> I think it would enhance broadcasting if functions like sum, mean, etc > didn't change the number of dimensions.
I strongly favor doing it, but with keepshape (or just "keep", to make it short) and not by default. It's at least as common to take a mean down an axis of a 2D array and plot it (requiring 1D) as to subtract it in a broadcasting way. But, the latter case is common. How about generalizing it to take a mean of more than one axis at a time, say to reduce 4 dimensions to 1 for plotting? That could be done by accepting a linear list of axis numbers to average over. a = ones((2,3,4,5)) b = a.mean([1,2,3]) I'd add an option to handle NaN data as missing, as well. That's standard in other array languages. The option is called "NAN" in IDL and I'd propose that name as well. Also, from the docstring... to compute the standard deviation of the flattened array. should say to compute the mean of the flattened array. Oops. But, it emphasizes the point that these behaviors should be universal to similar routines. Are there other routines for which these behaviors would not work well? --jh-- _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion