David, that doesn’t work, because np.cumsum(mask)[mask] is always equal to np.arange(mask.sum()) + 1. Robert’s answer is correct.
Eric On Sat, 21 Oct 2017 at 13:12 Daπid <davidmen...@gmail.com> wrote: On 21 October 2017 at 21:03, Robert Kern <robert.k...@gmail.com> wrote: > >> Index with a boolean mask. >> >> mask = (tmp_px > 2) >> px = tmp_px[mask] >> py = tmp_py[mask] >> # ... etc. >> >> > That isn't equivalent, note that j only increases when tmp_px > 2. I think > you can do it with something like: > > mask = tmp_px > 2 > j_values = np.cumsum(mask)[mask] > i_values = np.arange(len(j_values)) > > px[i_values] = tmp_i[j_values] > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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