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).
With pip:
python -m pip install cmcrameri
With conda:
conda install -c conda-forge cmcrameri
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')
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
This work is licensed under an MIT license.
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