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Plotting: scorequant.plotting

scorequant.plotting is a convenience, not part of the stable API: its figures, layout and signatures may change in any release. Code that must keep working should draw from the documented result fields instead. Matplotlib is optional and imported only when one of these functions is called; install the viz extra or synchronize all development extras.

plot_partition is a geometric view and therefore accepts only effective rank one or two. For higher rank, plot_summary uses a projection-free retained-eigenvalue spectrum, and plot_optimization summarizes center displacement norms across every informative coordinate.

plot_optimization 

plot_optimization(trace: OptimizationTrace) -> Figure

Plot objective, hard retention, occupancies, and center motion.

Parameters:

Returns:

  • Figure –

    Four-panel optimization summary.

plot_partition 

plot_partition(
    result: QuantizerResult,
    scores: ArrayLike,
    weights: ArrayLike | None = None,
) -> Figure

Plot observations in the fitted informative coordinate system.

Parameters:

  • result (QuantizerResult) –

    Fitted score-space partition.

  • scores (ArrayLike) –

    Raw score matrix compatible with result.

  • weights (ArrayLike | None, default: None ) –

    Optional weights used only to scale marker sizes.

Returns:

  • Figure –

    One- or two-dimensional partition view.

Raises:

  • ContractError –

    If the fitted informative space has rank above two. Use :func:plot_summary for a projection-free diagnostic instead.

plot_information 

plot_information(report: InformationReport) -> Figure

Plot retained information, its spectrum, and bin occupancy.

Parameters:

  • report (InformationReport) –

    Information report for one fixed partition and sample.

Returns:

  • Figure –

    Matrix, eigenvalue, and weighted-occupancy panels. The matrix uses a signed scale so negative off-diagonal values remain visible.

plot_summary 

plot_summary(
    result: QuantizerResult,
    scores: ArrayLike,
    weights: ArrayLike | None = None,
) -> Figure

Create a compact final-partition and optimization summary.

Parameters:

  • result (QuantizerResult) –

    Fitted score-space partition.

  • scores (ArrayLike) –

    Raw score matrix compatible with result.

  • weights (ArrayLike | None, default: None ) –

    Optional evaluation weights.

Returns:

  • Figure –

    Partition, retained matrix, trace, and occupancy panels.