[Python] How to draw multiple graphs with Matplotlib
Display two graphs on the left and right.
import matplotlib.pyplot as plt
import numpy as np
t = np.linspace(-np.pi, np.pi, 1000)
x1 = np.sin(2*t)
x2 = np.cos(2*t)
fig, (axL, axR) = plt.subplots(ncols=2, figsize=(10,4))
axL.plot(t, x1, linewidth=2)
axL.set_title('sin')
axL.set_xlabel('t')
axL.set_ylabel('x')
axL.set_xlim(-np.pi, np.pi)
axL.grid(True)
axR.plot(t, x2, linewidth=2)
axR.set_title('cos')
axR.set_xlabel('t')
axR.set_ylabel('x')
axR.set_xlim(-np.pi, np.pi)
axR.grid(True)
fig.show()
Axis Share
When displaying multiple graphs, Share can be used when it is troublesome to set the X-axis settings for all graphs. Just set sharex = True as an argument to subplots. Ai
share available
import matplotlib.pyplot as plt
import numpy as np
t = np.linspace(-np.pi*2, np.pi*2, 1000)
x1 = np.sin(2*t)
x2 = np.cos(2*t)
fig, (axL, axR) = plt.subplots(ncols=2, figsize=(10,4), sharex=True)
axL.plot(t, x1, linewidth=2)
axL.set_title('sin')
axL.set_xlabel('t')
axL.set_ylabel('x')
axL.set_xlim(-np.pi, np.pi)
axL.grid(True)
axR.plot(t, x2, linewidth=2)
axR.set_title('cos')
axR.set_xlabel('t')
axR.set_ylabel('x')
axR.grid(True)
fig.show()
no share
Make it a little complicated.
If you want to display two graphs normally in the first column and use all the graphs in the second column to display a long graph, you can use subplot2grid as shown below.
import matplotlib.pyplot as plt
import numpy as np
t = np.linspace(-np.pi, np.pi, 1000)
x1 = np.sin(2*t)
x2 = np.cos(2*t)
x3 = x1 + x2
fig = plt.figure(figsize=(10,8))
ax1 = plt.subplot2grid((2,2), (0,0))
ax2 = plt.subplot2grid((2,2), (0,1))
ax3 = plt.subplot2grid((2,2), (1,0), colspan=2)
ax1.plot(t, x1, linewidth=2)
ax1.set_title('sin')
ax1.set_xlabel('t')
ax1.set_ylabel('x')
ax1.set_xlim(-np.pi, np.pi)
ax1.grid(True)
ax2.plot(t, x2, linewidth=2)
ax2.set_title('cos')
ax2.set_xlabel('t')
ax2.set_ylabel('x')
ax2.set_xlim(-np.pi, np.pi)
ax2.grid(True)
ax3.plot(t, x3, linewidth=2)
ax3.set_title('sin+cos')
ax3.set_xlabel('t')
ax3.set_ylabel('x')
ax3.set_xlim(-np.pi, np.pi)
ax3.grid(True)
fig.show()
Another option is to use matplotlib.gridspec.
In this case, specify the used part of the 2D array obtained by gridspec.Gridspec (xxx, yyy) and use it as an argument of subplot.
For example, if you want to use the top left
gs = gridspec.GridSpec(2,2)
ax1 = plt.subplot(gs[0,0])
Will be.
Also, if you want to use the entire first row,
ax2 = plt.subplot(gs[1,:])
Will be.
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import numpy as np
t = np.linspace(-np.pi, np.pi, 1000)
x1 = np.sin(2*t)
x2 = np.cos(2*t)
x3 = x1 + x2
fig = plt.figure(figsize=(10,8))
gs = gridspec.GridSpec(2,2)
ax1 = plt.subplot(gs[0,0])
ax2 = plt.subplot(gs[0,1])
ax3 = plt.subplot(gs[1,:])
ax1.plot(t, x1, linewidth=2)
ax1.set_title('sin')
ax1.set_xlabel('t')
ax1.set_ylabel('x')
ax1.set_xlim(-np.pi, np.pi)
ax1.grid(True)
ax2.plot(t, x2, linewidth=2)
ax2.set_title('cos')
ax2.set_xlabel('t')
ax2.set_ylabel('x')
ax2.set_xlim(-np.pi, np.pi)
ax2.grid(True)
ax3.plot(t, x3, linewidth=2)
ax3.set_title('sin+cos')
ax3.set_xlabel('t')
ax3.set_ylabel('x')
ax3.set_xlim(-np.pi, np.pi)
ax3.grid(True)
fig.show()
Make a blank with subplots
If there are few graphs for the frame created by subplots, axis ('off') is applied to the area that you do not want to draw.
import matplotlib.pyplot as plt
import numpy as np
t = np.linspace(-np.pi, np.pi, 1000)
x1 = np.sin(2*t)
x2 = np.cos(2*t)
x3 = x1 + x2
fig,axes = plt.subplots(nrows=2,ncols=2,figsize=(10,8))
axes[0,0].plot(t, x1, linewidth=2)
axes[0,0].set_title('sin')
axes[0,0].set_xlabel('t')
axes[0,0].set_ylabel('x')
axes[0,0].set_xlim(-np.pi, np.pi)
axes[0,0].grid(True)
axes[0,1].plot(t, x2, linewidth=2)
axes[0,1].set_title('cos')
axes[0,1].set_xlabel('t')
axes[0,1].set_ylabel('x')
axes[0,1].set_xlim(-np.pi, np.pi)
axes[0,1].grid(True)
axes[1,0].plot(t, x3, linewidth=2)
axes[1,0].set_title('sin+cos')
axes[1,0].set_xlabel('t')
axes[1,0].set_ylabel('x')
axes[1,0].set_xlim(-np.pi, np.pi)
axes[1,0].grid(True)
axes[1,1].axis('off')
I referred to the following http://matplotlib.org/examples/pylab_examples/subplots_demo.html http://matplotlib.org/users/recipes.html
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