Hallo!
Thanks, this is interesting !
Do you also know how the situation is with sourceforge/launchpad/trac...
and other popular hosting systems ?
Do they also have these restrictions ?
LG
Georg
Matthew Brett schrieb:
> Hi,
>
> I am just visiting colleagues in the Cuban Neuroscience Center, a
Hallo!
> * A new ARGOUTVIEW suite of typemaps is provided that allows your
> wrapped function
>to provide a pointer to internal data and that returns a numpy
> array encapsulating
>it.
Thanks for integrating it !
> * New typemaps are provided that correctly handle FORTRAN ordered 2D
Hallo!
> First, my plan is to add to numpy.i, typemaps for signatures like the
> following:
>
> %typemap(argout) (double** ARGOUT_ARRAY1, int* DIM1)
>
> It is important to note that even though the same argument *names* are
> used, this is a different typemap signature than
>
> %typem
Hallo!
As chris said, I need to make an example:
http://grh.mur.at/software/numpy2carray.tar.gz
I added the following class-example:
class_example.h: the C++ code
class_example.i: the SWIG interface file
class_example_usage.py: example usage in python
And some comments:
Bill Spotz schrieb:
> H
Hallo!
> OK, so the key here is the *internal* matrix. I think you need to
> provide a way to extract that matrix from the C++ application as a numpy
> array. Then you can provide it to your function/method as an INPLACE
> array. No new memory will be allocated.
[...]
> The INPLACE typemaps
Hallo!
> Is there any doc on numpy.i usage?
yes there is a pdf in /numpy/doc/swig !
LG
Georg
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Hallo!
> Of course : http://matt.eifelle.com/item/5
> It's a basic version of the wrapper I use in my lab (pay attention to
> the constructor for instance), I hope you will be able to do something
Thanks !
But this assumes that the data in my C++ library is stored in a
PyArrayObject ?
This is
Hallo!
> E.g. in my algorithm I can have a very big internal matrix in C++ (say
> 700 MB - in fortran style). Now I want to have this matrix in numpy to
> plot some parts of it, get some data out of it ... whatever - if I again
> allocate an array of the same size, I am out of memo
Hallo!
> Really? I worked pretty hard to avoid copies when they were not
> necessary. For the ARGOUT typemaps, I allocate an array of the
> requested size and then pass its data buffer to your function. If
Yes but this means that you again allocate an array of the same size.
E.g. in my a
Hallo!
> How is this better/different than numpy.i in:
>
> numpy/doc/swig/numpy.i
The problem I had with numpy.i:
- it copies the arrays on output (Argout Arrays) which was not possible
for my algorithms (I have some very big matrices)
- it is not possible to 2D or 3D Argout Arrays (why?), in
Hallo!
Because I had some troubles in wrapping my C++ library in python/numpy,
I did (another) numpy2carray.i file for SWIG.
With that interface file it is possible to input/output arrays with or
without copying data (I also included an example for an interface to
fortran style arrays).
I am s
Hallo!
> This depends on what you are trying to do, but generally, I find that if
> you can afford it memory-wise, it is much faster to just get a C
> contiguous array if you treat your C array element per element. If you
Yes, but the problem is that this data is very big (up to my memory
lim
Hallo!
I found now a way to get the data:
> Therefore I do the following (2D example):
>
>obj = PyArray_FromDimsAndData(2, dim0, PyArray_DOUBLE, (char*)data);
>PyArrayObject *tmp = (PyArrayObject*)obj;
>tmp->flags = NPY_FARRAY;
if in that example I also change the strides:
int s
Hallo!
I have the following problem: I get a data array in column major storage
order and want to use it as numpy array without copying data.
Therefore I do the following (2D example):
obj = PyArray_FromDimsAndData(2, dim0, PyArray_DOUBLE, (char*)data);
PyArrayObject *tmp = (PyArrayObject
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