Browse code

starting som prediction fine-tuned class-performance visualisation

git-svn-id: https://svn.discofish.de/MATLAB/spmtoolbox/SVMCrossVal@112 83ab2cfd-5345-466c-8aeb-2b2739fb922d

Christoph Budziszewski authored on21/01/2009 16:34:25
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+function minima = som_dmatminima(sM,U,Ne)
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+
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+%SOM_DMATMINIMA Find clusters based on local minima of U-matrix.
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+%
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+% minima = som_dmatminima(sM,[U],[Ne])
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+%
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+%  Input and output arguments ([]'s are optional):
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+%   sM         (struct) map struct
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+%   U          (matrix) the distance matrix from which minima is
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+%                       searched from 
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+%                       size msize(1) x ... x msize(end) or 
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+%                            2*msize(1)-1 x 2*msize(2)-1 or 
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+%                            munits x 1
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+%   Ne         (matrix) neighborhood connections matrix
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+%
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+%   minima     (vector) indeces of the map units where locla minima of
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+%                       of U-matrix (or other distance matrix occured)
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+%   
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+% See also KMEANS_CLUSTERS, SOM_CLLINKAGE, SOM_CLSTRUCT.
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+
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+% Copyright (c) 2000 by Juha Vesanto
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+% Contributed to SOM Toolbox on June 16th, 2000 by Juha Vesanto
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+% http://www.cis.hut.fi/projects/somtoolbox/
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+ 
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+% Version 2.0beta juuso 220800
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+
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+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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+
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+% map 
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+if isstruct(sM), 
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+  switch sM.type, 
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+   case 'som_map',  M = sM.codebook; mask = sM.mask; 
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+   case 'som_data', M = sM.data; mask = ones(size(M,2),1);
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+  end
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+else
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+  M = sM; mask = ones(size(M,2),1);
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+end
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+[munits dim] = size(M);
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+
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+% distances between map units
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+if nargin<2, U = []; end
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+
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+% neighborhoods 
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+if nargin<3, Ne = som_neighbors(sM); end
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+
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+% distance matrix
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+if nargin<2 | isempty(U), U = som_dmat(sM,Ne,'median'); end
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+if prod(size(U))>munits, U = U(1:2:size(U,1),1:2:size(U,2)); end
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+U = U(:); 
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+if length(U) ~= munits, error('Distance matrix has incorrect size.'); end
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+
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+% find local minima
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+minima = []; 
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+for i=1:munits, 
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+  ne = find(Ne(i,:));
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+  if all(U(i)<=U(ne)) & ~anycommon(ne,minima), minima(end+1)=i; end
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+end
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+
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+return; 
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+
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+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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+
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+function t = anycommon(i1,i2)
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+  if isempty(i1) | isempty(i2), t = 0; 
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+  else 
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+    m = max(max(i1),max(i2));
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+    t = any(sparse(i1,1,1,m,1) & sparse(i2,1,1,m,1)); 
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+  end
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+  return;   
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+