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I want to check with most efficiency way (the fastest way), if some array (or list) is in numpy array. But when I do this:

import numpy

a = numpy.array(
    [
        [[1, 2]],
        [[3, 4]]
    ])

print([[3, 5]] in a)

It only compares the first value and returns True

Somebody knows, how can I solve it? Thank you.

3
  • 1
    Does this answer your question? Iterating over Numpy matrix rows to apply a function each? Commented Jan 27, 2021 at 15:26
  • Thank you, this helped me, too. Commented Jan 28, 2021 at 14:49
  • for your original data, is only the matrix a large or the query matrix is also large? Commented Feb 1, 2021 at 13:23

2 Answers 2

1

Your question seems to be a duplicate of: How to match pairs of values contained in two numpy arrays

In any case, something like the first answer should do it if I understand correctly:

import numpy

a = numpy.array(
    [
        [[1, 2]],
        [[3, 4]]
    ])

b = numpy.array([[3,5]])

print((b[:,None] == a).all(2).any(1))

Which outputs:

array([False,  True])
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1 Comment

Thank you! This works, it is faster than solution from joostblack, but it still takes a long time on my big data series. Is there any other faster solution? Thank you.
1

You could just add tolist() in your last line:

print([[3, 5]] in a.tolist())

gives

False

2 Comments

I do not know what your application is but I think you can drop the double brackets and instead use single brackets.
This works! Thank you, but it is really slow. I have big data series and with them it takes more than 1 minute. Is there any faster solution?

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