ribs.visualize¶

Visualization tools for pyribs.

These functions are similar to Matplotlib functions like scatter() and pcolormesh(). When called, these functions default to creating plots on the current axis. After plotting, functions like xlabel() and title() may be used to further modify the axis. Alternatively, if using Matplotlib’s object-oriented API, pass the ax parameter to these functions.

Note

This module only works with ribs[visualize] installed. As such, it is not imported with import ribs, and it must be explicitly imported with import ribs.visualize.

`aggregate_cdf`(archives[, ax, dfs, ...])	Plots a CDF/CCDF aggregated over multiple archives.
`archive_ecdf`(archive[, df])	Plots an ECDF or ECCDF of the objective values in an archive.
`archive_histogram`(archive[, ax, df, bins, ...])	Plots a histogram of the objective values in an archive.
`cvt_archive_3d_plot`(archive[, ax, df, ...])	Plots a `CVTArchive` with 3D measure space.
`cvt_archive_heatmap`(archive[, ax, df, ...])	Plots heatmap of a `CVTArchive` with 1D or 2D measure space.
`grid_archive_heatmap`(archive[, ax, df, ...])	Plots heatmap of a `GridArchive` with 1D or 2D measure space.
`parallel_axes_plot`(archive[, ax, df, ...])	Visualizes archive elites in measure space with a parallel axes plot.
`proximity_archive_plot`(archive[, ax, df, ...])	Plots scatterplot of a `ProximityArchive` with 2D measure space.
`sliding_boundaries_archive_heatmap`(archive)	Plots heatmap of a `SlidingBoundariesArchive` with 2D measure space.
`qdax_repertoire_3d_plot`(repertoire, ranges, ...)	Plots a single-objective QDax MapElitesRepertoire with 3D measure space.
`qdax_repertoire_heatmap`(repertoire, ranges, ...)	Plots a heatmap of a single-objective QDax MapElitesRepertoire.