On Wed, Feb 06, 2008 at 03:23:43AM -0600, Kent-Andre Mardal wrote:
> No problem, it is now under BSD. OK?
Perfect. Thank you.
Glen
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How does Instant compare to scipy.weave !?
-Sebastian Haase
On Feb 5, 2008 11:26 PM, Glen W. Mabey <[EMAIL PROTECTED]> wrote:
> On Tue, Feb 05, 2008 at 12:16:02PM -0600, Kent-Andre Mardal wrote:
> > We have created a small Python module Instant (www.fenics.org/instant) on
> > top
> > of SWIG,
On Tue, Feb 05, 2008 at 12:16:02PM -0600, Kent-Andre Mardal wrote:
> We have created a small Python module Instant (www.fenics.org/instant) on top
> of SWIG, which makes integration of C/C++ and NumPy arrays easy in some cases.
Hello,
Thank you for posting about instant. I think it looks like a
Dear Vince,
You probably have heard better solutions but I think what I do works and
is simple to learn. When I need to call C++ code from Python, I write a
wrapper extern "C" function that calls the C++ function that returns the
result. Then I just use ctypes to call the extern "C" function fr
Vince Fulco gmail.com> writes:
>
> Dear Numpy Experts- I find myself working with Numpy arrays and
> wanting to access *simple* C++ functions for time series returning the
> results to Numpy. As I am a relatively new user of Python/Numpy, the
> number of paths to use in incorporating C++ code
--- Gael Varoquaux <[EMAIL PROTECTED]>
wrote:
Re: ctypes
> I don't use windows much. One thing I liked about
> ctypes when I used it,
> was that what I found it pretty easy to get working
> on both Linux and
> Windows.
>
> Gaël
I got ctypes to install easily on Mac OS X 10.4.11 and
it passe
On Tue, Feb 05, 2008 at 06:45:25AM -0800, Lou Pecora wrote:
> Hmmm... last time I tried ctypes it seemed pretty
> Windows oriented and I got nowhere. But enough people
> have said how easy it is that I'll give it another
> try.
I don't use windows much. One thing I liked about ctypes when I used
Hmmm... last time I tried ctypes it seemed pretty
Windows oriented and I got nowhere. But enough people
have said how easy it is that I'll give it another
try.
Believe me, I'd be happy to be wrong and find a nice
easy way to pass NumPy arrays and such. Thanks.
-- Lou Pecora
--- Gael Varoquaux
On Feb 5, 2008 11:52 AM, Gael Varoquaux <[EMAIL PROTECTED]> wrote:
> On Tue, Feb 05, 2008 at 11:48:38AM +0100, Ondrej Certik wrote:
> > I use Cython, mostly for the same reasons Gael is using ctypes - it's
> > trivial.
>
> Actually, when I want to do something really trivial, I use
> scipy.weave.i
Gael Varoquaux wrote:
> On Tue, Feb 05, 2008 at 11:48:37AM +0100, Sebastian Haase wrote:
>> Thanks fr the reply.
>> How about "manual" overloading. I mean, if -- for example -- I have
>> two functions mmms_b and mmms_i in C, I could still use ctypes; could
>> I then "merge" them into one python fun
>
> This is what SWIG must be doing internally -- right ?!
>
Yes, it is with an additional typemap that checks the type of the data.
I don't think that it is a good idea for numpy to add such
multi-dispatching, it is not its job. There are a lot of ways to do it, and
besides it would be very cumb
On Tue, Feb 05, 2008 at 11:48:38AM +0100, Ondrej Certik wrote:
> I use Cython, mostly for the same reasons Gael is using ctypes - it's trivial.
Actually, when I want to do something really trivial, I use
scipy.weave.inline ( see http://scipy.org/PerformancePython for an
example of scipy.weave.inli
On Tue, Feb 05, 2008 at 11:48:37AM +0100, Sebastian Haase wrote:
> Thanks fr the reply.
> How about "manual" overloading. I mean, if -- for example -- I have
> two functions mmms_b and mmms_i in C, I could still use ctypes; could
> I then "merge" them into one python function, which "re-routes"
> d
On Feb 5, 2008 11:23 AM, David Cournapeau <[EMAIL PROTECTED]> wrote:
> Gael Varoquaux wrote:
> > On Tue, Feb 05, 2008 at 09:15:29AM +0100, Sebastian Haase wrote:
> >
> >> Can ctypes do this ?
> >>
> >
> > No. Ctypes is only a way of loading C (and not C++) libraries in Python.
> > That makes it ver
On Feb 5, 2008 9:21 AM, Gael Varoquaux <[EMAIL PROTECTED]> wrote:
> On Tue, Feb 05, 2008 at 09:15:29AM +0100, Sebastian Haase wrote:
> > Can ctypes do this ?
>
> No. Ctypes is only a way of loading C (and not C++) libraries in Python.
> That makes it very simple, but not very powerful.
>
> Gaël
(so
Gael Varoquaux wrote:
> On Tue, Feb 05, 2008 at 09:15:29AM +0100, Sebastian Haase wrote:
>
>> Can ctypes do this ?
>>
>
> No. Ctypes is only a way of loading C (and not C++) libraries in Python.
> That makes it very simple, but not very powerful.
>
I would not call ctypes not very powerf
On Tue, Feb 05, 2008 at 09:15:29AM +0100, Sebastian Haase wrote:
> Can ctypes do this ?
No. Ctypes is only a way of loading C (and not C++) libraries in Python.
That makes it very simple, but not very powerful.
Gaël
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On Feb 4, 2008 9:05 PM, Christopher Barker <[EMAIL PROTECTED]> wrote:
> Lou Pecora wrote:
> > I
> > would recommend using the C API
>
> I would recommend against this -- there is a lot of code to write in
> extensions to make sure you do reference counting, etc, and it is hard
> to get right.
>
> M
Bill Spotz wrote:
> On Feb 4, 2008, at 1:05 PM, Christopher Barker wrote:
>
>> Boost::python -- best for writing custom extensions in C++ -- also can
>> be used for interfacing with legacy C++. There were boost array
>> classes
>> for numpy -- are these being maintained?
>
> There are boo
For comparison of ctypes and SWIG wrappers of a simple C++ codebase,
feel free to take a look at the code for scikits.ann
(http://scipy.org/scipy/scikits/wiki/AnnWrapper). The original wrapper
was written using SWIG and the numpy typemaps. Rob Hetland has coded
an almost-the-same API wrapper using
On Mon, Feb 04, 2008 at 12:49:58PM -0800, Lou Pecora wrote:
> So, for those looking for speed up through some
> external C or C++ code, I would say (trying to be fair
> here), try what Chris recommends below, if you want,
> but IMHO, none of it is trivial. If you get it to
> work, great. If not,
--- Christopher Barker <[EMAIL PROTECTED]> wrote:
> Lou Pecora wrote:
> > I
> > would recommend using the C API
>
> I would recommend against this -- there is a lot of
> code to write in
> extensions to make sure you do reference counting,
> etc, and it is hard
> to get right.
Well, fair enou
On Mon, Feb 04, 2008 at 12:05:45PM -0800, Christopher Barker wrote:
> ctypes -- [...] Can it call C++ directly at all?
No, but you can use 'extern "C"' in you cpp file, if you have controle
over the file.
Gaël
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Christopher Barker wrote:
> Neal Becker wrote:
>> I have a variety of experiments that I put in this mercurial repo:
>> https://nbecker.dyndns.org/hg/
>>
>> The primary aim of this is to reuse c++ code written to a generic
>> container interface, with numpy.
>
> Neal,
>
> I'd love to hear more
On Feb 4, 2008, at 1:05 PM, Christopher Barker wrote:
> Boost::python -- best for writing custom extensions in C++ -- also can
> be used for interfacing with legacy C++. There were boost array
> classes
> for numpy -- are these being maintained?
There are boost array classes for Numeric, and *t
Neal Becker wrote:
> I have a variety of experiments that I put in this mercurial repo:
> https://nbecker.dyndns.org/hg/
>
> The primary aim of this is to reuse c++ code written to a generic container
> interface, with numpy.
Neal,
I'd love to hear more about this. Do you have a two paragraph
d
Lou Pecora wrote:
> I
> would recommend using the C API
I would recommend against this -- there is a lot of code to write in
extensions to make sure you do reference counting, etc, and it is hard
to get right.
Much of it is also boiler-plate code, so it makes more sense to have
that code auto-
On Feb 4, 2008, at 9:39 AM, Matthieu Brucher wrote:
> This can be avoided, but you'll have to use more powerful tools. I
> would advice SWIG (see my blog for some examples with C++ and SWIG).
Note that a lot of work has been done to bridge between numpy and
swig. There is a swig interface f
I have a variety of experiments that I put in this mercurial repo:
https://nbecker.dyndns.org/hg/
The primary aim of this is to reuse c++ code written to a generic container
interface, with numpy.
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--- Matthieu Brucher <[EMAIL PROTECTED]>
wrote:
> Whatever solution you choose (Boost.Python, ...),
> you will have to use the
> Numpy C API at least a little bit. So Travis' book
> is a good start. As Gaël
> told you, you can use ctypes if you wrap manually
> every method with a C
> function an
2008/2/4, Lou Pecora <[EMAIL PROTECTED]>:
>
> Dear Mr. Fulco ,
>
> This may not be exactly what you want to do, but I
> would recommend using the C API and then calling your
> C++ programs from there (where interface functions to
> the C++ code is compiled in the extern "C" {, }
> block. I will b
Dear Mr. Fulco ,
This may not be exactly what you want to do, but I
would recommend using the C API and then calling your
C++ programs from there (where interface functions to
the C++ code is compiled in the extern "C" {, }
block. I will be doing this soon with my own project.
Why? Because t
On Mon, Feb 04, 2008 at 11:02:29AM -0500, Vince Fulco wrote:
> Any trailheads for the simplest approach
I find ctypes very easy to understand. See
http://www.scipy.org/Cookbook/Ctypes for simple instructions.
HTH,
Gaël
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Dear Numpy Experts- I find myself working with Numpy arrays and
wanting to access *simple* C++ functions for time series returning the
results to Numpy. As I am a relatively new user of Python/Numpy, the
number of paths to use in incorporating C++ code into one's scripts is
daunting. I've attemp
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