pcagui.m

PLS_Toolbox是用于故障检测与诊断方面的matlab工具箱

        %Scaling
        switch modl.scale
        case 'mean'                               %mean center
          [x,modl.means] = mncn(x);
          modl.stds      = std(x);
        case 'auto'                               %autoscale
          [x,modl.means,modl.stds] = auto(x);
        otherwise                                 %no scaling
          modl.means     = mean(x);
          modl.stds      = std(x);
        end
        %SVD
        if n<m
          cx  = (x'*x)/(m-1);
          [u,s,v] = svd(cx);
          pcs = (1:n)';
        else
          cx  = (x*x')/(m-1);
          [u,s,v] = svd(cx);
          v   = x'*v;
          for i=1:m
            v(:,i) = v(:,i)/norm(v(:,i));
          end
          pcs = (1:m)';
        end
        s     = diag(s);
        cap   = s*100/(sum(s));
        pc    = 1;                   %default model
        modl.name   = 'PCA';
        modl.date   = date;          %date model was created
        modl.time   = clock;         %time model was created
        modl.scores = x*v(:,1:pc);   %PCA scores
        modl.samps  = m;             %Number of samples in (data)
        modl.loads  = v(:,1:pc);     %PCA loadings
        modl.ssq    = [pcs s cap cumsum(cap)]; %Variance information
        modl.xname  = get(d(4,1),'UserData');
    
        res   = (x - modl.scores*modl.loads')';
        res   = sum(res.^2)';
        %Q Residuals and Limit
        modl.res    = res;           %Sample residuals Q    
        modl.reslim = reslim(pc,s,95); %95% conf limit for Q
        %T^2 and Limit
        cap   = 1./sqrt(s(1:pc,1));
        cap   = modl.scores*diag(cap);
        if pc>1
          tsqs  = sum((cap.^2)')';
        else
          tsqs  = (cap.^2);
        end
        modl.tsq    = tsqs;            %Sample Hotelling T^2
        modl.tsqlim = tsqlim(m,pc,95); %95% confidence limit for T^2

        format= get(e(1,1),'UserData');
        s     = [];
        for jj=1:min([size(modl.ssq,1); 25]) %max PCs listed = 25
          s   = [s;sprintf(format,modl.ssq(jj,:))];
        end
        set(f(3,1),'UserData',v)
        set(f(4,1),'UserData',pc);
        set(e(3,1),'String',int2str(pc))
        set(e(4,1),'String',s,'Value',pc)
        stat.data = 'cal';
        stat.modl = 'calold';
      else
        stat.modl = 'none';
      end
    else
      stat.data   = 'none';
    end
    set(bb(15,1),'Enable','off')
  case 'apply'
    delfigs(as)
    if strcmp(stat.modl,'calnew')
      if ~isempty(modl.drow)
        jk   = [];
        for jj=1:length(modl.drow)
          jk = [jk,find(modl.irow==modl.drow(jj))];
        end
        modl.irow = delsamps(modl.irow',jk)';
      end
      x     = x(modl.irow,modl.icol);
    end
    n       = size(x,2);
    m       = size(modl.loads,1);
    if size(x,2)~=m
      erdlgpls('Error- num vars in x ~= num rows of loads', ...
        'Error on Apply');
    else
      switch modl.scale
      case 'mean'
        x  = scale(x,modl.means);
      case 'auto'
        x  = scale(x,modl.means,modl.stds);
      end
      m    = get(f(4,1),'UserData');
      if ~strcmp(stat.modl,'loaded')
        v    = get(f(3,1),'UserData');
        if ~isempty(v)
          modl.loads = v(:,1:m);
        end
        clear v
        modl.reslim = reslim(m,modl.ssq(:,2),95);
        modl.tsqlim = tsqlim(length(modl.irow),m,95);
        modl.scores = x*modl.loads;
        modl.res    = (x - modl.scores*modl.loads')';
        modl.res    = sum((modl.res).^2)';
        modl.tsq    = 1./sqrt(modl.ssq(1:m,2));
        modl.tsq    = modl.scores*diag(modl.tsq);
        if m>1
          modl.tsq  = sum(((modl.tsq).^2)')';
        else
          modl.tsq  = (modl.tsq).^2;
        end
        set(bb(15,1),'Enable','off')
      else
        test.scores = x*modl.loads;
        test.res    = (x - (test.scores)*(modl.loads)')';
        test.res    = sum((test.res).^2)';
        test.tsq    = 1./sqrt(modl.ssq(1:m,2));
        test.tsq    = test.scores*diag(test.tsq);
        test.xname  = get(d(4,1),'UserData');
        if m>1
          test.tsq  = sum(((test.tsq).^2)')';
        else
          test.tsq  = (test.tsq).^2;
        end
        set(bb(15,1),'Enable','on')
      end
      if strcmp(stat.data,'new')
        stat.data = 'test';
        stat.modl = 'loaded';
      end
      if strcmp(stat.data,'cal')
        stat.modl = 'calold';
      end
    end  
  case 'actssq'
    if strcmp(stat.modl,'loaded')
      n      = get(f(4,1),'UserData');
      set(e(3,1),'String',int2str(n))
      set(e(4,1),'Value',n)    
    elseif ~strcmp(stat.data,'none')
      n      = get(e(4,1),'Value');
      set(e(3,1),'String',int2str(n))
      set(f(4,1),'UserData',n);
      stat.modl = 'calnew';
    end
  case 'actssq2'
    if strcmp(stat.modl,'loaded')
      n      = get(f(4,1),'UserData');
      set(e(3,1),'String',int2str(n))
      set(e(4,1),'Value',n)    
    elseif ~strcmp(stat.data,'none')&~strcmp(stat.modl,'none')
      n      = str2num(get(e(3,1),'String'));
      n      = round(n);
      if (n<1)|(n>max(modl.ssq(:,1)))
        n    = 1;
      end
      set(e(4,1),'Value',n);
      set(e(3,1),'String',int2str(n))
      set(f(4,1),'UserData',n);
      stat.modl = 'calnew';
    end
  case 'printssqtable'
    ssqtable(modl,size(modl.loads,2));
  end

%button status
  if ~strcmp(lower(action),'exitpca')
    set(b(1,1),'UserData',stat)
    set(f(2,1),'UserData',modl)
    set(f(5,1),'UserData',test)
    if strcmp(stat.data,'none')&strcmp(stat.modl,'none')
      %no data, no model
      set(f(1:7,1),'Enable','off')
    elseif ~strcmp(stat.modl,'none')&strcmp(stat.data,'none')
      %no data, a model
      set(f([1:2 4:7],1),'Enable','off')
      set(f(3,1),'Enable','on')
    elseif ~strcmp(stat.data,'none')&strcmp(stat.modl,'none')
      %new data, no model
      set(f([1 7],1),'Enable','on')
      set(f(2:6,1),'Enable','off')
    elseif ~strcmp(stat.data,'none')&(~strcmp(stat.modl,'none'))
      %data and model
      if strcmp(stat.modl,'calold')
        set(f(1:2,1),'Enable','off')
        set(f(3:7,1),'Enable','on')
      elseif strcmp(stat.modl,'calnew')
        set(f([1 4:6],1),'Enable','off')
        set(f([2:3 7],1),'Enable','on')
      elseif strcmp(stat.modl,'loaded')
        if strcmp(stat.data,'test')
          set(f(1:2,1),'Enable','off')
          set(f(3:7,1),'Enable','on')
        else
          set(f([1 3:6],1),'Enable','off')
          set(f([2 7],1),'Enable','on')
        end
      end
    end
    if get(f(4,1),'UserData')<2
      set(f(6,1),'Enable','off') %biplot button
      h = findobj('Name','Biplot','Tag',as); close(h)
    end

    %scaling menu
    if strcmp(stat.modl,'loaded')|strcmp(stat.data,'none')
      set(bb(12:14,1),'Enable','off')
    else
      set(bb(12:14,1),'Enable','on')
    end
    
    %status strings and file menu
    if strcmp(stat.modl,'none')
      set(f(3:4,1),'UserData',[])
      set(e(3,1),'String',' ')
      set(e(4,1),'String',' ','Value',1)
      if strcmp(stat.data,'none')
        s  = ['Model: none loaded'];
      else
        s  = ['Model: not calculated'];
      end
      set(e(6,1),'String',s)
      set(bb([8:10 17],1),'Enable','off');
    else
      set(bb([8:10 17],1),'Enable','on');
      switch stat.modl  
      case 'loaded'
        if strcmp(stat.data,'none')
          s  = ['Model: loaded'];
        elseif strcmp(stat.data,'new')
          s  = ['Model: loaded but not applied'];
        elseif strcmp(stat.data,'test')
          s  = ['Model: loaded and applied'];
        end
      case 'calnew'
        s  = ['Model: not applied'];
      case 'calold'
        s  = ['Model: calibrated on loaded data'];
      end
      modl = get(f(2,1),'UserData');
      pc   = size(modl.loads,2);
      if strcmp(modl.scale,'auto')
        sc = 'autoscaled';
      elseif strcmp(modl.scale,'mean')
        sc = 'mean centered';
      else
        sc = 'not scaled';
      end
      s1   = ['PC(s): ',int2str(pc)];
      s2   = ['Scaling: ',sc];
      s3   = ['Data: ',int2str(length(modl.irow)),' sams x '];
      s3   = [s3,[int2str(length(modl.icol)),' vars']];
      set(e(6,1),'String',str2mat(s,s1,s3,s2))
    end
    if strcmp(stat.data,'none')
      set(f(1,1),'UserData',[])
      set(e(5,1),'String','Data: none loaded')
      set(bb([3:7 9],1),'Enable','off');
    else
      set(b(2:3,1),'Enable','on')
      set(bb([3:6 9],1),'Enable','on')
      if modl.drow|modl.dcol
        set(bb(7,1),'Enable','on');
      end
      if ~strcmp(stat.modl,'loaded')
        set(bb([4 6],1),'Enable','on');
      else
        set(bb([4 6],1),'Enable','off');
      end
      if strcmp(stat.data,'new')
        s   = ['Data: loaded but not analyzed'];
        s4  = ['Samp Lbls: ',modl.slbln];
      elseif strcmp(stat.data,'cal')
        s   = ['Data: modeled (calibration set)'];
        s4  = ['Samp Lbls: ',modl.slbln];
      elseif strcmp(stat.data,'test')
        s   = ['Data: modeled (test set)'];
        s4  = ['Samp Lbls: ',test.slbln];
      end
      [m,n] = size(get(f(1,1),'UserData'));
      s3    = ['Var: ',get(d(4,1),'UserData')];
      s2    = ['Size: ',int2str(m),' rows x ',int2str(n),' cols'];
      s5    = ['Var Lbls: ',modl.vlbln];
      set(e(5,1),'String',str2mat(s3,s,s2,s4,s5))
    end
  end
end

function [] = delfigs(as)
h = findobj('Name','Eigenvalues','Tag',as); close(h)
h = findobj('Name','Plot Scores','Tag',as); close(h)
h = findobj('Name','Plot Loads','Tag',as);  close(h)
h = findobj('Name','Biplot','Tag',as);      close(h)