python - Roll rows of a matrix independently

Question

I have a matrix (2d numpy ndarray, to be precise):

A = np.array([[4, 0, 0],
              [1, 2, 3],
              [0, 0, 5]])

And I want to roll each row of A independently, according to roll values in another array:

r = np.array([2, 0, -1])

That is, I want to do this:

print np.array([np.roll(row, x) for row,x in zip(A, r)])

[[0 0 4]
 [1 2 3]
 [0 5 0]]

Is there a way to do this efficiently? Perhaps using fancy indexing tricks?

Answer 1

Sure you can do it using advanced indexing, whether it is the fastest way probably depends on your array size (if your rows are large it may not be):

rows, column_indices = np.ogrid[:A.shape[0], :A.shape[1]]

# Use always a negative shift, so that column_indices are valid.
# (could also use module operation)
r[r < 0] += A.shape[1]
column_indices = column_indices - r[:, np.newaxis]

result = A[rows, column_indices]