function [ind_clust,bgi] = Find_Clusters(dot_dist,mean_dist,num_c,preSet_Centers)%% Clustering Through Ranking On Manifolds% Version 0.2%% Copyright by Markus Breitenbach and Gregory Z. Grudic% This code is for your personal and research use only.%% http://www.cs.colorado.edu/~grudic/% http://ucsu.colorado.edu/~breitenm/%% This software is provided "as is," without warranty of any kind, express% or implied.  In no event shall the authors be held liable% for any direct, indirect, incidental, special or consequential damages% arising out of the use of or inability to use this software.%bgi=[];if nargin<4    preSet_Centers=[];end;if length(preSet_Centers) > 2	pp=randperm(length(preSet_Centers)-1);	pq=preSet_Centers(2:length(preSet_Centers));	pq=pq(pp);	preSet_Centers=[preSet_Centers(1), pq];end;if length(preSet_Centers)==0    m_cls_pt = find(mean_dist == max(mean_dist));else    [m_cls_pt, preSet_Centers] = pop(preSet_Centers);end;if length(m_cls_pt)<1    ind_clust=[];    return;end;num_clusters = 1;val_max(num_clusters,1) = mean_dist(m_cls_pt(1));ind_clust(num_clusters,1) = m_cls_pt(1);wt = 1-dot_dist(m_cls_pt(1),:);next_mean = wt.*mean_dist;%figure;plot(next_mean);for num_clusters = 2:num_c    if length(preSet_Centers)==0        m_cls_pt = find(next_mean == max(next_mean));    else        [m_cls_pt, preSet_Centers] = pop(preSet_Centers);    end;    val_max(num_clusters,1) = mean_dist(m_cls_pt(1));    ind_clust(num_clusters,1) = m_cls_pt(1);    wt = (1-dot_dist(m_cls_pt(1),:)).*wt;    next_mean = wt.*next_mean;    %figure;plot(next_mean);    t5 = 5;end%ind_clust = unique(ind_clust); % remove duplicatesreturn;function [y,X]=pop(X)if length(X)>0    y=X(1);    X=X(2:length(X));else    y=[];end;return;