Match rows of two 2D arrays and get a row indices map using numpy

Question

Suppose you have two 2D arrays A and B, and you want to check, where a row of A is contained in B. How do you do this most efficiently using numpy?

E.g.

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Answer 1

You can take advantage of the automatic broadcasting:

np.argwhere(np.all(a.reshape(3,1,-1) == b,2))

which results in

array([[0, 2],
       [1, 0]])

Note for floats you might want to replace the == with np.islclose()