Notice: the answer by aqueiros, although higher up voted, is not correct. Particularly this statement "vor.regions always has an empty array in the first index", is not true.
I'm generating a simple 2D Voronoi tessellation, using the scipy.spatial.Voronoi function. I use a random 2D distribution of points (see MCVE below).
I need a way to go through each defined region (defined by scipy.spatial.Voronoi
) and get the coordinates of the point associated to it (ie: the point that said region encloses).
The issue is that there are N+1
regions (polygons) defined for the N
points, and I'm not sure what this means.
Here's a MCVE that will fail when it gets to the last region:
from scipy.spatial import Voronoi
import numpy as np
# Generate random data.
N = 10
x = [np.random.random() for i in xrange(N)]
y = [np.random.random() for i in xrange(N)]
points = zip(x, y)
# Obtain Voronoi regions.
vor = Voronoi(points)
# Loop through each defined region/polygon
for i, reg in enumerate(vor.regions):
print 'Region:', i
print 'Indices of vertices of Voronoi region:', reg
print 'Associated point:', points[i], '\n'
Another thing I don't understand is why are there empty vor.regions
stored? According to the docs:
regions: Indices of the Voronoi vertices forming each Voronoi region. -1 indicates vertex outside the Voronoi diagram.
What does an empty region mean?
Add
I tried the point_region
attribute but apparently I don't understand how it works. It returns indexes outside of the range of the points
list. For example: in the MCVE above it will always show an index 10
for a list of 10 points, which is clearly out of range.