comparing two matrices columns in python (numpy)

Question

Assuming I have two matrices, A of dimensions r X c, and B of dimensions r X d (i.e., both matrices have the same number of rows and a different number of columns). Now, I want to compare every column in A to every column in B. That is, I want to find all the pairs (i,j), where column i in matrix A equals column j in matrix B. Obviously, this can be easily done with a loop but I was wondering if there is an efficient fancy numpy style way to do that (where the emphasis is on being efficient)?

Thanks!

Can you make a reproducible example ?

akuiper
– akuiper

2021-06-18 16:33:22 +00:00
Commented Jun 18, 2021 at 16:33 — akuiper
– akuiper, Commented Jun 18, 2021 at 16:33
np.where((A[:,None] == B[...,None]).all(0))

akuiper
– akuiper

2021-06-18 16:49:40 +00:00
Commented Jun 18, 2021 at 16:49 — akuiper
– akuiper, Commented Jun 18, 2021 at 16:49

chatax · Accepted Answer · 2021-06-18 17:31:28Z

1

This function returns an array with column indices that are equal for both matrices.

def get_equal_columns(m1, m2):
    equal_column_indices = np.where((m1[:, None] == m2[..., None]).all(0))[0]
    return equal_column_indices

edited Jun 18, 2021 at 17:31

answered Jun 18, 2021 at 16:46

chatax

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