From what I can see, the ordering of the returned slices when you use more
I like this, thank you Phil. 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? best, On Fri, Apr 26, 2013 at 9:56 AM, Phil Elson <pelson.pub@gmail.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 iteration. 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]))) 20
Without focusing on my actual implementation, would this kind of interface be more desirable?
Cheers,
On 26 April 2013 12:33, Robert Kern <robert.kern@gmail.com> wrote:
On Fri, Apr 26, 2013 at 12:26 PM, Andrew Giessel <andrew_giessel@hms.harvard.edu> 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 array. Nothing about the iteration depends on rollaxis(), rollaxis is just giving you a different view of the array to call __getitem__() on, if I understand 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@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
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-- Andrew Giessel, PhD Department of Neurobiology, Harvard Medical School 220 Longwood Ave Boston, MA 02115 ph: 617.432.7971 email: andrew_giessel@hms.harvard.edu