cvdmaps

Colorblind-safe colormaps and color cycles for matplotlib. matplotlib's default color cycle (tab10) is not colorblind-safe — cvdmaps fixes that in one call, and every palette it ships is verified safe under protanopia, deuteranopia, and tritanopia.

pip install cvdmaps

import cvdmaps
cvdmaps.set_cycle()                 # every plot from here uses a colorblind-safe cycle

import matplotlib.pyplot as plt
plt.plot(x, y1); plt.plot(x, y2)    # colors now stay distinct for colorblind viewers

cvdmaps.palette("okabe_ito")        # ['#000000', '#E69F00', '#56B4E9', ...]
plt.imshow(data, cmap="okabe_ito_nb")   # registered colormaps, usable by name

API

• set_cycle(name="okabe_ito_nb") — set matplotlib's default color cycle to a colorblind-safe palette. The one call that makes all your plots safe.
• palette(name="okabe_ito", n=None) — the palette as a list of hex colors (optionally first n).
• register() — (re)register the colormaps with matplotlib; runs automatically on import.
• names() — ['okabe_ito', 'okabe_ito_nb'].

okabe_ito is the 8-color set (incl. black); okabe_ito_nb drops black for line plots on white.

Why trust it

The palettes are the Okabe–Ito colorblind-safe set, and each one passes the OpticQuiz cvdsafe check — the same Machado 2009 + CIEDE2000 engine behind the rest of the suite. Nothing ships that our own checker rejects. For a sequential colorblind-safe map, matplotlib's built-in cividis is a good default.

Licence

MIT.