How to add matrix and vector column-wise?

Question

Consider the following:

>>> matrix = numpy.array([[1, 2, 3],
...                       [4, 5, 6],
...                       [7, 8, 9]])
>>> vector = numpy.array([10, 20, 30])
>>> matrix + vector
array([[11, 22, 33],
       [14, 25, 36],
       [17, 28, 39]])

This adds the vector and the matrix row-wise (i.e. each row being added the vector).

How to perform the same column-wise? The result should be

>>> ???
array([[11, 12, 13],
       [24, 25, 26],
       [37, 38, 39]])

I'm aware that I can use

>>> (matrix.T + vector).T
array([[11, 12, 13],
       [24, 25, 26],
       [37, 38, 39]])

However I have many such additions and using this double transposition will make the code quite unreadable. Is there a way to configure ndarrays such that they will perform addition along the first axis (instead of the last)?

Answer 1

Make the vector a column:

matrix + vector[:, None]