Hello, I would like to propose adding the `out` array as an optional parameter to `bincount`. This makes `bincount` very useful when iteratively tallying data with large indices.
Consider this example tallying batches of values from some fictional source of data: >>> tally = np.zeros(10000**2) >>> for indices, weights in read_sensor_data(): ... tally += np.bincount(indices, weights, 10000**2) # slow: repeatedly adding large arrays This could be trivially sped up: >>> tally = np.zeros(10000**2) >>> for indices, weights in read_sensor_data(): ... np.bincount(indices, weights, out=tally) # fast: plain sum-loop in C As far as I can see, there is no equivalent numpy functionality. In fact, as far as I'm aware, there isn't any fast alternative outside of C/Cython/numba/... It also fits the purpose of `bincount` nicely, and does not change existing functionality. One might argue about the exact semantics if both `minlength` and `out` are given, but I think that a sensible answer exists in requiring `len(out) >= max(list.max(), minlength)`. _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
