On 2012/07/26 9:20 PM, Jeffrey Spencer wrote: > import numpy as np > import matplotlib as mpl > X, Y = np.meshgrid(arange(20),arange(20)) > Z = np.arange(20*20) > Z = Z.reshape(20,20) > logNorm = mpl.colors.Normalize(vmin=0,vmax=200) > fig = mpl.pyplot.figure(10) > ax = fig.add_subplot(111) > surf = ax.contourf(X,Y,Z, 100, cmap=matplotlib.cm.jet, norm = logNorm) > cbar = fig.colorbar(surf, shrink=0.70, norm=logNorm) > show()
OK, the basic problem here is that you are specifying 100 levels, which are being auto-selected to cover the actual data range; and the colorbar is doing what it is supposed to do, which is show the levels you actually have. Try leaving out the norm, and just specify the levels to cover what you want, more like this: surf = ax.contourf(X, Y, Z, np.arange(0, 200.1, 2), cmap=mpl.cm.jet, extend='both') cbar = fig.colorbar(surf, shrink=0.7) If you actually do want a log norm, you can pass that in to contourf and it will be passed on to colorbar; but most likely you should still specify the levels you want as an array, and not specify vmin and vmax in the norm. If you want log scaling, it may work better to simply plot the log of Z, and use the colorbar label to indicate that this is what you are doing. Note that with a recent change, you can use the set_under and set_over methods of the cmap to specify arbitrary colors, or no color, for the extended regions; or you can leave out the "extend" kwarg and not color the regions outside the range of your contour levels. In general, contourf is most appropriate when there is a moderate number of levels, well under 100; if you want that many gradations, then you might do better with pcolormesh or ax.pcolorfast or imshow. For those image-like methods, it is appropriate to use vmin and vmax, either directly, or in a norm. Eric ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
