Functor Statistics.Make


module Make: 
functor (G : Graph.Sig.G) -> sig .. end
Parameters:
G : Graph.Sig.G

module VS: Set.Make(G.V)
module UndG: Graph.Imperative.Graph.Concrete(G.V)
val undirect : G.t -> UndG.t
val clustering_coefficient : G.t -> G.vertex -> float
val average_distance : G.t -> VS.elt -> float
val _maxindegree : int option Pervasives.ref
val _maxoutdegree : int option Pervasives.ref
val _avgindegree : float option Pervasives.ref
val _avgoutdegree : float option Pervasives.ref
val _outdata : (int, int) ExtLib.Hashtbl.t option Pervasives.ref
val _indata : (int, int) ExtLib.Hashtbl.t option Pervasives.ref
val degree : G.t ->
(G.t -> G.vertex -> 'a list) -> float * int * (int, int) ExtLib.Hashtbl.t
val computeOutDegree : G.t -> unit
val computeInDegree : G.t -> unit
val get_option : 'a option -> 'a
val maxOutDegree : G.t -> int
val maxInDegree : G.t -> int
val averageOutDegree : G.t -> float
val averageInDegree : G.t -> float
val zdp : G.t -> int
val scatteredPlotIn : G.t -> (int, int) ExtLib.Hashtbl.t
val scatteredPlotOut : G.t -> (int, int) ExtLib.Hashtbl.t
val scatteredPlotBoth : G.t -> (int * int, int) ExtLib.Hashtbl.t
val centralityDegree : G.t -> (G.t -> G.vertex -> 'a list) -> float
val centralityOutDegree : G.t -> float
val centralityInDegree : G.t -> float
val clustering : G.t -> float
val averageShortestPathLength : G.t -> float
val components : G.t -> G.V.t list array
val weaklycomponents : G.t -> UndG.V.t list array
val numberComponents : ('a -> 'b array) -> 'a -> int
val averageComponents : ('a -> 'b list array) -> 'a -> float
val largestComponent : ('a -> 'b list array) -> 'a -> int
val numberComponentsSC : G.t -> int
val averageComponentsSC : G.t -> float
val largestComponentSC : G.t -> int
val numberComponentsWC : G.t -> int
val averageComponentsWC : G.t -> float
val largestComponentWC : G.t -> int
val density : G.t -> float
val averageTwoStepReach : G.t -> float