| 1 |
function [del] = griddata_preprocess(x,y,xi,yi,method) |
| 2 |
%GRIDDATA_PREPROCESS Pre-calculate Delaunay triangulation for use |
| 3 |
% with GRIDDATA_FAST. |
| 4 |
% |
| 5 |
% DEL = GRIDDATA_PREPROCESS(X,Y,XI,YI) |
| 6 |
|
| 7 |
% Based on |
| 8 |
% Clay M. Thompson 8-21-95 |
| 9 |
% Copyright 1984-2001 The MathWorks, Inc. |
| 10 |
% $Revision: 1.1 $ $Date: 2004/06/04 15:50:52 $ |
| 11 |
|
| 12 |
% $Header: $ |
| 13 |
% $Name: $ |
| 14 |
|
| 15 |
error(nargchk(4,5,nargin)) |
| 16 |
|
| 17 |
if prod(size(xi)) ~= prod(size(yi)) |
| 18 |
[yi,xi]=ndgrid(yi,xi); |
| 19 |
end |
| 20 |
|
| 21 |
if nargin<6, method = 'linear'; end |
| 22 |
if ~isstr(method), |
| 23 |
error('METHOD must be one of ''linear'',''cubic'',''nearest'', or ''v4''.'); |
| 24 |
end |
| 25 |
|
| 26 |
|
| 27 |
switch lower(method), |
| 28 |
case 'linear' |
| 29 |
del = linear(x,y,xi,yi); |
| 30 |
% case 'cubic' |
| 31 |
% zi = cubic(x,y,z,xi,yi); |
| 32 |
% case 'nearest' |
| 33 |
% zi = nearest(x,y,z,xi,yi); |
| 34 |
% case {'invdist','v4'} |
| 35 |
% zi = gdatav4(x,y,z,xi,yi); |
| 36 |
otherwise |
| 37 |
error('Unknown method.'); |
| 38 |
end |
| 39 |
|
| 40 |
|
| 41 |
|
| 42 |
%------------------------------------------------------------ |
| 43 |
function delau = linear(x,y,xi,yi) |
| 44 |
%LINEAR Triangle-based linear interpolation |
| 45 |
|
| 46 |
% Reference: David F. Watson, "Contouring: A guide |
| 47 |
% to the analysis and display of spacial data", Pergamon, 1994. |
| 48 |
|
| 49 |
siz = size(xi); |
| 50 |
xi = xi(:); yi = yi(:); % Treat these as columns |
| 51 |
x = x(:); y = y(:); % Treat these as columns |
| 52 |
|
| 53 |
% Triangularize the data |
| 54 |
tri = delaunayn([x y]); |
| 55 |
if isempty(tri), |
| 56 |
warning('Data cannot be triangulated.'); |
| 57 |
return |
| 58 |
end |
| 59 |
|
| 60 |
% Find the nearest triangle (t) |
| 61 |
t = tsearch(x,y,tri,xi,yi); |
| 62 |
|
| 63 |
% Only keep the relevant triangles. |
| 64 |
out = find(isnan(t)); |
| 65 |
if ~isempty(out), t(out) = ones(size(out)); end |
| 66 |
tri = tri(t,:); |
| 67 |
|
| 68 |
% Compute Barycentric coordinates (w). P. 78 in Watson. |
| 69 |
del = (x(tri(:,2))-x(tri(:,1))) .* (y(tri(:,3))-y(tri(:,1))) - ... |
| 70 |
(x(tri(:,3))-x(tri(:,1))) .* (y(tri(:,2))-y(tri(:,1))); |
| 71 |
w(:,3) = ((x(tri(:,1))-xi).*(y(tri(:,2))-yi) - ... |
| 72 |
(x(tri(:,2))-xi).*(y(tri(:,1))-yi)) ./ del; |
| 73 |
w(:,2) = ((x(tri(:,3))-xi).*(y(tri(:,1))-yi) - ... |
| 74 |
(x(tri(:,1))-xi).*(y(tri(:,3))-yi)) ./ del; |
| 75 |
w(:,1) = ((x(tri(:,2))-xi).*(y(tri(:,3))-yi) - ... |
| 76 |
(x(tri(:,3))-xi).*(y(tri(:,2))-yi)) ./ del; |
| 77 |
w(out,:) = zeros(length(out),3); |
| 78 |
|
| 79 |
delau.tri=tri; |
| 80 |
delau.w=w; |
| 81 |
delau.siz=siz; |
| 82 |
delau.out=out; |
| 83 |
|
| 84 |
%------------------------------------------------------------ |
Parent Directory
| 
Revision Log
| 
Revision Graph