[Numpy-discussion] Giving numpy the ability to multi-iterate excluding an axis

[John Salvatier]

This thread is a bit old, but since it's not possible to use the C-API is
possible to accomplish this same thing with the Python API?

On Tue, Dec 21, 2010 at 5:12 PM, Mark Wiebe <mwwiebe at gmail.com> wrote:

> On Mon, Dec 20, 2010 at 1:42 PM, John Salvatier <jsalvati at u.washington.edu
> > wrote:
>
>> A while ago, I asked a whether it was possible to multi-iterate over
>> several ndarrays but exclude a certain axis(
>> http://www.mail-archive.com/numpy-discussion@scipy.org/msg29204.html),
>> sort of a combination of PyArray_IterAllButAxis and PyArray_MultiIterNew. My
>> goal was to allow creation of relatively complex ufuncs that can allow
>> reduction or directionally dependent computation and still use broadcasting
>> (for example a moving averaging ufunc that can have changing averaging
>> parameters). I didn't get any solutions, which I take to mean that no one
>> knew how to do this.
>>
>> I am thinking about trying to make a numpy patch with this functionality,
>> and I have some questions: 1) How difficult would this kind of task be for
>> someone with non-expert C knowledge and good numpy knowledge? 2) Does anyone
>> have advice on how to do this kind of thing?
>>
>
> You may be able to do what you would like with the new iterator I've
> written.  In particular, it supports nesting multiple iterators by providing
> either pointers or offsets, and allowing you to specify any subset of the
> axes to iterate.  Here's how the code to do this in a simple 3D case might
> look, for making axis 1 the inner loop:
>
> PyArrayObject *op[2] = {a,b};
> npy_intp axes_outer[2] = {0,2}};
> npy_intp *op_axes[2];
> npy_intp axis_inner = 1;
> npy_int32 flags[2] = {NPY_ITER_READONLY, NPY_ITER_READONLY};
> NpyIter *outer, *inner;
> NpyIter_IterNext_Fn oiternext, iiternext;
> npy_intp *ooffsets;
> char **idataptrs;
>
> op_axes[0] = op_axes[1] = axes_outer;
> outer = NpyIter_MultiNew(2, op, NPY_ITER_OFFSETS,
>                            NPY_KEEPORDER, NPY_NO_CASTING, flags, NULL, 2,
> op_axes, 0);
> op_axes[0] = op_axes[1] = &axis_inner;
> inner = NpyIter_MultiNew(2, op, 0, NPY_KEEPORDER, NPY_NO_CASTING, flags,
> NULL, 1, op_axes, 0);
>
> oiternext = NpyIter_GetIterNext(outer);
> iiternext = NpyIter_GetIterNext(inner);
>
> ooffsets = (npy_intp *)NpyIter_GetDataPtrArray(outer);
> idataptrs = NpyIter_GetDataPtrArray(inner);
>
> do {
>    do {
>       char *a_data = idataptrs[0] + ooffsets[0], *b_data = idataptrs[0] +
> ooffsets[0];
>       /* Do stuff with the data */
>    } while(iiternext());
>    NpyIter_Reset(inner);
> } while(oiternext());
>
> NpyIter_Deallocate(outer);
> NpyIter_Deallocate(inner);
>
> Extending to more dimensions, or making both the inner and outer loops have
> multiple dimensions, isn't too crazy.  Is this along the lines of what you
> need?
>
> If you check out my code, note that it currently isn't exposed as NumPy API
> yet, but you can try a lot of things with the Python exposure.
>
> Cheers,
> Mark
>
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>
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