Incorrect voronoi polygons

[RenaudLN]

Hi, I was trying out this Polygon-bounded Voronoi which is pretty cool but I run into issues from time to time as the algorithm does not seem to find Voronoi polygons for some of the points in the data (points that are within the bounding polygon).

Below is a reproducible example:

import numpy as np
from voronoi import Voronoi, Polygon

# These points were initially taken at random with np.random.rand
pts = [
    (0.17094288, 0.96789158),
    (0.55449063, 0.72159817),
    (0.94036409, 0.82856818),
]
# A square bounding box
polygon = Polygon([
    (0., 0.),
    (0., 1.),
    (1., 1.),
    (1., 0.),
])
# Initialise the voronoi object
v = Voronoi(polygon)
# Create the diagram
v.create_diagram(points=pts, vis_steps=False, verbose=False, vis_result=False, vis_tree=False)

# Print 
for i, pt in enumerate(v.points):
    print(i, pt.get_coordinates())
# Notice that in the output, the first two polygons are the same (with permutation):
# 0 [(0.685, 1.0), (0.962, 0.0), (0.0, 0.0), (0.0, 0.28), (0.462, 1.0)]
# 1 [(0.0, 0.28), (0.462, 1.0), (0.685, 1.0), (0.962, 0.0), (0.0, 0.0)]
# 2 [(0.962, 0.0), (0.685, 1.0), (1.0, 1.0), (1.0, 0.0)]

And if I try to plot them I get the following:

[Yatoom]

I haven't yet had the time to look into it, but I plan to do it soon! Thanks for the reproducible example, cases like these are definitely useful for debugging problems! Dankjewel!

[Yatoom]

Hi @RenaudLN, thank you for reporting this issue! It should now be fixed.

The first set of coordinates is now describing the corner piece on the top left. The other polygons are still the same.

0 [(0.462, 1.0), (0.0, 0.28), (0.0, 1.0)] 
1 [(0.0, 0.28), (0.462, 1.0), (0.685, 1.0), (0.962, 0.0), (0.0, 0.0)]
2 [(0.962, 0.0), (0.685, 1.0), (1.0, 1.0), (1.0, 0.0)]