Fast Delaunay triangulation of 2D points implemented in Python.

This code was ported from Mapbox's Delaunator Project (JavaScript).

Test on FreeCAD.

Comparison result between python alternatives.

from Delaunator import Delaunator
points = [[168, 180], [168, 178], [168, 179], [168, 181], [168, 183], ...]
triangles = Delaunator(points).triangles
print(triangles)
>> [623, 636, 619,  636, 444, 619, ...]

Constructs a delaunay triangulation object given an array of points ([x, y] by default). Duplicate points are skipped.

An array of triangle vertex indices (each group of three numbers forms a triangle). All triangles are directed counterclockwise.

To get the coordinates of all triangles, use:

coordinates = []
for i in range(0, len(triangles), 3):
    coordinates.append([
        points[triangles[i]],
        points[triangles[i + 1]],
        points[triangles[i + 2]]])

An array of triangle half-edge indices that allows you to traverse the triangulation. i-th half-edge in the array corresponds to vertex triangles[i] the half-edge is coming from. halfedges[i] is the index of a twin half-edge in an adjacent triangle (or -1 for outer half-edges on the convex hull).

The flat array-based data structures might be counterintuitive, but they're one of the key reasons this library is fast.

An array of indices that reference points on the convex hull of the input data, counter-clockwise.

An array of input coordinates in the form [x0, y0, x1, y1, ....], of the type provided in the constructor.

Updates the triangulation if you modified Delaunator(points).coords values in place, avoiding expensive memory allocations. Useful for iterative relaxation algorithms such as Lloyd's.