Hi,
I am eager to implement the C version of the set_where function but
would like to do so in a numpy-esque way. Having implemented several
internal and released Python/C packages, I am familiar with the PyArray
object and the PyArrayIterObject and the like. After looking through the
code I
Hi,
Note that the plug-in idea is just my own idea, it is not something
agreed by anyone else. So maybe it won't be done for numpy 1.1, or at
all. It depends on the main maintainers of numpy.
I'm +3 for the plugin idea - it would have huge benefits for
installation and automatic
Hello,
I am encountering a problem (a bug?) with the numpy any function.
Since the python any function behaves in a slightly different way,
I would like to keep using numpy's.
Here is the problem:
$ python
Python 2.5.1 (r251:54863, Jan 26 2008, 01:34:00)
[GCC 4.1.2 (Gentoo 4.1.2)] on linux2
David Cournapeau wrote:
Gnata Xavier wrote:
Ok I will try to see what I can do but it is sure that we do need the
plug-in system first (read before the threads in the numpy release).
During the devel of 1.1, I will try to find some time to understand
where I should put some pragma into
A couple of thoughts on parallelism:
1. Can someone come up with a small set of cases and time them on
numpy, IDL, Matlab, and C, using various parallel schemes, for each of
a representative set of architectures? We're comparing a benchmark to
itself on different architectures, rather than
Hi all,
I looked at line 21902 of dlapack_lite.c, it is,
for (niter = iter; niter = 20; ++niter) {
Indeed the upper limit for iterations in the
linalg.svd code is set for 20. For now I will go with
my method (on earlier post) of squaring the matrix and
then doing svd when the
I cannot confirm the problem on my intel macbook pro using the same
Python and Numpy versions. Although any(numpy.array(large_none)) takes
a significantly longer time than any(numpy.array(large_zero)), the
former does not segfault on my machine.
J.
On 24 Mar 2008, at 14:05, Martin
A couple of thoughts on parallelism:
1. Can someone come up with a small set of cases and time them on
numpy, IDL, Matlab, and C, using various parallel schemes, for each of
a representative set of architectures? We're comparing a benchmark to
itself on different architectures, rather than
It was added as a compile-time #define on the SVN some days ago ;)
Matthieu
2008/3/24, Zachary Pincus [EMAIL PROTECTED]:
Hi all,
I looked at line 21902 of dlapack_lite.c, it is,
for (niter = iter; niter = 20; ++niter) {
Indeed the upper limit for iterations in the
It is a real problem in some communities like astronomers and images
processing people but the lack of documentation is the first one, that
is true.
Even in those communities, I think that a lot could be done at a higher
level, as what IPython1 does (tasks parallelism).
Matthieu
--
French
On Sat, Mar 22, 2008 at 4:25 PM, Charles R Harris
[EMAIL PROTECTED] wrote:
On Sat, Mar 22, 2008 at 2:59 PM, Robert Kern [EMAIL PROTECTED] wrote:
On Sat, Mar 22, 2008 at 2:04 PM, Charles R Harris
[EMAIL PROTECTED] wrote:
Maybe it's time to revisit the template subsystem I pulled out of
Matthieu Brucher wrote:
It is a real problem in some communities like astronomers and images
processing people but the lack of documentation is the first one,
that
is true.
Even in those communities, I think that a lot could be done at a
higher level, as what IPython1
On Mon, Mar 24, 2008 at 10:35 AM, Robert Kern [EMAIL PROTECTED] wrote:
On Sat, Mar 22, 2008 at 4:25 PM, Charles R Harris
[EMAIL PROTECTED] wrote:
On Sat, Mar 22, 2008 at 2:59 PM, Robert Kern [EMAIL PROTECTED]
wrote:
On Sat, Mar 22, 2008 at 2:04 PM, Charles R Harris
[EMAIL
On 24 Mar 2008, at 14:05, Martin Manns wrote:
Hello,
I am encountering a problem (a bug?) with the numpy any function.
Since the python any function behaves in a slightly different way,
I would like to keep using numpy's.
I cannot confirm the problem on my intel macbook pro using
Matthew Brett wrote:
I'm +3 for the plugin idea - it would have huge benefits for
installation and automatic optimization. What needs to be done? Who
could do it?
The main issues are portability, and reliability I think. All OS
supported by numpy have more or less a dynamic library loading
Hi,
This also crashes by numpy 1.0.4 under python 2.5.1. I am guessing it
may be due to numpy.any() probably not understanding the 'None' .
Bruce
Martin Manns wrote:
On 24 Mar 2008, at 14:05, Martin Manns wrote:
Hello,
I am encountering a problem (a bug?) with the numpy any function.
Bruce Southey [EMAIL PROTECTED] wrote: Hi,
This also crashes by numpy 1.0.4 under python 2.5.1. I am guessing it
may be due to numpy.any() probably not understanding the 'None' .
I doubt that because I get the segfault for all kinds of object arrays that I
try out:
~$ python
Python 2.4.5
On Mon, Mar 24, 2008 at 12:12 PM, Gnata Xavier [EMAIL PROTECTED] wrote:
Well it is not that easy. We have several numpy code following like this :
1) open an large data file to get a numpy array
2) perform computations on this array (I'm only talking of the numpy
part here. scipy is
Hi all,
I just got tripped up by this behavior in Numpy 1.0.4:
u = numpy.array([1,3])
v = numpy.array([0.2,0.1])
u+=v
u
array([1, 3])
I think this is highly undesirable and should be fixed, or at least warned
about. Opinions?
Andreas
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Description: This is a digitally
Hi,
True, I noticed that on my system (with 8 Gb memory) that using
works but not 1.
Also, use of a 2 dimensional array also crashes if the size if large enough:
large_m=numpy.vstack((large_none, large_none))
Bruce
Martin Manns wrote:
Bruce Southey [EMAIL PROTECTED] wrote: Hi,
On 24 Mar 2008, at 18:27, Martin Manns wrote:
I cannot confirm the problem on my intel macbook pro using the same
Python and Numpy versions. Although any(numpy.array(large_none))
takes
a significantly longer time than any(numpy.array(large_zero)), the
former does not segfault on my
On Mon, Mar 24, 2008 at 6:04 PM, Lou Pecora [EMAIL PROTECTED] wrote:
--- Matthieu Brucher [EMAIL PROTECTED]
wrote:
It was added as a compile-time #define on the SVN
some days ago ;)
Matthieu
Thanks, Matthieu, that's a good step. But when the
SVD function throws an
Stéfan van der Walt wrote:
On Mon, Mar 24, 2008 at 6:04 PM, Lou Pecora [EMAIL PROTECTED] wrote:
--- Matthieu Brucher [EMAIL PROTECTED]
wrote:
It was added as a compile-time #define on the SVN
some days ago ;)
Matthieu
Thanks, Matthieu, that's a good step. But when the
Robert Kern wrote:
On Mon, Mar 24, 2008 at 12:12 PM, Gnata Xavier [EMAIL PROTECTED] wrote:
Well it is not that easy. We have several numpy code following like this :
1) open an large data file to get a numpy array
2) perform computations on this array (I'm only talking of the numpy
On Mon, Mar 24, 2008 at 6:37 PM, David Cournapeau
[EMAIL PROTECTED] wrote:
That's one of the reason why I was thinking about a gradual move of most
core functionalities of the core toward a separate C library, with a
simple and crystal clear interface, without any reference to any python
Hi Andreas
On Mon, Mar 24, 2008 at 7:28 PM, Andreas Klöckner
[EMAIL PROTECTED] wrote:
I just got tripped up by this behavior in Numpy 1.0.4:
u = numpy.array([1,3])
v = numpy.array([0.2,0.1])
u+=v
u
array([1, 3])
I think this is highly undesirable and should be fixed, or at
Hi Martin
Please file a bug on the trac page: http://projects.scipy.org/scipy/numpy
You may mark memory errors as blockers for the next release.
Confirmed under latest SVN.
Thanks
Stéfan
On Mon, Mar 24, 2008 at 2:05 PM, Martin Manns [EMAIL PROTECTED] wrote:
Hello,
I am encountering a
Hi Joris
Also take a look at the work done by Neal Becker, and posted on this
list earlier this year or end of last. Please go ahead and create a
cookbook entry on the wiki -- that way we have a central plce for
writing up further explorations of this kind (also, let us know on the
list if you
On Montag 24 März 2008, Stéfan van der Walt wrote:
I think this is highly undesirable and should be fixed, or at least
warned about. Opinions?
I know the result is surprising, but it follows logically. You have
created two integers in memory, and now you add 0.2 and 0.1 to both --
not
Andreas Klöckner wrote:
On Montag 24 März 2008, Stéfan van der Walt wrote:
I think this is highly undesirable and should be fixed, or at least
warned about. Opinions?
I know the result is surprising, but it follows logically. You have
created two integers in memory, and now you
On Dienstag 25 März 2008, Travis E. Oliphant wrote:
Question: If it's a known trap, why not change it?
It also has useful applications. Also, it can only happen at with a
bump in version number to 1.1
I'm not trying to make the functionality go away. I'm arguing that
int_array +=
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