TMultiDimFit


class description - source file - inheritance tree

class TMultiDimFit : public TNamed


    protected:
virtual Double_t EvalControl(const Int_t* powers) virtual Double_t EvalFactor(Int_t p, Double_t x) virtual void MakeCandidates() virtual void MakeCoefficientErrors() virtual void MakeCoefficients() virtual void MakeCorrelation() virtual Double_t MakeGramSchmidt(Int_t function) virtual void MakeNormalized() virtual void MakeParameterization() virtual void MakeRealCode(const char* filename, const char* classname, Option_t* option) virtual Bool_t Select(const Int_t* iv) virtual Bool_t TestFunction(Double_t squareResidual, Double_t dResidur) public:
TMultiDimFit(Int_t dimension, TMultiDimFit::EMDFPolyType type = kMonomials, Option_t* option) TMultiDimFit(const TMultiDimFit&) TMultiDimFit() virtual ~TMultiDimFit() virtual void AddRow(const Double_t* x, Double_t D, Double_t E = 0) virtual void AddTestRow(const Double_t* x, Double_t D, Double_t E = 0) virtual void Browse(TBrowser* b) static TClass* Class() virtual void Clear(Option_t* option) virtual void Draw(Option_t* = "d") virtual Double_t Eval(const Double_t* x, const Double_t* coeff = 0) virtual void FindParameterization(Option_t* option) virtual void Fit(Option_t* option) Double_t GetChi2() const const TVectorD* GetCoefficients() const const TMatrixD* GetCorrelationMatrix() const Double_t GetError() const Int_t* GetFunctionCodes() const const TMatrixD* GetFunctions() const virtual TList* GetHistograms() const Double_t GetMaxAngle() const Int_t GetMaxFunctions() const Int_t* GetMaxPowers() const Double_t GetMaxQuantity() const Int_t GetMaxStudy() const Int_t GetMaxTerms() const const TVectorD* GetMaxVariables() const Double_t GetMeanQuantity() const const TVectorD* GetMeanVariables() const Double_t GetMinAngle() const Double_t GetMinQuantity() const Double_t GetMinRelativeError() const const TVectorD* GetMinVariables() const Int_t GetNCoefficients() const Int_t GetNVariables() const Int_t GetPolyType() const Int_t* GetPowerIndex() const Double_t GetPowerLimit() const const Int_t* GetPowers() const Double_t GetPrecision() const const TVectorD* GetQuantity() const Double_t GetResidualMax() const Int_t GetResidualMaxRow() const Double_t GetResidualMin() const Int_t GetResidualMinRow() const Double_t GetResidualSumSq() const Double_t GetRMS() const Int_t GetSampleSize() const const TVectorD* GetSqError() const Double_t GetSumSqAvgQuantity() const Double_t GetSumSqQuantity() const Double_t GetTestError() const Double_t GetTestPrecision() const const TVectorD* GetTestQuantity() const Int_t GetTestSampleSize() const const TVectorD* GetTestSqError() const const TVectorD* GetTestVariables() const const TVectorD* GetVariables() const static TMultiDimFit* Instance() virtual TClass* IsA() const virtual Bool_t IsFolder() const virtual Double_t MakeChi2(const Double_t* coeff = 0) virtual void MakeCode(const char* functionName = "MDF", Option_t* option) virtual void MakeHistograms(Option_t* option = "A") virtual void MakeMethod(const Char_t* className = "MDF", Option_t* option) virtual void Print(Option_t* option = "ps") const void SetMaxAngle(Double_t angle = 0) void SetMaxFunctions(Int_t n) void SetMaxPowers(const Int_t* powers) void SetMaxStudy(Int_t n) void SetMaxTerms(Int_t terms) void SetMinAngle(Double_t angle = 1) void SetMinRelativeError(Double_t error) void SetPowerLimit(Double_t limit = 1e-3) virtual void SetPowers(const Int_t* powers, Int_t terms) virtual void ShowMembers(TMemberInspector& insp, char* parent) virtual void Streamer(TBuffer& b) void StreamerNVirtual(TBuffer& b)

Data Members

    private:
static TMultiDimFit* fgInstance Static instance protected:
TVectorD fQuantity Training sample, dependent quantity TVectorD fSqError Training sample, error in quantity Double_t fMeanQuantity Mean of dependent quantity Double_t fMaxQuantity Max value of dependent quantity Double_t fMinQuantity Min value of dependent quantity Double_t fSumSqQuantity SumSquare of dependent quantity Double_t fSumSqAvgQuantity Sum of squares away from mean TVectorD fVariables Training sample, independent variables Int_t fNVariables Number of independent variables TVectorD fMeanVariables mean value of independent variables TVectorD fMaxVariables max value of independent variables TVectorD fMinVariables min value of independent variables Int_t fSampleSize Size of training sample TVectorD fTestQuantity Test sample, dependent quantity TVectorD fTestSqError Test sample, Error in quantity TVectorD fTestVariables Test sample, independent variables Int_t fTestSampleSize Size of test sample Double_t fMinAngle Min angle for acepting new function Double_t fMaxAngle Max angle for acepting new function Int_t fMaxTerms Max terms expected in final expr. Double_t fMinRelativeError Min relative error accepted Int_t* fMaxPowers [fNVariables] maximum powers Double_t fPowerLimit Control parameter TMatrixD fFunctions Functions evaluated over sample Int_t fMaxFunctions max number of functions Int_t* fFunctionCodes [fMaxFunctions] acceptance code Int_t fMaxStudy max functions to study TMatrixD fOrthFunctions As above, but orthogonalised TVectorD fOrthFunctionNorms Norm of the evaluated functions Int_t* fMaxPowersFinal [fNVariables] maximum powers from fit; Int_t* fPowers [fMaxFunctions*fNVariables] Int_t* fPowerIndex [fMaxTerms] Index of accepted powers TVectorD fResiduals Vector of the final residuals Double_t fMaxResidual Max redsidual value Double_t fMinResidual Min redsidual value Int_t fMaxResidualRow Row giving max residual Int_t fMinResidualRow Row giving min residual Double_t fSumSqResidual Sum of Square residuals Int_t fNCoefficients Dimension of model coefficients TVectorD fOrthCoefficients The model coefficients TMatrixD fOrthCurvatureMatrix Model matrix TVectorD fCoefficients Vector of the final coefficients TVectorD fCoefficientsRMS Vector of RMS of coefficients Double_t fRMS Root mean square of fit Double_t fChi2 Chi square of fit Int_t fParameterisationCode Exit code of parameterisation Double_t fError Error from parameterization Double_t fTestError Error from test Double_t fPrecision Relative precision of param Double_t fTestPrecision Relative precision of test Double_t fCorrelationCoeff Multi Correlation coefficient TMatrixD fCorrelationMatrix Correlation matrix Double_t fTestCorrelationCoeff Multi Correlation coefficient TList* fHistograms List of histograms unsigned char fHistogramMask Bit pattern of hisograms used TVirtualFitter* fFitter ! Fit object (MINUIT) TMultiDimFit::EMDFPolyType fPolyType Type of polynomials to use Bool_t fShowCorrelation print correlation matrix Bool_t fIsUserFunction Flag for user defined function Bool_t fIsVerbose public:
static const TMultiDimFit::EMDFPolyType kMonomials static const TMultiDimFit::EMDFPolyType kChebyshev static const TMultiDimFit::EMDFPolyType kLegendre

Class Description



Last update: Fri May 14 13:32:41 2004


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