Construct Numpy index given list of starting and ending positions

Question

I have two identically-sized numpy.array objects (both one-dimensional), one of which contains a list of starting index positions, and the other of which contains a list of ending index positions (alternatively you could say I have a list of starting positions and window lengths). In case it matters, the slices formed by the starting and ending positions are guaranteed to be non-overlapping. I am trying to figure out how to use these starting and ending positions to form an index for another array object, without having to use a loop.

For example:

import numpy as np
start = np.array([1,7,20])
end = np.array([3,10,25])

Want to reference

somearray[1,2,7,8,9,20,21,22,23,24])

Answer 1

I would use

np.r_[tuple(slice(s, e) for s, e in zip(start, end))]

EDIT: Here is a solution that does not use a Python loop:

def indices(start, end):
    lens = end - start
    np.cumsum(lens, out=lens)
    i = np.ones(lens[-1], dtype=int)
    i[0] = start[0]
    i[lens[:-1]] += start[1:]
    i[lens[:-1]] -= end[:-1]
    np.cumsum(i, out=i)
    return i

This only creates a single temporary NumPy array (lens) and is much faster than any of the other solutions.