matplotlib 创建两个子图,每个子图具有两个y轴

fzwojiic  于 2023-10-24  发布在  其他
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This matplotlib tutorial显示如何创建具有两个y轴(两种不同比例)的图:

import numpy as np
import matplotlib.pyplot as plt

def two_scales(ax1, time, data1, data2, c1, c2):

    ax2 = ax1.twinx()

    ax1.plot(time, data1, color=c1)
    ax1.set_xlabel('time (s)')
    ax1.set_ylabel('exp')

    ax2.plot(time, data2, color=c2)
    ax2.set_ylabel('sin')
    return ax1, ax2

# Create some mock data
t = np.arange(0.01, 10.0, 0.01)
s1 = np.exp(t)
s2 = np.sin(2 * np.pi * t)

# Create axes
fig, ax = plt.subplots()
ax1, ax2 = two_scales(ax, t, s1, s2, 'r', 'b')

# Change color of each axis
def color_y_axis(ax, color):
    """Color your axes."""
    for t in ax.get_yticklabels():
        t.set_color(color)
    return None

color_y_axis(ax1, 'r')
color_y_axis(ax2, 'b')
plt.show()

结果如下:

我的问题是:你如何修改代码来创建两个像这样的子图,只是水平对齐?

fig, ax = plt.subplots(1,2,figsize=(15, 8))
plt.subplot(121)
###plot something here
plt.subplot(122)
###plot something here

但是,如何确保创建轴时调用的fig, ax = plt.subplots()不会与创建水平对齐画布时调用的fig, ax = plt.subplots(1,2,figsize=(15, 8))冲突呢?

eqoofvh9

eqoofvh91#

您将创建两个子图fig, (ax1, ax2) = plt.subplots(1,2),并将two_scales应用于每个子图。

import numpy as np
import matplotlib.pyplot as plt

def two_scales(ax1, time, data1, data2, c1, c2):
    ax2 = ax1.twinx()
    ax1.plot(time, data1, color=c1)
    ax1.set_xlabel('time (s)')
    ax1.set_ylabel('exp')
    ax2.plot(time, data2, color=c2)
    ax2.set_ylabel('sin')
    return ax1, ax2

# Create some mock data
t = np.arange(0.01, 10.0, 0.01)
s1 = np.exp(t)
s2 = np.sin(2 * np.pi * t)

# Create axes
fig, (ax1, ax2) = plt.subplots(1,2, figsize=(10,4))
ax1, ax1a = two_scales(ax1, t, s1, s2, 'r', 'b')
ax2, ax2a = two_scales(ax2, t, s1, s2, 'gold', 'limegreen')

# Change color of each axis
def color_y_axis(ax, color):
    """Color your axes."""
    for t in ax.get_yticklabels():
        t.set_color(color)

color_y_axis(ax1, 'r')
color_y_axis(ax1a, 'b')
color_y_axis(ax2, 'gold')
color_y_axis(ax2a, 'limegreen')

plt.tight_layout()
plt.show()

o7jaxewo

o7jaxewo2#

这就是你想要的吗

[...]
# Create some mock data
t = np.arange(0.01, 10.0, 0.01)
s1 = np.exp(t)
s2 = np.sin(2 * np.pi * t)

# Create axes
ax = plt.subplot(2,2,1)
ax1, ax2 = two_scales(ax, t, s1, s2, 'r', 'b')

ax = plt.subplot(2,2,2)
ax1, ax2 = two_scales(ax, t, s1, s2, 'r', 'b')
[...]

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