Assign values to multiple columns of numpy matrix without looping

Question

I have a numpy matrix X with n columns, and I have a list I of n lists of indices i, and a corresponding list V of n lists of values v. For each column c in X, I want to assign the indices I[c] to the values V[c]. Is there a way to do this without a for loop, i.e.:

n = 3
X = np.zeros((4,n))
I = [[0,1],[1,2,3],[0]]
V = [[1,1],[2,2,2],[3]]

for c in range(n):
    X[I[c],c] = V[c]

I can't think of one, no.

Chris
– Chris

2019-04-10 14:28:02 +00:00
Commented Apr 10, 2019 at 14:28 — Chris
– Chris, Commented Apr 10, 2019 at 14:28

Paul Panzer · Accepted Answer · 2019-04-10 14:46:12Z

1

True vectorization I can't see, but no explicit for loops is doable:

X[np.concatenate(I), np.arange(len(I)).repeat(np.vectorize(len)(I))] = np.concatenate(V)
X
# array([[1., 0., 3.],
#        [1., 2., 0.],
#        [0., 2., 0.],
#        [0., 2., 0.]])

But I'm not sure this will be any faster than a for loop.

answered Apr 10, 2019 at 14:46

Paul Panzer

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