Hello all, I've got a few questions that came up as I tried to calculate various statistics about an image time-series. For example, I have an array of shape (t,x,y) representing t frames of a time-lapse of resolution (x,y).
Now, say I want to both argsort and sort this time-series, pixel- wise. (For example.) In 1-d it's easy: indices = a.argsort() sorted = a[indices] I would have thought that doing this on my 3-d array would work similarly: indices = a.argsort(axis=0) sorted = a.take(indices, axis=0) Unfortunately, this gives a ValueError of "dimensions too large." Now, I know that 'a.sort(axis=0)' works fine for the given example, but I'm curious about how to this sort of indexing operation in the general case. Thanks for any insight, Zach Pincus Program in Biomedical Informatics and Department of Biochemistry Stanford University School of Medicine _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
