Re: [Matplotlib-users] imshow with side plots whitespace problem

[Jeff T. <jef...@gm...>]

Jae-Joon Lee,

The data file I worked with is:

The file 'unl-1mm-3d_MagMultiField_25.h5' (370.0 MB) is available for
download at
<
http://dropbox.unl.edu/uploads/20090803/b42af1d24f319f10/unl-1mm-3d_MagMultiField_25.h5
>
for the next 7 days.
It will be removed after Monday, August  3, 2009.

It contains a 4D array which we make into a 3D array. Then that is worked
with.


Adding the keyword argument aspect = 'auto' works for now. Though, in the
future I am not sure this will work for plotting data in different ways.
Today I will look into using the divider commands you give.

Thanks,
Jeff Thomas

On Sat, Jul 25, 2009 at 2:07 PM, Jae-Joon Lee <lee...@gm...> wrote:

> 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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