Mercurial > hg > camir-aes2014
diff toolboxes/MIRtoolbox1.3.2/somtoolbox/som_eucdist2.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
---|---|
date | Tue, 10 Feb 2015 15:05:51 +0000 |
parents | |
children |
line wrap: on
line diff
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/toolboxes/MIRtoolbox1.3.2/somtoolbox/som_eucdist2.m Tue Feb 10 15:05:51 2015 +0000 @@ -0,0 +1,94 @@ +function d=som_eucdist2(Data, Proto) + +%SOM_EUCDIST2 Calculates matrix of squared euclidean distances between set of vectors or map, data struct +% +% d=som_eucdist2(D, P) +% +% d=som_eucdist(sMap, sData); +% d=som_eucdist(sData, sMap); +% d=som_eucdist(sMap1, sMap2); +% d=som_eucdist(datamatrix1, datamatrix2); +% +% Input and output arguments ([]'s are optional): +% D (matrix) size Nxd +% (struct) map or data struct +% P (matrix) size Pxd +% (struct) map or data struct +% d (matrix) distance matrix of size NxP +% +% IMPORTANT +% +% * Calculates _squared_ euclidean distances +% * Observe that the mask in the map struct is not taken into account while +% calculating the euclidean distance +% +% See also KNN, PDIST. + +% Contributed to SOM Toolbox 2.0, October 29th, 2000 by Johan Himberg +% Copyright (c) by Johan Himberg +% http://www.cis.hut.fi/projects/somtoolbox/ + +% Version 2.0beta Johan 291000 + +%% Init %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +if isstruct(Data); + if isfield(Data,'type') & ischar(Data.type), + ; + else + error('Invalid map/data struct?'); + end + switch Data.type + case 'som_map' + data=Data.codebook; + case 'som_data' + data=Data.data; + end +else + % is already a matrix + data=Data; +end + +% Take prototype vectors from prototype struct + +if isstruct(Proto), + + if isfield(Proto,'type') & ischar(Proto.type), + ; + else + error('Invalid map/data struct?'); + end + switch Proto.type + case 'som_map' + proto=Proto.codebook; + case 'som_data' + proto=Proto.data; + end +else + % is already a matrix + proto=Proto; +end + +% Check that inputs are matrices +if ~vis_valuetype(proto,{'nxm'}) | ~vis_valuetype(data,{'nxm'}), + error('Prototype or data input not valid.') +end + +% Record data&proto sizes and check their dims +[N_data dim_data]=size(data); +[N_proto dim_proto]=size(proto); +if dim_proto ~= dim_data, + error('Data and prototype vector dimension does not match.'); +end + +% Calculate euclidean distances between classifiees and prototypes +d=distance(data,proto); + +%%%% Classification %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function d=distance(X,Y); + +% Euclidean distance matrix between row vectors in X and Y + +U=~isnan(Y); Y(~U)=0; +V=~isnan(X); X(~V)=0; +d=abs(X.^2*U'+V*Y'.^2-2*X*Y');