KDTree(data[, leafsize]) |
kd-tree for quick nearest-neighbor lookup |

cKDTree |
kd-tree for quick nearest-neighbor lookup |

distance |

Delaunay(points[, furthest_site, ...]) |
Delaunay tesselation in N dimensions. |

ConvexHull(points[, furthest_site, ...]) |
Convex hulls in N dimensions. |

Voronoi(points[, furthest_site, ...]) |
Voronoi diagrams in N dimensions. |

delaunay_plot_2d(tri[, ax]) |
Plot the given Delaunay triangulation in 2-D |

convex_hull_plot_2d(hull[, ax]) |
Plot the given convex hull diagram in 2-D |

voronoi_plot_2d(vor[, ax]) |
Plot the given Voronoi diagram in 2-D |

See also

The simplices (triangles, tetrahedra, ...) appearing in the Delaunay tesselation (N-dim simplices), convex hull facets, and Voronoi ridges (N-1 dim simplices) are represented in the following scheme:

```
tess = Delaunay(points)
hull = ConvexHull(points)
voro = Voronoi(points)
# coordinates of the j-th vertex of the i-th simplex
tess.points[tess.simplices[i, j], :] # tesselation element
hull.points[hull.simplices[i, j], :] # convex hull facet
voro.vertices[voro.ridge_vertices[i, j], :] # ridge between Voronoi cells
```

For Delaunay triangulations and convex hulls, the neighborhood structure of the simplices satisfies the condition:

tess.neighbors[i,j]is the neighboring simplex of the i-th simplex, opposite to the j-vertex. It is -1 in case of no neighbor.

Convex hull facets also define a hyperplane equation:

(hull.equations[i,:-1] * coord).sum() + hull.equations[i,-1] == 0

Similar hyperplane equations for the Delaunay triangulation correspond to the convex hull facets on the corresponding N+1 dimensional paraboloid.

The Delaunay triangulation objects offer a method for locating the simplex containing a given point, and barycentric coordinate computations.

tsearch(tri, xi) |
Find simplices containing the given points. |

distance_matrix(x, y[, p, threshold]) |
Compute the distance matrix. |

minkowski_distance(x, y[, p]) |
Compute the L**p distance between two arrays. |

minkowski_distance_p(x, y[, p]) |
Compute the p-th power of the L**p distance between two arrays. |