How to find all neighbors of a given point in a delaunay triangulation using scipy.spatial.Delaunay?

Question

I have been searching for an answer to this question but cannot find anything useful.

I am working with the python scientific computing stack (scipy,numpy,matplotlib

Answer 1

I needed this too and came across the following answer. It turns out that if you need the neighbors for all initial points, it's much more efficient to produce a dictionary of neighbors in one go (the following example is for 2D):

def find_neighbors(tess, points):

    neighbors = {}
    for point in range(points.shape[0]):
        neighbors[point] = []

    for simplex in tess.simplices:
        neighbors[simplex[0]] += [simplex[1],simplex[2]]
        neighbors[simplex[1]] += [simplex[2],simplex[0]]
        neighbors[simplex[2]] += [simplex[0],simplex[1]]

    return neighbors

The neighbors of point v are then neighbors[v]. For 10,000 points in this takes 370ms to run on my laptop. Maybe others have ideas on optimizing this further?