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Comparing UserCode/JetFitAnalyzer/test/JetFinderAnalyzer.cc (file contents):
Revision 1.2 by dnisson, Thu Sep 3 18:00:45 2009 UTC vs.
Revision 1.27 by dnisson, Fri Jan 22 23:53:10 2010 UTC

#	Line 1 | Line 1
1	<	// TODO find why energies suddenly bigger
2	<	/* A simple jet-finding analyzer */
1	>	/* A JetFitAnalyzer that makes histograms with smearing */
2
3		#include "UserCode/JetFitAnalyzer/interface/JetFitAnalyzer.h"
4
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 "SimDataFormats/HepMCProduct/interface/HepMCProduct.h"
12	<	#include "DataFormats/Candidate/interface/Particle.h"
13	<	#include "DataFormats/ParticleFlowCandidate/interface/PFCandidateFwd.h"
14	<	#include "DataFormats/ParticleFlowCandidate/interface/PFCandidate.h"
15	<	#include "DataFormats/ParticleFlowReco/interface/PFBlock.h"
16	<
17	<	#include <map>
18	<	#include <vector>
19	<	#include <limits>
20	<	#include <cmath>
21	<	#include <cstdlib>
22	<	#include <fstream>
9	>	#include <iostream>
10		#include <sstream>
11
25	–	#include "TFormula.h"
12		#include "TF2.h"
13	+	#include "TNtuple.h"
14
15		#define PI 3.141593
16
17		using namespace std;
31	–	using namespace fastjet;
32	–
33	–	// Class to represent a "generic" particle, whether raw or reconstructed
34	–	class GenericParticle {
35	–	public:
36	–	GenericParticle(double __px, double __py, double __pz, double __e,
37	–	double __charge = 0.0)
38	–	: _px(__px), _py(__py), _pz(__pz), _e(__e), _charge(__charge) {
39	–	}
40	–	GenericParticle(const HepMC::GenParticle &genParticle)
41	–	: _charge(0.0) {
42	–	_px = genParticle.momentum().px();
43	–	_py = genParticle.momentum().py();
44	–	_pz = genParticle.momentum().pz();
45	–	_e = genParticle.momentum().e();
46	–	}
47	–	GenericParticle(const reco::PFCandidate &pfCandidate)
48	–	: _charge(0.0) {
49	–	_px = pfCandidate.px();
50	–	_py = pfCandidate.py();
51	–	_pz = pfCandidate.pz();
52	–	_e = pfCandidate.energy();
53	–	}
54	–	double px() {
55	–	return _px;
56	–	}
57	–	double py() {
58	–	return _py;
59	–	}
60	–	double pz() {
61	–	return _pz;
62	–	}
63	–	double e() {
64	–	return _e;
65	–	}
66	–	double charge() {
67	–	return _charge;
68	–	}
69	–	double eta() {
70	–	double theta = acos(_pz/sqrt(_px*_px + _py*_py + _pz*_pz));
71	–	return -log(tan(theta*0.5));
72	–	}
73	–	double phi() {
74	–	double phi0 = acos(_px/sqrt(_px*_px + _py*_py));
75	–	return _py > 0.0 ? phi0 : -phi0;
76	–	}
77	–	double m() {
78	–	return sqrt(_e*_e - _px*_px - _py*_py - _pz*_pz);
79	–	}
80	–	private:
81	–	double _px;
82	–	double _py;
83	–	double _pz;
84	–	double _e;
85	–	double _charge;
86	–	};
18
19		class JetFinderAnalyzer : public JetFitAnalyzer {
20		public:
90	–	struct jet {
91	–	double energy;
92	–	double eta;
93	–	double phi;
94	–	};
95	–
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_;
103	<
104	<	static double g2int(double xlo, double xhi, double ylo, double yhi,
105	<	double *pval) {
106	<	double sum1 = 0.0;
107	<	double sum2 = 0.0;
108	<	double xmid = 0.5 * (xlo + xhi);
109	<	double ymid = 0.5 * (ylo + yhi);
110	<	double xstep = (xhi - xlo) / 50.0;
111	<	double ystep = (yhi - ylo) / 50.0;
112	<	for (int i = 0; i < 50; i++) {
113	<	double x = (static_cast<double>(i) + 0.5) * xstep + xlo;
114	<	sum1 += xstep * jetfit::fit_fcn(x, ymid, pval);
115	<	}
116	<	for (int i = 0; i < 50; i++) {
117	<	double y = (static_cast<double>(i) + 0.5) * ystep + ylo;
118	<	sum2 += ystep * jetfit::fit_fcn(xmid, y, pval);
119	<	}
120	<	return sum1 * sum2;
121	<	}
122	<
123	<	static void jetfinder(TMinuit *gMinuit, TH2 *hist, int ngauss) {
124	<	double dist_sq = numeric_limits<double>::infinity();
125	<	unique_jets[hist].resize(ngauss);
126	<	int nbinsX = hist->GetXaxis()->GetNbins();
127	<	int nbinsY = hist->GetYaxis()->GetNbins();
128	<	double XbinSize = (hist->GetXaxis()->GetXmax()
129	<	- hist->GetXaxis()->GetXmin())
130	<	/ static_cast<double>(nbinsX);
131	<	double YbinSize = (hist->GetYaxis()->GetXmax()
132	<	- hist->GetYaxis()->GetXmin())
133	<	/ static_cast<double>(nbinsY);
134	<	for (int i = 0; i < ngauss; i++) {
135	<	double N, mu_x, mu_y, sig, err, lo, hi;
136	<	int iuint;
137	<	TString name;
138	<	gMinuit->mnpout(4*i, name, N, err, lo, hi, iuint);
139	<	gMinuit->mnpout(4*i + 1, name, mu_x, err, lo, hi, iuint);
140	<	gMinuit->mnpout(4*i + 2, name, mu_y, err, lo, hi, iuint);
141	<	gMinuit->mnpout(4*i + 3, name, sig, err, lo, hi, iuint);
142	<	for (int j = 0; j < i; j++) {
143	<	double N2, mu_x2, mu_y2, sig2;
144	<	gMinuit->mnpout(4*j, name, N2, err, lo, hi, iuint);
145	<	gMinuit->mnpout(4*j + 1, name, mu_x2, err, lo, hi, iuint);
146	<	gMinuit->mnpout(4*j + 2, name, mu_y2, err, lo, hi, iuint);
147	<	gMinuit->mnpout(4*j + 3, name, sig2, err, lo, hi, iuint);
148	<	double _dist_sq = (mu_x2 - mu_x)*(mu_x2 - mu_x)
149	<	+ (mu_y2 - mu_y)*(mu_y2 - mu_y);
150	<	if (_dist_sq < dist_sq)
151	<	dist_sq = _dist_sq;
152	<	}
153	<
154	<	jet j;
155	<	j.energy = N;
156	<	j.eta = mu_x; j.phi = mu_y;
157	<	unique_jets[hist][ngauss-1].push_back(j);
158	<	}
159	<	}
160	<
161	<	virtual void beginJob(const edm::EventSetup&);
162	<	virtual TH2D* make_histo(const edm::Event&, const edm::EventSetup&);
163	<	virtual jetfit::model_def& make_model_def(const edm::Event&,
164	<	const edm::EventSetup&,
165	<	TH2 *);
166	<	virtual void analyze_results(jetfit::results r,
167	<	std::vector<jetfit::trouble> t, TH2 *);
168	<	vector<GenericParticle *> get_particles(const edm::Event&);
169	<	void fetchCandidateCollection(edm::Handle<reco::PFCandidateCollection>&,
170	<	const edm::InputTag&, const edm::Event&) const;
171	<
172	<	fstream ofs;
173	<	edm::InputTag inputTagPFCandidates_;
174	<	int info_type_;
175	<	double smear_;
176	<	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
179	–	map<TH2 *, vector< vector< JetFinderAnalyzer::jet > > >
180	–	JetFinderAnalyzer::unique_jets;
181	–
30		JetFinderAnalyzer::JetFinderAnalyzer(const edm::ParameterSet &pSet)
31		: JetFitAnalyzer(pSet) // this is important!
32		{
185	–	info_type_ = pSet.getUntrackedParameter("info_type", 0);
186	–
187	–	if (info_type_ == 1) {
188	–	inputTagPFCandidates_ = pSet.getParameter<edm::InputTag>("PFCandidates");
189	–	}
190	–
191	–	smear_ = pSet.getUntrackedParameter("smear", 0.02);
192	–	smear_coord_ = pSet.getUntrackedParameter("smear_coord", 0);
193	–	// 0 = eta-phi smear
194	–	// 1 = proper angle smear
195	–	set_user_minuit(jetfinder);
196	–	}
197	–
198	–	void
199	–	JetFinderAnalyzer::fetchCandidateCollection(edm::Handle<reco::PFCandidateCollection>& c,
200	–	const edm::InputTag& tag,
201	–	const edm::Event& iEvent) const {
202	–
203	–	bool found = iEvent.getByLabel(tag, c);
204	–
205	–	if(!found ) {
206	–	ostringstream  err;
207	–	err<<" cannot get PFCandidates: "
208	–	<<tag<<endl;
209	–	edm::LogError("PFCandidates")<<err.str();
210	–	throw cms::Exception( "MissingProduct", err.str());
211	–	}
212	–
213	–	}
214	–
215	–	vector<GenericParticle *> JetFinderAnalyzer::get_particles(const edm::Event &evt) {
216	–	// fill unreduced histo
217	–	edm::Handle<edm::HepMCProduct> hRaw;
218	–	edm::Handle<reco::PFCandidateCollection> hPFlow;
219	–	if (info_type_ == 0) {
220	–	evt.getByLabel("source", hRaw);
221	–	}
222	–	if (info_type_ == 1) {
223	–	fetchCandidateCollection(hPFlow,
224	–	inputTagPFCandidates_,
225	–	evt);
226	–	}
227	–
228	–	vector<GenericParticle *> particles;
229	–
230	–	switch (info_type_) {
231	–	case 0:
232	–	const HepMC::GenEvent *hmcEvt = hRaw->GetEvent();
233	–	for (HepMC::GenEvent::particle_const_iterator
234	–	pit = hmcEvt->particles_begin(); pit != hmcEvt->particles_end();
235	–	pit++) {
236	–	if ((*pit)->status() == 1) {
237	–	particles.push_back(new GenericParticle(**pit));
238	–	}
239	–	}
240	–
241	–	break;
242	–	case 1:
243	–	for (unsigned i = 0; i < hPFlow->size(); i++) {
244	–	particles.push_back(new GenericParticle((*hPFlow)[i]));
245	–	}
246	–	break;
247	–	default:
248	–	cerr << "Unknown event type" << endl; // TODO use MessageLogger
249	–	}
250	–
251	–	return particles;
252	–	}
253	–
254	–	TH2D * JetFinderAnalyzer::make_histo(const edm::Event &evt, const edm::EventSetup&) {
255	–	ostringstream oss;
256	–	oss << "eta_phi_energy_unred"<<evt.id().event() << flush;
257	–	TH2D *unred_histo = new TH2D(oss.str().c_str(), oss.str().c_str(),
258	–	600, -2.5, 2.5, 600, -PI, PI);
259	–
260	–	vector<GenericParticle *> particles = get_particles(evt);
261	–	for (int i = 0; i < particles.size(); i++) {
262	–	unred_histo->Fill(particles[i]->eta(),
263	–	particles[i]->phi(),
264	–	particles[i]->e());
265	–	}
266	–
267	–	// reduce histo
268	–	ostringstream oss2;
269	–	oss2 << "eta_phi_energy_red"<<evt.id().event() << flush;
270	–	edm::Service<TFileService> fs;
271	–	// draw cone of radius 0.5 around highest energy bin, reduce
272	–	double maxE = 0.0;
273	–	int max_i = 29, max_j = 29;
274	–	for (int i = 0; i < unred_histo->GetNbinsX(); i++) {
275	–	for (int j = 0; j < unred_histo->GetNbinsY(); j++) {
276	–	double E = unred_histo->GetBinContent(i+1, j+1);
277	–	if (E > maxE) {
278	–	maxE = E;
279	–	max_i = i;
280	–	max_j = j;
281	–	}
282	–	}
283	–	}
284	–
285	–	double rcone = 0.5;
286	–	double Xlo = unred_histo->GetXaxis()->GetXmin();
287	–	double Xhi = unred_histo->GetXaxis()->GetXmax();
288	–	double Ylo = unred_histo->GetYaxis()->GetXmin();
289	–	double Yhi = unred_histo->GetYaxis()->GetXmax();
290	–	double XbinSize = (Xhi - Xlo) /
291	–	static_cast<double>(unred_histo->GetXaxis()->GetNbins());
292	–	double YbinSize = (Yhi - Ylo) /
293	–	static_cast<double>(unred_histo->GetYaxis()->GetNbins());
294	–	double max_x = (static_cast<double>(max_i) + 0.5) * XbinSize + Xlo;
295	–	double max_y = (static_cast<double>(max_j) + 0.5) * YbinSize + Ylo;
296	–	TH2D *histo = fs->make<TH2D>(oss2.str().c_str(), oss2.str().c_str(),
297	–	60, max_x-rcone, max_x+rcone,
298	–	60, max_y-rcone, max_y+rcone);
299	–
300	–	// create an unsmeared reduced histo
301	–	TH2D *histo_unsmeared = fs->make<TH2D>((oss2.str()+"_unsmeared").c_str(),
302	–	(oss2.str()+"_unsmeared").c_str(),
303	–	60, max_x-rcone, max_x+rcone,
304	–	60, max_y-rcone, max_y+rcone);
305	–	for (int i = 0; i < particles.size(); i++) {
306	–	double N = particles[i]->e();
307	–	double x = particles[i]->eta();
308	–	double y = particles[i]->phi();
309	–	histo_unsmeared->Fill(x, y, N);
310	–	}
311	–
312	–	// create a smeared reduced histo
313	–	// create a temporary 2D vector for smeared energies
314	–	XbinSize = (histo->GetXaxis()->GetXmax()
315	–	- histo->GetXaxis()->GetXmin()) /
316	–	static_cast<double>(histo->GetXaxis()->GetNbins());
317	–	YbinSize = (histo->GetYaxis()->GetXmax()
318	–	- histo->GetYaxis()->GetXmin()) /
319	–	static_cast<double>(histo->GetYaxis()->GetNbins());
320	–	vector< vector<double> > smeared(60, vector<double>(60, 0.0) );
321	–	switch (smear_coord_) {
322	–	case 1:
323	–	for (int i = 0; i < particles.size(); i++) {
324	–	double N = particles[i]->e();
325	–	double x = particles[i]->eta();
326	–	double y = particles[i]->phi();
327	–	// loop over bins and add Gaussian in proper angle to smeared
328	–	for (vector< vector<double> >::size_type i2 = 0; i2 < 60; i2++) {
329	–	for (vector< double >::size_type j2 = 0; j2 < 60; j2++) {
330	–	double eta = static_cast<double>((signed int)i2) * XbinSize +
331	–	max_x - rcone - x;
332	–	double phi = acos(cos(static_cast<double>((signed int)j2) * YbinSize +
333	–	max_y - rcone - y));
334	–	phi = sin(phi) > 0 ? phi : -phi;
335	–
336	–	// transform eta, phi to proper angle
337	–	double theta = 2.0*atan(exp(-eta));
338	–	double iota = asin(sin(theta)*sin(phi));
339	–
340	–	smeared[i2][j2] += (N*XbinSize*YbinSize/(2.0*PI*smear_*smear_))
341	–	* exp(-0.5*(theta*theta + iota*iota)/(smear_*smear_));
342	–	}
343	–	}
344	–	}
345	–	break;
346	–	case 0:
347	–	default:
348	–	for (int i = 0; i < particles.size(); i++) {
349	–	double N = particles[i]->e();
350	–	double x = particles[i]->eta();
351	–	double y = particles[i]->phi();
352	–	// loop over bins and add Gaussian to smeared
353	–	for (vector< vector<double> >::size_type i2 = 0; i2 < 60; i2++) {
354	–	for (vector< double >::size_type j2 = 0; j2 < 60; j2++) {
355	–	double eta = static_cast<double>((signed int)i2) * XbinSize
356	–	+ max_x - rcone - x;
357	–	double phi = acos(cos(static_cast<double>((signed int)j2) * YbinSize
358	–	+ max_y - rcone - y));
359	–	phi = sin(phi) > 0 ? phi : -phi;
360	–	smeared[i2][j2] += (N*XbinSize*YbinSize/(2.0*PI*smear_*smear_))
361	–	* exp(-0.5*(eta*eta + phi*phi)/(smear_*smear_));
362	–	}
363	–	}
364	–	}
365	–	}
366	–	// set histogram to match smear vector
367	–	for (int i = 1; i <= 60; i++) {
368	–	for (int j = 1; j <= 60; j++) {
369	–	histo->SetBinContent(i, j, smeared[i-1][j-1]);
370	–	}
371	–	}
372	–
373	–	return histo;
374	–	}
375	–
376	–	void seed_with_CA(vector<GenericParticle *> gParticles, TH2 *histo,
377	–	jetfit::model_def &_mdef) {
378	–	// create a PseudoJet vector
379	–	vector<PseudoJet> particles;
380	–	for (unsigned i = 0; i < gParticles.size(); i++) {
381	–	double x_max = (histo->GetXaxis()->GetXmax()
382	–	+ histo->GetXaxis()->GetXmin()) / 2.0;
383	–	double y_max = (histo->GetYaxis()->GetXmax()
384	–	+ histo->GetYaxis()->GetXmin()) / 2.0;
385	–	valarray<double> pmom(4);
386	–	pmom[0] = gParticles[i]->px();
387	–	pmom[1] = gParticles[i]->py();
388	–	pmom[2] = gParticles[i]->pz();
389	–	pmom[3] = gParticles[i]->e();
390	–	double eta = gParticles[i]->eta();
391	–	double phi = gParticles[i]->phi();
392	–	if ((eta - x_max)*(eta - x_max) + (phi - y_max)*(phi - y_max) < 0.25) {
393	–	PseudoJet j(pmom);
394	–	particles.push_back(j);
395	–	}
396	–	}
397	–
398	–	// choose a jet definition
399	–	double R = 0.2;
400	–	JetDefinition jet_def(cambridge_algorithm, R);
401	–
402	–	// run clustering and extract the jets
403	–	ClusterSequence cs(particles, jet_def);
404	–	vector<PseudoJet> jets = cs.inclusive_jets();
405	–
406	–	double XbinSize = (histo->GetXaxis()->GetXmax()
407	–	- histo->GetXaxis()->GetXmin()) /
408	–	static_cast<double>(histo->GetXaxis()->GetNbins());
409	–	double YbinSize = (histo->GetYaxis()->GetXmax()
410	–	- histo->GetYaxis()->GetXmin()) /
411	–	static_cast<double>(histo->GetYaxis()->GetNbins());
412	–
413	–	// seed with C-A jets
414	–	int ijset = 0;
415	–	for (unsigned ij = 0; ij < jets.size(); ij++) {
416	–	double N = jets[ij].e();
417	–	if (N > 50.0) {
418	–	_mdef.set_special_par(ijset, 0, N, _mdef.chisquare_error(N)*0.1,
419	–	0.0, 1.0e6);
420	–	_mdef.set_special_par(ijset, 1, jets[ij].eta(), 0.01,
421	–	0.0, 0.0);
422	–	double mdef_phi = jets[ij].phi() > PI ? jets[ij].phi() - 2*PI
423	–	: jets[ij].phi();
424	–	_mdef.set_special_par(ijset, 2, mdef_phi, 0.01,
425	–	0.0, 0.0);
426	–	_mdef.set_special_par(ijset, 3, 0.1, 0.001, 0.0, 0.0);
427	–	ijset++;
428	–	}
429	–	}
430	–	}
431	–
432	–	jetfit::model_def& JetFinderAnalyzer::make_model_def(const edm::Event& evt,
433	–	const edm::EventSetup&,
434	–	TH2 *histo) {
435	–	class jf_model_def : public jetfit::model_def {
436	–	public:
437	–	virtual double chisquare_error(double E) {
438	–	return 0.97*E + 14.0;
439	–	// study from 08-27-09
440	–	}
441	–	};
442	–
443	–	jf_model_def *_mdef = new jf_model_def();
444	–	TFormula *formula = new TFormula("gaus2d",
445	–	"[0]*exp(-0.5*((x-[1])**2 + (y-[2])**2)/([3]**2))/(2*pi*[3]**2)");
446	–	_mdef->set_formula(formula);
447	–	_mdef->set_indiv_max_E(0);
448	–	_mdef->set_indiv_max_x(1);
449	–	_mdef->set_indiv_max_y(2);
450	–	_mdef->set_indiv_par(0, string("N"), 0.0, 0.0, 0.0, 1.0e6);
451	–	_mdef->set_indiv_par(1, string("mu_x"), 0.0, 0.0, 0.0, 0.0);
452	–	_mdef->set_indiv_par(2, string("mu_y"), 0.0, 0.0, 0.0, 0.0);
453	–	_mdef->set_indiv_par(3, string("sig"), 0.1, 0.001, 0.0, 0.0);
454	–
455	–	seed_with_CA(get_particles(evt), histo, *_mdef);
456	–
457	–	jetfit::set_model_def(_mdef);
458	–
459	–	// generate initial fit histogram
460	–	edm::Service<TFileService> fs;
461	–	TH2D *init_fit_histo = fs->make<TH2D>(("init_fit_"+string(histo->GetName()))
462	–	.c_str(),
463	–	("Initial fit for "
464	–	+string(histo->GetName())).c_str(),
465	–	histo->GetXaxis()->GetNbins(),
466	–	histo->GetXaxis()->GetXmin(),
467	–	histo->GetXaxis()->GetXmax(),
468	–	histo->GetXaxis()->GetNbins(),
469	–	histo->GetXaxis()->GetXmin(),
470	–	histo->GetXaxis()->GetXmax());
471	–	double XbinSize = (histo->GetXaxis()->GetXmax()
472	–	- histo->GetXaxis()->GetXmin()) /
473	–	static_cast<double>(histo->GetXaxis()->GetNbins());
474	–	double YbinSize = (histo->GetYaxis()->GetXmax()
475	–	- histo->GetYaxis()->GetXmin()) /
476	–	static_cast<double>(histo->GetYaxis()->GetNbins());
477	–	double Xlo = histo->GetXaxis()->GetXmin();
478	–	double Xhi = histo->GetXaxis()->GetXmax();
479	–	double Ylo = histo->GetYaxis()->GetXmin();
480	–	double Yhi = histo->GetYaxis()->GetXmax();
481	–
482	–	for (int i = 0; i < 60; i++) {
483	–	for (int j = 0; j < 60; j++) {
484	–	double x = (static_cast<double>(i) + 0.5)*XbinSize + Xlo;
485	–	double y = (static_cast<double>(j) + 0.5)*YbinSize + Ylo;
486	–	double pval[256];
487	–	if (_mdef->get_n_special_par_sets() > 64) {
488	–	cerr << "Parameter overload" << endl;
489	–	return *_mdef;
490	–	}
491	–	else {
492	–	for (int is = 0; is < _mdef->get_n_special_par_sets(); is++) {
493	–	for (int ii = 0; ii < 4; ii++) {
494	–	double spval, sperr, splo, sphi;
495	–	_mdef->get_special_par(is, ii, spval, sperr, splo, sphi);
496	–	pval[4*is + ii] = spval;
497	–	}
498	–	}
499	–	}
500	–	jetfit::set_ngauss(_mdef->get_n_special_par_sets());
501	–	init_fit_histo->SetBinContent(i+1, j+1,
502	–	jetfit::fit_fcn(x, y, pval));
503	–	}
504	–	}
505	–
506	–	return *_mdef;
33		}
34
35		void JetFinderAnalyzer::beginJob(const edm::EventSetup &es) {
510	–	ofs.open("jetfindlog.txt", ios::out);
511	–	if (ofs.fail()) {
512	–	cerr << "Opening jetfindlog.txt FAILED" << endl;
513	–	}
514	–	ofs << "Jetfinder log" << endl
515	–	<< "=============" << endl << endl;
516	–	}
36
37	<	ostream& operator<<(ostream &out, jetfit::trouble t) {
519	<	string action, error_string;
520	<
521	<	if (t.istat != 3) {
522	<	switch(t.occ) {
523	<	case jetfit::T_NULL:
524	<	action = "Program"; break;
525	<	case jetfit::T_SIMPLEX:
526	<	action = "SIMPLEX"; break;
527	<	case jetfit::T_MIGRAD:
528	<	action = "MIGRAD"; break;
529	<	case jetfit::T_MINOS:
530	<	action = "MINOS"; break;
531	<	default:
532	<	action = "Program"; break;
533	<	}
534	<
535	<	switch (t.istat) {
536	<	case 0:
537	<	error_string = "Unable to calculate error matrix"; break;
538	<	case 1:
539	<	error_string = "Error matrix a diagonal approximation"; break;
540	<	case 2:
541	<	error_string = "Error matrix not positive definite"; break;
542	<	case 3:
543	<	error_string = "Converged successfully"; break;
544	<	default:
545	<	ostringstream oss;
546	<	oss<<"Unknown status code "<<t.istat << flush;
547	<	error_string = oss.str(); break;
548	<	}
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	<
556	<	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;
563	<	for (int i = 0; i < unique_jets[hist_orig].size(); i++) {
564	<	ofs << "For "<<i+1<<" gaussians: " << endl
565	<	<< t.at(i) << endl
566	<	<< unique_jets[hist_orig][i].size()<<" unique jets found" << endl;
567	<	for (int j = 0; j < unique_jets[hist_orig][i].size(); j++) {
568	<	jet _jet = unique_jets[hist_orig][i][j];
569	<	ofs << "Jet "<<j<<": Energy = "<<_jet.energy<<", eta = "<<_jet.eta
570	<	<< ", phi = "<<_jet.phi << endl;
571	<	}
572	<	ofs << endl;
573	<	}
574	<	ofs << endl;
575	<
576	<	// 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(),
600	<	hist_orig->GetYaxis()->GetXmin(),
601	<	hist_orig->GetYaxis()->GetXmax());
602	<	TH1 *tf2_histo = tf2->CreateHistogram();
603	<	double XbinSize = (fit_histo->GetXaxis()->GetXmax()
604	<	- fit_histo->GetXaxis()->GetXmin())
605	<	/ static_cast<double>(fit_histo->GetXaxis()->GetNbins());
606	<	double YbinSize = (fit_histo->GetYaxis()->GetXmax()
607	<	- fit_histo->GetYaxis()->GetXmin())
608	<	/ static_cast<double>(fit_histo->GetYaxis()->GetNbins());
609	<	for (int ih = 0; ih < tf2->GetNpx(); ih++) {
610	<	for (int jh = 0; jh < tf2->GetNpy(); jh++) {
611	<	fit_histo->SetBinContent(ih+1, jh+1,
612	<	tf2_histo->GetBinContent(ih+1, jh+1)
613	<	* XbinSize * YbinSize);
614	<	}
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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