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============================= test session starts ============================== |
platform linux -- Python 3.12.13, pytest-8.4.1, pluggy-1.6.0 -- /usr/local/bin/python3 |
rootdir: /app |
configfile: ../dev/null |
plugins: json-ctrf-0.3.5 |
collecting ... collected 11 items |
::test_artifacts_parse_and_cover_every_campaign_recording PASSED [ 9%] |
::test_frozen_inputs_and_public_metadata_are_untampered PASSED [ 18%] |
::test_campaign_landscapes_mobility_and_topology_are_recovered FAILED [ 27%] |
::test_recording_fields_match_truth_and_thermodynamic_constraints FAILED [ 36%] |
::test_stationary_density_zero_current_and_multilag_moments FAILED [ 45%] |
::test_relaxation_times_use_the_occupancy_supported_window FAILED [ 54%] |
::test_field_step_response_matches_forward_dynamics_and_observations FAILED [ 63%] |
::test_backward_committor_and_exit_times_are_physical FAILED [ 72%] |
::test_uncertainty_intervals_cover_truth_without_being_vacuous FAILED [ 81%] |
::test_noise_blind_single_lag_diffusion_is_rejected PASSED [ 90%] |
::test_regularization_summary_and_membership_are_consistent PASSED [100%] |
=================================== FAILURES =================================== |
_________ test_campaign_landscapes_mobility_and_topology_are_recovered _________ |
def test_campaign_landscapes_mobility_and_topology_are_recovered(): |
for campaign_id in CAMPAIGN_IDS: |
entry, x_grid, mobility, force, potential = _campaign(campaign_id) |
spec = SPEC["campaigns"][campaign_id] |
expected_grid = np.linspace( |
spec["x_range"][0], spec["x_range"][1], spec["n_grid"] |
) |
assert x_grid.shape == expected_grid.shape |
assert np.allclose(x_grid, expected_grid, rtol=1e-8, atol=1e-10) |
assert mobility.shape == force.shape == potential.shape == x_grid.shape |
assert abs(float(np.min(potential))) <= 1e-6 + 0.01 * max( |
float(np.ptp(potential)), 1e-9 |
) |
truth_u, truth_force = _potential_truth( |
x_grid, spec["potential"] |
) |
truth_mu, _ = _mobility_truth(x_grid, spec["mobility"]) |
mask = _campaign_mask(campaign_id) |
bands = CAMPAIGN_BANDS[campaign_id] |
> assert _potential_rel(potential, truth_u, mask) <= bands["potential"] |
E assert 0.197509332273848 <= 0.18 |
E + where 0.197509332273848 = _potential_rel(array([5.82527409, 4.73746816, 3.64835233, 2.55501041, 1.4968944 ,\n 0.65781416, 0.20778133, 0.07968637, 0.1848933 , 0.46155557,\n 0.84803642, 1.2831015 , 1.71747579, 2.10687305, 2.44717628,\n 2.72405473, 2.90855324, 2.97782514, 2.92427208, 2.75... |
/verifier/test_outputs.py:998: AssertionError |
_______ test_recording_fields_match_truth_and_thermodynamic_constraints ________ |
def test_recording_fields_match_truth_and_thermodynamic_constraints(): |
result, diagnostics, _, _, _ = _submission() |
for name in RECORDING_IDS: |
expected = SPEC["recordings"][name] |
campaign_id = expected["campaign_id"] |
campaign, x_grid, mobility, force, _ = _campaign(campaign_id) |
entry, drift, diffusion = _recording(name) |
assert drift.shape == diffusion.shape == x_grid.shape |
assert entry["campaign_id"] == campaign_id |
assert math.isclose(float(entry["temperature"]), expected["temperature"]) |
assert math.isclose(float(entry["tau"]), expected["tau_s"]) |
temperature = expected["temperature"] |
spec = SPEC["campaigns"][campaign_id] |
_, truth_force = _potential_truth(x_grid, spec["potential"]) |
truth_mu, truth_dmu = _mobility_truth(x_grid, spec["mobility"]) |
truth_D = temperature * truth_mu |
truth_f = truth_mu * truth_force + temperature * truth_dmu |
mask = _record_mask(name) |
bands = RECORDING_BANDS[name] |
> assert _rel_l2(drift, truth_f, mask) <= bands["drift"] |
E assert 0.42743529406936853 <= 0.4 |
E + where 0.42743529406936853 = _rel_l2(array([ 8.77485318e+00, 8.94157698e+00, 8.32295402e+00, 6.99845035e+00,\n 5.33663565e+00, 3.56135345e+00, 1.88992700e+00, 2.64566553e-01,\n -1.06644538e+00, -2.15625794e+00, -2.85641965e+00, -3.20917642e+00,\n -3.14661592e+00, -2.73176459e+00,... |
/verifier/test_outputs.py:1057: AssertionError |
__________ test_stationary_density_zero_current_and_multilag_moments ___________ |
def test_stationary_density_zero_current_and_multilag_moments(): |
for name in RECORDING_IDS: |
expected = SPEC["recordings"][name] |
campaign_id = expected["campaign_id"] |
_, x_grid, _, _, potential = _campaign(campaign_id) |
_, drift, diffusion = _recording(name) |
reported = _reported_diagnostics(name) |
clean = _equilibrium_density( |
potential, expected["temperature"], x_grid |
) |
observed_prediction = _localization_blur( |
clean, expected["meas_noise_std"], x_grid |
) |
empirical, count = _empirical_density(name) |
density_mask = count > max(80.0, 0.02 * float(np.max(count))) |
stationary = _rel_l2( |
observed_prediction, empirical, density_mask |
) |
current = _zero_current(drift, diffusion, clean, x_grid) |
bands = DIAGNOSTIC_BANDS[campaign_id] |
assert stationary <= bands["stationary"] |
assert current <= bands["current"] |
> assert math.isclose( |
float(reported["stationary_density_rel_l2"]), |
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