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, which
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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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.
Much of it is
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 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
(sorry, this
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 powerful :) For
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 very simple, but not
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
depending
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
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
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 function, which
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.inline (
--- 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 passed the
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 it,
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
Vince Fulco vfulco1 at 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++
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 from
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
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
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 and
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
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
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 be doing
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 about this. Do
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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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, you
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
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 boost array
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
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
--- 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 enough to some
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