Update documentation

nnfwtbn/model.py

@@ -361,7 +361,7 @@ class MixedCV(CrossValidator):
 
     def select_training_slices(self, fold_i, for_predicting = False):
         """
-        Returns array of arrays with integers corresponding 
+        Returns array with integers corresponding 
         to the data slices used in training fold_i.
         If 'for_predicting' is set to True only one slice 
         is returned for each fold so that the folds are equally represented
@@ -390,7 +390,7 @@ class MixedCV(CrossValidator):
             for sl in slices:
                 if sl not in exclusive_slices and sl in uniq_el(all_slices_for_folds[i:]):
                     exclusive_slices.append(sl)
-        return exclusive_slices[fold_i]
+        return [exclusive_slices[fold_i]]
         
     def select_training(self, df, fold_i, for_predicting = False):
         """
@@ -399,7 +399,7 @@ class MixedCV(CrossValidator):
         """
         selected = np.zeros(len(df), dtype='bool')
         slices = self.select_training_slices(fold_i, for_predicting = for_predicting)
-        for slice_i in np.array(slices).flatten():
+        for slice_i in slices:
             selected = selected | self.select_slice(df, slice_i)
 
         return selected