axtreme.plotting.doe

Helper function for plotting DoE behaviour.

Functions

plot_qoi_estimates(results[, ax, q, ...])

Plots how the QoI estimates changes over DoE process.

plot_qoi_estimates_from_experiment(experiment)

Plot how the QoI estimates changes over the DoE process from a given experiment with the QoI metric attached.
axtreme.plotting.doe.plot_qoi_estimates(results: ndarray[tuple[int, int], dtype[float64]], ax: None | Axes = None, q: tuple[float, ...] = (0.1, 0.5, 0.9), points_between_ests: int = 1, name: str | None = None, **kwargs: Any) → Axes

Plots how the QoI estimates changes over DoE process.

Parameters:

  • results –

    shape (n_doe_rounds, n_qoi_estimates).

    • n_doe_rounds: The number of DoE rounds in which a QoI estimate was produced.

    • n_qoi_estimates: the number of estimates produced by a single run of the QoI estimator.

  • ax – ax to add the plots to. If not provided, one will be created.

  • q – the quantiles that should be used/reported.

  • points_between_ests – This should be used if multplie DoE iterations are used between qoi estimates (e.g if the estimate is expensive). It adjusts the scale of the x axis.

  • name – optional name that should be added to the legend information for this plot

  • kwargs – kwargs that should be passed to matplotlib. Must be applicable to ax.plot and ax.fill_between

Returns:

the ax with the plot.

Return type:

Axes

axtreme.plotting.doe.plot_qoi_estimates_from_experiment(experiment: Experiment, ax: None | Axes = None, points_between_ests: int = 1, name: str | None = None, trial_index: int | None = None, **kwargs: Any) → Axes

Plot how the QoI estimates changes over the DoE process from a given experiment with the QoI metric attached.

Parameters:

  • experiment – the experiment to plot the results from, QOI metric must be present.

  • ax – ax to add the plots to. If not provided, one will be created.

  • points_between_ests – This should be used if multiple DoE iterations are used between qoi estimates (e.g if the estimate is expensive). It adjusts the scale of the x axis.

  • name – optional name that should be added to the legend information for this plot

  • trial_index – If provided, only plot data up to this trial index

  • kwargs – kwargs that should be passed to matplotlib. Must be applicable to ax.plot and ax.fill_between

Returns:

the ax with the plot.

Return type:

Axes