[Numpy-discussion] Why does np.repeat build a full array?

Sebastian Berg sebastian at sipsolutions.net
Tue Dec 15 02:56:45 EST 2015

On Di, 2015-12-15 at 17:49 +1100, Juan Nunez-Iglesias wrote:
> Hi,
> I've recently been using the following pattern to create arrays of a
> specific repeating value:
> from numpy.lib.stride_tricks import as_strided
> value = np.ones((1,), dtype=float)
> arr = as_strided(value, shape=input_array.shape, strides=(0,))
> I can then use arr e.g. to count certain pairs of elements using
> sparse.coo_matrix. It occurred to me that numpy might have a similar
> function, and found np.repeat. But it seems that repeat actually
> creates the full, replicated array, rather than using stride tricks to
> keep it small. Is there any reason for this?

Two reasons:
 1. For most arrays, arrays even the simple repeats cannot be done with
stride tricks. (yours has a dimension size of 1)
 2. Stride tricks can be nice, but they can also be
unexpected/inconsistent when you start writing to the result array, so
you should not do it (and the array should preferably be read-only IMO,
as_strided itself does not do that).

But yes, there might be room for a function or so to make some stride
tricks more convenient.

- Sebastian

> Thanks!
> Juan.
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at scipy.org
> https://mail.scipy.org/mailman/listinfo/numpy-discussion

-------------- next part --------------
A non-text attachment was scrubbed...
Name: signature.asc
Type: application/pgp-signature
Size: 819 bytes
Desc: This is a digitally signed message part
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20151215/5a5dbfa4/attachment.sig>

More information about the NumPy-Discussion mailing list