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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: /root
configfile: ../dev/null
plugins: json-ctrf-0.3.5
collecting ... collected 12 items
../root::test_nominal_schema PASSED [ 8%]
../root::test_nominal_equilibrium_and_curvature PASSED [ 16%]
../root::test_nominal_branch_internal_consistency PASSED [ 25%]
../root::test_nominal_matches_full_hessian_method FAILED [ 33%]
../root::test_nominal_lamb_dicke_and_sum_rule PASSED [ 41%]
../root::test_nominal_sympathetic_coupling PASSED [ 50%]
../root::test_nominal_json_derived_from_arrays PASSED [ 58%]
../root::test_nominal_convergence_study FAILED [ 66%]
../root::test_nominal_mass_ratio_scan FAILED [ 75%]
../root::test_nominal_mode_mediated_ising_scan PASSED [ 83%]
../root::test_nominal_anti_cheat PASSED [ 91%]
../root::test_submitted_solver_generalizes_to_heldout_configuration FAILED [100%]
=================================== FAILURES ===================================
___________________ test_nominal_matches_full_hessian_method ___________________
def test_nominal_matches_full_hessian_method() -> None:
> assert_matches_independent(load_bundle(ROOT, NOMINAL_INPUT), NOMINAL_INPUT)
test_outputs.py:1048:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
bundle = Bundle(output_dir=PosixPath('/root'), config={'model': 'mixed_species_linear_chain', 'convention': 'dc_axial_pseudopot...], [0.06279849880208363, 0.0016064239788763997, 0.02974041178453687, 0.005002514032107047, 0.19744965917143736, 0.0]]})
input_path = PosixPath('/verifier/nominal_input.json')
def assert_matches_independent(bundle: Bundle, input_path: Path) -> None:
reference = independent_reference(str(input_path))
assert reference.max_block_leakage < 1e-6, (
"method B: branches are not decoupled (spatial block leakage too large)"
)
fz = float(bundle.arrays["reference_axial_frequency_hz"])
for branch in BRANCHES:
agent_ratios = np.sort(bundle.arrays[f"frequencies_{branch}"] / fz)
> np.testing.assert_allclose(
agent_ratios, reference.frequency_ratios[branch],
rtol=FREQ_RTOL, atol=FREQ_ATOL,
err_msg=f"{branch} frequencies disagree with the full 3N Hessian (method B)",
)
E AssertionError:
E Not equal to tolerance rtol=1e-05, atol=1e-06
E radial_x frequencies disagree with the full 3N Hessian (method B)
E Mismatched elements: 3 / 6 (50%)
E Max absolute difference among violations: 0.0185081
E Max relative difference among violations: 0.00551998
E ACTUAL: array([3.334419, 3.421615, 3.575299, 7.828665, 7.913367, 8.049321])
E DESIRED: array([3.352927, 3.439655, 3.592586, 7.828676, 7.913381, 8.049324])
test_outputs.py:473: AssertionError
________________________ test_nominal_convergence_study ________________________
def test_nominal_convergence_study() -> None:
> assert_convergence(load_bundle(ROOT, NOMINAL_INPUT), NOMINAL_INPUT)
test_outputs.py:1064:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
bundle = Bundle(output_dir=PosixPath('/root'), config={'model': 'mixed_species_linear_chain', 'convention': 'dc_axial_pseudopot...], [0.06279849880208363, 0.0016064239788763997, 0.02974041178453687, 0.005002514032107047, 0.19744965917143736, 0.0]]})
input_path = PosixPath('/verifier/nominal_input.json')
def assert_convergence(bundle: Bundle, input_path: Path) -> None:
conv = bundle.convergence
assert conv["schema_version"] == "chain-convergence-v1"
assert float(conv["equilibrium_max_residual"]) < 1e-8
levels = conv["levels"]
expected_num_levels = int(bundle.config["hessian_convergence"]["num_levels"])
assert isinstance(levels, list) and len(levels) == expected_num_levels
for level in levels:
assert set(level) == {
"relative_step",
"grid_spacing_m",
"max_frequency_error_over_wz",
}
errors = [float(level["max_frequency_error_over_wz"]) for level in levels]
steps = [float(level["relative_step"]) for level in levels]
grid_spacings = [float(level["grid_spacing_m"]) for level in levels]
assert all(steps[i] > steps[i + 1] > 0.0 for i in range(len(steps) - 1))
assert all(
grid_spacings[i] > grid_spacings[i + 1] > 0.0
for i in range(len(grid_spacings) - 1)
)
factor = float(bundle.config["hessian_convergence"]["refinement_factor"])
expected_steps = [
float(bundle.config["hessian_convergence"]["initial_relative_step"]) / factor**level
for level in range(len(levels))
]
np.testing.assert_allclose(
steps, expected_steps, rtol=1e-12, atol=0.0,
err_msg="relative_step levels do not follow the configured refinement sequence",
)
np.testing.assert_allclose(
np.asarray(grid_spacings[:-1]) / np.asarray(grid_spacings[1:]),
np.full(len(grid_spacings) - 1, factor),
rtol=1e-10,
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