[Numpy-discussion] How to call methods from a class with custom matrices parameters with numpy arrays ?
Thu Apr 19 11:17:22 CDT 2007
> Doing the wrapping in an object oriented way is difficult, and maybe
> not that useful. This does not prevent the API exposed to python to be
> OO, of course.
I have some difficulties to do this in an automated way...
I'm trying now to make a derived object from my function, without templates
and, I'm hoping so, with a correct interface i.e. double + 2*int to save
make the conversions with numpy arrays.
> > That works great for C then, not that well for C++...
> Well, this is an inherent problem of C++ when you try to use it from
> other languages, but let's not start this (again :) ),
> The example shows basic wrapping, and some facilities provided by
> numpy to help. Again, ctype is pretty efficient as long as you do not
> need to do convertion. If you call it thousand of times, it will be
> slow, but this is more or less inherent to python (function calls are
> nowhere near as fast as in a compiled language, at least for now).
It's for optimization, so the function will be called several hundreds of
times, I suppose, and I tried porting the whole function to Python, but I'm
not sure that the Python version behaves like the C++ version - the results
are not identic, so... -, thus the wrapping.
SWIG may be better in your case because it is aware of C++ classes,
> and is *compiling* an extension, whereas ctypes does not compile
> anything. This means that you do not have to care about binary
> interfaces problemes between foreign object codes. SWIG parses a prett
> good deal of C++, and is aware of classes (template is another matter,
> obviously). numpy sources contain swig code to process automatically
> numpy arrays (that is convert C representation of a numpy array to a
> simple C array and vice et versa), if I remember correctly.
Yes, I will try to use this solution, I have trouble figuring how passing
the output numpy array, Bill Baxter asked the same question today, at
exactly the same time ;) Well, I saw on the docs that such arrays must be
passed to the function, and already allocated, and that is a problem for
There is also boost.python, but I don't know if its situation towards
> numpy array has changed (eg there was some code lying around to
> represent numpy arrays in C++).
That will be my next quest during the summer ;)
If I were you, and if there are only a few classes and a few member
> functions, I would try the C wrapper called from python first.
It's only one class and one method + the constructor. Not much but I'm a
real beginner in that domain. True, I could use the C API directly...
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