//____________________________________________________________________
Int_t multidimfit(bool doFit = true)
{
cout << "*************************************************" << endl;
cout << "* Multidimensional Fit *" << endl;
cout << "* *" << endl;
cout << "* By Christian Holm <*****@*****.**> 14/10/00 *" << endl;
cout << "*************************************************" << endl;
cout << endl;
// Initialize global TRannom object.
gRandom = new TRandom();
// Open output file
TFile* output = new TFile("mdf.root", "RECREATE");
// Global data parameters
Int_t nVars = 4;
Int_t nData = 500;
Double_t x[4];
// make fit object and set parameters on it.
TMultiDimFit* fit = new TMultiDimFit(nVars, TMultiDimFit::kMonomials,"v");
Int_t mPowers[] = { 6 , 6, 6, 6 };
fit->SetMaxPowers(mPowers);
fit->SetMaxFunctions(1000);
fit->SetMaxStudy(1000);
fit->SetMaxTerms(30);
fit->SetPowerLimit(1);
fit->SetMinAngle(10);
fit->SetMaxAngle(10);
fit->SetMinRelativeError(.01);
// variables to hold the temporary input data
Double_t d;
Double_t e;
// Print out the start parameters
fit->Print("p");
printf("======================================\n");
// Create training sample
Int_t i;
for (i = 0; i < nData ; i++) {
// Make some data
makeData(x,d,e);
// Add the row to the fit object
fit->AddRow(x,d,e);
}
// Print out the statistics
fit->Print("s");
// Book histograms
fit->MakeHistograms();
// Find the parameterization
fit->FindParameterization();
// Print coefficents
fit->Print("rc");
// Get the min and max of variables from the training sample, used
// for cuts in test sample.
Double_t *xMax = new Double_t[nVars];
Double_t *xMin = new Double_t[nVars];
for (i = 0; i < nVars; i++) {
xMax[i] = (*fit->GetMaxVariables())(i);
xMin[i] = (*fit->GetMinVariables())(i);
}
nData = fit->GetNCoefficients() * 100;
Int_t j;
// Create test sample
for (i = 0; i < nData ; i++) {
// Make some data
makeData(x,d,e);
for (j = 0; j < nVars; j++)
if (x[j] < xMin[j] || x[j] > xMax[j])
break;
// If we get through the loop above, all variables are in range
if (j == nVars)
// Add the row to the fit object
fit->AddTestRow(x,d,e);
else
i--;
}
//delete gRandom;
// Test the parameterizatio and coefficents using the test sample.
if (doFit)
fit->Fit("M");
// Print result
fit->Print("fc v");
// Write code to file
fit->MakeCode();
// Write histograms to disk, and close file
output->Write();
output->Close();
delete output;
// Compare results with reference run
Int_t compare = CompareResults(fit, doFit);
if (!compare) {
printf("\nmultidimfit .............................................. OK\n");
} else {
printf("\nmultidimfit .............................................. fails case %d\n",compare);
}
// We're done
delete fit;
return compare;
}
void AngularAcceptance(string filename)
{
bool imposesymmetry = true;
// Input
TFile* file = TFile::Open(filename.c_str());
TTree* tree = (TTree*)file->Get("DecayTree");
int n = tree->GetEntries();
double x[3],d;
tree->SetBranchAddress("Phi_angle", &x[0]);
tree->SetBranchAddress("cos_theta1",&x[1]);
tree->SetBranchAddress("cos_theta2",&x[2]);
// Configure and make the 3D histogram
int nbinsx = 10;
double xlow = imposesymmetry ? 0 : -TMath::Pi();
double xup = +TMath::Pi();
double xrange = xup - xlow;
int nbinsy = 10;
double ylow = imposesymmetry ? 0 : -1;
double yup = +1;
double yrange = yup - ylow;
int nbinsz = 20;
double zlow = imposesymmetry ? 0 : -1;
double zup = +1;
double zrange = zup - zlow;
// For TH3::Interpolate() to work properly, the points have to be within the centres of the edge bins
TH3D* hist = new TH3D("hist","",nbinsx,xlow-(xrange/(nbinsx)),xup+(xrange/(nbinsx)) // Phi range
,nbinsy,ylow-(yrange/(nbinsy)),yup+(yrange/(nbinsy)) // cos_theta1 range
,nbinsz,zlow-(zrange/(nbinsz)),zup+(zrange/(nbinsz)));// cos_theta2 range
// Fill the histogram
cout << "Filling a 3D histogram with " << n << " events." << endl;
for(int i = 0; i < n; i++)
{
tree->GetEntry(i);
imposesymmetry ?
hist->Fill(TMath::Abs(x[0]),TMath::Abs(x[1]),TMath::Abs(x[2]))
:
hist->Fill(x[0],x[1],x[2]);
}
// Output
TFile* outfile = TFile::Open("AngAcc.root", "RECREATE");
TMultiDimFit* fit = new TMultiDimFit(3, TMultiDimFit::kLegendre,"KV");
// Configuration
int maxpowers[3] = {2,2,6};
fit->SetMaxPowers(maxpowers);
fit->SetMaxFunctions(100000);
fit->SetMaxStudy(1000000);
fit->SetMaxTerms(30);
fit->SetPowerLimit(1);
fit->SetMinAngle(10);
fit->SetMaxAngle(10);
fit->SetMinRelativeError(.01);
// Event loop
for(int i = 0; i < n; i++)
{
tree->GetEntry(i);
d = imposesymmetry ?
hist->Interpolate(TMath::Abs(x[0]),TMath::Abs(x[1]),TMath::Abs(x[2]))
:
hist->Interpolate(x[0],x[1],x[2]);
(i < n/2) ?
fit->AddRow(x,d) // Training sample
:
fit->AddTestRow(x,d); // Test sample
}
// Print starting parameters
fit->Print("p");
// Print out the statistics
fit->Print("s");
// Book histograms
fit->MakeHistograms();
// Find the parameterization
fit->FindParameterization();
// Print coefficents
fit->Print("rc");
// Do the fit
fit->Fit("M");
// Print result
fit->Print("fc");
// Write code to file
fit->MakeMethod("AutoAngAcc");
hist->Write();
outfile->Write();
outfile->Close();
}
