Calculate distance from one point to all others

Question

I am working with a list of ID, X, and Y data for fire hydrant locations. I am trying to find the three closest fire hydrants for each fire hydrant in the list.

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Answer 1

You do not have to calculate all distances of all points to all others to get the three nearest neighbours for all points.

A kd-tree search will be much more efficient due to its O(log n) complexity instead of a O(n**2) time complexity for the brute force method (calculating all distances).

Example

import numpy as np
from scipy import spatial

#Create some coordinates and indices
#It is assumed that the coordinates are unique (only one entry per hydrant)
Coords=np.random.rand(1000*2).reshape(1000,2)
Coords*=100
Indices=np.arange(1000) #Indices 

def get_indices_of_nearest_neighbours(Coords,Indices):
  tree=spatial.cKDTree(Coords)
  #k=4 because the first entry is the nearest neighbour 
  # of a point with itself
  res=tree.query(Coords, k=4)[1][:,1:]
  return Indices[res]