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SVMCrossVal.git
somtoolbox2
som_clustercolor.m
starting som prediction fine-tuned class-performance visualisation
Christoph Budziszewski
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4dbef18
at 2009-01-21 16:34:25
som_clustercolor.m
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function color=som_clustercolor(m, class, colorcode) % SOM_CLUSTERCOLOR Sets map unit coloring according to classification % % syntax 1: color = som_clustercolor(m, class, [colorcode]) % syntax 2: color = som_clustercolor(class, colormatrix) % % Input and output arguments ([]'s are optional): % m (struct) map or topol struct % (cell array) of form {str,[m1 m2]} where str = 'hexa' % or 'rect' and [m1 m2] = msize. % class (matrix) Mxn matrix of integers (class labels) % where M is the number of map units and each % column gives some classification for the units. % colorcode (string) 'rgb1', 'rgb2' (default), 'rgb3', 'rgb4', 'hsv'. % colormatrix (matrix) Mx3 matrix of RGB triplets giving the % initial color code for each unit. % color (matrix) size Mx3xn of RGB triplets giving the % resulting color code for each unit % % The function gives a color coding by class and location for the % map units. The color is determined by calculating the mean of the % initial RGB values of units belonging to the same class. % % Function has two syntaxes: % % * If first argument gives the map topology, i.e. is map or topol struct % or cell indicating the topology, the initial color coding of the % units may be given by a string ('rgb1','rgb2','rgb3','rgb4', or 'hsv') % which describe a predefined coloring scheme. (see SOM_COLORCODE). % or an initial color matrix of size Mx3 with RGB triplets as rows. % * Another possibility is to give just the classification vector % of size Mx1 and an initial color matrix of size Mx3 with RGB % triplets as rows. % % EXAMPLE (requires Matlab Statistics Toolbox) % % % Do a 10-cluster single linkage hierachical clustering for SOM units % class=cluster(linkage(pdist(sM.codebook),'single'),10); % % Color code the clusters % C=som_clustercolor(sM, class, 'rgb2'); % % Visualize % som_show(sM,'color',C); % % See also SOM_COLORCODE, SOM_KMEANSCOLOR, SOM_CPLANE, SOM_SHOW % Contributed to SOM Toolbox 2.0, February 11th, 2000 by Johan Himberg % Copyright (c) by Johan Himberg % http://www.cis.hut.fi/projects/somtoolbox/ % Version 2.0beta Johan 100200 %%% Check arguments %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% error(nargchk(2, 3, nargin)); % check no. of input args is correct % Check 1s argument % Class matrix? if vis_valuetype(m, {'nxm'}); colorcode=class; class=m; if ~vis_valuetype(colorcode,{'nx3rgb',[size(class,1) 3]},'all'), error(['If map or topol is not specified the colorcode must be a' ... ' [size(class,1) 3] sized RGB matrix.']); end else [tmp,ok,tmp]=som_set(m); if isstruct(m) & all(ok) switch m.type case 'som_topol' % topol? msize=m.msize; lattice=m.lattice; case 'som_map' msize=m.topol.msize; % map? lattice=m.topol.lattice; otherwise error('Invalid map or topol struct.'); end % cell? elseif iscell(m) & vis_valuetype(size(m),{[1 2]}), if vis_valuetype(m{2},{[1 2]}) & vis_valuetype(m{1},{'string'}), lattice=m{1}; msize=m{2}; else error('Invalid map size information.'); end else % not known type error('Invalid first argument!'); end % Check map parameters switch lattice % lattice case 'hexa' ; case 'rect' ; otherwise error('Unknown lattice type'); end if length(msize)>2 % dimension error('Only 2D maps allowed!'); end % Check colorcode if nargin<3 | isempty(colorcode) colorcode='rgb2'; end end % Check class if any(class~=round(class)) error('Class labels must be integer numbers.'); end if min(class)<=0 error('Class numbers should be greater than 0'); end if ischar(colorcode), switch colorcode case{'rgb1','rgb2','rgb3','rgb4','hsv'} colorcode=som_colorcode(m, colorcode); otherwise error(['Color code not known: should be ''rgb1'',''rgb2'',' ... ' ''rgb3'',''rgb4'' or ''hsv''.']); end elseif ~vis_valuetype(colorcode,{'nx3rgb',[size(class,1) 3]},'all'); error(['Invalid colorcode matrix: should be a ' ... '[length(class) 3] sized RGB matrix.']); end %% Action %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Go through all i classifications (columns) for i=1:size(class,2), % Get unique class labels in ith classification c=unique(class(:,i))'; % row vector for loop indexing % Go through all class in ith classification for j=c; index=(class(:,i)==j); N=sum(index); colors=colorcode(index,:); % Calculate the mean color meancolor=repmat(mean(colors,1),N,1); % Select the original color that is closest to this mean dist=sum((meancolor-colors).^2,2); [tmp,min_dist_index]=min(dist); best_color=repmat(colors(min_dist_index,:),N,1); % Set the color to output variable color(index,:,i)=best_color; end end