source: trunk/MagicSoft/Mars/mcalib/MHCalibrationChargeBlindPix.h@ 3617

Last change on this file since 3617 was 3617, checked in by gaug, 20 years ago
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1#ifndef MARS_MHCalibrationChargeBlindPix
2#define MARS_MHCalibrationChargeBlindPix
3
4
5#ifndef MARS_MHCalibrationChargePix
6#include "MHCalibrationChargePix.h"
7#endif
8
9#ifndef ROOT_TMatrix
10#include <TMatrix.h>
11#endif
12
13#ifndef ROOT_TF1
14#include <TF1.h>
15#endif
16
17class TH1F;
18class TF1;
19class TPaveText;
20class TText;
21class MRawEvtData;
22class MRawEvtPixelIter;
23class MCalibrationChargeBlindPix;
24class MExtractedSignalBlindPixel;
25class MHCalibrationChargeBlindPix : public MHCalibrationChargePix
26{
27private:
28
29 static const Int_t fgChargeNbins; // Default for fChargeNBins (now set to: 5300 )
30 static const Axis_t fgChargeFirst; // Default for fChargeFirst (now set to: -100.5 )
31 static const Axis_t fgChargeLast; // Default for fChargeLast (now set to: 5199.5 )
32 static const Float_t fgSinglePheCut; // Default for fSinglePheCut (now set to: 200 )
33 static const Float_t fgNumSinglePheLimit; // Default for fNumSinglePheLimit (now set to: 50 )
34
35 static const Double_t gkElectronicAmp; // Electronic Amplification after the PMT (in FADC counts/N_e)
36 static const Double_t gkElectronicAmpErr; // Error of the electronic amplification
37
38 Float_t fSinglePheCut; // Value of summed FADC slices upon which event considered as single-phe
39 Float_t fNumSinglePheLimit; // Minimum number of single-phe events
40
41 MCalibrationChargeBlindPix *fBlindPix; //! Storage container results
42 MExtractedSignalBlindPixel *fSignal; //! Storage container extracted signal
43 MRawEvtData *fRawEvt; //! Storage container raw data
44
45 TVector fASinglePheFADCSlices; // Averaged FADC slice entries supposed single-phe events
46 TVector fAPedestalFADCSlices; // Averaged FADC slice entries supposed pedestal events
47
48 TF1 *fSinglePheFit; //-> Single Phe Fit (Gaussians convoluted with Poisson)
49
50 UInt_t fNumSinglePhes; // Number of entries in fASinglePheFADCSlices
51 UInt_t fNumPedestals; // Number of entries in fAPedestalFADCSlices
52
53 Double_t fLambda; // Poisson mean from Single-phe fit
54 Double_t fLambdaCheck; // Poisson mean from Pedestal fit alone
55 Double_t fMu0; // Mean of the pedestal
56 Double_t fMu1; // Mean of single-phe peak
57 Double_t fSigma0; // Sigma of the pedestal
58 Double_t fSigma1; // Sigma of single-phe peak
59
60 Double_t fLambdaErr; // Error of Poisson mean from Single-phe fit
61 Double_t fLambdaCheckErr; // Error of Poisson mean from Pedestal fit alone
62 Double_t fMu0Err; // Error of Mean of the pedestal
63 Double_t fMu1Err; // Error of Mean of single-phe peak
64 Double_t fSigma0Err; // Error of Sigma of the pedestal
65 Double_t fSigma1Err; // Error of Sigma of single-phe peak
66
67 Double_t fChisquare; // Chisquare of single-phe fit
68 Int_t fNDF; // Ndof of single-phe fit
69 Double_t fProb; // Probability of singleo-phe fit
70
71 Double_t fMeanPedestal; // Mean pedestal from pedestal run
72 Double_t fSigmaPedestal; // Sigma pedestal from pedestal run
73
74 Double_t fMeanPedestalErr; // Error of Mean pedestal from pedestal run
75 Double_t fSigmaPedestalErr; // Error of Sigma pedestal from pedestal run
76
77 Byte_t fFlags; // Bit-field for the flags
78 enum { kSinglePheFitOK, kPedestalFitOK }; // Possible bits to be set
79
80 TPaveText *fFitLegend; //! Some legend to display the fit results
81 TH1F *fHSinglePheFADCSlices; //! A histogram created and deleted only in Draw()
82 TH1F *fHPedestalFADCSlices; //! A histogram created and deleted only in Draw()
83
84 // Fill histos
85 void FillSinglePheFADCSlices(const MRawEvtPixelIter &iter);
86 void FillPedestalFADCSlices( const MRawEvtPixelIter &iter);
87
88 // Fit
89 Bool_t InitFit();
90 void ExitFit();
91
92public:
93
94 MHCalibrationChargeBlindPix(const char *name=NULL, const char *title=NULL);
95 ~MHCalibrationChargeBlindPix();
96
97 void Clear(Option_t *o="");
98
99 Bool_t SetupFill(const MParList *pList);
100 Bool_t ReInit ( MParList *pList);
101 Bool_t Fill (const MParContainer *par, const Stat_t w=1);
102 Bool_t Finalize();
103
104 // Setters
105 void SetChargeNbins ( const Int_t bins =fgChargeNbins ) { fChargeNbins = bins; }
106 void SetChargeFirst ( const Axis_t first=fgChargeFirst ) { fChargeFirst = first; }
107 void SetChargeLast ( const Axis_t last =fgChargeLast ) { fChargeLast = last; }
108 void SetSinglePheCut ( const Float_t cut =fgSinglePheCut ) { fSinglePheCut = cut; }
109 void SetNumSinglePheLimit ( const Float_t lim =fgNumSinglePheLimit ) { fNumSinglePheLimit = lim; }
110
111 void SetMeanPedestal ( const Float_t f ) { fMeanPedestal = f; }
112 void SetMeanPedestalErr ( const Float_t f ) { fMeanPedestalErr = f; }
113 void SetSigmaPedestal ( const Float_t f ) { fSigmaPedestal = f; }
114 void SetSigmaPedestalErr ( const Float_t f ) { fSigmaPedestalErr = f; }
115
116 void SetSinglePheFitOK ( const Bool_t b=kTRUE);
117 void SetPedestalFitOK ( const Bool_t b=kTRUE);
118
119 // Getters
120 const Double_t GetLambda() const { return fLambda; }
121 const Double_t GetLambdaCheck() const { return fLambdaCheck; }
122 const Double_t GetMu0() const { return fMu0; }
123 const Double_t GetMu1() const { return fMu1; }
124 const Double_t GetSigma0() const { return fSigma0; }
125 const Double_t GetSigma1() const { return fSigma1; }
126
127 const Double_t GetLambdaErr() const { return fLambdaErr; }
128 const Double_t GetLambdaCheckErr() const { return fLambdaCheckErr; }
129 const Double_t GetMu0Err() const { return fMu0Err; }
130 const Double_t GetMu1Err() const { return fMu1Err; }
131 const Double_t GetSigma0Err() const { return fSigma0Err; }
132 const Double_t GetSigma1Err() const { return fSigma1Err; }
133
134 TVector &GetASinglePheFADCSlices() { return fASinglePheFADCSlices; }
135 const TVector &GetASinglePheFADCSlices() const { return fASinglePheFADCSlices; }
136
137 TVector &GetAPedestalFADCSlices() { return fAPedestalFADCSlices; }
138 const TVector &GetAPedestalFADCSlices() const { return fAPedestalFADCSlices; }
139
140 const Bool_t IsSinglePheFitOK() const;
141 const Bool_t IsPedestalFitOK() const;
142
143 // Draws
144 void Draw(Option_t *opt="");
145
146private:
147 void DrawLegend();
148
149 // Fits
150public:
151 enum FitFunc_t { kEPoisson4, kEPoisson5, kEPoisson6, kEPoisson7, kEPolya, kEMichele }; // The possible fit functions
152
153private:
154 FitFunc_t fFitFunc;
155
156public:
157 Bool_t FitSinglePhe (Option_t *opt="RL0+Q");
158 void FitPedestal (Option_t *opt="RL0+Q");
159
160 void ChangeFitFunc(const FitFunc_t func) { fFitFunc = func; }
161
162 // Simulation
163 Bool_t SimulateSinglePhe(const Double_t lambda,
164 const Double_t mu0, const Double_t mu1,
165 const Double_t sigma0, const Double_t sigma1);
166
167private:
168
169 inline static Double_t fFitFuncMichele(Double_t *x, Double_t *par)
170 {
171
172 Double_t lambda1cat = par[0];
173 Double_t lambda1dyn = par[1];
174 Double_t mu0 = par[2];
175 Double_t mu1cat = par[3];
176 Double_t mu1dyn = par[4];
177 Double_t sigma0 = par[5];
178 Double_t sigma1cat = par[6];
179 Double_t sigma1dyn = par[7];
180
181 Double_t sumcat = 0.;
182 Double_t sumdyn = 0.;
183 Double_t arg = 0.;
184
185 if (mu1cat < mu0)
186 return FLT_MAX;
187
188 if (sigma1cat < sigma0)
189 return FLT_MAX;
190
191 // if (sigma1cat < sigma1dyn)
192 // return NoWay;
193
194 //if (mu1cat < mu1dyn)
195 // return NoWay;
196
197 // if (lambda1cat < lambda1dyn)
198 // return NoWay;
199
200 Double_t mu2cat = (2.*mu1cat)-mu0;
201 Double_t mu2dyn = (2.*mu1dyn)-mu0;
202 Double_t mu3cat = (3.*mu1cat)-(2.*mu0);
203 Double_t mu3dyn = (3.*mu1dyn)-(2.*mu0);
204
205 Double_t sigma2cat = TMath::Sqrt((2.*sigma1cat*sigma1cat) - (sigma0*sigma0));
206 Double_t sigma2dyn = TMath::Sqrt((2.*sigma1dyn*sigma1dyn) - (sigma0*sigma0));
207 Double_t sigma3cat = TMath::Sqrt((3.*sigma1cat*sigma1cat) - (2.*sigma0*sigma0));
208 Double_t sigma3dyn = TMath::Sqrt((3.*sigma1dyn*sigma1dyn) - (2.*sigma0*sigma0));
209
210 Double_t lambda2cat = lambda1cat*lambda1cat;
211 Double_t lambda2dyn = lambda1dyn*lambda1dyn;
212 Double_t lambda3cat = lambda2cat*lambda1cat;
213 Double_t lambda3dyn = lambda2dyn*lambda1dyn;
214
215 // k=0:
216 arg = (x[0] - mu0)/sigma0;
217 sumcat = TMath::Exp(-0.5*arg*arg)/sigma0;
218 sumdyn =sumcat;
219
220 // k=1cat:
221 arg = (x[0] - mu1cat)/sigma1cat;
222 sumcat += lambda1cat*TMath::Exp(-0.5*arg*arg)/sigma1cat;
223 // k=1dyn:
224 arg = (x[0] - mu1dyn)/sigma1dyn;
225 sumdyn += lambda1dyn*TMath::Exp(-0.5*arg*arg)/sigma1dyn;
226
227 // k=2cat:
228 arg = (x[0] - mu2cat)/sigma2cat;
229 sumcat += 0.5*lambda2cat*TMath::Exp(-0.5*arg*arg)/sigma2cat;
230 // k=2dyn:
231 arg = (x[0] - mu2dyn)/sigma2dyn;
232 sumdyn += 0.5*lambda2dyn*TMath::Exp(-0.5*arg*arg)/sigma2dyn;
233
234
235 // k=3cat:
236 arg = (x[0] - mu3cat)/sigma3cat;
237 sumcat += 0.1666666667*lambda3cat*TMath::Exp(-0.5*arg*arg)/sigma3cat;
238 // k=3dyn:
239 arg = (x[0] - mu3dyn)/sigma3dyn;
240 sumdyn += 0.1666666667*lambda3dyn*TMath::Exp(-0.5*arg*arg)/sigma3dyn;
241
242 sumcat = TMath::Exp(-1.*lambda1cat)*sumcat;
243 sumdyn = TMath::Exp(-1.*lambda1dyn)*sumdyn;
244
245 return par[8]*(sumcat+sumdyn)/2.;
246
247 }
248
249 inline static Double_t fPoissonKto4(Double_t *x, Double_t *par)
250 {
251
252 Double_t lambda = par[0];
253
254 Double_t sum = 0.;
255 Double_t arg = 0.;
256
257 Double_t mu0 = par[1];
258 Double_t mu1 = par[2];
259
260 if (mu1 < mu0)
261 return FLT_MAX;
262
263 Double_t sigma0 = par[3];
264 Double_t sigma1 = par[4];
265
266 if (sigma1 < sigma0)
267 return FLT_MAX;
268
269 Double_t mu2 = (2.*mu1)-mu0;
270 Double_t mu3 = (3.*mu1)-(2.*mu0);
271 Double_t mu4 = (4.*mu1)-(3.*mu0);
272
273 Double_t sigma2 = TMath::Sqrt((2.*sigma1*sigma1) - (sigma0*sigma0));
274 Double_t sigma3 = TMath::Sqrt((3.*sigma1*sigma1) - (2.*sigma0*sigma0));
275 Double_t sigma4 = TMath::Sqrt((4.*sigma1*sigma1) - (3.*sigma0*sigma0));
276
277 Double_t lambda2 = lambda*lambda;
278 Double_t lambda3 = lambda2*lambda;
279 Double_t lambda4 = lambda3*lambda;
280
281 // k=0:
282 arg = (x[0] - mu0)/sigma0;
283 sum = TMath::Exp(-0.5*arg*arg)/sigma0;
284
285 // k=1:
286 arg = (x[0] - mu1)/sigma1;
287 sum += lambda*TMath::Exp(-0.5*arg*arg)/sigma1;
288
289 // k=2:
290 arg = (x[0] - mu2)/sigma2;
291 sum += 0.5*lambda2*TMath::Exp(-0.5*arg*arg)/sigma2;
292
293 // k=3:
294 arg = (x[0] - mu3)/sigma3;
295 sum += 0.1666666667*lambda3*TMath::Exp(-0.5*arg*arg)/sigma3;
296
297 // k=4:
298 arg = (x[0] - mu4)/sigma4;
299 sum += 0.041666666666667*lambda4*TMath::Exp(-0.5*arg*arg)/sigma4;
300
301 return TMath::Exp(-1.*lambda)*par[5]*sum;
302
303 }
304
305
306 inline static Double_t fPoissonKto5(Double_t *x, Double_t *par)
307 {
308
309 Double_t lambda = par[0];
310
311 Double_t sum = 0.;
312 Double_t arg = 0.;
313
314 Double_t mu0 = par[1];
315 Double_t mu1 = par[2];
316
317 if (mu1 < mu0)
318 return FLT_MAX;
319
320 Double_t sigma0 = par[3];
321 Double_t sigma1 = par[4];
322
323 if (sigma1 < sigma0)
324 return FLT_MAX;
325
326
327 Double_t mu2 = (2.*mu1)-mu0;
328 Double_t mu3 = (3.*mu1)-(2.*mu0);
329 Double_t mu4 = (4.*mu1)-(3.*mu0);
330 Double_t mu5 = (5.*mu1)-(4.*mu0);
331
332 Double_t sigma2 = TMath::Sqrt((2.*sigma1*sigma1) - (sigma0*sigma0));
333 Double_t sigma3 = TMath::Sqrt((3.*sigma1*sigma1) - (2.*sigma0*sigma0));
334 Double_t sigma4 = TMath::Sqrt((4.*sigma1*sigma1) - (3.*sigma0*sigma0));
335 Double_t sigma5 = TMath::Sqrt((5.*sigma1*sigma1) - (4.*sigma0*sigma0));
336
337 Double_t lambda2 = lambda*lambda;
338 Double_t lambda3 = lambda2*lambda;
339 Double_t lambda4 = lambda3*lambda;
340 Double_t lambda5 = lambda4*lambda;
341
342 // k=0:
343 arg = (x[0] - mu0)/sigma0;
344 sum = TMath::Exp(-0.5*arg*arg)/sigma0;
345
346 // k=1:
347 arg = (x[0] - mu1)/sigma1;
348 sum += lambda*TMath::Exp(-0.5*arg*arg)/sigma1;
349
350 // k=2:
351 arg = (x[0] - mu2)/sigma2;
352 sum += 0.5*lambda2*TMath::Exp(-0.5*arg*arg)/sigma2;
353
354 // k=3:
355 arg = (x[0] - mu3)/sigma3;
356 sum += 0.1666666667*lambda3*TMath::Exp(-0.5*arg*arg)/sigma3;
357
358 // k=4:
359 arg = (x[0] - mu4)/sigma4;
360 sum += 0.041666666666667*lambda4*TMath::Exp(-0.5*arg*arg)/sigma4;
361
362 // k=5:
363 arg = (x[0] - mu5)/sigma5;
364 sum += 0.008333333333333*lambda5*TMath::Exp(-0.5*arg*arg)/sigma5;
365
366 return TMath::Exp(-1.*lambda)*par[5]*sum;
367
368 }
369
370
371 inline static Double_t fPoissonKto6(Double_t *x, Double_t *par)
372 {
373
374 Double_t lambda = par[0];
375
376 Double_t sum = 0.;
377 Double_t arg = 0.;
378
379 Double_t mu0 = par[1];
380 Double_t mu1 = par[2];
381
382 if (mu1 < mu0)
383 return FLT_MAX;
384
385 Double_t sigma0 = par[3];
386 Double_t sigma1 = par[4];
387
388 if (sigma1 < sigma0)
389 return FLT_MAX;
390
391
392 Double_t mu2 = (2.*mu1)-mu0;
393 Double_t mu3 = (3.*mu1)-(2.*mu0);
394 Double_t mu4 = (4.*mu1)-(3.*mu0);
395 Double_t mu5 = (5.*mu1)-(4.*mu0);
396 Double_t mu6 = (6.*mu1)-(5.*mu0);
397
398 Double_t sigma2 = TMath::Sqrt((2.*sigma1*sigma1) - (sigma0*sigma0));
399 Double_t sigma3 = TMath::Sqrt((3.*sigma1*sigma1) - (2.*sigma0*sigma0));
400 Double_t sigma4 = TMath::Sqrt((4.*sigma1*sigma1) - (3.*sigma0*sigma0));
401 Double_t sigma5 = TMath::Sqrt((5.*sigma1*sigma1) - (4.*sigma0*sigma0));
402 Double_t sigma6 = TMath::Sqrt((6.*sigma1*sigma1) - (5.*sigma0*sigma0));
403
404 Double_t lambda2 = lambda*lambda;
405 Double_t lambda3 = lambda2*lambda;
406 Double_t lambda4 = lambda3*lambda;
407 Double_t lambda5 = lambda4*lambda;
408 Double_t lambda6 = lambda5*lambda;
409
410 // k=0:
411 arg = (x[0] - mu0)/sigma0;
412 sum = TMath::Exp(-0.5*arg*arg)/sigma0;
413
414 // k=1:
415 arg = (x[0] - mu1)/sigma1;
416 sum += lambda*TMath::Exp(-0.5*arg*arg)/sigma1;
417
418 // k=2:
419 arg = (x[0] - mu2)/sigma2;
420 sum += 0.5*lambda2*TMath::Exp(-0.5*arg*arg)/sigma2;
421
422 // k=3:
423 arg = (x[0] - mu3)/sigma3;
424 sum += 0.1666666667*lambda3*TMath::Exp(-0.5*arg*arg)/sigma3;
425
426 // k=4:
427 arg = (x[0] - mu4)/sigma4;
428 sum += 0.041666666666667*lambda4*TMath::Exp(-0.5*arg*arg)/sigma4;
429
430 // k=5:
431 arg = (x[0] - mu5)/sigma5;
432 sum += 0.008333333333333*lambda5*TMath::Exp(-0.5*arg*arg)/sigma5;
433
434 // k=6:
435 arg = (x[0] - mu6)/sigma6;
436 sum += 0.001388888888889*lambda6*TMath::Exp(-0.5*arg*arg)/sigma6;
437
438 return TMath::Exp(-1.*lambda)*par[5]*sum;
439
440 }
441
442 inline static Double_t fPolya(Double_t *x, Double_t *par)
443 {
444
445 const Double_t QEcat = 0.247; // mean quantum efficiency
446 const Double_t sqrt2 = 1.4142135623731;
447 const Double_t sqrt3 = 1.7320508075689;
448 const Double_t sqrt4 = 2.;
449
450 const Double_t lambda = par[0]; // mean number of photons
451
452 const Double_t excessPoisson = par[1]; // non-Poissonic noise contribution
453 const Double_t delta1 = par[2]; // amplification first dynode
454 const Double_t delta2 = par[3]; // amplification subsequent dynodes
455
456 const Double_t electronicAmpl = par[4]; // electronic amplification and conversion to FADC charges
457
458 const Double_t pmtAmpl = delta1*delta2*delta2*delta2*delta2*delta2; // total PMT gain
459 const Double_t A = 1. + excessPoisson - QEcat
460 + 1./delta1
461 + 1./delta1/delta2
462 + 1./delta1/delta2/delta2; // variance contributions from PMT and QE
463
464 const Double_t totAmpl = QEcat*pmtAmpl*electronicAmpl; // Total gain and conversion
465
466 const Double_t mu0 = par[7]; // pedestal
467 const Double_t mu1 = totAmpl; // single phe position
468 const Double_t mu2 = 2*totAmpl; // double phe position
469 const Double_t mu3 = 3*totAmpl; // triple phe position
470 const Double_t mu4 = 4*totAmpl; // quadruple phe position
471
472 const Double_t sigma0 = par[5];
473 const Double_t sigma1 = electronicAmpl*pmtAmpl*TMath::Sqrt(QEcat*A);
474 const Double_t sigma2 = sqrt2*sigma1;
475 const Double_t sigma3 = sqrt3*sigma1;
476 const Double_t sigma4 = sqrt4*sigma1;
477
478 const Double_t lambda2 = lambda*lambda;
479 const Double_t lambda3 = lambda2*lambda;
480 const Double_t lambda4 = lambda3*lambda;
481
482 //-- calculate the area----
483 Double_t arg = (x[0] - mu0)/sigma0;
484 Double_t sum = TMath::Exp(-0.5*arg*arg)/sigma0;
485
486 // k=1:
487 arg = (x[0] - mu1)/sigma1;
488 sum += lambda*TMath::Exp(-0.5*arg*arg)/sigma1;
489
490 // k=2:
491 arg = (x[0] - mu2)/sigma2;
492 sum += 0.5*lambda2*TMath::Exp(-0.5*arg*arg)/sigma2;
493
494 // k=3:
495 arg = (x[0] - mu3)/sigma3;
496 sum += 0.1666666667*lambda3*TMath::Exp(-0.5*arg*arg)/sigma3;
497
498 // k=4:
499 arg = (x[0] - mu4)/sigma4;
500 sum += 0.041666666666667*lambda4*TMath::Exp(-0.5*arg*arg)/sigma4;
501
502 return TMath::Exp(-1.*lambda)*par[6]*sum;
503 }
504
505
506
507 ClassDef(MHCalibrationChargeBlindPix, 1) // Histogram class for the Calibration Blind Pixel
508};
509
510#endif /* MARS_MHCalibrationChargeBlindPix */
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