agmfit.h

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#ifndef snap_agmfit_h
#define snap_agmfit_h

#include "Snap.h"

class TAGMFit {
private:
  PUNGraph G; 
  TVec<TIntSet> CIDNSetV;  
  THash<TIntPr,TIntSet> EdgeComVH; 
  THash<TInt, TIntSet> NIDComVH; 
  TIntV ComEdgesV; 
  TFlt PNoCom; 
  TFltV LambdaV; 
  TRnd Rnd;
  THash<TIntPr,TFlt> NIDCIDPrH; 
  THash<TIntPr,TInt> NIDCIDPrS; 
  TFlt MinLambda; 
  TFlt MaxLambda; 
  TFlt RegCoef; 
  TInt BaseCID; 

public:
  TAGMFit() { }
  ~TAGMFit() { }
  TAGMFit(const PUNGraph& GraphPt, const TVec<TIntV>& CmtyVVPt, const int RndSeed = 0): G(GraphPt), PNoCom(0.0), Rnd(RndSeed), MinLambda(0.00001), MaxLambda(10.0), RegCoef(0), BaseCID(-1) { SetCmtyVV(CmtyVVPt);  }
  TAGMFit(const PUNGraph& GraphPt, const int InitComs, const int RndSeed = 0): G(GraphPt), PNoCom(0.0), Rnd(RndSeed), MinLambda(0.00001), MaxLambda(10.0), RegCoef(0), BaseCID(-1) { NeighborComInit(InitComs); }//RandomInitCmtyVV(InitComs);  }
  TAGMFit(const PUNGraph& GraphPt, const TVec<TIntV>& CmtyVVPt, const TRnd& RndPt): G(GraphPt), PNoCom(0.0), Rnd(RndPt), MinLambda(0.00001), MaxLambda(10.0), RegCoef(0), BaseCID(-1) { SetCmtyVV(CmtyVVPt); }
  void Save(TSOut& SOut);
  void Load(TSIn& SIn, const int& RndSeed = 0);

  void RandomInitCmtyVV(const int InitComs, const double ComSzAlpha = 1.3, const double MemAlpha = 1.8, const int MinComSz = 8, const int MaxComSz = 200, const int MinMem = 1, const int MaxMem = 10);
  void AddBaseCmty(); 
  double Likelihood();
  double Likelihood(const TFltV& NewLambdaV) { double Tmp1, Tmp2; return Likelihood(NewLambdaV, Tmp1, Tmp2); }
  double Likelihood(const TFltV& NewLambdaV, double& LEdges, double& LNoEdges);
  void SetRegCoef(const double Val) { RegCoef = Val; }
  void GetEdgeJointCom();
  void NeighborComInit(const int InitComs);
  // Gradient of likelihood for \c P_c.
  void GradLogLForLambda(TFltV& GradV);
  int MLEGradAscentGivenCAG(const double& Thres=0.001, const int& MaxIter=10000, const TStr PlotNm = TStr());
  void SetDefaultPNoCom();
  void SetPNoCom(const double& Epsilon) { if (BaseCID == -1 && Epsilon > 0.0) { PNoCom = Epsilon; } }
  double GetPNoCom() { return PNoCom; }
  double CalcPNoComByCmtyVV(const int& SamplePairs = -1);
  // OP RS 2014/04/10 commented out since there is no implementation
  //void GetNewtonStep(TFltVV& HVV, TFltV& GradV, TFltV& DeltaLV);
  double SelectLambdaSum(const TIntSet& ComK);
  double SelectLambdaSum(const TFltV& NewLambdaV, const TIntSet& ComK);
  
  void RandomInit(const int& MaxK);
  void RunMCMC(const int& MaxIter, const int& EvalLambdaIter, const TStr& PlotFPrx = TStr());
  void SampleTransition(int& NID, int& JoinCID, int& LeaveCID, double& DeltaL);
  void InitNodeData();
  void LeaveCom(const int& NID, const int& CID);
  // After MCMC, \c NID joins community \c CID.
  void JoinCom(const int& NID, const int& JoinCID);
  int RemoveEmptyCom();
  double SeekLeave(const int& UID, const int& CID);
  double SeekJoin(const int& UID, const int& CID);
  // Compute the change in likelihood (Delta) if node \c UID switches from \c CurCID to \c NewCID.
  double SeekSwitch(const int& UID, const int& CurCID, const int& NewCID);
  
  double GetStepSizeByLineSearchForLambda(const TFltV& DeltaV, const TFltV& GradV, const double& Alpha, const double& Beta);
  void SetLambdaV(const TFltV& LambdaPt) {LambdaV = LambdaPt;}
  void GetLambdaV(TFltV& OutV) {OutV = LambdaV;}
  void GetQV(TFltV& OutV);
  void GetCmtyVV(TVec<TIntV>& CmtyVV, const double QMax = 2.0);
  void GetCmtyVV(TVec<TIntV>& CmtyVV, TFltV& QV, const double QMax = 2.0);
  void SetCmtyVV(const TVec<TIntV>& CmtyVV);
  void PrintSummary();
};

#endif