From: cblume Date: Thu, 8 Mar 2007 09:06:02 +0000 (+0000) Subject: Remove EvaluateUni completely X-Git-Url: http://git.uio.no/git/?a=commitdiff_plain;h=95a5eb177ad759d71cb140eff7c4db31e208388c;hp=0e6391b21dd01170a56e147f08ee20cd475253d6;p=u%2Fmrichter%2FAliRoot.git Remove EvaluateUni completely --- diff --git a/TRD/AliTRDseed.cxx b/TRD/AliTRDseed.cxx index 64006e079e7..54b550533e0 100644 --- a/TRD/AliTRDseed.cxx +++ b/TRD/AliTRDseed.cxx @@ -432,74 +432,16 @@ void AliTRDseed::UpdateUsed() fNUsed = 0; for (Int_t i = 0; i < 25; i++) { - if (!fClusters[i]) continue; - if ((fClusters[i]->IsUsed())) fNUsed++; + if (!fClusters[i]) { + continue; + } + if ((fClusters[i]->IsUsed())) { + fNUsed++; + } } } -// //_____________________________________________________________________________ -// void AliTRDseed::EvaluateUni(Int_t nvectors, Double_t *data, Double_t &mean -// , Double_t &sigma, Int_t hh) -// { -// // -// // Robust estimator in 1D case MI version -// // -// // For the univariate case -// // estimates of location and scatter are returned in mean and sigma parameters -// // the algorithm works on the same principle as in multivariate case - -// // it finds a subset of size hh with smallest sigma, and then returns mean and -// // sigma of this subset -// // - -// if (hh == 0) { -// hh = (nvectors + 2) / 2; -// } - -// Double_t faclts[] = { 2.6477, 2.5092, 2.3826, 2.2662, 2.1587 -// , 2.0589, 1.9660, 1.879, 1.7973, 1.7203 -// , 1.6473 }; -// Int_t *index = new Int_t[nvectors]; -// TMath::Sort(nvectors, data, index, kFALSE); - -// Int_t nquant = TMath::Min(Int_t(Double_t(((hh * 1.0 / nvectors) - 0.5) * 40)) + 1,11); -// Double_t factor = faclts[nquant-1]; - -// Double_t sumx = 0.0; -// Double_t sumx2 = 0.0; -// Int_t bestindex = -1; -// Double_t bestmean = 0.0; -// Double_t bestsigma = data[index[nvectors-1]] - data[index[0]]; // Maximal possible sigma -// for (Int_t i = 0; i < hh; i++) { -// sumx += data[index[i]]; -// sumx2 += data[index[i]]*data[index[i]]; -// } - -// Double_t norm = 1.0 / Double_t(hh); -// Double_t norm2 = 1.0 / Double_t(hh - 1); -// for (Int_t i = hh; i < nvectors; i++) { - -// Double_t cmean = sumx*norm; -// Double_t csigma = (sumx2 - hh*cmean*cmean) * norm2; -// if (csigma < bestsigma) { -// bestmean = cmean; -// bestsigma = csigma; -// bestindex = i - hh; -// } - -// sumx += data[index[i]] - data[index[i-hh]]; -// sumx2 += data[index[i]]*data[index[i]] - data[index[i-hh]]*data[index[i-hh]]; - -// } - -// Double_t bstd = factor * TMath::Sqrt(TMath::Abs(bestsigma)); -// mean = bestmean; -// sigma = bstd; - -// delete [] index; - -// } - //_____________________________________________________________________________ Float_t AliTRDseed::FitRiemanTilt(AliTRDseed * cseed, Bool_t terror) { diff --git a/TRD/AliTRDseed.h b/TRD/AliTRDseed.h index 88614569b7d..a4018196ac0 100644 --- a/TRD/AliTRDseed.h +++ b/TRD/AliTRDseed.h @@ -26,7 +26,6 @@ class AliTRDseed : public TObject { AliTRDseed &operator=(const AliTRDseed &/*s*/) { return *this; } - // static void EvaluateUni(Int_t nvectors, Double_t *data, Double_t &mean, Double_t &sigma, Int_t hh); static Float_t FitRiemanTilt(AliTRDseed *seed, Bool_t error); void UseClusters(); void Update();