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findSet_2.m
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findSet_2.m
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function []=findSet_2(k,pik_full,filepath,Case,N)
% Function code extracts the sets defined from coarse-graining from PCCA+
% clustering. These sets represent the phenotypes and are needed for the
% further TPT analysis. They are saved in .mat files and called in
% TPTCases.m file for the TPT analysis.
% A maximum of three (k=3) sets are considered, since the PCCA analysis
% resulted in a maximum of three sets.
%% Implemented by Anna S. Frank (anna-simone.frank@uib.no)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Load Input data
Input
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if k==1
% Definition of set based on percental support of density:---------
pik_full=pik_full/sum(pik_full);
% Find phenotype
pik_2D=reshape(pik_full,N+1,N+1);
[maxValue, linearIndexesOfMaxes] = max(pik_2D(:));
[rowsOfMaxes colsOfMaxes] = find(pik_2D == maxValue);
% sets
[dens_sort,idx]=sort(pik_full,'descend');
last_idx=find(cumsum(dens_sort)>PercTH);
if rowsOfMaxes > colsOfMaxes
setHL=[];
setHL=idx(1:last_idx);
Set='setHL';
% save set
filename = fullfile(filepath, sprintf('SetCase%d%s.mat', Case,Set));
save(filename, 'setHL');
elseif abs(rowsOfMaxes-colsOfMaxes)<10
setLL=[];
setLL=idx(1:last_idx);
Set='setLL';
% save set
filename = fullfile(filepath, sprintf('SetCase%d%s.mat', Case,Set));
save(filename, 'setLL');
elseif rowsOfMaxes < colsOfMaxes
setLH=[];
setLH=idx(1:last_idx);
Set='setLH';
% save set
filename = fullfile(filepath, sprintf('SetCase%d%s.mat', Case,Set));
save(filename, 'setLH');
end
end
if k==2
% Definition of set based on percental support of density:---------
pik_full=pik_full/sum(pik_full);
% Find phenotype
pik_2D=reshape(pik_full,N+1,N+1);
[maxValue, linearIndexesOfMaxes] = max(pik_2D(:));
[rowsOfMaxes colsOfMaxes] = find(pik_2D == maxValue);
[dens_sort,idx]=sort(pik_full,'descend');
last_idx=find(cumsum(dens_sort)>PercTH);
if rowsOfMaxes > colsOfMaxes
setHL=[];
setHL=idx(1:last_idx);
Set='setHL';
% save set
filename = fullfile(filepath, sprintf('SetCase%d%s.mat', Case,Set));
save(filename, 'setHL');
elseif abs(rowsOfMaxes-colsOfMaxes)<10
setLL=[];
setLL=idx(1:last_idx);
Set='setLL';
% save set
filename = fullfile(filepath, sprintf('SetCase%d%s.mat', Case,Set));
save(filename, 'setLL');
elseif rowsOfMaxes < colsOfMaxes
setLH=[];
setLH=idx(1:last_idx);
Set='setLH';
% save set
filename = fullfile(filepath, sprintf('SetCase%d%s.mat', Case,Set));
save(filename, 'setLH');
end
end
if k==3
% Definition of set based on percental support of density:---------
pik_full=pik_full/sum(pik_full);
% Find phenotype
pik_2D=reshape(pik_full,N+1,N+1);
[maxValue, linearIndexesOfMaxes] = max(pik_2D(:));
[rowsOfMaxes colsOfMaxes] = find(pik_2D == maxValue);
[dens_sort,idx]=sort(pik_full,'descend');
last_idx=find(cumsum(dens_sort)>PercTH);
if rowsOfMaxes > colsOfMaxes
setHL=[];
setHL=idx(1:last_idx);
Set='setHL';
% save set
filename = fullfile(filepath, sprintf('SetCase%d%s.mat', Case,Set));
save(filename, 'setHL');
elseif abs(rowsOfMaxes-colsOfMaxes)<10
setLL=[];
setLL=idx(1:last_idx);
Set='setLL';
% save set
filename = fullfile(filepath, sprintf('SetCase%d%s.mat', Case,Set));
save(filename, 'setLL');
elseif rowsOfMaxes < colsOfMaxes
setLH=[];
setLH=idx(1:last_idx);
Set='setLH';
% save set
filename = fullfile(filepath, sprintf('SetCase%d%s.mat', Case,Set));
save(filename, 'setLH');
end
end
end