2018
DOI: 10.1371/journal.pone.0199239
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Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data

Abstract: Color vision deficiency (CVD) affects more than 4% of the population and leads to a different visual perception of colors. Though this has been known for decades, colormaps with many colors across the visual spectra are often used to represent data, leading to the potential for misinterpretation or difficulty with interpretation by someone with this deficiency. Until the creation of the module presented here, there were no colormaps mathematically optimized for CVD using modern color appearance models. While t… Show more

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Cited by 123 publications
(110 citation statements)
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References 36 publications
(47 reference statements)
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“…Subsequent statistical data analyses and plotting were performed in R Studio 43 using opensource packages [44][45][46][47] and custom-written scripts. To assess discriminative freezing between the CS+ and CS−, a discrimination ratio was calculated as freezing to CS+ divided by the sum of freezing to CS+ and CS−.…”
Section: Statistical Analysesmentioning
confidence: 99%
“…Subsequent statistical data analyses and plotting were performed in R Studio 43 using opensource packages [44][45][46][47] and custom-written scripts. To assess discriminative freezing between the CS+ and CS−, a discrimination ratio was calculated as freezing to CS+ divided by the sum of freezing to CS+ and CS−.…”
Section: Statistical Analysesmentioning
confidence: 99%
“…The dashed line indicates the tenth percentile redshift. The 'cividis' colormap used is described byNuñez et al (2018).dictions of their own model. However, Andrews et al used a slightly different version of theLacey et al (2016) model than in this work, as the one we use here has been recalibrated for implementation in merger trees from the P-Millennium dark matter simulation.…”
mentioning
confidence: 99%
“…Although this colormap performs well in gray-scale, it can cause problems when viewed by someone with CVD, as demonstrated by Nuñez et al (2018). Additionally, we felt that viridis did not allow for enough fine structure details.…”
Section: B Writing a Modellink Subclassmentioning
confidence: 96%
“…Therefore, we decided to do something similar to the work done by Kindlmann et al (2002), but instead of using the six major colors of the rainbow, we wanted to improve the existing "standards". By using the Python package cmaputil (Nuñez et al 2018), we converted the aforementioned jet and hot colormaps into versions that are CVD-proof and work well in gray-scale (see Fig. 11).…”
Section: B Writing a Modellink Subclassmentioning
confidence: 99%
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