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double fitFunction(double *x, double *par)
{
double a;
if(x[0] < par[0]) a = par[1] + (x[0] - par[0]) * par[2] + (x[0] - par[0]) *(x[0] - par[0]) * par[4] + (x[0] - par[0]) * (x[0] - par[0]) *(x[0] - par[0]) * par[6];
else a = par[1] + (x[0] - par[0]) * par[3] + (x[0] - par[0]) * (x[0] - par[0]) * par[5] + (x[0] - par[0]) * (x[0] - par[0]) * (x[0] - par[0]) * par[7];
return a;
}
double fitFunction2(double *x, double *par)
{
double a;
if(x[0] < par[0]) a = par[1] + (x[0] - par[0]) * par[2];
else a = par[1] + (x[0] - par[0]) * par[3];
return a;
}
double fitFunction3(double *x, double *par)
{
return par[1] + TMath::Sqrt(par[2] + par[3] * (x[0] - par[0]) * (x[0] - par[0]) );
}
double fitf(double *x, double *par)
{
double arg;
if(x[0] < par[3]) {
arg = par[1]*par[1]+par[2]*par[2]*(x[0]-par[3])*(x[0]-par[3]);
} else {
arg = par[1]*par[1]+par[4]*par[4]*(x[0]-par[3])*(x[0]-par[3]);
}
double fitval = par[0]+sqrt(arg);
return fitval;
}
int calculateLorentzAngleFromClusterSizeFpix()
{
// setTDRStyle();
cout << "hallo" << endl;
// TFile *f = new TFile("/nfs/data5/wilke/TrackerPointing_ALL_V9/lorentzangle.root");
TFile *f = new TFile("/data1/Users/wilke/LorentzAngle/CMSSW_2_2_3/lorentzangle_0T.root");
f->cd();
//
TF1 *f1 = new TF1("f1",fitFunction,60, 140, 8);
f1->SetParName(0,"p0");
f1->SetParName(1,"p1");
f1->SetParName(2,"p2");
f1->SetParName(3,"p3");
f1->SetParName(4,"p4");
f1->SetParName(5,"p5");
f1->SetParameters(114,1,-0.01,0.01);
TF1 *f2 = new TF1("f2",fitFunction2, -1.0, 1.0, 4);
f2->SetParName(0,"p0");
f2->SetParName(1,"p1");
f2->SetParName(2,"p2");
f2->SetParName(3,"p3");
f2->SetParameters(-0.4,1,-1.0,1.0);
TF1 *func = new TF1("func", fitf, -1, 1,5);//3.8T
//TF1 *func = new TF1("func", fitf, -1.5, 1.5,5);//0T
func->SetParameters(1.0,0.1,1.6,-0.4,1.2);
func->SetParNames("Offset","RMS Constant","SlopeL","cot(#alpha)_min","SlopeR");
TF1 *func_beta = new TF1("func_beta", fitf, -1., 1, 5);
func_beta->SetParameters(1.,0.1,1.6,-0.,1.2);
func_beta->SetParNames("Offset","RMS Constant","SlopeL","cot(beta)_min","SlopeR");
int hist_drift_ = 200;
int hist_depth_ = 50;
double min_drift_ = -1000;
double max_drift_ = 1000;
double min_depth_ = -100;
double max_depth_ = 400;
double width_ = 0.0285;
int anglebins = 90;
int anglebinscotan = 60;
//int anglebinscotan = 36; //for 0T
TH2F * h_sizex_alpha = new TH2F("h_sizex_alpha", "h_sizex_alpha", anglebins, 0, 180,10 , .5, 10.5);
TH2F * h_sizex_alpha_cotan = new TH2F("h_sizex_cotanalpha", "h_sizex_cotanalpha", anglebinscotan, -3, 3,10 , .5, 10.5);
TH2F * h_sizey_beta_cotan = new TH2F("h_sizey_cotanbeta", "h_sizey_cotanbeta", anglebinscotan, -3, 3,10 , .5, 10.5);
TH2F * h_alpha_beta_cotan = new TH2F("h_cotanalpha_cotanbeta", "h_cotanalpha_cotanbeta", 100, -5, 5,100 , -5, 5);
TH2F * h_alpha_beta = new TH2F("h_alpha_beta", "h_alpha_beta", anglebins, -180, 180,anglebins, -180, 180);
TH1F * h_alpha_cotan = new TH1F("h_cotanalpha", "h_cotanalpha", anglebinscotan, -3, 3 );
TH1F * h_beta_cotan = new TH1F("h_cotanbeta", "h_cotanbeta", anglebinscotan, -3, 3 );
TH1F * h_alpha = new TH1F("h_alpha", "h_alpha", anglebins, -180, 180 );
TH1F * h_beta = new TH1F("h_beta", "h_beta", anglebins, -180, 180 );
TH1F * h_chi2 = new TH1F("h_chi2", "h_chi2", 200, 0, 10 );
int run_;
int event_;
int module_;
int side_;
int panel_;
//int ladder_;
//int layer_;
//int isflipped_;
float pt_;
float eta_;
float phi_;
double chi2_;
double ndof_;
const int maxpix = 100;
struct Pixinfo
{
int npix;
float row[200];
float col[200];
float adc[200];
float x[200];
float y[200];
} pixinfo_;
struct Hit{
float x;
float y;
double alpha;
double beta;
double gamma;
};
Hit simhit_, trackhit_;
struct Clust {
float x;
float y;
float charge;
int size_x;
int size_y;
int maxPixelCol;
int maxPixelRow;
int minPixelCol;
int minPixelRow;
} clust_;
struct Rechit {
float x;
float y;
} rechit_;
// fill the histrograms with the ntpl
TTree * LATree = (TTree*)f->Get("SiPixelLorentzAngleTreeForward_");
int nentries = LATree->GetEntries();
LATree->SetBranchAddress("run", &run_);
LATree->SetBranchAddress("event", &event_);
LATree->SetBranchAddress("module", &module_);
LATree->SetBranchAddress("side", &side_);
LATree->SetBranchAddress("panel", &panel_);
//LATree->SetBranchAddress("ladder", &ladder_);
//LATree->SetBranchAddress("layer", &layer_);
//LATree->SetBranchAddress("isflipped", &isflipped_);
LATree->SetBranchAddress("pt", &pt_);
LATree->SetBranchAddress("eta", &eta_);
LATree->SetBranchAddress("phi", &phi_);
LATree->SetBranchAddress("chi2", &chi2_);
LATree->SetBranchAddress("ndof", &ndof_);
LATree->SetBranchAddress("trackhit", &trackhit_);
LATree->SetBranchAddress("simhit", &simhit_);
LATree->SetBranchAddress("npix", &pixinfo_.npix);
LATree->SetBranchAddress("rowpix", pixinfo_.row);
LATree->SetBranchAddress("colpix", pixinfo_.col);
LATree->SetBranchAddress("adc", pixinfo_.adc);
LATree->SetBranchAddress("xpix", pixinfo_.x);
LATree->SetBranchAddress("ypix", pixinfo_.y);
LATree->SetBranchAddress("clust", &clust_);
LATree->SetBranchAddress("rechit", &rechit_);
cout << "Running over " << nentries << " hits" << endl;
ofstream fAngles( "cotanangles.txt", ios::trunc );
int passcut = 0;
for(int ientrie = 0 ; ientrie < nentries ; ientrie++){
LATree->GetEntry(ientrie);
bool large_pix = false;
// is it a large pixel (needs to be excluded)
for (int j = 0; j < pixinfo_.npix; j++){
int colpos = static_cast<int>(pixinfo_.col[j]);
if (pixinfo_.row[j] == 0 || pixinfo_.row[j] == 79 || pixinfo_.row[j] == 80 || pixinfo_.row[j] == 159 || colpos % 52 == 0 || colpos % 52 == 51 ){
large_pix = true;
}
}
if(clust_.size_y < 2) continue;
//double residual = TMath::Sqrt( (trackhit_.x - rechit_.x) * (trackhit_.x - rechit_.x) + (trackhit_.y - rechit_.y) * (trackhit_.y - rechit_.y) );
h_chi2->Fill((chi2_/ndof_));
//if( (chi2_/ndof_) < 10 && !large_pix){
if( (chi2_/ndof_) < 2 && !large_pix ){
//if( (chi2_/ndof_) < 10 && side_ == 1 ){ // for -Z side
//if( (chi2_/ndof_) < 10 && side_ == 2 ){ // for +Z side
passcut++;
if(trackhit_.alpha > 0){
h_sizex_alpha->Fill(trackhit_.alpha*180. / TMath::Pi(),clust_.size_x);
h_sizex_alpha_cotan->Fill(TMath::Tan(TMath::Pi()/2. - trackhit_.alpha),clust_.size_x);
h_sizey_beta_cotan->Fill(TMath::Tan(TMath::Pi()/2. - trackhit_.beta),clust_.size_y);
h_alpha_cotan->Fill(TMath::Tan(TMath::Pi()/2. - trackhit_.alpha));
h_beta_cotan->Fill(TMath::Tan(TMath::Pi()/2. - trackhit_.beta));
fAngles << TMath::Tan(TMath::Pi()/2. - trackhit_.alpha) << "\t" << TMath::Tan(TMath::Pi()/2. - trackhit_.beta) << endl;
}
else{
h_sizex_alpha->Fill( (trackhit_.alpha + TMath::Pi())*180. / TMath::Pi(),clust_.size_x);
h_sizex_alpha_cotan->Fill(TMath::Tan(TMath::Pi()/2. - trackhit_.alpha),clust_.size_x);
h_sizey_beta_cotan->Fill(TMath::Tan(TMath::Pi()/2. - trackhit_.beta),clust_.size_y);
h_alpha_cotan->Fill(TMath::Tan(TMath::Pi()/2. - trackhit_.alpha));
h_beta_cotan->Fill(TMath::Tan(TMath::Pi()/2. - trackhit_.beta));
fAngles << TMath::Tan(TMath::Pi()/2. - trackhit_.alpha) << "\t" << TMath::Tan(TMath::Pi()/2. - trackhit_.beta) << endl;
}
h_alpha->Fill( trackhit_.alpha*180. / TMath::Pi());
h_beta->Fill( trackhit_.beta*180. / TMath::Pi());
h_alpha_beta->Fill( trackhit_.alpha*180. / TMath::Pi(), trackhit_.beta*180. / TMath::Pi());
if(TMath::Tan(TMath::Pi()/2. - trackhit_.alpha) < -0.3 && TMath::Tan(TMath::Pi()/2. - trackhit_.alpha) > -0.5) h_alpha_beta_cotan->Fill(TMath::Tan(TMath::Pi()/2. - trackhit_.alpha), TMath::Tan(TMath::Pi()/2. - trackhit_.beta));
}
}
cout << TMath::Pi()/2. << endl;
cout << "Passing selection " << passcut << " hits" << endl;
TH1F * h_mean = new TH1F("h_mean","h_mean", anglebins, 0, 180);
TH1F * h_slice_ = new TH1F("h_slice","h_slice", 10, .5, 10.5);
TH1F * h_mean_cotan = new TH1F("h_mean_cotan","h_mean_contan", anglebinscotan, -3, 3);
TH1F * h_slice_cotan_ = new TH1F("h_slice_cotan","h_slice_cotan", 10, .5, 10.5);
TH1F * h_mean_cotan_beta = new TH1F("h_mean_cotan_beta","h_mean_contan_beta", anglebinscotan, -3, 3);
TH1F * h_slice_cotan_beta = new TH1F("h_slice_cotan_beta","h_slice_cotan_beta", 10, .5, 10.5);
//loop over bins in depth (z-local-coordinate) (in order to fit slices)
for( int i = 1; i <= anglebins; i++){
// findMean(i, (i_module + (i_layer - 1) * 8));
h_slice_->Reset("ICE");
// determine sigma and sigma^2 of the adc counts and average adc counts
//loop over bins in drift width
for( int j = 1; j<= 10; j++){
h_slice_->SetBinContent(j,h_sizex_alpha->GetBinContent(i,j));
h_slice_cotan_beta->SetBinContent(j,h_sizey_beta_cotan->GetBinContent(i,j));
} // end loop over bins in drift width
double mean = h_slice_->GetMean(1);
double error = h_slice_->GetMeanError(1);
h_mean->SetBinContent(i, mean);
h_mean->SetBinError(i, error);
double mean_beta = h_slice_cotan_beta->GetMean(1);
double error_beta = h_slice_cotan_beta->GetMeanError(1);
h_mean_cotan_beta->SetBinContent(i, mean_beta);
h_mean_cotan_beta->SetBinError(i, error_beta);
}// end loop over bins in depth
for( int i = 1; i <= anglebinscotan; i++){
h_slice_cotan_->Reset("ICE");
//loop over bins in drift width
for( int j = 1; j<= 10; j++){
h_slice_cotan_->SetBinContent(j,h_sizex_alpha_cotan->GetBinContent(i,j));
} // end loop over bins in drift width
double mean = h_slice_cotan_->GetMean(1);
double error = h_slice_cotan_->GetMeanError(1);
h_mean_cotan->SetBinContent(i, mean);
h_mean_cotan->SetBinError(i, error);
}// end loop over bins in depth
gStyle->SetOptStat(0);
gStyle->SetOptTitle(0);
TCanvas * c1 = new TCanvas("c1", "c1", 1200, 600);
c1->Divide(2,1);
c1->cd(1);
h_sizex_alpha->GetXaxis()->SetTitle("#alpha [^{o}]");
h_sizex_alpha->GetYaxis()->SetTitle("cluster size [pixels]");
h_sizex_alpha->Draw("colz");
c1->cd(2);
h_mean->GetXaxis()->SetTitle("#alpha [^{o}]");
h_mean->GetYaxis()->SetTitle("average cluster size [pixels]");
h_mean->Draw();
//h_mean->Fit(f1,"ERQ");
TCanvas * c2 = new TCanvas("c2", "c2", 1200, 600);
c2->Divide(2,1);
c2->cd(1);
h_sizex_alpha_cotan->GetXaxis()->SetTitle("cotan(#alpha)");
h_sizex_alpha_cotan->GetYaxis()->SetTitle("cluster size [pixels]");
h_sizex_alpha_cotan->Draw("colz");
c2->cd(2);
h_mean_cotan->GetXaxis()->SetTitle("cotan(#alpha)");
h_mean_cotan->GetYaxis()->SetTitle("average cluster size [pixels]");
h_mean_cotan->Draw();
//h_mean_cotan->Fit(f2,"ERQ");
h_mean_cotan->Fit(func,"R");
TCanvas * c3 = new TCanvas("c3", "c3", 600, 600);
c3->Divide(1,1);
c3->cd(1);
//h_mean_cotan->GetXaxis()->SetTitle("cotan(#alpha)");
//h_mean_cotan->GetYaxis()->SetTitle("average cluster size [pixels]");
h_mean_cotan->Draw();
//h_mean_cotan->Fit(func,"R");
TCanvas * c8 = new TCanvas("c8", "c8", 600, 600);
h_mean_cotan_beta->GetXaxis()->SetTitle("cotan(#beta)");
h_mean_cotan_beta->GetYaxis()->SetTitle("longitudinal cluster size [pixels]");
h_mean_cotan_beta->Draw();
h_mean_cotan_beta->Fit(func_beta,"ERQ");
TCanvas * c4 = new TCanvas("c4", "c4", 600, 600);
h_alpha_cotan->Draw();
TCanvas * c5 = new TCanvas("c5", "c5", 600, 600);
h_beta_cotan->Draw();
TCanvas * c6 = new TCanvas("c6", "c6", 600, 600);
h_alpha->GetXaxis()->SetTitle("#alpha [^{o}]");
h_alpha->GetYaxis()->SetTitle("number of hits");
h_alpha->Draw();
TCanvas * c7 = new TCanvas("c7", "c7", 600, 600);
h_beta->GetXaxis()->SetTitle("#beta [^{o}]");
h_beta->GetYaxis()->SetTitle("number of hits");
h_beta->Draw();
TCanvas * c9 = new TCanvas("c9", "c9", 600, 600);
h_alpha_beta->GetXaxis()->SetTitle("#alpha [^{o}]");
h_alpha_beta->GetYaxis()->SetTitle("#beta [^{o}]");
h_alpha_beta->Draw("col");
TCanvas * c10 = new TCanvas("c10", "c10", 600, 600);
h_chi2->GetXaxis()->SetTitle("#chi^{2}/ndof");
h_chi2->GetYaxis()->SetTitle("number of hits");
h_chi2->Draw();
return 0;
}
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