ncaa_eval.evaluation.plotting module

Plotly visualization adapters for evaluation results.

Provides standalone functions that accept evaluation result objects and return interactive plotly.graph_objects.Figure instances for Jupyter notebook rendering.

ncaa_eval.evaluation.plotting.plot_advancement_heatmap(result: SimulationResult, team_labels: Mapping[int, str] | None = None) → Figure[source]

Heatmap of per-team advancement probabilities by round.

Parameters:

  • result – Simulation result with advancement_probs array.

  • team_labels – Optional mapping of team index (0..n-1, bracket position order) to display name. When None, team indices are shown as-is. Note: keys are bracket indices, not canonical team IDs — use BracketStructure.team_index_map to translate from team IDs to indices before passing this argument.

Returns:

Interactive Plotly Figure showing a heatmap with teams on y-axis and rounds on x-axis.

ncaa_eval.evaluation.plotting.plot_backtest_summary(result: BacktestResult, *, metrics: Sequence[str] | None = None) → Figure[source]

Per-year metric values from a backtest result.

Parameters:

  • result – Backtest result containing the summary DataFrame.

  • metrics – Metric column names to include. Defaults to all metric columns (excludes elapsed_seconds).

Returns:

Interactive Plotly Figure with one line per metric, x=year.

ncaa_eval.evaluation.plotting.plot_metric_comparison(results: Mapping[str, BacktestResult], metric: str) → Figure[source]

Multi-model overlay: one line per model for a given metric across years.

Parameters:

  • results – Mapping of model name to BacktestResult.

  • metric – Metric column name to compare.

Returns:

Interactive Plotly Figure with one line per model.

ncaa_eval.evaluation.plotting.plot_reliability_diagram(y_true: ndarray[tuple[Any, ...], dtype[float64]], y_prob: ndarray[tuple[Any, ...], dtype[float64]], *, n_bins: int = 10, title: str | None = None) → Figure[source]

Reliability diagram: predicted vs. actual probability with bin counts.

Parameters:

  • y_true – Binary labels (0 or 1).

  • y_prob – Predicted probabilities for the positive class.

  • n_bins – Number of calibration bins (default 10).

  • title – Optional figure title.

Returns:

Interactive Plotly Figure with calibration curve, diagonal reference, and bar overlay of per-bin sample counts.

ncaa_eval.evaluation.plotting.plot_score_distribution(dist: BracketDistribution, *, title: str | None = None) → Figure[source]

Histogram of bracket score distribution with percentile markers.

Parameters:

  • dist – Bracket distribution with pre-computed histogram data and percentile values.

  • title – Optional figure title.

Returns:

Interactive Plotly Figure with histogram bars and vertical percentile lines at 5th, 25th, 50th, 75th, and 95th.