如何添加单个colobar来显示来自2个不同子图的数据 [英] How to add a single colobar that will show the data from 2 different subplot

问题描述

我想要做的是添加一个颜色条(在下图的右侧)，它将显示两个子图的颜色条(它们的比例相同).

What i wanna do is adding a single colorbar (at the right side of the figure shown below), that will show the colorbar for both subplots (they are at the same scale).

另一件事对我来说没有意义是为什么我尝试在代码末尾绘制的线没有绘制(它们应该是两个图中心的水平线)

Another thing doesn't really make sense for me is why the lines I try to draw on the end of the code are not drawn (they are supposed to be horizontal lines on the center of both plots)

感谢您的帮助.

下面是代码:

 idx=0
b=plt.psd(dOD[:,idx],Fs=self.fs,NFFT=512)
B=np.zeros((2*len(self.Chan),len(b[0])))
B[idx,:]=20*log10(b[0])

c=plt.psd(dOD_filt[:,idx],Fs=self.fs,NFFT=512)
C=np.zeros((2*len(self.Chan),len(b[0])))
C[idx,:]=20*log10(c[0])

for idx in range(2*len(self.Chan)):
    b=plt.psd(dOD[:,idx],Fs=self.fs,NFFT=512)
    B[idx,:]=20*log10(b[0])

    c=plt.psd(dOD_filt[:,idx],Fs=self.fs,NFFT=512)
    C[idx,:]=20*log10(c[0])

## Calculate the color scaling for the imshow()    
aux1 = max(max(B[i,:]) for i in range(size(B,0)))
aux2 = min(min(B[i,:]) for i in range(size(B,0)))
bux1 = max(max(C[i,:]) for i in range(size(C,0)))
bux2 = min(min(C[i,:]) for i in range(size(C,0)))
scale1 = 0.75*max(aux1,bux1)
scale2 = 0.75*min(aux2,bux2)


fig, axes = plt.subplots(nrows=2, ncols=1,figsize=(7,7))#,sharey='True')
fig.subplots_adjust(wspace=0.24, hspace=0.35)

ii=find(c[1]>=frange)[0]
## Making the plots
cax=axes[0].imshow(B, origin = 'lower',vmin=scale2,vmax=scale1)
axes[0].set_ylim((0,2*len(self.Chan)))
axes[0].set_xlabel(' Frequency (Hz) ')
axes[0].set_ylabel(' Channel Number ') 
axes[0].set_title('Pre-Filtered')
cax2=axes[1].imshow(C, origin = 'lower',vmin=scale2,vmax=scale1)
axes[1].set_ylim(0,2*len(self.Chan))
axes[1].set_xlabel(' Frequency (Hz) ')
axes[1].set_ylabel(' Channel Number ')
axes[1].set_title('Post-Filtered')

axes[0].annotate('690nm', xy=((ii+1)/2, len(self.Chan)/2-1), 
        xycoords='data', va='center', ha='right')
axes[0].annotate('830nm', xy=((ii+1)/2, len(self.Chan)*3/2-1 ), 
        xycoords='data', va='center', ha='right')
axes[1].annotate('690nm', xy=((ii+1)/2, len(self.Chan)/2-1), 
        xycoords='data', va='center', ha='right')
axes[1].annotate('830nm', xy=((ii+1)/2, len(self.Chan)*3/2-1 ), 
        xycoords='data', va='center', ha='right')


axes[0].axis('tight')
axes[1].axis('tight')


## Set up the xlim to aprox frange Hz
axes[0].set_xlim(left=0,right=ii)
axes[1].set_xlim(left=0,right=ii)

## Make the xlabels become the actual frequency number
ticks = linspace(0,ii,10)
tickslabel = linspace(0.,frange,10)
for i in range(10):
    tickslabel[i]="%.1f" % tickslabel[i]
axes[0].set_xticks(ticks)
axes[0].set_xticklabels(tickslabel)
axes[1].set_xticks(ticks)
axes[1].set_xticklabels(tickslabel)

## Draw a line to separate the two different wave lengths, and name each region
l1 = Line2D([0,frange],[28,28],ls='-',color='black')
axes[0].add_line(l1)
axes[1].add_line(l1)    

这是它的图形:

如果需要更多信息，请问.

If any more info are needed, just ask.

推荐答案

基本上， figure.colorbar() 对两种图像都适用，只要它们的比例不会太大.因此，您可以让matplotlib为您做这件事...，也可以将颜色条手动放置在图像内的轴上.下面是如何控制颜色条的位置:

Basically, figure.colorbar() is good for both images, as long as their are not with too different scales. So you could let matplotlib do it for you... or you manually position your colorbar on axes inside the images. Here is how to control the location of the colorbar:

import numpy as np
from matplotlib import pyplot as plt

A = np.random.random_integers(0, 10, 100).reshape(10, 10)
B = np.random.random_integers(0, 10, 100).reshape(10, 10)

fig = plt.figure()
ax1 = fig.add_subplot(221)
ax2 = fig.add_subplot(222)

mapable = ax1.imshow(A, interpolation="nearest")
cax = ax2.imshow(A, interpolation="nearest")

# set the tickmarks *if* you want cutom (ie, arbitrary) tick labels:
cbar = fig.colorbar(cax, ax=None)

fig = plt.figure(2)
ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)
mapable = ax1.imshow(A, interpolation="nearest")
cax = ax2.imshow(A, interpolation="nearest")
# on the figure total in precent l    b      w , height 
ax3 = fig.add_axes([0.1, 0.1, 0.8, 0.05]) # setup colorbar axes. 
# put the colorbar on new axes
cbar = fig.colorbar(mapable,cax=ax3,orientation='horizontal')

plt.show()

当然，您可以根据需要将ax3放置在侧面，顶部，任何地方，只要在图的边界内.

Note ofcourse you can position ax3 as you wish, on the side, on the top, where ever, as long as it is in the boundaries of the figure.

我不知道为什么你的 line2D 没有出现.

I don't know why your line2D is not appearing.

我在 plt.show() 之前在我的代码中添加了以下内容，一切都在显示:

I added to my code before plt.show() the following and everything is showing:

from mpl_toolkits.axes_grid1 import anchored_artists
from matplotlib.patheffects import withStroke
txt = anchored_artists.AnchoredText("SC",
                                    loc=2,
                                    frameon=False,
                                    prop=dict(size=12))
if withStroke:
    txt.txt._text.set_path_effects([withStroke(foreground="w",
                                               linewidth=3)])
ax1.add_artist(txt)


## Draw a line to separate the two different wave lengths, and name each region
l1 = plt.Line2D([-1,10],[5,5],ls='-',color='black',lineswidth=10)
ax1.add_line(l1)

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