scipy.spatial.tsearch

scipy.spatial.tsearch(tri, xi)

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

New in version 0.9.

See also

Delaunay.find_simplex

Examples

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

The Delaunay triangulation of a set of random points:

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

Find the simplices containing a given set of points:

>>> loc = rng.uniform(0.2, 0.8, (5, 2))
>>> s = tsearch(tri, loc)
>>> plt.triplot(pts[:, 0], pts[:, 1], tri.simplices[s], 'b-', mask=s==-1)
>>> plt.scatter(loc[:, 0], loc[:, 1], c='r', marker='x')
>>> plt.show()

scipy.spatial.voronoi_plot_2d scipy.spatial.distance_matrix