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Merge pull request e-mission#917 from JGreenlee/composite-trip-sections
✨ Include 'sections' in composite trips
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@@ -89,6 +89,14 @@ Note that loading the data retains the object IDs. This means that if you load t | |
| $ ./e-mission-py.bash bin/debug/load_timeline_for_day_and_user.py -n /tmp/data-collection-eval/results_dec_2015/ucb.sdb.android.1/timeseries/active_day_2.2015-11-27 [email protected] | ||
| ``` | ||
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| Note that this will typically only generate cleaned sections which only distinguish between 4 modes - `walk`, `bike`, `motorized` and `air_or_hsr`. This should be sufficient in general, since the most of the server code falls back to cleaned sections if inferred sections are not present. | ||
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| However, if you do want to work with inferred sections, perhaps to test the UI with a more complex set of outputs, you will need to copy a saved random forest model. If you do not care about model accuracy, you can use the included model from test data. **DO NOT USE THIS MODEL IN PRODUCTION** | ||
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| ``` | ||
| $ cp emission/tests/data/seed_model_from_test_data.json seed_model.json | ||
| ``` | ||
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| #### Other data sources #### | ||
| 1. Get your own data. You can export your timeline for a particular day via email (Profile -> Download json dump) and then load and view it as above. | ||
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124 changes: 124 additions & 0 deletions
124
emission/tests/analysisTests/userInputTests/TestConfirmedObjectFakeData.py
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| import unittest | ||
| import logging | ||
| import json | ||
| import bson.json_util as bju | ||
| import argparse | ||
| import numpy as np | ||
| import uuid | ||
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| import emission.core.wrapper.entry as ecwe | ||
| import emission.analysis.userinput.matcher as eaum | ||
| import emission.storage.decorations.trip_queries as esdt | ||
| import emission.storage.timeseries.abstract_timeseries as esta | ||
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| import emission.core.wrapper.motionactivity as ecwma | ||
| import emission.core.wrapper.modeprediction as ecwmp | ||
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| import emission.analysis.userinput.matcher as eaum | ||
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| # Test imports | ||
| import emission.tests.common as etc | ||
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| class TestConfirmedObjectFakeData(unittest.TestCase): | ||
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| def setUp(self): | ||
| self.testUUID = uuid.uuid4() | ||
| self.test_ts = esta.TimeSeries.get_time_series(self.testUUID) | ||
| self.BLANK_RESULT={"distance": {}, "duration": {}, "count": {}} | ||
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| def tearDown(self): | ||
| logging.debug("Clearing related databases for %s" % self.testUUID) | ||
| self.clearRelatedDb() | ||
| logging.info("tearDown complete") | ||
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| def clearRelatedDb(self): | ||
| import emission.core.get_database as edb | ||
| logging.info("Timeseries delete result %s" % edb.get_timeseries_db().delete_many({"user_id": self.testUUID}).raw_result) | ||
| logging.info("Analysis delete result %s" % edb.get_analysis_timeseries_db().delete_many({"user_id": self.testUUID}).raw_result) | ||
| logging.info("Usercache delete result %s" % edb.get_usercache_db().delete_many({"user_id": self.testUUID}).raw_result) | ||
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| def testGetSectionSummaryCleaned(self): | ||
| fake_ct = ecwe.Entry({"metadata": {"key": "analysis/cleaned_trip"}, "data": {}}) | ||
| fake_ct_id = self.test_ts.insert(fake_ct) | ||
| fake_cs_list = [ | ||
| ecwe.Entry({"metadata": {"key": "analysis/cleaned_section", "write_ts": 1}, | ||
| "data": {"distance": 500, "duration": 50, "sensed_mode": ecwma.MotionTypes['BICYCLING'].value, | ||
| "trip_id": fake_ct["_id"]}}), | ||
| ecwe.Entry({"metadata": {"key": "analysis/cleaned_section", "write_ts": 2}, | ||
| "data": {"distance": 200, "duration": 20, "sensed_mode": ecwma.MotionTypes['BICYCLING'].value, | ||
| "trip_id": fake_ct["_id"]}}), | ||
| ecwe.Entry({"metadata": {"key": "analysis/cleaned_section", "write_ts": 3}, | ||
| "data": {"distance": 200, "duration": 20, "sensed_mode": ecwma.MotionTypes['UNKNOWN'].value, | ||
| "trip_id": fake_ct["_id"]}}), | ||
| ecwe.Entry({"metadata": {"key": "analysis/cleaned_section", "write_ts": 4}, | ||
| "data": {"distance": 400, "duration": 40, "sensed_mode": ecwma.MotionTypes['IN_VEHICLE'].value, | ||
| "trip_id": fake_ct["_id"]}}), | ||
| ecwe.Entry({"metadata": {"key": "analysis/cleaned_section", "write_ts": 5}, | ||
| "data": {"distance": 300, "duration": 30, "sensed_mode": ecwma.MotionTypes['WALKING'].value, | ||
| "trip_id": fake_ct["_id"]}})] | ||
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| fake_cs_ids = [self.test_ts.insert(fake_cs) for fake_cs in fake_cs_list] | ||
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| cleaned_section_summary = eaum.get_section_summary(self.test_ts, fake_ct, "analysis/cleaned_section") | ||
| logging.debug(cleaned_section_summary) | ||
| self.assertEqual(cleaned_section_summary['distance'], | ||
| {'BICYCLING': 700, 'UNKNOWN': 200, 'IN_VEHICLE': 400, 'WALKING': 300}) | ||
| self.assertEqual(cleaned_section_summary['duration'], | ||
| {'BICYCLING': 70, 'UNKNOWN': 20, 'IN_VEHICLE': 40, 'WALKING': 30}) | ||
| self.assertEqual(cleaned_section_summary['count'], | ||
| {'BICYCLING': 2, 'UNKNOWN': 1, 'IN_VEHICLE': 1, 'WALKING': 1}) | ||
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| def testGetSectionSummaryInferred(self): | ||
| fake_ct = ecwe.Entry({"metadata": {"key": "analysis/cleaned_trip"}, "data": {}}) | ||
| fake_ct_id = self.test_ts.insert(fake_ct) | ||
| fake_cs_list = [ | ||
| ecwe.Entry({"metadata": {"key": "analysis/inferred_section", "write_ts": 1}, | ||
| "data": {"distance": 500, "duration": 50, "sensed_mode": ecwmp.PredictedModeTypes['BUS'].value, | ||
| "trip_id": fake_ct["_id"]}}), | ||
| ecwe.Entry({"metadata": {"key": "analysis/inferred_section", "write_ts": 2}, | ||
| "data": {"distance": 200, "duration": 20, "sensed_mode": ecwmp.PredictedModeTypes['BUS'].value, | ||
| "trip_id": fake_ct["_id"]}}), | ||
| ecwe.Entry({"metadata": {"key": "analysis/inferred_section", "write_ts": 2}, | ||
| "data": {"distance": 200, "duration": 20, "sensed_mode": ecwmp.PredictedModeTypes['TRAIN'].value, | ||
| "trip_id": fake_ct["_id"]}}), | ||
| ecwe.Entry({"metadata": {"key": "analysis/inferred_section", "write_ts": 3}, | ||
| "data": {"distance": 300, "duration": 30, "sensed_mode": ecwmp.PredictedModeTypes['CAR'].value, | ||
| "trip_id": fake_ct["_id"]}})] | ||
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| fake_cs_ids = [self.test_ts.insert(fake_cs) for fake_cs in fake_cs_list] | ||
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| inferred_section_summary = eaum.get_section_summary(self.test_ts, fake_ct, "analysis/inferred_section") | ||
| logging.debug(inferred_section_summary) | ||
| self.assertEqual(inferred_section_summary['distance'], | ||
| {'BUS': 700, 'TRAIN': 200, 'CAR': 300}) | ||
| self.assertEqual(inferred_section_summary['duration'], | ||
| {'BUS': 70, 'TRAIN': 20, 'CAR': 30}) | ||
| self.assertEqual(inferred_section_summary['count'], | ||
| {'BUS': 2, 'TRAIN': 1, 'CAR': 1}) | ||
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| def testNoSections(self): | ||
| fake_ct = ecwe.Entry({"metadata": {"key": "analysis/cleaned_trip"}, "data": {}}) | ||
| fake_ct_id = self.test_ts.insert(fake_ct) | ||
| self.assertEqual(eaum.get_section_summary(self.test_ts, fake_ct, "analysis/inferred_section"), | ||
| self.BLANK_RESULT) | ||
| self.assertEqual(eaum.get_section_summary(self.test_ts, fake_ct, "analysis/cleaned_section"), | ||
| self.BLANK_RESULT) | ||
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| def testInvalidInput(self): | ||
| with self.assertRaises(TypeError) as te: | ||
| eaum.get_section_summary(self.test_ts, None, "foobar") | ||
| self.assertEqual(str(te.exception), "'NoneType' object is not subscriptable") | ||
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| with self.assertRaises(KeyError) as ke: | ||
| fake_ct = ecwe.Entry({"metadata": {"key": "analysis/cleaned_trip"}, "data": {}}) | ||
| eaum.get_section_summary(self.test_ts, fake_ct, "foobar") | ||
| self.assertEqual(str(ke.exception), "'user_id'") | ||
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| fake_ct = ecwe.Entry({"metadata": {"key": "analysis/cleaned_trip"}, "data": {}}) | ||
| fake_ct_id = self.test_ts.insert(fake_ct) | ||
| self.assertEqual(eaum.get_section_summary(self.test_ts, fake_ct, "foobar"), self.BLANK_RESULT) | ||
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| if __name__ == '__main__': | ||
| etc.configLogging() | ||
| unittest.main() |
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