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我正在尝试使用 scipy.spatial(来自 scipy.spatial 导入 ConvexHull)来绘制一系列点的凸包。

import pylab as pl
from scipy.spatial import ConvexHull

pl.figure()  
pl.hold(True)  

points = np.concatenate((x, y), axis=1)

hull = ConvexHull(points)

pl.plot(points[:,0], points[:,1], 'ro')

for simplex in hull.simplices:
    pl.plot(points[simplex,0], points[simplex,1], 'dk--')    

问题是我没有正确理解什么是 hull.simplices,我想找到凸包面上点的索引,这样我就可以使用这些索引从 x 和 y 中获取点

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1 回答 1

13

在二维情况下,对象的simplices属性ConvexHull包含构成凸包线段的点的索引对。仅获取索引的一种方法是获取展平simplices数组的唯一元素。但请注意,这些点不会按照集合周围的凸包的顺序排列。(在 scipy 0.13.0 及更高版本中,您可以使用该vertices属性来获取索引;见下文。)

例如,

import numpy as np
from scipy.spatial import ConvexHull
import matplotlib.pyplot as plt


# Generate some random points for the demo.
np.random.seed(4321)
pts = 0.1 + 0.8*np.random.rand(15, 2)

ch = ConvexHull(pts)

# hull_indices = ch.vertices   # This will work in the scipy 0.13
hull_indices = np.unique(ch.simplices.flat)
hull_pts = pts[hull_indices, :]

plt.plot(pts[:, 0], pts[:, 1], 'ko', markersize=10)
plt.plot(hull_pts[:, 0], hull_pts[:, 1], 'ro', alpha=.25, markersize=20)
plt.xlim(0, 1)
plt.ylim(0, 1)
plt.show()

这会产生:

点图和凸包

vertices属性是在 scipy 0.13.0 中添加的:

import numpy as np
from scipy.spatial import ConvexHull
import matplotlib.pyplot as plt


# Generate some random points for the demo.
np.random.seed(4321)
pts = 0.1 + 0.8*np.random.rand(15, 2)

ch = ConvexHull(pts)

# Get the indices of the hull points.
hull_indices = ch.vertices

# These are the actual points.
hull_pts = pts[hull_indices, :]

plt.plot(pts[:, 0], pts[:, 1], 'ko', markersize=10)
plt.fill(hull_pts[:,0], hull_pts[:,1], fill=False, edgecolor='b')
plt.xlim(0, 1)
plt.ylim(0, 1)
plt.show()

凸包示例

于 2013-08-11T13:29:37.243 回答