Forward fill Numpy matrix / mask with values based on condition

I have the following matrix

import numpy as np


A = np.array([
    [0, 0, 0, 0, 1, 0, 1],
    [0, 0, 0, 0, 0, 0, 1],
    [1, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0]
]).astype(bool)

How do I fill all the rows column-wise after a column is True?

My desired output:

    [0, 0, 0, 0, 1, 1, 1],
    [0, 0, 0, 0, 0, 0, 1],
    [1, 1, 1, 1, 1, 1, 1],
    [0, 0, 0, 0, 0, 0, 0]

You could use logical_or combined with accumulate:

np.logical_or.accumulate(A, axis=1)

Output:

array([[False, False, False, False,  True,  True,  True],
       [False, False, False, False, False, False,  True],
       [ True,  True,  True,  True,  True,  True,  True],
       [False, False, False, False, False, False, False]])

If you want integers, go with maximum:

np.maximum.accumulate(A.astype(int), axis=1)

array([[0, 0, 0, 0, 1, 1, 1],
       [0, 0, 0, 0, 0, 0, 1],
       [1, 1, 1, 1, 1, 1, 1],
       [0, 0, 0, 0, 0, 0, 0]])