Managers for faceting and aesthetics mapping

The classes in this module lay at the core of the library, and are consequently available at the arviz_plots top level namespace.

They abstract all information regarding faceting and aesthetic mapping in our figure to prevent duplication and ensure coherence between the different functions.

PlotCollection

Object creation

PlotCollection(data, viz_dt[, aes_dt, aes, ...])	Low level base class for plotting with xarray Datasets.
PlotCollection.grid(data[, cols, rows, ...])	Instantiate a PlotCollection and generate a plot grid iterating over rows and columns.
PlotCollection.wrap(data[, cols, col_wrap, ...])	Instantiate a PlotCollection and generate a grid iterating over subsets and wrapping.

Plotting

PlotCollection.add_legend(dim[, aes, ...])	Add a legend for the given visual/aesthetic to the plot.
PlotCollection.map(fun[, fun_label, data, ...])	Apply the given plotting function to all plots with the corresponding aesthetics.

Attributes

PlotCollection.aes	Information about aesthetic mapping as a DataTree.
PlotCollection.viz	Information about the visual elements in the plot as a DataTree.
PlotCollection.aes_set	Return all aesthetics with a mapping defined as a set.
PlotCollection.facet_dims	Dimensions over which one should loop for facetting when using this PlotCollection.
PlotCollection.data	Dataset to be used as data for plotting.

Faceting and aesthetics mapping

PlotCollection.generate_aes_dt(aes[, data])	Generate the aesthetic mappings.
PlotCollection.get_aes_as_dataset(aes_key)	Get the values of the provided aes_key for all variables as a Dataset.
PlotCollection.get_aes_kwargs(aes, var_name, ...)	Get the aesthetic mappings for the given variable and selection as a dictionary.
PlotCollection.update_aes([ignore_aes, coords])	Update list of aesthetics after indicating ignores and extra subsets.
PlotCollection.update_aes_from_dataset(...)	Update the values of aes_key with those in the provided Dataset.

Other

PlotCollection.allocate_artist(fun_label, ...)	Allocate a visual in the viz DataTree.
PlotCollection.get_viz(artist_name[, ...])	Get element from .viz that corresponds to the provided subset.
PlotCollection.get_target(var_name, selection)	Get the target that corresponds to the given variable and selection.
PlotCollection.show()	Call the backend function to show this figure.
PlotCollection.savefig(filename, **kwargs)	Call the backend function to save this figure.

PlotMatrix

Object creation

PlotMatrix(data, facet_dims[, aes, backend, ...])

Low level base class for pairwise matrix arranges of plots.

Plotting

PlotMatrix.map(fun[, fun_label, data, ...])	Apply the given plotting function along the diagonal with the corresponding aesthetics.
PlotMatrix.map_triangle(fun[, fun_label, ...])	Apply the given plotting function to all plots with the corresponding aesthetics.
PlotMatrix.map_lower(*args, **kwargs)	Call map_triangle with triangle="lower".
PlotMatrix.map_upper(*args, **kwargs)	Call map_triangle with triangle="upper".
PlotMatrix.map_row(fun[, fun_label, index, ...])	Apply the given plotting function along the row with the corresponding aesthetics.
PlotMatrix.map_col(fun[, fun_label, index, ...])	Apply the given plotting function along the column with the corresponding aesthetics.

Attributes

PlotMatrix.aes	Information about aesthetic mapping as a DataTree.
PlotMatrix.viz	Information about the visual elements in the plot as a DataTree.
PlotMatrix.aes_set	Return all aesthetics with a mapping defined as a set.
PlotMatrix.facet_dims	Facetting dimensions.
PlotMatrix.data	Dataset to be used as data for plotting.