Dear Eric, thanks again for your comment, I am aware that the script contained both the individual colorbars and the common one. My comment in the code was because the placement on the figure is somewhat cramped:
## doesn't really work :/ ## in what way? cax = fig.add_axes([0.25, 0.06, 0.5, 0.02]) fig.colorbar(im2, cax, orientation='horizontal') Ideally, I'd need to create a new subfig 313 with a much reduced height. Either way, you helped me a lot! 2011/6/7 Eric Firing <efir...@hawaii.edu>: > On 06/07/2011 01:37 AM, Daniel Mader wrote: >> >> Hi Eric, >> >> >> 2011/6/6 Eric Firing<efir...@hawaii.edu>: >>> >>> It's not quite clear to me yet, but I assume you want to use a call to >>> imshow with a different data set in the second subplot, but have the >>> color scale and colorbar be identical to those in the first subplot. Is >>> that correct? If so, all you need to do is use the same norm for both >>> calls to imshow--that is, define a norm, set the limits you want on it, >>> and supply it as a kwarg. >> >> thanks a lot, you helped me to work around my problem, see code below :) >> >>> Also, for this sort of comparison, sometimes it is more efficient to use >>> a single colorbar for multiple panels, as in this example: >>> >>> >>> http://matplotlib.sourceforge.net/examples/pylab_examples/multi_image.html >> >> Very nice example! It's a little too complex for me, though, with all >> the calculations for the axes layout -- I prefer subplots :) However, >> I think I have found a nice compromise: > > Attached is a slight modification, much simpler than the example above, but > retaining the single colorbar. Alternatively, if you stick with the > colorbar for each panel (which is sometimes clearer), it illustrates a > slightly clearer way of handling the cmap and norm, explicitly using the > same instance of each for both images. > > Eric > >> >> import pylab >> import matplotlib as mpl >> >> pylab.close('all') >> >> dat = pylab.array([[1,2,3,4],[5,6,7,8]]) >> datT = dat/2 >> >> fig = pylab.figure() >> >> ax1 = fig.add_subplot(211) >> ax1.set_title('raw data') >> im1 = ax1.imshow(dat, interpolation='nearest', >> cmap=mpl.cm.get_cmap('rainbow', 20)) >> fig.colorbar(im1) >> >> ax2 = fig.add_subplot(212) >> ax2.set_title('leveled') >> im2 = ax2.imshow(datT, interpolation='nearest', >> cmap=mpl.cm.get_cmap('rainbow', 20)) >> ## apply norm: >> norm = mpl.colors.Normalize(vmin=dat.min(), vmax=dat.max()) >> im2.set_norm(norm) >> fig.colorbar(im2) >> >> ## doesn't really work :/ >> cax = fig.add_axes([0.25, 0.04, 0.5, 0.02]) >> fig.colorbar(im2, cax, orientation='horizontal') >> >> pylab.show() >> >> Thanks a lot, >> best regards, >> >> Daniel ------------------------------------------------------------------------------ EditLive Enterprise is the world's most technically advanced content authoring tool. Experience the power of Track Changes, Inline Image Editing and ensure content is compliant with Accessibility Checking. http://p.sf.net/sfu/ephox-dev2dev _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
