Project Bivariate and Multivariate Colormapping, which resolves github.com//issues/14168 is divided into a number of milestones, of which this is one (highlighted in bold).

• Classes for bivariate and multivariate colormaps
• Colorizer and ColorizingArtist to replace ScalarMappable and handle the norm→color pipeline
• A MultiNorm class to handle the normalization of data for bivariate and multivariate colormaps
• Ensure the Colorizer and ColorizingArtist work with MultiNorm, BivarColormap and MultivarColormap
• Expose the new functionality via the top-level plotting functions: imshow(), pcolor() and pcolormesh()
• Create equivalents to fig.colorbar() for BivarColormap and MultivarColormap to work with ColorizingArtist
• Select bivariate and multivariate colormaps to include in matplotlib
• Examples demonstrating the new functionality

With the inclusion of #28454, matplotlib has support for BivarColormap and MultivarColormap. Two examples of BivarColormap and three of MultivarColormap were included:

Bivariate:

Multivariate, 2 channels, additive:

Multivariate, 2 channels, subtractive:

Multivariate, 3 channels, additive:

These are insufficient for real-world use, and more colormaps are required, with more varied use cases.