source: trunk/MagicSoft/Mars/manalysis/MHPedestalPix.cc@ 3660

Last change on this file since 3660 was 3642, checked in by gaug, 21 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): Markus Gaug 02/2004 <mailto:markus@ifae.es>
19!
20! Copyright: MAGIC Software Development, 2000-2004
21!
22!
23\* ======================================================================== */
24
25//////////////////////////////////////////////////////////////////////////////
26//
27// MHPedestalPix
28//
29// Histogram class for pedestal analysis.
30// Stores and fits the pedestals taken from MPedestalPix on an event-by-event
31// basis. The results are re-normalized to a value per slice with the formulae:
32//
33// - Mean Pedestal / slice = Mean Pedestal / Number slices
34// - Mean Pedestal Error / slice = Mean Pedestal Error / Number slices
35// - Sigma Pedestal / slice = Sigma Pedestal / Sqrt (Number slices)
36// - Sigma Pedestal Error / slice = Sigma Pedestal Error / Sqrt (Number slices)
37//
38// Derives from MHGausEvents, fits the pedestals to a Gaussian and performs
39// a Fourier analysis.
40//
41//////////////////////////////////////////////////////////////////////////////
42#include "MHPedestalPix.h"
43
44#include <TH1.h>
45
46ClassImp(MHPedestalPix);
47
48using namespace std;
49//
50const Int_t MHPedestalPix::fgChargeNbins = 450 ;
51const Axis_t MHPedestalPix::fgChargeFirst = -0.5;
52const Axis_t MHPedestalPix::fgChargeLast = 449.5;
53// --------------------------------------------------------------------------
54//
55// Default Constructor.
56//
57// Sets:
58// - the default number for fNbins (fgChargeNbins)
59// - the default number for fFirst (fgChargeFirst)
60// - the default number for fLast (fgChargeLast)
61//
62// - the default name of the fHGausHist ("HPedestalCharge")
63// - the default title of the fHGausHist ("Distribution of Summed FADC Pedestal slices Pixel ")
64// - the default x-axis title for fHGausHist ("Sum FADC Slices")
65// - the default y-axis title for fHGausHist ("Nr. of events")
66// - TH1::Sumw2() for fHGausHist
67//
68// Initializes:
69// - fNSlices to 1
70//
71MHPedestalPix::MHPedestalPix(const char *name, const char *title)
72 : fNSlices(1)
73{
74
75 fName = name ? name : "MHPedestalPix";
76 fTitle = title ? title : "Histogrammed Pedestal events";
77
78 SetNbins( fgChargeNbins );
79 SetFirst( fgChargeFirst );
80 SetLast( fgChargeLast );
81
82 // Create a large number of bins, later we will rebin
83 fHGausHist.SetName("HPedestalCharge");
84 fHGausHist.SetTitle("Distribution of Summed FADC Pedestal Slices Pixel ");
85 fHGausHist.SetXTitle("Sum FADC Slices");
86 fHGausHist.SetYTitle("Nr. of events");
87 fHGausHist.Sumw2();
88
89}
90
91// --------------------------------------------------------------------------
92//
93// If mean and sigma have not yet been set, returns.
94//
95// Renormalizes the pedestal fit results by the following formulae:
96//
97// - Mean Pedestal / slice = Mean Pedestal / Number slices
98// - Mean Pedestal Error / slice = Mean Pedestal Error / Number slices
99// - Sigma Pedestal / slice = Sigma Pedestal / Sqrt (Number slices)
100// - Sigma Pedestal Error / slice = Sigma Pedestal Error / Sqrt (Number slices)
101//
102void MHPedestalPix::Renorm()
103{
104
105 if (fMean == fMeanErr == fSigma == fSigmaErr == 0.)
106 return;
107
108 //
109 // One never knows...
110 //
111 if (fNSlices <= 0)
112 return;
113
114 const Float_t sqslices = TMath::Sqrt(fNSlices);
115
116 SetMean ( GetMean() / fNSlices );
117 //
118 // Mean error goes with PedestalRMS/Sqrt(entries) -> scale with slices
119 //
120 SetMeanErr ( GetMeanErr() / fNSlices );
121 //
122 // Sigma goes like PedestalRMS -> scale with sqrt(slices)
123 //
124 SetSigma ( GetSigma() / sqslices );
125 //
126 // Sigma error goes like PedestalRMS/2.(entries) -> scale with sqrt(slices)
127 //
128 SetSigmaErr ( GetSigmaErr() / sqslices );
129
130}
131
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