import matplotlib.pyplot as plt
import seaborn as sns
from mpl_visual_context.patheffects import (
HLSModify,
ColorMatrix as CMS,
PathEffectsContainer,
)
def test():
df_peng = sns.load_dataset("penguins")
# registry of path_effects
registry = dict(
bright=[HLSModify(l="-50%")],
bright_gray=[HLSModify(l="-50%") | CMS("grayscale")],
)
fig, axl = plt.subplots(1, 3, figsize=(11, 3), constrained_layout=True, clear=True)
ax = axl[0]
sns.countplot(y="species", data=df_peng, ax=ax)
# second axes; with brighter color, oe directly from the registry
ax = axl[1]
sns.countplot(y="species", data=df_peng, ax=ax)
pe = registry["bright"]
for p in ax.patches[:2]:
p.set_path_effects(pe)
# second axes; with brighter+gray color, using the pe container.
ax = axl[2]
sns.countplot(y="species", data=df_peng, ax=ax)
pe = PathEffectsContainer(registry)
for p in ax.patches[:2]:
p.set_path_effects(pe)
pe.use("bright_gray")
plt.show()
if __name__ == '__main__':
test()
Total running time of the script: (0 minutes 0.147 seconds)
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