On Fri, Jul 27, 2012 at 5:15 AM, Charles R Harris
wrote:
> I would support accumulating in 64 bits but, IIRC, the function will need to
> be rewritten so that it works by adding 32 bit floats to the accumulator to
> save space. There are also more stable methods that could also be
> investigated.
On Thu, 2012-07-26 at 22:15 -0600, Charles R Harris wrote:
> I would support accumulating in 64 bits but, IIRC, the function will
> need to be rewritten so that it works by adding 32 bit floats to the
> accumulator to save space. There are also more stable methods that
> could also be investigated.
On Thu, Jul 26, 2012 at 9:26 PM, Tom Aldcroft wrote:
> There was a thread in January discussing the non-obvious behavior of
> numpy.mean() for large arrays of float32 values [1]. This issue is
> nicely discussed at the end of the numpy.mean() documentation [2] with
> an example:
>
> >>> a = np.z
There was a thread in January discussing the non-obvious behavior of
numpy.mean() for large arrays of float32 values [1]. This issue is
nicely discussed at the end of the numpy.mean() documentation [2] with
an example:
>>> a = np.zeros((2, 512*512), dtype=np.float32)
>>> a[0, :] = 1.0
>>> a[1, :]
