# How to add one colobar that will display data from two different sub-boards

What I want to do is add one colored bar (to the right of the image shown below) that will show a colored bar for both subplots (they are in the same scale).

Another thing doesn't make sense to me: why the lines I'm trying to do at the end of the code aren't drawn (they should be horizontal lines in the center of both graphs)

Thanks for the help.

Here is the code:

`````` 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')

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')
```

```

And here is this figure:

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Basically figure.colorbar () is good for both images as long as they don't have too different scales. So you can let matplotlib do it for you ... or you can manually position your color wheel along the axes inside the images. Here's how to control the position 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()

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)
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()
```

```

Note that you can position ax3 however you want from the side, top, where ever, as long as it is within the bounds of the shape.

I don't know why your 2D line is not showing up.

I added the following to my code before plt.show () and that's it:

``````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)])

## 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)
```

```

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