예제 #1
0
///Generate sequence from Power law
void TAGMUtil::GenPLSeq(TIntV& SzSeq, const int& SeqLen, const double& Alpha, TRnd& Rnd, const int& Min, const int& Max) {
    SzSeq.Gen(SeqLen, 0);
    while (SzSeq.Len() < SeqLen) {
        int Sz = (int) TMath::Round(Rnd.GetPowerDev(Alpha));
        if (Sz >= Min && Sz <= Max) {
            SzSeq.Add(Sz);
        }
    }
}
예제 #2
0
/// Generates a random scale-free graph with power-law degree distribution with
/// exponent PowerExp. The method uses either the Configuration model (fast but
/// the result is approximate) or the Edge Rewiring method (slow but exact).
PUNGraph GenRndPowerLaw(const int& Nodes, const double& PowerExp, const bool& ConfModel, TRnd& Rnd) {
  TIntV DegSeqV;
  uint DegSum=0;
  for (int n = 0; n < Nodes; n++) {
    const int Val = (int) TMath::Round(Rnd.GetPowerDev(PowerExp));
    if (! (Val >= 1 && Val < Nodes/2)) { n--; continue; } // skip nodes with too large degree
    DegSeqV.Add(Val);
    DegSum += Val;
  }
  printf("%d nodes, %u edges\n", Nodes, DegSum);
  if (DegSum % 2 == 1) { DegSeqV[0] += 1; }
  if (ConfModel) {
    // use configuration model -- fast but does not exactly obey the degree sequence
    return GenConfModel(DegSeqV, Rnd);
  } else {
    PUNGraph G = TSnap::GenDegSeq(DegSeqV, Rnd);
    return TSnap::GenRewire(G, 10, Rnd);
  }
}