[Cython] accessing an array of ints

[Dag Sverre Seljebotn]

Brian Blais wrote:
> Hello,
>
> If I have an array of ints, as in numpy:
>
> a=numpy.zeros(5,int)
>
> and I call a cython function like:
>
> myfun(a)
>
> and in the cython I have:
>
> cpdef myfun(c_numpy.ndarray A):
>
>     # stuff here
>
>
> how can I access the data pointer?  I tried:
>
>     cdef int *ap=<int *> A.data
>
> but that doesn't seem to work (it works for double *, but not int  
> *).  I must be missing something really simple.
>   
1) Be aware that the "int" is really two different types (the latter one 
being a C "int", the former an identifier for numpy). Better use 
"numpy.int32" for numpy.zeros and a datatype that you know is 32 bit int 
in the cdef. I think that what you have written will fail on 64- bit 
machines but I'm not sure (could imagine that NumPy would choose int64 
as the default "int", while the C compiler would stick with 32 bit 
*shrug*). There are some npy_int32 etc. typedefs/defines in the NumPy 
header files that are better used for C types rather than plain "int".

2) It will still only work if you have exactly the array created by zero 
above. I.e., if you instead pass something like

numpy.zeros(10, int)[::-2]

for instance, then the buffer isn't modified -- instead, something 
called "strides" is set in the struct which tells you to iterator "-2" 
for every step along the 1st dimension. Same goes for 
numpy.zeros((5,5,5), int)[1,:,2] and so on.

So
a) Either make absolutely sure you have a C-contiguous array
or
b) Assign ap as you do, but access it like this:

a[i * A.strides[0]]

rather than a[i]. (a[i*A.strides[0] + j*A.strides[1]] will give you 2D 
access and so on)

Does this answer your question?

Dag Sverre