Try to Avoid for-loops for performance

[DeaD_EyE]

If I run your code, after importing numpy as np and adding distances as empty list, it runs very fast.

I change the code a little bit.

import math
import numpy as np



def calc_dists(volume, list_of_points):
    hypot = math.hypot
    distances = np.zeros(volume.shape)
    for index, voxel in np.ndenumerate(vol):
        if voxel == 1:
            for index2 in list_of_points:
                distance = hypot(
                    index[0] - index2[0],
                    index[1] - index2[1],
                    index[2] - index2[2],
                )
                distances[index] = distance
    return distances

 
shape = (100,100,100)
vol = np.ones(shape)
points = [(2,3,2), (2,3,3) ,(2,6,4),(9,6,8)]
result = calc_dists(vol, points)

print(result)

A shape of 100 x 100 x 100 consists of 1e6 elements.
This code takes also under 10 seconds.