void TMultinomial::AddFtr(const TStrV& StrV, const TFltV& FltV, TIntFltKdV& SpV) const {
// make sure we either do not have explicit values, or their dimension matches with string keys
EAssertR(FltV.Empty() || (StrV.Len() == FltV.Len()), "TMultinomial::AddFtr:: String and double values not aligned");
// generate internal feature vector
SpV.Gen(StrV.Len(), 0);
for (int StrN = 0; StrN < StrV.Len(); StrN++) {
const int FtrId = FtrGen.GetFtr(StrV[StrN]);
// only use features we've seen during updates
if (FtrId != -1) {
const double Val = FltV.Empty() ? 1.0 : FltV[StrN].Val;
if (Val > 1e-16) { SpV.Add(TIntFltKd(FtrId, Val)); }
}
}
SpV.Sort();
// merge elements with the same id
int GoodSpN = 0;
for (int SpN = 1; SpN < SpV.Len(); SpN++) {
if (SpV[GoodSpN].Key == SpV[SpN].Key) {
// repetition of previous id, sum counts
SpV[GoodSpN].Dat += SpV[SpN].Dat;
} else {
// increase the pointer to the next good position
GoodSpN++;
// and move the new value down to the good position
SpV[GoodSpN] = SpV[SpN];
}
}
// truncate the vector
SpV.Trunc(GoodSpN + 1);
// replace values with 1 if needed
if (IsBinary()) { for (TIntFltKd& Sp : SpV) { Sp.Dat = 1.0; } }
// final normalization, if needed
if (IsNormalize()) { TLinAlg::Normalize(SpV); }
}
double TEpidemModel::GetErr(const TFltV& TrueV, const TFltV& SimV, const int& SimT0) {
if (SimV.Empty() || TrueV.Empty()) { return -1.0; }
double Err = 0.0;
double S=0;
for (int t=0; t < TrueV.Len(); t++) {
if (t-SimT0 >= 0) { S = SimV[t-SimT0]; } else { S = 0; }
Err += TMath::Sqr(TrueV[t]-S);
}
if (Err <= 0) { Err = TFlt::Mx; }
return Err;
}
static void ConjugGrad(const TMatrix& Matrix, const TFltV& b, TFltV& x,
const int& CGMxIter, const double& RelErr, const TFltV& x0) {
// prepare start vector
x.Gen(Matrix.GetCols());
if (x0.Empty()) { x.PutAll(0.0); }
else { x = x0; }
// do the magic
}
TFltV KalmanFilter::Predict(TFltV control) {
// update the state: x'(k) = A * x(k)
TLinAlg::Multiply(transitionMatrix, statePost, statePre);
// x'(k) = x'(k) + B * u(k)
if (!control.Empty()) {
TLinAlg::Multiply(controlMatrix, control, temp1V);
TLinAlg::AddVec(1.0, statePre, temp1V, temp2V);
}
// update error covariance matrices: temp1 = A * P(k)
TLinAlg::Multiply(transitionMatrix, errorCovPost, temp1VV);
// P'(k) = temp1 * At + Q
TLinAlg::Gemm(1.0, temp1VV, transitionMatrix, 1.0, processNoiseCov, errorCovPre, TLinAlg::GEMM_B_T);
// return statePre
return statePre;
}
void GetInvParticipRat(const PUNGraph& Graph, int MaxEigVecs, int TimeLimit, TFltPrV& EigValIprV) {
TUNGraphMtx GraphMtx(Graph);
TFltVV EigVecVV;
TFltV EigValV;
TExeTm ExeTm;
if (MaxEigVecs<=1) { MaxEigVecs=1000; }
int EigVecs = TMath::Mn(Graph->GetNodes(), MaxEigVecs);
printf("start %d vecs...", EigVecs);
try {
TSparseSVD::Lanczos2(GraphMtx, EigVecs, TimeLimit, ssotFull, EigValV, EigVecVV, false);
} catch(...) {
printf("\n ***EXCEPTION: TRIED %d GOT %d values** \n", EigVecs, EigValV.Len()); }
printf(" ***TRIED %d GOT %d values in %s\n", EigVecs, EigValV.Len(), ExeTm.GetStr());
TFltV EigVec;
EigValIprV.Clr();
if (EigValV.Empty()) { return; }
for (int v = 0; v < EigVecVV.GetCols(); v++) {
EigVecVV.GetCol(v, EigVec);
EigValIprV.Add(TFltPr(EigValV[v], GetInvParticipRat(EigVec)));
}
EigValIprV.Sort();
}
void PlotSngValDistr(const PNGraph& Graph, const int& SngVals, const TStr& FNmPref, TStr DescStr) {
const int NBuckets = 50;
TFltV SngValV;
for (int f = 1; SngValV.Empty() && f < 4; f++) {
TSnap::GetSngVals(Graph, f*SngVals, SngValV);
}
SngValV.Sort(true);
THash<TFlt, TFlt> BucketCntH;
double Step = (SngValV.Last()-SngValV[0]) / double(NBuckets-1);
for (int i = 0; i < NBuckets; i++) {
BucketCntH.AddDat(SngValV[0]+Step*(i+0.5), 0);
}
for (int i = 0; i < SngValV.Len(); i++) {
const int Bucket = (int) floor((SngValV[i]-SngValV[0]) / Step);
BucketCntH[Bucket] += 1;
}
TFltPrV EigCntV;
BucketCntH.GetKeyDatPrV(EigCntV);
if (DescStr.Empty()) { DescStr = FNmPref; }
TGnuPlot::PlotValV(EigCntV, "sngDistr."+FNmPref, TStr::Fmt("%s. G(%d, %d). Largest eig val = %f", DescStr.CStr(),
Graph->GetNodes(), Graph->GetEdges(), SngValV.Last().Val), "Singular value", "Count", gpsAuto, false, gpwLinesPoints);
}
