sortFV.m

load VISAA
hh = newcolormap('heated');
Npatot = VIS.Npat + VIS.Ntest;

FV = VIS.FVs.FV;
Nbm = VIS.FVs.Nbm;


% AA 8/23/20 Poly sorted by class
reslabel = [1 2 3 13 14];
metlabel = [15 16 17 18 19 20 21];
senslabel = [4 5 6 7 8 9 10 11 12 22 23];

% % BB or DD 8/23/20 Straight Ag-Pol sorted by class
% reslabel = [1 2 3 4 22];
% metlabel = [5 6 7 8 9 10 11];
% senslabel = [12 23 13 14 15 16 17 18 19 20 21];

FVres = FV(reslabel,:);
FVmet = FV(metlabel,:);
FVsens = FV(senslabel,:);

[~,finalres] = hierarchcluster(vec2simtest(FVres,9));
[~,finalmet] = hierarchcluster(vec2simtest(FVmet,9));
[~,finalsens] = hierarchcluster(vec2simtest(FVsens,9));

newreslabel = reslabel(finalres);
newmetlabel = metlabel(finalmet);
newsenslabel = senslabel(finalsens);

newlabel = concat(concat(newreslabel,newmetlabel),newsenslabel);

FVsrt = FV(newlabel,:);

Sim = vec2simtest(FVsrt,9);

figure(100)
imagesc(Sim)
caxis([-1 1])
colormap(hh)

patmp = concat(concat(VIS.patnam.resist,VIS.patnam.sens),VIS.patnam.test);
patname = patmp(newlabel);

for loop = 1:Npatot
    text(Npatot+0.6,loop,char(patname(loop)))
end
set(gcf,'Color','white')

figure(101)
imagesc(FVsrt)
colormap(hh)
caxis([-2 2])
for loop = 1:Npatot
    text(Nbm+0.6,loop,char(patname(loop)))
end
bmname = VIS.FVs.BMName;
for loop = 1:Nbm
    text(loop-0.4,0,char(bmname(loop)))
end
set(gcf,'Color','white')


pred = concat(VIS.Pred,VIS.Pretest);
prederr = concat(VIS.Predstd,VIS.Preteststd);

predict = pred(newlabel);
predicterr = prederr(newlabel);
x = 1:length(predict);

figure(102)
bar(x,predict)
hold on
er = errorbar(x,predict,predicterr,predicterr);    
er.Color = [0 0 0];                            
er.LineStyle = 'none';  
er.LineWidth = 2;
hold off
g = gca;
for loop = 1:Npatot
    text(loop,g.YLim(2),char(patname(loop)),'Rotation',90)
end

fid = fopen('PatPredict.txt','w');
fprintf(fid,'%s \t %s \t %s\n','Patient','Predict','ste');
for ploop = 1:Npatot
    fprintf(fid,'%s \t %6.2f \t %6.2f\n',char(patname(ploop)),predict(ploop),predicterr(ploop));
end
fclose(fid);