Nearest neigbor from a point in 3d space

kdtree-nearest-neighbor.py

# find nearest neighbor of a point
import numpy as np
from scipy import spatial

# create 10 random points
x, y, z = np.random.rand(3,10)

# format our points for the kdtree function
points = [i for i in zip(x,y,z)]

# make the kdtree with the points
tree = spatial.KDTree(points)

# create a query point
qpoint = np.array([0,0,0])

# make the query, returns distance to point and the index in 'points'
tree.query(qpoint)