Hi,
I am trying to set up a colorbar that automatically resizes if I zoom in to an image (which changes the aspect ratio of the axes, so I want the colorbar to get resized too). Let's say I have two Axes instances, say ax (for the main image) and cax (for the colorbar). I can set up a callback if the view limits in one axes change, for example
ax.callbacks.connect('xlim_changed', update_colorbar)
ax.callbacks.connect('ylim_changed', update_colorbar)
Now I can store a reference to cax inside ax:
ax._cax = cax
And I can now define update_colorbar so that it basically changes the position of cax:
def update_colorbar(ax):
# Get current position
xmin = ax..get_position().xmin
...
# Compute new colorbar position
...
# Set new position
ax._cax.set_position(...)
# Return axes instance
return ax
Now the issue is that if I select a region of the image to zoom into, then as soon as I've selected the region, update_colorbar gets called, but by then, the aspect ratio of ax hasn't changed, and so the position I find when I do xmin = ax..get_position().xmin in update_colorbar is the *old* position of ax, not the new one. So the colorbar position is always one step behind compared to the main image axes.
Can anyone think of any way that would avoid this issue, and to be able to use the *new* position of ax inside update_colorbar?
Thanks in advance for any help,
Thomas
see
http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg15919.html
axes_grid toolkit provides some helper function that utilizes
axes_locator (take a look at demo_locatable_axes_easy function in the
example below)
http://matplotlib.sourceforge.net/examples/axes_grid/demo_axes_divider.html
-JJ
···
On Thu, Mar 4, 2010 at 9:05 PM, Thomas Robitaille <thomas.robitaille@...287...> wrote:
Hi,
I am trying to set up a colorbar that automatically resizes if I zoom in to an image (which changes the aspect ratio of the axes, so I want the colorbar to get resized too). Let's say I have two Axes instances, say ax (for the main image) and cax (for the colorbar). I can set up a callback if the view limits in one axes change, for example
ax.callbacks.connect('xlim_changed', update_colorbar)
ax.callbacks.connect('ylim_changed', update_colorbar)
Now I can store a reference to cax inside ax:
ax._cax = cax
And I can now define update_colorbar so that it basically changes the position of cax:
def update_colorbar(ax):
# Get current position
xmin = ax..get_position().xmin
...
# Compute new colorbar position
...
# Set new position
ax._cax.set_position(...)
# Return axes instance
return ax
Now the issue is that if I select a region of the image to zoom into, then as soon as I've selected the region, update_colorbar gets called, but by then, the aspect ratio of ax hasn't changed, and so the position I find when I do xmin = ax..get_position().xmin in update_colorbar is the *old* position of ax, not the new one. So the colorbar position is always one step behind compared to the main image axes.
Can anyone think of any way that would avoid this issue, and to be able to use the *new* position of ax inside update_colorbar?
Thanks in advance for any help,
Thomas
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Hi Jae-Joon,
Thanks! This is exactly what I needed. Putting the colorbar on the right or bottom works great - however, I am running into issues with trying to put the colorbar on the left or bottom (which, from my understanding, is controlled by using pack_start=True?). Should the following code work?
import matplotlib.pyplot as mpl
import numpy as np
from mpl_toolkits.axes_grid import make_axes_locatable
fig = mpl.figure()
ax = fig.add_subplot(1,1,1)
divider = make_axes_locatable(ax)
cax = divider.new_horizontal(size="5%", pad=0.05, pack_start=True)
fig.add_axes(cax)
image = ax.imshow(np.random.random((100,100)))
cb = fig.colorbar(image, cax=cax)
Cheers,
Thomas
···
On Mar 4, 2010, at 10:28 PM, Jae-Joon Lee wrote:
see
Re: [Matplotlib-users] Transform problem with fixed aspect ratio
axes_grid toolkit provides some helper function that utilizes
axes_locator (take a look at demo_locatable_axes_easy function in the
example below)
http://matplotlib.sourceforge.net/examples/axes_grid/demo_axes_divider.html
-JJ
On Thu, Mar 4, 2010 at 9:05 PM, Thomas Robitaille > <thomas.robitaille@...287...> wrote:
Hi,
I am trying to set up a colorbar that automatically resizes if I zoom in to an image (which changes the aspect ratio of the axes, so I want the colorbar to get resized too). Let's say I have two Axes instances, say ax (for the main image) and cax (for the colorbar). I can set up a callback if the view limits in one axes change, for example
ax.callbacks.connect('xlim_changed', update_colorbar)
ax.callbacks.connect('ylim_changed', update_colorbar)
Now I can store a reference to cax inside ax:
ax._cax = cax
And I can now define update_colorbar so that it basically changes the position of cax:
def update_colorbar(ax):
# Get current position
xmin = ax..get_position().xmin
...
# Compute new colorbar position
...
# Set new position
ax._cax.set_position(...)
# Return axes instance
return ax
Now the issue is that if I select a region of the image to zoom into, then as soon as I've selected the region, update_colorbar gets called, but by then, the aspect ratio of ax hasn't changed, and so the position I find when I do xmin = ax..get_position().xmin in update_colorbar is the *old* position of ax, not the new one. So the colorbar position is always one step behind compared to the main image axes.
Can anyone think of any way that would avoid this issue, and to be able to use the *new* position of ax inside update_colorbar?
Thanks in advance for any help,
Thomas
------------------------------------------------------------------------------
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proactively, and fine-tune applications for parallel performance.
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Hi Jae-Joon,
I am encountering another issue, when using the method you suggest in combination with the parasite_axes from the matplotlib toolkit:
···
---
import matplotlib.pyplot as mpl
import numpy as np
from mpl_toolkits.axes_grid import make_axes_locatable
import mpl_toolkits.axes_grid.parasite_axes as mpltk
fig = mpl.figure()
ax = mpltk.SubplotHost(fig, 1, 1, 1)
fig.add_axes(ax)
divider = make_axes_locatable(ax)
cax = divider.new_horizontal(size="5%", pad=0.05)
fig.add_axes(cax)
image = ax.imshow(np.random.random((100,100)))
cb = fig.colorbar(image, cax=cax)
---
In the above case, the labels end up on the wrong side of the plot, and the usual method for changing the label position, e.g.:
for tick in cax.xaxis.get_major_ticks():
tick.tick1On = True
tick.tick2On = True
tick.label1On = False
tick.label2On = True
does not work. Do you have any idea why this might be?
Thanks for any help,
Thomas
On Mar 4, 2010, at 10:28 PM, Jae-Joon Lee wrote:
see
Re: [Matplotlib-users] Transform problem with fixed aspect ratio
axes_grid toolkit provides some helper function that utilizes
axes_locator (take a look at demo_locatable_axes_easy function in the
example below)
http://matplotlib.sourceforge.net/examples/axes_grid/demo_axes_divider.html
-JJ
On Thu, Mar 4, 2010 at 9:05 PM, Thomas Robitaille > <thomas.robitaille@...287...> wrote:
Hi,
I am trying to set up a colorbar that automatically resizes if I zoom in to an image (which changes the aspect ratio of the axes, so I want the colorbar to get resized too). Let's say I have two Axes instances, say ax (for the main image) and cax (for the colorbar). I can set up a callback if the view limits in one axes change, for example
ax.callbacks.connect('xlim_changed', update_colorbar)
ax.callbacks.connect('ylim_changed', update_colorbar)
Now I can store a reference to cax inside ax:
ax._cax = cax
And I can now define update_colorbar so that it basically changes the position of cax:
def update_colorbar(ax):
# Get current position
xmin = ax..get_position().xmin
...
# Compute new colorbar position
...
# Set new position
ax._cax.set_position(...)
# Return axes instance
return ax
Now the issue is that if I select a region of the image to zoom into, then as soon as I've selected the region, update_colorbar gets called, but by then, the aspect ratio of ax hasn't changed, and so the position I find when I do xmin = ax..get_position().xmin in update_colorbar is the *old* position of ax, not the new one. So the colorbar position is always one step behind compared to the main image axes.
Can anyone think of any way that would avoid this issue, and to be able to use the *new* position of ax inside update_colorbar?
Thanks in advance for any help,
Thomas
------------------------------------------------------------------------------
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proactively, and fine-tune applications for parallel performance.
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Hi,
It turns out to be a bug (new_vertical works, but new_horizontal does not).
To work around this
right after
cax = divider.new_horizontal(size="5%", pad=0.05, pack_start=True)
add these lines
locator = divider.new_locator(nx=0, ny=0)
cax.set_axes_locator(locator)
These two lines only need to be executed when "new_horizontal" is
called with pack_start=True.
The code below does some monkey patching to fix this bug. Use this if
it fits your need.
Regards,
-JJ
# work around new_horizontal bug
from mpl_toolkits.axes_grid.axes_divider import AxesDivider
if not hasattr(AxesDivider, "_new_horizontal_bug_fixed"):
new_horizontal_orig = AxesDivider.new_horizontal
def new_horizontal(self, size, pad=None, pack_start=False, **kwargs):
ax = new_horizontal_orig(self, size, pad=pad,
pack_start=pack_start, **kwargs)
if pack_start:
locator = self.new_locator(nx=0, ny=0)
ax.set_axes_locator(locator)
return ax
AxesDivider.new_horizontal = new_horizontal
AxesDivider._new_horizontal_bug_fixed = True
···
On Fri, Mar 5, 2010 at 9:05 AM, Thomas Robitaille <thomas.robitaille@...287...> wrote:
Hi Jae-Joon,
Thanks! This is exactly what I needed. Putting the colorbar on the right or bottom works great - however, I am running into issues with trying to put the colorbar on the left or bottom (which, from my understanding, is controlled by using pack_start=True?). Should the following code work?
import matplotlib.pyplot as mpl
import numpy as np
from mpl_toolkits.axes_grid import make_axes_locatable
fig = mpl.figure()
ax = fig.add_subplot(1,1,1)
divider = make_axes_locatable(ax)
cax = divider.new_horizontal(size="5%", pad=0.05, pack_start=True)
fig.add_axes(cax)
image = ax.imshow(np.random.random((100,100)))
cb = fig.colorbar(image, cax=cax)
Cheers,
Thomas
On Mar 4, 2010, at 10:28 PM, Jae-Joon Lee wrote:
see
Re: [Matplotlib-users] Transform problem with fixed aspect ratio
axes_grid toolkit provides some helper function that utilizes
axes_locator (take a look at demo_locatable_axes_easy function in the
example below)
http://matplotlib.sourceforge.net/examples/axes_grid/demo_axes_divider.html
-JJ
On Thu, Mar 4, 2010 at 9:05 PM, Thomas Robitaille >> <thomas.robitaille@...287...> wrote:
Hi,
I am trying to set up a colorbar that automatically resizes if I zoom in to an image (which changes the aspect ratio of the axes, so I want the colorbar to get resized too). Let's say I have two Axes instances, say ax (for the main image) and cax (for the colorbar). I can set up a callback if the view limits in one axes change, for example
ax.callbacks.connect('xlim_changed', update_colorbar)
ax.callbacks.connect('ylim_changed', update_colorbar)
Now I can store a reference to cax inside ax:
ax._cax = cax
And I can now define update_colorbar so that it basically changes the position of cax:
def update_colorbar(ax):
# Get current position
xmin = ax..get_position().xmin
...
# Compute new colorbar position
...
# Set new position
ax._cax.set_position(...)
# Return axes instance
return ax
Now the issue is that if I select a region of the image to zoom into, then as soon as I've selected the region, update_colorbar gets called, but by then, the aspect ratio of ax hasn't changed, and so the position I find when I do xmin = ax..get_position().xmin in update_colorbar is the *old* position of ax, not the new one. So the colorbar position is always one step behind compared to the main image axes.
Can anyone think of any way that would avoid this issue, and to be able to use the *new* position of ax inside update_colorbar?
Thanks in advance for any help,
Thomas
------------------------------------------------------------------------------
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Try the new software tools for yourself. Speed compiling, find bugs
proactively, and fine-tune applications for parallel performance.
See why Intel Parallel Studio got high marks during beta.
http://p.sf.net/sfu/intel-sw-dev
_______________________________________________
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Unfortunately, axes_grid toolkit (in most cases) creates an axes using
its own Axes class by default. Here is some more details.
http://matplotlib.sourceforge.net/mpl_toolkits/axes_grid/users/overview.html#axisline
To use mpl's original Axes class, append axes_class parameter.
import matplotlib.axes as maxes
cax = divider.new_horizontal(size="5%", pad=0.05, axes_class=maxes.Axes)
Then your code should work.
Just in case, with the axes_grid's own Axes class, instead of looping
over major_ticks, you do
cax.axis["left"].toggle(all=False)
cax.axis["right"].toggle(all=True)
Regards,
-JJ
···
On Fri, Mar 5, 2010 at 9:38 AM, Thomas Robitaille <thomas.robitaille@...287...> wrote:
Hi Jae-Joon,
I am encountering another issue, when using the method you suggest in combination with the parasite_axes from the matplotlib toolkit:
---
import matplotlib.pyplot as mpl
import numpy as np
from mpl_toolkits.axes_grid import make_axes_locatable
import mpl_toolkits.axes_grid.parasite_axes as mpltk
fig = mpl.figure()
ax = mpltk.SubplotHost(fig, 1, 1, 1)
fig.add_axes(ax)
divider = make_axes_locatable(ax)
cax = divider.new_horizontal(size="5%", pad=0.05)
fig.add_axes(cax)
image = ax.imshow(np.random.random((100,100)))
cb = fig.colorbar(image, cax=cax)
---
In the above case, the labels end up on the wrong side of the plot, and the usual method for changing the label position, e.g.:
for tick in cax.xaxis.get_major_ticks():
tick.tick1On = True
tick.tick2On = True
tick.label1On = False
tick.label2On = True
does not work. Do you have any idea why this might be?
Thanks for any help,
Thomas
On Mar 4, 2010, at 10:28 PM, Jae-Joon Lee wrote:
see
Re: [Matplotlib-users] Transform problem with fixed aspect ratio
axes_grid toolkit provides some helper function that utilizes
axes_locator (take a look at demo_locatable_axes_easy function in the
example below)
http://matplotlib.sourceforge.net/examples/axes_grid/demo_axes_divider.html
-JJ
On Thu, Mar 4, 2010 at 9:05 PM, Thomas Robitaille >> <thomas.robitaille@...287...> wrote:
Hi,
I am trying to set up a colorbar that automatically resizes if I zoom in to an image (which changes the aspect ratio of the axes, so I want the colorbar to get resized too). Let's say I have two Axes instances, say ax (for the main image) and cax (for the colorbar). I can set up a callback if the view limits in one axes change, for example
ax.callbacks.connect('xlim_changed', update_colorbar)
ax.callbacks.connect('ylim_changed', update_colorbar)
Now I can store a reference to cax inside ax:
ax._cax = cax
And I can now define update_colorbar so that it basically changes the position of cax:
def update_colorbar(ax):
# Get current position
xmin = ax..get_position().xmin
...
# Compute new colorbar position
...
# Set new position
ax._cax.set_position(...)
# Return axes instance
return ax
Now the issue is that if I select a region of the image to zoom into, then as soon as I've selected the region, update_colorbar gets called, but by then, the aspect ratio of ax hasn't changed, and so the position I find when I do xmin = ax..get_position().xmin in update_colorbar is the *old* position of ax, not the new one. So the colorbar position is always one step behind compared to the main image axes.
Can anyone think of any way that would avoid this issue, and to be able to use the *new* position of ax inside update_colorbar?
Thanks in advance for any help,
Thomas
------------------------------------------------------------------------------
Download Intel® Parallel Studio Eval
Try the new software tools for yourself. Speed compiling, find bugs
proactively, and fine-tune applications for parallel performance.
See why Intel Parallel Studio got high marks during beta.
http://p.sf.net/sfu/intel-sw-dev
_______________________________________________
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Hi Jae-Joon,
Thanks for your help! One last question - if I create a colorbar axes with
cax = divider.new_horizontal(size="5%", pad=0.05)
Is it possible to then modify the size and pad parameters, or do I need to delete the axes and start again?
Cheers,
Tom
···
On Mar 5, 2010, at 12:20 PM, Jae-Joon Lee wrote:
Unfortunately, axes_grid toolkit (in most cases) creates an axes using
its own Axes class by default. Here is some more details.
http://matplotlib.sourceforge.net/mpl_toolkits/axes_grid/users/overview.html#axisline
To use mpl's original Axes class, append axes_class parameter.
import matplotlib.axes as maxes
cax = divider.new_horizontal(size="5%", pad=0.05, axes_class=maxes.Axes)
Then your code should work.
Just in case, with the axes_grid's own Axes class, instead of looping
over major_ticks, you do
cax.axis["left"].toggle(all=False)
cax.axis["right"].toggle(all=True)
Regards,
-JJ
On Fri, Mar 5, 2010 at 9:38 AM, Thomas Robitaille > <thomas.robitaille@...287...> wrote:
Hi Jae-Joon,
I am encountering another issue, when using the method you suggest in combination with the parasite_axes from the matplotlib toolkit:
---
import matplotlib.pyplot as mpl
import numpy as np
from mpl_toolkits.axes_grid import make_axes_locatable
import mpl_toolkits.axes_grid.parasite_axes as mpltk
fig = mpl.figure()
ax = mpltk.SubplotHost(fig, 1, 1, 1)
fig.add_axes(ax)
divider = make_axes_locatable(ax)
cax = divider.new_horizontal(size="5%", pad=0.05)
fig.add_axes(cax)
image = ax.imshow(np.random.random((100,100)))
cb = fig.colorbar(image, cax=cax)
---
In the above case, the labels end up on the wrong side of the plot, and the usual method for changing the label position, e.g.:
for tick in cax.xaxis.get_major_ticks():
tick.tick1On = True
tick.tick2On = True
tick.label1On = False
tick.label2On = True
does not work. Do you have any idea why this might be?
Thanks for any help,
Thomas
On Mar 4, 2010, at 10:28 PM, Jae-Joon Lee wrote:
see
Re: [Matplotlib-users] Transform problem with fixed aspect ratio
axes_grid toolkit provides some helper function that utilizes
axes_locator (take a look at demo_locatable_axes_easy function in the
example below)
http://matplotlib.sourceforge.net/examples/axes_grid/demo_axes_divider.html
-JJ
On Thu, Mar 4, 2010 at 9:05 PM, Thomas Robitaille >>> <thomas.robitaille@...287...> wrote:
Hi,
I am trying to set up a colorbar that automatically resizes if I zoom in to an image (which changes the aspect ratio of the axes, so I want the colorbar to get resized too). Let's say I have two Axes instances, say ax (for the main image) and cax (for the colorbar). I can set up a callback if the view limits in one axes change, for example
ax.callbacks.connect('xlim_changed', update_colorbar)
ax.callbacks.connect('ylim_changed', update_colorbar)
Now I can store a reference to cax inside ax:
ax._cax = cax
And I can now define update_colorbar so that it basically changes the position of cax:
def update_colorbar(ax):
# Get current position
xmin = ax..get_position().xmin
...
# Compute new colorbar position
...
# Set new position
ax._cax.set_position(...)
# Return axes instance
return ax
Now the issue is that if I select a region of the image to zoom into, then as soon as I've selected the region, update_colorbar gets called, but by then, the aspect ratio of ax hasn't changed, and so the position I find when I do xmin = ax..get_position().xmin in update_colorbar is the *old* position of ax, not the new one. So the colorbar position is always one step behind compared to the main image axes.
Can anyone think of any way that would avoid this issue, and to be able to use the *new* position of ax inside update_colorbar?
Thanks in advance for any help,
Thomas
------------------------------------------------------------------------------
Download Intel® Parallel Studio Eval
Try the new software tools for yourself. Speed compiling, find bugs
proactively, and fine-tune applications for parallel performance.
See why Intel Parallel Studio got high marks during beta.
http://p.sf.net/sfu/intel-sw-dev
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divider.get_horizontal() returns a list of size objects
(http://matplotlib.sourceforge.net/mpl_toolkits/axes_grid/api/axes_size_api.html#module-mpl_toolkits.axes_grid.axes_size)
that are currently used.
For example,
cax = divider.new_horizontal(size="5%", pad=0.05)
horiz_list = divider.get_horizontal()
horiz_list[0] is x-size of ax, horiz_list[1] is pad size, and
horiz_list[2] is x-size of cax. You can modify those size objects (but
usually they don't provide public interfaces). Or you can substitute
any of them with a valid size object.
horiz_list[1]._fixed_size = 0. # makes pad 0 inches
horiz_list[2]._fraction = 0.1 # width of cax becomes 10% of the width of ax
Or
from mpl_toolkits.axes_grid.axes_size import Fixed, Fraction
horiz_list[1] = Fixed(0.)
horiz_list[2] = Fraction(0.1, horiz_list[0])
There are not much of documentation available, but this may be helpful.
http://matplotlib.sourceforge.net/mpl_toolkits/axes_grid/users/axes_divider.html
Regards,
-JJ
···
On Fri, Mar 5, 2010 at 3:38 PM, Thomas Robitaille <thomas.robitaille@...287...> wrote:
Hi Jae-Joon,
Thanks for your help! One last question - if I create a colorbar axes with
cax = divider.new_horizontal(size="5%", pad=0.05)
Is it possible to then modify the size and pad parameters, or do I need to delete the axes and start again?
Cheers,
Tom
On Mar 5, 2010, at 12:20 PM, Jae-Joon Lee wrote:
Unfortunately, axes_grid toolkit (in most cases) creates an axes using
its own Axes class by default. Here is some more details.
http://matplotlib.sourceforge.net/mpl_toolkits/axes_grid/users/overview.html#axisline
To use mpl's original Axes class, append axes_class parameter.
import matplotlib.axes as maxes
cax = divider.new_horizontal(size="5%", pad=0.05, axes_class=maxes.Axes)
Then your code should work.
Just in case, with the axes_grid's own Axes class, instead of looping
over major_ticks, you do
cax.axis["left"].toggle(all=False)
cax.axis["right"].toggle(all=True)
Regards,
-JJ
On Fri, Mar 5, 2010 at 9:38 AM, Thomas Robitaille >> <thomas.robitaille@...287...> wrote:
Hi Jae-Joon,
I am encountering another issue, when using the method you suggest in combination with the parasite_axes from the matplotlib toolkit:
---
import matplotlib.pyplot as mpl
import numpy as np
from mpl_toolkits.axes_grid import make_axes_locatable
import mpl_toolkits.axes_grid.parasite_axes as mpltk
fig = mpl.figure()
ax = mpltk.SubplotHost(fig, 1, 1, 1)
fig.add_axes(ax)
divider = make_axes_locatable(ax)
cax = divider.new_horizontal(size="5%", pad=0.05)
fig.add_axes(cax)
image = ax.imshow(np.random.random((100,100)))
cb = fig.colorbar(image, cax=cax)
---
In the above case, the labels end up on the wrong side of the plot, and the usual method for changing the label position, e.g.:
for tick in cax.xaxis.get_major_ticks():
tick.tick1On = True
tick.tick2On = True
tick.label1On = False
tick.label2On = True
does not work. Do you have any idea why this might be?
Thanks for any help,
Thomas
On Mar 4, 2010, at 10:28 PM, Jae-Joon Lee wrote:
see
Re: [Matplotlib-users] Transform problem with fixed aspect ratio
axes_grid toolkit provides some helper function that utilizes
axes_locator (take a look at demo_locatable_axes_easy function in the
example below)
http://matplotlib.sourceforge.net/examples/axes_grid/demo_axes_divider.html
-JJ
On Thu, Mar 4, 2010 at 9:05 PM, Thomas Robitaille >>>> <thomas.robitaille@...287...> wrote:
Hi,
I am trying to set up a colorbar that automatically resizes if I zoom in to an image (which changes the aspect ratio of the axes, so I want the colorbar to get resized too). Let's say I have two Axes instances, say ax (for the main image) and cax (for the colorbar). I can set up a callback if the view limits in one axes change, for example
ax.callbacks.connect('xlim_changed', update_colorbar)
ax.callbacks.connect('ylim_changed', update_colorbar)
Now I can store a reference to cax inside ax:
ax._cax = cax
And I can now define update_colorbar so that it basically changes the position of cax:
def update_colorbar(ax):
# Get current position
xmin = ax..get_position().xmin
...
# Compute new colorbar position
...
# Set new position
ax._cax.set_position(...)
# Return axes instance
return ax
Now the issue is that if I select a region of the image to zoom into, then as soon as I've selected the region, update_colorbar gets called, but by then, the aspect ratio of ax hasn't changed, and so the position I find when I do xmin = ax..get_position().xmin in update_colorbar is the *old* position of ax, not the new one. So the colorbar position is always one step behind compared to the main image axes.
Can anyone think of any way that would avoid this issue, and to be able to use the *new* position of ax inside update_colorbar?
Thanks in advance for any help,
Thomas
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