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Scripts_Sharing/ISFC/Utils_KMeans/ComputeJaccard.m
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ComputeJaccard.m
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function [J_CTR,J_ASD,J_all] = ComputeJaccard(SL,GL,TL,n_CTR,n_ASD,n_TP,K)
% Information about the time points and the subject labels for each
% group
TL_CTR = TL(GL==1);
TL_ASD = TL(GL==2);
SL_CTR = SL(GL==1);
SL_ASD = SL(GL==2);
% Number of subjects that actually have frames from that cluster
CTR_vec = unique(SL_CTR);
ASD_vec = unique(SL_ASD);
% I create a matrix with time information for CTR subjects
Time_info_CTR = zeros(n_CTR,n_TP);
% FILLED FIRST ROWS REGARDLESS OF ORDER OF SUBJECTS BECAUSE NEVER USED
for s = 1:length(CTR_vec)
Time_info_CTR(s,TL_CTR(SL_CTR == CTR_vec(s))) = 1;
end
% I do the same for the ASD subjects
Time_info_ASD = zeros(n_ASD,n_TP);
for s = 1:length(ASD_vec)
Time_info_ASD(s,TL_ASD(SL_ASD == ASD_vec(s))) = 1;
end
Time_info_all = [Time_info_CTR;Time_info_ASD];
% I want to pick all my pairs of subjects and to assess temporal
% consistency
Pairs_CTR = nchoosek((1:n_CTR)',2);
Pairs_ASD = nchoosek((1:n_ASD)',2);
Pairs_all = nchoosek((1:(n_CTR+n_ASD))',2);
J_CTR = 0;
for i = 1:size(Pairs_CTR,1)
tmp1 = logical(Time_info_CTR(Pairs_CTR(i,1),:));
tmp2 = logical(Time_info_CTR(Pairs_CTR(i,2),:));
% Jaccard index update
if sum(tmp1 | tmp2) > 0
J_CTR = J_CTR + (sum(tmp1 & tmp2))/(n_TP/K^2);%(sum(tmp1 | tmp2));
end
end
J_CTR = J_CTR/size(Pairs_CTR,1);
J_ASD = 0;
for i = 1:size(Pairs_ASD,1)
tmp1 = logical(Time_info_ASD(Pairs_ASD(i,1),:));
tmp2 = logical(Time_info_ASD(Pairs_ASD(i,2),:));
% Jaccard index update
if sum(tmp1 | tmp2) > 0
J_ASD = J_ASD + (sum(tmp1 & tmp2))/(n_TP/K^2);%(sum(tmp1 | tmp2));
end
end
J_ASD = J_ASD/size(Pairs_ASD,1);
J_all = 0;
for i = 1:size(Pairs_all,1)
tmp1 = logical(Time_info_all(Pairs_all(i,1),:));
tmp2 = logical(Time_info_all(Pairs_all(i,2),:));
% Jaccard index update
if sum(tmp1 | tmp2) > 0
J_all = J_all + (sum(tmp1 & tmp2))/(n_TP/K^2);%(sum(tmp1 | tmp2));
end
end
J_all = J_all/size(Pairs_all,1);
end
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