analysesompls.m

有监督自组织映射-偏最小二乘算法(A supervised self-organising map–partial least squares algorithm),可以用语多变量数据的回归分析

function AnalyseSOMPLS(BestMLK,NBestMLK,MLKP,OPT,Tmax,SelVar);


[BSelect] = PlotBPLS(NBestMLK, OPT.LV, 0);
if (nargin == 6 & SelVar > 0)
    NBestMLK.Ytr=NBestMLK.Ytr(:,SelVar);
    BestMLK.YMap=BestMLK.YMap(SelVar,:);
    BSelect=BSelect(:,SelVar);
end
if (nargin < 5)
    Tmax = 1;
end
[Dummy,NvarX]=size(BestMLK.XMap);
[Nobj,Cmax]=size(NBestMLK.Ytr);
N=Nobj/Tmax;
BSelect=BSelect(1:NvarX,:);
close all

if (upper(MLKP.ProblemType) == 'REG')
    for t=1:Tmax
        XSel=NBestMLK.Xtr(1+(t-1)*N:t*N,1:NvarX);
        YSel=NBestMLK.Ytr(1+(t-1)*N:t*N,:);
        [ys,poso]=sort(YSel);
        [ys,posc]=sort(BestMLK.YMap'); 
        CT=CalcCorrTable([BestMLK.XMap; BestMLK.YMap],XSel);
        for c=1:Cmax
            figure(1)
            subplot(Tmax,Cmax,(t-1)*Cmax+c)
            imagesc(CT(:,poso(:,c))',[-1 1])
            if t == 1
                title('Sorted CI (XMap,Kernel)')
            end
            figure(2)
            subplot(Tmax,Cmax,(t-1)*Cmax+c)
            imagesc(XSel(poso(:,c),posc(:,c)));
            if t == 1
                title('Sorted Kernel')
            end
            colorbar
        end
    end
else
    [ClassMap] = AssignClass(BestMLK.YMap);
    LabYMap = Bin2Labs(ClassMap');
    LabYtr = Bin2Labs(BestMLK.Ytr);
    for t=1:Tmax
        XSel=NBestMLK.Xtr(1+(t-1)*N:t*N,:);
        YSel=LabYtr(1+(t-1)*N:t*N);
        [ys,poso]=sort(YSel);
        [ys,posc]=sort(LabYMap); 
        CT=CalcCorrTable(BestMLK.XMap,XSel);
        figure(1)
        subplot(Tmax,1,(t-1)+1)
        imagesc(CT(:,poso)',[-1 1])
        if t == 1
            title('CI (XMap,Kernel)')
        end
        figure(2)
        subplot(Tmax,1,(t-1)+1)
        imagesc(XSel(poso,posc));
        if t == 1
            title('Sorted Kernel')
        end
        colorbar
    end
end

figure(3)
subplot(1,3,1)
CT=CalcCorrTable(NBestMLK.XLoadings(1:NvarX,:)',BestMLK.YMap);
imagesc(CT)
title('CI (PLS loadings,YMap)')
colorbar
subplot(1,3,2)
CT=CalcCorrTable(BSelect',BestMLK.YMap);
imagesc(CT)
title('CI (Bcoefficients,YMap)')
colorbar
subplot(1,3,3)
CT=CalcCorrTable(NBestMLK.XLoadings(1:NvarX,:)',BSelect');
imagesc(CT)
title('CI (PLS loadings,Bcoefficients)')
colorbar

Nlv=min(5,OPT.LV);
figure(4);
for poslv=1:Nlv
    [ys,posl]=sort(NBestMLK.XLoadings(1:NvarX,poslv)');
    subplot(Nlv,1,poslv)
    imagesc(BestMLK.XMap(:,posl)')
    if poslv == 1
        title('XMap sorted for PLS loading values')
    end
end

figure(5)
CT=CalcCorrTable(NBestMLK.XLoadings(1:NvarX,:)',BestMLK.XMap);
subplot(3,1,1)
plot(BestMLK.Xtr')
axis tight
title('CI (XMap,PLS loadings)')
subplot(3,1,2)
imagesc(CT(1:Nlv,:))
subplot(3,1,3)
plot(CT(1:Nlv,:)')
axis tight

figure(6)
CT=CalcCorrTable(BSelect',BestMLK.XMap);
subplot(3,1,1)
plot(BestMLK.Xtr')
axis tight
title('CI (XMap,Bcoefficients)')
subplot(3,1,2)
imagesc(CT)
subplot(3,1,3)
plot(CT');
axis tight