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@ -4,7 +4,7 @@ import time |
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import pytest |
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from cereal import messaging |
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from openpilot.selfdrive.locationd.lagd import LateralLagEstimator, retrieve_initial_lag, masked_normalized_cross_correlation |
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from openpilot.selfdrive.locationd.lagd import LateralLagEstimator, retrieve_initial_lag, masked_normalized_cross_correlation, BLOCK_NUM_NEEDED, BLOCK_SIZE, MIN_OKAY_WINDOW_SEC |
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from openpilot.selfdrive.test.process_replay.migration import migrate, migrate_carParams |
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from openpilot.selfdrive.locationd.test.test_locationd_scenarios import TEST_ROUTE |
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from openpilot.common.params import Params |
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@ -15,16 +15,15 @@ MAX_ERR_FRAMES = 1 |
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DT = 0.05 |
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def run_estimator_on_fake_data(estimator, dt, lag_frames, n_frames, mocker): |
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def process_messages(mocker, estimator, lag_frames, n_frames, vego=20.0): |
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class ZeroMock(mocker.Mock): |
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def __getattr__(self, *args): |
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return 0 |
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for i in range(n_frames): |
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t = i * dt |
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vego = 20.0 |
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t = i * estimator.dt |
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desired_cuvature = np.cos(t) / (vego ** 2) |
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actual_yr = np.cos(t - lag_frames * dt) / vego |
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actual_yr = np.cos(t - lag_frames * estimator.dt) / vego |
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msgs = [ |
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(t, "carControl", mocker.Mock(latActive=True)), |
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(t, "carState", mocker.Mock(vEgo=vego, steeringPressed=False)), |
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@ -77,30 +76,33 @@ class TestLagd: |
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corr = masked_normalized_cross_correlation(desired_sig, actual_sig, mask, 200)[len(desired_sig) - 1:len(desired_sig) + 20] |
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assert np.argmax(corr) in range(lag_frames - MAX_ERR_FRAMES, lag_frames + MAX_ERR_FRAMES + 1) |
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# mask out 40% of the values, and make them noise |
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mask = np.random.choice([True, False], size=len(desired_sig), p=[0.6, 0.4]) |
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desired_sig[~mask] = np.random.normal(0, 1, size=np.sum(~mask)) |
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actual_sig[~mask] = np.random.normal(0, 1, size=np.sum(~mask)) |
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corr = masked_normalized_cross_correlation(desired_sig, actual_sig, mask, 200)[len(desired_sig) - 1:len(desired_sig) + 20] |
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assert np.argmax(corr) in range(lag_frames - MAX_ERR_FRAMES, lag_frames + MAX_ERR_FRAMES + 1) |
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def test_empty_estimator(self, mocker): |
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mocked_CP = mocker.Mock(steerActuatorDelay=0.8) |
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estimator = LateralLagEstimator(mocked_CP, DT) |
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msg = estimator.get_msg(True) |
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assert msg.liveDelay.status == 'unestimated' |
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assert np.allclose(msg.liveDelay.lateralDelay, 1.0) |
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def test_estimator(self, mocker): |
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iters = 100 |
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lag_frames = random.randint(1, 19) |
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assert np.allclose(msg.liveDelay.lateralDelay, estimator.initial_lag) |
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assert np.allclose(msg.liveDelay.lateralDelayEstimate, estimator.initial_lag) |
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assert msg.liveDelay.validBlocks == 0 |
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mocked_CP = mocker.Mock(steerActuatorDelay=1.0) |
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estimator = LateralLagEstimator(mocked_CP, DT, |
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block_count=10, min_valid_block_count=0, |
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block_size=1, okay_window_sec=iters * DT, |
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min_recovery_buffer_sec=0, min_yr=0) |
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run_estimator_on_fake_data(estimator, DT, lag_frames, iters, mocker) |
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# expect one block filled, with lateralDelayEstimate equal to lateralDelay equal to lag_frames |
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output = estimator.get_msg(True) |
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assert output.liveDelay.status == 'estimated' |
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assert np.allclose(output.liveDelay.lateralDelay, lag_frames * DT, atol=0.01) |
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assert np.allclose(output.liveDelay.lateralDelayEstimate, output.liveDelay.lateralDelay, atol=0.01) |
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assert output.liveDelay.validBlocks == 1 |
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def test_estimator_basics(self, mocker, subtests): |
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for lag_frames in range(5): |
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with subtests.test(msg=f"lag_frames={lag_frames}"): |
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mocked_CP = mocker.Mock(steerActuatorDelay=0.8) |
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estimator = LateralLagEstimator(mocked_CP, DT, min_recovery_buffer_sec=0.0, min_yr=0.0) |
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process_messages(mocker, estimator, lag_frames, int(MIN_OKAY_WINDOW_SEC / DT) + BLOCK_NUM_NEEDED * BLOCK_SIZE) |
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msg = estimator.get_msg(True) |
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assert msg.liveDelay.status == 'estimated' |
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assert np.allclose(msg.liveDelay.lateralDelay, lag_frames * DT, atol=0.01) |
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assert np.allclose(msg.liveDelay.lateralDelayEstimate, lag_frames * DT, atol=0.01) |
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assert msg.liveDelay.validBlocks == BLOCK_NUM_NEEDED |
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@pytest.mark.skipif(PC, reason="only on device") |
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@pytest.mark.timeout(30) |
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@ -117,3 +119,5 @@ class TestLagd: |
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ds.append(d) |
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assert np.mean(ds) < DT |
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import sys |