MMMPlotSuite.saturation_curves

MMMPlotSuite.saturation_curves(curve, original_scale=False, n_samples=10, hdi_probs=None, random_seed=None, colors=None, subplot_kwargs=None, rc_params=None, **plot_kwargs)

Overlay saturation‑curve scatter‑plots with posterior‑predictive sample curves and HDI bands.

allowing you to customize figsize and font sizes.

Parameters:

curvexr.DataArray

Posterior‑predictive curves (e.g. dims ("chain","draw","x","channel","geo")).

original_scalebool, default=False

Plot channel_contribution_original_scale if True, else channel_contribution.

n_samplesint, default=10

Number of sample‑curves per subplot.

hdi_probsfloat or list of float, optional

Credible interval probabilities (e.g. 0.94 or [0.5, 0.94]). If None, uses ArviZ’s default (0.94).

random_seednp.random.Generator, optional

RNG for reproducible sampling. If None, uses np.random.default_rng().

colorsiterable of str, optional

Colors for the sample & HDI plots.

subplot_kwargsdict, optional

Passed to plt.subplots (e.g. {"figsize": (10,8)}). Merged with the function’s own default sizing.

rc_paramsdict, optional

Temporary matplotlib.rcParams for this plot. Example keys: "xtick.labelsize", "ytick.labelsize", "axes.labelsize", "axes.titlesize".

**plot_kwargs

Any other kwargs forwarded to plot_curve (for instance same_axes=True, legend=True, etc.).

Returns:

figplt.Figure

Matplotlib figure with your grid.

axesnp.ndarray of plt.Axes

Array of shape (n_channels, n_geo).