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The axes_grid toolkit is base on use cases for images of aspect 1, and
I haven't carefully considered cases where the aspect is different
from 1. And I guess this is one of such cases I overlooked.
Please try to add below lines in your code (I couldn't try your code
because of the missing data file, but it works with the the scatter
example you referred).
ax.set_aspect("auto")
divider.set_aspect(True)
divider.get_horizontal()[0]._aspect=0.5
The interface should be improved but I guess this will work.
Regards,
-JJ
On Fri, Jul 24, 2009 at 1:19 PM, Jeff Thomas<jef...@gm...> wrote:
> Currently, I am trying to plot a 2D array with imshow and two 1D arrays
> on separate plots attached to the top and right of the imshow image. I got
> it to work, however when I change the aspect of the image (which I want to
> do) white space and unusual scalings appear. I want to get rid of it and
> have the scales that match the aspect.
> Basically, I want to do the same thing shown in the
> example http://matplotlib.sourceforge.net/examples/axes_grid/scatter_hist.html
> attached is the result with out the aspect change.
> also attached is the result with aspect change attempt.
> here is the code that produces the result above:
> import numpy as np
> import tables
> from matplotlib.pyplot import *
> import matplotlib as mpl
> import matplotlib.cm as cm
>
>
> fig = figure(figsize=[12.5,7.5])
> from mpl_toolkits.axes_grid import make_axes_locatable
> #get 3D array from hdf5 file
> a =
> tables.openFile("/Users/magoo/vorpal-data-2/unl-1mm-3d_ElecMultiField_25.h5")
> b = a.root.ElecMultiField[ : , : , : ,1]
> ax = fig.add_subplot(111)
> ax.set_autoscale_on(False)
> divider = make_axes_locatable(ax)
> axLOutx = divider.new_vertical(1, pad=0.3, sharex=ax)
> fig.add_axes(axLOutx)
> #plot line above
> axLOutx.plot(b[365,:,75])
> axLOutx.set_xlim( (0,145))
> axLOuty = divider.new_horizontal(2, pad=0.5, sharey=ax)
> fig.add_axes(axLOuty)
> #plot line on right
> yarr = np.arange(0, np.shape(b[:, 75, 75])[0], 1)
> axLOuty.plot(b[:,75,75], yarr)
> axLOuty.set_ylim( (769,0))
> # plot image/2D array
> im = ax.imshow(b[:,:,75], extent=[0,145,769,0],cmap=cm.jet) # when I add
> (aspect = .5) as another argument I get what is shown in the second attached
> image
> cb = colorbar(im, fraction=0.015)
>
> plt.draw()
> plt.show()
> ------------------------------------------------------------------------------
>
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Hi,
I am trying to use matplotlib to visually explore certain different
representation of images. I have the core functionality done. This allows to
explore one image that appears on two subplots w/ the possibility to highlight
regions on either subplot and see the corresponding one on the other. 
What I have left to do is to provide some mean to select the image one wants to
explore. I tried to follow some advice given on this list, but it seems gui
dialogs (file selection in this case) don't get along well with the thread
tricks done by ipython to maintain interactivity while using matplotlib (ipython
started w/ -gthread or -pylab option). If I start ipython without options, the
dialogs do respond, but then I loose the ipython shell. Am I trying to do
something out of normal with matplotlib? I would appreciate any advice or
pointers that would allow me overcome these limitations.
Jorge