void pAOSOAutostepGradTree::get_is_leaf( VecInt& is_leaf ) { is_leaf.clear(); is_leaf.resize(nodes_.size()); std::list<pAOSOAutostepGradNode>::iterator it = nodes_.begin(); for (int i = 0; it!=nodes_.end(); ++it, ++i) { if (it->left_==0 && it->right_==0) is_leaf[i] = 1; else is_leaf[i] = 0; } // for i }
//--- MAIN PROGRAM //------------------------------------------------------------------------------------- int main(int argc, char * argv[]) { int seed; int a_type; int w_type; string title; string if_weighted; string if_help; const char *file_network; const char *file_names; if ( argc != 5 ) { printHelpMessage( argv[0] ); } if_help = argv[1]; if( if_help.compare("-h") == 0 || if_help.compare("-help") == 0 ) { printHelpMessage( argv[0] ); } seed = atoi(argv[1]); cout << "> seed is " << seed << endl; //--- Initialize random seed: _rand.setSeed(seed); a_type = atoi(argv[2]); if( a_type < 1 || a_type > 3 ) { cout << "argument 2: the type of algorithm to run needs to be either (1,2,3): " << endl; cout << " : 1 = Geodesic edge Betweenness" << endl; cout << " : 2 = Random edge Betweenness" << endl; cout << " : 3 = Spectral Betweenness" << endl; exit(1); } switch(a_type) { case 1: cout << "> Using Geodesic edge Betweenness." << endl; title = "Geodesic edge Betweenness."; break; case 2: cout << "> Using Random edge Betweenness." << endl; title = "RandomWalk edge Betweenness."; break; case 3: cout << "> Using Spectral Betweenness." << endl; title = "Spectral Betweenness."; break; default: break; } if_weighted = argv[3]; if( if_weighted.compare("w") == 0 ) { w_type = 3; cout << "> Using a weighted network " << endl; } else { if( if_weighted.compare("nw") == 0 ) { w_type = 2; cout << "> Using a non-weighted network " << endl; } else { cout << "argument 3: specify if network file is weighted or not: " << endl; cout << " : w = Using a weighted network file " << endl; cout << " : nw = Using a non-weighted network file " << endl; exit(1); } } file_network = argv[4]; //--- Default values for parameters which may be modified from the commandline ihelper = Helper(); reader.readFile(file_network, w_type); Gn = reader.getNodeSet(); Gelist = reader.getEdgeSet(); vector<int> key_listi; vector<int> key_listj; vector<int> key_listk; cout << "> The Global node list..." << endl; for(int i=1; i<Gn.size(); i++) { key_listi.push_back(Gn[i].ID); key_listj.push_back(Gn[i].ID); key_listk.push_back(-1); Gn[i].print(); Gn[i].printEdges(); } //--- To use getSubSample, comment following two lines, and //--- uncomment getSubSample(key_listj). n = Gn; elist = Gelist; //getSubSample(key_listj); //cout << "The sub-node list ... " << endl; //for(int i=1; i<n.size(); i++){ //n[i].print(); //n[i].printEdges(); //} cout << "> The Global edge list..." << endl; for(int i=0; i<elist.size(); i++) { elist[i].print(); } forcytoscape = new fstream("OUT/communities_newman.txt",ios_base::out); (*forcytoscape) << "communities" << endl; removededges = new fstream("OUT/removededges.txt",ios_base::out); (*removededges) << "Removed Edges" << endl; (*removededges) << "so \t IDso \t si \t IDsi \t we \t Globalweight \t key" << endl; totallist = ihelper.cloneEdgeList(elist); com_max = 0; specQ = 0.0; double Q = 0.0; double Q_SD = 0.0; double Q_old = 0.0; double Q_SD_old = 0.0; int loop = elist.size(); int E = loop; double Q_max = 0.0; double Q_limit = 1.0; bool stopping = false; int N = n.size()-1; R.resize(N,N); Ri.resize(N,N); A.resize(N,N); Ai.resize(N,N); Bi.resize(N,N); C.resize(N); S.resize(N,1); V.resize(N,1); T.resize(N,N); Ti.resize(N,N); Rc.resize((N-1),(N-1)); Vi.resize(C.size(),1); B.resize(N,N); Bm.resize(N,N); Bgi.resize(N,N); keys_p.resize(N); keys_n.resize(N); u.resize(N,N); //eigenvectors betai.resize(N);//eigenvalues SI.resize(N,2); si.resize(N); visited.resize(N); setupMatrices(); cout << "> Running " << title.c_str() << endl; cstart = clock(); if( a_type == 3 ) { //--- Calculate betweenness using the Spectral algorithm calculateSpectralModularity(); } else { while( loop !=0 && !stopping ) { int old_max_com = com_max; //--- Calculate betweenness using Geodesic or RandomWalk algorithms if( a_type == 1 ) calculateEdgeBetweennessGeodesic(); else calculateEdgeBetweennessRandom(); //--- Calculate the Modularity Q_old = Q; Q_SD_old = Q_SD; Q = 0.0; Q_SD = 0.0; Modularity(Q, Q_SD); //--- Store networks state if Modularity has increased during this iteraction if(com_max > old_max_com) { vec_mod.push_back(Q); vec_mod_err.push_back(Q_SD); vec_com_max.push_back(com_max); vec_nodes.push_back(storeNodes()); } //--- Record the maximum Modularity value if( Q > Q_max ) { Q_max = Q; } else { if( Q_max > 0.0 && (Q_max - Q)/Q_max > Q_limit ) stopping = true; } //--- Find edge with maximum edge betweenness score and remove edge _max; _max = totallist[1].Clone(); for(int i=1; i<totallist.size(); i++) { if( totallist[i].removed == false ) { if(totallist[i].we >= _max.we) { if(totallist[i].we > _max.we) _max = totallist[i]; else { int rdm = rand()%2; if(rdm == 1) _max = totallist[i]; } } } totallist[i].we = 0; } //--- Record the removed edges. _max.print( removededges ); n[elist[_max.key-1].so].removeEdge(_max.key); n[elist[_max.key-1].si].removeEdge(_max.key); n[elist[_max.key-1].so].setDegree( (n[elist[_max.key-1].so].getDegree() - 1) ); n[elist[_max.key-1].si].setDegree( (n[elist[_max.key-1].si].getDegree() - 1) ); totallist[_max.key].removed = true; elist[_max.key-1].removed = true; --loop; //--- Calculate the remaining processor time DrawProgressBar( 20, ((double)E - (double)loop)/(double)E ); } } //--- Recored the CPU-time taken cend = clock(); double cpu_time_used = ((double) (cend - cstart)) / CLOCKS_PER_SEC; cout << "" << endl; cout << "> cputime: " << cpu_time_used << " seconds " << endl; cout << "> Network (nodes): " << N << " (edges): " << E << endl; if( a_type != 3 ) { //--- Print all stored Modularity values modularityscore = new fstream("OUT/modularityscore.txt",ios_base::out); (*modularityscore) << title.c_str() << endl; for(int i=0; i<vec_mod.size(); i++) { (*modularityscore) << vec_mod[i] << " " << vec_mod_err[i] << " " << vec_com_max[i] << endl; } modularityscore->close(); int ind = findMax(vec_mod); int com = 1; int _size = 0; int c_max = com_max; //--- Print node communities for maximum Modularity value, for Geodesic or RandomWalk runs communityout = new fstream("OUT/communityout.txt",ios_base::out); (*communityout) << "Max Q: " << vec_mod[ind] << " +- " << vec_mod_err[ind] << endl; (*communityout) << "cputime: " << cpu_time_used << " seconds " << endl; (*communityout) << "Network (nodes): " << N << " (edges): " << E << endl; while(com<(c_max+1)) { _size = 0; for(int i=0; i<vec_nodes[ind].size(); i++) { if(vec_nodes[ind][i].c == com ) { (*communityout) << vec_nodes[ind][i].ID << "\t" << vec_nodes[ind][i].c << endl; //vec_nodes[ind][i].print( communityout ); _size++; } } if(_size != 0) (*communityout) << "community: " << com << " size: " << _size << endl; com++; } for(int i=0; i<vec_nodes[ind].size(); i++) { for(int j=0; j<key_listi.size(); j++) { if(vec_nodes[ind][i].ID == key_listi[j]) { key_listk[j] = vec_nodes[ind][i].c; break; } } } //--- Print node communities for maximum Modularity for the consensus matrix consensusout = new fstream("OUT/consensusout.txt",ios_base::out); (*consensusout) << "key list" << endl; for(int i=0; i<key_listi.size(); i++) { if(key_listk[i] == -1 && key_listj[i] != -1) key_listj[i] = -1; (*consensusout) << key_listi[i] << " " << key_listj[i] << " " << key_listk[i] << endl; //(*consensusout) << key_listi[i] << " = " << key_listk[i] << endl; (*forcytoscape) << key_listi[i] << " = " << key_listk[i] << endl; cout << key_listi[i] << " " << key_listj[i] << " " << key_listk[i] << endl; } } else { int com = 1; int _size = 0; int c_max = maxCommunity(); //--- Store node communities for maximum Modularity for the Spectral Modularity run communityout = new fstream("OUT/communityout.txt",ios_base::out); (*communityout) << "communityout" << endl; (*communityout) << "Max Q: " << specQ << endl; (*communityout) << "cputime: " << cpu_time_used << " seconds " << endl; (*communityout) << "Network (nodes): " << N << " (edges): " << E << endl; while(com<(c_max+1)) { _size = 0; for(int i=0; i<n.size(); i++) { if(n[i].c == com ) { n[i].print( communityout ); _size++; } } if(_size != 0) (*communityout) << "community: " << com << " size: " << _size << endl; com++; } for(int i=1; i<n.size(); i++) { for(int j=0; j<key_listi.size(); j++) { if(n[i].ID == key_listi[j]) { key_listk[j] = n[i].c; break; } } } //--- Print node communities for maximum Modularity the consensus matrix consensusout = new fstream("OUT/consensusout.txt",ios_base::out); (*consensusout) << "key list" << endl; for(int i=0; i<key_listi.size(); i++) { if(key_listk[i] == -1 && key_listj[i] != -1) key_listj[i] = -1; (*consensusout) << key_listi[i] << " " << key_listj[i] << " " << key_listk[i] << endl; //(*consensusout) << key_listi[i] << " = " << key_listk[i] << endl; (*forcytoscape) << key_listi[i] << " = " << key_listk[i] << endl; cout << key_listi[i] << " " << key_listj[i] << " " << key_listk[i] << endl; } } //--- Remove data structures communityout->close(); forcytoscape->close(); vec_mod.clear(); vec_mod_err.clear(); vec_nodes.clear(); exit(1); }