cmap

library0.7.2pypypi✓ verified 86d ago

cmap provides a collection of scientific colormaps for Python, focusing on perceptual uniformity and colorblind-friendliness. It bundles various colormaps like Crameri, Tol, Viridis, and many others, offering a unified API to access and manipulate them. The library is actively maintained with frequent minor releases, currently at version 0.7.2.

data serialization

pip install cmap

github ↗package ↗docs ↗

INSTALL

IMPORT

SIG · CMAP

cmap

datapythonv0.7.2

Install

4.3s avg

Import

368ms

Disk

96MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.7.2 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 0.359s · 95.9MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 4.3s · import 0.376s · 92MB

96MB installed

● package 96MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Colormap

✓ from cmap import Colormap

get_cmap

✓ from cmap import get_cmap

This quickstart demonstrates how to fetch a colormap using `get_cmap`, convert data to RGBA colors, and integrate the `cmap` colormap with Matplotlib for visualization via the `to_mpl()` method.

import numpy as np import matplotlib.pyplot as plt from cmap import get_cmap, Colormap # Get a colormap by name using the utility function my_cmap = get_cmap("viridis") # Or, access namespaced colormaps directly # my_cmap = Colormap.scientific.viridis # Colormap objects are callable with normalized data [0, 1] or raw data data = np.linspace(0, 1, 256) # Example data colors_rgba = my_cmap(data) # Returns (N, 4) array of RGBA floats # Convert to a Matplotlib colormap for seamless integration with plotting mpl_cmap = my_cmap.to_mpl() # Example usage with Matplotlib fig, ax = plt.subplots(figsize=(6, 1)) plt.imshow([np.arange(256)], cmap=mpl_cmap, aspect='auto') plt.colorbar(ax.images[0], orientation='horizontal') plt.title(f"Example Colormap: {my_cmap.name}") plt.axis('off') plt.show()

Debug

Known issues

breakingPython 3.8 support was dropped in `cmap` version 0.6.0. Users on Python 3.8 or older will encounter errors or be unable to install recent versions.

fix

Upgrade to Python 3.9 or newer (e.g., `python -m pip install --upgrade python` or update your environment).

affects: >=0.6.0

breakingThe `crameri` colormaps were updated to version 8 in `cmap` v0.5.0. If you relied on pixel-perfect color values for `crameri` colormaps from older versions, these may have changed slightly.

fix

Review any code that depends on exact `crameri` color values when upgrading from versions prior to 0.5.0. Consider pinning `cmap<0.5.0` if strict adherence to old `crameri` maps is required.

affects: >=0.5.0

gotchaWhile many colormaps can be accessed via `cmap.get_cmap("name")`, some are organized into namespaces (e.g., `cmap.scientific.viridis`, `cmap.QUALITATIVE.tol.bright`). Attempting to access `cmap.name` directly for a namespaced colormap will result in an `AttributeError`.

fix

Always use `get_cmap("name")` for general access, or explicitly specify the namespace like `Colormap.scientific.viridis` when you know the colormap's location.

affects: all

gotchaSome colormaps in `cmap` are 'parametrized' and require keyword arguments during instantiation (e.g., `Colormap.linear_segmented(...)`). If you try to instantiate these without the required arguments, a `TypeError` will be raised.

fix

Consult the documentation for the specific colormap to understand its required parameters. For example, `my_parametrized_cmap = Colormap.get_cmap('my_param_map', arg1=value1, arg2=value2)` or `Colormap.linear_segmented(colors=['red', 'blue'])`.

affects: all

Errors

Common errors & fixes

AttributeError: module 'cmap' has no attribute 'my_colormap_name'

Trying to access a colormap directly as an attribute of the top-level `cmap` module or `Colormap` class without using `get_cmap` or the correct namespace.

fix

Use `from cmap import get_cmap; my_cmap = get_cmap('my_colormap_name')` or access through its specific namespace, e.g., `from cmap import Colormap; my_cmap = Colormap.scientific.my_colormap_name`.

ModuleNotFoundError: No module named 'matplotlib'

Although `matplotlib` is a direct dependency, this error can occur if `cmap` was installed with `--no-deps`, if your Python environment is corrupted, or if `matplotlib` failed to install properly.

fix

Ensure `matplotlib` is correctly installed in your environment: `pip install matplotlib` or `pip install cmap` without `--no-deps`.

TypeError: Colormap 'my_parametrized_colormap' expects keyword arguments: ['segment_colors']

Attempting to create or retrieve a parametrized colormap without providing its required keyword arguments.

fix

Check the colormap's documentation or source for expected parameters. Pass the required keyword arguments, e.g., `get_cmap('my_parametrized_colormap', segment_colors=['red', 'green', 'blue'])`.

Upgrade

Version history

0.7.2latest on PyPI · released Feb 24, 2026

Audit

Dependencies

numpyrequiredFundamental for numerical operations and array handling.

coloriorequiredProvides color science utilities and color conversions.

scikit-imagerequiredUsed for image processing tasks related to colormap generation and manipulation.

matplotlibrequiredRequired for the convenience method `Colormap.to_mpl()` to convert `cmap` colormaps into Matplotlib colormap objects.

Agent activity

21 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/pyapp-kit/cmap ↗

packagehttps://pypi.org/project/cmap/ ↗

docshttps://cmap-docs.rtfd.io/ ↗