|MATLAB Function Reference|
Data gridding and hypersurface fitting (dimension >= 2)
yi = griddatan(X, y, xi)
fits a hyper-surface of the form to the data in the (usually) nonuniformly-spaced vectors (
griddatan interpolates this hyper-surface at the points specified by
xi to produce
xi can be nonuniform.
X is of dimension
m points in
y is of dimension
m values of the hyper-surface (
xi is a vector of size
p points in the
n-D space whose surface value is to be fitted.
yi is a vector of length
p approximating the values (
xi). The hypersurface always goes through the data points (
xi is usually a uniform grid (as produced by
[...] = griddatan(...,'method')
defines the type of surface fit to the data, where
'method' is one of:
|| Tessellation-based linear interpolation (default)
|| Nearest neighbor interpolation
All the methods are based on a Delaunay tessellation of the data.
griddatan methods are based on a Delaunay triangulation of the data that uses Qhull . This triangulation uses the Qhull joggle option (
'QJ'). For information about Qhull, see http://www.geom.umn.edu/software/qhull/. For copyright information, see http://www.geom.umn.edu/software/download/COPYING.html.
 Barber, C. B., D.P. Dobkin, and H.T. Huhdanpaa, "The Quickhull Algorithm for Convex Hulls," ACM Transactions on Mathematical Software, Vol. 22, No. 4, Dec. 1996, p. 469-483. Available in HTML format at http://www.acm.org/pubs/citations/journals/toms/1996-22-4/p469-barber/ and in PostScript format at ftp://geom.umn.edu/pub/software/qhull-96.ps.
 National Science and Technology Research Center for Computation and Visualization of Geometric Structures (The Geometry Center), University of Minnesota. 1993.