Extracting 1d arrays from 3d numpy array using 2d boolean

Question

Say I have a 3d numpy array:

i, j, k = 10, 3, 4

arr = np.arange(120).reshape(i, j, k)

and a 2d boolean array:

mask = np.random.random((j, k)) > 0.5

n = mask.sum()

I want to be able to extract the 1d arrays from arr along its 1st dimension which correspond with the True values of mask. The result should have shape, (i, n). How could this be done?

I pulling up some old code and for some reason I was doing arr[mask] but this gives a shape of (n, k) (I'm not sure why) and a warning:

VisibleDeprecationWarning: boolean index did not match indexed array along dimension 0; dimension is 10949 but corresponding boolean dimension is 11

Did the posted solution work for you?

Divakar
– Divakar

2017-03-02 16:30:06 +00:00
Commented Mar 2, 2017 at 16:30 — Divakar
– Divakar, Commented Mar 2, 2017 at 16:30
Yes it did thanks! This makes a lot of sense now.

pbreach
– pbreach

2017-03-02 16:35:17 +00:00
Commented Mar 2, 2017 at 16:35 — pbreach
– pbreach, Commented Mar 2, 2017 at 16:35

Divakar · Accepted Answer · 2017-03-01 21:47:46Z

1

Simply mask along the last two axes -

arr[:,mask]

answered Mar 1, 2017 at 21:47

Divakar

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