numpy indexing into array of dtype=object

Question

I am creating an ndarray from ragged nested sequences, like this:

import numpy as np
arr = np.array([[1,2], [3,4,5], [6,7,8,9], [10]], dtype=object)

In a next step, I want to use a "boolean mask" of the same length as arr to get certain elements.

Passing a mask of all True works:

my_mask = [True, True, True, True]
arr[my_mask]
# array([[list([1, 2]), list([3, 4, 5]), list([6, 7, 8, 9]), list([10])]],
      dtype=object)

However, other masks don't seem to work:

my_mask = [True, False, True, True]
arr[my_mask]
# array([], shape=(0, 4), dtype=object)

Why does the above result in an empty array?

UPDATE: In the example above I wrote arr[my_mask], but the error I got locally was actually obtained via arr[True, False, True, True], which should rather be arr[[True, False, True, True]], note the double brackets. Thanks to @Ivan and @user1740577. As such, this is not unexpected behavior, but rather a user mistake during indexing.

this work for me and output is : array([list([1, 2]), list([6, 7, 8, 9]), list([10])], dtype=object) — Mahdi F.
– Mahdi F., Commented Aug 25, 2021 at 10:20
which version of numpy are you using ? I got the same output as @user1740577 — AcaNg
– AcaNg, Commented Aug 25, 2021 at 10:21
@S.A. are you actually calling arr[my_mask] or doing arr[True, True, True, True] directly? — Ivan
– Ivan, Commented Aug 25, 2021 at 10:23
about using bool to index array, i found this answer stackoverflow.com/a/58132572/10666066 — AcaNg
– AcaNg, Commented Aug 25, 2021 at 10:39

Mahdi F. · Accepted Answer · 2021-08-25 10:29:22Z

1

instead of using:

arr[True, False, True, True]

using this (when you want to pass mask, pass array of mask):

arr[[True, False, True, True]]

answered Aug 25, 2021 at 10:29

Mahdi F.

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Ivan · Accepted Answer · 2021-08-25 10:33:41Z

1

You should call arr[my_mask] instead of arr[True, False, True, True].

The reason is that by indexing with True you are adding a dimension,

>>> arr[True]
array([[list([1, 2]), list([3, 4, 5]), list([6, 7, 8, 9]), list([10])]],
      dtype=object)

but then mask the second axis (formerly the first axis) with False i.e. returning no elements.

answered Aug 25, 2021 at 10:33

Ivan

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