1.绘制多个子图

fig, axs = plt.subplots(2, 2)
axs[0, 0].plot(x, y)
axs[0, 0].set_title('Axis [0, 0]')
axs[0, 1].plot(x, y, 'tab:orange')
axs[0, 1].set_title('Axis [0, 1]')
axs[1, 0].plot(x, -y, 'tab:green')
axs[1, 0].set_title('Axis [1, 0]')
axs[1, 1].plot(x, -y, 'tab:red')
axs[1, 1].set_title('Axis [1, 1]')

for ax in axs.flat:
    ax.set(xlabel='x-label', ylabel='y-label')

# Hide x labels and tick labels for top plots and y ticks for right plots.
for ax in axs.flat:
    ax.label_outer()

多个子图共享坐标轴：fig, axs = plt.subplots(3, sharex=True, sharey=True)
参考资料：https://matplotlib.org/stable/gallery/subplots_axes_and_figures/subplots_demo.html

2.设置子图间距fig.subplots_adjust(hspace=0.5)

import numpy as np
import matplotlib.pyplot as plt


fig, (ax1, ax2) = plt.subplots(2, 1)
# make a little extra space between the subplots
fig.subplots_adjust(hspace=0.5)

dt = 0.01
t = np.arange(0, 30, dt)

# Fixing random state for reproducibility
np.random.seed(19680801)


nse1 = np.random.randn(len(t))                 # white noise 1
nse2 = np.random.randn(len(t))                 # white noise 2
r = np.exp(-t / 0.05)

cnse1 = np.convolve(nse1, r, mode='same') * dt   # colored noise 1
cnse2 = np.convolve(nse2, r, mode='same') * dt   # colored noise 2

# two signals with a coherent part and a random part
s1 = 0.01 * np.sin(2 * np.pi * 10 * t) + cnse1
s2 = 0.01 * np.sin(2 * np.pi * 10 * t) + cnse2

ax1.plot(t, s1, t, s2)
ax1.set_xlim(0, 5)
ax1.set_xlabel('time')
ax1.set_ylabel('s1 and s2')
ax1.grid(True)

cxy, f = ax2.csd(s1, s2, 256, 1. / dt)
ax2.set_ylabel('CSD (db)')
plt.show()

参考资料：https://matplotlib.org/stable/gallery/lines_bars_and_markers/csd_demo.html#sphx-glr-gallery-lines-bars-and-markers-csd-demo-py
3.Labelling subplots每个子图设置label
方法一：subplot_mosaic()函数创建

fig, axd = plt.subplot_mosaic([['upper left', 'upper right'],
                               ['lower left', 'lower right']],
                              figsize=(5.5, 3.5), constrained_layout=True)
for k in axd:
    annotate_axes(axd[k], f'axd["{k}"]', fontsize=14)
fig.suptitle('plt.subplot_mosaic()')

方法二：annotate（）

import matplotlib.pyplot as plt
import numpy as np

fig, axs = plt.subplots(ncols=2, nrows=2, figsize=(5.5, 3.5),
                        constrained_layout=True)
# add an artist, in this case a nice label in the middle...
for row in range(2):
    for col in range(2):
        axs[row, col].annotate(f'axs[{row}, {col}]', (0.5, 0.5),
                               transform=axs[row, col].transAxes,
                               ha='center', va='center', fontsize=18,
                               color='darkgrey')
fig.suptitle('plt.subplots()')

参考资料：https://matplotlib.org/devdocs/tutorials/intermediate/arranging_axes.html#sphx-glr-tutorials-intermediate-arranging-axes-py

4.自动调整分布情况：Self-regulating distribution
使用方法：

fig, axs = plt.subplots(ncols=2, nrows=2, figsize=(5.5, 3.5),
                        constrained_layout=True)

5.绘图坐标系之间的关系
https://blog.csdn.net/sinat_32570141/article/details/113048947