Figwise

Scientific Color Palette Generator

A color palette for scientific figures shouldn't need a design degree to get right. Build categorical, sequential, or diverging sets from Okabe-Ito, viridis, cividis, and ColorBrewer, then check every color against deuteranopia and protanopia before it reaches a reviewer.

Palette
#000000 0,0,0 #e69f00 230,159,0 #56b4e9 86,180,233 #009e73 0,158,115 #f0e442 240,228,66 #0072b2 0,114,178 #d55e00 213,94,0 #cc79a7 204,121,167 Original Deuteranopia Protanopia
01WHAT IS IT

What Is a Scientific Color Palette Generator, and What Does It Choose For You?

Categorical (qualitative) palettes assign a distinct hue to each group in your data — treatment arms, cell types, species, experimental conditions — where the goal is telling classes apart, not implying order or magnitude. A good categorical set stays visually distinct at a glance, even for a reader with red-green color vision deficiency, and still separates cleanly when a reviewer prints your manuscript in grayscale. Okabe-Ito, built specifically for color-universal design, and ColorBrewer's Set2 are the two categorical sets built into this scientific color palette generator — each one also works as a colorblind friendly palette on its own.

Sequential palettes encode one ordered quantity — expression level, p-value, concentration, elapsed time — as a smooth ramp from low to high, usually light to dark. They belong on heatmaps, density plots, and any figure where color stands in for magnitude alone. Viridis and cividis are perceptually uniform: equal steps in the data produce equal-looking steps in color, so a reader's eye doesn't misjudge where a gradient changes fastest. ColorBrewer Blues, a single-hue sequential set in this scientific color palette generator, does the same job with a simpler range.

Diverging palettes are for data with a meaningful center — zero fold-change, a control baseline, no correlation — with two directions branching away from it. Log2 fold-change heatmaps, correlation matrices, and effect-size plots all call for a diverging scheme, so a reader separates "above baseline" from "below baseline" by hue instead of squinting at axis numbers. ColorBrewer's RdBu keeps red and blue at opposite poles around a neutral midpoint, which also survives grayscale printing better than a red-green pair.

Three swatch rows comparing categorical, sequential, and diverging color palette structures
02EXAMPLES

Built-in Palettes, Rendered as Real Output

Every card below is the exact SVG this scientific color palette generator produces at its default settings — not a mockup.

Categorical: Okabe-Ito for Group Comparisons

Eight color-universal hues that double as a colorblind friendly palette for treatment arms, cell lines, or species labels — distinct under deuteranopia and protanopia, and still separable printed in black and white.

Sequential: Viridis for Continuous Data

A perceptually uniform ramp from dark purple to yellow, resampled at any step count from 2 to 12 for heatmaps and density plots where color encodes magnitude.

Diverging: ColorBrewer RdBu Around a Center

Red to blue with a neutral midpoint, for fold-change heatmaps and correlation matrices where readers need to see which values sit above or below a baseline.

Colorblind Simulation, Side by Side

The same palette rendered as it appears with typical vision, then transformed for deuteranopia and protanopia, so you catch a collision before a reviewer does.

03FEATURES

Everything This Scientific Color Palette Generator Automates

Palette family selector switching between categorical, sequential, and diverging modes
Categorical · Sequential · Diverging

One Generator, Three Ways to Encode Data

Switch between categorical, sequential, and diverging without leaving the page — pick the family that matches what your data actually means, then get a full set of research figure colors built around it.

Side-by-side colorblind simulation of a scientific color palette
Deuteranopia · Protanopia

Colorblind Simulation Built Into Every Preview

An estimated 1 in 12 men and roughly 1 in 200 women have some form of red-green color vision deficiency. This colorblind friendly palette check runs a real deuteranopia and protanopia transform on your chosen colors and shows all three versions side by side before you open your plotting software.

Slider control adjusting the number of colors in a scientific palette from two to twelve
2–12 colors

Adjustable Color Count, Without Guessing at Hex Codes

Drag from 2 to 12 colors and this scientific color palette generator resamples from each palette's reference points — categorical sets cycle through their fixed hues, sequential and diverging sets interpolate new steps — so you're never eyeballing a gradient by hand.

Exported color palette SVG with hex and RGB labels under each swatch
SVG · PNG · HEX

Export Straight Into Your Plotting Library

Download a labeled SVG or PNG for a figure legend, or click any swatch to copy its hex code and paste those research figure colors directly into matplotlib, ggplot2, or Prism — no separate color picker required.

04COMPARE

Why Rainbow and Jet Colormaps Fail Scientific Figures

The default rainbow or jet colormap in older plotting software still turns up in submitted manuscripts, and as a color palette for scientific figures it fails in two specific, well-documented ways.

Jet / Rainbow Colormap

  • Perceptually non-uniform — equal steps in the data produce uneven, sometimes reversed, jumps in apparent brightness, which can make a plateau read as a peak.
  • Collapses toward a similar mid-gray band when printed or photocopied in black and white, erasing the range readers most need to compare.
  • Confuses readers with red-green color vision deficiency, since its red and green segments sit close together with little brightness contrast between them.

Perceptually Uniform, Colorblind-Safe Palettes

  • Monotonic lightness — viridis and cividis increase brightness in one direction only, giving research figure colors that read correctly without decoding hue first.
  • Distinct in grayscale — ColorBrewer and Okabe-Ito sets are built and tested for legibility after conversion to black and white.
  • Verified against common types of color vision deficiency, not just checked by a single sighted designer.
05FAQ

Questions Before You Pick a Palette

Common questions from researchers preparing figures for journal submission.

06RELATED TOOLS

Give Your Next Figure a Palette That Holds Up in Review

Pick a palette family in this scientific color palette generator, check it against deuteranopia and protanopia, and copy the hex codes straight into your plotting script — building a colorblind friendly palette takes minutes, not another round of reviewer comments.

Build a palette