[Numpy-discussion] numpy c api general array handling

Mark Wiebe mwwiebe@gmail....
Wed Jun 8 10:49:30 CDT 2011


I believe what you may want is PyArray_ContiguousFromAny instead of
PyArray_ContiguousFromObject.

Cheers,
Mark

On Wed, Jun 8, 2011 at 2:58 AM, Yoshi Rokuko <yoshi@rokuko.net> wrote:

> hey,
>
> i'm writing my first python module in c using numpy/arrayobject.h
> and i have some problems with different platforms (both linux but
> really different setup) so i suspect my array handling is not cor-
> rect.
>
> i'm used to c arrays and want to access large numpy arrays from
> within my c module with no strange array-iter-methods. So what are
> your remarks to the following:
>
>   PyArg_ParseTuple(args, "OO|ii", &arg1, &arg2, &start, &stop);
>   index = (PyArrayObject *) PyArray_ContiguousFromObject(arg1,
>                             PyArray_INT, 1, 1);
>   ix = (int *)index->data;
>
> then using like:
>
>   for(k = ix[i]; k < ix[i+1]; k++) l = ix[k];
>
> this seems to work pretty well, but real problems come with:
>   PyArg_ParseTuple(args, "O", &arg);
>   adjc = (PyArrayObject *) PyArray_ContiguousFromObject(arg,
>                            PyArray_INT, 2, 2);
>   a = (int *)adjc->data;
>
> and then using like:
>
>   aik = a[i + n * k];
>
> it seems like on one system it does not accept 2d numpy arrays just
> 1d ones or i must hand him a list of 1d numpy arrays like that:
>
>   >>> A = np.array([[1,0],[0,1]])
>   >>> B = my.method(list(A))
>
> i would prefer to avoid the list() call in python.
>
> what are your remarks on performance would it be faster to do:
>
>   PyArg_ParseTuple(args, "OO|ii", &arg1, &arg2, &start, &stop);
>   index = (PyArrayObject *) PyArray_ContiguousFromObject(arg1,
>                             PyArray_INT, 1, 1);
>   ix = malloc(n * sizeof(int));
>   for(i = 0; i < n; i++)
>       ix[i] = (int *)index->data[i];
>
> and then use ix[] (i call a lot on ix).
>
> thank you and best regards, yoshi
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