Hmm, so how come this doesn't work now? mask = ((px > 2.) & ((py**2 + pz**2) / px**2 < 1.)) for arr in (px, py, pz, w, x, y, z): arr = arr[mask] On Mon, 23 Oct 2017 15:05:26 +0200 (CEST), "Andrei Berceanu" <berceanu@runbox.com> wrote:
Thank you so much, the solution was much simpler than I expected!
On Sat, 21 Oct 2017 23:04:43 +0200, Daπid <davidmenhur@gmail.com> wrote:
On 21 October 2017 at 22:32, Eric Wieser <wieser.eric+numpy@gmail.com> wrote:
David, that doesn’t work, because np.cumsum(mask)[mask] is always equal to np.arange(mask.sum()) + 1. Robert’s answer is correct.
Of course, you are right. It makes sense in my head now. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
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