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cmap is a work-in-progress colormap library for python, providing all of the colormaps in matplotlib, vispy, cmocean, (and more), with no dependencies beyond numpy.


Mapping scalar values to colors is a very common procedure in scientific visualization; as such, many visualization libraries (e.g. matplotlib, vispy, napari, etc...) have some need for and some internal representation of colors and colormaps.

Don't we already have this?

Many libraries that use colormaps end up either directly depending on matplotlib, vendoring just the colors module or colormap data, or reimplementing a colormapping solution internally (even if it's not the core purpose of the library).

This library attempts to avoid the need for that duplication, aiming to provide a comprehensive, dependency-free (except numpy) collection of colormaps; and an API for using these colormaps in a wide variety of third party libraries (beyond matplotlib).

Specifically there are three goals:

  1. Accumulate colormap data from a variety of sources into a single repository.
  2. Provide an API for creating and applying colormaps without any dependencies beyond numpy. (by "applying" here, we mean converting an array of scalar values to an array of RGBA values)
  3. Provide an API for converting colormaps to the native format for a variety of third party libraries (currently including, matplotlib, napari, vispy, pygfx, bokeh, plotly, altair, and more)


For a complete list of available colormaps, see the Colormaps catalog. You can also use the search bar at the top to search for a specific colormap.

For details on using the cmap.Colormap object, see Colormaps.


This library also offers a simple cmap.Color object. It can cast a variety of inputs (including strings, tuples/lists, arrays, integers) to an RGBA color representation, and offers some basic conversions. See Colors for details