clc
clear
close all
%先形成初始点
center=[1,1,1,1,1;10,10,10,10,10;100,100,100,100,100;1000,1000,1000,1000,1000];
center=[1;10;100;1000];
dataN=50;% 生成多少个数据
Dim=1;
data=zeros(Dim,dataN);
for I=1:dataN
    i=round(1+(4-1)*rand());
    data(:,I)=center(i)*( -1+(1+1)*rand(Dim,1));
end


SetS=[1;];

for clusterI=1:3
    maxG=-100*ones(dataN,1);
    for cluster=1:dataN
        if sum(ismember(cluster,SetS))>0
            continue
        end
        %选一个候选数据
        cddtI=cluster;
        cadSetS=[SetS;cddtI;];
        Cij=0;
        for J=1:dataN
            if sum(ismember(J,cadSetS))>0
                continue
            end
            d=data(:,J);
            %寻找最短距离
            minD=1e20;
            for D=1:length(SetS)%between j and the closest object in S.
%                 if J==cadSetS(D)
%                     continue
%                 end
                distance=sum((d-data(:,SetS(D))).^2).^.5;
                if distance<minD
                    minD=distance;
                end
            end
            distanceIJ=sum((d-data(:,cddtI)).^2).^.5;
            Cij=Cij+max([minD-distanceIJ,0]);
        end
        maxG(cluster)=Cij;
    end
    maxGInd=find(maxG==max(maxG));
    SetS=[SetS;maxGInd(1)];
end