Migrated to rule_engine for mode inference and added tests.

- Created TestMatchStops.py with full test coverage for transit stop matching functionality
- Updated match_stops.py to incorporate caching of overpass api results
- Implemented TestRuleEngine.py with test cases for mode inference rules. Originally there was no test coverage. This PR seeks to rectify that. See: e-mission#1026 (comment).
- Added additional cases based on 'bad' labels, see e-mission/e-mission-docs#1124 (comment)
- Regenerated ground truths now that we are using rule engine.

For Transit Matching Logic Tests:
- Test Overpass already tests the get_stops_near and predicted_transit_modes. TestMatchStops focuses on the caching mechanism to validate it works.

For RuleEngine Tests:
- Seeks to test several mode predictions such as walking, cycling, driving, etc based on different factors.
- Cases include empty sections, AirOrHSR, Motorized, Unknown, Combination
- Added test based on prefixed like 'XMAS:Train'

added shankari xmas real data to test behavior on prefix modes like XMAS:Train

rev

Author: TeachMeTW

emission/analysis/classification/inference/mode/rule_engine.py

@@ -68,10 +68,14 @@ def predictModesStep(self):
                 (section_entry.get_id(),
                  section_entry.data.start_fmt_time, section_entry.data.end_fmt_time) +
                 '~' * 10)
-            if section_entry.data.sensed_mode == ecwma.MotionTypes.AIR_OR_HSR:
-                predictedProb.append({'AIR_OR_HSR': 1})
-            else:
-                predictedProb.append(get_prediction(i, section_entry))
+            try:
+                if section_entry.data.sensed_mode == ecwma.MotionTypes.AIR_OR_HSR:
+                    predictedProb.append({'AIR_OR_HSR': 1})
+                else:
+                    predictedProb.append(get_prediction(i, section_entry))
+            except Exception as e:
+                logging.error(f"Found {e} while inferring sensed modes, skipping {section_entry.get_id()} and {section_entry.user_id}, starting at {section_entry.data.start_fmt_time}")
+                logging.exception(e)
 
         return predictedProb
 

emission/net/ext_service/transit_matching/cache/0673d87dac7aab331d9b47526386fe1e.json

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emission/net/ext_service/transit_matching/cache/0741f5ff4fdc8ba350cf805965f9399a.json

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emission/net/ext_service/transit_matching/cache/07a26e7054021d1cc485701f213a1e04.json

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