scipy.spatial.Delaunay.find_simplex¶
- Delaunay.find_simplex(self, xi, bruteforce=False, tol=None)¶
Find the simplices containing the given points.
Parameters: tri : DelaunayInfo
Delaunay triangulation
xi : ndarray of double, shape (..., ndim)
Points to locate
bruteforce : bool, optional
Whether to only perform a brute-force search
tol : float, optional
Tolerance allowed in the inside-triangle check. Default is 100*eps.
Returns: i : ndarray of int, same shape as xi
Indices of simplices containing each point. Points outside the triangulation get the value -1.
Notes
This uses an algorithm adapted from Qhull’s qh_findbestfacet, which makes use of the connection between a convex hull and a Delaunay triangulation. After finding the simplex closest to the point in N+1 dimensions, the algorithm falls back to directed search in N dimensions.