matplotlib 颜色设置

#!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
@FileName: 颜色
@Time: 2022/11/2,16:20
@Author: Zhang Yixing
"""
import numpy as np
import matplotlib.pyplot as plt

# 自己设定出颜色
prop_cycle = plt.rcParams['axes.prop_cycle']
colors = prop_cycle.by_key()['color']
print(colors) # ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf']

lwbase = plt.rcParams['lines.linewidth']
thin = lwbase / 2
thick = lwbase * 3

# 建一个两行两列的figure，又利用两个for循环画图
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()

下面是图片结果，为了帮助理解，我在图片上加了ax信息

参考资料