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Show all seaborn palettes and simulate what they look like with various color vision deficiencies. (The 10-element seaborn palettes will be part of the forthcoming 0.9 release).
"""Show seaborn palettes and simulate colorblind versions."""
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from colorspacious import cspace_converter
def show_palettes():
f = plt.figure(figsize=(6, 6))
ax_locs = dict(
deep=(.4, .4),
bright=(.8, .8),
muted=(.49, .71),
dark=(.8, .2),
pastel=(.2, .8),
colorblind=(.71, .49),
)
s = .35
for pal, (x, y) in ax_locs.items():
ax = f.add_axes([x - s / 2, y - s / 2, s, s])
ax.pie(np.ones(10),
colors=sns.color_palette(pal, 10),
counterclock=False, startangle=180,
wedgeprops=dict(linewidth=1, edgecolor="w"))
f.text(x, y, pal, ha="center", va="center", size=14,
bbox=dict(facecolor="white", alpha=0.85,
boxstyle="round,pad=0.2"))
f.text(.1, .05, "Saturation", size=18, ha="left", va="center",
bbox=dict(facecolor="white", edgecolor="w"))
f.text(.05, .1, "Luminance", size=18, ha="center", va="bottom",
rotation=90, bbox=dict(facecolor="white", edgecolor="w"))
ax = f.add_axes([0, 0, 1, 1])
ax.set_axis_off()
ax.arrow(.15, .05, .4, 0, width=.002, head_width=.015, color="k")
ax.arrow(.05, .15, 0, .4, width=.002, head_width=.015, color="k")
return f
if __name__ == "__main__":
f = show_palettes()
f.suptitle("Original palettes", size=14)
f.savefig("palettes.png", dpi=100)
plt.close(f)
converters = {}
_deuter50_space = {"name": "sRGB1+CVD",
"cvd_type": "deuteranomaly",
"severity": 50}
converters["deuter50"] = cspace_converter(_deuter50_space, "sRGB1")
_deuter100_space = {"name": "sRGB1+CVD",
"cvd_type": "deuteranomaly",
"severity": 100}
converters["deuter100"] = cspace_converter(_deuter100_space, "sRGB1")
_prot50_space = {"name": "sRGB1+CVD",
"cvd_type": "protanomaly",
"severity": 50}
converters["prot50"] = cspace_converter(_prot50_space, "sRGB1")
_prot100_space = {"name": "sRGB1+CVD",
"cvd_type": "protanomaly",
"severity": 100}
converters["prot100"] = cspace_converter(_prot100_space, "sRGB1")
for cbt, converter in converters.items():
f = show_palettes()
for ax in f.axes:
for patch in ax.patches:
fc = patch.get_facecolor()[:3]
patch.set_facecolor(np.clip(converter(fc), 0, 1))
f.suptitle(cbt.capitalize(), size=14)
f.savefig(f"palettes_{cbt}.png", dpi=100)
plt.close(f)
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