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How to Choose a Good Colour Map

Summary

Representing data through colours is a very common approach to conveying important information to an audience. We suggest some best practices scientists should consider when deciding how they should present their results.

Description

Representing data through colours is a very common approach to conveying important information to an audience. This is done throughout all fields in the scientific community and stakes a claim in the commercial and marketing realm as well. Colour maps and contour maps are the preferred way for scientists to visualise three-dimensional data in two dimensions. Research has shown that the choice of colourmap is crucial since the human brain interpolates hue poorly. We suggest some best practices scientists should consider when deciding how they should present their results. Specifically, we look at some examples of colourmaps that can easily be misinterpreted, making reference to an in-depth supportive study, and suggest alternative approaches to improve them. We conclude by listing some open source tools that aid making good colourmap choices. Kristen Thyng's talk on perception of colourmaps in matplotlib is an excellent follow-on from this.

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