On Thu, Jul 24, 2014 at 4:56 AM, Julian Taylor < jtaylor.deb...@googlemail.com> wrote:
> In practice one of the better methods is pairwise summation that is > pretty much as fast as a naive summation but has an accuracy of > O(logN) ulp. > This is the method numpy 1.9 will use this method by default (+ its > even a bit faster than our old implementation of the naive sum): > https://github.com/numpy/numpy/pull/3685 > > but it has some limitations, it is limited to blocks fo the buffer > size (8192 elements by default) and does not work along the slow axes > due to limitations in the numpy iterator. > For what it's worth, I see the issue on a 64-bit Windows numpy 1.8, but cannot on a 32-bit Windows numpy master: >>> np.__version__ '1.8.0' >>> np.ones(100000000, dtype=np.float32).mean() 0.16777216 >>> np.__version__ '1.10.0.dev-Unknown' >>> np.ones(100000000, dtype=np.float32).mean() 1.0 -- (\__/) ( O.o) ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus planes de dominación mundial.
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