( data.wrap !== undefined ) { + + texture.wrapS = parseConstant( data.wrap[ 0 ], TEXTURE_WRAPPING ); + texture.wrapT = parseConstant( data.wrap[ 1 ], TEXTURE_WRAPPING ); + + } + + if ( data.format !== undefined ) texture.format = data.format; + if ( data.internalFormat !== undefined ) texture.internalFormat = data.internalFormat; + if ( data.type !== undefined ) texture.type = data.type; + if ( data.colorSpace !== undefined ) texture.colorSpace = data.colorSpace; + + if ( data.minFilter !== undefined ) texture.minFilter = parseConstant( data.minFilter, TEXTURE_FILTER ); + if ( data.magFilter !== undefined ) texture.magFilter = parseConstant( data.magFilter, TEXTURE_FILTER ); + if ( data.anisotropy !== undefined ) texture.anisotropy = data.anisotropy; + + if ( data.flipY !== undefined ) texture.flipY = data.flipY; + + if ( data.generateMipmaps !== undefined ) texture.generateMipmaps = data.generateMipmaps; + if ( data.premultiplyAlpha !== undefined ) texture.premultiplyAlpha = data.premultiplyAlpha; + if ( data.unpackAlignment !== undefined ) texture.unpackAlignment = data.unpackAlignment; + if ( data.compareFunction !== undefined ) texture.compareFunction = data.compareFunction; + + if ( data.userData !== undefined ) texture.userData = data.userData; + + textures[ data.uuid ] = texture; + + } + + } + + return textures; + + } + + parseObject( data, geometries, materials, textures, animations ) { + + let object; + + function getGeometry( name ) { + + if ( geometries[ name ] === undefined ) { + + console.warn( 'THREE.ObjectLoader: Undefined geometry', name ); + + } + + return geometries[ name ]; + + } + + function getMaterial( name ) { + + if ( name === undefined ) return undefined; + + if ( Array.isArray( name ) ) { + + const array = []; + + for ( let i = 0, l = name.length; i < l; i ++ ) { + + const uuid = name[ i ]; + + if ( materials[ uuid ] === undefined ) { + + console.warn( 'THREE.ObjectLoader: Undefined material', uuid ); + + } + + array.push( materials[ uuid ] ); + + } + + return array; + + } + + if ( materials[ name ] === undefined ) { + + console.warn( 'THREE.ObjectLoader: Undefined material', name ); + + } + + return materials[ name ]; + + } + + function getTexture( uuid ) { + + if ( textures[ uuid ] === undefined ) { + + console.warn( 'THREE.ObjectLoader: Undefined texture', uuid ); + + } + + return textures[ uuid ]; + + } + + let geometry, material; + + switch ( data.type ) { + + case 'Scene': + + object = new Scene(); + + if ( data.background !== undefined ) { + + if ( Number.isInteger( data.background ) ) { + + object.background = new Color( data.background ); + + } else { + + object.background = getTexture( data.background ); + + } + + } + + if ( data.environment !== undefined ) { + + object.environment = getTexture( data.environment ); + + } + + if ( data.fog !== undefined ) { + + if ( data.fog.type === 'Fog' ) { + + object.fog = new Fog( data.fog.color, data.fog.near, data.fog.far ); + + } else if ( data.fog.type === 'FogExp2' ) { + + object.fog = new FogExp2( data.fog.color, data.fog.density ); + + } + + if ( data.fog.name !== '' ) { + + object.fog.name = data.fog.name; + + } + + } + + if ( data.backgroundBlurriness !== undefined ) object.backgroundBlurriness = data.backgroundBlurriness; + if ( data.backgroundIntensity !== undefined ) object.backgroundIntensity = data.backgroundIntensity; + if ( data.backgroundRotation !== undefined ) object.backgroundRotation.fromArray( data.backgroundRotation ); + + if ( data.environmentIntensity !== undefined ) object.environmentIntensity = data.environmentIntensity; + if ( data.environmentRotation !== undefined ) object.environmentRotation.fromArray( data.environmentRotation ); + + break; + + case 'PerspectiveCamera': + + object = new PerspectiveCamera( data.fov, data.aspect, data.near, data.far ); + + if ( data.focus !== undefined ) object.focus = data.focus; + if ( data.zoom !== undefined ) object.zoom = data.zoom; + if ( data.filmGauge !== undefined ) object.filmGauge = data.filmGauge; + if ( data.filmOffset !== undefined ) object.filmOffset = data.filmOffset; + if ( data.view !== undefined ) object.view = Object.assign( {}, data.view ); + + break; + + case 'OrthographicCamera': + + object = new OrthographicCamera( data.left, data.right, data.top, data.bottom, data.near, data.far ); + + if ( data.zoom !== undefined ) object.zoom = data.zoom; + if ( data.view !== undefined ) object.view = Object.assign( {}, data.view ); + + break; + + case 'AmbientLight': + + object = new AmbientLight( data.color, data.intensity ); + + break; + + case 'DirectionalLight': + + object = new DirectionalLight( data.color, data.intensity ); + + break; + + case 'PointLight': + + object = new PointLight( data.color, data.intensity, data.distance, data.decay ); + + break; + + case 'RectAreaLight': + + object = new RectAreaLight( data.color, data.intensity, data.width, data.height ); + + break; + + case 'SpotLight': + + object = new SpotLight( data.color, data.intensity, data.distance, data.angle, data.penumbra, data.decay ); + + break; + + case 'HemisphereLight': + + object = new HemisphereLight( data.color, data.groundColor, data.intensity ); + + break; + + case 'LightProbe': + + object = new LightProbe().fromJSON( data ); + + break; + + case 'SkinnedMesh': + + geometry = getGeometry( data.geometry ); + material = getMaterial( data.material ); + + object = new SkinnedMesh( geometry, material ); + + if ( data.bindMode !== undefined ) object.bindMode = data.bindMode; + if ( data.bindMatrix !== undefined ) object.bindMatrix.fromArray( data.bindMatrix ); + if ( data.skeleton !== undefined ) object.skeleton = data.skeleton; + + break; + + case 'Mesh': + + geometry = getGeometry( data.geometry ); + material = getMaterial( data.material ); + + object = new Mesh( geometry, material ); + + break; + + case 'InstancedMesh': + + geometry = getGeometry( data.geometry ); + material = getMaterial( data.material ); + const count = data.count; + const instanceMatrix = data.instanceMatrix; + const instanceColor = data.instanceColor; + + object = new InstancedMesh( geometry, material, count ); + object.instanceMatrix = new InstancedBufferAttribute( new Float32Array( instanceMatrix.array ), 16 ); + if ( instanceColor !== undefined ) object.instanceColor = new InstancedBufferAttribute( new Float32Array( instanceColor.array ), instanceColor.itemSize ); + + break; + + case 'BatchedMesh': + + geometry = getGeometry( data.geometry ); + material = getMaterial( data.material ); + + object = new BatchedMesh( data.maxGeometryCount, data.maxVertexCount, data.maxIndexCount, material ); + object.geometry = geometry; + object.perObjectFrustumCulled = data.perObjectFrustumCulled; + object.sortObjects = data.sortObjects; + + object._drawRanges = data.drawRanges; + object._reservedRanges = data.reservedRanges; + + object._visibility = data.visibility; + object._active = data.active; + object._bounds = data.bounds.map( bound => { + + const box = new Box3(); + box.min.fromArray( bound.boxMin ); + box.max.fromArray( bound.boxMax ); + + const sphere = new Sphere(); + sphere.radius = bound.sphereRadius; + sphere.center.fromArray( bound.sphereCenter ); + + return { + boxInitialized: bound.boxInitialized, + box: box, + + sphereInitialized: bound.sphereInitialized, + sphere: sphere + }; + + } ); + + object._maxGeometryCount = data.maxGeometryCount; + object._maxVertexCount = data.maxVertexCount; + object._maxIndexCount = data.maxIndexCount; + + object._geometryInitialized = data.geometryInitialized; + object._geometryCount = data.geometryCount; + + object._matricesTexture = getTexture( data.matricesTexture.uuid ); + if ( data.colorsTexture !== undefined ) object._colorsTexture = getTexture( data.colorsTexture.uuid ); + + break; + + case 'LOD': + + object = new LOD(); + + break; + + case 'Line': + + object = new Line( getGeometry( data.geometry ), getMaterial( data.material ) ); + + break; + + case 'LineLoop': + + object = new LineLoop( getGeometry( data.geometry ), getMaterial( data.material ) ); + + break; + + case 'LineSegments': + + object = new LineSegments( getGeometry( data.geometry ), getMaterial( data.material ) ); + + break; + + case 'PointCloud': + case 'Points': + + object = new Points( getGeometry( data.geometry ), getMaterial( data.material ) ); + + break; + + case 'Sprite': + + object = new Sprite( getMaterial( data.material ) ); + + break; + + case 'Group': + + object = new Group(); + + break; + + case 'Bone': + + object = new Bone(); + + break; + + default: + + object = new Object3D(); + + } + + object.uuid = data.uuid; + + if ( data.name !== undefined ) object.name = data.name; + + if ( data.matrix !== undefined ) { + + object.matrix.fromArray( data.matrix ); + + if ( data.matrixAutoUpdate !== undefined ) object.matrixAutoUpdate = data.matrixAutoUpdate; + if ( object.matrixAutoUpdate ) object.matrix.decompose( object.position, object.quaternion, object.scale ); + + } else { + + if ( data.position !== undefined ) object.position.fromArray( data.position ); + if ( data.rotation !== undefined ) object.rotation.fromArray( data.rotation ); + if ( data.quaternion !== undefined ) object.quaternion.fromArray( data.quaternion ); + if ( data.scale !== undefined ) object.scale.fromArray( data.scale ); + + } + + if ( data.up !== undefined ) object.up.fromArray( data.up ); + + if ( data.castShadow !== undefined ) object.castShadow = data.castShadow; + if ( data.receiveShadow !== undefined ) object.receiveShadow = data.receiveShadow; + + if ( data.shadow ) { + + if ( data.shadow.bias !== undefined ) object.shadow.bias = data.shadow.bias; + if ( data.shadow.normalBias !== undefined ) object.shadow.normalBias = data.shadow.normalBias; + if ( data.shadow.radius !== undefined ) object.shadow.radius = data.shadow.radius; + if ( data.shadow.mapSize !== undefined ) object.shadow.mapSize.fromArray( data.shadow.mapSize ); + if ( data.shadow.camera !== undefined ) object.shadow.camera = this.parseObject( data.shadow.camera ); + + } + + if ( data.visible !== undefined ) object.visible = data.visible; + if ( data.frustumCulled !== undefined ) object.frustumCulled = data.frustumCulled; + if ( data.renderOrder !== undefined ) object.renderOrder = data.renderOrder; + if ( data.userData !== undefined ) object.userData = data.userData; + if ( data.layers !== undefined ) object.layers.mask = data.layers; + + if ( data.children !== undefined ) { + + const children = data.children; + + for ( let i = 0; i < children.length; i ++ ) { + + object.add( this.parseObject( children[ i ], geometries, materials, textures, animations ) ); + + } + + } + + if ( data.animations !== undefined ) { + + const objectAnimations = data.animations; + + for ( let i = 0; i < objectAnimations.length; i ++ ) { + + const uuid = objectAnimations[ i ]; + + object.animations.push( animations[ uuid ] ); + + } + + } + + if ( data.type === 'LOD' ) { + + if ( data.autoUpdate !== undefined ) object.autoUpdate = data.autoUpdate; + + const levels = data.levels; + + for ( let l = 0; l < levels.length; l ++ ) { + + const level = levels[ l ]; + const child = object.getObjectByProperty( 'uuid', level.object ); + + if ( child !== undefined ) { + + object.addLevel( child, level.distance, level.hysteresis ); + + } + + } + + } + + return object; + + } + + bindSkeletons( object, skeletons ) { + + if ( Object.keys( skeletons ).length === 0 ) return; + + object.traverse( function ( child ) { + + if ( child.isSkinnedMesh === true && child.skeleton !== undefined ) { + + const skeleton = skeletons[ child.skeleton ]; + + if ( skeleton === undefined ) { + + console.warn( 'THREE.ObjectLoader: No skeleton found with UUID:', child.skeleton ); + + } else { + + child.bind( skeleton, child.bindMatrix ); + + } + + } + + } ); + + } + +} + +const TEXTURE_MAPPING = { + UVMapping: UVMapping, + CubeReflectionMapping: CubeReflectionMapping, + CubeRefractionMapping: CubeRefractionMapping, + EquirectangularReflectionMapping: EquirectangularReflectionMapping, + EquirectangularRefractionMapping: EquirectangularRefractionMapping, + CubeUVReflectionMapping: CubeUVReflectionMapping +}; + +const TEXTURE_WRAPPING = { + RepeatWrapping: RepeatWrapping, + ClampToEdgeWrapping: ClampToEdgeWrapping, + MirroredRepeatWrapping: MirroredRepeatWrapping +}; + +const TEXTURE_FILTER = { + NearestFilter: NearestFilter, + NearestMipmapNearestFilter: NearestMipmapNearestFilter, + NearestMipmapLinearFilter: NearestMipmapLinearFilter, + LinearFilter: LinearFilter, + LinearMipmapNearestFilter: LinearMipmapNearestFilter, + LinearMipmapLinearFilter: LinearMipmapLinearFilter +}; + +class ImageBitmapLoader extends Loader { + + constructor( manager ) { + + super( manager ); + + this.isImageBitmapLoader = true; + + if ( typeof createImageBitmap === 'undefined' ) { + + console.warn( 'THREE.ImageBitmapLoader: createImageBitmap() not supported.' ); + + } + + if ( typeof fetch === 'undefined' ) { + + console.warn( 'THREE.ImageBitmapLoader: fetch() not supported.' ); + + } + + this.options = { premultiplyAlpha: 'none' }; + + } + + setOptions( options ) { + + this.options = options; + + return this; + + } + + load( url, onLoad, onProgress, onError ) { + + if ( url === undefined ) url = ''; + + if ( this.path !== undefined ) url = this.path + url; + + url = this.manager.resolveURL( url ); + + const scope = this; + + const cached = Cache.get( url ); + + if ( cached !== undefined ) { + + scope.manager.itemStart( url ); + + // If cached is a promise, wait for it to resolve + if ( cached.then ) { + + cached.then( imageBitmap => { + + if ( onLoad ) onLoad( imageBitmap ); + + scope.manager.itemEnd( url ); + + } ).catch( e => { + + if ( onError ) onError( e ); + + } ); + return; + + } + + // If cached is not a promise (i.e., it's already an imageBitmap) + setTimeout( function () { + + if ( onLoad ) onLoad( cached ); + + scope.manager.itemEnd( url ); + + }, 0 ); + + return cached; + + } + + const fetchOptions = {}; + fetchOptions.credentials = ( this.crossOrigin === 'anonymous' ) ? 'same-origin' : 'include'; + fetchOptions.headers = this.requestHeader; + + const promise = fetch( url, fetchOptions ).then( function ( res ) { + + return res.blob(); + + } ).then( function ( blob ) { + + return createImageBitmap( blob, Object.assign( scope.options, { colorSpaceConversion: 'none' } ) ); + + } ).then( function ( imageBitmap ) { + + Cache.add( url, imageBitmap ); + + if ( onLoad ) onLoad( imageBitmap ); + + scope.manager.itemEnd( url ); + + return imageBitmap; + + } ).catch( function ( e ) { + + if ( onError ) onError( e ); + + Cache.remove( url ); + + scope.manager.itemError( url ); + scope.manager.itemEnd( url ); + + } ); + + Cache.add( url, promise ); + scope.manager.itemStart( url ); + + } + +} + +let _context; + +class AudioContext { + + static getContext() { + + if ( _context === undefined ) { + + _context = new ( window.AudioContext || window.webkitAudioContext )(); + + } + + return _context; + + } + + static setContext( value ) { + + _context = value; + + } + +} + +class AudioLoader extends Loader { + + constructor( manager ) { + + super( manager ); + + } + + load( url, onLoad, onProgress, onError ) { + + const scope = this; + + const loader = new FileLoader( this.manager ); + loader.setResponseType( 'arraybuffer' ); + loader.setPath( this.path ); + loader.setRequestHeader( this.requestHeader ); + loader.setWithCredentials( this.withCredentials ); + loader.load( url, function ( buffer ) { + + try { + + // Create a copy of the buffer. The `decodeAudioData` method + // detaches the buffer when complete, preventing reuse. + const bufferCopy = buffer.slice( 0 ); + + const context = AudioContext.getContext(); + context.decodeAudioData( bufferCopy, function ( audioBuffer ) { + + onLoad( audioBuffer ); + + } ).catch( handleError ); + + } catch ( e ) { + + handleError( e ); + + } + + }, onProgress, onError ); + + function handleError( e ) { + + if ( onError ) { + + onError( e ); + + } else { + + console.error( e ); + + } + + scope.manager.itemError( url ); + + } + + } + +} + +const _eyeRight = /*@__PURE__*/ new Matrix4(); +const _eyeLeft = /*@__PURE__*/ new Matrix4(); +const _projectionMatrix = /*@__PURE__*/ new Matrix4(); + +class StereoCamera { + + constructor() { + + this.type = 'StereoCamera'; + + this.aspect = 1; + + this.eyeSep = 0.064; + + this.cameraL = new PerspectiveCamera(); + this.cameraL.layers.enable( 1 ); + this.cameraL.matrixAutoUpdate = false; + + this.cameraR = new PerspectiveCamera(); + this.cameraR.layers.enable( 2 ); + this.cameraR.matrixAutoUpdate = false; + + this._cache = { + focus: null, + fov: null, + aspect: null, + near: null, + far: null, + zoom: null, + eyeSep: null + }; + + } + + update( camera ) { + + const cache = this._cache; + + const needsUpdate = cache.focus !== camera.focus || cache.fov !== camera.fov || + cache.aspect !== camera.aspect * this.aspect || cache.near !== camera.near || + cache.far !== camera.far || cache.zoom !== camera.zoom || cache.eyeSep !== this.eyeSep; + + if ( needsUpdate ) { + + cache.focus = camera.focus; + cache.fov = camera.fov; + cache.aspect = camera.aspect * this.aspect; + cache.near = camera.near; + cache.far = camera.far; + cache.zoom = camera.zoom; + cache.eyeSep = this.eyeSep; + + // Off-axis stereoscopic effect based on + // http://paulbourke.net/stereographics/stereorender/ + + _projectionMatrix.copy( camera.projectionMatrix ); + const eyeSepHalf = cache.eyeSep / 2; + const eyeSepOnProjection = eyeSepHalf * cache.near / cache.focus; + const ymax = ( cache.near * Math.tan( DEG2RAD * cache.fov * 0.5 ) ) / cache.zoom; + let xmin, xmax; + + // translate xOffset + + _eyeLeft.elements[ 12 ] = - eyeSepHalf; + _eyeRight.elements[ 12 ] = eyeSepHalf; + + // for left eye + + xmin = - ymax * cache.aspect + eyeSepOnProjection; + xmax = ymax * cache.aspect + eyeSepOnProjection; + + _projectionMatrix.elements[ 0 ] = 2 * cache.near / ( xmax - xmin ); + _projectionMatrix.elements[ 8 ] = ( xmax + xmin ) / ( xmax - xmin ); + + this.cameraL.projectionMatrix.copy( _projectionMatrix ); + + // for right eye + + xmin = - ymax * cache.aspect - eyeSepOnProjection; + xmax = ymax * cache.aspect - eyeSepOnProjection; + + _projectionMatrix.elements[ 0 ] = 2 * cache.near / ( xmax - xmin ); + _projectionMatrix.elements[ 8 ] = ( xmax + xmin ) / ( xmax - xmin ); + + this.cameraR.projectionMatrix.copy( _projectionMatrix ); + + } + + this.cameraL.matrixWorld.copy( camera.matrixWorld ).multiply( _eyeLeft ); + this.cameraR.matrixWorld.copy( camera.matrixWorld ).multiply( _eyeRight ); + + } + +} + +class Clock { + + constructor( autoStart = true ) { + + this.autoStart = autoStart; + + this.startTime = 0; + this.oldTime = 0; + this.elapsedTime = 0; + + this.running = false; + + } + + start() { + + this.startTime = now(); + + this.oldTime = this.startTime; + this.elapsedTime = 0; + this.running = true; + + } + + stop() { + + this.getElapsedTime(); + this.running = false; + this.autoStart = false; + + } + + getElapsedTime() { + + this.getDelta(); + return this.elapsedTime; + + } + + getDelta() { + + let diff = 0; + + if ( this.autoStart && ! this.running ) { + + this.start(); + return 0; + + } + + if ( this.running ) { + + const newTime = now(); + + diff = ( newTime - this.oldTime ) / 1000; + this.oldTime = newTime; + + this.elapsedTime += diff; + + } + + return diff; + + } + +} + +function now() { + + return ( typeof performance === 'undefined' ? Date : performance ).now(); // see #10732 + +} + +const _position$1 = /*@__PURE__*/ new Vector3(); +const _quaternion$1 = /*@__PURE__*/ new Quaternion(); +const _scale$1 = /*@__PURE__*/ new Vector3(); +const _orientation$1 = /*@__PURE__*/ new Vector3(); + +class AudioListener extends Object3D { + + constructor() { + + super(); + + this.type = 'AudioListener'; + + this.context = AudioContext.getContext(); + + this.gain = this.context.createGain(); + this.gain.connect( this.context.destination ); + + this.filter = null; + + this.timeDelta = 0; + + // private + + this._clock = new Clock(); + + } + + getInput() { + + return this.gain; + + } + + removeFilter() { + + if ( this.filter !== null ) { + + this.gain.disconnect( this.filter ); + this.filter.disconnect( this.context.destination ); + this.gain.connect( this.context.destination ); + this.filter = null; + + } + + return this; + + } + + getFilter() { + + return this.filter; + + } + + setFilter( value ) { + + if ( this.filter !== null ) { + + this.gain.disconnect( this.filter ); + this.filter.disconnect( this.context.destination ); + + } else { + + this.gain.disconnect( this.context.destination ); + + } + + this.filter = value; + this.gain.connect( this.filter ); + this.filter.connect( this.context.destination ); + + return this; + + } + + getMasterVolume() { + + return this.gain.gain.value; + + } + + setMasterVolume( value ) { + + this.gain.gain.setTargetAtTime( value, this.context.currentTime, 0.01 ); + + return this; + + } + + updateMatrixWorld( force ) { + + super.updateMatrixWorld( force ); + + const listener = this.context.listener; + const up = this.up; + + this.timeDelta = this._clock.getDelta(); + + this.matrixWorld.decompose( _position$1, _quaternion$1, _scale$1 ); + + _orientation$1.set( 0, 0, - 1 ).applyQuaternion( _quaternion$1 ); + + if ( listener.positionX ) { + + // code path for Chrome (see #14393) + + const endTime = this.context.currentTime + this.timeDelta; + + listener.positionX.linearRampToValueAtTime( _position$1.x, endTime ); + listener.positionY.linearRampToValueAtTime( _position$1.y, endTime ); + listener.positionZ.linearRampToValueAtTime( _position$1.z, endTime ); + listener.forwardX.linearRampToValueAtTime( _orientation$1.x, endTime ); + listener.forwardY.linearRampToValueAtTime( _orientation$1.y, endTime ); + listener.forwardZ.linearRampToValueAtTime( _orientation$1.z, endTime ); + listener.upX.linearRampToValueAtTime( up.x, endTime ); + listener.upY.linearRampToValueAtTime( up.y, endTime ); + listener.upZ.linearRampToValueAtTime( up.z, endTime ); + + } else { + + listener.setPosition( _position$1.x, _position$1.y, _position$1.z ); + listener.setOrientation( _orientation$1.x, _orientation$1.y, _orientation$1.z, up.x, up.y, up.z ); + + } + + } + +} + +class Audio extends Object3D { + + constructor( listener ) { + + super(); + + this.type = 'Audio'; + + this.listener = listener; + this.context = listener.context; + + this.gain = this.context.createGain(); + this.gain.connect( listener.getInput() ); + + this.autoplay = false; + + this.buffer = null; + this.detune = 0; + this.loop = false; + this.loopStart = 0; + this.loopEnd = 0; + this.offset = 0; + this.duration = undefined; + this.playbackRate = 1; + this.isPlaying = false; + this.hasPlaybackControl = true; + this.source = null; + this.sourceType = 'empty'; + + this._startedAt = 0; + this._progress = 0; + this._connected = false; + + this.filters = []; + + } + + getOutput() { + + return this.gain; + + } + + setNodeSource( audioNode ) { + + this.hasPlaybackControl = false; + this.sourceType = 'audioNode'; + this.source = audioNode; + this.connect(); + + return this; + + } + + setMediaElementSource( mediaElement ) { + + this.hasPlaybackControl = false; + this.sourceType = 'mediaNode'; + this.source = this.context.createMediaElementSource( mediaElement ); + this.connect(); + + return this; + + } + + setMediaStreamSource( mediaStream ) { + + this.hasPlaybackControl = false; + this.sourceType = 'mediaStreamNode'; + this.source = this.context.createMediaStreamSource( mediaStream ); + this.connect(); + + return this; + + } + + setBuffer( audioBuffer ) { + + this.buffer = audioBuffer; + this.sourceType = 'buffer'; + + if ( this.autoplay ) this.play(); + + return this; + + } + + play( delay = 0 ) { + + if ( this.isPlaying === true ) { + + console.warn( 'THREE.Audio: Audio is already playing.' ); + return; + + } + + if ( this.hasPlaybackControl === false ) { + + console.warn( 'THREE.Audio: this Audio has no playback control.' ); + return; + + } + + this._startedAt = this.context.currentTime + delay; + + const source = this.context.createBufferSource(); + source.buffer = this.buffer; + source.loop = this.loop; + source.loopStart = this.loopStart; + source.loopEnd = this.loopEnd; + source.onended = this.onEnded.bind( this ); + source.start( this._startedAt, this._progress + this.offset, this.duration ); + + this.isPlaying = true; + + this.source = source; + + this.setDetune( this.detune ); + this.setPlaybackRate( this.playbackRate ); + + return this.connect(); + + } + + pause() { + + if ( this.hasPlaybackControl === false ) { + + console.warn( 'THREE.Audio: this Audio has no playback control.' ); + return; + + } + + if ( this.isPlaying === true ) { + + // update current progress + + this._progress += Math.max( this.context.currentTime - this._startedAt, 0 ) * this.playbackRate; + + if ( this.loop === true ) { + + // ensure _progress does not exceed duration with looped audios + + this._progress = this._progress % ( this.duration || this.buffer.duration ); + + } + + this.source.stop(); + this.source.onended = null; + + this.isPlaying = false; + + } + + return this; + + } + + stop() { + + if ( this.hasPlaybackControl === false ) { + + console.warn( 'THREE.Audio: this Audio has no playback control.' ); + return; + + } + + this._progress = 0; + + if ( this.source !== null ) { + + this.source.stop(); + this.source.onended = null; + + } + + this.isPlaying = false; + + return this; + + } + + connect() { + + if ( this.filters.length > 0 ) { + + this.source.connect( this.filters[ 0 ] ); + + for ( let i = 1, l = this.filters.length; i < l; i ++ ) { + + this.filters[ i - 1 ].connect( this.filters[ i ] ); + + } + + this.filters[ this.filters.length - 1 ].connect( this.getOutput() ); + + } else { + + this.source.connect( this.getOutput() ); + + } + + this._connected = true; + + return this; + + } + + disconnect() { + + if ( this._connected === false ) { + + return; + + } + + if ( this.filters.length > 0 ) { + + this.source.disconnect( this.filters[ 0 ] ); + + for ( let i = 1, l = this.filters.length; i < l; i ++ ) { + + this.filters[ i - 1 ].disconnect( this.filters[ i ] ); + + } + + this.filters[ this.filters.length - 1 ].disconnect( this.getOutput() ); + + } else { + + this.source.disconnect( this.getOutput() ); + + } + + this._connected = false; + + return this; + + } + + getFilters() { + + return this.filters; + + } + + setFilters( value ) { + + if ( ! value ) value = []; + + if ( this._connected === true ) { + + this.disconnect(); + this.filters = value.slice(); + this.connect(); + + } else { + + this.filters = value.slice(); + + } + + return this; + + } + + setDetune( value ) { + + this.detune = value; + + if ( this.isPlaying === true && this.source.detune !== undefined ) { + + this.source.detune.setTargetAtTime( this.detune, this.context.currentTime, 0.01 ); + + } + + return this; + + } + + getDetune() { + + return this.detune; + + } + + getFilter() { + + return this.getFilters()[ 0 ]; + + } + + setFilter( filter ) { + + return this.setFilters( filter ? [ filter ] : [] ); + + } + + setPlaybackRate( value ) { + + if ( this.hasPlaybackControl === false ) { + + console.warn( 'THREE.Audio: this Audio has no playback control.' ); + return; + + } + + this.playbackRate = value; + + if ( this.isPlaying === true ) { + + this.source.playbackRate.setTargetAtTime( this.playbackRate, this.context.currentTime, 0.01 ); + + } + + return this; + + } + + getPlaybackRate() { + + return this.playbackRate; + + } + + onEnded() { + + this.isPlaying = false; + + } + + getLoop() { + + if ( this.hasPlaybackControl === false ) { + + console.warn( 'THREE.Audio: this Audio has no playback control.' ); + return false; + + } + + return this.loop; + + } + + setLoop( value ) { + + if ( this.hasPlaybackControl === false ) { + + console.warn( 'THREE.Audio: this Audio has no playback control.' ); + return; + + } + + this.loop = value; + + if ( this.isPlaying === true ) { + + this.source.loop = this.loop; + + } + + return this; + + } + + setLoopStart( value ) { + + this.loopStart = value; + + return this; + + } + + setLoopEnd( value ) { + + this.loopEnd = value; + + return this; + + } + + getVolume() { + + return this.gain.gain.value; + + } + + setVolume( value ) { + + this.gain.gain.setTargetAtTime( value, this.context.currentTime, 0.01 ); + + return this; + + } + +} + +const _position = /*@__PURE__*/ new Vector3(); +const _quaternion = /*@__PURE__*/ new Quaternion(); +const _scale = /*@__PURE__*/ new Vector3(); +const _orientation = /*@__PURE__*/ new Vector3(); + +class PositionalAudio extends Audio { + + constructor( listener ) { + + super( listener ); + + this.panner = this.context.createPanner(); + this.panner.panningModel = 'HRTF'; + this.panner.connect( this.gain ); + + } + + connect() { + + super.connect(); + + this.panner.connect( this.gain ); + + } + + disconnect() { + + super.disconnect(); + + this.panner.disconnect( this.gain ); + + } + + getOutput() { + + return this.panner; + + } + + getRefDistance() { + + return this.panner.refDistance; + + } + + setRefDistance( value ) { + + this.panner.refDistance = value; + + return this; + + } + + getRolloffFactor() { + + return this.panner.rolloffFactor; + + } + + setRolloffFactor( value ) { + + this.panner.rolloffFactor = value; + + return this; + + } + + getDistanceModel() { + + return this.panner.distanceModel; + + } + + setDistanceModel( value ) { + + this.panner.distanceModel = value; + + return this; + + } + + getMaxDistance() { + + return this.panner.maxDistance; + + } + + setMaxDistance( value ) { + + this.panner.maxDistance = value; + + return this; + + } + + setDirectionalCone( coneInnerAngle, coneOuterAngle, coneOuterGain ) { + + this.panner.coneInnerAngle = coneInnerAngle; + this.panner.coneOuterAngle = coneOuterAngle; + this.panner.coneOuterGain = coneOuterGain; + + return this; + + } + + updateMatrixWorld( force ) { + + super.updateMatrixWorld( force ); + + if ( this.hasPlaybackControl === true && this.isPlaying === false ) return; + + this.matrixWorld.decompose( _position, _quaternion, _scale ); + + _orientation.set( 0, 0, 1 ).applyQuaternion( _quaternion ); + + const panner = this.panner; + + if ( panner.positionX ) { + + // code path for Chrome and Firefox (see #14393) + + const endTime = this.context.currentTime + this.listener.timeDelta; + + panner.positionX.linearRampToValueAtTime( _position.x, endTime ); + panner.positionY.linearRampToValueAtTime( _position.y, endTime ); + panner.positionZ.linearRampToValueAtTime( _position.z, endTime ); + panner.orientationX.linearRampToValueAtTime( _orientation.x, endTime ); + panner.orientationY.linearRampToValueAtTime( _orientation.y, endTime ); + panner.orientationZ.linearRampToValueAtTime( _orientation.z, endTime ); + + } else { + + panner.setPosition( _position.x, _position.y, _position.z ); + panner.setOrientation( _orientation.x, _orientation.y, _orientation.z ); + + } + + } + +} + +class AudioAnalyser { + + constructor( audio, fftSize = 2048 ) { + + this.analyser = audio.context.createAnalyser(); + this.analyser.fftSize = fftSize; + + this.data = new Uint8Array( this.analyser.frequencyBinCount ); + + audio.getOutput().connect( this.analyser ); + + } + + + getFrequencyData() { + + this.analyser.getByteFrequencyData( this.data ); + + return this.data; + + } + + getAverageFrequency() { + + let value = 0; + const data = this.getFrequencyData(); + + for ( let i = 0; i < data.length; i ++ ) { + + value += data[ i ]; + + } + + return value / data.length; + + } + +} + +class PropertyMixer { + + constructor( binding, typeName, valueSize ) { + + this.binding = binding; + this.valueSize = valueSize; + + let mixFunction, + mixFunctionAdditive, + setIdentity; + + // buffer layout: [ incoming | accu0 | accu1 | orig | addAccu | (optional work) ] + // + // interpolators can use .buffer as their .result + // the data then goes to 'incoming' + // + // 'accu0' and 'accu1' are used frame-interleaved for + // the cumulative result and are compared to detect + // changes + // + // 'orig' stores the original state of the property + // + // 'add' is used for additive cumulative results + // + // 'work' is optional and is only present for quaternion types. It is used + // to store intermediate quaternion multiplication results + + switch ( typeName ) { + + case 'quaternion': + mixFunction = this._slerp; + mixFunctionAdditive = this._slerpAdditive; + setIdentity = this._setAdditiveIdentityQuaternion; + + this.buffer = new Float64Array( valueSize * 6 ); + this._workIndex = 5; + break; + + case 'string': + case 'bool': + mixFunction = this._select; + + // Use the regular mix function and for additive on these types, + // additive is not relevant for non-numeric types + mixFunctionAdditive = this._select; + + setIdentity = this._setAdditiveIdentityOther; + + this.buffer = new Array( valueSize * 5 ); + break; + + default: + mixFunction = this._lerp; + mixFunctionAdditive = this._lerpAdditive; + setIdentity = this._setAdditiveIdentityNumeric; + + this.buffer = new Float64Array( valueSize * 5 ); + + } + + this._mixBufferRegion = mixFunction; + this._mixBufferRegionAdditive = mixFunctionAdditive; + this._setIdentity = setIdentity; + this._origIndex = 3; + this._addIndex = 4; + + this.cumulativeWeight = 0; + this.cumulativeWeightAdditive = 0; + + this.useCount = 0; + this.referenceCount = 0; + + } + + // accumulate data in the 'incoming' region into 'accu' + accumulate( accuIndex, weight ) { + + // note: happily accumulating nothing when weight = 0, the caller knows + // the weight and shouldn't have made the call in the first place + + const buffer = this.buffer, + stride = this.valueSize, + offset = accuIndex * stride + stride; + + let currentWeight = this.cumulativeWeight; + + if ( currentWeight === 0 ) { + + // accuN := incoming * weight + + for ( let i = 0; i !== stride; ++ i ) { + + buffer[ offset + i ] = buffer[ i ]; + + } + + currentWeight = weight; + + } else { + + // accuN := accuN + incoming * weight + + currentWeight += weight; + const mix = weight / currentWeight; + this._mixBufferRegion( buffer, offset, 0, mix, stride ); + + } + + this.cumulativeWeight = currentWeight; + + } + + // accumulate data in the 'incoming' region into 'add' + accumulateAdditive( weight ) { + + const buffer = this.buffer, + stride = this.valueSize, + offset = stride * this._addIndex; + + if ( this.cumulativeWeightAdditive === 0 ) { + + // add = identity + + this._setIdentity(); + + } + + // add := add + incoming * weight + + this._mixBufferRegionAdditive( buffer, offset, 0, weight, stride ); + this.cumulativeWeightAdditive += weight; + + } + + // apply the state of 'accu' to the binding when accus differ + apply( accuIndex ) { + + const stride = this.valueSize, + buffer = this.buffer, + offset = accuIndex * stride + stride, + + weight = this.cumulativeWeight, + weightAdditive = this.cumulativeWeightAdditive, + + binding = this.binding; + + this.cumulativeWeight = 0; + this.cumulativeWeightAdditive = 0; + + if ( weight < 1 ) { + + // accuN := accuN + original * ( 1 - cumulativeWeight ) + + const originalValueOffset = stride * this._origIndex; + + this._mixBufferRegion( + buffer, offset, originalValueOffset, 1 - weight, stride ); + + } + + if ( weightAdditive > 0 ) { + + // accuN := accuN + additive accuN + + this._mixBufferRegionAdditive( buffer, offset, this._addIndex * stride, 1, stride ); + + } + + for ( let i = stride, e = stride + stride; i !== e; ++ i ) { + + if ( buffer[ i ] !== buffer[ i + stride ] ) { + + // value has changed -> update scene graph + + binding.setValue( buffer, offset ); + break; + + } + + } + + } + + // remember the state of the bound property and copy it to both accus + saveOriginalState() { + + const binding = this.binding; + + const buffer = this.buffer, + stride = this.valueSize, + + originalValueOffset = stride * this._origIndex; + + binding.getValue( buffer, originalValueOffset ); + + // accu[0..1] := orig -- initially detect changes against the original + for ( let i = stride, e = originalValueOffset; i !== e; ++ i ) { + + buffer[ i ] = buffer[ originalValueOffset + ( i % stride ) ]; + + } + + // Add to identity for additive + this._setIdentity(); + + this.cumulativeWeight = 0; + this.cumulativeWeightAdditive = 0; + + } + + // apply the state previously taken via 'saveOriginalState' to the binding + restoreOriginalState() { + + const originalValueOffset = this.valueSize * 3; + this.binding.setValue( this.buffer, originalValueOffset ); + + } + + _setAdditiveIdentityNumeric() { + + const startIndex = this._addIndex * this.valueSize; + const endIndex = startIndex + this.valueSize; + + for ( let i = startIndex; i < endIndex; i ++ ) { + + this.buffer[ i ] = 0; + + } + + } + + _setAdditiveIdentityQuaternion() { + + this._setAdditiveIdentityNumeric(); + this.buffer[ this._addIndex * this.valueSize + 3 ] = 1; + + } + + _setAdditiveIdentityOther() { + + const startIndex = this._origIndex * this.valueSize; + const targetIndex = this._addIndex * this.valueSize; + + for ( let i = 0; i < this.valueSize; i ++ ) { + + this.buffer[ targetIndex + i ] = this.buffer[ startIndex + i ]; + + } + + } + + + // mix functions + + _select( buffer, dstOffset, srcOffset, t, stride ) { + + if ( t >= 0.5 ) { + + for ( let i = 0; i !== stride; ++ i ) { + + buffer[ dstOffset + i ] = buffer[ srcOffset + i ]; + + } + + } + + } + + _slerp( buffer, dstOffset, srcOffset, t ) { + + Quaternion.slerpFlat( buffer, dstOffset, buffer, dstOffset, buffer, srcOffset, t ); + + } + + _slerpAdditive( buffer, dstOffset, srcOffset, t, stride ) { + + const workOffset = this._workIndex * stride; + + // Store result in intermediate buffer offset + Quaternion.multiplyQuaternionsFlat( buffer, workOffset, buffer, dstOffset, buffer, srcOffset ); + + // Slerp to the intermediate result + Quaternion.slerpFlat( buffer, dstOffset, buffer, dstOffset, buffer, workOffset, t ); + + } + + _lerp( buffer, dstOffset, srcOffset, t, stride ) { + + const s = 1 - t; + + for ( let i = 0; i !== stride; ++ i ) { + + const j = dstOffset + i; + + buffer[ j ] = buffer[ j ] * s + buffer[ srcOffset + i ] * t; + + } + + } + + _lerpAdditive( buffer, dstOffset, srcOffset, t, stride ) { + + for ( let i = 0; i !== stride; ++ i ) { + + const j = dstOffset + i; + + buffer[ j ] = buffer[ j ] + buffer[ srcOffset + i ] * t; + + } + + } + +} + +// Characters [].:/ are reserved for track binding syntax. +const _RESERVED_CHARS_RE = '\\[\\]\\.:\\/'; +const _reservedRe = new RegExp( '[' + _RESERVED_CHARS_RE + ']', 'g' ); + +// Attempts to allow node names from any language. ES5's `\w` regexp matches +// only latin characters, and the unicode \p{L} is not yet supported. So +// instead, we exclude reserved characters and match everything else. +const _wordChar = '[^' + _RESERVED_CHARS_RE + ']'; +const _wordCharOrDot = '[^' + _RESERVED_CHARS_RE.replace( '\\.', '' ) + ']'; + +// Parent directories, delimited by '/' or ':'. Currently unused, but must +// be matched to parse the rest of the track name. +const _directoryRe = /*@__PURE__*/ /((?:WC+[\/:])*)/.source.replace( 'WC', _wordChar ); + +// Target node. May contain word characters (a-zA-Z0-9_) and '.' or '-'. +const _nodeRe = /*@__PURE__*/ /(WCOD+)?/.source.replace( 'WCOD', _wordCharOrDot ); + +// Object on target node, and accessor. May not contain reserved +// characters. Accessor may contain any character except closing bracket. +const _objectRe = /*@__PURE__*/ /(?:\.(WC+)(?:\[(.+)\])?)?/.source.replace( 'WC', _wordChar ); + +// Property and accessor. May not contain reserved characters. Accessor may +// contain any non-bracket characters. +const _propertyRe = /*@__PURE__*/ /\.(WC+)(?:\[(.+)\])?/.source.replace( 'WC', _wordChar ); + +const _trackRe = new RegExp( '' + + '^' + + _directoryRe + + _nodeRe + + _objectRe + + _propertyRe + + '$' +); + +const _supportedObjectNames = [ 'material', 'materials', 'bones', 'map' ]; + +class Composite { + + constructor( targetGroup, path, optionalParsedPath ) { + + const parsedPath = optionalParsedPath || PropertyBinding.parseTrackName( path ); + + this._targetGroup = targetGroup; + this._bindings = targetGroup.subscribe_( path, parsedPath ); + + } + + getValue( array, offset ) { + + this.bind(); // bind all binding + + const firstValidIndex = this._targetGroup.nCachedObjects_, + binding = this._bindings[ firstValidIndex ]; + + // and only call .getValue on the first + if ( binding !== undefined ) binding.getValue( array, offset ); + + } + + setValue( array, offset ) { + + const bindings = this._bindings; + + for ( let i = this._targetGroup.nCachedObjects_, n = bindings.length; i !== n; ++ i ) { + + bindings[ i ].setValue( array, offset ); + + } + + } + + bind() { + + const bindings = this._bindings; + + for ( let i = this._targetGroup.nCachedObjects_, n = bindings.length; i !== n; ++ i ) { + + bindings[ i ].bind(); + + } + + } + + unbind() { + + const bindings = this._bindings; + + for ( let i = this._targetGroup.nCachedObjects_, n = bindings.length; i !== n; ++ i ) { + + bindings[ i ].unbind(); + + } + + } + +} + +// Note: This class uses a State pattern on a per-method basis: +// 'bind' sets 'this.getValue' / 'setValue' and shadows the +// prototype version of these methods with one that represents +// the bound state. When the property is not found, the methods +// become no-ops. +class PropertyBinding { + + constructor( rootNode, path, parsedPath ) { + + this.path = path; + this.parsedPath = parsedPath || PropertyBinding.parseTrackName( path ); + + this.node = PropertyBinding.findNode( rootNode, this.parsedPath.nodeName ); + + this.rootNode = rootNode; + + // initial state of these methods that calls 'bind' + this.getValue = this._getValue_unbound; + this.setValue = this._setValue_unbound; + + } + + + static create( root, path, parsedPath ) { + + if ( ! ( root && root.isAnimationObjectGroup ) ) { + + return new PropertyBinding( root, path, parsedPath ); + + } else { + + return new PropertyBinding.Composite( root, path, parsedPath ); + + } + + } + + /** + * Replaces spaces with underscores and removes unsupported characters from + * node names, to ensure compatibility with parseTrackName(). + * + * @param {string} name Node name to be sanitized. + * @return {string} + */ + static sanitizeNodeName( name ) { + + return name.replace( /\s/g, '_' ).replace( _reservedRe, '' ); + + } + + static parseTrackName( trackName ) { + + const matches = _trackRe.exec( trackName ); + + if ( matches === null ) { + + throw new Error( 'PropertyBinding: Cannot parse trackName: ' + trackName ); + + } + + const results = { + // directoryName: matches[ 1 ], // (tschw) currently unused + nodeName: matches[ 2 ], + objectName: matches[ 3 ], + objectIndex: matches[ 4 ], + propertyName: matches[ 5 ], // required + propertyIndex: matches[ 6 ] + }; + + const lastDot = results.nodeName && results.nodeName.lastIndexOf( '.' ); + + if ( lastDot !== undefined && lastDot !== - 1 ) { + + const objectName = results.nodeName.substring( lastDot + 1 ); + + // Object names must be checked against an allowlist. Otherwise, there + // is no way to parse 'foo.bar.baz': 'baz' must be a property, but + // 'bar' could be the objectName, or part of a nodeName (which can + // include '.' characters). + if ( _supportedObjectNames.indexOf( objectName ) !== - 1 ) { + + results.nodeName = results.nodeName.substring( 0, lastDot ); + results.objectName = objectName; + + } + + } + + if ( results.propertyName === null || results.propertyName.length === 0 ) { + + throw new Error( 'PropertyBinding: can not parse propertyName from trackName: ' + trackName ); + + } + + return results; + + } + + static findNode( root, nodeName ) { + + if ( nodeName === undefined || nodeName === '' || nodeName === '.' || nodeName === - 1 || nodeName === root.name || nodeName === root.uuid ) { + + return root; + + } + + // search into skeleton bones. + if ( root.skeleton ) { + + const bone = root.skeleton.getBoneByName( nodeName ); + + if ( bone !== undefined ) { + + return bone; + + } + + } + + // search into node subtree. + if ( root.children ) { + + const searchNodeSubtree = function ( children ) { + + for ( let i = 0; i < children.length; i ++ ) { + + const childNode = children[ i ]; + + if ( childNode.name === nodeName || childNode.uuid === nodeName ) { + + return childNode; + + } + + const result = searchNodeSubtree( childNode.children ); + + if ( result ) return result; + + } + + return null; + + }; + + const subTreeNode = searchNodeSubtree( root.children ); + + if ( subTreeNode ) { + + return subTreeNode; + + } + + } + + return null; + + } + + // these are used to "bind" a nonexistent property + _getValue_unavailable() {} + _setValue_unavailable() {} + + // Getters + + _getValue_direct( buffer, offset ) { + + buffer[ offset ] = this.targetObject[ this.propertyName ]; + + } + + _getValue_array( buffer, offset ) { + + const source = this.resolvedProperty; + + for ( let i = 0, n = source.length; i !== n; ++ i ) { + + buffer[ offset ++ ] = source[ i ]; + + } + + } + + _getValue_arrayElement( buffer, offset ) { + + buffer[ offset ] = this.resolvedProperty[ this.propertyIndex ]; + + } + + _getValue_toArray( buffer, offset ) { + + this.resolvedProperty.toArray( buffer, offset ); + + } + + // Direct + + _setValue_direct( buffer, offset ) { + + this.targetObject[ this.propertyName ] = buffer[ offset ]; + + } + + _setValue_direct_setNeedsUpdate( buffer, offset ) { + + this.targetObject[ this.propertyName ] = buffer[ offset ]; + this.targetObject.needsUpdate = true; + + } + + _setValue_direct_setMatrixWorldNeedsUpdate( buffer, offset ) { + + this.targetObject[ this.propertyName ] = buffer[ offset ]; + this.targetObject.matrixWorldNeedsUpdate = true; + + } + + // EntireArray + + _setValue_array( buffer, offset ) { + + const dest = this.resolvedProperty; + + for ( let i = 0, n = dest.length; i !== n; ++ i ) { + + dest[ i ] = buffer[ offset ++ ]; + + } + + } + + _setValue_array_setNeedsUpdate( buffer, offset ) { + + const dest = this.resolvedProperty; + + for ( let i = 0, n = dest.length; i !== n; ++ i ) { + + dest[ i ] = buffer[ offset ++ ]; + + } + + this.targetObject.needsUpdate = true; + + } + + _setValue_array_setMatrixWorldNeedsUpdate( buffer, offset ) { + + const dest = this.resolvedProperty; + + for ( let i = 0, n = dest.length; i !== n; ++ i ) { + + dest[ i ] = buffer[ offset ++ ]; + + } + + this.targetObject.matrixWorldNeedsUpdate = true; + + } + + // ArrayElement + + _setValue_arrayElement( buffer, offset ) { + + this.resolvedProperty[ this.propertyIndex ] = buffer[ offset ]; + + } + + _setValue_arrayElement_setNeedsUpdate( buffer, offset ) { + + this.resolvedProperty[ this.propertyIndex ] = buffer[ offset ]; + this.targetObject.needsUpdate = true; + + } + + _setValue_arrayElement_setMatrixWorldNeedsUpdate( buffer, offset ) { + + this.resolvedProperty[ this.propertyIndex ] = buffer[ offset ]; + this.targetObject.matrixWorldNeedsUpdate = true; + + } + + // HasToFromArray + + _setValue_fromArray( buffer, offset ) { + + this.resolvedProperty.fromArray( buffer, offset ); + + } + + _setValue_fromArray_setNeedsUpdate( buffer, offset ) { + + this.resolvedProperty.fromArray( buffer, offset ); + this.targetObject.needsUpdate = true; + + } + + _setValue_fromArray_setMatrixWorldNeedsUpdate( buffer, offset ) { + + this.resolvedProperty.fromArray( buffer, offset ); + this.targetObject.matrixWorldNeedsUpdate = true; + + } + + _getValue_unbound( targetArray, offset ) { + + this.bind(); + this.getValue( targetArray, offset ); + + } + + _setValue_unbound( sourceArray, offset ) { + + this.bind(); + this.setValue( sourceArray, offset ); + + } + + // create getter / setter pair for a property in the scene graph + bind() { + + let targetObject = this.node; + const parsedPath = this.parsedPath; + + const objectName = parsedPath.objectName; + const propertyName = parsedPath.propertyName; + let propertyIndex = parsedPath.propertyIndex; + + if ( ! targetObject ) { + + targetObject = PropertyBinding.findNode( this.rootNode, parsedPath.nodeName ); + + this.node = targetObject; + + } + + // set fail state so we can just 'return' on error + this.getValue = this._getValue_unavailable; + this.setValue = this._setValue_unavailable; + + // ensure there is a value node + if ( ! targetObject ) { + + console.warn( 'THREE.PropertyBinding: No target node found for track: ' + this.path + '.' ); + return; + + } + + if ( objectName ) { + + let objectIndex = parsedPath.objectIndex; + + // special cases were we need to reach deeper into the hierarchy to get the face materials.... + switch ( objectName ) { + + case 'materials': + + if ( ! targetObject.material ) { + + console.error( 'THREE.PropertyBinding: Can not bind to material as node does not have a material.', this ); + return; + + } + + if ( ! targetObject.material.materials ) { + + console.error( 'THREE.PropertyBinding: Can not bind to material.materials as node.material does not have a materials array.', this ); + return; + + } + + targetObject = targetObject.material.materials; + + break; + + case 'bones': + + if ( ! targetObject.skeleton ) { + + console.error( 'THREE.PropertyBinding: Can not bind to bones as node does not have a skeleton.', this ); + return; + + } + + // potential future optimization: skip this if propertyIndex is already an integer + // and convert the integer string to a true integer. + + targetObject = targetObject.skeleton.bones; + + // support resolving morphTarget names into indices. + for ( let i = 0; i < targetObject.length; i ++ ) { + + if ( targetObject[ i ].name === objectIndex ) { + + objectIndex = i; + break; + + } + + } + + break; + + case 'map': + + if ( 'map' in targetObject ) { + + targetObject = targetObject.map; + break; + + } + + if ( ! targetObject.material ) { + + console.error( 'THREE.PropertyBinding: Can not bind to material as node does not have a material.', this ); + return; + + } + + if ( ! targetObject.material.map ) { + + console.error( 'THREE.PropertyBinding: Can not bind to material.map as node.material does not have a map.', this ); + return; + + } + + targetObject = targetObject.material.map; + break; + + default: + + if ( targetObject[ objectName ] === undefined ) { + + console.error( 'THREE.PropertyBinding: Can not bind to objectName of node undefined.', this ); + return; + + } + + targetObject = targetObject[ objectName ]; + + } + + + if ( objectIndex !== undefined ) { + + if ( targetObject[ objectIndex ] === undefined ) { + + console.error( 'THREE.PropertyBinding: Trying to bind to objectIndex of objectName, but is undefined.', this, targetObject ); + return; + + } + + targetObject = targetObject[ objectIndex ]; + + } + + } + + // resolve property + const nodeProperty = targetObject[ propertyName ]; + + if ( nodeProperty === undefined ) { + + const nodeName = parsedPath.nodeName; + + console.error( 'THREE.PropertyBinding: Trying to update property for track: ' + nodeName + + '.' + propertyName + ' but it wasn\'t found.', targetObject ); + return; + + } + + // determine versioning scheme + let versioning = this.Versioning.None; + + this.targetObject = targetObject; + + if ( targetObject.needsUpdate !== undefined ) { // material + + versioning = this.Versioning.NeedsUpdate; + + } else if ( targetObject.matrixWorldNeedsUpdate !== undefined ) { // node transform + + versioning = this.Versioning.MatrixWorldNeedsUpdate; + + } + + // determine how the property gets bound + let bindingType = this.BindingType.Direct; + + if ( propertyIndex !== undefined ) { + + // access a sub element of the property array (only primitives are supported right now) + + if ( propertyName === 'morphTargetInfluences' ) { + + // potential optimization, skip this if propertyIndex is already an integer, and convert the integer string to a true integer. + + // support resolving morphTarget names into indices. + if ( ! targetObject.geometry ) { + + console.error( 'THREE.PropertyBinding: Can not bind to morphTargetInfluences because node does not have a geometry.', this ); + return; + + } + + if ( ! targetObject.geometry.morphAttributes ) { + + console.error( 'THREE.PropertyBinding: Can not bind to morphTargetInfluences because node does not have a geometry.morphAttributes.', this ); + return; + + } + + if ( targetObject.morphTargetDictionary[ propertyIndex ] !== undefined ) { + + propertyIndex = targetObject.morphTargetDictionary[ propertyIndex ]; + + } + + } + + bindingType = this.BindingType.ArrayElement; + + this.resolvedProperty = nodeProperty; + this.propertyIndex = propertyIndex; + + } else if ( nodeProperty.fromArray !== undefined && nodeProperty.toArray !== undefined ) { + + // must use copy for Object3D.Euler/Quaternion + + bindingType = this.BindingType.HasFromToArray; + + this.resolvedProperty = nodeProperty; + + } else if ( Array.isArray( nodeProperty ) ) { + + bindingType = this.BindingType.EntireArray; + + this.resolvedProperty = nodeProperty; + + } else { + + this.propertyName = propertyName; + + } + + // select getter / setter + this.getValue = this.GetterByBindingType[ bindingType ]; + this.setValue = this.SetterByBindingTypeAndVersioning[ bindingType ][ versioning ]; + + } + + unbind() { + + this.node = null; + + // back to the prototype version of getValue / setValue + // note: avoiding to mutate the shape of 'this' via 'delete' + this.getValue = this._getValue_unbound; + this.setValue = this._setValue_unbound; + + } + +} + +PropertyBinding.Composite = Composite; + +PropertyBinding.prototype.BindingType = { + Direct: 0, + EntireArray: 1, + ArrayElement: 2, + HasFromToArray: 3 +}; + +PropertyBinding.prototype.Versioning = { + None: 0, + NeedsUpdate: 1, + MatrixWorldNeedsUpdate: 2 +}; + +PropertyBinding.prototype.GetterByBindingType = [ + + PropertyBinding.prototype._getValue_direct, + PropertyBinding.prototype._getValue_array, + PropertyBinding.prototype._getValue_arrayElement, + PropertyBinding.prototype._getValue_toArray, + +]; + +PropertyBinding.prototype.SetterByBindingTypeAndVersioning = [ + + [ + // Direct + PropertyBinding.prototype._setValue_direct, + PropertyBinding.prototype._setValue_direct_setNeedsUpdate, + PropertyBinding.prototype._setValue_direct_setMatrixWorldNeedsUpdate, + + ], [ + + // EntireArray + + PropertyBinding.prototype._setValue_array, + PropertyBinding.prototype._setValue_array_setNeedsUpdate, + PropertyBinding.prototype._setValue_array_setMatrixWorldNeedsUpdate, + + ], [ + + // ArrayElement + PropertyBinding.prototype._setValue_arrayElement, + PropertyBinding.prototype._setValue_arrayElement_setNeedsUpdate, + PropertyBinding.prototype._setValue_arrayElement_setMatrixWorldNeedsUpdate, + + ], [ + + // HasToFromArray + PropertyBinding.prototype._setValue_fromArray, + PropertyBinding.prototype._setValue_fromArray_setNeedsUpdate, + PropertyBinding.prototype._setValue_fromArray_setMatrixWorldNeedsUpdate, + + ] + +]; + +/** + * + * A group of objects that receives a shared animation state. + * + * Usage: + * + * - Add objects you would otherwise pass as 'root' to the + * constructor or the .clipAction method of AnimationMixer. + * + * - Instead pass this object as 'root'. + * + * - You can also add and remove objects later when the mixer + * is running. + * + * Note: + * + * Objects of this class appear as one object to the mixer, + * so cache control of the individual objects must be done + * on the group. + * + * Limitation: + * + * - The animated properties must be compatible among the + * all objects in the group. + * + * - A single property can either be controlled through a + * target group or directly, but not both. + */ + +class AnimationObjectGroup { + + constructor() { + + this.isAnimationObjectGroup = true; + + this.uuid = generateUUID(); + + // cached objects followed by the active ones + this._objects = Array.prototype.slice.call( arguments ); + + this.nCachedObjects_ = 0; // threshold + // note: read by PropertyBinding.Composite + + const indices = {}; + this._indicesByUUID = indices; // for bookkeeping + + for ( let i = 0, n = arguments.length; i !== n; ++ i ) { + + indices[ arguments[ i ].uuid ] = i; + + } + + this._paths = []; // inside: string + this._parsedPaths = []; // inside: { we don't care, here } + this._bindings = []; // inside: Array< PropertyBinding > + this._bindingsIndicesByPath = {}; // inside: indices in these arrays + + const scope = this; + + this.stats = { + + objects: { + get total() { + + return scope._objects.length; + + }, + get inUse() { + + return this.total - scope.nCachedObjects_; + + } + }, + get bindingsPerObject() { + + return scope._bindings.length; + + } + + }; + + } + + add() { + + const objects = this._objects, + indicesByUUID = this._indicesByUUID, + paths = this._paths, + parsedPaths = this._parsedPaths, + bindings = this._bindings, + nBindings = bindings.length; + + let knownObject = undefined, + nObjects = objects.length, + nCachedObjects = this.nCachedObjects_; + + for ( let i = 0, n = arguments.length; i !== n; ++ i ) { + + const object = arguments[ i ], + uuid = object.uuid; + let index = indicesByUUID[ uuid ]; + + if ( index === undefined ) { + + // unknown object -> add it to the ACTIVE region + + index = nObjects ++; + indicesByUUID[ uuid ] = index; + objects.push( object ); + + // accounting is done, now do the same for all bindings + + for ( let j = 0, m = nBindings; j !== m; ++ j ) { + + bindings[ j ].push( new PropertyBinding( object, paths[ j ], parsedPaths[ j ] ) ); + + } + + } else if ( index < nCachedObjects ) { + + knownObject = objects[ index ]; + + // move existing object to the ACTIVE region + + const firstActiveIndex = -- nCachedObjects, + lastCachedObject = objects[ firstActiveIndex ]; + + indicesByUUID[ lastCachedObject.uuid ] = index; + objects[ index ] = lastCachedObject; + + indicesByUUID[ uuid ] = firstActiveIndex; + objects[ firstActiveIndex ] = object; + + // accounting is done, now do the same for all bindings + + for ( let j = 0, m = nBindings; j !== m; ++ j ) { + + const bindingsForPath = bindings[ j ], + lastCached = bindingsForPath[ firstActiveIndex ]; + + let binding = bindingsForPath[ index ]; + + bindingsForPath[ index ] = lastCached; + + if ( binding === undefined ) { + + // since we do not bother to create new bindings + // for objects that are cached, the binding may + // or may not exist + + binding = new PropertyBinding( object, paths[ j ], parsedPaths[ j ] ); + + } + + bindingsForPath[ firstActiveIndex ] = binding; + + } + + } else if ( objects[ index ] !== knownObject ) { + + console.error( 'THREE.AnimationObjectGroup: Different objects with the same UUID ' + + 'detected. Clean the caches or recreate your infrastructure when reloading scenes.' ); + + } // else the object is already where we want it to be + + } // for arguments + + this.nCachedObjects_ = nCachedObjects; + + } + + remove() { + + const objects = this._objects, + indicesByUUID = this._indicesByUUID, + bindings = this._bindings, + nBindings = bindings.length; + + let nCachedObjects = this.nCachedObjects_; + + for ( let i = 0, n = arguments.length; i !== n; ++ i ) { + + const object = arguments[ i ], + uuid = object.uuid, + index = indicesByUUID[ uuid ]; + + if ( index !== undefined && index >= nCachedObjects ) { + + // move existing object into the CACHED region + + const lastCachedIndex = nCachedObjects ++, + firstActiveObject = objects[ lastCachedIndex ]; + + indicesByUUID[ firstActiveObject.uuid ] = index; + objects[ index ] = firstActiveObject; + + indicesByUUID[ uuid ] = lastCachedIndex; + objects[ lastCachedIndex ] = object; + + // accounting is done, now do the same for all bindings + + for ( let j = 0, m = nBindings; j !== m; ++ j ) { + + const bindingsForPath = bindings[ j ], + firstActive = bindingsForPath[ lastCachedIndex ], + binding = bindingsForPath[ index ]; + + bindingsForPath[ index ] = firstActive; + bindingsForPath[ lastCachedIndex ] = binding; + + } + + } + + } // for arguments + + this.nCachedObjects_ = nCachedObjects; + + } + + // remove & forget + uncache() { + + const objects = this._objects, + indicesByUUID = this._indicesByUUID, + bindings = this._bindings, + nBindings = bindings.length; + + let nCachedObjects = this.nCachedObjects_, + nObjects = objects.length; + + for ( let i = 0, n = arguments.length; i !== n; ++ i ) { + + const object = arguments[ i ], + uuid = object.uuid, + index = indicesByUUID[ uuid ]; + + if ( index !== undefined ) { + + delete indicesByUUID[ uuid ]; + + if ( index < nCachedObjects ) { + + // object is cached, shrink the CACHED region + + const firstActiveIndex = -- nCachedObjects, + lastCachedObject = objects[ firstActiveIndex ], + lastIndex = -- nObjects, + lastObject = objects[ lastIndex ]; + + // last cached object takes this object's place + indicesByUUID[ lastCachedObject.uuid ] = index; + objects[ index ] = lastCachedObject; + + // last object goes to the activated slot and pop + indicesByUUID[ lastObject.uuid ] = firstActiveIndex; + objects[ firstActiveIndex ] = lastObject; + objects.pop(); + + // accounting is done, now do the same for all bindings + + for ( let j = 0, m = nBindings; j !== m; ++ j ) { + + const bindingsForPath = bindings[ j ], + lastCached = bindingsForPath[ firstActiveIndex ], + last = bindingsForPath[ lastIndex ]; + + bindingsForPath[ index ] = lastCached; + bindingsForPath[ firstActiveIndex ] = last; + bindingsForPath.pop(); + + } + + } else { + + // object is active, just swap with the last and pop + + const lastIndex = -- nObjects, + lastObject = objects[ lastIndex ]; + + if ( lastIndex > 0 ) { + + indicesByUUID[ lastObject.uuid ] = index; + + } + + objects[ index ] = lastObject; + objects.pop(); + + // accounting is done, now do the same for all bindings + + for ( let j = 0, m = nBindings; j !== m; ++ j ) { + + const bindingsForPath = bindings[ j ]; + + bindingsForPath[ index ] = bindingsForPath[ lastIndex ]; + bindingsForPath.pop(); + + } + + } // cached or active + + } // if object is known + + } // for arguments + + this.nCachedObjects_ = nCachedObjects; + + } + + // Internal interface used by befriended PropertyBinding.Composite: + + subscribe_( path, parsedPath ) { + + // returns an array of bindings for the given path that is changed + // according to the contained objects in the group + + const indicesByPath = this._bindingsIndicesByPath; + let index = indicesByPath[ path ]; + const bindings = this._bindings; + + if ( index !== undefined ) return bindings[ index ]; + + const paths = this._paths, + parsedPaths = this._parsedPaths, + objects = this._objects, + nObjects = objects.length, + nCachedObjects = this.nCachedObjects_, + bindingsForPath = new Array( nObjects ); + + index = bindings.length; + + indicesByPath[ path ] = index; + + paths.push( path ); + parsedPaths.push( parsedPath ); + bindings.push( bindingsForPath ); + + for ( let i = nCachedObjects, n = objects.length; i !== n; ++ i ) { + + const object = objects[ i ]; + bindingsForPath[ i ] = new PropertyBinding( object, path, parsedPath ); + + } + + return bindingsForPath; + + } + + unsubscribe_( path ) { + + // tells the group to forget about a property path and no longer + // update the array previously obtained with 'subscribe_' + + const indicesByPath = this._bindingsIndicesByPath, + index = indicesByPath[ path ]; + + if ( index !== undefined ) { + + const paths = this._paths, + parsedPaths = this._parsedPaths, + bindings = this._bindings, + lastBindingsIndex = bindings.length - 1, + lastBindings = bindings[ lastBindingsIndex ], + lastBindingsPath = path[ lastBindingsIndex ]; + + indicesByPath[ lastBindingsPath ] = index; + + bindings[ index ] = lastBindings; + bindings.pop(); + + parsedPaths[ index ] = parsedPaths[ lastBindingsIndex ]; + parsedPaths.pop(); + + paths[ index ] = paths[ lastBindingsIndex ]; + paths.pop(); + + } + + } + +} + +class AnimationAction { + + constructor( mixer, clip, localRoot = null, blendMode = clip.blendMode ) { + + this._mixer = mixer; + this._clip = clip; + this._localRoot = localRoot; + this.blendMode = blendMode; + + const tracks = clip.tracks, + nTracks = tracks.length, + interpolants = new Array( nTracks ); + + const interpolantSettings = { + endingStart: ZeroCurvatureEnding, + endingEnd: ZeroCurvatureEnding + }; + + for ( let i = 0; i !== nTracks; ++ i ) { + + const interpolant = tracks[ i ].createInterpolant( null ); + interpolants[ i ] = interpolant; + interpolant.settings = interpolantSettings; + + } + + this._interpolantSettings = interpolantSettings; + + this._interpolants = interpolants; // bound by the mixer + + // inside: PropertyMixer (managed by the mixer) + this._propertyBindings = new Array( nTracks ); + + this._cacheIndex = null; // for the memory manager + this._byClipCacheIndex = null; // for the memory manager + + this._timeScaleInterpolant = null; + this._weightInterpolant = null; + + this.loop = LoopRepeat; + this._loopCount = - 1; + + // global mixer time when the action is to be started + // it's set back to 'null' upon start of the action + this._startTime = null; + + // scaled local time of the action + // gets clamped or wrapped to 0..clip.duration according to loop + this.time = 0; + + this.timeScale = 1; + this._effectiveTimeScale = 1; + + this.weight = 1; + this._effectiveWeight = 1; + + this.repetitions = Infinity; // no. of repetitions when looping + + this.paused = false; // true -> zero effective time scale + this.enabled = true; // false -> zero effective weight + + this.clampWhenFinished = false;// keep feeding the last frame? + + this.zeroSlopeAtStart = true;// for smooth interpolation w/o separate + this.zeroSlopeAtEnd = true;// clips for start, loop and end + + } + + // State & Scheduling + + play() { + + this._mixer._activateAction( this ); + + return this; + + } + + stop() { + + this._mixer._deactivateAction( this ); + + return this.reset(); + + } + + reset() { + + this.paused = false; + this.enabled = true; + + this.time = 0; // restart clip + this._loopCount = - 1;// forget previous loops + this._startTime = null;// forget scheduling + + return this.stopFading().stopWarping(); + + } + + isRunning() { + + return this.enabled && ! this.paused && this.timeScale !== 0 && + this._startTime === null && this._mixer._isActiveAction( this ); + + } + + // return true when play has been called + isScheduled() { + + return this._mixer._isActiveAction( this ); + + } + + startAt( time ) { + + this._startTime = time; + + return this; + + } + + setLoop( mode, repetitions ) { + + this.loop = mode; + this.repetitions = repetitions; + + return this; + + } + + // Weight + + // set the weight stopping any scheduled fading + // although .enabled = false yields an effective weight of zero, this + // method does *not* change .enabled, because it would be confusing + setEffectiveWeight( weight ) { + + this.weight = weight; + + // note: same logic as when updated at runtime + this._effectiveWeight = this.enabled ? weight : 0; + + return this.stopFading(); + + } + + // return the weight considering fading and .enabled + getEffectiveWeight() { + + return this._effectiveWeight; + + } + + fadeIn( duration ) { + + return this._scheduleFading( duration, 0, 1 ); + + } + + fadeOut( duration ) { + + return this._scheduleFading( duration, 1, 0 ); + + } + + crossFadeFrom( fadeOutAction, duration, warp ) { + + fadeOutAction.fadeOut( duration ); + this.fadeIn( duration ); + + if ( warp ) { + + const fadeInDuration = this._clip.duration, + fadeOutDuration = fadeOutAction._clip.duration, + + startEndRatio = fadeOutDuration / fadeInDuration, + endStartRatio = fadeInDuration / fadeOutDuration; + + fadeOutAction.warp( 1.0, startEndRatio, duration ); + this.warp( endStartRatio, 1.0, duration ); + + } + + return this; + + } + + crossFadeTo( fadeInAction, duration, warp ) { + + return fadeInAction.crossFadeFrom( this, duration, warp ); + + } + + stopFading() { + + const weightInterpolant = this._weightInterpolant; + + if ( weightInterpolant !== null ) { + + this._weightInterpolant = null; + this._mixer._takeBackControlInterpolant( weightInterpolant ); + + } + + return this; + + } + + // Time Scale Control + + // set the time scale stopping any scheduled warping + // although .paused = true yields an effective time scale of zero, this + // method does *not* change .paused, because it would be confusing + setEffectiveTimeScale( timeScale ) { + + this.timeScale = timeScale; + this._effectiveTimeScale = this.paused ? 0 : timeScale; + + return this.stopWarping(); + + } + + // return the time scale considering warping and .paused + getEffectiveTimeScale() { + + return this._effectiveTimeScale; + + } + + setDuration( duration ) { + + this.timeScale = this._clip.duration / duration; + + return this.stopWarping(); + + } + + syncWith( action ) { + + this.time = action.time; + this.timeScale = action.timeScale; + + return this.stopWarping(); + + } + + halt( duration ) { + + return this.warp( this._effectiveTimeScale, 0, duration ); + + } + + warp( startTimeScale, endTimeScale, duration ) { + + const mixer = this._mixer, + now = mixer.time, + timeScale = this.timeScale; + + let interpolant = this._timeScaleInterpolant; + + if ( interpolant === null ) { + + interpolant = mixer._lendControlInterpolant(); + this._timeScaleInterpolant = interpolant; + + } + + const times = interpolant.parameterPositions, + values = interpolant.sampleValues; + + times[ 0 ] = now; + times[ 1 ] = now + duration; + + values[ 0 ] = startTimeScale / timeScale; + values[ 1 ] = endTimeScale / timeScale; + + return this; + + } + + stopWarping() { + + const timeScaleInterpolant = this._timeScaleInterpolant; + + if ( timeScaleInterpolant !== null ) { + + this._timeScaleInterpolant = null; + this._mixer._takeBackControlInterpolant( timeScaleInterpolant ); + + } + + return this; + + } + + // Object Accessors + + getMixer() { + + return this._mixer; + + } + + getClip() { + + return this._clip; + + } + + getRoot() { + + return this._localRoot || this._mixer._root; + + } + + // Interna + + _update( time, deltaTime, timeDirection, accuIndex ) { + + // called by the mixer + + if ( ! this.enabled ) { + + // call ._updateWeight() to update ._effectiveWeight + + this._updateWeight( time ); + return; + + } + + const startTime = this._startTime; + + if ( startTime !== null ) { + + // check for scheduled start of action + + const timeRunning = ( time - startTime ) * timeDirection; + if ( timeRunning < 0 || timeDirection === 0 ) { + + deltaTime = 0; + + } else { + + + this._startTime = null; // unschedule + deltaTime = timeDirection * timeRunning; + + } + + } + + // apply time scale and advance time + + deltaTime *= this._updateTimeScale( time ); + const clipTime = this._updateTime( deltaTime ); + + // note: _updateTime may disable the action resulting in + // an effective weight of 0 + + const weight = this._updateWeight( time ); + + if ( weight > 0 ) { + + const interpolants = this._interpolants; + const propertyMixers = this._propertyBindings; + + switch ( this.blendMode ) { + + case AdditiveAnimationBlendMode: + + for ( let j = 0, m = interpolants.length; j !== m; ++ j ) { + + interpolants[ j ].evaluate( clipTime ); + propertyMixers[ j ].accumulateAdditive( weight ); + + } + + break; + + case NormalAnimationBlendMode: + default: + + for ( let j = 0, m = interpolants.length; j !== m; ++ j ) { + + interpolants[ j ].evaluate( clipTime ); + propertyMixers[ j ].accumulate( accuIndex, weight ); + + } + + } + + } + + } + + _updateWeight( time ) { + + let weight = 0; + + if ( this.enabled ) { + + weight = this.weight; + const interpolant = this._weightInterpolant; + + if ( interpolant !== null ) { + + const interpolantValue = interpolant.evaluate( time )[ 0 ]; + + weight *= interpolantValue; + + if ( time > interpolant.parameterPositions[ 1 ] ) { + + this.stopFading(); + + if ( interpolantValue === 0 ) { + + // faded out, disable + this.enabled = false; + + } + + } + + } + + } + + this._effectiveWeight = weight; + return weight; + + } + + _updateTimeScale( time ) { + + let timeScale = 0; + + if ( ! this.paused ) { + + timeScale = this.timeScale; + + const interpolant = this._timeScaleInterpolant; + + if ( interpolant !== null ) { + + const interpolantValue = interpolant.evaluate( time )[ 0 ]; + + timeScale *= interpolantValue; + + if ( time > interpolant.parameterPositions[ 1 ] ) { + + this.stopWarping(); + + if ( timeScale === 0 ) { + + // motion has halted, pause + this.paused = true; + + } else { + + // warp done - apply final time scale + this.timeScale = timeScale; + + } + + } + + } + + } + + this._effectiveTimeScale = timeScale; + return timeScale; + + } + + _updateTime( deltaTime ) { + + const duration = this._clip.duration; + const loop = this.loop; + + let time = this.time + deltaTime; + let loopCount = this._loopCount; + + const pingPong = ( loop === LoopPingPong ); + + if ( deltaTime === 0 ) { + + if ( loopCount === - 1 ) return time; + + return ( pingPong && ( loopCount & 1 ) === 1 ) ? duration - time : time; + + } + + if ( loop === LoopOnce ) { + + if ( loopCount === - 1 ) { + + // just started + + this._loopCount = 0; + this._setEndings( true, true, false ); + + } + + handle_stop: { + + if ( time >= duration ) { + + time = duration; + + } else if ( time < 0 ) { + + time = 0; + + } else { + + this.time = time; + + break handle_stop; + + } + + if ( this.clampWhenFinished ) this.paused = true; + else this.enabled = false; + + this.time = time; + + this._mixer.dispatchEvent( { + type: 'finished', action: this, + direction: deltaTime < 0 ? - 1 : 1 + } ); + + } + + } else { // repetitive Repeat or PingPong + + if ( loopCount === - 1 ) { + + // just started + + if ( deltaTime >= 0 ) { + + loopCount = 0; + + this._setEndings( true, this.repetitions === 0, pingPong ); + + } else { + + // when looping in reverse direction, the initial + // transition through zero counts as a repetition, + // so leave loopCount at -1 + + this._setEndings( this.repetitions === 0, true, pingPong ); + + } + + } + + if ( time >= duration || time < 0 ) { + + // wrap around + + const loopDelta = Math.floor( time / duration ); // signed + time -= duration * loopDelta; + + loopCount += Math.abs( loopDelta ); + + const pending = this.repetitions - loopCount; + + if ( pending <= 0 ) { + + // have to stop (switch state, clamp time, fire event) + + if ( this.clampWhenFinished ) this.paused = true; + else this.enabled = false; + + time = deltaTime > 0 ? duration : 0; + + this.time = time; + + this._mixer.dispatchEvent( { + type: 'finished', action: this, + direction: deltaTime > 0 ? 1 : - 1 + } ); + + } else { + + // keep running + + if ( pending === 1 ) { + + // entering the last round + + const atStart = deltaTime < 0; + this._setEndings( atStart, ! atStart, pingPong ); + + } else { + + this._setEndings( false, false, pingPong ); + + } + + this._loopCount = loopCount; + + this.time = time; + + this._mixer.dispatchEvent( { + type: 'loop', action: this, loopDelta: loopDelta + } ); + + } + + } else { + + this.time = time; + + } + + if ( pingPong && ( loopCount & 1 ) === 1 ) { + + // invert time for the "pong round" + + return duration - time; + + } + + } + + return time; + + } + + _setEndings( atStart, atEnd, pingPong ) { + + const settings = this._interpolantSettings; + + if ( pingPong ) { + + settings.endingStart = ZeroSlopeEnding; + settings.endingEnd = ZeroSlopeEnding; + + } else { + + // assuming for LoopOnce atStart == atEnd == true + + if ( atStart ) { + + settings.endingStart = this.zeroSlopeAtStart ? ZeroSlopeEnding : ZeroCurvatureEnding; + + } else { + + settings.endingStart = WrapAroundEnding; + + } + + if ( atEnd ) { + + settings.endingEnd = this.zeroSlopeAtEnd ? ZeroSlopeEnding : ZeroCurvatureEnding; + + } else { + + settings.endingEnd = WrapAroundEnding; + + } + + } + + } + + _scheduleFading( duration, weightNow, weightThen ) { + + const mixer = this._mixer, now = mixer.time; + let interpolant = this._weightInterpolant; + + if ( interpolant === null ) { + + interpolant = mixer._lendControlInterpolant(); + this._weightInterpolant = interpolant; + + } + + const times = interpolant.parameterPositions, + values = interpolant.sampleValues; + + times[ 0 ] = now; + values[ 0 ] = weightNow; + times[ 1 ] = now + duration; + values[ 1 ] = weightThen; + + return this; + + } + +} + +const _controlInterpolantsResultBuffer = new Float32Array( 1 ); + + +class AnimationMixer extends EventDispatcher { + + constructor( root ) { + + super(); + + this._root = root; + this._initMemoryManager(); + this._accuIndex = 0; + this.time = 0; + this.timeScale = 1.0; + + } + + _bindAction( action, prototypeAction ) { + + const root = action._localRoot || this._root, + tracks = action._clip.tracks, + nTracks = tracks.length, + bindings = action._propertyBindings, + interpolants = action._interpolants, + rootUuid = root.uuid, + bindingsByRoot = this._bindingsByRootAndName; + + let bindingsByName = bindingsByRoot[ rootUuid ]; + + if ( bindingsByName === undefined ) { + + bindingsByName = {}; + bindingsByRoot[ rootUuid ] = bindingsByName; + + } + + for ( let i = 0; i !== nTracks; ++ i ) { + + const track = tracks[ i ], + trackName = track.name; + + let binding = bindingsByName[ trackName ]; + + if ( binding !== undefined ) { + + ++ binding.referenceCount; + bindings[ i ] = binding; + + } else { + + binding = bindings[ i ]; + + if ( binding !== undefined ) { + + // existing binding, make sure the cache knows + + if ( binding._cacheIndex === null ) { + + ++ binding.referenceCount; + this._addInactiveBinding( binding, rootUuid, trackName ); + + } + + continue; + + } + + const path = prototypeAction && prototypeAction. + _propertyBindings[ i ].binding.parsedPath; + + binding = new PropertyMixer( + PropertyBinding.create( root, trackName, path ), + track.ValueTypeName, track.getValueSize() ); + + ++ binding.referenceCount; + this._addInactiveBinding( binding, rootUuid, trackName ); + + bindings[ i ] = binding; + + } + + interpolants[ i ].resultBuffer = binding.buffer; + + } + + } + + _activateAction( action ) { + + if ( ! this._isActiveAction( action ) ) { + + if ( action._cacheIndex === null ) { + + // this action has been forgotten by the cache, but the user + // appears to be still using it -> rebind + + const rootUuid = ( action._localRoot || this._root ).uuid, + clipUuid = action._clip.uuid, + actionsForClip = this._actionsByClip[ clipUuid ]; + + this._bindAction( action, + actionsForClip && actionsForClip.knownActions[ 0 ] ); + + this._addInactiveAction( action, clipUuid, rootUuid ); + + } + + const bindings = action._propertyBindings; + + // increment reference counts / sort out state + for ( let i = 0, n = bindings.length; i !== n; ++ i ) { + + const binding = bindings[ i ]; + + if ( binding.useCount ++ === 0 ) { + + this._lendBinding( binding ); + binding.saveOriginalState(); + + } + + } + + this._lendAction( action ); + + } + + } + + _deactivateAction( action ) { + + if ( this._isActiveAction( action ) ) { + + const bindings = action._propertyBindings; + + // decrement reference counts / sort out state + for ( let i = 0, n = bindings.length; i !== n; ++ i ) { + + const binding = bindings[ i ]; + + if ( -- binding.useCount === 0 ) { + + binding.restoreOriginalState(); + this._takeBackBinding( binding ); + + } + + } + + this._takeBackAction( action ); + + } + + } + + // Memory manager + + _initMemoryManager() { + + this._actions = []; // 'nActiveActions' followed by inactive ones + this._nActiveActions = 0; + + this._actionsByClip = {}; + // inside: + // { + // knownActions: Array< AnimationAction > - used as prototypes + // actionByRoot: AnimationAction - lookup + // } + + + this._bindings = []; // 'nActiveBindings' followed by inactive ones + this._nActiveBindings = 0; + + this._bindingsByRootAndName = {}; // inside: Map< name, PropertyMixer > + + + this._controlInterpolants = []; // same game as above + this._nActiveControlInterpolants = 0; + + const scope = this; + + this.stats = { + + actions: { + get total() { + + return scope._actions.length; + + }, + get inUse() { + + return scope._nActiveActions; + + } + }, + bindings: { + get total() { + + return scope._bindings.length; + + }, + get inUse() { + + return scope._nActiveBindings; + + } + }, + controlInterpolants: { + get total() { + + return scope._controlInterpolants.length; + + }, + get inUse() { + + return scope._nActiveControlInterpolants; + + } + } + + }; + + } + + // Memory management for AnimationAction objects + + _isActiveAction( action ) { + + const index = action._cacheIndex; + return index !== null && index < this._nActiveActions; + + } + + _addInactiveAction( action, clipUuid, rootUuid ) { + + const actions = this._actions, + actionsByClip = this._actionsByClip; + + let actionsForClip = actionsByClip[ clipUuid ]; + + if ( actionsForClip === undefined ) { + + actionsForClip = { + + knownActions: [ action ], + actionByRoot: {} + + }; + + action._byClipCacheIndex = 0; + + actionsByClip[ clipUuid ] = actionsForClip; + + } else { + + const knownActions = actionsForClip.knownActions; + + action._byClipCacheIndex = knownActions.length; + knownActions.push( action ); + + } + + action._cacheIndex = actions.length; + actions.push( action ); + + actionsForClip.actionByRoot[ rootUuid ] = action; + + } + + _removeInactiveAction( action ) { + + const actions = this._actions, + lastInactiveAction = actions[ actions.length - 1 ], + cacheIndex = action._cacheIndex; + + lastInactiveAction._cacheIndex = cacheIndex; + actions[ cacheIndex ] = lastInactiveAction; + actions.pop(); + + action._cacheIndex = null; + + + const clipUuid = action._clip.uuid, + actionsByClip = this._actionsByClip, + actionsForClip = actionsByClip[ clipUuid ], + knownActionsForClip = actionsForClip.knownActions, + + lastKnownAction = + knownActionsForClip[ knownActionsForClip.length - 1 ], + + byClipCacheIndex = action._byClipCacheIndex; + + lastKnownAction._byClipCacheIndex = byClipCacheIndex; + knownActionsForClip[ byClipCacheIndex ] = lastKnownAction; + knownActionsForClip.pop(); + + action._byClipCacheIndex = null; + + + const actionByRoot = actionsForClip.actionByRoot, + rootUuid = ( action._localRoot || this._root ).uuid; + + delete actionByRoot[ rootUuid ]; + + if ( knownActionsForClip.length === 0 ) { + + delete actionsByClip[ clipUuid ]; + + } + + this._removeInactiveBindingsForAction( action ); + + } + + _removeInactiveBindingsForAction( action ) { + + const bindings = action._propertyBindings; + + for ( let i = 0, n = bindings.length; i !== n; ++ i ) { + + const binding = bindings[ i ]; + + if ( -- binding.referenceCount === 0 ) { + + this._removeInactiveBinding( binding ); + + } + + } + + } + + _lendAction( action ) { + + // [ active actions | inactive actions ] + // [ active actions >| inactive actions ] + // s a + // <-swap-> + // a s + + const actions = this._actions, + prevIndex = action._cacheIndex, + + lastActiveIndex = this._nActiveActions ++, + + firstInactiveAction = actions[ lastActiveIndex ]; + + action._cacheIndex = lastActiveIndex; + actions[ lastActiveIndex ] = action; + + firstInactiveAction._cacheIndex = prevIndex; + actions[ prevIndex ] = firstInactiveAction; + + } + + _takeBackAction( action ) { + + // [ active actions | inactive actions ] + // [ active actions |< inactive actions ] + // a s + // <-swap-> + // s a + + const actions = this._actions, + prevIndex = action._cacheIndex, + + firstInactiveIndex = -- this._nActiveActions, + + lastActiveAction = actions[ firstInactiveIndex ]; + + action._cacheIndex = firstInactiveIndex; + actions[ firstInactiveIndex ] = action; + + lastActiveAction._cacheIndex = prevIndex; + actions[ prevIndex ] = lastActiveAction; + + } + + // Memory management for PropertyMixer objects + + _addInactiveBinding( binding, rootUuid, trackName ) { + + const bindingsByRoot = this._bindingsByRootAndName, + bindings = this._bindings; + + let bindingByName = bindingsByRoot[ rootUuid ]; + + if ( bindingByName === undefined ) { + + bindingByName = {}; + bindingsByRoot[ rootUuid ] = bindingByName; + + } + + bindingByName[ trackName ] = binding; + + binding._cacheIndex = bindings.length; + bindings.push( binding ); + + } + + _removeInactiveBinding( binding ) { + + const bindings = this._bindings, + propBinding = binding.binding, + rootUuid = propBinding.rootNode.uuid, + trackName = propBinding.path, + bindingsByRoot = this._bindingsByRootAndName, + bindingByName = bindingsByRoot[ rootUuid ], + + lastInactiveBinding = bindings[ bindings.length - 1 ], + cacheIndex = binding._cacheIndex; + + lastInactiveBinding._cacheIndex = cacheIndex; + bindings[ cacheIndex ] = lastInactiveBinding; + bindings.pop(); + + delete bindingByName[ trackName ]; + + if ( Object.keys( bindingByName ).length === 0 ) { + + delete bindingsByRoot[ rootUuid ]; + + } + + } + + _lendBinding( binding ) { + + const bindings = this._bindings, + prevIndex = binding._cacheIndex, + + lastActiveIndex = this._nActiveBindings ++, + + firstInactiveBinding = bindings[ lastActiveIndex ]; + + binding._cacheIndex = lastActiveIndex; + bindings[ lastActiveIndex ] = binding; + + firstInactiveBinding._cacheIndex = prevIndex; + bindings[ prevIndex ] = firstInactiveBinding; + + } + + _takeBackBinding( binding ) { + + const bindings = this._bindings, + prevIndex = binding._cacheIndex, + + firstInactiveIndex = -- this._nActiveBindings, + + lastActiveBinding = bindings[ firstInactiveIndex ]; + + binding._cacheIndex = firstInactiveIndex; + bindings[ firstInactiveIndex ] = binding; + + lastActiveBinding._cacheIndex = prevIndex; + bindings[ prevIndex ] = lastActiveBinding; + + } + + + // Memory management of Interpolants for weight and time scale + + _lendControlInterpolant() { + + const interpolants = this._controlInterpolants, + lastActiveIndex = this._nActiveControlInterpolants ++; + + let interpolant = interpolants[ lastActiveIndex ]; + + if ( interpolant === undefined ) { + + interpolant = new LinearInterpolant( + new Float32Array( 2 ), new Float32Array( 2 ), + 1, _controlInterpolantsResultBuffer ); + + interpolant.__cacheIndex = lastActiveIndex; + interpolants[ lastActiveIndex ] = interpolant; + + } + + return interpolant; + + } + + _takeBackControlInterpolant( interpolant ) { + + const interpolants = this._controlInterpolants, + prevIndex = interpolant.__cacheIndex, + + firstInactiveIndex = -- this._nActiveControlInterpolants, + + lastActiveInterpolant = interpolants[ firstInactiveIndex ]; + + interpolant.__cacheIndex = firstInactiveIndex; + interpolants[ firstInactiveIndex ] = interpolant; + + lastActiveInterpolant.__cacheIndex = prevIndex; + interpolants[ prevIndex ] = lastActiveInterpolant; + + } + + // return an action for a clip optionally using a custom root target + // object (this method allocates a lot of dynamic memory in case a + // previously unknown clip/root combination is specified) + clipAction( clip, optionalRoot, blendMode ) { + + const root = optionalRoot || this._root, + rootUuid = root.uuid; + + let clipObject = typeof clip === 'string' ? AnimationClip.findByName( root, clip ) : clip; + + const clipUuid = clipObject !== null ? clipObject.uuid : clip; + + const actionsForClip = this._actionsByClip[ clipUuid ]; + let prototypeAction = null; + + if ( blendMode === undefined ) { + + if ( clipObject !== null ) { + + blendMode = clipObject.blendMode; + + } else { + + blendMode = NormalAnimationBlendMode; + + } + + } + + if ( actionsForClip !== undefined ) { + + const existingAction = actionsForClip.actionByRoot[ rootUuid ]; + + if ( existingAction !== undefined && existingAction.blendMode === blendMode ) { + + return existingAction; + + } + + // we know the clip, so we don't have to parse all + // the bindings again but can just copy + prototypeAction = actionsForClip.knownActions[ 0 ]; + + // also, take the clip from the prototype action + if ( clipObject === null ) + clipObject = prototypeAction._clip; + + } + + // clip must be known when specified via string + if ( clipObject === null ) return null; + + // allocate all resources required to run it + const newAction = new AnimationAction( this, clipObject, optionalRoot, blendMode ); + + this._bindAction( newAction, prototypeAction ); + + // and make the action known to the memory manager + this._addInactiveAction( newAction, clipUuid, rootUuid ); + + return newAction; + + } + + // get an existing action + existingAction( clip, optionalRoot ) { + + const root = optionalRoot || this._root, + rootUuid = root.uuid, + + clipObject = typeof clip === 'string' ? + AnimationClip.findByName( root, clip ) : clip, + + clipUuid = clipObject ? clipObject.uuid : clip, + + actionsForClip = this._actionsByClip[ clipUuid ]; + + if ( actionsForClip !== undefined ) { + + return actionsForClip.actionByRoot[ rootUuid ] || null; + + } + + return null; + + } + + // deactivates all previously scheduled actions + stopAllAction() { + + const actions = this._actions, + nActions = this._nActiveActions; + + for ( let i = nActions - 1; i >= 0; -- i ) { + + actions[ i ].stop(); + + } + + return this; + + } + + // advance the time and update apply the animation + update( deltaTime ) { + + deltaTime *= this.timeScale; + + const actions = this._actions, + nActions = this._nActiveActions, + + time = this.time += deltaTime, + timeDirection = Math.sign( deltaTime ), + + accuIndex = this._accuIndex ^= 1; + + // run active actions + + for ( let i = 0; i !== nActions; ++ i ) { + + const action = actions[ i ]; + + action._update( time, deltaTime, timeDirection, accuIndex ); + + } + + // update scene graph + + const bindings = this._bindings, + nBindings = this._nActiveBindings; + + for ( let i = 0; i !== nBindings; ++ i ) { + + bindings[ i ].apply( accuIndex ); + + } + + return this; + + } + + // Allows you to seek to a specific time in an animation. + setTime( timeInSeconds ) { + + this.time = 0; // Zero out time attribute for AnimationMixer object; + for ( let i = 0; i < this._actions.length; i ++ ) { + + this._actions[ i ].time = 0; // Zero out time attribute for all associated AnimationAction objects. + + } + + return this.update( timeInSeconds ); // Update used to set exact time. Returns "this" AnimationMixer object. + + } + + // return this mixer's root target object + getRoot() { + + return this._root; + + } + + // free all resources specific to a particular clip + uncacheClip( clip ) { + + const actions = this._actions, + clipUuid = clip.uuid, + actionsByClip = this._actionsByClip, + actionsForClip = actionsByClip[ clipUuid ]; + + if ( actionsForClip !== undefined ) { + + // note: just calling _removeInactiveAction would mess up the + // iteration state and also require updating the state we can + // just throw away + + const actionsToRemove = actionsForClip.knownActions; + + for ( let i = 0, n = actionsToRemove.length; i !== n; ++ i ) { + + const action = actionsToRemove[ i ]; + + this._deactivateAction( action ); + + const cacheIndex = action._cacheIndex, + lastInactiveAction = actions[ actions.length - 1 ]; + + action._cacheIndex = null; + action._byClipCacheIndex = null; + + lastInactiveAction._cacheIndex = cacheIndex; + actions[ cacheIndex ] = lastInactiveAction; + actions.pop(); + + this._removeInactiveBindingsForAction( action ); + + } + + delete actionsByClip[ clipUuid ]; + + } + + } + + // free all resources specific to a particular root target object + uncacheRoot( root ) { + + const rootUuid = root.uuid, + actionsByClip = this._actionsByClip; + + for ( const clipUuid in actionsByClip ) { + + const actionByRoot = actionsByClip[ clipUuid ].actionByRoot, + action = actionByRoot[ rootUuid ]; + + if ( action !== undefined ) { + + this._deactivateAction( action ); + this._removeInactiveAction( action ); + + } + + } + + const bindingsByRoot = this._bindingsByRootAndName, + bindingByName = bindingsByRoot[ rootUuid ]; + + if ( bindingByName !== undefined ) { + + for ( const trackName in bindingByName ) { + + const binding = bindingByName[ trackName ]; + binding.restoreOriginalState(); + this._removeInactiveBinding( binding ); + + } + + } + + } + + // remove a targeted clip from the cache + uncacheAction( clip, optionalRoot ) { + + const action = this.existingAction( clip, optionalRoot ); + + if ( action !== null ) { + + this._deactivateAction( action ); + this._removeInactiveAction( action ); + + } + + } + +} + +class Uniform { + + constructor( value ) { + + this.value = value; + + } + + clone() { + + return new Uniform( this.value.clone === undefined ? this.value : this.value.clone() ); + + } + +} + +let _id = 0; + +class UniformsGroup extends EventDispatcher { + + constructor() { + + super(); + + this.isUniformsGroup = true; + + Object.defineProperty( this, 'id', { value: _id ++ } ); + + this.name = ''; + + this.usage = StaticDrawUsage; + this.uniforms = []; + + } + + add( uniform ) { + + this.uniforms.push( uniform ); + + return this; + + } + + remove( uniform ) { + + const index = this.uniforms.indexOf( uniform ); + + if ( index !== - 1 ) this.uniforms.splice( index, 1 ); + + return this; + + } + + setName( name ) { + + this.name = name; + + return this; + + } + + setUsage( value ) { + + this.usage = value; + + return this; + + } + + dispose() { + + this.dispatchEvent( { type: 'dispose' } ); + + return this; + + } + + copy( source ) { + + this.name = source.name; + this.usage = source.usage; + + const uniformsSource = source.uniforms; + + this.uniforms.length = 0; + + for ( let i = 0, l = uniformsSource.length; i < l; i ++ ) { + + const uniforms = Array.isArray( uniformsSource[ i ] ) ? uniformsSource[ i ] : [ uniformsSource[ i ] ]; + + for ( let j = 0; j < uniforms.length; j ++ ) { + + this.uniforms.push( uniforms[ j ].clone() ); + + } + + } + + return this; + + } + + clone() { + + return new this.constructor().copy( this ); + + } + +} + +class InstancedInterleavedBuffer extends InterleavedBuffer { + + constructor( array, stride, meshPerAttribute = 1 ) { + + super( array, stride ); + + this.isInstancedInterleavedBuffer = true; + + this.meshPerAttribute = meshPerAttribute; + + } + + copy( source ) { + + super.copy( source ); + + this.meshPerAttribute = source.meshPerAttribute; + + return this; + + } + + clone( data ) { + + const ib = super.clone( data ); + + ib.meshPerAttribute = this.meshPerAttribute; + + return ib; + + } + + toJSON( data ) { + + const json = super.toJSON( data ); + + json.isInstancedInterleavedBuffer = true; + json.meshPerAttribute = this.meshPerAttribute; + + return json; + + } + +} + +class GLBufferAttribute { + + constructor( buffer, type, itemSize, elementSize, count ) { + + this.isGLBufferAttribute = true; + + this.name = ''; + + this.buffer = buffer; + this.type = type; + this.itemSize = itemSize; + this.elementSize = elementSize; + this.count = count; + + this.version = 0; + + } + + set needsUpdate( value ) { + + if ( value === true ) this.version ++; + + } + + setBuffer( buffer ) { + + this.buffer = buffer; + + return this; + + } + + setType( type, elementSize ) { + + this.type = type; + this.elementSize = elementSize; + + return this; + + } + + setItemSize( itemSize ) { + + this.itemSize = itemSize; + + return this; + + } + + setCount( count ) { + + this.count = count; + + return this; + + } + +} + +const _matrix = /*@__PURE__*/ new Matrix4(); + +class Raycaster { + + constructor( origin, direction, near = 0, far = Infinity ) { + + this.ray = new Ray( origin, direction ); + // direction is assumed to be normalized (for accurate distance calculations) + + this.near = near; + this.far = far; + this.camera = null; + this.layers = new Layers(); + + this.params = { + Mesh: {}, + Line: { threshold: 1 }, + LOD: {}, + Points: { threshold: 1 }, + Sprite: {} + }; + + } + + set( origin, direction ) { + + // direction is assumed to be normalized (for accurate distance calculations) + + this.ray.set( origin, direction ); + + } + + setFromCamera( coords, camera ) { + + if ( camera.isPerspectiveCamera ) { + + this.ray.origin.setFromMatrixPosition( camera.matrixWorld ); + this.ray.direction.set( coords.x, coords.y, 0.5 ).unproject( camera ).sub( this.ray.origin ).normalize(); + this.camera = camera; + + } else if ( camera.isOrthographicCamera ) { + + this.ray.origin.set( coords.x, coords.y, ( camera.near + camera.far ) / ( camera.near - camera.far ) ).unproject( camera ); // set origin in plane of camera + this.ray.direction.set( 0, 0, - 1 ).transformDirection( camera.matrixWorld ); + this.camera = camera; + + } else { + + console.error( 'THREE.Raycaster: Unsupported camera type: ' + camera.type ); + + } + + } + + setFromXRController( controller ) { + + _matrix.identity().extractRotation( controller.matrixWorld ); + + this.ray.origin.setFromMatrixPosition( controller.matrixWorld ); + this.ray.direction.set( 0, 0, - 1 ).applyMatrix4( _matrix ); + + return this; + + } + + intersectObject( object, recursive = true, intersects = [] ) { + + intersect( object, this, intersects, recursive ); + + intersects.sort( ascSort ); + + return intersects; + + } + + intersectObjects( objects, recursive = true, intersects = [] ) { + + for ( let i = 0, l = objects.length; i < l; i ++ ) { + + intersect( objects[ i ], this, intersects, recursive ); + + } + + intersects.sort( ascSort ); + + return intersects; + + } + +} + +function ascSort( a, b ) { + + return a.distance - b.distance; + +} + +function intersect( object, raycaster, intersects, recursive ) { + + let propagate = true; + + if ( object.layers.test( raycaster.layers ) ) { + + const result = object.raycast( raycaster, intersects ); + + if ( result === false ) propagate = false; + + } + + if ( propagate === true && recursive === true ) { + + const children = object.children; + + for ( let i = 0, l = children.length; i < l; i ++ ) { + + intersect( children[ i ], raycaster, intersects, true ); + + } + + } + +} + +/** + * Ref: https://en.wikipedia.org/wiki/Spherical_coordinate_system + * + * phi (the polar angle) is measured from the positive y-axis. The positive y-axis is up. + * theta (the azimuthal angle) is measured from the positive z-axis. + */ +class Spherical { + + constructor( radius = 1, phi = 0, theta = 0 ) { + + this.radius = radius; + this.phi = phi; // polar angle + this.theta = theta; // azimuthal angle + + return this; + + } + + set( radius, phi, theta ) { + + this.radius = radius; + this.phi = phi; + this.theta = theta; + + return this; + + } + + copy( other ) { + + this.radius = other.radius; + this.phi = other.phi; + this.theta = other.theta; + + return this; + + } + + // restrict phi to be between EPS and PI-EPS + makeSafe() { + + const EPS = 0.000001; + this.phi = Math.max( EPS, Math.min( Math.PI - EPS, this.phi ) ); + + return this; + + } + + setFromVector3( v ) { + + return this.setFromCartesianCoords( v.x, v.y, v.z ); + + } + + setFromCartesianCoords( x, y, z ) { + + this.radius = Math.sqrt( x * x + y * y + z * z ); + + if ( this.radius === 0 ) { + + this.theta = 0; + this.phi = 0; + + } else { + + this.theta = Math.atan2( x, z ); + this.phi = Math.acos( clamp( y / this.radius, - 1, 1 ) ); + + } + + return this; + + } + + clone() { + + return new this.constructor().copy( this ); + + } + +} + +/** + * Ref: https://en.wikipedia.org/wiki/Cylindrical_coordinate_system + */ + +class Cylindrical { + + constructor( radius = 1, theta = 0, y = 0 ) { + + this.radius = radius; // distance from the origin to a point in the x-z plane + this.theta = theta; // counterclockwise angle in the x-z plane measured in radians from the positive z-axis + this.y = y; // height above the x-z plane + + return this; + + } + + set( radius, theta, y ) { + + this.radius = radius; + this.theta = theta; + this.y = y; + + return this; + + } + + copy( other ) { + + this.radius = other.radius; + this.theta = other.theta; + this.y = other.y; + + return this; + + } + + setFromVector3( v ) { + + return this.setFromCartesianCoords( v.x, v.y, v.z ); + + } + + setFromCartesianCoords( x, y, z ) { + + this.radius = Math.sqrt( x * x + z * z ); + this.theta = Math.atan2( x, z ); + this.y = y; + + return this; + + } + + clone() { + + return new this.constructor().copy( this ); + + } + +} + +const _vector$4 = /*@__PURE__*/ new Vector2(); + +class Box2 { + + constructor( min = new Vector2( + Infinity, + Infinity ), max = new Vector2( - Infinity, - Infinity ) ) { + + this.isBox2 = true; + + this.min = min; + this.max = max; + + } + + set( min, max ) { + + this.min.copy( min ); + this.max.copy( max ); + + return this; + + } + + setFromPoints( points ) { + + this.makeEmpty(); + + for ( let i = 0, il = points.length; i < il; i ++ ) { + + this.expandByPoint( points[ i ] ); + + } + + return this; + + } + + setFromCenterAndSize( center, size ) { + + const halfSize = _vector$4.copy( size ).multiplyScalar( 0.5 ); + this.min.copy( center ).sub( halfSize ); + this.max.copy( center ).add( halfSize ); + + return this; + + } + + clone() { + + return new this.constructor().copy( this ); + + } + + copy( box ) { + + this.min.copy( box.min ); + this.max.copy( box.max ); + + return this; + + } + + makeEmpty() { + + this.min.x = this.min.y = + Infinity; + this.max.x = this.max.y = - Infinity; + + return this; + + } + + isEmpty() { + + // this is a more robust check for empty than ( volume <= 0 ) because volume can get positive with two negative axes + + return ( this.max.x < this.min.x ) || ( this.max.y < this.min.y ); + + } + + getCenter( target ) { + + return this.isEmpty() ? target.set( 0, 0 ) : target.addVectors( this.min, this.max ).multiplyScalar( 0.5 ); + + } + + getSize( target ) { + + return this.isEmpty() ? target.set( 0, 0 ) : target.subVectors( this.max, this.min ); + + } + + expandByPoint( point ) { + + this.min.min( point ); + this.max.max( point ); + + return this; + + } + + expandByVector( vector ) { + + this.min.sub( vector ); + this.max.add( vector ); + + return this; + + } + + expandByScalar( scalar ) { + + this.min.addScalar( - scalar ); + this.max.addScalar( scalar ); + + return this; + + } + + containsPoint( point ) { + + return point.x < this.min.x || point.x > this.max.x || + point.y < this.min.y || point.y > this.max.y ? false : true; + + } + + containsBox( box ) { + + return this.min.x <= box.min.x && box.max.x <= this.max.x && + this.min.y <= box.min.y && box.max.y <= this.max.y; + + } + + getParameter( point, target ) { + + // This can potentially have a divide by zero if the box + // has a size dimension of 0. + + return target.set( + ( point.x - this.min.x ) / ( this.max.x - this.min.x ), + ( point.y - this.min.y ) / ( this.max.y - this.min.y ) + ); + + } + + intersectsBox( box ) { + + // using 4 splitting planes to rule out intersections + + return box.max.x < this.min.x || box.min.x > this.max.x || + box.max.y < this.min.y || box.min.y > this.max.y ? false : true; + + } + + clampPoint( point, target ) { + + return target.copy( point ).clamp( this.min, this.max ); + + } + + distanceToPoint( point ) { + + return this.clampPoint( point, _vector$4 ).distanceTo( point ); + + } + + intersect( box ) { + + this.min.max( box.min ); + this.max.min( box.max ); + + if ( this.isEmpty() ) this.makeEmpty(); + + return this; + + } + + union( box ) { + + this.min.min( box.min ); + this.max.max( box.max ); + + return this; + + } + + translate( offset ) { + + this.min.add( offset ); + this.max.add( offset ); + + return this; + + } + + equals( box ) { + + return box.min.equals( this.min ) && box.max.equals( this.max ); + + } + +} + +const _startP = /*@__PURE__*/ new Vector3(); +const _startEnd = /*@__PURE__*/ new Vector3(); + +class Line3 { + + constructor( start = new Vector3(), end = new Vector3() ) { + + this.start = start; + this.end = end; + + } + + set( start, end ) { + + this.start.copy( start ); + this.end.copy( end ); + + return this; + + } + + copy( line ) { + + this.start.copy( line.start ); + this.end.copy( line.end ); + + return this; + + } + + getCenter( target ) { + + return target.addVectors( this.start, this.end ).multiplyScalar( 0.5 ); + + } + + delta( target ) { + + return target.subVectors( this.end, this.start ); + + } + + distanceSq() { + + return this.start.distanceToSquared( this.end ); + + } + + distance() { + + return this.start.distanceTo( this.end ); + + } + + at( t, target ) { + + return this.delta( target ).multiplyScalar( t ).add( this.start ); + + } + + closestPointToPointParameter( point, clampToLine ) { + + _startP.subVectors( point, this.start ); + _startEnd.subVectors( this.end, this.start ); + + const startEnd2 = _startEnd.dot( _startEnd ); + const startEnd_startP = _startEnd.dot( _startP ); + + let t = startEnd_startP / startEnd2; + + if ( clampToLine ) { + + t = clamp( t, 0, 1 ); + + } + + return t; + + } + + closestPointToPoint( point, clampToLine, target ) { + + const t = this.closestPointToPointParameter( point, clampToLine ); + + return this.delta( target ).multiplyScalar( t ).add( this.start ); + + } + + applyMatrix4( matrix ) { + + this.start.applyMatrix4( matrix ); + this.end.applyMatrix4( matrix ); + + return this; + + } + + equals( line ) { + + return line.start.equals( this.start ) && line.end.equals( this.end ); + + } + + clone() { + + return new this.constructor().copy( this ); + + } + +} + +const _vector$3 = /*@__PURE__*/ new Vector3(); + +class SpotLightHelper extends Object3D { + + constructor( light, color ) { + + super(); + + this.light = light; + + this.matrixAutoUpdate = false; + + this.color = color; + + this.type = 'SpotLightHelper'; + + const geometry = new BufferGeometry(); + + const positions = [ + 0, 0, 0, 0, 0, 1, + 0, 0, 0, 1, 0, 1, + 0, 0, 0, - 1, 0, 1, + 0, 0, 0, 0, 1, 1, + 0, 0, 0, 0, - 1, 1 + ]; + + for ( let i = 0, j = 1, l = 32; i < l; i ++, j ++ ) { + + const p1 = ( i / l ) * Math.PI * 2; + const p2 = ( j / l ) * Math.PI * 2; + + positions.push( + Math.cos( p1 ), Math.sin( p1 ), 1, + Math.cos( p2 ), Math.sin( p2 ), 1 + ); + + } + + geometry.setAttribute( 'position', new Float32BufferAttribute( positions, 3 ) ); + + const material = new LineBasicMaterial( { fog: false, toneMapped: false } ); + + this.cone = new LineSegments( geometry, material ); + this.add( this.cone ); + + this.update(); + + } + + dispose() { + + this.cone.geometry.dispose(); + this.cone.material.dispose(); + + } + + update() { + + this.light.updateWorldMatrix( true, false ); + this.light.target.updateWorldMatrix( true, false ); + + // update the local matrix based on the parent and light target transforms + if ( this.parent ) { + + this.parent.updateWorldMatrix( true ); + + this.matrix + .copy( this.parent.matrixWorld ) + .invert() + .multiply( this.light.matrixWorld ); + + } else { + + this.matrix.copy( this.light.matrixWorld ); + + } + + this.matrixWorld.copy( this.light.matrixWorld ); + + const coneLength = this.light.distance ? this.light.distance : 1000; + const coneWidth = coneLength * Math.tan( this.light.angle ); + + this.cone.scale.set( coneWidth, coneWidth, coneLength ); + + _vector$3.setFromMatrixPosition( this.light.target.matrixWorld ); + + this.cone.lookAt( _vector$3 ); + + if ( this.color !== undefined ) { + + this.cone.material.color.set( this.color ); + + } else { + + this.cone.material.color.copy( this.light.color ); + + } + + } + +} + +const _vector$2 = /*@__PURE__*/ new Vector3(); +const _boneMatrix = /*@__PURE__*/ new Matrix4(); +const _matrixWorldInv = /*@__PURE__*/ new Matrix4(); + + +class SkeletonHelper extends LineSegments { + + constructor( object ) { + + const bones = getBoneList( object ); + + const geometry = new BufferGeometry(); + + const vertices = []; + const colors = []; + + const color1 = new Color( 0, 0, 1 ); + const color2 = new Color( 0, 1, 0 ); + + for ( let i = 0; i < bones.length; i ++ ) { + + const bone = bones[ i ]; + + if ( bone.parent && bone.parent.isBone ) { + + vertices.push( 0, 0, 0 ); + vertices.push( 0, 0, 0 ); + colors.push( color1.r, color1.g, color1.b ); + colors.push( color2.r, color2.g, color2.b ); + + } + + } + + geometry.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + geometry.setAttribute( 'color', new Float32BufferAttribute( colors, 3 ) ); + + const material = new LineBasicMaterial( { vertexColors: true, depthTest: false, depthWrite: false, toneMapped: false, transparent: true } ); + + super( geometry, material ); + + this.isSkeletonHelper = true; + + this.type = 'SkeletonHelper'; + + this.root = object; + this.bones = bones; + + this.matrix = object.matrixWorld; + this.matrixAutoUpdate = false; + + } + + updateMatrixWorld( force ) { + + const bones = this.bones; + + const geometry = this.geometry; + const position = geometry.getAttribute( 'position' ); + + _matrixWorldInv.copy( this.root.matrixWorld ).invert(); + + for ( let i = 0, j = 0; i < bones.length; i ++ ) { + + const bone = bones[ i ]; + + if ( bone.parent && bone.parent.isBone ) { + + _boneMatrix.multiplyMatrices( _matrixWorldInv, bone.matrixWorld ); + _vector$2.setFromMatrixPosition( _boneMatrix ); + position.setXYZ( j, _vector$2.x, _vector$2.y, _vector$2.z ); + + _boneMatrix.multiplyMatrices( _matrixWorldInv, bone.parent.matrixWorld ); + _vector$2.setFromMatrixPosition( _boneMatrix ); + position.setXYZ( j + 1, _vector$2.x, _vector$2.y, _vector$2.z ); + + j += 2; + + } + + } + + geometry.getAttribute( 'position' ).needsUpdate = true; + + super.updateMatrixWorld( force ); + + } + + dispose() { + + this.geometry.dispose(); + this.material.dispose(); + + } + +} + + +function getBoneList( object ) { + + const boneList = []; + + if ( object.isBone === true ) { + + boneList.push( object ); + + } + + for ( let i = 0; i < object.children.length; i ++ ) { + + boneList.push.apply( boneList, getBoneList( object.children[ i ] ) ); + + } + + return boneList; + +} + +class PointLightHelper extends Mesh { + + constructor( light, sphereSize, color ) { + + const geometry = new SphereGeometry( sphereSize, 4, 2 ); + const material = new MeshBasicMaterial( { wireframe: true, fog: false, toneMapped: false } ); + + super( geometry, material ); + + this.light = light; + + this.color = color; + + this.type = 'PointLightHelper'; + + this.matrix = this.light.matrixWorld; + this.matrixAutoUpdate = false; + + this.update(); + + + /* + // TODO: delete this comment? + const distanceGeometry = new THREE.IcosahedronGeometry( 1, 2 ); + const distanceMaterial = new THREE.MeshBasicMaterial( { color: hexColor, fog: false, wireframe: true, opacity: 0.1, transparent: true } ); + + this.lightSphere = new THREE.Mesh( bulbGeometry, bulbMaterial ); + this.lightDistance = new THREE.Mesh( distanceGeometry, distanceMaterial ); + + const d = light.distance; + + if ( d === 0.0 ) { + + this.lightDistance.visible = false; + + } else { + + this.lightDistance.scale.set( d, d, d ); + + } + + this.add( this.lightDistance ); + */ + + } + + dispose() { + + this.geometry.dispose(); + this.material.dispose(); + + } + + update() { + + this.light.updateWorldMatrix( true, false ); + + if ( this.color !== undefined ) { + + this.material.color.set( this.color ); + + } else { + + this.material.color.copy( this.light.color ); + + } + + /* + const d = this.light.distance; + + if ( d === 0.0 ) { + + this.lightDistance.visible = false; + + } else { + + this.lightDistance.visible = true; + this.lightDistance.scale.set( d, d, d ); + + } + */ + + } + +} + +const _vector$1 = /*@__PURE__*/ new Vector3(); +const _color1 = /*@__PURE__*/ new Color(); +const _color2 = /*@__PURE__*/ new Color(); + +class HemisphereLightHelper extends Object3D { + + constructor( light, size, color ) { + + super(); + + this.light = light; + + this.matrix = light.matrixWorld; + this.matrixAutoUpdate = false; + + this.color = color; + + this.type = 'HemisphereLightHelper'; + + const geometry = new OctahedronGeometry( size ); + geometry.rotateY( Math.PI * 0.5 ); + + this.material = new MeshBasicMaterial( { wireframe: true, fog: false, toneMapped: false } ); + if ( this.color === undefined ) this.material.vertexColors = true; + + const position = geometry.getAttribute( 'position' ); + const colors = new Float32Array( position.count * 3 ); + + geometry.setAttribute( 'color', new BufferAttribute( colors, 3 ) ); + + this.add( new Mesh( geometry, this.material ) ); + + this.update(); + + } + + dispose() { + + this.children[ 0 ].geometry.dispose(); + this.children[ 0 ].material.dispose(); + + } + + update() { + + const mesh = this.children[ 0 ]; + + if ( this.color !== undefined ) { + + this.material.color.set( this.color ); + + } else { + + const colors = mesh.geometry.getAttribute( 'color' ); + + _color1.copy( this.light.color ); + _color2.copy( this.light.groundColor ); + + for ( let i = 0, l = colors.count; i < l; i ++ ) { + + const color = ( i < ( l / 2 ) ) ? _color1 : _color2; + + colors.setXYZ( i, color.r, color.g, color.b ); + + } + + colors.needsUpdate = true; + + } + + this.light.updateWorldMatrix( true, false ); + + mesh.lookAt( _vector$1.setFromMatrixPosition( this.light.matrixWorld ).negate() ); + + } + +} + +class GridHelper extends LineSegments { + + constructor( size = 10, divisions = 10, color1 = 0x444444, color2 = 0x888888 ) { + + color1 = new Color( color1 ); + color2 = new Color( color2 ); + + const center = divisions / 2; + const step = size / divisions; + const halfSize = size / 2; + + const vertices = [], colors = []; + + for ( let i = 0, j = 0, k = - halfSize; i <= divisions; i ++, k += step ) { + + vertices.push( - halfSize, 0, k, halfSize, 0, k ); + vertices.push( k, 0, - halfSize, k, 0, halfSize ); + + const color = i === center ? color1 : color2; + + color.toArray( colors, j ); j += 3; + color.toArray( colors, j ); j += 3; + color.toArray( colors, j ); j += 3; + color.toArray( colors, j ); j += 3; + + } + + const geometry = new BufferGeometry(); + geometry.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + geometry.setAttribute( 'color', new Float32BufferAttribute( colors, 3 ) ); + + const material = new LineBasicMaterial( { vertexColors: true, toneMapped: false } ); + + super( geometry, material ); + + this.type = 'GridHelper'; + + } + + dispose() { + + this.geometry.dispose(); + this.material.dispose(); + + } + +} + +class PolarGridHelper extends LineSegments { + + constructor( radius = 10, sectors = 16, rings = 8, divisions = 64, color1 = 0x444444, color2 = 0x888888 ) { + + color1 = new Color( color1 ); + color2 = new Color( color2 ); + + const vertices = []; + const colors = []; + + // create the sectors + + if ( sectors > 1 ) { + + for ( let i = 0; i < sectors; i ++ ) { + + const v = ( i / sectors ) * ( Math.PI * 2 ); + + const x = Math.sin( v ) * radius; + const z = Math.cos( v ) * radius; + + vertices.push( 0, 0, 0 ); + vertices.push( x, 0, z ); + + const color = ( i & 1 ) ? color1 : color2; + + colors.push( color.r, color.g, color.b ); + colors.push( color.r, color.g, color.b ); + + } + + } + + // create the rings + + for ( let i = 0; i < rings; i ++ ) { + + const color = ( i & 1 ) ? color1 : color2; + + const r = radius - ( radius / rings * i ); + + for ( let j = 0; j < divisions; j ++ ) { + + // first vertex + + let v = ( j / divisions ) * ( Math.PI * 2 ); + + let x = Math.sin( v ) * r; + let z = Math.cos( v ) * r; + + vertices.push( x, 0, z ); + colors.push( color.r, color.g, color.b ); + + // second vertex + + v = ( ( j + 1 ) / divisions ) * ( Math.PI * 2 ); + + x = Math.sin( v ) * r; + z = Math.cos( v ) * r; + + vertices.push( x, 0, z ); + colors.push( color.r, color.g, color.b ); + + } + + } + + const geometry = new BufferGeometry(); + geometry.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + geometry.setAttribute( 'color', new Float32BufferAttribute( colors, 3 ) ); + + const material = new LineBasicMaterial( { vertexColors: true, toneMapped: false } ); + + super( geometry, material ); + + this.type = 'PolarGridHelper'; + + } + + dispose() { + + this.geometry.dispose(); + this.material.dispose(); + + } + +} + +const _v1 = /*@__PURE__*/ new Vector3(); +const _v2 = /*@__PURE__*/ new Vector3(); +const _v3 = /*@__PURE__*/ new Vector3(); + +class DirectionalLightHelper extends Object3D { + + constructor( light, size, color ) { + + super(); + + this.light = light; + + this.matrix = light.matrixWorld; + this.matrixAutoUpdate = false; + + this.color = color; + + this.type = 'DirectionalLightHelper'; + + if ( size === undefined ) size = 1; + + let geometry = new BufferGeometry(); + geometry.setAttribute( 'position', new Float32BufferAttribute( [ + - size, size, 0, + size, size, 0, + size, - size, 0, + - size, - size, 0, + - size, size, 0 + ], 3 ) ); + + const material = new LineBasicMaterial( { fog: false, toneMapped: false } ); + + this.lightPlane = new Line( geometry, material ); + this.add( this.lightPlane ); + + geometry = new BufferGeometry(); + geometry.setAttribute( 'position', new Float32BufferAttribute( [ 0, 0, 0, 0, 0, 1 ], 3 ) ); + + this.targetLine = new Line( geometry, material ); + this.add( this.targetLine ); + + this.update(); + + } + + dispose() { + + this.lightPlane.geometry.dispose(); + this.lightPlane.material.dispose(); + this.targetLine.geometry.dispose(); + this.targetLine.material.dispose(); + + } + + update() { + + this.light.updateWorldMatrix( true, false ); + this.light.target.updateWorldMatrix( true, false ); + + _v1.setFromMatrixPosition( this.light.matrixWorld ); + _v2.setFromMatrixPosition( this.light.target.matrixWorld ); + _v3.subVectors( _v2, _v1 ); + + this.lightPlane.lookAt( _v2 ); + + if ( this.color !== undefined ) { + + this.lightPlane.material.color.set( this.color ); + this.targetLine.material.color.set( this.color ); + + } else { + + this.lightPlane.material.color.copy( this.light.color ); + this.targetLine.material.color.copy( this.light.color ); + + } + + this.targetLine.lookAt( _v2 ); + this.targetLine.scale.z = _v3.length(); + + } + +} + +const _vector = /*@__PURE__*/ new Vector3(); +const _camera = /*@__PURE__*/ new Camera(); + +/** + * - shows frustum, line of sight and up of the camera + * - suitable for fast updates + * - based on frustum visualization in lightgl.js shadowmap example + * https://github.com/evanw/lightgl.js/blob/master/tests/shadowmap.html + */ + +class CameraHelper extends LineSegments { + + constructor( camera ) { + + const geometry = new BufferGeometry(); + const material = new LineBasicMaterial( { color: 0xffffff, vertexColors: true, toneMapped: false } ); + + const vertices = []; + const colors = []; + + const pointMap = {}; + + // near + + addLine( 'n1', 'n2' ); + addLine( 'n2', 'n4' ); + addLine( 'n4', 'n3' ); + addLine( 'n3', 'n1' ); + + // far + + addLine( 'f1', 'f2' ); + addLine( 'f2', 'f4' ); + addLine( 'f4', 'f3' ); + addLine( 'f3', 'f1' ); + + // sides + + addLine( 'n1', 'f1' ); + addLine( 'n2', 'f2' ); + addLine( 'n3', 'f3' ); + addLine( 'n4', 'f4' ); + + // cone + + addLine( 'p', 'n1' ); + addLine( 'p', 'n2' ); + addLine( 'p', 'n3' ); + addLine( 'p', 'n4' ); + + // up + + addLine( 'u1', 'u2' ); + addLine( 'u2', 'u3' ); + addLine( 'u3', 'u1' ); + + // target + + addLine( 'c', 't' ); + addLine( 'p', 'c' ); + + // cross + + addLine( 'cn1', 'cn2' ); + addLine( 'cn3', 'cn4' ); + + addLine( 'cf1', 'cf2' ); + addLine( 'cf3', 'cf4' ); + + function addLine( a, b ) { + + addPoint( a ); + addPoint( b ); + + } + + function addPoint( id ) { + + vertices.push( 0, 0, 0 ); + colors.push( 0, 0, 0 ); + + if ( pointMap[ id ] === undefined ) { + + pointMap[ id ] = []; + + } + + pointMap[ id ].push( ( vertices.length / 3 ) - 1 ); + + } + + geometry.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + geometry.setAttribute( 'color', new Float32BufferAttribute( colors, 3 ) ); + + super( geometry, material ); + + this.type = 'CameraHelper'; + + this.camera = camera; + if ( this.camera.updateProjectionMatrix ) this.camera.updateProjectionMatrix(); + + this.matrix = camera.matrixWorld; + this.matrixAutoUpdate = false; + + this.pointMap = pointMap; + + this.update(); + + // colors + + const colorFrustum = new Color( 0xffaa00 ); + const colorCone = new Color( 0xff0000 ); + const colorUp = new Color( 0x00aaff ); + const colorTarget = new Color( 0xffffff ); + const colorCross = new Color( 0x333333 ); + + this.setColors( colorFrustum, colorCone, colorUp, colorTarget, colorCross ); + + } + + setColors( frustum, cone, up, target, cross ) { + + const geometry = this.geometry; + + const colorAttribute = geometry.getAttribute( 'color' ); + + // near + + colorAttribute.setXYZ( 0, frustum.r, frustum.g, frustum.b ); colorAttribute.setXYZ( 1, frustum.r, frustum.g, frustum.b ); // n1, n2 + colorAttribute.setXYZ( 2, frustum.r, frustum.g, frustum.b ); colorAttribute.setXYZ( 3, frustum.r, frustum.g, frustum.b ); // n2, n4 + colorAttribute.setXYZ( 4, frustum.r, frustum.g, frustum.b ); colorAttribute.setXYZ( 5, frustum.r, frustum.g, frustum.b ); // n4, n3 + colorAttribute.setXYZ( 6, frustum.r, frustum.g, frustum.b ); colorAttribute.setXYZ( 7, frustum.r, frustum.g, frustum.b ); // n3, n1 + + // far + + colorAttribute.setXYZ( 8, frustum.r, frustum.g, frustum.b ); colorAttribute.setXYZ( 9, frustum.r, frustum.g, frustum.b ); // f1, f2 + colorAttribute.setXYZ( 10, frustum.r, frustum.g, frustum.b ); colorAttribute.setXYZ( 11, frustum.r, frustum.g, frustum.b ); // f2, f4 + colorAttribute.setXYZ( 12, frustum.r, frustum.g, frustum.b ); colorAttribute.setXYZ( 13, frustum.r, frustum.g, frustum.b ); // f4, f3 + colorAttribute.setXYZ( 14, frustum.r, frustum.g, frustum.b ); colorAttribute.setXYZ( 15, frustum.r, frustum.g, frustum.b ); // f3, f1 + + // sides + + colorAttribute.setXYZ( 16, frustum.r, frustum.g, frustum.b ); colorAttribute.setXYZ( 17, frustum.r, frustum.g, frustum.b ); // n1, f1 + colorAttribute.setXYZ( 18, frustum.r, frustum.g, frustum.b ); colorAttribute.setXYZ( 19, frustum.r, frustum.g, frustum.b ); // n2, f2 + colorAttribute.setXYZ( 20, frustum.r, frustum.g, frustum.b ); colorAttribute.setXYZ( 21, frustum.r, frustum.g, frustum.b ); // n3, f3 + colorAttribute.setXYZ( 22, frustum.r, frustum.g, frustum.b ); colorAttribute.setXYZ( 23, frustum.r, frustum.g, frustum.b ); // n4, f4 + + // cone + + colorAttribute.setXYZ( 24, cone.r, cone.g, cone.b ); colorAttribute.setXYZ( 25, cone.r, cone.g, cone.b ); // p, n1 + colorAttribute.setXYZ( 26, cone.r, cone.g, cone.b ); colorAttribute.setXYZ( 27, cone.r, cone.g, cone.b ); // p, n2 + colorAttribute.setXYZ( 28, cone.r, cone.g, cone.b ); colorAttribute.setXYZ( 29, cone.r, cone.g, cone.b ); // p, n3 + colorAttribute.setXYZ( 30, cone.r, cone.g, cone.b ); colorAttribute.setXYZ( 31, cone.r, cone.g, cone.b ); // p, n4 + + // up + + colorAttribute.setXYZ( 32, up.r, up.g, up.b ); colorAttribute.setXYZ( 33, up.r, up.g, up.b ); // u1, u2 + colorAttribute.setXYZ( 34, up.r, up.g, up.b ); colorAttribute.setXYZ( 35, up.r, up.g, up.b ); // u2, u3 + colorAttribute.setXYZ( 36, up.r, up.g, up.b ); colorAttribute.setXYZ( 37, up.r, up.g, up.b ); // u3, u1 + + // target + + colorAttribute.setXYZ( 38, target.r, target.g, target.b ); colorAttribute.setXYZ( 39, target.r, target.g, target.b ); // c, t + colorAttribute.setXYZ( 40, cross.r, cross.g, cross.b ); colorAttribute.setXYZ( 41, cross.r, cross.g, cross.b ); // p, c + + // cross + + colorAttribute.setXYZ( 42, cross.r, cross.g, cross.b ); colorAttribute.setXYZ( 43, cross.r, cross.g, cross.b ); // cn1, cn2 + colorAttribute.setXYZ( 44, cross.r, cross.g, cross.b ); colorAttribute.setXYZ( 45, cross.r, cross.g, cross.b ); // cn3, cn4 + + colorAttribute.setXYZ( 46, cross.r, cross.g, cross.b ); colorAttribute.setXYZ( 47, cross.r, cross.g, cross.b ); // cf1, cf2 + colorAttribute.setXYZ( 48, cross.r, cross.g, cross.b ); colorAttribute.setXYZ( 49, cross.r, cross.g, cross.b ); // cf3, cf4 + + colorAttribute.needsUpdate = true; + + } + + update() { + + const geometry = this.geometry; + const pointMap = this.pointMap; + + const w = 1, h = 1; + + // we need just camera projection matrix inverse + // world matrix must be identity + + _camera.projectionMatrixInverse.copy( this.camera.projectionMatrixInverse ); + + // center / target + + setPoint( 'c', pointMap, geometry, _camera, 0, 0, - 1 ); + setPoint( 't', pointMap, geometry, _camera, 0, 0, 1 ); + + // near + + setPoint( 'n1', pointMap, geometry, _camera, - w, - h, - 1 ); + setPoint( 'n2', pointMap, geometry, _camera, w, - h, - 1 ); + setPoint( 'n3', pointMap, geometry, _camera, - w, h, - 1 ); + setPoint( 'n4', pointMap, geometry, _camera, w, h, - 1 ); + + // far + + setPoint( 'f1', pointMap, geometry, _camera, - w, - h, 1 ); + setPoint( 'f2', pointMap, geometry, _camera, w, - h, 1 ); + setPoint( 'f3', pointMap, geometry, _camera, - w, h, 1 ); + setPoint( 'f4', pointMap, geometry, _camera, w, h, 1 ); + + // up + + setPoint( 'u1', pointMap, geometry, _camera, w * 0.7, h * 1.1, - 1 ); + setPoint( 'u2', pointMap, geometry, _camera, - w * 0.7, h * 1.1, - 1 ); + setPoint( 'u3', pointMap, geometry, _camera, 0, h * 2, - 1 ); + + // cross + + setPoint( 'cf1', pointMap, geometry, _camera, - w, 0, 1 ); + setPoint( 'cf2', pointMap, geometry, _camera, w, 0, 1 ); + setPoint( 'cf3', pointMap, geometry, _camera, 0, - h, 1 ); + setPoint( 'cf4', pointMap, geometry, _camera, 0, h, 1 ); + + setPoint( 'cn1', pointMap, geometry, _camera, - w, 0, - 1 ); + setPoint( 'cn2', pointMap, geometry, _camera, w, 0, - 1 ); + setPoint( 'cn3', pointMap, geometry, _camera, 0, - h, - 1 ); + setPoint( 'cn4', pointMap, geometry, _camera, 0, h, - 1 ); + + geometry.getAttribute( 'position' ).needsUpdate = true; + + } + + dispose() { + + this.geometry.dispose(); + this.material.dispose(); + + } + +} + + +function setPoint( point, pointMap, geometry, camera, x, y, z ) { + + _vector.set( x, y, z ).unproject( camera ); + + const points = pointMap[ point ]; + + if ( points !== undefined ) { + + const position = geometry.getAttribute( 'position' ); + + for ( let i = 0, l = points.length; i < l; i ++ ) { + + position.setXYZ( points[ i ], _vector.x, _vector.y, _vector.z ); + + } + + } + +} + +const _box = /*@__PURE__*/ new Box3(); + +class BoxHelper extends LineSegments { + + constructor( object, color = 0xffff00 ) { + + const indices = new Uint16Array( [ 0, 1, 1, 2, 2, 3, 3, 0, 4, 5, 5, 6, 6, 7, 7, 4, 0, 4, 1, 5, 2, 6, 3, 7 ] ); + const positions = new Float32Array( 8 * 3 ); + + const geometry = new BufferGeometry(); + geometry.setIndex( new BufferAttribute( indices, 1 ) ); + geometry.setAttribute( 'position', new BufferAttribute( positions, 3 ) ); + + super( geometry, new LineBasicMaterial( { color: color, toneMapped: false } ) ); + + this.object = object; + this.type = 'BoxHelper'; + + this.matrixAutoUpdate = false; + + this.update(); + + } + + update( object ) { + + if ( object !== undefined ) { + + console.warn( 'THREE.BoxHelper: .update() has no longer arguments.' ); + + } + + if ( this.object !== undefined ) { + + _box.setFromObject( this.object ); + + } + + if ( _box.isEmpty() ) return; + + const min = _box.min; + const max = _box.max; + + /* + 5____4 + 1/___0/| + | 6__|_7 + 2/___3/ + + 0: max.x, max.y, max.z + 1: min.x, max.y, max.z + 2: min.x, min.y, max.z + 3: max.x, min.y, max.z + 4: max.x, max.y, min.z + 5: min.x, max.y, min.z + 6: min.x, min.y, min.z + 7: max.x, min.y, min.z + */ + + const position = this.geometry.attributes.position; + const array = position.array; + + array[ 0 ] = max.x; array[ 1 ] = max.y; array[ 2 ] = max.z; + array[ 3 ] = min.x; array[ 4 ] = max.y; array[ 5 ] = max.z; + array[ 6 ] = min.x; array[ 7 ] = min.y; array[ 8 ] = max.z; + array[ 9 ] = max.x; array[ 10 ] = min.y; array[ 11 ] = max.z; + array[ 12 ] = max.x; array[ 13 ] = max.y; array[ 14 ] = min.z; + array[ 15 ] = min.x; array[ 16 ] = max.y; array[ 17 ] = min.z; + array[ 18 ] = min.x; array[ 19 ] = min.y; array[ 20 ] = min.z; + array[ 21 ] = max.x; array[ 22 ] = min.y; array[ 23 ] = min.z; + + position.needsUpdate = true; + + this.geometry.computeBoundingSphere(); + + } + + setFromObject( object ) { + + this.object = object; + this.update(); + + return this; + + } + + copy( source, recursive ) { + + super.copy( source, recursive ); + + this.object = source.object; + + return this; + + } + + dispose() { + + this.geometry.dispose(); + this.material.dispose(); + + } + +} + +class Box3Helper extends LineSegments { + + constructor( box, color = 0xffff00 ) { + + const indices = new Uint16Array( [ 0, 1, 1, 2, 2, 3, 3, 0, 4, 5, 5, 6, 6, 7, 7, 4, 0, 4, 1, 5, 2, 6, 3, 7 ] ); + + const positions = [ 1, 1, 1, - 1, 1, 1, - 1, - 1, 1, 1, - 1, 1, 1, 1, - 1, - 1, 1, - 1, - 1, - 1, - 1, 1, - 1, - 1 ]; + + const geometry = new BufferGeometry(); + + geometry.setIndex( new BufferAttribute( indices, 1 ) ); + + geometry.setAttribute( 'position', new Float32BufferAttribute( positions, 3 ) ); + + super( geometry, new LineBasicMaterial( { color: color, toneMapped: false } ) ); + + this.box = box; + + this.type = 'Box3Helper'; + + this.geometry.computeBoundingSphere(); + + } + + updateMatrixWorld( force ) { + + const box = this.box; + + if ( box.isEmpty() ) return; + + box.getCenter( this.position ); + + box.getSize( this.scale ); + + this.scale.multiplyScalar( 0.5 ); + + super.updateMatrixWorld( force ); + + } + + dispose() { + + this.geometry.dispose(); + this.material.dispose(); + + } + +} + +class PlaneHelper extends Line { + + constructor( plane, size = 1, hex = 0xffff00 ) { + + const color = hex; + + const positions = [ 1, - 1, 0, - 1, 1, 0, - 1, - 1, 0, 1, 1, 0, - 1, 1, 0, - 1, - 1, 0, 1, - 1, 0, 1, 1, 0 ]; + + const geometry = new BufferGeometry(); + geometry.setAttribute( 'position', new Float32BufferAttribute( positions, 3 ) ); + geometry.computeBoundingSphere(); + + super( geometry, new LineBasicMaterial( { color: color, toneMapped: false } ) ); + + this.type = 'PlaneHelper'; + + this.plane = plane; + + this.size = size; + + const positions2 = [ 1, 1, 0, - 1, 1, 0, - 1, - 1, 0, 1, 1, 0, - 1, - 1, 0, 1, - 1, 0 ]; + + const geometry2 = new BufferGeometry(); + geometry2.setAttribute( 'position', new Float32BufferAttribute( positions2, 3 ) ); + geometry2.computeBoundingSphere(); + + this.add( new Mesh( geometry2, new MeshBasicMaterial( { color: color, opacity: 0.2, transparent: true, depthWrite: false, toneMapped: false } ) ) ); + + } + + updateMatrixWorld( force ) { + + this.position.set( 0, 0, 0 ); + + this.scale.set( 0.5 * this.size, 0.5 * this.size, 1 ); + + this.lookAt( this.plane.normal ); + + this.translateZ( - this.plane.constant ); + + super.updateMatrixWorld( force ); + + } + + dispose() { + + this.geometry.dispose(); + this.material.dispose(); + this.children[ 0 ].geometry.dispose(); + this.children[ 0 ].material.dispose(); + + } + +} + +const _axis = /*@__PURE__*/ new Vector3(); +let _lineGeometry, _coneGeometry; + +class ArrowHelper extends Object3D { + + // dir is assumed to be normalized + + constructor( dir = new Vector3( 0, 0, 1 ), origin = new Vector3( 0, 0, 0 ), length = 1, color = 0xffff00, headLength = length * 0.2, headWidth = headLength * 0.2 ) { + + super(); + + this.type = 'ArrowHelper'; + + if ( _lineGeometry === undefined ) { + + _lineGeometry = new BufferGeometry(); + _lineGeometry.setAttribute( 'position', new Float32BufferAttribute( [ 0, 0, 0, 0, 1, 0 ], 3 ) ); + + _coneGeometry = new CylinderGeometry( 0, 0.5, 1, 5, 1 ); + _coneGeometry.translate( 0, - 0.5, 0 ); + + } + + this.position.copy( origin ); + + this.line = new Line( _lineGeometry, new LineBasicMaterial( { color: color, toneMapped: false } ) ); + this.line.matrixAutoUpdate = false; + this.add( this.line ); + + this.cone = new Mesh( _coneGeometry, new MeshBasicMaterial( { color: color, toneMapped: false } ) ); + this.cone.matrixAutoUpdate = false; + this.add( this.cone ); + + this.setDirection( dir ); + this.setLength( length, headLength, headWidth ); + + } + + setDirection( dir ) { + + // dir is assumed to be normalized + + if ( dir.y > 0.99999 ) { + + this.quaternion.set( 0, 0, 0, 1 ); + + } else if ( dir.y < - 0.99999 ) { + + this.quaternion.set( 1, 0, 0, 0 ); + + } else { + + _axis.set( dir.z, 0, - dir.x ).normalize(); + + const radians = Math.acos( dir.y ); + + this.quaternion.setFromAxisAngle( _axis, radians ); + + } + + } + + setLength( length, headLength = length * 0.2, headWidth = headLength * 0.2 ) { + + this.line.scale.set( 1, Math.max( 0.0001, length - headLength ), 1 ); // see #17458 + this.line.updateMatrix(); + + this.cone.scale.set( headWidth, headLength, headWidth ); + this.cone.position.y = length; + this.cone.updateMatrix(); + + } + + setColor( color ) { + + this.line.material.color.set( color ); + this.cone.material.color.set( color ); + + } + + copy( source ) { + + super.copy( source, false ); + + this.line.copy( source.line ); + this.cone.copy( source.cone ); + + return this; + + } + + dispose() { + + this.line.geometry.dispose(); + this.line.material.dispose(); + this.cone.geometry.dispose(); + this.cone.material.dispose(); + + } + +} + +class AxesHelper extends LineSegments { + + constructor( size = 1 ) { + + const vertices = [ + 0, 0, 0, size, 0, 0, + 0, 0, 0, 0, size, 0, + 0, 0, 0, 0, 0, size + ]; + + const colors = [ + 1, 0, 0, 1, 0.6, 0, + 0, 1, 0, 0.6, 1, 0, + 0, 0, 1, 0, 0.6, 1 + ]; + + const geometry = new BufferGeometry(); + geometry.setAttribute( 'position', new Float32BufferAttribute( vertices, 3 ) ); + geometry.setAttribute( 'color', new Float32BufferAttribute( colors, 3 ) ); + + const material = new LineBasicMaterial( { vertexColors: true, toneMapped: false } ); + + super( geometry, material ); + + this.type = 'AxesHelper'; + + } + + setColors( xAxisColor, yAxisColor, zAxisColor ) { + + const color = new Color(); + const array = this.geometry.attributes.color.array; + + color.set( xAxisColor ); + color.toArray( array, 0 ); + color.toArray( array, 3 ); + + color.set( yAxisColor ); + color.toArray( array, 6 ); + color.toArray( array, 9 ); + + color.set( zAxisColor ); + color.toArray( array, 12 ); + color.toArray( array, 15 ); + + this.geometry.attributes.color.needsUpdate = true; + + return this; + + } + + dispose() { + + this.geometry.dispose(); + this.material.dispose(); + + } + +} + +class ShapePath { + + constructor() { + + this.type = 'ShapePath'; + + this.color = new Color(); + + this.subPaths = []; + this.currentPath = null; + + } + + moveTo( x, y ) { + + this.currentPath = new Path(); + this.subPaths.push( this.currentPath ); + this.currentPath.moveTo( x, y ); + + return this; + + } + + lineTo( x, y ) { + + this.currentPath.lineTo( x, y ); + + return this; + + } + + quadraticCurveTo( aCPx, aCPy, aX, aY ) { + + this.currentPath.quadraticCurveTo( aCPx, aCPy, aX, aY ); + + return this; + + } + + bezierCurveTo( aCP1x, aCP1y, aCP2x, aCP2y, aX, aY ) { + + this.currentPath.bezierCurveTo( aCP1x, aCP1y, aCP2x, aCP2y, aX, aY ); + + return this; + + } + + splineThru( pts ) { + + this.currentPath.splineThru( pts ); + + return this; + + } + + toShapes( isCCW ) { + + function toShapesNoHoles( inSubpaths ) { + + const shapes = []; + + for ( let i = 0, l = inSubpaths.length; i < l; i ++ ) { + + const tmpPath = inSubpaths[ i ]; + + const tmpShape = new Shape(); + tmpShape.curves = tmpPath.curves; + + shapes.push( tmpShape ); + + } + + return shapes; + + } + + function isPointInsidePolygon( inPt, inPolygon ) { + + const polyLen = inPolygon.length; + + // inPt on polygon contour => immediate success or + // toggling of inside/outside at every single! intersection point of an edge + // with the horizontal line through inPt, left of inPt + // not counting lowerY endpoints of edges and whole edges on that line + let inside = false; + for ( let p = polyLen - 1, q = 0; q < polyLen; p = q ++ ) { + + let edgeLowPt = inPolygon[ p ]; + let edgeHighPt = inPolygon[ q ]; + + let edgeDx = edgeHighPt.x - edgeLowPt.x; + let edgeDy = edgeHighPt.y - edgeLowPt.y; + + if ( Math.abs( edgeDy ) > Number.EPSILON ) { + + // not parallel + if ( edgeDy < 0 ) { + + edgeLowPt = inPolygon[ q ]; edgeDx = - edgeDx; + edgeHighPt = inPolygon[ p ]; edgeDy = - edgeDy; + + } + + if ( ( inPt.y < edgeLowPt.y ) || ( inPt.y > edgeHighPt.y ) ) continue; + + if ( inPt.y === edgeLowPt.y ) { + + if ( inPt.x === edgeLowPt.x ) return true; // inPt is on contour ? + // continue; // no intersection or edgeLowPt => doesn't count !!! + + } else { + + const perpEdge = edgeDy * ( inPt.x - edgeLowPt.x ) - edgeDx * ( inPt.y - edgeLowPt.y ); + if ( perpEdge === 0 ) return true; // inPt is on contour ? + if ( perpEdge < 0 ) continue; + inside = ! inside; // true intersection left of inPt + + } + + } else { + + // parallel or collinear + if ( inPt.y !== edgeLowPt.y ) continue; // parallel + // edge lies on the same horizontal line as inPt + if ( ( ( edgeHighPt.x <= inPt.x ) && ( inPt.x <= edgeLowPt.x ) ) || + ( ( edgeLowPt.x <= inPt.x ) && ( inPt.x <= edgeHighPt.x ) ) ) return true; // inPt: Point on contour ! + // continue; + + } + + } + + return inside; + + } + + const isClockWise = ShapeUtils.isClockWise; + + const subPaths = this.subPaths; + if ( subPaths.length === 0 ) return []; + + let solid, tmpPath, tmpShape; + const shapes = []; + + if ( subPaths.length === 1 ) { + + tmpPath = subPaths[ 0 ]; + tmpShape = new Shape(); + tmpShape.curves = tmpPath.curves; + shapes.push( tmpShape ); + return shapes; + + } + + let holesFirst = ! isClockWise( subPaths[ 0 ].getPoints() ); + holesFirst = isCCW ? ! holesFirst : holesFirst; + + // console.log("Holes first", holesFirst); + + const betterShapeHoles = []; + const newShapes = []; + let newShapeHoles = []; + let mainIdx = 0; + let tmpPoints; + + newShapes[ mainIdx ] = undefined; + newShapeHoles[ mainIdx ] = []; + + for ( let i = 0, l = subPaths.length; i < l; i ++ ) { + + tmpPath = subPaths[ i ]; + tmpPoints = tmpPath.getPoints(); + solid = isClockWise( tmpPoints ); + solid = isCCW ? ! solid : solid; + + if ( solid ) { + + if ( ( ! holesFirst ) && ( newShapes[ mainIdx ] ) ) mainIdx ++; + + newShapes[ mainIdx ] = { s: new Shape(), p: tmpPoints }; + newShapes[ mainIdx ].s.curves = tmpPath.curves; + + if ( holesFirst ) mainIdx ++; + newShapeHoles[ mainIdx ] = []; + + //console.log('cw', i); + + } else { + + newShapeHoles[ mainIdx ].push( { h: tmpPath, p: tmpPoints[ 0 ] } ); + + //console.log('ccw', i); + + } + + } + + // only Holes? -> probably all Shapes with wrong orientation + if ( ! newShapes[ 0 ] ) return toShapesNoHoles( subPaths ); + + + if ( newShapes.length > 1 ) { + + let ambiguous = false; + let toChange = 0; + + for ( let sIdx = 0, sLen = newShapes.length; sIdx < sLen; sIdx ++ ) { + + betterShapeHoles[ sIdx ] = []; + + } + + for ( let sIdx = 0, sLen = newShapes.length; sIdx < sLen; sIdx ++ ) { + + const sho = newShapeHoles[ sIdx ]; + + for ( let hIdx = 0; hIdx < sho.length; hIdx ++ ) { + + const ho = sho[ hIdx ]; + let hole_unassigned = true; + + for ( let s2Idx = 0; s2Idx < newShapes.length; s2Idx ++ ) { + + if ( isPointInsidePolygon( ho.p, newShapes[ s2Idx ].p ) ) { + + if ( sIdx !== s2Idx ) toChange ++; + + if ( hole_unassigned ) { + + hole_unassigned = false; + betterShapeHoles[ s2Idx ].push( ho ); + + } else { + + ambiguous = true; + + } + + } + + } + + if ( hole_unassigned ) { + + betterShapeHoles[ sIdx ].push( ho ); + + } + + } + + } + + if ( toChange > 0 && ambiguous === false ) { + + newShapeHoles = betterShapeHoles; + + } + + } + + let tmpHoles; + + for ( let i = 0, il = newShapes.length; i < il; i ++ ) { + + tmpShape = newShapes[ i ].s; + shapes.push( tmpShape ); + tmpHoles = newShapeHoles[ i ]; + + for ( let j = 0, jl = tmpHoles.length; j < jl; j ++ ) { + + tmpShape.holes.push( tmpHoles[ j ].h ); + + } + + } + + //console.log("shape", shapes); + + return shapes; + + } + +} + +class WebGLMultipleRenderTargets extends WebGLRenderTarget { // @deprecated, r162 + + constructor( width = 1, height = 1, count = 1, options = {} ) { + + console.warn( 'THREE.WebGLMultipleRenderTargets has been deprecated and will be removed in r172. Use THREE.WebGLRenderTarget and set the "count" parameter to enable MRT.' ); + + super( width, height, { ...options, count } ); + + this.isWebGLMultipleRenderTargets = true; + + } + + get texture() { + + return this.textures; + + } + +} + +if ( typeof __THREE_DEVTOOLS__ !== 'undefined' ) { + + __THREE_DEVTOOLS__.dispatchEvent( new CustomEvent( 'register', { detail: { + revision: REVISION, + } } ) ); + +} + +if ( typeof window !== 'undefined' ) { + + if ( window.__THREE__ ) { + + console.warn( 'WARNING: Multiple instances of Three.js being imported.' ); + + } else { + + window.__THREE__ = REVISION; + + } + +} + +export { ACESFilmicToneMapping, AddEquation, AddOperation, AdditiveAnimationBlendMode, AdditiveBlending, AgXToneMapping, AlphaFormat, AlwaysCompare, AlwaysDepth, AlwaysStencilFunc, AmbientLight, AnimationAction, AnimationClip, AnimationLoader, AnimationMixer, AnimationObjectGroup, AnimationUtils, ArcCurve, ArrayCamera, ArrowHelper, AttachedBindMode, Audio, AudioAnalyser, AudioContext, AudioListener, AudioLoader, AxesHelper, BackSide, BasicDepthPacking, BasicShadowMap, BatchedMesh, Bone, BooleanKeyframeTrack, Box2, Box3, Box3Helper, BoxGeometry, BoxHelper, BufferAttribute, BufferGeometry, BufferGeometryLoader, ByteType, Cache, Camera, CameraHelper, CanvasTexture, CapsuleGeometry, CatmullRomCurve3, CineonToneMapping, CircleGeometry, ClampToEdgeWrapping, Clock, Color, ColorKeyframeTrack, ColorManagement, CompressedArrayTexture, CompressedCubeTexture, CompressedTexture, CompressedTextureLoader, ConeGeometry, ConstantAlphaFactor, ConstantColorFactor, CubeCamera, CubeReflectionMapping, CubeRefractionMapping, CubeTexture, CubeTextureLoader, CubeUVReflectionMapping, CubicBezierCurve, CubicBezierCurve3, CubicInterpolant, CullFaceBack, CullFaceFront, CullFaceFrontBack, CullFaceNone, Curve, CurvePath, CustomBlending, CustomToneMapping, CylinderGeometry, Cylindrical, Data3DTexture, DataArrayTexture, DataTexture, DataTextureLoader, DataUtils, DecrementStencilOp, DecrementWrapStencilOp, DefaultLoadingManager, DepthFormat, DepthStencilFormat, DepthTexture, DetachedBindMode, DirectionalLight, DirectionalLightHelper, DiscreteInterpolant, DisplayP3ColorSpace, DodecahedronGeometry, DoubleSide, DstAlphaFactor, DstColorFactor, DynamicCopyUsage, DynamicDrawUsage, DynamicReadUsage, EdgesGeometry, EllipseCurve, EqualCompare, EqualDepth, EqualStencilFunc, EquirectangularReflectionMapping, EquirectangularRefractionMapping, Euler, EventDispatcher, ExtrudeGeometry, FileLoader, Float16BufferAttribute, Float32BufferAttribute, FloatType, Fog, FogExp2, FramebufferTexture, FrontSide, Frustum, GLBufferAttribute, GLSL1, GLSL3, GreaterCompare, GreaterDepth, GreaterEqualCompare, GreaterEqualDepth, GreaterEqualStencilFunc, GreaterStencilFunc, GridHelper, Group, HalfFloatType, HemisphereLight, HemisphereLightHelper, IcosahedronGeometry, ImageBitmapLoader, ImageLoader, ImageUtils, IncrementStencilOp, IncrementWrapStencilOp, InstancedBufferAttribute, InstancedBufferGeometry, InstancedInterleavedBuffer, InstancedMesh, Int16BufferAttribute, Int32BufferAttribute, Int8BufferAttribute, IntType, InterleavedBuffer, InterleavedBufferAttribute, Interpolant, InterpolateDiscrete, InterpolateLinear, InterpolateSmooth, InvertStencilOp, KeepStencilOp, KeyframeTrack, LOD, LatheGeometry, Layers, LessCompare, LessDepth, LessEqualCompare, LessEqualDepth, LessEqualStencilFunc, LessStencilFunc, Light, LightProbe, Line, Line3, LineBasicMaterial, LineCurve, LineCurve3, LineDashedMaterial, LineLoop, LineSegments, LinearDisplayP3ColorSpace, LinearFilter, LinearInterpolant, LinearMipMapLinearFilter, LinearMipMapNearestFilter, LinearMipmapLinearFilter, LinearMipmapNearestFilter, LinearSRGBColorSpace, LinearToneMapping, LinearTransfer, Loader, LoaderUtils, LoadingManager, LoopOnce, LoopPingPong, LoopRepeat, LuminanceAlphaFormat, LuminanceFormat, MOUSE, Material, MaterialLoader, MathUtils, Matrix3, Matrix4, MaxEquation, Mesh, MeshBasicMaterial, MeshDepthMaterial, MeshDistanceMaterial, MeshLambertMaterial, MeshMatcapMaterial, MeshNormalMaterial, MeshPhongMaterial, MeshPhysicalMaterial, MeshStandardMaterial, MeshToonMaterial, MinEquation, MirroredRepeatWrapping, MixOperation, MultiplyBlending, MultiplyOperation, NearestFilter, NearestMipMapLinearFilter, NearestMipMapNearestFilter, NearestMipmapLinearFilter, NearestMipmapNearestFilter, NeutralToneMapping, NeverCompare, NeverDepth, NeverStencilFunc, NoBlending, NoColorSpace, NoToneMapping, NormalAnimationBlendMode, NormalBlending, NotEqualCompare, NotEqualDepth, NotEqualStencilFunc, NumberKeyframeTrack, Object3D, ObjectLoader, ObjectSpaceNormalMap, OctahedronGeometry, OneFactor, OneMinusConstantAlphaFactor, OneMinusConstantColorFactor, OneMinusDstAlphaFactor, OneMinusDstColorFactor, OneMinusSrcAlphaFactor, OneMinusSrcColorFactor, OrthographicCamera, P3Primaries, PCFShadowMap, PCFSoftShadowMap, PMREMGenerator, Path, PerspectiveCamera, Plane, PlaneGeometry, PlaneHelper, PointLight, PointLightHelper, Points, PointsMaterial, PolarGridHelper, PolyhedronGeometry, PositionalAudio, PropertyBinding, PropertyMixer, QuadraticBezierCurve, QuadraticBezierCurve3, Quaternion, QuaternionKeyframeTrack, QuaternionLinearInterpolant, RED_GREEN_RGTC2_Format, RED_RGTC1_Format, REVISION, RGBADepthPacking, RGBAFormat, RGBAIntegerFormat, RGBA_ASTC_10x10_Format, RGBA_ASTC_10x5_Format, RGBA_ASTC_10x6_Format, RGBA_ASTC_10x8_Format, RGBA_ASTC_12x10_Format, RGBA_ASTC_12x12_Format, RGBA_ASTC_4x4_Format, RGBA_ASTC_5x4_Format, RGBA_ASTC_5x5_Format, RGBA_ASTC_6x5_Format, RGBA_ASTC_6x6_Format, RGBA_ASTC_8x5_Format, RGBA_ASTC_8x6_Format, RGBA_ASTC_8x8_Format, RGBA_BPTC_Format, RGBA_ETC2_EAC_Format, RGBA_PVRTC_2BPPV1_Format, RGBA_PVRTC_4BPPV1_Format, RGBA_S3TC_DXT1_Format, RGBA_S3TC_DXT3_Format, RGBA_S3TC_DXT5_Format, RGBFormat, RGB_BPTC_SIGNED_Format, RGB_BPTC_UNSIGNED_Format, RGB_ETC1_Format, RGB_ETC2_Format, RGB_PVRTC_2BPPV1_Format, RGB_PVRTC_4BPPV1_Format, RGB_S3TC_DXT1_Format, RGFormat, RGIntegerFormat, RawShaderMaterial, Ray, Raycaster, Rec709Primaries, RectAreaLight, RedFormat, RedIntegerFormat, ReinhardToneMapping, RenderTarget, RepeatWrapping, ReplaceStencilOp, ReverseSubtractEquation, RingGeometry, SIGNED_RED_GREEN_RGTC2_Format, SIGNED_RED_RGTC1_Format, SRGBColorSpace, SRGBTransfer, Scene, ShaderChunk, ShaderLib, ShaderMaterial, ShadowMaterial, Shape, ShapeGeometry, ShapePath, ShapeUtils, ShortType, Skeleton, SkeletonHelper, SkinnedMesh, Source, Sphere, SphereGeometry, Spherical, SphericalHarmonics3, SplineCurve, SpotLight, SpotLightHelper, Sprite, SpriteMaterial, SrcAlphaFactor, SrcAlphaSaturateFactor, SrcColorFactor, StaticCopyUsage, StaticDrawUsage, StaticReadUsage, StereoCamera, StreamCopyUsage, StreamDrawUsage, StreamReadUsage, StringKeyframeTrack, SubtractEquation, SubtractiveBlending, TOUCH, TangentSpaceNormalMap, TetrahedronGeometry, Texture, TextureLoader, TorusGeometry, TorusKnotGeometry, Triangle, TriangleFanDrawMode, TriangleStripDrawMode, TrianglesDrawMode, TubeGeometry, UVMapping, Uint16BufferAttribute, Uint32BufferAttribute, Uint8BufferAttribute, Uint8ClampedBufferAttribute, Uniform, UniformsGroup, UniformsLib, UniformsUtils, UnsignedByteType, UnsignedInt248Type, UnsignedInt5999Type, UnsignedIntType, UnsignedShort4444Type, UnsignedShort5551Type, UnsignedShortType, VSMShadowMap, Vector2, Vector3, Vector4, VectorKeyframeTrack, VideoTexture, WebGL3DRenderTarget, WebGLArrayRenderTarget, WebGLCoordinateSystem, WebGLCubeRenderTarget, WebGLMultipleRenderTargets, WebGLRenderTarget, WebGLRenderer, WebGLUtils, WebGPUCoordinateSystem, WireframeGeometry, WrapAroundEnding, ZeroCurvatureEnding, ZeroFactor, ZeroSlopeEnding, ZeroStencilOp, createCanvasElement }; diff --git a/docs/practical_performance.md b/docs/practical_performance.md new file mode 100644 index 0000000..0e86842 --- /dev/null +++ b/docs/practical_performance.md @@ -0,0 +1,148 @@ +# Practical Performance +The genus for various cage graphs using the adjacency lists from [win.tue.nl](https://www.win.tue.nl/~aeb/graphs/cages/cages.html). Number (\# links to adjacency list), valency (k), girth (g), vertices (v), edges (e), size of the automorphism group (\|G\|), genus, computation time for the genus (time), computation time for the genus using SageMath (SM time), and computation time using multi_genus.c (MG time). +\# | k | g | v | e | \|G\| | genus | time (s) | SM time (s) | MG time (s) +----------------------------------------------- | --- | --- | ---- | ----- | ---------- | ---------- | -------- | ----------- | ----------- +[1/1](../PAGE/adjacency_lists/3-3-cage.txt) | 3 | 3 | 4 | 6 | 24 | 0 | 0.004 | 0.004 | 0.006 +[1/1](../PAGE/adjacency_lists/3-4-cage.txt) | 3 | 4 | 6 | 9 | 72 | 1 | 0.003 | 0.039 | 0.006 +[1/1](../PAGE/adjacency_lists/3-5-cage.txt) | 3 | 5 | 10 | 15 | 120 | 1 | 0.005 | 0.027 | 0.006 +[1/1](../PAGE/adjacency_lists/3-6-cage.txt) | 3 | 6 | 14 | 21 | 336 | 1 | 0.005 | 0.010 | 0.006 +[1/1](../PAGE/adjacency_lists/3-7-cage.txt) | 3 | 7 | 24 | 36 | 32 | 2 | 0.005 | 1.737 | 0.006 +[1/1](../PAGE/adjacency_lists/3-8-cage.txt) | 3 | 8 | 30 | 45 | 1440 | 4 | 0.016 | 118.958 | 0.012 +[1/18](../PAGE/adjacency_lists/3-9-cage1.txt) | 3 | 9 | 58 | 87 | 4 | 7 | 0.222 | days | 29.084 +[2/18](../PAGE/adjacency_lists/3-9-cage2.txt) | 3 | 9 | 58 | 87 | 2 | 7 | 1.018 | days | 30.909 +[3/18](../PAGE/adjacency_lists/3-9-cage3.txt) | 3 | 9 | 58 | 87 | 24 | 7 | 1.851 | days | 25.993 +[4/18](../PAGE/adjacency_lists/3-9-cage4.txt) | 3 | 9 | 58 | 87 | 4 | 7 | 0.301 | days | 54.396 +[5/18](../PAGE/adjacency_lists/3-9-cage5.txt) | 3 | 9 | 58 | 87 | 4 | 7 | 0.380 | days | 67.89 +[6/18](../PAGE/adjacency_lists/3-9-cage6.txt) | 3 | 9 | 58 | 87 | 2 | 7 | 0.330 | days | 45.310 +[7/18](../PAGE/adjacency_lists/3-9-cage7.txt) | 3 | 9 | 58 | 87 | 1 | 7 | 0.639 | days | 37.257 +[8/18](../PAGE/adjacency_lists/3-9-cage8.txt) | 3 | 9 | 58 | 87 | 2 | 7 | 1.024 | days | 42.843 +[9/18](../PAGE/adjacency_lists/3-9-cage9.txt) | 3 | 9 | 58 | 87 | 1 | 7 | 0.903 | days | 34.437 +[10/18](../PAGE/adjacency_lists/3-9-cage10.txt) | 3 | 9 | 58 | 87 | 2 | 7 | 0.215 | days | 86.54 +[11/18](../PAGE/adjacency_lists/3-9-cage11.txt) | 3 | 9 | 58 | 87 | 1 | 7 | 0.204 | days | 54.990 +[12/18](../PAGE/adjacency_lists/3-9-cage12.txt) | 3 | 9 | 58 | 87 | 2 | 7 | 1.273 | days | 51.589 +[13/18](../PAGE/adjacency_lists/3-9-cage13.txt) | 3 | 9 | 58 | 87 | 1 | 7 | 0.839 | days | 32.340 +[14/18](../PAGE/adjacency_lists/3-9-cage14.txt) | 3 | 9 | 58 | 87 | 12 | 7 | 1.056 | days | 30.824 +[15/18](../PAGE/adjacency_lists/3-9-cage15.txt) | 3 | 9 | 58 | 87 | 8 | 7 | 0.530 | days | 44.888 +[16/18](../PAGE/adjacency_lists/3-9-cage16.txt) | 3 | 9 | 58 | 87 | 2 | 7 | 0.208 | days | 57.890 +[17/18](../PAGE/adjacency_lists/3-9-cage17.txt) | 3 | 9 | 58 | 87 | 6 | 7 | 0.879 | days | 140.50 +[18/18](../PAGE/adjacency_lists/3-9-cage18.txt) | 3 | 9 | 58 | 87 | 6 | 7 | 0.849 | days | 47.737 +[1/3](../PAGE/adjacency_lists/3-10-cage1.txt) | 3 | 10 | 70 | 105 | 120 | 9 | 0.547 | DNF | 9354.14 +[2/3](../PAGE/adjacency_lists/3-10-cage2.txt) | 3 | 10 | 70 | 105 | 24 | 9 | 0.694 | DNF | 9556.13 +[3/3](../PAGE/adjacency_lists/3-10-cage3.txt) | 3 | 10 | 70 | 105 | 80 | 9 | 0.418 | DNF | 10680.89 +[1/1](../PAGE/adjacency_lists/3-11-cage.txt) | 3 | 11 | 112 | 168 | 64 | [15, 17] | days | DNF | days +[1/1](../PAGE/adjacency_lists/3-12-cage.txt) | 3 | 12 | 126 | 189 | 12096 | 17 | 0.427 | DNF | days +[1/1](../PAGE/adjacency_lists/4-5-cage.txt) | 4 | 5 | 19 | 38 | 24 | 4 | 0.064 | days | 0.019 +[1/1](../PAGE/adjacency_lists/4-6-cage.txt) | 4 | 6 | 26 | 52 | 11232 | 6 | 0.016 | DNF | 0.013 +[1/?](../PAGE/adjacency_lists/4-7-cage1.txt) | 4 | 7 | 67 | 134 | 4 | [16, 21] | days | DNF | days +[1/1](../PAGE/adjacency_lists/4-8-cage.txt) | 4 | 8 | 80 | 160 | 51840 | [21, 27] | days | DNF | days +[1/?](../PAGE/adjacency_lists/4-12-cage1.txt) | 4 | 12 | 728 | 1456 | 8491392 | [244, 363] | DNF | DNF | too big for bit operations +[1/4](../PAGE/adjacency_lists/5-5-cage1.txt) | 5 | 5 | 30 | 75 | 120 | [9, 10] | days | DNF | days +[2/4](../PAGE/adjacency_lists/5-5-cage2.txt) | 5 | 5 | 30 | 75 | 20 | [9, 13] | days | DNF | days +[3/4](../PAGE/adjacency_lists/5-5-cage3.txt) | 5 | 5 | 30 | 75 | 30 | [9, 14] | days | DNF | days +[4/4](../PAGE/adjacency_lists/5-5-cage4.txt) | 5 | 5 | 30 | 75 | 96 | [9, 14] | days | DNF | days +[1/1](../PAGE/adjacency_lists/5-6-cage.txt) | 5 | 6 | 42 | 105 | 241920 | [15, 17] | days | DNF | days +[1/1](../PAGE/adjacency_lists/5-8-cage.txt) | 5 | 8 | 170 | 425 | 3916800 | [76, 126] | DNF | DNF | too big for bit operations +[1/?](../PAGE/adjacency_lists/5-12-cage1.txt) | 5 | 12 | 2730 | 6825 | 503193600 |[1480, 2048]| OOM | DNF | too big for bit operations +[1/1](../PAGE/adjacency_lists/6-5-cage.txt) | 6 | 5 | 40 | 120 | 480 | [17, 22] | days | DNF | days +[1/1](../PAGE/adjacency_lists/6-6-cage.txt) | 6 | 6 | 62 | 186 | 744000 | [32, 60] | DNF | DNF | DNF +[1/1](../PAGE/adjacency_lists/6-8-cage.txt) | 6 | 8 | 312 | 936 | 9360000 | [196, 310] | DNF | DNF | too big for bit operations +[1/?](../PAGE/adjacency_lists/6-12-cage1.txt) | 6 | 12 | 7812 | 23436 | 5859000000 |[5860, 7810]| OOM | DNF | too big for bit operations +[1/1](../PAGE/adjacency_lists/7-5-cage.txt) | 7 | 5 | 50 | 175 | 252000 | [29, 39] | DNF | DNF | DNF +[1/1](../PAGE/adjacency_lists/7-6-cage.txt) | 7 | 6 | 90 | 315 | 15120 | [61, 110] | DNF | DNF | DNF + +The genus for various complete graphs generated using the `CompleteGraph` function in SageMath follows. +\# | k | g | v | e | \|G\| | genus | time (s) | SM time (s) | MG time (s) +-------------------------------------- | --- | --- | ---- | ----- | ------------------ | -------- | -------- | ----------- | ----------- +[k2](../PAGE/adjacency_lists/k2.txt) | 1 | Inf | 2 | 1 | 2 | 0 | --- | 0.004 | --- +[k3](../PAGE/adjacency_lists/k3.txt) | 2 | 3 | 3 | 3 | 6 | 0 | 0.004 | 0.004 | 0.008 +[k4](../PAGE/adjacency_lists/k4.txt) | 3 | 3 | 4 | 6 | 24 | 0 | 0.004 | 0.003 | 0.008 +[k5](../PAGE/adjacency_lists/k5.txt) | 4 | 3 | 5 | 10 | 120 | 1 | 0.004 | 0.005 | 0.008 +[k6](../PAGE/adjacency_lists/k6.txt) | 5 | 3 | 6 | 15 | 720 | 1 | 0.004 | 0.023 | 0.008 +[k7](../PAGE/adjacency_lists/k7.txt) | 6 | 3 | 7 | 21 | 5040 | 1 | 0.004 | days | 0.009 +[k8](../PAGE/adjacency_lists/k8.txt) | 7 | 3 | 8 | 28 | 40320 | 2 | 0.004 | DNF | 0.008 +[k9](../PAGE/adjacency_lists/k9.txt) | 8 | 3 | 9 | 36 | 362880 | 3 | 0.004 | DNF | 0.008 + +The genus for various complete bipartite graphs generated using the `CompleteBipartiteGraph` function in SageMath follows. Number (\# links to adjacency list), valency (k), girth (g), vertices (v), edges (e), size of the automorphism group (\|G\|), genus, computation time for the genus (time), and computation time for the genus using SageMath (SM time). +\# | k | g | v | e | \|G\| | genus | time (s) | SM time (s) | MG time (s) +---------------------------------------- | --- | --- | ---- | ----- | ------------ | -------- | -------- | ----------- | ----------- +[k3-3](../PAGE/adjacency_lists/k3-3.txt) | 3 | 4 | 6 | 9 | 72 | 1 | 0.004 | 0.047 | 0.006 +[k4-4](../PAGE/adjacency_lists/k4-4.txt) | 4 | 4 | 8 | 16 | 1152 | 1 | 0.004 | 0.010 | 0.010 +[k5-5](../PAGE/adjacency_lists/k5-5.txt) | 5 | 4 | 10 | 25 | 28800 | 3 | 0.008 | DNF | 0.008 +[k6-6](../PAGE/adjacency_lists/k6-6.txt) | 6 | 4 | 12 | 36 | 1036800 | 4 | 0.005 | DNF | 0.009 + +The genus for various complete n-partite graphs generated using the `CompleteMultipartiteGraph` function in SageMath follows. +\# | v | e | genus | time (s) | MG time (s) +------------------------------------------------------------------------------ | ---- | ----- | -------- | -------- | ----------- +[k2-2](../PAGE/adjacency_lists/k2-2.txt) | 4 | 4 | 0 | 0.004 | 0.008 +[k2-2-2](../PAGE/adjacency_lists/k2-2-2.txt) | 6 | 12 | 0 | 0.004 | 0.009 +[k2-2-2-2](../PAGE/adjacency_lists/k2-2-2-2.txt) | 8 | 24 | 1 | 0.004 | 0.009 +[k2-2-2-2-2](../PAGE/adjacency_lists/k2-2-2-2-2.txt) | 10 | 40 | 3 | 0.006 | 0.009 + +The genus for various Johnson graphs generated using Mathematica follows. +\# | v | e | genus | time (s) | MG time (s) +------------------------------------------------------------------------------ | ---- | ----- | ---------- | -------- | ----------- +[Johnson (5, 2)](../PAGE/adjacency_lists/Johnson5-2.txt) | 10 | 30 | 2 | 0.004 | 0.009 +[Johnson (6, 2)](../PAGE/adjacency_lists/Johnson6-2.txt) | 15 | 60 | 5 | 23.101 | hours +[Johnson (6, 3)](../PAGE/adjacency_lists/Johnson6-3.txt) | 20 | 90 | 7 | 19.374 | hours +[Johnson (8, 4)](../PAGE/adjacency_lists/Johnson8-4.txt) | 70 | 560 | [60,238] | days | too big for bit operations +[Johnson (9, 4)](../PAGE/adjacency_lists/Johnson9-4.txt) | 70 | 560 | [148,558] | days | too big for bit operations + +The genus for various Circulant graphs generated using Mathematica follows. +\# | v | e | genus | time (s) | MG time (s) +------------------------------------------------------------------- | ---- | ----- | -------- | -------- | ----------- +[C10_1,2,5](../PAGE/adjacency_lists/Circulant10_1-2-5.txt) | 10 | 25 | 1 | 0.005 | 0.007 +[C10_1,2,4,5](../PAGE/adjacency_lists/Circulant10_1-2-4-5.txt) | 10 | 35 | 3 | 0.009 | 0.023 +[C14_1,2,3,6](../PAGE/adjacency_lists/Circulant14_1-2-3-6.txt) | 14 | 48 | 4 | 0.013 | 0.896 +[C15_1,5](../PAGE/adjacency_lists/Circulant15_1-5.txt) | 15 | 30 | 1 | 0.008 | 0.006 +[C16_1,7](../PAGE/adjacency_lists/Circulant16_1-7.txt) | 16 | 32 | 1 | 0.005 | 0.014 +[C18_1,3,9](../PAGE/adjacency_lists/Circulant18_1-3-9.txt) | 18 | 45 | 4 | 0.579 | 0.021 +[C20_1,3,5](../PAGE/adjacency_lists/Circulant20_1-3-5.txt) | 20 | 60 | 6 | 0.010 | 13.698 +[C20_1,6,9](../PAGE/adjacency_lists/Circulant20_1-6-9.txt) | 20 | 60 | 6 | 0.009 | 20.637 +[C21_1,4,5](../PAGE/adjacency_lists/Circulant21_1-4-5.txt) | 21 | 63 | 1 | 0.011 | 0.008 +[C26_1,3,9](../PAGE/adjacency_lists/Circulant26_1-3-9.txt) | 26 | 78 | [8, 27] | hours | hours +[C30_1,9,11](../PAGE/adjacency_lists/Circulant30_1-9-11.txt) | 30 | 90 | [9, 31] | hours | hours +[C30_1,4,11,14](../PAGE/adjacency_lists/Circulant30_1-4-11-14.txt) | 30 | 120 | [16, 20] | hours | hours +[C31_1,5,6](../PAGE/adjacency_lists/Circulant31_1-5-6.txt) | 31 | 93 | 1 | 0.021 | 0.006 +[C20_*](../PAGE/adjacency_lists/Circulant20_1-3-5-7-9-10.txt) | 20 | 110 | [10, 17] | hours | hours + +The genus for various Cyclotomic graphs generated using Mathematica follows. +\# | v | e | genus | time (s) | MG time (s) +------------------------------------------------------------------- | ---- | ----- | -------- | -------- | ----------- +[16](../PAGE/adjacency_lists/Cyclotomic16.txt) | 16 | 40 | 4 | 0.117 | 0.042 +[19](../PAGE/adjacency_lists/Cyclotomic19.txt) | 19 | 57 | 1 | 0.009 | 0.010 +[31](../PAGE/adjacency_lists/Cyclotomic31.txt) | 31 | 155 | [12,58] | hours | hours +[61](../PAGE/adjacency_lists/Cyclotomic61.txt) | 61 | 610 | [73,265] | days | too big for bit operations +[67](../PAGE/adjacency_lists/Cyclotomic67.txt) | 67 | 737 | [91,325] | days | too big for bit operations + +The genus for various DifferenceSetIncidence graphs generated using Mathematica follows. +\# | v | e | genus | time (s) | MG time (s) +------------------------------------------------------------------------------ | ---- | ----- | -------- | -------- | ----------- +[11,5,2](../PAGE/adjacency_lists/DifferenceSetIncidence11-5-2.txt) | 22 | 55 | 5 | 0.914 | 1.770 +[40,13,4](../PAGE/adjacency_lists/DifferenceSetIncidence40-13-4.txt) | 80 | 520 | [91,214] | hours | too big for bit operations + +The genus for various Bipartite Kneser graphs generated using Mathematica follows. +\# | v | e | genus | time (s) | MG time (s) +------------------------------------------------------------------------------ | ---- | ----- | --------- | -------------------------------- | ----------- +[Bipartite Kneser (6, 2)](../PAGE/adjacency_lists/bipartite-kneser6-2.txt) | 30 | 90 | [9,28] | days | days +[Bipartite Kneser (7, 2)](../PAGE/adjacency_lists/bipartite-kneser7-2.txt) | 42 | 210 | [33,80] | days | days +[Bipartite Kneser (8, 2)](../PAGE/adjacency_lists/bipartite-kneser8-2.txt) | 56 | 420 | [78,175] | days | days +[Bipartite Kneser (8, 3)](../PAGE/adjacency_lists/bipartite-kneser8-3.txt) | 112 | 560 | [85,143] | days | too big for bit operations +[Bipartite Kneser (9, 2)](../PAGE/adjacency_lists/bipartite-kneser9-2.txt) | 72 | 756 | [154,332] | days | too big for bit operations +[Bipartite Kneser (9, 3)](../PAGE/adjacency_lists/bipartite-kneser9-3.txt) | 168 | 1680 | [337,338] | days | too big for bit operations +[Bipartite Kneser (10, 2)](../PAGE/adjacency_lists/bipartite-kneser10-2.txt) | 90 | 1260 | [271,572] | days | too big for bit operations +[Bipartite Kneser (10, 3)](../PAGE/adjacency_lists/bipartite-kneser10-3.txt) | 240 | 4200 | [931,1963]| days | too big for bit operations +[Bipartite Kneser (10, 4)](../PAGE/adjacency_lists/bipartite-kneser10-4.txt) | 420 | 3150 | [579,1358]| days | too big for bit operations +[Bipartite Kneser (11, 2)](../PAGE/adjacency_lists/bipartite-kneser11-2.txt) | 110 | 1980 | [441,918] | days | too big for bit operations +[Bipartite Kneser (11, 3)](../PAGE/adjacency_lists/bipartite-kneser11-3.txt) | 330 | 9240 |[2146,4428]| days | too big for bit operations +[Bipartite Kneser (11, 4)](../PAGE/adjacency_lists/bipartite-kneser11-4.txt) | 660 | 11550 |[2558,5428]| days | too big for bit operations +[Bipartite Kneser (12, 2)](../PAGE/adjacency_lists/bipartite-kneser12-2.txt) | 132 | 2970 | [677,1397]| days | too big for bit operations +[Bipartite Kneser (12, 3)](../PAGE/adjacency_lists/bipartite-kneser12-3.txt) | 440 | 18480 |[4401,8979]| days | too big for bit operations +[Bipartite Kneser (12, 4)](../PAGE/adjacency_lists/bipartite-kneser12-4.txt) | 990 | 34650 | ? | adjacency list too large to load | too big for bit operations + +The genus for various miscellaneous graphs generated using Mathematica follows. +\# | v | e | genus | time (s) | MG time (s) +------------------------------------------------------------------------------ | ---- | ----- | -------- | -------- | ----------- +[Klein Bottle](../PAGE/adjacency_lists/KleinBottleTriangulation9-1.txt) | 9 | 27 | 2 | 0.005 | 0.006 +[TRC](../PAGE/adjacency_lists/TriangleReplacedCoxeterGraph.txt) | 84 | 126 | 3 | hours | 0.006 +[Fan (3, 6)](../PAGE/adjacency_lists/Fan3-6.txt) | 9 | 23 | 1 | 0.004 | 0.006 +[Co-Herschel](../PAGE/adjacency_lists/coHerschel.txt) | 11 | 37 | 2 | 0.004 | 0.006 diff --git a/docs/references.md b/docs/references.md new file mode 100644 index 0000000..91a57db --- /dev/null +++ b/docs/references.md @@ -0,0 +1,117 @@ +# References +- Adjacency Lists + - [Win.tue.nl](https://www.win.tue.nl/~aeb/graphs/cages/cages.html) + - [SageMath Generators](https://doc.sagemath.org/html/en/reference/graphs/sage/graphs/graph_generators.html) + - [Mathematica](https://www.wolfram.com/mathematica/) + - [ROME and other practical graph datasets](http://graphdrawing.org/data.html) + +- Genus problem is NP-Hard + - [The graph genus problem is NP-complete](https://www.sciencedirect.com/science/article/abs/pii/0196677489900060?via%3Dihub) + - The general problem of determining the genus of a graph is NP-hard + - [Triangulating a Surface with a Prescribed Graph](https://www.sciencedirect.com/science/article/pii/S0095895683710166) + - Determining the non-orientable genus of a graph is NP-hard + +- Background Information + - [Rotation Systems](https://sites.math.washington.edu/~morrow/papers/tom-thesis.pdf) + - [Pearls in Graph Theory - A Comprehensive Introduction - By Nora Hartsfield and Gerhard Ringel](https://proofits.wordpress.com/wp-content/uploads/2012/09/nora_hartsfield_gerhard_ringel_pearls_in_graph.pdf) (particularly Chapter 10) + - [Topological Graph Theory - A Survey](http://www.math.u-szeged.hu/~hajnal/courses/PhD_Specialis/Archdeacon.pdf) + +- Existing Graph Embedding Algorithms + - Planarity Testing (genus = 0) + - [Efficient Planarity Testing](https://dl.acm.org/doi/10.1145/321850.321852) + - O(V) linear time, successfully implemented in ALGOL and can handle 900+ vertices in less than 12 seconds on 1974 hardware + - [An Implementation of the Hopcroft and Tarjan Planarity Test and Embedding Algorithm](https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=6a2fa11f47e315f108698feaabb287ab9751b921) + - Lists flaws and corrections to the original algorithm needed to actually implement it + - [Testing for the consecutive ones property, interval graphs, and graph planarity using PQ-tree algorithms](https://www.sciencedirect.com/science/article/pii/S0022000076800451) + - Also linear but introduces a cool datastructure called a PQ-tree that is good for handling permutations + - [Depth-First Search and Planarity](https://arxiv.org/pdf/math/0610935) + - Linear time, good explanation + - [A Simple Test for Planar Graphs](https://iasl.iis.sinica.edu.tw/webpdf/paper-1993-A_simple_test_for_planar_graphs.pdf) + - O(V + E), good diagrams/explanation + - [Depth-First Search and Kuratowski Subgraphs](https://dl.acm.org/doi/10.1145/1634.322451) + - Extracts the Kuratowski subgraph in O(V) linear time + - [Graphes Planaires: Reconnaissance et Construction de Representations Planaires Topologiques](https://www.mathe2.uni-bayreuth.de/EWS/demoucron.pdf) + - O(V^2) quadratic time but simple and practical to implement + - Torus Embedding (genus = 1) + - [Embedding graphs in the torus in linear time](https://link.springer.com/chapter/10.1007/3-540-59408-6_64) + - Linear time but near impossible to implement + - Has complicated substeps that require entire papers to prove: [Obstructions for simple embeddings](https://www.sfu.ca/~mohar/Papers/Corner.pdf) + - [An algorithm for embedding graphs in the torus](https://www.sfu.ca/~mohar/Papers/Torus.pdf) + - Cubic time but hard to implement + - [A Practical Algorithm for Embedding Graphs on Torus](http://www.ijnc.org/index.php/ijnc/article/view/122/124) + - Exponential but has actually been implemented + - [Practical Toroidality Testing](https://dl.acm.org/doi/pdf/10.5555/314161.314392) + - Exponential but has actually been implemented in C and C++ + - Scales ok up to 10 vertices (11 with up to 24 edges) + - Used to find a set of 2K forbidden minors for the torus (biggest at the time of publication) + - [A large set of torus obstructions and how they were discovered](https://www.combinatorics.org/ojs/index.php/eljc/article/download/v25i1p16/pdf) + - Exponential but actually implemented in C. The best practical algorithm for torus embedding so far + - Projective Plane Embedding (genus = 1, non-orientable) + - [Projective Planarity in Linear Time](https://www.sciencedirect.com/science/article/abs/pii/S0196677483710503) + - Linear time but hard to implement + - [Simpler Projective Plane Embedding](https://www.sciencedirect.com/science/article/abs/pii/S1571065305801751) + - O(n^2) but much easier to implement + - Flawed Algorithms + - [Errors in graph embedding algorithms](https://www.sciencedirect.com/science/article/pii/S0022000010000863?ref=pdf_download&fr=RR-2&rr=8ae048cc8db8c71d) + - Explains errors in many existing algorithms and how fixing them would make them exponential time + - Only currently practical algorithms are exponential time + - Less Efficient Algorithms for Arbitrary Surfaces/Genus + - [SageMath](https://github.com/sagemath/sage/blob/develop/src/sage/graphs/genus.pyx) + - Johnson Trotter to check all rotation systems (exhaustive search with a few optimizations) + - O(V \prod_{v \in V(G)} (deg(v)-1)!) + - SAT/ILP + - [A Practical Method for the Minimum Genus of a Graph: Models and Experiments](https://tcs.informatik.uos.de/_media/pubs/sea16_preprint_mingenus.pdf) + - First SAT and ILP implementation + - Cannot handle genus > 1 + - [Stronger ILPs for the Graph Genus Problem](https://drops.dagstuhl.de/storage/00lipics/lipics-vol144-esa2019/LIPIcs.ESA.2019.30/LIPIcs.ESA.2019.30.pdf) + - Solves most of ROME and NORTH graph datasets + - 42 hours for the Gray graph (genus 7) + - Similar Efficiency with Different Trade-Offs + - [A Practical Algorithm for the Computation of the Genus](https://www.researchgate.net/publication/361684162_A_practical_algorithm_for_the_computation_of_the_genus) + - Scales worse with Genus but better with Vertices + - Theoretically more efficient but Nearly Impossible to Implement + - [A Linear Time Algorithm for Embedding Graphs in an Arbitrary Surface](https://www.sfu.ca/~mohar/Papers/General.pdf) + - Linear for fixed genus + - Has not been implemented correctly in multiple decades + - [A Simpler Linear Time Algorithm for Embedding Graphs into an Arbitrary Surface and the Genus of Graphs of Bounded Tree-Width](https://www.researchgate.net/publication/221499244_A_Simpler_Linear_Time_Algorithm_for_Embedding_Graphs_into_an_Arbitrary_Surface_and_the_Genus_of_Graphs_of_Bounded_Tree-Width) + - Linear for bounded tree-width + - Simpler than the general for fixed genus + - Has not been implemented correctly in multiple decades + - [Graph Minors .XIII. The Disjoint Paths Problem](https://www.sciencedirect.com/science/article/pii/S0095895685710064) + - Cubic time for fixed genus since checking if one of finitely many obstructions is a minor is cubic time + - The complete lists of forbidden minors is only known for the plane (genus 0) and projective plane (non-orientable genus 1) + +- Obstructions and Forbiddden Minors + - [Graph Minor Theorem](https://en.wikipedia.org/wiki/Robertson%E2%80%93Seymour_theorem) + - The minors can be used to determine if a graph contains an obstruction + - [Kuratowski's theorem](https://onlinelibrary.wiley.com/doi/10.1002/jgt.3190050304) + - 3 short proofs of Kuratowski's theorem + - A graph is planar if and only if it has no subdivision of K5 or K3,3 + - [Graph minors. VIII. A kuratowski theorem for general surfaces](https://www.sciencedirect.com/science/article/pii/009589569090121F) + - Every surface has a finite list of forbidden minors + - A graph is embeddable in the surface if and only if it has none of these minors + - [A Kuatowsky Theorem for the Projective Plane](https://onlinelibrary.wiley.com/doi/10.1002/jgt.3190050305) and [103 Graphs that are irreducible for the projective plan](https://www.sciencedirect.com/science/article/pii/0095895679900224) + - The complete list of 103 forbidden minors for the projective plane + - A graph is embeddable in the projective plane if and only if it has none of these minors + - [A Kuratowski theorem for nonorientable surfaces](https://www.sciencedirect.com/science/article/pii/0095895689900439) + - Even nonorientable surfaces have a finite list of forbidden minors + - A graph is embeddable in the nonorientable surface if and only if it has none of these minors + - [Hunting for torus obstructions](https://dspace.library.uvic.ca/items/760d538c-023d-45ff-8d85-57fabd1cd858) + - Largest set at the time ~16K minor order obstructions + - Split delete method to non-exhaustively search for obstructions + - [A large set of torus obstructions and how they were discovered](https://www.combinatorics.org/ojs/index.php/eljc/article/download/v25i1p16/pdf) + - Exponential but simple torus embedding algorithm based on DMP quardratic time planarity testing algorithm + - Growing database of torus obstructions: https://webhome.cs.uvic.ca/~wendym/torus/torus_obstructions.html + - 250,815 torus obstructions, 17,523 of which are minors + - Possibly complete set for all 3 regular graphs, but likely not complete for all graphs + - Overview of current progress (split delete, only 11 obstructions that don't have K3,3 as a subgraph) + - [On Computing Graph Minor Obstruction Sets](https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=7ed5e446f2a1b487a7d9a28fddb83de8772c2402) + - Stopping time of an obstruction algorithm is nonconstructive and other theoretical results + +- Cycle Finding Algorithms + - [Finding All the Elementary Circuits of a Directed Graph](https://www.cs.tufts.edu/comp/150GA/homeworks/hw1/Johnson%2075.PDF) + - O((c + 1)(V + E)) = O(cV + cE) time to find all c elementary cycles of a graph + - [A new way to enumerate cycles in graph](https://ieeexplore.ieee.org/document/1602189) + +- Visualization of Embedding + - [Non-Euclidean Spring Embedders](https://www2.cs.arizona.edu/~kobourov/riemann_embedders.pdf) diff --git a/docs/time_complexity.md b/docs/time_complexity.md new file mode 100644 index 0000000..4586ae6 --- /dev/null +++ b/docs/time_complexity.md @@ -0,0 +1,19 @@ +# Time Complexity +Let `n` be the size of the vertex set `V` and `m` the size of the edge set `E`. Let `G` be the girth of the graph. + +The algorithm in this repository is roughly `O(n(4^m/n)^(n/G))`. It has some optimizations that allows it to stop early not captured in the below analysis. + +- Upper bound on the number of directed trails of length `k`: `2m choose k = (2m)!/k!/(2m-k)!` which is bounded above by `\sqrt{\frac{1}{2\pi}}\frac{\left(2m\right)^{\left(2m+\frac{1}{2}\right)}}{k^{\left(k+\frac{1}{2}\right)}\left(2m-k\right)^{\left(2m-k+\frac{1}{2}\right)}}` as seen in [Bob Gallager's Information Theory and Reliable Communications](https://mathoverflow.net/questions/236508/are-there-good-bounds-on-binomial-coefficients). This is maximized for `k=m` where it simplifies to `4^m/\sqrt{\pi m}`. A simpler but less tight bound is `2m choose k <= (2em/k)^k`. +- The number of directed trails of any length is `O(4^m)` because it is the sum of the values in the `2m`th row of Pascal's triangle. +- This can also be used to upper bound the number of *non-backtracking closed* directed trails which is what our trail finding algorithm enumerates. Let `c` be the number of trails enumerated by our trail finding algorithm. +- Organizing the `c` trails by vertex is `O(2mc) < O(2m4^m)` since each trail has at most `2m` edges. + +- Finding the most used vertex to explore: `O(n)` by iterating through the vertices (overall time complexity is better when write is kept `O(1)`) +- Looking up the cycles that use a vertex: `O(1)` via hashset lookup +- Checking if a cycle is used: `O(1)` via hashset lookup +- Checking if the edges of a cycle are used: `O(m)` by storing the edges used in a hashset +- Checking if adding cycle breaks rotation system: `O(m)` by storing the current rotation with the adjacency list +- Search iteration (f = implied fit, b = cycles by vertex >= u = unused >= a = w/ edges available >= d = rotation valid): `T(f) = O(n) + O(1) + b O(1) + u O(m) + a O(m) + d T(f-1); T(0) = 0` => `O(d^f * (n + b + um + am)) = O(d^f * (n + b + m(u + a))) < O(b^(f + 2))` +- All search iterations (h = number of start cycles to try out < `4^m`): `O(b^(f + 2) * h) < O((4^m / n)^(n/G) * 4^m) = O(n(4^m/n)^(n/G))`. + +The algorithm is particularly advantageous for high girth graphs such as the cage family of graphs. diff --git a/experiments/GenusPolynomial/Makefile b/experiments/GenusPolynomial/Makefile new file mode 100644 index 0000000..ca6bdc9 --- /dev/null +++ b/experiments/GenusPolynomial/Makefile @@ -0,0 +1,23 @@ +CC ?= gcc +NAUTY_PREFIX ?= /opt/homebrew + +CFLAGS ?= -O3 -march=native -flto -DNDEBUG +CFLAGS += -std=c17 -Wall -Wextra -pedantic -I$(NAUTY_PREFIX)/include +LDFLAGS += -L$(NAUTY_PREFIX)/lib +LDLIBS += -lnauty -lm -pthread + +BIN = genus_properties +SRC = genus_properties.c + +.PHONY: all clean run-petersen + +all: $(BIN) + +$(BIN): $(SRC) + $(CC) $(CFLAGS) $(LDFLAGS) -o $@ $(SRC) $(LDLIBS) + +run-petersen: $(BIN) + printf 'IheA@GUAo\n' | ./$(BIN) --stdin + +clean: + rm -f $(BIN) *.o diff --git a/experiments/GenusPolynomial/README.md b/experiments/GenusPolynomial/README.md new file mode 100644 index 0000000..e087cc9 --- /dev/null +++ b/experiments/GenusPolynomial/README.md @@ -0,0 +1,93 @@ +# GenusPolynomial C pipeline + +The main program is `genus_properties.c`. It reads graph6 records, validates +that each graph is simple, connected, and cubic, and writes one CSV row per +graph with ordinary invariants plus the exact orientable genus spectrum. + +The `spectrum` column contains coefficients that count labeled orientable cubic +rotation systems. A connected cubic graph on `n` vertices has `2^n` such +systems. The C code enumerates half of them by fixing the highest vertex's +rotation bit and doubles the counts using global mirror symmetry. + +## Build + +```bash +cd GenusPolynomial +make +``` + +The Makefile assumes Homebrew's nauty install at `/opt/homebrew`. Override it +if needed: + +```bash +make NAUTY_PREFIX=/usr/local +``` + +## Run + +Analyze a graph6 file: + +```bash +./genus_properties --graph6 graphs.g6 --out results.csv +``` + +Stream all connected non-isomorphic cubic graphs of order `n` from nauty +`geng`: + +```bash +./genus_properties --generate-cubic 20 --out cubic20_results.csv +``` + +Quick benchmark or smoke test: + +```bash +./genus_properties --generate-cubic 20 --limit 100 --out cubic20_100.csv +``` + +Useful speed switches: + +- `--threads N`: set worker threads. +- `--no-automorphisms`: skip libnauty automorphism group order. +- `--no-matrix-spectra`: skip adjacency and Laplacian spectra. +- `--no-spanning-trees`: skip Matrix-Tree determinant. +- `--progress-every N`: progress on stderr. + +## CSV format + +The output is a headered CSV with one row per valid input graph. Fields are: + +- `index`: zero-based record index after reading the input stream or file. +- `graph6`: the graph6 string for the graph. +- `n`: number of vertices. +- `m`: number of edges. +- `girth`: length of the shortest cycle. +- `diameter`: maximum shortest-path distance between two vertices. +- `bipartite`: `True` or `False`. +- `vertex_connectivity`: minimum number of vertices whose removal disconnects + the graph, capped naturally at `3` for cubic graphs. +- `edge_connectivity`: minimum number of edges whose removal disconnects the + graph, capped naturally at `3` for cubic graphs. +- `automorphism_group_order`: order of the automorphism group computed by + nauty, or `NA` with `--no-automorphisms`. +- `triangle_count`, `four_cycle_count`, `five_cycle_count`, + `six_cycle_count`: number of undirected simple cycles of lengths 3, 4, 5, + and 6. +- `adjacency_spectrum`: sorted adjacency-matrix eigenvalues separated by + semicolons, or `NA` with `--no-matrix-spectra`. +- `laplacian_spectrum`: sorted Laplacian-matrix eigenvalues separated by + semicolons, or `NA` with `--no-matrix-spectra`. +- `spanning_tree_count`: exact number of spanning trees from the Matrix-Tree + theorem, or `NA` with `--no-spanning-trees`. +- `spectrum`: exact orientable genus polynomial coefficients as + `genus:count` terms separated by semicolons, for example `1:40;2:664;3:320`. +- `gamma`: minimum genus with nonzero coefficient in `spectrum`. +- `g_max`: maximum genus with nonzero coefficient in `spectrum`. +- `expected_genus`: expectation of genus under the uniform distribution over + labeled orientable rotation systems. +- `variance`: variance of genus under that same distribution. +- `R`: probability of achieving `gamma`, equal to the `gamma` coefficient + divided by `total_rotation_systems`. +- `R_1`: probability of genus at most `gamma + 1`. +- `R_2`: probability of genus at most `gamma + 2`. +- `total_rotation_systems`: total labeled orientable rotation systems; for a + connected cubic graph this is `2^n`. diff --git a/experiments/GenusPolynomial/genus_properties.c b/experiments/GenusPolynomial/genus_properties.c new file mode 100644 index 0000000..4e57a55 --- /dev/null +++ b/experiments/GenusPolynomial/genus_properties.c @@ -0,0 +1,1508 @@ +// Fast exact orientable genus-polynomial and invariant collector for simple +// connected cubic graph6 inputs. + +#define _DARWIN_C_SOURCE +#define _DEFAULT_SOURCE +#define _POSIX_C_SOURCE 200809L +#ifndef MAXN +#define MAXN 64 +#endif + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#ifdef __APPLE__ +#include +#endif +#include + +#include + +#define GP_MAX_N 64 +#define GP_MAX_EDGES ((GP_MAX_N * 3) / 2) +#define GP_MAX_DARTS (GP_MAX_EDGES * 2) +#define GP_MAX_GENUS (GP_MAX_N + 2) +#define GP_FIELD_CAP 4096 +#define GP_ROW_CAP 16384 +#define GP_ERROR_CAP 512 + +typedef struct { + size_t index; + const char *graph6; + int n; + int m; + uint64_t adj[GP_MAX_N]; + uint8_t degree[GP_MAX_N]; + uint8_t neigh[GP_MAX_N][3]; + uint8_t edge_u[GP_MAX_EDGES]; + uint8_t edge_v[GP_MAX_EDGES]; +} Graph; + +typedef struct { + bool input_stdin; + const char *input_path; + int generate_cubic_n; + const char *geng_path; + const char *out_path; + int threads; + size_t limit; + size_t progress_every; + bool skip_invalid; + bool compute_automorphisms; + bool compute_matrix_spectra; + bool compute_spanning_trees; +} Options; + +typedef struct { + char **items; + size_t count; + size_t capacity; +} StringVec; + +typedef struct { + char *row; + char error[GP_ERROR_CAP]; + bool ok; + bool skipped; +} Result; + +typedef struct { + const Options *options; + char **lines; + size_t count; + size_t next_index; + size_t processed; + bool stop_requested; + pthread_mutex_t mutex; + Result *results; +} WorkQueue; + +typedef struct { + size_t index; + char *line; +} StreamJob; + +typedef enum { + STREAM_RESULT_EMPTY = 0, + STREAM_RESULT_OK, + STREAM_RESULT_SKIPPED, + STREAM_RESULT_ERROR, +} StreamResultKind; + +typedef struct { + StreamResultKind kind; + bool ready; + char *row; + char error[GP_ERROR_CAP]; +} StreamResult; + +typedef struct { + const Options *options; + FILE *out; + StreamJob *jobs; + size_t job_capacity; + size_t job_head; + size_t job_tail; + size_t job_count; + StreamResult *results; + size_t result_capacity; + size_t next_to_emit; + size_t enqueued; + size_t processed; + size_t written; + size_t skipped; + size_t errors; + bool producer_done; + bool stop_requested; + pthread_mutex_t mutex; + pthread_cond_t not_empty; + pthread_cond_t not_full; +} StreamQueue; + +typedef struct { + uint64_t counts[GP_MAX_GENUS]; + int gamma; + int g_max; + double expected; + double variance; + double r; + double r1; + double r2; + uint64_t total_rotation_systems; + char spectrum[GP_FIELD_CAP]; +} GenusStats; + +typedef struct { + uint8_t dart_count; + uint8_t head[GP_MAX_DARTS]; + uint8_t next0[GP_MAX_DARTS]; + uint8_t next1[GP_MAX_DARTS]; + uint64_t head_bit[GP_MAX_DARTS]; +} RotationData; + +static void die(const char *message) { + fprintf(stderr, "error: %s\n", message); + exit(1); +} + +static void die_errno(const char *message) { + fprintf(stderr, "error: %s: %s\n", message, strerror(errno)); + exit(1); +} + +static char *xstrdup(const char *s) { + size_t len = strlen(s); + char *copy = malloc(len + 1); + if (!copy) die_errno("malloc"); + memcpy(copy, s, len + 1); + return copy; +} + +static void string_vec_push(StringVec *vec, char *item) { + if (vec->count == vec->capacity) { + size_t new_capacity = vec->capacity ? vec->capacity * 2 : 1024; + char **new_items = realloc(vec->items, new_capacity * sizeof(*new_items)); + if (!new_items) die_errno("realloc"); + vec->items = new_items; + vec->capacity = new_capacity; + } + vec->items[vec->count++] = item; +} + +static void string_vec_free(StringVec *vec) { + for (size_t i = 0; i < vec->count; ++i) free(vec->items[i]); + free(vec->items); + vec->items = NULL; + vec->count = 0; + vec->capacity = 0; +} + +static char *trim_graph6_line(char *line) { + while (*line && isspace((unsigned char)*line)) ++line; + size_t len = strlen(line); + while (len > 0 && isspace((unsigned char)line[len - 1])) line[--len] = '\0'; + + const char *header = ">>graph6<<"; + size_t header_len = strlen(header); + if (strncmp(line, header, header_len) == 0) line += header_len; + return line; +} + +static void read_lines_from_stream(FILE *stream, StringVec *lines, size_t limit) { + char *buffer = NULL; + size_t cap = 0; + ssize_t len; + + while ((len = getline(&buffer, &cap, stream)) != -1) { + (void)len; + char *trimmed = trim_graph6_line(buffer); + if (*trimmed == '\0') continue; + string_vec_push(lines, xstrdup(trimmed)); + if (limit > 0 && lines->count >= limit) break; + } + free(buffer); +} + +static void read_graph6_file(const char *path, StringVec *lines, size_t limit) { + FILE *stream = fopen(path, "r"); + if (!stream) die_errno(path); + read_lines_from_stream(stream, lines, limit); + fclose(stream); +} + +static bool add_edge(Graph *g, int u, int v, char *err, size_t err_len) { + if (u < 0 || v < 0 || u >= g->n || v >= g->n || u == v) { + snprintf(err, err_len, "invalid edge (%d,%d)", u, v); + return false; + } + if ((g->adj[u] >> v) & 1ULL) { + snprintf(err, err_len, "duplicate edge (%d,%d)", u, v); + return false; + } + g->adj[u] |= 1ULL << v; + g->adj[v] |= 1ULL << u; + return true; +} + +static int graph6_size(const unsigned char *s, size_t len, size_t *pos, char *err, + size_t err_len) { + if (len == 0) { + snprintf(err, err_len, "empty graph6 record"); + return -1; + } + if (s[0] != '~') { + if (s[0] < 63 || s[0] > 126) { + snprintf(err, err_len, "invalid graph6 size byte"); + return -1; + } + *pos = 1; + return (int)s[0] - 63; + } + if (len < 4) { + snprintf(err, err_len, "truncated graph6 size"); + return -1; + } + if (s[1] != '~') { + int n = 0; + for (int i = 1; i <= 3; ++i) { + if (s[i] < 63 || s[i] > 126) { + snprintf(err, err_len, "invalid graph6 extended size byte"); + return -1; + } + n = (n << 6) | ((int)s[i] - 63); + } + *pos = 4; + return n; + } + if (len < 8) { + snprintf(err, err_len, "truncated graph6 large size"); + return -1; + } + uint64_t n = 0; + for (int i = 2; i <= 7; ++i) { + if (s[i] < 63 || s[i] > 126) { + snprintf(err, err_len, "invalid graph6 large size byte"); + return -1; + } + n = (n << 6) | ((uint64_t)s[i] - 63); + } + if (n > INT32_MAX) { + snprintf(err, err_len, "graph6 size is too large"); + return -1; + } + *pos = 8; + return (int)n; +} + +static bool parse_graph6(const char *record, size_t index, Graph *g, char *err, + size_t err_len) { + memset(g, 0, sizeof(*g)); + g->index = index; + g->graph6 = record; + + const unsigned char *s = (const unsigned char *)record; + size_t len = strlen(record); + size_t pos = 0; + int n = graph6_size(s, len, &pos, err, err_len); + if (n < 0) return false; + if (n > GP_MAX_N) { + snprintf(err, err_len, "graph has %d vertices; max supported is %d", n, GP_MAX_N); + return false; + } + g->n = n; + + size_t bit_count = (size_t)n * (size_t)(n - 1) / 2; + size_t body_len = (bit_count + 5) / 6; + if (len < pos + body_len) { + snprintf(err, err_len, "graph6 record is truncated"); + return false; + } + + size_t bit_index = 0; + for (size_t byte_index = 0; byte_index < body_len; ++byte_index) { + unsigned char c = s[pos + byte_index]; + if (c < 63 || c > 126) { + snprintf(err, err_len, "invalid graph6 data byte"); + return false; + } + int value = (int)c - 63; + for (int bit = 5; bit >= 0 && bit_index < bit_count; --bit, ++bit_index) { + if ((value >> bit) & 1) { + int v = 1; + size_t before = 0; + while (before + (size_t)v <= bit_index) { + before += (size_t)v; + ++v; + } + int u = (int)(bit_index - before); + if (!add_edge(g, u, v, err, err_len)) return false; + ++g->m; + } + } + } + + if (n == 0) { + snprintf(err, err_len, "graph has no vertices"); + return false; + } + if (n % 2 != 0) { + snprintf(err, err_len, "graph has %d vertices; cubic graphs need even order", n); + return false; + } + if (g->m != (3 * n) / 2) { + snprintf(err, err_len, "graph has %d edges; expected 3n/2=%d", g->m, + (3 * n) / 2); + return false; + } + + int edge_index = 0; + for (int u = 0; u < n; ++u) { + uint64_t bits = g->adj[u]; + while (bits) { + int v = __builtin_ctzll(bits); + bits &= bits - 1; + if (g->degree[u] < 3) g->neigh[u][g->degree[u]] = (uint8_t)v; + ++g->degree[u]; + if (u < v) { + if (edge_index >= GP_MAX_EDGES) { + snprintf(err, err_len, "too many edges"); + return false; + } + g->edge_u[edge_index] = (uint8_t)u; + g->edge_v[edge_index] = (uint8_t)v; + ++edge_index; + } + } + if (g->degree[u] != 3) { + snprintf(err, err_len, "vertex %d has degree %u; expected 3", u, + (unsigned)g->degree[u]); + return false; + } + } + + uint64_t visited = 1ULL; + int queue[GP_MAX_N]; + int head = 0, tail = 0; + queue[tail++] = 0; + while (head < tail) { + int u = queue[head++]; + uint64_t unseen = g->adj[u] & ~visited; + while (unseen) { + int v = __builtin_ctzll(unseen); + unseen &= unseen - 1; + visited |= 1ULL << v; + queue[tail++] = v; + } + } + if (tail != n) { + snprintf(err, err_len, "graph is disconnected"); + return false; + } + + return true; +} + +static int bfs_distances(const Graph *g, int source, uint64_t blocked_vertices, + int blocked_edge_a, int blocked_edge_b, int *dist) { + for (int i = 0; i < g->n; ++i) dist[i] = -1; + if ((blocked_vertices >> source) & 1ULL) return 0; + + int queue[GP_MAX_N]; + int head = 0, tail = 0; + dist[source] = 0; + queue[tail++] = source; + + while (head < tail) { + int u = queue[head++]; + for (int i = 0; i < 3; ++i) { + int v = g->neigh[u][i]; + if ((blocked_vertices >> v) & 1ULL) continue; + bool blocked = false; + if (blocked_edge_a >= 0) { + int a = g->edge_u[blocked_edge_a], b = g->edge_v[blocked_edge_a]; + blocked = (u == a && v == b) || (u == b && v == a); + } + if (!blocked && blocked_edge_b >= 0) { + int a = g->edge_u[blocked_edge_b], b = g->edge_v[blocked_edge_b]; + blocked = (u == a && v == b) || (u == b && v == a); + } + if (blocked || dist[v] >= 0) continue; + dist[v] = dist[u] + 1; + queue[tail++] = v; + } + } + return tail; +} + +static bool connected_after_blocks(const Graph *g, uint64_t blocked_vertices, + int blocked_edge_a, int blocked_edge_b) { + int start = -1; + int remaining = 0; + for (int i = 0; i < g->n; ++i) { + if (((blocked_vertices >> i) & 1ULL) == 0) { + if (start < 0) start = i; + ++remaining; + } + } + if (remaining <= 1) return true; + int dist[GP_MAX_N]; + int reached = bfs_distances(g, start, blocked_vertices, blocked_edge_a, + blocked_edge_b, dist); + return reached == remaining; +} + +static int compute_diameter(const Graph *g) { + int best = 0; + int dist[GP_MAX_N]; + for (int source = 0; source < g->n; ++source) { + bfs_distances(g, source, 0, -1, -1, dist); + for (int v = 0; v < g->n; ++v) { + if (dist[v] < 0) return -1; + if (dist[v] > best) best = dist[v]; + } + } + return best; +} + +static int compute_girth(const Graph *g) { + int best = GP_MAX_N + 1; + int dist[GP_MAX_N], parent[GP_MAX_N], queue[GP_MAX_N]; + + for (int source = 0; source < g->n; ++source) { + for (int i = 0; i < g->n; ++i) { + dist[i] = -1; + parent[i] = -1; + } + int head = 0, tail = 0; + dist[source] = 0; + queue[tail++] = source; + while (head < tail) { + int u = queue[head++]; + for (int i = 0; i < 3; ++i) { + int v = g->neigh[u][i]; + if (dist[v] < 0) { + dist[v] = dist[u] + 1; + parent[v] = u; + queue[tail++] = v; + } else if (parent[u] != v && parent[v] != u) { + int cycle_len = dist[u] + dist[v] + 1; + if (cycle_len < best) best = cycle_len; + } + } + } + } + return best == GP_MAX_N + 1 ? -1 : best; +} + +static bool is_bipartite(const Graph *g) { + int color[GP_MAX_N]; + for (int i = 0; i < g->n; ++i) color[i] = -1; + int queue[GP_MAX_N]; + + for (int start = 0; start < g->n; ++start) { + if (color[start] >= 0) continue; + int head = 0, tail = 0; + color[start] = 0; + queue[tail++] = start; + while (head < tail) { + int u = queue[head++]; + for (int i = 0; i < 3; ++i) { + int v = g->neigh[u][i]; + if (color[v] < 0) { + color[v] = 1 - color[u]; + queue[tail++] = v; + } else if (color[v] == color[u]) { + return false; + } + } + } + } + return true; +} + +static int vertex_connectivity(const Graph *g) { + if (g->n <= 1) return 0; + for (int v = 0; v < g->n; ++v) { + if (!connected_after_blocks(g, 1ULL << v, -1, -1)) return 1; + } + for (int a = 0; a < g->n; ++a) { + for (int b = a + 1; b < g->n; ++b) { + uint64_t blocked = (1ULL << a) | (1ULL << b); + if (!connected_after_blocks(g, blocked, -1, -1)) return 2; + } + } + return 3; +} + +static int edge_connectivity(const Graph *g) { + for (int e = 0; e < g->m; ++e) { + if (!connected_after_blocks(g, 0, e, -1)) return 1; + } + for (int a = 0; a < g->m; ++a) { + for (int b = a + 1; b < g->m; ++b) { + if (!connected_after_blocks(g, 0, a, b)) return 2; + } + } + return 3; +} + +static void cycle_dfs(const Graph *g, int start, int current, int depth, int length, + uint64_t visited, uint64_t *oriented_count) { + if (depth == length - 1) { + if ((g->adj[current] >> start) & 1ULL) ++(*oriented_count); + return; + } + for (int i = 0; i < 3; ++i) { + int v = g->neigh[current][i]; + if (v == start) continue; + if ((visited >> v) & 1ULL) continue; + if (v < start) continue; + cycle_dfs(g, start, v, depth + 1, length, visited | (1ULL << v), + oriented_count); + } +} + +static uint64_t count_cycles_length(const Graph *g, int length) { + uint64_t oriented_count = 0; + for (int start = 0; start < g->n; ++start) { + cycle_dfs(g, start, start, 0, length, 1ULL << start, &oriented_count); + } + return oriented_count / 2; +} + +static int cmp_double(const void *a, const void *b) { + double da = *(const double *)a; + double db = *(const double *)b; + return (da > db) - (da < db); +} + +static void jacobi_eigenvalues(int n, double matrix[GP_MAX_N][GP_MAX_N], + double *eigenvalues) { + if (n == 0) return; + const double tolerance = 1e-13; + int max_iterations = n > 1 ? 80 * n * n : 1; + if (max_iterations < 100) max_iterations = 100; + + for (int iter = 0; iter < max_iterations; ++iter) { + int p = 0, q = 1; + double max_offdiag = n > 1 ? fabs(matrix[0][1]) : 0.0; + for (int i = 0; i < n; ++i) { + for (int j = i + 1; j < n; ++j) { + double value = fabs(matrix[i][j]); + if (value > max_offdiag) { + max_offdiag = value; + p = i; + q = j; + } + } + } + if (max_offdiag < tolerance) break; + + double app = matrix[p][p]; + double aqq = matrix[q][q]; + double apq = matrix[p][q]; + double tau = (aqq - app) / (2.0 * apq); + double sign = tau >= 0.0 ? 1.0 : -1.0; + double t = sign / (fabs(tau) + sqrt(1.0 + tau * tau)); + double c = 1.0 / sqrt(1.0 + t * t); + double s = t * c; + + for (int k = 0; k < n; ++k) { + if (k == p || k == q) continue; + double akp = matrix[k][p]; + double akq = matrix[k][q]; + matrix[k][p] = matrix[p][k] = c * akp - s * akq; + matrix[k][q] = matrix[q][k] = s * akp + c * akq; + } + matrix[p][p] = app - t * apq; + matrix[q][q] = aqq + t * apq; + matrix[p][q] = matrix[q][p] = 0.0; + } + + for (int i = 0; i < n; ++i) eigenvalues[i] = matrix[i][i]; + qsort(eigenvalues, (size_t)n, sizeof(double), cmp_double); +} + +static void append_formatted_double(char *out, size_t out_cap, double value) { + double rounded = nearbyint(value * 1e10) / 1e10; + if (fabs(rounded) < 1e-8) rounded = 0.0; + + char tmp[64]; + snprintf(tmp, sizeof(tmp), "%.10f", rounded); + size_t len = strlen(tmp); + while (len > 0 && tmp[len - 1] == '0') tmp[--len] = '\0'; + if (len > 0 && tmp[len - 1] == '.') tmp[--len] = '\0'; + if (strcmp(tmp, "-0") == 0 || tmp[0] == '\0') strcpy(tmp, "0"); + strncat(out, tmp, out_cap - strlen(out) - 1); +} + +static void compute_spectrum_string(const Graph *g, bool laplacian, char *out, + size_t out_cap) { + double matrix[GP_MAX_N][GP_MAX_N] = {{0.0}}; + double eigenvalues[GP_MAX_N]; + int n = g->n; + + if (laplacian) { + for (int i = 0; i < n; ++i) matrix[i][i] = (double)g->degree[i]; + } + for (int e = 0; e < g->m; ++e) { + int u = g->edge_u[e], v = g->edge_v[e]; + if (laplacian) { + matrix[u][v] = -1.0; + matrix[v][u] = -1.0; + } else { + matrix[u][v] = 1.0; + matrix[v][u] = 1.0; + } + } + + jacobi_eigenvalues(n, matrix, eigenvalues); + out[0] = '\0'; + for (int i = 0; i < n; ++i) { + if (i > 0) strncat(out, ";", out_cap - strlen(out) - 1); + append_formatted_double(out, out_cap, eigenvalues[i]); + } +} + +static __int128 bareiss_determinant(int n, __int128 matrix[GP_MAX_N][GP_MAX_N]) { + if (n == 0) return 1; + if (n == 1) return matrix[0][0]; + + int sign = 1; + __int128 previous_pivot = 1; + for (int k = 0; k < n - 1; ++k) { + if (matrix[k][k] == 0) { + int swap_row = -1; + for (int r = k + 1; r < n; ++r) { + if (matrix[r][k] != 0) { + swap_row = r; + break; + } + } + if (swap_row < 0) return 0; + for (int c = 0; c < n; ++c) { + __int128 tmp = matrix[k][c]; + matrix[k][c] = matrix[swap_row][c]; + matrix[swap_row][c] = tmp; + } + sign *= -1; + } + __int128 pivot = matrix[k][k]; + for (int i = k + 1; i < n; ++i) { + for (int j = k + 1; j < n; ++j) { + matrix[i][j] = + (matrix[i][j] * pivot - matrix[i][k] * matrix[k][j]) / + previous_pivot; + } + } + previous_pivot = pivot; + for (int i = k + 1; i < n; ++i) matrix[i][k] = 0; + for (int j = k + 1; j < n; ++j) matrix[k][j] = 0; + } + return sign > 0 ? matrix[n - 1][n - 1] : -matrix[n - 1][n - 1]; +} + +static void int128_to_string(__int128 value, char *out, size_t out_cap) { + if (out_cap == 0) return; + if (value == 0) { + snprintf(out, out_cap, "0"); + return; + } + bool negative = value < 0; + unsigned __int128 u = negative ? (unsigned __int128)(-value) : (unsigned __int128)value; + char tmp[128]; + size_t len = 0; + while (u > 0 && len < sizeof(tmp) - 1) { + tmp[len++] = (char)('0' + (u % 10)); + u /= 10; + } + size_t pos = 0; + if (negative && pos + 1 < out_cap) out[pos++] = '-'; + while (len > 0 && pos + 1 < out_cap) out[pos++] = tmp[--len]; + out[pos] = '\0'; +} + +static void compute_spanning_tree_count(const Graph *g, char *out, size_t out_cap) { + int n = g->n; + if (n <= 1) { + snprintf(out, out_cap, "1"); + return; + } + + __int128 lap[GP_MAX_N][GP_MAX_N] = {{0}}; + for (int v = 0; v < n; ++v) lap[v][v] = g->degree[v]; + for (int e = 0; e < g->m; ++e) { + int u = g->edge_u[e], v = g->edge_v[e]; + lap[u][v] -= 1; + lap[v][u] -= 1; + } + + __int128 cofactor[GP_MAX_N][GP_MAX_N] = {{0}}; + for (int i = 0; i < n - 1; ++i) + for (int j = 0; j < n - 1; ++j) cofactor[i][j] = lap[i][j]; + __int128 det = bareiss_determinant(n - 1, cofactor); + if (det < 0) det = -det; + int128_to_string(det, out, out_cap); +} + +static void compute_automorphism_order(const Graph *g, char *out, size_t out_cap) { + int n = g->n; + int m = SETWORDSNEEDED(n); + graph ng[MAXN * MAXM]; + int lab[GP_MAX_N], ptn[GP_MAX_N], orbits[GP_MAX_N]; + DEFAULTOPTIONS_GRAPH(options); + statsblk stats; + + nauty_check(WORDSIZE, m, n, NAUTYVERSIONID); + EMPTYGRAPH(ng, m, n); + for (int e = 0; e < g->m; ++e) { + ADDONEEDGE(ng, g->edge_u[e], g->edge_v[e], m); + } + + options.getcanon = FALSE; + densenauty(ng, lab, ptn, orbits, &options, &stats, m, n, NULL); + if (stats.errstatus != 0) { + snprintf(out, out_cap, "NA"); + return; + } + + if (stats.grpsize2 == 0) { + snprintf(out, out_cap, "%.0f", stats.grpsize1); + } else { + snprintf(out, out_cap, "%.12ge%d", stats.grpsize1, stats.grpsize2); + } +} + +static bool prepare_rotation_data(const Graph *g, RotationData *data, char *err, + size_t err_len) { + memset(data, 0, sizeof(*data)); + int dart_index[GP_MAX_N][GP_MAX_N]; + for (int i = 0; i < GP_MAX_N; ++i) + for (int j = 0; j < GP_MAX_N; ++j) dart_index[i][j] = -1; + + int dart = 0; + for (int e = 0; e < g->m; ++e) { + int u = g->edge_u[e], v = g->edge_v[e]; + dart_index[u][v] = dart; + data->head[dart] = (uint8_t)v; + ++dart; + dart_index[v][u] = dart; + data->head[dart] = (uint8_t)u; + ++dart; + } + data->dart_count = (uint8_t)dart; + + for (int tail = 0; tail < g->n; ++tail) { + for (int ni = 0; ni < 3; ++ni) { + int head = g->neigh[tail][ni]; + int d = dart_index[tail][head]; + if (d < 0) { + snprintf(err, err_len, "internal dart-index error"); + return false; + } + + int pos = -1; + for (int k = 0; k < 3; ++k) { + if (g->neigh[head][k] == tail) { + pos = k; + break; + } + } + if (pos < 0) { + snprintf(err, err_len, "internal neighbor-order error"); + return false; + } + + int next0_neighbor = g->neigh[head][(pos + 1) % 3]; + int next1_neighbor = g->neigh[head][(pos + 2) % 3]; + data->next0[d] = (uint8_t)dart_index[head][next0_neighbor]; + data->next1[d] = (uint8_t)dart_index[head][next1_neighbor]; + data->head_bit[d] = 1ULL << head; + } + } + return true; +} + +static int count_faces_fast(const RotationData *data, uint64_t mask, uint32_t *seen, + uint32_t stamp) { + int faces = 0; + int dart_count = data->dart_count; + for (int start = 0; start < dart_count; ++start) { + if (seen[start] == stamp) continue; + ++faces; + int current = start; + while (seen[current] != stamp) { + seen[current] = stamp; + current = (mask & data->head_bit[current]) ? data->next1[current] + : data->next0[current]; + } + } + return faces; +} + +static bool compute_genus_stats(const Graph *g, GenusStats *stats, char *err, + size_t err_len) { + memset(stats, 0, sizeof(*stats)); + if (g->n <= 0 || g->n >= 64) { + snprintf(err, err_len, "exact rotation spectrum needs 1 <= n < 64"); + return false; + } + + RotationData data; + if (!prepare_rotation_data(g, &data, err, err_len)) return false; + + uint64_t masks_to_enumerate = 1ULL << (g->n - 1); + uint64_t total = 1ULL << g->n; + uint32_t seen[GP_MAX_DARTS] = {0}; + uint32_t stamp = 0; + + for (uint64_t mask = 0; mask < masks_to_enumerate; ++mask) { + ++stamp; + if (stamp == 0) { + memset(seen, 0, sizeof(seen)); + stamp = 1; + } + int faces = count_faces_fast(&data, mask, seen, stamp); + int two_g = 2 - g->n + g->m - faces; + if (two_g < 0 || (two_g & 1)) { + snprintf(err, err_len, + "invalid genus from n=%d m=%d faces=%d two_g=%d", g->n, + g->m, faces, two_g); + return false; + } + int genus = two_g / 2; + if (genus < 0 || genus >= GP_MAX_GENUS) { + snprintf(err, err_len, "computed genus %d out of range", genus); + return false; + } + stats->counts[genus] += 2; + } + + uint64_t actual_total = 0; + stats->gamma = -1; + stats->g_max = -1; + double first_moment = 0.0; + double second_moment = 0.0; + for (int genus = 0; genus < GP_MAX_GENUS; ++genus) { + uint64_t count = stats->counts[genus]; + if (!count) continue; + actual_total += count; + if (stats->gamma < 0) stats->gamma = genus; + stats->g_max = genus; + first_moment += (double)genus * (double)count; + second_moment += (double)genus * (double)genus * (double)count; + } + if (actual_total != total) { + snprintf(err, err_len, "spectrum total is %" PRIu64 "; expected %" PRIu64, + actual_total, total); + return false; + } + stats->total_rotation_systems = total; + stats->expected = first_moment / (double)total; + double second = second_moment / (double)total; + stats->variance = second - stats->expected * stats->expected; + if (stats->variance < 0.0 && stats->variance > -1e-12) stats->variance = 0.0; + stats->r = (double)stats->counts[stats->gamma] / (double)total; + uint64_t r1_count = 0, r2_count = 0; + for (int genus = 0; genus < GP_MAX_GENUS; ++genus) { + if (genus <= stats->gamma + 1) r1_count += stats->counts[genus]; + if (genus <= stats->gamma + 2) r2_count += stats->counts[genus]; + } + stats->r1 = (double)r1_count / (double)total; + stats->r2 = (double)r2_count / (double)total; + + stats->spectrum[0] = '\0'; + for (int genus = 0; genus < GP_MAX_GENUS; ++genus) { + if (!stats->counts[genus]) continue; + char part[64]; + snprintf(part, sizeof(part), "%s%d:%" PRIu64, + stats->spectrum[0] ? ";" : "", genus, stats->counts[genus]); + strncat(stats->spectrum, part, sizeof(stats->spectrum) - strlen(stats->spectrum) - 1); + } + return true; +} + +static char *analyze_graph_to_csv(const Graph *g, const Options *options, char *err, + size_t err_len) { + int girth = compute_girth(g); + int diameter = compute_diameter(g); + bool bipartite = is_bipartite(g); + int vconn = vertex_connectivity(g); + int econn = edge_connectivity(g); + uint64_t triangle_count = count_cycles_length(g, 3); + uint64_t four_cycle_count = count_cycles_length(g, 4); + uint64_t five_cycle_count = count_cycles_length(g, 5); + uint64_t six_cycle_count = count_cycles_length(g, 6); + + char automorphism_order[128] = "NA"; + char adjacency_spectrum[GP_FIELD_CAP] = "NA"; + char laplacian_spectrum[GP_FIELD_CAP] = "NA"; + char spanning_trees[128] = "NA"; + + if (options->compute_automorphisms) { + compute_automorphism_order(g, automorphism_order, sizeof(automorphism_order)); + } + if (options->compute_matrix_spectra) { + compute_spectrum_string(g, false, adjacency_spectrum, sizeof(adjacency_spectrum)); + compute_spectrum_string(g, true, laplacian_spectrum, sizeof(laplacian_spectrum)); + } + if (options->compute_spanning_trees) { + compute_spanning_tree_count(g, spanning_trees, sizeof(spanning_trees)); + } + + GenusStats genus_stats; + if (!compute_genus_stats(g, &genus_stats, err, err_len)) return NULL; + + char *row = malloc(GP_ROW_CAP); + if (!row) die_errno("malloc row"); + int written = snprintf( + row, GP_ROW_CAP, + "%zu,%s,%d,%d,%d,%d,%s,%d,%d,%s,%" PRIu64 ",%" PRIu64 ",%" PRIu64 + ",%" PRIu64 ",%s,%s,%s,%s,%d,%d,%.12g,%.12g,%.12g,%.12g,%.12g,%" PRIu64, + g->index, g->graph6, g->n, g->m, girth, diameter, + bipartite ? "True" : "False", vconn, econn, automorphism_order, + triangle_count, four_cycle_count, five_cycle_count, six_cycle_count, + adjacency_spectrum, laplacian_spectrum, spanning_trees, genus_stats.spectrum, + genus_stats.gamma, genus_stats.g_max, genus_stats.expected, genus_stats.variance, + genus_stats.r, genus_stats.r1, genus_stats.r2, + genus_stats.total_rotation_systems); + if (written < 0 || written >= GP_ROW_CAP) { + free(row); + snprintf(err, err_len, "CSV row exceeded internal buffer"); + return NULL; + } + return row; +} + +static void *worker_main(void *arg) { + WorkQueue *work = (WorkQueue *)arg; + + for (;;) { + pthread_mutex_lock(&work->mutex); + if (work->stop_requested || work->next_index >= work->count) { + pthread_mutex_unlock(&work->mutex); + break; + } + size_t index = work->next_index++; + pthread_mutex_unlock(&work->mutex); + + Result *result = &work->results[index]; + Graph graph; + char err[GP_ERROR_CAP] = ""; + + if (!parse_graph6(work->lines[index], index, &graph, err, sizeof(err))) { + snprintf(result->error, sizeof(result->error), "%s", err); + result->skipped = work->options->skip_invalid; + if (!work->options->skip_invalid) { + pthread_mutex_lock(&work->mutex); + work->stop_requested = true; + pthread_mutex_unlock(&work->mutex); + } + } else { + char *row = analyze_graph_to_csv(&graph, work->options, err, sizeof(err)); + if (!row) { + snprintf(result->error, sizeof(result->error), "%s", err); + result->skipped = work->options->skip_invalid; + if (!work->options->skip_invalid) { + pthread_mutex_lock(&work->mutex); + work->stop_requested = true; + pthread_mutex_unlock(&work->mutex); + } + } else { + result->row = row; + result->ok = true; + } + } + + pthread_mutex_lock(&work->mutex); + ++work->processed; + if (work->options->progress_every > 0 && + work->processed % work->options->progress_every == 0) { + fprintf(stderr, "Processed %zu/%zu graphs\n", work->processed, work->count); + } + pthread_mutex_unlock(&work->mutex); + } + return NULL; +} + +static bool stream_queue_stopped(StreamQueue *queue) { + bool stopped; + pthread_mutex_lock(&queue->mutex); + stopped = queue->stop_requested; + pthread_mutex_unlock(&queue->mutex); + return stopped; +} + +static void stream_queue_init(StreamQueue *queue, const Options *options, FILE *out) { + memset(queue, 0, sizeof(*queue)); + queue->options = options; + queue->out = out; + queue->job_capacity = (size_t)options->threads * 8; + if (queue->job_capacity < 128) queue->job_capacity = 128; + if (queue->job_capacity > 8192) queue->job_capacity = 8192; + queue->jobs = calloc(queue->job_capacity, sizeof(*queue->jobs)); + if (!queue->jobs) die_errno("calloc stream jobs"); + pthread_mutex_init(&queue->mutex, NULL); + pthread_cond_init(&queue->not_empty, NULL); + pthread_cond_init(&queue->not_full, NULL); +} + +static void stream_queue_destroy(StreamQueue *queue) { + for (size_t i = 0; i < queue->job_count; ++i) { + size_t pos = (queue->job_head + i) % queue->job_capacity; + free(queue->jobs[pos].line); + } + for (size_t i = 0; i < queue->result_capacity; ++i) { + free(queue->results[i].row); + } + free(queue->jobs); + free(queue->results); + pthread_cond_destroy(&queue->not_empty); + pthread_cond_destroy(&queue->not_full); + pthread_mutex_destroy(&queue->mutex); +} + +static void stream_queue_finish_producer(StreamQueue *queue) { + pthread_mutex_lock(&queue->mutex); + queue->producer_done = true; + pthread_cond_broadcast(&queue->not_empty); + pthread_mutex_unlock(&queue->mutex); +} + +static bool stream_queue_enqueue(StreamQueue *queue, char *line, size_t index) { + pthread_mutex_lock(&queue->mutex); + while (queue->job_count == queue->job_capacity && !queue->stop_requested) { + pthread_cond_wait(&queue->not_full, &queue->mutex); + } + if (queue->stop_requested) { + pthread_mutex_unlock(&queue->mutex); + return false; + } + + queue->jobs[queue->job_tail].index = index; + queue->jobs[queue->job_tail].line = line; + queue->job_tail = (queue->job_tail + 1) % queue->job_capacity; + ++queue->job_count; + ++queue->enqueued; + pthread_cond_signal(&queue->not_empty); + pthread_mutex_unlock(&queue->mutex); + return true; +} + +static void stream_queue_ensure_result_capacity_locked(StreamQueue *queue, + size_t index) { + if (index < queue->result_capacity) return; + + size_t new_capacity = queue->result_capacity ? queue->result_capacity * 2 : 1024; + while (new_capacity <= index) new_capacity *= 2; + StreamResult *new_results = + realloc(queue->results, new_capacity * sizeof(*queue->results)); + if (!new_results) die_errno("realloc stream results"); + memset(new_results + queue->result_capacity, 0, + (new_capacity - queue->result_capacity) * sizeof(*new_results)); + queue->results = new_results; + queue->result_capacity = new_capacity; +} + +static void stream_queue_flush_ready_locked(StreamQueue *queue) { + while (queue->next_to_emit < queue->result_capacity) { + StreamResult *result = &queue->results[queue->next_to_emit]; + if (!result->ready) break; + + if (result->kind == STREAM_RESULT_OK) { + fprintf(queue->out, "%s\n", result->row); + free(result->row); + result->row = NULL; + ++queue->written; + } else if (result->kind == STREAM_RESULT_SKIPPED) { + fprintf(stderr, "skipped graph %zu: %s\n", queue->next_to_emit, + result->error); + ++queue->skipped; + } else if (result->kind == STREAM_RESULT_ERROR) { + fprintf(stderr, "failed graph %zu: %s\n", queue->next_to_emit, + result->error); + ++queue->errors; + } + + result->ready = false; + result->kind = STREAM_RESULT_EMPTY; + ++queue->next_to_emit; + } +} + +static void *stream_worker_main(void *arg) { + StreamQueue *queue = (StreamQueue *)arg; + + for (;;) { + pthread_mutex_lock(&queue->mutex); + while (queue->job_count == 0 && !queue->producer_done && + !queue->stop_requested) { + pthread_cond_wait(&queue->not_empty, &queue->mutex); + } + if (queue->job_count == 0 && (queue->producer_done || queue->stop_requested)) { + pthread_mutex_unlock(&queue->mutex); + break; + } + + StreamJob job = queue->jobs[queue->job_head]; + queue->jobs[queue->job_head].line = NULL; + queue->job_head = (queue->job_head + 1) % queue->job_capacity; + --queue->job_count; + pthread_cond_signal(&queue->not_full); + pthread_mutex_unlock(&queue->mutex); + + Graph graph; + char err[GP_ERROR_CAP] = ""; + StreamResultKind kind = STREAM_RESULT_EMPTY; + char *row = NULL; + + if (!parse_graph6(job.line, job.index, &graph, err, sizeof(err))) { + kind = queue->options->skip_invalid ? STREAM_RESULT_SKIPPED + : STREAM_RESULT_ERROR; + } else { + row = analyze_graph_to_csv(&graph, queue->options, err, sizeof(err)); + if (row) { + kind = STREAM_RESULT_OK; + } else { + kind = queue->options->skip_invalid ? STREAM_RESULT_SKIPPED + : STREAM_RESULT_ERROR; + } + } + free(job.line); + + pthread_mutex_lock(&queue->mutex); + stream_queue_ensure_result_capacity_locked(queue, job.index); + StreamResult *result = &queue->results[job.index]; + result->kind = kind; + result->row = row; + if (kind == STREAM_RESULT_SKIPPED || kind == STREAM_RESULT_ERROR) { + snprintf(result->error, sizeof(result->error), "%s", err); + } + result->ready = true; + if (kind == STREAM_RESULT_ERROR) { + queue->stop_requested = true; + pthread_cond_broadcast(&queue->not_full); + pthread_cond_broadcast(&queue->not_empty); + } + + ++queue->processed; + stream_queue_flush_ready_locked(queue); + if (queue->options->progress_every > 0 && + queue->processed % queue->options->progress_every == 0) { + fprintf(stderr, "Processed %zu graphs\n", queue->processed); + fflush(stderr); + fflush(queue->out); + } + pthread_mutex_unlock(&queue->mutex); + } + return NULL; +} + +static size_t stream_graph6_records(FILE *stream, StreamQueue *queue, + bool *hit_limit) { + char *buffer = NULL; + size_t cap = 0; + ssize_t len; + size_t produced = 0; + + while ((len = getline(&buffer, &cap, stream)) != -1) { + (void)len; + char *trimmed = trim_graph6_line(buffer); + if (*trimmed == '\0') continue; + + if (queue->options->limit > 0 && produced >= queue->options->limit) { + *hit_limit = true; + break; + } + + char *line = xstrdup(trimmed); + if (!stream_queue_enqueue(queue, line, produced)) { + free(line); + break; + } + ++produced; + + if (queue->options->limit > 0 && produced >= queue->options->limit) { + *hit_limit = true; + break; + } + } + + free(buffer); + return produced; +} + +static int stream_graph6_from_geng(const Options *options, StreamQueue *queue) { + char command[256]; + if (options->generate_cubic_n <= 0 || options->generate_cubic_n > GP_MAX_N) { + die("--generate-cubic N needs 1 <= N <= 64"); + } + int written = snprintf(command, sizeof(command), "%s -cd3D3 -q %d", + options->geng_path, options->generate_cubic_n); + if (written < 0 || written >= (int)sizeof(command)) { + die("geng command is too long"); + } + + FILE *stream = popen(command, "r"); + if (!stream) die_errno("popen(geng)"); + bool hit_limit = false; + stream_graph6_records(stream, queue, &hit_limit); + stream_queue_finish_producer(queue); + int status = pclose(stream); + if (status != 0 && !hit_limit && !stream_queue_stopped(queue)) { + fprintf(stderr, "warning: geng command exited with status %d\n", status); + } + return status; +} + +static int default_thread_count(void) { +#ifdef _SC_NPROCESSORS_ONLN + long ncpu = sysconf(_SC_NPROCESSORS_ONLN); + if (ncpu < 1) return 1; + if (ncpu > 64) return 64; + return (int)ncpu; +#elif defined(__APPLE__) + int ncpu = 1; + size_t len = sizeof(ncpu); + if (sysctlbyname("hw.ncpu", &ncpu, &len, NULL, 0) == 0 && ncpu > 0) { + return ncpu > 64 ? 64 : ncpu; + } + return 1; +#else + return 1; +#endif +} + +static void print_usage(FILE *stream) { + fprintf(stream, + "Usage: genus_properties [--graph6 FILE | --stdin | --generate-cubic N] [options]\n" + "\n" + "Inputs:\n" + " --graph6 FILE Read one graph6 cubic graph per line.\n" + " --stdin Read graph6 records from stdin.\n" + " --generate-cubic N Stream connected non-isomorphic cubic graphs from nauty geng.\n" + "\n" + "Options:\n" + " --out FILE Write CSV to FILE instead of stdout.\n" + " --threads N Worker threads (default: online CPU count).\n" + " --limit N Stop after N graph6 records.\n" + " --progress-every N Print progress every N processed graphs (default: 1000).\n" + " --skip-invalid Skip invalid records instead of failing.\n" + " --geng PATH geng executable path/name (default: geng).\n" + " --no-automorphisms Write NA for automorphism_group_order.\n" + " --no-matrix-spectra Write NA for adjacency/laplacian spectra.\n" + " --no-spanning-trees Write NA for spanning_tree_count.\n" + " --help Show this help.\n"); +} + +static bool parse_positive_int(const char *text, int *out) { + char *end = NULL; + errno = 0; + long value = strtol(text, &end, 10); + if (errno || end == text || *end != '\0' || value <= 0 || value > INT32_MAX) { + return false; + } + *out = (int)value; + return true; +} + +static bool parse_size(const char *text, size_t *out) { + char *end = NULL; + errno = 0; + unsigned long long value = strtoull(text, &end, 10); + if (errno || end == text || *end != '\0') return false; + *out = (size_t)value; + return true; +} + +static Options parse_options(int argc, char **argv) { + Options options = { + .input_stdin = false, + .input_path = NULL, + .generate_cubic_n = 0, + .geng_path = "geng", + .out_path = NULL, + .threads = default_thread_count(), + .limit = 0, + .progress_every = 1000, + .skip_invalid = false, + .compute_automorphisms = true, + .compute_matrix_spectra = true, + .compute_spanning_trees = true, + }; + + for (int i = 1; i < argc; ++i) { + const char *arg = argv[i]; + if (strcmp(arg, "--help") == 0 || strcmp(arg, "-h") == 0) { + print_usage(stdout); + exit(0); + } else if (strcmp(arg, "--stdin") == 0) { + options.input_stdin = true; + } else if (strcmp(arg, "--graph6") == 0 || strcmp(arg, "-i") == 0) { + if (++i >= argc) die("--graph6 needs a path"); + options.input_path = argv[i]; + } else if (strcmp(arg, "--generate-cubic") == 0) { + if (++i >= argc || !parse_positive_int(argv[i], &options.generate_cubic_n)) { + die("--generate-cubic needs a positive integer"); + } + } else if (strcmp(arg, "--geng") == 0) { + if (++i >= argc) die("--geng needs a path"); + options.geng_path = argv[i]; + } else if (strcmp(arg, "--out") == 0 || strcmp(arg, "-o") == 0) { + if (++i >= argc) die("--out needs a path"); + options.out_path = argv[i]; + } else if (strcmp(arg, "--threads") == 0 || strcmp(arg, "-j") == 0) { + if (++i >= argc || !parse_positive_int(argv[i], &options.threads)) { + die("--threads needs a positive integer"); + } + } else if (strcmp(arg, "--limit") == 0) { + if (++i >= argc || !parse_size(argv[i], &options.limit)) { + die("--limit needs a nonnegative integer"); + } + } else if (strcmp(arg, "--progress-every") == 0) { + if (++i >= argc || !parse_size(argv[i], &options.progress_every)) { + die("--progress-every needs a nonnegative integer"); + } + } else if (strcmp(arg, "--skip-invalid") == 0) { + options.skip_invalid = true; + } else if (strcmp(arg, "--no-automorphisms") == 0) { + options.compute_automorphisms = false; + } else if (strcmp(arg, "--no-matrix-spectra") == 0) { + options.compute_matrix_spectra = false; + } else if (strcmp(arg, "--no-spanning-trees") == 0) { + options.compute_spanning_trees = false; + } else { + fprintf(stderr, "unknown option: %s\n", arg); + print_usage(stderr); + exit(2); + } + } + + int input_modes = (options.input_stdin ? 1 : 0) + (options.input_path ? 1 : 0) + + (options.generate_cubic_n > 0 ? 1 : 0); + if (input_modes != 1) { + die("choose exactly one input mode: --graph6, --stdin, or --generate-cubic"); + } + if (options.threads < 1) options.threads = 1; + return options; +} + +static void write_csv_header(FILE *out) { + fprintf(out, + "index,graph6,n,m,girth,diameter,bipartite,vertex_connectivity," + "edge_connectivity,automorphism_group_order,triangle_count," + "four_cycle_count,five_cycle_count,six_cycle_count,adjacency_spectrum," + "laplacian_spectrum,spanning_tree_count,spectrum,gamma,g_max," + "expected_genus,variance,R,R_1,R_2,total_rotation_systems\n"); +} + +static FILE *open_output(const Options *options) { + if (!options->out_path) return stdout; + FILE *out = fopen(options->out_path, "w"); + if (!out) die_errno(options->out_path); + return out; +} + +int main(int argc, char **argv) { + Options options = parse_options(argc, argv); + StringVec lines = {0}; + + if (options.generate_cubic_n > 0) { + FILE *out = open_output(&options); + write_csv_header(out); + fflush(out); + + StreamQueue queue; + stream_queue_init(&queue, &options, out); + pthread_t *threads = calloc((size_t)options.threads, sizeof(*threads)); + if (!threads) die_errno("calloc stream threads"); + + for (int i = 0; i < options.threads; ++i) { + int rc = pthread_create(&threads[i], NULL, stream_worker_main, &queue); + if (rc != 0) { + errno = rc; + die_errno("pthread_create"); + } + } + + stream_graph6_from_geng(&options, &queue); + + for (int i = 0; i < options.threads; ++i) pthread_join(threads[i], NULL); + free(threads); + + pthread_mutex_lock(&queue.mutex); + stream_queue_flush_ready_locked(&queue); + fflush(queue.out); + size_t enqueued = queue.enqueued; + size_t written = queue.written; + size_t skipped = queue.skipped; + size_t errors = queue.errors; + pthread_mutex_unlock(&queue.mutex); + + if (out != stdout) fclose(out); + stream_queue_destroy(&queue); + + if (enqueued == 0) { + fprintf(stderr, "error: no graph6 records found\n"); + return 1; + } + if (skipped > 0) { + fprintf(stderr, "Skipped %zu invalid graph%s\n", skipped, + skipped == 1 ? "" : "s"); + } + fprintf(stderr, "Wrote %zu graph row%s\n", written, + written == 1 ? "" : "s"); + return errors > 0 ? 1 : 0; + } + + if (options.input_stdin) { + read_lines_from_stream(stdin, &lines, options.limit); + } else { + read_graph6_file(options.input_path, &lines, options.limit); + } + + if (lines.count == 0) die("no graph6 records found"); + if ((size_t)options.threads > lines.count) options.threads = (int)lines.count; + + Result *results = calloc(lines.count, sizeof(*results)); + pthread_t *threads = calloc((size_t)options.threads, sizeof(*threads)); + if (!results || !threads) die_errno("calloc"); + + WorkQueue work = { + .options = &options, + .lines = lines.items, + .count = lines.count, + .next_index = 0, + .processed = 0, + .stop_requested = false, + .mutex = PTHREAD_MUTEX_INITIALIZER, + .results = results, + }; + + for (int i = 0; i < options.threads; ++i) { + int rc = pthread_create(&threads[i], NULL, worker_main, &work); + if (rc != 0) { + errno = rc; + die_errno("pthread_create"); + } + } + for (int i = 0; i < options.threads; ++i) pthread_join(threads[i], NULL); + + FILE *out = open_output(&options); + write_csv_header(out); + + size_t ok_count = 0, skipped_count = 0, error_count = 0; + for (size_t i = 0; i < lines.count; ++i) { + if (results[i].ok) { + fprintf(out, "%s\n", results[i].row); + ++ok_count; + } else if (results[i].skipped) { + ++skipped_count; + fprintf(stderr, "skipped graph %zu: %s\n", i, results[i].error); + } else if (results[i].error[0]) { + ++error_count; + fprintf(stderr, "failed graph %zu: %s\n", i, results[i].error); + } + } + if (out != stdout) fclose(out); + + for (size_t i = 0; i < lines.count; ++i) free(results[i].row); + free(results); + free(threads); + string_vec_free(&lines); + + if (skipped_count > 0) { + fprintf(stderr, "Skipped %zu invalid graph%s\n", skipped_count, + skipped_count == 1 ? "" : "s"); + } + if (error_count > 0) return 1; + fprintf(stderr, "Wrote %zu graph row%s\n", ok_count, ok_count == 1 ? "" : "s"); + return 0; +} diff --git a/Obstructions/KuratowskiMinors.csv b/experiments/Obstructions/KuratowskiMinors.csv similarity index 100% rename from Obstructions/KuratowskiMinors.csv rename to experiments/Obstructions/KuratowskiMinors.csv diff --git a/Obstructions/KuratowskiMinors.ipynb b/experiments/Obstructions/KuratowskiMinors.ipynb similarity index 100% rename from Obstructions/KuratowskiMinors.ipynb rename to experiments/Obstructions/KuratowskiMinors.ipynb diff --git a/Obstructions/KuratowskiMinors2.csv b/experiments/Obstructions/KuratowskiMinors2.csv similarity index 100% rename from Obstructions/KuratowskiMinors2.csv rename to experiments/Obstructions/KuratowskiMinors2.csv diff --git a/Obstructions/KuratowskiMinorsParallel.py b/experiments/Obstructions/KuratowskiMinorsParallel.py similarity index 100% rename from Obstructions/KuratowskiMinorsParallel.py rename to experiments/Obstructions/KuratowskiMinorsParallel.py diff --git a/Obstructions/SDMvertexcutsnomorethan1.png b/experiments/Obstructions/SDMvertexcutsnomorethan1.png similarity index 100% rename from Obstructions/SDMvertexcutsnomorethan1.png rename to experiments/Obstructions/SDMvertexcutsnomorethan1.png diff --git a/Obstructions/Test.ipynb b/experiments/Obstructions/Test.ipynb similarity index 100% rename from Obstructions/Test.ipynb rename to experiments/Obstructions/Test.ipynb diff --git a/Obstructions/adj_format.py b/experiments/Obstructions/adj_format.py similarity index 100% rename from Obstructions/adj_format.py rename to experiments/Obstructions/adj_format.py diff --git a/Obstructions/compute_stats.py b/experiments/Obstructions/compute_stats.py similarity index 100% rename from Obstructions/compute_stats.py rename to experiments/Obstructions/compute_stats.py diff --git a/Obstructions/disconnected0.png b/experiments/Obstructions/disconnected0.png similarity index 100% rename from Obstructions/disconnected0.png rename to experiments/Obstructions/disconnected0.png diff --git a/Obstructions/disconnected1.png b/experiments/Obstructions/disconnected1.png similarity index 100% rename from Obstructions/disconnected1.png rename to experiments/Obstructions/disconnected1.png diff --git a/Obstructions/disconnected2.png b/experiments/Obstructions/disconnected2.png similarity index 100% rename from Obstructions/disconnected2.png rename to experiments/Obstructions/disconnected2.png diff --git a/Obstructions/find_obstructions.py b/experiments/Obstructions/find_obstructions.py similarity index 100% rename from Obstructions/find_obstructions.py rename to experiments/Obstructions/find_obstructions.py diff --git a/Obstructions/genus_algos.py b/experiments/Obstructions/genus_algos.py similarity index 89% rename from Obstructions/genus_algos.py rename to experiments/Obstructions/genus_algos.py index d9d9408..e0bcdfa 100644 --- a/Obstructions/genus_algos.py +++ b/experiments/Obstructions/genus_algos.py @@ -5,7 +5,7 @@ def run_page(g, max_degree, filename, timeout=100): command = Command( - f'cd ../CalcGenus && S="0" DEG="{max_degree}" ADJ="{filename}" make run' + f'cd ../PAGE && S="0" DEG="{max_degree}" ADJ="{filename}" make run' ) returncode = command.run(timeout=timeout, hide_output=False) if returncode != 0: @@ -40,11 +40,11 @@ def run_algorithm(graph, algorithm="MULTI", timeout=100): genus = 0 for g in graph.connected_components_subgraphs(): if algorithm == "PAGE": - filename = "../CalcGenus/adjacency_lists/nauty_temp.txt" + filename = "../PAGE/adjacency_lists/nauty_temp.txt" _, max_degree = to_adj_list(g, filename) genus += run_page(g, max_degree, filename, timeout=timeout) # type: ignore elif algorithm == "MULTI": - filename = "../CalcGenus/adjacency_lists/nauty_temp.txt" + filename = "../PAGE/adjacency_lists/nauty_temp.txt" adjacency_list, max_degree = to_adj_list(g, filename) multi_filename = "../MultiGenus/graphs/nauty_temp.mc" to_multi_code(adjacency_list, multi_filename) diff --git a/Obstructions/inner_paths.py b/experiments/Obstructions/inner_paths.py similarity index 100% rename from Obstructions/inner_paths.py rename to experiments/Obstructions/inner_paths.py diff --git a/Obstructions/list_genus_g_embeddings.py b/experiments/Obstructions/list_genus_g_embeddings.py similarity index 100% rename from Obstructions/list_genus_g_embeddings.py rename to experiments/Obstructions/list_genus_g_embeddings.py diff --git a/Obstructions/minor_obs_stats.csv b/experiments/Obstructions/minor_obs_stats.csv similarity index 100% rename from Obstructions/minor_obs_stats.csv rename to experiments/Obstructions/minor_obs_stats.csv diff --git a/Obstructions/myrvold_minor_obs.txt b/experiments/Obstructions/myrvold_minor_obs.txt similarity index 100% rename from Obstructions/myrvold_minor_obs.txt rename to experiments/Obstructions/myrvold_minor_obs.txt diff --git a/Obstructions/myrvold_minor_obs_split_delete_min.txt b/experiments/Obstructions/myrvold_minor_obs_split_delete_min.txt similarity index 100% rename from Obstructions/myrvold_minor_obs_split_delete_min.txt rename to experiments/Obstructions/myrvold_minor_obs_split_delete_min.txt diff --git a/Obstructions/myrvold_obs.txt b/experiments/Obstructions/myrvold_obs.txt similarity index 100% rename from Obstructions/myrvold_obs.txt rename to experiments/Obstructions/myrvold_obs.txt diff --git a/Obstructions/obs_stats.csv b/experiments/Obstructions/obs_stats.csv similarity index 100% rename from Obstructions/obs_stats.csv rename to experiments/Obstructions/obs_stats.csv diff --git a/Obstructions/one_vertex_sum.py b/experiments/Obstructions/one_vertex_sum.py similarity index 100% rename from Obstructions/one_vertex_sum.py rename to experiments/Obstructions/one_vertex_sum.py diff --git a/Obstructions/plot_myrvold.py b/experiments/Obstructions/plot_myrvold.py similarity index 100% rename from Obstructions/plot_myrvold.py rename to experiments/Obstructions/plot_myrvold.py diff --git a/Obstructions/run_shell.py b/experiments/Obstructions/run_shell.py similarity index 100% rename from Obstructions/run_shell.py rename to experiments/Obstructions/run_shell.py diff --git a/Obstructions/split_delete_stats.csv b/experiments/Obstructions/split_delete_stats.csv similarity index 100% rename from Obstructions/split_delete_stats.csv rename to experiments/Obstructions/split_delete_stats.csv diff --git a/Obstructions/test_obstructions.py b/experiments/Obstructions/test_obstructions.py similarity index 100% rename from Obstructions/test_obstructions.py rename to experiments/Obstructions/test_obstructions.py diff --git a/Obstructions/torus_plot.py b/experiments/Obstructions/torus_plot.py similarity index 100% rename from Obstructions/torus_plot.py rename to experiments/Obstructions/torus_plot.py