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HBCalibData.cc
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HBCalibData.cc
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#define HBHitsTree_cxx
#include "HBHitsTree.h"
#include "HBCalibData.h"
#include "TCanvas.h"
CalibConfiguration CalibConfiguration::theConfig;
CalibConfiguration::CalibConfiguration() {
for (int i=0; i<NUMBER_OF_HB_LAYERS; i++) {
scaling_for_layer[i]=1;
depth_for_layer[i]=(i*4/(NUMBER_OF_HB_LAYERS))+1;
}
}
void CalibConfiguration::setScaleForLumi(double fbinv) {
static const double lambda[] = {889.220391,889.220391,1201.809419,1380.303173,
1693.128914,2048.36654,2761.785792,3040.950936,
4109.941152,4607.435714,4607.435714,5687.691846,
6522.888776,8094.368931,9903.555204,17698.14427,17698.14427};
for (int i=0; i<NUMBER_OF_HB_LAYERS; i++) {
scaling_for_layer[i]=exp(-fbinv/lambda[i]);
}
}
void CalibConfiguration::setupLayers(int n1, int n2, int n3, int n4) {
for (int i=0; i<NUMBER_OF_HB_LAYERS; i++) {
if (i<n1) depth_for_layer[i]=1;
else if (i<(n1+n2)) depth_for_layer[i]=2;
else if (i<(n1+n2+n3)) depth_for_layer[i]=3;
else if (i<(n1+n2+n3+n4)) depth_for_layer[i]=4;
}
}
HBEvent::HBEvent() {
EB_energy=0;
for (int i=0; i<NUMBER_OF_HB_LAYERS; i++)
energy_by_layer[i]=0;
}
double HBEvent::calc(double* w, double* bydepth) const {
double theTotal=EB_energy*w[0]; // first parameter is EB weighting
if (bydepth!=0) {
bydepth[0]=EB_energy;
for (int i=1; i<=4; i++) bydepth[i]=0;
}
for (int i=0; i<NUMBER_OF_HB_LAYERS; i++) {
// get the energy
double x=energy_by_layer[i];
// scale the energy for damage to this layer
x*=CalibConfiguration::theConfig.scaling_for_layer[i];
// get the right depth
int idepth=CalibConfiguration::theConfig.depth_for_layer[i];
// add to the bydepth if needed
if (bydepth!=0) bydepth[idepth]+=x;
// apply the weight
x*=w[idepth];
// add to the total
theTotal+=x;
}
return theTotal;
}
void HBData::load(const char* filename, double target) {
m_target=target;
TFile mf(filename);
TTree* theTree=(TTree*)(mf.Get("demo/Calo"));
HBHitsTree loader(theTree);
Long64_t nentries = loader.fChain->GetEntriesFast();
m_data.reserve(nentries);
for (Long64_t jentry=0; jentry<nentries;jentry++) {
Long64_t ientry = loader.LoadTree(jentry);
if (ientry < 0) break;
loader.fChain->GetEntry(jentry);
HBEvent point;
point.setEBenergy(loader.EBenergy);
for (int ihit=0; ihit<loader.nhits; ihit++) {
point.addEnergy(loader.layer[ihit],loader.energy[ihit]);
}
m_data.push_back(point);
}
}
double HBData::calcQuality(double* w, double* grad) const {
std::vector<HBEvent>::const_iterator i;
double sum=0;
double sum2=0;
double xij[5];
if (grad!=0)
for (int j=0; j<5; j++) grad[j]=0;
for (i=m_data.begin(); i!=m_data.end(); i++) {
double pt=i->calc(w,xij);
pt-=m_target;
if (grad!=0) {
for (int j=0; j<5; j++) {
grad[j]+=2*pt*xij[j];
}
}
sum+=pt;
sum2+=pt*pt;
}
sum2/=m_data.size();
if (grad!=0)
for (int j=0; j<5; j++) grad[j]/=m_data.size();
// sum/=m_data.size(); // sum is now average!
// double sigma2=sum2-sum*sum;
double quality=sum2; // interestingly...
return quality;
}
void HBData::fillHist(double* w, TH1* hist) const {
std::vector<HBEvent>::const_iterator i;
for (i=m_data.begin(); i!=m_data.end(); i++) {
double pt=i->calc(w);
pt-=m_target;
pt/=m_target;
hist->Fill(pt);
}
}
HBData* theData;
HBData::HBData() { theData=this; }
void FitHB(Int_t& npar, Double_t* grad, Double_t& fn, Double_t* par, Int_t flags) {
if (npar!=5) {
fn=0;
printf("%d %d\n",npar,flags);
} else fn=theData->calcQuality(par,grad);
}
#include "TMinuit.h"
void doFitNow(double* w=0) {
TMinuit *ptMinuit = new TMinuit(5); //initialize TMinuit with a maximum of 5 params
ptMinuit->SetPrintLevel(2);
ptMinuit->SetFCN(FitHB);
ptMinuit->DefineParameter(0,"eb",0.47,0.05,0,0);
ptMinuit->DefineParameter(1,"d1",45,0.5,0,0);
ptMinuit->DefineParameter(2,"d2",45,0.5,0,0);
ptMinuit->DefineParameter(3,"d3",45,0.5,0,0);
ptMinuit->DefineParameter(4,"d4",45,0.5,0,0);
double arglist[10];
int tool=0;
arglist[0] = 500;
arglist[1] = 1.;
ptMinuit->mnexcm("MIGRAD", arglist,2,tool);
Double_t amin,edm,errdef;
Int_t nvpar,nparx,icstat;
ptMinuit->mnstat(amin,edm,errdef,nvpar,nparx,icstat);
//void mnstat(Double_t &fmin, Double_t &fedm, Double_t &errdef, Int_t &npari, Int_t &nparx, Int_t &istat)
//*-*-*-*-*Returns concerning the current status of the minimization*-*-*-*-*
//*-* =========================================================
//*-* User-called
//*-* Namely, it returns:
//*-* FMIN: the best function value found so far
//*-* FEDM: the estimated vertical distance remaining to minimum
//*-* ERRDEF: the value of UP defining parameter uncertainties
//*-* NPARI: the number of currently variable parameters
//*-* NPARX: the highest (external) parameter number defined by user
//*-* ISTAT: a status integer indicating how good is the covariance
//*-* matrix: 0= not calculated at all
//*-* 1= approximation only, not accurate
//*-* 2= full matrix, but forced positive-definite
//*-* 3= full accurate covariance matrix
//*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*
// cout << "\n";
// cout << " Minimum chi square = " << amin << "\n";
//cout << " Estimated vert. distance to min. = " << edm << "\n";
//cout << " Number of variable parameters = " << nvpar << "\n";
//cout << " Highest number of parameters defined by user = " << nparx << "\n";
//cout << " Status of covariance matrix = " << icstat << "\n";
// cout << "\n";
ptMinuit->mnprin(3,amin);
if (w!=0) {
double dummy;
for (int j=0; j<5; j++)
ptMinuit->GetParameter(j,w[j],dummy);
TH1* h=new TH1F("AfterFit","AfterFit",100,-2,2);
theData->fillHist(w,h);
h->Draw("HIST");
printf(" Resolutions : %.2f %% raw , %.2f %% corrected\n",h->GetRMS()*100,
h->GetRMS()/(1.0+h->GetMean())*100);
}
}
class MagicHB {
public:
MagicHB() {
e2.load("/local/cms/user/jmmans/hbstudy/processed/single_pi_2.root",2);
e5.load("/local/cms/user/jmmans/hbstudy/processed/single_pi_5.root",5);
e10.load("/local/cms/user/jmmans/hbstudy/processed/single_pi_10.root",10);
e50.load("/local/cms/user/jmmans/hbstudy/processed/single_pi_50.root",50);
e100.load("/local/cms/user/jmmans/hbstudy/processed/single_pi_100.root",100);
e200.load("/local/cms/user/jmmans/hbstudy/processed/single_pi_200.root",200);
elist[0]=&e2;
elist[1]=&e5;
elist[2]=&e10;
elist[3]=&e50;
elist[4]=&e100;
elist[5]=&e200;
}
void process() {
double w[5];
// best fit at 50 GeV
theData=&e50;
doFitNow(w);
// get results at full range
TCanvas* c1=new TCanvas("c1","c1",1200,900);
c1->Divide(3,2);
for (int i=0; i<6; i++) {
c1->cd(i+1);
char name[100],title[100];
sprintf(name,"FitRes%d",int(elist[i]->target()));
sprintf(title,"Resolution for %d GeV Pions",int(elist[i]->target()));
TH1* h=new TH1F(name,title,100,-2,2);
elist[i]->fillHist(w,h);
h->Draw("HIST");
printf(" Resolutions at %d GeV : %.2f %% raw , %.2f %% corrected\n",int(elist[i]->target()),
h->GetRMS()*100,
h->GetRMS()/(1.0+h->GetMean())*100);
}
}
private:
HBData e2,e5,e10,e50,e100,e200;
HBData* elist[6];
};