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fig5_preprocessResourceEfficiencyReceive.m
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fig5_preprocessResourceEfficiencyReceive.m
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nreg=360;
nedge=64620;
cd('/data/faGlasser')
fa_network_files = dir('*FA_GlasserPNC.mat');
nfiles = length(fa_network_files);
nsub=nfiles;
fa_sq = zeros(nsub, nedge);
for k = 1:nfiles
fa_net = load(fa_network_files(k).name);
fa_net = fa_net.connectivity;
fa_net = fa_net - diag(diag(fa_net));
fa_sq(k,:) = squareform(fa_net);
end
cd /data/jux/BBL/projects/ASLnetwork/scripts
for probability=[0.999,0.98,0.96,0.94,0.92,0.9,0.8,0.7,0.6,0.5,0.4, 0.3, 0.2, 0.1]
disp(probability)
resEff_array=zeros(nsub,nreg+1);
for s=1:nsub
A_fa=squareform(fa_sq(s,:));
A = A_fa - diag(diag(A_fa));
[comps,~] = get_components(A);
A = A(comps==1,comps==1);
islands = find(comps>1);
Eres = resource_efficiency_wei(A,probability);
Eres = nanmean(Eres,1);
if length(islands)>0
for k=1:length(islands)
i = islands(k);
if k>1
B = [B(1:i-1),nan,B(i:end)];
else
B = [Eres(1:i-1),nan,Eres(i:end)];
end
end
resEff_array(s,2:nreg+1) = B;
else
resEff_array(s,2:nreg+1) = Eres;
end
% N = size(A,1);
% GEres = mean(Eres(~eye(N)>0))
subj_name = fa_network_files(s).name
resEff_array(s,1) = str2num(strtok(subj_name, '_'));
end
currentProb = num2str(probability, 16);
currentProb(currentProb=='.') = []
outName = strcat('/data/resource_efficiency',currentProb,'_receive.txt')
dlmwrite(outName,resEff_array,'delimiter',' ', 'precision', 10)
end