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SVMCrossVal.git
somtoolbox2
sammon.m
starting som prediction fine-tuned class-performance visualisation
Christoph Budziszewski
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4dbef18
at 2009-01-21 16:34:25
sammon.m
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function P = sammon(D, P, varargin) %SAMMON Computes Sammon's mapping of a data set. % % P = sammon(D, P, [value], [mode], [alpha], [Mdist]) % % P = sammon(D,2); % projection to 2-dim space % P = sammon(sMap,3); % projects the codebook vectors % P = sammon(sMap,3,[],[],[],Md) % uses distance matrix Md % som_grid(sMap,'Coord',P) % visualization of map projection % % Input and output arguments ([]'s are optional): % D (matrix) size dlen x dim, data to be projected % (struct) data or map struct % P (scalar) output dimension % (matrix) size dlen x odim, initial projection matrix % [value] (scalar) all different modes (the next argument) require % a value, default = 100 % [mode] (string) 'steps' or 'errlimit' or 'errchange' or 'seconds', % see below, default is 'steps' % [alpha] (scalar) iteration step size, default = 0.2 % [Dist] (matrix) pairwise distance matrix, size dlen x dlen. % If the distances in the input space should % be calculated otherwise than as euclidian % distances, the distance from each vector % to each other vector can be given here, % size dlen x dlen. For example PDIST % function can be used to calculate the % distances: Dist = squareform(pdist(D,'mahal')); % % P (matrix) size dlen x odim, the projections % % The output dimension must be 2 or higher but (naturally) lower % than data set dimension. % % The mode argument determines the end condition for iteration. If % the mode argument is used, also the value argument has to be % specified. Different mode possibilities are: % 'steps' the iteration is terminated when it is run <value> % 'errlimit' steps, the iteration is terminated when projection error % is lower than <value>, % 'errchange' the iteration is terminated when change between % projection error on two successive iteration rounds % is less than <value> percent of total error, and % 'seconds' the iteration is terminated after <value> seconds % of iteration. % % See also CCA, PCAPROJ, SOM_GRID. % Reference: Sammon, J.W. Jr., "A nonlinear mapping for data % structure analysis", IEEE Transactions on Computers, vol. C-18, % no. 5, 1969, pp. 401-409. % Contributed to SOM Toolbox vs2, February 2nd, 2000 by Juha Vesanto % Copyright (c) by Juha Vesanto % http://www.cis.hut.fi/projects/somtoolbox/ % juuso 040100 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% check arguments error(nargchk(2, 6, nargin)); % check no. of input arguments is correct % input data if isstruct(D), if isfield(D, 'data'), D = D.data; % data struct elseif isfield(D, 'codebook'), D = D.codebook; % map struct else error('Invalid structure'); end end if any(isnan(D(:))), error('Cannot make Sammon''s projection for data with unknown components') end % compute data dimensions orig_si = size(D); dim = orig_si(end); noc = prod(orig_si)/dim; if length(orig_si)>2, D = reshape(D,[noc dim]); end % output dimension / initial projection matrix if prod(size(P))==1, odim = P; P = rand(noc,odim)-0.5; else si = size(P); odim = si(end); if prod(si) ~= noc*odim, error('Initial projection matrix size does not match data size'); end if length(si)>2, P = reshape(P,[noc odim]); end inds = find(isnan(P)); if length(inds), P(inds) = rand(size(inds)); end end if odim > dim | odim < 2, error('Output dimension must be within [2, dimension of data]'); end % determine operating mode if nargin < 3 | isempty(varargin{1}) | isnan(varargin{1}), value=100; else value = varargin{1}; end if nargin < 4 | isempty(varargin{2}) | isnan(varargin{2}), mode='steps'; else mode = varargin{2}; end switch mode, case 'steps', runlen = value; case 'errlimit', errlimit = value; case 'errchange', errchange = value; e_prev = 0; case 'seconds', endtime = value; otherwise, error(['Illegal mode: ' mode]); end % iteration step size if nargin > 4, alpha = varargin{3}; else alpha = NaN; end if isempty(alpha) | isnan(alpha), alpha = 0.2; end % mutual distances if nargin > 5, Mdist = varargin{4}; else Mdist = []; end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% initialization % these are used quite frequently noc_x_1 = ones(noc, 1); odim_x_1 = ones(odim,1); % compute mutual distances between vectors if isempty(Mdist) | all(isnan(Mdist(:))), fprintf(2, 'computing mutual distances\r'); dim_x_1 = ones(dim,1); for i = 1:noc, x = D(i,:); Diff = D - x(noc_x_1,:); N = isnan(Diff); Diff(find(N)) = 0; Mdist(:,i) = sqrt((Diff.^2)*dim_x_1); N = find(sum(N')==dim); %mutual distance unknown if ~isempty(N), Mdist(N,i) = NaN; end end else % if the distance matrix is output from PDIST function if size(Mdist,1)==1, Mdist = squareform(Mdist); end if size(Mdist,1)~=noc, error('Mutual distance matrix size and data set size do not match'); end end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% action if strcmp(mode, 'seconds'), tic; end; fprintf(2, 'iterating \r'); % sammon iteration x = P ; xu = zeros(noc, odim); xd = zeros(noc, odim); dq = zeros(noc, 1); dr = zeros(noc, 1); i = 0; ready = 0; while ~ready for j = 1:noc, xd = -x + x(j*noc_x_1,:); xd2 = xd.^2; dpj = sqrt(sum(xd2'))'; dq = Mdist(:,j) - dpj; dr = Mdist(:,j) .* dpj; ind = find(dr ~= 0); term = dq(ind) ./ dr(ind); e1 = sum(xd(ind,:) .* term(:,odim_x_1)); term2 = ((1.0 + dq(ind) ./ dpj(ind)) ./ dpj(ind)) ./ dr(ind); e2 = sum(term) - sum(xd2(ind,:) .* term2(:,odim_x_1)); xu(j,:) = x(j,:) + alpha * e1 ./ abs(e2); end % move the center of mass to the center c = sum(xu) / noc; x = xu - c(noc_x_1, :); i = i + 1; % compute mapping error % doing this adds about 25% to computing time if 0, e = 0; tot = 0; for j = 2:noc, d = Mdist(1:(j - 1), j); tot = tot + sum(d); ind = find(d ~= 0); xd = -x(1:(j - 1), :) + x(j * ones(j - 1, 1), :); ee = d - sqrt(sum(xd'.^2))'; e = e + sum(ee(ind).^2 ./ d(ind)); end e = e/tot; fprintf(2, '\r%d iterations, error %f', i, e); else fprintf(2, '\r%d iterations', i); end % determine is the iteration ready switch mode case 'steps', if i == runlen, ready = 1; end; case 'errlimit', if e < errlimit, ready = 1; end; case 'errchange', if i > 1 change = 100 * abs(e - e_prev) / e_prev; if change < errchange, ready = 1; end; fprintf(2, ', change of error %f %% ', change); end e_prev = e; case 'seconds' if toc > endtime, ready = 1; end; fprintf(2, ', elapsed time %f seconds ', toc); end fprintf(2, ' '); % If you want to see the Sammon's projection plotted (in 2-D and 3-D case), % execute the code below; it is not in use by default to speed up % computation. if 0, clf if odim == 1, plot(x(:,1), noc_x_1, 'o'); elseif odim == 2, plot(x(:,1), x(:,2), 'o'); else plot3(x(:,1), x(:,2), x(:,3), 'o') end drawnow end end fprintf(2, '\n'); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% clean up % reshape orig_si(end) = odim; P = reshape(x, orig_si); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%