source: trunk/MagicSoft/Mars/mhflux/MAlphaFitter.cc@ 7667

Last change on this file since 7667 was 7618, checked in by tbretz, 20 years ago
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1/* ======================================================================== *\
2!
3! *
4! * This file is part of MARS, the MAGIC Analysis and Reconstruction
5! * Software. It is distributed to you in the hope that it can be a useful
6! * and timesaving tool in analysing Data of imaging Cerenkov telescopes.
7! * It is distributed WITHOUT ANY WARRANTY.
8! *
9! * Permission to use, copy, modify and distribute this software and its
10! * documentation for any purpose is hereby granted without fee,
11! * provided that the above copyright notice appear in all copies and
12! * that both that copyright notice and this permission notice appear
13! * in supporting documentation. It is provided "as is" without express
14! * or implied warranty.
15! *
16!
17!
18! Author(s): Thomas Bretz, 3/2004 <mailto:tbretz@astro.uni-wuerzburg.de>
19!
20! Copyright: MAGIC Software Development, 2000-2004
21!
22!
23\* ======================================================================== */
24
25//////////////////////////////////////////////////////////////////////////////
26//
27// MAlphaFitter
28//
29// Create a single Alpha-Plot. The alpha-plot is fitted online. You can
30// check the result when it is filles in the MStatusDisplay
31// For more information see MHFalseSource::FitSignificance
32//
33// For convinience (fit) the output significance is stored in a
34// container in the parlisrt
35//
36// Version 2:
37// ----------
38// + Double_t fSignificanceExc; // significance of a known excess
39//
40//
41//////////////////////////////////////////////////////////////////////////////
42#include "MAlphaFitter.h"
43
44#include <TF1.h>
45#include <TH1.h>
46#include <TH3.h>
47
48#include <TRandom.h>
49#include <TFeldmanCousins.h>
50
51#include <TLine.h>
52#include <TLatex.h>
53#include <TVirtualPad.h>
54
55#include "MMath.h"
56
57#include "MLogManip.h"
58
59ClassImp(MAlphaFitter);
60
61using namespace std;
62
63void MAlphaFitter::Clear(Option_t *o)
64{
65 fSignificance=0;
66 fSignificanceExc=0;
67 fEventsExcess=0;
68 fEventsSignal=0;
69 fEventsBackground=0;
70
71 fChiSqSignal=0;
72 fChiSqBg=0;
73 fIntegralMax=0;
74 fScaleFactor=1;
75
76 fCoefficients.Reset();
77}
78
79// --------------------------------------------------------------------------
80//
81// This is a preliminary implementation of a alpha-fit procedure for
82// all possible source positions. It will be moved into its own
83// more powerfull class soon.
84//
85// The fit function is "gaus(0)+pol2(3)" which is equivalent to:
86// [0]*exp(-0.5*((x-[1])/[2])^2) + [3] + [4]*x + [5]*x^2
87// or
88// A*exp(-0.5*((x-mu)/sigma)^2) + a + b*x + c*x^2
89//
90// Parameter [1] is fixed to 0 while the alpha peak should be
91// symmetric around alpha=0.
92//
93// Parameter [4] is fixed to 0 because the first derivative at
94// alpha=0 should be 0, too.
95//
96// In a first step the background is fitted between bgmin and bgmax,
97// while the parameters [0]=0 and [2]=1 are fixed.
98//
99// In a second step the signal region (alpha<sigmax) is fittet using
100// the whole function with parameters [1], [3], [4] and [5] fixed.
101//
102// The number of excess and background events are calculated as
103// s = int(hist, 0, 1.25*sigint)
104// b = int(pol2(3), 0, 1.25*sigint)
105//
106// The Significance is calculated using the Significance() member
107// function.
108//
109Bool_t MAlphaFitter::Fit(TH1D &h, Bool_t paint)
110{
111 Clear();
112 if (h.GetEntries()==0)
113 return kFALSE;
114
115 Double_t sigmax=fSigMax;
116 Double_t bgmin =fBgMin;
117 Double_t bgmax =fBgMax;
118
119 const Double_t alpha0 = h.GetBinContent(1);
120 const Double_t alphaw = h.GetXaxis()->GetBinWidth(1);
121
122 // Check for the regios which is not filled...
123 if (alpha0==0)
124 return kFALSE; //*fLog << warn << "Histogram empty." << endl;
125
126 // First fit a polynom in the off region
127 fFunc->FixParameter(0, 0);
128 fFunc->FixParameter(1, 0);
129 fFunc->FixParameter(2, 1);
130 fFunc->ReleaseParameter(3);
131 if (fPolynomOrder!=1)
132 fFunc->FixParameter(4, 0);
133
134 for (int i=5; i<fFunc->GetNpar(); i++)
135 if (fFitBackground)
136 fFunc->ReleaseParameter(i);
137 else
138 fFunc->SetParameter(i, 0);
139
140 fFunc->SetParLimits(2, 0, 90);
141 // fFunc->SetParLimits(3, -1, 1);
142
143 // options : N do not store the function, do not draw
144 // I use integral of function in bin rather than value at bin center
145 // R use the range specified in the function range
146 // Q quiet mode
147 // E Perform better Errors estimation using Minos technique
148 if (fFitBackground)
149 {
150 h.Fit(fFunc, "NQI", "", bgmin, bgmax);
151 fChiSqBg = fFunc->GetChisquare()/fFunc->GetNDF();
152 }
153
154
155 // ------------------------------------
156 if (paint && fFitBackground)
157 {
158 fFunc->SetRange(0, 90);
159 fFunc->SetLineColor(kRed);
160 fFunc->SetLineWidth(2);
161 fFunc->Paint("same");
162 }
163 // ------------------------------------
164
165 fFunc->ReleaseParameter(0);
166 //func.ReleaseParameter(1);
167 fFunc->ReleaseParameter(2);
168 for (int i=3; i<fFunc->GetNpar(); i++)
169 fFunc->FixParameter(i, fFunc->GetParameter(i));
170
171 // Do not allow signals smaller than the background
172 const Double_t s = fSignalFunc==kGauss ? fFunc->GetParameter(3) : TMath::Exp(fFunc->GetParameter(3));
173 const Double_t A = alpha0-s;
174 const Double_t dA = TMath::Abs(A);
175 fFunc->SetParLimits(0, -dA*4, dA*4);
176 fFunc->SetParLimits(2, 0, 90);
177
178 // Now fit a gaus in the on region on top of the polynom
179 fFunc->SetParameter(0, A);
180 fFunc->SetParameter(2, sigmax*0.75);
181
182 // options : N do not store the function, do not draw
183 // I use integral of function in bin rather than value at bin center
184 // R use the range specified in the function range
185 // Q quiet mode
186 // E Perform better Errors estimation using Minos technique
187 h.Fit(fFunc, "NQI", "", 0, sigmax);
188
189 fChiSqSignal = fFunc->GetChisquare()/fFunc->GetNDF();
190 fCoefficients.Set(fFunc->GetNpar(), fFunc->GetParameters());
191
192 //const Bool_t ok = NDF>0 && chi2<2.5*NDF;
193
194 // ------------------------------------
195 if (paint)
196 {
197 fFunc->SetLineColor(kGreen);
198 fFunc->SetLineWidth(2);
199 fFunc->Paint("same");
200 }
201 // ------------------------------------
202
203 //const Double_t s = fFunc->Integral(0, fSigInt)/alphaw;
204 fFunc->SetParameter(0, 0);
205 fFunc->SetParameter(2, 1);
206 //const Double_t b = fFunc->Integral(0, fSigInt)/alphaw;
207 //fSignificance = MMath::SignificanceLiMaSigned(s, b);
208
209 const Int_t bin = h.GetXaxis()->FindFixBin(fSigInt*0.999);
210
211 fIntegralMax = h.GetBinLowEdge(bin+1);
212 fEventsBackground = fFunc->Integral(0, fIntegralMax)/alphaw;
213 fEventsSignal = h.Integral(1, bin);
214 fEventsExcess = fEventsSignal-fEventsBackground;
215 fSignificance = MMath::SignificanceLiMaSigned(fEventsSignal, fEventsBackground);
216 fSignificanceExc = MMath::SignificanceLiMaExc(fEventsSignal, fEventsBackground);
217
218 if (TMath::IsNaN(fSignificance))
219 fSignificance=0;
220
221 if (fEventsExcess<0)
222 fEventsExcess=0;
223
224 return kTRUE;
225}
226
227Bool_t MAlphaFitter::Fit(const TH1D &hon, const TH1D &hof, Double_t alpha, Bool_t paint)
228{
229 TH1D h(hon);
230 h.Add(&hof, -1); // substracts also number of entries!
231 h.SetEntries(hon.GetEntries());
232
233 MAlphaFitter fit(*this);
234 fit.SetPolynomOrder(0);
235
236 if (alpha<=0 || !fit.Fit(h, paint))
237 return kFALSE;
238
239 fChiSqSignal = fit.GetChiSqSignal();
240 fChiSqBg = fit.GetChiSqBg();
241 fCoefficients = fit.GetCoefficients();
242
243 const Int_t bin = hon.GetXaxis()->FindFixBin(fSigInt*0.999);
244
245 fIntegralMax = hon.GetBinLowEdge(bin+1);
246 fEventsBackground = hof.Integral(1, bin);
247 fEventsSignal = hon.Integral(1, bin);
248 fEventsExcess = fEventsSignal-fEventsBackground;
249 fScaleFactor = alpha;
250 fSignificance = MMath::SignificanceLiMaSigned(fEventsSignal, fEventsBackground/alpha, alpha);
251 fSignificanceExc = MMath::SignificanceLiMaExc(fEventsSignal, fEventsBackground/alpha, alpha);
252
253 if (TMath::IsNaN(fSignificance))
254 fSignificance=0;
255 if (fEventsExcess<0)
256 fEventsExcess=0;
257
258 return kTRUE;
259}
260
261// --------------------------------------------------------------------------
262//
263// Calculate the upper limit for fEventsSignal number of observed events
264// and fEventsBackground number of background events.
265//
266// Therefor TFeldmanCousin is used.
267//
268// The Feldman-Cousins method as described in PRD V57 #7, p3873-3889
269//
270Double_t MAlphaFitter::CalcUpperLimit() const
271{
272 // get a FeldmanCousins calculation object with the default limits
273 // of calculating a 90% CL with the minimum signal value scanned
274 // = 0.0 and the maximum signal value scanned of 50.0
275 TFeldmanCousins f;
276 f.SetMuStep(0.05);
277 f.SetMuMax(100);
278 f.SetMuMin(0);
279 f.SetCL(90);
280
281 return f.CalculateUpperLimit(fEventsSignal, fEventsBackground);
282}
283
284void MAlphaFitter::PaintResult(Float_t x, Float_t y, Float_t size) const
285{
286 const Double_t w = GetGausSigma();
287 const Double_t m = fIntegralMax;
288
289 const Int_t l1 = w<=0 ? 0 : (Int_t)TMath::Ceil(-TMath::Log10(w));
290 const Int_t l2 = m<=0 ? 0 : (Int_t)TMath::Ceil(-TMath::Log10(m));
291 const TString fmt = Form("\\sigma_{L/M}=%%.1f \\omega=%%.%df\\circ E=%%d B=%%d x<%%.%df \\tilde\\chi_{b}=%%.1f \\tilde\\chi_{s}=%%.1f c=%%.1f f=%%.2f",
292 l1<1?1:l1+1, l2<1?1:l2+1);
293
294 TLatex text(x, y, Form(fmt.Data(), fSignificance, w, (int)fEventsExcess,
295 (int)fEventsBackground, m, fChiSqBg, fChiSqSignal,
296 fCoefficients[3], fScaleFactor));
297
298 text.SetBit(TLatex::kTextNDC);
299 text.SetTextSize(size);
300 text.Paint();
301
302 TLine line;
303 line.SetLineColor(14);
304 line.PaintLine(m, gPad->GetUymin(), m, gPad->GetUymax());
305}
306
307void MAlphaFitter::Copy(TObject &o) const
308{
309 MAlphaFitter &f = static_cast<MAlphaFitter&>(o);
310
311 // Setup
312 f.fSigInt = fSigInt;
313 f.fSigMax = fSigMax;
314 f.fBgMin = fBgMin;
315 f.fBgMax = fBgMax;
316 f.fScaleMin = fScaleMin;
317 f.fScaleMax = fScaleMax;
318 f.fPolynomOrder = fPolynomOrder;
319 f.fFitBackground= fFitBackground;
320 f.fSignalFunc = fSignalFunc;
321 f.fScaleMode = fScaleMode;
322 f.fScaleUser = fScaleUser;
323 f.fStrategy = fStrategy;
324 f.fCoefficients.Set(fCoefficients.GetSize());
325 f.fCoefficients.Reset();
326
327 // Result
328 f.fSignificance = fSignificance;
329 f.fSignificanceExc = fSignificanceExc;
330 f.fEventsExcess = fEventsExcess;
331 f.fEventsSignal = fEventsSignal;
332 f.fEventsBackground = fEventsBackground;
333 f.fChiSqSignal = fChiSqSignal;
334 f.fChiSqBg = fChiSqBg;
335 f.fIntegralMax = fIntegralMax;
336 f.fScaleFactor = fScaleFactor;
337
338 // Function
339 TF1 *fcn = f.fFunc;
340 f.fFunc = new TF1(*fFunc);
341 f.fFunc->SetName("Dummy");
342 gROOT->GetListOfFunctions()->Remove(f.fFunc);
343 delete fcn;
344}
345
346void MAlphaFitter::Print(Option_t *o) const
347{
348 *fLog << GetDescriptor() << ": Fitting..." << endl;
349 *fLog << " ...signal to " << fSigMax << " (integrate into bin at " << fSigInt << ")" << endl;
350 *fLog << " ...signal function: ";
351 switch (fSignalFunc)
352 {
353 case kGauss: *fLog << "gauss(x)/pol" << fPolynomOrder; break;
354 case kThetaSq: *fLog << "gauss(sqrt(x))/expo"; break;
355 }
356 *fLog << endl;
357 if (!fFitBackground)
358 *fLog << " ...no background." << endl;
359 else
360 {
361 *fLog << " ...background from " << fBgMin << " to " << fBgMax << endl;
362 *fLog << " ...polynom order " << fPolynomOrder << endl;
363 *fLog << " ...scale mode: ";
364 switch (fScaleMode)
365 {
366 case kNone: *fLog << "none."; break;
367 case kEntries: *fLog << "entries."; break;
368 case kIntegral: *fLog << "integral."; break;
369 case kOffRegion: *fLog << "off region (integral between " << fScaleMin << " and " << fScaleMax << ")"; break;
370 case kBackground: *fLog << "background (integral between " << fBgMin << " and " << fBgMax << ")"; break;
371 case kLeastSquare: *fLog << "least square (N/A)"; break;
372 case kUserScale: *fLog << "user def (" << fScaleUser << ")"; break;
373 }
374 *fLog << endl;
375 }
376
377 if (TString(o).Contains("result"))
378 {
379 *fLog << "Result:" << endl;
380 *fLog << " - Significance (Li/Ma) " << fSignificance << endl;
381 *fLog << " - Excess Events " << fEventsExcess << endl;
382 *fLog << " - Signal Events " << fEventsSignal << endl;
383 *fLog << " - Background Events " << fEventsBackground << endl;
384 *fLog << " - Chi^2/ndf (Signal) " << fChiSqSignal << endl;
385 *fLog << " - Chi^2/ndf (Background) " << fChiSqBg << endl;
386 *fLog << " - Signal integrated up to " << fIntegralMax << "°" << endl;
387 *fLog << " - Scale Factor (Off) " << fScaleFactor << endl;
388 }
389}
390
391Bool_t MAlphaFitter::FitEnergy(const TH3D &hon, UInt_t bin, Bool_t paint)
392{
393 const TString name(Form("TempAlphaEnergy%06d", gRandom->Integer(1000000)));
394 TH1D *h = hon.ProjectionZ(name, -1, 9999, bin, bin, "E");
395 h->SetDirectory(0);
396
397 const Bool_t rc = Fit(*h, paint);
398 delete h;
399 return rc;
400}
401
402Bool_t MAlphaFitter::FitTheta(const TH3D &hon, UInt_t bin, Bool_t paint)
403{
404 const TString name(Form("TempAlphaTheta%06d", gRandom->Integer(1000000)));
405 TH1D *h = hon.ProjectionZ(name, bin, bin, -1, 9999, "E");
406 h->SetDirectory(0);
407
408 const Bool_t rc = Fit(*h, paint);
409 delete h;
410 return rc;
411}
412/*
413Bool_t MAlphaFitter::FitTime(const TH3D &hon, UInt_t bin, Bool_t paint)
414{
415 const TString name(Form("TempAlphaTime%06d", gRandom->Integer(1000000)));
416
417 hon.GetZaxis()->SetRange(bin,bin);
418 TH1D *h = (TH1D*)hon.Project3D("ye");
419 hon.GetZaxis()->SetRange(-1,9999);
420
421 h->SetDirectory(0);
422
423 const Bool_t rc = Fit(*h, paint);
424 delete h;
425 return rc;
426}
427*/
428Bool_t MAlphaFitter::FitAlpha(const TH3D &hon, Bool_t paint)
429{
430 const TString name(Form("TempAlpha%06d", gRandom->Integer(1000000)));
431 TH1D *h = hon.ProjectionZ(name, -1, 9999, -1, 9999, "E");
432 h->SetDirectory(0);
433
434 const Bool_t rc = Fit(*h, paint);
435 delete h;
436 return rc;
437}
438
439Bool_t MAlphaFitter::FitEnergy(const TH3D &hon, const TH3D &hof, UInt_t bin, Bool_t paint)
440{
441 const TString name1(Form("TempAlpha%06d_on", gRandom->Integer(1000000)));
442 const TString name0(Form("TempAlpha%06d_off", gRandom->Integer(1000000)));
443
444 TH1D *h1 = hon.ProjectionZ(name1, -1, 9999, bin, bin, "E");
445 TH1D *h0 = hof.ProjectionZ(name0, -1, 9999, bin, bin, "E");
446 h1->SetDirectory(0);
447 h0->SetDirectory(0);
448
449 const Bool_t rc = ScaleAndFit(*h1, h0, paint);
450
451 delete h0;
452 delete h1;
453
454 return rc;
455}
456
457Bool_t MAlphaFitter::FitTheta(const TH3D &hon, const TH3D &hof, UInt_t bin, Bool_t paint)
458{
459 const TString name1(Form("TempAlpha%06d_on", gRandom->Integer(1000000)));
460 const TString name0(Form("TempAlpha%06d_off", gRandom->Integer(1000000)));
461
462 TH1D *h1 = hon.ProjectionZ(name1, bin, bin, -1, 9999, "E");
463 TH1D *h0 = hof.ProjectionZ(name0, bin, bin, -1, 9999, "E");
464 h1->SetDirectory(0);
465 h0->SetDirectory(0);
466
467 const Bool_t rc = ScaleAndFit(*h1, h0, paint);
468
469 delete h0;
470 delete h1;
471
472 return rc;
473}
474/*
475Bool_t MAlphaFitter::FitTime(const TH3D &hon, const TH3D &hof, UInt_t bin, Bool_t paint)
476{
477 const TString name1(Form("TempAlphaTime%06d_on", gRandom->Integer(1000000)));
478 const TString name0(Form("TempAlphaTime%06d_off", gRandom->Integer(1000000)));
479
480 hon.GetZaxis()->SetRange(bin,bin);
481 TH1D *h1 = (TH1D*)hon.Project3D("ye");
482 hon.GetZaxis()->SetRange(-1,9999);
483 h1->SetDirectory(0);
484
485 hof.GetZaxis()->SetRange(bin,bin);
486 TH1D *h0 = (TH1D*)hof.Project3D("ye");
487 hof.GetZaxis()->SetRange(-1,9999);
488 h0->SetDirectory(0);
489
490 const Bool_t rc = ScaleAndFit(*h1, h0, paint);
491
492 delete h0;
493 delete h1;
494
495 return rc;
496}
497*/
498Bool_t MAlphaFitter::FitAlpha(const TH3D &hon, const TH3D &hof, Bool_t paint)
499{
500 const TString name1(Form("TempAlpha%06d_on", gRandom->Integer(1000000)));
501 const TString name0(Form("TempAlpha%06d_off", gRandom->Integer(1000000)));
502
503 TH1D *h1 = hon.ProjectionZ(name1, -1, 9999, -1, 9999, "E");
504 TH1D *h0 = hof.ProjectionZ(name0, -1, 9999, -1, 9999, "E");
505 h1->SetDirectory(0);
506 h0->SetDirectory(0);
507
508 const Bool_t rc = ScaleAndFit(*h1, h0, paint);
509
510 delete h0;
511 delete h1;
512
513 return rc;
514}
515
516Double_t MAlphaFitter::Scale(TH1D &of, const TH1D &on) const
517{
518 Float_t scaleon = 1;
519 Float_t scaleof = 1;
520 switch (fScaleMode)
521 {
522 case kNone:
523 return 1;
524
525 case kEntries:
526 scaleon = on.GetEntries();
527 scaleof = of.GetEntries();
528 break;
529
530 case kIntegral:
531 scaleon = on.Integral();
532 scaleof = of.Integral();
533 break;
534
535 case kOffRegion:
536 {
537 const Int_t min = on.GetXaxis()->FindFixBin(fScaleMin);
538 const Int_t max = on.GetXaxis()->FindFixBin(fScaleMax);
539 scaleon = on.Integral(min, max);
540 scaleof = of.Integral(min, max);
541 }
542 break;
543
544 case kBackground:
545 {
546 const Int_t min = on.GetXaxis()->FindFixBin(fBgMin);
547 const Int_t max = on.GetXaxis()->FindFixBin(fBgMax);
548 scaleon = on.Integral(min, max);
549 scaleof = of.Integral(min, max);
550 }
551 break;
552
553 case kUserScale:
554 scaleon = fScaleUser;
555 break;
556
557 // This is just to make some compiler happy
558 default:
559 return 1;
560 }
561
562 if (scaleof!=0)
563 {
564 of.Scale(scaleon/scaleof);
565 return scaleon/scaleof;
566 }
567 else
568 {
569 of.Reset();
570 return 0;
571 }
572}
573
574Double_t MAlphaFitter::GetMinimizationValue() const
575{
576 switch (fStrategy)
577 {
578 case kSignificance:
579 return -GetSignificance();
580 case kSignificanceChi2:
581 return -GetSignificance()/GetChiSqSignal();
582 case kSignificanceLogExcess:
583 if (GetEventsExcess()<1)
584 return 0;
585 return -GetSignificance()*TMath::Log10(GetEventsExcess());
586 case kSignificanceExcess:
587 return -GetSignificance()*GetEventsExcess();
588 case kExcess:
589 return -GetEventsExcess();
590 case kGaussSigma:
591 return GetGausSigma();
592 case kWeakSource:
593 return GetEventsBackground()<1 ? -GetEventsExcess() : -GetEventsExcess()/TMath::Sqrt(GetEventsBackground());
594 }
595 return 0;
596}
597
598Int_t MAlphaFitter::ReadEnv(const TEnv &env, TString prefix, Bool_t print)
599{
600 Bool_t rc = kFALSE;
601
602 //void SetScaleUser(Float_t scale) { fScaleUser = scale; fScaleMode=kUserScale; }
603 //void SetScaleMode(ScaleMode_t mode) { fScaleMode = mode; }
604
605 if (IsEnvDefined(env, prefix, "SignalIntegralMax", print))
606 {
607 SetSignalIntegralMax(GetEnvValue(env, prefix, "SignalIntegralMax", fSigInt));
608 rc = kTRUE;
609 }
610 if (IsEnvDefined(env, prefix, "SignalFitMax", print))
611 {
612 SetSignalIntegralMax(GetEnvValue(env, prefix, "SignalFitMax", fSigMax));
613 rc = kTRUE;
614 }
615 if (IsEnvDefined(env, prefix, "BackgroundFitMax", print))
616 {
617 SetBackgroundFitMax(GetEnvValue(env, prefix, "BackgroundFitMax", fBgMax));
618 rc = kTRUE;
619 }
620 if (IsEnvDefined(env, prefix, "BackgroundFitMin", print))
621 {
622 SetBackgroundFitMin(GetEnvValue(env, prefix, "BackgroundFitMin", fBgMin));
623 rc = kTRUE;
624 }
625 if (IsEnvDefined(env, prefix, "ScaleMin", print))
626 {
627 SetScaleMin(GetEnvValue(env, prefix, "ScaleMin", fScaleMin));
628 rc = kTRUE;
629 }
630 if (IsEnvDefined(env, prefix, "ScaleMax", print))
631 {
632 SetScaleMax(GetEnvValue(env, prefix, "ScaleMax", fScaleMax));
633 rc = kTRUE;
634 }
635 if (IsEnvDefined(env, prefix, "PolynomOrder", print))
636 {
637 SetPolynomOrder(GetEnvValue(env, prefix, "PolynomOrder", fPolynomOrder));
638 rc = kTRUE;
639 }
640
641 if (IsEnvDefined(env, prefix, "MinimizationStrategy", print))
642 {
643 TString txt = GetEnvValue(env, prefix, "MinimizationStrategy", "");
644 txt = txt.Strip(TString::kBoth);
645 txt.ToLower();
646 if (txt==(TString)"significance")
647 fStrategy = kSignificance;
648 if (txt==(TString)"significancechi2")
649 fStrategy = kSignificanceChi2;
650 if (txt==(TString)"significanceexcess")
651 fStrategy = kSignificanceExcess;
652 if (txt==(TString)"excess")
653 fStrategy = kExcess;
654 if (txt==(TString)"gausssigma" || txt==(TString)"gaussigma")
655 fStrategy = kGaussSigma;
656 if (txt==(TString)"weaksource")
657 fStrategy = kWeakSource;
658 rc = kTRUE;
659 }
660 if (IsEnvDefined(env, prefix, "Scale", print))
661 {
662 fScaleUser = GetEnvValue(env, prefix, "Scale", fScaleUser);
663 rc = kTRUE;
664 }
665 if (IsEnvDefined(env, prefix, "ScaleMode", print))
666 {
667 TString txt = GetEnvValue(env, prefix, "ScaleMode", "");
668 txt = txt.Strip(TString::kBoth);
669 txt.ToLower();
670 if (txt==(TString)"none")
671 fScaleMode = kNone;
672 if (txt==(TString)"entries")
673 fScaleMode = kEntries;
674 if (txt==(TString)"integral")
675 fScaleMode = kIntegral;
676 if (txt==(TString)"offregion")
677 fScaleMode = kOffRegion;
678 if (txt==(TString)"background")
679 fScaleMode = kBackground;
680 if (txt==(TString)"leastsquare")
681 fScaleMode = kLeastSquare;
682 if (txt==(TString)"userscale")
683 fScaleMode = kUserScale;
684 if (txt==(TString)"fixed")
685 {
686 fScaleMode = kUserScale;
687 fScaleUser = fScaleFactor;
688 cout << "---------> " << fScaleFactor << " <----------" << endl;
689 }
690 rc = kTRUE;
691 }
692 if (IsEnvDefined(env, prefix, "SignalFunction", print))
693 {
694 TString txt = GetEnvValue(env, prefix, "SignalFunction", "");
695 txt = txt.Strip(TString::kBoth);
696 txt.ToLower();
697 if (txt==(TString)"gauss" || txt==(TString)"gaus")
698 SetSignalFunction(kGauss);
699 if (txt==(TString)"thetasq")
700 SetSignalFunction(kThetaSq);
701 rc = kTRUE;
702 }
703
704 return rc;
705}
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