在Matlab中，Python等价于“hold on”。

Is there an explicit equivalent command in Python's matplotlib for Matlab's hold on? I'm trying to plot all my graphs on the same axes. Some graphs are generated inside a for loop, and these are plotted separately from su and sl:

在Python的matplotlib中是否有一个明确的等效命令用于Matlab的控制?我要把所有的图都画在同一个坐标轴上。在for循环中生成了一些图，这些图分别从su和sl中绘制出来:

import numpy as np
import matplotlib.pyplot as plt

for i in np.arange(1,5):
    z = 68 + 4 * np.random.randn(50)
    zm = np.cumsum(z) / range(1,len(z)+1)
    plt.plot(zm)
    plt.axis([0,50,60,80])

plt.show()

n = np.arange(1,51)
su = 68 + 4 / np.sqrt(n)
sl = 68 - 4 / np.sqrt(n)

plt.plot(n,su,n,sl)

plt.axis([0,50,60,80])
plt.show()

4 个解决方案

#1

Just call plt.show() at the end:

就叫plt.show()在结尾:

import numpy as np
import matplotlib.pyplot as plt

plt.axis([0,50,60,80])
for i in np.arange(1,5):
    z = 68 + 4 * np.random.randn(50)
    zm = np.cumsum(z) / range(1,len(z)+1)
    plt.plot(zm)    

n = np.arange(1,51)
su = 68 + 4 / np.sqrt(n)
sl = 68 - 4 / np.sqrt(n)

plt.plot(n,su,n,sl)

plt.show()

#2

You can use the following:

你可以使用以下方法:

plt.hold(True)

#3

The hold on feature is switched on by default in matplotlib.pyplot. So each time you evoke plt.plot() before plt.show() a drawing is added to the plot. Launching plt.plot() after the function plt.show() leads to redrawing the whole picture.

在matplotlib.pyplot中，默认情况下打开了对feature的保留。所以每次你唤起plt.plot()的时候，就会把画加到图中。启动plt.plot()后，函数plt.show()会导致重新绘制整个图像。

#4

check pyplot docs. For completeness,

检查pyplot文档。出于完整性的考虑,

import numpy as np
import matplotlib.pyplot as plt

#evenly sampled time at 200ms intervals
t = np.arange(0., 5., 0.2)

# red dashes, blue squares and green triangles
plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')
plt.show()

#1