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.robitai...@gmail.com> 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 > _______________________________________________ > Matplotlib-users mailing list > Matplotlib-users@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > ------------------------------------------------------------------------------ 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 _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
