[Numpy-discussion] SWIG wrappers: Inplace arrays
fullung at gmail.com
Tue Apr 25 14:16:06 CDT 2006
I am using the SWIG Numpy typemaps to wrap some C code. I ran into the
following problem when wrapping a function with INPLACE_ARRAY1.
In Python, I create the following array:
x = array(,dtype='<i4')
When this is passed to the C function expecting an int*, it goes via
obj_to_array_no_conversion in numpy.i where a direct comparison of the
typecodes is done, at which point a TypeError is raised.
In this case:
desired type = int [typecode 5]
actual type = long [typecode 7]
The typecode is obtained as follows:
#define array_type(a) (int)(((PyArrayObject *)a)->descr->type_num)
Given that I created the array with '<i4', I would expect type_num to map to
int instead of long. Why isn't this happening?
Assuming the is a good reason for type_num being what it is, I think
obj_to_array_no_conversion needs to be slightly cleverer about the
conversions it allows. Is there any way to figure out that int and long are
actually identical (at least on my system) using the Numpy C API? Any other
suggestions or comments for solving this problem?
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