int main(int argc, char* argv[]) {
//Here is the input file name:
ifstream input(argv[1]);
Network my_net(input);
ComponentPart cp;
auto_ptr<NetworkPartition> components(cp.partition(my_net));
int component = 0;
auto_ptr<Iterator<Network*> > comp_it(components->getComponents());
while(comp_it->moveNext()) {
stringstream name;
name << argv[1] << "." << component;
component++;
ofstream output(name.str().c_str());
Network* this_comp = comp_it->current();
this_comp->printTo(output);
}
return 1;
}
int main(int argc, char** argv) {
Network my_net(cin);
cout << "graph G {" << endl;
Network::EdgeSet printed_edges;
//Look on components:
ComponentPart cp;
NewmanCom comfinder;
auto_ptr<NetworkPartition> components_np(cp.partition(my_net));
const vector<Network*>& components = components_np->asVector();
vector<Network*>::const_iterator comp_it;
int community = 0;
for(comp_it = components.begin(); comp_it != components.end(); comp_it++) {
stringstream com;
com << community++;
Network* this_net = *comp_it;
printCommunities(comfinder, com.str(), *this_net, cout, printed_edges, 1);
}
printEdges(my_net, printed_edges, "[len=16, color=green]");
cout << "}" << endl;
return 1;
}
int main(int argc, char* argv[]) {
if( argc < 4 ) {
//
cout << "Usage: " << argv[0] << " graph blacklist whitelist" << endl;
return 0;
}
ifstream input(argv[1]);
ofstream spam(argv[2]);
ofstream ham(argv[3]);
Network graph(input);
double min_cc = 0.1;
double kmfrac = 0.6;
int min_size = 10;
double whole_graph_c = graph.getTransitivity();
//The subgraphs of spam and nonspam
set<Network*> spamg, hamg;
ComponentPart cp;
auto_ptr<NetworkPartition> netpart(cp.partition(graph));
vector<Network*> components(netpart->asVector());
vector<Network*>::iterator comp_it;
Edge* cut_edge = 0;
while( components.size() > 0 ) {
//Choose the biggest graph
comp_it = components.begin();
Network* this_net = *comp_it;
Network::NodePSet::const_iterator n_it;
int kmax = 0;
auto_ptr<NodeIterator> ni( this_net->getNodeIterator() );
while( ni->moveNext() ) {
Node* this_node = ni->current();
if( kmax < this_net->getDegree( this_node ) ) {
kmax = this_net->getDegree( this_node );
}
}
int size = this_net->getNodeSize();
if( size > min_size ) {
if( this_net->getClusterCoefficient() > min_cc ) {
//Ham:
hamg.insert( this_net );
}
//Maybe spam:
else if( (kmax + 1) < kmfrac * size ) {
if( this_net->getClusterCoefficient() == 0.0 ) {
//Spam:
spamg.insert( this_net );
}
else {
//Ambiguous
map<Edge*, double> bet;
Network* this_comp = *comp_it;
cut_edge = this_comp->getEdgeBetweenness(bet);
this_comp->remove( cut_edge->first );
this_comp->remove( cut_edge->second );
auto_ptr<NetworkPartition> split_part(cp.partition(*this_comp));
const vector<Network*>& split = split_part->asVector();
components.insert(components.end(), split.begin(), split.end());
}
}
}
//cout << "graphs: " << components.size() << endl;
components.erase( comp_it );
}
//Print out the nodes in each spamg and hamg
Network::NodePSet::const_iterator nit;
set<Network*>::iterator netsetit;
for(netsetit = spamg.begin(); netsetit != spamg.end(); netsetit++) {
auto_ptr<NodeIterator> ni2( (*netsetit)->getNodeIterator() );
while( ni2->moveNext() ) {
Node* this_node = ni2->current();
spam << this_node->toString() << endl;
}
}
for(netsetit = hamg.begin(); netsetit != hamg.end(); netsetit++) {
auto_ptr<NodeIterator> ni2( (*netsetit)->getNodeIterator() );
while( ni2->moveNext() ) {
Node* this_node = ni2->current();
ham << this_node->toString() << endl;
}
}
//Delete the memory:
return 1;
}
int main(int argc, char* argv[]) {
//Here we consider a network for a P2P topology
Ran1Random r1(time(NULL)), r2(-1000), r3(-1000000), r4(-5678);
ContentNetwork* my_cnet = 0;
Node* a_node = 0;
ContentNode* c_node = 0;
vector<Node*> node_vector;
//Here is all the content
vector<ContentNode*> content_vector;
int cont_count = 10;
//Look for each content 10 times:
int runs = 10*cont_count;
content_vector.reserve(cont_count);
for(int i = 0; i < cont_count; i++) {
content_vector.push_back(new ContentNode);
}
Network* my_net = 0;
//my_net = new PrefDelCompNetwork(RandomNetwork(10,1.0,r1),r1,0.75,1,0.6666);
//my_net = new DoublePrefAtNetwork( RandomNetwork(10,0.6,r1), r1, 1 );
//my_net = new PrefAtNetwork( RandomNetwork(2,1.0,r1), r1, 1 );
//ifstream input("internal.dat");
//my_net = new Network(input);
/*while(my_net->getNodes().size() < 40000) {
dynamic_cast<Incrementable*>(my_net)->incrementTime();
}*/
//The exponent -2.236 is what we fit to DPA network of the same size
PowerLawDRV pl(r1, -2.3,2,1000);
DegreeLawNetFac nf(40000, pl, r1, true);
my_net = nf.create();
//my_net = new DegreeLawRandomNetwork(nodes, *pl, r1);
//my_net = new GnutellaNetwork(argv[1],"limecrawler");
//my_net = new GnutellaNetwork(argv[1],"ripeanu");
Network *net = 0;
int choice = 2;
if(choice == 1){
ComponentPart cp;
auto_ptr<NetworkPartition> netpart(cp.partition(*my_net));
const vector<Network*>& net_set = netpart->asVector();
cout << "The number of components of this network is: " << net_set.size() << endl;
vector<Network*>::const_iterator comp_it;
cout << "The components have the following sizes: ";
for(comp_it = net_set.begin(); comp_it != net_set.end(); comp_it++){
net = *(comp_it);
cout << net->getNodeSize() << " ";
}
net = 0;
}
else{
//The exponent -1.81 is what we want for the email network
int nodes = 10000;
PowerLawDRV pl(r1,-2.1,2,(int)sqrt(nodes));
DegreeLawNetFac my_fact(nodes, pl, r1, true);
net = my_fact.create();
}
cout << endl;
//use the biggest connected component;
IntStats ns;
auto_ptr<NodeIterator> ni( net->getNodeIterator() );
ns.collect(net, &Network::getDegree, ni.get());
cout << "#nodes: " << net->getNodeSize() << endl
<< "#edges: " << net->getEdgeSize() << endl
<< "#<k>: " << ns.getAverage() << endl
<< "#<k^2>: " << ns.getMoment2() << endl;
cout << "#ttl p hit_rate edges_crossed nodes_reached" << endl;
//Put the nodes into a vector so we can randomly select them easier:
node_vector.clear();
ni->reset();
while( ni->moveNext() ) {
node_vector.push_back( ni->current() );
}
Message* query = 0;
Message* implant = 0;
int hits;
double last_hr = 0.0;
double hit_rate = 0.0;
double av_edges = 0.0;
double av_nodes = 0.0;
double p, delta_p = 0.01;
int ttl=15;
//for(ttl = 2; ttl < 12; ttl++)
{
p = 0.01;
//p = 1.0;
while(p < 0.51)
{
delete query;
query = new WalkAndPercMessage(r2,p,ttl,ttl);
//query = new MagnetMessage(r2,p,ttl);
//query = new BroadcastMessage(ttl);
delete implant;
implant = new AnycastMessage(r4,1,ttl);
//implant = new MagnetMessage(r2,0.75, 2 * ttl);
//implant = new WalkAndPercMessage(r4,p,ttl);
//implant = new AnycastMessage(r4,1,0);
delete my_cnet;
my_cnet = new ContentNetwork(*net);
// Insert the content into the network
for(int i = 0; i < cont_count; i++)
{
a_node = node_vector[ r3.getInt( node_vector.size() - 1 ) ];
c_node = content_vector[i];
auto_ptr<Network> implantnet( implant->visit( a_node, *net) );
auto_ptr<NodeIterator> nit( implantnet->getNodeIterator() );
my_cnet->insertContent(c_node, nit.get() );
}
//Do a random search for each node and see how many are successful.
Network::NodePSet res_nodes;
hits = 0;
int hit_nodes = 0, crossed_edges = 0;
for(int i = 0; i < runs; i++) {
a_node = node_vector[ r3.getInt( node_vector.size() - 1 ) ];
c_node = content_vector[ i % cont_count ];
auto_ptr<Network> visited( query->visit(a_node, *net) );
auto_ptr<NodeIterator> nit( visited->getNodeIterator() );
auto_ptr<Network> res_nodes(
my_cnet->queryForContent(c_node, nit.get() ) );
if( res_nodes->getNodeSize() != 0) {
++hits;
}
hit_nodes += visited->getNodeSize();
crossed_edges += visited->getEdgeSize();
}
hit_rate = (double)hits/(double)runs;
av_edges = (double)crossed_edges/(double)runs;
av_nodes = (double)hit_nodes/(double)runs;
cout << ttl << " " << p
<< " " << hit_rate
<< " " << av_edges
<< " " << av_nodes
<< endl;
/* Do an adapative step:
delta_p = 0.00005/abs(hit_rate - last_hr);
if( delta_p < 0.001 ) {
delta_p = 0.001;
}
if( delta_p > 0.1 ) {
delta_p = 0.1;
}*/
p += delta_p;
}
}
//Delete all the content
my_cnet->deleteContent();
delete my_cnet;
delete my_net;
delete net;
return 1;
}
