arviz_plots.add_bands

arviz_plots.add_bands(plot_collection, values, orientation='vertical', aes_by_visuals=None, visuals=None, sample_dims=None, ref_dim=None, **kwargs)

Add bands.

This function adds bands (shared areas) to a plot collection based on the provided values. It supports both vertical and horizontal bands, depending on the specified orientation.

Parameters:

plot_collectionPlotCollection

Plot collection to which the bands will be added.

valuestuple, list or dict

Start and end values for the bands to be plotted.

orientationstr, default “vertical”

The orientation of the bands, either “vertical” or “horizontal”.

aes_by_visualsmapping of {strsequence of str}, optional

Mapping of visuals to aesthetics that should use their mapping in plot_collection when plotted. Valid keys are the same as for visuals.

The default is to use an “overlay_band” aesthetic for all elements.

It is possible to request aesthetics without mappings defined in the provided plot_collection. In those cases, a mapping of the dimensions in ref_dim minus its last element to the requested aesthetic will be automatically added.

visualsmapping of {strmapping or False}, optional

Valid keys are:

• “ref_band” -> passed to vspan for vertical orientation and to hspan for horizontal orientation

sample_dimslist, optional

Dimensions that should not be added to the Dataset generated from values via arviz_base.references_to_dataset. Defaults to all dimensions in plot_collection.data that are not facet_dims

ref_dimlist, optional

List of dimension names that define the axes along which the band values are stored. These dimensions are used to align or compare input data with band data. Defaults to [“ref_dim”, “band_dim”].

**kwargssequence, optional

Mapping of aesthetic keys to the values to be used in their mapping. See generate_aes_dt for more details.

Returns:

plot_collectionPlotCollection

Plot collection with the bands added.

Examples

Add two bands for the theta variable, one from -2 to 2 and the other from -5 to 5.

>>> from arviz_plots import plot_dist, add_bands, style
>>> style.use("arviz-variat")
>>> from arviz_base import load_arviz_data
>>> dt = load_arviz_data('centered_eight')
>>> pc = plot_dist(dt)
>>> add_bands(pc, values=[[-2, 2], [-5, 5]])