[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.
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