Concatenate each string combination from two numpy arrays

Question

Given two arrays (A and B) of different shapes, I like to create an array containing the concatenation of each row from A to each row from B.

eg. Given:

A = np.array([[1, 2],
              [3, 4],
              [5, 6]])

B = np.array([[7, 8, 9],
              [10, 11, 12]])

would like to create an array:

[[1, 2, 7, 8, 9],
 [1, 2, 10, 11, 12],
 [3, 4, 7, 8, 9],
 [3, 4, 10, 11, 12],
 [5, 6, 7, 8, 9],
 [5, 6, 10, 11, 12]]

I can do this using iteration, but it is very slow, so you are looking for a combination of functions numpythat can recreate the above as efficiently as possible (input arrays A and B will contain up to 10,000 lines, therefore, to avoid nested loops).

Answer 1

Great problem to learn about slicingand broadcasted-indexing.

-

def concatenate_per_row(A, B):
    m1,n1 = A.shape
    m2,n2 = B.shape

    out = np.zeros((m1,m2,n1+n2),dtype=A.dtype)
    out[:,:,:n1] = A[:,None,:]
    out[:,:,n1:] = B
    return out.reshape(m1*m2,-1)

-

In [441]: A
Out[441]: 
array([[1, 2],
       [3, 4],
       [5, 6]])

In [442]: B
Out[442]: 
array([[ 7,  8,  9],
       [10, 11, 12]])

In [443]: concatenate_per_row(A, B)
Out[443]: 
array([[ 1,  2,  7,  8,  9],
       [ 1,  2, 10, 11, 12],
       [ 3,  4,  7,  8,  9],
       [ 3,  4, 10, 11, 12],
       [ 5,  6,  7,  8,  9],
       [ 5,  6, 10, 11, 12]])

Answer 2

: numpy.concatenate ,

import numpy as np
from numpy.lib.recfunctions import stack_arrays
from pprint import pprint

A = np.array([[1, 2],
              [3, 4],
              [5, 6]])

B = np.array([[7, 8, 9],
              [10, 11, 12]])

cartesian = [stack_arrays((a, b), usemask=False) for a in A
                                                 for b in B]

pprint(cartesian)

:

[array([1, 2, 7, 8, 9]),
 array([ 1,  2, 10, 11, 12]),
 array([3, 4, 7, 8, 9]),
 array([ 3,  4, 10, 11, 12]),
 array([5, 6, 7, 8, 9]),
 array([ 5,  6, 10, 11, 12])]