Hi,
> I've now got a bit more time.
>
> I don't know how things are going at Sage days; but if you're still up
> for it, and e.g. Robert has an hour for you later on, I could spend some
> time posting an outline for how I'd go about the (2) project and then
> perhaps Robert could mentor a bit from there.
>
> I.e. the goal would be to allow for instance
>
> cdef np.ndarray[int, ndim=3] arr1 = ..., arr2
> for idx in cython.iterate(arr1, arr2):
> arr1[idx] = arr1[idx] + arr2[idx]
>
> where idx is some "psuedo-tuple" of ndim length, and have it compile to
> a native loop.
I have been swamped the past week trying to get a research project
back on track, so unfortunately I haven't been able to take advantage
of sage days here :-(. Bummer. However, I still want to help out
with this and take up your mentoring offer and work on this. To be honest,
I probably won't have a significant chunk of time, though, until after June 5.
I'm wondering, though, if it would be better to do this in two stages.
It seems like having a type, say index_tuple, which the user can
define and then manipulate. It seems we would be doing this anyway,
and explicitly exposing it to the user could have use cases. In the C
code, it seems like it'd just be an int array.
e.g.
cdef size_t i
cdef index_tuple[2] idx
cdef ndarray[double, ndim=2] A
idx[0] = 0
for 0 <= i < A.shape[1]:
idx[1] = i
A[idx] = 1
Obviously this is a simple example, but there might easily be other
use cases, such as passing indices to a function, etc..
What do you think?
--Hoyt
++++++++++++++++++++++++++++++++++++++++++++++++
+ Hoyt Koepke
+ University of Washington Department of Statistics
+ http://www.stat.washington.edu/~hoytak/
+ [email protected]
++++++++++++++++++++++++++++++++++++++++++
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