def test_compute_mse_error(tmp_path: Path) -> None:
data = ChunkedStateDataset(path="./l5kit/tests/data/single_scene.zarr")
data.open()
export_zarr_to_ground_truth_csv(data, str(tmp_path / "gt1.csv"), 0, 12,
0.5)
export_zarr_to_ground_truth_csv(data, str(tmp_path / "gt2.csv"), 0, 12,
0.5)
err = compute_mse_error_csv(str(tmp_path / "gt1.csv"),
str(tmp_path / "gt2.csv"))
assert err == 0.0
data_fake = ChunkedStateDataset("")
data_fake.scenes = np.asarray(data.scenes).copy()
data_fake.frames = np.asarray(data.frames).copy()
data_fake.agents = np.asarray(data.agents).copy()
data_fake.root = data.root
data_fake.agents["centroid"] += np.random.rand(
*data_fake.agents["centroid"].shape)
export_zarr_to_ground_truth_csv(data_fake, str(tmp_path / "gt3.csv"), 0,
12, 0.5)
err = compute_mse_error_csv(str(tmp_path / "gt1.csv"),
str(tmp_path / "gt3.csv"))
assert err > 0.0
# test invalid conf by removing lines in gt1
with open(str(tmp_path / "gt4.csv"), "w") as fp:
lines = open(str(tmp_path / "gt1.csv")).readlines()
fp.writelines(lines[:-10])
with pytest.raises(ValueError):
compute_mse_error_csv(str(tmp_path / "gt1.csv"),
str(tmp_path / "gt4.csv"))
def dataset() -> ChunkedStateDataset:
dataset = ChunkedStateDataset("")
dataset.scenes = np.zeros(1, dtype=dataset.scenes.dtype)
dataset.frames = np.zeros(SCENE_LENGTH, dtype=dataset.frames.dtype)
dataset.agents = np.zeros(SCENE_LENGTH, dtype=dataset.agents.dtype)
dataset.scenes[0]["frame_index_interval"] = (0, SCENE_LENGTH)
for idx in range(len(dataset.frames)):
dataset.frames[idx]["agent_index_interval"] = (idx, idx + 1)
dataset.frames[idx]["timestamp"] = idx
for idx in range(len(dataset.agents)):
# we don't check moving anymore, so the agent can stay still
dataset.agents[idx]["extent"] = (5, 5, 5)
dataset.agents[idx]["yaw"] = 0
dataset.agents[idx]["track_id"] = 1
dataset.agents[idx]["label_probabilities"][3] = 1.0
return dataset