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 |
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43 | #include <TF1.h>
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44 | #include <TH2.h>
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45 | #include <TCanvas.h>
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46 | #include <TPad.h>
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47 | #include <TPaveText.h>
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48 |
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49 | #include "MParList.h"
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50 |
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51 | #include "MLog.h"
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52 | #include "MLogManip.h"
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53 |
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54 | ClassImp(MHCalibrationPixel);
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55 |
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56 | using namespace std;
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57 | // --------------------------------------------------------------------------
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58 | //
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59 | // Default Constructor.
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60 | //
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61 | MHCalibrationPixel::MHCalibrationPixel(Int_t pix, const char *name, const char *title)
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62 | : fFitOK(kFALSE), fPixId(pix), fTGausFit(NULL), fQGausFit(NULL), fFitLegend(NULL)
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63 | {
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64 |
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65 | fName = name ? name : "MHCalibrationPixel";
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66 | fTitle = title ? title : "Fill the accumulated charges and times of all events and perform fits";
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67 |
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68 | TString qname = "HQ";
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69 | TString qtitle = "Distribution of Summed FADC Slices Pixel ";
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70 | qname += pix;
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71 | qtitle += pix;
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72 |
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73 | // Create a large number of bins, later we will rebin
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74 | fQfirst = -0.5;
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75 | fQlast = gkStartQlast - 0.5;
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76 | fQnbins = gkStartPixelBinNr;
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77 |
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78 | fHQ = new TH1I( qname.Data(),qtitle.Data(),
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79 | fQnbins,fQfirst,fQlast);
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80 | fHQ->SetXTitle("Sum FADC Slices");
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81 | fHQ->SetYTitle("Nr. of events");
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82 | fHQ->Sumw2();
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83 |
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84 | TString tname = "HT";
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85 | TString ttitle = "Distribution of Mean Arrival Times Pixel ";
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86 | tname += pix;
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87 | ttitle += pix;
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88 |
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89 | Axis_t tfirst = -0.5;
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90 | Axis_t tlast = 15.5;
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91 | Int_t nbins = 16;
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92 |
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93 | fHT = new TH1I(tname.Data(),ttitle.Data(),
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94 | nbins,tfirst,tlast);
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95 | fHT->SetXTitle("Mean Arrival Times [FADC slice nr]");
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96 | fHT->SetYTitle("Nr. of events");
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97 | fHT->Sumw2();
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98 |
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99 | TString qvsnname = "HQvsN";
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100 | TString qvsntitle = "Sum of Charges vs. Event Number Pixel ";
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101 | qvsnname += pix;
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102 | qvsntitle += pix;
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103 |
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104 | // We define a reasonable number and later enlarge it if necessary
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105 | nbins = 20000;
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106 | Axis_t nfirst = -0.5;
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107 | Axis_t nlast = (Axis_t)nbins - 0.5;
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108 |
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109 | fHQvsN = new TH1I(qvsnname.Data(),qvsntitle.Data(),
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110 | nbins,nfirst,nlast);
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111 | fHQvsN->SetXTitle("Event Nr.");
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112 | fHQvsN->SetYTitle("Sum of FADC slices");
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113 |
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114 | fQChisquare = -1.;
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115 | fQProb = -1.;
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116 | fQNdf = -1;
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117 |
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118 | fTChisquare = -1.;
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119 | fTProb = -1.;
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120 | fTNdf = -1;
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121 |
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122 | }
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123 |
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124 | MHCalibrationPixel::~MHCalibrationPixel()
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125 | {
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126 |
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127 | delete fHQ;
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128 | delete fHT;
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129 | delete fHQvsN;
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130 |
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131 | if (fQGausFit)
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132 | delete fQGausFit;
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133 | if (fTGausFit)
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134 | delete fTGausFit;
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135 | if (fFitLegend)
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136 | delete fFitLegend;
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137 |
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138 | }
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139 |
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140 | void MHCalibrationPixel::Reset()
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141 | {
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142 |
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143 | for (Int_t i = fHQ->FindBin(fQfirst); i <= fHQ->FindBin(fQlast); i++)
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144 | fHQ->SetBinContent(i, 1.e-20);
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145 |
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146 | for (Int_t i = 0; i < 16; i++)
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147 | fHT->SetBinContent(i, 1.e-20);
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148 |
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149 | fQlast = gkStartQlast;
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150 |
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151 | fHQ->GetXaxis()->SetRangeUser(0.,fQlast);
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152 |
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153 | return;
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154 | }
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155 |
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156 |
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157 | // -------------------------------------------------------------------------
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158 | //
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159 | // Set the binnings and prepare the filling of the histograms
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160 | //
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161 | Bool_t MHCalibrationPixel::SetupFill(const MParList *plist)
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162 | {
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163 |
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164 | fHQ->Reset();
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165 | fHT->Reset();
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166 |
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167 | return kTRUE;
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168 | }
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169 |
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170 |
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171 |
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172 | // -------------------------------------------------------------------------
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173 | //
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174 | // Draw a legend with the fit results
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175 | //
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176 | void MHCalibrationPixel::DrawLegend()
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177 | {
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178 |
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179 | fFitLegend = new TPaveText(0.05,0.05,0.95,0.95);
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180 |
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181 | if (fFitOK)
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182 | fFitLegend->SetFillColor(80);
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183 | else
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184 | fFitLegend->SetFillColor(2);
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185 |
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186 | fFitLegend->SetLabel("Results of the Gauss Fit:");
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187 | fFitLegend->SetTextSize(0.05);
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188 |
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189 | char line1[32];
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190 | sprintf(line1,"Mean: Q_{#mu} = %2.2f #pm %2.2f",fQMean,fQMeanErr);
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191 | fFitLegend->AddText(line1);
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192 |
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193 | char line4[32];
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194 | sprintf(line4,"Sigma: #sigma_{Q} = %2.2f #pm %2.2f",fQSigma,fQSigmaErr);
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195 | fFitLegend->AddText(line4);
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196 |
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197 | char line7[32];
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198 | sprintf(line7,"#chi^{2} / N_{dof}: %4.2f / %3i",fQChisquare,fQNdf);
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199 | fFitLegend->AddText(line7);
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200 |
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201 | char line8[32];
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202 | sprintf(line8,"Probability: %4.2f ",fQProb);
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203 | fFitLegend->AddText(line8);
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204 |
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205 | if (fFitOK)
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206 | fFitLegend->AddText("Result of the Fit: OK");
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207 | else
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208 | fFitLegend->AddText("Result of the Fit: NOT OK");
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209 |
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210 | fFitLegend->SetBit(kCanDelete);
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211 | fFitLegend->Draw();
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212 |
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213 | }
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214 |
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215 |
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216 | // -------------------------------------------------------------------------
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217 | //
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218 | // Draw the histogram
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219 | //
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220 | void MHCalibrationPixel::Draw(Option_t *opt)
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221 | {
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222 |
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223 | gStyle->SetOptFit(0);
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224 | gStyle->SetOptStat(1111111);
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225 |
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226 | TCanvas *c = MakeDefCanvas(this,600,900);
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227 |
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228 | gROOT->SetSelectedPad(NULL);
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229 |
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230 | c->Divide(2,2);
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231 |
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232 | c->cd(1);
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233 | gPad->SetBorderMode(0);
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234 | gPad->SetLogy(1);
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235 | gPad->SetTicks();
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236 |
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237 | fHQ->DrawCopy(opt);
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238 |
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239 | if (fQGausFit)
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240 | {
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241 | if (fFitOK)
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242 | fQGausFit->SetLineColor(kGreen);
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243 | else
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244 | fQGausFit->SetLineColor(kRed);
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245 |
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246 | fQGausFit->DrawCopy("same");
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247 | c->Modified();
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248 | c->Update();
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249 | }
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250 |
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251 |
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252 | c->cd(2);
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253 | DrawLegend();
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254 | c->Update();
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255 |
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256 | c->cd(3);
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257 | gStyle->SetOptStat(1111111);
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258 |
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259 | gPad->SetLogy(1);
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260 | fHT->DrawCopy(opt);
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261 |
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262 | if (fHT->GetFunction("GausTime"))
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263 | {
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264 | TF1 *tfit = fHT->GetFunction("GausTime");
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265 | if (tfit->GetProb() < 0.01)
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266 | tfit->SetLineColor(kRed);
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267 | else
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268 | tfit->SetLineColor(kGreen);
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269 |
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270 | tfit->DrawCopy("same");
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271 | c->Modified();
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272 | c->Update();
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273 | }
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274 |
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275 | c->Modified();
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276 | c->Update();
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277 |
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278 | c->cd(4);
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279 | fHQvsN->DrawCopy(opt);
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280 | }
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281 |
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282 |
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283 |
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284 | Bool_t MHCalibrationPixel::FitT(Axis_t rmin, Axis_t rmax, Option_t *option)
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285 | {
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286 |
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287 | if (fTGausFit)
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288 | return kFALSE;
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289 |
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290 | rmin = (rmin != 0.) ? rmin : -0.5;
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291 | rmax = (rmax != 0.) ? rmax : 15.5;
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292 |
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293 | const Stat_t entries = fHT->GetEntries();
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294 | const Double_t mu_guess = fHT->GetBinCenter(fHT->GetMaximumBin());
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295 | const Double_t sigma_guess = (rmax - rmin)/2.;
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296 | const Double_t area_guess = entries/gkSq2Pi;
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297 |
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298 | fTGausFit = new TF1("GausTime","gaus",rmin,rmax);
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299 |
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300 | if (!fTGausFit)
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301 | {
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302 | *fLog << err << dbginf << "Could not create fit function for Gauss fit" << endl;
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303 | return kFALSE;
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304 | }
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305 |
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306 | fTGausFit->SetParameters(area_guess,mu_guess,sigma_guess);
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307 | fTGausFit->SetParNames("Area","#mu","#sigma");
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308 | fTGausFit->SetParLimits(0,0.,entries);
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309 | fTGausFit->SetParLimits(1,rmin,rmax);
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310 | fTGausFit->SetParLimits(2,0.,rmax-rmin);
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311 |
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312 | fHT->Fit("GausTime",option);
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313 |
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314 | fTChisquare = fTGausFit->GetChisquare();
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315 | fTNdf = fTGausFit->GetNDF();
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316 | fTProb = fTGausFit->GetProb();
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317 | fTMean = fTGausFit->GetParameter(1);
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318 | fTSigma = fTGausFit->GetParameter(2);
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319 |
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320 | if (fTProb < gkProbLimit)
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321 | {
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322 | *fLog << warn << "Fit of the Arrival times failed ! " << endl;
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323 | return kFALSE;
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324 | }
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325 |
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326 | return kTRUE;
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327 |
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328 | }
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329 |
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330 | Bool_t MHCalibrationPixel::FitQ(Axis_t rmin, Axis_t rmax, Option_t *option)
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331 | {
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332 |
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333 | if (fQGausFit)
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334 | return kFALSE;
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335 |
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336 | //
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337 | // Get the fitting ranges
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338 | //
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339 | rmin = (rmin != 0.) ? rmin : fQfirst;
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340 | rmax = (rmax != 0.) ? rmax : fQlast;
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341 |
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342 | //
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343 | // First guesses for the fit (should be as close to reality as possible,
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344 | // otherwise the fit goes gaga because of high number of dimensions ...
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345 | //
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346 | const Stat_t entries = fHQ->GetEntries();
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347 | const Double_t ar_guess = entries/gkSq2Pi;
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348 | const Double_t mu_guess = fHQ->GetBinCenter(fHQ->GetMaximumBin());
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349 | const Double_t si_guess = mu_guess/500.;
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350 |
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351 | fQGausFit = new TF1("QGausFit","gaus",rmin,rmax);
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352 |
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353 | if (!fQGausFit)
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354 | {
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355 | *fLog << err << dbginf << "Could not create fit function for Gauss fit" << endl;
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356 | return kFALSE;
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357 | }
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358 |
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359 | fQGausFit->SetParameters(ar_guess,mu_guess,si_guess);
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360 | fQGausFit->SetParNames("Area","#mu","#sigma");
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361 | fQGausFit->SetParLimits(0,0.,entries);
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362 | fQGausFit->SetParLimits(1,rmin,rmax);
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363 | fQGausFit->SetParLimits(2,0.,rmax-rmin);
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364 |
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365 | fHQ->Fit("QGausFit",option);
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366 |
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367 | fQChisquare = fQGausFit->GetChisquare();
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368 | fQNdf = fQGausFit->GetNDF();
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369 | fQProb = fQGausFit->GetProb();
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370 | fQMean = fQGausFit->GetParameter(1);
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371 | fQMeanErr = fQGausFit->GetParError(1);
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372 | fQSigma = fQGausFit->GetParameter(2);
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373 | fQSigmaErr = fQGausFit->GetParError(2);
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374 |
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375 | //
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376 | // The fit result is accepted under condition
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377 | // The Probability is greater than gkProbLimit (default 0.01 == 99%)
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378 | //
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379 | if (fQProb < gkProbLimit)
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380 | {
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381 | *fLog << warn << "Prob: " << fQProb << " is smaller than the allowed value: " << gkProbLimit << endl;
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382 | fFitOK = kFALSE;
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383 | return kFALSE;
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384 | }
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385 |
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386 |
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387 | fFitOK = kTRUE;
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388 |
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389 | return kTRUE;
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390 | }
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391 |
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392 |
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393 | void MHCalibrationPixel::CutAllEdges()
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394 | {
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395 |
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396 | //
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397 | // The number 100 is necessary because it is the internal binning
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398 | // of ROOT functions. A call to SetNpx() does NOT help
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399 | // If you find another solution which WORKS!!, please tell me!!
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400 | //
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401 | Int_t nbins = 100;
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402 |
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403 | CutEdges(fHQ,nbins);
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404 |
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405 | fQfirst = fHQ->GetBinLowEdge(fHQ->GetXaxis()->GetFirst());
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406 | fQlast = fHQ->GetBinLowEdge(fHQ->GetXaxis()->GetLast())+fHQ->GetBinWidth(0);
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407 | fQnbins = nbins;
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408 |
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409 | CutEdges(fHQvsN,0);
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410 |
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411 | }
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412 |
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413 | void MHCalibrationPixel::PrintQFitResult()
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414 | {
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415 |
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416 | *fLog << "Results of the Summed Charges Fit: " << endl;
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417 | *fLog << "Chisquare: " << fQChisquare << endl;
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418 | *fLog << "DoF: " << fQNdf << endl;
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419 | *fLog << "Probability: " << fQProb << endl;
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420 | *fLog << endl;
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421 |
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422 | }
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423 |
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424 | void MHCalibrationPixel::PrintTFitResult()
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425 | {
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426 |
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427 | *fLog << "Results of the Arrival Time Slices Fit: " << endl;
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428 | *fLog << "Chisquare: " << fTChisquare << endl;
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429 | *fLog << "Ndf: " << fTNdf << endl;
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430 | *fLog << "Probability: " << fTProb << endl;
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431 | *fLog << endl;
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432 |
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433 | }
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