Create triangular mesh from vertex coordinates

You can use scipy.spatial.Delaunay. Here is an example from the

import numpy as nppoints = np.array([[-1,1],[-1.3, .6],[0,0],[.2,.8],[1,.85],[-.1,-.4],[.4,-.15],[.6,-.6],[.9,-.2]])from scipy.spatial import Delaunaytri = Delaunay(points)import matplotlib.pyplot as pltplt.triplot(points[:,0], points[:,1], tri.simplices)plt.plot(points[:,0], points[:,1], 'o')plt.show()

Here is the result on an input similar to yours:

The triangles are stored in the simplices attribute of the Delaunay object which reference the coordinates stored in the points attribute:

>>> tri.pointsarray([[-1.  ,  1.  ],       [-1.3 ,  0.6 ],       [ 0.  ,  0.  ],       [ 0.2 ,  0.8 ],       [ 1.  ,  0.85],       [-0.1 , -0.4 ],       [ 0.4 , -0.15],       [ 0.6 , -0.6 ],       [ 0.9 , -0.2 ]])>>> tri.simplicesarray([[5, 2, 1],       [0, 3, 4],       [2, 0, 1],       [3, 0, 2],       [8, 6, 7],       [6, 5, 7],       [5, 6, 2],       [6, 3, 2],       [3, 6, 4],       [6, 8, 4]], dtype=int32)

If you are looking for which vertices are connected, there is an attribute containing that info also:

>>> tri.vertex_neighbor_vertices(array([ 0,  4,  7, 12, 16, 20, 24, 30, 33, 36], dtype=int32), array([3, 4, 2, 1, 5, 2, 0, 5, 1, 0, 3, 6, 0, 4, 2, 6, 0, 3, 6, 8, 2, 1,       6, 7, 8, 7, 5, 2, 3, 4, 8, 6, 5, 6, 7, 4], dtype=int32))

You can try scipy.spatial.Delaunay. From that link:

points = np.array([[0, 0], [0, 1.1], [1, 0], [1, 1]])from scipy.spatial import Delaunaytri = Delaunay(points)plt.triplot(points[:,0], points[:,1], tri.simplices)plt.plot(points[:,0], points[:,1], 'o')plt.show()

Output: