{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/7"}],"enrichment":{"capability":"Provides perceptually uniform colormaps by Fabio Crameri for matplotlib, enabling scientific visualizations designed to be readable across different media and accessible to colorblind viewers.","skillfed_tags":["visualization","scientific-computing","colormap"],"use_cases":["Create publication-ready scientific plots where color gradients must remain perceptually uniform across print and digital media.","Build heatmaps and contour plots in geophysics, oceanography, or climate science where standard colormaps introduce perceptual bias.","Discretize continuous colormaps into categorical levels for segmented data visualization without losing perceptual uniformity.","Integrate Crameri's colormaps into existing matplotlib workflows using registered string names like 'cmc.batlow'.","Access reversed colormaps by appending `_r` to colormap names for inverted data representations."],"what_it_does":"cmcrameri is a Python wrapper that brings Fabio Crameri's scientifically designed colormaps into matplotlib. The package registers a collection of perceptually uniform colormaps\u2014colormaps engineered to represent data changes uniformly across the full range of colors, making them suitable for scientific publication. You import the colormaps directly or by registered string name and use them with matplotlib's standard plotting functions.\n\nThe package ships the original colormap definitions and provides convenient access through tab-completable attributes. You can discretize colormaps into a specific number of levels, reverse them by appending `_r`, and access categorical variants with the `S` suffix. It requires matplotlib and numpy as runtime dependencies and supports Python 3.7 and later.","worth_installing":"Yes. The package is actively maintained, has no known vulnerabilities, installs with minimal friction, and solves a real problem for scientific visualization. If you create plots for publication or need colormaps designed for perceptual uniformity, this is a straightforward addition to matplotlib. The MIT license imposes no restrictions."},"id":"cmcrameri","links":{"html":"https://skillfed.io/packages/cmcrameri","md":"https://skillfed.io/packages/cmcrameri.md","pypi":"https://pypi.org/project/cmcrameri/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-04","license_spdx":null,"license_treatment":"permissive","name":"cmcrameri","python_support":"supports_current","summary":"Perceptually uniform colormaps by Fabio Crameri"},"popularity":{"monthly_downloads":111890,"position":12391,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.10"}