Frank Sauerburger
--- a/nnfwtbn/model.py
+++ b/nnfwtbn/model.py
+        # if we select the slices for training we are done
+        if not for_predicting: return all_slices_for_folds[fold_i]
+        
+        # all_slices_for_folds looks e.g. like:
+        # [[0, 1, 2], [0, 1, 4], [0, 3, 4], [2, 3, 4], [1, 2, 3]]
+        # need to select array with uniq entries:
+        # [0, 1, 2, 4, 3]
+        uniq_el = lambda ar: set(x for l in ar for x in l)
+        exclusive_slices = []
+        for i, slices in enumerate(all_slices_for_folds):
+            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]
+        
+    def select_training(self, df, fold_i, for_predicting = False):