Update generate_synthetic_df.R

caravagnalab · Jan 9, 2025 · 91aea10 · 91aea10
1 parent d45543d
commit 91aea10
Showing 1 changed file with 18 additions and 12 deletions.
diff --git a/R/generate_synthetic_df.R b/R/generate_synthetic_df.R
@@ -13,7 +13,7 @@ generate_synthetic_df = function(N_values,
                                  filename="",
                                  check_present=T,
                                  default_lm=FALSE,
-                                 run=T) {
+                                 run=T, py_pkg=NULL) {
 
   if (!endsWith(path, "/"))
     path = paste0(path, "/")
@@ -22,7 +22,7 @@ generate_synthetic_df = function(N_values,
     dir.create(path)
 
   torch = reticulate::import("torch")
-  py_pkg = reticulate::import("pylineaGT")
+  if (is.null(py_pkg)) py_pkg = reticulate::import("pylineaGT")
 
   mean_scale_inp = mean_scale
   alpha_inp = alpha
@@ -38,16 +38,16 @@ generate_synthetic_df = function(N_values,
       for (tt in T_values) {
         for (kk in K_values) {
 
-          if (tt == 1 && kk > 6) {
-            mean_scale = max(10100, mean_scale_inp)
-            alpha = max(0.45, alpha_inp)
-          } else if ((tt == 2 && kk > 6) || (tt == 1 && kk == 6)) {
-            mean_scale = max(8000, mean_scale_inp)
-            alpha = max(0.35, alpha_inp)
-          } else {
-            mean_scale = mean_scale_inp
-            alpha = alpha_inp
-          }
+          # if (tt == 1 && kk > 6) {
+          #   mean_scale = max(10100, mean_scale_inp)
+          #   # alpha = max(0.45, alpha_inp)
+          # } else if ((tt == 2 && kk > 6) || (tt == 1 && kk == 6)) {
+          #   mean_scale = max(8000, mean_scale_inp)
+          #   # alpha = max(0.35, alpha_inp)
+          # } else {
+          #   mean_scale = mean_scale_inp
+          #   # alpha = alpha_inp
+          # }
 
           cat(paste0("K=", kk, ", T=", tt, "\nmean_scale=", mean_scale, ", alpha=", alpha, "\n"))
 
@@ -91,6 +91,8 @@ generate_synthetic_df = function(N_values,
 
           k_interval = get_sim_k_interval(x, cov.df)
 
+          start_time = Sys.time()
+
           x_fit = fit(cov.df=cov.df,
                       k_interval=k_interval,
                       infer_growth=F,
@@ -106,10 +108,14 @@ generate_synthetic_df = function(N_values,
                       # init_seed=5,
                       sample_id=x$sim_id)
 
+          end_time = Sys.time()
+
           x_fit$cov.dataframe = tibble::as_tibble(x$dataset) %>%
             dplyr::mutate(coverage=as.integer(coverage)) %>%
             dplyr::inner_join(x_fit$cov.dataframe, by=c("IS","timepoints","lineage","coverage"))
 
+          x_fit$time = end_time - start_time
+
           print(aricode::ARI(x_fit$cov.dataframe$labels, x_fit$cov.dataframe$labels_true))
 
           saveRDS(x_fit, paste0(subpath, filename, ".fit.Rds"))