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"
wrote:
> Thank you so much, the solution was much simp
Thank you so much, the solution was much simpler than I expected!
On Sat, 21 Oct 2017 23:04:43 +0200, Daπid wrote:
> On 21 October 2017 at 22:32, Eric Wieser
> wrote:
>
> > David, that doesn’t work, because np.cumsum(mask)[mask] is always equal
> > to np.arange(mask.sum()) + 1. Robert’s answer
Hi,
I am new to Numpy, and would like to start by translating a (badly written?)
piece of MATLAB code.
What I have come up with so far is this:
px = np.zeros_like(tmp_px); py = np.zeros_like(tmp_py); pz =
np.zeros_like(tmp_pz)
w = np.zeros_like(tmp_w)
x = np.zeros_like(tmp_x); y = np.zeros_lik
