cmcrameri

This is a Python wrapper around Fabio Crameri's perceptually uniform colormaps.

https://www.fabiocrameri.ch/colourmaps/

All credit for creating the colormaps to Fabio. Any errors in the Python implementation of colormaps are my own.

This version is based on Scientific colour maps version 8.0 (2023-06-14).

Install

With pip:

python -m pip install cmcrameri

With conda:

conda install -c conda-forge cmcrameri

Usage example

import cmcrameri.cm as cmc
import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 1, 100)[np.newaxis, :]

plt.imshow(x, aspect='auto', cmap=cmc.batlow)
plt.axis('off')
plt.show()

For a discretized colormap like batlow split into 25 levels, you can use the .resampled method on any of the colormaps:

plt.imshow(x, aspect='auto', cmap=cmc.batlow.resampled(25))

Alternatively, the registered name string can be used.

import cmcrameri # required in order to register the colormaps with Matplotlib
...
plt.imshow(x, aspect='auto', cmap='cmc.batlow')

Extra instructions

You can access all the core colormaps from Fabio Crameri's list by cmcrameri.cm.<colormapname>.

You can use tab autocompletion on cmcrameri.cm if your editor supports it.

For a reversed colormap, append _r to the colormap name.

Categorical colormaps have the suffix S.

For an image of all the available colormaps without leaving the comfort of your Python session:

from cmcrameri import show_cmaps

show_cmaps()

The original colormap text files are shipped as part of the package. Find them on your system with:

from cmcrameri.cm import paths

paths

License

This work is licensed under an MIT license.