Python子图不能正常工作

Question

我试图在一个图中的三个子图中绘制三个不同的图。另外，我希望第一个数字的宽度是其他两个。因此我使用了

gs = gridspec.GridSpec(2, 2, width_ratios=[2,1], height_ratios=[1,1])

但是输出的所有数字都是在ax3上绘制的。

我的代码在这里给出

import matplotlib
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import matplotlib.gridspec as gridspec

gs = gridspec.GridSpec(2, 2, width_ratios=[2,1], height_ratios=[1,1])
ax1=plt.subplot(gs[:,:-1])
ax2=plt.subplot(gs[:-1,-1])
ax3=plt.subplot(gs[-1,-1])


# ax 1
X=np.linspace(0,10,100)
Y=np.sin(X)
ax1 = plt.gca()
ax1.scatter(X, Y)
ax1.axis("tight")
ax1.set_title('ax1')
ax1.set_xlim([0,10])
ax1.set_ylim([-1,1])
plt.xticks([])
plt.yticks([])


# ax 2
ax2 = plt.gca()
vel=np.random.rand(1000)
n, bins, patches = plt.hist(vel, 10, normed=True, histtype='stepfilled', facecolor='green', alpha=1.0)
ax2.set_title('Velocity Distribution')
ax2.axis("tight")
plt.xticks([0,0.05,0.10])
plt.yticks([0,10,20])


# ax 3
Z=np.exp(X)
ax3.plot(X,Z,'red',lw=5)

plt.show()

有人可以告诉我如何纠正这个问题。提前谢谢。

Answer 1

修正了几行。请与您的代码进行比较。

import matplotlib
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import matplotlib.gridspec as gridspec


gs = gridspec.GridSpec(2, 2, width_ratios=[2,1], height_ratios=[1,1])
ax1=plt.subplot(gs[:,:-1])
ax2=plt.subplot(gs[:-1,-1])
ax3=plt.subplot(gs[-1,-1])


# ax 1
X=np.linspace(0,10,100)
Y=np.sin(X)
#ax1 = plt.gca()
ax1.scatter(X, Y)
ax1.axis("tight")
ax1.set_title('ax1')
ax1.set_xlim([0,10])
ax1.set_ylim([-1,1])
# You can use ax1.set_xticks() and ax1.set_xticklabels() instead.
ax1.set_xticks([])
ax1.set_yticks([])
#plt.xticks([])
#plt.yticks([])


# ax 2
#ax2 = plt.gca()
vel=np.random.rand(1000)
n, bins, patches = ax2.hist(vel, 10, normed=True, histtype='stepfilled', facecolor='green', alpha=1.0)
ax2.set_title('Velocity Distribution')
ax2.axis("tight")
# You can use ax2.set_xticks() and ax2.set_xticklabels() instead.
ax2.set_xticks([0,0.5,1])
ax2.set_yticks([0,1,2])
#plt.xticks([0,0.05,0.10])
#plt.yticks([0,10,20])


# ax 3
Z=np.exp(X)
ax3.plot(X, Z,'red', lw=5)
# You can use ax3.set_xticks() and ax3.set_xticklabels() instead.
ax3.set_xticks([0, 5, 10])
ax3.set_yticks([0, 10000, 20000])
ax3.set_yticklabels(['0', '10K', '20K'])

plt.show()