On Jun 21, 2011, at 1:16 PM, Charles R Harris wrote:
> It's because of the type conversion sum uses by default for greater precision.
Aah, makes sense. Thanks for the detailed explanations and timings!
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On Tue, Jun 21, 2011 at 11:17 AM, Keith Goodman wrote:
> On Tue, Jun 21, 2011 at 9:46 AM, Zachary Pincus
> wrote:
> > Hello all,
> >
> > As a result of the "fast greyscale conversion" thread, I noticed an
> anomaly with numpy.ndararray.sum(): summing along certain axes is much
> slower with sum(
On Tue, Jun 21, 2011 at 9:46 AM, Zachary Pincus wrote:
> Hello all,
>
> As a result of the "fast greyscale conversion" thread, I noticed an anomaly
> with numpy.ndararray.sum(): summing along certain axes is much slower with
> sum() than versus doing it explicitly, but only with integer dtypes a
On Tue, Jun 21, 2011 at 10:46 AM, Zachary Pincus wrote:
> Hello all,
>
> As a result of the "fast greyscale conversion" thread, I noticed an anomaly
> with numpy.ndararray.sum(): summing along certain axes is much slower with
> sum() than versus doing it explicitly, but only with integer dtypes an
Hello all,
As a result of the "fast greyscale conversion" thread, I noticed an anomaly
with numpy.ndararray.sum(): summing along certain axes is much slower with
sum() than versus doing it explicitly, but only with integer dtypes and when
the size of the dtype is less than the machine word. I c