use accept_values method instead of accessing metadata directly

3 files changed, 5 insertions, 3 deletions

diff --git a/lib/ot_predictions.rb b/lib/ot_predictions.rb
index df1efc3..d0530a3 100755
--- a/lib/ot_predictions.rb
+++ b/lib/ot_predictions.rb
@@ -81,7 +81,7 @@ module Lib
           raise "test dataset is empty "+test_dataset_uri.to_s unless compounds.size>0
           
           if feature_type=="classification"
-            av = test_target_dataset.features[prediction_feature][OT.acceptValue]
+            av = test_target_dataset.accept_values(prediction_feature)
             raise "'"+OT.acceptValue.to_s+"' missing/invalid for feature '"+prediction_feature.to_s+"' in dataset '"+
               test_target_dataset_uri.to_s+"', acceptValues are: '"+av.inspect+"'" if av==nil or av.length<2
             if accept_values==nil
diff --git a/report/validation_access.rb b/report/validation_access.rb
index d421a0b..ef6a806 100755
--- a/report/validation_access.rb
+++ b/report/validation_access.rb
@@ -109,7 +109,7 @@ class Reports::ValidationDB
     test_target_dataset = validation.test_dataset_uri unless test_target_dataset
     d = Lib::DatasetCache.find( test_target_dataset, subjectid )
     raise "cannot get test target dataset for accept values, dataset: "+test_target_dataset.to_s unless d
-    accept_values = d.features[validation.prediction_feature][OT.acceptValue]
+    accept_values = d.accept_values(validation.prediction_feature)
     raise "cannot get accept values from dataset "+test_target_dataset.to_s+" for feature "+
       validation.prediction_feature+":\n"+d.features[validation.prediction_feature].to_yaml unless accept_values!=nil
     accept_values
diff --git a/validation/validation_service.rb b/validation/validation_service.rb
index e16e45d..6954a33 100755
--- a/validation/validation_service.rb
+++ b/validation/validation_service.rb
@@ -392,7 +392,9 @@ module Validation
         split_compounds = shuffled_compounds.chunk( self.num_folds.to_i )
       else
         class_compounds = {} # "inactive" => compounds[], "active" => compounds[] .. 
-        accept_values = orig_dataset.features[prediction_feature][OT.acceptValue]
+        accept_values = orig_dataset.accept_values(prediction_feature)
+        raise BadRequestError.new("cannot apply stratification (not implemented for regression), acceptValue missing for prediction-feature '"+
+          prediction_feature.to_s+"' in dataset '"+dataset_uri.to_s+"'") unless accept_values and accept_values.size>0
         accept_values.each do |value|
           class_compounds[value] = []
           shuffled_compounds.each do |c|