如何在 Python 中设置 Delaunay 三角形边的最大距离

问题描述

我正在尝试使用 scipy.spatial.Delaunay 对象处理一些数据集.但问题是我无法设置最大三角形边长.我想做类似

# 构建输入点集np.random.seed(0)x = 3.0 * np.random.rand(1000)y = 2.0 * np.random.rand(1000) - 1.0里面 = ((x ** 2 + y ** 2 > 1.0) & ((x - 3) ** 2 + y ** 2 > 1.0) & ((x-1.5) ** 2 + y** 2 > 0.09))点 = np.vstack([x[inside], y[inside]]).T

I'm trying to work on some datasets using the scipy.spatial.Delaunay object.But the problem is that I'm not able to set a maximum triangle side lenght. I would like to do something like How to set maximum length of triangle side in Delaunay triangulation?, but in Python

解决方案

Here is some code that separates large edges from small:

# Computing Delaunay
tri = Delaunay(points)

# Separating small and large edges:
thresh = 1.0  # user defined threshold
small_edges = set()
large_edges = set()
for tr in tri.vertices:
    for i in xrange(3):
        edge_idx0 = tr[i]
        edge_idx1 = tr[(i+1)%3]
        if (edge_idx1, edge_idx0) in small_edges:
            continue  # already visited this edge from other side
        if (edge_idx1, edge_idx0) in large_edges:
            continue
        p0 = points[edge_idx0]
        p1 = points[edge_idx1]
        if np.linalg.norm(p1 - p0) <  thresh:
            small_edges.add((edge_idx0, edge_idx1))
        else:
            large_edges.add((edge_idx0, edge_idx1))

# Plotting the output
figure()
plot(points[:, 0], points[:, 1], '.')
for i, j in small_edges:
    plot(points[[i, j], 0], points[[i, j], 1], 'b')
for i, j in large_edges:
    plot(points[[i, j], 0], points[[i, j], 1], 'c')

On the data generated from the following code, I get this figure:

# Constructing the input point set
np.random.seed(0)
x = 3.0 * np.random.rand(1000)
y = 2.0 * np.random.rand(1000) - 1.0
inside = ((x ** 2 + y ** 2 > 1.0) & ((x - 3) ** 2 + y ** 2 > 1.0) & ((x-1.5) ** 2 + y ** 2 > 0.09))
points = np.vstack([x[inside], y[inside]]).T

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