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
On Tue, Jun 21, 2011 at 10:46 AM, Zachary Pincus zachary.pin...@yale.eduwrote:
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
On Tue, Jun 21, 2011 at 9:46 AM, Zachary Pincus zachary.pin...@yale.edu 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
On Tue, Jun 21, 2011 at 11:17 AM, Keith Goodman kwgood...@gmail.com wrote:
On Tue, Jun 21, 2011 at 9:46 AM, Zachary Pincus zachary.pin...@yale.edu
wrote:
Hello all,
As a result of the fast greyscale conversion thread, I noticed an
anomaly with numpy.ndararray.sum(): summing along certain
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!
___
NumPy-Discussion mailing list
