Merge the commits to main into adaMala

.Rbuildignore

@@ -1,3 +1,5 @@
+^renv$
+^renv\.lock$
 ^.*\.Rproj$
 ^\.Rproj\.user$
 

.github/workflows/pr-commands.yaml

@@ -0,0 +1,91 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  issue_comment:
+    types: [created]
+
+name: pr-commands.yaml
+
+permissions: read-all
+
+jobs:
+  document:
+    if: ${{ github.event.issue.pull_request && (github.event.comment.author_association == 'MEMBER' || github.event.comment.author_association == 'OWNER') && startsWith(github.event.comment.body, '/document') }}
+    name: document
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+    permissions:
+      contents: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/pr-fetch@v2
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::roxygen2
+          needs: pr-document
+
+      - name: Document
+        run: roxygen2::roxygenise()
+        shell: Rscript {0}
+
+      - name: commit
+        run: |
+          git config --local user.name "$GITHUB_ACTOR"
+          git config --local user.email "[email protected]"
+          git add man/\* NAMESPACE
+          git commit -m 'Document'
+
+      - uses: r-lib/actions/pr-push@v2
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+
+  style:
+    if: ${{ github.event.issue.pull_request && (github.event.comment.author_association == 'MEMBER' || github.event.comment.author_association == 'OWNER') && startsWith(github.event.comment.body, '/style') }}
+    name: style
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+    permissions:
+      contents: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/pr-fetch@v2
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+
+      - uses: r-lib/actions/setup-r@v2
+
+      - name: Install dependencies
+        run: install.packages(c("styler", "roxygen2"))
+        shell: Rscript {0}
+
+      - name: Style
+        run: |
+          source("inst/styler/bgms_style.R")
+          styler::style_pkg(
+            style = bgms_style,
+            exclude_files = c("R/RcppExports\\.R", "R/cpp11\\.R", "R/import-standalone.*\\.R", "\\.Rprofile\\.R")
+          )
+
+        shell: Rscript {0}
+
+      - name: commit
+        run: |
+          git config --local user.name "$GITHUB_ACTOR"
+          git config --local user.email "[email protected]"
+          git add \*.R
+          git commit -m 'Style'
+
+      - uses: r-lib/actions/pr-push@v2
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}

.gitignore

@@ -6,5 +6,4 @@ src/*.o
 src/*.so
 src/*.dll
 inst/doc
-/doc/
-/Meta/
+.DS_Store

DESCRIPTION

@@ -2,7 +2,11 @@ Package: bgms
 Type: Package
 Title: Bayesian Analysis of Networks of Binary and/or Ordinal Variables
 Version: 0.1.5.0
+<<<<<<< HEAD
+Date: 2025-08-03
+=======
 Date: 2025-06-27
+>>>>>>> adaMala
 Authors@R: c(
     person("Maarten", "Marsman", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0001-5309-7502")),
@@ -16,19 +20,21 @@ Authors@R: c(
     comment = c(ORCID = "0000-0002-9838-7308"))
   )
 Maintainer: Maarten Marsman <[email protected]>
-Description: Bayesian variable selection methods for analyzing the structure of a Markov Random Field model for a network of binary and/or ordinal variables. Details of the implemented methods can be found in: Marsman, van den Bergh, and Haslbeck (in press) <doi:10.31234/osf.io/ukwrf>.
+Description: Bayesian variable selection methods for analyzing the structure of a Markov Random Field model for a network of binary and/or ordinal variables. Details of the implemented methods can be found in: Marsman, van den Bergh, and Haslbeck (2025) <doi:10.31234/osf.io/ukwrf>. 
+Copyright: Includes datasets 'ADHD' and 'Boredom', which are licensed under CC-BY 4. See individual data documentation for license and citation.
 License: GPL (>= 2)
-URL: https://maartenmarsman.github.io/bgms/
-BugReports: https://github.com/MaartenMarsman/bgms/issues
+URL: https://Bayesian-Graphical-Modelling-Lab.github.io/bgms/
+BugReports: https://github.com/Bayesian-Graphical-Modelling-Lab/bgms/issues
 Imports: Rcpp (>= 1.0.7), RcppParallel, Rdpack, methods, coda, dqrng
 RdMacros: Rdpack
 LinkingTo: Rcpp, RcppProgress, RcppArmadillo, RcppParallel, dqrng, BH
 RoxygenNote: 7.3.2
 Depends: 
-    R (>= 2.10)
+    R (>= 3.5)
 LazyData: true
 Encoding: UTF-8
 Suggests: 
+    ggplot2,
     knitr,
     parallel,
     qgraph,
@@ -37,4 +43,4 @@ Suggests:
     testthat (>= 3.0.0)
 VignetteBuilder: knitr
 Config/testthat/edition: 3
-Config/Needs/website: tidyverse/tidytemplate
+Config/Needs/website: tidyverse/tidytemplate

NEWS.md

@@ -1,20 +1,24 @@
-# bgms 0.1.4.3
+# bgms 0.1.5.0
 
 ## New features
 
 * The bgmCompare function now allows for network comparison for two or more groups.
 * The new summary_sbm function can be used to summarize the output from the bgm function with the "Stochastic-Block" prior. 
+* Two new data sets are included in the package: ADHD and Boredom.
 
 ## Other changes
 
 * The bgm function with the "Stochastic-Block" prior can now also return the sampled allocations and block probabilities, and sample and return the number of blocks.
 * The underlying R and c++ functions received a massive update to improve their efficiency and maintainance.
+* Repository moved to the Bayesian Graphical Modelling Lab organization.
+* Included custom c++ implementations for exp and log on Windows. 
 
 ## Bug fixes
 
 * Fixed a bug in the bgmCompare function with selecting group differences of blume-capel parameters. Parameter differences that were not selected and should be fixed to zero were still updated.
 * Fixed a bug in the bgmCompare function with handling the samples of blume-capel parameters. Output was not properly stored.
 * Fixed a bug in the bgmCompare function with handling threshold estimation when missing categories and main_model = "Free". The sufficient statistics and number of categories were not computed correctly.
+* Partially fixed a bug in which the bgms package is slower on Windows than on Linux or MacOS. This is because the computation of exp and log using the gcc compiler for Windows is really slow. With a custom c++ implementation, the speed is now closer to the speed achieved on Linux and MacOS.
 
 # bgms 0.1.4.2
 

R/RcppExports.R

@@ -1,6 +1,18 @@
 # Generated by using Rcpp::compileAttributes() -> do not edit by hand
 # Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
 
+get_explog_switch <- function() {
+    .Call(`_bgms_get_explog_switch`)
+}
+
+rcpp_ieee754_exp <- function(x) {
+    .Call(`_bgms_rcpp_ieee754_exp`, x)
+}
+
+rcpp_ieee754_log <- function(x) {
+    .Call(`_bgms_rcpp_ieee754_log`, x)
+}
+
 run_bgmCompare_parallel <- function(observations, num_groups, counts_per_category, blume_capel_stats, pairwise_stats, num_categories, main_alpha, main_beta, pairwise_scale, difference_scale, difference_selection_alpha, difference_selection_beta, difference_prior, iter, burnin, na_impute, missing_data_indices, is_ordinal_variable, baseline_category, difference_selection, main_effect_indices, pairwise_effect_indices, target_accept, nuts_max_depth, learn_mass_matrix, projection, group_membership, group_indices, interaction_index_matrix, inclusion_probability, num_chains, nThreads, seed, update_method, hmc_num_leapfrogs) {
     .Call(`_bgms_run_bgmCompare_parallel`, observations, num_groups, counts_per_category, blume_capel_stats, pairwise_stats, num_categories, main_alpha, main_beta, pairwise_scale, difference_scale, difference_selection_alpha, difference_selection_beta, difference_prior, iter, burnin, na_impute, missing_data_indices, is_ordinal_variable, baseline_category, difference_selection, main_effect_indices, pairwise_effect_indices, target_accept, nuts_max_depth, learn_mass_matrix, projection, group_membership, group_indices, interaction_index_matrix, inclusion_probability, num_chains, nThreads, seed, update_method, hmc_num_leapfrogs)
 }
@@ -19,5 +31,4 @@ sample_bcomrf_gibbs <- function(no_states, no_variables, no_categories, interact
 
 compute_Vn_mfm_sbm <- function(no_variables, dirichlet_alpha, t_max, lambda) {
     .Call(`_bgms_compute_Vn_mfm_sbm`, no_variables, dirichlet_alpha, t_max, lambda)
-}
-
+}