Efficiently find row intersections of two 2-D numpy arrays

Question

I am trying to figure out an efficient way of finding row intersections of two np.arrays.

Two arrays have the same shapes, and duplicate values in each

Answer 1

If you have no duplicates within a row you can try to replicate what np.intersect1d does under the hood (see the source code here):

>>> c = np.hstack((a, b))
>>> c
array([[2, 5, 6, 2, 3, 4],
       [8, 2, 3, 7, 4, 3],
       [4, 1, 5, 5, 4, 1],
       [1, 7, 9, 7, 6, 9]])
>>> c.sort(axis=1)
>>> c
array([[2, 2, 3, 4, 5, 6],
       [2, 3, 3, 4, 7, 8],
       [1, 1, 4, 4, 5, 5],
       [1, 6, 7, 7, 9, 9]])
>>> c[:, 1:] == c[:, :-1]
array([[ True, False, False, False, False],
       [False,  True, False, False, False],
       [ True, False,  True, False,  True],
       [False, False,  True, False,  True]], dtype=bool)
>>> np.sum(c[:, 1:] == c[:, :-1], axis=1)
array([1, 1, 3, 2])