parallel progress bar and interrupt (#56)

* parallel progress bar and interrupt

* let's rebase first

* fix rebase

* almost done

* cleanup

* fix rebase again

Author: vandenman

R/RcppExports.R

@@ -1,12 +1,12 @@
 # Generated by using Rcpp::compileAttributes() -> do not edit by hand
 # Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
 
-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)
+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, progress_type) {
+    .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, progress_type)
 }
 
-run_bgm_parallel <- function(observations, num_categories, pairwise_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed) {
-    .Call(`_bgms_run_bgm_parallel`, observations, num_categories, pairwise_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed)
+run_bgm_parallel <- function(observations, num_categories, pairwise_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed, progress_type) {
+    .Call(`_bgms_run_bgm_parallel`, observations, num_categories, pairwise_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed, progress_type)
 }
 
 get_explog_switch <- function() {

R/bgm.R

@@ -237,7 +237,7 @@ bgm = function(
     dirichlet_alpha = 1,
     lambda = 1,
     na_action = c("listwise", "impute"),
-    display_progress = TRUE,
+    display_progress = c("per-chain", "total", "none"),
     update_method = c("nuts", "adaptive-metropolis", "hamiltonian-mc"),
     target_accept,
     hmc_num_leapfrogs = 100,
@@ -324,7 +324,7 @@ bgm = function(
                 "."))
 
   #Check display_progress ------------------------------------------------------
-  display_progress = check_logical(display_progress, "display_progress")
+  progress_type = progress_type_from_display_progress(display_progress)
 
   #Format the data input -------------------------------------------------------
   data = reformat_data(x = x,
@@ -428,7 +428,7 @@ bgm = function(
     target_accept = target_accept, pairwise_stats = pairwise_stats,
     hmc_num_leapfrogs = hmc_num_leapfrogs, nuts_max_depth = nuts_max_depth,
     learn_mass_matrix = learn_mass_matrix, num_chains = chains,
-    nThreads = cores, seed = seed
+    nThreads = cores, seed = seed, progress_type = progress_type
   )
 
   # Main output handler in the wrapper function
@@ -457,5 +457,9 @@ bgm = function(
     output$nuts_diag = nuts_diag
   }
 
+  userInterrupt = any(vapply(out, FUN = `[[`, FUN.VALUE = logical(1L), "userInterrupt"))
+  if (userInterrupt)
+    warning("Stopped sampling after user interrupt, results are likely uninterpretable.")
+
   return(output)
 }

R/bgmCompare.R

@@ -122,7 +122,7 @@ bgmCompare = function(
     iter = 1e3,
     burnin = 1e3,
     na_action = c("listwise", "impute"),
-    display_progress = TRUE,
+    display_progress =  c("per-chain", "total", "none"),
     update_method = c("nuts", "adaptive-metropolis", "hamiltonian-mc"),
     target_accept,
     hmc_num_leapfrogs = 100,
@@ -202,7 +202,8 @@ bgmCompare = function(
   }
 
   # Check display_progress
-  display_progress = check_logical(display_progress, "display_progress")
+  progress_type = progress_type_from_display_progress(display_progress)
+
 
   ## Format data
   data = compare_reformat_data(
@@ -340,7 +341,8 @@ bgmCompare = function(
     inclusion_probability = model$inclusion_probability_difference,
     num_chains = chains, nThreads = cores,
     seed = seed,
-    update_method = update_method, hmc_num_leapfrogs = hmc_num_leapfrogs
+    update_method = update_method, hmc_num_leapfrogs = hmc_num_leapfrogs,
+    progress_type = progress_type
   )
 
   # Main output handler in the wrapper function

R/function_input_utils.R

@@ -463,4 +463,15 @@ check_compare_model = function(
       inclusion_probability_difference = inclusion_probability_difference
       )
   )
-}
+}
+
+progress_type_from_display_progress <- function(display_progress = c("per-chain", "total", "none")) {
+  if (is.logical(display_progress) && length(display_progress) == 1) {
+    if (is.na(display_progress))
+      stop("The display_progress argument must be a single logical value, but not NA.")
+    display_progress = if (display_progress) "per-chain" else "none"
+  } else {
+    display_progress = match.arg(display_progress)
+  }
+  return(if (display_progress == "per-chain") 2L else if (display_progress == "total") 1L else 0L)
+}

src/Makevars.win

@@ -1,4 +1,4 @@
-CXX_STD = CXX14
+CXX_STD = CXX20
 
 PKG_CPPFLAGS = \
   $(shell "$(R_HOME)\bin\Rscript.exe" -e "cat(RcppParallel::CxxFlags())")

src/RcppExports.cpp

@@ -12,8 +12,8 @@ Rcpp::Rostream<false>& Rcpp::Rcerr = Rcpp::Rcpp_cerr_get();
 #endif
 
 // run_bgmCompare_parallel
-Rcpp::List run_bgmCompare_parallel(const arma::imat& observations, int num_groups, const std::vector<arma::imat>& counts_per_category, const std::vector<arma::imat>& blume_capel_stats, const std::vector<arma::mat>& pairwise_stats, const arma::ivec& num_categories, double main_alpha, double main_beta, double pairwise_scale, double difference_scale, double difference_selection_alpha, double difference_selection_beta, const std::string& difference_prior, int iter, int burnin, bool na_impute, const arma::imat& missing_data_indices, const arma::uvec& is_ordinal_variable, const arma::ivec& baseline_category, bool difference_selection, const arma::imat& main_effect_indices, const arma::imat& pairwise_effect_indices, double target_accept, int nuts_max_depth, bool learn_mass_matrix, const arma::mat& projection, const arma::ivec& group_membership, const arma::imat& group_indices, const arma::imat& interaction_index_matrix, const arma::mat& inclusion_probability, int num_chains, int nThreads, int seed, const std::string& update_method, int hmc_num_leapfrogs);
-RcppExport SEXP _bgms_run_bgmCompare_parallel(SEXP observationsSEXP, SEXP num_groupsSEXP, SEXP counts_per_categorySEXP, SEXP blume_capel_statsSEXP, SEXP pairwise_statsSEXP, SEXP num_categoriesSEXP, SEXP main_alphaSEXP, SEXP main_betaSEXP, SEXP pairwise_scaleSEXP, SEXP difference_scaleSEXP, SEXP difference_selection_alphaSEXP, SEXP difference_selection_betaSEXP, SEXP difference_priorSEXP, SEXP iterSEXP, SEXP burninSEXP, SEXP na_imputeSEXP, SEXP missing_data_indicesSEXP, SEXP is_ordinal_variableSEXP, SEXP baseline_categorySEXP, SEXP difference_selectionSEXP, SEXP main_effect_indicesSEXP, SEXP pairwise_effect_indicesSEXP, SEXP target_acceptSEXP, SEXP nuts_max_depthSEXP, SEXP learn_mass_matrixSEXP, SEXP projectionSEXP, SEXP group_membershipSEXP, SEXP group_indicesSEXP, SEXP interaction_index_matrixSEXP, SEXP inclusion_probabilitySEXP, SEXP num_chainsSEXP, SEXP nThreadsSEXP, SEXP seedSEXP, SEXP update_methodSEXP, SEXP hmc_num_leapfrogsSEXP) {
+Rcpp::List run_bgmCompare_parallel(const arma::imat& observations, int num_groups, const std::vector<arma::imat>& counts_per_category, const std::vector<arma::imat>& blume_capel_stats, const std::vector<arma::mat>& pairwise_stats, const arma::ivec& num_categories, double main_alpha, double main_beta, double pairwise_scale, double difference_scale, double difference_selection_alpha, double difference_selection_beta, const std::string& difference_prior, int iter, int burnin, bool na_impute, const arma::imat& missing_data_indices, const arma::uvec& is_ordinal_variable, const arma::ivec& baseline_category, bool difference_selection, const arma::imat& main_effect_indices, const arma::imat& pairwise_effect_indices, double target_accept, int nuts_max_depth, bool learn_mass_matrix, const arma::mat& projection, const arma::ivec& group_membership, const arma::imat& group_indices, const arma::imat& interaction_index_matrix, const arma::mat& inclusion_probability, int num_chains, int nThreads, int seed, const std::string& update_method, int hmc_num_leapfrogs, int progress_type);
+RcppExport SEXP _bgms_run_bgmCompare_parallel(SEXP observationsSEXP, SEXP num_groupsSEXP, SEXP counts_per_categorySEXP, SEXP blume_capel_statsSEXP, SEXP pairwise_statsSEXP, SEXP num_categoriesSEXP, SEXP main_alphaSEXP, SEXP main_betaSEXP, SEXP pairwise_scaleSEXP, SEXP difference_scaleSEXP, SEXP difference_selection_alphaSEXP, SEXP difference_selection_betaSEXP, SEXP difference_priorSEXP, SEXP iterSEXP, SEXP burninSEXP, SEXP na_imputeSEXP, SEXP missing_data_indicesSEXP, SEXP is_ordinal_variableSEXP, SEXP baseline_categorySEXP, SEXP difference_selectionSEXP, SEXP main_effect_indicesSEXP, SEXP pairwise_effect_indicesSEXP, SEXP target_acceptSEXP, SEXP nuts_max_depthSEXP, SEXP learn_mass_matrixSEXP, SEXP projectionSEXP, SEXP group_membershipSEXP, SEXP group_indicesSEXP, SEXP interaction_index_matrixSEXP, SEXP inclusion_probabilitySEXP, SEXP num_chainsSEXP, SEXP nThreadsSEXP, SEXP seedSEXP, SEXP update_methodSEXP, SEXP hmc_num_leapfrogsSEXP, SEXP progress_typeSEXP) {
 BEGIN_RCPP
     Rcpp::RObject rcpp_result_gen;
     Rcpp::RNGScope rcpp_rngScope_gen;
@@ -52,13 +52,14 @@ BEGIN_RCPP
     Rcpp::traits::input_parameter< int >::type seed(seedSEXP);
     Rcpp::traits::input_parameter< const std::string& >::type update_method(update_methodSEXP);
     Rcpp::traits::input_parameter< int >::type hmc_num_leapfrogs(hmc_num_leapfrogsSEXP);
-    rcpp_result_gen = Rcpp::wrap(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));
+    Rcpp::traits::input_parameter< int >::type progress_type(progress_typeSEXP);
+    rcpp_result_gen = Rcpp::wrap(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, progress_type));
     return rcpp_result_gen;
 END_RCPP
 }
 // run_bgm_parallel
-Rcpp::List run_bgm_parallel(const arma::imat& observations, const arma::ivec& num_categories, double pairwise_scale, const std::string& edge_prior, const arma::mat& inclusion_probability, double beta_bernoulli_alpha, double beta_bernoulli_beta, double dirichlet_alpha, double lambda, const arma::imat& interaction_index_matrix, int iter, int burnin, const arma::imat& counts_per_category, const arma::imat& blume_capel_stats, double main_alpha, double main_beta, bool na_impute, const arma::imat& missing_index, const arma::uvec& is_ordinal_variable, const arma::ivec& baseline_category, bool edge_selection, const std::string& update_method, const arma::imat& pairwise_effect_indices, double target_accept, const arma::imat& pairwise_stats, int hmc_num_leapfrogs, int nuts_max_depth, bool learn_mass_matrix, int num_chains, int nThreads, uint64_t seed);
-RcppExport SEXP _bgms_run_bgm_parallel(SEXP observationsSEXP, SEXP num_categoriesSEXP, SEXP pairwise_scaleSEXP, SEXP edge_priorSEXP, SEXP inclusion_probabilitySEXP, SEXP beta_bernoulli_alphaSEXP, SEXP beta_bernoulli_betaSEXP, SEXP dirichlet_alphaSEXP, SEXP lambdaSEXP, SEXP interaction_index_matrixSEXP, SEXP iterSEXP, SEXP burninSEXP, SEXP counts_per_categorySEXP, SEXP blume_capel_statsSEXP, SEXP main_alphaSEXP, SEXP main_betaSEXP, SEXP na_imputeSEXP, SEXP missing_indexSEXP, SEXP is_ordinal_variableSEXP, SEXP baseline_categorySEXP, SEXP edge_selectionSEXP, SEXP update_methodSEXP, SEXP pairwise_effect_indicesSEXP, SEXP target_acceptSEXP, SEXP pairwise_statsSEXP, SEXP hmc_num_leapfrogsSEXP, SEXP nuts_max_depthSEXP, SEXP learn_mass_matrixSEXP, SEXP num_chainsSEXP, SEXP nThreadsSEXP, SEXP seedSEXP) {
+Rcpp::List run_bgm_parallel(const arma::imat& observations, const arma::ivec& num_categories, double pairwise_scale, const std::string& edge_prior, const arma::mat& inclusion_probability, double beta_bernoulli_alpha, double beta_bernoulli_beta, double dirichlet_alpha, double lambda, const arma::imat& interaction_index_matrix, int iter, int burnin, const arma::imat& counts_per_category, const arma::imat& blume_capel_stats, double main_alpha, double main_beta, bool na_impute, const arma::imat& missing_index, const arma::uvec& is_ordinal_variable, const arma::ivec& baseline_category, bool edge_selection, const std::string& update_method, const arma::imat& pairwise_effect_indices, double target_accept, const arma::imat& pairwise_stats, int hmc_num_leapfrogs, int nuts_max_depth, bool learn_mass_matrix, int num_chains, int nThreads, uint64_t seed, int progress_type);
+RcppExport SEXP _bgms_run_bgm_parallel(SEXP observationsSEXP, SEXP num_categoriesSEXP, SEXP pairwise_scaleSEXP, SEXP edge_priorSEXP, SEXP inclusion_probabilitySEXP, SEXP beta_bernoulli_alphaSEXP, SEXP beta_bernoulli_betaSEXP, SEXP dirichlet_alphaSEXP, SEXP lambdaSEXP, SEXP interaction_index_matrixSEXP, SEXP iterSEXP, SEXP burninSEXP, SEXP counts_per_categorySEXP, SEXP blume_capel_statsSEXP, SEXP main_alphaSEXP, SEXP main_betaSEXP, SEXP na_imputeSEXP, SEXP missing_indexSEXP, SEXP is_ordinal_variableSEXP, SEXP baseline_categorySEXP, SEXP edge_selectionSEXP, SEXP update_methodSEXP, SEXP pairwise_effect_indicesSEXP, SEXP target_acceptSEXP, SEXP pairwise_statsSEXP, SEXP hmc_num_leapfrogsSEXP, SEXP nuts_max_depthSEXP, SEXP learn_mass_matrixSEXP, SEXP num_chainsSEXP, SEXP nThreadsSEXP, SEXP seedSEXP, SEXP progress_typeSEXP) {
 BEGIN_RCPP
     Rcpp::RObject rcpp_result_gen;
     Rcpp::RNGScope rcpp_rngScope_gen;
@@ -93,7 +94,8 @@ BEGIN_RCPP
     Rcpp::traits::input_parameter< int >::type num_chains(num_chainsSEXP);
     Rcpp::traits::input_parameter< int >::type nThreads(nThreadsSEXP);
     Rcpp::traits::input_parameter< uint64_t >::type seed(seedSEXP);
-    rcpp_result_gen = Rcpp::wrap(run_bgm_parallel(observations, num_categories, pairwise_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed));
+    Rcpp::traits::input_parameter< int >::type progress_type(progress_typeSEXP);
+    rcpp_result_gen = Rcpp::wrap(run_bgm_parallel(observations, num_categories, pairwise_scale, edge_prior, inclusion_probability, beta_bernoulli_alpha, beta_bernoulli_beta, dirichlet_alpha, lambda, interaction_index_matrix, iter, burnin, counts_per_category, blume_capel_stats, main_alpha, main_beta, na_impute, missing_index, is_ordinal_variable, baseline_category, edge_selection, update_method, pairwise_effect_indices, target_accept, pairwise_stats, hmc_num_leapfrogs, nuts_max_depth, learn_mass_matrix, num_chains, nThreads, seed, progress_type));
     return rcpp_result_gen;
 END_RCPP
 }
@@ -179,8 +181,8 @@ END_RCPP
 }
 
 static const R_CallMethodDef CallEntries[] = {
-    {"_bgms_run_bgmCompare_parallel", (DL_FUNC) &_bgms_run_bgmCompare_parallel, 35},
-    {"_bgms_run_bgm_parallel", (DL_FUNC) &_bgms_run_bgm_parallel, 31},
+    {"_bgms_run_bgmCompare_parallel", (DL_FUNC) &_bgms_run_bgmCompare_parallel, 36},
+    {"_bgms_run_bgm_parallel", (DL_FUNC) &_bgms_run_bgm_parallel, 32},
     {"_bgms_get_explog_switch", (DL_FUNC) &_bgms_get_explog_switch, 0},
     {"_bgms_rcpp_ieee754_exp", (DL_FUNC) &_bgms_rcpp_ieee754_exp, 1},
     {"_bgms_rcpp_ieee754_log", (DL_FUNC) &_bgms_rcpp_ieee754_log, 1},