Numpy array: how to reduce a single dimension

Question

If I have an array of shape (500, 363, 3) which looks like the one below, how can I reduce it to shape (500, 363, 1) where each value will be a single bool equivalent to the result of all(). So [False, False, False] would become False?

Array([[[False, False, False],
    [False, False, False],
    [False, False, False],
    ...,
    [False, False, False],
    [False, False, False],
    [False, False, False]],

   [[False, False, False],
    [False, False, False],
    [False, False, False],
    ...,
    [False, False, False],
    [False, False, False],
    [False, False, False]],

   [[False, False, False],
    [False, False, False],
    [False, False, False],
    ...,
    [False, False, False],
    [False, False, False],
    [False, False, False]],

   ...,

   [[False, False, False],
    [False, False, False],
    [False, False, False],
    ...,
    [False, False, False],
    [False, False, False],
    [False, False, False]],

   [[False, False, False],
    [False, False, False],
    [False, False, False],
    ...,
    [False, False, False],
    [False, False, False],
    [False, False, False]],

   [[False, False, False],
    [False, False, False],
    [False, False, False],
    ...,
    [False, False, False],
    [False, False, False],
    [False, False, False]]])

arr.all(axis=2) should work

hpaulj
– hpaulj

2019-06-14 22:08:21 +00:00
Commented Jun 14, 2019 at 22:08 — hpaulj
– hpaulj, Commented Jun 14, 2019 at 22:08

yatu · Accepted Answer · 2019-06-14 22:07:21Z

3

np.all has an axis argument, in this case you want to take all along the last axis, so you need:

a.all(-1)

a = np.random.choice([0,1], size=(500, 363, 3))
print(a.all(-1).shape)
# (500, 363)

answered Jun 14, 2019 at 22:07

yatu

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Ayoub ZAROU · Accepted Answer · 2019-06-14 22:07:30Z

2

you may do

import numpy as np
reduced = np.all(arr, axis = 2)

answered Jun 14, 2019 at 22:07

Ayoub ZAROU

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