Some functions for computing Voronoi diagrams for points in the plane for metrics other than the Euclidean metric.

• voronoi_l1 creates 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_grid is 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 given points array that is closest to the grid point. It uses scipy.spatial.distance.cdist to compute the distance, so any metric provided by that function can be used. voronoi_grid requires 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: