On Wed, Oct 21, 2009 at 11:13:35AM -0400, Michael Droettboom wrote:
Sorry for the noise. Found the instructions in HOWTO_BUILD_DOCS.txt .
Not sure if this is part of what you discovered, but numpydoc is at the Cheese
Shop too:
http://pypi.python.org/pypi/numpydoc
David
Robert Kern skrev:
No, I think you're right. Using SIMD to refer to numpy-like
operations is an abuse of the term not supported by any outside
community that I am aware of. Everyone else uses SIMD to describe
hardware instructions, not the application of a single syntactical
element of a high
OK, I should have said Object-oriented SIMD API that is implemented
using hardware SIMD instructions.
No, I think you're right. Using SIMD to refer to numpy-like
operations is an abuse of the term not supported by any outside
community that I am aware of. Everyone else uses SIMD to describe
Matthieu Brucher skrev:
I agree with Sturla, for instance nVidia GPUs do SIMD computations
with blocs of 16 values at a time, but the hardware behind can't
compute on so much data at a time. It's SIMD from our point of view,
just like Numpy does ;)
A computer with a CPU and a GPU is a
Mathieu Blondel skrev:
Peter Norvig suggested to merge Numpy into Cython but he didn't
mention SIMD as the reason (this one is from me).
I don't know what Norvig said or meant.
However:
There is NumPy support in Cython. Cython has a general syntax applicable
to any PEP 3118 buffer. (As
On Thu, Oct 22, 2009 at 5:05 PM, Sturla Molden stu...@molden.no wrote:
Mathieu Blondel skrev:
The PEP 3118 buffer syntax in Cython can be used to port NumPy to Py3k,
replacing the current C source. That might be what Norvig meant if he
suggested merging NumPy into Cython.
As I wrote earlier
Mathieu Blondel skrev:
As I wrote earlier in this thread, I confused Cython and CPython. PN
was suggesting to include Numpy in the CPython distribution (not
Cython). The reason why was also given earlier.
First, that would currently not be possible, as NumPy does not support
Py3k.
Is there a way to proper convolve a masked array with a normal (nonmasked)
array?
My specific problem is a convolution of a 2D masked array with a separable
kernel (a convolution with 2 1D array along each axis).
Nadav.
___
NumPy-Discussion
Hi all,
The weekend is just around the corner, and we're looking forward to
the sprint! Here is the detail again:
Our patch queue keeps getting longer and longer, so here is an
opportunity to do some spring cleaning (it's spring in South Africa,
at least)!
Please join us for an October SciPy
josef.p...@gmail.com wrote:
Is it really possible to get the same as np.sum(a*a, axis) with
tensordot if a.ndim=2 ?
Any way I try the something_else, I get extra terms as in np.dot(a.T, a)
Just to answer this question, np.dot(a,a) is equivalent to
np.tensordot(a,a, axis=(0,0))
but the
On Tue, Oct 20, 2009 at 11:17 AM, markus.proel...@ifm.com wrote:
Hello,
I'm always wondering why binary_repr doesn't allow arrays as input values.
I always have to use a work around like:
import numpy as np
def binary_repr(arr, width=None):
binary_list = map((lambda foo:
2009/10/21 Neal Becker ndbeck...@gmail.com
...
I once wrote a module that replaces the built in transcendental
functions of numpy by optimized versions from Intels vector math
library. If someone is interested, I can publish it. In my experience it
was of little use since real world
Robert Kern wrote:
On Wed, Oct 21, 2009 at 22:32, Mathieu Blondel math...@mblondel.org wrote:
On Thu, Oct 22, 2009 at 11:31 AM, Sturla Molden stu...@molden.no wrote:
Mathieu Blondel skrev:
Hello,
About one year ago, a high-level, objected-oriented SIMD API was added
to
numpy-discussion-boun...@scipy.org schrieb am 22.10.2009 12:36:46:
On Tue, Oct 20, 2009 at 11:17 AM, markus.proel...@ifm.com wrote:
Hello,
I'm always wondering why binary_repr doesn't allow arrays as input
values. I always have to use a work around like:
import numpy as
On Oct 22, 2009, at 1:35 AM, Sturla Molden wrote:
Robert Kern skrev:
No, I think you're right. Using SIMD to refer to numpy-like
operations is an abuse of the term not supported by any outside
community that I am aware of. Everyone else uses SIMD to describe
hardware instructions, not the
On Thu, Oct 22, 2009 at 02:35, Sturla Molden stu...@molden.no wrote:
Robert Kern skrev:
No, I think you're right. Using SIMD to refer to numpy-like
operations is an abuse of the term not supported by any outside
community that I am aware of. Everyone else uses SIMD to describe
hardware
On Thu, Oct 22, 2009 at 06:20, Dag Sverre Seljebotn
da...@student.matnat.uio.no wrote:
Robert Kern wrote:
On Wed, Oct 21, 2009 at 22:32, Mathieu Blondel math...@mblondel.org wrote:
On Thu, Oct 22, 2009 at 11:31 AM, Sturla Molden stu...@molden.no wrote:
Mathieu Blondel skrev:
Hello,
About
It seems that either Sphinx or NumpyDoc is having troubles with property
attributes.
Considering the following piece of code in foo.py
class Profil(object):
Blabla
Attributes
--
tfin
tdeb : float
Robert Kern skrev:
I would be delighted to see a reference to one that refers to a high
level language's API as SIMD. Please point one out to me. It's
certainly not any of the ones I have available to me.
Numerical Receipes in Fortran 90, page 964 and 985-986, describes the
syntax of
It seems that
class Profil(object):
def __init__(self):
pass
def bla(self):
Blabla.
return 0
@property
def tdeb(self):
The time horizon startpoint.
return self.pts[0,:].min()
and a foo.rst containing
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