return marginal and cumulative scores from candidate search

montilab · Sep 11, 2023 · 1d75276 · 1d75276
1 parent a142320
commit 1d75276
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Showing 4 changed files with 29 additions and 17 deletions.
diff --git a/R/candidate_search.R b/R/candidate_search.R
@@ -333,12 +333,20 @@ candidate_search <- function(
     global_best_s_indices <- which(names(rowscore) %in% global_best_s_features)
     names(global_best_s_indices) <- global_best_s_features
 
-    return(list("feature_set" = FS_best,
-                "input_score" = input_score,
-                "score" = global_best_s,
-                "best_features" = global_best_s_features,
-                "best_scores" = global_best_s_scores,
-                "best_indices" = global_best_s_indices))
+    # Get marginal scores of best features
+    marginal_best_scores <- rowscore[which(names(rowscore) %in% global_best_s_features)]
+    names(marginal_best_scores) <- global_best_s_features
+
+    return(
+      list("feature_set" = FS_best,
+           "input_score" = input_score,
+           "score" = global_best_s,
+           "best_features" = global_best_s_features,
+           "best_indices" = global_best_s_indices,
+           "marginal_best_scores" = marginal_best_scores,
+           "cumulative_best_scores" = global_best_s_scores
+      )
+    )
 
   })
 

diff --git a/R/topn_best.R b/R/topn_best.R
@@ -46,22 +46,26 @@ topn_best <- function(topn_list){
   # Corresponding FS object
   best_meta <- topn_list[[n]]$feature_set
 
-  # Correspoding input_score
+  # Corresponding input_score
   best_input_score <- topn_list[[n]]$input_score
 
-  # get scores of best features
-  best_meta_scores <- topn_list[[n]]$best_scores
-
   # get indices of best features
   best_meta_indices <- topn_list[[n]]$best_indices
+
+  # Get scores of best features
+  marginal_best_scores <- topn_list[[n]]$marginal_best_scores
 
+  # Get scores of best features
+  cumulative_best_scores <- topn_list[[n]]$cumulative_best_scores  
+
   return(
     list(
       "feature_set" = best_meta,
       "input_score" = best_input_score,
       "score" = top_score,
-      "best_scores" = best_meta_scores,
-      "best_indices" = best_meta_indices
+      "best_indices" = best_meta_indices,
+      "marginal_best_scores" = marginal_best_scores,
+      "cumulative_best_scores" = cumulative_best_scores
     )
   )
 

diff --git a/tests/testthat/test-candidate_search.R b/tests/testthat/test-candidate_search.R
@@ -30,7 +30,7 @@ test_that("candidate_search returns expected result ",{
 
   testthat::expect_length(result, 1L)
   testthat::expect_type(result, "list")
-  testthat::expect_length(result[[1]], 6L)
+  testthat::expect_length(result[[1]], 7L)
   testthat::expect_s4_class(result[[1]][[1]], "SummarizedExperiment")
 
   testthat::expect_length(result[[1]][[2]], 100L)
@@ -58,7 +58,7 @@ test_that("candidate_search returns expected result ",{
 
   testthat::expect_length(result, 1L)
   testthat::expect_type(result, "list")
-  testthat::expect_length(result[[1]], 6L)
+  testthat::expect_length(result[[1]], 7L)
   testthat::expect_s4_class(result[[1]][[1]], "SummarizedExperiment")
 
   testthat::expect_length(result[[1]][[2]], 100L)
@@ -87,7 +87,7 @@ test_that("candidate_search returns expected result ",{
 
   testthat::expect_length(result, 1L)
   testthat::expect_type(result, "list")
-  testthat::expect_length(result[[1]], 6L)
+  testthat::expect_length(result[[1]], 7L)
   testthat::expect_s4_class(result[[1]][[1]], "SummarizedExperiment")
 
   testthat::expect_length(result[[1]][[2]], 100L)

diff --git a/tests/testthat/test-topn_best.R b/tests/testthat/test-topn_best.R
@@ -3,9 +3,9 @@ test_that("topn_best returns expected results",{
   data(topn_list)
   result <- topn_best(topn_list = topn_list)
 
-  testthat::expect_length(result, 3L)
+  testthat::expect_length(result, 6L)
   testthat::expect_type(result, "list")
-  testthat::expect_named(result, c("feature_set", "input_score", "score"))
+  testthat::expect_named(result, c("feature_set", "input_score", "score", "best_indices", "marginal_best_scores", "cumulative_best_scores"))
 
   testthat::expect_s4_class(result$feature_set, "SummarizedExperiment")
   testthat::expect_identical(dim(result$feature_set), c(10L, 100L))