29.4 Interpolation on Scattered Data

An important use of the Delaunay tessellation is that it can be used to interpolate from scattered data to an arbitrary set of points. To do this the N-simplex of the known set of points is calculated with delaunay, delaunay3 or delaunayn. Then the simplicies in to which the desired points are found are identified. Finally the vertices of the simplicies are used to interpolate to the desired points. The functions that perform this interpolation are griddata, griddata3 and griddatan.

Function File: zi = griddata (x, y, z, xi, yi, method)

Function File: [xi, yi, zi] = griddata (x, y, z, xi, yi, method)

Generate a regular mesh from irregular data using interpolation. The function is defined by z = f (x, y). The interpolation points are all (xi, yi). If xi, yi are vectors then they are made into a 2D mesh.

The interpolation method can be "nearest", "cubic" or "linear". If method is omitted it defaults to "linear".

See also: delaunay.

Function File: vi = griddata3 (x, y, z, v xi, yi, zi, method, options)

Generate a regular mesh from irregular data using interpolation. The function is defined by y = f (x,y,z). The interpolation points are all xi.

The interpolation method can be "nearest" or "linear". If method is omitted it defaults to "linear".

See also: griddata, delaunayn.

Function File: yi = griddatan (x, y, xi, method, options)

Generate a regular mesh from irregular data using interpolation. The function is defined by y = f (x). The interpolation points are all xi.

The interpolation method can be "nearest" or "linear". If method is omitted it defaults to "linear".

See also: griddata, delaunayn.

An example of the use of the griddata function is

rand("state",1);
x=2*rand(1000,1)-1;
y=2*rand(size(x))-1;
z=sin(2*(x.^2+y.^2));
[xx,yy]=meshgrid(linspace(-1,1,32));
griddata(x,y,z,xx,yy);