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Copy pathICI_extract_Sequence2.m
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ICI_extract_Sequence2.m
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function [Send_seq,Send_seq2,class_max,class_sum]=ICI_extract_Sequence2(time,ey_norm,locs,pks,Y_zoom,F_ds,consistency_T,ICI_max,ICI_min,Th)
% locs=Times; pks=Powers;
%
% Th=Th_echo;
% ICI_min=ICI_min_echo;
% ICI_max=ICI_max_echo;
%
% locs=[]; locs=Locs;
% pks=[]; pks=Pks;
no_clusters_flag=0;
class_max={}; class_sum={};
Final_seq={}; Final_ICI={}; Final_L={}; Compare=[]; Candidate_Trains={}; Send_seq=[];
Send_seq2=[]; Compare2=[]; Candidate_Trains2={};
T_locs=locs;
locs_inds=T_locs*F_ds;
slice=0.015*F_ds;
for ij=1:length(locs_inds)
BANK(ij,:)=Y_zoom(int32(locs_inds(ij)-slice):int32(locs_inds(ij)+slice));
M_bank(ij)=max(BANK(ij,:));
end
T_pks=M_bank;
S=0; C_ind=0; C=[]; Triple=[]; Save_C=[]; Triple_ind=[];
for n=1:length(T_locs)-1
for m=n+1:length(T_locs)
for l=m+1:length(T_locs)
S=S+1;
C(S,:)=[log((T_locs(l)-T_locs(m))/(T_locs(m)-T_locs(n))) n m l];
AD(S)=(T_pks(l)+T_pks(m)+T_pks(n))^2/(3*(T_pks(l)^2+T_pks(m)^2+T_pks(n)^2)) ;
if abs(C(S,1))<consistency_T && AD(S)>Th && T_locs(l)-T_locs(m)<ICI_max && T_locs(l)-T_locs(m)>ICI_min
C_ind=C_ind+1;
Triple(C_ind,:)= [T_locs(n) T_locs(m) T_locs(l)];
Triple_ind(C_ind,:)= [n m l];
Save_C(C_ind,:)=[abs(C(S,1)) C(S,2:end) T_locs(l)-T_locs(m) AD(S)];
end
end
end
end
Tmp=Save_C;
Flag=size(Save_C,1);
if Flag>1 && Flag<3
Send_seq=unique(Tmp(:,2:4));
Send_seq=Send_seq';
Send_seq2=Send_seq;
elseif Flag>1
if Flag<5
En=1;
else
En=Flag-4;
end
for Q=1:En
Save_C=Tmp(Q:end,:);
SEQ=Save_C(:,2:4);
seq_save=[];
i=1;
Final_seq={};
Final_flag=0;
q=1; init=0;
%%
while(Final_flag==0)
Candidates=[];
for T=seq_save
[eliminate_inds , ~]=find(Save_C(:,2:4)==T);
Save_C(eliminate_inds,:)=[];
eliminate_inds=[]; a1=[];
end
if isempty(seq_save) && init>0
Save_C(1,:)=[];
end
if size(Save_C,1)<1
Final_flag=1;
end
seq_save=[];
SEQ=Save_C(:,2:4);
i=1;
j=i+1; k=1;
Exit_flag=0;
while(i<(size(SEQ,1)) && Exit_flag==0)
s=1;
while(j<size(SEQ,1)+1)
Inter=intersect(SEQ(i,:),SEQ(j,:));
if length(Inter)==2
DIF=abs(Save_C(i,5)-Save_C(j,5));
if Inter(2)==SEQ(i,3) && Inter(2)~=SEQ(j,3) && DIF<0.2
Candidates(s,:)=[SEQ(j,:) Save_C(j,1) Save_C(j,5) j Save_C(j,6)];
s=s+1;
end
end
j=j+1;
end
if length(Candidates)>1
Candidates_diversity=Candidates(:,7);
Choose=find(Candidates_diversity==max(Candidates_diversity));
seq_save(k,:)=Candidates(Choose(1),:);
i= seq_save(k,6);
j=i+1;
k=k+1;
Candidates=[];
elseif isempty(Candidates)
Exit_flag=1;
else
seq_save(k,:)=Candidates;
i= seq_save(k,6);
j=i+1;
k=k+1;
Candidates=[];
end
end
contents=seq_save;
if ~isempty(seq_save)
seq_save=[SEQ(1,1) seq_save(:,1)' seq_save(end,2:3)];
seq_save=unique(seq_save);
end
if length(seq_save)<4
Final_seq(q)={[]};
Final_ICI(q)={[]};
Final_L(q)={[]};
L1(q)=0;
q=q+1;
else
Final_seq(q)={seq_save};
Final_ICI(q)={ones(1,length(seq_save))*mean(contents(:,5))};
Final_L(q)={ones(1,length(seq_save))*length(seq_save)};
L1(q)=length(seq_save);
q=q+1;
end
contents=[];
SEQ=[];
init=init+1;
end
Cluster_cands(Q)={Final_seq(find(~cellfun(@isempty,Final_seq)))};
S_index=find(L1==max(L1));
Candidate_Trains(Q)={cell2mat(Final_seq(S_index(1)))};
Compare(Q)=max(L1);
Candidate_Trains2(Q)={cell2mat(Final_seq)};
Compare2(Q)=sum(L1);
L1=[];
end
if ~isempty(Compare) && sum(Compare)>0
no_clusters_flag=1;
Final_selection=find(Compare==max(Compare));
Final_selection2=find(Compare2==max(Compare2));
if ~isempty(Final_selection)
Send_seq=Candidate_Trains(Final_selection(1));
end
if ~isempty(Final_selection2)
Send_seq2=Candidate_Trains2(Final_selection2(1));
end
Send_seq2=cell2mat(Send_seq2);
else
no_clusters_flag=0;
end
end
if no_clusters_flag
for i=1:length(Cluster_cands{Final_selection(1)})
class_max(i)={Cluster_cands{Final_selection(1)}{i}};
end
if length(Final_selection2)>1
for j=1:length(Final_selection2)
cellsz = cellfun(@length,Cluster_cands{Final_selection2(j)},'uni',false);
Lj(j)=max([cellsz{:}]);
end
pick=find(Lj==max(Lj));
for i=1:length(Cluster_cands{Final_selection2(pick(1))})
class_sum(i)={Cluster_cands{Final_selection2(pick(1))}{i}};
end
else
for i=1:length(Cluster_cands{Final_selection2})
class_sum(i)={Cluster_cands{Final_selection2}{i}};
end
end
end
%% Extract the taged clicks
% % peaks_tag=find(Compare==max(Compare));
% for i=1:length(Compare)
% Score(i)=mean(pks(cell2mat(Candidate_Trains(i))));
% end
%
% Eli=find(Compare<10); Score(Eli)=0;
% Tag_choice=find(Score==max(Score));
% if Score(Tag_choice(1))>0.5
% Send_seq2=[];
% Send_seq2=cell2mat(Candidate_Trains(Tag_choice(1)));
% end
end