On 11/14/2011 04:23 PM, David Cournapeau wrote: > 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. I am particularly interested in the std function. Is this implemented as a separate function or an instantiation of a general reduce operations?
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