Given the numpy array a
a = [[[0 0] [1 0] [2 0]]
[[0 1] [1 1] [2 1]]
[[0 2] [1 2] [2 2]]]
And the list b
b = [[1, 0], [2, 0]]
How can I get the mask c
c = [[False True True]
[False False False]
[False False False]]
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Could you post the code that creates the numpy arrayDani Mesejo– Dani Mesejo2019-09-30 15:11:06 +00:00Commented Sep 30, 2019 at 15:11
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a = np.dstack((np.meshgrid(x, y))), where x = y = [0, 1, 2]Ivan– Ivan2019-10-01 13:19:56 +00:00Commented Oct 1, 2019 at 13:19
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1 Answer
you can use numpy broadcast feature to compare each number pair in b with all pairs on b like below
## np.newaxis add a new dimension at that position. missing dimension (i.e
## dimension with size 1) will repeat to match size of corresponding dimension
a = np.asarray([[[0, 0], [1, 0], [2, 0]],
[[0, 1], [1, 1], [2, 1]],
[[0, 2], [1, 2], [2, 2]]])[:,:,np.newaxis,:]
b = np.array([[1, 0], [2, 0]])[np.newaxis,:,:]
(a == b).all(axis=3).any(axis=2)
Result
array([[False, True, True],
[False, False, False],
[False, False, False]])
1 Comment
Ivan
I know that comments are used to ask for clarification or to point out problems in the post, but thank you.