#!/usr/bin/env python3
import pytest
import unittest
import numpy as np
from collections import defaultdict
from enum import Enum
from openpilot.tools.lib.logreader import LogReader
from openpilot.selfdrive.test.process_replay.migration import migrate_all
from openpilot.selfdrive.test.process_replay.process_replay import replay_process_with_name
TEST_ROUTE = "ff2bd20623fcaeaa|2023-09-05--10-14-54/4"
GPS_MESSAGES = ['gpsLocationExternal', 'gpsLocation']
SELECT_COMPARE_FIELDS = {
'yaw_rate': ['angularVelocityCalibrated', 'value', 2],
'roll': ['orientationNED', 'value', 0],
'gps_flag': ['gpsOK'],
'inputs_flag': ['inputsOK'],
'sensors_flag': ['sensorsOK'],
}
JUNK_IDX = 100
[docs]
class Scenario(Enum):
BASE = 'base'
GPS_OFF = 'gps_off'
GPS_OFF_MIDWAY = 'gps_off_midway'
GPS_ON_MIDWAY = 'gps_on_midway'
GPS_TUNNEL = 'gps_tunnel'
GYRO_OFF = 'gyro_off'
GYRO_SPIKE_MIDWAY = 'gyro_spike_midway'
ACCEL_OFF = 'accel_off'
ACCEL_SPIKE_MIDWAY = 'accel_spike_midway'
[docs]
def get_select_fields_data(logs):
def get_nested_keys(msg, keys):
val = None
for key in keys:
val = getattr(msg if val is None else val, key) if isinstance(key, str) else val[key]
return val
llk = [x.liveLocationKalman for x in logs if x.which() == 'liveLocationKalman']
data = defaultdict(list)
for msg in llk:
for key, fields in SELECT_COMPARE_FIELDS.items():
data[key].append(get_nested_keys(msg, fields))
for key in data:
data[key] = np.array(data[key][JUNK_IDX:], dtype=float)
return data
[docs]
def run_scenarios(scenario, logs):
if scenario == Scenario.BASE:
pass
elif scenario == Scenario.GPS_OFF:
logs = sorted([x for x in logs if x.which() not in GPS_MESSAGES], key=lambda x: x.logMonoTime)
elif scenario == Scenario.GPS_OFF_MIDWAY:
non_gps = [x for x in logs if x.which() not in GPS_MESSAGES]
gps = [x for x in logs if x.which() in GPS_MESSAGES]
logs = sorted(non_gps + gps[: len(gps) // 2], key=lambda x: x.logMonoTime)
elif scenario == Scenario.GPS_ON_MIDWAY:
non_gps = [x for x in logs if x.which() not in GPS_MESSAGES]
gps = [x for x in logs if x.which() in GPS_MESSAGES]
logs = sorted(non_gps + gps[len(gps) // 2:], key=lambda x: x.logMonoTime)
elif scenario == Scenario.GPS_TUNNEL:
non_gps = [x for x in logs if x.which() not in GPS_MESSAGES]
gps = [x for x in logs if x.which() in GPS_MESSAGES]
logs = sorted(non_gps + gps[:len(gps) // 4] + gps[-len(gps) // 4:], key=lambda x: x.logMonoTime)
elif scenario == Scenario.GYRO_OFF:
logs = sorted([x for x in logs if x.which() != 'gyroscope'], key=lambda x: x.logMonoTime)
elif scenario == Scenario.GYRO_SPIKE_MIDWAY:
non_gyro = [x for x in logs if x.which() not in 'gyroscope']
gyro = [x for x in logs if x.which() in 'gyroscope']
temp = gyro[len(gyro) // 2].as_builder()
temp.gyroscope.gyroUncalibrated.v[0] += 3.0
gyro[len(gyro) // 2] = temp.as_reader()
logs = sorted(non_gyro + gyro, key=lambda x: x.logMonoTime)
elif scenario == Scenario.ACCEL_OFF:
logs = sorted([x for x in logs if x.which() != 'accelerometer'], key=lambda x: x.logMonoTime)
elif scenario == Scenario.ACCEL_SPIKE_MIDWAY:
non_accel = [x for x in logs if x.which() not in 'accelerometer']
accel = [x for x in logs if x.which() in 'accelerometer']
temp = accel[len(accel) // 2].as_builder()
temp.accelerometer.acceleration.v[0] += 10.0
accel[len(accel) // 2] = temp.as_reader()
logs = sorted(non_accel + accel, key=lambda x: x.logMonoTime)
replayed_logs = replay_process_with_name(name='locationd', lr=logs)
return get_select_fields_data(logs), get_select_fields_data(replayed_logs)
[docs]
@pytest.mark.xdist_group("test_locationd_scenarios")
@pytest.mark.shared_download_cache
class TestLocationdScenarios(unittest.TestCase):
"""
Test locationd with different scenarios. In all these scenarios, we expect the following:
- 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
"""
[docs]
@classmethod
def setUpClass(cls):
cls.logs = migrate_all(LogReader(TEST_ROUTE))
[docs]
def test_base(self):
"""
Test: unchanged log
Expected Result:
- yaw_rate: unchanged
- roll: unchanged
"""
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)))
[docs]
def test_gps_off(self):
"""
Test: no GPS message for the entire segment
Expected Result:
- yaw_rate: unchanged
- roll:
- gpsOK: False
"""
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))
[docs]
def test_gps_off_midway(self):
"""
Test: no GPS message for the second half of the segment
Expected Result:
- yaw_rate: unchanged
- roll:
- gpsOK: True for the first half, False for the second half
"""
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)
[docs]
def test_gps_on_midway(self):
"""
Test: no GPS message for the first half of the segment
Expected Result:
- yaw_rate: unchanged
- roll:
- gpsOK: False for the first half, True for the second half
"""
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)
[docs]
def test_gps_tunnel(self):
"""
Test: no GPS message for the middle section of the segment
Expected Result:
- yaw_rate: unchanged
- roll:
- gpsOK: False for the middle section, True for the rest
"""
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)
self.assertTrue(np.diff(replayed_data['gps_flag'])[805] == 1.0)
[docs]
def test_gyro_off(self):
"""
Test: no gyroscope message for the entire segment
Expected Result:
- yaw_rate: 0
- roll: 0
- sensorsOK: False
"""
_, 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))
[docs]
def test_gyro_spikes(self):
"""
Test: a gyroscope spike in the middle of the segment
Expected Result:
- yaw_rate: unchanged
- roll: unchanged
- inputsOK: False for some time after the spike, True for the rest
"""
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)
self.assertTrue(np.diff(replayed_data['inputs_flag'])[694] == 1.0)
[docs]
def test_accel_off(self):
"""
Test: no accelerometer message for the entire segment
Expected Result:
- yaw_rate: 0
- roll: 0
- sensorsOK: False
"""
_, 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))
[docs]
def test_accel_spikes(self):
"""
ToDo:
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, 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)))
if __name__ == "__main__":
unittest.main()