On Di, 2015-12-15 at 08:56 +0100, Sebastian Berg wrote: > 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. >
Actually, your particular use-case is covered by the new `broadcast_to` function. > - Sebastian > > > > > Thanks! > > > > > > Juan. > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@scipy.org > > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion
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