text stringclasses 371
values |
|---|
tmp_path: Path, |
) -> None: |
payload, _, valid_output = hidden_outputs[0] |
dummy_trajectory = tmp_path / "dummy-trajectory" |
shutil.copytree(valid_output, dummy_trajectory) |
rows = load_trajectory(dummy_trajectory) |
for row in rows[4:]: |
row["theta_mean"] = "1.0" |
row["theta_sd"] = "1.0" |
row["phi_mean"] = "10.0" |
row["phi_sd"] = "1.0" |
with (dummy_trajectory / "posterior_trajectories.csv").open("w", newline="", encoding="utf-8") as handle: |
writer = csv.DictWriter(handle, fieldnames=TRAJECTORY_COLUMNS) |
writer.writeheader() |
writer.writerows(rows) |
with pytest.raises(AssertionError): |
validate_trajectory(payload, dummy_trajectory) |
fake_design = tmp_path / "fake-design" |
shutil.copytree(valid_output, fake_design) |
design_rows = load_design(fake_design) |
for row in design_rows: |
row["detuning_mhz"] = "999" |
row["zeta"] = "999" |
row["expected_variance_reduction"] = "999" |
with (fake_design / "precision_gain.csv").open("w", newline="", encoding="utf-8") as handle: |
writer = csv.DictWriter(handle, fieldnames=DESIGN_COLUMNS) |
writer.writeheader() |
writer.writerows(design_rows) |
valid_rows = [numeric_trajectory_row(row) for row in load_trajectory(fake_design)] |
normalization_error = validate_checkpoints(payload, fake_design, valid_rows) |
with pytest.raises(AssertionError): |
validate_summary_and_design(payload, fake_design, valid_rows, normalization_error) |
fake_summary = tmp_path / "fake-summary" |
shutil.copytree(valid_output, fake_summary) |
summary = load_json(fake_summary / "summary.json") |
summary["model"]["linewidth_mhz"] = 999 |
summary["design_cases"][0]["case_id"] = "fabricated" |
summary["headline_comparison"]["adaptive_final_nsr"] = 999 |
summary["max_checkpoint_normalization_error"] = 999 |
(fake_summary / "summary.json").write_text(json.dumps(summary), encoding="utf-8") |
valid_rows = [numeric_trajectory_row(row) for row in load_trajectory(fake_summary)] |
normalization_error = validate_checkpoints(payload, fake_summary, valid_rows) |
with pytest.raises(AssertionError): |
validate_summary_and_design(payload, fake_summary, valid_rows, normalization_error) |
fake_diagnostics = tmp_path / "fake-diagnostics" |
shutil.copytree(valid_output, fake_diagnostics) |
diagnostics = load_json(fake_diagnostics / "analysis_diagnostics.json") |
diagnostics["convergence"]["max_abs_theta_mean_change"] = 999 |
diagnostics["phi_bound_sensitivity"]["expanded_bounds"] = [999, 999] |
(fake_diagnostics / "analysis_diagnostics.json").write_text(json.dumps(diagnostics), encoding="utf-8") |
valid_rows = [numeric_trajectory_row(row) for row in load_trajectory(fake_diagnostics)] |
normalization_error = validate_checkpoints(payload, fake_diagnostics, valid_rows) |
> valid_summary = validate_summary_and_design(payload, fake_diagnostics, valid_rows, normalization_error) |
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
/verifier/test_outputs.py:740: |
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ |
/verifier/test_outputs.py:278: in validate_summary_and_design |
assert_close(actual[f"shot_{shot}"][key], from_rows[strategy][f"shot_{shot}"][key], atol=1e-10, rtol=1e-10) |
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ |
actual = 0.10931989857220785, expected = 0.011950840223837814 |
def assert_close(actual: float, expected: float, *, atol: float = 3e-3, rtol: float = 3e-3, message: str = "") -> None: |
> assert math.isclose(actual, expected, abs_tol=atol, rel_tol=rtol), message or f"{actual} != {expected}" |
E AssertionError: 0.10931989857220785 != 0.011950840223837814 |
E assert False |
E + where False = <built-in function isclose>(0.10931989857220785, 0.011950840223837814, abs_tol=1e-10, rel_tol=1e-10) |
E + where <built-in function isclose> = math.isclose |
/verifier/test_outputs.py:132: AssertionError |
=============================== warnings summary =============================== |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:64 |
/usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:64: PyparsingDeprecationWarning: 'oneOf' deprecated - use 'one_of' |
prop = Group((name + Suppress("=") + comma_separated(value)) | oneOf(_CONSTANTS)) |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:85 |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:85 |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:85 |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:85 |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:85 |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:85 |
/usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:85: PyparsingDeprecationWarning: 'parseString' deprecated - use 'parse_string' |
parse = parser.parseString(pattern) |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:89 |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:89 |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:89 |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:89 |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:89 |
../usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:89 |
/usr/local/lib/python3.12/site-packages/matplotlib/_fontconfig_pattern.py:89: PyparsingDeprecationWarning: 'resetCache' deprecated - use 'reset_cache' |
parser.resetCache() |
../usr/local/lib/python3.12/site-packages/matplotlib/_mathtext.py:45 |
/usr/local/lib/python3.12/site-packages/matplotlib/_mathtext.py:45: PyparsingDeprecationWarning: 'enablePackrat' deprecated - use 'enable_packrat' |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.