Scientific Color Maps

Treat color as a quantitative axis, not decoration. Preserve the structure of the data, make the mapping interpretable, and keep it readable under common color-vision deficiencies and grayscale reproduction.

Workflow

1. Inspect the data and intended claim before choosing colors.
2. Identify whether color is the primary quantitative channel or only reinforces position, length, height, or labels.
3. Classify the variable and select the matching map class.
4. Decide whether hue changes have a defensible semantic or perceptual purpose.
5. Choose a documented perceptually uniform palette.
6. Separate direct visualization evidence from adjacent color-psychology evidence.
7. Implement the scale, normalization, limits, and color bar together.
8. Validate the result under grayscale, color-vision simulation, and the final background.
9. Report the exact palette and mapping decisions when reproducibility matters.

Read references/selection-and-audit.md when selecting among map classes, auditing an existing figure, or needing implementation guidance.

Read references/evidence-and-tools.md when applying visual-weight research, standardizing colors across figures, evaluating evidence strength, or deciding which validation tools to use.