ykcheungab
60 lines
2.4 KiB
Python
60 lines
2.4 KiB
Python
"""Feature identities use effective measurement settings, never display metadata."""
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from copy import deepcopy
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import numpy as np
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import pytest
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from orisys.calibration_context import build_context, domain_fingerprint
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def config():
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return {"camera": {"resolution_raw": [1280, 720], "resolution_stitch": [700, 750]},
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"tracker": {"dis_mode": 4}}
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@pytest.mark.parametrize("raw,expected", [(None, 1), ("bad", 1), (0, 1), (-3, 1), ("3", 3), (3.7, 3)])
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def test_hhd_uses_actual_sensor_normalization(raw, expected):
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data = config()
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data["tracker"]["hhd_downsample"] = raw
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assert build_context(data)["hhd_downsample"] == expected
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def test_default_values_equal_explicit_effective_settings():
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implicit = build_context(config())
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data = config()
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data["tracker"]["hhd_downsample"] = 1
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explicit = build_context(data, {"flow_ema_alpha": 1.0})
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assert implicit["hhd_downsample"] == 1
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assert implicit["filters"]["measurement"] == {"flow_ema_alpha": 1.0}
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assert implicit["feature_signature_sha256"] == explicit["feature_signature_sha256"]
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def test_measurement_filters_change_identity_but_readout_and_paths_do_not():
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data = config()
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original = build_context(data)
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assert build_context(data, {"flow_ema_alpha": 0.5})["feature_signature_sha256"] != original["feature_signature_sha256"]
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data.update(name="other", video="D:/other.mp4", cal_path="E:/calibration.json")
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assert build_context(data, {"force_median_window": 7, "force_lowpass_cutoff_hz": 2}) == original
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def test_explicit_empty_filter_mapping_overrides_config_defaults():
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data = config()
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data["filters"] = {"flow_ema_alpha": 0.5}
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assert build_context(data, {})["filters"]["measurement"] == {"flow_ema_alpha": 1.0}
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def test_source_scale_numeric_types_have_identical_identity():
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assert build_context(config(), source_scale=1) == build_context(config(), source_scale=1.0)
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def test_domain_fingerprint_binds_map_content_not_only_dimensions():
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domain = {"map_x": np.zeros((2, 3)), "map_y": np.zeros((2, 3)),
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"valid_mask": np.ones((2, 3), dtype=bool), "world_xyz": np.zeros((2, 3, 3))}
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original = domain_fingerprint(domain)
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for key in domain:
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changed = deepcopy(domain)
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changed[key].flat[0] = not changed[key].flat[0] if key == "valid_mask" else 1
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assert domain_fingerprint(changed) != original
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assert domain_fingerprint({key: value.copy() for key, value in domain.items()}) == original
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