On Mon, Nov 14, 2011 at 12:46 PM, Andreas Müller <amuel...@ais.uni-bonn.de> wrote: > Hi everybody. > When I did some normalization using numpy, I noticed that numpy.std uses > more ram than I was expecting. > A quick google search gave me this: > http://luispedro.org/software/ncreduce > The site claims that std and other reduce operations are implemented > naively with many temporaries. > Is that true? And if so, is there a particular reason for that? > This issues seems quite easy to fix. > In particular the link I gave above provides code.
The code provided only implements a few special cases: being more efficient in those cases only is indeed easy. cheers, David _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
