Check whether each row of a matrix is in another matrix [Python]

Question

I have two matrices (or, better, 2D numpy arrays), A and B, with same number of columns (well, to be fair they have a different number of rows, however

Answer 1

You can use a vectorized approach using NumPy broadcasting, like so -

np.argwhere((B[:,None,[0,1]] == A[:,[1,2]]).all(-1))

Alternatively, since you are dealing with rows of just 2 elements, a memory efficient approach that stays 2D could be suggested, like so -

np.argwhere((B[:,None,0] == A[:,1]) & (B[:,None,1] == A[:,2]))

The output would be (N,2) shaped array, in which the first column gives us the row indices of B and the second column of A corresponding to matches across all elements in a row.

Sample run -

In [154]: A[:,[1,2]]
Out[154]: 
array([[0, 1],
       [0, 2],
       [2, 1],
       [1, 2],
       [0, 1]])

In [155]: B[:,[0,1]]
Out[155]: 
array([[0, 1],
       [2, 2],
       [1, 2],
       [0, 2],
       [2, 1],
       [2, 1],
       [1, 0]])

In [156]: np.argwhere((B[:,None,[0,1]] == A[:,[1,2]]).all(-1))
Out[156]: 
array([[0, 0],
       [0, 4],
       [2, 3],
       [3, 1],
       [4, 2],
       [5, 2]])