Some functions for computing Voronoi diagrams for points in the plane for metrics other than the Euclidean metric.
voronoi_l1creates Voronoi cells (polygons) for a set of points using the L1 metric (also known as the city-block metric, the Manhattan metric, or the taxicab metric). The function requires the Shapely library (https://pypi.org/project/Shapely/).voronoi_gridis for displaying a Voronoi diagram as an image. It samples a grid of points and generates an array of integers that indicate the index in the givenpointsarray that is closest to the grid point. It usesscipy.spatial.distance.cdistto compute the distance, so any metric provided by that function can be used.voronoi_gridrequires SciPy.
Demonstration code is in examples/voronoi_demo.py. When that file
is run, it generates these plots of the result of voronoi_l1 and
voronoi_grid applied to a random set of points:
