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Comparing UserCode/JetFitAnalyzer/test/JetFinderAnalyzer.cc (file contents):
Revision 1.1 by dnisson, Wed Sep 2 21:48:13 2009 UTC vs.
Revision 1.27 by dnisson, Fri Jan 22 23:53:10 2010 UTC

#	Line 1 | Line 1
1	<	/* A simple jet-finding analyzer */
1	>	/* A JetFitAnalyzer that makes histograms with smearing */
2
3		#include "UserCode/JetFitAnalyzer/interface/JetFitAnalyzer.h"
4
5	–	#include "SimDataFormats/HepMCProduct/interface/HepMCProduct.h"
6	–	#include "fastjet/ClusterSequence.hh"
5		#include "FWCore/ServiceRegistry/interface/Service.h"
6	+	#include "FWCore/MessageLogger/interface/MessageLogger.h"
7		#include "PhysicsTools/UtilAlgos/interface/TFileService.h"
8
9	<	#include <map>
11	<	#include <vector>
12	<	#include <limits>
13	<	#include <cmath>
14	<	#include <cstdlib>
15	<	#include <fstream>
9	>	#include <iostream>
10		#include <sstream>
11
18	–	#include "TFormula.h"
12		#include "TF2.h"
13	+	#include "TNtuple.h"
14
15		#define PI 3.141593
16
17		using namespace std;
24	–	using namespace fastjet;
18
19		class JetFinderAnalyzer : public JetFitAnalyzer {
20		public:
28	–	struct jet {
29	–	double energy;
30	–	double eta;
31	–	double phi;
32	–	};
33	–
21		explicit JetFinderAnalyzer( const edm::ParameterSet&);
22		~JetFinderAnalyzer() {}
23
24		private:
25	<	static map<TH2 *, vector< vector<jet> > > unique_jets;
26	<
27	<	static double phi_cutoff_;
41	<
42	<	static double g2int(double xlo, double xhi, double ylo, double yhi,
43	<	double *pval) {
44	<	double sum1 = 0.0;
45	<	double sum2 = 0.0;
46	<	double xmid = 0.5 * (xlo + xhi);
47	<	double ymid = 0.5 * (ylo + yhi);
48	<	double xstep = (xhi - xlo) / 50.0;
49	<	double ystep = (yhi - ylo) / 50.0;
50	<	for (int i = 0; i < 50; i++) {
51	<	double x = (static_cast<double>(i) + 0.5) * xstep + xlo;
52	<	sum1 += xstep * jetfit::fit_fcn(x, ymid, pval);
53	<	}
54	<	for (int i = 0; i < 50; i++) {
55	<	double y = (static_cast<double>(i) + 0.5) * ystep + ylo;
56	<	sum2 += ystep * jetfit::fit_fcn(xmid, y, pval);
57	<	}
58	<	return sum1 * sum2;
59	<	}
60	<
61	<	static void jetfinder(TMinuit *gMinuit, TH2 *hist, int ngauss) {
62	<	double dist_sq = numeric_limits<double>::infinity();
63	<	unique_jets[hist].resize(ngauss);
64	<	int nbinsX = hist->GetXaxis()->GetNbins();
65	<	int nbinsY = hist->GetYaxis()->GetNbins();
66	<	double XbinSize = (hist->GetXaxis()->GetXmax()
67	<	- hist->GetXaxis()->GetXmin())
68	<	/ static_cast<double>(nbinsX);
69	<	double YbinSize = (hist->GetYaxis()->GetXmax()
70	<	- hist->GetYaxis()->GetXmin())
71	<	/ static_cast<double>(nbinsY);
72	<	for (int i = 0; i < ngauss; i++) {
73	<	double N, mu_x, mu_y, sig, err, lo, hi;
74	<	int iuint;
75	<	TString name;
76	<	gMinuit->mnpout(4*i, name, N, err, lo, hi, iuint);
77	<	gMinuit->mnpout(4*i + 1, name, mu_x, err, lo, hi, iuint);
78	<	gMinuit->mnpout(4*i + 2, name, mu_y, err, lo, hi, iuint);
79	<	gMinuit->mnpout(4*i + 3, name, sig, err, lo, hi, iuint);
80	<	for (int j = 0; j < i; j++) {
81	<	double N2, mu_x2, mu_y2, sig2;
82	<	gMinuit->mnpout(4*j, name, N2, err, lo, hi, iuint);
83	<	gMinuit->mnpout(4*j + 1, name, mu_x2, err, lo, hi, iuint);
84	<	gMinuit->mnpout(4*j + 2, name, mu_y2, err, lo, hi, iuint);
85	<	gMinuit->mnpout(4*j + 3, name, sig2, err, lo, hi, iuint);
86	<	double _dist_sq = (mu_x2 - mu_x)*(mu_x2 - mu_x)
87	<	+ (mu_y2 - mu_y)*(mu_y2 - mu_y);
88	<	if (_dist_sq < dist_sq)
89	<	dist_sq = _dist_sq;
90	<	}
91	<
92	<	jet j;
93	<	j.energy = N;
94	<	j.eta = mu_x; j.phi = mu_y;
95	<	unique_jets[hist][ngauss-1].push_back(j);
96	<	}
97	<	}
98	<
99	<	virtual void beginJob(const edm::EventSetup&);
100	<	virtual TH2D* make_histo(const edm::Event&, const edm::EventSetup&);
101	<	virtual jetfit::model_def& make_model_def(const edm::Event&,
102	<	const edm::EventSetup&,
103	<	TH2 *);
104	<	virtual void analyze_results(jetfit::results r,
105	<	std::vector<jetfit::trouble> t, TH2 *);
106	<
107	<	fstream ofs;
108	<	double smear_;
109	<	int smear_coord_;
25	>	virtual void beginJob(const edm::EventSetup &es);
26	>	virtual void analyze_results(HistoFitter::FitResults, std::vector<HistoFitter::Trouble>,
27	>	TH2 *);
28		};
29
112	–	map<TH2 *, vector< vector< JetFinderAnalyzer::jet > > >
113	–	JetFinderAnalyzer::unique_jets;
114	–
30		JetFinderAnalyzer::JetFinderAnalyzer(const edm::ParameterSet &pSet)
31		: JetFitAnalyzer(pSet) // this is important!
32		{
118	–	smear_ = pSet.getUntrackedParameter("smear", 0.02);
119	–	smear_coord_ = pSet.getUntrackedParameter("smear_coord", 0);
120	–	// 0 = eta-phi smear
121	–	// 1 = proper angle smear
122	–	set_user_minuit(jetfinder);
123	–	}
124	–
125	–	TH2D * JetFinderAnalyzer::make_histo(const edm::Event &evt, const edm::EventSetup&) {
126	–	ostringstream oss;
127	–	oss << "eta_phi_energy_unred"<<evt.id().event() << flush;
128	–	TH2D *unred_histo = new TH2D(oss.str().c_str(), oss.str().c_str(),
129	–	600, -2.5, 2.5, 600, -PI, PI);
130	–
131	–	// fill unreduced histo
132	–	edm::Handle<edm::HepMCProduct> hRaw;
133	–	evt.getByLabel("source",
134	–	hRaw);
135	–	vector<HepMC::GenParticle *> particles;
136	–	const HepMC::GenEvent *hmcEvt = hRaw->GetEvent();
137	–	for (HepMC::GenEvent::particle_const_iterator
138	–	pit = hmcEvt->particles_begin(); pit != hmcEvt->particles_end();
139	–	pit++) {
140	–	if ((*pit)->status() == 1) {
141	–	particles.push_back(*pit);
142	–	}
143	–	}
144	–
145	–	for (int i = 0; i < particles.size(); i++) {
146	–	unred_histo->Fill(particles[i]->momentum().eta(),
147	–	particles[i]->momentum().phi(),
148	–	particles[i]->momentum().e());
149	–	}
150	–
151	–	// reduce histo
152	–	ostringstream oss2;
153	–	oss2 << "eta_phi_energy_red"<<evt.id().event() << flush;
154	–	edm::Service<TFileService> fs;
155	–	// draw cone of radius 0.5 around highest energy bin, reduce
156	–	double maxE = 0.0;
157	–	int max_i = 29, max_j = 29;
158	–	for (int i = 0; i < unred_histo->GetNbinsX(); i++) {
159	–	for (int j = 0; j < unred_histo->GetNbinsY(); j++) {
160	–	double E = unred_histo->GetBinContent(i+1, j+1);
161	–	if (E > maxE) {
162	–	maxE = E;
163	–	max_i = i;
164	–	max_j = j;
165	–	}
166	–	}
167	–	}
168	–
169	–	double rcone = 0.5;
170	–	double Xlo = unred_histo->GetXaxis()->GetXmin();
171	–	double Xhi = unred_histo->GetXaxis()->GetXmax();
172	–	double Ylo = unred_histo->GetYaxis()->GetXmin();
173	–	double Yhi = unred_histo->GetYaxis()->GetXmax();
174	–	double XbinSize = (Xhi - Xlo) /
175	–	static_cast<double>(unred_histo->GetXaxis()->GetNbins());
176	–	double YbinSize = (Yhi - Ylo) /
177	–	static_cast<double>(unred_histo->GetYaxis()->GetNbins());
178	–	double max_x = (static_cast<double>(max_i) + 0.5) * XbinSize + Xlo;
179	–	double max_y = (static_cast<double>(max_j) + 0.5) * YbinSize + Ylo;
180	–	TH2D *histo = fs->make<TH2D>(oss2.str().c_str(), oss2.str().c_str(),
181	–	60, max_x-rcone, max_x+rcone,
182	–	60, max_y-rcone, max_y+rcone);
183	–
184	–	// create an unsmeared reduced histo
185	–	TH2D *histo_unsmeared = fs->make<TH2D>((oss2.str()+"_unsmeared").c_str(),
186	–	(oss2.str()+"_unsmeared").c_str(),
187	–	60, max_x-rcone, max_x+rcone,
188	–	60, max_y-rcone, max_y+rcone);
189	–	for (int i = 0; i < particles.size(); i++) {
190	–	double N = particles[i]->momentum().e();
191	–	double x = particles[i]->momentum().eta();
192	–	double y = particles[i]->momentum().phi();
193	–	histo_unsmeared->Fill(x, y, N);
194	–	}
195	–
196	–	// create a smeared reduced histo
197	–	// create a temporary 2D vector for smeared energies
198	–	XbinSize = (histo->GetXaxis()->GetXmax()
199	–	- histo->GetXaxis()->GetXmin()) /
200	–	static_cast<double>(histo->GetXaxis()->GetNbins());
201	–	YbinSize = (histo->GetYaxis()->GetXmax()
202	–	- histo->GetYaxis()->GetXmin()) /
203	–	static_cast<double>(histo->GetYaxis()->GetNbins());
204	–	vector< vector<double> > smeared(60, vector<double>(60, 0.0) );
205	–	switch (smear_coord_) {
206	–	case 1:
207	–	for (int i = 0; i < particles.size(); i++) {
208	–	double N = particles[i]->momentum().e();
209	–	double x = particles[i]->momentum().eta();
210	–	double y = particles[i]->momentum().phi();
211	–	// loop over bins and add Gaussian in proper angle to smeared
212	–	for (vector< vector<double> >::size_type i2 = 0; i2 < 60; i2++) {
213	–	for (vector< double >::size_type j2 = 0; j2 < 60; j2++) {
214	–	double eta = static_cast<double>((signed int)i2) * XbinSize +
215	–	max_x - rcone - x;
216	–	double phi = acos(cos(static_cast<double>((signed int)j2) * YbinSize +
217	–	max_y - rcone - y));
218	–	phi = sin(phi) > 0 ? phi : -phi;
219	–
220	–	// transform eta, phi to proper angle
221	–	double theta = 2.0*atan(exp(-eta));
222	–	double iota = asin(sin(theta)*sin(phi));
223	–
224	–	smeared[i2][j2] += (N*XbinSize*YbinSize/(2.0*PI*smear_*smear_))
225	–	* exp(-0.5*(theta*theta + iota*iota)/(smear_*smear_));
226	–	}
227	–	}
228	–	}
229	–	break;
230	–	case 0:
231	–	default:
232	–	for (int i = 0; i < particles.size(); i++) {
233	–	double N = particles[i]->momentum().e();
234	–	double x = particles[i]->momentum().eta();
235	–	double y = particles[i]->momentum().phi();
236	–	// loop over bins and add Gaussian to smeared
237	–	for (vector< vector<double> >::size_type i2 = 0; i2 < 60; i2++) {
238	–	for (vector< double >::size_type j2 = 0; j2 < 60; j2++) {
239	–	double eta = static_cast<double>((signed int)i2) * XbinSize
240	–	+ max_x - rcone - x;
241	–	double phi = acos(cos(static_cast<double>((signed int)j2) * YbinSize
242	–	+ max_y - rcone - y));
243	–	phi = sin(phi) > 0 ? phi : -phi;
244	–	smeared[i2][j2] += (N*XbinSize*YbinSize/(2.0*PI*smear_*smear_))
245	–	* exp(-0.5*(eta*eta + phi*phi)/(smear_*smear_));
246	–	}
247	–	}
248	–	}
249	–	}
250	–	// set histogram to match smear vector
251	–	for (int i = 1; i <= 60; i++) {
252	–	for (int j = 1; j <= 60; j++) {
253	–	histo->SetBinContent(i, j, smeared[i-1][j-1]);
254	–	}
255	–	}
256	–
257	–	return histo;
258	–	}
259	–
260	–	void seed_with_CA(const edm::Event &evt, TH2 *histo,
261	–	jetfit::model_def &_mdef) {
262	–	edm::Handle<edm::HepMCProduct> hMC;
263	–	evt.getByLabel("source", hMC);
264	–
265	–	// create a PseudoJet vector
266	–	vector<PseudoJet> particles;
267	–	const HepMC::GenEvent *hmcEvt = hMC->GetEvent();
268	–	for (HepMC::GenEvent::particle_const_iterator
269	–	pit = hmcEvt->particles_begin(); pit != hmcEvt->particles_end();
270	–	pit++) {
271	–	if ((*pit)->status() == 1) {
272	–	double x_max = (histo->GetXaxis()->GetXmax()
273	–	+ histo->GetXaxis()->GetXmin()) / 2.0;
274	–	double y_max = (histo->GetYaxis()->GetXmax()
275	–	+ histo->GetYaxis()->GetXmin()) / 2.0;
276	–	valarray<double> pmom(4);
277	–	pmom[0] = (*pit)->momentum().px();
278	–	pmom[1] = (*pit)->momentum().py();
279	–	pmom[2] = (*pit)->momentum().pz();
280	–	pmom[3] = (*pit)->momentum().e();
281	–	double eta = (*pit)->momentum().eta();
282	–	double phi = (*pit)->momentum().phi();
283	–	if ((eta - x_max)*(eta - x_max) + (phi - y_max)*(phi - y_max) < 0.25) {
284	–	PseudoJet j(pmom);
285	–	particles.push_back(j);
286	–	}
287	–	}
288	–	}
289	–
290	–	// choose a jet definition
291	–	double R = 0.2;
292	–	JetDefinition jet_def(cambridge_algorithm, R);
293	–
294	–	// run clustering and extract the jets
295	–	ClusterSequence cs(particles, jet_def);
296	–	vector<PseudoJet> jets = cs.inclusive_jets();
297	–
298	–	double XbinSize = (histo->GetXaxis()->GetXmax()
299	–	- histo->GetXaxis()->GetXmin()) /
300	–	static_cast<double>(histo->GetXaxis()->GetNbins());
301	–	double YbinSize = (histo->GetYaxis()->GetXmax()
302	–	- histo->GetYaxis()->GetXmin()) /
303	–	static_cast<double>(histo->GetYaxis()->GetNbins());
304	–
305	–	// seed with C-A jets
306	–	int ijset = 0;
307	–	for (unsigned ij = 0; ij < jets.size(); ij++) {
308	–	double N = jets[ij].e();
309	–	if (N > 10.0) {
310	–	_mdef.set_special_par(ijset, 0, N, _mdef.chisquare_error(N)*0.1,
311	–	0.0, 1.0e6);
312	–	_mdef.set_special_par(ijset, 1, jets[ij].eta(), 0.01,
313	–	0.0, 0.0);
314	–	double mdef_phi = jets[ij].phi() > PI ? jets[ij].phi() - 2*PI
315	–	: jets[ij].phi();
316	–	_mdef.set_special_par(ijset, 2, mdef_phi, 0.01,
317	–	0.0, 0.0);
318	–	_mdef.set_special_par(ijset, 3, 0.1, 0.001, 0.0, 0.0);
319	–	ijset++;
320	–	}
321	–	}
322	–	}
323	–
324	–	jetfit::model_def& JetFinderAnalyzer::make_model_def(const edm::Event& evt,
325	–	const edm::EventSetup&,
326	–	TH2 *histo) {
327	–	class jf_model_def : public jetfit::model_def {
328	–	public:
329	–	virtual double chisquare_error(double E) {
330	–	return 0.97*E + 14.0;
331	–	// study from 08-27-09
332	–	}
333	–	};
334	–
335	–	jf_model_def *_mdef = new jf_model_def();
336	–	TFormula *formula = new TFormula("gaus2d",
337	–	"[0]*exp(-0.5*((x-[1])**2 + (y-[2])**2)/([3]**2))/(2*pi*[3]**2)");
338	–	_mdef->set_formula(formula);
339	–	_mdef->set_indiv_max_E(0);
340	–	_mdef->set_indiv_max_x(1);
341	–	_mdef->set_indiv_max_y(2);
342	–	_mdef->set_indiv_par(0, string("N"), 0.0, 0.0, 0.0, 1.0e6);
343	–	_mdef->set_indiv_par(1, string("mu_x"), 0.0, 0.0, 0.0, 0.0);
344	–	_mdef->set_indiv_par(2, string("mu_y"), 0.0, 0.0, 0.0, 0.0);
345	–	_mdef->set_indiv_par(3, string("sig"), 0.1, 0.001, 0.0, 0.0);
346	–
347	–	seed_with_CA(evt, histo, *_mdef);
348	–
349	–	jetfit::set_model_def(_mdef);
350	–
351	–	// generate initial fit histogram
352	–	edm::Service<TFileService> fs;
353	–	TH2D *init_fit_histo = fs->make<TH2D>(("init_fit_"+string(histo->GetName()))
354	–	.c_str(),
355	–	("Initial fit for "
356	–	+string(histo->GetName())).c_str(),
357	–	histo->GetXaxis()->GetNbins(),
358	–	histo->GetXaxis()->GetXmin(),
359	–	histo->GetXaxis()->GetXmax(),
360	–	histo->GetXaxis()->GetNbins(),
361	–	histo->GetXaxis()->GetXmin(),
362	–	histo->GetXaxis()->GetXmax());
363	–	double XbinSize = (histo->GetXaxis()->GetXmax()
364	–	- histo->GetXaxis()->GetXmin()) /
365	–	static_cast<double>(histo->GetXaxis()->GetNbins());
366	–	double YbinSize = (histo->GetYaxis()->GetXmax()
367	–	- histo->GetYaxis()->GetXmin()) /
368	–	static_cast<double>(histo->GetYaxis()->GetNbins());
369	–	double Xlo = histo->GetXaxis()->GetXmin();
370	–	double Xhi = histo->GetXaxis()->GetXmax();
371	–	double Ylo = histo->GetYaxis()->GetXmin();
372	–	double Yhi = histo->GetYaxis()->GetXmax();
373	–
374	–	for (int i = 0; i < 60; i++) {
375	–	for (int j = 0; j < 60; j++) {
376	–	double x = (static_cast<double>(i) + 0.5)*XbinSize + Xlo;
377	–	double y = (static_cast<double>(j) + 0.5)*YbinSize + Ylo;
378	–	double pval[256];
379	–	if (_mdef->get_n_special_par_sets() > 64) {
380	–	cerr << "Parameter overload" << endl;
381	–	return *_mdef;
382	–	}
383	–	else {
384	–	for (int is = 0; is < _mdef->get_n_special_par_sets(); is++) {
385	–	for (int ii = 0; ii < 4; ii++) {
386	–	double spval, sperr, splo, sphi;
387	–	_mdef->get_special_par(is, ii, spval, sperr, splo, sphi);
388	–	pval[4*is + ii] = spval;
389	–	}
390	–	}
391	–	}
392	–	jetfit::set_ngauss(_mdef->get_n_special_par_sets());
393	–	init_fit_histo->SetBinContent(i+1, j+1,
394	–	jetfit::fit_fcn(x, y, pval));
395	–	}
396	–	}
397	–
398	–	return *_mdef;
33		}
34
35		void JetFinderAnalyzer::beginJob(const edm::EventSetup &es) {
402	–	ofs.open("jetfindlog.txt", ios::out);
403	–	if (ofs.fail()) {
404	–	cerr << "Opening jetfindlog.txt FAILED" << endl;
405	–	}
406	–	ofs << "Jetfinder log" << endl
407	–	<< "=============" << endl << endl;
408	–	}
36
37	<	ostream& operator<<(ostream &out, jetfit::trouble t) {
411	<	string action, error_string;
412	<
413	<	if (t.istat != 3) {
414	<	switch(t.occ) {
415	<	case jetfit::T_NULL:
416	<	action = "Program"; break;
417	<	case jetfit::T_SIMPLEX:
418	<	action = "SIMPLEX"; break;
419	<	case jetfit::T_MIGRAD:
420	<	action = "MIGRAD"; break;
421	<	case jetfit::T_MINOS:
422	<	action = "MINOS"; break;
423	<	default:
424	<	action = "Program"; break;
425	<	}
426	<
427	<	switch (t.istat) {
428	<	case 0:
429	<	error_string = "Unable to calculate error matrix"; break;
430	<	case 1:
431	<	error_string = "Error matrix a diagonal approximation"; break;
432	<	case 2:
433	<	error_string = "Error matrix not positive definite"; break;
434	<	case 3:
435	<	error_string = "Converged successfully"; break;
436	<	default:
437	<	ostringstream oss;
438	<	oss<<"Unknown status code "<<t.istat << flush;
439	<	error_string = oss.str(); break;
440	<	}
37	>	}
38
39	<	if (t.occ != jetfit::T_NULL)
40	<	out << action<<" trouble: "<<error_string;
41	<	else
42	<	out << "Not calculated" << endl;
39	>	double evalFitFunction(HistoFitter::FitResults r, double x, double y) {
40	>	unsigned nFits = r.pars.size();
41	>	unsigned nGauss = r.pars[nFits-1].size() / 4;
42	>	double fitVal = 0.0;
43	>	for (unsigned i = 0; i < nGauss; i++) {
44	>	double N = r.pval[nFits-1][4*i];
45	>	double mu_x = r.pval[nFits-1][4*i + 1];
46	>	double mu_y = r.pval[nFits-1][4*i + 2];
47	>	double sig = r.pval[nFits-1][4*i + 3];
48	>
49	>	double rel_x = x - mu_x; double rel_y = y - mu_y;
50	>	fitVal += (N / 2.0 / M_PI / sig / sig)
51	>	* exp(-(rel_x * rel_x + rel_y * rel_y)/2.0/sig/sig);
52		}
53	<
448	<	return out;
53	>	return fitVal;
54		}
55
56	<	void JetFinderAnalyzer::analyze_results(jetfit::results r,
57	<	std::vector<jetfit::trouble> t,
56	>	void JetFinderAnalyzer::analyze_results(HistoFitter::FitResults r,
57	>	std::vector<HistoFitter::Trouble> t,
58		TH2 *hist_orig) {
59	<	ofs << "Histogram "<<hist_orig->GetName() << endl;
455	<	for (int i = 0; i < unique_jets[hist_orig].size(); i++) {
456	<	ofs << "For "<<i+1<<" gaussians: " << endl
457	<	<< t.at(i) << endl
458	<	<< unique_jets[hist_orig][i].size()<<" unique jets found" << endl;
459	<	for (int j = 0; j < unique_jets[hist_orig][i].size(); j++) {
460	<	jet _jet = unique_jets[hist_orig][i][j];
461	<	ofs << "Jet "<<j<<": Energy = "<<_jet.energy<<", eta = "<<_jet.eta
462	<	<< ", phi = "<<_jet.phi << endl;
463	<	}
464	<	ofs << endl;
465	<	}
466	<	ofs << endl;
467	<
468	<	// save fit function histograms to root file
59	>	// perform analysis of fit results
60		edm::Service<TFileService> fs;
61	<	for (vector< vector<double> >::size_type i = 0;
62	<	i < r.pval.size(); i++) {
63	<	jetfit::set_ngauss(r.pval[i].size() / 4);
64	<	TF2 *tf2 = new TF2("fit_func", jetfit::fit_fcn_TF2,
65	<	hist_orig->GetXaxis()->GetXmin(),
66	<	hist_orig->GetXaxis()->GetXmax(),
67	<	hist_orig->GetYaxis()->GetXmin(),
68	<	hist_orig->GetYaxis()->GetXmax(),
69	<	r.pval[i].size());
70	<	for (vector<double>::size_type j = 0; j < r.pval[i].size(); j++) {
71	<	tf2->SetParameter(j, r.pval[i][j]);
72	<	}
73	<	ostringstream fit_histo_oss;
74	<	fit_histo_oss << hist_orig->GetName()<<"_fit_"<<i << flush;
75	<	tf2->SetNpx(hist_orig->GetXaxis()->GetNbins());
76	<	tf2->SetNpy(hist_orig->GetYaxis()->GetNbins());
77	<	TH2D *fit_histo = fs->make<TH2D>(fit_histo_oss.str().c_str(),
78	<	fit_histo_oss.str().c_str(),
79	<	hist_orig->GetXaxis()->GetNbins(),
80	<	hist_orig->GetXaxis()->GetXmin(),
81	<	hist_orig->GetXaxis()->GetXmax(),
82	<	hist_orig->GetYaxis()->GetNbins(),
492	<	hist_orig->GetYaxis()->GetXmin(),
493	<	hist_orig->GetYaxis()->GetXmax());
494	<	TH1 *tf2_histo = tf2->CreateHistogram();
495	<	double XbinSize = (fit_histo->GetXaxis()->GetXmax()
496	<	- fit_histo->GetXaxis()->GetXmin())
497	<	/ static_cast<double>(fit_histo->GetXaxis()->GetNbins());
498	<	double YbinSize = (fit_histo->GetYaxis()->GetXmax()
499	<	- fit_histo->GetYaxis()->GetXmin())
500	<	/ static_cast<double>(fit_histo->GetYaxis()->GetNbins());
501	<	for (int ih = 0; ih < tf2->GetNpx(); ih++) {
502	<	for (int jh = 0; jh < tf2->GetNpy(); jh++) {
503	<	fit_histo->SetBinContent(ih+1, jh+1,
504	<	tf2_histo->GetBinContent(ih+1, jh+1)
505	<	* XbinSize * YbinSize);
506	<	}
61	>	TH2D *fitHisto = fs->make<TH2D>((std::string(hist_orig->GetName())+"_fit").c_str(),
62	>	("Fitted distribution to "
63	>	+std::string(hist_orig->GetName())).c_str(),
64	>	hist_orig->GetNbinsX(),
65	>	hist_orig->GetXaxis()->GetXmin(),
66	>	hist_orig->GetXaxis()->GetXmax(),
67	>	hist_orig->GetNbinsY(),
68	>	hist_orig->GetYaxis()->GetXmin(),
69	>	hist_orig->GetYaxis()->GetXmax());
70	>
71	>	double Xlo = fitHisto->GetXaxis()->GetXmin();
72	>	double Xhi = fitHisto->GetXaxis()->GetXmax();
73	>	double Ylo = fitHisto->GetYaxis()->GetXmin();
74	>	double Yhi = fitHisto->GetYaxis()->GetXmax();
75	>	double XbinSize = (Xhi - Xlo) / static_cast<double>(fitHisto->GetNbinsX());
76	>	double YbinSize = (Yhi - Ylo) / static_cast<double>(fitHisto->GetNbinsY());
77	>
78	>	for (int i = 1; i <= fitHisto->GetNbinsX(); i++) {
79	>	for (int j = 1; j <= fitHisto->GetNbinsY(); j++) {
80	>	double x = (static_cast<double>(i) - 0.5) * XbinSize + Xlo;
81	>	double y = (static_cast<double>(j) - 0.5) * YbinSize + Ylo;
82	>	fitHisto->SetBinContent(i, j, evalFitFunction(r, x, y) * XbinSize * YbinSize);
83		}
84		}
85
86	<	// save results to file
87	<	ostringstream res_tree_oss, rt_title_oss;
88	<	res_tree_oss << hist_orig->GetName()<<"_results" << flush;
89	<	rt_title_oss << "Fit results for "<<hist_orig->GetName() << flush;
86	>	// save fit results to an ntuple
87	>	TNtuple *rNtuple = fs->make<TNtuple>((std::string(hist_orig->GetName())+"_results").c_str(),
88	>	("Fit results for "+std::string(hist_orig->GetName())).c_str(),
89	>	"N:mu_x:mu_y:sigma");
90	>	unsigned nFits = r.pval.size();
91	>	unsigned nGauss = r.pval[nFits-1].size() / 4;
92	>	for (unsigned i = 0; i < nGauss; i++) {
93	>	rNtuple->Fill(r.pval[nFits-1][4*i], r.pval[nFits-1][4*i+1], r.pval[nFits-1][4*i+2],
94	>	r.pval[nFits-1][4*i+3]);
95	>	}
96	>
97	>	// save chisquares to ntuple
98	>	for (unsigned i = 0; i < r.chisquare.size(); i++) {
99	>	ostringstream csNtupleName, csNtupleTitle;
100	>	csNtupleName << hist_orig->GetName() << "_chi2_" << i << flush;
101	>	csNtupleTitle << "Chisquare "<<i<<" for histo "<<hist_orig->GetName()
102	>	<< flush;
103	>	TNtuple *csNtuple = fs->make<TNtuple>(csNtupleName.str().c_str(),
104	>	csNtupleTitle.str().c_str(),
105	>	"chisq");
106	>	csNtuple->Fill(r.chisquare[i]);
107	>	}
108		}
109
110		DEFINE_FWK_MODULE(JetFinderAnalyzer);

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