 # Dual Y-Axes on Imshow

Jason Stone, on 2011-02-18 14:39, wrote:

Good afternoon all,

``````    > One last matplotlib question for the group for today.  On
``````

one of my GUI

``````    > plots, I'm calling imshow on an array of data (to display
``````

it in the same way

``````    > MATLAB's imagesc command does).  I'd like to add a second
``````

y-axis to the

``````    > right side of the plot that is completely dependent on the
``````

values on the

``````    > primary y-axis.  Essentially, for each y-axis tick point,
``````

I’ll put the

``````    > y-axis 'value' into a formula and then put the result on
``````

the second y-axis.

``````    >  I did this in MATLAB by essentially overlaying a second
``````

set of axes over

``````    > the plot, but I haven't found the exact way to do it with
``````

matplotlib yet.

``````    >  I've seen a few examples online, but they all use the
``````

second overlaid plot

``````    > to actually plot new data - I wouldn't be doing this.

> Would I need to use the twinx (or twiny) function?

> Are there examples of this on the web that I haven't found
``````

that somebody

``````    > could point me towards?
``````

Hi Jason,

``````here's an example that does what you want, using e^x as the

formula, change the paramter to fmtr to suit your needs:

ax = plt.subplot(1,1,1)

ax.plot(np.sin(np.linspace(0,np.pi)))

ax2 = ax.twinx()

ax2._sharey = ax # share both x and y

fmtr = mpl.ticker.FuncFormatter(lambda x,pos: "%.2f"%np.exp(x))

ax2.yaxis.set_major_formatter(fmtr)

plt.draw()

best,
``````
···

``````  Paul Ivanov

314 address only used for lists,  off-list direct email at:

[http://pirsquared.org](http://pirsquared.org) | GPG/PGP key id:
``````

0x0F3E28F7

``````Paul,

I am currently doing something very similar and was hoping I could
``````

ask for a little clarification. I want to have two y axes where the
ticks are in the same locations and the 2nd y-axis labels are just
twice the 1st y-axis labels. When I implement your example, I don’t
quite understand how to ensure the ticks are at the same locations.
Also, when the data changes to a new image, the 1st y-axis updates
but the 2nd y-axis does not. Is there a convenient way to force both
to update each time, or does the figure need to be cleared and
essentially built from scratch each time.

``````for example, with the following code:

import numpy as np

import matplotlib

import matplotlib.colorbar as cb

import matplotlib.pyplot as plt

y = np.reshape(np.arange(0, 1000000, 1), (20000, 50))

test = 'hot'

f1 = plt.figure(1)

f1.patch.set_facecolor('#c0c0c0')

ax1 = f1.add_axes([0.09, 0.15, 0.82, 0.80])

axc = f1.add_axes([0.09, 0.05, 0.82, 0.05])

im1 = ax1.imshow(y, cmap=test, aspect='auto', origin='lower')

cb.Colorbar(axc, im1, orientation='horizontal')

ax2 = ax1.twinx()

ax2._sharey = ax1 # share both x and y

fmtr = matplotlib.ticker.FuncFormatter(lambda x,pos:
``````

“%.2f”%np.exp(x))

``````ax2.yaxis.set_major_formatter(fmtr)

plt.show()

The ticks on the right are obviously at different locations compared
``````

to the left ticks. Also, if imshow was to be called a new array of
data, the ticks on the right would remain the same. So is there an
easy way to force the locations to be the same, and is there an easy
way force the right y-axis to update each time? Thank you very much

``````-Thomas

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``````

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``````Real-Time with Splunk. Collect, index and harness all the fast
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moving IT data

``````generated by your applications, servers and devices whether
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``````

For this to work correctly, you need to manually keep two axes in sync
(you can use a callback). Also note that this approach cannot be used

Another way is to use axes_grid1 toolkit.
Here is the modified version of your script w/ axes_grid1.

Regards,

-JJ

import numpy as np
import matplotlib
import matplotlib.colorbar as cb
import matplotlib.pyplot as plt

y = np.reshape(np.arange(0, 1000000, 1), (20000, 50))
test = 'hot'
f1 = plt.figure(1)
f1.patch.set_facecolor('#c0c0c0')

import mpl_toolkits.axes_grid1 as axes_grid1
# use axes_grid1.host_axes
ax1 = axes_grid1.host_axes([0.09, 0.15, 0.82, 0.80])

axc = f1.add_axes([0.09, 0.05, 0.82, 0.05])
im1 = ax1.imshow(y, cmap=test, aspect='auto', origin='lower')
cb.Colorbar(axc, im1, orientation='horizontal')

# use twin() not twinx()
ax2 = ax1.twin()
# make ticklabels on the top invisible
ax2.axis["top"].toggle(ticklabels=False)

fmtr = matplotlib.ticker.FuncFormatter(lambda x,pos: "%.2f"% (x*2,))
ax2.yaxis.set_major_formatter(fmtr)
plt.show()

···

On Sat, Mar 12, 2011 at 9:01 AM, Thomas Brezinski <thomasb@...2544...> wrote:

Jason Stone, on 2011-02-18 14:39, wrote:

Good afternoon all,
One last matplotlib question for the group for today. On one of my GUI
plots, I'm calling imshow on an array of data (to display it in the same
way
MATLAB's imagesc command does). I'd like to add a second y-axis to the
right side of the plot that is completely dependent on the values on the
primary y-axis. Essentially, for each y-axis tick point, I'll put the
y-axis 'value' into a formula and then put the result on the second
y-axis.
I did this in MATLAB by essentially overlaying a second set of axes over
the plot, but I haven't found the exact way to do it with matplotlib yet.
I've seen a few examples online, but they all use the second overlaid
plot
to actually plot new data - I wouldn't be doing this.
Would I need to use the twinx (or twiny) function?
Are there examples of this on the web that I haven't found that somebody
could point me towards?

Hi Jason,

here's an example that does what you want, using e^x as the
formula, change the paramter to fmtr to suit your needs:

ax = plt.subplot(1,1,1)
ax.plot(np.sin(np.linspace(0,np.pi)))
ax2 = ax.twinx()
ax2._sharey = ax # share both x and y
fmtr = mpl.ticker.FuncFormatter(lambda x,pos: "%.2f"%np.exp(x))
ax2.yaxis.set_major_formatter(fmtr)
plt.draw()

best,
--
Paul Ivanov
314 address only used for lists, off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7

Paul,
I am currently doing something very similar and was hoping I could ask for a
little clarification. I want to have two y axes where the ticks are in the
same locations and the 2nd y-axis labels are just twice the 1st y-axis
labels. When I implement your example, I don't quite understand how to
ensure the ticks are at the same locations. Also, when the data changes to a
new image, the 1st y-axis updates but the 2nd y-axis does not. Is there a
convenient way to force both to update each time, or does the figure need to
be cleared and essentially built from scratch each time.

for example, with the following code:

import numpy as np
import matplotlib
import matplotlib.colorbar as cb
import matplotlib.pyplot as plt

y = np.reshape(np.arange(0, 1000000, 1), (20000, 50))
test = 'hot'
f1 = plt.figure(1)
f1.patch.set_facecolor('#c0c0c0')
ax1 = f1.add_axes([0.09, 0.15, 0.82, 0.80])
axc = f1.add_axes([0.09, 0.05, 0.82, 0.05])
im1 = ax1.imshow(y, cmap=test, aspect='auto', origin='lower')
cb.Colorbar(axc, im1, orientation='horizontal')
ax2 = ax1.twinx()
ax2._sharey = ax1 # share both x and y
fmtr = matplotlib.ticker.FuncFormatter(lambda x,pos: "%.2f"%np.exp(x))
ax2.yaxis.set_major_formatter(fmtr)
plt.show()

The ticks on the right are obviously at different locations compared to the
left ticks. Also, if imshow was to be called a new array of data, the ticks
on the right would remain the same. So is there an easy way to force the
locations to be the same, and is there an easy way force the right y-axis to
update each time? Thank you very much for your time and help.

-Thomas

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