int main( int argc, char* argv[] ) {
char c;
while( (c = getopt( argc, argv, "+h" )) >= 0 ) {
if( c == 'h' ) {
usage( argv[0] );
return 0;
}
}
if( argc != optind ) {
usage( argv[0] );
return 1;
}
WeightedNetwork network = WeightedNetwork::readNetwork( cin );
for( vertex_t v1 = 0; v1 < network.vertexCount(); ++v1 ) {
for( vertex_t v2 = 0; v2 < network.vertexCount(); ++v2 ) {
if( v1 != v2 ) {
cout << network.translateIntToExt( v1 ) << " " << network.translateIntToExt( v2 ) << "\n";
}
}
}
return 0;
}
int main( int argc, char* argv[] ) {
char c;
while( (c = getopt( argc, argv, "+h" )) >= 0 ) {
if( c == 'h' ) {
usage( argv[0] );
return 0;
}
}
if( argc != optind ) {
usage( argv[0] );
return 1;
}
WeightedNetwork network = WeightedNetwork::readNetwork( cin );
vector<WeightedNetwork> sccs = network.sccs();
unsigned int maxsize = 0;
const WeightedNetwork* largestSCC = NULL;
for( vector<WeightedNetwork>::const_iterator sccIterator = sccs.begin(); sccIterator != sccs.end(); sccIterator++ ) {
if( sccIterator->vertexCount() >= maxsize ) {
maxsize = sccIterator->vertexCount();
largestSCC = &(*sccIterator);
}
}
largestSCC->print( cout );
return 0;
}
int main( int argc, char* argv[] ) {
char c;
while( (c = getopt( argc, argv, "+h" )) >= 0 ) {
if( c == 'h' ) {
usage( argv[0] );
return 0;
}
}
if( argc != optind ) {
usage( argv[0] );
return 1;
}
WeightedNetwork network = WeightedNetwork::readNetwork( cin );
network.printAdjacencyList( cout );
return 0;
}
int main( int argc, char* argv[] ) {
char c;
while( (c = getopt( argc, argv, "+h" )) >= 0 ) {
if( c == 'h' ) {
usage( argv[0] );
return 0;
}
}
if( argc != optind ) {
usage( argv[0] );
return 1;
}
WeightedNetwork network = WeightedNetwork::readNetwork( cin );
cout << network.freeChoiceMutualityIndex() << "\n";
return 0;
}
WeightedTriangleLinkPredictor::WeightedTriangleLinkPredictor( const WeightedNetwork& network, int selection = -1 ) : LinkPredictor( network ), selection( selection ) {
if( this->selection > -1 ) {
return;
}
weight_t allCounts[graphlets] = {0};
for( vertex_t vertex = 0; vertex < network.vertexCount(); ++vertex ) {
const neighbor_set_t& outNeighbors = network.outNeighbors( vertex );
for( neighbor_set_t::const_iterator neighborIterator = outNeighbors.begin(); neighborIterator != outNeighbors.end(); ++neighborIterator ) {
const vertex_t neighbor = neighborIterator->first;
weight_t vCounts[graphlets] = {0};
this->edgeProfile( vertex, neighbor, vCounts );
for( size_t i = 0; i < graphlets; ++i ) {
allCounts[i] += vCounts[i];
}
}
}
for( size_t i = 0; i < graphlets; ++i ) {
this->counts[i] = (weight_t)allCounts[i] / network.edgeCount();
}
}
int main( int argc, char* argv[] ) {
char c;
while( (c = getopt( argc, argv, "+h" )) >= 0 ) {
if( c == 'h' ) {
usage( argv[0] );
return 0;
}
}
if( argc != optind ) {
usage( argv[0] );
return 1;
}
WeightedNetwork network = WeightedNetwork::readNetwork( cin );
for( vertex_t vertex = 0; vertex < network.vertexCount(); vertex++ ) {
cout << network.eccentricity( vertex ) << "\n";
}
return 0;
}
int main( int argc, char* argv[] ) {
char c;
while( (c = getopt( argc, argv, "+h" )) >= 0 ) {
if( c == 'h' ) {
usage( argv[0] );
return 0;
}
}
if( argc != optind + 1 ) {
usage( argv[0] );
return 1;
}
char* spec = argv[optind];
unsigned int currentDistance = 0;
unsigned int distance = strlen( spec );
vector<bool> direction( distance );
while( currentDistance < distance ) {
if( tolower( spec[currentDistance] ) == 'o' ) {
direction[currentDistance++] = true;
} else if( tolower( spec[currentDistance] ) == 'i' ) {
direction[currentDistance++] = false;
} else {
usage( argv[0] );
return 1;
}
}
WeightedNetwork network = WeightedNetwork::readNetwork( cin );
for( vertex_t v1 = 0; v1 < network.vertexCount(); ++v1 ) {
vector<bool> found = vector<bool>( network.vertexCount() );
vector<vertex_t> search;
found.at( v1 ) = true;
search.push_back( v1 );
for( currentDistance = 0; currentDistance < distance; ++currentDistance ) {
vector<vertex_t> newSearch;
for( vector<vertex_t>::const_iterator vertexIterator = search.begin(); vertexIterator != search.end(); ++vertexIterator ) {
const vertex_t searchVertex = *vertexIterator;
const neighbor_set_t& neighbors = direction[currentDistance] ? network.outNeighbors( searchVertex ) : network.inNeighbors( searchVertex );
for( neighbor_set_t::const_iterator neighborIterator = neighbors.begin(); neighborIterator != neighbors.end(); neighborIterator++ ) {
const vertex_t neighbor = neighborIterator->first;
if( !found.at( neighbor ) ) {
found.at( neighbor ) = true;
if( currentDistance == distance - 1 ) {
cout << network.translateIntToExt( v1 ) << " " << network.translateIntToExt( neighbor ) << "\n";
} else {
newSearch.push_back( neighbor );
}
}
}
}
search.swap( newSearch );
}
}
return 0;
}
VCP4DirectedLinkPredictor::VCP4DirectedLinkPredictor( const WeightedNetwork& network, const WeightedNetwork& completeNetwork ) : LinkPredictor(network,completeNetwork), connectedPairs( 0 ), amutualPairs( 0 ), mutualPairs( 0 ), unconnectedPairs( 0 ) {
// compute the total number of somehow-connected pairs in the graph
for( vertex_t i = 0; i < network.vertexCount(); ++i ) {
neighbor_set_t::const_iterator outIt = network.outNeighbors( i ).begin();
neighbor_set_t::const_iterator outEnd = network.outNeighbors( i ).end();
neighbor_set_t::const_iterator inIt = network.inNeighbors( i ).begin();
neighbor_set_t::const_iterator inEnd = network.inNeighbors( i ).end();
while( outIt != outEnd && outIt->first <= i ) {
++outIt;
}
while( inIt != inEnd && inIt->first <= i ) {
++inIt;
}
while( outIt != outEnd && inIt != inEnd ) {
++connectedPairs;
if( outIt->first < inIt->first ) {
++amutualPairs;
++outIt;
} else if( outIt->first > inIt->first ) {
++amutualPairs;
++inIt;
} else {
++mutualPairs;
++outIt;
++inIt;
}
}
while( outIt != outEnd ) {
++amutualPairs;
++connectedPairs;
++outIt;
}
while( inIt != inEnd ) {
++amutualPairs;
++connectedPairs;
++inIt;
}
}
unsigned long potentialConnections = (unsigned long)network.vertexCount() * (unsigned long)(network.vertexCount() - 1) / 2;
unconnectedPairs = potentialConnections - connectedPairs;
}
int main( int argc, char* argv[] ) {
char c;
while( (c = getopt( argc, argv, "+h" )) >= 0 ) {
if( c == 'h' ) {
usage( argv[0] );
return 0;
}
}
if( argc != optind + 1 ) {
usage( argv[0] );
return 1;
}
unsigned int distance = atoi( argv[optind++] );
WeightedNetwork network = WeightedNetwork::readNetwork( cin );
for( vertex_t vertex = 0; vertex < network.vertexCount(); vertex++ ) {
WeightedNetwork snowball = network.snowballSample( vertex, distance ).removeIsolates();
cout << snowball.vertexCount() << " " << snowball.edgeCount() << "\n";
}
return 0;
}
int main( int argc, char* argv[] ) {
char c;
bool specifiedPredictions = false;
bool outEdges = true;
unsigned int degree = 2;
ifstream file;
while( (c = getopt( argc, argv, "+hcd:f:n:" )) >= 0 ) {
if( c == 'd' ) {
if( strcmp( optarg, "I" ) == 0 ) {
outEdges = false;
}
} else if( c == 'f' ) {
file.open( optarg, ios::in );
} else if( c == 'n' ) {
degree = atoi( optarg );
} else if( c == 'c' ) {
specifiedPredictions = true;
} else if( c == 'h' ) {
usage( argv[0] );
exit(0);
}
}
if( argc < optind + 1 ) {
usage( argv[0] );
return 1;
}
const char* predictorName = argv[optind++];
WeightedNetwork network = WeightedNetwork::readNetwork( file );
if( !outEdges ) {
network = network.reverseEdges();
}
LinkPredictor* predictor = NULL;
if( strcmp( predictorName, "AdamicAdar" ) == 0 ) {
predictor = new AdamicAdarLinkPredictor( network );
} else if( strcmp( predictorName, "CommonNeighbor" ) == 0 ) {
predictor = new CommonNeighborLinkPredictor( network );
} else if( strcmp( predictorName, "ClusteringCoefficient" ) == 0 ) {
predictor = new ClusteringCoefficientLinkPredictor( network );
} else if( strcmp( predictorName, "Distance" ) == 0 ) {
unsigned int l = argc > optind ? atoi( argv[optind++] ) : 5;
predictor = new DistanceLinkPredictor( network, l );
} else if( strcmp( predictorName, "IDegree" ) == 0 ) {
predictor = new IDegreeLinkPredictor( network );
} else if( strcmp( predictorName, "IPageRank" ) == 0 ) {
double d = argc > optind ? atof( argv[optind++] ) : 0.85;
predictor = new IPageRankLinkPredictor( network, d );
} else if( strcmp( predictorName, "IVolume" ) == 0 ) {
predictor = new IVolumeLinkPredictor( network );
} else if( strcmp( predictorName, "JaccardCoefficient" ) == 0 ) {
predictor = new JaccardCoefficientLinkPredictor( network );
} else if( strcmp( predictorName, "JDegree" ) == 0 ) {
predictor = new JDegreeLinkPredictor( network );
} else if( strcmp( predictorName, "JPageRank" ) == 0 ) {
double d = argc > optind ? atof( argv[optind++] ) : 0.85;
predictor = new JPageRankLinkPredictor( network, d );
} else if( strcmp( predictorName, "JVolume" ) == 0 ) {
predictor = new JVolumeLinkPredictor( network );
} else if( strcmp( predictorName, "Katz" ) == 0 ) {
unsigned int l = argc > optind ? atoi( argv[optind++] ) : 5;
double beta = argc > optind ? atof( argv[optind++] ) : 0.005;
predictor = new KatzLinkPredictor( network, l, beta );
} else if( strcmp( predictorName, "Mutuality" ) == 0 ) {
predictor = new MutualityLinkPredictor( network );
} else if( strcmp( predictorName, "One" ) == 0 ) {
predictor = new OneLinkPredictor( network );
} else if( strcmp( predictorName, "PreferentialAttachment" ) == 0 ) {
predictor = new PreferentialAttachmentLinkPredictor( network );
} else if( strcmp( predictorName, "PropFlow" ) == 0 ) {
unsigned int l = argc > optind ? atoi( argv[optind++] ) : 5;
predictor = new PropFlowLinkPredictor( network, l );
} else if( strcmp( predictorName, "RootedPageRank" ) == 0 ) {
double alpha = argc > optind ? atof( argv[optind++] ) : 0.15;
predictor = new RootedPageRankLinkPredictor( network, alpha );
} else if( strcmp( predictorName, "ShortestPathCount" ) == 0 ) {
unsigned int l = argc > optind ? atoi( argv[optind++] ) : 5;
predictor = new ShortestPathCountLinkPredictor( network, l );
} else if( strcmp( predictorName, "SimRank" ) == 0 ) {
double C = argc > optind ? atof( argv[optind++ ] ) : 0.8;
predictor = new SimRankLinkPredictor( network, C );
} else if( strcmp( predictorName, "UnweightedPropFlow" ) == 0 ) {
unsigned int l = argc > optind ? atoi( argv[optind++] ) : 5;
predictor = new UnweightedPropFlowLinkPredictor( network, l );
} else if( strcmp( predictorName, "VCP3Directed" ) == 0 ) {
predictor = new VCP3DirectedLinkPredictor( network );
} else if( strcmp( predictorName, "VCP3Undirected" ) == 0 ) {
predictor = new VCP3UndirectedLinkPredictor( network );
} else if( strcmp( predictorName, "VCP4Directed" ) == 0 ) {
predictor = new VCP4DirectedLinkPredictor( network );
} else if( strcmp( predictorName, "VCP4Undirected" ) == 0 ) {
predictor = new VCP4UndirectedLinkPredictor( network );
} else if( strcmp( predictorName, "WeightedRootedPageRank" ) == 0 ) {
double alpha = argc > optind ? atof( argv[optind++] ) : 5;
predictor = new WeightedRootedPageRankLinkPredictor( network, alpha );
} else {
cerr << "invalid link predictor: " << predictorName << "\n";
return 1;
}
cout.precision( 15 );
if( specifiedPredictions ) {
vertex_t vertex;
vertex_t neighbor;
while( cin >> vertex >> neighbor ) {
vertex_t internalVertex = network.translateExtToInt( vertex );
vertex_t internalNeighbor = network.translateExtToInt( neighbor );
if( internalVertex != INVALID_VERTEX && internalNeighbor != INVALID_VERTEX ) {
cout << vertex << " " << neighbor << " " << predictor->generateScore( internalVertex, internalNeighbor );
}
}
} else {
if( !outEdges ) {
