forked from ilarinieminen/SOM-Toolbox
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathsom_dmat.m
68 lines (55 loc) · 1.82 KB
/
som_dmat.m
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
function dmat = som_dmat(sM,Ne,mode)
%SOM_DMAT Find distance to neighbors for each map unit.
%
% dmat = som_dmat(sM,[Ne],[mode])
%
% Input and output arguments ([]'s are optional):
% sM (struct) map or data struct
% (matrix) data matrix, size n x dim
% [Ne] (matrix) neighborhood connections matrix
% (string) 'Nk' (on map) or 'kNN' (any vector set)
% where k = some number, e.g. 'N1' or '10NN'
% (empty) use default
% [mode] (string) 'min', 'median', 'mean', 'max', or
% some arbitrary scalar function of
% a set of vectors
%
% dmat (vector) size n x 1, distance associated with each vector
%
% See also KMEANS_CLUSTERS, SOM_CLLINKAGE, SOM_CLSTRUCT.
% Copyright (c) 2000 by Juha Vesanto
% Contributed to SOM Toolbox on June 16th, 2000 by Juha Vesanto
% http://www.cis.hut.fi/projects/somtoolbox/
% Version 2.0beta juuso 220800
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% map
if isstruct(sM),
switch sM.type,
case 'som_map', M = sM.codebook; mask = sM.mask;
case 'som_data', M = sM.data; mask = ones(size(M,2),1);
end
else
M = sM; mask = ones(size(M,2),1);
end
[n dim] = size(M);
% neighborhoods
if nargin<2 || isempty(Ne), Ne = som_neighbors(sM);
elseif ischar(Ne), Ne = som_neighbors(sM,Ne);
end
l = size(Ne,1); Ne([0:l-1]*l+[1:l]) = 0; % set diagonal elements = 0
% mode
if nargin<3 || isempty(mode), mode = 'median'; end
calc = sprintf('%s(x)',mode);
% distances
dmat = zeros(n,1);
for i=1:n,
ne = find(Ne(i,:));
if any(ne),
[dummy,x] = som_bmus(M(ne,:),M(i,:),[1:length(ne)],mask);
dmat(i) = eval(calc);
else
dmat(i) = NaN;
end
end
return;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%