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


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


[Qhull](1, 2, 3, 4)


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.)


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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