[Cython] Automatic buffer dtype conversion?

[Dag Sverre Seljebotn]

Hei der!

Magnus Lie Hetland wrote:
> Hi!
> 
> I've been trying to get the simple Cython+NumPy example from Robert  
> Bradshaw's slides to work:
> 
>> # footest.pyx
> 
>> cimport numpy
>>
>> def sum(x):
>>     cdef numpy.ndarray[int, ndim=1] arr = x
>>     cdef int i, s = 0
>>     for i in range(arr.shape[0]):
>>         s += arr[i]
>>     return s
> 
> I get it to compile/link, but then I try to actually use it, with the  
> following code:
> 
>> import footest
>> import numpy as np
>>
>> a = np.arange(1000, dtype=np.int)
>> print footest.sum(a)
> 
> The np.int shouldn't be necessary -- and I started without it -- but  
> even *with* it, I get the following error:
> 
>>   File "footest.pyx", line 4, in footest.sum (footest.c:392)
>>     cdef numpy.ndarray[int, ndim=1] arr = x
>> ValueError: Buffer dtype mismatch (expected int, got long)

Yes, this is very expected on 64-bit systems, I suppose Robert's slides 
are in error.

Basically the "np.int" type object is defined (by NumPy) to be long 
(probably on merit of being the most convenient int type; read "np.int" 
as saying "Integer", not a C int).

To be safe with these things, you should use the compile-time types 
defined in the numpy cimport:

cdef numpy.ndarray[numpy.int_t, ndim=1] arr = x

numpy.int_t is typedef-ed to always be whatever np.int refers to.

If you really want a C int, use e.g. numpy.int32(_t).

-- 
Dag Sverre