From a45be0776cf886ce758a7781c22abc1faaa59dd6 Mon Sep 17 00:00:00 2001
From: Alex Zwanenburg <alexander.zwanenburg@nct-dresden.de>
Date: Wed, 15 May 2024 11:21:48 +0200
Subject: [PATCH 1/8] Add checks on packages being present.

---
 R/TestDataCreators.R                    | 27 +++++++++++++++
 R/TestFunctions.R                       | 45 +++++++++++++++++++++++++
 tests/testthat/test-collection_labels.R |  2 ++
 tests/testthat/test-stratification.R    |  2 ++
 4 files changed, 76 insertions(+)

diff --git a/R/TestDataCreators.R b/R/TestDataCreators.R
index 13f13d19..d5a35583 100644
--- a/R/TestDataCreators.R
+++ b/R/TestDataCreators.R
@@ -1,3 +1,30 @@
+test_data_package_installed <- function(outcome_type) {
+  run_test <- TRUE
+
+  data_packages <- list(
+    "survival" = "survival",
+    "multinomial" = "datasets",
+    "binomial" = "MASS",
+    "continuous" = "Ecdat",
+    "count" = "MASS"
+  )
+  
+  if (!is_package_installed(data_packages[[outcome_type]])) run_test <- FALSE
+  
+  if (!run_test) {
+    rlang::inform(
+      message = paste0(
+        "Cannot run test because the ", 
+        data_packages[[outcome_type]], 
+        " package is not installed."),
+      class = "familiar_message_inform_no_test"
+    )
+  }
+  
+  return(run_test)
+}
+
+
 test.create_good_data_set <- function(outcome_type, to_data_object=TRUE){
   
   # Suppress NOTES due to non-standard evaluation in data.table
diff --git a/R/TestFunctions.R b/R/TestFunctions.R
index 95698d5c..bc1cdd32 100644
--- a/R/TestFunctions.R
+++ b/R/TestFunctions.R
@@ -1,3 +1,26 @@
+test_object_package_installed <- function(x) {
+  run_test <- TRUE
+  if (!is.null(x$error)) {
+    if (any(grepl("following package has to be installed", x$error, fixed = TRUE))) {
+      run_test <- FALSE
+    } else if (any(grepl("following packages have to be installed", x$error, fixed = TRUE))) {
+      run_test <- FALSE
+    } else {
+      stop(x$error)
+    }
+  }
+  
+  if (!run_test) {
+    rlang::inform(
+      message = x$error,
+      class = "familiar_message_inform_no_test"
+    )
+  }
+  
+  return(run_test)
+}
+
+
 test_all_learners_available <- function(learners){
   
   # Create placeholder flags.
@@ -57,6 +80,8 @@ test_all_learners_train_predict_vimp <- function(
   # Iterate over the outcome type.
   for(outcome_type in c("count", "continuous", "binomial", "multinomial", "survival")){
     
+    if (!test_data_package_installed(outcome_type)) next
+    
     # Obtain data.
     full_data <- test.create_good_data_set(outcome_type)
     full_one_sample_data <- test.create_one_sample_data_set(outcome_type)
@@ -1048,6 +1073,8 @@ test_all_learners_parallel_train_predict_vimp <- function(learners,
   # Iterate over the outcome type.
   for(outcome_type in c("count", "continuous", "binomial", "multinomial", "survival")){
     
+    if (!test_data_package_installed(outcome_type)) next
+    
     # Obtain data.
     full_data <- test.create_good_data_set(outcome_type)
     
@@ -1211,6 +1238,8 @@ test_all_novelty_detectors <- function(detectors,
   # Outcome type is not important, but set to get suitable datasets.
   outcome_type <- "continuous"
   
+  if (!test_data_package_installed(outcome_type)) return()
+  
   # Obtain data.
   full_data <- test.create_good_data_set(outcome_type)
   full_one_sample_data <- test.create_one_sample_data_set(outcome_type)
@@ -1418,6 +1447,8 @@ test_all_novelty_detectors_parallel <- function(detectors,
   # Outcome type is not important, but set to get suitable datasets.
   outcome_type <- "continuous"
   
+  if (!test_data_package_installed(outcome_type)) return()
+  
   # Obtain data.
   full_data <- test.create_good_data_set(outcome_type)
   
@@ -1531,6 +1562,8 @@ test_all_vimp_methods <- function(vimp_methods,
   # Iterate over the outcome type.
   for(outcome_type in c("count", "continuous", "binomial", "multinomial", "survival")){
     
+    if (!test_data_package_installed(outcome_type)) next
+    
     # Obtain data.
     full_data <- test.create_good_data_set(outcome_type)
     full_one_sample_data <- test.create_one_sample_data_set(outcome_type)
@@ -1858,6 +1891,8 @@ test_all_vimp_methods_parallel <- function(vimp_methods,
   # Iterate over the outcome type.
   for(outcome_type in c("count", "continuous", "binomial", "multinomial", "survival")){
     
+    if (!test_data_package_installed(outcome_type)) next
+    
     # Obtain data.
     full_data <- test.create_good_data_set(outcome_type)
     
@@ -1984,6 +2019,8 @@ test_all_metrics <- function(metrics,
   # Iterate over the outcome type.
   for(outcome_type in c("count", "continuous", "binomial", "multinomial", "survival")){
     
+    if (!test_data_package_installed(outcome_type)) next
+
     # Obtain data.
     full_data <- test.create_good_data_set(outcome_type)
     identical_sample_data <- test.create_all_identical_data_set(outcome_type)
@@ -2911,6 +2948,8 @@ test_hyperparameter_optimisation <- function(vimp_methods=NULL,
   # Iterate over the outcome type.
   for(outcome_type in outcome_type_available){
     
+    if (!test_data_package_installed(outcome_type)) next
+    
     # Multi-feature data sets.
     full_data <- test.create_good_data_set(outcome_type)
     identical_sample_data <- test.create_all_identical_data_set(outcome_type)
@@ -3482,6 +3521,8 @@ test_plots <- function(plot_function,
   # Iterate over the outcome type.
   for(outcome_type in c("count", "continuous", "survival", "binomial", "multinomial")){
     
+    if (!test_data_package_installed(outcome_type)) next
+    
     # Obtain data.
     full_data <- test.create_good_data_set(outcome_type)
     identical_sample_data <- test.create_all_identical_data_set(outcome_type)
@@ -5171,6 +5212,8 @@ test_export_specific <- function(export_function,
   # Iterate over the outcome type.
   for(outcome_type in outcome_type_available){
     
+    if (!test_data_package_installed(outcome_type)) next
+    
     # Obtain data.
     main_data <- test.create_good_data_set(outcome_type)
     
@@ -5283,6 +5326,8 @@ integrated_test <- function(...,
   
   for(outcome_type in outcome_type_available){
     
+    if (!test_data_package_installed(outcome_type)) next
+    
     .warning_good <- warning_good
     if(is.list(warning_good)) .warning_good <- warning_good[[outcome_type]]
     
diff --git a/tests/testthat/test-collection_labels.R b/tests/testthat/test-collection_labels.R
index 0158d461..da5ff7c6 100644
--- a/tests/testthat/test-collection_labels.R
+++ b/tests/testthat/test-collection_labels.R
@@ -2,6 +2,8 @@ outcome_type <- "multinomial"
 
 for(outcome_type in c("continuous", "multinomial",  "survival")){
   
+  if (!familiar:::test_data_package_installed(outcome_type)) next
+  
   # Get data.
   data <- familiar:::test.create_good_data_set(outcome_type = outcome_type)
   
diff --git a/tests/testthat/test-stratification.R b/tests/testthat/test-stratification.R
index 7dfd6858..dd2c088b 100644
--- a/tests/testthat/test-stratification.R
+++ b/tests/testthat/test-stratification.R
@@ -1,6 +1,8 @@
 # Find available stratification methods.
 stratification_methods <- familiar:::.get_available_stratification_methods()
 
+if (!familiar:::test_data_package_installed("survival")) testthat::skip()
+
 # Test for good dataset.
 for(stratification_method in stratification_methods){
   # Create a dataset using the good dataset.

From dfda1798b1e5047a6dea07c4b16d9a930b260d58 Mon Sep 17 00:00:00 2001
From: Alex Zwanenburg <alexander.zwanenburg@nct-dresden.de>
Date: Wed, 15 May 2024 11:22:24 +0200
Subject: [PATCH 2/8] Add checks to test-stratification

---
 tests/testthat/test-stratification.R | 20 +++++++++++++-------
 1 file changed, 13 insertions(+), 7 deletions(-)

diff --git a/tests/testthat/test-stratification.R b/tests/testthat/test-stratification.R
index dd2c088b..2b0b5d08 100644
--- a/tests/testthat/test-stratification.R
+++ b/tests/testthat/test-stratification.R
@@ -9,13 +9,19 @@ for(stratification_method in stratification_methods){
   data <- familiar:::test.create_good_data_set("survival")
   
   # Train a simple linear GLM using the good dataset.
-  fam_model <- familiar:::test_train(data=data,
-                                     cluster_method="none",
-                                     imputation_method="simple",
-                                     hyperparameter_list=list("sign_size"=familiar:::get_n_features(data)),
-                                     learner="cox",
-                                     stratification_method=stratification_method,
-                                     create_novelty_detector=FALSE)
+  fam_model <- familiar:::do.call_with_handlers(
+    familiar:::test_train,
+    args = list(data=data,
+                cluster_method="none",
+                imputation_method="simple",
+                hyperparameter_list=list("sign_size"=familiar:::get_n_features(data)),
+                learner="cox",
+                stratification_method=stratification_method,
+                create_novelty_detector=FALSE)
+  )
+  
+  if (!test_object_package_installed(fam_model)) testthat::skip()
+  fam_model <- fam_model$value
   
   # Risk stratification.
   predictions_risk <- familiar::predict(object=fam_model,

From 23fb5de651ab80aa3dfdab20e619fdaedf4a31c4 Mon Sep 17 00:00:00 2001
From: Alex Zwanenburg <alexander.zwanenburg@nct-dresden.de>
Date: Wed, 15 May 2024 11:23:07 +0200
Subject: [PATCH 3/8] Add checks to test-vimp_table

---
 tests/testthat/test-vimp_table.R | 27 ++++++++++++++++-----------
 1 file changed, 16 insertions(+), 11 deletions(-)

diff --git a/tests/testthat/test-vimp_table.R b/tests/testthat/test-vimp_table.R
index d7cced92..01f3096b 100644
--- a/tests/testthat/test-vimp_table.R
+++ b/tests/testthat/test-vimp_table.R
@@ -4,17 +4,22 @@ data <- familiar:::test_create_synthetic_correlated_data(outcome_type="continuou
                                                          n_numeric=2,
                                                          cluster_size=c(1, 1, 2, 3))
 
-vimp_object <- familiar:::prepare_vimp_object(data=data,
-                                              vimp_method="pearson",
-                                              outcome_type="continuous",
-                                              transformation_method="none",
-                                              normalisation_method="none",
-                                              cluster_method="hclust",
-                                              cluster_cut_method="fixed_cut",
-                                              cluster_similarity_metric="mcfadden_r2",
-                                              cluster_similarity_threshold=0.99,
-                                              imputation_method="simple")
-
+vimp_object <- familiar:::do.call_with_handlers(
+  familiar:::prepare_vimp_object,
+  args = list(data=data,
+              vimp_method="pearson",
+              outcome_type="continuous",
+              transformation_method="none",
+              normalisation_method="none",
+              cluster_method="hclust",
+              cluster_cut_method="fixed_cut",
+              cluster_similarity_metric="mcfadden_r2",
+              cluster_similarity_threshold=0.99,
+              imputation_method="simple")
+)
+if (!test_object_package_installed(vimp_object)) testthat::skip()
+vimp_object <- vimp_object$value
+  
 vimp_table_object <- suppressWarnings(familiar:::.vimp(vimp_object, data))
 
 

From a9f41969c18553c2ca7bb22fce8119bc7384e963 Mon Sep 17 00:00:00 2001
From: Alex Zwanenburg <alexander.zwanenburg@nct-dresden.de>
Date: Wed, 15 May 2024 11:23:23 +0200
Subject: [PATCH 4/8] Add checks to test-collection_labels

---
 tests/testthat/test-collection_labels.R | 23 ++++++++++++++---------
 1 file changed, 14 insertions(+), 9 deletions(-)

diff --git a/tests/testthat/test-collection_labels.R b/tests/testthat/test-collection_labels.R
index da5ff7c6..50cc6d07 100644
--- a/tests/testthat/test-collection_labels.R
+++ b/tests/testthat/test-collection_labels.R
@@ -19,15 +19,20 @@ for(outcome_type in c("continuous", "multinomial",  "survival")){
   skip_data_elements <- c("ice_data", "permutation_vimp")
   
   # Create experiment data.
-  experiment_data <- familiar::summon_familiar(
-    data=data,
-    experimental_design="fs+mb",
-    fs_method="mim",
-    imputation_method="simple",
-    learner=learner,
-    estimation_type="point",
-    skip_evaluation_elements=skip_data_elements,
-    parallel=FALSE)
+  experiment_data <- familiar:::do.call_with_handlers(
+    familiar::summon_familiar,
+    args = list(data=data,
+                experimental_design="fs+mb",
+                fs_method="mim",
+                imputation_method="simple",
+                learner=learner,
+                estimation_type="point",
+                skip_evaluation_elements=skip_data_elements,
+                parallel=FALSE)
+  )
+  
+  if (!test_object_package_installed(experiment_data)) next
+  experiment_data <- experiment_data$value
   
   # Test both familiarCollection and familiarModel objects.
   familiar_collection_list <- list(

From 9bcba508f3627599d017d84933473cc434dbeb09 Mon Sep 17 00:00:00 2001
From: Alex Zwanenburg <alexander.zwanenburg@nct-dresden.de>
Date: Wed, 15 May 2024 11:36:51 +0200
Subject: [PATCH 5/8] Check for packages being installed.

---
 R/TestFunctions.R | 154 +++++++++++++++++++++++++++++-----------------
 1 file changed, 98 insertions(+), 56 deletions(-)

diff --git a/R/TestFunctions.R b/R/TestFunctions.R
index bc1cdd32..3f962187 100644
--- a/R/TestFunctions.R
+++ b/R/TestFunctions.R
@@ -127,13 +127,18 @@ test_all_learners_train_predict_vimp <- function(
       #### Full dataset --------------------------------------------------------
       
       # Train the model.
-      model <- suppressWarnings(test_train(data=full_data,
-                                           cluster_method="none",
-                                           imputation_method="simple",
-                                           hyperparameter_list=hyperparameters,
-                                           learner=learner,
-                                           time_max=1832,
-                                           trim_model=FALSE))
+      model <- do.call_with_handlers(
+        test_train,
+        args = list(data=full_data,
+                    cluster_method="none",
+                    imputation_method="simple",
+                    hyperparameter_list=hyperparameters,
+                    learner=learner,
+                    time_max=1832,
+                    trim_model=FALSE)
+      )
+      if (!test_object_package_installed(model)) next
+      model <- model$value
       
       # Create a trimmed model -- this is the only instance were we do that
       # without setting the time-out to infinite to test whether the timeout
@@ -1266,11 +1271,15 @@ test_all_novelty_detectors <- function(detectors,
     #####Full dataset#########################################################
     
     # Train the novelty detector.
-    model <- suppressWarnings(test_train_novelty_detector(data=full_data,
-                                                          cluster_method="none",
-                                                          imputation_method="simple",
-                                                          hyperparameter_list=hyperparameter_list,
-                                                          detector=detector))
+    model <- do.call_with_handlers(
+      test_train_novelty_detector,
+      args = list(data=full_data,
+                  cluster_method="none",
+                  imputation_method="simple",
+                  hyperparameter_list=hyperparameter_list,
+                  detector=detector))
+    if (!test_object_package_installed(model)) next
+    model <- model$value
     
     # Create a trimmed detector.
     trimmed_model <- trim_model(model, timeout=Inf)
@@ -2080,12 +2089,17 @@ test_all_metrics <- function(metrics,
       #####Full dataset#########################################################
       
       # Train the model.
-      model <- suppressWarnings(test_train(data=full_data,
-                                           cluster_method="none",
-                                           imputation_method="simple",
-                                           hyperparameter_list=hyperparameters,
-                                           learner="glm",
-                                           time_max=1832))
+      model <- do.call_with_handlers(
+        test_train,
+        args = list(data=full_data,
+                    cluster_method="none",
+                    imputation_method="simple",
+                    hyperparameter_list=hyperparameters,
+                    learner="glm",
+                    time_max=1832))
+      
+      if (!test_object_package_installed(model)) next
+      model <- model$value
       
       # Create metric object
       metric_object <- as_metric(metric=metric,
@@ -3578,15 +3592,20 @@ test_plots <- function(plot_function,
     #####Full data set########################################################
     
     # Train the model.
-    model_full_1 <- suppressWarnings(test_train(cl=cl,
-                                                data=full_data,
-                                                cluster_method="none",
-                                                imputation_method="simple",
-                                                fs_method="mim",
-                                                hyperparameter_list=hyperparameters,
-                                                learner="lasso",
-                                                time_max=1832,
-                                                create_novelty_detector=create_novelty_detector))
+    model_full_1 <- do.call_with_handlers(
+      test_train,
+      args = list(cl=cl,
+                  data=full_data,
+                  cluster_method="none",
+                  imputation_method="simple",
+                  fs_method="mim",
+                  hyperparameter_list=hyperparameters,
+                  learner="lasso",
+                  time_max=1832,
+                  create_novelty_detector=create_novelty_detector))
+    
+    if (!test_object_package_installed(model_full_1)) next
+    model_full_1 <- model_full_1$value
     
     model_full_2 <- model_full_1
     model_full_2@fs_method <- "mifs"
@@ -4254,6 +4273,8 @@ test_plot_ordering <- function(
   # Iterate over the outcome type.
   for(outcome_type in outcome_type_available){
     
+    if (!test_data_package_installed(outcome_type)) next
+    
     # Obtain data.
     full_data <- test.create_good_data_set(outcome_type)
     empty_data <- test.create_empty_data_set(outcome_type)
@@ -4271,8 +4292,9 @@ test_plot_ordering <- function(
         "survival"="cox"))
     
     # Train the lasso model.
-    model_full_lasso_1 <- suppressWarnings(
-      do.call(
+    
+    
+    model_full_lasso_1 <- do.call_with_handlers(
         test_train,
         args=c(
           list(
@@ -4280,7 +4302,10 @@ test_plot_ordering <- function(
             "hyperparameter_list"=hyperparameters_lasso,
             "learner"="lasso",
             "create_novelty_detector"=create_novelty_detector),
-          experiment_args)))
+          experiment_args))
+    
+    if (!test_object_package_installed(model_full_lasso_1)) next
+    model_full_lasso_1 <- model_full_lasso_1$value
     
     model_full_lasso_2 <- model_full_lasso_1
     model_full_lasso_2@fs_method <- "mifs"
@@ -4445,6 +4470,8 @@ test_export <- function(export_function,
   # Iterate over the outcome type.
   for(outcome_type in c("count", "continuous", "binomial", "multinomial", "survival")){
     
+    if (!test_data_package_installed(outcome_type)) next
+    
     # Obtain data.
     full_data <- test.create_good_data_set(outcome_type)
     identical_sample_data <- test.create_all_identical_data_set(outcome_type)
@@ -4499,15 +4526,20 @@ test_export <- function(export_function,
     
     if(n_models == 1){
       # Train the model.
-      model_full_1 <- suppressWarnings(test_train(cl=cl,
-                                                  data=full_data,
-                                                  cluster_method="none",
-                                                  imputation_method="simple",
-                                                  fs_method="mim",
-                                                  hyperparameter_list=hyperparameters,
-                                                  learner="lasso",
-                                                  time_max=1832,
-                                                  create_novelty_detector=create_novelty_detector))
+      model_full_1 <- do.call_with_handlers(
+        test_train,
+        args = list(cl=cl,
+                    data=full_data,
+                    cluster_method="none",
+                    imputation_method="simple",
+                    fs_method="mim",
+                    hyperparameter_list=hyperparameters,
+                    learner="lasso",
+                    time_max=1832,
+                    create_novelty_detector=create_novelty_detector))
+      
+      if (!test_object_package_installed(model_full_1)) next
+      model_full_1 <- model_full_1$value
       
       model_full_2 <- model_full_1
       model_full_2@fs_method <- "mifs"
@@ -5233,14 +5265,19 @@ test_export_specific <- function(export_function,
     
     if(n_models == 1){
       # Train the model.
-      model_full_1 <- suppressWarnings(test_train(data=main_data,
-                                                  cluster_method="none",
-                                                  imputation_method="simple",
-                                                  fs_method="mim",
-                                                  hyperparameter_list=hyperparameters,
-                                                  learner="lasso",
-                                                  time_max=1832,
-                                                  create_novelty_detector=create_novelty_detector))
+      model_full_1 <- do.call_with_handlers(
+        test_train,
+        args = list(data=main_data,
+                    cluster_method="none",
+                    imputation_method="simple",
+                    fs_method="mim",
+                    hyperparameter_list=hyperparameters,
+                    learner="lasso",
+                    time_max=1832,
+                    create_novelty_detector=create_novelty_detector))
+      
+      if (!test_object_package_installed(model_full_1)) next
+      model_full_1 <- model_full_1$value
       
       model_full_2 <- model_full_1
       model_full_2@fs_method <- "mifs"
@@ -5251,15 +5288,20 @@ test_export_specific <- function(export_function,
       model_full_2 <- list()
       
       for(ii in seq_len(n_models)){
-        temp_model_1 <- suppressWarnings(test_train(data=main_data,
-                                                    cluster_method="none",
-                                                    imputation_method="simple",
-                                                    fs_method="mim",
-                                                    hyperparameter_list=hyperparameters,
-                                                    learner="lasso",
-                                                    time_max=1832,
-                                                    create_bootstrap=TRUE,
-                                                    create_novelty_detector=create_novelty_detector))
+        temp_model_1 <- do.call_with_handlers(
+          test_train,
+          args = list(data=main_data,
+                      cluster_method="none",
+                      imputation_method="simple",
+                      fs_method="mim",
+                      hyperparameter_list=hyperparameters,
+                      learner="lasso",
+                      time_max=1832,
+                      create_bootstrap=TRUE,
+                      create_novelty_detector=create_novelty_detector))
+        
+        if (!test_object_package_installed(temp_model_1)) next
+        temp_model_1 <- temp_model_1$value
         
         temp_model_2 <- temp_model_1
         temp_model_2@fs_method <- "mifs"

From 355e3f1b430b3192dc9e75cf1bb12e17baa405ca Mon Sep 17 00:00:00 2001
From: Alex Zwanenburg <alexander.zwanenburg@nct-dresden.de>
Date: Wed, 15 May 2024 11:44:13 +0200
Subject: [PATCH 6/8] Update news and description.

---
 DESCRIPTION | 2 +-
 NEWS.md     | 6 ++++++
 2 files changed, 7 insertions(+), 1 deletion(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 88d82ddd..16bf4b75 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: familiar
 Title: End-to-End Automated Machine Learning and Model Evaluation
-Version: 1.4.7
+Version: 1.4.8
 Authors@R: c(
     person("Alex", "Zwanenburg",
            email = "alexander.zwanenburg@nct-dresden.de",
diff --git a/NEWS.md b/NEWS.md
index f4fb9ac2..37a6d50d 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,9 @@
+# Version 1.4.8 (Valorous Viper)
+
+## Bug fixes
+
+- Adapted tests to work when packages are missing.
+
 # Version 1.4.7 (Uncertain Unicorn)
 
 ## Bug fixes

From f650fd983cded57626fa78c54b20a0a0d4f0eb65 Mon Sep 17 00:00:00 2001
From: Alex Zwanenburg <alexander.zwanenburg@nct-dresden.de>
Date: Wed, 15 May 2024 11:49:36 +0200
Subject: [PATCH 7/8] Update auto-test-no-suggests-pull.yml

---
 .github/workflows/auto-test-no-suggests-pull.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/auto-test-no-suggests-pull.yml b/.github/workflows/auto-test-no-suggests-pull.yml
index 2878e773..a54cac78 100644
--- a/.github/workflows/auto-test-no-suggests-pull.yml
+++ b/.github/workflows/auto-test-no-suggests-pull.yml
@@ -6,7 +6,7 @@
 # See https://github.com/r-lib/actions/tree/master/examples#readme for
 # additional example workflows available for the R community.
 
-name: Run R CMD check for no 
+name: Run R CMD check for strong dependencies only (nosuggests)
 
 on: [pull_request, workflow_dispatch]
 
@@ -39,6 +39,7 @@ jobs:
             any::knitr
             any::rmarkdown
             any::ggplot2
+            any::roxygen2
           needs: check
           
       - name: Create documentation

From 709ebc3fafc2256b6eb304642a65b92c7d260261 Mon Sep 17 00:00:00 2001
From: Alex Zwanenburg <alexander.zwanenburg@nct-dresden.de>
Date: Wed, 15 May 2024 16:11:07 +0200
Subject: [PATCH 8/8] Update cran-comments.md

---
 cran-comments.md | 17 +++++++++++++++--
 1 file changed, 15 insertions(+), 2 deletions(-)

diff --git a/cran-comments.md b/cran-comments.md
index f8749c1b..cfa3307c 100644
--- a/cran-comments.md
+++ b/cran-comments.md
@@ -1,4 +1,4 @@
-Update familiar to version 1.4.7
+Update familiar to version 1.4.8
 
 Vignettes are pre-compiled to avoid long compilation times on build (several minutes).
 
@@ -8,7 +8,7 @@ Longer tests and tests involving parallel processing are not performed on CRAN,
 
 ## R CMD check results
 
-R CMD check was run on GitHub against R-release using r-lib/actions/check-r-package:
+R CMD check was run on GitHub using https://github.com/alexzwanenburg/familiar/actions/workflows/auto-test-package_pull.yml
 
 ----------------------------------
 window-latest:
@@ -28,7 +28,20 @@ macos-latest
 ubuntu-latest:
 0 errors | 0 warnings | 0 notes
 
+## R CMD check for strong dependencies only
 
+R CMD check was run on GitHub using https://github.com/alexzwanenburg/familiar/actions/workflows/auto-test-no-suggests-pull.yml
+
+----------------------------------
+ubuntu-latest:
+0 errors | 0 warnings | 1 note
+
+* checking package dependencies ... NOTE
+Packages suggested but not available for checking:
+  'BART', 'CORElearn', 'coro', 'dynamicTreeCut', 'e1071', 'Ecdat',
+  'fastcluster', 'fastglm', 'glmnet', 'harmonicmeanp', 'isotree',
+  'laGP', 'maxstat', 'mboost', 'microbenchmark', 'partykit', 'praznik',
+  'proxy', 'qvalue', 'randomForestSRC', 'ranger', 'VGAM', 'xgboost'
 
 ## Downstream dependencies