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.