[Numpy-discussion] Memory hungry reduce ops in Numpy

[Andreas Müller]

On 11/14/2011 04:23 PM, David Cournapeau wrote:
> On Mon, Nov 14, 2011 at 12:46 PM, Andreas Müller
> <amueller at 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?