SVMCrossVal.git

starting som prediction fine-tuned class-performance visualisation
Parent fd18aa8
Christoph Budziszewski

Christoph Budziszewski commited on 2009-01-21 16:34:25
Zeige 100 geänderte Dateien mit 31716 Einfügungen und 15 Löschungen. 

git-svn-id: https://svn.discofish.de/MATLAB/spmtoolbox/SVMCrossVal@112 83ab2cfd-5345-466c-8aeb-2b2739fb922d
classify.asv
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,100 @@
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+function classify(varargin)
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+
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+
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+
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+switch nargin
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+    case 1
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+        paramModel = varargin{1};
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+        % PROJECT_BASE_PATH = 'D:\Analyze\Stimolos';
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+        PROJECT_BASE_PATH = 'D:\Analyze\Choice\24pilot';
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+        PROJECT_RESULT_PATH = 'results\SPM.mat';
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+    otherwise
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+        error('spmtoolbox:SVMCrossVal:arginError','Please Specify action and parameter model');
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+end
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+
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+
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+        % common params
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+        calculateParams  = struct;
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+        calculateParams.smoothed        = getDouble(paramModel.txtSmoothed);
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+
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+        calculateParams.frameShiftStart = getDouble(paramModel.txtFrameShiftStart);  % -20;
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+        calculateParams.frameShiftEnd   = getDouble(paramModel.txtFrameShiftEnd); %15;
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+        calculateParams.decodeDuration  = getDouble(paramModel.txtFrameShiftDur);
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+        calculateParams.psthStart       = getDouble(paramModel.txtPSTHStart); % -25;
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+        calculateParams.psthEnd         = getDouble(paramModel.txtPSTHEnd); % 20;
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+        calculateParams.baselineStart   = getDouble(paramModel.txtBaselineStart); % -22;
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+        calculateParams.baselineEnd     = getDouble(paramModel.txtBaselineEnd); % -20;
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+
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+        calculateParams.svmargs         = get(paramModel.txtSVMopts,'String');
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+        calculateParams.sessionList     = 1:3;
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+
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+        classStruct = parseClassDef(paramModel);
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+
33 
+
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+        calculateParams.labelMap        = LabelMap(classStruct.labelCells , classStruct.conditionCells, 'auto'); % LabelMap({'<','>','<+<','>+>','<+>','>+<'},{-2,-1,1,2,3,4}); 0 is autolabel
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+        calculateParams.classList       = getClasses(calculateParams.labelMap);
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+        calculateParams.eventList       = classStruct.eventMatrix; %[9,11,13; 10,12,14];
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+%         calculateParams.eventList       = getPSTEventMatrix(calculateParams.labelMap);
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+
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+        subjectSelection = getSubjectIDString(paramModel);
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+        decode = struct;
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+        decode.decodePerformance = [];
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+        decode.rawTimeCourse     = [];
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+
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+        for subjectCell = subjectSelection
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+            SubjectID = cell2mat(subjectCell);
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+            namehelper = strcat('s',SubjectID); %Vars can not start with numbers.
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+
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+            display('loading SPM.mat ...');
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+            spm = load(fullfile(PROJECT_BASE_PATH,SubjectID,PROJECT_RESULT_PATH));
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+            display('... done.');
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+
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+            %% calculate
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+            calculateParams.(namehelper).des             = spm.SPM;
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+            calculateParams.(namehelper).voxelList       = parseVoxelList(paramModel,SubjectID);
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+            assignin('base','calculateParams',calculateParams);
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+
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+            display(sprintf('calculating cross-validation performance time-shift for Subject %s. Please Wait. ...',SubjectID));
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+            display('switching off all warnings');
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+            warning_state               = warning('off','all');
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+            display('calculating ...');
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+            decode.(namehelper)         = calculateDecodePerformance(calculateParams,SubjectID);
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+            display('... done');
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+            display('restoring warnings');
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+            warning(warning_state);
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+
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+            decode.decodePerformance    = [decode.decodePerformance decode.(namehelper).decodePerformance];
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+            decode.rawTimeCourse        = [decode.rawTimeCourse decode.(namehelper).rawTimeCourse];
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+
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+            assignin('base','decode',decode);
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+        end
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+
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+        display('Finished calculations.');
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+        display('Plotting...');
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+
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+        plotParams                  = struct;
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+        plotParams.psthStart        = calculateParams.psthStart;
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+        plotParams.psthEnd   =  calculateParams.psthEnd;
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+        plotParams.nClasses  = length(calculateParams.classList);
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+
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+        plotParams.frameShiftStart   = calculateParams.frameShiftStart;
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+        plotParams.frameShiftEnd     = calculateParams.frameShiftEnd;
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+        plotParams.decodePerformance = decode.decodePerformance;
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+        plotParams.rawTimeCourse     = decode.rawTimeCourse;
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+
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+        if numel(subjectSelection) == 1
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+          plotParams.SubjectID         = SubjectID;
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+        else
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+          plotParams.SubjectID         = 'Multiple';
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+        end
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+
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+        plotParams.smoothed          = boolToYesNoString(calculateParams.smoothed);
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+
93 
+
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+        assignin('base','plotParams',plotParams);
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+%         plotDecodePerformance(params.psthStart,params.psthEnd,params.nClasses,decode.decodeTable,params.frameShiftStart,params.frameShiftEnd,decode.rawTimeCourse);
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+        plotDecodePerformance(plotParams);
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+
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+        display('all done.');
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+
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+    end
0 101 
\ No newline at end of file
plotDecodePerformance.asv
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,103 @@
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+function plotDecodePerformance(varargin)
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+% plotDecodePerformance(timeline,decodePerformance,nClasses,rawData)
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+
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+PSTH_AXIS_MIN = -1;
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+PSTH_AXIS_MAX = 1;
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+
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+switch nargin
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+
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+    case 1
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+        inputStruct       = cell2mat(varargin(1));
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+
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+        psthStart         = inputStruct.psthStart;
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+        psthEnd           = inputStruct.psthEnd;
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+        nClasses          = inputStruct.nClasses;
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+        decodePerformance = inputStruct.decodePerformance;
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+        frameStart        = inputStruct.frameShiftStart;
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+        frameEnd          = inputStruct.frameShiftEnd;
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+        psth              = inputStruct.rawTimeCourse;
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+        SubjectID         = inputStruct.SubjectID;
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+        smoothed          = inputStruct.smoothed;
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+
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+    otherwise
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+        error('spmtoolbox:SVMCrossVal:plotDecodePerformance:WrongArgument','Wrong Arguments');
24 
+end
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+
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+    f = figure;
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+    subplot(2,1,1);
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+    hold on;
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+      for voxel = 1:size(psth,2)
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+          for label = 1:size(psth{voxel},2)
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+              psthData = [];
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+              for timepoint = 1:size(psth{voxel}{label},2)
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+                  psthData = nanmean(psth{voxel}{label});
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+              end
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+              plot(psthStart:psthEnd,psthData,[colorChooser(voxel), lineStyleChooser(label)]);
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+          end
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+      end
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+    axis([psthStart psthEnd PSTH_AXIS_MIN PSTH_AXIS_MAX])
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+    hold off
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+
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+    subplot(2,1,2)
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+    hold on;
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+
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+    chanceLevel = 100/nClasses;
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+    goodPredictionLevel = chanceLevel*1.5;
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+    plot([psthStart psthEnd],[chanceLevel chanceLevel],'r');
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+    plot([psthStart psthEnd],[goodPredictionLevel goodPredictionLevel],'g');
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+    axis([psthStart psthEnd 0 100])
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+
50 
+    plot(frameStart:frameEnd, mean(decodePerformance,2) ,'b');
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+    PLOT_STD_ERR = 1;
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+    PLOT_CLASS_PERFORMANCE = 1;
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+    if PLOT_STD_ERR
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+        se = myStdErr(decodePerformance,2);
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+        plot(frameStart:frameEnd, mean(decodePerformance,2)+se ,'b:');
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+        plot(frameStart:frameEnd, mean(decodePerformance,2)-se ,'b:');
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+    end
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+    if PLOT_CLASS_PERFORMANCE
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+        for c = 1:nClasses
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+            plot(frameStart:frameEnd, decodePerformance() ,[colorChooser(c+2) '-']);
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+        end
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+    end
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+
64 
+
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+    hold off;
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+
67 
+    title = sprintf('Subject %s, over %g voxel, smoothed %s',SubjectID,size(psth,2),smoothed);
68 
+    set(f,'Name',title);
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+    display(sprintf('%s',title));
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+
71 
+
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+
73 
+end
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+
75 
+
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+function color = colorChooser(n)
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+    switch (mod(n,8))
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+    case 0
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+        color = 'y';
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+    case 1
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+        color = 'r';
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+    case 2
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+        color = 'b';
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+    case 3
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+        color = 'g';
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+    otherwise
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+        color = 'k';
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+    end
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+end
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+
91 
+function style = lineStyleChooser(n)
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+switch(mod(n,4))
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+    case 0
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+      style = '--';
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+    case 1
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+        style = '-';
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+    case 2
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+        style = ':';
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+    case 3
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+        style = '-.';
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+end
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+end
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+
plotDecodePerformance.m
Zeige Datei @ 4dbef18
... ... 
@@ -43,14 +43,28 @@ end
43 43
44 44 
     chanceLevel = 100/nClasses;
45 45 
     goodPredictionLevel = chanceLevel*1.5;
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-    plot([psthStart psthEnd],[chanceLevel chanceLevel],'r');
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-    plot([psthStart psthEnd],[goodPredictionLevel goodPredictionLevel],'g');
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+    plot([psthStart psthEnd],[chanceLevel chanceLevel],'k:');
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+    plot([psthStart psthEnd],[goodPredictionLevel goodPredictionLevel],'k:');
48 48 
     axis([psthStart psthEnd 0 100])
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50 
+
51 
+    PLOT_EXTRAS = 'class performance'
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+
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+    switch PLOT_EXTRAS
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+        case 'stderr'
50 55 
             plot(frameStart:frameEnd, mean(decodePerformance,2) ,'b');
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+
51 57 
             se = myStdErr(decodePerformance,2);
52 58 
             plot(frameStart:frameEnd, mean(decodePerformance,2)+se ,'b:');
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             plot(frameStart:frameEnd, mean(decodePerformance,2)-se ,'b:');
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+        case 'class performance'
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+            for c = 1:size(decodePerformance,2)
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+                plot(frameStart:frameEnd, decodePerformance(:,c) ,[colorChooser(mod(c,nClasses)+3) '-']);
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+            end
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+
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+            plot(frameStart:frameEnd, mean(decodePerformance,2) ,'b','LineWidth',2);
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+
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+    end
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56 70 
     hold off;
... ... 
@@ -67,13 +81,17 @@ end
67 81 
 function color = colorChooser(n)
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     switch (mod(n,8))
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     case 0
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-        color = 'y';
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-    case 1
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         color = 'r';
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+    case 1
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+        color = 'g';
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     case 2
74 88 
         color = 'b';
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     case 3
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-        color = 'g';
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+        color = 'c';
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+    case 4
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+        color = 'm';
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+    case 5
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+        color = 'y';
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     otherwise
78 96 
         color = 'k';
79 97 
     end
private/calculateDecodePerformance.m
Zeige Datei @ 4dbef18
... ... 
@@ -59,33 +59,38 @@ maxPerformance = -inf;
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                 svmlabel  = svmlabel(rndindex);
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             end
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-            SVM_METHOD = 2;
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+            SVM_METHOD = 'class performance'
63 63 
             switch SVM_METHOD;
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-                case 1
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+                case 'libsvm crossval'
65 65 
                     performance  = svmtrain(svmlabel, svmdata, svmargs);
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67 67 
                     minPerformance = min(minPerformance,performance);
68 68 
                     maxPerformance = max(maxPerformance,performance);
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70 70 
                     decodePerformance = [decodePerformance; performance];
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-                case 2
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+                case 'class performance'
72 72 
                     newsvmopt = killCrossvalOpt(svmargs);
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74 74 
                     model = svmtrain(svmlabel,svmdata,newsvmopt);
75 75 
                     classperformance = [];
76 76 
                     for class = unique(svmlabel)';
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-%                         assignin('base','uniquelabel',unique(svmlabel));
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-%                         assignin('base','class',class);
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-%                         assignin('base','svmlabel',svmlabel);
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+
80 78 
                         filterindex = find(class == svmlabel);
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-                        testing_label = svmlabel(filterindex)
82 
-                        testing_data  = svmdata(filterindex)
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-                        [plabel accuracy dvalue] = svmpredict(testing_label,testing_data,model,'')
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-%                         assignin('base','accuracy',accuracy);
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+                        testing_label = svmlabel(filterindex);
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+                        testing_data  = svmdata(filterindex);
81 
+                        [plabel accuracy dvalue] = svmpredict(testing_label,testing_data,model,'');
82 
+
85 83 
                         classperformance = [classperformance accuracy(1)];
86 84 
                     end
87 85 
                     decodePerformance = [decodePerformance; classperformance];
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87 
+                case 'som training'
88 
+                    display('SOM TRAINING');
89 
+                    addpath 'somtoolbox2';
90 
+                    sD = som_data_struct(svmdata);
91 
+                    assignin('base','sD',sD);
92 
+                    sM = som_make(sD,'msize', [3 4],'lattice', 'rect');
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+
89 94 
             end
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91 96 
         end
somtoolbox2/Contents.m
Zeige Datei @ 4dbef18
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@@ -0,0 +1,196 @@
1 
+% SOM Toolbox
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+% Version 2.0beta, May 30 2002
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+%
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+% Copyright 1997-2000 by
5 
+% Esa Alhoniemi, Johan Himberg, Juha Parhankangas and Juha Vesanto
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+% Contributed files may contain copyrights of their own.
7 
+%
8 
+% SOM Toolbox comes with ABSOLUTELY NO WARRANTY; for details
9 
+% see License.txt in the program package. This is free software,
10 
+% and you are welcome to redistribute it under certain conditions;
11 
+% see License.txt for details.
12 
+%
13 
+%
14 
+% Demos
15 
+%
16 
+%            som_demo1   SOM Toolbox demo 1: basic properties
17 
+%            som_demo2   SOM Toolbox demo 2: basic usage
18 
+%            som_demo3   SOM Toolbox demo 3: visualization
19 
+%            som_demo4   SOM Toolbox demo 4: data analysis
20 
+%
21 
+% Creation of structs
22 
+%
23 
+%              som_set   create & set (& check) values to structs
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+%             som_info   print out information on a given struct
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+%      som_data_struct   create & initialize a data struct
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+%       som_map_struct   create & initialize a map struct
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+%     som_topol_struct   create & initialize a topology struct
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+%     som_train_struct   create & initialize a train struct
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+%         som_clstruct   create a cluster struct
30 
+%            som_clset   set properties in a cluster struct
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+%            som_clget   get stuff from a cluster struct
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+%
33 
+% Struct conversion and file I/O
34 
+%
35 
+%           som_vs1to2   converts a version 1.0 struct to version 2.0 struct
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+%           som_vs2to1   converts a version 2.0 struct to version 1.0 struct
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+%        som_read_data   reads a (SOM_PAK format) ASCII data file
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+%       som_write_data   writes a SOM_PAK format codebook file
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+%        som_write_cod   writes a SOM_PAK format data file
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+%         som_read_cod   reads a SOM_PAK format codebook file
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+%
42 
+% Data preprocessing
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+%
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+%        som_normalize   normalize data set
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+%      som_denormalize   denormalize data set
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+%    som_norm_variable   (de)normalize one variable
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+%           preprocess   preprocessing GUI
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+%
49 
+% Initialization and training functions
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+%
51 
+%             som_make   create, initialize and train a SOM
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+%         som_randinit   random initialization algorithm
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+%          som_lininit   linear initialization algorithm
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+%         som_seqtrain   sequential training algorithm
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+%       som_batchtrain   batch training algorithm
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+%              som_gui   SOM initialization and training GUI
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+%       som_prototrain   a simple version of sequential training: easy to modify
58 
+%
59 
+% Clustering algorithms
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+%
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+%           som_kmeans   k-means algorithm (was earlier kmeans)
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+%      kmeans_clusters   try and evaluate several k-means clusterings
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+%           neural_gas   neural gas vector quantization algorithm
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+%          som_linkage   hierarchical clustering algorithms
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+%        som_cllinkage   hierarchical clustering of SOM
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+%       som_dmatminima   local minima from distance (or U-) matrix
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+%     som_dmatclusters   distance (or U-) matrix based clustering
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+%         som_clspread   spreads clusters to unassinged map units
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+%           som_cldist   calculate distances between clusters
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+%         som_gapindex   gap validity index of clustering
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+%             db_index   Davies-Bouldin validity index of clustering
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+%
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+% Supervised/classification algorithms
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+%
75 
+%       som_supervised   supervised SOM algorithm
76 
+%                 lvq1   LVQ1 algorithm
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+%                 lvq3   LVQ3 algorithm
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+%                  knn   k-NN classification algorithm
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+%              knn_old   k-NN classification algorithm (old version)
80 
+%
81 
+% SOM error measures
82 
+%
83 
+%          som_quality   quantization and topographic error of SOM
84 
+%       som_distortion   SOM distortion measure
85 
+%      som_distortion3   elements of the SOM distortion measure
86 
+%
87 
+% Auxiliary functions
88 
+%
89 
+%             som_bmus   calculates BMUs for given data vectors
90 
+%         som_eucdist2   pairwise squared euclidian distances between vectors
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+%            som_mdist   calculates pairwise distances between vectors
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+%           som_divide   extract subsets of data based on map
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+%            som_label   give labels to map units
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+%        som_label2num   rcodes string data labels to interger class labels
95 
+%        som_autolabel   automatically labels the SOM based on given data
96 
+%      som_unit_coords   calculates coordinates in output space for map units
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+%       som_unit_dists   distances in output space between map units
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+%      som_unit_neighs   units in 1-neighborhood for each map unit
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+%     som_neighborhood   calculates neighborhood matrix for the given map
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+%        som_neighbors   calculates different kinds of neighborhoods
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+%           som_neighf   calculates neighborhood function values
102 
+%           som_select   GUI for manual selection of map units
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+%     som_estimate_gmm   create Gaussian mixture model on top of SOM
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+%  som_probability_gmm   evaluate Gaussian mixture model
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+%          som_ind2sub   from linear index to subscript index
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+%          som_sub2ind   from subscript index to linear index
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+%          som_ind2cod   from linear index to SOM_PAK linear index
108 
+%          som_cod2ind   from SOM_linear index to SOM_PAK linear index
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+%             nanstats   mean, std and median which ignore NaNs
110 
+%   som_modify_dataset   add, remove, or extract samples and components
111 
+%         som_fillnans   fill NaNs in a data set based on given SOM
112 
+%            som_stats   statistics of a data set
113 
+%           som_drmake   calculate descriptive rules for a cluster
114 
+%           som_dreval   evaluate descriptive rules for a cluster
115 
+%         som_drsignif   rule significance measures
116 
+%
117 
+% Using SOM_PAK from Matlab
118 
+%
119 
+%      som_sompaktrain   uses SOM_PAK to train a map
120 
+%           sompak_gui   GUI for using SOM_PAK from Matlab
121 
+%          sompak_init   call SOM_PAK's initialization programs from Matlab
122 
+%      sompak_init_gui   GUI for using SOM_PAK's initialization from Matlab
123 
+%    sompak_rb_control   an auxiliary function for sompak_*_gui functions.
124 
+%        sompak_sammon   call SOM_PAK's Sammon program from Matlab
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+%    sompak_sammon_gui   GUI for using SOM_PAK's Sammon program from Matlab
126 
+%         sompak_train   call SOM_PAK's training program from Matlab
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+%     sompak_train_gui   GUI for using SOM_PAK's training program from Matlab
128 
+%
129 
+% Visualization
130 
+%
131 
+%             som_show   basic visualization
132 
+%         som_show_add   add labels, hits and trajectories
133 
+%       som_show_clear   remove extra markers
134 
+%       som_recolorbar   refresh/reconfigure colorbars
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+%         som_show_gui   GUI for using som_show and associated functions
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+%             som_grid   visualization of SOM grid
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+%           som_cplane   component planes and U-matrices
138 
+%         som_barplane   bar chart visualization of map
139 
+%         som_pieplane   pie chart visualization of map
140 
+%        som_plotplane   plot chart visualization of map
141 
+%       som_trajectory   launches a GUI for presenting comet-trajectories
142 
+%       som_dendrogram   visualization of clustering tree
143 
+%       som_plotmatrix   pairwise scatter plots and histograms
144 
+%    som_order_cplanes   order and visualize the component planes
145 
+%           som_clplot   plots of clusters (based on cluster struct)
146 
+% som_projections_plot   projections plots (see som_projections)
147 
+%       som_stats_plot   plots of statistics (see som_stats)
148 
+%
149 
+% Auxiliary functions for visualization
150 
+%
151 
+%                 hits   calculates hits, or sum of values for each map unit
152 
+%             som_hits   calculates the response of data on the map
153 
+%             som_umat   calculates the U-matrix
154 
+%                  cca   curvilinear component analysis projection algorithm
155 
+%              pcaproj   principal component projection algorithm
156 
+%               sammon   Sammon's mapping projection algorithm
157 
+%       som_connection   connection matrix for map
158 
+%       som_vis_coords   map unit coordinates used in visualizations
159 
+%        som_colorcode   create color coding for map/2D data
160 
+%         som_bmucolor   colors of the BMUs from a given map color code
161 
+%        som_normcolor   simulate indexed colormap
162 
+%     som_clustercolor   color coding which depends on clustering structure
163 
+%      som_kmeanscolor   color coding according to k-means clustering
164 
+%     som_kmeanscolor2   a newer version of the som_kmeanscolor function
165 
+%       som_fuzzycolor   a fuzzy color coding
166 
+%         som_coloring   a SOM-based color coding
167 
+%      som_projections   calculates a default set of projections
168 
+%
169 
+% Report generation stuff
170 
+%
171 
+%     som_table_struct   creates a table struct
172 
+%     som_table_modify   modifies a table struct
173 
+%      som_table_print   print a table in various formats
174 
+%            rep_utils   various utilities for printing report elements
175 
+%      som_stats_table   a table of data set statistics
176 
+%     som_stats_report   report on data set statistics
177 
+%
178 
+% Low level routines used by visualization functions
179 
+%
180 
+%            vis_patch   defines hexagonal and rectangular patches
181 
+%    vis_som_show_data   returns UserData and subplot handles stored by som_show.m
182 
+%        vis_valuetype   used for type checks
183 
+%         vis_footnote   adds a movable text to the current figure
184 
+%          vis_trajgui   the actual GUI started by som_trajectory.m
185 
+% vis_PlaneAxisProperties   set axis properties in visualization functions
186 
+% vis_footnoteButtonDownFcn   callback function for vis_footnote.m
187 
+%     vis_planeGetArgs   converts topol struct to lattice, msize argument pair
188 
+%    vis_show_gui_comp   internal function used by som_show_gui.m
189 
+%    vis_show_gui_tool   internal function used by som_show_gui.m
190 
+%
191 
+% Other
192 
+%
193 
+%           somtoolbox   this file
194 
+%            iris.data   IRIS data set (used in demos)
195 
+%          License.txt   GNU General Public License
196 
+%        Copyright.txt   Copyright notice
somtoolbox2/Copyright.txt
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1 
+COPYRIGHT
2 
+---------
3 
+
4 
+SOM Toolbox 2.0, a software library for Matlab 5 implementing the
5 
+Self-Organizing Map algorithm is Copyright (C) 1999 by Esa Alhoniemi,
6 
+Johan Himberg, Jukka Parviainen and Juha Vesanto.
7 
+
8 
+This package is free software; you can redistribute it and/or
9 
+modify it under the terms of the GNU General Public License
10 
+as published by the Free Software Foundation; either version 2
11 
+of the License, or any later version.
12 
+
13 
+Note: only part of the files distributed in the package belong to the
14 
+SOM Toolbox. The package also contains contributed files, which may
15 
+have their own copyright notices. If not, the GNU General Public
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+License holds for them, too, but so that the author(s) of the file
17 
+have the Copyright.
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+
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+This package is distributed in the hope that it will be useful,
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+but WITHOUT ANY WARRANTY; without even the implied warranty of
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+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
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+GNU General Public License for more details.
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+
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+You should have received a copy of the GNU General Public License
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+along with this package (file License.txt); if not, write to the Free
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+Software Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
27 
+02111-1307, USA.
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+
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+
30 
+LICENSING THE LIBRARY FOR PROPRIETARY PROGRAMS
31 
+----------------------------------------------
32 
+
33 
+As stated in the GNU General Public License (see License.txt) it is
34 
+not possible to include this software library in a commercial
35 
+proprietary program without written permission from the owners of the
36 
+copyright. If you wish to obtain such permission, you can reach us by
37 
+paper mail:
38 
+
39 
+  SOM Toolbox team
40 
+  Laboratory of Computer and Information Science
41 
+  P.O.Box 5400
42 
+  FIN-02015 HUT
43 
+  Finland
44 
+  Europe
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+
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+and by email:
47 
+
48 
+  somtlbx@mail.cis.hut.fi
49 
+
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+
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+
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+
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+
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+
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+
somtoolbox2/License.txt
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... ... 
@@ -0,0 +1,386 @@
1 
+GNU GENERAL PUBLIC LICENSE
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+
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+Version 2, June 1991
4 
+
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+Copyright (C) 1989, 1991 Free Software Foundation, Inc.
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+
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+------------------------------------------------------------------------
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+How to Apply These Terms to Your New Programs
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+If you develop a new program, and you want it to be of the greatest
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+ <signature of Ty Coon>, 1 April 1989
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+ Ty Coon, President of Vice
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+This General Public License does not permit incorporating your program
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+you may consider it more useful to permit linking proprietary
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+FSF & GNU inquiries & questions to gnu@prep.ai.mit.edu.
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+Copyright notice above.
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+
somtoolbox2/cca.m
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@@ -0,0 +1,282 @@
1 
+function [P] = cca(D, P, epochs, Mdist, alpha0, lambda0)
2 
+
3 
+%CCA Projects data vectors using Curvilinear Component Analysis.
4 
+%
5 
+% P = cca(D, P, epochs, [Dist], [alpha0], [lambda0])
6 
+%
7 
+%  P = cca(D,2,10);           % projects the given data to a plane
8 
+%  P = cca(D,pcaproj(D,2),5); % same, but with PCA initialization
9 
+%  P = cca(D, 2, 10, Dist);   % same, but the given distance matrix is used
10 
+%
11 
+%  Input and output arguments ([]'s are optional):
12 
+%   D          (matrix) the data matrix, size dlen x dim
13 
+%              (struct) data or map struct
14 
+%   P          (scalar) output dimension
15 
+%              (matrix) size dlen x odim, the initial projection
16 
+%   epochs     (scalar) training length
17 
+%   [Dist]     (matrix) pairwise distance matrix, size dlen x dlen.
18 
+%                       If the distances in the input space should
19 
+%                       be calculated otherwise than as euclidian
20 
+%                       distances, the distance from each vector
21 
+%                       to each other vector can be given here,
22 
+%                       size dlen x dlen. For example PDIST
23 
+%                       function can be used to calculate the
24 
+%                       distances: Dist = squareform(pdist(D,'mahal'));
25 
+%   [alpha0]   (scalar) initial step size, 0.5 by default
26 
+%   [lambda0]  (scalar) initial radius of influence, 3*max(std(D)) by default
27 
+%
28 
+%   P          (matrix) size dlen x odim, the projections
29 
+%
30 
+% Unknown values (NaN's) in the data: projections of vectors with
31 
+% unknown components tend to drift towards the center of the
32 
+% projection distribution. Projections of totally unknown vectors are
33 
+% set to unknown (NaN).
34 
+%
35 
+% See also SAMMON, PCAPROJ.
36 
+
37 
+% Reference: Demartines, P., Herault, J., "Curvilinear Component
38 
+%   Analysis: a Self-Organizing Neural Network for Nonlinear
39 
+%   Mapping of Data Sets", IEEE Transactions on Neural Networks,
40 
+%   vol 8, no 1, 1997, pp. 148-154.
41 
+
42 
+% Contributed to SOM Toolbox 2.0, February 2nd, 2000 by Juha Vesanto
43 
+% Copyright (c) by Juha Vesanto
44 
+% http://www.cis.hut.fi/projects/somtoolbox/
45 
+
46 
+% juuso 171297 040100
47 
+
48 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
49 
+%% Check arguments
50 
+
51 
+error(nargchk(3, 6, nargin)); % check the number of input arguments
52 
+
53 
+% input data
54 
+if isstruct(D),
55 
+  if strcmp(D.type,'som_map'), D = D.codebook; else D = D.data; end
56 
+end
57 
+[noc dim] = size(D);
58 
+noc_x_1  = ones(noc, 1); % used frequently
59 
+me = zeros(1,dim); st = zeros(1,dim);
60 
+for i=1:dim,
61 
+  me(i) = mean(D(find(isfinite(D(:,i))),i));
62 
+  st(i) = std(D(find(isfinite(D(:,i))),i));
63 
+end
64 
+
65 
+% initial projection
66 
+if prod(size(P))==1,
67 
+  P = (2*rand(noc,P)-1).*st(noc_x_1,1:P) + me(noc_x_1,1:P);
68 
+else
69 
+  % replace unknown projections with known values
70 
+  inds = find(isnan(P)); P(inds) = rand(size(inds));
71 
+end
72 
+[dummy odim] = size(P);
73 
+odim_x_1  = ones(odim, 1); % this is used frequently
74 
+
75 
+% training length
76 
+train_len = epochs*noc;
77 
+
78 
+% random sample order
79 
+rand('state',sum(100*clock));
80 
+sample_inds = ceil(noc*rand(train_len,1));
81 
+
82 
+% mutual distances
83 
+if nargin<4 | isempty(Mdist) | all(isnan(Mdist(:))),
84 
+  fprintf(2, 'computing mutual distances\r');
85 
+  dim_x_1 = ones(dim,1);
86 
+  for i = 1:noc,
87 
+    x = D(i,:);
88 
+    Diff = D - x(noc_x_1,:);
89 
+    N = isnan(Diff);
90 
+    Diff(find(N)) = 0;
91 
+    Mdist(:,i) = sqrt((Diff.^2)*dim_x_1);
92 
+    N = find(sum(N')==dim); %mutual distance unknown
93 
+    if ~isempty(N), Mdist(N,i) = NaN; end
94 
+  end
95 
+else
96 
+  % if the distance matrix is output from PDIST function
97 
+  if size(Mdist,1)==1, Mdist = squareform(Mdist); end
98 
+  if size(Mdist,1)~=noc,
99 
+    error('Mutual distance matrix size and data set size do not match');
100 
+  end
101 
+end
102 
+
103 
+% alpha and lambda
104 
+if nargin<5 | isempty(alpha0) | isnan(alpha0), alpha0 = 0.5; end
105 
+alpha = potency_curve(alpha0,alpha0/100,train_len);
106 
+
107 
+if nargin<6 | isempty(lambda0) | isnan(lambda0), lambda0 = max(st)*3; end
108 
+lambda = potency_curve(lambda0,0.01,train_len);
109 
+
110 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
111 
+%% Action
112 
+
113 
+k=0; fprintf(2, 'iterating: %d / %d epochs\r',k,epochs);
114 
+
115 
+for i=1:train_len,
116 
+
117 
+  ind = sample_inds(i);     % sample index
118 
+  dx = Mdist(:,ind);        % mutual distances in input space
119 
+  known = find(~isnan(dx)); % known distances
120 
+
121 
+  if ~isempty(known),
122 
+    % sample vector's projection
123 
+    y = P(ind,:);
124 
+
125 
+    % distances in output space
126 
+    Dy = P(known,:) - y(noc_x_1(known),:);
127 
+    dy = sqrt((Dy.^2)*odim_x_1);
128 
+
129 
+    % relative effect
130 
+    dy(find(dy==0)) = 1;        % to get rid of div-by-zero's
131 
+    fy = exp(-dy/lambda(i)) .* (dx(known) ./ dy - 1);
132 
+
133 
+    % Note that the function F here is e^(-dy/lambda))
134 
+    % instead of the bubble function 1(lambda-dy) used in the
135 
+    % paper.
136 
+
137 
+    % Note that here a simplification has been made: the derivatives of the
138 
+    % F function have been ignored in calculating the gradient of error
139 
+    % function w.r.t. to changes in dy.
140 
+
141 
+    % update
142 
+    P(known,:) = P(known,:) + alpha(i)*fy(:,odim_x_1).*Dy;
143 
+  end
144 
+
145 
+  % track
146 
+  if rem(i,noc)==0,
147 
+    k=k+1; fprintf(2, 'iterating: %d / %d epochs\r',k,epochs);
148 
+  end
149 
+
150 
+end
151 
+
152 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
153 
+%% clear up
154 
+
155 
+% calculate error
156 
+error = cca_error(P,Mdist,lambda(train_len));
157 
+fprintf(2,'%d iterations, error %f          \n', epochs, error);
158 
+
159 
+% set projections of totally unknown vectors as unknown
160 
+unknown = find(sum(isnan(D)')==dim);
161 
+P(unknown,:) = NaN;
162 
+
163 
+return;
164 
+
165 
+
166 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
167 
+%% tips
168 
+
169 
+% to plot the results, use the code below
170 
+
171 
+%subplot(2,1,1),
172 
+%switch(odim),
173 
+%  case 1, plot(P(:,1),ones(dlen,1),'x')
174 
+%  case 2, plot(P(:,1),P(:,2),'x');
175 
+%  otherwise, plot3(P(:,1),P(:,2),P(:,3),'x'); rotate3d on
176 
+%end
177 
+%subplot(2,1,2), dydxplot(P,Mdist);
178 
+
179 
+% to a project a new point x in the input space to the output space
180 
+% do the following:
181 
+
182 
+% Diff = D - x(noc_x_1,:); Diff(find(isnan(Diff))) = 0;
183 
+% dx = sqrt((Diff.^2)*dim_x_1);
184 
+% p = project_point(P,x,dx); % this function can be found from below
185 
+% tlen = size(p,1);
186 
+% plot(P(:,1),P(:,2),'bx',p(tlen,1),p(tlen,2),'ro',p(:,1),p(:,2),'r-')
187 
+
188 
+% similar trick can be made to the other direction
189 
+
190 
+
191 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
192 
+%% subfunctions
193 
+
194 
+function vals = potency_curve(v0,vn,l)
195 
+
196 
+  % curve that decreases from v0 to vn with a rate that is
197 
+  % somewhere between linear and 1/t
198 
+  vals = v0 * (vn/v0).^([0:(l-1)]/(l-1));
199 
+
200 
+
201 
+function error = cca_error(P,Mdist,lambda)
202 
+
203 
+  [noc odim] = size(P);
204 
+  noc_x_1 = ones(noc,1);
205 
+  odim_x_1 = ones(odim,1);
206 
+
207 
+  error = 0;
208 
+  for i=1:noc,
209 
+    known = find(~isnan(Mdist(:,i)));
210 
+    if ~isempty(known),
211 
+      y = P(i,:);
212 
+      Dy = P(known,:) - y(noc_x_1(known),:);
213 
+      dy = sqrt((Dy.^2)*odim_x_1);
214 
+      fy = exp(-dy/lambda);
215 
+      error = error + sum(((Mdist(known,i) - dy).^2).*fy);
216 
+    end
217 
+  end
218 
+  error = error/2;
219 
+
220 
+
221 
+function [] = dydxplot(P,Mdist)
222 
+
223 
+  [noc odim] = size(P);
224 
+  noc_x_1 = ones(noc,1);
225 
+  odim_x_1 = ones(odim,1);
226 
+  Pdist = zeros(noc,noc);
227 
+
228 
+  for i=1:noc,
229 
+    y = P(i,:);
230 
+    Dy = P - y(noc_x_1,:);
231 
+    Pdist(:,i) = sqrt((Dy.^2)*odim_x_1);
232 
+  end
233 
+
234 
+  Pdist = tril(Pdist,-1);
235 
+  inds = find(Pdist > 0);
236 
+  n = length(inds);
237 
+  plot(Pdist(inds),Mdist(inds),'.');
238 
+  xlabel('dy'), ylabel('dx')
239 
+
240 
+
241 
+function p = project_point(P,x,dx)
242 
+
243 
+  [noc odim] = size(P);
244 
+  noc_x_1 = ones(noc,1);
245 
+  odim_x_1 = ones(odim,1);
246 
+
247 
+  % initial projection
248 
+  [dummy,i] = min(dx);
249 
+  y = P(i,:)+rand(1,odim)*norm(P(i,:))/20;
250 
+
251 
+  % lambda
252 
+  lambda = norm(std(P));
253 
+
254 
+  % termination
255 
+  eps = 1e-3; i_max = noc*10;
256 
+
257 
+  i=1; p(i,:) = y;
258 
+  ready = 0;
259 
+  while ~ready,
260 
+
261 
+    % mutual distances
262 
+    Dy = P - y(noc_x_1,:);        % differences in output space
263 
+    dy = sqrt((Dy.^2)*odim_x_1);  % distances in output space
264 
+    f = exp(-dy/lambda);
265 
+
266 
+    fprintf(2,'iteration %d, error %g \r',i,sum(((dx - dy).^2).*f));
267 
+
268 
+    % all the other vectors push the projected one
269 
+    fy = f .* (dx ./ dy - 1) / sum(f);
270 
+
271 
+    % update
272 
+    step = - sum(fy(:,odim_x_1).*Dy);
273 
+    y = y + step;
274 
+
275 
+    i=i+1;
276 
+    p(i,:) = y;
277 
+    ready = (norm(step)/norm(y) < eps | i > i_max);
278 
+
279 
+  end
280 
+  fprintf(2,'\n');
281 
+
282 
+
0 283 
\ No newline at end of file
somtoolbox2/db_index.m
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,83 @@
1 
+function [t,r] = db_index(D, cl, C, p, q)
2 
+
3 
+% DB_INDEX Davies-Bouldin clustering evaluation index.
4 
+%
5 
+% [t,r] = db_index(D, cl, C, p, q)
6 
+%
7 
+%  Input and output arguments ([]'s are optional):
8 
+%    D     (matrix) data (n x dim)
9 
+%          (struct) map or data struct
10 
+%    cl    (vector) cluster numbers corresponding to data samples (n x 1)
11 
+%    [C]   (matrix) prototype vectors (c x dim) (default = cluster means)
12 
+%    [p]   (scalar) norm used in the computation (default == 2)
13 
+%    [q]   (scalar) moment used to calculate cluster dispersions (default = 2)
14 
+%
15 
+%    t     (scalar) Davies-Bouldin index for the clustering (=mean(r))
16 
+%    r     (vector) maximum DB index for each cluster (size c x 1)
17 
+%
18 
+% See also  KMEANS, KMEANS_CLUSTERS, SOM_GAPINDEX.
19 
+
20 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
21 
+%% input arguments
22 
+
23 
+if isstruct(D),
24 
+    switch D.type,
25 
+    case 'som_map', D = D.codebook;
26 
+    case 'som_data', D = D.data;
27 
+    end
28 
+end
29 
+
30 
+% cluster centroids
31 
+[l dim] = size(D);
32 
+u = unique(cl);
33 
+c = length(u);
34 
+if nargin <3,
35 
+  C = zeros(c,dim);
36 
+  for i=1:c,
37 
+      me = nanstats(D(find(cl==u(i)),:));
38 
+      C(i,:) = me';
39 
+  end
40 
+end
41 
+
42 
+u2i = zeros(max(u),1); u2i(u) = 1:c;
43 
+D = som_fillnans(D,C,u2i(cl)); % replace NaN's with cluster centroid values
44 
+
45 
+if nargin <4, p = 2; end % euclidian distance between cluster centers
46 
+if nargin <5, q = 2; end % dispersion = standard deviation
47 
+
48 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
49 
+%% action
50 
+
51 
+% dispersion in each cluster
52 
+for i = 1:c
53 
+  ind = find(cl==u(i)); % points in this cluster
54 
+  l   = length(ind);
55 
+  if l > 0
56 
+    S(i) = (mean(sqrt(sum((D(ind,:) - ones(l,1) * C(i,:)).^2,2)).^q))^(1/q);
57 
+  else
58 
+    S(i) = NaN;
59 
+  end
60 
+end
61 
+
62 
+% distances between clusters
63 
+%for i = 1:c
64 
+%  for j = i+1:c
65 
+%    M(i,j) = sum(abs(C(i,:) - C(j,:)).^p)^(1/p);
66 
+%  end
67 
+%end
68 
+M = som_mdist(C,p);
69 
+
70 
+% Davies-Bouldin index
71 
+R = NaN * zeros(c);
72 
+r = NaN * zeros(c,1);
73 
+for i = 1:c
74 
+  for j = i+1:c
75 
+    R(i,j) = (S(i) + S(j))/M(i,j);
76 
+  end
77 
+  r(i) = max(R(i,:));
78 
+end
79 
+
80 
+t = mean(r(isfinite(r)));
81 
+
82 
+return;
83 
+
somtoolbox2/hits.m
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,53 @@
1 
+function [hits,ninvalid] = hits(bmus, mmax, values)
2 
+
3 
+%HITS Calculate number of occurances of each value.
4 
+%
5 
+% hits = hits(bmus,[mmax],[values])
6 
+%
7 
+%   h = hits(bmus);
8 
+%   h = hits(bmus,length(sM.codebook));
9 
+%
10 
+%  Input and output arguments ([]'s are optional):
11 
+%   bmus     (vector) BMU indeces (or other similar)
12 
+%   [mmax]   (scalar) maximum index, default value max(bmus)
13 
+%            (struct) map or topology struct from where the maximum
14 
+%                     index is acquired
15 
+%   [values] (vector) values associated with the data (default = 1)
16 
+%
17 
+%   hits     (vector) the number of occurances of each index
18 
+%                     (or if values are given, their sum for each index)
19 
+%   ninvalid (scalar) number of invalid indeces (NaN, Inf or
20 
+%                     <=0 or > mmax)
21 
+%
22 
+% See also SOM_HITS, SOM_BMUS.
23 
+
24 
+% Copyright (c) 2002 by the SOM toolbox programming team.
25 
+% Contributed to SOM Toolbox by Juha Vesanto, April 24th, 2002
26 
+% http://www.cis.hut.fi/projects/somtoolbox/
27 
+
28 
+% Version 2.0beta juuso 240402
29 
+
30 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
31 
+
32 
+if nargin<2 | isempty(mmax),
33 
+  mmax = max(bmus);
34 
+elseif isstruct(mmax),
35 
+  switch mmax.type,
36 
+   case 'som_map',   mmax = prod(mmax.topol.msize);
37 
+   case 'som_topol', mmax = prod(mmax.msize);
38 
+   otherwise,
39 
+    error('Illegal struct for 2nd argument.')
40 
+  end
41 
+end
42 
+
43 
+if nargin<3, values = 1; end
44 
+
45 
+valid_bmus = find(isfinite(bmus) & bmus>0 & bmus<=mmax);
46 
+ninvalid = length(bmus)-length(valid_bmus);
47 
+
48 
+bmus = bmus(valid_bmus);
49 
+if length(values)>length(bmus), values = values(valid_bmus); end
50 
+hits = full(sum(sparse(bmus,1:length(bmus),values,mmax,length(bmus)),2));
51 
+
52 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
53 
+
somtoolbox2/kmeans_clusters.m
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,120 @@
1 
+function [centers,clusters,errors,ind] = kmeans_clusters(sD, n_max, c_max, verbose)
2 
+
3 
+% KMEANS_CLUSTERS Clustering with k-means with different values for k.
4 
+%
5 
+% [c, p, err, ind] = kmeans_clusters(sD, [n_max], [c_max], [verbose])
6 
+%
7 
+%   [c, p, err, ind] = kmeans_clusters(sD);
8 
+%
9 
+%  Input and output arguments ([]'s are optional):
10 
+%   D         (struct) map or data struct
11 
+%             (matrix) size dlen x dim, the data
12 
+%   [n_max]   (scalar) maximum number of clusters, default is sqrt(dlen)
13 
+%   [c_max]   (scalar) maximum number of k-means runs, default is 5
14 
+%   [verbose] (scalar) verbose level, 0 by default
15 
+%
16 
+%   c         (cell array) c{i} contains cluster centroids for k=i
17 
+%   p         (cell array) p{i} contains cluster indeces for k=i
18 
+%   err       (vector) squared sum of errors for each value of k
19 
+%   ind       (vector) Davies-Bouldin index value for each clustering
20 
+%
21 
+% Makes a k-means to the given data set with different values of
22 
+% k. The k-means is run multiple times for each k, and the best of
23 
+% these is selected based on sum of squared errors. Finally, the
24 
+% Davies-Bouldin index is calculated for each clustering.
25 
+%
26 
+% For example to cluster a SOM:
27 
+%    [c, p, err, ind] = kmeans_clusters(sM); % find clusterings
28 
+%    [dummy,i] = min(ind); % select the one with smallest index
29 
+%    som_show(sM,'color',{p{i},sprintf('%d clusters',i)}); % visualize
30 
+%    colormap(jet(i)), som_recolorbar % change colormap
31 
+%
32 
+% See also SOM_KMEANS.
33 
+
34 
+% References:
35 
+%   Jain, A.K., Dubes, R.C., "Algorithms for Clustering Data",
36 
+%   Prentice Hall, 1988, pp. 96-101.
37 
+%
38 
+%   Davies, D.L., Bouldin, D.W., "A Cluster Separation Measure",
39 
+%   IEEE Transactions on Pattern Analysis and Machine Intelligence,
40 
+%   vol. PAMI-1, no. 2, 1979, pp. 224-227.
41 
+%
42 
+%   Vesanto, J., Alhoniemi, E., "Clustering of the Self-Organizing
43 
+%   Map", IEEE Transactions on Neural Networks, 2000.
44 
+
45 
+% Contributed to SOM Toolbox vs2, February 2nd, 2000 by Esa Alhoniemi
46 
+% Copyright (c) by Esa Alhoniemi
47 
+% http://www.cis.hut.fi/projects/somtoolbox/
48 
+
49 
+% ecco 301299 juuso 020200 211201
50 
+
51 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
52 
+%% input arguments and initialization
53 
+
54 
+if isstruct(sD),
55 
+  if isfield(sD,'data'), D = sD.data;
56 
+  else D = sD.codebook;
57 
+  end
58 
+else D = sD;
59 
+end
60 
+[dlen dim] = size(D);
61 
+
62 
+if nargin < 2 | isempty(n_max) | isnan(n_max), n_max = ceil(sqrt(dlen)); end
63 
+if nargin < 3 | isempty(c_max) | isnan(c_max), c_max = 5; end
64 
+if nargin < 4 | isempty(verbose) | isnan(verbose), verbose = 0; end
65 
+
66 
+centers   = cell(n_max,1);
67 
+clusters  = cell(n_max,1);
68 
+ind       = zeros(1,n_max)+NaN;
69 
+errors    = zeros(1,n_max)+NaN;
70 
+
71 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
72 
+%% action
73 
+
74 
+% the case k=1 is trivial, but Davies-Boulding index cannot be evaluated
75 
+m = zeros(1,dim);
76 
+for i=1:dim, m(i)=mean(D(isfinite(D(:,i)),i)); end
77 
+centers{1} = m;
78 
+clusters{1} = ones(dlen,1);
79 
+[dummy qerr] = som_bmus(m,D);
80 
+errors(1) = sum(qerr.^2);
81 
+ind(1) = NaN;
82 
+
83 
+if verbose, fprintf(2,'Doing k-means for 2-%d clusters\n',n_max); end
84 
+
85 
+for i = 2:n_max, % number of clusters
86 
+
87 
+  % make k-means with k=i for c_max times and select the best based
88 
+  % on sum-of-squared errors (SSE)
89 
+  best = realmax;
90 
+  for j = 1:c_max     % run number j for cluster i
91 
+    if verbose,
92 
+      fprintf('%d/%d clusters, k-means run %d/%d\r', i, n_max,j, c_max);
93 
+    end
94 
+    [c, k, err] = som_kmeans('batch', D, i, 100, 0);
95 
+    if err < best, k_best = k'; c_best = c; best = err; end
96 
+    % ' added in k_best = k'; by kr 1.10.02
97 
+  end
98 
+  if verbose, fprintf(1, '\n');  end
99 
+
100 
+  % store the results
101 
+  centers{i}  = c_best;
102 
+  clusters{i} = k_best;
103 
+  errors(i)   = best;
104 
+%  ind(i)      = db_index(D, c_best, k_best, 2); wrong version in somtbx ??
105 
+  ind(i)      = db_index(D, k_best, c_best, 2); % modified by kr 1.10.02
106 
+
107 
+  % if verbose mode, plot the index & SSE
108 
+  if verbose
109 
+    subplot(2,1,1), plot(ind), grid
110 
+    title('Davies-Bouldin''s index')
111 
+    subplot(2,1,2), plot(errors), grid
112 
+    title('SSE')
113 
+    drawnow
114 
+  end
115 
+end
116 
+
117 
+return;
118 
+
119 
+
120 
+
somtoolbox2/knn.m
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,158 @@
1 
+function [C,P]=knn(d, Cp, K)
2 
+
3 
+%KNN K-Nearest Neighbor classifier using an arbitrary distance matrix
4 
+%
5 
+%  [C,P]=knn(d, Cp, [K])
6 
+%
7 
+%  Input and output arguments ([]'s are optional):
8 
+%   d     (matrix) of size NxP: This is a precalculated dissimilarity (distance matrix).
9 
+%           P is the number of prototype vectors and N is the number of data vectors
10 
+%           That is, d(i,j) is the distance between data item i and prototype j.
11 
+%   Cp    (vector) of size Px1 that contains integer class labels. Cp(j) is the class of
12 
+%            jth prototype.
13 
+%   [K]   (scalar) the maximum K in K-NN classifier, default is 1
14 
+%   C     (matrix) of size NxK: integers indicating the class
15 
+%           decision for data items according to the K-NN rule for each K.
16 
+%           C(i,K) is the classification for data item i using the K-NN rule
17 
+%   P     (matrix) of size NxkxK: the relative amount of prototypes of
18 
+%           each class among the K closest prototypes for each classifiee.
19 
+%           That is, P(i,j,K) is the relative amount of prototypes of class j
20 
+%           among K nearest prototypes for data item i.
21 
+%
22 
+% If there is a tie between representatives of two or more classes
23 
+% among the K closest neighbors to the classifiee, the class i selected randomly
24 
+% among these candidates.
25 
+%
26 
+% IMPORTANT  If K>1 this function uses 'sort' which is considerably slower than
27 
+%            'max' which is used for K=1. If K>1 the knn always calculates
28 
+%            results for all K-NN models from 1-NN up to K-NN.
29 
+%
30 
+% EXAMPLE 1
31 
+%
32 
+% sP;                           % a SOM Toolbox data struct containing labeled prototype vectors
33 
+% [Cp,label]=som_label2num(sP); % get integer class labels for prototype vectors
34 
+% sD;                           % a SOM Toolbox data struct containing vectors to be classified
35 
+% d=som_eucdist2(sD,sP);        % calculate euclidean distance matrix
36 
+% class=knn(d,Cp,10);           % classify using 1,2,...,10-rules
37 
+% class(:,5);                   % includes results for 5NN
38 
+% label(class(:,5))             % original class labels for 5NN
39 
+%
40 
+% EXAMPLE 2 (leave-one-out-crossvalidate KNN for selection of proper K)
41 
+%
42 
+% P;                          % a data matrix of prototype vectors (rows)
43 
+% Cp;                         % column vector of integer class labels for vectors in P
44 
+% d=som_eucdist2(P,P);        % calculate euclidean distance matrix PxP
45 
+% d(eye(size(d))==1)=NaN;     % set self-dissimilarity to NaN:
46 
+%                             % this drops the prototype itself away from its neighborhood
47 
+%                             % leave-one-out-crossvalidation (LOOCV)
48 
+% class=knn(d,Cp,size(P,1));  % classify using all possible K
49 
+%                             % calculate and plot LOOC-validated errors for all K
50 
+% failratep = ...
51 
+%  100*sum((class~=repmat(Cp,1,size(P,1))))./size(P,1); plot(1:size(P,1),failratep)
52 
+
53 
+% See also SOM_LABEL2NUM, SOM_EUCDIST2, PDIST.
54 
+%
55 
+% Contributed to SOM Toolbox 2.0, October 29th, 2000 by Johan Himberg
56 
+% Copyright (c) by Johan Himberg
57 
+% http://www.cis.hut.fi/projects/somtoolbox/
58 
+
59 
+% Version 2.0beta Johan 291000
60 
+
61 
+%% Init %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
62 
+
63 
+% Check K
64 
+if nargin<3 | isempty(K),
65 
+  K=1;
66 
+end
67 
+
68 
+if ~vis_valuetype(K,{'1x1'})
69 
+  error('Value for K must be a scalar');
70 
+end
71 
+
72 
+% Check that dist is a matrix
73 
+if ~vis_valuetype(d,{'nxm'}),
74 
+  error('Distance matrix not valid.')
75 
+end
76 
+
77 
+[N_data N_proto]=size(d);
78 
+
79 
+% Check class label vector: must be numerical and of integers
80 
+if ~vis_valuetype(Cp,{[N_proto 1]});
81 
+  error(['Class vector is invalid: has to be a N-of-data_rows x 1' ...
82 
+	 ' vector of integers']);
83 
+elseif sum(fix(Cp)-Cp)~=0
84 
+  error('Class labels in vector ''Cp'' must be integers.');
85 
+end
86 
+
87 
+if size(d,2) ~= length(Cp),
88 
+  error('Distance matrix and prototype class vector dimensions do not match.');
89 
+end
90 
+
91 
+% Check if the classes are given as labels (no class input arg.)
92 
+% if they are take them from prototype struct
93 
+
94 
+% Find all class labels
95 
+ClassIndex=unique(Cp);
96 
+N_class=length(ClassIndex); % number of different classes
97 
+
98 
+
99 
+%%%% Classification %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
100 
+
101 
+if K==1,   % sort distances only if K>1
102 
+
103 
+  % 1NN
104 
+  % Select the closest prototype
105 
+  [tmp,proto_index]=min(d,[],2);
106 
+  C=Cp(proto_index);
107 
+
108 
+else
109 
+
110 
+  % Sort the prototypes for each classifiee according to distance
111 
+  [tmp, proto_index]=sort(d');
112 
+
113 
+  %% Select up to K closest prototypes
114 
+  proto_index=proto_index(1:K,:);
115 
+  knn_class=Cp(proto_index);
116 
+  for i=1:N_class,
117 
+    classcounter(:,:,i)=cumsum(knn_class==ClassIndex(i));
118 
+  end
119 
+
120 
+  %% Vote between classes of K neighbors
121 
+  [winner,vote_index]=max(classcounter,[],3);
122 
+
123 
+  %%% Handle ties
124 
+
125 
+  % Set index to classes that got as much votes as winner
126 
+
127 
+  equal_to_winner=(repmat(winner,[1 1 N_class])==classcounter);
128 
+
129 
+  % set index to ties
130 
+  [tie_indexi,tie_indexj]=find(sum(equal_to_winner,3)>1); % drop the winner from counter
131 
+
132 
+  % Go through tie cases and reset vote_index randomly to one
133 
+  % of them
134 
+
135 
+  for i=1:length(tie_indexi),
136 
+    tie_class_index=find(squeeze(equal_to_winner(tie_indexi(i),tie_indexj(i),:)));
137 
+    fortuna=randperm(length(tie_class_index));
138 
+    vote_index(tie_indexi(i),tie_indexj(i))=tie_class_index(fortuna(1));
139 
+  end
140 
+
141 
+  C=ClassIndex(vote_index)';
142 
+end
143 
+
144 
+%% Build output %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
145 
+
146 
+% Relative amount of classes in K neighbors for each classifiee
147 
+
148 
+if K==1,
149 
+  P=zeros(N_data,N_class);
150 
+  if nargout>1,
151 
+    for i=1:N_data,
152 
+      P(i,ClassIndex==C(i))=1;
153 
+    end
154 
+  end
155 
+else
156 
+  P=shiftdim(classcounter,1)./repmat(shiftdim(1:K,-1), [N_data N_class 1]);
157 
+end
158 
+
somtoolbox2/knn_old.m
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,251 @@
1 
+function [Class,P]=knn_old(Data, Proto, proto_class, K)
2 
+
3 
+%KNN_OLD A K-nearest neighbor classifier using Euclidean distance
4 
+%
5 
+% [Class,P]=knn_old(Data, Proto, proto_class, K)
6 
+%
7 
+%  [sM_class,P]=knn_old(sM, sData, [], 3);
8 
+%  [sD_class,P]=knn_old(sD, sM, class);
9 
+%  [class,P]=knn_old(data, proto, class);
10 
+%  [class,P]=knn_old(sData, sM, class,5);
11 
+%
12 
+%  Input and output arguments ([]'s are optional):
13 
+%   Data   (matrix) size Nxd, vectors to be classified (=classifiees)
14 
+%          (struct) map or data struct: map codebook vectors or
15 
+%                   data vectors are considered as classifiees.
16 
+%   Proto  (matrix) size Mxd, prototype vector matrix (=prototypes)
17 
+%          (struct) map or data struct: map codebook vectors or
18 
+%                   data vectors are considered as prototypes.
19 
+%   [proto_class] (vector) size Nx1, integers 1,2,...,k indicating the
20 
+%                   classes of corresponding protoptypes, default: see the
21 
+%                   explanation below.
22 
+%   [K]    (scalar) the K in KNN classifier, default is 1
23 
+%
24 
+%   Class  (matrix) size Nx1, vector of 1,2, ..., k indicating the class
25 
+%                   desicion according to the KNN rule
26 
+%   P      (matrix) size Nxk, the relative amount of prototypes of
27 
+%                   each class among the K closest prototypes for
28 
+%                   each classifiee.
29 
+%
30 
+% If 'proto_class' is _not_ given, 'Proto' _must_ be a labeled SOM
31 
+% Toolbox struct. The label of the data vector or the first label of
32 
+% the map model vector is considered as class label for th prototype
33 
+% vector. In this case the output 'Class' is a copy of 'Data' (map or
34 
+% data struct) relabeled according to the classification.  If input
35 
+% argument 'proto_class' _is_ given, the output argument 'Class' is
36 
+% _always_ a vector of integers 1,2,...,k indiacating the class.
37 
+%
38 
+% If there is a tie between representatives of two or more classes
39 
+% among the K closest neighbors to the classifiee, the class is
40 
+% selected randomly among these candidates.
41 
+%
42 
+% IMPORTANT
43 
+%
44 
+% ** Even if prototype vectors are given in a map struct the mask _is not
45 
+%    taken into account_ when calculating Euclidean distance
46 
+% ** The function calculates the total distance matrix between all
47 
+%    classifiees and prototype vectors. This results to an MxN matrix;
48 
+%    if N is high it is recommended to divide the matrix 'Data'
49 
+%    (the classifiees) into smaller sets in order to avoid memory
50 
+%    overflow or swapping. Also, if K>1 this function uses 'sort' which is
51 
+%    considerably slower than 'max' which is used for K==1.
52 
+%
53 
+% See also KNN, SOM_LABEL, SOM_AUTOLABEL
54 
+
55 
+% Contributed to SOM Toolbox 2.0, February 11th, 2000 by Johan Himberg
56 
+% Copyright (c) by Johan Himberg
57 
+% http://www.cis.hut.fi/projects/somtoolbox/
58 
+
59 
+% Version 2.0beta Johan 040200
60 
+
61 
+%% Init %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
62 
+% This must exist later
63 
+classnames='';
64 
+
65 
+% Check K
66 
+if nargin<4 | isempty(K),
67 
+  K=1;
68 
+end
69 
+
70 
+if ~vis_valuetype(K,{'1x1'})
71 
+  error('Value for K must be a scalar.');
72 
+end
73 
+
74 
+% Take data from data or map struct
75 
+
76 
+if isstruct(Data);
77 
+  if isfield(Data,'type') & ischar(Data.type),
78 
+    ;
79 
+  else
80 
+    error('Invalid map/data struct?');
81 
+  end
82 
+  switch Data.type
83 
+   case 'som_map'
84 
+    data=Data.codebook;
85 
+   case 'som_data'
86 
+    data=Data.data;
87 
+  end
88 
+else
89 
+  % is already a matrix
90 
+  data=Data;
91 
+end
92 
+
93 
+% Take prototype vectors from prototype struct
94 
+
95 
+if isstruct(Proto),
96 
+
97 
+  if isfield(Proto,'type') & ischar(Proto.type),
98 
+    ;
99 
+  else
100 
+    error('Invalid map/data struct?');
101 
+  end
102 
+  switch Proto.type
103 
+   case 'som_map'
104 
+    proto=Proto.codebook;
105 
+   case 'som_data'
106 
+    proto=Proto.data;
107 
+  end
108 
+else
109 
+  % is already a matrix
110 
+  proto=Proto;
111 
+end
112 
+
113 
+% Check that inputs are matrices
114 
+if ~vis_valuetype(proto,{'nxm'}) | ~vis_valuetype(data,{'nxm'}),
115 
+  error('Prototype or data input not valid.')
116 
+end
117 
+
118 
+% Record data&proto sizes and check their dims
119 
+[N_data dim_data]=size(data);
120 
+[N_proto dim_proto]=size(proto);
121 
+if dim_proto ~= dim_data,
122 
+  error('Data and prototype vector dimension does not match.');
123 
+end
124 
+
125 
+% Check if the classes are given as labels (no class input arg.)
126 
+% if they are take them from prototype struct
127 
+
128 
+if nargin<3 | isempty(proto_class)
129 
+  if ~isstruct(Proto)
130 
+    error(['If prototypes are not in labeled map or data struct' ...
131 
+	   'class must be given.']);
132 
+    % transform to interger (numerical) class labels
133 
+  else
134 
+    [proto_class,classnames]=class2num(Proto.labels);
135 
+  end
136 
+end
137 
+
138 
+% Check class label vector: must be numerical and of integers
139 
+if ~vis_valuetype(proto_class,{[N_proto 1]});
140 
+  error(['Class vector is invalid: has to be a N-of-data_rows x 1' ...
141 
+	 ' vector of integers']);
142 
+elseif sum(fix(proto_class)-proto_class)~=0
143 
+  error('Class labels in vector ''Class'' must be integers.');
144 
+end
145 
+
146 
+% Find all class labels
147 
+ClassIndex=unique(proto_class);
148 
+N_class=length(ClassIndex); % number of different classes
149 
+
150 
+% Calculate euclidean distances between classifiees and prototypes
151 
+d=distance(proto,data);
152 
+
153 
+%%%% Classification %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
154 
+
155 
+if K==1,   % sort distances only if K>1
156 
+
157 
+  % 1NN
158 
+  % Select the closest prototype
159 
+  [tmp,proto_index]=min(d);
160 
+  class=proto_class(proto_index);
161 
+
162 
+else
163 
+
164 
+  % Sort the prototypes for each classifiee according to distance
165 
+  [tmp,proto_index]=sort(d);
166 
+
167 
+  %% Select K closest prototypes
168 
+  proto_index=proto_index(1:K,:);
169 
+  knn_class=proto_class(proto_index);
170 
+  for i=1:N_class,
171 
+    classcounter(i,:)=sum(knn_class==ClassIndex(i));
172 
+  end
173 
+
174 
+  %% Vote between classes of K neighbors
175 
+  [winner,vote_index]=max(classcounter);
176 
+
177 
+  %% Handle ties
178 
+
179 
+  % set index to clases that got as amuch votes as winner
180 
+
181 
+  equal_to_winner=(repmat(winner,N_class,1)==classcounter);
182 
+
183 
+  % set index to ties
184 
+  tie_index=find(sum(equal_to_winner)>1); % drop the winner from counter
185 
+
186 
+  % Go through equal classes and reset vote_index randomly to one
187 
+  % of them
188 
+
189 
+  for i=1:length(tie_index),
190 
+    tie_class_index=find(equal_to_winner(:,tie_index(i)));
191 
+    fortuna=randperm(length(tie_class_index));
192 
+    vote_index(tie_index(i))=tie_class_index(fortuna(1));
193 
+  end
194 
+
195 
+  class=ClassIndex(vote_index);
196 
+end
197 
+
198 
+%% Build output %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
199 
+
200 
+% Relative amount of classes in K neighbors for each classifiee
201 
+
202 
+if K==1,
203 
+  P=zeros(N_data,N_class);
204 
+  if nargout>1,
205 
+    for i=1:N_data,
206 
+      P(i,ClassIndex==class(i))=1;
207 
+    end
208 
+  end
209 
+else
210 
+  P=classcounter'./K;
211 
+end
212 
+
213 
+% xMake class names to struct if they exist
214 
+if ~isempty(classnames),
215 
+  Class=Data;
216 
+  for i=1:N_data,
217 
+    Class.labels{i,1}=classnames{class(i)};
218 
+  end
219 
+else
220 
+  Class=class;
221 
+end
222 
+
223 
+
224 
+%%% Subfunctions %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
225 
+
226 
+function [nos,names] = class2num(class)
227 
+
228 
+% Change string labels in map/data struct to integer numbers
229 
+
230 
+names = {};
231 
+nos = zeros(length(class),1);
232 
+for i=1:length(class)
233 
+  if ~isempty(class{i}) & ~any(strcmp(class{i},names))
234 
+    names=cat(1,names,class(i));
235 
+  end
236 
+end
237 
+
238 
+tmp_nos = (1:length(names))';
239 
+for i=1:length(class)
240 
+  if ~isempty(class{i})
241 
+    nos(i,1) = find(strcmp(class{i},names));
242 
+  end
243 
+end
244 
+
245 
+function d=distance(X,Y);
246 
+
247 
+% Euclidean distance matrix between row vectors in X and Y
248 
+
249 
+U=~isnan(Y); Y(~U)=0;
250 
+V=~isnan(X); X(~V)=0;
251 
+d=X.^2*U'+V*Y'.^2-2*X*Y';
somtoolbox2/lvq1.m
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,180 @@
1 
+function codebook=lvq1(codebook, data, rlen, alpha);
2 
+
3 
+%LVQ1 Trains a codebook with the LVQ1 -algorithm.
4 
+%
5 
+%  sM = lvq1(sM, D, rlen, alpha)
6 
+%
7 
+%   sM = lvq1(sM,sD,30*length(sM.codebook),0.08);
8 
+%
9 
+%  Input and output arguments:
10 
+%   sM    (struct) map struct, the class information must be
11 
+%                  present on the first column of .labels field
12 
+%   D     (struct) data struct, the class information must
13 
+%                  be present on the first column of .labels field
14 
+%   rlen  (scalar) running length
15 
+%   alpha (scalar) learning parameter
16 
+%
17 
+%   sM    (struct) map struct, the trained codebook
18 
+%
19 
+% NOTE: does not take mask into account.
20 
+%
21 
+% For more help, try 'type lvq1', or check out online documentation.
22 
+% See also LVQ3, SOM_SUPERVISED, SOM_SEQTRAIN.
23 
+
24 
+%%%%%%%%%%%%% DETAILED DESCRIPTION %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
25 
+%
26 
+% lvq1
27 
+%
28 
+% PURPOSE
29 
+%
30 
+% Trains codebook with the LVQ1 -algorithm (described below).
31 
+%
32 
+% SYNTAX
33 
+%
34 
+%  sM = lvq1(sM, D, rlen, alpha)
35 
+%
36 
+% DESCRIPTION
37 
+%
38 
+% Trains codebook with the LVQ1 -algorithm. Codebook contains a number
39 
+% of vectors (mi, i=1,2,...,n) and so does data (vectors xj,
40 
+% j=1,2,...,k).  Both vector sets are classified: vectors may have a
41 
+% class (classes are set to the first column of data or map -structs'
42 
+% .labels -field). For each xj there is defined the nearest codebook
43 
+% -vector index c by searching the minimum of the euclidean distances
44 
+% between the current xj and codebook -vectors:
45 
+%
46 
+%    c = min{ ||xj - mi|| },  i=[1,..,n], for fixed xj
47 
+%         i
48 
+% If xj and mc belong to the same class, mc is updated as follows:
49 
+%    mc(t+1) = mc(t) + alpha * (xj(t) - mc(t))
50 
+% If xj and mc belong to different classes, mc is updated as follows:
51 
+%    mc(t+1) = mc(t) - alpha * (xj(t) - mc(t))
52 
+% Otherwise updating is not performed.
53 
+%
54 
+% Argument 'rlen' tells how many times training sequence is performed.
55 
+% LVQ1 -algorithm may be stopped after a number of steps, that is
56 
+% 30-50 times the number of codebook vectors.
57 
+%
58 
+% Argument 'alpha' is the learning rate, recommended to be smaller
59 
+% than 0.1.
60 
+%
61 
+% NOTE: does not take mask into account.
62 
+%
63 
+% REFERENCES
64 
+%
65 
+% Kohonen, T., "Self-Organizing Map", 2nd ed., Springer-Verlag,
66 
+%    Berlin, 1995, pp. 176-179.
67 
+%
68 
+% See also LVQ_PAK from http://www.cis.hut.fi/research/som_lvq_pak.shtml
69 
+%
70 
+% REQUIRED INPUT ARGUMENTS
71 
+%
72 
+%  sM                The data to be trained.
73 
+%          (struct)  A map struct.
74 
+%
75 
+%  D                 The data to use in training.
76 
+%          (struct)  A data struct.
77 
+%
78 
+%  rlen    (integer) Running length of LVQ1 -algorithm.
79 
+%
80 
+%  alpha   (float)   Learning rate used in training.
81 
+%
82 
+% OUTPUT ARGUMENTS
83 
+%
84 
+%  codebook          Trained data.
85 
+%          (struct)  A map struct.
86 
+%
87 
+% EXAMPLE
88 
+%
89 
+%   lab = unique(sD.labels(:,1));         % different classes
90 
+%   mu = length(lab)*5;                   % 5 prototypes for each
91 
+%   sM = som_randinit(sD,'msize',[mu 1]); % initial prototypes
92 
+%   sM.labels = [lab;lab;lab;lab;lab];    % their classes
93 
+%   sM = lvq1(sM,sD,50*mu,0.05);          % use LVQ1 to adjust
94 
+%                                         % the prototypes
95 
+%   sM = lvq3(sM,sD,50*mu,0.05,0.2,0.3);  % then use LVQ3
96 
+%
97 
+% SEE ALSO
98 
+%
99 
+%  lvq3             Use LVQ3 algorithm for training.
100 
+%  som_supervised   Train SOM using supervised training.
101 
+%  som_seqtrain     Train SOM with sequential algorithm.
102 
+
103 
+% Contributed to SOM Toolbox vs2, February 2nd, 2000 by Juha Parhankangas
104 
+% Copyright (c) Juha Parhankangas
105 
+% http://www.cis.hut.fi/projects/somtoolbox/
106 
+
107 
+% Juha Parhankangas 310100 juuso 020200
108 
+
109 
+cod = codebook.codebook;
110 
+c_class = class2num(codebook.labels(:,1));
111 
+
112 
+dat = data.data;
113 
+d_class = class2num(data.labels(:,1));
114 
+
115 
+x=size(dat,1);
116 
+y=size(cod,2);
117 
+
118 
+ONES=ones(size(cod,1),1);
119 
+
120 
+for t=1:rlen
121 
+
122 
+  fprintf(1,'\rTraining round: %d',t);
123 
+  tmp=NaN*ones(x,y);
124 
+
125 
+  for j=1:x
126 
+    no_NaN=find(~isnan(dat(j,:)));
127 
+    di = sqrt(sum([cod(:,no_NaN)  - ONES*dat(j,no_NaN)].^2,2));
128 
+
129 
+    [foo,ind] = min(di);
130 
+
131 
+    if d_class(j) & d_class(j) == c_class(ind) % 0 is for unclassified vectors
132 
+      tmp(ind,:) = cod(ind,:) + alpha * (dat(j,:) - cod(ind,:));
133 
+    elseif d_class(j)
134 
+      tmp(ind,:) = cod(ind,:) - alpha*(dat(j,:) - cod(ind,:));
135 
+    end
136 
+  end
137 
+
138 
+  inds = find(~isnan(sum(tmp,2)));
139 
+  cod(inds,:) = tmp(inds,:);
140 
+end
141 
+
142 
+codebook.codebook = cod;
143 
+
144 
+sTrain = som_set('som_train','algorithm','lvq1',...
145 
+		 'data_name',data.name,...
146 
+		 'neigh','',...
147 
+		 'mask',ones(y,1),...
148 
+		 'radius_ini',NaN,...
149 
+		 'radius_fin',NaN,...
150 
+		 'alpha_ini',alpha,...
151 
+		 'alpha_type','constant',...
152 
+		 'trainlen',rlen,...
153 
+		 'time',datestr(now,0));
154 
+codebook.trainhist(end+1) = sTrain;
155 
+
156 
+return;
157 
+
158 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
159 
+
160 
+function nos = class2num(class)
161 
+
162 
+names = {};
163 
+nos = zeros(length(class),1);
164 
+
165 
+for i=1:length(class)
166 
+  if ~isempty(class{i}) & ~any(strcmp(class{i},names))
167 
+    names=cat(1,names,class(i));
168 
+  end
169 
+end
170 
+
171 
+tmp_nos = (1:length(names))';
172 
+
173 
+for i=1:length(class)
174 
+  if ~isempty(class{i})
175 
+    nos(i,1) = find(strcmp(class{i},names));
176 
+  end
177 
+end
178 
+
179 
+
180 
+
somtoolbox2/lvq3.m
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,215 @@
1 
+function codebook = lvq3(codebook,data,rlen,alpha,win,epsilon)
2 
+
3 
+%LVQ3 trains codebook with LVQ3 -algorithm
4 
+%
5 
+% sM = lvq3(sM,D,rlen,alpha,win,epsilon)
6 
+%
7 
+%   sM = lvq3(sM,sD,50*length(sM.codebook),0.05,0.2,0.3);
8 
+%
9 
+%  Input and output arguments:
10 
+%   sM      (struct) map struct, the class information must be
11 
+%                    present on the first column of .labels field
12 
+%   D       (struct) data struct, the class information must
13 
+%                    be present on the first column of .labels field
14 
+%   rlen    (scalar) running length
15 
+%   alpha   (scalar) learning parameter, e.g. 0.05
16 
+%   win     (scalar) window width parameter, e.g. 0.25
17 
+%   epsilon (scalar) relative learning parameter, e.g. 0.3
18 
+%
19 
+%   sM      (struct) map struct, the trained codebook
20 
+%
21 
+% NOTE: does not take mask into account.
22 
+%
23 
+% For more help, try 'type lvq3', or check out online documentation.
24 
+% See also LVQ1, SOM_SUPERVISED, SOM_SEQTRAIN.
25 
+
26 
+%%%%%%%%%%%%% DETAILED DESCRIPTION %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
27 
+%
28 
+% lvq3
29 
+%
30 
+% PURPOSE
31 
+%
32 
+% Trains codebook with the LVQ3 -algorithm (described below).
33 
+%
34 
+% SYNTAX
35 
+%
36 
+% sM = lvq3(sM, data, rlen, alpha, win, epsilon)
37 
+%
38 
+% DESCRIPTION
39 
+%
40 
+% Trains codebook with the LVQ3 -algorithm. Codebook contains a number
41 
+% of vectors (mi, i=1,2,...,n) and so does data (vectors xj, j=1,2,...k).
42 
+% Both vector sets are classified: vectors may have a class (classes are
43 
+% set to data- or map -structure's 'labels' -field. For each xj the two
44 
+% closest codebookvectors mc1 and mc2 are searched (euclidean distances
45 
+% d1 and d2). xj must fall into the zone of window. That happens if:
46 
+%
47 
+%    min(d1/d2, d2/d1) > s, where s = (1-win) / (1+win).
48 
+%
49 
+% If xj belongs to the same class of one of the mc1 and mc1, codebook
50 
+% is updated as follows (let mc1 belong to the same class as xj):
51 
+%    mc1(t+1) = mc1(t) + alpha * (xj(t) - mc1(t))
52 
+%    mc2(t+1) = mc2(t) - alpha * (xj(t) - mc2(t))
53 
+% If both mc1 and mc2 belong to the same class as xj, codebook is
54 
+% updated as follows:
55 
+%    mc1(t+1) = mc1(t) + epsilon * alpha * (xj(t) - mc1(t))
56 
+%    mc2(t+1) = mc2(t) + epsilon * alpha * (xj(t) - mc2(t))
57 
+% Otherwise updating is not performed.
58 
+%
59 
+% Argument 'rlen' tells how many times training -sequence is performed.
60 
+%
61 
+% Argument 'alpha' is recommended to be smaller than 0.1 and argument
62 
+% 'epsilon' should be between 0.1 and 0.5.
63 
+%
64 
+% NOTE: does not take mask into account.
65 
+%
66 
+% REFERENCES
67 
+%
68 
+% Kohonen, T., "Self-Organizing Map", 2nd ed., Springer-Verlag,
69 
+%    Berlin, 1995, pp. 181-182.
70 
+%
71 
+% See also LVQ_PAK from http://www.cis.hut.fi/research/som_lvq_pak.shtml
72 
+%
73 
+% REQUIRED INPUT ARGUMENTS
74 
+%
75 
+%  sM                The data to be trained.
76 
+%          (struct)  A map struct.
77 
+%
78 
+%  data              The data to use in training.
79 
+%          (struct)  A data struct.
80 
+%
81 
+%  rlen    (integer) Running length of LVQ3 -algorithm.
82 
+%
83 
+%  alpha   (float)   Learning rate used in training, e.g. 0.05
84 
+%
85 
+%  win     (float)   Window length, e.g. 0.25
86 
+%
87 
+%  epsilon (float)   Relative learning parameter, e.g. 0.3
88 
+%
89 
+% OUTPUT ARGUMENTS
90 
+%
91 
+%  sM          Trained data.
92 
+%          (struct)  A map struct.
93 
+%
94 
+% EXAMPLE
95 
+%
96 
+%   lab = unique(sD.labels(:,1));         % different classes
97 
+%   mu = length(lab)*5;                   % 5 prototypes for each
98 
+%   sM = som_randinit(sD,'msize',[mu 1]); % initial prototypes
99 
+%   sM.labels = [lab;lab;lab;lab;lab];    % their classes
100 
+%   sM = lvq1(sM,sD,50*mu,0.05);          % use LVQ1 to adjust
101 
+%                                         % the prototypes
102 
+%   sM = lvq3(sM,sD,50*mu,0.05,0.2,0.3);  % then use LVQ3
103 
+%
104 
+% SEE ALSO
105 
+%
106 
+%  lvq1             Use LVQ1 algorithm for training.
107 
+%  som_supervised   Train SOM using supervised training.
108 
+%  som_seqtrain     Train SOM with sequential algorithm.
109 
+
110 
+% Contributed to SOM Toolbox vs2, February 2nd, 2000 by Juha Parhankangas
111 
+% Copyright (c) by Juha Parhankangas
112 
+% http://www.cis.hut.fi/projects/somtoolbox/
113 
+
114 
+% Juha Parhankangas 310100 juuso 020200
115 
+
116 
+NOTFOUND = 1;
117 
+
118 
+cod = codebook.codebook;
119 
+dat = data.data;
120 
+
121 
+c_class = codebook.labels(:,1);
122 
+d_class = data.labels(:,1);
123 
+
124 
+s = (1-win)/(1+win);
125 
+
126 
+x = size(dat,1);
127 
+y = size(cod,2);
128 
+
129 
+c_class=class2num(c_class);
130 
+d_class=class2num(d_class);
131 
+
132 
+ONES=ones(size(cod,1),1);
133 
+
134 
+for t=1:rlen
135 
+  fprintf('\rTraining round: %d/%d',t,rlen);
136 
+  tmp = NaN*ones(x,y);
137 
+
138 
+  for j=1:x
139 
+    flag = 0;
140 
+    mj = 0;
141 
+    mi = 0;
142 
+    no_NaN=find(~isnan(dat(j,:)));
143 
+    di=sqrt(sum([cod(:,no_NaN) - ONES*dat(j,no_NaN)].^2,2));
144 
+    [foo, ind1] = min(di);
145 
+    di(ind1)=Inf;
146 
+    [foo,ind2] =  min(di);
147 
+
148 
+    %ind2=ind2+1;
149 
+
150 
+    if d_class(j) & d_class(j)==c_class(ind1)
151 
+      mj = ind1;
152 
+      mi = ind2;
153 
+      if d_class(j)==c_class(ind2)
154 
+        flag = 1;
155 
+      end
156 
+    elseif d_class(j) & d_class(j)==c_class(ind2)
157 
+      mj = ind2;
158 
+      mi = ind1;
159 
+      if d_class(j)==c_class(ind1)
160 
+        flag = 1;
161 
+      end
162 
+    end
163 
+
164 
+    if mj & mi
165 
+      if flag
166 
+        tmp([mj mi],:) = cod([mj mi],:) + epsilon*alpha*...
167 
+                       (dat([j j],:) - cod([mj mi],:));
168 
+      else
169 
+        tmp(mj,:) = cod(mj,:) + alpha * (dat(j,:)-cod(mj,:));
170 
+        tmp(mi,:) = cod(mi,:) - alpha * (dat(j,:)-cod(mj,:));
171 
+      end
172 
+    end
173 
+  end
174 
+  inds = find(~isnan(sum(tmp,2)));
175 
+  cod(inds,:) = tmp(inds,:);
176 
+end
177 
+fprintf(1,'\n');
178 
+
179 
+sTrain = som_set('som_train','algorithm','lvq3',...
180 
+		 'data_name',data.name,...
181 
+		 'neigh','',...
182 
+		 'mask',ones(y,1),...
183 
+		 'radius_ini',NaN,...
184 
+		 'radius_fin',NaN,...
185 
+		 'alpha_ini',alpha,...
186 
+		 'alpha_type','constant',...
187 
+		 'trainlen',rlen,...
188 
+		 'time',datestr(now,0));
189 
+codebook.trainhist(end+1) = sTrain;
190 
+
191 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
192 
+
193 
+function nos = class2num(class)
194 
+
195 
+names = {};
196 
+nos = zeros(length(class),1);
197 
+
198 
+for i=1:length(class)
199 
+  if ~isempty(class{i}) & ~any(strcmp(class{i},names))
200 
+    names=cat(1,names,class(i));
201 
+  end
202 
+end
203 
+
204 
+tmp_nos = (1:length(names))';
205 
+
206 
+for i=1:length(class)
207 
+  if ~isempty(class{i})
208 
+    nos(i,1) = find(strcmp(class{i},names));
209 
+  end
210 
+end
211 
+
212 
+
213 
+
214 
+
215 
+
somtoolbox2/nanstats.m
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,65 @@
1 
+function [me, st, md, no] = nanstats(D)
2 
+
3 
+%NANSTATS Statistical operations that ignore NaNs and Infs.
4 
+%
5 
+% [mean, std, median, nans] = nanstats(D)
6 
+%
7 
+%  Input and output arguments:
8 
+%   D   (struct) data or map struct
9 
+%       (matrix) size dlen x dim
10 
+%
11 
+%   me  (double) columnwise mean
12 
+%   st  (double) columnwise standard deviation
13 
+%   md  (double) columnwise median
14 
+%   no  (vector) columnwise number of samples (finite, not-NaN)
15 
+
16 
+% Contributed to SOM Toolbox vs2, February 2nd, 2000 by Juha Vesanto
17 
+% http://www.cis.hut.fi/projects/somtoolbox/
18 
+
19 
+% Version 2.0beta juuso 300798 200900
20 
+
21 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
22 
+%% check arguments
23 
+
24 
+(nargchk(1, 1, nargin));  % check no. of input args is correct
25 
+
26 
+if isstruct(D),
27 
+  if strcmp(D.type,'som_map'), D = D.codebook;
28 
+  else D = D.data;
29 
+  end
30 
+end
31 
+[dlen dim] = size(D);
32 
+me = zeros(dim,1)+NaN;
33 
+md = me;
34 
+st = me;
35 
+no = me;
36 
+
37 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
38 
+%% computation
39 
+
40 
+for i = 1:dim,
41 
+  ind = find(isfinite(D(:, i))); % indices of non-NaN/Inf elements
42 
+  n   = length(ind);             % no of non-NaN/Inf elements
43 
+
44 
+  me(i) = sum(D(ind, i)); % compute average
45 
+  if n == 0, me(i) = NaN; else me(i) = me(i) / n; end
46 
+
47 
+  if nargout>1,
48 
+    md(i) = median(D(ind, i)); % compute median
49 
+
50 
+    if nargout>2,
51 
+      st(i) = sum((me(i) - D(ind, i)).^2); % compute standard deviation
52 
+      if n == 0,     st(i) = NaN;
53 
+      elseif n == 1, st(i) = 0;
54 
+      else st(i) = sqrt(st(i) / (n - 1));
55 
+      end
56 
+
57 
+      if nargout>3,
58 
+	no(i) = n; % number of samples (finite, not-NaN)
59 
+      end
60 
+    end
61 
+  end
62 
+end
63 
+
64 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
65 
+
somtoolbox2/neural_gas.m
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,89 @@
1 
+function [Neurons] = neural_gas(D,n,epochs,alpha0,lambda0)
2 
+
3 
+%NEURAL_GAS Quantizes the data space using the neural gas algorithm.
4 
+%
5 
+% Neurons = neural_gas(D, n, epochs, [alpha0], [lambda0])
6 
+%
7 
+%   C = neural_gas(D,50,10);
8 
+%   sM = som_map_struct(sD);
9 
+%   sM.codebook = neural_gas(sD,size(sM.codebook,1),10);
10 
+%
11 
+%  Input and output arguments ([]'s are optional):
12 
+%   D          (matrix) the data matrix, size dlen x dim
13 
+%              (struct) a data struct
14 
+%   n          (scalar) the number of neurons
15 
+%   epochs     (scalar) the number of training epochs (the number of
16 
+%                       training steps is dlen*epochs)
17 
+%   [alpha0]   (scalar) initial step size, 0.5 by default
18 
+%   [lambda0]  (scalar) initial decay constant, n/2 by default
19 
+%
20 
+%   Neurons    (matrix) the neuron matrix, size n x dim
21 
+%
22 
+% See also SOM_MAKE, KMEANS.
23 
+
24 
+% References:
25 
+%  T.M.Martinetz, S.G.Berkovich, and K.J.Schulten. "Neural-gas" network
26 
+%  for vector quantization and its application to time-series prediction.
27 
+%  IEEE Transactions on Neural Networks, 4(4):558-569, 1993.
28 
+
29 
+% Contributed to SOM Toolbox vs2, February 2nd, 2000 by Juha Vesanto
30 
+% Copyright (c) by Juha Vesanto
31 
+% http://www.cis.hut.fi/projects/somtoolbox/
32 
+
33 
+% juuso 101297 020200
34 
+
35 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
36 
+%% Check arguments and initialize
37 
+
38 
+error(nargchk(3, 5, nargin));  % check the number of input arguments
39 
+
40 
+if isstruct(D), D = D.data; end
41 
+[dlen,dim] = size(D);
42 
+Neurons = (rand(n,dim)-0.5)*10e-5; % small initial values
43 
+train_len = epochs*dlen;
44 
+
45 
+if nargin<4 | isempty(alpha0) | isnan(alpha0), alpha0 = 0.5; end
46 
+if nargin<5 | isempty(lambda0) | isnan(lambda0), lambda0 = n/2; end
47 
+
48 
+% random sample order
49 
+rand('state',sum(100*clock));
50 
+sample_inds = ceil(dlen*rand(train_len,1));
51 
+
52 
+% lambda
53 
+lambda = lambda0 * (0.01/lambda0).^([0:(train_len-1)]/train_len);
54 
+
55 
+% alpha
56 
+alpha = alpha0 * (0.005/alpha0).^([0:(train_len-1)]/train_len);
57 
+
58 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
59 
+%% Action
60 
+
61 
+for i=1:train_len,
62 
+
63 
+  % sample vector
64 
+  x = D(sample_inds(i),:); % sample vector
65 
+  known = ~isnan(x);       % its known components
66 
+  X = x(ones(n,1),known);  % we'll need this
67 
+
68 
+  % neighborhood ranking
69 
+  Dx = Neurons(:,known) - X;  % difference between vector and all map units
70 
+  [qerrs, inds] = sort((Dx.^2)*known'); % 1-BMU, 2-BMU, etc.
71 
+  ranking(inds) = [0:(n-1)];
72 
+  h = exp(-ranking/lambda(i));
73 
+  H = h(ones(length(known),1),:)';
74 
+
75 
+  % update
76 
+  Neurons = Neurons + alpha(i)*H.*(x(ones(n,1),known) - Neurons(:,known));
77 
+
78 
+  % track
79 
+  fprintf(1,'%d / %d \r',i,train_len);
80 
+  if 0 & mod(i,50) == 0,
81 
+    hold off, plot3(D(:,1),D(:,2),D(:,3),'bo')
82 
+    hold on, plot3(Neurons(:,1),Neurons(:,2),Neurons(:,3),'r+')
83 
+    drawnow
84 
+  end
85 
+end
86 
+
87 
+fprintf(1,'\n');
88 
+
89 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0 90 
\ No newline at end of file
somtoolbox2/pcaproj.m
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,80 @@
1 
+function [P,V,me,l] = pcaproj(D,arg1,arg2)
2 
+
3 
+%PCAPROJ Projects data vectors using Principal Component Analysis.
4 
+%
5 
+% [P,V,me,l] = pcaproj(D, odim)
6 
+% P =          pcaproj(D, V, me)
7 
+%
8 
+%  Input and output arguments ([]'s are optional)
9 
+%   D      (matrix) size dlen x dim, the data matrix
10 
+%          (struct) data or map struct
11 
+%   odim   (scalar) how many principal vectors are used
12 
+%
13 
+%   P      (matrix) size dlen x odim, the projections
14 
+%   V      (matrix) size dim x odim, principal eigenvectors (unit length)
15 
+%   me     (vector) size 1 x dim, center point of D
16 
+%   l      (vector) size 1 x odim, the corresponding eigenvalues,
17 
+%                   relative to total sum of eigenvalues
18 
+%
19 
+% See also SAMMON, CCA.
20 
+
21 
+% Contributed to SOM Toolbox 2.0, February 2nd, 2000 by Juha Vesanto
22 
+% Copyright (c) by Juha Vesanto
23 
+% http://www.cis.hut.fi/projects/somtoolbox/
24 
+
25 
+% juuso 191297 070200
26 
+
27 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
28 
+
29 
+error(nargchk(2, 3, nargin)); % check the number of input arguments
30 
+
31 
+% the data
32 
+if isstruct(D),
33 
+  if strcmp(D.type,'som_map'), D=D.codebook; else D=D.data; end
34 
+end
35 
+[dlen dim] = size(D);
36 
+
37 
+if nargin==2,
38 
+
39 
+  odim = arg1;
40 
+
41 
+  % autocorrelation matrix
42 
+  A = zeros(dim);
43 
+  me = zeros(1,dim);
44 
+  for i=1:dim,
45 
+    me(i) = mean(D(isfinite(D(:,i)),i));
46 
+    D(:,i) = D(:,i) - me(i);
47 
+  end
48 
+  for i=1:dim,
49 
+    for j=i:dim,
50 
+      c = D(:,i).*D(:,j); c = c(isfinite(c));
51 
+      A(i,j) = sum(c)/length(c); A(j,i) = A(i,j);
52 
+    end
53 
+  end
54 
+
55 
+  % eigenvectors, sort them according to eigenvalues, and normalize
56 
+  [V,S]   = eig(A);
57 
+  eigval  = diag(S);
58 
+  [y,ind] = sort(abs(eigval));
59 
+  eigval  = eigval(flipud(ind));
60 
+  V       = V(:,flipud(ind));
61 
+  for i=1:odim, V(:,i) = (V(:,i) / norm(V(:,i))); end
62 
+
63 
+  % take only odim first eigenvectors
64 
+  V = V(:,1:odim);
65 
+  l = abs(eigval)/sum(abs(eigval));
66 
+  l = l(1:odim);
67 
+
68 
+else % nargin==3,
69 
+
70 
+  V = arg1;
71 
+  me = arg2;
72 
+  odim = size(V,2);
73 
+  D = D-me(ones(dlen,1),:);
74 
+
75 
+end
76 
+
77 
+% project the data using odim first eigenvectors
78 
+P = D*V;
79 
+
80 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
somtoolbox2/preprocess.m
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,6642 @@
1 
+function preprocess(sData,arg2)
2 
+
3 
+%PREPROCESS  A GUI for data preprocessing.
4 
+%
5 
+%  preprocess(sData)
6 
+%
7 
+%    preprocess(sData)
8 
+%
9 
+% Launches a preprocessing GUI. The optional input argument can be
10 
+% either a data struct or a struct array of such. However, primarily
11 
+% the processed data sets are loaded to the application using the
12 
+% tools in the GUI. Also, the only way to get the preprocessed data
13 
+% sets back into the workspace is to use the tools in the GUI (press
14 
+% the button DATA SET MANAGEMENT).
15 
+%
16 
+% For a more throughout description, see online documentation.
17 
+% See also SOM_GUI.
18 
+
19 
+%%%%%%%%%%%% DETAILED DESCRIPTION %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
20 
+%
21 
+% IN FILES: preprocess.html,preproc.jpg,sDman.jpg,clip.jpg,delay.jpg,window.jpg,selVect.jpg
22 
+
23 
+% Contributed to SOM Toolbox vs2, February 2nd, 2000 by Juha Parhankangas
24 
+% Copyright (c) by Juha Parhankangas and the SOM Toolbox team
25 
+
26 
+% http://www.cis.hut.fi/projects/somtoolbox/
27 
+
28 
+% Juha Parhankangas 050100
29 
+
30 
+global no_of_sc  % every Nth component in 'relative values' is drawn stronger.
31 
+no_of_sc=5;
32 
+
33 
+if nargin < 1 | nargin > 2
34 
+  error('Invalid number of input arguments');
35 
+  return;
36 
+end
37 
+
38 
+if nargin == 1, arg2=[]; end
39 
+
40 
+if ~isstr(sData)   %%% Preprocess is started...
41 
+data.LOG{1}='% Starting the ''Preprocess'' -window...';
42 
+data.LOG{2}=cat(2,'preprocess(',...
43 
+                     sprintf('%s);',inputname(1)));
44 
+
45 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
46 
+if ~isempty(pre_h)
47 
+  figure(pre_h);
48 
+  msgbox('''Preprocess''-figure already exists.');
49 
+  return;
50 
+end
51 
+
52 
+h0 = figure('Color',[0.8 0.8 0.8], ...
53 
+	'PaperPosition',[18 180 576 432], ...
54 
+	'PaperUnits','points', ...
55 
+	'Position',[595 216 600 775], ...
56 
+	'Tag','Preprocess');
57 
+
58 
+h1 = uicontrol('Parent',h0, ...
59 
+	'Units','normalized', ...
60 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
61 
+	'FontWeight','demi', ...
62 
+	'HorizontalAlignment','left', ...
63 
+	'ListboxTop',0, ...
64 
+	'Position',[0.015 0.06064516129032258 0.9550000000000001 0.1458064516129032], ...
65 
+	'Style','text', ...
66 
+	'Tag','StaticText1');
67 
+
68 
+data.results_h = h1;
69 
+
70 
+h1 = uicontrol('Parent',h0, ...
71 
+	'Units','normalized', ...
72 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
73 
+	'Callback','preprocess close', ...
74 
+	'FontWeight','demi', ...
75 
+	'ListboxTop',0, ...
76 
+	'Position',[0.8067 0.0142 0.1667 0.0348],...
77 
+	'String','CLOSE', ...
78 
+	'Tag','Pushbutton1');
79 
+
80 
+h1 = uicontrol('Parent',h0, ...
81 
+	'Units','normalized', ...
82 
+	'BackgroundColor',[0.8 0.8 0.8], ...
83 
+	'FontWeight','demi', ...
84 
+	'HorizontalAlignment','left', ...
85 
+	'ListboxTop',0, ...
86 
+	'Position',[0.01833333333333333 0.2141935483870968 0.07000000000000001 0.01806451612903226], ...
87 
+	'String','LOG', ...
88 
+	'Style','text', ...
89 
+	'Tag','StaticText2');
90 
+
91 
+h1 = uicontrol('Parent',h0, ...
92 
+	'Units','normalized', ...
93 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
94 
+	'Callback','preprocess sel_comp',...
95 
+	'FontWeight','demi', ...
96 
+	'ListboxTop',0, ...
97 
+	'Position',[0.7983333333333333 0.2090322580645161 0.1666666666666667 0.03483870967741935], ...
98 
+	'String',' ', ...
99 
+	'Style','popupmenu', ...
100 
+	'Tag','sel_comp_h', ...
101 
+	'Value',1);
102 
+
103 
+data.sel_comp_h=h1;
104 
+
105 
+h1 = uicontrol('Parent',h0, ...
106 
+	'Units','normalized', ...
107 
+	'BackgroundColor',[1 1 1], ...
108 
+	'ListboxTop',0, ...
109 
+	'Position',[0.0183 0.2568 0.2133 0.1290], ...
110 
+	'Style','text', ...
111 
+	'Tag','StaticText3');
112 
+
113 
+data.sel_cdata_h=h1;
114 
+
115 
+h1 = axes('Parent',h0, ...
116 
+	'CameraUpVector',[0 1 0], ...
117 
+	'CameraUpVectorMode','manual', ...
118 
+	'Color',[1 1 1], ...
119 
+	'Position',[0.2583 0.2568 0.2133 0.1290], ...
120 
+	'Tag','Axes1', ...
121 
+	'XColor',[0 0 0], ...
122 
+	'XTickLabel',['0  ';'0.5';'1  '], ...
123 
+	'XTickLabelMode','manual', ...
124 
+	'XTickMode','manual', ...
125 
+	'YColor',[0 0 0], ...
126 
+	'YTickMode','manual', ...
127 
+	'ZColor',[0 0 0]);
128 
+
129 
+data.sel_chist_h=h1;
130 
+
131 
+h2 = text('Parent',h1, ...
132 
+	'Color',[0 0 0], ...
133 
+	'HandleVisibility','off', ...
134 
+	'HorizontalAlignment','center', ...
135 
+	'Position',[0.4960629921259843 -0.08080808080808044 9.160254037844386], ...
136 
+	'Tag','Axes1Text4', ...
137 
+	'VerticalAlignment','cap');
138 
+set(get(h2,'Parent'),'XLabel',h2);
139 
+h2 = text('Parent',h1, ...
140 
+	'Color',[0 0 0], ...
141 
+	'HandleVisibility','off', ...
142 
+	'HorizontalAlignment','center', ...
143 
+	'Position',[-0.0551181102362206 0.4848484848484853 9.160254037844386], ...
144 
+	'Rotation',90, ...
145 
+	'Tag','Axes1Text3', ...
146 
+	'VerticalAlignment','baseline');
147 
+set(get(h2,'Parent'),'YLabel',h2);
148 
+h2 = text('Parent',h1, ...
149 
+	'Color',[0 0 0], ...
150 
+	'HandleVisibility','off', ...
151 
+	'HorizontalAlignment','right', ...
152 
+	'Position',[-1.2283    5.7980    9.1603], ...
153 
+	'Tag','Axes1Text2', ...
154 
+	'Visible','off');
155 
+set(get(h2,'Parent'),'ZLabel',h2);
156 
+h2 = text('Parent',h1, ...
157 
+	'Color',[0 0 0], ...
158 
+	'HandleVisibility','off', ...
159 
+	'HorizontalAlignment','center', ...
160 
+	'Position',[0.4960629921259843 1.070707070707071 9.160254037844386], ...
161 
+	'Tag','Axes1Text1', ...
162 
+	'VerticalAlignment','bottom');
163 
+set(get(h2,'Parent'),'Title',h2);
164 
+
165 
+h1 = axes('Parent',h0, ...
166 
+	'CameraUpVector',[0 1 0], ...
167 
+	'CameraUpVectorMode','manual', ...
168 
+	'Color',[0.7529 0.7529 0.7529], ...
169 
+	'Position',[0.4950000000000001 0.2567741935483871 0.4766666666666667 0.1290322580645161], ...
170 
+	'Tag','Axes2', ...
171 
+	'XColor',[0 0 0], ...
172 
+	'XTickMode','manual', ...
173 
+	'YColor',[0 0 0], ...
174 
+	'YTick',[0 0.5 1], ...
175 
+	'YTickMode','manual', ...
176 
+	'ZColor',[0 0 0]);
177 
+
178 
+data.vector_h=h1;
179 
+
180 
+h2 = text('Parent',h1, ...
181 
+	'Color',[0 0 0], ...
182 
+	'HandleVisibility','off', ...
183 
+	'HorizontalAlignment','center', ...
184 
+	'Position',[0.4982456140350879 -0.08080808080808044 9.160254037844386], ...
185 
+	'Tag','Axes2Text4', ...
186 
+	'VerticalAlignment','cap');
187 
+set(get(h2,'Parent'),'XLabel',h2);
188 
+h2 = text('Parent',h1, ...
189 
+	'Color',[0 0 0], ...
190 
+	'HandleVisibility','off', ...
191 
+	'HorizontalAlignment','center', ...
192 
+	'Position',[-0.1018    0.4848    9.1603], ...
193 
+	'Rotation',90, ...
194 
+	'Tag','Axes2Text3', ...
195 
+	'VerticalAlignment','baseline');
196 
+set(get(h2,'Parent'),'YLabel',h2);
197 
+h2 = text('Parent',h1, ...
198 
+	'Color',[0 0 0], ...
199 
+	'HandleVisibility','off', ...
200 
+	'HorizontalAlignment','right', ...
201 
+	'Position',[-1.045614035087719 5.797979797979799 9.160254037844386], ...
202 
+	'Tag','Axes2Text2', ...
203 
+	'Visible','off');
204 
+set(get(h2,'Parent'),'ZLabel',h2);
205 
+h2 = text('Parent',h1, ...
206 
+	'Color',[0 0 0], ...
207 
+	'HandleVisibility','off', ...
208 
+	'HorizontalAlignment','center', ...
209 
+	'Position',[0.4982456140350879 1.070707070707071 9.160254037844386], ...
210 
+	'Tag','Axes2Text1', ...
211 
+	'VerticalAlignment','bottom');
212 
+set(get(h2,'Parent'),'Title',h2);
213 
+
214 
+h1 = uicontrol('Parent',h0, ...
215 
+	'Units','normalized', ...
216 
+	'BackgroundColor',[0.8 0.8 0.8], ...
217 
+	'FontWeight','demi', ...
218 
+	'HorizontalAlignment','left', ...
219 
+	'ListboxTop',0, ...
220 
+	'Position',[0.01833333333333333 0.3922580645161291 0.17 0.01806451612903226], ...
221 
+	'String','STATISTICS', ...
222 
+	'Style','text', ...
223 
+	'Tag','StaticText4');
224 
+
225 
+h1 = uicontrol('Parent',h0, ...
226 
+	'Units','normalized', ...
227 
+	'BackgroundColor',[0.8 0.8 0.8], ...
228 
+	'FontWeight','demi', ...
229 
+	'HorizontalAlignment','left', ...
230 
+	'ListboxTop',0, ...
231 
+	'Position',[0.2583333333333334 0.3922580645161291 0.1633333333333333 0.01806451612903226], ...
232 
+	'String','HISTOGRAM', ...
233 
+	'Style','text', ...
234 
+	'Tag','StaticText5');
235 
+
236 
+h1 = uicontrol('Parent',h0, ...
237 
+	'Units','normalized', ...
238 
+	'BackgroundColor',[0.8 0.8 0.8], ...
239 
+	'FontWeight','demi',...
240 
+	'FontSize',6,...
241 
+	'HorizontalAlignment','left',...
242 
+	'String',{'LEFT: NEW SELECTION';'RIGHT: ADD TO SELECTION'}, ...
243 
+	'ListboxTop',0, ...
244 
+	'Position',[0.5016666666666667 0.38 0.235 0.03741935483870968], ...
245 
+	'Style','text', ...
246 
+	'Tag','StaticText6', ...
247 
+	'UserData','[ ]');
248 
+
249 
+h1 = uicontrol('Parent',h0, ...
250 
+	'Units','normalized', ...
251 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
252 
+	'Callback','preprocess selall', ...
253 
+	'FontWeight','demi', ...
254 
+	'ListboxTop',0, ...
255 
+	'Position',[0.8066666666666668 0.3922580645161291 0.1666666666666667 0.03483870967741935], ...
256 
+	'String','SELECT ALL', ...
257 
+	'Tag','Pushbutton2', ...
258 
+	'UserData','[ ]');
259 
+
260 
+h1 = uicontrol('Parent',h0, ...
261 
+	'Units','normalized', ...
262 
+	'BackgroundColor',[0.7529 0.7529 0.7529], ...
263 
+	'Position',[0.01833333333333333 0.4503225806451613 0.23 0.3225806451612903], ...
264 
+	'String',' ', ...
265 
+	'Style','listbox', ...
266 
+	'Tag','Listbox1', ...
267 
+	'Value',1);
268 
+
269 
+data.comp_names_h=h1;
270 
+
271 
+h1 = uicontrol('Parent',h0, ...
272 
+	'Units','normalized', ...
273 
+	'BackgroundColor',[1 1 1], ...
274 
+	'Position',[0.4950000000000001 0.4503225806451613 0.2333333333333333 0.3225806451612903], ...
275 
+	'String',' ', ...
276 
+	'Style','listbox', ...
277 
+	'Tag','Listbox2', ...
278 
+	'Value',1);
279 
+
280 
+data.vect_mean_h = h1;
281 
+
282 
+h1 = axes('Parent',h0, ...
283 
+	'CameraUpVector',[0 1 0], ...
284 
+	'CameraUpVectorMode','manual', ...
285 
+	'Color',[1 1 1], ...
286 
+	'Position',[0.7383333333333334 0.4503225806451613 0.2333333333333333 0.3225806451612903], ...
287 
+	'Tag','Axes3', ...
288 
+	'XColor',[0 0 0], ...
289 
+	'XTickMode','manual', ...
290 
+	'YColor',[0 0 0], ...
291 
+	'YTickMode','manual', ...
292 
+	'ZColor',[0 0 0]);
293 
+
294 
+data.sel_cplot_h = h1;
295 
+
296 
+h2 = text('Parent',h1, ...
297 
+	'Color',[0 0 0], ...
298 
+	'HandleVisibility','off', ...
299 
+	'HorizontalAlignment','center', ...
300 
+	'Position',[0.4964028776978418 -0.03212851405622486 9.160254037844386], ...
301 
+	'Tag','Axes3Text4', ...
302 
+	'VerticalAlignment','cap');
303 
+set(get(h2,'Parent'),'XLabel',h2);
304 
+h2 = text('Parent',h1, ...
305 
+	'Color',[0 0 0], ...
306 
+	'HandleVisibility','off', ...
307 
+	'HorizontalAlignment','center', ...
308 
+	'Position',[-0.05035971223021596 0.493975903614458 9.160254037844386], ...
309 
+	'Rotation',90, ...
310 
+	'Tag','Axes3Text3', ...
311 
+	'VerticalAlignment','baseline');
312 
+set(get(h2,'Parent'),'YLabel',h2);
313 
+h2 = text('Parent',h1, ...
314 
+	'Color',[0 0 0], ...
315 
+	'HandleVisibility','off', ...
316 
+	'HorizontalAlignment','right', ...
317 
+	'Position',[-3.1942    1.7028    9.1603], ...
318 
+	'Tag','Axes3Text2', ...
319 
+	'Visible','off');
320 
+set(get(h2,'Parent'),'ZLabel',h2);
321 
+h2 = text('Parent',h1, ...
322 
+	'Color',[0 0 0], ...
323 
+	'HandleVisibility','off', ...
324 
+	'HorizontalAlignment','center', ...
325 
+	'Position',[0.4964028776978418 1.028112449799197 9.160254037844386], ...
326 
+	'Tag','Axes3Text1', ...
327 
+	'VerticalAlignment','bottom');
328 
+set(get(h2,'Parent'),'Title',h2);
329 
+
330 
+h1 = uicontrol('Parent',h0, ...
331 
+	'Units','normalized', ...
332 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
333 
+	'Callback','preprocess plxy', ...
334 
+	'FontWeight','demi', ...
335 
+	'ListboxTop',0, ...
336 
+	'Position',[0.265 0.4683870967741936 0.125 0.03483870967741935], ...
337 
+	'String','XY-PLOT', ...
338 
+	'Tag','Pushbutton3');
339 
+
340 
+h1 = uicontrol('Parent',h0, ...
341 
+	'Units','normalized', ...
342 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
343 
+	'Callback','preprocess hist', ...
344 
+	'FontWeight','demi', ...
345 
+	'ListboxTop',0, ...
346 
+	'Position',[0.265 0.5303225806451613 0.125 0.03483870967741935], ...
347 
+	'String','HISTOGRAM', ...
348 
+	'Tag','Pushbutton4');
349 
+
350 
+h1 = uicontrol('Parent',h0, ...
351 
+	'Units','normalized', ...
352 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
353 
+	'Callback','preprocess bplo', ...
354 
+	'FontWeight','demi', ...
355 
+	'ListboxTop',0, ...
356 
+	'Position',[0.265 0.5922580645161291 0.125 0.03483870967741935], ...
357 
+	'String','BOX PLOT', ...
358 
+	'Tag','Pushbutton5');
359 
+
360 
+h1 = uicontrol('Parent',h0, ...
361 
+	'Units','normalized', ...
362 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
363 
+	'Callback','preprocess plot', ...
364 
+	'FontWeight','demi', ...
365 
+	'ListboxTop',0, ...
366 
+	'Position',[0.265 0.654195483870968 0.125 0.03483870967741935], ...
367 
+	'String','PLOT', ...
368 
+	'Tag','Pushbutton6');
369 
+
370 
+h1 = uicontrol('Parent',h0, ...
371 
+	'Units','normalized', ...
372 
+	'BackgroundColor',[1 1 1], ...
373 
+	'ListboxTop',0, ...
374 
+	'Position',[0.4088888888888889 0.5333333333333333 0.06 0.03268817204301075], ...
375 
+	'String','30', ...
376 
+	'Style','edit', ...
377 
+	'Tag','EditText1');
378 
+
379 
+data.no_of_bins_h = h1;
380 
+
381 
+
382 
+h1 = uicontrol('Parent',h0, ...
383 
+	'Units','normalized', ...
384 
+	'BackgroundColor',[0.8 0.8 0.8], ...
385 
+	'FontWeight','demi', ...
386 
+	'HorizontalAlignment','left', ...
387 
+	'ListboxTop',0, ...
388 
+	'Position',[0.01833333333333333 0.775483870967742 0.2016666666666667 0.01806451612903226], ...
389 
+	'String','COMPONENT LIST', ...
390 
+	'Style','text', ...
391 
+	'Tag','StaticText7');
392 
+
393 
+h1 = uicontrol('Parent',h0, ...
394 
+	'Units','normalized', ...
395 
+	'BackgroundColor',[0.8 0.8 0.8], ...
396 
+	'FontWeight','demi', ...
397 
+	'HorizontalAlignment','left', ...
398 
+	'ListboxTop',0, ...
399 
+	'Position',[0.4950000000000001 0.775483870967742 0.1966666666666667 0.01806451612903226], ...
400 
+	'String','AVERAGE', ...
401 
+	'Style','text', ...
402 
+	'Tag','StaticText8');
403 
+
404 
+h1 = uicontrol('Parent',h0, ...
405 
+	'Units','normalized', ...
406 
+	'BackgroundColor',[0.8 0.8 0.8], ...
407 
+	'FontWeight','demi', ...
408 
+	'HorizontalAlignment','left', ...
409 
+	'ListboxTop',0, ...
410 
+	'Position',[0.7383333333333334 0.775483870967742 0.225 0.01806451612903226], ...
411 
+	'String','RELATIVE VALUES', ...
412 
+	'Style','text', ...
413 
+	'Tag','StaticText9');
414 
+
415 
+h1 = uicontrol('Parent',h0, ...
416 
+	'Units','normalized', ...
417 
+	'BackgroundColor',[0.8 0.8 0.8], ...
418 
+	'FontSize',10, ...
419 
+	'FontWeight','demi', ...
420 
+	'HorizontalAlignment','left', ...
421 
+	'ListboxTop',0, ...
422 
+	'Position',[0.01833333333333333 0.8154838709677419 0.2033333333333333 0.0232258064516129], ...
423 
+	'String','COMPONENTS', ...
424 
+	'Style','text', ...
425 
+	'Tag','StaticText10');
426 
+
427 
+h1 = uicontrol('Parent',h0, ...
428 
+	'Units','normalized', ...
429 
+	'BackgroundColor',[0.8 0.8 0.8], ...
430 
+	'FontSize',10, ...
431 
+	'FontWeight','demi', ...
432 
+	'HorizontalAlignment','left', ...
433 
+	'ListboxTop',0, ...
434 
+	'Position',[0.4950000000000001 0.8154838709677419 0.2 0.0232258064516129], ...
435 
+	'String','VECTORS', ...
436 
+	'Style','text', ...
437 
+	'Tag','StaticText11');
438 
+
439 
+h1 = uicontrol('Parent',h0, ...
440 
+	'Units','normalized', ...
441 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
442 
+	'Callback','preprocess sD_management', ...
443 
+	'FontSize',5, ...
444 
+	'FontWeight','demi', ...
445 
+	'ListboxTop',0, ...
446 
+	'Position',[0.01833333333333333 0.8503225806451613 0.1666666666666667 0.03483870967741935], ...
447 
+	'String','DATA SET MANAGEMENT', ...
448 
+	'Tag','Pushbutton7');
449 
+
450 
+h1 = uicontrol('Parent',h0, ...
451 
+	'Units','normalized', ...
452 
+	'Callback','preprocess sel_sD', ...
453 
+	'ListboxTop',0, ...
454 
+	'Position',[0.01833333333333333 0.8890322580645161 0.1666666666666667 0.03483870967741935], ...
455 
+	'String',' ', ...
456 
+	'Style','popupmenu', ...
457 
+	'Tag','PopupMenu2', ...
458 
+	'Value',1);
459 
+
460 
+data.sD_set_h = h1;
461 
+
462 
+h1 = uicontrol('Parent',h0, ...
463 
+	'Units','normalized', ...
464 
+	'BackgroundColor',[1 1 1], ...
465 
+	'ListboxTop',0, ...
466 
+	'Position',[0.2516666666666667 0.8503225806451613 0.7216666666666667 0.07354838709677419], ...
467 
+	'Style','text', ...
468 
+	'Tag','StaticText12');
469 
+
470 
+data.sD_name_h = h1;
471 
+
472 
+h1 = uicontrol('Parent',h0, ...
473 
+	'Units','normalized', ...
474 
+	'BackgroundColor',[0.8 0.8 0.8], ...
475 
+	'FontSize',10, ...
476 
+	'FontWeight','demi', ...
477 
+	'HorizontalAlignment','left', ...
478 
+	'ListboxTop',0, ...
479 
+	'Position',[0.01833333333333333 0.9341935483870968 0.1616666666666667 0.02064516129032258], ...
480 
+	'String','DATA SETS', ...
481 
+	'Style','text', ...
482 
+	'Tag','StaticText13');
483 
+
484 
+h1 = uicontrol('Parent',h0, ...
485 
+	'Units','normalized', ...
486 
+	'BackgroundColor',[0.8 0.8 0.8], ...
487 
+	'FontSize',10, ...
488 
+	'FontWeight','demi', ...
489 
+	'HorizontalAlignment','left', ...
490 
+	'ListboxTop',0, ...
491 
+	'Position',[0.2516666666666667 0.9341935483870968 0.2833333333333333 0.02064516129032258], ...
492 
+	'String','SELECTED DATA SET', ...
493 
+	'Style','text', ...
494 
+	'Tag','StaticText14');
495 
+
496 
+if ~isstruct(sData),
497 
+  sData=som_data_struct(sData);
498 
+end
499 
+
500 
+ui_h=uimenu('Label','&Normalization');
501 
+uimenu(ui_h,'Label','Scale [0,1]','Callback','preprocess zscale');
502 
+uimenu(ui_h,'Label','Scale var=1','Callback','preprocess vscale');
503 
+uimenu(ui_h,'Label','HistD','Callback','preprocess histeq');
504 
+uimenu(ui_h,'Label','HistC','Callback','preprocess histeq2');
505 
+uimenu(ui_h,'Label','Log','Callback','preprocess log');
506 
+uimenu(ui_h,'Label','Eval (1-comp)','Callback','preprocess eval1');
507 
+
508 
+ui_h=uimenu('Label','&Components');
509 
+uimenu(ui_h,'Label','Move component','Callback','preprocess move');
510 
+uimenu(ui_h,'Label','Copy component','Callback','preprocess copy');
511 
+uimenu(ui_h,'Label','Add: N binary types','Callback','preprocess oneo');
512 
+uimenu(ui_h,'Label','Add: zeros','Callback','preprocess zero');
513 
+uimenu(ui_h,'Label','Remove component','Callback','preprocess remove');
514 
+uimenu(ui_h,'Label','Remove selected vectors',...
515 
+            'Callback','preprocess remove_vects');
516 
+uimenu(ui_h,'Label','Select all components',...
517 
+            'Callback','preprocess sel_all_comps');
518 
+
519 
+ui_h=uimenu('Label','&Misc');
520 
+ui_h1=uimenu(ui_h,'Label','Calculate');
521 
+ui_h2=uimenu(ui_h,'Label','Process');
522 
+
523 
+uimenu(ui_h,'Label','Get LOG-file','Callback','preprocess LOG');
524 
+uimenu(ui_h,'Label','Indices of the selected vectors',...
525 
+            'Callback','preprocess get_inds');
526 
+uimenu(ui_h,'Label','Undo','Callback','preprocess undo');
527 
+uimenu(ui_h1,'Label','Number of values','Callback','preprocess noof');
528 
+uimenu(ui_h1,'Label','Number of selected vectors',...
529 
+             'Callback','preprocess no_of_sel');
530 
+uimenu(ui_h1,'Label','Correlation','Callback','preprocess corr');
531 
+uimenu(ui_h2,'Label','Unit length','Callback','preprocess unit');
532 
+uimenu(ui_h2,'Label','Eval','Callback','preprocess eval2');
533 
+uimenu(ui_h2,'Label','Clipping','Callback','preprocess clipping');
534 
+uimenu(ui_h2,'Label','Delay','Callback','preprocess delay');
535 
+uimenu(ui_h2,'Label','Windowed','Callback','preprocess window');
536 
+uimenu(ui_h2,'Label','Select vectors','Callback','preprocess select');
537 
+
538 
+len=getfield(size(sData(1).data),{1});
539 
+data.selected_vects=find(ones(1,len));
540 
+data.sD_set=sData;
541 
+set(data.vector_h,'ButtonDownFcn','preprocess(''vector_bdf'',''down'')');
542 
+set(gcf,'UserData',data);
543 
+if ~set_sD_stats;
544 
+  return;
545 
+end
546 
+sel_sD;
547 
+return;    %%% Preprocess-window is ready.
548 
+
549 
+else
550 
+ arg=sData;
551 
+ if strcmp(arg,'rename')
552 
+   rename(arg2);
553 
+ elseif strcmp(arg,'sel_sD')
554 
+   if isempty(arg2)
555 
+     sel_sD;
556 
+   else
557 
+     sel_sD(arg2);
558 
+   end
559 
+ elseif strcmp(arg,'zscale')
560 
+   if isempty(arg2)
561 
+      zero2one_scale;
562 
+   else
563 
+      zero2one_scale(arg2);
564 
+   end
565 
+ elseif strcmp(arg,'vscale');
566 
+   if isempty(arg2)
567 
+      var_scale;
568 
+   else
569 
+      var_scale(arg2);
570 
+   end
571 
+ elseif strcmp(arg,'histeq2')
572 
+   if isempty(arg2)
573 
+     hist_eq2;
574 
+   else
575 
+     hist_eq2(arg2);
576 
+   end
577 
+ elseif strcmp(arg,'log')
578 
+   if isempty(arg2)
579 
+     logarithm;
580 
+   else
581 
+     logarithm(arg2);
582 
+   end
583 
+ elseif strcmp(arg,'eval1')
584 
+   if isempty(arg2)
585 
+     eval1;
586 
+   else
587 
+     eval1(arg2);
588 
+   end
589 
+ elseif strcmp(arg,'eval2')
590 
+   if isempty(arg2)
591 
+     eval2;
592 
+   else
593 
+     eval2(arg2);
594 
+   end
595 
+ elseif strcmp(arg,'histeq');
596 
+   if isempty(arg2)
597 
+     hist_eq;
598 
+   else
599 
+      hist_eq(arg2);
600 
+   end
601 
+ elseif strcmp(arg,'selall')
602 
+   if isempty(arg2)
603 
+     select_all;
604 
+   else
605 
+     select_all(arg2);
606 
+   end
607 
+ elseif strcmp(arg,'sel_button');
608 
+   if isempty(arg2)
609 
+     sel_button;
610 
+   else
611 
+     sel_button(arg2);
612 
+   end
613 
+ elseif strcmp(arg,'clear_button')
614 
+   if isempty(arg2)
615 
+     clear_button;
616 
+   else
617 
+     clear_button(arg2)
618 
+   end
619 
+ elseif(strcmp(arg,'move'))
620 
+   if isempty(arg2)
621 
+     move_component;
622 
+   else
623 
+     move_component(arg2);
624 
+   end
625 
+ elseif(strcmp(arg,'copy'))
626 
+   if isempty(arg2)
627 
+     copy_component;
628 
+   else
629 
+     copy_component(arg2);
630 
+   end
631 
+ elseif strcmp(arg,'oneo')
632 
+   if isempty(arg2)
633 
+     one_of_n;
634 
+   else
635 
+     one_of_n(arg2);
636 
+   end
637 
+ elseif strcmp(arg,'zero')
638 
+   if isempty(arg2)
639 
+     add_zeros;
640 
+   else
641 
+     add_zeros(arg2);
642 
+   end
643 
+ elseif strcmp(arg,'remove')
644 
+   if isempty(arg2)
645 
+     remove_component;
646 
+   else
647 
+     remove_component(arg2);
648 
+   end
649 
+ elseif strcmp(arg,'remove_vects')
650 
+   if isempty(arg2)
651 
+     remove_vects;
652 
+   else
653 
+     remove_vects(arg2);
654 
+   end
655 
+ elseif strcmp(arg,'noof')
656 
+   if isempty(arg2)
657 
+     no_of_values;
658 
+   else
659 
+     no_of_values(arg2);
660 
+   end
661 
+ elseif strcmp(arg,'corr');
662 
+   if isempty(arg2)
663 
+     correlation;
664 
+   else
665 
+     correlation(arg2);
666 
+   end
667 
+ elseif strcmp(arg,'unit')
668 
+   if isempty(arg2)
669 
+     unit_length;
670 
+   else
671 
+     unit_length(arg2);
672 
+   end
673 
+ elseif strcmp(arg,'clip_data')
674 
+   clip_data(arg2);
675 
+ elseif strcmp(arg,'copy_delete')
676 
+   copy_delete(arg2);
677 
+ elseif strcmp(arg,'and_or_cb')
678 
+   and_or_cb(arg2);
679 
+ elseif strcmp(arg,'all_sel_cb')
680 
+   all_sel_cb(arg2);
681 
+ elseif strcmp(arg,'clip_exp_cb')
682 
+   clip_exp_cb(arg2);
683 
+ elseif strcmp(arg,'window_cb')
684 
+   window_cb(arg2);
685 
+ elseif strcmp(arg,'set_state_vals')
686 
+   set_state_vals(arg2);
687 
+ elseif strcmp(arg,'vector_bdf')
688 
+   vector_bdf(arg2);
689 
+ elseif strcmp(arg,'sD_management');
690 
+   if isempty(arg2)
691 
+     sD_management;
692 
+   else
693 
+     sD_management(arg2);
694 
+   end
695 
+ elseif strcmp(arg,'clipping')
696 
+   if isempty(arg2)
697 
+     clipping;
698 
+   else
699 
+     clipping(arg2);
700 
+   end
701 
+ elseif strcmp(arg,'delay')
702 
+   if isempty(arg2)
703 
+     delay;
704 
+   else
705 
+     delay(arg2);
706 
+   end
707 
+ elseif strcmp(arg,'window');
708 
+   if isempty(arg2)
709 
+     window;
710 
+   else
711 
+     window(arg2);
712 
+   end
713 
+ elseif strcmp(arg,'select');
714 
+   if isempty(arg2)
715 
+     select;
716 
+   else
717 
+     select(arg2);
718 
+   end
719 
+ elseif strcmp(arg,'import')
720 
+   if isempty(arg2)
721 
+     import;
722 
+   else
723 
+     import(arg2);
724 
+   end
725 
+ elseif strcmp(arg,'export')
726 
+   if isempty(arg2)
727 
+     export;
728 
+   else
729 
+     export(arg2);
730 
+   end
731 
+ elseif strcmp(arg,'undo');
732 
+   if isempty(arg2)
733 
+     undo;
734 
+   else
735 
+     undo(arg2);
736 
+   end
737 
+ elseif strcmp(arg,'delay_data')
738 
+   if isempty(arg2)
739 
+     delay_data;
740 
+   else
741 
+     delay_data(arg2);
742 
+   end
743 
+ elseif strcmp(arg,'eval_windowed')
744 
+   if isempty(arg2)
745 
+     eval_windowed;
746 
+   else
747 
+     eval_windowed(arg2);
748 
+   end
749 
+ elseif strcmp(arg,'get_inds')
750 
+   if isempty(arg2)
751 
+     get_selected_inds;
752 
+   else
753 
+     get_selected_inds(arg2);
754 
+   end
755 
+ elseif strcmp(arg,'no_of_sel')
756 
+   if isempty(arg2)
757 
+     no_of_selected;
758 
+   else
759 
+     no_of_selected(arg2);
760 
+   end
761 
+ elseif strcmp(arg,'sel_comp');
762 
+   if isempty(arg2)
763 
+     sel_comp;
764 
+   else
765 
+     sel_comp(arg2);
766 
+   end
767 
+ elseif strcmp(arg,'sel_all_comps')
768 
+   if isempty(arg2)
769 
+     select_all_comps;
770 
+   else
771 
+     select_all_comps(arg2);
772 
+   end
773 
+ elseif strcmp(arg,'refresh')
774 
+   set_var_names;
775 
+ elseif any(strcmp(arg,{'close_c','close_d','close_s','close_w','close_sD'}))
776 
+   if isempty(arg2)
777 
+     close_func(arg)
778 
+   else
779 
+     close_func(arg,arg2);
780 
+   end
781 
+ end
782 
+
783 
+
784 
+ switch arg
785 
+   case 'sD_stats'
786 
+     sD_stats;
787 
+   case 'LOG'
788 
+     log_file;
789 
+   otherwise
790 
+     pro_tools(arg);
791 
+ end
792 
+end
793 
+
794 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
795 
+
796 
+function set_compnames(sData,h)
797 
+
798 
+%SET_COMPNAMES
799 
+%
800 
+% set_compnames(sData,h)
801 
+%
802 
+% ARGUMENTS
803 
+%
804 
+%  sData     (struct)  som_data_struct
805 
+%  h         (scalar)  handle to a list box object
806 
+%
807 
+%
808 
+% This function sets the component names of sData to the list box
809 
+% indicated by 'h'.
810 
+%
811 
+
812 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
813 
+
814 
+if isempty(pre_h)
815 
+  error('Figure ''Preprocess'' does not exist. Closing program...');
816 
+  close_preprocess;
817 
+end
818 
+
819 
+udata=get(pre_h,'UserData');
820 
+
821 
+set(h,'Value',[]);
822 
+for i=1:length(sData.comp_names)
823 
+  tmp=sprintf('#%d: ',i);
824 
+  names{i,1}=cat(2,tmp, sData.comp_names{i});
825 
+end
826 
+
827 
+
828 
+set(h,'String',names,'Max',2);
829 
+set(udata.sel_comp_h,'String',names);
830 
+
831 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
832 
+
833 
+function draw_vectors(vectors,h)
834 
+
835 
+%DRAW_VECTORS
836 
+%
837 
+% draw_vectors(vectors,h)
838 
+%
839 
+% ARGUMENTS
840 
+%
841 
+%  vectors  (vector) vector of 0's and 1's
842 
+%  h        (scalar) handle to an axis object
843 
+%
844 
+%
845 
+%  This function draws an horizontal bar of 'vectors' in the axis
846 
+%  indicated by 'h'.
847 
+%
848 
+%
849 
+
850 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
851 
+subplot(h);
852 
+hold off;
853 
+cla;
854 
+
855 
+set(h,'YLim',[0 1]);
856 
+set(h,'YTick',[]);
857 
+set(h,'XLim',[0 length(vectors)+1]);
858 
+hold on;
859 
+
860 
+comp_no=get(getfield(get(pre_h,'UserData'),'sel_comp_h'),'Value');
861 
+comp=getfield(get(pre_h,'UserData'),'sData');
862 
+comp=comp.data(:,comp_no);
863 
+Max = max(comp);
864 
+Min = min(comp);
865 
+lims=get(gca,'YLim');
866 
+lims(1)=Min;
867 
+h=abs(0.1*Max);
868 
+lims(2)=Max;
869 
+if Max - Min <= eps
870 
+  tmp=Max;
871 
+  lims(1)=tmp-1;
872 
+  lims(2)=tmp+1;
873 
+end
874 
+lims(2)=lims(2)+h;
875 
+if ~all(isnan(lims))
876 
+  set(gca,'YLim',lims);
877 
+end
878 
+h=(lims(2)-lims(1))/4;
879 
+set(gca,'YTickMode','auto');
880 
+t=1:length(vectors);
881 
+h=plot(t,comp);
882 
+set(h,'ButtonDownFcn','preprocess(''vector_bdf'',''down'')');
883 
+indices =find(vectors);
884 
+vectors(indices)=0.1*(getfield(get(gca,'YLim'),...
885 
+                      {2})-getfield(get(gca,'YLim'),{1}));
886 
+plot(indices,vectors(indices)+getfield(get(gca,'YLim'),{1}),...
887 
+     'ored','MarkerSize',4);
888 
+
889 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
890 
+
891 
+function vect_means(sData,handle,indices)
892 
+
893 
+%VECT_MEANS
894 
+%
895 
+% vect_means(sData,handle,indices)
896 
+%
897 
+% ARGUMENTS
898 
+%
899 
+%  sData    (struct)    som_data_struct
900 
+%  handle   (scalar)    handle to the static text box object
901 
+%  indices  (vector)    indices of selected vectors
902 
+%
903 
+%
904 
+% This function calculates means of selected vectors' components
905 
+% and writes them in the static text box indicated by 'handle'.
906 
+%
907 
+%
908 
+
909 
+sData= sData.data(indices,:);
910 
+
911 
+for i=1:length(sData(1,:))
912 
+  names{i}=sprintf('#%d: ',i);
913 
+end
914 
+
915 
+
916 
+for i=1:length(sData(1,:))
917 
+  tmp=sData(:,i);
918 
+  tmp=cat(2,names{i},sprintf('%-10.3g',mean(tmp(find(~isnan(tmp))))));
919 
+  string{i}=tmp;
920 
+end
921 
+
922 
+set(handle,'String',string);
923 
+set(handle,'HorizontalAlignment','left');
924 
+
925 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
926 
+
927 
+function vector_bdf(arg)
928 
+
929 
+%VECTOR_BDF   A button down function.
930 
+%
931 
+% vector_bdf(arg)
932 
+%
933 
+% ARGUMENTS
934 
+%
935 
+%  arg      (string)  'down' or 'up',  tells the mouse button's state.
936 
+%
937 
+%
938 
+%  This function selects vectors in the vector-window and plots maxima,
939 
+%  minima and means of the selected vectors. It also writes means of the
940 
+%  selected vectors' components in a static text box and takes care of
941 
+%  changes of the chosen component's data.
942 
+%
943 
+%  See also VECTOR_MEANS, SEL_COMP
944 
+%
945 
+%
946 
+
947 
+
948 
+arg2=arg(6:length(arg));
949 
+if ~isempty(arg2)
950 
+  LOG=1;
951 
+else
952 
+  LOG=0;
953 
+end
954 
+arg=arg(1:4);
955 
+
956 
+%%% arg's first "word" is 4 letters long and it can be:
957 
+%%%
958 
+%%% 'key '
959 
+%%% 'down'
960 
+%%% 'drag'
961 
+%%% 'up  '
962 
+
963 
+if strcmp(arg,'key ') %string is 'key' + 1 space!!!
964 
+  if ~LOG
965 
+    key=get(gcf,'CurrentCharacter');
966 
+   else
967 
+    key=arg2
968 
+  end
969 
+  if ~strcmp(key,'<') & ~strcmp(key,'>')
970 
+    return;
971 
+  end
972 
+  data=get(gcf,'UserData');
973 
+  sel=data.selected_vects;
974 
+  if length(sel) == 1
975 
+    if strcmp(key,'<') & sel ~= 1
976 
+      data.selected_vects=sel-1;
977 
+      set(gcf,'UserData',data);
978 
+     elseif strcmp(key,'>') & sel ~= length(data.sData.data(:,1))
979 
+      data.selected_vects = sel + 1;
980 
+      set(gcf,'UserData',data);
981 
+     end
982 
+  else
983 
+    if strcmp(key,'<') & sel(1) ~= 1
984 
+      data.selected_vects=cat(2,sel(1)-1,sel);
985 
+      set(gcf,'UserData',data);
986 
+     elseif strcmp(key,'>') & sel(length(sel)) ~= length(sel)
987 
+      data.selected_vects=cat(2,sel,sel(length(sel))+1);
988 
+      set(gcf,'UserData',data);
989 
+     end
990 
+  end
991 
+  cplot_mimema;
992 
+  pro_tools('plot_hist');
993 
+  pro_tools('c_stat');
994 
+  vects=zeros(1,length(data.sData.data(:,1)));
995 
+  vects(data.selected_vects)=1;
996 
+  draw_vectors(vects,data.vector_h);
997 
+
998 
+  if ~LOG
999 
+    data=get(gcf,'UserData');
1000 
+    data.LOG{length(data.LOG)+1}=...
1001 
+    sprintf('preprocess(''vector_bdf'',''key  %s'');',key);
1002 
+                                                %string is 'key'+2spaces+%s
1003 
+    set(gcf,'UserData',data);
1004 
+  end
1005 
+  return;
1006 
+end
1007 
+
1008 
+switch arg
1009 
+  case 'down'
1010 
+   set(gcf,'WindowButtonUpFcn','preprocess(''vector_bdf'',''up  '')');
1011 
+   set(gcf,'WindowButtonMotionFcn','preprocess(''vector_bdf'',''drag'')');
1012 
+   switch get(gcf,'SelectionType')
1013 
+     case 'normal'
1014 
+      data.lims1=round(getfield(get(gca,'CurrentPoint'),{1,1}));
1015 
+      data.lims2=[];
1016 
+     case 'alt'
1017 
+      tmp=round(getfield(get(gca,'CurrentPoint'),{1,1}));
1018 
+      if isempty(get(gca,'UserData'))
1019 
+        data.lims1=tmp;
1020 
+        data.lims2=[];
1021 
+      else
1022 
+        data.lims1=cat(2,getfield(get(gca,'UserData'),'lims1'),tmp);
1023 
+        data.lims2=getfield(get(gca,'UserData'),'lims2');
1024 
+      end
1025 
+   end
1026 
+   coords=get(gca,'CurrentPoint');
1027 
+   h=line([coords(1),coords(1)],get(gca,'YLim'),'EraseMode','xor');
1028 
+   set(h,'Color','red');
1029 
+   h2=line([coords(1),coords(1)],get(gca,'YLim'),'EraseMode','xor');
1030 
+   set(h2,'Color','red');
1031 
+   data.h=h;
1032 
+   data.h2=h2;
1033 
+   set(gca,'UserData',data);
1034 
+
1035 
+  case 'drag'
1036 
+   coords=get(gca,'CurrentPoint');
1037 
+   lim=get(gca,'XLim');
1038 
+   h2=getfield(get(gca,'UserData'),'h2');
1039 
+   if lim(1) >= coords(1)
1040 
+     set(h2,'XData',[lim(1) lim(1)]);
1041 
+   elseif lim(2) <= coords(2)
1042 
+     set(h2,'XData',[lim(2) lim(2)]);
1043 
+   else
1044 
+     set(h2,'XData',[coords(1) coords(1)]);
1045 
+   end
1046 
+  case 'up  '   % string is 'up' + 2 spaces!!!
1047 
+   set(gcf,'WindowButtonUpFcn','');
1048 
+   set(gcf,'WindowButtonMotionFcn','');
1049 
+   if ~LOG
1050 
+     data=get(gca,'UserData');
1051 
+     delete(data.h);
1052 
+     delete(data.h2);
1053 
+     tmp=round(getfield(get(gca,'CurrentPoint'),{1,1}));
1054 
+     data.lims2=cat(2,data.lims2,tmp);
1055 
+     tmp_data=sort(cat(1,data.lims1,data.lims2));
1056 
+     high=getfield(get(gca,'XLim'),{2})-1;
1057 
+     vectors=zeros(1,high);
1058 
+     tmp_data(find(tmp_data<1))=1;
1059 
+     tmp_data(find(tmp_data>high))=high;
1060 
+
1061 
+     for i=1:getfield(size(tmp_data),{2})
1062 
+       vectors(tmp_data(1,i):tmp_data(2,i))=1;
1063 
+     end
1064 
+     selected_vects=find(vectors);
1065 
+   else
1066 
+     pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1067 
+     len=size(getfield(getfield(get(pre_h,'UserData'),'sData'),'data'));
1068 
+     vectors=zeros(1,len(1));
1069 
+     i=1;
1070 
+     while i <= length(arg2) & (isspace(arg2(i)) | ~isletter(arg2(i)))
1071 
+      i=i+1;
1072 
+     end
1073 
+     arg3=arg2(i:length(arg2));
1074 
+     selected_vects=str2num(arg2(1:i-1));
1075 
+     if ~isempty(arg3) & ~all(isspace(arg3))
1076 
+       selected_vects=unique(cat(2,selected_vects,...
1077 
+                            getfield(get(pre_h,'UserData'),'selected_vects')));
1078 
+     end
1079 
+     vectors(selected_vects)=1;
1080 
+     set(pre_h,'CurrentAxes',getfield(get(pre_h,'UserData'),'vector_h'));
1081 
+     set(0,'CurrentFigure',pre_h);
1082 
+   end
1083 
+   draw_vectors(vectors,gca);
1084 
+   sData=getfield(get(gcf,'UserData'),'sData');
1085 
+   h=getfield(get(gcf,'UserData'),'vect_mean_h');
1086 
+   vect_means(sData,h,selected_vects);
1087 
+   if ~LOG
1088 
+     set(gca,'UserData',data);
1089 
+   end
1090 
+   data=get(gcf,'UserData');
1091 
+   data.undo.sData=data.sData;
1092 
+   data.undo.selected=data.selected_vects;
1093 
+   data.selected_vects=selected_vects;
1094 
+   if ~LOG
1095 
+     data.LOG{length(data.LOG)+1}='% Vector selection by using the mouse...';
1096 
+     tmp=sprintf('preprocess(''vector_bdf'',''up   %s'');',...
1097 
+                num2str(data.selected_vects));
1098 
+     if length(tmp) > 500
1099 
+       tmp=textwrap({tmp},500);
1100 
+       data.LOG{length(data.LOG)+1}=cat(2,tmp{1},''');');
1101 
+       for i=2:length(tmp)-1
1102 
+         data.LOG{length(data.LOG)+1}=...
1103 
+               cat(2,sprintf('preprocess(''vector_bdf'',''up   %s',...
1104 
+                     tmp{i}),'add'');');
1105 
+       end
1106 
+       data.LOG{length(data.LOG)+1}=...
1107 
+             cat(2,sprintf('preprocess(''vector_bdf'',''up   %s',...
1108 
+                   tmp{length(tmp)}(1:length(tmp{length(tmp)})-3)),' add'');');
1109 
+     else
1110 
+       data.LOG{length(data.LOG)+1}=tmp;
1111 
+     end
1112 
+   end
1113 
+   set(gcf,'UserData',data);
1114 
+   cplot_mimema;
1115 
+   sel_comp;
1116 
+end
1117 
+
1118 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1119 
+
1120 
+function sel_button(varargin)
1121 
+
1122 
+%SEL_BUTTON     A Callback function. It performs the operations needed
1123 
+%               when vector components are selected.
1124 
+%
1125 
+% See also SEL_COMP
1126 
+%
1127 
+
1128 
+if nargin == 1
1129 
+  LOG=1;
1130 
+  pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1131 
+  string=getfield(get(pre_h,'UserData'),'comp_names_h');
1132 
+  string=getfield(get(string,'String'),{str2num(varargin{1})});
1133 
+  set(0,'CurrentFigure',pre_h);
1134 
+else
1135 
+  LOG=0;
1136 
+  val=get(getfield(get(gcf,'UserData'),'comp_names_h'),'Value');
1137 
+end
1138 
+
1139 
+sel_button_h=getfield(get(gcf,'UserData'),'sel_button_h');
1140 
+sel_comps_h=getfield(get(gcf,'UserData'),'sel_comps_h');
1141 
+comp_names_h=getfield(get(gcf,'UserData'),'comp_names_h');
1142 
+if ~LOG
1143 
+  string=getfield(get(comp_names_h,'String'),{get(comp_names_h,'Value')});
1144 
+end
1145 
+tmp_string=get(sel_comps_h,'String');
1146 
+
1147 
+if iscell(tmp_string)
1148 
+
1149 
+  for i=1:length(string)
1150 
+    if ~any(strcmp(string{i},tmp_string))
1151 
+      tmp_string=cat(1,tmp_string,string(i));
1152 
+    end
1153 
+  end
1154 
+  string=tmp_string;
1155 
+end
1156 
+
1157 
+set(sel_comps_h,'String',string);
1158 
+set(comp_names_h,'Value',[]);
1159 
+sel_comp;
1160 
+if ~LOG
1161 
+  data=get(gcf,'UserData');
1162 
+  data.LOG{length(data.LOG)+1}='% Select components';
1163 
+  data.LOG{length(data.LOG)+1}=sprintf('preprocess(''sel_button'',''%s'');',...
1164 
+                                        num2str(val));
1165 
+  set(gcf,'UserData',data);
1166 
+end
1167 
+
1168 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1169 
+
1170 
+function clear_button(varargin)
1171 
+
1172 
+%CLEAR_BUTTON  Function callback evaluated when a 'Clear'-button is
1173 
+%              pressed. It removes texts from the 'selected components'
1174 
+%              -window and the 'selected component data' -window and
1175 
+%              clears the 'histogram' -axis.
1176 
+%
1177 
+%
1178 
+
1179 
+if nargin==1
1180 
+  LOG=1;
1181 
+  pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1182 
+  set(0,'CurrentFigure',pre_h);
1183 
+else
1184 
+  LOG=0;
1185 
+end
1186 
+
1187 
+sel_comp_h=getfield(get(gcf,'UserData'),'sel_comp_h');
1188 
+sel_cdata_h=getfield(get(gcf,'UserData'),'sel_cdata_h');
1189 
+sel_cplot_h=getfield(get(gcf,'UserData'),'sel_cplot_h');
1190 
+sel_chist_h=getfield(get(gcf,'UserData'),'sel_chist_h');
1191 
+vector_h=getfield(get(gcf,'UserData'),'vector_h');
1192 
+
1193 
+set(sel_comp_h,'Value',1);
1194 
+set(sel_cdata_h,'String',' ');
1195 
+subplot(sel_chist_h);
1196 
+hold off;
1197 
+cla;
1198 
+
1199 
+selected=getfield(get(gcf,'UserData'),'selected_vects');
1200 
+dims=size(getfield(getfield(get(gcf,'UserData'),'sData'),'data'));
1201 
+vectors=zeros(1,dims(1));
1202 
+vectors(selected)=1;
1203 
+subplot(vector_h);
1204 
+draw_vectors(vectors,vector_h);
1205 
+if ~LOG
1206 
+  data=get(gcf,'UserData');
1207 
+  data.LOG{length(data.LOG)+1}='% Remove components from the selected list.';
1208 
+  data.LOG{length(data.LOG)+1}='preprocess(''clear_button'',''foo'');';
1209 
+  set(gcf,'UserData',data);
1210 
+end
1211 
+
1212 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1213 
+
1214 
+function sel_comp(varargin)
1215 
+
1216 
+%SEL_COMP  performs the operations needed when vector components are
1217 
+%          chosen. It writes maxima, minima, mean and standard deviation
1218 
+%          of the chosen component to a text box window and draws a
1219 
+%          histogram of the chosen component of selected vectors'
1220 
+%
1221 
+%
1222 
+
1223 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1224 
+set(0,'CurrentFigure',pre_h);
1225 
+sel_comp_h=getfield(get(pre_h,'UserData'),'sel_comp_h');
1226 
+
1227 
+if nargin == 1
1228 
+  set(sel_comp_h,'Value',str2num(varargin{1}));
1229 
+elseif ~isempty(gcbo)
1230 
+  no=get(sel_comp_h,'Value');
1231 
+  data=get(gcf,'UserData');
1232 
+  data.LOG{length(data.LOG)+1}='% Select one component';
1233 
+  data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''sel_comp'',''',...
1234 
+                                      num2str(no),''');');
1235 
+  set(gcf,'UserData',data);
1236 
+end
1237 
+
1238 
+pro_tools('c_stat');
1239 
+pro_tools('plot_hist');
1240 
+data=get(gcf,'UserData');
1241 
+sData=data.sData;
1242 
+vector_h=data.vector_h;
1243 
+len=length(sData.data(:,1));
1244 
+vects=zeros(1,len);
1245 
+vects(data.selected_vects)=1;
1246 
+draw_vectors(vects,vector_h);
1247 
+
1248 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1249 
+
1250 
+function cplot_mimema
1251 
+
1252 
+global no_of_sc
1253 
+
1254 
+sData=getfield(get(gcf,'UserData'),'sData');
1255 
+sel_cplot_h=getfield(get(gcf,'UserData'),'sel_cplot_h');
1256 
+selected=getfield(get(gcf,'UserData'),'selected_vects');
1257 
+
1258 
+set(sel_cplot_h,'YLim',[0 length(sData.data(1,:))+1]);
1259 
+
1260 
+subplot(sel_cplot_h);
1261 
+hold off;
1262 
+cla;
1263 
+hold on;
1264 
+
1265 
+for i=1:length(sData.data(1,:))
1266 
+  Max=max(sData.data(:,i));
1267 
+  Min=min(sData.data(:,i));
1268 
+  tmp=sData.data(selected,i);
1269 
+
1270 
+  selMax=max(tmp);
1271 
+  selMin=min(tmp);
1272 
+  Mean=abs(mean(tmp(find(~isnan(tmp)))));
1273 
+  Median=abs(median(tmp(find(~isnan(tmp)))));
1274 
+
1275 
+  if Max ~= Min & ~all(isnan(sData.data(:,i)))
1276 
+
1277 
+    if rem(i,no_of_sc)   % no_of_sc is defined in the beginning of this file...
1278 
+
1279 
+      line([abs(selMin-Min)/(Max-Min) (selMax-Min)/(Max-Min)],...
1280 
+           [i i],'Color','black');
1281 
+      plot(abs(Mean-Min)/(Max-Min),i,'oblack');
1282 
+      plot(abs(Median-Min)/(Max-Min),i,'xblack');
1283 
+    else
1284 
+      line([abs(selMin-Min)/(Max-Min) (selMax-Min)/(Max-Min)],...
1285 
+           [i i],'Color','black','LineWidth',2);
1286 
+      plot(abs(Mean-Min)/(Max-Min),i,'oblack','LineWidth',2);
1287 
+      plot(abs(Median-Min)/(Max-Min),i,'xblack','LineWidth',2);
1288 
+    end
1289 
+  else
1290 
+
1291 
+    if rem(i,no_of_sc)     % N is defined in the beginning of this file.
1292 
+
1293 
+      plot(mean(get(gca,'XLim')),i,'oblack');
1294 
+      plot(mean(get(gca,'XLim')),i,'xblack');
1295 
+    else
1296 
+      plot(mean(get(gca,'XLim')),i,'oblack','LineWidth',2);
1297 
+      plot(mean(get(gca,'XLim')),i,'xblack','LineWidth',2);
1298 
+    end
1299 
+  end
1300 
+end
1301 
+
1302 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1303 
+
1304 
+
1305 
+function bool=set_sD_stats
1306 
+
1307 
+%SET_SD_STATS Writes the data set names to popup menu.
1308 
+%
1309 
+%
1310 
+
1311 
+bool=1;
1312 
+data=get(gcf,'UserData');
1313 
+
1314 
+for i=1:length(data.sD_set)
1315 
+ % if ~isvalid_var_name({data.sD_set(i).name})
1316 
+ %   close_preprocess;
1317 
+ %   bool=0;
1318 
+ %   return;
1319 
+ % end
1320 
+  string{i}=cat(2,sprintf('#%d: ',i),data.sD_set(i).name);
1321 
+end
1322 
+
1323 
+set(data.sD_set_h,'String',string);
1324 
+data.sData=data.sD_set(get(data.sD_set_h,'Value'));
1325 
+data.sData.MODIFIED=0;
1326 
+data.sData.INDEX=1;
1327 
+set(gcf,'UserData',data);
1328 
+write_sD_stats;
1329 
+
1330 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1331 
+
1332 
+function write_sD_stats
1333 
+
1334 
+%WRITE_SD_STATS  writes data's name, length and dimension to text box.
1335 
+%
1336 
+%
1337 
+
1338 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1339 
+
1340 
+
1341 
+sD_name_h=getfield(get(pre_h,'UserData'),'sD_name_h');
1342 
+sData=getfield(get(pre_h,'UserData'),'sData');
1343 
+dims=size(sData.data);
1344 
+string{1}=cat(2,'Name:   ',sData.name);
1345 
+string{2}=cat(2,'Length: ',sprintf('%d',dims(1)));
1346 
+string{3}=cat(2,'Dim:     ',sprintf('%d',dims(2)));
1347 
+
1348 
+set(sD_name_h,'String',string);
1349 
+set(sD_name_h,'HorizontalAlignment','left');
1350 
+
1351 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1352 
+
1353 
+
1354 
+
1355 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1356 
+
1357 
+function sel_sD(varargin)
1358 
+
1359 
+%SEL_SD  sets new data to UserData's 'sData'.
1360 
+%
1361 
+%
1362 
+
1363 
+if nargin==1
1364 
+  LOG=1;
1365 
+  index=str2num(varargin{1});
1366 
+  pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1367 
+  set(0,'CurrentFigure',pre_h);
1368 
+else
1369 
+  LOG=0;
1370 
+end
1371 
+
1372 
+sD_set_h=getfield(get(gcf,'UserData'),'sD_set_h');
1373 
+comp_names_h=getfield(get(gcf,'UserData'),'comp_names_h');
1374 
+vector_h=getfield(get(gcf,'UserData'),'vector_h');
1375 
+vect_mean_h=getfield(get(gcf,'UserData'),'vect_mean_h');
1376 
+
1377 
+if ~LOG
1378 
+  index=get(sD_set_h,'Value');
1379 
+end
1380 
+data=get(gcf,'UserData');
1381 
+data.undo = [];
1382 
+INDEX=data.sData.INDEX;
1383 
+data.sData=rmfield(data.sData,'MODIFIED');
1384 
+data.sData=rmfield(data.sData,'INDEX');
1385 
+
1386 
+tmp=data.sD_set(index);
1387 
+tmp.MODIFIED=0;
1388 
+tmp.INDEX=index;
1389 
+data.sD_set(INDEX)=data.sData;
1390 
+data.sData=tmp;
1391 
+
1392 
+len=getfield(size(tmp.data),{1});
1393 
+
1394 
+data.selected_vects=find(ones(1,len));
1395 
+if ~LOG
1396 
+  data.LOG{length(data.LOG)+1}='% Select a new data set.';
1397 
+  data.LOG{length(data.LOG)+1}=sprintf('preprocess(''sel_sD'',''%s'');',...
1398 
+                                        num2str(index));
1399 
+end
1400 
+set(gcf,'UserData',data);
1401 
+write_sD_stats;
1402 
+set_compnames(tmp,comp_names_h);
1403 
+draw_vectors(ones(1,len),vector_h);
1404 
+vect_means(tmp,vect_mean_h,data.selected_vects);
1405 
+clear_button;
1406 
+sel_comp;
1407 
+cplot_mimema;
1408 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1409 
+
1410 
+function indices=get_indices
1411 
+
1412 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1413 
+
1414 
+comp_names_h=getfield(get(pre_h,'UserData'),'comp_names_h');
1415 
+indices = get(comp_names_h,'Value');
1416 
+
1417 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1418 
+
1419 
+
1420 
+
1421 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1422 
+
1423 
+function sD_management(varargin)
1424 
+
1425 
+if nargin ~= 1
1426 
+  pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1427 
+  preh_udata=get(pre_h,'UserData');
1428 
+  preh_udata.LOG{length(preh_udata.LOG)+1}=...
1429 
+           '% Starting the ''Data Set Management'' -window...';
1430 
+  preh_udata.LOG{length(preh_udata.LOG)+1}=...
1431 
+                 'preprocess(''sD_management'',''foo'');';
1432 
+  set(pre_h,'UserData',preh_udata);
1433 
+end
1434 
+
1435 
+man_h=findobj(get(0,'Children'),'Tag','Management');
1436 
+if ~isempty(man_h)
1437 
+  figure(man_h);
1438 
+  return;
1439 
+end
1440 
+
1441 
+h0 = figure('BackingStore','off', ...
1442 
+	'Color',[0.8 0.8 0.8], ...
1443 
+	'Name','Data Set Management', ...
1444 
+	'PaperPosition',[18 180 576 432], ...
1445 
+	'PaperUnits','points', ...
1446 
+	'Position',[753 523 324 470], ...
1447 
+	'RendererMode','manual', ...
1448 
+	'Tag','Management');
1449 
+h1 = uicontrol('Parent',h0, ...
1450 
+	'Units','normalized', ...
1451 
+	'BackgroundColor',[1 1 1], ...
1452 
+	'FontWeight','demi', ...
1453 
+	'HorizontalAlignment','left', ...
1454 
+	'ListboxTop',0, ...
1455 
+	'Max',2, ...
1456 
+	'Position',[0.02777777777777778 0.0723404255319149 0.7716049382716049 0.1914893617021277], ...
1457 
+	'String',' ', ...
1458 
+	'Style','edit', ...
1459 
+	'Tag','EditText1');
1460 
+
1461 
+data.new_c_name_h = h1;
1462 
+
1463 
+h1 = uicontrol('Parent',h0, ...
1464 
+	'Callback','preprocess rename comp',...
1465 
+	'Units','normalized', ...
1466 
+	'FontSize',6, ...
1467 
+	'FontWeight','demi', ...
1468 
+	'ListboxTop',0, ...
1469 
+	'Position',[0.8240740740740741 0.2106382978723404 0.154320987654321 0.05319148936170213], ...
1470 
+	'String','RENAME', ...
1471 
+	'Tag','Pushbutton1');
1472 
+
1473 
+h1 = uicontrol('Parent',h0, ...
1474 
+	'Callback','preprocess close_sD',...
1475 
+	'Units','normalized', ...
1476 
+	'FontWeight','demi', ...
1477 
+	'ListboxTop',0, ...
1478 
+	'Position',[0.8240740740740741 0.01914893617021277 0.154320987654321 0.05319148936170213], ...
1479 
+	'String','CLOSE', ...
1480 
+	'Tag','Pushbutton2');
1481 
+h1 = uicontrol('Parent',h0, ...
1482 
+	'Units','normalized', ...
1483 
+	'BackgroundColor',[0.8 0.8 0.8], ...
1484 
+	'FontWeight','demi', ...
1485 
+	'HorizontalAlignment','left', ...
1486 
+	'ListboxTop',0, ...
1487 
+	'Position',[0.02777777777777778 0.2680851063829787 0.345679012345679 0.02978723404255319], ...
1488 
+	'String','COMPONENTS:', ...
1489 
+	'Style','text', ...
1490 
+	'Tag','StaticText1');
1491 
+h1 = uicontrol('Parent',h0, ...
1492 
+	'Units','normalized', ...
1493 
+	'BackgroundColor',[1 1 1], ...
1494 
+	'HorizontalAlignment','left', ...
1495 
+	'Position',[0.02777777777777778 0.3170212765957447 0.3549382716049382 0.5319148936170213], ...
1496 
+	'String',' ', ...
1497 
+	'Style','listbox', ...
1498 
+	'Tag','Listbox1', ...
1499 
+	'Value',1);
1500 
+
1501 
+data.sets_h=h1;
1502 
+
1503 
+h1 = uicontrol('Parent',h0, ...
1504 
+	'Units','normalized', ...
1505 
+	'BackgroundColor',[1 1 1], ...
1506 
+	'HorizontalAlignment','left', ...
1507 
+	'Position',[0.6234567901234568 0.3170212765957447 0.3549382716049382 0.5319148936170213], ...
1508 
+	'String',' ', ...
1509 
+	'Style','listbox', ...
1510 
+	'Tag','Listbox2', ...
1511 
+	'Value',1);
1512 
+
1513 
+
1514 
+data.variables_h = h1;
1515 
+
1516 
+h1 = uicontrol('Parent',h0, ...
1517 
+	'Callback','preprocess export',...
1518 
+	'Units','normalized', ...
1519 
+	'FontWeight','demi', ...
1520 
+	'ListboxTop',0, ...
1521 
+	'Position',[0.4259259259259259 0.551063829787234 0.154320987654321 0.0425531914893617], ...
1522 
+	'String','->', ...
1523 
+	'Tag','Pushbutton4');
1524 
+
1525 
+h1 = uicontrol('Parent',h0, ...
1526 
+	'Callback','preprocess import',...
1527 
+	'Units','normalized', ...
1528 
+	'FontWeight','demi', ...
1529 
+	'ListboxTop',0, ...
1530 
+	'Position',[0.4259259259259259 0.625531914893617 0.154320987654321 0.0425531914893617], ...
1531 
+	'String','<-', ...
1532 
+	'Tag','Pushbutton3');
1533 
+
1534 
+
1535 
+
1536 
+h1 = uicontrol('Parent',h0, ...
1537 
+	'Units','normalized', ...
1538 
+	'BackgroundColor',[0.8 0.8 0.8], ...
1539 
+	'FontWeight','demi', ...
1540 
+	'HorizontalAlignment','left', ...
1541 
+	'ListboxTop',0, ...
1542 
+	'Position',[0.02777777777777778 0.8531914893617022 0.2993827160493827 0.02978723404255319], ...
1543 
+	'String','DATA SETS', ...
1544 
+	'Style','text', ...
1545 
+	'Tag','StaticText2');
1546 
+
1547 
+h1 = uicontrol('Parent',h0, ...
1548 
+	'Units','normalized', ...
1549 
+	'BackgroundColor',[0.8 0.8 0.8], ...
1550 
+	'FontWeight','demi', ...
1551 
+	'HorizontalAlignment','left', ...
1552 
+	'ListboxTop',0, ...
1553 
+	'Position',[0.6234567901234568 0.8531914893617022 0.2561728395061728 0.02978723404255319], ...
1554 
+	'String','WORKSPACE', ...
1555 
+	'Style','text', ...
1556 
+	'Tag','StaticText3');
1557 
+
1558 
+h1 = uicontrol('Parent',h0, ...
1559 
+	'Callback','preprocess rename set',...
1560 
+	'Units','normalized', ...
1561 
+	'BackgroundColor',[1 1 1], ...
1562 
+	'HorizontalAlignment','left', ...
1563 
+	'ListboxTop',0, ...
1564 
+	'Position',[0.1820987654320987 0.9127659574468086 0.7808641975308641 0.0425531914893617], ...
1565 
+	'Style','edit', ...
1566 
+	'Tag','EditText2');
1567 
+
1568 
+data.new_name_h = h1;
1569 
+
1570 
+
1571 
+h1 = uicontrol('Parent',h0, ...
1572 
+	'Units','normalized', ...
1573 
+	'BackgroundColor',[0.8 0.8 0.8], ...
1574 
+	'FontWeight','demi', ...
1575 
+	'HorizontalAlignment','left', ...
1576 
+	'ListboxTop',0, ...
1577 
+	'Position',[0.02777777777777778 0.9127659574468086 0.1388888888888889 0.02978723404255319], ...
1578 
+	'String','NAME:', ...
1579 
+	'Style','text', ...
1580 
+	'Tag','StaticText4');
1581 
+
1582 
+
1583 
+ui_h=uimenu('Label','&Tools');
1584 
+uimenu(ui_h,'Label','Copy','Callback','preprocess copy_delete copy');
1585 
+uimenu(ui_h,'Label','Delete','Callback','preprocess copy_delete delete');
1586 
+uimenu(ui_h,'Label','Refresh','Callback','preprocess refresh');
1587 
+
1588 
+set(gcf,'UserData',data);
1589 
+set_var_names;
1590 
+sD_names;
1591 
+sD_stats;
1592 
+
1593 
+
1594 
+
1595 
+%%% Subfunction: set_var_names %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1596 
+
1597 
+function set_var_names
1598 
+
1599 
+
1600 
+variables_h=getfield(get(gcf,'UserData'),'variables_h');
1601 
+value=get(variables_h,'Value');
1602 
+len=evalin('base','length(who)');
1603 
+
1604 
+names=cell(len,1);
1605 
+
1606 
+for i=1:len
1607 
+  string=cat(2,'getfield(who,{',num2str(i),'})');
1608 
+  names(i)=evalin('base',string);
1609 
+end
1610 
+
1611 
+set(variables_h,'String',names);
1612 
+if(value > length(names))
1613 
+  set(variables_h,'Value',1);
1614 
+end
1615 
+
1616 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1617 
+
1618 
+%%% Subfunction: sD_names %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1619 
+
1620 
+function sD_names
1621 
+
1622 
+sets_h=getfield(get(gcf,'UserData'),'sets_h');
1623 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1624 
+
1625 
+sD_set = getfield(get(pre_h,'UserData'),'sD_set');
1626 
+
1627 
+for i=1:length(sD_set)
1628 
+  names{i,1}=cat(2,sprintf('#%d: ',i),sD_set(i).name);
1629 
+end
1630 
+
1631 
+set(sets_h,'String',names);
1632 
+
1633 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1634 
+
1635 
+%%% Subfunction: sD_stats %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1636 
+
1637 
+function sD_stats
1638 
+
1639 
+man_h=findobj(get(0,'Children'),'Tag','Management');
1640 
+c_names_h=getfield(get(man_h,'UserData'),'new_c_name_h');
1641 
+sD_name_h=getfield(get(man_h,'UserData'),'new_name_h');
1642 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1643 
+INDEX=getfield(getfield(get(pre_h,'UserData'),'sData'),'INDEX');
1644 
+MODIFIED=getfield(getfield(get(pre_h,'UserData'),'sData'),'MODIFIED');
1645 
+value=get(getfield(get(man_h,'UserData'),'sets_h'),'Value');
1646 
+
1647 
+if value==INDEX
1648 
+  data=get(pre_h,'UserData');
1649 
+  sData=rmfield(data.sData,[{'INDEX'};{'MODIFIED'}]);
1650 
+  data.sD_set(INDEX)=sData;
1651 
+  data.sData.MODIFIED=0;
1652 
+  set(pre_h,'UserData',data);
1653 
+end
1654 
+
1655 
+sData=getfield(getfield(get(pre_h,'UserData'),'sD_set'),{value});
1656 
+string1=[{sData.name}];
1657 
+
1658 
+
1659 
+set(sD_name_h,'String',string1);
1660 
+set(c_names_h,'String',sData.comp_names);
1661 
+
1662 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1663 
+
1664 
+%%% Subfunction: import %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1665 
+
1666 
+function import(varargin)
1667 
+
1668 
+if nargin==1
1669 
+  LOG=1;
1670 
+  man_h=findobj(get(0,'Children'),'Tag','Management');
1671 
+  set(0,'CurrentFigure',man_h);
1672 
+  name=varargin;
1673 
+else
1674 
+  LOG=0;
1675 
+end
1676 
+
1677 
+variables_h=getfield(get(gcf,'UserData'),'variables_h');
1678 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1679 
+if ~LOG
1680 
+  name=getfield(get(variables_h,'String'),{get(variables_h,'Value')});
1681 
+end
1682 
+errstr='Data to be imported must be real matrix or ''som_data_struct''.';
1683 
+new_sD=evalin('base',name{1});
1684 
+
1685 
+if isempty(pre_h)
1686 
+  errordlg('''Preprocess'' -figure does not exist. Terminating program...');
1687 
+  close_preprocess;
1688 
+  return;
1689 
+end
1690 
+
1691 
+if isstr(new_sD) | (~isstruct(new_sD) & ~isreal(new_sD))
1692 
+  errordlg(errstr);
1693 
+  return;
1694 
+elseif isstruct(new_sD) & length(new_sD) > 1
1695 
+  errordlg(errstr)
1696 
+  return;
1697 
+elseif ~isstruct(new_sD)
1698 
+  new_sD=som_data_struct(new_sD);
1699 
+  new_sD.name=name{1};
1700 
+end
1701 
+
1702 
+new_sD_names=fieldnames(new_sD);
1703 
+right_names=fieldnames(som_data_struct(1));
1704 
+for i=1:length(new_sD_names)
1705 
+  if ~any(strcmp(new_sD_names(i),right_names));
1706 
+    errordlg(errstr);
1707 
+    return;
1708 
+  end
1709 
+end
1710 
+
1711 
+data=get(pre_h,'UserData');
1712 
+data.sD_set(length(data.sD_set) + 1)=new_sD;
1713 
+if ~LOG
1714 
+  data.LOG{length(data.LOG)+1}='% Import a data set from the workspace.';
1715 
+  data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''import'',''',...
1716 
+                                    name{1},''');');
1717 
+end
1718 
+set(pre_h,'UserData',data);
1719 
+sD_names;
1720 
+sD_stats;
1721 
+old =gcf;
1722 
+set(0,'CurrentFigure',pre_h);
1723 
+set_sD_stats;
1724 
+set(0,'CurrentFigure',old);
1725 
+
1726 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1727 
+
1728 
+%%% Subfunction: export %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1729 
+
1730 
+function export(varargin)
1731 
+
1732 
+if nargin == 1
1733 
+  LOG=1;
1734 
+  man_h=findobj(get(0,'Children'),'Tag','Management');
1735 
+  set(0,'CurrentFigure',man_h);
1736 
+  index=str2num(varargin{1});
1737 
+else
1738 
+  LOG=0;
1739 
+end
1740 
+
1741 
+sets_h=getfield(get(gcf,'UserData'),'sets_h');
1742 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1743 
+
1744 
+if ~LOG
1745 
+  index=get(sets_h,'Value');
1746 
+end
1747 
+
1748 
+if isempty(pre_h)
1749 
+  errordlg('''Preprocess''-figure does not exist. Terminating program...');
1750 
+  close(findobj(get(0,'Children'),'Tag','Management'));
1751 
+  close(findobj(get(0,'Children'),'Tag','PlotWin'));
1752 
+  return;
1753 
+end
1754 
+
1755 
+sData=getfield(getfield(get(pre_h,'UserData'),'sD_set'),{index});
1756 
+
1757 
+if ~isvalid_var_name({sData.name})
1758 
+  return;
1759 
+end
1760 
+
1761 
+assignin('base',sData.name,sData);
1762 
+disp(sprintf('Data set ''%s'' is set to the workspace.',sData.name));
1763 
+if ~LOG
1764 
+  data=get(pre_h,'UserData');
1765 
+  data.LOG{length(data.LOG)+1}='% Export a data set to the workspace.';
1766 
+  data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''export'',''',...
1767 
+                                   num2str(index),''');');
1768 
+  set(pre_h,'UserData',data);
1769 
+end
1770 
+set_var_names;
1771 
+
1772 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1773 
+
1774 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1775 
+%%% Subfunction: rename %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1776 
+
1777 
+function rename(arg)
1778 
+
1779 
+i=1;
1780 
+while i <= length(arg) & arg(i) ~= ' '
1781 
+  i=i+1;
1782 
+end
1783 
+
1784 
+arg2=arg(i+1:length(arg));
1785 
+arg=arg(1:i-1);
1786 
+if ~isempty(arg2)
1787 
+  LOG=1;
1788 
+  i=1;
1789 
+  if arg2(1) ~= '{'
1790 
+    while i <= length(arg2) & arg2(i) ~= ' '
1791 
+      i=i+1;
1792 
+    end
1793 
+    index=str2num(arg2(i+1:length(arg2)));
1794 
+    arg2=arg2(1:i-1);
1795 
+  else
1796 
+    while i <= length(arg2) & arg2(i) ~= '}'
1797 
+      i=i+1;
1798 
+    end
1799 
+    index=str2num(arg2(i+1:length(arg2)));
1800 
+    arg2=arg2(1:i);
1801 
+  end
1802 
+else
1803 
+  LOG=0;
1804 
+end
1805 
+
1806 
+new_name_h=getfield(get(gcf,'UserData'),'new_name_h');
1807 
+new_c_name_h=getfield(get(gcf,'UserData'),'new_c_name_h');
1808 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1809 
+
1810 
+if isempty(pre_h)
1811 
+  errordlg('''Preprocess'' -figure does not exist. Terminating program...');
1812 
+  close_preprocess;
1813 
+  return;
1814 
+end
1815 
+
1816 
+switch arg
1817 
+  case 'set'
1818 
+   if LOG
1819 
+     name={arg2};
1820 
+   else
1821 
+     name=get(new_name_h,'String');
1822 
+   end
1823 
+   if ~isempty(name{1}) & ~any(isspace(name{1}))
1824 
+     if ~isvalid_var_name(name)
1825 
+       sD_stats;
1826 
+       return;
1827 
+     end
1828 
+     if ~LOG
1829 
+       index=get(getfield(get(gcf,'UserData'),'sets_h'),'Value');
1830 
+     end
1831 
+     data=get(pre_h,'UserData');
1832 
+     tmp_set.name=name{1};
1833 
+     data.sD_set(index).name=name{1};
1834 
+     if data.sData.INDEX == index
1835 
+       data.sData.name=name{1};
1836 
+     end
1837 
+     if ~LOG
1838 
+       data.LOG{length(data.LOG)+1}='% Rename a data set.';
1839 
+       data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''rename'',''set ',...
1840 
+                                                       name{1},' ',...
1841 
+                                                       num2str(index),...
1842 
+                                                       ''');');
1843 
+     end
1844 
+
1845 
+     set(pre_h,'UserData',data);
1846 
+     sD_names;
1847 
+     string=get(data.sD_set_h,'String');
1848 
+     string{index}=cat(2,sprintf('#%d: ',index),name{1});
1849 
+     set(data.sD_set_h,'String',string);
1850 
+     string=get(data.sD_name_h,'String');
1851 
+     string{1}=cat(2,'Name:   ',name{1});
1852 
+     if index==data.sData.INDEX
1853 
+       set(data.sD_name_h,'String',string);
1854 
+     end
1855 
+   else
1856 
+     sD_stats;
1857 
+   end
1858 
+  case 'comp'
1859 
+   if ~LOG
1860 
+     names=get(new_c_name_h,'String');
1861 
+     index=get(getfield(get(gcf,'UserData'),'sets_h'),'Value');
1862 
+   else
1863 
+     names=eval(arg2);
1864 
+   end
1865 
+   if check_cell_names(names)
1866 
+     data=get(pre_h,'UserData');
1867 
+     sData=data.sD_set(index);
1868 
+     if length(sData.comp_names)==length(names)
1869 
+       data.sD_set(index).comp_names=names;
1870 
+       if index == data.sData.INDEX
1871 
+         for i=1:length(names)
1872 
+           names{i}=cat(2,sprintf('#%d: ',i),names{i});
1873 
+         end
1874 
+         set(data.comp_names_h,'String',names);
1875 
+         set(data.sel_comp_h,'String',names);
1876 
+       end
1877 
+       if ~LOG
1878 
+         data.LOG{length(data.LOG)+1}='% Rename components.';
1879 
+         str='preprocess(''rename'',''comp {';
1880 
+         for i=1:length(names)-1
1881 
+           str=cat(2,str,'''''',names{i},''''',');
1882 
+         end
1883 
+         str=cat(2,str,'''''',names{length(names)},'''''} ',...
1884 
+                 num2str(index),''');');
1885 
+         data.LOG{length(data.LOG)+1}=str;
1886 
+       else
1887 
+         set(new_c_name_h,'String',names);
1888 
+       end
1889 
+       set(pre_h,'UserData',data);
1890 
+     else
1891 
+       errordlg('There are less components in data.');
1892 
+       sD_stats;
1893 
+       return;
1894 
+     end
1895 
+   else
1896 
+     sD_stats;
1897 
+   end
1898 
+end
1899 
+
1900 
+%%% Subfunction: check_cell_names %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1901 
+
1902 
+function bool=check_cell_names(names)
1903 
+
1904 
+bool = 1;
1905 
+
1906 
+if isempty(names)
1907 
+  bool= 0;
1908 
+  return;
1909 
+end
1910 
+for i=1:length(names)
1911 
+  if isempty(names{i}) | isspace(names{i})
1912 
+    bool = 0;
1913 
+    return;
1914 
+  end
1915 
+end
1916 
+
1917 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1918 
+
1919 
+%%% Subfunction: isvalid_var_name %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1920 
+
1921 
+function bool=isvalid_var_name(name)
1922 
+
1923 
+bool=1;
1924 
+
1925 
+tmp=name{1};
1926 
+if ~((tmp(1)>='a' & tmp(1)<='z') | (tmp(1)>='A' & tmp(1)<='Z'))
1927 
+  errordlg('Invalid name.');
1928 
+  bool=0;
1929 
+  return;
1930 
+end
1931 
+for j=1:length(tmp)
1932 
+  if ~((tmp(j)>='a' & tmp(j)<='z') | ...
1933 
+       (tmp(j)>='A' & tmp(j)<='Z') | ...
1934 
+       (j>1 & tmp(j) == '_') | ...
1935 
+       (tmp(j)>='0' & tmp(j) <= '9')) | tmp(j) == '.'
1936 
+    errordlg('Invalid name.');
1937 
+    bool=0;
1938 
+    return;
1939 
+  end
1940 
+  if j == length(tmp) & tmp(j) == '_'
1941 
+    errordlg('Invalid name.');
1942 
+    bool=0;
1943 
+    return;
1944 
+  end
1945 
+end
1946 
+
1947 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1948 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1949 
+
1950 
+%%% Subfunction: copy_delete %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1951 
+
1952 
+function copy_delete(arg)
1953 
+
1954 
+i=1;
1955 
+while i <= length(arg) & arg(i) ~= ' '
1956 
+  i=i+1;
1957 
+end
1958 
+
1959 
+arg2=arg(i+1:length(arg));
1960 
+arg=arg(1:i-1);
1961 
+
1962 
+if ~isempty(arg2)
1963 
+  index=str2num(arg2);
1964 
+  LOG=1;
1965 
+else
1966 
+  LOG=0;
1967 
+end
1968 
+
1969 
+sets_h=getfield(get(gcf,'UserData'),'sets_h');
1970 
+if ~LOG
1971 
+  index=get(sets_h,'Value');
1972 
+end
1973 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
1974 
+
1975 
+if isempty(pre_h)
1976 
+  errordlg('''Preprocess'' -figure does not exist. Terminating program.');
1977 
+  close_preprocess;
1978 
+  return;
1979 
+end
1980 
+
1981 
+switch arg
1982 
+  case 'copy'
1983 
+   data=get(pre_h,'UserData');
1984 
+   data.sD_set(length(data.sD_set)+1)=data.sD_set(index);
1985 
+   if ~LOG
1986 
+     data.LOG{length(data.LOG)+1}='% Copy a data set.';
1987 
+     data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''copy_delete'',''',...
1988 
+                                      'copy ',num2str(index),''');');
1989 
+   end
1990 
+   set(pre_h,'UserData',data);
1991 
+   sD_names;
1992 
+   old=gcf;
1993 
+   set(0,'CurrentFigure',pre_h);
1994 
+   set_sD_stats;
1995 
+   set(0,'CurrentFigure',old);
1996 
+  case 'delete'
1997 
+   if length(get(sets_h,'String')) == 1
1998 
+     msgbox('No data left. Closing program...')
1999 
+     close_preprocess;
2000 
+     return;
2001 
+   end
2002 
+   data=get(pre_h,'UserData');
2003 
+   if ~isempty(data.undo) &  any(strcmp('index',fieldnames(data.undo)))
2004 
+     if data.undo.index > index
2005 
+       data.undo.index = data.undo.index-1;
2006 
+     elseif data.undo.index==index;
2007 
+       data.undo=[];
2008 
+     end
2009 
+   end
2010 
+   set1=data.sD_set(1:index-1);
2011 
+   set2=data.sD_set(index+1:length(data.sD_set));
2012 
+
2013 
+   if ~isempty(set1)
2014 
+     data.sD_set=[set1 set2];
2015 
+   else
2016 
+     data.sD_set=set2;
2017 
+   end
2018 
+   if ~LOG
2019 
+     data.LOG{length(data.LOG)+1}='% Delete a data set.';
2020 
+     data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''copy_delete'',''',...
2021 
+                                      'delete ',num2str(index),''');');
2022 
+   end
2023 
+   set(pre_h,'UserData',data);
2024 
+
2025 
+   set(sets_h,'Value',1);
2026 
+   sD_names;
2027 
+   sD_stats;
2028 
+   old = gcf;
2029 
+   set(0,'CurrentFigure',pre_h);
2030 
+
2031 
+   for i=1:length(data.sD_set)
2032 
+     string{i}=cat(2,sprintf('#%d: ',i),data.sD_set(i).name);
2033 
+   end
2034 
+
2035 
+   set(data.sD_set_h,'String',string);
2036 
+   data.sData=data.sD_set(get(data.sD_set_h,'Value'));
2037 
+   data.sData.MODIFIED=0;
2038 
+   data.sData.INDEX=1;
2039 
+   set(gcf,'UserData',data);
2040 
+   write_sD_stats;
2041 
+
2042 
+   sData=getfield(get(gcf,'UserData'),'sData');
2043 
+   if sData.INDEX > index
2044 
+     value=get(getfield(get(gcf,'UserData'),'sD_set_h'),'Value');
2045 
+     set(getfield(get(gcf,'UserData'),'sD_set_h'),'Value',value-1);
2046 
+     sData.INDEX = sData.INDEX -1;
2047 
+   elseif sData.INDEX == index
2048 
+     set(getfield(get(gcf,'UserData'),'sD_set_h'),'Value',1);
2049 
+   end
2050 
+
2051 
+   sel_sD;
2052 
+   set(0,'CurrentFigure',old);
2053 
+end
2054 
+
2055 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2056 
+
2057 
+function clipping(varargin)
2058 
+
2059 
+if nargin ~= 1
2060 
+  pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
2061 
+  preh_udata=get(pre_h,'UserData');
2062 
+  preh_udata.LOG{length(preh_udata.LOG)+1}=...
2063 
+        '% Starting the ''Clipping'' -window...';
2064 
+  preh_udata.LOG{length(preh_udata.LOG)+1}='preprocess(''clipping'',''foo'');';
2065 
+  set(pre_h,'UserData',preh_udata);
2066 
+end
2067 
+
2068 
+clip_h=findobj(get(0,'Children'),'Tag','Clipping');
2069 
+
2070 
+if ~isempty(clip_h)
2071 
+  figure(clip_h);
2072 
+  return;
2073 
+end
2074 
+
2075 
+h0 = figure('Color',[0.8 0.8 0.8], ...
2076 
+	'PaperPosition',[18 180 575 432], ...
2077 
+	'PaperUnits','points', ...
2078 
+	'Position',[718 389 300 249], ...
2079 
+	'Tag','Clipping');
2080 
+
2081 
+h1 = uicontrol('Parent',h0, ...
2082 
+	'Units','normalized', ...
2083 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
2084 
+	'ListboxTop',0, ...
2085 
+	'Position',[0.03 0.03614457831325301 0.4666666666666667 0.9236947791164658], ...
2086 
+	'Style','frame', ...
2087 
+	'Tag','Frame1');
2088 
+
2089 
+h1 = uicontrol('Parent',h0, ...
2090 
+	'Units','normalized', ...
2091 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2092 
+	'ListboxTop',0, ...
2093 
+	'Position',[0.05333333333333334 0.5983935742971887 0.42 0.3333333333333333], ...
2094 
+	'Style','frame', ...
2095 
+	'Tag','Frame2');
2096 
+
2097 
+h1 = uicontrol('Parent',h0, ...
2098 
+	'Units','normalized', ...
2099 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2100 
+	'ListboxTop',0, ...
2101 
+	'Style','frame', ...
2102 
+	'Position',[0.05333333333333334 0.33 0.42 0.24], ...
2103 
+	'Tag','Frame3');
2104 
+
2105 
+h1 = uicontrol('Parent',h0, ...
2106 
+	'Units','normalized', ...
2107 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2108 
+	'ListboxTop',0, ...
2109 
+	'Style','frame', ...
2110 
+	'Position',[0.05333333333333334 0.06 0.42 0.24],...
2111 
+	'Tag','Frame4');
2112 
+
2113 
+h1 = uicontrol('Parent',h0, ...
2114 
+	'Units','normalized', ...
2115 
+	'ListboxTop',0, ...
2116 
+	'Position',[0.5133333333333334 0.6385542168674698 0.4666666666666667 0.321285140562249], ...
2117 
+	'Style','frame', ...
2118 
+	'Tag','Frame5');
2119 
+
2120 
+h1 = uicontrol('Parent',h0, ...
2121 
+	'Units','normalized', ...
2122 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2123 
+	'ListboxTop',0, ...
2124 
+	'Position',[0.5366666666666667 0.6666666666666666 0.42 0.2650602409638554], ...
2125 
+	'Style','frame', ...
2126 
+	'Tag','Frame6');
2127 
+
2128 
+h1 = uicontrol('Parent',h0, ...
2129 
+	'Units','normalized', ...
2130 
+	'BackgroundColor',[1 1 1], ...
2131 
+	'ListboxTop',0, ...
2132 
+	'Position',[0.31 0.823293172690763 0.15 0.09638554216867469], ...
2133 
+	'Style','edit', ...
2134 
+	'Tag','EditText1');
2135 
+
2136 
+data.big_val_h = h1;
2137 
+
2138 
+h1 = uicontrol('Parent',h0, ...
2139 
+	'Units','normalized', ...
2140 
+	'BackgroundColor',[1 1 1], ...
2141 
+	'ListboxTop',0, ...
2142 
+	'Position',[0.31 0.7148594377510039 0.15 0.09638554216867469], ...
2143 
+	'Style','edit', ...
2144 
+	'Tag','EditText2');
2145 
+
2146 
+data.small_val_h = h1;
2147 
+
2148 
+h1 = uicontrol('Parent',h0, ...
2149 
+	'Units','normalized', ...
2150 
+	'BackgroundColor',[1 1 1], ...
2151 
+	'ListboxTop',0, ...
2152 
+	'Position',[0.31 0.606425702811245 0.15 0.09638554216867469], ...
2153 
+	'Style','edit', ...
2154 
+	'Tag','EditText3');
2155 
+
2156 
+data.equal_val_h=h1;
2157 
+
2158 
+h1 = uicontrol('Parent',h0, ...
2159 
+	'Units','normalized', ...
2160 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2161 
+	'FontSize',6, ...
2162 
+	'FontWeight','demi', ...
2163 
+	'HorizontalAlignment','left', ...
2164 
+	'ListboxTop',0, ...
2165 
+	'Position',[0.06000000000000001 0.8473895582329316 0.22 0.05622489959839357], ...
2166 
+	'String','Bigger than', ...
2167 
+	'Style','text', ...
2168 
+	'Tag','StaticText1');
2169 
+h1 = uicontrol('Parent',h0, ...
2170 
+	'Units','normalized', ...
2171 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2172 
+	'FontSize',6, ...
2173 
+	'FontWeight','demi', ...
2174 
+	'HorizontalAlignment','left', ...
2175 
+	'ListboxTop',0, ...
2176 
+	'Position',[0.06000000000000001 0.7389558232931727 0.24 0.04819277108433735], ...
2177 
+	'String','Smaller than', ...
2178 
+	'Style','text', ...
2179 
+	'Tag','StaticText2');
2180 
+h1 = uicontrol('Parent',h0, ...
2181 
+	'Units','normalized', ...
2182 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2183 
+	'FontSize',6, ...
2184 
+	'FontWeight','demi', ...
2185 
+	'HorizontalAlignment','left', ...
2186 
+	'ListboxTop',0, ...
2187 
+	'Position',[0.06000000000000001 0.610441767068273 0.22 0.07228915662650602], ...
2188 
+	'String','Equal to', ...
2189 
+	'Style','text', ...
2190 
+	'Tag','StaticText3');
2191 
+
2192 
+h1 = uicontrol('Parent',h0, ...
2193 
+	'Units','normalized', ...
2194 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2195 
+	'ListboxTop',0, ...
2196 
+	'Position',[0.07000000000000001 0.465863453815261 0.06333333333333334 0.07228915662650602], ...
2197 
+	'Style','radiobutton', ...
2198 
+	'Value',1,...
2199 
+	'Tag','Radiobutton1');
2200 
+
2201 
+data.and_button_h=h1;
2202 
+
2203 
+h1 = uicontrol('Parent',h0, ...
2204 
+	'Units','normalized', ...
2205 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2206 
+	'ListboxTop',0, ...
2207 
+	'Position',[0.07000000000000001 0.3734939759036144 0.06333333333333334 0.07228915662650602], ...
2208 
+	'Style','radiobutton', ...
2209 
+	'Tag','Radiobutton2');
2210 
+
2211 
+data.or_button_h=h1;
2212 
+
2213 
+h1 = uicontrol('Parent',h0, ...
2214 
+	'Units','normalized', ...
2215 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2216 
+	'FontSize',6, ...
2217 
+	'FontWeight','demi', ...
2218 
+	'HorizontalAlignment','left', ...
2219 
+	'Position',[0.1466666666666667 0.45 0.2333333333333333 0.07228915662650602], ...
2220 
+	'String','AND', ...
2221 
+	'Style','text', ...
2222 
+	'Tag','StaticText4');
2223 
+
2224 
+h1 = uicontrol('Parent',h0, ...
2225 
+	'Units','normalized', ...
2226 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2227 
+	'FontSize',6, ...
2228 
+	'FontWeight','demi', ...
2229 
+	'HorizontalAlignment','left', ...
2230 
+	'ListboxTop',0, ...
2231 
+	'String','OR', ...
2232 
+	'Position',[0.1466666666666667 0.35 0.2333333333333333 0.07228915662650602], ...
2233 
+	'Style','text', ...
2234 
+	'Tag','StaticText5');
2235 
+
2236 
+h1 = uicontrol('Parent',h0, ...
2237 
+	'Units','normalized', ...
2238 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2239 
+	'ListboxTop',0, ...
2240 
+	'Position',[0.07000000000000001 0.1967871485943775 0.06333333333333334 0.07228915662650602], ...
2241 
+	'Style','radiobutton', ...
2242 
+	'Value',1,...
2243 
+	'Tag','Radiobutton3');
2244 
+
2245 
+data.all_button_h=h1;
2246 
+
2247 
+h1 = uicontrol('Parent',h0, ...
2248 
+	'Units','normalized', ...
2249 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2250 
+	'ListboxTop',0, ...
2251 
+	'Position',[0.07000000000000001 0.09236947791164658 0.06333333333333334 0.07228915662650602], ...
2252 
+	'Style','radiobutton', ...
2253 
+	'Tag','Radiobutton4');
2254 
+
2255 
+data.sel_vects_button_h=h1;
2256 
+
2257 
+h1 = uicontrol('Parent',h0, ...
2258 
+	'Units','normalized', ...
2259 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2260 
+	'FontSize',6, ...
2261 
+	'FontWeight','demi', ...
2262 
+	'HorizontalAlignment','left', ...
2263 
+	'ListboxTop',0, ...
2264 
+	'Position',[0.1466666666666667 0.1927710843373494 0.2333333333333333 0.07228915662650602], ...
2265 
+	'String','All vectors', ...
2266 
+	'Style','text', ...
2267 
+	'Tag','StaticText6');
2268 
+h1 = uicontrol('Parent',h0, ...
2269 
+	'Units','normalized', ...
2270 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2271 
+	'FontSize',6, ...
2272 
+	'FontWeight','demi', ...
2273 
+	'HorizontalAlignment','left', ...
2274 
+	'ListboxTop',0, ...
2275 
+	'Position',[0.1466666666666667 0.09638554216867469 0.3133333333333334 0.05622489959839357], ...
2276 
+	'String','Among selected', ...
2277 
+	'Style','text', ...
2278 
+	'Tag','StaticText7');
2279 
+h1 = uicontrol('Parent',h0, ...
2280 
+	'Units','normalized', ...
2281 
+	'BackgroundColor',[1 1 1], ...
2282 
+	'ListboxTop',0, ...
2283 
+	'Position',[0.7866666666666667 0.823293172690763 0.1366666666666667 0.09236947791164658], ...
2284 
+	'Style','edit', ...
2285 
+	'Tag','EditText4');
2286 
+
2287 
+data.replace_val_h=h1;
2288 
+
2289 
+h1 = uicontrol('Parent',h0, ...
2290 
+	'Units','normalized', ...
2291 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2292 
+	'FontSize',6, ...
2293 
+	'FontWeight','demi', ...
2294 
+	'HorizontalAlignment','left', ...
2295 
+	'ListboxTop',0, ...
2296 
+	'Position',[0.5633333333333334 0.8273092369477911 0.2066666666666667 0.07630522088353413], ...
2297 
+	'String','Replace', ...
2298 
+	'Style','text', ...
2299 
+	'Tag','StaticText8');
2300 
+h1 = uicontrol('Parent',h0, ...
2301 
+	'Units','normalized', ...
2302 
+	'FontWeight','demi', ...
2303 
+	'ListboxTop',0, ...
2304 
+	'Position',[0.5700000000000001 0.6827309236947791 0.3566666666666667 0.08032128514056225], ...
2305 
+	'String','Replace', ...
2306 
+	'Tag','Pushbutton1');
2307 
+
2308 
+data.OK_button_h=h1;
2309 
+
2310 
+h1 = uicontrol('Parent',h0, ...
2311 
+	'Units','normalized', ...
2312 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
2313 
+	'Callback','preprocess close_c',...
2314 
+	'FontWeight','demi', ...
2315 
+	'ListboxTop',0, ...
2316 
+	'Position',[0.6633333333333333 0.07228915662650602 0.2833333333333333 0.09638554216867469], ...
2317 
+	'String','Close', ...
2318 
+	'Tag','Pushbutton2');
2319 
+
2320 
+
2321 
+data.state.and=1;
2322 
+data.state.all=1;
2323 
+data.state.big=[];
2324 
+data.state.small=[];
2325 
+data.state.equal=[];
2326 
+data.state.replace=[];
2327 
+
2328 
+set(data.or_button_h,'Callback','preprocess and_or_cb or');
2329 
+set(data.and_button_h,'Callback','preprocess and_or_cb and');
2330 
+set(data.and_button_h,'Value',1);
2331 
+set(data.all_button_h,'Callback','preprocess all_sel_cb all');
2332 
+set(data.sel_vects_button_h,'Callback','preprocess all_sel_cb sel');
2333 
+set(data.big_val_h,'Callback','preprocess set_state_vals big');
2334 
+set(data.small_val_h,'Callback','preprocess set_state_vals small');
2335 
+set(data.equal_val_h,'Callback','preprocess set_state_vals equal');
2336 
+set(data.replace_val_h,'Callback','preprocess set_state_vals replace');
2337 
+set(data.OK_button_h,'Callback','preprocess clip_data clip');
2338 
+set(h0,'UserData',data);
2339 
+
2340 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2341 
+
2342 
+function select(varargin)
2343 
+
2344 
+if nargin ~= 1
2345 
+  pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
2346 
+  preh_udata=get(pre_h,'UserData');
2347 
+  preh_udata.LOG{length(preh_udata.LOG)+1}=...
2348 
+      '% Starting the ''Select'' -window...';
2349 
+  preh_udata.LOG{length(preh_udata.LOG)+1}='preprocess(''select'',''foo'');';
2350 
+  set(pre_h,'UserData',preh_udata);
2351 
+end
2352 
+
2353 
+sel_h=findobj(get(0,'Children'),'Tag','Select');
2354 
+
2355 
+if ~isempty(sel_h)
2356 
+  figure(sel_h);
2357 
+  return;
2358 
+end
2359 
+
2360 
+h0 = figure('Color',[0.8 0.8 0.8], ...
2361 
+	'PaperPosition',[18 180 576 432], ...
2362 
+	'PaperUnits','points', ...
2363 
+	'Position',[750 431 168 365], ...
2364 
+	'Tag','Select');
2365 
+h1 = uicontrol('Parent',h0, ...
2366 
+	'Units','normalized', ...
2367 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
2368 
+	'ListboxTop',0, ...
2369 
+	'Position',[0.05357142857142857 0.2712328767123288 0.8333333333333333 0.6301369863013698], ...
2370 
+	'Style','frame', ...
2371 
+	'Tag','Frame1');
2372 
+
2373 
+h1 = uicontrol('Parent',h0, ...
2374 
+	'Units','normalized', ...
2375 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
2376 
+	'ListboxTop',0, ...
2377 
+	'Position',[0.05357142857142857 0.1041095890410959 0.8333333333333333 0.1397260273972603], ...
2378 
+	'Style','frame', ...
2379 
+	'Tag','Frame2');
2380 
+
2381 
+h1 = uicontrol('Parent',h0,...
2382 
+	'Units','normalized', ...
2383 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2384 
+	'ListboxTop',0, ...
2385 
+	'Position',[0.09523809523809523 0.6547945205479452 0.75 0.2273972602739726], ...
2386 
+	'Style','frame', ...
2387 
+	'Tag','Frame3');
2388 
+
2389 
+h1 = uicontrol('Parent',h0, ...
2390 
+	'Units','normalized', ...
2391 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2392 
+	'ListboxTop',0, ...
2393 
+	'Position',[0.09523809523809523 0.4794520547945206 0.75 0.1506849315068493], ...
2394 
+	'Style','frame', ...
2395 
+	'Tag','Frame4');
2396 
+
2397 
+h1 = uicontrol('Parent',h0, ...
2398 
+	'Units','normalized', ...
2399 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2400 
+	'ListboxTop',0, ...
2401 
+	'Position',[0.09523809523809523 0.2986301369863014 0.75 0.1506849315068493], ...
2402 
+	'Style','frame', ...
2403 
+	'Tag','Frame5');
2404 
+
2405 
+h1 = uicontrol('Parent',h0, ...
2406 
+	'Units','normalized', ...
2407 
+	'BackgroundColor',[1 1 1], ...
2408 
+	'ListboxTop',0, ...
2409 
+	'Position',[0.5535714285714285 0.8082191780821918 0.2678571428571429 0.06575342465753425], ...
2410 
+	'Style','edit', ...
2411 
+	'Tag','EditText1');
2412 
+
2413 
+data.big_val_h=h1;
2414 
+
2415 
+h1 = uicontrol('Parent',h0, ...
2416 
+	'Units','normalized', ...
2417 
+	'BackgroundColor',[1 1 1], ...
2418 
+	'ListboxTop',0, ...
2419 
+	'Position',[0.5535714285714285 0.7342465753424657 0.2678571428571429 0.06575342465753425], ...
2420 
+	'Style','edit', ...
2421 
+	'Tag','EditText2');
2422 
+
2423 
+data.small_val_h = h1;
2424 
+
2425 
+h1 = uicontrol('Parent',h0, ...
2426 
+	'Units','normalized', ...
2427 
+	'BackgroundColor',[1 1 1], ...
2428 
+	'ListboxTop',0, ...
2429 
+	'Position',[0.5535714285714285 0.6602739726027397 0.2678571428571429 0.06575342465753425], ...
2430 
+	'Style','edit', ...
2431 
+	'Tag','EditText3');
2432 
+
2433 
+data.equal_val_h=h1;
2434 
+
2435 
+h1 = uicontrol('Parent',h0, ...
2436 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2437 
+	'Units','normalized', ...
2438 
+	'FontWeight','demi', ...
2439 
+	'FontSize',8,...
2440 
+	'HorizontalAlignment','left', ...
2441 
+	'ListboxTop',0, ...
2442 
+	'Position',[0.1071 0.8247 0.3929 0.0384], ...
2443 
+	'String','Bigger than', ...
2444 
+	'Style','text', ...
2445 
+	'Tag','StaticText1');
2446 
+
2447 
+h1 = uicontrol('Parent',h0, ...
2448 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2449 
+	'Units','normalized', ...
2450 
+	'FontWeight','demi', ...
2451 
+	'FontSize',8,...
2452 
+	'HorizontalAlignment','left', ...
2453 
+	'ListboxTop',0, ...
2454 
+	'Position',[0.1071 0.7507 0.4286 0.0329], ...
2455 
+	'String','Smaller than', ...
2456 
+	'Style','text', ...
2457 
+	'Tag','StaticText2');
2458 
+
2459 
+h1 = uicontrol('Parent',h0, ...
2460 
+	'Units','normalized', ...
2461 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2462 
+	'FontWeight','demi', ...
2463 
+	'FontSize',8,...
2464 
+	'HorizontalAlignment','left', ...
2465 
+	'ListboxTop',0, ...
2466 
+	'Position',[0.1071 0.6630 0.3929 0.0493], ...
2467 
+	'String','Equal to', ...
2468 
+	'Style','text', ...
2469 
+	'Tag','StaticText3');
2470 
+
2471 
+h1 = uicontrol('Parent',h0, ...
2472 
+	'Units','normalized', ...
2473 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2474 
+	'ListboxTop',0, ...
2475 
+	'Position',[0.125 0.5643835616438356 0.1130952380952381 0.04931506849315068], ...
2476 
+	'Style','radiobutton', ...
2477 
+	'Tag','Radiobutton1');
2478 
+
2479 
+data.and_button_h = h1;
2480 
+
2481 
+h1 = uicontrol('Parent',h0, ...
2482 
+	'Units','normalized', ...
2483 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2484 
+	'ListboxTop',0, ...
2485 
+	'Position',[0.125 0.5013698630136987 0.1130952380952381 0.04931506849315068], ...
2486 
+	'Style','radiobutton', ...
2487 
+	'Tag','Radiobutton2');
2488 
+
2489 
+data.or_button_h = h1;
2490 
+
2491 
+h1 = uicontrol('Parent',h0, ...
2492 
+	'Units','normalized', ...
2493 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2494 
+	'FontWeight','demi', ...
2495 
+	'FontSize',8,...
2496 
+	'HorizontalAlignment','left', ...
2497 
+	'ListboxTop',0, ...
2498 
+	'Position',[0.2619047619047619 0.5561643835616439 0.3809523809523809 0.05205479452054795], ...
2499 
+	'String','AND', ...
2500 
+	'Style','text', ...
2501 
+	'Tag','StaticText4');
2502 
+
2503 
+h1 = uicontrol('Parent',h0, ...
2504 
+	'Units','normalized', ...
2505 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2506 
+	'FontWeight','demi', ...
2507 
+	'FontSize',8,...
2508 
+	'HorizontalAlignment','left', ...
2509 
+	'ListboxTop',0, ...
2510 
+	'Position',[0.2619047619047619 0.4986301369863014 0.3809523809523809 0.04657534246575343], ...
2511 
+	'String','OR', ...
2512 
+	'Style','text', ...
2513 
+	'Tag','StaticText5');
2514 
+
2515 
+h1 = uicontrol('Parent',h0, ...
2516 
+	'Units','normalized', ...
2517 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2518 
+	'ListboxTop',0, ...
2519 
+	'Position',[0.125 0.3808219178082192 0.1130952380952381 0.04931506849315068], ...
2520 
+	'Style','radiobutton', ...
2521 
+	'Tag','Radiobutton3');
2522 
+
2523 
+data.all_button_h = h1;
2524 
+
2525 
+h1 = uicontrol('Parent',h0, ...
2526 
+	'Units','normalized', ...
2527 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2528 
+	'ListboxTop',0, ...
2529 
+	'Position',[0.125 0.3095890410958904 0.1130952380952381 0.04931506849315068], ...
2530 
+	'Style','radiobutton', ...
2531 
+	'Tag','Radiobutton4');
2532 
+
2533 
+data.sel_vects_button_h = h1;
2534 
+
2535 
+h1 = uicontrol('Parent',h0, ...
2536 
+	'Units','normalized', ...
2537 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2538 
+	'FontWeight','demi', ...
2539 
+	'FontSize',8,...
2540 
+	'HorizontalAlignment','left', ...
2541 
+	'ListboxTop',0, ...
2542 
+	'Position',[0.2619047619047619 0.3780821917808219 0.4166666666666666 0.04931506849315068], ...
2543 
+	'String','All vectors', ...
2544 
+	'Style','text', ...
2545 
+	'Tag','StaticText6');
2546 
+
2547 
+h1 = uicontrol('Parent',h0, ...
2548 
+	'Units','normalized', ...
2549 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2550 
+	'FontWeight','demi', ...
2551 
+	'FontSize',8,...
2552 
+	'HorizontalAlignment','left', ...
2553 
+	'ListboxTop',0, ...
2554 
+	'Position',[0.2619047619047619 0.3123287671232877 0.5595238095238095 0.03835616438356165], ...
2555 
+	'String','Among selected', ...
2556 
+	'Style','text', ...
2557 
+	'Tag','StaticText7');
2558 
+
2559 
+h1 = uicontrol('Parent',h0, ...
2560 
+	'Units','normalized', ...
2561 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2562 
+	'ListboxTop',0, ...
2563 
+	'Position',[0.0952    0.1178    0.7500    0.1068], ...
2564 
+	'Style','frame', ...
2565 
+	'Tag','Frame6');
2566 
+
2567 
+h1 = uicontrol('Parent',h0, ...
2568 
+	'Units','normalized', ...
2569 
+	'BackgroundColor',[1 1 1], ...
2570 
+	'ListboxTop',0, ...
2571 
+	'Position',[0.5298    0.1342    0.2738    0.0712], ...
2572 
+	'Style','edit', ...
2573 
+	'Tag','EditText4');
2574 
+
2575 
+data.replace_val_h = h1;
2576 
+
2577 
+h1 = uicontrol('Parent',h0, ...
2578 
+	'Units','normalized', ...
2579 
+	'BackgroundColor',[0.8 0.8 0.8], ...
2580 
+	'FontSize',8,...
2581 
+	'FontWeight','demi', ...
2582 
+	'HorizontalAlignment','left', ...
2583 
+	'ListboxTop',0, ...
2584 
+	'Position',[0.1369047619047619 0.136986301369863 0.3214285714285714 0.06027397260273973], ...
2585 
+	'String','Vectors', ...
2586 
+	'Style','text', ...
2587 
+	'Tag','StaticText8');
2588 
+
2589 
+h1 = uicontrol('Parent',h0, ...
2590 
+	'Units','normalized', ...
2591 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
2592 
+	'FontWeight','demi', ...
2593 
+	'ListboxTop',0, ...
2594 
+	'Position',[0.05357142857142857 0.01917808219178082 0.3869047619047619 0.0684931506849315], ...
2595 
+	'String','OK', ...
2596 
+	'Tag','Pushbutton1');
2597 
+
2598 
+data.OK_button_h = h1;
2599 
+
2600 
+h1 = uicontrol('Parent',h0, ...
2601 
+	'Units','normalized', ...
2602 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
2603 
+	'Callback','preprocess close_s',...
2604 
+	'FontWeight','demi', ...
2605 
+	'ListboxTop',0, ...
2606 
+	'Position',[0.5 0.01917808219178082 0.3869047619047619 0.0684931506849315], ...
2607 
+	'String','Close', ...
2608 
+	'Tag','Pushbutton2');
2609 
+
2610 
+
2611 
+
2612 
+data.state.and=1;
2613 
+data.state.all=1;
2614 
+data.state.big=[];
2615 
+data.state.small=[];
2616 
+data.state.equal=[];
2617 
+data.state.replace=[];
2618 
+
2619 
+set(data.or_button_h,'Callback','preprocess and_or_cb or');
2620 
+set(data.and_button_h,'Callback','preprocess and_or_cb and');
2621 
+set(data.and_button_h,'Value',1);
2622 
+set(data.all_button_h,'Callback','preprocess all_sel_cb all');
2623 
+set(data.sel_vects_button_h,'Callback','preprocess all_sel_cb sel');
2624 
+set(data.big_val_h,'Callback','preprocess set_state_vals big');
2625 
+set(data.small_val_h,'Callback','preprocess set_state_vals small');
2626 
+set(data.equal_val_h,'Callback','preprocess set_state_vals equal');
2627 
+set(data.replace_val_h,'Callback','preprocess set_state_vals replace');
2628 
+set(data.OK_button_h,'Callback','preprocess clip_data sel');
2629 
+set(h0,'UserData',data);
2630 
+
2631 
+
2632 
+
2633 
+%%% Subfunction: and_or_cb %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2634 
+
2635 
+function and_or_cb(arg)
2636 
+
2637 
+%AND_OR_CB  A callback function. Checks that only one of the radiobox
2638 
+%           buttons 'AND' and 'OR' is pressed down.
2639 
+%
2640 
+%
2641 
+
2642 
+and_button_h=getfield(get(gcf,'UserData'),'and_button_h');
2643 
+or_button_h=getfield(get(gcf,'UserData'),'or_button_h');
2644 
+data=get(gcf,'UserData');
2645 
+
2646 
+switch arg
2647 
+  case 'or'
2648 
+   set(and_button_h,'Value',0);
2649 
+   set(or_button_h,'Value',1);
2650 
+   data.state.and=0;
2651 
+  case 'and'
2652 
+   set(or_button_h,'Value',0);
2653 
+   set(and_button_h,'Value',1);
2654 
+   data.state.and=1;
2655 
+end
2656 
+
2657 
+set(gcf,'UserData',data);
2658 
+
2659 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2660 
+
2661 
+%%% Subfunction: all_sel_cb %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2662 
+
2663 
+function all_sel_cb(arg)
2664 
+
2665 
+all_button_h=getfield(get(gcf,'UserData'),'all_button_h');
2666 
+sel_vects_button_h=getfield(get(gcf,'UserData'),'sel_vects_button_h');
2667 
+data=get(gcf,'UserData');
2668 
+
2669 
+switch arg
2670 
+ case 'all'
2671 
+  set(sel_vects_button_h,'Value',0);
2672 
+  set(all_button_h,'Value',1);
2673 
+  data.state.all=1;
2674 
+ case 'sel'
2675 
+  set(all_button_h,'Value',0);
2676 
+  set(sel_vects_button_h,'Value',1);
2677 
+  data.state.all=0;
2678 
+end
2679 
+
2680 
+set(gcf,'UserData',data);
2681 
+
2682 
+%%% Subfunction: set_state_vals %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2683 
+
2684 
+function set_state_vals(arg)
2685 
+
2686 
+%SET_STATE_VALS  sets the values to the UserData's state-struct.
2687 
+%
2688 
+%
2689 
+
2690 
+
2691 
+data=get(gcf,'UserData');
2692 
+
2693 
+switch arg
2694 
+  case 'big'
2695 
+   big_val_h=getfield(get(gcf,'UserData'),'big_val_h');
2696 
+   val =str2num(get(big_val_h,'String'));
2697 
+   dims=size(val);
2698 
+   if dims(1) ~= 1 | dims(2) ~= 1
2699 
+     errordlg('Argument of the operation must be scalar.');
2700 
+     set(big_val_h,'String','');
2701 
+     return;
2702 
+   end
2703 
+   if isreal(val)
2704 
+     data.state.big=val;
2705 
+   else
2706 
+     errordlg('Limits of the operation must be real.');
2707 
+     set(big_val_h,'String','');
2708 
+     return;
2709 
+   end
2710 
+  case 'small'
2711 
+   small_val_h=getfield(get(gcf,'UserData'),'small_val_h');
2712 
+   val=str2num(get(small_val_h,'String'));
2713 
+   dims=size(val);
2714 
+   if dims(1) ~= 1 | dims(2) ~= 1
2715 
+     errordlg('Argument of the operation must be scalar.')
2716 
+     set(small_val_h,'String','');
2717 
+     return;
2718 
+   end
2719 
+   if isreal(val)
2720 
+     data.state.small=val;
2721 
+   else
2722 
+     errordlg('Limits of the operation must be real.');
2723 
+     set(small_val_h,'String','');
2724 
+     return;
2725 
+   end
2726 
+  case 'equal'
2727 
+   equal_val_h=getfield(get(gcf,'UserData'),'equal_val_h');
2728 
+   val = str2num(get(equal_val_h,'String'));
2729 
+   dims=size(val);
2730 
+   if dims(1) ~= 1 | dims(2) ~= 1
2731 
+     errordlg('Argument of the operation must be scalar.');
2732 
+     set(equal_val_h,'String','');
2733 
+     return;
2734 
+   end
2735 
+   if isreal(val)
2736 
+     data.state.equal=val;
2737 
+   else
2738 
+     errordlg('Limits of the operation must be real.');
2739 
+     set(equal_val_h,'String','');
2740 
+     return;
2741 
+   end
2742 
+  case 'replace'
2743 
+   replace_val_h=getfield(get(gcf,'UserData'),'replace_val_h');
2744 
+   val=str2num(get(replace_val_h,'String'));
2745 
+   dims=size(val);
2746 
+   if (dims(1) ~= 1 | dims(2) ~= 1) & ~strcmp(get(gcf,'Tag'),'Select')
2747 
+     errordlg('Argument of the operation must be scalar.');
2748 
+     set(replace_val_h,'String','');
2749 
+     return;
2750 
+   end
2751 
+   if isreal(val)
2752 
+     data.state.replace=val;
2753 
+   else
2754 
+     errordlg('Limits of the operation must be real.');
2755 
+     set(replace_val_h,'String','');
2756 
+     return;
2757 
+   end
2758 
+end
2759 
+
2760 
+set(gcf,'UserData',data);
2761 
+
2762 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2763 
+
2764 
+%%% Subfunction: clip_data %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
2765 
+
2766 
+function clip_data(arg)
2767 
+
2768 
+%CLIP_DATA  A callback function. Filters the data.
2769 
+%
2770 
+%
2771 
+
2772 
+i=1;
2773 
+while i <= length(arg) & arg(i) ~= ' '
2774 
+  i=i+1;
2775 
+end
2776 
+
2777 
+arg2=arg(i+1:length(arg));
2778 
+arg=arg(1:i-1);
2779 
+
2780 
+if ~isempty(arg2)
2781 
+  LOG=1;
2782 
+  if strcmp(arg,'sel')
2783 
+    c_h=findobj(get(0,'Children'),'Tag','Select');
2784 
+  else
2785 
+    c_h=findobj(get(0,'Children'),'Tag','Clipping');
2786 
+  end
2787 
+  set(0,'CurrentFigure',c_h);
2788 
+  i=1;
2789 
+  while i <= length(arg2) & arg2(i) ~= ' '
2790 
+    i=i+1;
2791 
+  end
2792 
+  BT=str2num(arg2(1:i-1));
2793 
+  i=i+1;
2794 
+  j=i;
2795 
+  while i <= length(arg2) & arg2(i) ~= ' '
2796 
+    i=i+1;
2797 
+  end
2798 
+  ST=str2num(arg2(j:i-1));
2799 
+  i=i+1;
2800 
+  j=i;
2801 
+  while i <= length(arg2) & arg2(i) ~= ' '
2802 
+    i=i+1;
2803 
+  end
2804 
+  EQ=str2num(arg2(j:i-1));
2805 
+  i=i+1;
2806 
+  j=i;
2807 
+  while i <= length(arg2) & arg2(i) ~= ' '
2808 
+    i=i+1;
2809 
+  end
2810 
+  AND_OR=str2num(arg2(j:i-1));
2811 
+  i=i+1;
2812 
+  j=i;
2813 
+  while i <= length(arg2) & arg2(i) ~= ' '
2814 
+    i=i+1;
2815 
+  end
2816 
+  ALL_AMONG=str2num(arg2(j:i-1));
2817 
+  i=i+1;
2818 
+  j=i;
2819 
+  while i <= length(arg2)
2820 
+    i=i+1;
2821 
+  end
2822 
+  VECT_REPL=str2num(arg2(j:i-1));
2823 
+else
2824 
+  LOG=0;
2825 
+end
2826 
+
2827 
+if ~LOG
2828 
+  big_val_h=getfield(get(gcf,'UserData'),'big_val_h');
2829 
+  small_val_h=getfield(get(gcf,'UserData'),'small_val_h');
2830 
+  equal_val_h=getfield(get(gcf,'UserData'),'equal_val_h');
2831 
+  replace_val_h=getfield(get(gcf,'UserData'),'replace_val_h');
2832 
+end
2833 
+
2834 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
2835 
+
2836 
+if isempty(pre_h)
2837 
+  errordlg('''Preprocess'' -figure does not exist. Terminating program...');
2838 
+  pro_tools('close');
2839 
+  return;
2840 
+end
2841 
+
2842 
+comp_names_h=getfield(get(pre_h,'UserData'),'comp_names_h');
2843 
+selected=getfield(get(pre_h,'UserData'),'selected_vects');
2844 
+sData=getfield(get(pre_h,'UserData'),'sData');
2845 
+undo = sData;
2846 
+state=getfield(get(gcf,'UserData'),'state');
2847 
+
2848 
+if LOG
2849 
+  state.big=BT;
2850 
+  state.small=ST;
2851 
+  state.equal=EQ;
2852 
+  state.replace=VECT_REPL;
2853 
+  state.and=AND_OR;
2854 
+  state.all=ALL_AMONG;
2855 
+end
2856 
+
2857 
+if isempty(pre_h)
2858 
+  pro_tools('close');
2859 
+end
2860 
+
2861 
+if isempty(get(comp_names_h,'Value'))
2862 
+  clear_state_vals;
2863 
+  errordlg('There must be one component chosen for the operation.');
2864 
+  return;
2865 
+end
2866 
+
2867 
+n_th_comp=getfield(get_indices,{1});
2868 
+
2869 
+if isempty(state.big) & isempty(state.small) & isempty(state.equal) & ...
2870 
+   strcmp(arg,'clip')
2871 
+  clear_state_vals;
2872 
+  errordlg('At least one limit must be chosen for the-operation.');
2873 
+  return;
2874 
+end
2875 
+
2876 
+if ~isempty(state.replace) & strcmp(arg,'sel')
2877 
+  if ~all(state.replace == round(state.replace)) | any(state.replace < 1)
2878 
+    errordlg('Indices of vectors must be positive integers.');
2879 
+    return;
2880 
+  elseif any(state.replace > length(sData.data(:,1)))
2881 
+    errordlg('Indices of the vectors to be selected are too big.');
2882 
+    return;
2883 
+  end
2884 
+end
2885 
+
2886 
+if isempty(state.replace) & strcmp(arg,'clip')
2887 
+  clear_state_vals;
2888 
+  errordlg('Replace value must be determined for Clipping-operation.');
2889 
+  return;
2890 
+end
2891 
+
2892 
+if isempty(state.big) & isempty(state.small) & isempty(state.equal) & ...
2893 
+   isempty(state.replace)
2894 
+   clear_state_vals;
2895 
+   return;
2896 
+end
2897 
+
2898 
+bt_indices=[];
2899 
+lt_indices=[];
2900 
+equal_indices=[];
2901 
+
2902 
+
2903 
+if ~isempty(state.big)
2904 
+  if state.all
2905 
+    bt_indices=find(sData.data(:,n_th_comp) > state.big);
2906 
+  else
2907 
+    bt_indices=selected(find(sData.data(selected,n_th_comp) > state.big));
2908 
+  end
2909 
+end
2910 
+
2911 
+if ~isempty(state.small)
2912 
+  if state.all
2913 
+    lt_indices=find(sData.data(:,n_th_comp) < state.small);
2914 
+  else
2915 
+    lt_indices=selected(find(sData.data(selected,n_th_comp) < state.small));
2916 
+  end
2917 
+end
2918 
+
2919 
+if ~isempty(state.equal)
2920 
+  if isnan(state.equal)
2921 
+    if state.all
2922 
+      equal_indices=find(isnan(sData.data(:,n_th_comp)));
2923 
+    else
2924 
+      equal_indices=selected(find(isnan(sData.data(selected,n_th_comp))));
2925 
+    end
2926 
+  elseif state.all
2927 
+    equal_indices=find(sData.data(:,n_th_comp)==state.equal);
2928 
+  else
2929 
+    equal_indices=selected(find(sData.data(selected,n_th_comp)==state.equal));
2930 
+  end
2931 
+end
2932 
+
2933 
+if state.and
2934 
+
2935 
+  if ~isempty(bt_indices) | ~isempty(lt_indices) | ~isempty(equal_indices)...
2936 
+     | strcmp(arg,'sel')
2937 
+
2938 
+    if isempty(bt_indices) & isempty(lt_indices) & isempty(equal_indices) &...
2939 
+       isempty(state.replace)
2940 
+      clear_state_vals;
2941 
+      return;
2942 
+    end
2943 
+    if isempty(bt_indices)
2944 
+      if ~state.all
2945 
+        bt_indices=selected;
2946 
+      else
2947 
+        bt_indices=1:getfield(size(sData.data),{1});
2948 
+      end
2949 
+    end
2950 
+    if isempty(lt_indices)
2951 
+      if ~state.all
2952 
+        lt_indices=selected;
2953 
+      else
2954 
+        lt_indices=1:getfield(size(sData.data),{1});
2955 
+      end
2956 
+    end
2957 
+    if isempty(equal_indices)
2958 
+      if ~state.all
2959 
+        equal_indices=selected;
2960 
+      else
2961 
+        equal_indices=1:getfield(size(sData.data),{1});
2962 
+      end
2963 
+    end
2964 
+
2965 
+    indices=intersect(intersect(bt_indices,lt_indices),equal_indices);
2966 
+    if strcmp(arg,'sel')
2967 
+      if ~isempty(indices) | ~isempty(state.replace)
2968 
+        if isempty(state.replace)
2969 
+          NOTEMPTY=0;
2970 
+          if ~state.all
2971 
+            state.replace=selected;
2972 
+          else
2973 
+            state.replace=1:getfield(size(sData.data),{1});
2974 
+          end
2975 
+        else
2976 
+          NOTEMPTY=1;
2977 
+        end
2978 
+        if isempty(indices)
2979 
+          indices=selected;
2980 
+        end
2981 
+        indices=intersect(indices,state.replace);
2982 
+        if isempty(indices)
2983 
+          indices=selected;
2984 
+        end
2985 
+        data=get(pre_h,'UserData');
2986 
+        data.undo.sData=sData;
2987 
+        data.undo.selected=data.selected_vects;
2988 
+        data.selected_vects=indices;
2989 
+        if ~LOG
2990 
+         if ~NOTEMPTY
2991 
+           data.LOG{length(data.LOG)+1}='% Select vectors.';
2992 
+           data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''clip_data'',''',...
2993 
+                                                 arg,...
2994 
+                                                 ' ',num2str(state.big),...
2995 
+                                                 ' ',num2str(state.small),...
2996 
+                                                 ' ',num2str(state.equal),...
2997 
+                                                 ' ',num2str(state.and),...
2998 
+                                                 ' ',num2str(state.all),...
2999 
+                                                 ''');');
3000 
+         else
3001 
+           code=write_log_code(state.replace,...
3002 
+                               arg,...
3003 
+                               state.big,...
3004 
+                               state.small,...
3005 
+                               state.equal,...
3006 
+                               state.and,...
3007 
+                               state.all);
3008 
+           data.LOG(length(data.LOG)+1:length(data.LOG)+length(code))=code;
3009 
+         end
3010 
+        end
3011 
+        set(pre_h,'UserData',data);
3012 
+        old=gcf;
3013 
+        set(0,'CurrentFigure',pre_h);
3014 
+        sel_comp;
3015 
+        cplot_mimema;
3016 
+        vect_means(data.sData,data.vect_mean_h,data.selected_vects);
3017 
+        set(0,'CurrentFigure',old);
3018 
+      end
3019 
+      clear_state_vals;
3020 
+      return;
3021 
+    end
3022 
+    sData.data(indices,n_th_comp) = state.replace;
3023 
+    sData.MODIFIED=1;
3024 
+  end
3025 
+else
3026 
+  indices=union(union(bt_indices,lt_indices),equal_indices);
3027 
+  if ~isempty(indices) | strcmp(arg,'sel')
3028 
+    if strcmp(arg,'sel')
3029 
+      if ~isempty(indices) | ~isempty(state.replace')
3030 
+        data=get(pre_h,'UserData');
3031 
+        data.undo.sData=sData;
3032 
+        data.undo.selected=data.selected_vects;
3033 
+        data.selected_vects=union(indices,state.replace);
3034 
+        if ~LOG
3035 
+         if isempty(state.replace);
3036 
+           data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''clip_data'',''',...
3037 
+                                                 arg,...
3038 
+                                                 ' ',num2str(state.big),...
3039 
+                                                 ' ',num2str(state.small),...
3040 
+                                                 ' ',num2str(state.equal),...
3041 
+                                                 ' ',num2str(state.and),...
3042 
+                                                 ' ',num2str(state.all),...
3043 
+                                                 ''');');
3044 
+         else
3045 
+           code=write_log_code(state.replace,...
3046 
+                               arg,...
3047 
+                               state.big,...
3048 
+                               state.small,...
3049 
+                               state.equal,...
3050 
+                               state.and,...
3051 
+                               state.all);
3052 
+           data.LOG(length(data.LOG)+1:length(data.LOG)+length(code))=code;
3053 
+         end
3054 
+        end
3055 
+        set(pre_h,'UserData',data);
3056 
+        old=gcf;
3057 
+        set(0,'CurrentFigure',pre_h);
3058 
+        sel_comp;
3059 
+	vect_means(data.sData,data.vect_mean_h,data.selected_vects);
3060 
+        cplot_mimema;
3061 
+        set(0,'CurrentFigure',old);
3062 
+      end
3063 
+      clear_state_vals;
3064 
+      return;
3065 
+    end
3066 
+    sData.data(indices,n_th_comp)=state.replace;
3067 
+    sData.MODIFIED=1;
3068 
+  end
3069 
+end
3070 
+
3071 
+if sData.MODIFIED
3072 
+  data=get(pre_h,'UserData');
3073 
+  data.sData=sData;
3074 
+  data.undo.sData=undo;
3075 
+  if ~LOG
3076 
+    if strcmp(arg,'sel')
3077 
+      data.LOG{length(data.LOG)+1}='% Select vectors';
3078 
+    else
3079 
+      data.LOG{length(data.LOG)+1}='% Clip values.';
3080 
+    end
3081 
+    if strcmp(arg,'clip') | isempty(state.replace)
3082 
+     data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''clip_data'',''',arg,...
3083 
+                                                 ' ',num2str(state.big),...
3084 
+                                                 ' ',num2str(state.small),...
3085 
+                                                 ' ',num2str(state.equal),...
3086 
+                                                 ' ',num2str(state.and),...
3087 
+                                                 ' ',num2str(state.all),...
3088 
+                                                 ' ',num2str(state.replace),...
3089 
+                                                 ''');');
3090 
+    else
3091 
+      code=write_log_code(state.replace,...
3092 
+                          arg,...
3093 
+                          state.big,...
3094 
+                          state.small,...
3095 
+                          state.equal,...
3096 
+                          state.and,...
3097 
+                          state.all);
3098 
+      data.LOG(length(data.LOG)+1:length(data.LOG)+length(code))=code;
3099 
+    end
3100 
+  end
3101 
+  set(pre_h,'UserData',data);
3102 
+  old=gcf;
3103 
+  set(0,'CurrentFigure',pre_h)
3104 
+
3105 
+  vector_h=getfield(get(gcf,'UserData'),'vector_h');
3106 
+  vect_mean_h=getfield(get(gcf,'UserData'),'vect_mean_h');
3107 
+  set(gcf,'CurrentAxes',vector_h);
3108 
+  vect_means(sData,vect_mean_h,selected);
3109 
+  cplot_mimema;
3110 
+  sel_comp;
3111 
+
3112 
+  set(0,'CurrentFigure',old);
3113 
+end
3114 
+
3115 
+clear_state_vals;
3116 
+
3117 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3118 
+
3119 
+%%% Subfunction: clear_state_vals %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3120 
+
3121 
+function clear_state_vals
3122 
+
3123 
+%CLEAR_STATE_VALS  Sets the fields of the UserData's state-struct empty.
3124 
+%
3125 
+%
3126 
+
3127 
+
3128 
+data=get(gcf,'UserData');
3129 
+set(data.big_val_h,'String','');
3130 
+set(data.small_val_h,'String','');
3131 
+set(data.equal_val_h,'String','');
3132 
+set(data.replace_val_h,'String','');
3133 
+data.state.big=[];
3134 
+data.state.small=[];
3135 
+data.state.equal=[];
3136 
+data.state.replace=[];
3137 
+set(gcf,'UserData',data);
3138 
+
3139 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3140 
+
3141 
+function delay(varargin)
3142 
+
3143 
+delay_h=findobj(get(0,'Children'),'Tag','Delay');
3144 
+
3145 
+if nargin ~= 1
3146 
+  pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
3147 
+  preh_udata=get(pre_h,'UserData');
3148 
+  preh_udata.LOG{length(preh_udata.LOG)+1}=...
3149 
+      '% Starting the ''Delay'' -window...';
3150 
+  preh_udata.LOG{length(preh_udata.LOG)+1}='preprocess(''delay'',''foo'');';
3151 
+  set(pre_h,'UserData',preh_udata);
3152 
+end
3153 
+
3154 
+if ~isempty(delay_h)
3155 
+  figure(delay_h);
3156 
+  return;
3157 
+end
3158 
+
3159 
+h0 = figure('Color',[0.8 0.8 0.8], ...
3160 
+	'PaperPosition',[18 180 576 432], ...
3161 
+	'PaperUnits','points', ...
3162 
+	'Position',[759 664 162 215], ...
3163 
+	'Tag','Delay');
3164 
+
3165 
+h1 = uicontrol('Parent',h0, ...
3166 
+	'Units','normalized', ...
3167 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
3168 
+	'ListboxTop',0, ...
3169 
+	'Position',[0.05555555555555555 0.2046511627906977 0.8950617283950617 0.7441860465116279], ...
3170 
+	'Style','frame', ...
3171 
+	'Tag','Frame1');
3172 
+
3173 
+h1 = uicontrol('Parent',h0, ...
3174 
+	'Units','normalized', ...
3175 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3176 
+	'ListboxTop',0, ...
3177 
+	'Position',[0.08641975308641975 0.6976744186046512 0.8333333333333333 0.2232558139534884], ...
3178 
+	'Style','frame', ...
3179 
+	'Tag','Frame2');
3180 
+
3181 
+h1 = uicontrol('Parent',h0, ...
3182 
+	'Units','normalized', ...
3183 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3184 
+	'ListboxTop',0, ...
3185 
+	'Position',[0.08641975308641975 0.227906976744186 0.8333333333333333 0.4418604651162791], ...
3186 
+	'Style','frame', ...
3187 
+	'Tag','Frame3');
3188 
+
3189 
+h1 = uicontrol('Parent',h0, ...
3190 
+	'Units','normalized', ...
3191 
+	'Callback','preprocess delay_data',...
3192 
+	'FontWeight','demi', ...
3193 
+	'ListboxTop',0, ...
3194 
+	'Position',[0.0556 0.0326 0.4012 0.1163], ...
3195 
+	'String','OK', ...
3196 
+	'Tag','Pushbutton1');
3197 
+
3198 
+h1 = uicontrol('Parent',h0, ...
3199 
+	'Units','normalized', ...
3200 
+	'Callback','preprocess close_d',...
3201 
+	'FontWeight','demi', ...
3202 
+	'ListboxTop',0, ...
3203 
+	'Position',[0.5494 0.0326 0.4012 0.1163], ...
3204 
+	'String','Close', ...
3205 
+	'Tag','Pushbutton2');
3206 
+
3207 
+h1 = uicontrol('Parent',h0, ...
3208 
+	'Units','normalized', ...
3209 
+	'BackgroundColor',[1 1 1], ...
3210 
+	'ListboxTop',0, ...
3211 
+	'Position',[0.4876543209876543 0.7534883720930232 0.3518518518518519 0.1255813953488372], ...
3212 
+	'Style','edit', ...
3213 
+	'Tag','EditText1');
3214 
+
3215 
+data.delay_val_h = h1;
3216 
+
3217 
+h1 = uicontrol('Parent',h0, ...
3218 
+	'Units','normalized', ...
3219 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3220 
+	'FontWeight','demi', ...
3221 
+	'HorizontalAlignment','left', ...
3222 
+	'ListboxTop',0, ...
3223 
+	'Position',[0.1173 0.7860 0.3086 0.0651], ...
3224 
+	'String','Delay', ...
3225 
+	'Style','text', ...
3226 
+	'Tag','StaticText1');
3227 
+
3228 
+h1 = uicontrol('Parent',h0, ...
3229 
+	'Units','normalized', ...
3230 
+	'Callback','preprocess clip_exp_cb c_this',...
3231 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3232 
+	'ListboxTop',0, ...
3233 
+	'Position',[0.1173 0.5349 0.1173 0.0837], ...
3234 
+	'Style','radiobutton', ...
3235 
+	'Tag','Radiobutton1');
3236 
+
3237 
+data.c_this_button_h=h1;
3238 
+data.mode='c_this';
3239 
+
3240 
+h1 = uicontrol('Parent',h0, ...
3241 
+	'Units','normalized', ...
3242 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3243 
+	'Callback','preprocess clip_exp_cb c_all',...
3244 
+	'ListboxTop',0, ...
3245 
+	'Position',[0.1173 0.4047 0.1173 0.0837], ...
3246 
+	'Style','radiobutton', ...
3247 
+	'Tag','Radiobutton2');
3248 
+
3249 
+data.c_all_button_h=h1;
3250 
+
3251 
+h1 = uicontrol('Parent',h0, ...
3252 
+	'Units','normalized', ...
3253 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3254 
+	'Callback','preprocess clip_exp_cb e_all',...
3255 
+	'ListboxTop',0, ...
3256 
+	'Position',[0.1173    0.2651    0.1173    0.0837], ...
3257 
+	'Style','radiobutton', ...
3258 
+	'Tag','Radiobutton3');
3259 
+
3260 
+data.e_all_button_h=h1;
3261 
+
3262 
+
3263 
+h1 = uicontrol('Parent',h0, ...
3264 
+	'Units','normalized', ...
3265 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3266 
+	'FontWeight','demi', ...
3267 
+	'FontSize',8,...
3268 
+	'HorizontalAlignment','left', ...
3269 
+	'ListboxTop',0, ...
3270 
+	'Position',[0.26 0.5534883720930233 0.4135802469135802 0.06511627906976744], ...
3271 
+	'String','Clip this', ...
3272 
+	'Style','text', ...
3273 
+	'Tag','StaticText2');
3274 
+h1 = uicontrol('Parent',h0, ...
3275 
+	'Units','normalized', ...
3276 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3277 
+	'FontWeight','demi', ...
3278 
+	'FontSize',8,...
3279 
+	'HorizontalAlignment','left', ...
3280 
+	'ListboxTop',0, ...
3281 
+	'Position',[0.26 0.413953488372093 0.3765432098765432 0.06511627906976744], ...
3282 
+	'String','Clip all', ...
3283 
+	'Style','text', ...
3284 
+	'Tag','StaticText3');
3285 
+h1 = uicontrol('Parent',h0, ...
3286 
+	'Units','normalized', ...
3287 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3288 
+	'FontWeight','demi', ...
3289 
+	'FontSize',8,...
3290 
+	'HorizontalAlignment','left', ...
3291 
+	'ListboxTop',0, ...
3292 
+	'Position',[0.26 0.2744186046511628 0.4197530864197531 0.06511627906976744], ...
3293 
+	'String','Expand all', ...
3294 
+	'Style','text', ...
3295 
+	'Tag','StaticText4');
3296 
+
3297 
+
3298 
+set(gcf,'UserData',data);
3299 
+
3300 
+%%% Subfunction clip_exp_cb %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3301 
+
3302 
+function clip_exp_cb(arg)
3303 
+
3304 
+c_this_button_h=getfield(get(gcf,'UserData'),'c_this_button_h');
3305 
+c_all_button_h=getfield(get(gcf,'UserData'),'c_all_button_h');
3306 
+e_all_button_h=getfield(get(gcf,'UserData'),'e_all_button_h');
3307 
+data=get(gcf,'UserData');
3308 
+
3309 
+
3310 
+switch arg
3311 
+  case 'c_this'
3312 
+   set(c_all_button_h,'Value',0);
3313 
+   set(e_all_button_h,'Value',0);
3314 
+   set(c_this_button_h,'Value',1);
3315 
+   data.mode='c_this';
3316 
+  case 'c_all'
3317 
+   set(c_this_button_h,'Value',0);
3318 
+   set(e_all_button_h,'Value',0);
3319 
+   set(c_all_button_h,'Value',1);
3320 
+   data.mode='c_all';
3321 
+  case 'e_all'
3322 
+   set(c_this_button_h,'Value',0);
3323 
+   set(c_all_button_h,'Value',0);
3324 
+   set(e_all_button_h,'Value',1);
3325 
+   data.mode='e_all';
3326 
+end
3327 
+
3328 
+set(gcf,'UserData',data);
3329 
+
3330 
+%%% Subfunction: delay_data %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3331 
+
3332 
+function delay_data(varargin)
3333 
+
3334 
+if nargin == 1
3335 
+  del_h=findobj(get(0,'Children'),'Tag','Delay');
3336 
+  set(0,'CurrentFigure',del_h);
3337 
+  LOG=1;
3338 
+  arg=varargin{1};
3339 
+  i=1;
3340 
+  while i <= length(arg) & arg(i) ~= ' '
3341 
+    i=i+1;
3342 
+  end
3343 
+  delay=str2num(arg(1:i-1));
3344 
+  no=str2num(arg(i+1:length(arg)));
3345 
+else
3346 
+  LOG=0;
3347 
+end
3348 
+
3349 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
3350 
+q='Delay operation is not evaluated.';
3351 
+t='Warning';
3352 
+if isempty(pre_h)
3353 
+  errordlg('''Preprocess'' -figure does not exist. Terminating program...');
3354 
+  pro_tools('close');
3355 
+  return;
3356 
+end
3357 
+
3358 
+sData=getfield(get(pre_h,'UserData'),'sData');
3359 
+undo = sData;
3360 
+data=get(gcf,'UserData');
3361 
+if ~LOG
3362 
+  delay=str2num(get(data.delay_val_h,'String'));
3363 
+  if isempty(delay)
3364 
+    errordlg('Value of ''Delay'' must be defined.');
3365 
+    return
3366 
+  end
3367 
+  set(data.delay_val_h,'String','');
3368 
+  if round(delay) ~= delay
3369 
+    errordlg('Value of ''Delay'' must be integer.');
3370 
+    return;
3371 
+  end
3372 
+end
3373 
+comp_names_h=getfield(get(pre_h,'UserData'),'comp_names_h');
3374 
+if isempty(get(comp_names_h,'Value'))
3375 
+  errordlg('There are not components chosen.');
3376 
+  return;
3377 
+end
3378 
+n_th_comp=getfield(get_indices,{1});
3379 
+len=length(sData.data(:,1));
3380 
+
3381 
+if LOG
3382 
+  switch no
3383 
+    case 1
3384 
+     data.mode='c_this';
3385 
+     preprocess('clip_exp_cb','c_this');
3386 
+    case 2
3387 
+     data.mode='c_all';
3388 
+     preprocess('clip_exp_cb','c_all');
3389 
+    case 3
3390 
+     data.mode='e_all';
3391 
+     preprocess('clip_exp_cb','e_all');
3392 
+  end
3393 
+end
3394 
+
3395 
+switch data.mode
3396 
+  case 'c_this'
3397 
+   MODE='1';
3398 
+   if delay > 0
3399 
+     sData.data(delay+1:len,n_th_comp)=sData.data(1:len-delay);
3400 
+     if delay >= len
3401 
+       errordlg(q,t);
3402 
+       return;
3403 
+     else
3404 
+       sData.data(1:delay,n_th_comp)=NaN;
3405 
+     end
3406 
+   elseif delay < 0
3407 
+     sData.data(1:len+delay,n_th_comp)=...
3408 
+              sData.data(abs(delay)+1:len,n_th_comp);
3409 
+     if abs(delay) >= len
3410 
+       errordlg(q,t);
3411 
+       return;
3412 
+     else
3413 
+       sData.data(len+delay+1:len,n_th_comp)=NaN;
3414 
+     end
3415 
+   end
3416 
+   if delay ~= 0
3417 
+     data=get(pre_h,'UserData');
3418 
+     sData.MODIFIED=1;
3419 
+     sData.comp_norm(n_th_comp)=[];
3420 
+     data.sData=sData;
3421 
+     data.undo.sData=undo;
3422 
+     set(pre_h,'UserData',data);
3423 
+     old = gcf;
3424 
+     set(0,'CurrentFigure',pre_h);
3425 
+     sel_comp;
3426 
+     cplot_mimema;
3427 
+     set(0,'CurrentFigure',old);
3428 
+   end
3429 
+  case 'c_all'
3430 
+   MODE='2';
3431 
+   if delay > 0
3432 
+     sData.data(delay+1:len,n_th_comp)=sData.data(1:len-delay,n_th_comp);
3433 
+     if delay >= len
3434 
+       errordlg(q,t);
3435 
+       return;
3436 
+     else
3437 
+       sData.data=sData.data(delay+1:len,:);
3438 
+     end
3439 
+   elseif delay < 0
3440 
+    sData.data(1:len+delay,n_th_comp)=sData.data(abs(delay)+1:len,n_th_comp);
3441 
+    if abs(delay) >= len
3442 
+      errordlg(q,t);
3443 
+      return;
3444 
+    else
3445 
+      sData.data=sData.data(1:len+delay,:);
3446 
+    end
3447 
+   end
3448 
+   if delay ~= 0
3449 
+     data=get(pre_h,'UserData');
3450 
+     sData.MODIFIED=1;
3451 
+     sData.comp_norm(:,:)={[]};
3452 
+     data.sData=sData;
3453 
+     data.undo.sData=undo;
3454 
+     data.undo.selected=data.selected_vects;
3455 
+     if delay > 0
3456 
+       data.selected_vects=...
3457 
+                        data.selected_vects(find(data.selected_vects>delay));
3458 
+       data.selected_vects=data.selected_vects-delay;
3459 
+     elseif nargin == 1
3460 
+       data.selected_vects=...
3461 
+         data.selected_vects(find(data.selected_vects<=len-abs(delay)));
3462 
+     end
3463 
+     set(pre_h,'UserData',data);
3464 
+     old=gcf;
3465 
+     set(0,'CurrentFigure',pre_h);
3466 
+     vects=zeros(1,length(sData.data(:,1)));
3467 
+     vects(data.selected_vects)=1;
3468 
+     write_sD_stats;
3469 
+     draw_vectors(vects,data.vector_h);
3470 
+     sel_comp;
3471 
+     cplot_mimema;
3472 
+     set(0,'CurrentFigure',old);
3473 
+   end
3474 
+  case 'e_all'
3475 
+   MODE='3';
3476 
+   if delay > 0
3477 
+     sData.data(len+1:len+delay,:)=NaN;
3478 
+     sData.data(1+delay:delay+len,n_th_comp)=sData.data(1:len,n_th_comp);
3479 
+     sData.data(1:delay,n_th_comp)=NaN;
3480 
+   elseif delay < 0
3481 
+     delay=abs(delay);
3482 
+     sData.data(delay+1:len+delay,:)=sData.data;
3483 
+     sData.data(1:delay,:)=NaN;
3484 
+     sData.data(1:len,n_th_comp)=sData.data(delay+1:len+delay,n_th_comp);
3485 
+     sData.data(len+1:len+delay,n_th_comp)=NaN;
3486 
+   end
3487 
+   if delay ~= 0
3488 
+     data=get(pre_h,'UserData');
3489 
+     sData.MODIFIED=1;
3490 
+     sData.comp_norm(:,:)={[]};
3491 
+     data.sData=sData;
3492 
+     data.undo.sData=undo;
3493 
+     data.undo.selected=data.selected_vects;
3494 
+     set(pre_h,'UserData',data);
3495 
+     old=gcf;
3496 
+     set(0,'CurrentFigure',pre_h);
3497 
+     write_sD_stats;
3498 
+     pro_tools('selall');
3499 
+     set(0,'CurrentFigure',old);
3500 
+   end
3501 
+end
3502 
+
3503 
+if ~LOG
3504 
+  data=get(pre_h,'UserData');
3505 
+  data.LOG{length(data.LOG)+1}='% Delay a component.';
3506 
+  data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''delay_data'',''',...
3507 
+                                      num2str(delay),' ',MODE,''');');
3508 
+  set(pre_h,'UserData',data);
3509 
+end
3510 
+
3511 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3512 
+
3513 
+function window(varargin)
3514 
+
3515 
+if nargin ~= 1
3516 
+  pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
3517 
+  preh_udata=get(pre_h,'UserData');
3518 
+  preh_udata.LOG{length(preh_udata.LOG)+1}=...
3519 
+    '% Starting the ''Windowed'' -window...';
3520 
+  preh_udata.LOG{length(preh_udata.LOG)+1}='preprocess(''window'',''foo'');';
3521 
+  set(pre_h,'UserData',preh_udata);
3522 
+end
3523 
+
3524 
+win_h=findobj(get(0,'Children'),'Tag','Window');
3525 
+
3526 
+if ~isempty(win_h)
3527 
+  figure(win_h);
3528 
+  return;
3529 
+end
3530 
+
3531 
+h0 = figure('Color',[0.8 0.8 0.8], ...
3532 
+	'PaperPosition',[18 180 576 432], ...
3533 
+	'PaperUnits','points', ...
3534 
+	'Position',[513 703 288 219], ...
3535 
+	'Tag','Window');
3536 
+
3537 
+h1 = uicontrol('Parent',h0, ...
3538 
+	'Units','normalized', ...
3539 
+	'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
3540 
+	'ListboxTop',0, ...
3541 
+	'Position',[0.03125 0.1552511415525114 0.9375 0.7990867579908676], ...
3542 
+	'Style','frame', ...
3543 
+	'Tag','Frame1');
3544 
+h1 = uicontrol('Parent',h0, ...
3545 
+	'Units','normalized', ...
3546 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3547 
+	'ListboxTop',0, ...
3548 
+	'Position',[0.04861111111111111 0.7214611872146118 0.9027777777777777 0.2009132420091324], ...
3549 
+	'Style','frame', ...
3550 
+	'Tag','Frame2');
3551 
+h1 = uicontrol('Parent',h0, ...
3552 
+	'Units','normalized', ...
3553 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3554 
+	'ListboxTop',0, ...
3555 
+	'Position',[0.04861111111111111 0.1780821917808219 0.2777777777777778 0.5251141552511416], ...
3556 
+	'Style','frame', ...
3557 
+	'Tag','Frame3');
3558 
+h1 = uicontrol('Parent',h0, ...
3559 
+	'Units','normalized', ...
3560 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3561 
+	'ListboxTop',0, ...
3562 
+	'Position',[0.3611111111111111 0.1780821917808219 0.2777777777777778 0.5251141552511416], ...
3563 
+	'Style','frame', ...
3564 
+	'Tag','Frame4');
3565 
+h1 = uicontrol('Parent',h0, ...
3566 
+	'Units','normalized', ...
3567 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3568 
+	'ListboxTop',0, ...
3569 
+	'Position',[0.6736111111111111 0.1780821917808219 0.2777777777777778 0.5251141552511416], ...
3570 
+	'Style','frame', ...
3571 
+	'Tag','Frame5');
3572 
+
3573 
+h1 = uicontrol('Parent',h0, ...
3574 
+	'Callback','preprocess eval_windowed',...
3575 
+	'Units','normalized', ...
3576 
+	'FontWeight','demi', ...
3577 
+	'ListboxTop',0, ...
3578 
+	'Position',[0.03125 0.0319634703196347 0.2256944444444444 0.091324200913242], ...
3579 
+	'String','OK', ...
3580 
+	'Tag','Pushbutton1');
3581 
+
3582 
+h1 = uicontrol('Parent',h0, ...
3583 
+	'Callback','preprocess close_w', ...
3584 
+	'Units','normalized', ...
3585 
+	'FontWeight','demi', ...
3586 
+	'ListboxTop',0, ...
3587 
+	'Position',[0.7430555555555555 0.0319634703196347 0.2256944444444444 0.091324200913242], ...
3588 
+	'String','Close', ...
3589 
+	'Tag','Pushbutton2');
3590 
+
3591 
+h1 = uicontrol('Parent',h0, ...
3592 
+	'Units','normalized', ...
3593 
+	'BackgroundColor',[1 1 1], ...
3594 
+	'ListboxTop',0, ...
3595 
+	'Position',[0.7083333333333333 0.7625570776255708 0.2083333333333333 0.1232876712328767], ...
3596 
+	'Style','edit', ...
3597 
+	'Tag','EditText1');
3598 
+
3599 
+data.win_len_h=h1;
3600 
+
3601 
+h1 = uicontrol('Parent',h0, ...
3602 
+	'Units','normalized', ...
3603 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3604 
+	'FontWeight','demi', ...
3605 
+	'HorizontalAlignment','left', ...
3606 
+	'ListboxTop',0, ...
3607 
+	'Position',[0.07638888888888888 0.8036529680365296 0.3784722222222222 0.0547945205479452], ...
3608 
+	'String','Window length', ...
3609 
+	'Style','text', ...
3610 
+	'Tag','StaticText1');
3611 
+
3612 
+h1 = uicontrol('Parent',h0, ...
3613 
+	'Units','normalized', ...
3614 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3615 
+	'Callback','preprocess window_cb centered',...
3616 
+	'ListboxTop',0, ...
3617 
+	'Position',[0.06597222222222222 0.5616438356164384 0.06597222222222222 0.0821917808219178], ...
3618 
+	'Style','radiobutton', ...
3619 
+	'Tag','Radiobutton1');
3620 
+
3621 
+data.centered_h=h1;
3622 
+data.position='center';
3623 
+
3624 
+h1 = uicontrol('Parent',h0, ...
3625 
+	'Units','normalized', ...
3626 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3627 
+	'Callback','preprocess window_cb previous',...
3628 
+	'ListboxTop',0, ...
3629 
+	'Position',[0.06597222222222222 0.4018264840182648 0.06597222222222222 0.0821917808219178], ...
3630 
+	'Style','radiobutton', ...
3631 
+	'Tag','Radiobutton2');
3632 
+
3633 
+data.previous_h=h1;
3634 
+
3635 
+h1 = uicontrol('Parent',h0, ...
3636 
+	'Units','normalized', ...
3637 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3638 
+	'Callback','preprocess window_cb next',...
3639 
+	'ListboxTop',0, ...
3640 
+	'Position',[0.06597222222222222 0.2465753424657534 0.06597222222222222 0.0821917808219178], ...
3641 
+	'Style','radiobutton', ...
3642 
+	'Tag','Radiobutton3');
3643 
+
3644 
+data.next_h=h1;
3645 
+
3646 
+h1 = uicontrol('Parent',h0, ...
3647 
+	'Units','normalized', ...
3648 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3649 
+	 'Callback','preprocess window_cb mean',...
3650 
+	'ListboxTop',0, ...
3651 
+	'Position',[0.3784722222222222 0.5799086757990868 0.06597222222222222 0.0821917808219178], ...
3652 
+	'Style','radiobutton', ...
3653 
+	'Tag','Radiobutton4');
3654 
+
3655 
+data.mean_h=h1;
3656 
+data.mode='mean';
3657 
+
3658 
+
3659 
+h1 = uicontrol('Parent',h0, ...
3660 
+	'Units','normalized', ...
3661 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3662 
+	'Callback','preprocess window_cb median',...
3663 
+	'ListboxTop',0, ...
3664 
+	'Position',[0.3784722222222222 0.4611872146118721 0.06597222222222222 0.0821917808219178], ...
3665 
+	'Style','radiobutton', ...
3666 
+	'Tag','Radiobutton5');
3667 
+
3668 
+
3669 
+data.median_h=h1;
3670 
+
3671 
+h1 = uicontrol('Parent',h0, ...
3672 
+	'Units','normalized', ...
3673 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3674 
+	'Callback','preprocess window_cb max',...
3675 
+	'ListboxTop',0, ...
3676 
+	'Position',[0.3784722222222222 0.3515981735159817 0.06597222222222222 0.0821917808219178], ...
3677 
+	'Style','radiobutton', ...
3678 
+	'Tag','Radiobutton6');
3679 
+
3680 
+data.max_h=h1;
3681 
+
3682 
+h1 = uicontrol('Parent',h0, ...
3683 
+	'Units','normalized', ...
3684 
+	'Callback','preprocess window_cb min',...
3685 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3686 
+	'ListboxTop',0, ...
3687 
+	'Position',[0.3784722222222222 0.2374429223744292 0.06597222222222222 0.0821917808219178], ...
3688 
+	'Style','radiobutton', ...
3689 
+	'Tag','Radiobutton7');
3690 
+
3691 
+data.min_h = h1;
3692 
+
3693 
+h1 = uicontrol('Parent',h0, ...
3694 
+	'Units','normalized', ...
3695 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3696 
+	'Callback','preprocess window_cb clip',...
3697 
+	'ListboxTop',0, ...
3698 
+	'Position',[0.6909722222222222 0.5525114155251141 0.06597222222222222 0.0821917808219178], ...
3699 
+	'Style','radiobutton', ...
3700 
+	'Tag','Radiobutton8');
3701 
+
3702 
+data.clip_h=h1;
3703 
+data.eval_mode='clip';
3704 
+
3705 
+h1 = uicontrol('Parent',h0, ...
3706 
+	'Units','normalized', ...
3707 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3708 
+	'Callback','preprocess window_cb expand',...
3709 
+	'ListboxTop',0, ...
3710 
+	'Position',[0.6909722222222222 0.2922374429223744 0.06597222222222222 0.0821917808219178], ...
3711 
+	'Style','radiobutton', ...
3712 
+	'Tag','Radiobutton9');
3713 
+
3714 
+data.expand_h=h1;
3715 
+
3716 
+h1 = uicontrol('Parent',h0, ...
3717 
+	'Units','normalized', ...
3718 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3719 
+	'FontWeight','demi', ...
3720 
+	'FontSize',8,...
3721 
+	'HorizontalAlignment','left', ...
3722 
+	'ListboxTop',0, ...
3723 
+	'Position',[0.132 0.5799 0.19 0.0548], ...
3724 
+	'String','Centered', ...
3725 
+	'Style','text', ...
3726 
+	'Tag','StaticText2');
3727 
+h1 = uicontrol('Parent',h0, ...
3728 
+	'Units','normalized', ...
3729 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3730 
+	'FontWeight','demi', ...
3731 
+	'FontSize',8,...
3732 
+	'HorizontalAlignment','left', ...
3733 
+	'ListboxTop',0, ...
3734 
+	'Position',[0.132 0.4247 0.1667 0.0548], ...
3735 
+	'String','Previous', ...
3736 
+	'Style','text', ...
3737 
+	'Tag','StaticText3');
3738 
+h1 = uicontrol('Parent',h0, ...
3739 
+	'Units','normalized', ...
3740 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3741 
+	'FontWeight','demi', ...
3742 
+	'FontSize',8,...
3743 
+	'HorizontalAlignment','left', ...
3744 
+	'ListboxTop',0, ...
3745 
+	'Position',[0.132 0.2648 0.1632 0.0548], ...
3746 
+	'String','Next', ...
3747 
+	'Style','text', ...
3748 
+	'Tag','StaticText4');
3749 
+h1 = uicontrol('Parent',h0, ...,
3750 
+	'Units','normalized', ...
3751 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3752 
+	'FontWeight','demi', ...
3753 
+	'FontSize',8,...
3754 
+	'HorizontalAlignment','left', ...
3755 
+	'ListboxTop',0, ...
3756 
+	'Position',[0.445 0.6027397260273972 0.19 0.0547945205479452], ...
3757 
+	'String','Mean', ...
3758 
+	'Style','text', ...
3759 
+	'Tag','StaticText5');
3760 
+h1 = uicontrol('Parent',h0, ...
3761 
+	'Units','normalized', ...
3762 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3763 
+	'FontWeight','demi', ...
3764 
+	'FontSize',8,...
3765 
+	'HorizontalAlignment','left', ...
3766 
+	'ListboxTop',0, ...
3767 
+	'Position',[0.445 0.4795 0.1806 0.0548], ...
3768 
+	'String','Median', ...
3769 
+	'Style','text', ...
3770 
+	'Tag','StaticText6');
3771 
+
3772 
+h1 = uicontrol('Parent',h0, ...
3773 
+	'Units','normalized', ...
3774 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3775 
+	'FontWeight','demi', ...
3776 
+	'FontSize',8,...
3777 
+	'HorizontalAlignment','left', ...
3778 
+	'ListboxTop',0, ...
3779 
+	'Position',[0.445 0.3699 0.1667 0.0548], ...
3780 
+	'String','Max', ...
3781 
+	'Style','text', ...
3782 
+	'Tag','StaticText7');
3783 
+h1 = uicontrol('Parent',h0, ...
3784 
+	'Units','normalized', ...
3785 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3786 
+	'FontWeight','demi', ...
3787 
+	'FontSize',8,...
3788 
+	'HorizontalAlignment','left', ...
3789 
+	'ListboxTop',0, ...
3790 
+	'Position',[0.445 0.2557077625570776 0.1597222222222222 0.0547945205479452], ...
3791 
+	'String','Min', ...
3792 
+	'Style','text', ...
3793 
+	'Tag','StaticText8');
3794 
+h1 = uicontrol('Parent',h0, ...
3795 
+	'Units','normalized', ...
3796 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3797 
+	'FontWeight','demi', ...
3798 
+	'FontSize',8,...
3799 
+	'HorizontalAlignment','left', ...
3800 
+	'ListboxTop',0, ...
3801 
+	'Position',[0.7535 0.5753 0.1354 0.054], ...
3802 
+	'String','Clip', ...
3803 
+	'Style','text', ...
3804 
+	'Tag','StaticText9');
3805 
+h1 = uicontrol('Parent',h0, ...
3806 
+	'Units','normalized', ...
3807 
+	'BackgroundColor',[0.8 0.8 0.8], ...
3808 
+	'FontWeight','demi', ...
3809 
+	'FontSize',8,...
3810 
+	'HorizontalAlignment','left', ...
3811 
+	'ListboxTop',0, ...
3812 
+	'Position',[0.7534722222222222 0.3150684931506849 0.1527777777777778 0.0547945205479452], ...
3813 
+	'String','Expand', ...
3814 
+	'Style','text', ...
3815 
+	'Tag','StaticText10');
3816 
+
3817 
+
3818 
+
3819 
+set(gcf,'UserData',data);
3820 
+
3821 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3822 
+
3823 
+function window_cb(arg)
3824 
+
3825 
+data=get(gcf,'UserData');
3826 
+
3827 
+if any(strcmp(arg,[{'centered'},{'previous'},{'next'}]))
3828 
+  switch arg
3829 
+    case 'centered'
3830 
+     data.position='center';
3831 
+     set(data.previous_h,'Value',0);
3832 
+     set(data.next_h,'Value',0);
3833 
+     set(data.centered_h,'Value',1);
3834 
+    case 'previous'
3835 
+     data.position='previous';
3836 
+     set(data.centered_h,'Value',0);
3837 
+     set(data.next_h,'Value',0);
3838 
+     set(data.previous_h,'Value',1);
3839 
+    case 'next'
3840 
+     data.position='next';
3841 
+     set(data.centered_h,'Value',0);
3842 
+     set(data.previous_h,'Value',0);
3843 
+     set(data.next_h,'Value',1);
3844 
+  end
3845 
+elseif any(strcmp(arg,[{'mean'},{'median'},{'min'},{'max'}]))
3846 
+  switch arg
3847 
+    case 'mean'
3848 
+     data.mode='mean';
3849 
+     set(data.median_h,'Value',0);
3850 
+     set(data.min_h,'Value',0);
3851 
+     set(data.max_h,'Value',0);
3852 
+     set(data.mean_h,'Value',1);
3853 
+    case 'median'
3854 
+     data.mode='median';
3855 
+     set(data.mean_h,'Value',0);
3856 
+     set(data.max_h,'Value',0);
3857 
+     set(data.min_h,'Value',0);
3858 
+     set(data.median_h,'Value',1);
3859 
+    case 'max'
3860 
+     data.mode='max';
3861 
+     set(data.mean_h,'Value',0);
3862 
+     set(data.median_h,'Value',0);
3863 
+     set(data.min_h,'Value',0);
3864 
+     set(data.max_h,'Value',1);
3865 
+    case 'min'
3866 
+     data.mode='min';
3867 
+     set(data.mean_h,'Value',0);
3868 
+     set(data.median_h,'Value',0);
3869 
+     set(data.max_h,'Value',0);
3870 
+     set(data.min_h,'Value',1);
3871 
+  end
3872 
+elseif any(strcmp(arg,[{'clip','expand'}]))
3873 
+  switch arg
3874 
+    case 'clip'
3875 
+     data.eval_mode='clip';
3876 
+     set(data.expand_h,'Value',0);
3877 
+     set(data.clip_h,'Value',1);
3878 
+    case 'expand'
3879 
+     data.eval_mode='expand';
3880 
+     set(data.clip_h,'Value',0);
3881 
+     set(data.expand_h,'Value',1);
3882 
+  end
3883 
+end
3884 
+
3885 
+set(gcf,'UserData',data);
3886 
+
3887 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3888 
+
3889 
+function eval_windowed(varargin)
3890 
+
3891 
+if nargin == 1
3892 
+  LOG=1;
3893 
+  i=1;
3894 
+  arg=varargin{1};
3895 
+  while i <= length(arg) & arg(i) ~= ' '
3896 
+    i=i+1;
3897 
+  end
3898 
+  value=str2num(arg(1:i-1));
3899 
+  i=i+1;
3900 
+  j=i;
3901 
+  while i <= length(arg) & arg(i) ~= ' '
3902 
+    i=i+1;
3903 
+  end
3904 
+  position=arg(j:i-1);
3905 
+  i=i+1;
3906 
+  j=i;
3907 
+  while i <= length(arg) & arg(i) ~= ' '
3908 
+    i=i+1;
3909 
+  end
3910 
+  mode=arg(j:i-1);
3911 
+  i=i+1;
3912 
+  j=i;
3913 
+  while i <= length(arg) & arg(i) ~= ' '
3914 
+    i=i+1;
3915 
+  end
3916 
+  eval_mode=arg(j:i-1);
3917 
+else
3918 
+  LOG=0;
3919 
+end
3920 
+
3921 
+data=get(gcf,'UserData');
3922 
+if LOG
3923 
+  data.position=position;
3924 
+  data.eval_mode=eval_mode;
3925 
+  data.mode=mode;
3926 
+end
3927 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
3928 
+
3929 
+if isempty(pre_h)
3930 
+  errordlg('''Preprocess''-window does not exist. Terminating program...');
3931 
+  pro_tools('close');
3932 
+  return;
3933 
+end
3934 
+
3935 
+comp_names_h=getfield(get(pre_h,'UserData'),'comp_names_h');
3936 
+sData=getfield(get(pre_h,'UserData'),'sData');
3937 
+undo=sData;
3938 
+
3939 
+if isempty(get(comp_names_h,'Value'))
3940 
+ errordlg('There are not components chosen.');
3941 
+ return;
3942 
+end
3943 
+
3944 
+if ~LOG
3945 
+  if isempty(get(data.win_len_h,'String'))
3946 
+    errordlg('Window length must be defined');
3947 
+    return;
3948 
+  end
3949 
+
3950 
+  value=str2num(get(data.win_len_h,'String'));
3951 
+end
3952 
+
3953 
+set(data.win_len_h,'String','');
3954 
+
3955 
+if ~LOG
3956 
+  if isempty(value) | value < 0 | value ~= round(value)
3957 
+    errordlg('Window length must be positive integer.');
3958 
+    return;
3959 
+  end
3960 
+
3961 
+  if value > length(sData.data(:,1))
3962 
+    errordlg('Length of window is too big.');
3963 
+    return;
3964 
+  end
3965 
+end
3966 
+
3967 
+index=getfield(get_indices,{1});
3968 
+
3969 
+sData=eval_operation(sData,value,data.mode,data.eval_mode,data.position,index);
3970 
+sData.comp_norm(index)={[]};
3971 
+u_data=get(pre_h,'UserData');
3972 
+u_data.sData=sData;
3973 
+u_data.undo.sData=undo;
3974 
+u_data.undo.selected=u_data.selected_vects;
3975 
+
3976 
+if ~LOG
3977 
+  u_data.LOG{length(u_data.LOG)+1}=...
3978 
+    '% Evaluating the wanted ''windowed'' -operation.';
3979 
+  u_data.LOG{length(u_data.LOG)+1}=cat(2,'preprocess(''eval_windowed'',',...
3980 
+                                        '''',num2str(value),...
3981 
+                                       ' ',data.position,' ',data.mode,...
3982 
+                                       ' ',data.eval_mode,''');');
3983 
+end
3984 
+
3985 
+set(pre_h,'UserData',u_data);
3986 
+old=gcf;
3987 
+set(0,'CurrentFigure',pre_h);
3988 
+
3989 
+if strcmp(data.eval_mode,'expand');
3990 
+  write_sD_stats;
3991 
+  pro_tools('selall');
3992 
+else
3993 
+  sel_comp;
3994 
+  cplot_mimema;
3995 
+end
3996 
+
3997 
+set(0,'CurrentFigure',old);
3998 
+
3999 
+
4000 
+
4001 
+%%% Subfunction: eval_operation %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4002 
+
4003 
+
4004 
+function sData=eval_operation(sData,winlen,mode,evalmode,position,n)
4005 
+
4006 
+
4007 
+len=length(sData.data(:,1));
4008 
+dim=length(sData.data(1,:));
4009 
+
4010 
+switch(position)
4011 
+  case 'center'
4012 
+   prev=round(winlen/2)-1;
4013 
+   next=winlen-round(winlen/2);
4014 
+  case 'previous'
4015 
+   prev=winlen-1;
4016 
+   next=0;
4017 
+  case 'next'
4018 
+   prev=0;
4019 
+   next=winlen-1;
4020 
+end
4021 
+
4022 
+switch(evalmode)
4023 
+  case 'clip'
4024 
+   for center=1:len
4025 
+     win=center-prev:center-prev+winlen-1;
4026 
+     win=win(find(win > 0 & win <= len));
4027 
+     str=cat(2,mode,'(sData.data(win(find(~isnan(sData.data(win,n)))),n))');
4028 
+     tmp(center)=eval(str);
4029 
+   end
4030 
+   sData.data(:,n)=tmp;
4031 
+  case 'expand'
4032 
+   for i=1:len+winlen-1
4033 
+     win=i-(winlen-1):i;
4034 
+     win=win(find(win > 0 & win <= len));
4035 
+     str=cat(2,mode,'(sData.data(win(find(~isnan(sData.data(win,n)))),n))');
4036 
+     tmp(i)=eval(str);
4037 
+   end
4038 
+  sData.data=cat(1,repmat(NaN,next,dim),sData.data,repmat(NaN,prev,dim));
4039 
+  sData.data(:,n)=tmp;
4040 
+end
4041 
+
4042 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4043 
+
4044 
+
4045 
+
4046 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4047 
+
4048 
+function pro_tools(arg)
4049 
+
4050 
+switch arg
4051 
+  case 'close'
4052 
+   close_preprocess;
4053 
+  case 'c_stat'
4054 
+   write_c_stats;
4055 
+  case 'plot_hist'
4056 
+   plot_hist;
4057 
+  case 'plot'
4058 
+   plot_button;
4059 
+  case 'plxy'
4060 
+   plxy_button;
4061 
+  case 'bplo'
4062 
+   bplo_button;
4063 
+  case 'hist'
4064 
+   hist_button;
4065 
+end
4066 
+
4067 
+
4068 
+%%% Subfunction close_preprocess %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4069 
+
4070 
+function close_preprocess
4071 
+
4072 
+
4073 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
4074 
+man_h=findobj(get(0,'Children'),'Tag','Management');
4075 
+clip_h=findobj(get(0,'Children'),'Tag','Clipping');
4076 
+plot_h=findobj(get(0,'Children'),'Tag','PlotWin');
4077 
+delay_h=findobj(get(0,'Children'),'Tag','Delay');
4078 
+window_h=findobj(get(0,'Children'),'Tag','Window');
4079 
+sel_h=findobj(get(0,'Children'),'Tag','Select');
4080 
+
4081 
+if ~isempty(man_h)
4082 
+  close(man_h);
4083 
+end
4084 
+if ~isempty(clip_h)
4085 
+  close(clip_h);
4086 
+end
4087 
+if ~isempty(plot_h)
4088 
+  close(plot_h);
4089 
+end
4090 
+if ~isempty(delay_h)
4091 
+  close(delay_h);
4092 
+end
4093 
+if ~isempty(window_h)
4094 
+  close(window_h);
4095 
+end
4096 
+if ~isempty(sel_h)
4097 
+  close(sel_h);
4098 
+end
4099 
+if ~isempty(pre_h)
4100 
+  close(pre_h);
4101 
+end
4102 
+
4103 
+
4104 
+
4105 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4106 
+
4107 
+%%% Subfunction: undo %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4108 
+
4109 
+function undo(varargin)
4110 
+
4111 
+if nargin == 1
4112 
+  pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
4113 
+  set(0,'CurrentFigure',pre_h);
4114 
+  LOG=1;
4115 
+else
4116 
+  LOG=0;
4117 
+end
4118 
+
4119 
+data=get(gcf,'UserData');
4120 
+if ~isempty(data.undo)
4121 
+  if any(strcmp('selected',fieldnames(data.undo)))
4122 
+    data.selected_vects=data.undo.selected;
4123 
+  end
4124 
+  if ~any(strcmp('index',fieldnames(data.undo)))
4125 
+    data.sData=data.undo.sData;
4126 
+    data.undo=[];
4127 
+    if ~LOG
4128 
+      data.LOG{length(data.LOG)+1}='% Undo the most recent operation.';
4129 
+      data.LOG{length(data.LOG)+1}='preprocess(''undo'',''foo'');';
4130 
+    end
4131 
+    set(gcf,'UserData',data);
4132 
+    set_compnames(data.sData,data.comp_names_h);
4133 
+    write_sD_stats;
4134 
+    vect_means(data.sData,data.vect_mean_h,data.selected_vects);
4135 
+    sel_comp;
4136 
+    cplot_mimema;
4137 
+    return;
4138 
+  end
4139 
+
4140 
+  % 'undo.sData' does not exist in sD_set - array
4141 
+
4142 
+  index=data.undo.index;
4143 
+  data.undo.sData=rmfield(data.undo.sData,[{'INDEX'};{'MODIFIED'}]);
4144 
+  if index<=length(data.sD_set)
4145 
+    rest=data.sD_set(index:length(data.sD_set));
4146 
+  else
4147 
+    rest=[];
4148 
+  end
4149 
+  data.sD_set=cat(2,data.sD_set(1:index-1),data.undo.sData,rest);
4150 
+  data.undo=[];
4151 
+  if ~LOG
4152 
+    data.LOG{length(data.LOG)+1}='% Undo the most recent operation.';
4153 
+    data.LOG{length(data.LOG)+1}='preprocess(''undo'',''foo'');';
4154 
+  end
4155 
+  set(gcf,'UserData',data);
4156 
+  set(getfield(get(gcf,'UserData'),'sD_set_h'),'Value',index);
4157 
+  set_sD_stats;
4158 
+  sel_sD;
4159 
+else
4160 
+  msgbox('Can''t do...');
4161 
+end
4162 
+
4163 
+%%% Subfunction: write_c_stats %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4164 
+
4165 
+function write_c_stats(varargin)
4166 
+
4167 
+
4168 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
4169 
+comp_names_h=getfield(get(pre_h,'UserData'),'comp_names_h');
4170 
+sel_comp_h=getfield(get(pre_h,'UserData'),'sel_comp_h');
4171 
+sel_chist_h=getfield(get(pre_h,'UserData'),'sel_chist_h');
4172 
+
4173 
+if nargin==1
4174 
+  val1=varargin(1);
4175 
+else
4176 
+  val1=get(sel_comp_h,'String');
4177 
+end
4178 
+
4179 
+if ~isempty(val1) & iscell(val1)
4180 
+  selected_vects=getfield(get(pre_h,'UserData'),'selected_vects');
4181 
+  sData=getfield(get(pre_h,'UserData'),'sData');
4182 
+  sel_cdata_h=getfield(get(pre_h,'UserData'),'sel_cdata_h');
4183 
+  name=getfield(get(sel_comp_h,'String'),{get(sel_comp_h,'Value')});
4184 
+  name=name{1};
4185 
+  i=2;
4186 
+
4187 
+  while ~isempty(str2num(name(i)))
4188 
+   value(i-1)=name(i);
4189 
+   i=i+1;
4190 
+  end
4191 
+
4192 
+  value=str2num(value);
4193 
+
4194 
+
4195 
+  data=sData.data(selected_vects,value);
4196 
+
4197 
+  string{1} = cat(2,'Min: ',sprintf('%-10.3g',min(data)));
4198 
+  string{2} = cat(2,'Mean: ',sprintf('%-10.3g',mean(data(find(~isnan(data))))));
4199 
+  string{3} = cat(2,'Max: ',sprintf('%-10.3g',max(data)));
4200 
+  string{4} = cat(2,'Std: ',sprintf('%-10.3g',std(data(find(~isnan(data))))));
4201 
+  string{5} = cat(2,'Number of NaNs: ',sprintf('%-10.3g',sum(isnan(data))));
4202 
+  string{6} = cat(2,'NaN (%):',...
4203 
+                    sprintf('%-10.3g',100*sum(isnan(data))/length(data)));
4204 
+  string{7} = cat(2,'Number of values: ',sprintf('%-10.3g',...
4205 
+                    length(find(~isnan(unique(data))))));
4206 
+  set(sel_cdata_h,'String',string);
4207 
+  set(sel_cdata_h,'HorizontalAlignment','left');
4208 
+end
4209 
+
4210 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4211 
+
4212 
+%%% Subfunction plot_hist %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4213 
+
4214 
+function plot_hist
4215 
+
4216 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
4217 
+sel_chist_h=getfield(get(pre_h,'UserData'),'sel_chist_h');
4218 
+sData=getfield(get(pre_h,'UserData'),'sData');
4219 
+selected=getfield(get(pre_h,'UserData'),'selected_vects');
4220 
+
4221 
+value=get(getfield(get(pre_h,'UserData'),'sel_comp_h'),'Value');
4222 
+subplot(sel_chist_h);
4223 
+hold off;
4224 
+cla;
4225 
+if all(isnan(sData.data(:,value)));
4226 
+  return;
4227 
+end
4228 
+hold on;
4229 
+lim1=min(sData.data(:,value));
4230 
+lim2=max(sData.data(:,value));
4231 
+if lim2 - lim1 >= eps
4232 
+  x=lim1:(lim2-lim1)/(30-1):lim2;
4233 
+  set(sel_chist_h,'XLim',[lim1 lim2]);
4234 
+elseif lim1 ~= 0
4235 
+  x=(lim1)/2:lim1/(30-1):lim1+(lim1)/2;
4236 
+  set(sel_chist_h,'Xlim',[lim1-abs(lim1/2) lim1+abs(lim1/2)]);
4237 
+else
4238 
+  x=-1:2/(30-1):1;
4239 
+  set(sel_chist_h,'XLim',[-1 1]);
4240 
+end
4241 
+
4242 
+hist(sData.data(selected,value),x);
4243 
+
4244 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4245 
+
4246 
+%%% Subfunction: select_all %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4247 
+
4248 
+function select_all(varargin)
4249 
+
4250 
+if nargin == 1
4251 
+  LOG=1;
4252 
+else
4253 
+  LOG=0;
4254 
+end
4255 
+
4256 
+data=get(gcf,'UserData');
4257 
+data.selected_vects=(1:length(data.sData.data(:,1)));
4258 
+if ~LOG
4259 
+  data.LOG{length(data.LOG)+1}='% Select all vectors.';
4260 
+  data.LOG{length(data.LOG)+1}='selall(''foo'');';
4261 
+end
4262 
+set(gcf,'UserData',data);
4263 
+tmp=zeros(1,length(data.sData.data(:,1)));
4264 
+tmp(data.selected_vects)=1;
4265 
+draw_vectors(tmp,data.vector_h);
4266 
+cplot_mimema;
4267 
+vect_means(data.sData,data.vect_mean_h,data.selected_vects);
4268 
+sel_comp;
4269 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4270 
+
4271 
+%%% Subfunction: plot_button %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4272 
+
4273 
+function plot_button
4274 
+
4275 
+%PLOT_BUTTON  A callback function. Plots all the components and marks
4276 
+%             the chosen components.
4277 
+%
4278 
+%
4279 
+
4280 
+sData=getfield(get(gcf,'UserData'),'sData');
4281 
+selected=getfield(get(gcf,'UserData'),'selected_vects');
4282 
+
4283 
+indices=get_indices;
4284 
+if isempty(indices)
4285 
+  return;
4286 
+end
4287 
+h=findobj(get(0,'Children'),'Tag','PlotWin');
4288 
+if isempty(h)
4289 
+  h= figure;
4290 
+  set(h,'Tag','PlotWin');
4291 
+end
4292 
+
4293 
+names=sData.comp_names(indices);
4294 
+data=sData.data(:,indices);
4295 
+
4296 
+set(0,'CurrentFigure',h);
4297 
+hold off;
4298 
+clf;
4299 
+t=0:1/(getfield(size(data),{1})-1):1;
4300 
+tmp=setdiff(1:length(data(:,1)),selected);
4301 
+for i=1:length(names)
4302 
+  subplot(length(names),1,i);
4303 
+  hold on;
4304 
+  if max(data(:,i))- min(data(:,i)) <= eps
4305 
+    set(gca,'YLim',[max(data(:,i))-1 max(data(:,i))+1]);
4306 
+  end
4307 
+  plot(t,data(:,i));
4308 
+  if ~isempty(tmp);
4309 
+    data(tmp,i)=NaN;
4310 
+  end
4311 
+  plot(t,data(:,i),'red');
4312 
+  ylabel(names{i});
4313 
+  set(gca,'XTick',[]);
4314 
+end
4315 
+set(gcf,'Name','Plotted Data Components');
4316 
+
4317 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4318 
+
4319 
+%%% Subfunction: plxy_button %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4320 
+
4321 
+function plxy_button
4322 
+
4323 
+%PLXY_BUTTON  A callback function. XY-plots the first and the second
4324 
+%             components chosen.
4325 
+%
4326 
+%
4327 
+
4328 
+
4329 
+sData=getfield(get(gcf,'UserData'),'sData');
4330 
+selected=getfield(get(gcf,'UserData'),'selected_vects');
4331 
+
4332 
+inds = get_indices;
4333 
+if length(inds) < 2
4334 
+  errordlg('There must be two components chosen for XY-plot.');
4335 
+  return;
4336 
+end
4337 
+
4338 
+inds=inds(1:2);
4339 
+names=getfield(sData,'comp_names',{inds});
4340 
+
4341 
+h=findobj(get(0,'Children'),'Tag','PlotWin');
4342 
+
4343 
+if isempty(h)
4344 
+  h= figure;
4345 
+  set(h,'Tag','PlotWin');
4346 
+end
4347 
+
4348 
+set(0,'CurrentFigure',h);
4349 
+clf;
4350 
+axes;
4351 
+if max(sData.data(:,inds(1))) - min(sData.data(:,inds(1))) <= eps
4352 
+  set(gca,'XLim',[max(sData.data(:,inds(1)))-1 max(sData.data(:,inds(1)))+1]);
4353 
+end
4354 
+if max(sData.data(:,inds(2))) - min(sData.data(:,inds(2))) <= eps
4355 
+  set(gca,'YLim',[max(sData.data(:,inds(2)))-1 max(sData.data(:,inds(2)))+1]);
4356 
+end
4357 
+hold on;
4358 
+plot(sData.data(:,inds(1)),sData.data(:,inds(2)),'o');
4359 
+x=sData.data(selected,inds(1));
4360 
+y=sData.data(selected,inds(2));
4361 
+
4362 
+plot(x,y,'ored','MarkerSize',4);
4363 
+xlabel(names(1));
4364 
+ylabel(names(2));
4365 
+set(h,'Name','Plotted Data Components');
4366 
+
4367 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4368 
+
4369 
+%%% Sub_function: bplo_button %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4370 
+
4371 
+function bplo_button
4372 
+
4373 
+%BPLO_BUTTON  A callback function. Box-plots the first component chosen.
4374 
+
4375 
+
4376 
+sData=getfield(get(gcf,'UserData'),'sData');
4377 
+selected=getfield(get(gcf,'UserData'),'selected_vects');
4378 
+
4379 
+if length(selected) == 1
4380 
+  errordlg('There are too few vectors chosen for box-plotting.');
4381 
+else
4382 
+  indices=get_indices;
4383 
+  if isempty(indices)
4384 
+    return;
4385 
+  end
4386 
+  for i=1:length(indices)
4387 
+    if length(unique(sData.data(selected,indices(i))))==1
4388 
+      errordlg('All the values are the same. Operation can''t be evaluated.');
4389 
+      return;
4390 
+    end
4391 
+  end
4392 
+  names=getfield(sData,'comp_names',{indices});
4393 
+  h= findobj(get(0,'Children'),'Tag','PlotWin');
4394 
+  if isempty(h)
4395 
+    h= figure;
4396 
+    set(h,'Tag','PlotWin');
4397 
+  end
4398 
+
4399 
+  data=sData.data(selected,indices);
4400 
+
4401 
+  set(0,'CurrentFigure',h);
4402 
+  hold off;
4403 
+  clf;
4404 
+  hold on;
4405 
+  for i=1:getfield(size(data),{2})
4406 
+    subplot(getfield(size(data),{2}),1,i);
4407 
+    if ~all(isnan(data(:,i)))
4408 
+      boxplot(data(:,i));
4409 
+    end
4410 
+    name=names{i};
4411 
+    tmp=get(get(gca,'YLabel'),'String');
4412 
+    ylabel(cat(2,sprintf('[%s]    ',name),tmp));
4413 
+  end
4414 
+  set(h,'Name','Box-plot');
4415 
+end
4416 
+
4417 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4418 
+
4419 
+%%% Subfunction: hist_button %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4420 
+
4421 
+function hist_button
4422 
+
4423 
+no_of_bins_h=getfield(get(gcf,'UserData'),'no_of_bins_h');
4424 
+selected=getfield(get(gcf,'UserData'),'selected_vects');
4425 
+sData=getfield(get(gcf,'UserData'),'sData');
4426 
+n=str2num(get(no_of_bins_h,'String'));
4427 
+s1='Invalid number of bins.';
4428 
+s2=sprintf('\nSet new value to the box under the ''Histogram''-button.');
4429 
+
4430 
+if isempty(n)
4431 
+  errordlg(cat(2,s1,s2));
4432 
+else
4433 
+  indices=get_indices;
4434 
+  if isempty(indices)
4435 
+    return;
4436 
+  end
4437 
+  n=round(n);
4438 
+  if n < 1
4439 
+    errordlg('Number of bins must be positive integer.');
4440 
+  else
4441 
+    h= findobj(get(0,'Children'),'Tag','PlotWin');
4442 
+    if isempty(h)
4443 
+      h= figure;
4444 
+      set(h,'Tag','PlotWin');
4445 
+    end
4446 
+
4447 
+    set(0,'CurrentFigure',h);
4448 
+    hold off;
4449 
+    clf;
4450 
+    data=sData.data(selected,indices);
4451 
+    names=sData.comp_names(indices);
4452 
+    for i=1:length(names)
4453 
+      subplot(length(names),1,i);
4454 
+      hold on;
4455 
+      lim1=min(sData.data(:,indices(i)));
4456 
+      lim2=max(sData.data(:,indices(i)));
4457 
+      if n > 1
4458 
+        if lim2 - lim1 >= eps
4459 
+          x=lim1:(lim2-lim1)/(n-1):lim2;
4460 
+          set(gca,'XLim',[lim1 lim2]);
4461 
+        elseif lim1 ~= 0
4462 
+          x=lim1/2:lim1/(n-1):lim1/2+lim1;
4463 
+          if ~all(isnan([lim1 lim2]))
4464 
+            set(gca,'XLim',[lim1-abs(lim1/2) lim1+abs(lim1/2)]);
4465 
+          end
4466 
+        else
4467 
+          x=-1:2/(n-1):1;
4468 
+          set(gca,'XLim',[-1 1]);
4469 
+        end
4470 
+      else
4471 
+        x=1;
4472 
+        if lim2 ~= lim1
4473 
+          set(gca,'XLim',[lim1 lim2]);
4474 
+        else
4475 
+          set(gca,'XLim',[lim1/2 lim1/2+lim1]);
4476 
+        end
4477 
+      end
4478 
+      if ~all(isnan(data(:,i)))
4479 
+        hist(data(:,i),x);
4480 
+      end
4481 
+      name=names{i};
4482 
+      xlabel(name);
4483 
+    end
4484 
+    set(h,'Name','Histogram');
4485 
+  end
4486 
+end
4487 
+
4488 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4489 
+
4490 
+%%% Subfunction: no_of_values %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4491 
+
4492 
+function no_of_values(varargin);
4493 
+
4494 
+%NO_OF_VALUES  A callback function. Calculates the number of different
4495 
+%              values of the chosen components.
4496 
+%
4497 
+%
4498 
+
4499 
+if nargin==1;
4500 
+  LOG=1;
4501 
+else
4502 
+  LOG=0;
4503 
+end
4504 
+
4505 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
4506 
+results_h=getfield(get(pre_h,'UserData'),'results_h');
4507 
+sData=getfield(get(pre_h,'UserData'),'sData');
4508 
+selected=getfield(get(pre_h,'UserData'),'selected_vects');
4509 
+str1='There must be one component chosen for ''Number of Values''-operation';
4510 
+
4511 
+
4512 
+if ~LOG & isempty(get_indices)
4513 
+  errordlg(str1);
4514 
+else
4515 
+  indices=get_indices;
4516 
+  data=sData.data(selected,indices);
4517 
+
4518 
+  string{1} = 'Number of different values:';
4519 
+
4520 
+  for i=1:getfield(size(data),{2})
4521 
+
4522 
+    tmp=data(:,i);
4523 
+    string{i+1}=cat(2,sprintf('#%d:',indices(i)),...
4524 
+                      sprintf('%d',length(find(~isnan(unique(data(:,i)))))));
4525 
+  end
4526 
+
4527 
+  set(results_h,'String',string);
4528 
+  set(results_h,'HorizontalAlignment','left');
4529 
+  if ~LOG
4530 
+    data=get(pre_h,'UserData');
4531 
+    data.LOG{length(data.LOG)+1}='% Number of values';
4532 
+    data.LOG{length(data.LOG)+1}='preprocess(''noof'',''foo'');';
4533 
+    set(pre_h,'UserData',data);
4534 
+  end
4535 
+end
4536 
+
4537 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4538 
+
4539 
+%%% Subfunction: correlation %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4540 
+
4541 
+function correlation(varargin)
4542 
+
4543 
+if nargin == 1
4544 
+  LOG=1;
4545 
+else
4546 
+  LOG=0;
4547 
+end
4548 
+
4549 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
4550 
+results_h=getfield(get(pre_h,'UserData'),'results_h');
4551 
+selected=getfield(get(pre_h,'UserData'),'selected_vects');
4552 
+sData=getfield(get(pre_h,'UserData'),'sData');
4553 
+
4554 
+if length(get_indices) < 2
4555 
+  errordlg('There must be two components chosen for Correlation');
4556 
+else
4557 
+  indices=getfield(get_indices,{1:2});
4558 
+  data=sData.data(selected,indices);
4559 
+  inds=find(~isnan(data(:,1)) & ~isnan(data(:,2)));
4560 
+  value=getfield(corrcoef(data(inds,1),data(inds,2)),{1,2});
4561 
+  names=sData.comp_names(indices);
4562 
+  string{1}='Correlation between';
4563 
+  string{2}=cat(2,names{1},' and ',names{2},':');
4564 
+  string{3}=sprintf('%-10.3g',value);
4565 
+
4566 
+  set(results_h,'String',string);
4567 
+  set(results_h,'HorizontalAlignment','left');
4568 
+  if ~LOG
4569 
+    data=get(pre_h,'UserData');
4570 
+    data.LOG{length(data.LOG)+1}='% Correlation';
4571 
+    data.LOG{length(data.LOG)+1}='preprocess(''corr'',''foo'');';
4572 
+    set(pre_h,'UserData',data);
4573 
+  end
4574 
+end
4575 
+
4576 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4577 
+
4578 
+%%% Subfunction: unit_length %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4579 
+
4580 
+function unit_length(varargin)
4581 
+
4582 
+%UNIT_LENGTH  A callback function Scales all the vectors to the unit
4583 
+%             length.
4584 
+%
4585 
+%
4586 
+
4587 
+if nargin==1
4588 
+  LOG=1;
4589 
+else
4590 
+  LOG=0;
4591 
+end
4592 
+
4593 
+vect_mean_h=getfield(get(gcf,'UserData'),'vect_mean_h');
4594 
+sData=getfield(get(gcf,'UserData'),'sData');
4595 
+sData.MODIFIED=1;
4596 
+scaled=sData.data;
4597 
+comp_names_h=getfield(get(gcf,'UserData'),'comp_names_h');
4598 
+
4599 
+if ~LOG & isempty(get(comp_names_h,'Value'))
4600 
+  errordlg('There must be components chosen for the ''unit length''- operation');
4601 
+  return;
4602 
+end
4603 
+inds=get_indices;
4604 
+for i=1:length(scaled(:,1));
4605 
+  x=find(~isnan(scaled(i,inds)));
4606 
+  scaled(i,inds(x))=(1/sqrt(sum(scaled(i,inds(x)).^2)))*scaled(i,inds(x));
4607 
+end
4608 
+
4609 
+data=get(gcf,'UserData');
4610 
+
4611 
+
4612 
+data.undo.sData = sData;
4613 
+data.sData.data=scaled;
4614 
+
4615 
+for i=1:length(inds)
4616 
+  data.sData.comp_norm{inds(i)}=[];
4617 
+end
4618 
+
4619 
+if ~LOG
4620 
+  data.LOG{length(data.LOG)+1}='% Unit length';
4621 
+  data.LOG{length(data.LOG)+1}='preprocess(''unit'',''foo'');';
4622 
+end
4623 
+set(gcf,'UserData',data);
4624 
+
4625 
+vects=zeros(1,length(sData.data(:,1)));
4626 
+vects(data.selected_vects)=1;
4627 
+
4628 
+draw_vectors(vects,data.vector_h);
4629 
+vect_means(sData,vect_mean_h,data.selected_vects);
4630 
+cplot_mimema;
4631 
+plot_hist;
4632 
+
4633 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4634 
+
4635 
+%%% Subfunction: one_of_n %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4636 
+
4637 
+function one_of_n(varargin)
4638 
+
4639 
+if nargin==1
4640 
+  LOG=1;
4641 
+else
4642 
+  LOG=0;
4643 
+end
4644 
+
4645 
+data=get(gcf,'UserData');
4646 
+vector_h=getfield(get(gcf,'Userdata'),'vector_h');
4647 
+comp_names_h=getfield(get(gcf,'Userdata'),'comp_names_h');
4648 
+vect_mean_h=getfield(get(gcf,'UserData'),'vect_mean_h');
4649 
+sData=data.sData;
4650 
+undo=data.sData;
4651 
+selected=getfield(get(gcf,'UserData'),'selected_vects');
4652 
+msg='Creating over 10 new components. Stop operation?';
4653 
+
4654 
+if ~LOG
4655 
+  if isempty(get(data.comp_names_h,'Value'))
4656 
+    errordlg('There must be one component chosen for ''Add: N binary types'' -operation');
4657 
+    return;
4658 
+  end
4659 
+end
4660 
+
4661 
+index=getfield(get_indices,{1});
4662 
+
4663 
+tmp=unique(sData.data(:,index));
4664 
+n=length(tmp);
4665 
+
4666 
+if ~LOG
4667 
+  if n>10
4668 
+    answer=questdlg(msg,'Question','Yes','No','Yes');
4669 
+
4670 
+    if strcmp(answer,'Yes')
4671 
+      msgbox('Operation stopped.');
4672 
+      return;
4673 
+    end
4674 
+
4675 
+  end
4676 
+end
4677 
+
4678 
+dim1=getfield(size(sData.data),{1});
4679 
+dim2=getfield(size(sData.data),{2});
4680 
+sData.data=cat(2,sData.data,zeros(dim1,n));
4681 
+
4682 
+dim=dim2+n;
4683 
+for i=1:n
4684 
+  sData.data(:,dim-(n-i))=(sData.data(:,index) == tmp(i));
4685 
+end
4686 
+
4687 
+INDEX=sData.INDEX;
4688 
+for i=1:n
4689 
+  sData.comp_names{dim2+i}=sprintf('%dNewVar',dim2+i);
4690 
+end
4691 
+tmp_norm=cat(1,sData.comp_norm,cell(n,1));
4692 
+sData=som_data_struct(sData.data,...
4693 
+                      'name',sData.name,...
4694 
+                      'labels',sData.labels,...
4695 
+                      'comp_names',sData.comp_names);
4696 
+
4697 
+sData.MODIFIED=1;
4698 
+sData.INDEX=INDEX;
4699 
+sData.comp_norm=tmp_norm;
4700 
+data.undo.sData=undo;
4701 
+data.sData=sData;
4702 
+data.selected_vects=1:length(sData.data(:,1));
4703 
+if ~LOG
4704 
+  data.LOG{length(data.LOG)+1}='% Add: N binary types';
4705 
+  data.LOG{length(data.LOG)+1}='preprocess(''oneo'',''foo'');';
4706 
+end
4707 
+set(gcf,'UserData',data);
4708 
+clear_button;
4709 
+write_sD_stats;
4710 
+set_compnames(sData,comp_names_h);
4711 
+tmp=ones(1,length(sData.data(:,1)));
4712 
+draw_vectors(tmp,vector_h);
4713 
+vect_means(sData,vect_mean_h,1:length(sData.data(:,1)));
4714 
+cplot_mimema;
4715 
+sel_comp;
4716 
+
4717 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4718 
+
4719 
+%%% Subfunction: add_zeros %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4720 
+
4721 
+function add_zeros(varargin)
4722 
+
4723 
+if nargin == 1
4724 
+  LOG=1;
4725 
+else
4726 
+  LOG=0;
4727 
+end
4728 
+
4729 
+data=get(gcf,'UserData');
4730 
+vector_h=getfield(get(gcf,'Userdata'),'vector_h');
4731 
+comp_names_h=getfield(get(gcf,'Userdata'),'comp_names_h');
4732 
+vect_mean_h=getfield(get(gcf,'UserData'),'vect_mean_h');
4733 
+sData=data.sData;
4734 
+undo=sData;
4735 
+
4736 
+dim1=getfield(size(sData.data),{1});
4737 
+dim2=getfield(size(sData.data),{2});
4738 
+sData.data=cat(2,sData.data,zeros(dim1,1));
4739 
+
4740 
+INDEX=sData.INDEX;
4741 
+
4742 
+sData.comp_names{dim2+1}=sprintf('%dNewVar',dim2+1);
4743 
+tmp_norm=cat(1,sData.comp_norm,cell(1,1));
4744 
+sData=som_data_struct(sData.data,...
4745 
+                      'name',sData.name,...
4746 
+                      'labels',sData.labels,...
4747 
+                      'comp_names',sData.comp_names);
4748 
+
4749 
+sData.MODIFIED=1;
4750 
+sData.INDEX=INDEX;
4751 
+sData.comp_norm=tmp_norm;
4752 
+data.sData=sData;
4753 
+data.undo.sData=undo;
4754 
+data.selected_vects=1:length(sData.data(:,1));
4755 
+if ~LOG
4756 
+  data.LOG{length(data.LOG)+1}='% Add: zeros';
4757 
+  data.LOG{length(data.LOG)+1}='preprocess(''zero'',''foo'');';
4758 
+end
4759 
+set(gcf,'UserData',data);
4760 
+clear_button;
4761 
+write_sD_stats;
4762 
+set_compnames(sData,comp_names_h);
4763 
+tmp=ones(1,length(sData.data(:,1)));
4764 
+draw_vectors(tmp,vector_h);
4765 
+vect_means(sData,vect_mean_h,1:length(sData.data(:,1)));
4766 
+cplot_mimema;
4767 
+sel_comp;
4768 
+
4769 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4770 
+
4771 
+%%% Subfunction: move_component %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4772 
+
4773 
+function move_component(varargin)
4774 
+
4775 
+%MOVE_COMPONENT  A callback function. Moves one component of vectors to
4776 
+%                the position wanted.
4777 
+%
4778 
+%
4779 
+
4780 
+if nargin == 1
4781 
+  LOG=1;
4782 
+  i=1;
4783 
+  while varargin{1}(i) ~= ' '
4784 
+    value(i)=varargin{1}(i);
4785 
+    i=i+1;
4786 
+  end
4787 
+  value=str2num(value);                                 % the new place
4788 
+  index=str2num(varargin{1}(i:length(varargin{1})));    % index of the chosen
4789 
+                                                        % component
4790 
+else
4791 
+  LOG=0;
4792 
+end
4793 
+
4794 
+data=get(gcf,'UserData');
4795 
+sData=data.sData;
4796 
+undo=sData;
4797 
+prompt='Enter the number of the new component place:';
4798 
+
4799 
+
4800 
+if isempty(get(data.comp_names_h,'Value'))
4801 
+  errordlg('There must be one component chosen for ''Move Component''-operation');
4802 
+  return;
4803 
+end
4804 
+
4805 
+if ~LOG
4806 
+  index=getfield(get_indices,{1});
4807 
+  answer=inputdlg(prompt);
4808 
+
4809 
+  if isempty(answer) | (iscell(answer) & isempty(answer{1}))
4810 
+    msgbox('No components moved');
4811 
+    return;
4812 
+  end
4813 
+
4814 
+  value=str2num(answer{1});
4815 
+
4816 
+
4817 
+  dims=size(value);
4818 
+
4819 
+  if dims(1) ~= 1 | dims(2) ~= 1 | ~isreal(value)
4820 
+    errordlg('The new component place must be positive integer.')
4821 
+    return;
4822 
+  end
4823 
+
4824 
+  if value <= 0 | round(value) ~= value
4825 
+    errordlg('The new component place must be positive integer.');
4826 
+    return;
4827 
+  end
4828 
+
4829 
+  if value > getfield(size(sData.data),{2})
4830 
+    errordlg('Too big value for the new component place.');
4831 
+    return;
4832 
+  end
4833 
+end
4834 
+
4835 
+sData.MODIFIED=1;
4836 
+if index < value
4837 
+  indices1=setdiff(1:value,index);
4838 
+  indices2=setdiff(value+1:length(sData.data(1,:)),index);
4839 
+elseif index > value
4840 
+  indices1=setdiff(1:value-1,index);
4841 
+  indices2=setdiff(value:length(sData.data(1,:)),index);
4842 
+else
4843 
+  data.sData=sData;
4844 
+  data.undo.sData=undo;
4845 
+  set(gcf,'UserData',data);
4846 
+  return;
4847 
+end
4848 
+
4849 
+tmp1=sData.data(:,indices1);
4850 
+tmp2=sData.data(:,indices2);
4851 
+sData.data=cat(2,tmp1,sData.data(:,index),tmp2);
4852 
+
4853 
+tmp1=sData.comp_names(indices1);
4854 
+tmp2=sData.comp_names(indices2);
4855 
+sData.comp_names=cat(1,tmp1,sData.comp_names(index),tmp2);
4856 
+
4857 
+tmp1=sData.comp_norm(indices1);
4858 
+tmp2=sData.comp_norm(indices2);
4859 
+sData.comp_norm=cat(1,tmp1,sData.comp_norm(index),tmp2);
4860 
+
4861 
+data.sData=sData;
4862 
+data.undo.sData=undo;
4863 
+if ~LOG
4864 
+  data.LOG{length(data.LOG)+1}='% Move component.';
4865 
+  data.LOG{length(data.LOG)+1}=sprintf('preprocess(''move'',''%s %s'');',...
4866 
+           num2str(value),num2str(index));
4867 
+end
4868 
+comp_names_h=getfield(get(gcf,'UserData'),'comp_names_h');
4869 
+vect_mean_h=getfield(get(gcf,'UserData'),'vect_mean_h');
4870 
+vector_h=getfield(get(gcf,'UserData'),'vector_h');
4871 
+data.selected_vects=1:length(sData.data(:,1));
4872 
+set(gcf,'UserData',data);
4873 
+clear_button;
4874 
+set_compnames(sData,comp_names_h);
4875 
+draw_vectors(ones(1,length(sData.data(:,1))),vector_h);
4876 
+vect_means(sData,vect_mean_h,data.selected_vects);
4877 
+cplot_mimema;
4878 
+sel_comp;
4879 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4880 
+
4881 
+%%% Subfunction: copy_component %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4882 
+
4883 
+function copy_component(varargin)
4884 
+
4885 
+%COPY_COMPONENT  Copies one component of vectors to the position wanted.
4886 
+%
4887 
+%
4888 
+
4889 
+if nargin == 1
4890 
+  LOG=1;
4891 
+  i=1;
4892 
+  while varargin{1}(i) ~= ' '
4893 
+    value(i)=varargin{1}(i);
4894 
+    i=i+1;
4895 
+  end
4896 
+  value=str2num(value);                                 % the new place
4897 
+  index=str2num(varargin{1}(i:length(varargin{1})));    % index of the chosen
4898 
+                                                        % component
4899 
+else
4900 
+  LOG=0;
4901 
+end
4902 
+
4903 
+
4904 
+data=get(gcf,'UserData');
4905 
+sData=data.sData;
4906 
+undo=sData;
4907 
+if ~LOG
4908 
+  prompt='Enter the number of the new component place:';
4909 
+
4910 
+
4911 
+  if isempty(get(data.comp_names_h,'Value'))
4912 
+    errordlg('There must be one component chosen for ''Copy Component''-operation');
4913 
+    return;
4914 
+  end
4915 
+
4916 
+  index=getfield(get_indices,{1});
4917 
+  answer=inputdlg(prompt);
4918 
+
4919 
+  if isempty(answer) | (iscell(answer) & isempty(answer{1}))
4920 
+    msgbox('No components moved');
4921 
+    return
4922 
+  end
4923 
+
4924 
+
4925 
+  value=str2num(answer{1});
4926 
+  dims=size(value);
4927 
+
4928 
+  if dims(1) ~= 1 | dims(2) ~= 1 | ~isreal(value)
4929 
+    errordlg('The new component place must be positive integer.')
4930 
+    return;
4931 
+  end
4932 
+
4933 
+  if value <= 0 | round(value) ~= value
4934 
+    errordlg('The new component place must be positive integer.');
4935 
+    return;
4936 
+  end
4937 
+
4938 
+  if value > getfield(size(sData.data),{2}) + 1
4939 
+    errordlg('Too big value for the new component place.');
4940 
+    return;
4941 
+  end
4942 
+end
4943 
+
4944 
+sData.MODIFIED=1;
4945 
+
4946 
+indices1=1:value-1;
4947 
+indices2=value:length(sData.data(1,:));
4948 
+tmp1=sData.data(:,indices1);
4949 
+tmp2=sData.data(:,indices2);
4950 
+sData.data=cat(2,tmp1,sData.data(:,index),tmp2);
4951 
+
4952 
+tmp1=sData.comp_names(indices1);
4953 
+tmp2=sData.comp_names(indices2);
4954 
+name=cell(1,1);
4955 
+name{1}=cat(2,'Copied',sData.comp_names{index});
4956 
+sData.comp_names=cat(1,tmp1,name,tmp2);
4957 
+
4958 
+tmp1=sData.comp_norm(indices1);
4959 
+tmp2=sData.comp_norm(indices2);
4960 
+norm=cell(1,1);
4961 
+norm{1}=sData.comp_norm{index};
4962 
+sData.comp_norm=cat(1,tmp1,norm,tmp2);
4963 
+
4964 
+data.sData=sData;
4965 
+data.undo.sData=undo;
4966 
+if ~LOG
4967 
+  data.LOG{length(data.LOG)+1}='% Copy component';
4968 
+  data.LOG{length(data.LOG)+1}=sprintf('preprocess(''copy'',''%s %s'');',...
4969 
+           num2str(value),num2str(index));
4970 
+end
4971 
+
4972 
+
4973 
+comp_names_h=getfield(get(gcf,'UserData'),'comp_names_h');
4974 
+vect_mean_h=getfield(get(gcf,'UserData'),'vect_mean_h');
4975 
+vector_h=getfield(get(gcf,'UserData'),'vector_h');
4976 
+data.selected_vects=1:length(sData.data(:,1));
4977 
+set(gcf,'UserData',data);
4978 
+clear_button;
4979 
+write_sD_stats;
4980 
+set_compnames(sData,comp_names_h);
4981 
+draw_vectors(ones(1,length(sData.data(:,1))),vector_h);
4982 
+vect_means(sData,vect_mean_h,data.selected_vects);
4983 
+cplot_mimema;
4984 
+sel_comp;
4985 
+
4986 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4987 
+
4988 
+%%% Subfunction: remove_component %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
4989 
+
4990 
+function remove_component(varargin)
4991 
+
4992 
+if nargin == 1
4993 
+  LOG=1;
4994 
+  value=str2num(varargin{1});
4995 
+else
4996 
+  LOG=0;
4997 
+end
4998 
+
4999 
+data=get(gcf,'UserData');
5000 
+vect_mean_h=getfield(get(gcf,'UserData'),'vect_mean_h');
5001 
+vector_h=getfield(get(gcf,'UserData'),'vector_h');
5002 
+comp_names_h=getfield(get(gcf,'UserData'),'comp_names_h');
5003 
+sData=data.sData;
5004 
+undo=sData;
5005 
+prompt='Enter the number of component to be removed.';
5006 
+dim=length(sData.data(1,:));
5007 
+
5008 
+if ~LOG
5009 
+  answer=inputdlg(prompt);
5010 
+
5011 
+  if isempty(answer) | (iscell(answer) & isempty(answer{1}))
5012 
+    msgbox('Components not removed.');
5013 
+    return;
5014 
+  end
5015 
+
5016 
+  value=str2num(answer{1});
5017 
+  dims=size(value);
5018 
+
5019 
+  if dims(1) ~= 1 | dims(2) ~= 1 | ~isreal(value)
5020 
+    errordlg('Number of the component to be removed must be positive integer.')
5021 
+    return;
5022 
+  end
5023 
+
5024 
+  if value <= 0 | round(value) ~= value
5025 
+    errordlg('Number of the component to be removed must be positive integer.');
5026 
+    return;
5027 
+  end
5028 
+
5029 
+  if value > getfield(size(sData.data),{2})
5030 
+    errordlg('There are less components.');
5031 
+    return;
5032 
+  end
5033 
+end
5034 
+
5035 
+sD_set_h=getfield(get(gcf,'UserData'),'sD_set_h');
5036 
+index=get(sD_set_h,'Value');
5037 
+if value == 1 & getfield(size(sData.data),{2}) == 1
5038 
+   if length(get(sD_set_h,'String')) == 1
5039 
+    msgbox('No data left. Closing program...')
5040 
+    pro_tools('close');
5041 
+    return;
5042 
+  end
5043 
+
5044 
+  set1=data.sD_set(1:index-1);
5045 
+  set2=data.sD_set(index+1:length(data.sD_set));
5046 
+  data.sD_set=[set1 set2];
5047 
+   set(gcf,'UserData',data);
5048 
+
5049 
+  set_sD_stats;
5050 
+  sel_sD;
5051 
+  data=get(gcf,'UserData');
5052 
+  data.undo.sData=undo;
5053 
+  data.undo.index=index;
5054 
+  set(gcf,'UserData',data);
5055 
+  return;
5056 
+end
5057 
+dims=size(sData.data);
5058 
+tmp_data=cat(2,sData.data(:,1:value-1),sData.data(:,value+1:dims(2)));
5059 
+tmp_norm=cat(1,sData.comp_norm(1:value-1),sData.comp_norm(value+1:dims(2)));
5060 
+names=cat(1,sData.comp_names(1:value-1),sData.comp_names(value+1:dims(2)));
5061 
+INDEX=sData.INDEX;
5062 
+comp_norm=sData.comp_norm;
5063 
+sData=som_data_struct(tmp_data,...
5064 
+                      'name',sData.name,...
5065 
+                      'labels',sData.labels,...
5066 
+                      'comp_names',names);
5067 
+sData.comp_norm=tmp_norm;
5068 
+sData.MODIFIED=1;
5069 
+sData.INDEX=INDEX;
5070 
+data=get(gcf,'UserData');
5071 
+data.sData=sData;
5072 
+data.undo.sData=undo;
5073 
+data.selected_vects=1:length(sData.data(:,1));
5074 
+if ~LOG
5075 
+  data.LOG{length(data.LOG)+1}='% Remove component';
5076 
+  data.LOG{length(data.LOG)+1}=sprintf('preprocess(''remove'',''%s'');',...
5077 
+                                        answer{1});
5078 
+end
5079 
+set(gcf,'UserData',data);
5080 
+clear_button;
5081 
+write_sD_stats;
5082 
+set_compnames(sData,comp_names_h);
5083 
+tmp=ones(1,length(sData.data(:,1)));
5084 
+draw_vectors(tmp,vector_h);
5085 
+vect_means(sData,vect_mean_h,1:length(sData.data(:,1)));
5086 
+cplot_mimema;
5087 
+sel_comp;
5088 
+
5089 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5090 
+
5091 
+%%% Subfunction: remove_vects %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5092 
+
5093 
+function remove_vects(varargin)
5094 
+
5095 
+if nargin==1
5096 
+  LOG=1;
5097 
+  tmp_str=varargin{1};
5098 
+else
5099 
+  LOG=0;
5100 
+  tmp_str='_foo';
5101 
+end
5102 
+data=get(gcf,'UserData');
5103 
+vect_mean_h=data.vect_mean_h;
5104 
+vector_h=data.vector_h;
5105 
+sData=data.sData;
5106 
+undo=sData;
5107 
+
5108 
+if length(data.selected_vects) == getfield(size(sData.data),{1})
5109 
+  if LOG
5110 
+    answer='Yes';
5111 
+  else
5112 
+    answer=questdlg('Do you want to delete this data set?');
5113 
+  end
5114 
+  if strcmp(answer,'No')
5115 
+    return;
5116 
+  else
5117 
+    index=get(data.sD_set_h,'Value');
5118 
+    if length(get(data.sD_set_h,'String')) == 1
5119 
+      msgbox('No data left. Closing program...')
5120 
+      pro_tools('close');
5121 
+      return;
5122 
+    end
5123 
+
5124 
+    set1=data.sD_set(1:index-1);
5125 
+    set2=data.sD_set(index+1:length(data.sD_set));
5126 
+    data.sD_set=[set1 set2];
5127 
+    set(gcf,'UserData',data);
5128 
+
5129 
+    set(data.sD_set_h,'Value',1);
5130 
+    set_sD_stats;
5131 
+    sel_sD;
5132 
+    data=get(gcf,'UserData');
5133 
+    data.undo.sData=undo;
5134 
+    data.undo.index=index;
5135 
+    if ~LOG
5136 
+      data.LOG{length(data.LOG)+1}='% Remove selected vectors';
5137 
+      data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''remove_vects'',''',...
5138 
+                                          tmp_str,''');');
5139 
+    end
5140 
+    set(gcf,'UserData',data);
5141 
+    return;
5142 
+  end
5143 
+end
5144 
+
5145 
+tmp=sData.data(data.selected_vects,:);
5146 
+if ~LOG
5147 
+  answer=questdlg('Do you want to save removed values to workspace?');
5148 
+else
5149 
+  if ~strcmp(tmp_str,'_foo')
5150 
+    answer='Yes';
5151 
+  else
5152 
+    answer='No';
5153 
+  end
5154 
+end
5155 
+old=gcf;
5156 
+if strcmp(answer,'Yes')
5157 
+  if ~LOG
5158 
+    answer=inputdlg('Give the name of the output -variable.');
5159 
+  else
5160 
+    answer={tmp_str};
5161 
+  end
5162 
+  if isvalid_var_name(answer)
5163 
+    assignin('base',answer{1},tmp);
5164 
+    disp(sprintf('Removed values are set to workspace as''%s''.',answer{1}));
5165 
+    tmp_str=answer{1};
5166 
+  end
5167 
+end
5168 
+set(0,'CurrentFigure',old);
5169 
+sData.data(data.selected_vects,:)=[];
5170 
+sData.labels(data.selected_vects,:)=[];
5171 
+sData.MODIFIED=1;
5172 
+data.sData=sData;
5173 
+data.selected=1:length(sData.data(:,1));
5174 
+data.undo.sData=undo;
5175 
+if ~LOG
5176 
+  data.LOG{length(data.LOG)}='% Remove selected vectors';
5177 
+  data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''remove_vects'',''',...
5178 
+                                      tmp_str,''');');
5179 
+end
5180 
+set(gcf,'UserData',data);
5181 
+
5182 
+
5183 
+draw_vectors(ones(1,length(data.selected)),data.vector_h);
5184 
+write_sD_stats;
5185 
+select_all('foo');
5186 
+
5187 
+
5188 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5189 
+
5190 
+
5191 
+
5192 
+
5193 
+%%% Subfunction: eval1 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5194 
+
5195 
+function eval1(varargin);
5196 
+
5197 
+if nargin == 1
5198 
+  answer=varargin
5199 
+  LOG=1;
5200 
+else
5201 
+  LOG=0;
5202 
+end
5203 
+
5204 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
5205 
+if isempty(pre_h)
5206 
+  errordlg('''Preprocess''-figure does not exist. Terminating program...');
5207 
+  pro_tools('close');
5208 
+  return;
5209 
+end
5210 
+
5211 
+undo=getfield(get(pre_h,'UserData'),'sData');
5212 
+
5213 
+if ~LOG
5214 
+  prompt={'Enter the expression to be evaluated.',...
5215 
+          'Enter the inverse normalization method (optional).'};
5216 
+  title='Single component eval.';
5217 
+  answer= inputdlg(prompt,title,1);
5218 
+end
5219 
+
5220 
+if ~isempty(answer)
5221 
+  tmp=[];
5222 
+  if ~isempty(answer{1})
5223 
+    [tmp,method]=build_expr(answer{1},'single');
5224 
+    if ~isstr(tmp)
5225 
+      sData=getfield(get(gcf,'UserData'),'sData');
5226 
+      tmp='Done.';
5227 
+      %if ~isempty(answer{2})
5228 
+      %  sN=som_norm_struct('eval',{method,answer{2}});
5229 
+      %else
5230 
+      %  sN=som_norm_struct('eval',{method});
5231 
+      %end
5232 
+      %sN=som_set(sN,'status','done');
5233 
+      params={answer{1};answer{2}};
5234 
+      ind=getfield(get_indices,{1});
5235 
+      x.type='';
5236 
+      x.method='eval';
5237 
+      x.params={answer{1};answer{2}};
5238 
+      x.status='';
5239 
+      sData.comp_norm{ind}=x;
5240 
+      data=get(gcf,'UserData');
5241 
+      data.undo.sData=undo;
5242 
+      data.sData=sData;
5243 
+      if ~LOG
5244 
+        data.LOG{length(data.LOG)+1}='% Eval (1-comp)';
5245 
+        data.LOG{length(data.LOG)+1}=cat(2,'preprocess eval1 ',...
5246 
+                 sprintf('{''%s''  ''%s''};',answer{1},answer{2}));
5247 
+      end
5248 
+      set(pre_h,'UserData',data);
5249 
+
5250 
+    end
5251 
+  end
5252 
+  set(getfield(get(pre_h,'UserData'),'results_h'),'String',tmp);
5253 
+end
5254 
+
5255 
+
5256 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5257 
+
5258 
+%%% Subfunction: eval2
5259 
+
5260 
+function eval2(varargin)
5261 
+
5262 
+if nargin == 1
5263 
+  answer=varargin{1};
5264 
+  LOG=1;
5265 
+else
5266 
+  LOG=0;
5267 
+end
5268 
+
5269 
+undo=getfield(get(gcf,'UserData'),'sData');
5270 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
5271 
+
5272 
+if isempty(pre_h)
5273 
+  errordlg('''Preprocess''-figure does not exist. Terminating program.');
5274 
+  pro_tools('close');
5275 
+  return;
5276 
+end
5277 
+
5278 
+if ~LOG
5279 
+  prompt='Enter the expression to be evaluated.';
5280 
+  title ='Eval';
5281 
+  answer=inputdlg(prompt,title,1);
5282 
+end
5283 
+
5284 
+if ~isempty(answer) & ~isempty(answer{1})
5285 
+   str=answer{1};
5286 
+   [answer,foo]=build_expr(answer{1},'multiple');
5287 
+   if ~isstr(answer)
5288 
+
5289 
+     answer='Done.';
5290 
+     data=get(gcf,'UserData');
5291 
+     data.undo.sData=undo;
5292 
+     if ~LOG
5293 
+        data.LOG{length(data.LOG)+1}='% Eval';
5294 
+        data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''eval2'',',...
5295 
+                 sprintf('{''%s''});',str));
5296 
+      end
5297 
+     set(gcf,'UserData',data);
5298 
+   end
5299 
+end
5300 
+
5301 
+set(getfield(get(pre_h,'UserData'),'results_h'),'String',answer);
5302 
+
5303 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5304 
+
5305 
+%%% Subfunction: zero2one_scale %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5306 
+
5307 
+function zero2one_scale(varargin)
5308 
+
5309 
+if nargin == 1
5310 
+  LOG=1;
5311 
+else
5312 
+  LOG=0;
5313 
+end
5314 
+
5315 
+
5316 
+data=get(gcf,'UserData');
5317 
+sData=data.sData;
5318 
+undo=sData;
5319 
+INDEX=sData.INDEX;
5320 
+sData=rmfield(sData,[{'INDEX'};{'MODIFIED'}]);
5321 
+
5322 
+if isempty(get(data.comp_names_h,'Value'))
5323 
+  errordlg('There must be components chosen for scaling.');
5324 
+  return;
5325 
+end
5326 
+
5327 
+sData=som_normalize(sData,'range',get_indices);
5328 
+sData.MODIFIED=1;
5329 
+sData.INDEX=INDEX;
5330 
+
5331 
+data.sData=sData;
5332 
+data.undo.sData=undo;
5333 
+if ~LOG
5334 
+  data.LOG{length(data.LOG)+1}='% Scale [0,1]';
5335 
+  data.LOG{length(data.LOG)+1}='preprocess(''zscale'', ''foo'');';
5336 
+end
5337 
+set(gcf,'UserData',data);
5338 
+
5339 
+vects=zeros(1,length(sData.data(:,1)));
5340 
+vects(data.selected_vects)=1;
5341 
+
5342 
+cplot_mimema;
5343 
+plot_hist;
5344 
+vect_means(sData,data.vect_mean_h,data.selected_vects);
5345 
+draw_vectors(vects,data.vector_h);
5346 
+
5347 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5348 
+
5349 
+%%% Subfunction: var_scale %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5350 
+
5351 
+function var_scale(varargin)
5352 
+
5353 
+if nargin == 1
5354 
+  LOG=1;
5355 
+else
5356 
+  LOG=0;
5357 
+end
5358 
+
5359 
+data=get(gcf,'UserData');
5360 
+sData=data.sData;
5361 
+undo=sData;
5362 
+INDEX=sData.INDEX;
5363 
+sData=rmfield(sData,[{'INDEX'};{'MODIFIED'}]);
5364 
+
5365 
+if isempty(get(data.comp_names_h,'Value'))
5366 
+  errordlg('There must be components chosen for scaling.');
5367 
+  return;
5368 
+end
5369 
+
5370 
+sData=som_normalize(sData,'var',get_indices);
5371 
+
5372 
+sData.INDEX=INDEX;
5373 
+sData.MODIFIED=1;
5374 
+
5375 
+data.sData=sData;
5376 
+data.undo.sData=undo;
5377 
+if ~LOG
5378 
+  data.LOG{length(data.LOG)+1}='% Scale var=1';
5379 
+  data.LOG{length(data.LOG)+1}='preprocess(''vscale'', ''foo'');';
5380 
+end
5381 
+set(gcf,'UserData',data);
5382 
+
5383 
+vects=zeros(1,length(sData.data(:,1)));
5384 
+vects(data.selected_vects)=1;
5385 
+
5386 
+cplot_mimema;
5387 
+plot_hist;
5388 
+vect_means(sData,data.vect_mean_h,data.selected_vects);
5389 
+draw_vectors(vects,data.vector_h);
5390 
+
5391 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5392 
+
5393 
+%%% Subfunction: hist_eq %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5394 
+
5395 
+function hist_eq(varargin)
5396 
+
5397 
+if nargin == 1
5398 
+  LOG=1;
5399 
+else
5400 
+  LOG=0;
5401 
+end
5402 
+
5403 
+data=get(gcf,'UserData');
5404 
+sData=data.sData;
5405 
+undo=sData;
5406 
+INDEX=sData.INDEX;
5407 
+sData=rmfield(sData,[{'INDEX'},{'MODIFIED'}]);
5408 
+
5409 
+if isempty(get(data.comp_names_h,'Value'))
5410 
+  errordlg('There must be components chosen for ''Histogram eq''.');
5411 
+  return;
5412 
+end
5413 
+
5414 
+sData=som_normalize(sData,'histD',get_indices);
5415 
+
5416 
+sData.INDEX=INDEX;
5417 
+sData.MODIFIED=1;
5418 
+
5419 
+data.sData=sData;
5420 
+data.undo.sData=undo;
5421 
+if ~LOG
5422 
+  data.LOG{length(data.LOG)+1}='% Histogram eq';
5423 
+  data.LOG{length(data.LOG)+1}='preprocess(''histeq'', ''foo'');';
5424 
+end
5425 
+set(gcf,'UserData',data);
5426 
+
5427 
+vects=zeros(1,length(sData.data(:,1)));
5428 
+vects(data.selected_vects)=1;
5429 
+
5430 
+cplot_mimema;
5431 
+plot_hist;
5432 
+vect_means(sData,data.vect_mean_h,data.selected_vects);
5433 
+draw_vectors(vects,data.vector_h);
5434 
+
5435 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5436 
+
5437 
+%%% Subfunction: hist_eq2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5438 
+
5439 
+function hist_eq2(varargin)
5440 
+
5441 
+if nargin == 1
5442 
+  LOG=1;
5443 
+else
5444 
+  LOG=0;
5445 
+end
5446 
+
5447 
+
5448 
+data=get(gcf,'UserData');
5449 
+sData=data.sData;
5450 
+undo=sData;
5451 
+
5452 
+INDEX=sData.INDEX;
5453 
+sData=rmfield(sData,[{'INDEX'};{'MODIFIED'}]);
5454 
+
5455 
+if isempty(get(data.comp_names_h,'Value'))
5456 
+  errordlg('There must be components chosen for ''Histogram eq2''.');
5457 
+  return;
5458 
+end
5459 
+
5460 
+inds=get_indices;
5461 
+%%%[sData,ok]=som_normalize(sData,inds,'histC');
5462 
+sData=som_normalize(sData,'histC',inds);
5463 
+sData.INDEX=INDEX;
5464 
+sData.MODIFIED=1;
5465 
+
5466 
+data.sData=sData;
5467 
+data.undo.sData=undo;
5468 
+if ~LOG
5469 
+  data.LOG{length(data.LOG)+1}='% Histogram eq2';
5470 
+  data.LOG{length(data.LOG)+1}='preprocess(''histeq2'', ''foo'');';
5471 
+end
5472 
+set(gcf,'UserData',data);
5473 
+
5474 
+vects=zeros(1,length(sData.data(:,1)));
5475 
+vects(data.selected_vects)=1;
5476 
+
5477 
+cplot_mimema;
5478 
+plot_hist;
5479 
+vect_means(sData,data.vect_mean_h,data.selected_vects);
5480 
+draw_vectors(vects,data.vector_h);
5481 
+
5482 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5483 
+
5484 
+%%% Subfunction: logarithm %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5485 
+
5486 
+function logarithm(varargin)
5487 
+
5488 
+if nargin == 1
5489 
+  LOG=1;
5490 
+else
5491 
+  LOG=0;
5492 
+end
5493 
+
5494 
+data=get(gcf,'UserData');
5495 
+sData=data.sData;
5496 
+undo=sData;
5497 
+
5498 
+INDEX=sData.INDEX;
5499 
+sData=rmfield(sData,[{'INDEX'},{'MODIFIED'}]);
5500 
+
5501 
+if isempty(get(data.comp_names_h,'Value'))
5502 
+  errordlg('There must be components chosen for ''Log''.');
5503 
+  return;
5504 
+end
5505 
+
5506 
+Data=som_normalize(sData,'log',get_indices);
5507 
+
5508 
+sData.INDEX=INDEX;
5509 
+sData.MODIFIED=1;
5510 
+
5511 
+data.sData=sData;
5512 
+data.undo.sData=undo;
5513 
+if ~LOG
5514 
+  data.LOG{length(data.LOG)+1}='% Log';
5515 
+  data.LOG{length(data.LOG)+1}='preprocess(''log'', ''foo'');';
5516 
+end
5517 
+set(gcf,'UserData',data);
5518 
+
5519 
+vects=zeros(1,length(sData.data(:,1)));
5520 
+vects(data.selected_vects)=1;
5521 
+
5522 
+cplot_mimema;
5523 
+plot_hist;
5524 
+vect_means(sData,data.vect_mean_h,data.selected_vects);
5525 
+draw_vectors(vects,data.vector_h);
5526 
+
5527 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5528 
+
5529 
+function [answer,method]=build_expr(string,evaltype)
5530 
+
5531 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
5532 
+
5533 
+method=[];
5534 
+if isempty(pre_h)
5535 
+  close_preprocess;
5536 
+  errordlg('''Preprocess'' -figure does not exist. Terminating program...');
5537 
+  return;
5538 
+
5539 
+end
5540 
+
5541 
+if isempty(string)
5542 
+  str = '[]';
5543 
+  return;
5544 
+end
5545 
+
5546 
+tmp=[];
5547 
+[name,assign,skip]=check_assign(string,evaltype);
5548 
+
5549 
+if ~strcmp(assign,'NOTASSIGN') & ~strcmp(assign,'error')
5550 
+  string=string(skip:length(string));
5551 
+end
5552 
+
5553 
+if ~strcmp(assign,'error')
5554 
+  if isempty(string)
5555 
+    answer='Illegal expression.';
5556 
+    return;
5557 
+  end
5558 
+  [str,skip]=check_token(string,evaltype);
5559 
+  method=string;
5560 
+  while ~strcmp(str,'error') & ~strcmp(tmp,'error') & skip < length(string)
5561 
+    if ~strcmp(tmp,')')
5562 
+      str=cat(2,str,tmp);
5563 
+    end
5564 
+    [tmp,skip2]=check_token(string(skip+1:length(string)),evaltype);
5565 
+    skip=skip+skip2;
5566 
+
5567 
+  end
5568 
+   if ~strcmp(tmp,')') & ~strcmp(tmp,'error')
5569 
+     str=cat(2,str,tmp);
5570 
+   elseif strcmp(tmp,'error')
5571 
+     str='error';
5572 
+   end
5573 
+end
5574 
+
5575 
+if ~strcmp(assign,'error') & ~strcmp(str,'error');
5576 
+  answer=evalin('caller',str,'lasterr');
5577 
+else
5578 
+  answer='??? Illegal expression.';
5579 
+end
5580 
+
5581 
+
5582 
+data=get(pre_h,'UserData');
5583 
+sData=data.sData;
5584 
+if strcmp(assign,'NOTASSIGN') & strcmp(evaltype,'single') & ~isstr(answer)
5585 
+  if isempty(get(getfield(get(pre_h,'UserData'),'comp_names_h'),'Value'))
5586 
+    errordlg('There are not components chosen.');
5587 
+    answer='??? Illegal expression.';
5588 
+    return;
5589 
+  end
5590 
+  index=getfield(get_indices,{1});
5591 
+  if strcmp(assign,'NOTASSIGN')
5592 
+    if length(sData.data(:,index)) ~=length(answer) & ~isscalar(answer)
5593 
+      answer='??? Illegal assignment.';
5594 
+    else
5595 
+      sData.data(:,index)=answer;
5596 
+      sData.MODIFIED=1;
5597 
+      data.sData=sData;
5598 
+      set(pre_h,'UserData',data);
5599 
+    end
5600 
+  else
5601 
+    if length(sData.data(str2num(assign),index)) ~=length(answer) & ~isscalar(answer)
5602 
+      answer='??? Illegal assignment.';
5603 
+    else
5604 
+      sData.data(str2num(assign),index)=answer;
5605 
+      sData.MODIFIED=1;
5606 
+      data.sData=sData;
5607 
+      set(pre_h,'UserData',data);
5608 
+    end
5609 
+  end
5610 
+elseif ~strcmp(assign,'error') & ~isstr(answer) & ~strcmp(assign,'NOTASSIGN')
5611 
+  switch name
5612 
+    case 'x'
5613 
+     if isempty(get(data.comp_names_h,'Value'))
5614 
+       return;
5615 
+     end
5616 
+     index = getfield(get_indices,{1});
5617 
+     if isempty(assign)
5618 
+       if length(sData.data(:,index)) ~= length(answer) & ~isscalar(answer)
5619 
+         answer='??? Illegal assignment.';
5620 
+       else
5621 
+         sData.data(:,index)=answer;
5622 
+         sData.MODIFIED=1;
5623 
+         data.sData=sData;
5624 
+         if strcmp(evaltype,'multiple')
5625 
+           data.sData.comp_norm(index)={[]};
5626 
+         end
5627 
+         set(pre_h,'UserData',data);
5628 
+       end
5629 
+     else
5630 
+       args=create_args(assign,'x');
5631 
+       if length(args) == 1
5632 
+         len=max(str2num(args{1}));
5633 
+         if ~isscalar(len)
5634 
+           answer='??? Illegal assignment.';
5635 
+           return;
5636 
+         elseif len > length(sData.data(:,1)) | min(str2num(args{1})) < 1
5637 
+           answer='??? Illegal assignment.';
5638 
+           return;
5639 
+         elseif ~all(size(sData.data(str2num(args{1}),index))) == size(answer) & ~isscalar(answer)
5640 
+           answer='??? Illegal assignment.';
5641 
+           return;
5642 
+         else
5643 
+           sData.data(str2num(args{1}),index)=answer;
5644 
+           sData.MODIFIED=1;
5645 
+           data.sData=sData;
5646 
+           if strcmp(evaltype,'multiple')
5647 
+             data.sData.comp_norm(index)={[]};
5648 
+           end
5649 
+           set(pre_h,'UserData',data);
5650 
+         end
5651 
+       else
5652 
+         len=max(str2num(args{1}));
5653 
+         dim=max(str2num(args{2}));
5654 
+         asize=size(answer);
5655 
+         msize=size(sData.data);
5656 
+         if ~isscalar(len) | ~isscalar(dim)
5657 
+           answer='??? Illegal assignment.';
5658 
+           return;
5659 
+         elseif len > length(sData.data(:,1)) | len < 1
5660 
+           answer='??? Illegal assignment.';
5661 
+           return;
5662 
+         elseif dim > 1 | dim > msize(2) | min(str2num(args{2})) < 1
5663 
+           answer='??? Illegal assignment.';
5664 
+           return;
5665 
+         end
5666 
+         len=length(str2num(args{1}));
5667 
+         dim=length(str2num(args{1}));
5668 
+         if ~all([len dim] == asize) & ~isscalar(answer)
5669 
+           answer='??? Illegal assignment.';
5670 
+           return;
5671 
+         else
5672 
+           tmp=sData.data(:,index);
5673 
+           tmp([str2num(args{1})],[str2num(args{2})])=answer;
5674 
+           sData.data(:,index)=tmp;
5675 
+           sData.MODIFIED=1;
5676 
+           data.sData=sData;
5677 
+           if strcmp(evaltype,'multiple')
5678 
+             data.sData.comp_norm(index)={[]};
5679 
+           end
5680 
+           set(pre_h,'UserData',data);
5681 
+         end
5682 
+       end
5683 
+     end
5684 
+
5685 
+    case 'xs'
5686 
+     if isempty(get(data.comp_names_h,'Value'))
5687 
+       return;
5688 
+     end
5689 
+     indices=get_indices;
5690 
+     if isempty(assign)
5691 
+       if ~all(size(answer) == size(sData.data(:,indices))) & ~isscalar(answer)
5692 
+         answer='??? Illegal assignment.';
5693 
+       else
5694 
+         sData.data(:,indices) = answer;
5695 
+         sData.MODIFIED=1;
5696 
+         data.sData=sData;
5697 
+         data.sData.comp_norm(indices)={[]};
5698 
+         set(pre_h,'UserData',data);
5699 
+       end
5700 
+     else
5701 
+       args=create_args(assign,'xs');
5702 
+       if length(args) == 1
5703 
+         len=max(str2num(args{1}));
5704 
+         if ~isscalar(len)
5705 
+           answer='??? Illegal assignment.';
5706 
+           return;
5707 
+         elseif len > length(sData.data(:,1)) | min(str2num(args{1})) < 1
5708 
+           answer='??? Illegal assignment.';
5709 
+           return;
5710 
+         end
5711 
+         if ~all(size(answer) == size(sData.data(str2num(args{1})))) &...
5712 
+            ~isscalar(answer)
5713 
+           answer='??? Illegal assignment.';
5714 
+           return;
5715 
+         else
5716 
+           tmp=sData.data(:,indices);
5717 
+           tmp(str2num(args{1}))=answer;
5718 
+           sData.data(:,indices)=tmp;
5719 
+           sData.MODIFIED=1;
5720 
+           sData.comp_norm{indices}={[]};
5721 
+           data.sData=sData;
5722 
+           set(pre_h,'UserData',data);
5723 
+         end
5724 
+       else
5725 
+         len=max(str2num(args{1}));
5726 
+         dim=max(str2num(args{2}));
5727 
+         asize=size(answer);
5728 
+         msize=size(sData.data(:,indices));
5729 
+         if ~isscalar(len) | ~isscalar(dim)
5730 
+           answer='??? Illegal assignment.';
5731 
+           return;
5732 
+         elseif len > msize(1) | min(str2num(args{1})) < 1
5733 
+           answer='??? Illegal assignment.';
5734 
+           return;
5735 
+         elseif dim > msize(2) | min(str2num(args{2})) < 1
5736 
+           answer='??? Illegal assignment.';
5737 
+           return;
5738 
+         end
5739 
+         len=length(str2num(args{1}));
5740 
+         dim=length(str2num(args{2}));
5741 
+         if ~all([len dim] == asize) & ~isscalar(answer)
5742 
+           answer='??? Illegal assignment';
5743 
+           return;
5744 
+         else
5745 
+           tmp=sData.data(:,indices);
5746 
+           tmp([str2num(args{1})],[str2num(args{2})])=answer;
5747 
+           sData.MODIFIED=1;
5748 
+           sData.data(:,indices)=tmp;
5749 
+           data.sData=sData;
5750 
+           data.sData.comp_norm(indices)={[]};
5751 
+           set(pre_h,'UserData',data);
5752 
+         end
5753 
+
5754 
+       end
5755 
+     end
5756 
+
5757 
+    case 'D'
5758 
+     if isempty(assign)
5759 
+       if ~all(size(answer) == size(sData.data)) & ~isscalar(answer)
5760 
+         answer='??? Illegal assignment.';
5761 
+       else
5762 
+         if isscalar(answer)
5763 
+           sData.data(:,:)=answer;
5764 
+         else
5765 
+           sData.data=answer;
5766 
+         end
5767 
+         sData.MODIFIED=1;
5768 
+         data.sData=sData;
5769 
+         data.sData.comp_norm(1:length(sData.data(1,:)))={[]};
5770 
+         set(pre_h,'UserData',data);
5771 
+       end
5772 
+     else
5773 
+       args=create_args(assign,'D');
5774 
+       if length(args) == 1
5775 
+         len=max(str2num(args{1}));
5776 
+         if ~isscalar(len)
5777 
+           answer='??? Illegal assignment.';
5778 
+           return;
5779 
+         elseif len > length(sData.data(:,1)) | min(str2num(args{1})) < 1
5780 
+           answer='??? Illegal assignment.';
5781 
+           return;
5782 
+         end
5783 
+         if ~all(size(answer) == size(sData.data(str2num(args{1})))) &...
5784 
+            ~isscalar(answer)
5785 
+           answer='??? Illegal assignment.';
5786 
+         else
5787 
+           sData.data(str2num(args{1}))=answer;
5788 
+           sData.MODIFIED=1;
5789 
+           data.sData=sData;
5790 
+           [i,j]=ind2sub(size(sData.data),str2num(args{1}));
5791 
+           data.sData.comp_norm(j)={[]};
5792 
+           set(pre_h,'UserData',data);
5793 
+         end
5794 
+       else
5795 
+         len=max(str2num(args{1}));
5796 
+         dim=max(str2num(args{2}));
5797 
+         asize=size(answer);
5798 
+         msize=size(sData.data);
5799 
+         if ~isscalar(len) | ~isscalar(dim)
5800 
+           answer='??? Illegal assignment.';
5801 
+           return;
5802 
+         elseif len > msize(1) | min(str2num(args{1})) < 1
5803 
+           answer='??? Illegal assignment.';
5804 
+           return;
5805 
+         elseif dim > msize(2) | min(str2num(args{2})) < 1
5806 
+           answer= '??? Illegal assignment.';
5807 
+           return;
5808 
+         end
5809 
+         len = length(str2num(args{1}));
5810 
+         dim = length(str2num(args{2}));
5811 
+         if ~all([len dim] == asize) & ~isscalar(answer)
5812 
+           answer='??? Illegal assignment.';
5813 
+           return;
5814 
+         else
5815 
+           sData.data([str2num(args{1})],[str2num(args{2})])=answer;
5816 
+           sData.MODIFIED=1;
5817 
+           data.sData=sData;
5818 
+           data.sData.comp_norm(str2num(args{2}))={[]};
5819 
+           set(pre_h,'UserData',data);
5820 
+         end
5821 
+       end
5822 
+     end
5823 
+  end
5824 
+end
5825 
+if sData.MODIFIED
5826 
+  selected=getfield(get(pre_h,'UserData'),'selected_vects');
5827 
+  vector_h=getfield(get(pre_h,'UserData'),'vector_h');
5828 
+  vect_mean_h=getfield(get(pre_h,'UserData'),'vect_mean_h');
5829 
+  vects=zeros(length(sData.data(:,1)));
5830 
+  vects(selected)=1;
5831 
+  draw_vectors(vects,vector_h);
5832 
+  vect_means(sData,vect_mean_h,selected);
5833 
+  pro_tools('plot_hist');
5834 
+  pro_tools('c_stat');
5835 
+  cplot_mimema;
5836 
+end
5837 
+
5838 
+
5839 
+%%% Subfunction: check_assign %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5840 
+
5841 
+function [name,string,skip]=check_assign(string,evaltype)
5842 
+
5843 
+
5844 
+reswords=[{'D'};{'x'};{'xs'}];
5845 
+flag=0;
5846 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
5847 
+
5848 
+if isempty(pre_h)
5849 
+  man_h=findobj(get(0,'Children'),'Tag','Management');
5850 
+  clip_h=findobj(get(0,'Children'),'Tag','Clipping');
5851 
+  errordlg('''Preprocess'' -window does not exist. Terminating program.');
5852 
+  if ~isempty(man_h)
5853 
+    close man_h;
5854 
+  end
5855 
+  if ~isempty(clip_h)
5856 
+    close clip_h;
5857 
+  end
5858 
+  return;
5859 
+end
5860 
+
5861 
+EMPTY=isempty(get(getfield(get(pre_h,'UserData'),'comp_names_h'),'Value'));
5862 
+
5863 
+[name,s]=give_token(string,evaltype);
5864 
+skip=length(s);
5865 
+
5866 
+if strcmp(evaltype,'single') & ~strcmp(name,'x')
5867 
+  string='NOTASSIGN';
5868 
+  return;
5869 
+end
5870 
+
5871 
+if strcmp(name,'other') & ~strcmp(s,'x')
5872 
+  string = 'error';
5873 
+  return;
5874 
+end
5875 
+
5876 
+if strcmp(name,[{'x'};{'xs'}])
5877 
+  comp_names_h=getfield(get(gcf,'UserData'),'comp_names_h');
5878 
+  if isempty(get(comp_names_h,'Value'))
5879 
+    errordlg('There are not components chosen.');
5880 
+    string='error';
5881 
+    return;
5882 
+  end
5883 
+end
5884 
+
5885 
+
5886 
+if skip == length(string) | ~strcmp(name,reswords)
5887 
+  string = 'NOTASSIGN';
5888 
+  return;
5889 
+end
5890 
+
5891 
+if (strcmp(name,'x') | strcmp(name,'xs')) & EMPTY
5892 
+  errordlg('There are not components chosen.');
5893 
+  string = 'error';
5894 
+  return;
5895 
+end
5896 
+
5897 
+[t,s]=give_token(string(length(name)+1),evaltype);
5898 
+
5899 
+if strcmp(t,'(')
5900 
+  flag=1;
5901 
+end
5902 
+
5903 
+[foo,skip]=check_token(string,evaltype);
5904 
+if length(name) ~= skip-1
5905 
+  skip=skip-1;
5906 
+  tmp=string(length(name)+1:skip);
5907 
+else
5908 
+  tmp = [];
5909 
+end
5910 
+
5911 
+if flag & tmp(length(tmp)) ~= ')'
5912 
+  tmp(length(tmp)+1)=')';
5913 
+end
5914 
+
5915 
+if skip==length(string)
5916 
+  return;
5917 
+end
5918 
+
5919 
+skip=skip+1;
5920 
+if length(string) ~= skip
5921 
+  [t,s]=give_token(string(skip+1:length(string)),evaltype);
5922 
+else
5923 
+  string='NOTASSIGN';
5924 
+  return;
5925 
+end
5926 
+
5927 
+if ~strcmp(t,'=')
5928 
+  string = 'NOTASSIGN';
5929 
+  return;
5930 
+end
5931 
+string=tmp;
5932 
+skip = skip+2;
5933 
+
5934 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5935 
+
5936 
+%%% Subfunction: isscalar %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5937 
+
5938 
+function bool = isscalar(x)
5939 
+
5940 
+  m= size(x);
5941 
+
5942 
+  bool = m(1) == 1 & m(2) == 1;
5943 
+
5944 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5945 
+
5946 
+%%% Subfunction: create_args %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5947 
+
5948 
+function args=create_args(string,type)
5949 
+
5950 
+arg2='';
5951 
+i=2;
5952 
+j=1;
5953 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
5954 
+msize=size(getfield(getfield(get(pre_h,'UserData'),'sData'),'data'));
5955 
+
5956 
+
5957 
+if string(i) == ':'
5958 
+  arg1=num2str(cat(2,'1:',num2str(msize(1))));
5959 
+  i=i+1;
5960 
+  j=j+length(arg1);
5961 
+end
5962 
+
5963 
+while string(i) ~=',' & string(i) ~=')'
5964 
+  arg1(j)=string(i);
5965 
+  i=i+1;
5966 
+  j=j+1;
5967 
+end
5968 
+
5969 
+
5970 
+
5971 
+if string(i) ==','
5972 
+  j=1;
5973 
+  i=i+1;
5974 
+  if string(i)==':'
5975 
+    switch type
5976 
+      case 'x'
5977 
+       arg2='1';
5978 
+      case 'cs'
5979 
+       arg2=num2str(get_indices);
5980 
+      case 'D'
5981 
+       arg2=num2str(cat(2,'1:',num2str(msize(2))));
5982 
+    end
5983 
+    i=i+1;
5984 
+    j=j+length(arg2);
5985 
+  end
5986 
+
5987 
+  while string(i) ~= ')'
5988 
+    arg2(j)=string(i);
5989 
+    j=j+1;
5990 
+    i=i+1;
5991 
+  end
5992 
+end
5993 
+
5994 
+
5995 
+args{1}=arg1;
5996 
+if ~isempty(arg2)
5997 
+  args{2} = arg2;
5998 
+end
5999 
+
6000 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6001 
+
6002 
+function [str,skip] = check_token(string,evaltype)
6003 
+
6004 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
6005 
+
6006 
+tmp_string=string;
6007 
+[t,s]=give_token(tmp_string,evaltype);
6008 
+skip=length(s);
6009 
+
6010 
+if strcmp(t,'c')
6011 
+  if isempty(get(getfield(get(pre_h,'UserData'),'comp_names_h'),'Value'))
6012 
+    errordlg('There are no components chosen.');
6013 
+    str='error';
6014 
+    return;
6015 
+  end
6016 
+  index=getfield(get_indices,{1});
6017 
+  str=cat(2,'[',num2str(index),']');
6018 
+  if skip == length(tmp_string)
6019 
+    return;
6020 
+  end
6021 
+  tmp_string=tmp_string(skip+1:length(tmp_string));
6022 
+  [t,s] = give_token(tmp_string,evaltype);
6023 
+  if ~strcmp(t,'(')
6024 
+    return;
6025 
+  end
6026 
+  [args,skip2] = get_args(tmp_string(length(s)+1:length(tmp_string)),'c',...
6027 
+                          evaltype);
6028 
+  skip=skip+skip2+2;
6029 
+  if strcmp(args,'error')
6030 
+    str = 'error'
6031 
+    return;
6032 
+  elseif ~strcmp(args,'all')
6033 
+    str=cat(2,'getfield(',str,',',args,')');
6034 
+  else
6035 
+    str=cat(2,'getfield(',str,',{[1]})');
6036 
+  end
6037 
+elseif strcmp(t,'cs')
6038 
+  if isempty(get(getfield(get(pre_h,'UserData'),'comp_names_h'),'Value'))
6039 
+    errordlg('There are no components chosen.');
6040 
+    str='error';
6041 
+    return;
6042 
+  end
6043 
+  str =cat(2,'[',num2str(get_indices),']');
6044 
+  if length(s) == length(string)
6045 
+    return;
6046 
+  end
6047 
+  tmp_string=tmp_string(1+length(s):length(string));
6048 
+  [t,s]=give_token(tmp_string,evaltype);
6049 
+  if ~strcmp(t,'(')
6050 
+    return;
6051 
+  else
6052 
+    [args,skip2]=get_args(tmp_string(1+length(s):length(tmp_string)),'cs',...
6053 
+                          evaltype);
6054 
+    skip=2+skip+skip2;
6055 
+    if strcmp(args,'error')
6056 
+      str='error';
6057 
+      return;
6058 
+    elseif ~strcmp(args,'all')
6059 
+      str = cat(2,'getfield(',str,',',args,')');
6060 
+    else
6061 
+      tmp_str=str;
6062 
+      str=cat(2,'[getfield(',str,',','{1})');
6063 
+      for i=2:length(get_indices)
6064 
+        str=cat(2,str,';getfield(',tmp_str,',',sprintf('{%d})',i));
6065 
+      end
6066 
+      str=cat(2,str,']');
6067 
+    end
6068 
+  end
6069 
+elseif strcmp(t,'dim')
6070 
+  ind1=getfield(size(getfield(getfield(get(pre_h,'UserData'),'sData'),'data')),{2});
6071 
+  str=cat(2,'[',num2str(ind1),']');
6072 
+  if length(s)==length(string)
6073 
+    return;
6074 
+  end
6075 
+  tmp_string=string(1+length(s):length(string));
6076 
+  [t,s]=give_token(tmp_string,evaltype);
6077 
+  if ~strcmp(t,'(')
6078 
+    return;
6079 
+  end
6080 
+  skip=1+skip+length(s);
6081 
+  [args,skip2]=get_args(tmp_string(1+length(s):length(tmp_string)),'dim',...
6082 
+                        evaltype);
6083 
+  if strcmp(args,'error')
6084 
+    str = 'error';
6085 
+    return;
6086 
+  else
6087 
+    skip=skip+skip2;
6088 
+    if ~strcmp(args,'all')
6089 
+      str=cat(2,'getfield(',str,',',args,')');
6090 
+    end
6091 
+  end
6092 
+
6093 
+elseif strcmp(t,'dlen')
6094 
+  ind1=getfield(size(getfield(getfield(get(pre_h,'UserData'),'sData'),'data')),{1});
6095 
+  str=cat(2,'[',num2str(ind1),']');
6096 
+  if length(s)==length(string)
6097 
+    return;
6098 
+  end
6099 
+  tmp_string=string(1+length(s):length(string));
6100 
+  [t,s]=give_token(tmp_string,evaltype);
6101 
+  if ~strcmp(t,'(')
6102 
+    return;
6103 
+  end
6104 
+  skip=skip+length(s);
6105 
+  [args,skip2]=get_args(tmp_string(1+length(s):length(tmp_string)),'dlen',...
6106 
+                        evaltype);
6107 
+  if strcmp(args,'error')
6108 
+    str='error';
6109 
+    return;
6110 
+  else
6111 
+    skip=1+skip+skip2;
6112 
+    if ~strcmp(args,'all')
6113 
+      str=cat(2,'getfield(',str,',',args,')');
6114 
+    end
6115 
+  end
6116 
+
6117 
+elseif strcmp(t,'x')
6118 
+  if isempty(get(getfield(get(pre_h,'UserData'),'comp_names_h'),'Value'))
6119 
+    errordlg('There are not components chosen.');
6120 
+    str='error';
6121 
+    return;
6122 
+  end
6123 
+  len=getfield(size(getfield(getfield(get(pre_h,'UserData'),...
6124 
+               'sData'),'data')),{1});
6125 
+  index=num2str(getfield(get_indices,{1}));
6126 
+  h_str='findobj(get(0,''Children''),''Tag'',''Preprocess'')';
6127 
+  get_str=cat(2,'getfield(get(',h_str,',''UserData''),''sData'')');
6128 
+  get_str=cat(2,'getfield(',get_str,',''data'')');
6129 
+  str=cat(2,'getfield(',get_str,',{[1:',num2str(len),'],',index,'})');
6130 
+  if length(s) == length(string)
6131 
+    return;
6132 
+  end
6133 
+  tmp_string=string(1+length(s):length(string));
6134 
+  [t,s]=give_token(tmp_string,evaltype);
6135 
+  if ~strcmp(t,'(');
6136 
+    return;
6137 
+  end
6138 
+  skip=skip+length(s);
6139 
+  [args,skip2]=get_args(tmp_string(1+length(s):length(tmp_string)),'x',...
6140 
+                        evaltype);
6141 
+  if strcmp(args,'error')
6142 
+    str = 'error';
6143 
+    return;
6144 
+  else
6145 
+    skip=1+skip+skip2;
6146 
+    if ~strcmp(args,'all')
6147 
+      str=cat(2,'getfield(',str,',',args,')');
6148 
+    end
6149 
+  end
6150 
+
6151 
+elseif strcmp(t,'xs')
6152 
+  if isempty(get(getfield(get(pre_h,'UserData'),'comp_names_h'),'Value'))
6153 
+    errordlg('There are not components chosen.');
6154 
+    str='error';
6155 
+    return;
6156 
+  end
6157 
+  len=getfield(size(getfield(getfield(get(pre_h,'UserData'),...
6158 
+               'sData'),'data')),{1});
6159 
+  index=get_indices;
6160 
+  index=cat(2,'[',num2str(index),']');
6161 
+  h_str='findobj(get(0,''Children''),''Tag'',''Preprocess'')';
6162 
+  get_str=cat(2,'getfield(get(',h_str,',''UserData''),''sData'')');
6163 
+  get_str=cat(2,'getfield(',get_str,',''data'')');
6164 
+  str=cat(2,'getfield(',get_str,',{[1:',num2str(len),'],',index,'})');
6165 
+  if length(s) == length(string)
6166 
+    return;
6167 
+  end
6168 
+  tmp_string=string(1+length(s):length(string));
6169 
+  [t,s]=give_token(tmp_string,evaltype);
6170 
+  if ~strcmp(t,'(')
6171 
+    return;
6172 
+  end
6173 
+  skip=1+skip+length(s);
6174 
+
6175 
+  [args,skip2]=get_args(tmp_string(1+length(s):length(tmp_string)),'xs',...
6176 
+                        evaltype);
6177 
+  if strcmp(args,'error')
6178 
+    str = 'error';
6179 
+    return;
6180 
+  elseif ~strcmp(args,'all')
6181 
+    str=cat(2,'getfield(',str,',',args,')');
6182 
+    skip=skip+skip2;
6183 
+  else
6184 
+    skip=skip+skip2;
6185 
+    [dlen,dim]=size(eval(str));
6186 
+    tmp_str=str;
6187 
+    str=cat(2,'[','getfield(',tmp_str,sprintf(',{1:%d,1})',dlen));
6188 
+    for i=2:dim
6189 
+      tmp=sprintf(',{1:%d,%d})',dlen,dim);
6190 
+      str=cat(2,str,';','getfield(',tmp_str,tmp);
6191 
+    end
6192 
+    str=cat(2,str,']');
6193 
+  end
6194 
+elseif strcmp(t,'D')
6195 
+  get_h='findobj(get(0,''Children''),''Tag'',''Preprocess'')';
6196 
+  str=cat(2,'getfield(getfield(get(',get_h,',''UserData''),''sData''),''data'')');
6197 
+
6198 
+  if length(s) >= length(tmp_string)
6199 
+    return;
6200 
+  end
6201 
+
6202 
+  tmp_string=tmp_string(1+length(s):length(tmp_string));
6203 
+  [t,s]=give_token(tmp_string,evaltype);
6204 
+  if ~strcmp(t,'(')
6205 
+    return;
6206 
+  else
6207 
+    tmp_string=tmp_string(1+length(s):length(tmp_string));
6208 
+    skip = skip+length(s);
6209 
+    [args, skip2]=get_args(tmp_string,'D',evaltype);
6210 
+    if strcmp(args,'error')
6211 
+      str='error';
6212 
+      return;
6213 
+    elseif ~strcmp(args,'all')
6214 
+      str=cat(2,'getfield(',str,',',args,')');
6215 
+      skip=1+skip+skip2;
6216 
+    else
6217 
+      skip=1+skip+skip2;
6218 
+      [dlen,dim]=size(eval(str));
6219 
+      tmp_str=str;
6220 
+      str=cat(2,'[getfield(',str,sprintf(',{1:%d,1})',dlen));
6221 
+      for i=2:dim
6222 
+        tmp=sprintf(',{1:%d,%d}',dlen,i);
6223 
+        str=cat(2,str,';getfield(',tmp_str,tmp,')');
6224 
+      end
6225 
+      str=cat(2,str,']');
6226 
+    end
6227 
+  end
6228 
+else
6229 
+  if strcmp(t,'(')
6230 
+    str = t;
6231 
+    str2='';
6232 
+    tmp_string=tmp_string(1+length(s):length(tmp_string));
6233 
+    while ~strcmp(str2,')') & ~isempty(tmp_string)
6234 
+      [str2,skip2]=check_token(tmp_string,evaltype);
6235 
+      if strcmp(str2,'error')
6236 
+        str='error';
6237 
+        return;
6238 
+      end
6239 
+      skip=skip+skip2;
6240 
+      tmp_string=tmp_string(skip2+1:length(tmp_string));
6241 
+      str=cat(2,str,str2);
6242 
+    end
6243 
+    if ~strcmp(str2,')')
6244 
+      str = 'error';
6245 
+    end
6246 
+  else
6247 
+    str = s;
6248 
+  end
6249 
+end
6250 
+
6251 
+%%% Subfunction: get_args %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6252 
+
6253 
+function [str,skip] = get_args(string,flag,evaltype)
6254 
+
6255 
+res_words=[{'D'};{'c'};{'cs'};{'dim'};{'dlen'};{'x'};{'xs'}];
6256 
+NOTALL=1;
6257 
+if isempty(string)
6258 
+  str='error'
6259 
+  skip=[];
6260 
+  return;
6261 
+end
6262 
+[t,s] = give_token(string,evaltype);
6263 
+
6264 
+
6265 
+skip=length(s);
6266 
+if any(strcmp(t,res_words));
6267 
+  [str,skip2] = check_token(string,evaltype);
6268 
+  string=string(1+length(s):length(string));
6269 
+  str=cat(2,'{[',str);
6270 
+  [t,s]=give_token(string,evaltype);
6271 
+elseif t==')' | t==','
6272 
+  str = 'error';
6273 
+  return;
6274 
+elseif strcmp(t,':');
6275 
+  if length(s) == length(string)
6276 
+    str='error';
6277 
+    return;
6278 
+  end
6279 
+  [t,s]=give_token(string(1+length(s):length(string)),evaltype);
6280 
+  if t == ')'
6281 
+    str = 'all';
6282 
+    return;
6283 
+  end
6284 
+  switch flag
6285 
+    case {'c','cs','dim','dlen'}
6286 
+     str= '{[1';
6287 
+    otherwise
6288 
+     str=cat(2,'{[',get_all('vect'));
6289 
+  end
6290 
+  NOTALL=0;
6291 
+  string=string(1+length(s):length(string));
6292 
+  [t,s]=give_token(string,evaltype);
6293 
+  skip=skip+1;
6294 
+else
6295 
+  str = cat(2,'{[',s);
6296 
+end
6297 
+str2 =[];
6298 
+
6299 
+
6300 
+if ~strcmp(t,',') & ~strcmp(t,')')
6301 
+  skip=skip-length(s);
6302 
+end
6303 
+
6304 
+
6305 
+
6306 
+while ~strcmp(t,',') & ~strcmp(t,')') & NOTALL;
6307 
+  str=cat(2,str,str2);
6308 
+  [t,s] = give_token(string,evaltype);
6309 
+  if length(s) == length(string)
6310 
+    str = 'error';
6311 
+    return;
6312 
+  end
6313 
+  string=string(1+length(s):length(string));
6314 
+  skip=skip+length(s);
6315 
+  [t,s]=give_token(string,evaltype);
6316 
+  if length(s) == length(string) & ~strcmp(t,')')
6317 
+    str = 'error';
6318 
+    return;
6319 
+  end
6320 
+
6321 
+  [str2,foo]=check_token(string,evaltype);
6322 
+end
6323 
+
6324 
+if NOTALL & ~strcmp(t,')')
6325 
+ skip=skip+1;
6326 
+end
6327 
+
6328 
+if strcmp(t,')')
6329 
+  str=cat(2,str,']}');
6330 
+  return
6331 
+end
6332 
+
6333 
+str=cat(2,str,']',',','[');
6334 
+str2 = [];
6335 
+
6336 
+
6337 
+[t,s] = give_token(string,evaltype);
6338 
+if strcmp(t,')')
6339 
+  str = 'error'
6340 
+  return;
6341 
+end
6342 
+NOTALL=1;
6343 
+string=string(1+length(s):length(string));
6344 
+[t,s]=give_token(string,evaltype);
6345 
+if strcmp(t,':');
6346 
+   switch flag
6347 
+     case {'c','dim','dlen','x'}
6348 
+      str=cat(2,str,'1');
6349 
+     case 'D'
6350 
+      str=cat(2,str,get_all('comp'));
6351 
+     case {'cs','xs'}
6352 
+      str=cat(2,str,'1:',num2str(length(get_indices)));
6353 
+   end
6354 
+   NOTALL=0;
6355 
+   if length(s) == length(string)
6356 
+    str='error';
6357 
+    return;
6358 
+   end
6359 
+   string=string(1+length(s):length(string));
6360 
+   [t,s]=give_token(string,evaltype);
6361 
+end
6362 
+
6363 
+if ~strcmp(t,')') & NOTALL
6364 
+  skip=skip-1;
6365 
+end
6366 
+
6367 
+while ~strcmp(t,')') & NOTALL
6368 
+  str=cat(2,str,str2);
6369 
+  skip=skip+length(s);
6370 
+  if length(s) == length(string) & ~strcmp(t,')')
6371 
+    str='error';
6372 
+    return;
6373 
+  end
6374 
+  [str2,foo]=check_token(string,evaltype);
6375 
+  string=string(1+length(s):length(string));
6376 
+  [t,s]=give_token(string,evaltype);
6377 
+end
6378 
+if ~strcmp(t,')')
6379 
+  str='error';
6380 
+  return;
6381 
+end
6382 
+
6383 
+
6384 
+str=cat(2,str,str2,']}');
6385 
+skip=skip+length(s);
6386 
+
6387 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6388 
+
6389 
+%%% Subfunction: get_all %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6390 
+
6391 
+function str=get_all(vect_or_comp)
6392 
+
6393 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
6394 
+
6395 
+switch vect_or_comp
6396 
+  case 'vect'
6397 
+   dim=getfield(size(getfield(getfield(get(pre_h,'UserData'),...
6398 
+                'sData'),'data')),{1});
6399 
+   str=cat(2,'1:',num2str(dim));
6400 
+  case 'comp'
6401 
+   dim=getfield(size(getfield(getfield(get(pre_h,'UserData'),...
6402 
+                'sData'),'data')),{2});
6403 
+   str=cat(2,'1:',num2str(dim));
6404 
+end
6405 
+
6406 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6407 
+
6408 
+function [token,str]=give_token(string,evaltype)
6409 
+
6410 
+n=length(string);
6411 
+i=1;
6412 
+char=string(i);
6413 
+
6414 
+switch analyze_char(string(i));
6415 
+  case 'num'
6416 
+   token='num';
6417 
+   while i <= n & strcmp('num',analyze_char(string(i)))
6418 
+     str(i)=string(i);
6419 
+     i=i+1;
6420 
+   end
6421 
+  case 'other'
6422 
+   switch string(i)
6423 
+     case ':'
6424 
+      token = ':';
6425 
+     case ','
6426 
+      token = ',';
6427 
+     case '('
6428 
+      token = '(';
6429 
+     case ')'
6430 
+      token = ')';
6431 
+     case '='
6432 
+      token = '=';
6433 
+     otherwise
6434 
+      token='other';
6435 
+   end
6436 
+   str=string(i);
6437 
+  case 'alpha'
6438 
+   while i <= n & strcmp('alpha',analyze_char(string(i)))
6439 
+    str(i)=string(i);
6440 
+    i=i+1;
6441 
+   end
6442 
+   token = find_res_word(str,evaltype);
6443 
+end
6444 
+
6445 
+%%% Subfunction: analyze_char %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6446 
+
6447 
+function type=analyze_char(char)
6448 
+
6449 
+
6450 
+if ((char-0) >= ('0'-0) &  (char-0) <= ('9'-0))
6451 
+  type='num';
6452 
+elseif   ((char-0) >= ('a'-0) & (char-0) <= ('z'-0)) ...
6453 
+       | ((char-0) >= ('A'-0) & (char-0) <= ('Z'-0))
6454 
+  type='alpha';
6455 
+else
6456 
+  type='other';
6457 
+end
6458 
+
6459 
+
6460 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6461 
+
6462 
+%%% Subfunction: find_res_word %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6463 
+
6464 
+function token = find_res_word(string,evaltype)
6465 
+
6466 
+reswords=[{'D'};{'c'};{'cs'};{'dim'};{'dlen'};{'x'};{'xs'};{'other'}];
6467 
+
6468 
+for i=1:length(reswords);
6469 
+  token=reswords{i};
6470 
+  if strcmp(string,reswords{i})
6471 
+    if strcmp(evaltype,'single') & ~strcmp(string,'x')
6472 
+      token = 'other';
6473 
+    end
6474 
+    return;
6475 
+  end
6476 
+end
6477 
+
6478 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6479 
+
6480 
+function close_func(varargin)
6481 
+
6482 
+switch varargin{1}
6483 
+  case 'close_c'
6484 
+   str='% Closing the ''Clipping'' -window...';
6485 
+   clip_h=findobj(get(0,'Children'),'Tag','Clipping');
6486 
+   close(clip_h);
6487 
+  case 'close_sD'
6488 
+   str='% Closing the ''Data Set Management'' -window...';
6489 
+   sD_h=findobj(get(0,'Children'),'Tag','Management');
6490 
+   close(sD_h);
6491 
+  case 'close_w'
6492 
+   str='% Closing the ''Windowed'' -window...';
6493 
+   win_h=findobj(get(0,'Children'),'Tag','Window');
6494 
+   close(win_h);
6495 
+  case 'close_s'
6496 
+   str='% Closing the ''Select'' -window...';
6497 
+   sel_h=findobj(get(0,'Children'),'Tag','Select');
6498 
+   close(sel_h);
6499 
+  case 'close_d'
6500 
+   str='% Closing the ''Delay'' -window...';
6501 
+   del_h=findobj(get(0,'Children'),'Tag','Delay');
6502 
+   close(del_h);
6503 
+end
6504 
+
6505 
+if nargin ~= 2
6506 
+  pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
6507 
+  preh_udata=get(pre_h,'UserData');
6508 
+  str2=cat(2,'preprocess(''',varargin{1},''',''foo'');');
6509 
+  preh_udata.LOG{length(preh_udata.LOG)+1}=str;
6510 
+  preh_udata.LOG{length(preh_udata.LOG)+1}=str2;
6511 
+  set(pre_h,'UserData',preh_udata);
6512 
+end
6513 
+
6514 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6515 
+
6516 
+function log_file
6517 
+
6518 
+answer=inputdlg('Give the name of the outputfile:','LOG function',1,...
6519 
+                {'log_function'});
6520 
+
6521 
+if isempty(answer)
6522 
+  return;
6523 
+end
6524 
+
6525 
+
6526 
+tmp=clock;
6527 
+str =cat(2,'% Created: ',...
6528 
+           date,...
6529 
+           ' ',sprintf('%d:%d\n%\n\n',tmp(4),tmp(5)));
6530 
+pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
6531 
+LOG=getfield(get(pre_h,'UserData'),'LOG');
6532 
+file=cat(2,pwd,'/',answer{1},'.m');
6533 
+fid =fopen(file,'w');
6534 
+
6535 
+arg=LOG{2}(12:length(LOG{2})-2);
6536 
+fprintf(fid,'%s\n \n',cat(2,'function ',answer{1},'(',arg,')'));
6537 
+fprintf(fid,'%s\n',str);
6538 
+for i=1:length(LOG)
6539 
+  fprintf(fid,'%s\n',LOG{i});
6540 
+end
6541 
+fclose(fid);
6542 
+disp(sprintf('LOG-file ''%s'' is done.',file));
6543 
+
6544 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6545 
+
6546 
+function get_selected_inds(varargin)
6547 
+
6548 
+if nargin == 1
6549 
+  LOG=1;
6550 
+  answer = {varargin{1}};
6551 
+else
6552 
+  LOG=0;
6553 
+end
6554 
+
6555 
+selected=getfield(get(gcf,'UserData'),'selected_vects');
6556 
+if ~LOG
6557 
+  answer=inputdlg('Give the name of the output variable:',...
6558 
+                '',1,{'indices'});
6559 
+end
6560 
+
6561 
+if isempty(answer) | isempty(answer{1})
6562 
+  return;
6563 
+else
6564 
+  assignin('base',answer{1},selected);
6565 
+  disp(cat(2,'Indices of the selected vectors are set to the workspace ',...
6566 
+           sprintf(' as ''%s''.',answer{1})));
6567 
+  if ~LOG
6568 
+    data=get(gcf,'UserData');
6569 
+    data.LOG{length(data.LOG)+1}=...
6570 
+    '% Saving indices of the selected vectors to the workspace.';
6571 
+    data.LOG{length(data.LOG)+1}=cat(2,'preprocess(''get_inds'',',...
6572 
+                                        '''',answer{1},''');');
6573 
+    set(gcf,'UserData',data);
6574 
+  end
6575 
+end
6576 
+
6577 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6578 
+
6579 
+function no_of_selected(varargin)
6580 
+
6581 
+if nargin == 1
6582 
+  pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
6583 
+  set(0,'CurrentFigure',pre_h);
6584 
+  LOG = 1;
6585 
+else
6586 
+  LOG = 0;
6587 
+end
6588 
+
6589 
+results_h=getfield(get(gcf,'UserData'),'results_h');
6590 
+no=length(getfield(get(gcf,'UserData'),'selected_vects'));
6591 
+str={sprintf('Number of selected vectors: %d\n', no)};
6592 
+set(results_h,'String',str,'HorizontalAlignment','left');
6593 
+
6594 
+if ~LOG
6595 
+  data=get(gcf,'UserData');
6596 
+  data.LOG{length(data.LOG)+1}='% Number of selected vectors';
6597 
+  data.LOG{length(data.LOG)+1}='preprocess(''no_of_sel'',''foo'');';
6598 
+  set(gcf,'UserData',data);
6599 
+end
6600 
+
6601 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6602 
+
6603 
+function select_all_comps(varargin)
6604 
+
6605 
+if nargin == 1
6606 
+  pre_h=findobj(get(0,'Children'),'Tag','Preprocess');
6607 
+  set(0,'CurrentFigure',pre_h);
6608 
+  LOG=1;
6609 
+else
6610 
+  LOG=0;
6611 
+end
6612 
+
6613 
+comp_names_h=getfield(get(gcf,'UserData'),'comp_names_h');
6614 
+
6615 
+set(comp_names_h,'Value',[1:length(get(comp_names_h,'String'))]);
6616 
+sel_comp;
6617 
+
6618 
+if ~LOG
6619 
+  data=get(gcf,'UserData');
6620 
+  data.LOG{length(data.LOG)+1}='% Select all components';
6621 
+  data.LOG{length(data.LOG)+1}='preprocess(''sel_all_comps'',''foo'');';
6622 
+  set(gcf,'UserData',data);
6623 
+end
6624 
+
6625 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6626 
+
6627 
+function code=write_log_code(indices,arg1,arg2,arg3,arg4,arg5,arg6);
6628 
+
6629 
+str=textwrap({num2str(indices)},500);
6630 
+
6631 
+code{1}=sprintf('inds=[];');
6632 
+for i=1:length(str);
6633 
+  code{i+1}=sprintf('  inds=cat(2,inds,[%s]);',str{i});
6634 
+end
6635 
+str=cat(2,'preprocess(''''clip_data'''',''''',arg1,' ',num2str(arg2),' ',...
6636 
+                      num2str(arg3),' ',num2str(arg4),...
6637 
+                      ' ',num2str(arg5),' ',num2str(arg6),' ');
6638 
+code{length(code)+1}=cat(2,'eval(cat(2,',...
6639 
+                            '''',str,'''',...
6640 
+                            ',num2str(inds),'''''');''));');
6641 
+
6642 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
somtoolbox2/rep_utils.m
Zeige Datei @ 4dbef18
... ... 
@@ -0,0 +1,572 @@
1 
+function aout = rep_utils(action,fmt,fid)
2 
+
3 
+%REP_UTILS Utilities for print reports and report elements.
4 
+%
5 
+% aout = rep_utils(action,fmt,[fid])
6 
+%
7 
+%  Input and output arguments ([]'s are optional):
8 
+%   action      (string)     action identifier
9 
+%               (cell array) {action,par1,par2,...}
10 
+%                            the action identifier, followed by action
11 
+%                            parameters
12 
+%   [fmt]       (string)     format of output, 'txt' by default
13 
+%   [fid]       (scalar)     output file id, by default NaN in which
14 
+%                            case output is not written, only returned
15 
+%                            in aout
16 
+%
17 
+%   aout        (varies)     output of the action
18 
+%
19 
+%  Here are the actions and their arguments:
20 
+%  'printlines'   par1 (cellstr)   print par1, each cell on a new line
21 
+%  'header'       par1 (string)    print document header using par1 as title
22 
+%  'footer'                        print document footer
23 
+%  'compile'      par1 (string)    compile the named document (only 'ps' and 'pdf')
24 
+%  'inserttable'  par1 (struct)    print given table
25 
+%                 par2 (scalar)    print lines between rows if par2=1
26 
+%                 par3 (scalar)    use longtable format (only 'ps' and 'pdf')
27 
+%  'printfigure'  par1 (string)    print current figure to file, par1 = filename
28 
+%                 par2 (scalar)    used resolution (150 dpi by default)
29 
+%                 par3 (scalar)    if par3=1, insert figure in minipage
30 
+%  'insertfigure' par1 (string)    insert figure to report, par1 = filename of figure
31 
+%                 par2 (vector)    size 2 x 1, size of figure relative to page size
32 
+%                                  NaN = automatic scaling
33 
+%                 par3 (scalar)    if par3=1, insert figure in minipage (only 'ps' and 'pdf')
34 
+%  'insertbreak'                   insert paragraph break into report
35 
+%
36 
+% See also  REP_STATS.
37 
+
38 
+% Contributed to SOM Toolbox 2.0, January 2nd, 2002 by Juha Vesanto
39 
+% Copyright (c) by Juha Vesanto
40 
+% http://www.cis.hut.fi/projects/somtoolbox/
41 
+
42 
+% Version 2.0beta juuso 020102
43 
+
44 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
45 
+%% input arguments
46 
+
47 
+pars = {''};
48 
+if iscell(action),
49 
+    if length(action)>1, pars = action(2:end); end
50 
+    action = action{1};
51 
+end
52 
+
53 
+if nargin<2 | isempty(fmt), fmt = 'txt'; end
54 
+global REPORT_OUTPUT_FMT
55 
+REPORT_OUTPUT_FMT = fmt;
56 
+
57 
+if nargin<3 | isempty(fid), fid = NaN; end
58 
+
59 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
60 
+%% action
61 
+
62 
+aout = [];
63 
+printable = 0;
64 
+
65 
+switch action,
66 
+case 'printlines',
67 
+    aout = pars{1};
68 
+case 'header',
69 
+    switch fmt,
70 
+    case {'ps','pdf'}, aout = tex_startdocument(pars{1});
71 
+    case 'html',       aout = html_startpage(pars{1});
72 
+    case 'txt',        aout = cell(0);
73 
+    end
74 
+    printable = 1;
75 
+case 'footer',
76 
+    switch fmt,
77 
+    case {'ps','pdf'}, aout = tex_enddocument;
78 
+    case 'html',       aout = html_endpage;
79 
+    case 'txt',        aout = cell(0);
80 
+    end
81 
+    printable = 1;
82 
+case 'compile',      aout = compiledocument(pars{1});
83 
+case 'inserttable',  aout = inserttable(pars{:}); printable = 1;
84 
+case 'printfigure',  printfigure(pars{:});
85 
+case 'insertfigure', aout = insertfigure(pars{:}); printable = 1;
86 
+case 'insertbreak',  aout = insertbreak; printable = 1;
87 
+case 'joinstr',      aout = joinstr(pars{:}); printable = 1;
88 
+case 'rulestr',      aout = rulestr(pars{:}); printable = 1;
89 
+case 'c_and_p_str',  aout = c_and_p_str(pars{:}); printable = 1;
90 
+case 'p_str',        aout = p_str(pars{:}); printable = 1;
91 
+end
92 
+
93 
+% if output file is given, print lines
94 
+if ~isnan(fid) & printable,
95 
+    if ~iscell(aout), aout = {aout}; end
96 
+    for i = 1:length(aout), fprintf(fid,'%s\n',fmtline(aout{i})); end
97 
+end
98 
+
99 
+return;
100 
+
101 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
102 
+%% subfunctions
103 
+
104 
+%% simple formatter strings
105 
+
106 
+function s = joinstr(cs, sep1, sep2)
107 
+  if nargin==1, sep1 = ', '; sep2 = ' and '; end
108 
+  if nargin<3, sep2 = sep1; end
109 
+  if isempty(cs),
110 
+    s = '';
111 
+  elseif strcmp(sep1,'\n'),
112 
+    if size(cs,1)==1, cs = cs'; end
113 
+    s = char(cs);
114 
+  else
115 
+    s = cs{1};
116 
+    for i=2:length(cs)-1, s = [s sep1 cs{i}]; end
117 
+    if length(cs)>1, s = [s sep2 cs{end}]; end
118 
+  end
119 
+  return;
120 
+
121 
+function str = c_and_p_str(n,m)
122 
+
123 
+  % return a string of form # (%), e.g. '23 (12%)'
124 
+  if n==m, p = '100';
125 
+  elseif n==0, p = '0';
126 
+  else p = sprintf('%.2g',100*n/m);
127 
+  end
128 
+  str = sprintf('%d (%s%%)',round(n),p);
129 
+  return;
130 
+
131 
+function str = p_str(p)
132 
+  % return a string of form %, e.g. '12%'
133 
+  if round(p*100)>=100, p = sprintf('%3g',100*p);
134 
+  elseif abs(p)<eps, p = '0';
135 
+  else p = sprintf('%.2g',100*p);
136 
+  end
137 
+  str = sprintf('%s%%',p);
138 
+  return;
139 
+
140 
+function cs = rulestr(sR,cnames)
141 
+  global REPORT_OUTPUT_FMT
142 
+  switch REPORT_OUTPUT_FMT
143 
+   case {'ps','pdf'}, [leq,geq,infi,m,less,in] = deal('\leq','\geq','\inf','$','<','\in');
144 
+   case 'html',  [leq,geq,infi,m,less,in]  = deal('&lt;=','&gt;=','Inf',' ','&lt;',' ');
145 
+   case 'txt', [leq,geq,infi,m,less,in]  = deal('<=','>=','inf',' ','<','');
146 
+  end
147 
+  nr = length(sR);
148 
+  cs = cell(nr,1);
149 
+  fmt = '%.2g';
150 
+  if nargin<2, cnames = {sR.name}; end
151 
+  if isempty(cnames), cnames = cell(nr,1); cnames(:) = {''}; end
152 
+  for i=1:nr,
153 
+    low  = sR(i).low;
154 
+    high = sR(i).high;
155 
+    switch isfinite(low) + 2*isfinite(high),
156 
+     case 0, cs{i} = [cnames{i} ' ' 'any'];
157 
+     case 1, cs{i} = [cnames{i} ' ' m geq sprintf(fmt,low) m];
158 
+     case 2, cs{i} = [cnames{i} ' ' m less sprintf(fmt,high) m];
159 
+     case 3, cs{i} = [cnames{i} ' ' m in '[' sprintf(fmt,low) ',' sprintf(fmt,high) ']' m];
160 
+    end
161 
+  end
162 
+  return;
163 
+
164 
+%% print figure
165 
+