From: Brian B. <bb...@br...> - 2010-03-27 12:17:20
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On Mar 27, 2010, at 1:13 , Ariel Rokem wrote: > In particular, I am interested in using the plt.cm.RdYlBu_r > colormap. If the data has both negative and positive values, I want > 0 to map to the central value of this colormap (a pale whitish > yellow) and I want negative values to be in blue and positive > numbers to be in red. not sure if this is what you want (I'd never heard of RdYlBu_r...I need to go read up!), but I've used a similar colormap with the code posted below. You might be able to modify it for your case. hope this helps! bb from pylab import * def bluewhitered(a,N=256): bottom = [0, 0, 0.5] botmiddle = [0, 0.5, 1] middle = [1, 1, 1] topmiddle = [1, 0, 0] top = [0.5, 0, 0] lims=[a.min(),a.max()] if lims[0]<0 and lims[1]>0: ratio=abs(lims[0])/(abs(lims[0])+lims[1]) cdict={} cdict['red']=[] cdict['green']=[] cdict['blue']=[] # negative part red=[(0.0, 0.0, 0.0), (ratio/2, 0.0, 0.0), (ratio, 1.0, 1.0)] green=[(0.0, 0.0, 0.0), (ratio/2, 0.5, 0.5), (ratio, 1.0, 1.0)] blue=[(0.0, 0.5, 0.5), (ratio/2, 1, 1), (ratio, 1.0, 1.0)] cdict['red'].extend(red) cdict['green'].extend(green) cdict['blue'].extend(blue) nratio=1-(1-ratio)/2.0 # positive part red=[(ratio, 1.0, 1.0), (nratio, 1.0, 1.0), (1, 0.5, 0.5)] green=[(ratio, 1.0, 1.0), (nratio, 0., 0.), (1, 0.0, 0.0)] blue=[(ratio, 1., 1.), (nratio, 0, 0), (1, 0, 0)] cdict['red'].extend(red) cdict['green'].extend(green) cdict['blue'].extend(blue) elif lims[0]>=0: # all positive cdict={} cdict['red']=[] cdict['green']=[] cdict['blue']=[] ratio=0.0 nratio=0.5 # positive part red=[(ratio, 1.0, 1.0), (nratio, 1.0, 1.0), (1, 0.5, 0.5)] green=[(ratio, 1.0, 1.0), (nratio, 0., 0.), (1, 0.0, 0.0)] blue=[(ratio, 1., 1.), (nratio, 0, 0), (1, 0, 0)] cdict['red'].extend(red) cdict['green'].extend(green) cdict['blue'].extend(blue) else: # all negative cdict={} cdict['red']=[] cdict['green']=[] cdict['blue']=[] ratio=1.0 # negative part red=[(0.0, 0.0, 0.0), (ratio/2, 0.0, 0.0), (ratio, 1.0, 1.0)] green=[(0.0, 0.0, 0.0), (ratio/2, 0.5, 0.5), (ratio, 1.0, 1.0)] blue=[(0.0, 0.5, 0.5), (ratio/2, 1, 1), (ratio, 1.0, 1.0)] cdict['red'].extend(red) cdict['green'].extend(green) cdict['blue'].extend(blue) my_cmap = matplotlib.colors.LinearSegmentedColormap ('my_colormap',cdict,N) return my_cmap if __name__=="__main__": a=randn(20,20) my_cmap=bluewhitered(a,256) clf() pcolor(a,cmap=my_cmap) colorbar() -- Brian Blais bb...@br... http://web.bryant.edu/~bblais http://bblais.blogspot.com/ |