Matplotlib 2个子图，1个颜色条 [英] Matplotlib 2 Subplots, 1 Colorbar

问题描述

我花了很长时间研究如何在Matplotlib中使用两个颜色共享的单个颜色条来使两个子图共享相同的y轴.

I've spent entirely too long researching how to get two subplots to share the same y-axis with a single colorbar shared between the two in Matplotlib.

发生的事情是，当我在subplot1或subplot2中调用colorbar()函数时，它将自动缩放绘图，以使颜色栏和绘图可以放入子绘图"边界框内，从而导致两个并排图的大小是两个非常不同的.

What was happening was that when I called the colorbar() function in either subplot1 or subplot2, it would autoscale the plot such that the colorbar plus the plot would fit inside the 'subplot' bounding box, causing the two side-by-side plots to be two very different sizes.

为了解决这个问题，我尝试创建第三个子图，然后黑客入侵它，仅用一个色条就不渲染任何图. 唯一的问题是，现在两个图的高度和宽度是不均匀的，我不知道如何使它看起来还不错.

To get around this, I tried to create a third subplot which I then hacked to render no plot with just a colorbar present. The only problem is, now the heights and widths of the two plots are uneven, and I can't figure out how to make it look okay.

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()

推荐答案

只需将颜色栏放置在其自己的轴上，并使用subplots_adjust为其留出空间.

Just place the colorbar in its own axis and use subplots_adjust to make room for it.

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()

请注意，即使值的范围由vmin和vmax设置，颜色范围也将由最后绘制的图像(引起im)设置.例如，如果另一个图的最大值更高，则比im的最大值更高的点将以统一的颜色显示.

Note that the color range will be set by the last image plotted (that gave rise to im) even if the range of values is set by vmin and vmax. If another plot has, for example, a higher max value, points with higher values than the max of im will show in uniform color.

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