[Numpy-discussion] Proposal of new function: iteraxis()
Fri Apr 26 12:02:00 CDT 2013
I like this, thank you Phil.
>From what I can see, the ordering of the returned slices when you use more
than one axis (ie: slices(a, [1,2]), increments the last axis fastest.
Does this makes sense based on the default ordering of, say, nditer()? I
know that C-order (row major) and Fortran order (column major) are two ways
of ordering the returned values- which does this default to? Is there a
default across numpy?
On Fri, Apr 26, 2013 at 9:56 AM, Phil Elson <email@example.com> wrote:
> I didn't find the rollaxis solution particularly obvious and also had to
> think about what rollaxis did before understanding its usefulness for
> Now that I've understood it, I'm +1 for the statement that, as it stands,
> the proposed iteraxis method doesn't add enough to warrant its inclusion.
> That said, I do think array iteration could be made simpler (or the
> function I've missed better documented!). I've put together an
> implementation of a "slices" function which can return subsets of an array
> based on the axes provided (a generalisation of iteraxis but implemented
> slightly differently):
> def slices(a, axes=-1):
> indices = np.repeat(slice(None), a.ndim)
> # turn axes into a 1d array of axes indices
> axes = np.array(axes).flatten()
> bad_indices = (axes < (-a.ndim + 1)) | axes > (a.ndim - 1)
> if np.any(bad_indices):
> raise ValueError('The axis index/indices were out of range.')
> # Turn negative indices into real indices
> axes[axes < 0] = a.ndim + axes[axes < 0]
> if np.unique(axes).shape != axes.shape:
> raise ValueError('Repeated axis indices were given.')
> indexing_shape = np.array(a.shape)[axes]
> for ind in np.ndindex(*indexing_shape):
> indices[axes] = ind
> yield a[tuple(indices)]
> This can be used simply with:
> >>> a = np.ones([2, 3, 4, 5])
> >>> for s in slices(a, 2):
> ... print s.shape
> (2, 3, 5)
> (2, 3, 5)
> (2, 3, 5)
> (2, 3, 5)
> Or slightly with the slightly more complex:
> >>> len(list(slices(a, [2, -1])))
> Without focusing on my actual implementation, would this kind of interface
> be more desirable?
> On 26 April 2013 12:33, Robert Kern <firstname.lastname@example.org> wrote:
>> On Fri, Apr 26, 2013 at 12:26 PM, Andrew Giessel
>> <email@example.com> wrote:
>> > I agree with Charles that rollaxis() isn't immediately intuitive.
>> > It seems to me that documentation like this doesn't belong in
>> rollaxis() but
>> > instead wherever people talk about indexing and/or iterating over an
>> > Nothing about the iteration depends on rollaxis(), rollaxis is just
>> > you a different view of the array to call __getitem__() on, if I
>> > correctly.
>> Docstrings are perfect places to briefly describe and demonstrate
>> common use cases for a function. There is no problem with including
>> the example that I wrote in the rollaxis() docstring.
>> In any case, whether you put the documentation in the rollaxis()
>> docstring or in one of the indexing/iteration sections, or
>> (preferably) both, I strongly encourage you to do that first and see
>> how it goes before adding a new alias.
>> Robert Kern
>> NumPy-Discussion mailing list
> NumPy-Discussion mailing list
Andrew Giessel, PhD
Department of Neurobiology, Harvard Medical School
220 Longwood Ave Boston, MA 02115
ph: 617.432.7971 email: firstname.lastname@example.org
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