Updated TestRunGreedyModel + Debug Cleanup

Receive a prediction list of (prediction, n) for each trip in trip_list.

Then for each of the predictions in the prediction list, run the assertion tests.

Also, cleaned up some debug print statements from earlier commits / PRs.

emission/storage/timeseries/builtin_timeseries.py

@@ -461,8 +461,6 @@ def find_entries_count(self, key_list = None, time_query = None, geo_query = Non
 
         For key_list = None or empty, total count of all documents are returned considering the matching entries from entire dataset.
         """
-        print("builtin_timeseries.find_entries_count() called")
-
         orig_tsdb = self.timeseries_db
         analysis_tsdb = self.analysis_timeseries_db
 

emission/tests/modellingTests/TestRunGreedyModel.py

@@ -163,15 +163,15 @@ def test1RoundTripGreedySimilarityBinning(self):
             origin=self.origin,
             destination=self.destination
         )
-        prediction, n = eamur.predict_labels_with_n(
+
+        predictions_list = eamur.predict_labels_with_n(
             user_id = self.user_id,
             trip_list = [test],
             model_type=eamumt.ModelType.GREEDY_SIMILARITY_BINNING,
             model_storage=eamums.ModelStorage.DOCUMENT_DATABASE,
             model_config=greedy_model_config
         )
 
-        [logging.debug(p) for p in sorted(prediction, key=lambda r: r['p'], reverse=True)]
-
-        self.assertNotEqual(len(prediction), 0, "should have a prediction")
-
+        for prediction, n in predictions_list:
+            [logging.debug(p) for p in sorted(prediction, key=lambda r: r['p'], reverse=True)]
+            self.assertNotEqual(len(prediction), 0, "should have a prediction")

emission/tests/storageTests/TestSectionQueries.py

@@ -100,7 +100,6 @@ def testCleaned2InferredSectionList(self):
         # Total = 25 = 10 (UUID1) + 15 (UUID2)
         curr_predicted_entries = esds.cleaned2inferred_section_list(section_user_list)
         self.assertEqual(len(curr_predicted_entries), len(sections_entries))
-        print(curr_predicted_entries)
 
         # Testcase 2: Null user_id value is passed
         curr_predicted_entries = esds.cleaned2inferred_section_list([{'section' : section_id, 'user_id' : ''}])