do you mean that the values in the kernel depends on the kernels
position relative to the data to be convolved, or that the kernel is
not composed of homogeneous values but otherwise does not change as it
is slid around the source data?
If the case is the latter, you may be better off doing the co
Stéfan van der Walt a écrit :
> If your kernel varies with i and j, you have little choice but to do
> this at the C level.
>
> Have a look at the Cython convolution example here:
Thanks.
I'm looking at it.
> Alternatively, David Cournapeau can take this opportunity to
> illustrate his very nift
2009/6/24 fred :
> fred a écrit :
>> Hi all,
>>
>> Say I have a 2D array A(nx, ny).
>>
>> In each A[i, j] I want to compute convolve(a, kernel)
>>
>> where a is subarray of A.
>>
>> a and kernel are small besides A.
> I forgot to mention: kernel is not constant, of course.
> It varies vs. others pa
fred a écrit :
> Hi all,
>
> Say I have a 2D array A(nx, ny).
>
> In each A[i, j] I want to compute convolve(a, kernel)
>
> where a is subarray of A.
>
> a and kernel are small besides A.
I forgot to mention: kernel is not constant, of course.
It varies vs. others parameters.
Cheers,
--
Fred
Hi all,
Say I have a 2D array A(nx, ny).
In each A[i, j] I want to compute convolve(a, kernel)
where a is subarray of A.
a and kernel are small besides A.
The problem is that nx & ny are quite "big", ie ~1000, so using a
loop on i & j is forbidden here.
So how can I do what I want? Any idea?
