[Numpy-discussion] access ndarray in C++

Christopher Barker Chris.Barker@noaa....
Wed Apr 23 14:08:40 CDT 2008


Thomas Hrabe wrote:
> One can find multiple approaches to arrays, the old numeric array and 
> the new ndarray. The new stuff seems to be backward compatible.

mostly, yes. numpy (ndarray) is the only option going forward, as it's 
the only one being maintained.

> However, where is a free  documentation of the ndarray?

You are right, the most complete set is Travis' book. It's a pretty good 
deal when you consider that he wrote much of numpy -- if it saves you an 
hour, it's worth the money!

That being said, I think you were pointed to:

http://projects.scipy.org/scipy/numpy/wiki/NumPyCAPI

Which should get you going, though it does seem to be missing your key 
question:

> Which headers do I have to use in order to access the ndarray object 
> that, in my eyes, should be compatible wit PyObject in some way?

#include <numpy/arrayobject.h>

You should use distutils to compile your extension, and in your 
setup.py, you can put:

include_dirs=[numpy.get_include()]

and the header should be found.

> run in C should look like this:
> PyObject run{
> PyObject* ndArray;
> PyArg_ParseTuple( argv, ???? ,ndArray);

I think you had that right before -- you were just using the wrong headers:

PyArg_ParseTuple(args, "O!",&PyArray_Type, &array)

> Is it possible to access the ndarray object like this?

yes, something like that certainly should work.

When you've got it worked out, please add it to the Wiki.

I'd poke around the wiki, and this mailing list archives, for more examples.

NOTE:
Most folks now think that the pain of writing extensions completely by 
hand is not worth it -- it's just too easy to make reference counting 
mistakes, etc. Most folks are now using one of:

Cython (or Pyrex)
SWIG
ctypes

For example, the SWIG typemaps distributed with numpy make it very easy 
to pass a numpy array into a C function such as:

void MyFunc(int i, int j, int k, double *arr)

where *arr is a pointer to a block of doubles that represent an (i,j,k) 
3-d array.

Equally easy methods are available with Cython and ctypes.

-Chris


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