Val.P = P_test; Val.T = T_test;
[P_train_n minp maxp] = premnmx(P_train);
Val_n.P = tramnmx(P_test,minp,maxp);
[T_train_n mint maxt] = premnmx(T_train);
Val_n.T = tramnmx(T_test,mint,maxt);

[P_train_std meanp stdp] = prestd(P_train);
Val_std.P = trastd(P_test,meanp,stdp);
[T_train_std meant stdt] = prestd(T_train);
Val_std.T = trastd(T_test,meant,stdt);
%Val_std.T = T_test;

%[P_pca transMatp] = prepca(P_train_std,0.2);
%Val_pca.P = trapca(Val_std.P,transMatp);
%[T_pca transMatt] = prepca(T_train_std,0.2);
%Val_pca.T = trapca(Val_std.T,transMatt);

[pc latent explained] = pcacov(P_train_std*P_train_std');
n = 8; explained
Q = pc(:,1:n);
P_train_pca = Q'*P_train_std;
Val_pca.P = Q'*Val_std.P;

Val_pca.T = Val_std.T;