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Uranie / Modeler v4.9.0
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TPolynomialChaos.h
Go to the documentation of this file.
Interface of the class URANIE::Modeler::TNisp.
Description of the class TPolynomialChaos.
Definition TPolynomialChaos.h:61
Double_t getInvQuantile(Double_t seuil, Int_t j=1)
Return the probability of a value overrun.
Double_t getQuantile(Double_t alpha, TString yname)
Return the quantile of order "alpha".
Double_t getErrLoo(Int_t input, Int_t rank=0)
Get the Leave-One-Out uncertainty for the input (input) and the output (rank)
void propagateInput()
Propagation of input which has been specified SetInput()
Double_t getIndexTotalOrder(Int_t i, Int_t j=0)
Total index of sensitivity.
void setAutoDegreeBoundaries(int amin, int amax=-1)
Change the min and max degree tested for automatise degree determination.
int _degval
memory arry for the degree in the tree
Definition TPolynomialChaos.h:87
TTree * getAutoDegreeResults()
Return a pointer to the TTree that contains the degree optimisation results.
Definition TPolynomialChaos.h:156
double _eqmval
memory arry for the eqm in the tree
Definition TPolynomialChaos.h:88
void generateSample(TString type, Int_t np, Int_t order=1)
Build a sample for statitical analysis (quantile). Build a sample of size "np" by the method "type".
void getAnovaOrderedCoefficients(Double_t seuil, TString yname="")
Edition of the ANOVA ordered decomposition / coefficients.
void setCoefficient(Int_t noutput, Int_t num, Double_t coef)
Set the coefficient beta of _pc.
void getAnovaOrdered(Double_t seuil, Int_t j)
int _bestAutoDeg
Best value for automatic degree scan.
Definition TPolynomialChaos.h:84
TPolynomialChaos(TDataServer *tds, TNisp *nisp, TString soutput="")
default constructor from a set of stochastic variables
PolynomialChaos * _pc
Object of type polynomialChaos (library Nisp)
Definition TPolynomialChaos.h:71
int _minAutoDeg
Minimal value for automatic degree scan.
Definition TPolynomialChaos.h:82
Double_t getIndexFirstOrder(TString xname, TString yname="")
First index of sensitivity.
TNisp * _nisp
Message logger.
Definition TPolynomialChaos.h:67
Int_t getDimensionExpansion()
Number of the coefficients of the polynomial chaos.
Int_t _nx
Number of stochastic variables i.e number of input.
Definition TPolynomialChaos.h:73
void realisation()
Polynomial chaos is a random variable : a realisation of this random variable (GetOutput()).
TTree * _degreeResults
TDSNtupleD used to store the results of the automatisedDegree method.
Definition TPolynomialChaos.h:80
Int_t _degree
Degree of the Chaos polynomial.
Definition TPolynomialChaos.h:69
void automatisedDegree(Option_t *option="")
Computation of coefficients.
void readTarget(Char_t *file)
Read a set of target from a file.
Double_t getCovariance(Int_t i, Int_t j)
Get the Covariance.
void computeOutput(double *input)
Computation of output in relation with input : input[0...nx-1].
void getAnovaOrderedCoefficients(Double_t seuil, Int_t j)
void computeChaosExpansion(TString type, Option_t *option="")
Computation of coefficients.
TPolynomialChaos(const TPolynomialChaos &TPC)
copy constructor
Double_t getIndexInteraction(TString sinput="", TString yname="")
Index of interaction sensitivity of a set of variables.
Double_t getQuantileWilks(Double_t alpha, Double_t beta, Int_t j=1)
Return the Wilks' quantile of order "alpha" with confidence "beta".
void propagateInput(Double_t *dt)
Propagation of dt[1...nx].
virtual void printLog(Option_t *option="")
Int_t _np
Number of simulation.
Definition TPolynomialChaos.h:75
void setAutoDegreeFactor(double autodeg)
Change the factor that links the number of samples, coefficient and the highest possible degree.
Bool_t _blog
Boolean for edit the log.
Definition TPolynomialChaos.h:94
void save(string file)
Double_t getIndexFirstOrder(Int_t i, Int_t j=0)
First index of sensitivity.
Double_t getEqmLoo(Int_t rank=0)
Get the Mean squared uncertainty for the output with rank.
int _maxAutoDeg
Maximal value for automatic degree scan.
Definition TPolynomialChaos.h:83
Double_t getVariance(TString name="")
Get the variance.
Double_t getSample(Int_t k, Int_t j)
double _autoDegreeFactor
Factor used to scale the maximum degree knowing _nx and _np.
Definition TPolynomialChaos.h:81
Double_t getCovariance(TString xname, TString yname)
Get the Covariance.
void getAnova(Int_t nt)
Edition of the ANOVA decomposition.
TPolynomialChaos(const char *ct)
Double_t getCorrelation(TString xname, TString yname)
Get the correlation.
Double_t getInvQuantile(Double_t seuil, TString yname)
Return the probability of a value overrun.
Double_t getIndexTotalOrder(TString xname, TString yname="")
Total index of sensitivity.
void exportFunction(const char *file="nisp", const char *name="nisp_fct")
Export the model in C++ langage in a file.
void writeCodeCToDenormalizeInput(std::ofstream *sourcefile)
Write set Denormalization.
Double_t getCorrelation(Int_t i, Int_t j)
Get the correlation.
Double_t getSample(Int_t k, TString yname)
The value of the output yname for the example k.
TDataSpecification * _listAttOut
Object of type TDataSpecification used to index the name of the variables.
Definition TPolynomialChaos.h:92
void getAnovaOrdered(Double_t seuil, TString yname="")
Return the ANOVA ordered decomposition.
Double_t getCoefficient(Int_t noutput, Int_t num)
Get the coefficient beta of _pc.
vector< double > * _verrloo
vector to contains the err loo and store them in the tree
Definition TPolynomialChaos.h:86
URANIE::DataServer::UMessageLogger * _fLogger
Definition TPolynomialChaos.h:63
Double_t getQuantileWilks(Double_t alpha, Double_t beta, TString yname)
Return the Wilks' quantile of order "alpha" with confidence "beta".
Double_t getCoefficient(Int_t k, TString jname="")
Get coefficents value.
Double_t getQuantile(Double_t alpha, Int_t j)
Return the quantile of order "alpha".
Double_t getIndex(TString sinput="", TString yname="")
Index of sensitivity of a set of variables.
Bool_t _bStoreYHat
Boolean to specify if we add the \hat{} attribute in the TDS [default kTRUE].
Definition TPolynomialChaos.h:78
int getBestAutoDegree()
Return the bet estimated degree when optimisation is done with regression.
Definition TPolynomialChaos.h:162