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scipy convex hull controid

FishBrawler answered on April 25, 2022 Popularity 4/10 Helpfulness 1/10

answer scipy convex hull controid

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scipy convex hull controid

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import numpy as np
from scipy.spatial import ConvexHull

points = np.random.rand(30, 2)   # 30 random points in 2-D
hull = ConvexHull(points)

#Get centroid
cx = np.mean(hull.points[hull.vertices,0])
cy = np.mean(hull.points[hull.vertices,1])

Popularity 4/10 Helpfulness 1/10 Language whatever

Source: stackoverflow.com

Tags: convex-hull scipy whatever

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Contributed on Aug 16 2023

FishBrawler

0 Answers Avg Quality 2/10

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SciPy Convex Hull

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# A convex hull is the smallest polygon that covers all of the given points

import numpy as np
from scipy.spatialdata import ConvexHull
import mathplotlib.pyplot as plt

points = np.array([
  [2, 4],
  [3, 4],
  [3, 0],
  [2, 2],
  [4, 1],
  [1, 2],
  [5, 0],
  [3, 1],
  [1, 2],
  [0, 2]
])

hull = ConvexHull(points)
hull_points = hull.simplices

plt.scatter(points[:, 0], points [:, 1])

for simplex in hull_points:
	plt.plot(points[simplex, 0], points[simplex, 1], 'k-')

plt.show()

Popularity 7/10 Helpfulness 4/10 Language python

Source: Grepper

Tags: convex-hull python scipy convex-hu

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Contributed on Apr 25 2022

Astra Logical

0 Answers Avg Quality 2/10

scipy convex hull controid

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