您应该能够使用以下方法计算它matplotlib.delaunay.triangulate.Triangulation
:
三角测量(x, y)
x, y -- 作为一维浮点数数组的点的坐标
.
.
.
属性:(全部应视为
只读以保持一致性)
x, y -- 作为一维浮点数数组的点的坐标。
circumcenters -- (ntriangles, 2) array of floats giving the (x,y)
coordinates of the circumcenters of each triangle (indexed by a triangle_id).
改编自 matplotlib 示例之一(可能有一种更简洁的方法来执行此操作,但它应该有效):
import matplotlib.pyplot as plt
import matplotlib.delaunay
import matplotlib.tri as tri
import numpy as np
import math
# Creating a Triangulation without specifying the triangles results in the
# Delaunay triangulation of the points.
# First create the x and y coordinates of the points.
n_angles = 36
n_radii = 8
min_radius = 0.25
radii = np.linspace(min_radius, 0.95, n_radii)
angles = np.linspace(0, 2*math.pi, n_angles, endpoint=False)
angles = np.repeat(angles[...,np.newaxis], n_radii, axis=1)
angles[:,1::2] += math.pi/n_angles
x = (radii*np.cos(angles)).flatten()
y = (radii*np.sin(angles)).flatten()
tt = matplotlib.delaunay.triangulate.Triangulation(x,y)
triang = tri.Triangulation(x, y)
# Plot the triangulation.
plt.figure()
plt.gca().set_aspect('equal')
plt.triplot(triang, 'bo-')
plt.plot(tt.circumcenters[:,0],tt.circumcenters[:,1],'r.')
plt.show()