`scipy.spatial._qhull:tsearch`

Signature

def tsearch ( tri , xi )

Find simplices containing the given points. This function does the same thing as Delaunay.find_simplex.

i : ndarray of int, same shape as `xi`: Indices of simplices containing each point. Points outside the triangulation get the value -1.

import numpy as np
import matplotlib.pyplot as plt
from scipy.spatial import Delaunay, delaunay_plot_2d, tsearch
rng = np.random.default_rng()

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The Delaunay triangulation of a set of random points:

pts = rng.random((20, 2))
tri = Delaunay(pts)
_ = delaunay_plot_2d(tri)

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Find the simplices containing a given set of points:

loc = rng.uniform(0.2, 0.8, (5, 2))
s = tsearch(tri, loc)

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plt.triplot(pts[:, 0], pts[:, 1], tri.simplices[s], 'b-', mask=s==-1)
plt.scatter(loc[:, 0], loc[:, 1], c='r', marker='x')

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plt.show()

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