This example is based on barh.py example from matplotlib.
import matplotlib.pyplot as plt
import numpy as np
# Fixing random state for reproducibility
np.random.seed(19680801)
fig, ax = plt.subplots()
# Example data
people = ('Tom', 'Dick', 'Harry', 'Slim', 'Jim')
y_pos = np.arange(len(people))
performance = 3 + 10 * np.random.rand(len(people))
error = np.random.rand(len(people))
bars = ax.barh(y_pos, performance, xerr=error, align='center')
ax.set_yticks(y_pos, labels=people)
ax.invert_yaxis() # labels read top-to-bottom
ax.set_xlabel('Performance')
ax.set_title('How fast do you want to go today?')
# Now we pick Harry's bar and change its luminosity at 50 20%, and set
# luminosity of others at 80%.
from mpl_visual_context.patheffects import HLSModify, ColorMatrix
pe_active = HLSModify(l="-80%")
pe_inactive = HLSModify(l="-30%") | ColorMatrix("grayscale")
for name, p in zip(people, bars.patches):
if name == "Harry":
p.set_path_effects([pe_active])
else:
p.set_path_effects([pe_inactive])
# The plot also shows errorbar for each bar plot. The errorbar is represented
# as a line_collection, and it is not straight forward to apply path_effects
# only to the part of them. So, it it not attempted in this example.
plt.show()
Total running time of the script: (0 minutes 0.042 seconds)
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