Colors and Colormaps

This page covers practical usage: picking colors, mixing them, interpolating gradients, and using colormaps. For full visual catalogs of every palette and colormap, see the Color System reference.

Named colors

dartwork-mpl registers named palettes from OpenColor, Tailwind, Material, Ant Design, Chakra, and Primer. Use them anywhere matplotlib accepts a color.

Prefix

Library

Example

oc.*

OpenColor

oc.blue5

tw.*

Tailwind CSS

tw.blue500

md.*

Material Design

md.red500

an.*

Ant Design

an.blue6

ch.*

Chakra UI

ch.teal500

pr.*

Primer

pr.blue5

 
import matplotlib.pyplot as plt
import dartwork_mpl as dm
import numpy as np

dm.style.use("presentation")

fig, ax = plt.subplots(figsize=(dm.cm2in(8), dm.cm2in(5)), dpi=300)
ax.plot([0, 1, 2], [1, 2, 1.5], marker="o", color="oc.green5", label="oc.*")
ax.plot([0, 1, 2], [1.2, 1.6, 2.1], marker="s", color="tw.blue500", label="Tailwind")
highlight = dm.mix_colors("md.orange600", "white", alpha=0.45)
ax.fill_between([0, 1, 2], 0.9, 1.3, color=highlight, label="Mixed shade")
muted_line = dm.pseudo_alpha("pr.blue5", alpha=0.65, background="white")
ax.plot([0, 1, 2], [0.8, 1.1, 1.4], color=muted_line, label="Pseudo alpha")
ax.legend(fontsize=dm.fs(-1))
dm.simple_layout(fig)
dartwork Color
dc.autumn
0#EEC643
1#DA7B5C
2#A77B5C
3#BC4749
4#386641
5#6A4C3C
dc.cyber
0#4CC9F0
1#00B4D8
2#F72585
3#4361EE
4#7209B7
5#3A0CA3
dc.forest
0#95D5B2
1#74C69D
2#52B788
3#B5838D
4#2D6A4F
5#1B4332
dc.nordic
0#B2BEC3
1#00B894
2#0984E3
3#D63031
4#636E72
5#2D3436
dc.ocean
0#62B6CB
1#1B98E0
2#00838F
3#4A6FA5
4#0B3D91
5#2E4057
dc.pop
0#FFCA3A
1#8AC926
2#FF924C
3#FF595E
4#1982C4
5#6A4C93
dc.sunset
0#FFC857
1#F28C28
2#E63946
3#457B9D
4#6B4D57
5#264653
dc.vivid
0#F59E0B
1#06B6D4
2#16A34A
3#DC2626
4#9333EA
5#2563EB

Color class

For most plots, named color strings like "oc.blue5" are all you need. When you need to programmatically adjust hue, saturation, or lightness — or interpolate between colors in a perceptually uniform space — use the Color class:

import dartwork_mpl as dm

color = dm.oklch(0.7, 0.15, 150)    # OKLCH (L, C, h°)
color.oklch.C *= 1.2                 # boost chroma in-place
print(color.to_hex())                # '#...'

→ Full guide: Color Space & Manipulation — constructors, views, interpolation, and custom colormaps.

Exploring Available Colors

dartwork-mpl provides utilities to discover and explore available color palettes:

import dartwork_mpl as dm

# List all discrete color palettes
palettes = dm.list_palettes()
print(palettes[:5])  # ['dc.vivid', 'oc.blue', 'oc.red', 'tw.emerald', ...]

# List all colormaps
cmaps = dm.list_colormaps()
print(cmaps[:5])  # ['dc.deep_sea', 'dc.forest', 'dc.sunset', ...]

# Preview a specific palette
dm.show_palette('oc.blue')  # Shows all shades: blue0, blue1, ..., blue9

# Visualize multiple palettes at once
dm.plot_colors(['oc.blue', 'tw.emerald', 'md.purple'])

# Visualize colormaps
dm.plot_colormaps(['dc.deep_sea', 'dc.forest'])

# Classify a colormap by type
cmap_type = dm.classify_colormap('viridis')
print(cmap_type)  # 'sequential'

Color interpolation

import dartwork_mpl as dm

# Perceptual interpolation between colors (OKLCH by default)
palette = dm.cspace('#FF6B6B', '#4ECDC4', n=5, space='oklch')
for i, c in enumerate(palette):
    ax.bar(i, 1, color=c.to_hex())

# Also supports 'oklab' and 'rgb' spaces
gradient = dm.cspace(dm.named('oc.red5'), dm.named('oc.blue5'), n=10)
From
→
To
Steps n=5
dm.cspace('#FF6B6B', '#4ECDC4', n=5, space='oklch')

Why OKLCH matters: Interpolating in RGB produces muddy, desaturated midtones. OKLCH maintains perceptual uniformity — every step looks equally spaced to the human eye:

OKLCH vs RGB Interpolation
Why color space matters for gradient quality
Steps n=20
OKLCHperceptually uniform
RGBmuddy midtones
↑ OKLCH maintains vivid hues through the transition. ↓ RGB produces muddy, desaturated midtones — notice the grey-brown colors in the middle.

Colormaps

dartwork-mpl bundles custom colormaps prefixed with dc. — curated for perceptually uniform gradients. They work like any matplotlib colormap:

import matplotlib.pyplot as plt
import dartwork_mpl as dm

cmap = plt.colormaps["dc.deep_sea"]
print(cmap.name)                       # 'dc.deep_sea'
print(dm.classify_colormap(cmap))      # 'sequential' (tells you the type)

Add _r to reverse any colormap (e.g., dc.sunset_r). Browse all available colormaps on the Colormaps page.

Where things live