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"""
====================================
Colors in the default property cycle
====================================
Display the colors from the default prop_cycle, which is obtained from the
:doc:`rc parameters</tutorials/introductory/customizing>`.
"""
import numpy as np
import matplotlib.pyplot as plt
prop_cycle = plt.rcParams['axes.prop_cycle']
colors = prop_cycle.by_key()['color']
lwbase = plt.rcParams['lines.linewidth']
thin = lwbase / 2
thick = lwbase * 3
fig, axs = plt.subplots(nrows=2, ncols=2, sharex=True, sharey=True)
for icol in range(2):
if icol == 0:
lwx, lwy = thin, lwbase
else:
lwx, lwy = lwbase, thick
for irow in range(2):
for i, color in enumerate(colors):
axs[irow, icol].axhline(i, color=color, lw=lwx)
axs[irow, icol].axvline(i, color=color, lw=lwy)
axs[1, icol].set_facecolor('k')
axs[1, icol].xaxis.set_ticks(np.arange(0, 10, 2))
axs[0, icol].set_title('line widths (pts): %g, %g' % (lwx, lwy),
fontsize='medium')
for irow in range(2):
axs[irow, 0].yaxis.set_ticks(np.arange(0, 10, 2))
fig.suptitle('Colors in the default prop_cycle', fontsize='large')
plt.show()
#############################################################################
#
# ------------
#
# References
# """"""""""
#
# The use of the following functions, methods, classes and modules is shown
# in this example:
import matplotlib
matplotlib.axes.Axes.axhline
matplotlib.axes.Axes.axvline
matplotlib.pyplot.axhline
matplotlib.pyplot.axvline
matplotlib.axes.Axes.set_facecolor
matplotlib.figure.Figure.suptitle
|
