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@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion
signature.asc
Description: This is a digitally signed message part
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
