Datasets:
benchflow
/
frontierphysics-pr25-evidence

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submitted_series = {
"low_energy": {
"x_field": "energy_kev",
"y_field": "transient_excess",
"selection": "used_in_fit",
},
"high_energy": {
"x_field": "energy_kev",
"y_field": "transient_excess",
"selection": "used_in_fit",
},
}
series: dict[str, dict[str, object]] = {}
if isinstance(submitted_series, dict):
items = submitted_series.items()
elif isinstance(submitted_series, list):
items = []
for declaration in submitted_series:
assert isinstance(declaration, dict), (
"figure manifest series entries must be objects")
submitted_name = declaration.get(
"name",
declaration.get("series_id"),
)
assert isinstance(submitted_name, str), (
"figure manifest series entries need a name")
items.append((submitted_name, declaration))
else:
> raise AssertionError(
"figure manifest panel series must be an object or list")
E AssertionError: figure manifest panel series must be an object or list
test_outputs.py:1102: AssertionError
_________ test_scientific_figure_matches_submitted_series_fit_and_band _________
def test_scientific_figure_matches_submitted_series_fit_and_band() -> None:
_analysis, _slope_rows, _report = load_submission()
reference = independent_reference()
> image, manifest = load_figure()
^^^^^^^^^^^^^
test_outputs.py:1938:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
test_outputs.py:1257: in load_figure
manifest = normalize_figure_manifest(raw_manifest)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
test_outputs.py:1237: in normalize_figure_manifest
normalize_panel(panel, palette)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
panel = {'axis_labels': {'x': 'Electron Energy (keV)', 'y': 'Differential Number Intensity (cm^-2 s^-1 sr^-1 keV^-1)'}, 'axis_...ock': '#277da1', 'precursor_transient': '#2a9d8f', 'primary_transient': '#7b2cbf', 'quiet_background': '#d1495b'}, ...}
palette = {}
def normalize_panel(
panel: dict[str, object],
palette: dict[str, object],
) -> dict[str, object]:
panel_palette = panel.get("palette", {})
if not isinstance(panel_palette, dict):
panel_palette = {}
effective_palette = {
**palette,
**panel_palette,
}
axis_labels = panel.get("axis_labels", {})
if not isinstance(axis_labels, dict):
axis_labels = {}
normalized = {
"title": panel.get("title"),
"x_label": panel.get(
"x_label",
panel.get("x_axis_label", axis_labels.get("x")),
),
"y_label": panel.get(
"y_label",
panel.get("y_axis_label", axis_labels.get("y")),
),
"event_id": panel.get("event_id"),
}
scales = panel.get(
"axis_scales",
panel.get("scales", {}),
)
if not isinstance(scales, dict):
scales = {}
normalized["x_scale"] = panel.get("x_scale", scales.get("x"))
normalized["y_scale"] = panel.get("y_scale", scales.get("y"))
limits = panel.get(
"axis_limits",
panel.get("limits", {}),
)
if not isinstance(limits, dict):
limits = {}
normalized["x_limits"] = panel.get("x_limits", limits.get("x"))
normalized["y_limits"] = panel.get("y_limits", limits.get("y"))
bounds = panel.get(
"pixel_bounds_top_left",
panel.get(