Matplotlib 2子图,1色条,如何实现?

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我花了很长时间研究如何在Matplotlib中得到两个子图来共享同一个y轴,其中两个色条共享一个。

这是我的代码:

from __future__ import division
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import patches
from matplotlib.ticker import NullFormatter

# SIS Functions
TE = 1 # Einstein radius
g1 = lambda x,y: (TE/2) * (y**2-x**2)/((x**2+y**2)**(3/2)) 
g2 = lambda x,y: -1*TE*x*y / ((x**2+y**2)**(3/2))
kappa = lambda x,y: TE / (2*np.sqrt(x**2+y**2))

coords = np.linspace(-2,2,400)
X,Y = np.meshgrid(coords,coords)
g1out = g1(X,Y)
g2out = g2(X,Y)
kappaout = kappa(X,Y)
for i in range(len(coords)):
    for j in range(len(coords)):
        if np.sqrt(coords[i]**2+coords[j]**2) <= TE:
            g1out[i][j]=0
            g2out[i][j]=0

fig = plt.figure()
fig.subplots_adjust(wspace=0,hspace=0)

# subplot number 1
ax1 = fig.add_subplot(1,2,1,aspect='equal',xlim=[-2,2],ylim=[-2,2])
plt.title(r"$\gamma_{1}$",fontsize="18")
plt.xlabel(r"x ($\theta_{E}$)",fontsize="15")
plt.ylabel(r"y ($\theta_{E}$)",rotation='horizontal',fontsize="15")
plt.xticks([-2.0,-1.5,-1.0,-0.5,0,0.5,1.0,1.5])
plt.xticks([-2.0,-1.5,-1.0,-0.5,0,0.5,1.0,1.5])
plt.imshow(g1out,extent=(-2,2,-2,2))
plt.axhline(y=0,linewidth=2,color='k',linestyle="--")
plt.axvline(x=0,linewidth=2,color='k',linestyle="--")
e1 = patches.Ellipse((0,0),2,2,color='white')
ax1.add_patch(e1)

# subplot number 2
ax2 = fig.add_subplot(1,2,2,sharey=ax1,xlim=[-2,2],ylim=[-2,2])
plt.title(r"$\gamma_{2}$",fontsize="18")
plt.xlabel(r"x ($\theta_{E}$)",fontsize="15")
ax2.yaxis.set_major_formatter( NullFormatter() )
plt.axhline(y=0,linewidth=2,color='k',linestyle="--")
plt.axvline(x=0,linewidth=2,color='k',linestyle="--")
plt.imshow(g2out,extent=(-2,2,-2,2))
e2 = patches.Ellipse((0,0),2,2,color='white')
ax2.add_patch(e2)

# subplot for colorbar
ax3 = fig.add_subplot(1,1,1)
ax3.axis('off')
cbar = plt.colorbar(ax=ax2)

plt.show()
提问于
用户回答回答于

只需将颜色条放在自己的轴上,然后使用subplots_adjust为它腾出空间。

作为一个简单的例子:

import numpy as np
import matplotlib.pyplot as plt

fig, axes = plt.subplots(nrows=2, ncols=2)
for ax in axes.flat:
    im = ax.imshow(np.random.random((10,10)), vmin=0, vmax=1)

fig.subplots_adjust(right=0.8)
cbar_ax = fig.add_axes([0.85, 0.15, 0.05, 0.7])
fig.colorbar(im, cax=cbar_ax)

plt.show()

用户回答回答于

import numpy as np
import matplotlib.pyplot as plt

fig, axes = plt.subplots(nrows=2, ncols=2)
for ax in axes.flat:
    im = ax.imshow(np.random.random((10,10)), vmin=0, vmax=1)

fig.colorbar(im, ax=axes.ravel().tolist())

plt.show()

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