如何使用 Python 并排绘制两个图？
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How to make two plots side-by-side using Python?
提问by Hei?enberg93
I found the following example on matplotlib:
我在 matplotlib 上找到了以下示例：
import numpy as np
import matplotlib.pyplot as plt
x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 2.0)
y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
y2 = np.cos(2 * np.pi * x2)
plt.subplot(2, 1, 1)
plt.plot(x1, y1, 'ko-')
plt.title('A tale of 2 subplots')
plt.ylabel('Damped oscillation')
plt.subplot(2, 1, 2)
plt.plot(x2, y2, 'r.-')
plt.xlabel('time (s)')
plt.ylabel('Undamped')
plt.show()
My question is: What do i need to change, to have the plots side-by-side?
我的问题是：我需要改变什么，让这些情节并排？
回答by Jonathan Eunice
Change your subplot settings to:
将您的子图设置更改为：
plt.subplot(1, 2, 1)
...
plt.subplot(1, 2, 2)
The parameters for subplotare: number of rows, number of columns, and which subplot you're currently on. So 1, 2, 1means "a 1-row, 2-column figure: go to the first subplot." Then 1, 2, 2means "a 1-row, 2-column figure: go to the second subplot."
参数为subplot：行数、列数以及您当前所在的子图。所以1, 2, 1意思是“一个 1 行 2 列的图形：转到第一个子图。” 然后1, 2, 2表示“一个 1 行 2 列的图形：转到第二个子图。”
You currently are asking for a 2-row, 1-column (that is, one atop the other) layout. You need to ask for a 1-row, 2-column layout instead. When you do, the result will be:
您目前要求 2 行 1 列（即一个在另一个之上）布局。您需要改为要求 1 行 2 列布局。当你这样做时，结果将是：
In order to minimize the overlap of subplots, you might want to kick in a:
为了最大限度地减少子图的重叠，您可能需要启动：
plt.tight_layout()
before the show. Yielding:
演出前。产量：
回答by busybear
Check this page out: http://matplotlib.org/examples/pylab_examples/subplots_demo.html
查看此页面：http: //matplotlib.org/examples/pylab_examples/subplots_demo.html
plt.subplotsis similar. I think it's better since it's easier to set parameters of the figure. The first two arguments define the layout (in your case 1 row, 2 columns), and other parameters change features such as figure size:
plt.subplots类似。我认为它更好，因为设置图形参数更容易。前两个参数定义布局（在您的情况下为 1 行 2 列），其他参数用于更改图形大小等功能：
import numpy as np
import matplotlib.pyplot as plt
x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 2.0)
y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
y2 = np.cos(2 * np.pi * x2)
fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(5, 3))
axes[0].plot(x1, y1)
axes[1].plot(x2, y2)
fig.tight_layout()
