如何使用Delaunay三角剖分来输出包含三角剖分中所有连接及其距离的矩阵？

import numpy as np
from scipy.spatial import Delaunay

# 输入点集
points = np.array([[0, 0], [1, 0], [0, 1], [1, 1]])

# 进行Delaunay三角剖分
tri = Delaunay(points)

# 获取三角形连接和距离
connections = tri.simplices
distances = np.zeros((len(connections), len(connections)))

for i, conn1 in enumerate(connections):
    for j, conn2 in enumerate(connections):
        if i != j:
            # 计算连接的距离
            distance = np.linalg.norm(points[conn1] - points[conn2])
            distances[i, j] = distance

# 打印连接和距离矩阵
print(distances)