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
:
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()
This question is related to
python
matlab
graph
matplotlib
check pyplot
docs. For completeness,
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()
You can use the following:
plt.hold(True)
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.
Source: Stackoverflow.com