%% MAIN SVD

% We use data from a CCA model that we run using the toolkit, so as to make
% sure that we respect the train and test sets appropriately.

clear

% Change the two directories to where the main model is,
% abcdAll_noA\framework\spls_fair20-5_fair_modeA_pub_noAnom_new_common_bmi,
% as well as to where the main SVD model is,
% abcdAll_noA\framework\cca_holdout1-0.20_common_PCA_CCA_9_correct_outmat.
svd_framework = 'C:\Users\Konstantinos Tsirlis\Dropbox\My Desktop\Mourao - Miranda\ABCD results\abcdAll_noA\framework\cca_holdout1-0.20_common_PCA_CCA_9_correct_outmat';
main_framework = 'C:\Users\Konstantinos Tsirlis\Dropbox\My Desktop\Mourao - Miranda\ABCD results\abcdAll_noA\framework\spls_fair20-5_fair_modeA_pub_noAnom_new_common_bmi';



cd([svd_framework '\load\svd']);
clear svd_framework
to_load = dir('tr_svd*');
load(to_load(1).name);
clear to_load


explained_var = sqrt(LY);
explained_var = explained_var*100/sum(explained_var);


% Compute correlations between (only the non-zero) SPLS weights and the SVD weights 

cd([main_framework '\res']);

spls_weights_svd_correl = [];
spls_loadings_svd_correl = [];


for j = 1:length(dir('level*'))

cd([main_framework '\res\level' num2str(j)]);

model = dir('model*'); load(model.name,'wY');
clear model
load('corrCell.mat')


for i = 1:size(VY,2)

spls_loadings_svd_correl(i,j) = corr(VY(:,i),corrCell{1,2}');
spls_weights_svd_correl(i,j) = corr(VY(find(wY),i),wY(find(wY))');

end %i

clear wY corrCell

end %j


cd([main_framework '\res']);
save('svd_correl.mat','spls_loadings_svd_correl','spls_weights_svd_correl','explained_var')