On 2011-02-18 07:32:48 +0100, Robert Abiad said: > Dear Folks, > > I'm finding that hist has problems computing on 2d arrays. > > import numpy > import pylab > mu, sigma = 2, 0.5 > v = numpy.random.normal(mu,sigma,160000) > pylab.hist(v, bins=1000, normed=1) > > This works without any problems. But if you try this: > > w=v.reshape(400,400) > pylab.hist(w, bins=1000, normed=1) > > it doesn't come back on my machine until all of memory is used up. However: > > n,bins = numpy.histogram(w,bins=1000,normed=1) > > works just fine.
That's by design. For a n x m array, pylab.hist is doing m times a histogram of the n items subarray and then tries to plot them somehow on top of each other. The detail I don't know, but most likely you want to do pylab.hist(w.flatten(), ....) to get a 1-dim array that you want to fill in ONE histogram. (for example for image arrays). HTH, Michael > > > > ------------------------------------------------------------------------------ > The ultimate all-in-one performance toolkit: Intel(R) Parallel Studio XE: > Pinpoint memory and threading errors before they happen. > Find and fix more than 250 security defects in the development cycle. > Locate bottlenecks in serial and parallel code that limit performance. > http://p.sf.net/sfu/intel-dev2devfeb ------------------------------------------------------------------------------ The ultimate all-in-one performance toolkit: Intel(R) Parallel Studio XE: Pinpoint memory and threading errors before they happen. Find and fix more than 250 security defects in the development cycle. Locate bottlenecks in serial and parallel code that limit performance. http://p.sf.net/sfu/intel-dev2devfeb _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
