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.j.j...@gmail.com> 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<jeff.thomas...@gmail.com> > 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() > > > ------------------------------------------------------------------------------ > > > > _______________________________________________ > > Matplotlib-users mailing list > > Matplotlib-users@lists.sourceforge.net > > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > > > >
------------------------------------------------------------------------------
_______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
