locationd: Unit tests for different scenarios (#29908)

* add different scenarios for locationd

* add locationd scenario tests to unit tests
old-commit-hash: e9edf1300a

.github/workflows/selfdrive_tests.yaml

@@ -264,6 +264,7 @@ jobs:
       run: |
         ${{ env.RUN }} "export SKIP_LONG_TESTS=1 && \
                         $PYTEST -n auto --dist=loadscope --timeout 30 -o cpp_files=test_* && \
+                        ./selfdrive/locationd/test/test_locationd_scenarios.py && \
                         ./selfdrive/ui/tests/create_test_translations.sh && \
                         QT_QPA_PLATFORM=offscreen ./selfdrive/ui/tests/test_translations && \
                         ./selfdrive/ui/tests/test_translations.py && \

selfdrive/locationd/test/test_locationd_scenarios.py

@@ -0,0 +1,223 @@
+#!/usr/bin/env python3
+import unittest
+import numpy as np
+from collections import defaultdict
+from enum import Enum
+
+
+from openpilot.selfdrive.test.openpilotci import get_url
+from openpilot.tools.lib.logreader import LogReader
+from openpilot.selfdrive.test.process_replay.process_replay import replay_process_with_name
+
+TEST_ROUTE, TEST_SEG_NUM = "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
+
+
+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'
+
+
+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
+
+
+def run_scenarios(scenario):
+  logs = list(LogReader(get_url(TEST_ROUTE, TEST_SEG_NUM)))
+  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)
+
+
+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
+  """
+  def test_base(self):
+    """
+    Test: unchanged log
+    Expected Result:
+      - yaw_rate: unchanged
+      - roll: unchanged
+    """
+    orig_data, replayed_data = run_scenarios(Scenario.BASE)
+    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)))
+
+  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.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))
+
+  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.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)
+
+  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.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)
+
+  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.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)
+
+  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.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))
+
+  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.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)
+
+  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.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))
+
+  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.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()