>Psychtoolbox>PsychColorimetric>PsychMunsell

[w,X,tri] = MunsellGriddata3(x,y,z,v,xi,yi,zi,method,options,X,tri)

This is a modified version of the Matlab function griddata3. We modified
to allow precomputing of the triangulation, and then direct use of that.
This will allows us to precompute the triangulation (slow) and
then interpolate using the same triangulation many times (fast, we hope).

GRIDDATA3 Data gridding and hyper-surface fitting for 3-dimensional data.
W = GRIDDATA3(X,Y,Z,V,XI,YI,ZI) fits a hyper-surface of the form
W = F(X,Y,Z) to the data in the (usually) nonuniformly-spaced vectors
(X,Y,Z,V). GRIDDATA3 interpolates this hyper-surface at the points
specified by (XI,YI,ZI) to produce W.

(XI,YI,ZI) is usually a uniform grid (as produced by MESHGRID) and is
where GRIDDATA3 gets its name.

[…] = GRIDDATA3(X,Y,Z,V,XI,YI,ZI,METHOD) where METHOD is one of
‘linear’ - Tessellation-based linear interpolation (default)
‘nearest’ - Nearest neighbor interpolation

defines the type of surface fit to the data.
All the methods are based on a Delaunay triangulation of the data.
If METHOD is [], then the default ‘linear’ method will be used.

[…] = GRIDDATA3(X,Y,Z,V,XI,YI,ZI,METHOD,OPTIONS) specifies a cell
array of strings OPTIONS to be used as options in Qhull via DELAUNAYN.
If OPTIONS is [], the default options will be used.
If OPTIONS is {‘’}, no options will be used, not even the default.

Example:
rand(‘state’,0);
x = 2*rand(5000,1)-1; y = 2*rand(5000,1)-1; z = 2*rand(5000,1)-1;
v = x.^2 + y.^2 + z.^2;
d = -0.8:0.05:0.8;
[xi,yi,zi] = meshgrid(d,d,d);
w = griddata3(x,y,z,v,xi,yi,zi);
Since it is difficult to visualize 4D data sets, use isosurface at 0.8:
p = patch(isosurface(xi,yi,zi,w,0.8));
isonormals(xi,yi,zi,w,p);
set(p,’FaceColor’,’blue’,’EdgeColor’,’none’);
view(3), axis equal, axis off, camlight, lighting phong

Class support for inputs X,Y,Z,V,XI,YI,ZI: double

See also GRIDDATA, GRIDDATAN, QHULL, DELAUNAYN, MESHGRID.