From: Ariel Rokem <arokem@be...>  20100330 14:38:28

Hi Friedrich, Thanks a lot  very nice! Cheers  Ariel On Tue, Mar 30, 2010 at 6:52 AM, Friedrich Romstedt < friedrichromstedt@...> wrote: > 2010/3/30 Ariel Rokem <arokem@...>: > > I ended up with the code below, using Chloe's previously posted > > 'subcolormap' and, in order to make the colorbar nicely attached to the > main > > imshow plot, I use make_axes_locatable in order to generate the colorbar > > axes. I tried it out with a couple of usecases and it seems to do what > it > > is supposed to, (with ticks only for the edges of the range of the data > and > > 0, if that is within that range), but I am not entirely sure. Do you > think > > it works? > > I think even Chloe would agree that you should avoid the subcolormap() > if you can. I tried to create an as minimalistic as possible but > working selfcontained example, please find the code also attached as > .py file: > > from matplotlib import pyplot as plt > import matplotlib as mpl > from mpl_toolkits.axes_grid import make_axes_locatable > import numpy as np > > fig = plt.figure() > ax_im = fig.add_subplot(1, 1, 1) > divider = make_axes_locatable(ax_im) > ax_cb = divider.new_vertical(size = '20%', pad = 0.2, pack_start = True) > fig.add_axes(ax_cb) > > x = np.linspace(5, 5, 101) > y = x > Z = np.sin(x*y[:,None]).clip(1,10.1) > > # Leave out if you want: > Z += 2 > > min_val = Z.min() > max_val = Z.max() > bound = max(np.abs(Z.max()), np.abs(Z.min())) > > patch = ax_im.imshow(Z, origin = 'upper', interpolation = 'nearest', > vmin = bound, vmax = bound) > > cb = fig.colorbar(patch, cax = ax_cb, orientation = 'horizontal', > norm = patch.norm, > boundaries = np.linspace(bound, bound, 256), > ticks = [min_val, 0, max_val], > format = '%.2f') > > plt.show() > > Friedrich >  Ariel Rokem Helen Wills Neuroscience Institute University of California, Berkeley http://argentum.ucbso.berkeley.edu/ariel 