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dnisson |
1.1 |
// -*- C++ -*-
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//
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// Package: JetFitAnalyzer
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// Class: JetFitAnalyzer
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//
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/**\class JetFitAnalyzer JetFitAnalyzer.cc UserCode/JetFitAnalyzer/src/JetFitAnalyzer.cc
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Description: Base class for using jetfit with CMSSW
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Implementation:
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o Method make_histo is used to prepare a histogram for analysis;
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the user can read this from a file or generate from the actual event
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o Method make_model_def is used to define a formula and initial
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parameters for the model used
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o Method analyze_results performs user analysis on results;
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the user is given a trouble vector and the original histogram in
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addition.
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o The function pointer user_minuit defines what to do after each fit
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is done. The pointer should be obtained in the subclass constructor.
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*/
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//
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// Original Author: David Nisson
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// Created: Wed Aug 5 16:38:38 PDT 2009
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dnisson |
1.6 |
// $Id: JetFitAnalyzer.cc,v 1.5 2009/11/11 22:24:41 dnisson Exp $
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dnisson |
1.1 |
//
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//
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#include "UserCode/JetFitAnalyzer/interface/JetFitAnalyzer.h"
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dnisson |
1.6 |
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#include <cstdlib>
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#include <cmath>
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#include <ctime>
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#include <cstdio>
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#include <cstring>
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#include <cctype>
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#include <iostream>
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#include <fstream>
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#include <sstream>
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#include <string>
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dnisson |
1.1 |
#include <vector>
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dnisson |
1.6 |
#include <set>
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#include <map>
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#include <limits>
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#include <exception>
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#include <TMinuit.h>
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#include <TH1.h>
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#include <TH2.h>
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#include <TF2.h>
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#include <TRandom3.h>
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#include <Rtypes.h>
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#include <TFormula.h>
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#include <TSystem.h>
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#include <TMath.h>
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#include "UserCode/JetFitAnalyzer/interface/jetfit.h"
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#define PI 3.141592653
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#define MAX_GAUSS 3
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using namespace std;
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JetFitAnalyzer::ModelDefinition *mdef;
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JetFitAnalyzer::ModelDefinition& curr_ModelDefinition() {
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return *mdef;
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}
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void JetFitAnalyzer::set_ModelDefinition(ModelDefinition *_mdef) {
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mdef = _mdef;
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}
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int JetFitAnalyzer::ModelDefinition::get_ngauss() {
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return ngauss;
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}
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void JetFitAnalyzer::ModelDefinition::set_ngauss(int _ngauss) {
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ngauss = _ngauss;
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}
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// fit function
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double JetFitAnalyzer::ModelDefinition::fit_fcn(double x, double y, double *xval) {
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int npar_indiv = get_formula()->GetNpar();
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double val = 0.0;
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for (int i = 0; i < ngauss; i++) {
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get_formula()->SetParameters(xval + i*npar_indiv);
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val += mdef->get_formula()->Eval(x, y);
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}
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return val;
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}
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// TF2-compatible fit function
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double JetFitAnalyzer::fit_fcn_TF2(double *x, double *pval) {
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double val = mdef->fit_fcn(x[0], x[1], pval);
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return val;
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}
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// Integral of (model formula)^2 / chisquare sigma
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double JetFitAnalyzer::ModelDefinition::formula_int(double xlo, double xhi, double ylo, double yhi,
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double *pval, double XbinSize, double YbinSize,
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double *xval) {
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double xstep = (xhi - xlo) / static_cast<double>(20);
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double ystep = (yhi - ylo) / static_cast<double>(20);
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double fsum = 0.0;
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double pval_old[256];
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int npar = get_formula()->GetNpar();
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if (npar > 256) {
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cerr << "Parameter overload" << endl;
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return 0.0;
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}
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get_formula()->GetParameters(pval_old);
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get_formula()->SetParameters(pval);
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for (int i = 0; i < 20; i++) {
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for (int j = 0; j < 20; j++) {
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double x = (static_cast<double>(i) + 0.5)*xstep + xlo;
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double y = (static_cast<double>(j) + 0.5)*ystep + ylo;
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double sig_cut = 1.0e-5;
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double nu = XbinSize * YbinSize * fit_fcn(x, y, xval);
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double sigma = fabs(chisquare_error(0.0)) < sig_cut
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? sig_cut : chisquare_error(0.0);
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fsum += pow(xstep * ystep * get_formula()->Eval(x, y), 2.0)
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/ sigma / sigma;
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}
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}
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get_formula()->SetParameters(pval_old);
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return fsum;
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}
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// MINUIT objective function
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void fcn(int &npar, double *grad, double &fcnval, double *xval, int iflag)
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{
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double chisquare = 0.0;
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double XbinSize = (energy.Xhi - energy.Xlo)
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/ static_cast<double>(energy.bins.size());
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double YbinSize = (energy.Yhi - energy.Ylo)
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/ static_cast<double>(energy.bins.at(0).size());
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try {
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// add errors in data points in histogram
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for (int i = 0; i < energy.bins.size(); i++) {
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for (int j = 0; j < energy.bins.at(i).size(); j++) {
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double x = (static_cast<double>(i) + 0.5) * (energy.Xhi - energy.Xlo)
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/ static_cast<double>(energy.bins.size()) + energy.Xlo;
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double y = (static_cast<double>(j) + 0.5) * (energy.Yhi - energy.Ylo)
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/ static_cast<double>(energy.bins.at(i).size()) + energy.Ylo;
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double nu = mdef->fit_fcn(x, y, xval) * XbinSize * YbinSize;
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double sig_cut = 1.0e-5;
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if (fabs(mdef->chisquare_error(energy.bins.at(i).at(j))) > sig_cut || !ignorezero_) {
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chisquare += pow(energy.bins.at(i).at(j) - nu, 2.0)
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/ pow(mdef->chisquare_error(energy.bins.at(i).at(j)), 2.0);
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}
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else {
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chisquare += pow(energy.bins.at(i).at(j) - nu, 2.0)
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/ pow(sig_cut, 2.0);
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}
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}
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}
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// add errors due to Gaussians outside histogram
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double eps = 0.01; // accuracy set for this function
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for (int i = 0; i < mdef->get_ngauss(); i++) {
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double *pval = xval+i*(mdef->get_formula()->GetNpar());
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double par_x = pval[mdef->get_indiv_max_x()];
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double par_y = pval[mdef->get_indiv_max_y()];
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double par_sig = pval[3];
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double cutoff_rad = sqrt(-log(eps * 2.0 * PI * par_sig * par_sig
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/ pval[0]) * 2.0 * par_sig * par_sig);
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bool left = par_x < energy.Xlo + cutoff_rad;
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bool right = par_x > energy.Xhi - cutoff_rad;
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bool top = par_y > energy.Yhi - cutoff_rad;
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bool bottom = par_y < energy.Ylo + cutoff_rad;
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if (left) {
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double xlo = par_x - cutoff_rad;
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double xhi = energy.Xlo;
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double ylo = energy.Ylo;
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double yhi = energy.Yhi;
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chisquare += 2.0*mdef->formula_int(xlo, xhi, ylo, yhi, pval,
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XbinSize, YbinSize, xval);
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}
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if (right) {
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double xlo = energy.Xhi;
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double xhi = par_x + cutoff_rad;
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double ylo = energy.Ylo;
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double yhi = energy.Yhi;
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chisquare += 2.0*mdef->formula_int(xlo, xhi, ylo, yhi, pval,
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XbinSize, YbinSize, xval);
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}
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if (top) {
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double xlo = left ? par_x - cutoff_rad : energy.Xlo;
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double xhi = right ? par_x + cutoff_rad : energy.Xhi;
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double ylo = energy.Yhi;
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double yhi = par_y + cutoff_rad;
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chisquare += 2.0*mdef->formula_int(xlo, xhi, ylo, yhi, pval,
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XbinSize, YbinSize, xval);
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}
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if (bottom) {
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double xlo = left ? par_x - cutoff_rad : energy.Xlo;
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double xhi = right ? par_x + cutoff_rad : energy.Xhi;
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double ylo = par_y - cutoff_rad;
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double yhi = energy.Ylo;
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chisquare += 2.0*mdef->formula_int(xlo, xhi, ylo, yhi, pval,
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XbinSize, YbinSize, xval);
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}
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}
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fcnval = chisquare;
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}
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catch (exception ex) {
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cerr << "Exception in jetfit::fcn" << endl;
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}
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| 218 |
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}
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| 220 |
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TFormula * JetFitAnalyzer::ModelDefinition::get_formula() {
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return indiv_formula;
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}
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| 224 |
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void JetFitAnalyzer::ModelDefinition::set_formula(TFormula *new_formula) {
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| 225 |
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indiv_formula = new_formula;
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}
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| 227 |
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| 228 |
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void JetFitAnalyzer::ModelDefinition::get_indiv_par(int i, string &name, double &start, double &step,
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double &lo, double &hi) {
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| 230 |
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try {
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| 231 |
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name = indiv_par_names.at(i);
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start = indiv_par_starts.at(i);
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step = indiv_par_start_steps.at(i);
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lo = indiv_par_lo.at(i);
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hi = indiv_par_hi.at(i);
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} catch (exception ex) {
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| 237 |
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cerr << "exception in jetfit::ModelDefinition::get_indiv_par" << endl;
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| 238 |
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}
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| 239 |
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}
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| 240 |
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| 241 |
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void JetFitAnalyzer::ModelDefinition::set_indiv_par(int i, string name, double start, double step,
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double lo, double hi) {
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| 243 |
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if (indiv_par_names.size() < i+1) {
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| 244 |
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indiv_par_names.resize(i+1);
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| 245 |
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indiv_par_starts.resize(i+1);
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| 246 |
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indiv_par_start_steps.resize(i+1);
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| 247 |
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indiv_par_lo.resize(i+1);
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| 248 |
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indiv_par_hi.resize(i+1);
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| 249 |
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}
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| 250 |
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try {
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| 251 |
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indiv_par_names.at(i) = name;
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| 252 |
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indiv_par_starts.at(i) = start;
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| 253 |
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indiv_par_start_steps.at(i) = step;
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| 254 |
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indiv_par_lo.at(i) = lo;
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| 255 |
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indiv_par_hi.at(i) = hi;
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| 256 |
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}
|
| 257 |
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catch (exception ex) {
|
| 258 |
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cerr << "exception in jetfit::ModelDefinition::set_indiv_par" << endl;
|
| 259 |
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}
|
| 260 |
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}
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| 261 |
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| 262 |
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int JetFitAnalyzer::ModelDefinition::get_indiv_max_E() {
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| 263 |
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return indiv_max_E;
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| 264 |
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}
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| 265 |
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| 266 |
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void JetFitAnalyzer::ModelDefinition::set_indiv_max_E(int _new_max_E) {
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| 267 |
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indiv_max_E = _new_max_E;
|
| 268 |
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}
|
| 269 |
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| 270 |
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int JetFitAnalyzer::ModelDefinition::get_indiv_max_x() {
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| 271 |
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return indiv_max_x;
|
| 272 |
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}
|
| 273 |
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| 274 |
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void JetFitAnalyzer::ModelDefinition::set_indiv_max_x(int new_max_x) {
|
| 275 |
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indiv_max_x = new_max_x;
|
| 276 |
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}
|
| 277 |
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| 278 |
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int JetFitAnalyzer::ModelDefinition::get_indiv_max_y() {
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| 279 |
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return indiv_max_y;
|
| 280 |
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}
|
| 281 |
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| 282 |
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void JetFitAnalyzer::ModelDefinition::set_indiv_max_y(int new_max_y) {
|
| 283 |
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indiv_max_y = new_max_y;
|
| 284 |
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}
|
| 285 |
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| 286 |
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unsigned JetFitAnalyzer::ModelDefinition::get_n_special_par_sets() {
|
| 287 |
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return special_par_starts.size();
|
| 288 |
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}
|
| 289 |
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|
| 290 |
|
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void JetFitAnalyzer::ModelDefinition::get_special_par(int g, int i, double &pstart,
|
| 291 |
|
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double &perr, double &plo, double &phi) {
|
| 292 |
|
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try {
|
| 293 |
|
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pstart = special_par_starts.at(g).at(i);
|
| 294 |
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perr = special_par_start_steps.at(g).at(i);
|
| 295 |
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plo = special_par_lo.at(g).at(i);
|
| 296 |
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phi = special_par_hi.at(g).at(i);
|
| 297 |
|
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} catch (exception ex) {
|
| 298 |
|
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cerr << "Exception in ModelDefinition::get_special_par" << endl;
|
| 299 |
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}
|
| 300 |
|
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}
|
| 301 |
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|
| 302 |
|
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void JetFitAnalyzer::ModelDefinition::set_special_par(int g, int i, double pstart,
|
| 303 |
|
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double perr, double plo, double phi) {
|
| 304 |
|
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if (g+1 > special_par_starts.size()) {
|
| 305 |
|
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special_par_starts.resize(g+1);
|
| 306 |
|
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special_par_start_steps.resize(g+1);
|
| 307 |
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special_par_lo.resize(g+1);
|
| 308 |
|
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special_par_hi.resize(g+1);
|
| 309 |
|
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}
|
| 310 |
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| 311 |
|
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try {
|
| 312 |
|
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if (i+1 > special_par_starts.at(g).size()) {
|
| 313 |
|
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special_par_starts.at(g).resize(i+1);
|
| 314 |
|
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special_par_start_steps.at(g).resize(i+1);
|
| 315 |
|
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special_par_lo.at(g).resize(i+1);
|
| 316 |
|
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special_par_hi.at(g).resize(i+1);
|
| 317 |
|
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}
|
| 318 |
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| 319 |
|
|
special_par_starts.at(g).at(i) = pstart;
|
| 320 |
|
|
special_par_start_steps.at(g).at(i) = perr;
|
| 321 |
|
|
special_par_lo.at(g).at(i) = plo;
|
| 322 |
|
|
special_par_hi.at(g).at(i) = phi;
|
| 323 |
|
|
}
|
| 324 |
|
|
catch (exception ex) {
|
| 325 |
|
|
cerr << "exception in jetfit::ModelDefinition::set_special_par" << endl;
|
| 326 |
|
|
}
|
| 327 |
|
|
}
|
| 328 |
|
|
|
| 329 |
|
|
void JetFitAnalyzer::fill_histo_with_vec(TH2 *hist, vector< vector<double> > &vec) {
|
| 330 |
|
|
for (int i = 0; i < vec.size(); i++) {
|
| 331 |
|
|
for (int j = 0; j < vec[i].size(); j++) {
|
| 332 |
|
|
hist->SetBinContent(i+1, j+1, vec[i][j]);
|
| 333 |
|
|
}
|
| 334 |
|
|
}
|
| 335 |
|
|
}
|
| 336 |
|
|
|
| 337 |
|
|
void JetFitAnalyzer::ModelDefinition::par_init(TH2 *hist, TMinuit *gMinuit, vector<TString> &pars,
|
| 338 |
|
|
double *pval, double *perr, double *plo, double *phi,
|
| 339 |
|
|
int npar, FitResults r) {
|
| 340 |
|
|
int npar1 = npar - get_formula()->GetNpar();
|
| 341 |
|
|
bool init_spec_pars = false;
|
| 342 |
|
|
if (ngauss <= get_n_special_par_sets()) {
|
| 343 |
|
|
init_spec_pars = true;
|
| 344 |
|
|
for (int k = 0; k < ngauss; k++) {
|
| 345 |
|
|
int ipar0 = k*get_formula()->GetNpar(); // index of indiv par 0
|
| 346 |
|
|
for (int l = 0; l < get_formula()->GetNpar(); l++) {
|
| 347 |
|
|
int ipar = ipar0 + l;
|
| 348 |
|
|
if (ipar < npar)
|
| 349 |
|
|
get_special_par(k, l, pval[ipar], perr[ipar], plo[ipar],
|
| 350 |
|
|
phi[ipar]);
|
| 351 |
|
|
else
|
| 352 |
|
|
cerr << "WARNING: Attempt to set parameter out of index range!"
|
| 353 |
|
|
<< endl;
|
| 354 |
|
|
}
|
| 355 |
|
|
}
|
| 356 |
|
|
}
|
| 357 |
|
|
else {
|
| 358 |
|
|
double XbinSize = (energy.Xhi - energy.Xlo)
|
| 359 |
|
|
/ static_cast<double>(energy.bins.size());
|
| 360 |
|
|
double YbinSize = (energy.Xhi - energy.Xlo)
|
| 361 |
|
|
/ static_cast<double>(energy.bins.at(0).size());
|
| 362 |
|
|
vector< vector<double> > sub_energy(energy.bins.size());
|
| 363 |
|
|
double max_sub, max_x = 0.0, max_y = 0.0;
|
| 364 |
|
|
double pval_other[256];
|
| 365 |
|
|
max_sub = -(numeric_limits<double>::max());
|
| 366 |
|
|
for (int i = 0; i < energy.bins.size(); i++) {
|
| 367 |
|
|
sub_energy[i].resize(energy.bins[i].size());
|
| 368 |
|
|
for (int j = 0; j < energy.bins[i].size(); j++) {
|
| 369 |
|
|
double x = static_cast<double>(i)*(energy.Xhi - energy.Xlo)
|
| 370 |
|
|
/ static_cast<double>(energy.bins.size()) + energy.Xlo;
|
| 371 |
|
|
double y = static_cast<double>(j)*(energy.Yhi - energy.Ylo)
|
| 372 |
|
|
/ static_cast<double>(energy.bins[i].size()) + energy.Ylo;
|
| 373 |
|
|
if (ngauss > 1) {
|
| 374 |
|
|
// subtract integral of fit function
|
| 375 |
|
|
try {
|
| 376 |
|
|
int npval_other = r.pval.at(r.pval.size()-1).size();
|
| 377 |
|
|
if (npval_other > 256) {
|
| 378 |
|
|
cerr << "Parameter overload" << endl;
|
| 379 |
|
|
return;
|
| 380 |
|
|
}
|
| 381 |
|
|
for (int k = 0; k < npval_other; k++) {
|
| 382 |
|
|
pval_other[k] = r.pval[r.pval.size()-1][k];
|
| 383 |
|
|
}
|
| 384 |
|
|
ngauss--;
|
| 385 |
|
|
double nu = fit_fcn(x, y, pval_other) * XbinSize * YbinSize;
|
| 386 |
|
|
ngauss++;
|
| 387 |
|
|
sub_energy[i][j] = energy.bins[i][j] - nu;
|
| 388 |
|
|
}
|
| 389 |
|
|
catch (exception ex) {
|
| 390 |
|
|
cerr << "Exception in par_init" << endl;
|
| 391 |
|
|
}
|
| 392 |
|
|
}
|
| 393 |
|
|
else {
|
| 394 |
|
|
sub_energy[i][j] = energy.bins[i][j];
|
| 395 |
|
|
}
|
| 396 |
|
|
}
|
| 397 |
|
|
}
|
| 398 |
|
|
TH2D *hist_sub = new TH2D("hist_sub", "Subtracted histo",
|
| 399 |
|
|
sub_energy.size(), energy.Xlo,
|
| 400 |
|
|
energy.Xhi,
|
| 401 |
|
|
sub_energy[0].size(), energy.Ylo,
|
| 402 |
|
|
energy.Yhi);
|
| 403 |
|
|
fill_histo_with_vec(hist_sub, sub_energy);
|
| 404 |
|
|
max_sub = 0.0;
|
| 405 |
|
|
max_x = 0.0;
|
| 406 |
|
|
max_y = 0.0;
|
| 407 |
|
|
for (int i = 1; i <= hist_sub->GetXaxis()->GetNbins(); i++) {
|
| 408 |
|
|
for (int j = 1; j <= hist_sub->GetYaxis()->GetNbins(); j++) {
|
| 409 |
|
|
double nu = energy.bins[i-1][j-1] - sub_energy[i-1][j-1];
|
| 410 |
|
|
if (hist_sub->GetBinContent(i, j)
|
| 411 |
|
|
- 3.0*pow(chisquare_error(nu), 2.0) > max_sub) {
|
| 412 |
|
|
max_sub = hist_sub->GetBinContent(i, j);
|
| 413 |
|
|
max_x = static_cast<double>(i-1)*XbinSize
|
| 414 |
|
|
+ hist_sub->GetXaxis()->GetXmin();
|
| 415 |
|
|
max_y = static_cast<double>(j-1)*YbinSize
|
| 416 |
|
|
+ hist_sub->GetYaxis()->GetXmin();
|
| 417 |
|
|
}
|
| 418 |
|
|
}
|
| 419 |
|
|
}
|
| 420 |
|
|
|
| 421 |
|
|
for (int i = npar1; i < npar; i++) {
|
| 422 |
|
|
if (get_indiv_max_E() == i - npar1) {
|
| 423 |
|
|
pval[i] = max_sub / XbinSize / YbinSize;
|
| 424 |
|
|
perr[i] = mdef->chisquare_error(pval[i])*0.5;
|
| 425 |
|
|
plo[i] = 0.0;
|
| 426 |
|
|
phi[i] = 1.0e6;
|
| 427 |
|
|
}
|
| 428 |
|
|
else if (get_indiv_max_x() == i - npar1) {
|
| 429 |
|
|
pval[i] = max_x;
|
| 430 |
|
|
perr[i] = (energy.Xhi - energy.Xlo) / static_cast<double>(hist->GetXaxis()->GetNbins());
|
| 431 |
|
|
plo[i] = 0.0;
|
| 432 |
|
|
phi[i] = 0.0;
|
| 433 |
|
|
}
|
| 434 |
|
|
else if (get_indiv_max_y() == i - npar1) {
|
| 435 |
|
|
pval[i] = max_y;
|
| 436 |
|
|
perr[i] = (energy.Yhi - energy.Ylo) / static_cast<double>(hist->GetYaxis()->GetNbins());
|
| 437 |
|
|
plo[i] = 0.0;
|
| 438 |
|
|
phi[i] = 0.0;
|
| 439 |
|
|
}
|
| 440 |
|
|
else {
|
| 441 |
|
|
string dummy;
|
| 442 |
|
|
get_indiv_par(i-npar1, dummy, pval[i], perr[i], plo[i], phi[i]);
|
| 443 |
|
|
}
|
| 444 |
|
|
}
|
| 445 |
|
|
}
|
| 446 |
|
|
int n_pars_to_set = init_spec_pars ? ngauss*get_formula()->GetNpar()
|
| 447 |
|
|
: npar - npar1;
|
| 448 |
|
|
int init_par_to_set = init_spec_pars ? 0 : npar1;
|
| 449 |
|
|
for (int i = 0; i < n_pars_to_set; i++) {
|
| 450 |
|
|
double dummy;
|
| 451 |
|
|
string s;
|
| 452 |
|
|
int ipar = i + init_par_to_set;
|
| 453 |
|
|
get_indiv_par(i % get_formula()->GetNpar(), s,
|
| 454 |
|
|
dummy, dummy, dummy, dummy);
|
| 455 |
|
|
ostringstream par_oss;
|
| 456 |
|
|
par_oss << s << ipar / (get_formula()->GetNpar()) << flush;
|
| 457 |
|
|
try {
|
| 458 |
|
|
pars.at(ipar) = TString(par_oss.str());
|
| 459 |
|
|
}
|
| 460 |
|
|
catch (exception ex) {
|
| 461 |
|
|
cerr << "exception 2 in par_init" << endl;
|
| 462 |
|
|
}
|
| 463 |
|
|
int error_flag;
|
| 464 |
|
|
try {
|
| 465 |
|
|
gMinuit->mnparm(ipar, pars.at(ipar),
|
| 466 |
|
|
pval[ipar], perr[ipar], plo[ipar], phi[ipar], error_flag);
|
| 467 |
|
|
} catch (exception ex) {
|
| 468 |
|
|
cerr << "exception 3 in par_init" << endl;
|
| 469 |
|
|
}
|
| 470 |
|
|
}
|
| 471 |
|
|
}
|
| 472 |
|
|
|
| 473 |
|
|
FitResults JetFitAnalyzer::fit_histo(TH2 *hist, vector<trouble> &t_vec,
|
| 474 |
|
|
void (*cc_minuit)(TMinuit *, TH2 *, int),
|
| 475 |
|
|
int start_ngauss,
|
| 476 |
|
|
int rebinX, int rebinY,
|
| 477 |
|
|
double P_cutoff_val) {
|
| 478 |
|
|
TMinuit *gMinuit = new TMinuit();
|
| 479 |
|
|
int npar_indiv = mdef->get_formula()->GetNpar();
|
| 480 |
|
|
int istat, erflg;
|
| 481 |
|
|
FitResults r;
|
| 482 |
|
|
|
| 483 |
|
|
gMinuit->SetFCN(fcn);
|
| 484 |
|
|
gMinuit->mninit(5, 6, 7);
|
| 485 |
|
|
|
| 486 |
|
|
// set error def and machine accuracy
|
| 487 |
|
|
double cs_err_def = 1.0;
|
| 488 |
|
|
double fcn_eps = 0.2;
|
| 489 |
|
|
gMinuit->mnexcm("SET ERR", &cs_err_def, 1, erflg);
|
| 490 |
|
|
gMinuit->mnexcm("SET EPS", &fcn_eps, 1, erflg);
|
| 491 |
|
|
|
| 492 |
|
|
// rebin histogram
|
| 493 |
|
|
TH2 *hist_rebinned;
|
| 494 |
|
|
if (rebinX_ > 1 && rebinY_ > 1)
|
| 495 |
|
|
hist_rebinned = hist->Rebin2D(rebinX_, rebinY_);
|
| 496 |
|
|
else
|
| 497 |
|
|
hist_rebinned = hist;
|
| 498 |
|
|
|
| 499 |
|
|
r.hist_rebinned = hist_rebinned;
|
| 500 |
|
|
// load histogram into energies vector
|
| 501 |
|
|
energy.bins.resize(hist_rebinned->GetXaxis()->GetNbins());
|
| 502 |
|
|
for (int i = 0; i < energy.bins.size(); i++) {
|
| 503 |
|
|
energy.bins[i].resize(hist_rebinned->GetYaxis()->GetNbins());
|
| 504 |
|
|
for (int j = 0; j < energy.bins[i].size(); j++) {
|
| 505 |
|
|
energy.bins[i][j] = hist_rebinned->GetBinContent(i+1, j+1);
|
| 506 |
|
|
}
|
| 507 |
|
|
}
|
| 508 |
|
|
|
| 509 |
|
|
energy.Xlo = hist->GetXaxis()->GetXmin();
|
| 510 |
|
|
energy.Xhi = hist->GetXaxis()->GetXmax();
|
| 511 |
|
|
energy.Ylo = hist->GetYaxis()->GetXmin();
|
| 512 |
|
|
energy.Yhi = hist->GetYaxis()->GetXmax();
|
| 513 |
|
|
|
| 514 |
|
|
if (start_ngauss < 1) {
|
| 515 |
|
|
start_ngauss = 1;
|
| 516 |
|
|
}
|
| 517 |
|
|
|
| 518 |
|
|
for (mdef->set_ngauss(start_ngauss);
|
| 519 |
|
|
mdef->get_ngauss() <=
|
| 520 |
|
|
(MAX_GAUSS > start_ngauss ? MAX_GAUSS : start_ngauss);
|
| 521 |
|
|
mdef->set_ngauss(mdef->get_ngauss()+1)) {
|
| 522 |
|
|
|
| 523 |
|
|
int ngauss = mdef->get_ngauss();
|
| 524 |
|
|
t_vec.resize(t_vec.size() + 1);
|
| 525 |
|
|
int npar = npar_indiv*mdef->get_ngauss();
|
| 526 |
|
|
double pval[256], perr[256], plo[256], phi[256];
|
| 527 |
|
|
if (npar > 256) {
|
| 528 |
|
|
cerr << "Parameter overload" << endl;
|
| 529 |
|
|
return r;
|
| 530 |
|
|
}
|
| 531 |
|
|
vector<TString> pars(npar);
|
| 532 |
|
|
|
| 533 |
|
|
// initialize parameters
|
| 534 |
|
|
mdef->par_init(hist, gMinuit, pars, pval, perr, plo, phi, npar, r);
|
| 535 |
|
|
|
| 536 |
|
|
// minimize
|
| 537 |
|
|
double chisquare, edm, errdef;
|
| 538 |
|
|
int nvpar, nparx;
|
| 539 |
|
|
trouble t;
|
| 540 |
|
|
t.occ = T_NULL;
|
| 541 |
|
|
t.istat = 3;
|
| 542 |
|
|
// fix sigmas of the Gaussians
|
| 543 |
|
|
for (int i = 0; i < ngauss; i++) {
|
| 544 |
|
|
double parno[2];
|
| 545 |
|
|
parno[0] = i*npar_indiv + 4;
|
| 546 |
|
|
gMinuit->mnexcm("FIX", parno, 1, erflg);
|
| 547 |
|
|
}
|
| 548 |
|
|
gMinuit->mnexcm("SIMPLEX", 0, 0, erflg);
|
| 549 |
|
|
gMinuit->mnexcm("MIGRAD", 0, 0, erflg);
|
| 550 |
|
|
gMinuit->mnstat(chisquare, edm, errdef, nvpar, nparx, istat);
|
| 551 |
|
|
if (istat == 3) {
|
| 552 |
|
|
/* we're not concerned about MINOS errors right now
|
| 553 |
|
|
gMinuit->mnexcm("MINOS", 0, 0, erflg);
|
| 554 |
|
|
gMinuit->mnstat(chisquare, edm, errdef, nvpar, nparx, istat);
|
| 555 |
|
|
if (istat != 3) {
|
| 556 |
|
|
t.occ = T_MINOS;
|
| 557 |
|
|
t.istat = istat;
|
| 558 |
|
|
}
|
| 559 |
|
|
*/
|
| 560 |
|
|
}
|
| 561 |
|
|
else {
|
| 562 |
|
|
t.occ = T_MIGRAD;
|
| 563 |
|
|
t.istat = istat;
|
| 564 |
|
|
}
|
| 565 |
|
|
|
| 566 |
|
|
try {
|
| 567 |
|
|
if (t_vec.size() < ngauss) {
|
| 568 |
|
|
t_vec.resize(ngauss);
|
| 569 |
|
|
}
|
| 570 |
|
|
t_vec.at(ngauss-1) = t;
|
| 571 |
|
|
}
|
| 572 |
|
|
catch (exception ex) {
|
| 573 |
|
|
cerr << "exception in fit_histo" << endl;
|
| 574 |
|
|
}
|
| 575 |
|
|
|
| 576 |
|
|
// put parameters in map
|
| 577 |
|
|
for (int i = 0; i < npar && i < 256; i++) {
|
| 578 |
|
|
int iuint; // internal parameter number
|
| 579 |
|
|
gMinuit->mnpout(i, pars[i], pval[i], perr[i], plo[i], phi[i], iuint);
|
| 580 |
|
|
}
|
| 581 |
|
|
vector<double> pval_copy(npar);
|
| 582 |
|
|
vector<double> perr_copy(npar);
|
| 583 |
|
|
vector<double> plo_copy(npar);
|
| 584 |
|
|
vector<double> phi_copy(npar);
|
| 585 |
|
|
for (int i = 0; i < npar && i < 256; i++) {
|
| 586 |
|
|
pval_copy[i] = pval[i];
|
| 587 |
|
|
perr_copy[i] = perr[i];
|
| 588 |
|
|
plo_copy[i] = plo[i];
|
| 589 |
|
|
phi_copy[i] = phi[i];
|
| 590 |
|
|
}
|
| 591 |
|
|
r.pars.push_back(pars);
|
| 592 |
|
|
r.pval.push_back(pval_copy);
|
| 593 |
|
|
r.perr.push_back(perr_copy);
|
| 594 |
|
|
r.plo.push_back(plo_copy);
|
| 595 |
|
|
r.phi.push_back(phi_copy);
|
| 596 |
|
|
|
| 597 |
|
|
// execute user minuit code
|
| 598 |
|
|
if (cc_minuit != 0)
|
| 599 |
|
|
(*cc_minuit)(gMinuit, hist_rebinned, ngauss);
|
| 600 |
|
|
|
| 601 |
|
|
int ndof = 0;
|
| 602 |
|
|
if (!ignorezero)
|
| 603 |
|
|
ndof = energy.bins.size() * energy.bins[0].size();
|
| 604 |
|
|
else {
|
| 605 |
|
|
for (int i = 0; i < energy.bins.size(); i++) {
|
| 606 |
|
|
for (int j = 0; j < energy.bins[i].size(); j++) {
|
| 607 |
|
|
if (energy.bins[i][j] > 1.0e-30)
|
| 608 |
|
|
ndof++;
|
| 609 |
|
|
}
|
| 610 |
|
|
}
|
| 611 |
|
|
}
|
| 612 |
|
|
ndof -= npar;
|
| 613 |
|
|
|
| 614 |
|
|
r.chisquare.push_back(chisquare);
|
| 615 |
|
|
double P = TMath::Prob(chisquare, ndof);
|
| 616 |
|
|
if (P > P_cutoff_val) {
|
| 617 |
|
|
break;
|
| 618 |
|
|
}
|
| 619 |
|
|
}
|
| 620 |
|
|
|
| 621 |
|
|
delete gMinuit;
|
| 622 |
|
|
return r;
|
| 623 |
|
|
}
|
| 624 |
dnisson |
1.1 |
|
| 625 |
|
|
JetFitAnalyzer::JetFitAnalyzer(const edm::ParameterSet& iConfig)
|
| 626 |
|
|
: user_minuit(0)
|
| 627 |
|
|
{
|
| 628 |
|
|
// get parameters from iConfig
|
| 629 |
|
|
ignorezero_ = iConfig.getUntrackedParameter("ignorezero", false);
|
| 630 |
|
|
rebinX_ = iConfig.getUntrackedParameter("rebinX", 1);
|
| 631 |
|
|
rebinY_ = iConfig.getUntrackedParameter("rebinY", 1);
|
| 632 |
|
|
P_cutoff_val_ = iConfig.getUntrackedParameter("P_cutoff_val", 0.5);
|
| 633 |
|
|
|
| 634 |
|
|
jetfit::set_ignorezero(ignorezero_);
|
| 635 |
|
|
}
|
| 636 |
|
|
|
| 637 |
|
|
|
| 638 |
|
|
JetFitAnalyzer::~JetFitAnalyzer()
|
| 639 |
|
|
{
|
| 640 |
|
|
|
| 641 |
|
|
// do anything here that needs to be done at desctruction time
|
| 642 |
|
|
// (e.g. close files, deallocate resources etc.)
|
| 643 |
|
|
|
| 644 |
|
|
}
|
| 645 |
|
|
|
| 646 |
|
|
|
| 647 |
|
|
//
|
| 648 |
|
|
// member functions
|
| 649 |
|
|
//
|
| 650 |
|
|
|
| 651 |
|
|
// ------------ method called to for each event ------------
|
| 652 |
|
|
void
|
| 653 |
|
|
JetFitAnalyzer::analyze(const edm::Event& iEvent, const edm::EventSetup& iSetup)
|
| 654 |
|
|
{
|
| 655 |
|
|
using namespace edm;
|
| 656 |
|
|
|
| 657 |
dnisson |
1.4 |
std::vector<jetfit::trouble> t;
|
| 658 |
dnisson |
1.1 |
|
| 659 |
|
|
TH2D *histo = make_histo(iEvent, iSetup);
|
| 660 |
dnisson |
1.2 |
if (histo != 0) {
|
| 661 |
dnisson |
1.6 |
jetfit::ModelDefinition &_mdef = make_model_def(iEvent, iSetup, histo);
|
| 662 |
dnisson |
1.5 |
jetfit::results r(fit_histo(histo, t, user_minuit,
|
| 663 |
|
|
_mdef.get_n_special_par_sets(),
|
| 664 |
|
|
rebinX_, rebinY_, P_cutoff_val_));
|
| 665 |
dnisson |
1.2 |
analyze_results(r, t, histo);
|
| 666 |
|
|
}
|
| 667 |
|
|
else {
|
| 668 |
dnisson |
1.3 |
std::cerr << "Fitting not performed" << std::endl;
|
| 669 |
dnisson |
1.2 |
}
|
| 670 |
dnisson |
1.1 |
}
|
| 671 |
|
|
|
| 672 |
|
|
|
| 673 |
|
|
// ------------ method called once each job just before starting event loop ------------
|
| 674 |
|
|
void
|
| 675 |
|
|
JetFitAnalyzer::beginJob(const edm::EventSetup&)
|
| 676 |
|
|
{
|
| 677 |
|
|
}
|
| 678 |
|
|
|
| 679 |
|
|
// ------------ method called once each job just after ending the event loop ------------
|
| 680 |
|
|
void
|
| 681 |
|
|
JetFitAnalyzer::endJob() {
|
| 682 |
|
|
}
|
| 683 |
|
|
|
| 684 |
|
|
//define this as a plug-in
|
| 685 |
|
|
// this is a base class-we can't do this DEFINE_FWK_MODULE(JetFitAnalyzer);
|
