1 | #ifndef MARS_MJOptimize
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2 | #define MARS_MJOptimize
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3 |
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4 | #ifndef MARS_MJob
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5 | #include "MJob.h"
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6 | #endif
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7 |
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8 | #ifndef ROOT_TArrayD
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9 | #include <TArrayD.h>
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10 | #endif
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11 |
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12 | class TMinuit;
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13 |
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14 | class MAlphaFitter;
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15 |
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16 | class MEvtLoop;
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17 | class MParList;
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18 | class MFilter;
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19 | class MFilterList;
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20 | class MFitParameters;
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21 | class MFitParametersCalc;
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22 |
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23 | class MHMatrix;
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24 | class MGeomCam;
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25 | class MRead;
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26 | class MReadTree;
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27 |
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28 | class MJOptimize : public MJob
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29 | {
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30 | public:
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31 | enum Optimizer_t
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32 | {
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33 | kMigrad, // Minimize by the method of Migrad
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34 | kSimplex, // Minimize by the method of Simplex
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35 | kMinimize, // Migrad + Simplex (if Migrad fails)
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36 | kMinos, // Minos error determination
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37 | kImprove, // Local minimum search
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38 | kSeek, // Minimize by the method of Monte Carlo
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39 | kNone // Skip optimization
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40 | };
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41 |
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42 | private:
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43 | Int_t fDebug; // -1 no output, 0 MJOptimize output, 1 PrintStatistics output
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44 | Int_t fNumEvents;
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45 |
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46 | TList fRules;
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47 | TList fFilter;
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48 | TList fPreCuts;
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49 |
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50 | TList fNamesOn;
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51 | TList fNamesOff;
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52 |
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53 | TString fNameOut;
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54 |
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55 | void AddPoint(TList *l, Int_t idx, Float_t val) const;
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56 | TList *GetPlots() const;
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57 |
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58 | void AddRulesToMatrix(MHMatrix &m) const;
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59 | void SetupFilters(MFilterList &list, MFilter *filter=0) const;
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60 | Bool_t FillMatrix(MReadTree &read, MParList &l, Bool_t userules=kFALSE);
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61 |
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62 | MEvtLoop *fEvtLoop; //!
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63 |
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64 | Bool_t AddSequences(MRead &read, TList &list) const;
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65 |
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66 | // Minuit Interface
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67 | static void fcn(Int_t &npar, Double_t *gin, Double_t &f, Double_t *par, Int_t iflag);
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68 | Double_t Fcn(const TArrayD &par, TMinuit *minuit=0);
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69 |
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70 | Int_t Minuit(TMinuit &minuit, const char *cmd) const;
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71 | Int_t Migrad(TMinuit &minuit) const { return Minuit(minuit, "MIGRAD"); }
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72 | Int_t Simplex(TMinuit &minuit) const { return Minuit(minuit, "SIMPLEX"); }
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73 | Int_t Minimize(TMinuit &minuit) const { return Minuit(minuit, "MINIMIZE"); }
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74 | Int_t Seek(TMinuit &minuit) const { return Minuit(minuit, "SEEK"); }
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75 | Int_t Improve(TMinuit &minuit) const { return Minuit(minuit, "IMPROVE"); }
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76 | Int_t Minos(TMinuit &minuit) const { return Minuit(minuit, "MINOS"); }
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77 |
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78 | TArrayD fParameters; //!
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79 | TArrayD fLimLo; //!
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80 | TArrayD fLimUp; //!
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81 | TArrayD fStep; //!
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82 |
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83 | Optimizer_t fType;
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84 | UInt_t fNumMaxCalls;
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85 | Float_t fTolerance;
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86 | Int_t fTestTrain;
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87 |
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88 | Bool_t Optimize(MEvtLoop &evtloop);
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89 |
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90 | public:
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91 | MJOptimize();
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92 |
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93 | // I/O
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94 | void AddSequenceOn(const char *fname, const char *dir="");
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95 | void AddSequenceOff(const char *fname, const char *dir="");
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96 |
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97 | void ResetSequences();
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98 |
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99 | // Interface for filter cuts
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100 | Int_t AddParameter(const char *rule);
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101 | void AddFilter(const char *rule);
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102 | void AddPreCut(const char *rule);
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103 | void AddPreCut(MFilter *f);
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104 |
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105 | // Steering of optimization
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106 | void SetNumEvents(UInt_t n);
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107 | void SetDebug(UInt_t n);
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108 | void SetNameOut(const char *name="") { fNameOut = name; }
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109 | void SetOptimizer(Optimizer_t o);
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110 | void SetNumMaxCalls(UInt_t num=0) { fNumMaxCalls=num; }
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111 | void SetTolerance(Float_t tol=0) { fTolerance=tol; }
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112 | void EnableTestTrain(Int_t b=2) { fTestTrain=b; }
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113 |
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114 | // Parameter access
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115 | void SetParameters(const TArrayD &par);
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116 | void SetParameter(Int_t idx, Double_t start, Double_t lo=0, Double_t up=0, Double_t step=-1)
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117 | {
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118 | if (fParameters.GetSize()<=idx)
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119 | {
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120 | fParameters.Set(idx+1);
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121 | fLimLo.Set(idx+1);
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122 | fLimUp.Set(idx+1);
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123 | fStep.Set(idx+1);
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124 | }
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125 |
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126 | fParameters[idx] = start;
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127 | fLimLo[idx] = lo;
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128 | fLimUp[idx] = up;
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129 | if (step<=0)
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130 | fStep[idx] = start==0 ? 0.1 : TMath::Abs(start*0.15);
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131 | else
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132 | fStep[idx] = step;
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133 | }
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134 | void FixParameter(Int_t idx, Double_t start, Double_t lo=0, Double_t up=0, Double_t step=-1)
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135 | {
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136 | if (fParameters.GetSize()<=idx)
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137 | {
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138 | fParameters.Set(idx+1);
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139 | fLimLo.Set(idx+1);
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140 | fLimUp.Set(idx+1);
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141 | fStep.Set(idx+1);
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142 | }
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143 |
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144 | fParameters[idx] = start;
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145 | fLimLo[idx] = 0;
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146 | fLimUp[idx] = 0;
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147 | fStep[idx] = 0;
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148 | }
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149 |
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150 | const TArrayD &GetParameters() const { return fParameters; }
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151 |
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152 | // Generalized optimizing routines
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153 | Bool_t Optimize(MParList &list);
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154 |
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155 | // Special optimizing routines
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156 | Bool_t Run(const char *fname, MFilter *filter, MAlphaFitter *fit=0);
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157 | Bool_t Run(const char *fname, MAlphaFitter *fit=0)
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158 | {
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159 | return Run(fname, 0, fit);
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160 | }
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161 |
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162 | Bool_t Run(MFilter *filter, MAlphaFitter *fit=0)
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163 | {
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164 | return Run(0, filter, fit);
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165 | }
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166 | Bool_t Run(MAlphaFitter *fit=0)
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167 | {
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168 | return Run(0, 0, fit);
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169 | }
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170 |
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171 | Bool_t RunOnOff(const char *fname, MFilter *filter, MAlphaFitter *fit=0, const char *tree="Events");
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172 | Bool_t RunOnOff(const char *fname, MAlphaFitter *fit=0, const char *tree="Events")
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173 | {
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174 | return RunOnOff(fname, 0, fit, tree);
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175 | }
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176 | Bool_t RunEnergy(const char *fname, const char *rule);
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177 |
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178 | Bool_t RunOnOff(MFilter *filter, MAlphaFitter *fit=0, const char *tree="Events")
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179 | {
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180 | return RunOnOff(0, filter, fit, tree);
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181 | }
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182 | Bool_t RunOnOff(MAlphaFitter *fit=0, const char *tree="Events")
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183 | {
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184 | return RunOnOff(fit, tree);
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185 | }
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186 | Bool_t RunEnergy(const char *rule)
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187 | {
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188 | return RunEnergy(0, rule);
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189 | }
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190 |
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191 | ClassDef(MJOptimize, 0) // Class for optimization of the Supercuts
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192 | };
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193 |
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194 | #endif
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