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test_locationd: don't redownload logs #29929

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Sep 15, 2023
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test_locationd: don't redownload logs #29929

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26 changes: 15 additions & 11 deletions selfdrive/locationd/test/test_locationd_scenarios.py
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Original file line number Diff line number Diff line change
Expand Up @@ -49,8 +49,7 @@ def get_nested_keys(msg, keys):
return data


def run_scenarios(scenario):
logs = list(LogReader(get_url(TEST_ROUTE, TEST_SEG_NUM)))
def run_scenarios(scenario, logs):
if scenario == Scenario.BASE:
pass

Expand Down Expand Up @@ -104,14 +103,19 @@ class TestLocationdScenarios(unittest.TestCase):
- locationd kalman filter should never go unstable (we care mostly about yaw_rate, roll, gpsOK, inputsOK, sensorsOK)
- faulty values should be ignored, with appropriate flags set
"""

@classmethod
def setUpClass(cls):
cls.logs = list(LogReader(get_url(TEST_ROUTE, TEST_SEG_NUM)))

def test_base(self):
"""
Test: unchanged log
Expected Result:
- yaw_rate: unchanged
- roll: unchanged
"""
orig_data, replayed_data = run_scenarios(Scenario.BASE)
orig_data, replayed_data = run_scenarios(Scenario.BASE, self.logs)
self.assertTrue(np.allclose(orig_data['yaw_rate'], replayed_data['yaw_rate'], atol=np.radians(0.2)))
self.assertTrue(np.allclose(orig_data['roll'], replayed_data['roll'], atol=np.radians(0.5)))

Expand All @@ -123,7 +127,7 @@ def test_gps_off(self):
- roll:
- gpsOK: False
"""
orig_data, replayed_data = run_scenarios(Scenario.GPS_OFF)
orig_data, replayed_data = run_scenarios(Scenario.GPS_OFF, self.logs)
self.assertTrue(np.allclose(orig_data['yaw_rate'], replayed_data['yaw_rate'], atol=np.radians(0.2)))
self.assertTrue(np.allclose(orig_data['roll'], replayed_data['roll'], atol=np.radians(0.5)))
self.assertTrue(np.all(replayed_data['gps_flag'] == 0.0))
Expand All @@ -136,7 +140,7 @@ def test_gps_off_midway(self):
- roll:
- gpsOK: True for the first half, False for the second half
"""
orig_data, replayed_data = run_scenarios(Scenario.GPS_OFF_MIDWAY)
orig_data, replayed_data = run_scenarios(Scenario.GPS_OFF_MIDWAY, self.logs)
self.assertTrue(np.allclose(orig_data['yaw_rate'], replayed_data['yaw_rate'], atol=np.radians(0.2)))
self.assertTrue(np.allclose(orig_data['roll'], replayed_data['roll'], atol=np.radians(0.5)))
self.assertTrue(np.diff(replayed_data['gps_flag'])[512] == -1.0)
Expand All @@ -149,7 +153,7 @@ def test_gps_on_midway(self):
- roll:
- gpsOK: False for the first half, True for the second half
"""
orig_data, replayed_data = run_scenarios(Scenario.GPS_ON_MIDWAY)
orig_data, replayed_data = run_scenarios(Scenario.GPS_ON_MIDWAY, self.logs)
self.assertTrue(np.allclose(orig_data['yaw_rate'], replayed_data['yaw_rate'], atol=np.radians(0.2)))
self.assertTrue(np.allclose(orig_data['roll'], replayed_data['roll'], atol=np.radians(1.5)))
self.assertTrue(np.diff(replayed_data['gps_flag'])[505] == 1.0)
Expand All @@ -162,7 +166,7 @@ def test_gps_tunnel(self):
- roll:
- gpsOK: False for the middle section, True for the rest
"""
orig_data, replayed_data = run_scenarios(Scenario.GPS_TUNNEL)
orig_data, replayed_data = run_scenarios(Scenario.GPS_TUNNEL, self.logs)
self.assertTrue(np.allclose(orig_data['yaw_rate'], replayed_data['yaw_rate'], atol=np.radians(0.2)))
self.assertTrue(np.allclose(orig_data['roll'], replayed_data['roll'], atol=np.radians(0.5)))
self.assertTrue(np.diff(replayed_data['gps_flag'])[213] == -1.0)
Expand All @@ -176,7 +180,7 @@ def test_gyro_off(self):
- roll: 0
- sensorsOK: False
"""
_, replayed_data = run_scenarios(Scenario.GYRO_OFF)
_, replayed_data = run_scenarios(Scenario.GYRO_OFF, self.logs)
self.assertTrue(np.allclose(replayed_data['yaw_rate'], 0.0))
self.assertTrue(np.allclose(replayed_data['roll'], 0.0))
self.assertTrue(np.all(replayed_data['sensors_flag'] == 0.0))
Expand All @@ -189,7 +193,7 @@ def test_gyro_spikes(self):
- roll: unchanged
- inputsOK: False for some time after the spike, True for the rest
"""
orig_data, replayed_data = run_scenarios(Scenario.GYRO_SPIKE_MIDWAY)
orig_data, replayed_data = run_scenarios(Scenario.GYRO_SPIKE_MIDWAY, self.logs)
self.assertTrue(np.allclose(orig_data['yaw_rate'], replayed_data['yaw_rate'], atol=np.radians(0.2)))
self.assertTrue(np.allclose(orig_data['roll'], replayed_data['roll'], atol=np.radians(0.5)))
self.assertTrue(np.diff(replayed_data['inputs_flag'])[500] == -1.0)
Expand All @@ -203,7 +207,7 @@ def test_accel_off(self):
- roll: 0
- sensorsOK: False
"""
_, replayed_data = run_scenarios(Scenario.ACCEL_OFF)
_, replayed_data = run_scenarios(Scenario.ACCEL_OFF, self.logs)
self.assertTrue(np.allclose(replayed_data['yaw_rate'], 0.0))
self.assertTrue(np.allclose(replayed_data['roll'], 0.0))
self.assertTrue(np.all(replayed_data['sensors_flag'] == 0.0))
Expand All @@ -214,7 +218,7 @@ def test_accel_spikes(self):
Test: an accelerometer spike in the middle of the segment
Expected Result: Right now, the kalman filter is not robust to small spikes like it is to gyroscope spikes.
"""
orig_data, replayed_data = run_scenarios(Scenario.ACCEL_SPIKE_MIDWAY)
orig_data, replayed_data = run_scenarios(Scenario.ACCEL_SPIKE_MIDWAY, self.logs)
self.assertTrue(np.allclose(orig_data['yaw_rate'], replayed_data['yaw_rate'], atol=np.radians(0.2)))
self.assertTrue(np.allclose(orig_data['roll'], replayed_data['roll'], atol=np.radians(0.5)))

Expand Down