On 31/05/07, Travis Oliphant [EMAIL PROTECTED] wrote:
2) I think it's scope should be limited to papers that describe
algorithms and code that are in NumPy / SciPy / SciKits. Perhaps we
could also accept papers that describe code that depends on NumPy /
SciPy that is also easily available.
Hi,
1) I'd like to get it going so that we can push out an electronic issue
after the SciPy conference (in September)
That would be great for the fame of numpy and scipy :)
2) I think it's scope should be limited to papers that describe
algorithms and code that are in NumPy / SciPy /
Hi,
I can see your point I think, that situation 1 seems to be the more
common and obvious, and coming at it from outside, you would have
thought that a.byteswap would change both.
I think the reason that byteswap behaves the way it does is that for
situation 1 you often don't actually
Albert Strasheim wrote:
Hello
I took a quick look at the code, and it seems like new_fcompiler(...) is too
soon to throw an error if a Fortran compiler cannot be detected.
Instead, you might want to return some kind of NoneFCompiler that throws an
error if the build actually tries to
Hi all,
I've got an easy question for you. I looked in Travis' book, but I couldn't
figure out the answer...
If I have an array1D (obtained reading a stream of numbers with
numpy.fromfile) like that:
In [150]: data
Out[150]: array([ 2., 3., 4., 3., 4., 5., 4., 5., 6., 5., 6.,
7.],
I agree with this idea. Very good. Although I also
agree with Anne Archibald that the requirement of an
article in the journal to submit code is not a good
idea. I would be willing to contribute an article on
writing C extensions that use numpy arrays. I
already have something on this on the
A colleague of mine is trying to update our production environment
with the latest releases of numpy, scipy, mpl and ipython, and is
worried about the lag time when there is a new numpy and old scipy,
etc... as the build progresses. This is the scheme he is considering,
which looks fine to me,
On 5/31/07, Matthew Brett [EMAIL PROTECTED] wrote:
Hi,
That would get them all built as a cohesive set. Then I'd repeat the
installs without PYTHONPATH:
Is that any different from:
cd ~/src
cd numpy
python setup.py build
cd ../scipy
python setup.py build
Well, the scipy
Ah, yes, I was typing too fast, thinking too little.
On 5/31/07, John Hunter [EMAIL PROTECTED] wrote:
On 5/31/07, Matthew Brett [EMAIL PROTECTED] wrote:
Hi,
That would get them all built as a cohesive set. Then I'd repeat the
installs without PYTHONPATH:
Is that any different
Anne Archibald wrote:
On 31/05/07, Travis Oliphant [EMAIL PROTECTED] wrote:
2) I think it's scope should be limited to papers that describe
algorithms and code that are in NumPy / SciPy / SciKits. Perhaps we
could also accept papers that describe code that depends on NumPy /
SciPy that is
Matthieu Brucher wrote:
For this point, I have the same opinion as Anne :
- having an equivalence between cde and article is raising the entry
level, but as Anne said, some code could be somehow too trivial ?
- a peer-review process implies that an article can be rejected, so
the code is
lorenzo bolla wrote:
Hi all,
I've got an easy question for you. I looked in Travis' book, but I
couldn't figure out the answer...
If I have an array1D (obtained reading a stream of numbers with
numpy.fromfile) like that:
In [150]: data
Out[150]: array([ 2., 3., 4., 3., 4., 5.,
I am not finding an answer to this question in the latest numpy
documentation. I have a package that still uses Numeric (GDAL with
python bindings). Is this valid code that will work as expected to
convert the Numeric array to a numpy array (very simplified from my
script)?
import numpy
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Hi!
I am using numpy-1.0.1 and ran into problems with 4 routines in
lapack_litemodule.c on 64 bit machines. Traced it back to parsing of
ints as longs. This has been fixed in numpy-1.0.3 for three of the
routines. lapack_lite_zgeqrf() still has the
2007/5/31, Travis Oliphant [EMAIL PROTECTED]:
1) I'd like to get it going so that we can push out an electronic issue
after the SciPy conference (in September)
Such a journal is a very good idea indeed. This would also support the
credibility of python/scipy/numpy for an academic audience that
Hello there,
I'm new here, so excuse me if the solution is trivial:
i have installed ATLAS and LAPACK on my ubuntu 7 dual core intel machine.
now, when i try to install numpy, it tells me it doesn't find these
libraries:
$ python setup.py install
Running from numpy source directory.
F2PY
Lou Pecora wrote:
I agree with this idea. Very good. Although I also
agree with Anne Archibald that the requirement of an
article in the journal to submit code is not a good
idea. I would be willing to contribute an article on
writing C extensions that use numpy arrays. I
already have
Philip Riggs wrote:
I am not finding an answer to this question in the latest numpy
documentation. I have a package that still uses Numeric (GDAL with
python bindings). Is this valid code that will work as expected to
convert the Numeric array to a numpy array (very simplified from my
[EMAIL PROTECTED] wrote:
Hello there,
I'm new here, so excuse me if the solution is trivial:
i have installed ATLAS and LAPACK on my ubuntu 7 dual core intel machine.
now, when i try to install numpy, it tells me it doesn't find these
libraries:
$ python setup.py install
Running from
Anne Archibald wrote:
I implemented the Kuiper statistic and would be happy to
contribute it to scipy (once it's seen a bit more debugging), but it's
quite adequately described in the literature already, so it doesn't
seem worth writing an article about it.
It could be a very short article
I'm trying to compile a simple Fortran code with f2py but I get a bunch
of errors apparently related to my setup of python + numpy + ifort.
The final error is:
error: Command ifort -L/Users/acorriga/pythonroot/lib
/tmp/tmp9KOZQM/tmp/tmp9KOZQM/src.linux-i686-2.5/simplemodule.o
Well just go to
http://projects.scipy.org/mailman/listinfo/numpy-discussion and enter
your email address in the form.
Nice to see some one from LKB interested in numpy. You might want to talk
to Thomas Nirrengarten, from the Haroche group, is has been learning
Python and numpy recently.
Cheers,
I was wondering if anyone has thought about accelerating NumPy with a
GPU. For example nVidia's CUDA SDK provides a feasible way to offload
vector math onto the very fast SIMD processors available on the GPU.
Currently GPUs primarily support single precision floats and are not
IEEE compliant, but
On 5/31/07, Martin Ünsal [EMAIL PROTECTED] wrote:
I was wondering if anyone has thought about accelerating NumPy with a
GPU. For example nVidia's CUDA SDK provides a feasible way to offload
vector math onto the very fast SIMD processors available on the GPU.
Currently GPUs primarily support
Hi Martin,
I was wondering if anyone has thought about accelerating NumPy with a
GPU. For example nVidia's CUDA SDK provides a feasible way to offload
vector math onto the very fast SIMD processors available on the GPU.
Currently GPUs primarily support single precision floats and are not
Martin Ünsal martinunsal at gmail.com writes:
I was wondering if anyone has thought about accelerating NumPy with a
GPU. For example nVidia's CUDA SDK provides a feasible way to offload
vector math onto the very fast SIMD processors available on the GPU.
Currently GPUs primarily support
Robert Kern wrote:
[EMAIL PROTECTED] wrote:
Hello there,
I'm new here, so excuse me if the solution is trivial:
i have installed ATLAS and LAPACK on my ubuntu 7 dual core intel machine.
now, when i try to install numpy, it tells me it doesn't find these
libraries:
$ python setup.py
This is very much worth pursuing. I have been working on things
related to this on and off at my day job. I can't say specifically
what I have been doing, but I can make some general comments:
* It is very easy to wrap the different parts of cude using ctypes and
call it from/numpy.
* Compared
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