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NetworKit Namespace Reference

Namespaces

 GraphClusteringTools
 
 GraphTools
 
 
 

Classes

struct  Triplet
 Represents a matrix entry s.t. More...
 
class  AlgebraicBellmanFord
 Implementation of the Bellman-Ford algorithm using the GraphBLAS interface. More...
 
class  AlgebraicBFS
 Implementation of Breadth-First-Search using the GraphBLAS interface. More...
 
class  AlgebraicMatchingCoarsening
 Implements an algebraic version of the MatchingCoarsening algorithm by computing a projection matrix from fine to coarse. More...
 
class  AlgebraicPageRank
 Implementation of PageRank using the GraphBLAS interface. More...
 
class  AlgebraicSpanningEdgeCentrality
 Implementation of Spanning edge centrality with algebraic notation. More...
 
class  AlgebraicTriangleCounting
 Implements a triangle counting algorithm for nodes based on algebraic methods. More...
 
class  CSRMatrix
 The CSRMatrix class represents a sparse matrix stored in CSR-Format (i.e. More...
 
class  DenseMatrix
 Represents a dense matrix. More...
 
class  DynamicMatrix
 The DynamicMatrix class represents a matrix that is optimized for sparse matrices and internally uses a graph data structure. More...
 
class  SparseAccumulator
 The SparseAccumulator class represents the sparse accumulator datastructure as described in Kepner, Jeremy, and John Gilbert, eds. More...
 
class  Vector
 The Vector class represents a basic vector with double coefficients. More...
 
class  Algorithm
 
class  DynAlgorithm
 
class  ApproxBetweenness
 Approximation of betweenness centrality according to algorithm described in Matteo Riondato and Evgenios M. More...
 
struct  ListEntry_struct
 
class  ApproxCloseness
 Approximation of closeness centrality according to algorithm described in Cohen et al., Computing Classic Closeness Centrality, at Scale. More...
 
class  Betweenness
 
class  Centrality
 Abstract base class for centrality measures. More...
 
class  Closeness
 
class  CoreDecomposition
 Computes k-core decomposition of a graph. More...
 
class  DegreeCentrality
 Node centrality index which ranks nodes by their degree. More...
 
class  DynApproxBetweenness
 Interface for dynamic approximated betweenness centrality algorithm. More...
 
class  CompareDist
 
class  DynBetweenness
 Dynamic APSP. More...
 
class  EigenvectorCentrality
 Computes the leading eigenvector of the graph's adjacency matrix (normalized in 2-norm). More...
 
class  EstimateBetweenness
 Estimation of betweenness centrality according to algorithm described in Sanders, Geisberger, Schultes: Better Approximation of Betweenness Centrality. More...
 
class  KatzCentrality
 Computes the Katz centrality of the graph. More...
 
class  KPathCentrality
 
class  LocalClusteringCoefficient
 
class  LocalPartitionCoverage
 The local partition coverage is the amount of neighbors of a node u that are in the same partition as u. More...
 
class  PageRank
 Compute PageRank as node centrality measure. More...
 
class  PermanenceCentrality
 
class  Sfigality
 A. More...
 
class  SpanningEdgeCentrality
 SpanningEdgeCentrality edge centrality. More...
 
class  TopCloseness
 
class  MaximalCliques
 Algorithm for listing all maximal cliques. More...
 
class  ClusteringProjector
 
class  GraphCoarsening
 Abstract base class for graph coarsening/contraction algorithms. More...
 
class  MatchingCoarsening
 Coarsens graph according to a matching. More...
 
class  ParallelPartitionCoarsening
 
class  AdjustedRandMeasure
 The adjusted rand dissimilarity measure as proposed by Huber and Arabie in "Comparing partitions" (http://link.springer.com/article/10.1007/BF01908075) More...
 
class  ClusteringGenerator
 Provides several methods for generating special clusterings. More...
 
class  CommunityDetectionAlgorithm
 Abstract base class for community detection/graph clustering algorithms. More...
 
class  Conductance
 Compute conductance of a 2-partition, i.e. More...
 
class  Coverage
 Coverage is the fraction of intra-cluster edges. More...
 
class  CoverHubDominance
 A quality measure that measures the dominance of hubs in clusters. More...
 
class  CutClustering
 Cut clustering algorithm as defined in Flake, Gary William; Tarjan, Robert E. More...
 
class  DissimilarityMeasure
 Base class for all clustering dissimilarity measures. More...
 
class  DynamicNMIDistance
 
class  EdgeCut
 
class  GraphStructuralRandMeasure
 The graph-structural Rand measure assigns a similarity value in [0,1] to two partitions of a graph, by considering connected pairs of nodes. More...
 
class  HubDominance
 A quality measure that measures the dominance of hubs in clusters. More...
 
class  IntrapartitionDensity
 The intra-cluster density of a partition is defined as the number of existing edges divided by the number of possible edges. More...
 
class  IsolatedInterpartitionConductance
 Isolated inter-partition conductance is a measure for how well a partition (communtiy/cluster) is separated from the rest of the graph. More...
 
class  IsolatedInterpartitionExpansion
 Isolated inter-partition expansion is a measure for how well a partition (communtiy/cluster) is separated from the rest of the graph. More...
 
class  JaccardMeasure
 
class  LocalCommunityEvaluation
 Virtual base class of all evaluation methods for a single clustering which is based on the evaluation of single clusters. More...
 
class  LocalCoverEvaluation
 Virtual base class of all evaluation methods for a single Cover which is based on the evaluation of single clusters. More...
 
class  LocalPartitionEvaluation
 Virtual base class of all evaluation methods for a single Partition which is based on the evaluation of single clusters. More...
 
class  LPDegreeOrdered
 Label propagation-based community detection algorithm which processes nodes in increasing order of node degree. More...
 
class  Modularity
 Modularity is a quality index for community detection. More...
 
class  NMIDistance
 NMIDistance quantifies the dissimilarity between two clusterings using Normalized Mutual Information. More...
 
class  NodeStructuralRandMeasure
 The node-structural Rand measure assigns a similarity value in [0,1] to two partitions of a graph, by considering all pairs of nodes. More...
 
class  ParallelAgglomerativeClusterer
 A parallel agglomerative community detection algorithm, maximizing modularity. More...
 
class  PartitionFragmentation
 This measure evaluates how fragmented a partition is. More...
 
class  PartitionHubDominance
 A quality measure that measures the dominance of hubs in clusters. More...
 
class  PartitionIntersection
 Class for calculating the intersection of two partitions, i.e. More...
 
class  PLM
 Parallel Louvain Method - a multi-level modularity maximizer. More...
 
class  PLP
 As described in Ovelgoenne et al: An Ensemble Learning Strategy for Graph Clustering Raghavan et al. More...
 
class  QualityMeasure
 Abstract base class for all clustering quality measures. More...
 
class  SampledGraphStructuralRandMeasure
 The graph-structural Rand measure assigns a similarity value in [0,1] to two partitions of a graph, by considering connected pairs of nodes. More...
 
class  SampledNodeStructuralRandMeasure
 The node-structural Rand measure assigns a similarity value in [0,1] to two partitions of a graph, by considering pairs of nodes. More...
 
class  StablePartitionNodes
 Evaluates how stable a given partition is. More...
 
class  ConnectedComponents
 Determines the connected components of an undirected graph. More...
 
class  DynConnectedComponents
 Determines and updates the connected components of an undirected graph. More...
 
class  ParallelConnectedComponents
 Determines the connected components of an undirected graph. More...
 
class  StronglyConnectedComponents
 Determines the strongly connected components of an directed graph. More...
 
class  WeaklyConnectedComponents
 Determines the weakly connected components of a directed graph. More...
 
class  Assortativity
 Assortativity computes a coefficient that expresses the correlation of a node attribute among connected pairs of nodes. More...
 
class  AdamicAdarDistance
 An implementation of the Adamic Adar distance measure. More...
 
class  AlgebraicDistance
 Algebraic distance assigns a distance value to pairs of nodes according to their structural closeness in the graph. More...
 
class  AllSimplePaths
 Determines all the possible simple paths from a given source node to a target node of a directed unweighted graph. More...
 
class  APSP
 Class for all-pair shortest path algorithm. More...
 
class  BFS
 The BFS class is used to do a breadth-first search on a Graph from a given source node. More...
 
class  CommuteTimeDistance
 CommuteTimeDistance edge centrality. More...
 
class  Diameter
 
class  Dijkstra
 Dijkstra's SSSP algorithm. More...
 
class  DynAPSP
 Dynamic APSP. More...
 
class  DynBFS
 Dynamic breadth-first search. More...
 
class  DynDijkstra
 Dynamic Dijkstra. More...
 
class  DynSSSP
 Interface for dynamic single-source shortest path algorithms. More...
 
class  Eccentricity
 
class  EffectiveDiameter
 
class  EffectiveDiameterApproximation
 
class  GraphDistance
 
class  HopPlotApproximation
 
class  IncompleteDijkstra
 Implementation of IncompleteSSSP using a normal Dijkstra with binary heaps. More...
 
class  IncompleteSSSP
 Abstract base class for single-source shortest path algorithms that return the nodes in order of increasing distance from the source and do not necessarily need to compute all distances. More...
 
class  JaccardDistance
 Jaccard distance assigns a distance value to pairs of nodes according to the similarity of their neighborhoods. More...
 
class  NeighborhoodFunction
 
class  NeighborhoodFunctionApproximation
 
class  NeighborhoodFunctionHeuristic
 
class  NodeDistance
 Abstract base class for node distance measures. More...
 
class  SSSP
 Abstract base class for single-source shortest path algorithms. More...
 
class  DGSStreamParser
 
class  DGSWriter
 
class  GraphEvent
 
class  GraphEventHandler
 
class  GraphEventProxy
 This class enables the observer pattern for dynamic graphs: It has the same modifiers as a Graph object. More...
 
class  GraphUpdater
 
class  ChibaNishizekiQuadrangleEdgeScore
 
class  ChibaNishizekiTriangleEdgeScore
 An implementation of the triangle counting algorithm by Chiba/Nishizeki. More...
 
class  EdgeScore
 Abstract base class for an edge score. More...
 
class  EdgeScoreAsWeight
 
class  EdgeScoreBlender
 
class  EdgeScoreLinearizer
 
class  EdgeScoreNormalizer
 
class  GeometricMeanScore
 
class  PrefixJaccardScore
 
class  TriangleEdgeScore
 A parallel triangle counting implementation based on ideas in [0]. More...
 
class  EdmondsKarp
 The EdmondsKarp class implements the maximum flow algorithm by Edmonds and Karp. More...
 
class  BarabasiAlbertGenerator
 Generates a scale-free graph using the Barabasi-Albert preferential attachment model. More...
 
class  ChungLuGenerator
 Given an arbitrary degree sequence, the Chung-Lu generative model will produce a random graph with the same expected degree sequence. More...
 
class  ClusteredRandomGraphGenerator
 The ClusteredRandomGraphGenerator class is used to create a clustered random graph. More...
 
class  DorogovtsevMendesGenerator
 
class  DynamicBarabasiAlbertGenerator
 
class  DynamicDGSParser
 
class  DynamicDorogovtsevMendesGenerator
 
class  DynamicForestFireGenerator
 The Forest Fire generative model produces dynamic graphs with the following properties: More...
 
class  DynamicGraphGenerator
 Abstract base class for a dynamic graph generator (in the new dynamic architecture). More...
 
class  DynamicGraphSource
 
class  DynamicHyperbolicGenerator
 
class  DynamicPathGenerator
 Example dynamic graph generator: Generates a dynamically growing path. More...
 
class  DynamicPubWebGenerator
 
class  EdgeSwitchingMarkovChainGenerator
 Graph generator for generating a random simple graph with exactly the given degree sequence based on the Edge-Switching Markov-Chain method. More...
 
class  ErdosRenyiGenerator
 Creates G(n, p) graphs. More...
 
class  HavelHakimiGenerator
 Havel-Hakimi algorithm for generating a graph according to a given degree sequence. More...
 
class  HyperbolicGenerator
 
class  LFRGenerator
 The LFR clustered graph generator as introduced by Andrea Lancichinetti, Santo Fortunato, and Filippo Radicchi. More...
 
class  PowerlawDegreeSequence
 
struct  circle
 
class  PubWebGenerator
 Generates a static graph that resembles an assumed geometric distribution of nodes in a P2P network. More...
 
class  QuadNode
 
class  QuadNodeCartesianEuclid
 
class  QuadNodePolarEuclid
 
class  Quadtree
 
class  QuadtreeCartesianEuclid
 
class  QuadtreePolarEuclid
 
class  RegularRingLatticeGenerator
 
class  RmatGenerator
 Generates static R-MAT graphs. More...
 
class  StaticDegreeSequenceGenerator
 
class  StaticGraphGenerator
 Abstract base class for static graph generators. More...
 
class  StochasticBlockmodel
 
class  WattsStrogatzGenerator
 
class  HyperbolicSpace
 
class  Point2D
 Points in any dimension of templated type. More...
 
class  ClusteringCoefficient
 
class  GlobalClusteringCoefficient
 
class  Coordinates
 DEPRECATED: A specialized container for node coordinates is no longer consistent with NetworKit's approach to node attributes. More...
 
struct  WeightedEdge
 A weighted edge used for the graph constructor with initializer list syntax. More...
 
struct  Edge
 
class  Graph
 A graph (with optional weights) and parallel iterator methods. More...
 
class  GraphBuilder
 
struct  MyEdge
 
class  KruskalMSF
 Creates a minimum spanning tree for each connected component. More...
 
class  RandomMaximumSpanningForest
 Computes a random maximum-weight spanning forest using Kruskal's algorithm by randomizing the order of edges of the same weight. More...
 
class  RandomSpanningForest
 Creates a random spanning tree for each connected component. More...
 
class  Sampling
 
class  SpanningForest
 Base class for spanning forest/tree algorithms. More...
 
class  UnionMaximumSpanningForest
 Union maximum-weight spanning forest algorithm, computes the union of all maximum-weight spanning forests using Kruskal's algorithm. More...
 
class  IndependentSetFinder
 DEPRECATED: put into code archive, nobody seems to be using it Abstract base class for independent set algorithms. More...
 
class  Luby
 DEPRECATED: put into code archive as nobody seems to be using it Luby's parallel independent set algorithm. More...
 
class  CoverReader
 
class  CoverWriter
 Write a clustering to a file. More...
 
class  DGSReader
 DGS is a file format allowing to store graphs and dynamic graphs in a textual human readable way, yet with a small size allowing to store large graphs. More...
 
class  DibapGraphReader
 TODO: class documentation. More...
 
class  DotGraphWriter
 This class turns a graph into a very basic GraphViz file as documented in the official manual [1]. More...
 
class  DotPartitionWriter
 
class  DynamicGraphReader
 
class  EdgeListCoverReader
 
class  EdgeListPartitionReader
 
class  EdgeListReader
 A reader for various edge list formats, in which each line contains an edge as two node ids. More...
 
class  EdgeListWriter
 A writer for the edge list format. More...
 
class  GMLGraphReader
 Reader for the GML file format documented in [1]. More...
 
class  GMLGraphWriter
 Writes a graph and its coordinates as a GML file. More...
 
class  GraphIO
 
class  GraphReader
 Abstract base class for graph readers. More...
 
class  GraphToolBinaryReader
 Reads graphs from files in the binary format defined by graph-tool[1]. More...
 
class  GraphToolBinaryWriter
 Writes graphs to files in the binary format defined by graph-tool[1]. More...
 
class  GraphWriter
 Abstract base class for graph writers. More...
 
class  KONECTGraphReader
 
class  LineFileReader
 Reads a file and puts each line as a string into a vector. More...
 
class  MatrixMarketReader
 Reader for the matrix market file format as described in http://math.nist.gov/MatrixMarket/reports/MMformat.ps. More...
 
class  MatrixReader
 Abstract base class for matrix readers. More...
 
class  METISGraphReader
 Reader for the METIS file format documented in [1]. More...
 
class  METISGraphWriter
 
class  METISParser
 Parser for the METIS file format. More...
 
class  PartitionReader
 
class  PartitionWriter
 Write a clustering to a file. More...
 
class  RasterReader
 Reader for NASA raster data of population. More...
 
class  SNAPEdgeListPartitionReader
 Reads the clustering files from the SNAP collection. More...
 
class  SNAPGraphReader
 
class  SNAPGraphWriter
 Write graph in the Georgia Tech SNAP (Small-world Network Analysis and Partitioning) (http://snap-graph.sourceforge.net/) file format (do not confuse this with the Stanford Network Analysis Project.) From the SNAP user guide: More...
 
class  LayoutAlgorithm
 Base class for graph layout algorithms, i.e. More...
 
class  AdamicAdarIndex
 Implementation of the Adamic/Adar Index. More...
 
class  AdjustedRandIndex
 AdjustedRandIndex proposed by Hoffman et al. More...
 
class  AlgebraicDistanceIndex
 Algebraic distance assigns a distance value to pairs of nodes according to their structural closeness in the graph. More...
 
class  CommonNeighborsIndex
 The CommonNeighborsIndex calculates the number of common neighbors of a node-pair in a given graph. More...
 
class  EvaluationMetric
 Abstract base class for evaluation curves. More...
 
class  JaccardIndex
 Implementation of the Jaccard index which normalizes the Common Neighbors Index. More...
 
class  KatzIndex
 Implementation of the Katz index. More...
 
class  LinkPredictor
 Abstract base class for link predictors. More...
 
class  MissingLinksFinder
 Allows the user to find missing links in the given graph. More...
 
class  NeighborhoodDistanceIndex
 Assigns a distance value to pairs of nodes according to the overlap of their neighborhoods. More...
 
class  NeighborhoodUtility
 Provides basic operations on neighborhoods in a given graph. More...
 
class  NeighborsMeasureIndex
 Implementation of the Neighbors Measure Index. More...
 
class  PrecisionRecallMetric
 Provides points that define the Precision-Recall curve for a given set of predictions. More...
 
class  PredictionsSorter
 Allows the sorting of predictions by score or node-pair. More...
 
class  PreferentialAttachmentIndex
 Implementation of the Preferential Attachment Index. More...
 
class  ResourceAllocationIndex
 Implementation of the ResourceAllocationIndex. More...
 
class  ROCMetric
 Provides points that define the Receiver Operating Characteristic curve for a given set of predictions. More...
 
class  SameCommunityIndex
 Index to determine whether two nodes are in the same community. More...
 
class  TotalNeighborsIndex
 Implementation of the Total Neighbors Index. More...
 
class  UDegreeIndex
 Index that simply returns the degree of the first given node. More...
 
class  VDegreeIndex
 Index that simply returns the degree of the second given node. More...
 
class  LocalMaxMatcher
 LocalMax matching similar to the one described in the EuroPar13 paper by the Sanders group (Birn, Osipov, Sanders, Schulz, Sitchinava) More...
 
class  Matcher
 Abstract base class for matching algorithms. More...
 
class  Matching
 
class  PathGrowingMatcher
 Path growing matching algorithm as described by Hougardy and Drake, http://dx.doi.org/10.1016/S0020-0190(02)00393-9 Computes an approximate maximum weight matching with guarantee 1/2. More...
 
class  ConjugateGradient
 Implementation of Conjugate Gradient. More...
 
class  GaussSeidelRelaxation
 Implementation of the Gauss-Seidel smoother. More...
 
class  Lamg
 Represents the interface to the Lean Algebraic Multigrid (LAMG) graph Laplacian linear solver by Oren E. More...
 
class  EliminationStage
 
class  Level
 Abstract base class for an LAMG Level. More...
 
class  LevelAggregation
 
class  LevelElimination
 
class  LevelFinest
 
class  LevelHierarchy
 
class  MultiLevelSetup
 Implements the setup phase of LAMG (Lean Algebraic Multigrid by Livne et al.). More...
 
struct  LAMGSolverStatus
 Status parameters of the solver. More...
 
class  SolverLamg
 Implements the solve phase of LAMG (Lean Algebraic Multigrid by Livne et al.). More...
 
struct  SolverStatus
 Describes the status of a LinearSolver after the solver finished. More...
 
class  LinearSolver
 Abstract base class for solvers that solve linear systems. More...
 
class  DiagonalPreconditioner
 Simple preconditioner that approximates the matrix by a diagonal matrix. More...
 
class  IdentityPreconditioner
 Simple preconditioner that returns the given vector unchanged. More...
 
class  Smoother
 Abstract base class of a smoother. More...
 
class  HashingOverlapper
 Determines the overlap of multiple partitions by hashing partition identifiers. More...
 
class  Overlapper
 Abstract base class for algorithms which determine the overlap of multiple partitions. More...
 
class  ApproximatePageRank
 Computes an approximate PageRank vector from a given seed. More...
 
class  GCE
 The Greedy Community Expansion algorithm. More...
 
class  PageRankNibble
 Variant of PageRank-Nibble algorithm due to Andersen, Chung and Lang. More...
 
class  SelectiveCommunityDetector
 
class  EdgeScoring
 Abstract base class for algorithms associating a score with an edge. More...
 
class  ModularityScoring
 
class  EpidemicSimulationSEIR
 Node centrality index which ranks nodes by their degree. More...
 
class  PseudoRandomSpanningTree
 
class  RandomSpanningTree
 DEPRECATED: uniform random spanning tree algorithm, see graph module for implementation that can handle disconnected graphs. More...
 
class  ChanceCorrectedTriangleScore
 
class  ForestFireScore
 Based on the Forest Fire algorithm introduced by Leskovec et al. More...
 
class  GlobalThresholdFilter
 Calculates a sparsified graph by applying a global threshold to an edge score. More...
 
struct  AttributizedEdge
 
class  LocalDegreeScore
 Local Degree sparsification method. More...
 
class  LocalFilterScore
 Local filtering edge scoring. More...
 
struct  greater
 
class  LocalSimilarityScore
 Implementation of the Local Sparsification Algorithm by Sataluri et al. More...
 
class  MultiscaleScore
 Calculates the multiscale edge score for a given graph. More...
 
class  RandomEdgeScore
 Generates a random edge attribute. More...
 
class  RandomNodeEdgeScore
 
class  SCANStructuralSimilarityScore
 
class  SimmelianOverlapScore
 Calculates the Simmelian backbone (paramaetric variant) for a given input graph. More...
 
struct  RankedEdge
 A directed edge with a simmelianness int value. More...
 
struct  Redundancy
 Represents the result of the comparison of two ranked neighborhood lists, namely the overlap of the top-k neighbors and the maximum jaccard index. More...
 
class  SimmelianScore
 Abstract base class for the two variants of Simmelian backbones (OverlapFilter, JaccardFilter). More...
 
class  Sparsifier
 In this file, edge score calculators and edge score filters are combined into different sparsification algorithms. More...
 
class  SimmelianSparsifierNonParametric
 Imlementation of the non-parametric variant of Simmelian Backbones, as introduced by Nick et al. More...
 
class  SimmelianSparsifierParametric
 Imlementation of the parametric variant (Top-k neighborhood overlap) of Simmelian Backbones, as introduced by Nick et al. More...
 
class  MultiscaleSparsifier
 Implementation of the Multiscale Backbone, as introduced by Serrano et al. More...
 
class  LocalSimilaritySparsifier
 Local Similarity Sparsification as introduced by Satuluri et al. More...
 
class  SimmelianMultiscaleSparsifier
 Multiscale backbone using simmelianness as input weight. More...
 
class  RandomSparsifier
 Produces sparsified graphs that contain approximately a given percentage of edges of the original graph. More...
 
class  Cover
 Implements a cover of a set, i.e. More...
 
class  Partition
 Implements a partition of a set, i.e. More...
 
class  UnionFind
 Implements the Union Find data structure to maintain disjoint sets efficiently. More...
 
class  FruchtermanReingold
 DEPRECATED Fruchterman-Reingold graph drawing algorithm. More...
 
class  GraphLayoutAlgorithm
 Abstract base class for algorithms that compute a layout of the Graph vertices in d-dimensional space. More...
 
struct  ForwardEdge
 
class  MaxentStress
 Implementation of MaxentStress by Ganser et al. More...
 
class  MultilevelLayouter
 DEPRECATED. More...
 
struct  BoundingBox
 Bounding box used by the Octree class. More...
 
struct  OctreeNode
 Node in the octree data structure. More...
 
class  Octree
 Implementation of a k-dimensional octree for the purpose of Barnes-Hut approximation. More...
 
class  PivotMDS
 Implementation of PivotMDS proposed by Brandes and Pich. More...
 
class  Point
 Formerly marked as deprecated: To take advantage of automatic mapping between C++ and Python data structures, use standard library containers (std::pair, std::tuple..) instead. More...
 
class  PostscriptWriter
 EPS output of graphs with 2D coordinates. More...
 

Typedefs

typedef EstimateBetweenness
ApproxBetweenness2 
__attribute__ ((deprecated("Use EstimateBetweenness instead.")))
 
typedef struct
NetworKit::ListEntry_struct 
ListEntry
 
typedef std::vector
< std::vector< count > > 
Matrix
 
typedef index label
 
typedef std::function
< std::vector< node >node)> 
neighborFunction
 
typedef float distance
 
typedef std::pair< node, nodeedge
 
typedef uint64_t index
 Typedefs. More...
 
typedef uint64_t count
 
typedef ttmath::Big
< TTMATH_BITS(64), TTMATH_BITS(64)> 
bigfloat
 
typedef index node
 
typedef double edgeweight
 
typedef index edgeid
 
typedef std::vector< RankedEdgeRankedNeighbors
 
typedef std::vector< VectorCoordinateVector
 

Enumerations

enum  DiameterAlgo {
  automatic = 0, exact = 1, estimatedRange = 2, estimatedSamples = 3,
  estimatedPedantic = 4
}
 
enum  LevelType { FINEST, ELIMINATION, AGGREGATION, COARSEST }
 

Functions

Vector operator* (const double &scalar, const Vector &v)
 Multiplies the vector v with a scalar specified in scalar and returns the result. More...
 
class deprecated ("Use MaximalCliques instead.")]] MaxClique
 Exact algorithm for computing the size of the largest clique in a graph. More...
 
int uniformRandom (int max)
 
unsigned int findIndex (const std::vector< int > &w, int v, unsigned int lowerIdx, unsigned int upperIdx)
 
bool operator< (const WeightedEdge &e1, const WeightedEdge &e2)
 
bool operator== (const Edge &e1, const Edge &e2)
 
template<bool objectiveIsM>
std::set< nodeexpandseed_internal (const Graph &G, node s)
 
class deprecated ("Use base class LayoutAlgorithm instead")]] Layouter
 DEPRECATED: use base class LayoutAlgorithm instead. More...
 
template<class T >
std::ostream & operator<< (std::ostream &out, Point< T > &point)
 

Variables

constexpr double FLOAT_EPSILON = 1e-9
 Floating point epsilon to use in comparisons. More...
 
std::vector< std::vector
< std::string > > 
localNodeCategories
 
const int MAX_RAND_VAL = 1000
 
const float MAX_DENSE_AREA_RADIUS = 0.2f
 
const float MIN_MAX_DENSE_AREA_FACTOR = 5.0f
 
const edgeweight BASE_WEIGHT = 0.01f
 
const short NO = 0
 
const short YES = 1
 
const short UNKNOWN = 2
 
constexpr index none = std::numeric_limits<index>::max()
 Constants. More...
 
constexpr edgeweight defaultEdgeWeight = 1.0
 
constexpr edgeweight nullWeight = 0.0
 
constexpr count TV_NUM = 4
 
constexpr count TV_INC = 1
 
constexpr count TV_MAX = 10
 
constexpr count SETUP_TV_SWEEPS = 4
 
constexpr count MAX_DIRECT_SOLVE_SIZE = 200
 
constexpr count SETUP_MAX_AGG_LEVELS = 100
 
constexpr count SETUP_MAX_LEVELS = 100
 
constexpr double SETUP_CYCLE_INDEX = 1.5
 
constexpr count SETUP_RELAX_ACF_MIN_SWEEPS = 7
 
constexpr double SETUP_MAX_COARSE_RELAX_ACF = 0.3
 
constexpr count MAX_COMBINED_ITERATES = 4
 
constexpr count SETUP_ELIMINATION_MAX_DEGREE = 4
 
constexpr count SETUP_ELIMINATION_MAX_STAGES = 1000
 
constexpr double SETUP_ELIMINATION_MIN_ELIM_FRACTION = 0.01
 
constexpr double SETUP_AGGREGATION_WEAK_EDGE_THRESHOLD = 0.1
 
constexpr count SETUP_AGGREGATION_DEGREE_THRESHOLD = 8
 
constexpr count SETUP_NU_DEFAULT = 3
 
constexpr double SETUP_COARSENING_WORK_GUARD = 0.7
 
constexpr count SETUP_MIN_AGGREGATION_STAGES = 1
 
constexpr count SETUP_MAX_AGGREGATION_STAGES = 2
 
constexpr count SETUP_RELAX_COARSEST_SWEEPS = 400
 
const count MAX_ITER = 300
 
const double EPS = 0.1
 
Lamg< CSRMatrixnoneGiven (0.001)
 

Typedef Documentation

typedef EstimateBetweenness ApproxBetweenness2 NetworKit::__attribute__((deprecated("Use EstimateBetweenness instead.")))
typedef std::vector<Vector> NetworKit::CoordinateVector
typedef uint64_t NetworKit::count
typedef float NetworKit::distance
typedef std::pair<node, node> NetworKit::edge
typedef double NetworKit::edgeweight
typedef uint64_t NetworKit::index

Typedefs.

typedef std::vector<std::vector<count> > NetworKit::Matrix
typedef std::function<std::vector<node>node)> NetworKit::neighborFunction
typedef std::vector<RankedEdge> NetworKit::RankedNeighbors

Enumeration Type Documentation

Enumerator
automatic 
exact 
estimatedRange 
estimatedSamples 
estimatedPedantic 
Enumerator
FINEST 
ELIMINATION 
AGGREGATION 
COARSEST 

Function Documentation

class NetworKit::deprecated ( "Use MaximalCliques instead."  )

Exact algorithm for computing the size of the largest clique in a graph.

Worst-case running time is exponential, but in practice the algorithm is fairly fast. Reference: Pattabiraman et al., http://arxiv.org/pdf/1411.7460.pdf DEPRECATED: Use MaximalCliques instead.

Subroutine that goes through every relevant clique containing a certain node in a recursive fashion and computes the size of the largest.

Constructor for maximum clique algorithm.

Parameters
[in]GGraph G for which algorithm should be run.
[in]lbLower bound for maximum clique size.

Actual maximum clique algorithm. Determines largest clique each vertex is contained in and returns size of largest. Pruning steps keep running time acceptable in practice.

Returns
Size of maximum clique.

Get size of maximum clique.

Returns
Size of maximum clique
Largest clique of the graph.
template<bool objectiveIsM>
std::set<node> NetworKit::expandseed_internal ( const Graph &  G,
node  s 
)

Check if set contains node.

internal and external weighted degree of a node with respect to the community

unsigned int NetworKit::findIndex ( const std::vector< int > &  w,
int  v,
unsigned int  lowerIdx,
unsigned int  upperIdx 
)
Vector NetworKit::operator* ( const double &  scalar,
const Vector &  v 
)
inline

Multiplies the vector v with a scalar specified in scalar and returns the result.

Returns
The result of multiplying this vector with scalar.
bool NetworKit::operator< ( const WeightedEdge &  e1,
const WeightedEdge &  e2 
)
inline
template<class T >
std::ostream& NetworKit::operator<< ( std::ostream &  out,
Point< T > &  point 
)
bool NetworKit::operator== ( const Edge &  e1,
const Edge &  e2 
)
inline
int NetworKit::uniformRandom ( int  max)

Variable Documentation

const edgeweight NetworKit::BASE_WEIGHT = 0.01f
constexpr edgeweight NetworKit::defaultEdgeWeight = 1.0
const double NetworKit::EPS = 0.1
constexpr double NetworKit::FLOAT_EPSILON = 1e-9

Floating point epsilon to use in comparisons.

std::vector<std::vector<std::string> > NetworKit::localNodeCategories
constexpr count NetworKit::MAX_COMBINED_ITERATES = 4
const float NetworKit::MAX_DENSE_AREA_RADIUS = 0.2f
constexpr count NetworKit::MAX_DIRECT_SOLVE_SIZE = 200
const count NetworKit::MAX_ITER = 300
const int NetworKit::MAX_RAND_VAL = 1000
const float NetworKit::MIN_MAX_DENSE_AREA_FACTOR = 5.0f
const short NetworKit::NO = 0
constexpr index NetworKit::none = std::numeric_limits<index>::max()

Constants.

Lamg<CSRMatrix> NetworKit::noneGiven(0.001)
constexpr edgeweight NetworKit::nullWeight = 0.0
constexpr count NetworKit::SETUP_AGGREGATION_DEGREE_THRESHOLD = 8
constexpr double NetworKit::SETUP_AGGREGATION_WEAK_EDGE_THRESHOLD = 0.1
constexpr double NetworKit::SETUP_COARSENING_WORK_GUARD = 0.7
constexpr double NetworKit::SETUP_CYCLE_INDEX = 1.5
constexpr count NetworKit::SETUP_ELIMINATION_MAX_DEGREE = 4
constexpr count NetworKit::SETUP_ELIMINATION_MAX_STAGES = 1000
constexpr double NetworKit::SETUP_ELIMINATION_MIN_ELIM_FRACTION = 0.01
constexpr count NetworKit::SETUP_MAX_AGG_LEVELS = 100
constexpr count NetworKit::SETUP_MAX_AGGREGATION_STAGES = 2
constexpr double NetworKit::SETUP_MAX_COARSE_RELAX_ACF = 0.3
constexpr count NetworKit::SETUP_MAX_LEVELS = 100
constexpr count NetworKit::SETUP_MIN_AGGREGATION_STAGES = 1
constexpr count NetworKit::SETUP_NU_DEFAULT = 3
constexpr count NetworKit::SETUP_RELAX_ACF_MIN_SWEEPS = 7
constexpr count NetworKit::SETUP_RELAX_COARSEST_SWEEPS = 400
constexpr count NetworKit::SETUP_TV_SWEEPS = 4
constexpr count NetworKit::TV_INC = 1
constexpr count NetworKit::TV_MAX = 10
constexpr count NetworKit::TV_NUM = 4
const short NetworKit::UNKNOWN = 2
const short NetworKit::YES = 1