#include <WeightCalc.h>

Inheritance diagram for evwgh::WeightCalc:

Public Member Functions
virtual void	Configure (fhicl::ParameterSet const &pset, CLHEP::HepRandomEngine &)=0

virtual std::vector< std::vector< double > >	GetWeight (art::Event &e)=0

void	SetName (std::string name)

std::string	GetName ()

Static Public Member Functions
static std::vector< std::vector< double > >	MultiGaussianSmearing (std::vector< double > const &centralValues, std::vector< std::vector< double >> const &inputCovarianceMatrix, int n_multisims, CLHEP::RandGaussQ &GaussRandom)
	Applies Gaussian smearing to a set of data. More...

static std::vector< double >	MultiGaussianSmearing (std::vector< double > const &centralValue, TMatrixD *const &inputCovarianceMatrix, std::vector< double > rand)
	Over load of the above function that only returns a single varied parameter set. More...

static std::vector< double >	MultiGaussianSmearing (std::vector< double > const &centralValue, TMatrixD *const &LowerTriangleCovarianceMatrix, bool isDecomposed, std::vector< double > rand)

Private Attributes
std::string	fName

Detailed Description

Definition at line 19 of file WeightCalc.h.

Member Function Documentation

virtual void evwgh::WeightCalc::Configure	(	fhicl::ParameterSet const &	pset,
		CLHEP::HepRandomEngine &
	)

pure virtual

std::string evwgh::WeightCalc::GetName ( void )

inline

Definition at line 26 of file WeightCalc.h.

26 {return fName;}

evwgh::WeightCalc::fName

std::string fName

Definition: WeightCalc.h:56

virtual std::vector<std::vector<double> > evwgh::WeightCalc::GetWeight ( art::Event & e )

pure virtual

Implemented in evwgh::GenieWeightCalc.

static std::vector<std::vector<double> > evwgh::WeightCalc::MultiGaussianSmearing	(	std::vector< double > const &	centralValues,
		std::vector< std::vector< double >> const &	inputCovarianceMatrix,
		int	n_multisims,
		CLHEP::RandGaussQ &	GaussRandom
	)

static

Applies Gaussian smearing to a set of data.

Parameters

centralValues	the values to be smeared
inputCovarianceMatrix	covariance matrix for smearing
n_multisims	number of sets of smeared values to be produced

Returns: a set of n_multisims value sets smeared from the central value

If centralValues is of dimension N, inputCovarianceMatrix needs to be NxN, and each of the returned data sets will be also of dimension N.

std::vector< double > evwgh::WeightCalc::MultiGaussianSmearing	(	std::vector< double > const &	centralValue,
		TMatrixD *const &	inputCovarianceMatrix,
		std::vector< double >	rand
	)

static

Over load of the above function that only returns a single varied parameter set.

Definition at line 102 of file WeightCalc.cxx.

   {
 
     //compute the smeared central values
     std::vector<double> smearedCentralValues;
 
     //
     //perform Choleskey Decomposition
     //
     // Best description I have found
     //     is in the PDG (Monte Carlo techniques, Algorithms, Gaussian distribution)
     //
     //  http://pdg.lbl.gov/2016/reviews/rpp2016-rev-monte-carlo-techniques.pdf (Page 5)
     //
     //
     TDecompChol dc = TDecompChol(*(inputCovarianceMatrix));
     if(!dc.Decompose())
       {
         throw art::Exception(art::errors::StdException)
           << "Cannot decompose covariance matrix to begin smearing.";
         return smearedCentralValues;
       }
 
     //Get upper triangular matrix. This maintains the relations in the
     //covariance matrix, but simplifies the structure.
     TMatrixD U = dc.GetU();
 
 
     for(unsigned int col = 0; col < centralValue.size(); ++col)
       {
         //find the weight of each col of the upper triangular cov. matrix
         double weightFromU = 0.;
 
         for(unsigned int row = 0; row < col+1; ++row)
           {
             weightFromU += U(row,col)*rand[row];
           }
 
         //multiply this weight by each col of the central values to obtain
         //the gaussian smeared and constrained central values
         // smearedCentralValues.push_back(weightFromU * centralValue[col]);
         smearedCentralValues.push_back(weightFromU + centralValue[col]);
       }
   return smearedCentralValues;
   } // WeightCalc::MultiGaussianSmearing() - Gives a single set of smeared parameters

std::vector< double > evwgh::WeightCalc::MultiGaussianSmearing	(	std::vector< double > const &	centralValue,
		TMatrixD *const &	LowerTriangleCovarianceMatrix,
		bool	isDecomposed,
		std::vector< double >	rand
	)

static

Definition at line 159 of file WeightCalc.cxx.

   {
 
     //compute the smeared central values
     std::vector<double> smearedCentralValues;
 
     // This guards against accidentally
     if(!isDecomposed){
       throw art::Exception(art::errors::StdException)
         << "Must supply the decomposed lower triangular covariance matrix.";
       return smearedCentralValues;
     }
 
 
     for(unsigned int col = 0; col < centralValue.size(); ++col)
       {
         //find the weight of each col of the upper triangular cov. matrix
         double weightFromU = 0.;
 
         for(unsigned int row = 0; row < col+1; ++row)
           {
             weightFromU += LowerTriangleCovarianceMatrix[0][row][col]*rand[row];
           }
 
         //multiply this weight by each col of the central values to obtain
         //the gaussian smeared and constrained central values
         // smearedCentralValues.push_back(weightFromU * centralValue[col]);
         smearedCentralValues.push_back(weightFromU + centralValue[col]);
       }
   return smearedCentralValues;
   } // WeightCalc::MultiGaussianSmearing() - Gives a single set of smeared parameters