nicetoolbox.evaluation.metrics.metric_result¶

Classes

`FrameResult`	Per-frame result stored as NPZ files.
`MetricResult`	Complete output from a single metric run.
`PlotResult`	Matplotlib figures to save as PNG.
`SummaryResult`	Tabular results written to CSV.

class nicetoolbox.evaluation.metrics.metric_result.FrameResult(arrays: dict[str, list[nicetoolbox.evaluation.data.input_loader.LoadedArray]] = <factory>)[source]¶

Per-frame result stored as NPZ files.

Arrays at the same index across all keys belong to the same NPZ file.

arrays¶

Maps NPZ key name to a list of LoadedArrays (one per sequence/algorithm).

Type:: dict[str, list[nicetoolbox.evaluation.data.input_loader.LoadedArray]]

class nicetoolbox.evaluation.metrics.metric_result.MetricResult(metric_name: str, summary: SummaryResult | None = None, frames: FrameResult | None = None, plots: PlotResult | None = None)[source]¶

Complete output from a single metric run.

metric_name¶

Identifier used to name the output directory.

Type:: str

summary¶

Optional tabular results written to CSV.

Type:: nicetoolbox.evaluation.metrics.metric_result.SummaryResult | None

frames¶

Optional per-frame arrays written to NPZ.

Type:: nicetoolbox.evaluation.metrics.metric_result.FrameResult | None

plots¶

Optional figures written to PNG.

Type:: nicetoolbox.evaluation.metrics.metric_result.PlotResult | None

class nicetoolbox.evaluation.metrics.metric_result.PlotResult(figures: dict[str, matplotlib.figure.Figure] = <factory>)[source]¶

Matplotlib figures to save as PNG.

figures¶

Named figures; each key becomes a separate PNG file.

Type:: dict[str, matplotlib.figure.Figure]

class nicetoolbox.evaluation.metrics.metric_result.SummaryResult(summaries: dict[str, pandas.core.frame.DataFrame] = <factory>)[source]¶

Tabular results written to CSV.

summaries¶

Named DataFrames; each key becomes a separate CSV file.

Type:: dict[str, pandas.core.frame.DataFrame]