1 | #ifndef MARS_MRanForestCalc
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2 | #define MARS_MRanForestCalc
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3 |
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4 | #ifndef MARS_MTask
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5 | #include "MTask.h"
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6 | #endif
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7 |
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8 | #ifndef ROOT_TObjArray
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9 | #include <TObjArray.h>
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10 | #endif
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11 |
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12 | #ifndef ROOT_TArrayD
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13 | #include <TArrayD.h>
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14 | #endif
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15 |
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16 | class MDataArray;
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17 | class MParameterD;
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18 | class MHMatrix;
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19 |
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20 | class MRanForestCalc : public MTask
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21 | {
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22 | public:
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23 | enum EstimationMode_t
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24 | {
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25 | kMean,
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26 | kMaximum,
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27 | kFit
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28 | };
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29 |
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30 | private:
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31 | static const TString gsDefName; //! Default Name
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32 | static const TString gsDefTitle; //! Default Title
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33 | static const TString gsNameOutput; //! Default Output name
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34 |
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35 | Bool_t fDebug; // Debugging of eventloop while training on/off
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36 |
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37 | TString fFileName; // File name to forest
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38 | TObjArray fEForests; // List of forests
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39 |
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40 | TString fNameOutput; // Name of output container
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41 |
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42 | MDataArray *fData; //! Used to store the MDataChains to get the event values
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43 | MParameterD *fRFOut; //! Used to store result
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44 |
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45 | Int_t fNumTrees; //! Training parameters
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46 | Int_t fNumTry; //! Training parameters
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47 | Int_t fNdSize; //! Training parameters
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48 |
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49 | Int_t fNumObsoleteVariables;
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50 |
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51 | MHMatrix *fTestMatrix; //! Test Matrix used in Process (together with MMatrixLoop)
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52 |
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53 | EstimationMode_t fEstimationMode;
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54 |
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55 | private:
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56 | // MTask
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57 | Int_t PreProcess(MParList *plist);
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58 | Int_t Process();
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59 |
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60 | // MRanForestCalc
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61 | Int_t ReadForests(MParList &plist);
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62 |
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63 | // MParContainer
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64 | Int_t ReadEnv(const TEnv &env, TString prefix, Bool_t print);
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65 |
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66 | // Train Interface
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67 | Int_t Train(const MHMatrix &n, const TArrayD &grid, Int_t ver=2);
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68 |
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69 | public:
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70 | MRanForestCalc(const char *name=NULL, const char *title=NULL);
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71 | ~MRanForestCalc();
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72 |
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73 | // Setter for estimation
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74 | void SetFileName(TString filename) { fFileName = filename; }
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75 | void SetEstimationMode(EstimationMode_t op) { fEstimationMode = op; }
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76 | void SetNameOutput(TString name=gsNameOutput) { fNameOutput = name; }
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77 |
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78 | // Setter for training
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79 | void SetNumTrees(UShort_t n=100) { fNumTrees = n; }
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80 | void SetNdSize(UShort_t n=5) { fNdSize = n; }
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81 | void SetNumTry(UShort_t n=0) { fNumTry = n; }
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82 | void SetDebug(Bool_t b=kTRUE) { fDebug = b; }
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83 |
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84 | void SetNumObsoleteVariables(Int_t n=1) { fNumObsoleteVariables = n; }
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85 |
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86 | // Train Interface
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87 | Int_t TrainMultiRF(const MHMatrix &n, const TArrayD &grid)
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88 | {
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89 | return Train(n, grid, 0);
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90 | }
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91 | Int_t TrainSingleRF(const MHMatrix &n, const TArrayD &grid=TArrayD())
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92 | {
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93 | return Train(n, grid, grid.GetSize()==0 ? 2 : 1);
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94 | }
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95 |
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96 | // Test Interface
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97 | void SetTestMatrix(MHMatrix *m=0) { fTestMatrix=m; }
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98 | void InitMapping(MHMatrix *m=0) { fTestMatrix=m; }
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99 |
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100 | ClassDef(MRanForestCalc, 0) // Task to calculate RF output and for RF training
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101 | };
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102 |
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103 | #endif
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