1 | /* ======================================================================== *\
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2 | !
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3 | ! *
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4 | ! * This file is part of MARS, the MAGIC Analysis and Reconstruction
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5 | ! * Software. It is distributed to you in the hope that it can be a useful
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6 | ! * and timesaving tool in analysing Data of imaging Cerenkov telescopes.
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7 | ! * It is distributed WITHOUT ANY WARRANTY.
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8 | ! *
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9 | ! * Permission to use, copy, modify and distribute this software and its
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10 | ! * documentation for any purpose is hereby granted without fee,
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11 | ! * provided that the above copyright notice appear in all copies and
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12 | ! * that both that copyright notice and this permission notice appear
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13 | ! * in supporting documentation. It is provided "as is" without express
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14 | ! * or implied warranty.
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15 | ! *
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16 | !
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17 | !
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18 | ! Author(s): Markus Gaug 11/2003 <mailto:markus@ifae.es>
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19 | !
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20 | ! Copyright: MAGIC Software Development, 2000-2002
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21 | !
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22 | !
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23 | \* ======================================================================== */
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24 |
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25 | //////////////////////////////////////////////////////////////////////////////
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26 | // //
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27 | // MHCalibrationPixel //
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28 | // //
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29 | // Performs all the necessary fits to extract the mean number of photons //
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30 | // out of the derived light flux //
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31 | // //
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32 | //////////////////////////////////////////////////////////////////////////////
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33 |
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34 | #include "MHCalibrationPixel.h"
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35 | #include "MHCalibrationConfig.h"
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36 | #include "MCalibrationFits.h"
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37 |
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38 | #include <TStyle.h>
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39 | #include <TMath.h>
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40 |
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41 | #include <TFitter.h>
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42 | #include <TGraph.h>
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43 | #include <TAxis.h>
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44 |
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45 | #include <TF1.h>
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46 | #include <TH2.h>
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47 | #include <TCanvas.h>
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48 | #include <TPad.h>
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49 | #include <TPaveText.h>
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50 |
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51 | #include "MParList.h"
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52 |
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53 | #include "MLog.h"
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54 | #include "MLogManip.h"
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55 |
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56 | ClassImp(MHCalibrationPixel);
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57 |
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58 | using namespace std;
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59 |
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60 | // --------------------------------------------------------------------------
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61 | //
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62 | // Default Constructor.
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63 | //
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64 | MHCalibrationPixel::MHCalibrationPixel(const char *name, const char *title)
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65 | : fPixId(-1),
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66 | fHiGainvsLoGain(NULL),
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67 | fTotalEntries(0),
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68 | fHiGains(NULL),
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69 | fLoGains(NULL),
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70 | fChargeGausFit(NULL),
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71 | fTimeGausFit(NULL),
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72 | fFitLegend(NULL),
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73 | fLowerFitRange(-2000.),
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74 | fChargeFirstHiGain(-2000.5),
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75 | fChargeLastHiGain(9999.5),
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76 | fChargeNbinsHiGain(12000),
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77 | fChargeFirstLoGain(-2000.5),
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78 | fChargeLastLoGain(9999.5),
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79 | fChargeNbinsLoGain(1200),
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80 | fFitOK(kFALSE),
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81 | fChargeChisquare(-1.),
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82 | fChargeProb(-1.),
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83 | fChargeNdf(-1),
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84 | fTimeChisquare(-1.),
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85 | fTimeProb(-1.),
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86 | fTimeNdf(-1),
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87 | fUseLoGain(kFALSE)
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88 | {
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89 |
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90 | fName = name ? name : "MHCalibrationPixel";
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91 | fTitle = title ? title : "Fill the accumulated charges and times of all events and perform fits";
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92 |
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93 | // Create a large number of bins, later we will rebin
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94 | fHChargeHiGain = new TH1F("HChargeHiGain","Distribution of Summed FADC Hi Gain Slices Pixel ",
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95 | fChargeNbinsHiGain,fChargeFirstHiGain,fChargeLastHiGain);
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96 | fHChargeHiGain->SetXTitle("Sum FADC Slices (Hi Gain)");
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97 | fHChargeHiGain->SetYTitle("Nr. of events");
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98 | fHChargeHiGain->Sumw2();
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99 |
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100 | fHChargeHiGain->SetDirectory(NULL);
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101 |
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102 | fHChargeLoGain = new TH1F("HChargeLoGain","Distribution of Summed FADC Lo Gain Slices Pixel ",
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103 | fChargeNbinsLoGain,fChargeFirstLoGain,fChargeLastLoGain);
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104 | fHChargeLoGain->SetXTitle("Sum FADC Slices (Lo Gain)");
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105 | fHChargeLoGain->SetYTitle("Nr. of events");
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106 | fHChargeLoGain->Sumw2();
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107 |
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108 | fHChargeLoGain->SetDirectory(NULL);
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109 |
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110 | Axis_t tfirst = -0.5;
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111 | Axis_t tlast = 15.5;
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112 | Int_t ntbins = 16;
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113 |
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114 | fHTimeHiGain = new TH1I("HTimeHiGain","Distribution of Mean Arrival Hi Gain Times Pixel ",
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115 | ntbins,tfirst,tlast);
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116 | fHTimeHiGain->SetXTitle("Mean Arrival Times [Hi Gain FADC slice nr]");
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117 | fHTimeHiGain->SetYTitle("Nr. of events");
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118 | // fHTimeHiGain->Sumw2();
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119 |
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120 | fHTimeHiGain->SetDirectory(NULL);
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121 |
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122 | fHTimeLoGain = new TH1I("HTimeLoGain","Distribution of Mean Arrival Lo Gain Times Pixel ",
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123 | ntbins,tfirst,tlast);
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124 | fHTimeLoGain->SetXTitle("Mean Arrival Times [Lo Gain FADC slice nr]");
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125 | fHTimeLoGain->SetYTitle("Nr. of events");
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126 | // fHTimeLoGain->Sumw2();
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127 |
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128 | fHTimeLoGain->SetDirectory(NULL);
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129 |
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130 | // We define a reasonable number and later enlarge it if necessary
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131 | Int_t nqbins = 20000;
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132 | Axis_t nfirst = -0.5;
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133 | Axis_t nlast = (Axis_t)nqbins - 0.5;
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134 |
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135 | fHChargevsNHiGain = new TH1I("HChargevsNHiGain","Sum of Hi Gain Charges vs. Event Number Pixel ",
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136 | nqbins,nfirst,nlast);
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137 | fHChargevsNHiGain->SetXTitle("Event Nr.");
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138 | fHChargevsNHiGain->SetYTitle("Sum of Hi Gain FADC slices");
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139 |
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140 | fHChargevsNHiGain->SetDirectory(NULL);
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141 |
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142 | fHChargevsNLoGain = new TH1I("HChargevsNLoGain","Sum of Lo Gain Charges vs. Event Number Pixel ",
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143 | nqbins,nfirst,nlast);
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144 | fHChargevsNLoGain->SetXTitle("Event Nr.");
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145 | fHChargevsNLoGain->SetYTitle("Sum of Lo Gain FADC slices");
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146 |
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147 | fHChargevsNLoGain->SetDirectory(NULL);
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148 |
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149 | fHiGains = new TArrayF();
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150 | fLoGains = new TArrayF();
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151 |
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152 | }
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153 |
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154 | MHCalibrationPixel::~MHCalibrationPixel()
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155 | {
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156 |
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157 | delete fHChargeHiGain;
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158 | delete fHTimeHiGain;
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159 | delete fHChargevsNHiGain;
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160 |
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161 | delete fHChargeLoGain;
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162 | delete fHTimeLoGain;
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163 | delete fHChargevsNLoGain;
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164 |
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165 | if (fHiGainvsLoGain)
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166 | delete fHiGainvsLoGain;
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167 |
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168 | delete fHiGains;
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169 | delete fLoGains;
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170 |
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171 | if (fChargeGausFit)
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172 | delete fChargeGausFit;
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173 | if (fTimeGausFit)
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174 | delete fTimeGausFit;
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175 | if (fFitLegend)
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176 | delete fFitLegend;
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177 |
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178 | }
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179 |
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180 |
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181 | void MHCalibrationPixel::ChangeHistId(Int_t id)
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182 | {
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183 |
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184 | fPixId = id;
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185 |
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186 | //
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187 | // Names Hi gain Histograms
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188 | //
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189 | TString nameQHiGain = TString(fHChargeHiGain->GetName());
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190 | nameQHiGain += id;
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191 | fHChargeHiGain->SetName(nameQHiGain.Data());
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192 |
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193 | TString nameTHiGain = TString(fHTimeHiGain->GetName());
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194 | nameTHiGain += id;
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195 | fHTimeHiGain->SetName(nameTHiGain.Data());
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196 |
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197 | TString nameQvsNHiGain = TString(fHChargevsNHiGain->GetName());
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198 | nameQvsNHiGain += id;
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199 | fHChargevsNHiGain->SetName(nameQvsNHiGain.Data());
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200 |
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201 | //
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202 | // Title Hi gain Histograms
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203 | //
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204 | TString titleQHiGain = TString(fHChargeHiGain->GetTitle());
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205 | titleQHiGain += id;
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206 | fHChargeHiGain->SetTitle(titleQHiGain.Data());
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207 |
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208 | TString titleTHiGain = TString(fHTimeHiGain->GetTitle());
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209 | titleTHiGain += id;
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210 | fHTimeHiGain->SetTitle(titleTHiGain.Data());
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211 |
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212 | TString titleQvsNHiGain = TString(fHChargevsNHiGain->GetTitle());
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213 | titleQvsNHiGain += id;
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214 | fHChargevsNHiGain->SetTitle(titleQvsNHiGain.Data());
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215 |
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216 | //
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217 | // Names Low Gain Histograms
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218 | //
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219 | TString nameQLoGain = TString(fHChargeLoGain->GetName());
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220 | nameQLoGain += id;
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221 | fHChargeLoGain->SetName(nameQLoGain.Data());
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222 |
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223 | TString nameTLoGain = TString(fHTimeLoGain->GetName());
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224 | nameTLoGain += id;
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225 | fHTimeLoGain->SetName(nameTLoGain.Data());
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226 |
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227 | TString nameQvsNLoGain = TString(fHChargevsNLoGain->GetName());
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228 | nameQvsNLoGain += id;
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229 | fHChargevsNLoGain->SetName(nameQvsNLoGain.Data());
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230 |
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231 | //
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232 | // Titles Low Gain Histograms
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233 | //
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234 | TString titleQLoGain = TString(fHChargeLoGain->GetTitle());
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235 | titleQLoGain += id;
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236 | fHChargeLoGain->SetTitle(titleQLoGain.Data());
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237 |
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238 | TString titleTLoGain = TString(fHTimeLoGain->GetTitle());
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239 | titleTLoGain += id;
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240 | fHTimeLoGain->SetTitle(titleTLoGain.Data());
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241 |
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242 | TString titleQvsNLoGain = TString(fHChargevsNLoGain->GetTitle());
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243 | titleQvsNLoGain += id;
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244 | fHChargevsNLoGain->SetTitle(titleQvsNLoGain.Data());
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245 | }
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246 |
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247 |
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248 | void MHCalibrationPixel::Reset()
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249 | {
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250 |
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251 | for (Int_t i = fHChargeHiGain->FindBin(fChargeFirstHiGain);
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252 | i <= fHChargeHiGain->FindBin(fChargeLastHiGain); i++)
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253 | fHChargeHiGain->SetBinContent(i, 1.e-20);
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254 |
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255 | for (Int_t i = 0; i < 16; i++)
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256 | fHTimeHiGain->SetBinContent(i, 1.e-20);
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257 |
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258 | fChargeLastHiGain = 9999.5;
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259 |
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260 | fHChargeHiGain->GetXaxis()->SetRangeUser(0.,fChargeLastHiGain);
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261 |
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262 | for (Int_t i = fHChargeLoGain->FindBin(fChargeFirstLoGain);
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263 | i <= fHChargeLoGain->FindBin(fChargeLastLoGain); i++)
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264 | fHChargeLoGain->SetBinContent(i, 1.e-20);
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265 |
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266 | for (Int_t i = 0; i < 16; i++)
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267 | fHTimeLoGain->SetBinContent(i, 1.e-20);
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268 |
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269 | fChargeLastLoGain = 9999.5;
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270 |
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271 | fHChargeLoGain->GetXaxis()->SetRangeUser(0.,fChargeLastLoGain);
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272 |
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273 | return;
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274 | }
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275 |
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276 |
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277 | // -------------------------------------------------------------------------
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278 | //
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279 | // Set the binnings and prepare the filling of the histograms
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280 | //
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281 | Bool_t MHCalibrationPixel::SetupFill(const MParList *plist)
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282 | {
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283 |
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284 | fHChargeHiGain->Reset();
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285 | fHTimeHiGain->Reset();
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286 | fHChargeLoGain->Reset();
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287 | fHTimeLoGain->Reset();
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288 |
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289 | return kTRUE;
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290 | }
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291 |
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292 |
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293 | Bool_t MHCalibrationPixel::UseLoGain()
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294 | {
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295 |
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296 | if (fHChargeHiGain->GetEntries() > fHChargeLoGain->GetEntries())
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297 | {
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298 | fUseLoGain = kFALSE;
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299 | return kFALSE;
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300 | }
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301 | else
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302 | {
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303 | fUseLoGain = kTRUE;
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304 | return kTRUE;
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305 | }
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306 | }
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307 |
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308 | void MHCalibrationPixel::SetPointInGraph(Float_t qhi,Float_t qlo)
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309 | {
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310 |
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311 | fHiGains->Set(++fTotalEntries);
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312 | fLoGains->Set(fTotalEntries);
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313 |
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314 | fHiGains->AddAt(qhi,fTotalEntries-1);
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315 | fLoGains->AddAt(qlo,fTotalEntries-1);
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316 |
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317 | }
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318 |
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319 |
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320 | // -------------------------------------------------------------------------
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321 | //
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322 | // Draw a legend with the fit results
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323 | //
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324 | void MHCalibrationPixel::DrawLegend()
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325 | {
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326 |
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327 | fFitLegend = new TPaveText(0.05,0.05,0.95,0.95);
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328 |
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329 | if (fFitOK)
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330 | fFitLegend->SetFillColor(80);
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331 | else
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332 | fFitLegend->SetFillColor(2);
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333 |
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334 | fFitLegend->SetLabel("Results of the Gauss Fit:");
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335 | fFitLegend->SetTextSize(0.05);
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336 |
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337 | const TString line1 =
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338 | Form("Mean: Q_{#mu} = %2.2f #pm %2.2f",fChargeMean,fChargeMeanErr);
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339 |
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340 | fFitLegend->AddText(line1);
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341 |
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342 |
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343 | const TString line4 =
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344 | Form("Sigma: #sigma_{Q} = %2.2f #pm %2.2f",fChargeSigma,fChargeSigmaErr);
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345 |
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346 | fFitLegend->AddText(line4);
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347 |
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348 |
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349 | const TString line7 =
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350 | Form("#chi^{2} / N_{dof}: %4.2f / %3i",fChargeChisquare,fChargeNdf);
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351 |
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352 | fFitLegend->AddText(line7);
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353 |
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354 |
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355 | const TString line8 =
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356 | Form("Probability: %4.3f ",fChargeProb);
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357 |
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358 | fFitLegend->AddText(line8);
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359 |
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360 | if (fFitOK)
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361 | fFitLegend->AddText("Result of the Fit: OK");
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362 | else
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363 | fFitLegend->AddText("Result of the Fit: NOT OK");
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364 |
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365 | fFitLegend->SetBit(kCanDelete);
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366 | fFitLegend->Draw();
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367 |
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368 | }
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369 |
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370 |
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371 | // -------------------------------------------------------------------------
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372 | //
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373 | // Draw the histogram
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374 | //
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375 | void MHCalibrationPixel::Draw(Option_t *opt)
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376 | {
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377 |
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378 | if (!fHiGainvsLoGain)
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379 | {
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380 |
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381 | // Create TGraph, we set the points later, get hold of the number of points with fTotalEntries
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382 | fHiGainvsLoGain = new TGraph(fTotalEntries,fHiGains->GetArray(),fLoGains->GetArray());
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383 | fHiGainvsLoGain->SetName("HiGainvsLoGain");
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384 | fHiGainvsLoGain->SetTitle("Plot the High Gain vs. Low Gain");
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385 | fHiGainvsLoGain->GetXaxis()->Set(300,0.,1500.);
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386 | fHiGainvsLoGain->GetYaxis()->Set(400,0.,2000.);
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387 | fHiGainvsLoGain->GetXaxis()->SetTitle("Sum of Charges High Gain");
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388 | fHiGainvsLoGain->GetYaxis()->SetTitle("Sum of Charges Low Gain");
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389 | fHiGainvsLoGain->SetMarkerStyle(7);
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390 |
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391 | }
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392 |
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393 | gStyle->SetOptFit(0);
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394 | gStyle->SetOptStat(1111111);
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395 |
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396 | TCanvas *c = MakeDefCanvas(this,600,900);
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397 |
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398 | gROOT->SetSelectedPad(NULL);
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399 |
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400 | c->Divide(2,4);
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401 |
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402 | c->cd(1);
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403 | gPad->SetBorderMode(0);
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404 | gPad->SetLogy(1);
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405 | gPad->SetTicks();
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406 |
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407 | fHChargeHiGain->DrawCopy(opt);
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408 |
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409 | c->Modified();
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410 | c->Update();
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411 |
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412 | if (fUseLoGain)
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413 | {
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414 | c->cd(2);
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415 | gPad->SetLogy(1);
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416 | gPad->SetTicks();
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417 | fHChargeLoGain->DrawCopy(opt);
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418 |
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419 | if (fChargeGausFit)
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420 | {
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421 | if (fFitOK)
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422 | fChargeGausFit->SetLineColor(kGreen);
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423 | else
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424 | fChargeGausFit->SetLineColor(kRed);
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425 |
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426 | fChargeGausFit->DrawCopy("same");
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427 | }
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428 | c->Modified();
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429 | c->Update();
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430 |
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431 | c->cd(3);
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432 | gROOT->SetSelectedPad(NULL);
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433 | gStyle->SetOptFit();
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434 | fHiGainvsLoGain->DrawClone("Apq")->SetBit(kCanDelete);
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435 | fHiGainvsLoGain->Fit("p1","q");
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436 | gPad->Modified();
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437 | gPad->Update();
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438 |
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439 | c->cd(4);
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440 | DrawLegend();
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441 |
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442 | }
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443 | else
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444 | {
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445 | if (fChargeGausFit)
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446 | {
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447 | if (fFitOK)
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448 | fChargeGausFit->SetLineColor(kGreen);
|
---|
449 | else
|
---|
450 | fChargeGausFit->SetLineColor(kRed);
|
---|
451 |
|
---|
452 | fChargeGausFit->DrawCopy("same");
|
---|
453 | }
|
---|
454 | c->cd(2);
|
---|
455 | gPad->SetLogy(1);
|
---|
456 | gPad->SetTicks();
|
---|
457 |
|
---|
458 | fHChargeLoGain->DrawCopy(opt);
|
---|
459 | c->Modified();
|
---|
460 | c->Update();
|
---|
461 |
|
---|
462 | c->cd(3);
|
---|
463 | DrawLegend();
|
---|
464 |
|
---|
465 | c->cd(4);
|
---|
466 |
|
---|
467 | gROOT->SetSelectedPad(NULL);
|
---|
468 | gStyle->SetOptFit();
|
---|
469 | fHiGainvsLoGain->DrawClone("Apq")->SetBit(kCanDelete);
|
---|
470 | fHiGainvsLoGain->Fit("p1","q");
|
---|
471 | gPad->Modified();
|
---|
472 | gPad->Update();
|
---|
473 |
|
---|
474 |
|
---|
475 | }
|
---|
476 |
|
---|
477 | c->Modified();
|
---|
478 | c->Update();
|
---|
479 |
|
---|
480 | c->cd(5);
|
---|
481 | gStyle->SetOptStat(1111111);
|
---|
482 |
|
---|
483 | gPad->SetLogy(1);
|
---|
484 | fHTimeHiGain->DrawCopy(opt);
|
---|
485 | c->Modified();
|
---|
486 | c->Update();
|
---|
487 |
|
---|
488 | if (fUseLoGain)
|
---|
489 | {
|
---|
490 |
|
---|
491 | c->cd(6);
|
---|
492 | gPad->SetLogy(1);
|
---|
493 | fHTimeLoGain->DrawCopy(opt);
|
---|
494 | c->Modified();
|
---|
495 | c->Update();
|
---|
496 |
|
---|
497 | if (fTimeGausFit)
|
---|
498 | {
|
---|
499 | if (fTimeChisquare > 20.)
|
---|
500 | fTimeGausFit->SetLineColor(kRed);
|
---|
501 | else
|
---|
502 | fTimeGausFit->SetLineColor(kGreen);
|
---|
503 |
|
---|
504 | fTimeGausFit->DrawCopy("same");
|
---|
505 | c->Modified();
|
---|
506 | c->Update();
|
---|
507 | }
|
---|
508 | }
|
---|
509 | else
|
---|
510 | {
|
---|
511 | if (fTimeGausFit)
|
---|
512 | {
|
---|
513 | if (fTimeChisquare > 20.)
|
---|
514 | fTimeGausFit->SetLineColor(kRed);
|
---|
515 | else
|
---|
516 | fTimeGausFit->SetLineColor(kGreen);
|
---|
517 |
|
---|
518 | fTimeGausFit->DrawCopy("same");
|
---|
519 | c->Modified();
|
---|
520 | c->Update();
|
---|
521 | }
|
---|
522 |
|
---|
523 | c->cd(6);
|
---|
524 | gPad->SetLogy(1);
|
---|
525 | fHTimeLoGain->DrawCopy(opt);
|
---|
526 | c->Modified();
|
---|
527 | c->Update();
|
---|
528 |
|
---|
529 | }
|
---|
530 | c->Modified();
|
---|
531 | c->Update();
|
---|
532 |
|
---|
533 | c->cd(7);
|
---|
534 | fHChargevsNHiGain->DrawCopy(opt);
|
---|
535 | c->Modified();
|
---|
536 | c->Update();
|
---|
537 |
|
---|
538 | c->cd(8);
|
---|
539 | fHChargevsNLoGain->DrawCopy(opt);
|
---|
540 | c->Modified();
|
---|
541 | c->Update();
|
---|
542 |
|
---|
543 |
|
---|
544 | }
|
---|
545 |
|
---|
546 |
|
---|
547 |
|
---|
548 | Bool_t MHCalibrationPixel::FitTimeHiGain(Axis_t rmin, Axis_t rmax, Option_t *option)
|
---|
549 | {
|
---|
550 |
|
---|
551 | if (fTimeGausFit)
|
---|
552 | return kFALSE;
|
---|
553 |
|
---|
554 | rmin = (rmin != 0.) ? rmin : 3.;
|
---|
555 | rmax = (rmax != 0.) ? rmax : 9.;
|
---|
556 |
|
---|
557 | const Stat_t entries = fHTimeHiGain->GetEntries();
|
---|
558 | const Double_t mu_guess = fHTimeHiGain->GetBinCenter(fHTimeHiGain->GetMaximumBin());
|
---|
559 | const Double_t sigma_guess = (rmax - rmin)/2.;
|
---|
560 | const Double_t area_guess = entries/gkSq2Pi;
|
---|
561 |
|
---|
562 | TString name = TString("GausTime");
|
---|
563 | name += fPixId;
|
---|
564 | fTimeGausFit = new TF1(name.Data(),"gaus",rmin,rmax);
|
---|
565 |
|
---|
566 | if (!fTimeGausFit)
|
---|
567 | {
|
---|
568 | *fLog << err << dbginf << "Could not create fit function for Gauss fit" << endl;
|
---|
569 | return kFALSE;
|
---|
570 | }
|
---|
571 |
|
---|
572 | fTimeGausFit->SetParameters(area_guess,mu_guess,sigma_guess);
|
---|
573 | fTimeGausFit->SetParNames("Area","#mu","#sigma");
|
---|
574 | fTimeGausFit->SetParLimits(0,0.,entries);
|
---|
575 | fTimeGausFit->SetParLimits(1,rmin,rmax);
|
---|
576 | fTimeGausFit->SetParLimits(2,0.,(rmax-rmin));
|
---|
577 | fTimeGausFit->SetRange(rmin,rmax);
|
---|
578 |
|
---|
579 | fHTimeHiGain->Fit(fTimeGausFit,option);
|
---|
580 |
|
---|
581 | rmin = fTimeGausFit->GetParameter(1) - 3.*fTimeGausFit->GetParameter(2);
|
---|
582 | rmax = fTimeGausFit->GetParameter(1) + 3.*fTimeGausFit->GetParameter(2);
|
---|
583 | fTimeGausFit->SetRange(rmin,rmax);
|
---|
584 |
|
---|
585 | fHTimeHiGain->Fit(fTimeGausFit,option);
|
---|
586 |
|
---|
587 | fTimeChisquare = fTimeGausFit->GetChisquare();
|
---|
588 | fTimeNdf = fTimeGausFit->GetNDF();
|
---|
589 | fTimeProb = fTimeGausFit->GetProb();
|
---|
590 |
|
---|
591 | fTimeMean = fTimeGausFit->GetParameter(1);
|
---|
592 | fTimeSigma = fTimeGausFit->GetParameter(2);
|
---|
593 |
|
---|
594 | if (fTimeChisquare > 20.) // Cannot use Probability because Ndf is sometimes < 1
|
---|
595 | {
|
---|
596 | *fLog << warn << "Fit of the Arrival times failed ! " << endl;
|
---|
597 | return kFALSE;
|
---|
598 | }
|
---|
599 |
|
---|
600 | return kTRUE;
|
---|
601 |
|
---|
602 | }
|
---|
603 |
|
---|
604 | Bool_t MHCalibrationPixel::FitTimeLoGain(Axis_t rmin, Axis_t rmax, Option_t *option)
|
---|
605 | {
|
---|
606 |
|
---|
607 | if (fTimeGausFit)
|
---|
608 | return kFALSE;
|
---|
609 |
|
---|
610 | rmin = (rmin != 0.) ? rmin : 3.;
|
---|
611 | rmax = (rmax != 0.) ? rmax : 9.;
|
---|
612 |
|
---|
613 | const Stat_t entries = fHTimeLoGain->GetEntries();
|
---|
614 | const Double_t mu_guess = fHTimeLoGain->GetBinCenter(fHTimeLoGain->GetMaximumBin());
|
---|
615 | const Double_t sigma_guess = (rmax - rmin)/2.;
|
---|
616 | const Double_t area_guess = entries/gkSq2Pi;
|
---|
617 |
|
---|
618 | TString name = TString("GausTime");
|
---|
619 | name += fPixId;
|
---|
620 | fTimeGausFit = new TF1(name.Data(),"gaus",rmin,rmax);
|
---|
621 |
|
---|
622 | if (!fTimeGausFit)
|
---|
623 | {
|
---|
624 | *fLog << err << dbginf << "Could not create fit function for Gauss fit" << endl;
|
---|
625 | return kFALSE;
|
---|
626 | }
|
---|
627 |
|
---|
628 | fTimeGausFit->SetParameters(area_guess,mu_guess,sigma_guess);
|
---|
629 | fTimeGausFit->SetParNames("Area","#mu","#sigma");
|
---|
630 | fTimeGausFit->SetParLimits(0,0.,entries);
|
---|
631 | fTimeGausFit->SetParLimits(1,rmin,rmax);
|
---|
632 | fTimeGausFit->SetParLimits(2,0.,(rmax-rmin));
|
---|
633 | fTimeGausFit->SetRange(rmin,rmax);
|
---|
634 |
|
---|
635 | fHTimeLoGain->Fit(fTimeGausFit,option);
|
---|
636 |
|
---|
637 | rmin = fTimeGausFit->GetParameter(1) - 3.*fTimeGausFit->GetParameter(2);
|
---|
638 | rmax = fTimeGausFit->GetParameter(1) + 3.*fTimeGausFit->GetParameter(2);
|
---|
639 | fTimeGausFit->SetRange(rmin,rmax);
|
---|
640 |
|
---|
641 | fHTimeLoGain->Fit(fTimeGausFit,option);
|
---|
642 |
|
---|
643 | fTimeChisquare = fTimeGausFit->GetChisquare();
|
---|
644 | fTimeNdf = fTimeGausFit->GetNDF();
|
---|
645 | fTimeProb = fTimeGausFit->GetProb();
|
---|
646 |
|
---|
647 | fTimeMean = fTimeGausFit->GetParameter(1);
|
---|
648 | fTimeSigma = fTimeGausFit->GetParameter(2);
|
---|
649 |
|
---|
650 | if (fTimeChisquare > 20.) // Cannot use Probability because Ndf is sometimes < 1
|
---|
651 | {
|
---|
652 | *fLog << warn << "Fit of the Arrival times failed ! " << endl;
|
---|
653 | return kFALSE;
|
---|
654 | }
|
---|
655 |
|
---|
656 | return kTRUE;
|
---|
657 |
|
---|
658 | }
|
---|
659 |
|
---|
660 | Bool_t MHCalibrationPixel::FitChargeHiGain(Option_t *option)
|
---|
661 | {
|
---|
662 |
|
---|
663 | if (fChargeGausFit)
|
---|
664 | return kFALSE;
|
---|
665 |
|
---|
666 | //
|
---|
667 | // Get the fitting ranges
|
---|
668 | //
|
---|
669 | Axis_t rmin = (fLowerFitRange != 0.) ? fLowerFitRange : fChargeFirstHiGain;
|
---|
670 | Axis_t rmax = 0.;
|
---|
671 |
|
---|
672 | //
|
---|
673 | // First guesses for the fit (should be as close to reality as possible,
|
---|
674 | // otherwise the fit goes gaga because of high number of dimensions ...
|
---|
675 | //
|
---|
676 | const Stat_t entries = fHChargeHiGain->GetEntries();
|
---|
677 | const Double_t area_guess = entries/gkSq2Pi;
|
---|
678 | const Double_t mu_guess = fHChargeHiGain->GetBinCenter(fHChargeHiGain->GetMaximumBin());
|
---|
679 | const Double_t sigma_guess = mu_guess/15.;
|
---|
680 |
|
---|
681 | TString name = TString("ChargeGausFit");
|
---|
682 | name += fPixId;
|
---|
683 |
|
---|
684 | fChargeGausFit = new TF1(name.Data(),"gaus",rmin,fChargeLastHiGain);
|
---|
685 |
|
---|
686 | if (!fChargeGausFit)
|
---|
687 | {
|
---|
688 | *fLog << err << dbginf << "Could not create fit function for Gauss fit" << endl;
|
---|
689 | return kFALSE;
|
---|
690 | }
|
---|
691 |
|
---|
692 | fChargeGausFit->SetParameters(area_guess,mu_guess,sigma_guess);
|
---|
693 | fChargeGausFit->SetParNames("Area","#mu","#sigma");
|
---|
694 | fChargeGausFit->SetParLimits(0,0.,entries);
|
---|
695 | fChargeGausFit->SetParLimits(1,rmin,fChargeLastHiGain);
|
---|
696 | fChargeGausFit->SetParLimits(2,0.,fChargeLastHiGain-rmin);
|
---|
697 | fChargeGausFit->SetRange(rmin,fChargeLastHiGain);
|
---|
698 |
|
---|
699 | fHChargeHiGain->Fit(fChargeGausFit,option);
|
---|
700 |
|
---|
701 | Axis_t rtry = fChargeGausFit->GetParameter(1) - 2.0*fChargeGausFit->GetParameter(2);
|
---|
702 |
|
---|
703 | rmin = (rtry < rmin ? rmin : rtry);
|
---|
704 | rmax = fChargeGausFit->GetParameter(1) + 3.5*fChargeGausFit->GetParameter(2);
|
---|
705 | fChargeGausFit->SetRange(rmin,rmax);
|
---|
706 |
|
---|
707 | fHChargeHiGain->Fit(fChargeGausFit,option);
|
---|
708 |
|
---|
709 | fChargeChisquare = fChargeGausFit->GetChisquare();
|
---|
710 | fChargeNdf = fChargeGausFit->GetNDF();
|
---|
711 | fChargeProb = fChargeGausFit->GetProb();
|
---|
712 | fChargeMean = fChargeGausFit->GetParameter(1);
|
---|
713 | fChargeMeanErr = fChargeGausFit->GetParError(1);
|
---|
714 | fChargeSigma = fChargeGausFit->GetParameter(2);
|
---|
715 | fChargeSigmaErr = fChargeGausFit->GetParError(2);
|
---|
716 |
|
---|
717 | //
|
---|
718 | // The fit result is accepted under condition
|
---|
719 | // The Probability is greater than gkProbLimit (default 0.01 == 99%)
|
---|
720 | //
|
---|
721 | if (fChargeProb < gkProbLimit)
|
---|
722 | {
|
---|
723 | *fLog << warn << "Prob: " << fChargeProb << " is smaller than the allowed value: " << gkProbLimit << endl;
|
---|
724 | fFitOK = kFALSE;
|
---|
725 | return kFALSE;
|
---|
726 | }
|
---|
727 |
|
---|
728 | fFitOK = kTRUE;
|
---|
729 |
|
---|
730 | return kTRUE;
|
---|
731 | }
|
---|
732 |
|
---|
733 |
|
---|
734 | Bool_t MHCalibrationPixel::FitChargeLoGain(Option_t *option)
|
---|
735 | {
|
---|
736 |
|
---|
737 | if (fChargeGausFit)
|
---|
738 | return kFALSE;
|
---|
739 |
|
---|
740 | //
|
---|
741 | // Get the fitting ranges
|
---|
742 | //
|
---|
743 | Axis_t rmin = (fLowerFitRange != 0.) ? fLowerFitRange : fChargeFirstLoGain;
|
---|
744 | Axis_t rmax = 0.;
|
---|
745 |
|
---|
746 | //
|
---|
747 | // First guesses for the fit (should be as close to reality as possible,
|
---|
748 | // otherwise the fit goes gaga because of high number of dimensions ...
|
---|
749 | //
|
---|
750 | const Stat_t entries = fHChargeLoGain->GetEntries();
|
---|
751 | const Double_t area_guess = entries/gkSq2Pi;
|
---|
752 | const Double_t mu_guess = fHChargeLoGain->GetBinCenter(fHChargeLoGain->GetMaximumBin());
|
---|
753 | const Double_t sigma_guess = mu_guess/15.;
|
---|
754 |
|
---|
755 | TString name = TString("ChargeGausFit");
|
---|
756 | name += fPixId;
|
---|
757 |
|
---|
758 | fChargeGausFit = new TF1(name.Data(),"gaus",rmin,fChargeLastLoGain);
|
---|
759 |
|
---|
760 | if (!fChargeGausFit)
|
---|
761 | {
|
---|
762 | *fLog << err << dbginf << "Could not create fit function for Gauss fit" << endl;
|
---|
763 | return kFALSE;
|
---|
764 | }
|
---|
765 |
|
---|
766 | fChargeGausFit->SetParameters(area_guess,mu_guess,sigma_guess);
|
---|
767 | fChargeGausFit->SetParNames("Area","#mu","#sigma");
|
---|
768 | fChargeGausFit->SetParLimits(0,0.,entries);
|
---|
769 | fChargeGausFit->SetParLimits(1,rmin,fChargeLastLoGain);
|
---|
770 | fChargeGausFit->SetParLimits(2,0.,fChargeLastLoGain-rmin);
|
---|
771 | fChargeGausFit->SetRange(rmin,fChargeLastLoGain);
|
---|
772 |
|
---|
773 | fHChargeLoGain->Fit(fChargeGausFit,option);
|
---|
774 |
|
---|
775 | Axis_t rtry = fChargeGausFit->GetParameter(1) - 2.*fChargeGausFit->GetParameter(2);
|
---|
776 |
|
---|
777 | rmin = (rtry < rmin ? rmin : rtry);
|
---|
778 | rmax = fChargeGausFit->GetParameter(1) + 3.5*fChargeGausFit->GetParameter(2);
|
---|
779 | fChargeGausFit->SetRange(rmin,rmax);
|
---|
780 |
|
---|
781 | fHChargeLoGain->Fit(fChargeGausFit,option);
|
---|
782 |
|
---|
783 | // rmin = fChargeGausFit->GetParameter(1) - 2.5*fChargeGausFit->GetParameter(2);
|
---|
784 | // rmax = fChargeGausFit->GetParameter(1) + 2.5*fChargeGausFit->GetParameter(2);
|
---|
785 | // fChargeGausFit->SetRange(rmin,rmax);
|
---|
786 |
|
---|
787 | // fHChargeLoGain->Fit(fChargeGausFit,option);
|
---|
788 |
|
---|
789 | fChargeChisquare = fChargeGausFit->GetChisquare();
|
---|
790 | fChargeNdf = fChargeGausFit->GetNDF();
|
---|
791 | fChargeProb = fChargeGausFit->GetProb();
|
---|
792 | fChargeMean = fChargeGausFit->GetParameter(1);
|
---|
793 | fChargeMeanErr = fChargeGausFit->GetParError(1);
|
---|
794 | fChargeSigma = fChargeGausFit->GetParameter(2);
|
---|
795 | fChargeSigmaErr = fChargeGausFit->GetParError(2);
|
---|
796 |
|
---|
797 | //
|
---|
798 | // The fit result is accepted under condition
|
---|
799 | // The Probability is greater than gkProbLimit (default 0.01 == 99%)
|
---|
800 | //
|
---|
801 | if (fChargeProb < gkProbLimit)
|
---|
802 | {
|
---|
803 | *fLog << warn << "Prob: " << fChargeProb << " is smaller than the allowed value: " << gkProbLimit << endl;
|
---|
804 | fFitOK = kFALSE;
|
---|
805 | return kFALSE;
|
---|
806 | }
|
---|
807 |
|
---|
808 |
|
---|
809 | fFitOK = kTRUE;
|
---|
810 |
|
---|
811 | return kTRUE;
|
---|
812 | }
|
---|
813 |
|
---|
814 |
|
---|
815 | void MHCalibrationPixel::CutAllEdges()
|
---|
816 | {
|
---|
817 |
|
---|
818 | Int_t nbins = 30;
|
---|
819 |
|
---|
820 | CutEdges(fHChargeHiGain,nbins);
|
---|
821 |
|
---|
822 | fChargeFirstHiGain = fHChargeHiGain->GetBinLowEdge(fHChargeHiGain->GetXaxis()->GetFirst());
|
---|
823 | fChargeLastHiGain = fHChargeHiGain->GetBinLowEdge(fHChargeHiGain->GetXaxis()->GetLast())
|
---|
824 | +fHChargeHiGain->GetBinWidth(0);
|
---|
825 | fChargeNbinsHiGain = nbins;
|
---|
826 |
|
---|
827 | CutEdges(fHChargeLoGain,nbins);
|
---|
828 |
|
---|
829 | fChargeFirstLoGain = fHChargeLoGain->GetBinLowEdge(fHChargeLoGain->GetXaxis()->GetFirst());
|
---|
830 | fChargeLastLoGain = fHChargeLoGain->GetBinLowEdge(fHChargeLoGain->GetXaxis()->GetLast())
|
---|
831 | +fHChargeLoGain->GetBinWidth(0);
|
---|
832 | fChargeNbinsLoGain = nbins;
|
---|
833 |
|
---|
834 | CutEdges(fHChargevsNHiGain,0);
|
---|
835 | CutEdges(fHChargevsNLoGain,0);
|
---|
836 |
|
---|
837 | }
|
---|
838 |
|
---|
839 | void MHCalibrationPixel::PrintChargeFitResult()
|
---|
840 | {
|
---|
841 |
|
---|
842 | *fLog << "Results of the Summed Charges Fit: " << endl;
|
---|
843 | *fLog << "Chisquare: " << fChargeChisquare << endl;
|
---|
844 | *fLog << "DoF: " << fChargeNdf << endl;
|
---|
845 | *fLog << "Probability: " << fChargeProb << endl;
|
---|
846 | *fLog << endl;
|
---|
847 |
|
---|
848 | }
|
---|
849 |
|
---|
850 | void MHCalibrationPixel::PrintTimeFitResult()
|
---|
851 | {
|
---|
852 |
|
---|
853 | *fLog << "Results of the Time Slices Fit: " << endl;
|
---|
854 | *fLog << "Chisquare: " << fTimeChisquare << endl;
|
---|
855 | *fLog << "Ndf: " << fTimeNdf << endl;
|
---|
856 | *fLog << "Probability: " << fTimeProb << endl;
|
---|
857 | *fLog << endl;
|
---|
858 |
|
---|
859 | }
|
---|