Thanks Ralf!
this module looks great in fact. I didn't know it existed, and in fact
It is only available in Scipy 0.11.0 (had to install from source since
an Ubuntu 12.04 bin is not available). Too bad that the User-defined
function only accepts one single array. If that function should take
m
On Wed, Dec 26, 2012 at 8:09 PM, Nicolas Rougier
wrote:
>
>
> Hi all,
>
>
> I'm looking for a way to "reduce" dtype1 into dtype2 (when it is possible of
> course).
> Is there some easy way to do that by any chance ?
>
>
> dtype1 = np.dtype( [ ('vertex', [('x', 'f4'),
>
Dear all,
I found here
http://mail.scipy.org/pipermail/numpy-discussion/2009-January/039681.html
that to use* numpy.ma.testutils.assert_almost_equal* for masked array
assertion, but I cannot find the np.ma.testutils module?
Am I getting somewhere wrong? my numpy version is 1.6.2 thanks!
Chao
--
Hi all,
I'm looking for a way to "reduce" dtype1 into dtype2 (when it is possible of
course).
Is there some easy way to do that by any chance ?
dtype1 = np.dtype( [ ('vertex', [('x', 'f4'),
('y', 'f4'),
('z', 'f4')]),
On Wed, Dec 26, 2012 at 10:09 AM, Eric Emsellem wrote:
> Hi!
>
> I am looking for an efficient way of doing some simple binning of points
> and then applying some functions to points within each bin.
>
That's exactly what scipy.stats.binned_statistic does:
http://docs.scipy.org/doc/scipy-dev/refe
This looks like the perfect work for cython. It it's great opp optimizing
loops.
Another option is the new
Numba, an automatic compiler.
David.
El 26/12/2012 10:09, "Eric Emsellem" escribió:
> Hi!
>
> I am looking for an efficient way of doing some simple binning of points
> and then applying so
Hi!
I am looking for an efficient way of doing some simple binning of points
and then applying some functions to points within each bin.
I have tried several ways, including crude looping over the indices, or
using digitize (see below) but I cannot manage to get it as efficient as
I need it to
