After some discussion on the Cython lists I thought I would try my hand at
writing some Cython accelerators for empty and zeros. This will involve using
PyArray_EMPTY, I have a simple prototype I would like to get working, but
currently it segfaults. Any tips on what I might be missing?
import num
> There is resistance. Please don't remove the old names. Also note that
> your proposed change will alter people's code in subtle, but potentially
> very "interesting" ways:
>
> >>> from math import *
> >>> from numpy import *
> >>> type(arcsin(1)) is type(asin(1))
> False
> >>> from numpy impo
On Mon, Nov 24, 2008 at 07:45:56PM +0100, Francesc Alted wrote:
> Hi,
>
> After dealing with another issue, I realized that the names of inverse
> trigonometrical/hyperbolic functions in NumPy don't follow the main
> standards in computer science. For example, where Python writes:
>
> asin, ac
Something I use a lot is a little generator that iterates over a ndarray by a
given axis. I was wondering if this is already built-in to numpy (and not
using the apply_along_axis which I find ugly) and if not would there be
interest in adding it?
the function is just:
def by_axis(nobj, axis=0):
On Wed, Nov 12, 2008 at 12:34:51PM -0600, Ryan May wrote:
> Charles سمير Doutriaux wrote:
> > Hello,
> >
> > I'm wondering if there's aquick way to do the following:
> >
> > s[:,5]=value
> >
> > in a "general" function
> > def setval(array,index,value,axis=0):
> > ## code here
>
> Assuming
On Wed, Nov 12, 2008 at 09:43:34AM -0800, Charles سمير Doutriaux wrote:
> Hello,
>
> I'm wondering if there's aquick way to do the following:
>
> s[:,5]=value
>
> in a "general" function
> def setval(array,index,value,axis=0):
> ## code here
>
> The issue is to put enough ":" before the i
On Wed, Nov 05, 2008 at 03:19:09PM +0100, Matthieu Brucher wrote:
> > Not in this case: I always get the same sequence with seed=0
> > (different for both implementation, but the same each time I run it.)
> > I got around it by installing pygsl and taking random numbers from
> > there instead of fr
On Mon, Oct 27, 2008 at 12:45:44PM +0100, Uwe Schmitt wrote:
> Nicolas ROUX schrieb:
> > Hello,
> >
> > I hope this is not a silly question ;-)
> > I have a Numpy array, and I want to process it with :
> > "if the value is lower than Threshold, then increase by Threshold"
> >
> >
> > I would like
On Mon, Oct 27, 2008 at 12:41:06PM +0100, Nicolas ROUX wrote:
> Hello,
>
> I hope this is not a silly question ;-)
> I have a Numpy array, and I want to process it with :
> "if the value is lower than Threshold, then increase by Threshold"
>
>
> I would like to translate it as:
> y[y
You are
>Since, the programs are heavily using numpy, scipy and matplotlib
>libraries, I send this announcement to all the three lists and the main
>python-list; sorry for double-posting. The announcement with the related
>links is uploaded here [1]http://blog.deductivethinking.com/?p=29. T
On Wed, Oct 22, 2008 at 02:00:20PM -0700, Fernando Perez wrote:
> Hi all,
>
> much delayed, but here it is, finally. The doc regarding our
> discussion about PEP 225 is attached, and I'm keeping a public copy
> for viewing convenience (with html) here:
>
> https://cirl.berkeley.edu/fperez/static
On Wed, Oct 15, 2008 at 09:45:39AM -0500, Travis E. Oliphant wrote:
> Gabriel Gellner wrote:
> > Some colleagues noticed that var uses biased formula's by default in numpy,
> > searching for the reason only brought up:
> >
> > http://article.gmane.org/gmane.comp.py
Some colleagues noticed that var uses biased formula's by default in numpy,
searching for the reason only brought up:
http://article.gmane.org/gmane.comp.python.numeric.general/12438/match=var+bias
which I totally agree with, but there was no response? Any reason for this? Is
there any way I can
> Let's be clear, there are two very closely related things: recarrays
> and record arrays. Record arrays are just ndarrays with a complicated
> dtype. E.g.
>
> In [1]: from numpy import *
>
> In [2]: ones(3, dtype=dtype([('foo', int), ('bar', float)]))
> Out[2]:
> array([(1, 1.0), (1, 1.0), (1,
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