# scipy.spatial.Delaunay¶

class scipy.spatial.Delaunay(points)

Delaunay tesselation in N dimensions

New in version 0.9.

Parameters : points : ndarray of floats, shape (npoints, ndim) Coordinates of points to triangulate

Notes

The tesselation is computed using the Qhull libary [Qhull].

References

 [Qhull] (1, 2, 3, 4) http://www.qhull.org/

Attributes

 transform Affine transform from x to the barycentric coordinates c. vertex_to_simplex Lookup array, from a vertex, to some simplex which it is a part of. convex_hull Vertices of facets forming the convex hull of the point set.
 points ndarray of double, shape (npoints, ndim) Points in the triangulation vertices ndarray of ints, shape (nsimplex, ndim+1) Indices of vertices forming simplices in the triangulation neighbors ndarray of ints, shape (nsimplex, ndim+1) Indices of neighbor simplices for each simplex. The kth neighbor is opposite to the kth vertex. For simplices at the boundary, -1 denotes no neighbor. equations ndarray of double, shape (nsimplex, ndim+2) [normal, offset] forming the hyperplane equation of the facet on the paraboloid. (See [Qhull] documentation for more.) paraboloid_scale, paraboloid_shift float Scale and shift for the extra paraboloid dimension. (See [Qhull] documentation for more.)

Methods

 find_simplex(xi[, bruteforce]) Find the simplices containing the given points. lift_points(tri, x) Lift points to the Qhull paraboloid. plane_distance(xi) Compute hyperplane distances to the point xi from all simplices.

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