SNAP Library , User Reference
2013-01-07 14:03:36
SNAP, a general purpose, high performance system for analysis and manipulation of large networks
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Functions | |
void | GetMinMax (const TFltPrV &XYValV, double &Min, double &Max, const bool &ResetMinMax) |
void | PlotGrad (const TFltPrV &EstLLV, const TFltPrV &TrueLLV, const TVec< TFltPrV > &GradVV, const TFltPrV &AcceptV, const TStr &OutFNm, const TStr &Desc) |
void | PlotAutoCorrelation (const TFltV &ValV, const int &MaxK, const TStr &OutFNm, const TStr &Desc) |
void | McMcGetAvgAvg (const TFltV &AvgJV, double &AvgAvg) |
void | McMcGetAvgJ (const TVec< TFltV > &ChainLLV, TFltV &AvgJV) |
void | PlotTrueAndEst (const TStr &OutFNm, const TStr &Desc, const TStr &YLabel, const TFltPrV &EstV, const TFltPrV &TrueV) |
void McMcGetAvgAvg | ( | const TFltV & | AvgJV, |
double & | AvgAvg | ||
) |
Definition at line 1876 of file kronecker.cpp.
void McMcGetAvgJ | ( | const TVec< TFltV > & | ChainLLV, |
TFltV & | AvgJV | ||
) |
void PlotAutoCorrelation | ( | const TFltV & | ValV, |
const int & | MaxK, | ||
const TStr & | OutFNm, | ||
const TStr & | Desc | ||
) |
Definition at line 1773 of file kronecker.cpp.
{ double Avg=0.0, Var=0.0; for (int i = 0; i < ValV.Len(); i++) { Avg += ValV[i]; } Avg /= (double) ValV.Len(); for (int i = 0; i < ValV.Len(); i++) { Var += TMath::Sqr(ValV[i]-Avg); } TFltPrV ACorrV; for (int k = 0; k < TMath::Mn(ValV.Len(), MaxK); k++) { double corr = 0.0; for (int i = 0; i < ValV.Len() - k; i++) { corr += (ValV[i]-Avg)*(ValV[i+k]-Avg); } ACorrV.Add(TFltPr(k, corr/Var)); } // plot grads TGnuPlot GP("sAutoCorr-"+OutFNm, TStr::Fmt("AutoCorrelation (%d samples). %s", ValV.Len(), Desc.CStr()), true); GP.AddPlot(ACorrV, gpwLines, "", "linewidth 1"); GP.SetXYLabel("Lag, k", "Autocorrelation, r_k"); GP.SavePng(); }
void PlotGrad | ( | const TFltPrV & | EstLLV, |
const TFltPrV & | TrueLLV, | ||
const TVec< TFltPrV > & | GradVV, | ||
const TFltPrV & | AcceptV, | ||
const TStr & | OutFNm, | ||
const TStr & | Desc | ||
) |
Definition at line 1740 of file kronecker.cpp.
{ double Min, Max, Min1, Max1; // plot log-likelihood { TGnuPlot GP("sLL-"+OutFNm, TStr::Fmt("Log-likelihood (avg 1k samples). %s", Desc.CStr()), true); GP.AddPlot(EstLLV, gpwLines, "Esimated LL", "linewidth 1"); if (! TrueLLV.Empty()) { GP.AddPlot(TrueLLV, gpwLines, "TRUE LL", "linewidth 1"); } //GetMinMax(EstLLV, Min, Max, true); GetMinMax(TrueLLV, Min, Max, false); //GP.SetYRange((int)floor(Min-1), (int)ceil(Max+1)); GP.SetXYLabel("Sample Index (time)", "Log-likelihood"); GP.SavePng(); } // plot accept { TGnuPlot GP("sAcc-"+OutFNm, TStr::Fmt("Pct. accepted rnd moves (over 1k samples). %s", Desc.CStr()), true); GP.AddPlot(AcceptV, gpwLines, "Pct accepted swaps", "linewidth 1"); GP.SetXYLabel("Sample Index (time)", "Pct accept permutation swaps"); GP.SavePng(); } // plot grads TGnuPlot GPAll("sGradAll-"+OutFNm, TStr::Fmt("Gradient (avg 1k samples). %s", Desc.CStr()), true); GetMinMax(GradVV[0], Min1, Max1, true); for (int g = 0; g < GradVV.Len(); g++) { GPAll.AddPlot(GradVV[g], gpwLines, TStr::Fmt("param %d", g+1), "linewidth 1"); GetMinMax(GradVV[g], Min1, Max1, false); TGnuPlot GP(TStr::Fmt("sGrad%02d-", g+1)+OutFNm, TStr::Fmt("Gradient (avg 1k samples). %s", Desc.CStr()), true); GP.AddPlot(GradVV[g], gpwLines, TStr::Fmt("param id %d", g+1), "linewidth 1"); GetMinMax(GradVV[g], Min, Max, true); GP.SetYRange((int)floor(Min-1), (int)ceil(Max+1)); GP.SetXYLabel("Sample Index (time)", "Gradient"); GP.SavePng(); } GPAll.SetYRange((int)floor(Min1-1), (int)ceil(Max1+1)); GPAll.SetXYLabel("Sample Index (time)", "Gradient"); GPAll.SavePng(); }
void PlotTrueAndEst | ( | const TStr & | OutFNm, |
const TStr & | Desc, | ||
const TStr & | YLabel, | ||
const TFltPrV & | EstV, | ||
const TFltPrV & | TrueV | ||
) |
Definition at line 2009 of file kronecker.cpp.