MATLAB Mathematics - SERC - Index of

Interpolation
Functions for Multidimensional Geometrical Analysis
Function
convhulln
delaunayn
dsearchn
griddatan
tsearchn
voronoin
Description
N-dimensional convex hull.
N-dimensional Delaunay tessellation.
N-dimensional nearest point search.
N-dimensional data gridding and hypersurface fitting.
N-dimensional closest simplex search.
N-dimensional Voronoi diagrams.
This section demonstrates these geometric analysis techniques:
• Convex hulls
• Delaunay triangulations
• Voronoi diagrams
• Interpolation of scattered multidimensional data
Convex Hulls
The convex hull of a data set in n-dimensional space is defined as the smallest
convex region that contains the data set.
Computing a Convex Hull. The convhulln function returns the indices of the
points in a data set that comprise the facets of the convex hull for the set. For
example, suppose X is an 8-by-3 matrix that consists of the 8 vertices of a cube.
The convex hull of X then consists of 12 facets:
d = [-1 1];
[x,y,z] = meshgrid(d,d,d);
X = [x(:),y(:),z(:)];
C = convhulln(X)
% 8 corner points of a cube
C =
4 2 1
3 4 1
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