『Python』matplotlib共享绘图区域坐标轴

1. 共享单一绘图区域的坐标轴

有时候，我们想将多张图形放在同一个绘图区域，不想在每个绘图区域只绘制一幅图形。这时候，就可以借助共享坐标轴的方法实现在一个绘图区域绘制多幅图形的目的。

import numpy as np

import matplotlib.pyplot as plt

import matplotlib as mpl

mpl.use('Qt5Agg')

mpl.rcParams['font.sans-serif'] = ['SimHei']

mpl.rcParams['font.serif'] = ['SimHei']

mpl.rcParams['axes.unicode_minus'] = False  # 解决保存图像是负号'-'显示为方块的问题,或者转换负号为字符串

fig, ax1 = plt.subplots()

t = np.arange(0.05, 10., 0.01)

s1 = np.exp(t)

ax1.plot(t, s1, c="b", ls="-")

ax1.set_xlabel("x坐标轴")

ax1.set_ylabel("以e为底的指数", color="b")

ax1.tick_params("y", colors="b")

ax2 = ax1.twinx()

s2 = np.cos(t ** 2)

ax2.plot(t, s2, c="r", ls=":")

ax2.set_ylabel("余弦函数", color="r")

ax2.tick_params("y", colors="r")

plt.show()

同样可以用twiny()方法共享y轴

2. 共享不同子区绘图区域的坐标轴

subplots()函数有两个命名关键字参数sharex和sharey，有四种取值

'row'
'col'
'all'，等同于True
'none'，等同于False

import numpy as np

import matplotlib.pyplot as plt

import matplotlib as mpl

mpl.use('Qt5Agg')

mpl.rcParams['font.sans-serif'] = ['SimHei']

mpl.rcParams['font.serif'] = ['SimHei']

mpl.rcParams['axes.unicode_minus'] = False  # 解决保存图像是负号'-'显示为方块的问题,或者转换负号为字符串

x1 = np.linspace(0, 2 * np.pi, 400)

y1 = np.cos(x1 ** 2)

x2 = np.linspace(0.01, 10, 100)

y2 = np.sin(x2)

x3 = np.random.rand(100)

y3 = np.linspace(0, 3, 100)

x4 = np.arange(0, 6, 0.5)

y4 = np.power(x4, 3)

fig, ax = plt.subplots(2, 2)

ax1 = ax[0, 0]

ax1.plot(x1, y1)

ax2 = ax[0, 1]

ax2.plot(x2, y2)

ax3 = ax[1, 0]

ax3.scatter(x3, y3)

ax4 = ax[1, 1]

ax4.scatter(x4, y4)

plt.show()

基本图形如图所示：

sharex='all'

sharex='none'

sharex='row'

sharex='col'

sharey类似

将共享坐标轴的子区之间的空隙去掉

import numpy as np

import matplotlib.pyplot as plt

import matplotlib as mpl

mpl.use('Qt5Agg')

mpl.rcParams['font.sans-serif'] = ['SimHei']

mpl.rcParams['font.serif'] = ['SimHei']

mpl.rcParams['axes.unicode_minus'] = False  # 解决保存图像是负号'-'显示为方块的问题,或者转换负号为字符串

x1 = np.linspace(0, 2 * np.pi, 400)

y1 = np.cos(x1 ** 2)

x2 = np.linspace(0.01, 10, 100)

y2 = np.sin(x2)

x3 = np.random.rand(100)

y3 = np.linspace(0, 3, 100)

x4 = np.arange(0, 6, 0.5)

y4 = np.power(x4, 3)

fig, ax = plt.subplots(2, 2, sharex='all', sharey='all')

fig.subplots_adjust(hspace=0, wspace=0)

ax1 = ax[0, 0]

ax1.plot(x1, y1)

ax2 = ax[0, 1]

ax2.plot(x2, y2)

ax3 = ax[1, 0]

ax3.scatter(x3, y3)

ax4 = ax[1, 1]

ax4.scatter(x4, y4)

plt.show()

3. 共享个别子区绘图区域的坐标轴

import numpy as np

import matplotlib.pyplot as plt

import matplotlib as mpl

mpl.use('Qt5Agg')

mpl.rcParams['font.sans-serif'] = ['SimHei']

mpl.rcParams['font.serif'] = ['SimHei']

mpl.rcParams['axes.unicode_minus'] = False  # 解决保存图像是负号'-'显示为方块的问题,或者转换负号为字符串

x1 = np.linspace(0, 2 * np.pi, 400)

y1 = np.cos(x1 ** 2)

x2 = np.linspace(0.01, 10, 100)

y2 = np.sin(x2)

x3 = np.random.rand(100)

y3 = np.linspace(0, 3, 100)

x4 = np.arange(0, 6, 0.5)

y4 = np.power(x4, 3)

fig, ax = plt.subplots(2, 2)

ax1 = plt.subplot(221)

ax1.plot(x1, y1)

ax2 = plt.subplot(222)

ax2.plot(x2, y2)

ax3 = plt.subplot(223)

ax3.scatter(x3, y3)

ax4 = plt.subplot(224, sharex=ax1)

ax4.scatter(x4, y4)

plt.show()

4. 优化坐标轴范围显示

plt.autoscale(enable=True, axis="both", tight=True)

巴特西

『Python』matplotlib共享绘图区域坐标轴

1. 共享单一绘图区域的坐标轴

2. 共享不同子区绘图区域的坐标轴

3. 共享个别子区绘图区域的坐标轴

4. 优化坐标轴范围显示

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