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Use colorblind-friendly colors in the scatter plots gallery example #1013

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merged 7 commits into from
Apr 12, 2021
Merged

Use colorblind-friendly colors in the scatter plots gallery example #1013

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90585ad
Accessible colors for color blindness
vitorgt Mar 6, 2021
2b235ea
change colors, add different symbols
vitorgt Mar 7, 2021
c6d0936
Merge branch 'master' into patch-1
michaelgrund Mar 10, 2021
44d090b
Merge branch 'master' into patch-1
michaelgrund Mar 11, 2021
d1bafa1
remove style change; more opaque symbols
vitorgt Apr 6, 2021
85611b2
move plot/scatter.py to symbols/scatter.py
vitorgt Apr 10, 2021
e20c030
Merge branch 'master' into patch-1
vitorgt Apr 10, 2021
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2 changes: 1 addition & 1 deletion examples/gallery/plot/scatter.py
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Expand Up @@ -21,7 +21,7 @@
projection="X10c/10c",
frame=["xa0.2fg", "ya0.2fg", "WSrt"],
)
for color in ["blue", "orange", "green"]:
for color in ["seagreen2", "chocolate1", "mediumpurple1"]:
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@michaelgrund michaelgrund Mar 7, 2021 •
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Suggested change
for color in ["seagreen2", "chocolate1", "mediumpurple1"]:
for color in ["seagreen2", "chocolate1", "mediumpurple1"]:

Not sure if these colors solve the problem (please correct me if I'm wrong). Maybe it would be better to select colors from cpts that really focus on the color blindness issue.

Here's a deuteranopia (green-blind) simulation of your example @vitorgt:

deuteranopia

By the way, here's a nice article about the use (or misuse) of color in scientific visualization by Crameri et al.: https://www.nature.com/articles/s41467-020-19160-7.

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I agree, but colorblind friendly colorschemes are very limited, and transparency makes this case even worst, I've changed green to a grey, this change will produce greater differences on protanopia and deuteranopia, but purple will get closer to grey on tritanopia (the rarest of the three).

Everywhere i looked on how to choose colorblind friendly colors they say not to rely only color, but to create other ways to differentiate set, usualy changing marker. So i added this.

Also, i couldn't find colorblind friendly cpts on gmt.

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transparency makes this case even worst,

Perhaps we can try to increase the transparency slightly?

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transparency makes this case even worst,

Perhaps we can try to increase the transparency slightly?

Agree, perhaps transparency=50 gives a better result.

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No, @michaelgrund, "transparency makes this case even worst" means we sould remove transparency.
Like transparency=90 or remove that line completely (which would be equal to transparency=100 (default)).

Transparenncy makes it worst beacuse it blends the colors and changes their luminance when adding two or more symbols with equal or different colors, notting that color addition with colorblindness is a little bit tricky. That's why transparency should be avoided if we want it more coverage considering colorblindness.

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I think we're getting a bit confused here. transparency=0 means opaque while transparency=100 means invincible. We probably want to reduce transparency (i.e. increase opacity).

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Right @weiji14. I think we should not drop transparency here since it allows to deal with overplotting.

x, y = np.random.rand(2, n) # random X and Y data in [0,1]
sizes = np.random.rand(n) * 0.5 # random size [0,0.5], in cm
# plot data points as circles (style="c"), with different sizes
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