Fastest way to convert a list of indices to 2D numpy array of ones

Question

I have a list of indices

a = [
  [1,2,4],
  [0,2,3],
  [1,3,4],
  [0,2]]

What\'s the fastest way to convert this to a numpy array of ones,

Answer 1

How about this:

ncol = 5
nrow = len(a)
out = np.zeros((nrow, ncol), int)
out[np.arange(nrow).repeat([*map(len,a)]), np.concatenate(a)] = 1
out
# array([[0, 1, 1, 0, 1],
#        [1, 0, 1, 1, 0],
#        [0, 1, 0, 1, 1],
#        [1, 0, 1, 0, 0]])

Here are timings for a 1000x1000 binary array, note that I use an optimized version of the above, see function pp below:

pp 21.717635259992676 ms
ts 37.10938713003998 ms
u9 37.32933565042913 ms

Code to produce timings:

import itertools as it
import numpy as np

def make_data(n,m):
    I,J = np.where(np.random.random((n,m))