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 02/2004 <mailto:markus@ifae.es>
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19 | !
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20 | ! Copyright: MAGIC Software Development, 2000-2004
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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 | // MHCalibrationPix
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28 | //
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29 | // A base class for events which are believed to follow a Gaussian distribution
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30 | // with time, e.g. calibration events, observables containing white noise, ...
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31 | //
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32 | // MHCalibrationPix derives from MHGausEvents, thus all features of
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33 | // MHGausEvents can be used by a class deriving from MHCalibrationPix
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34 | //
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35 | // See also: MHGausEvents
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36 | //
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37 | //////////////////////////////////////////////////////////////////////////////
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38 | #include "MHCalibrationPix.h"
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39 |
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40 | #include <TH1.h>
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41 | #include <TF1.h>
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42 | #include <TGraph.h>
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43 |
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44 | #include "MLog.h"
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45 | #include "MLogManip.h"
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46 |
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47 | ClassImp(MHCalibrationPix);
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48 |
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49 | using namespace std;
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50 |
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51 | const Float_t MHCalibrationPix::fgBlackoutLimit = 5.;
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52 | const Float_t MHCalibrationPix::fgPickupLimit = 5.;
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53 | // --------------------------------------------------------------------------
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54 | //
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55 | // Default Constructor.
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56 | // Sets:
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57 | // - the default number for fPickupLimit (fgPickupLimit)
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58 | // - the default number for fBlackoutLimit (fgBlackoutLimit)
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59 | //
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60 | // Initializes:
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61 | // - all variables to 0.
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62 | //
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63 | MHCalibrationPix::MHCalibrationPix(const char *name, const char *title)
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64 | : fPixId(-1)
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65 | {
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66 |
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67 | fName = name ? name : "MHCalibrationPix";
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68 | fTitle = title ? title : "Calibration histogram events";
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69 |
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70 | Clear();
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71 |
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72 | SetBlackoutLimit();
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73 | SetPickupLimit();
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74 | }
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75 |
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76 | // --------------------------------------------------------------------------
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77 | //
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78 | // Default Clear(), can be overloaded.
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79 | //
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80 | // Sets:
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81 | // - all other pointers to NULL
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82 | // - all variables to 0., except fPixId to -1
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83 | // - all flags to kFALSE
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84 | //
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85 | // - all pointers
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86 | //
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87 | void MHCalibrationPix::Clear(Option_t *o)
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88 | {
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89 |
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90 | MHGausEvents::Clear();
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91 | fSaturated = 0;
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92 | }
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93 |
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94 | // -----------------------------------------------------------------------------
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95 | //
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96 | // Bypasses the Gauss fit by taking mean and RMS from the histogram
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97 | //
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98 | // Errors are determined in the following way:
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99 | // MeanErr = RMS / Sqrt(entries)
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100 | // SigmaErr = RMS / (2.*Sqrt(entries) )
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101 | //
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102 | void MHCalibrationPix::BypassFit()
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103 | {
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104 |
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105 | const Stat_t entries = fHGausHist.GetEntries();
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106 |
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107 | if (entries <= 0.)
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108 | {
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109 | *fLog << warn << GetDescriptor()
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110 | << ": Cannot bypass fit. Number of entries smaller or equal 0 in pixel: " << fPixId << endl;
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111 | return;
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112 | }
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113 |
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114 | fMean = fHGausHist.GetMean();
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115 | fMeanErr = fHGausHist.GetRMS() / TMath::Sqrt(entries);
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116 | fSigma = fHGausHist.GetRMS() ;
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117 | fSigmaErr = fHGausHist.GetRMS() / TMath::Sqrt(entries) / 2.;
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118 | }
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119 |
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120 | // --------------------------------------------------------------------------
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121 | //
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122 | // - Set fPixId to id
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123 | //
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124 | // Add id to names and titles of:
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125 | // - fHGausHist
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126 | //
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127 | void MHCalibrationPix::ChangeHistId(const Int_t id)
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128 | {
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129 |
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130 | fPixId = id;
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131 |
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132 | fHGausHist.SetName( Form("%s%d", fHGausHist.GetName(), id));
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133 | fHGausHist.SetTitle( Form("%s%d", fHGausHist.GetTitle(), id));
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134 |
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135 | fName = Form("%s%d", fName.Data(), id);
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136 | fTitle = Form("%s%d", fTitle.Data(), id);
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137 |
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138 | }
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139 |
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140 | // -------------------------------------------------------------------------------
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141 | //
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142 | // Return the number of "blackout" events, which are events with values higher
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143 | // than fBlackoutLimit sigmas from the mean
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144 | //
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145 | //
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146 | const Double_t MHCalibrationPix::GetBlackout() const
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147 | {
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148 |
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149 | if ((fMean == 0.) && (fSigma == 0.))
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150 | return -1.;
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151 |
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152 | const Int_t first = fHGausHist.GetXaxis()->GetFirst();
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153 | const Int_t last = fHGausHist.GetXaxis()->FindBin(fMean-fBlackoutLimit*fSigma);
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154 |
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155 | if (first >= last)
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156 | return 0.;
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157 |
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158 | return fHGausHist.Integral(first, last, "width");
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159 | }
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160 |
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161 |
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162 | // -------------------------------------------------------------------------------
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163 | //
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164 | // Return the number of "pickup" events, which are events with values higher
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165 | // than fPickupLimit sigmas from the mean
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166 | //
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167 | //
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168 | const Double_t MHCalibrationPix::GetPickup() const
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169 | {
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170 |
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171 | if ((fMean == 0.) && (fSigma == 0.))
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172 | return -1.;
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173 |
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174 | const Int_t first = fHGausHist.GetXaxis()->FindBin(fMean+fPickupLimit*fSigma);
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175 | const Int_t last = fHGausHist.GetXaxis()->GetLast();
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176 |
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177 | if (first >= last)
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178 | return 0.;
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179 |
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180 | return fHGausHist.Integral(first, last, "width");
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181 | }
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182 |
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183 |
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184 | // --------------------------------------------------------------------------
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185 | //
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186 | // Re-normalize the results, has to be overloaded
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187 | //
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188 | void MHCalibrationPix::Renorm()
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189 | {
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190 | }
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191 |
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192 | // -----------------------------------------------------------------------------
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193 | //
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194 | // If flag IsGausFitOK() is set (histogram already successfully fitted),
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195 | // returns kTRUE
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196 | //
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197 | // If both fMean and fSigma are still zero, call FitGaus()
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198 | //
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199 | // Repeats the Gauss fit in a smaller range, defined by:
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200 | //
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201 | // min = GetMean() - fBlackoutLimit * GetSigma();
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202 | // max = GetMean() + fPickupLimit * GetSigma();
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203 | //
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204 | // The fit results are retrieved and stored in class-own variables.
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205 | //
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206 | // A flag IsGausFitOK() is set according to whether the fit probability
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207 | // is smaller or bigger than fProbLimit, whether the NDF is bigger than
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208 | // fNDFLimit and whether results are NaNs.
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209 | //
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210 | Bool_t MHCalibrationPix::RepeatFit(const Option_t *option)
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211 | {
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212 |
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213 | if (IsGausFitOK())
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214 | return kTRUE;
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215 |
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216 | if ((fMean == 0.) && (fSigma == 0.))
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217 | return FitGaus();
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218 |
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219 | //
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220 | // Get new fitting ranges
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221 | //
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222 | Axis_t rmin = fMean - fBlackoutLimit * fSigma;
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223 | Axis_t rmax = fMean + fPickupLimit * fSigma;
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224 |
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225 | Axis_t hmin = fHGausHist.GetBinCenter(fHGausHist.GetXaxis()->GetFirst());
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226 | Axis_t hmax = fHGausHist.GetBinCenter(fHGausHist.GetXaxis()->GetLast()) ;
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227 |
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228 | fFGausFit->SetRange(hmin < rmin ? rmin : hmin , hmax > rmax ? rmax : hmax);
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229 |
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230 | fHGausHist.Fit(fFGausFit,option);
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231 |
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232 | fMean = fFGausFit->GetParameter(1);
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233 | fSigma = fFGausFit->GetParameter(2);
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234 | fMeanErr = fFGausFit->GetParError(1) ;
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235 | fSigmaErr = fFGausFit->GetParError(2) ;
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236 | fProb = fFGausFit->GetProb() ;
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237 |
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238 | //
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239 | // The fit result is accepted under condition:
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240 | // 1) The results are not nan's
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241 | // 2) The NDF is not smaller than fNDFLimit (default: fgNDFLimit)
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242 | // 3) The Probability is greater than fProbLimit (default: fgProbLimit)
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243 | //
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244 | if ( TMath::IsNaN ( fMean )
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245 | || TMath::IsNaN ( fMeanErr )
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246 | || TMath::IsNaN ( fProb )
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247 | || TMath::IsNaN ( fSigma )
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248 | || TMath::IsNaN ( fSigmaErr )
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249 | || fFGausFit->GetNDF() < fNDFLimit
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250 | || fProb < fProbLimit )
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251 | return kFALSE;
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252 |
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253 | SetGausFitOK(kTRUE);
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254 | return kTRUE;
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255 |
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256 | }
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257 |
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