npstat::AbsUnfold1D Class Reference

Inheritance diagram for npstat::AbsUnfold1D:

Public Member Functions
	AbsUnfold1D (const Matrix< double > &responseMatrix)
const Matrix< double > &	responseMatrix () const
const Matrix< double > &	transposedResponseMatrix () const
const std::vector< double > &	efficiency () const
std::pair< double, double >	smoothingNDoF () const
std::pair< double, double >	responseNDoF () const
std::pair< double, double >	smoothedResponseNDoF () const
std::pair< double, double >	modelNDoF ()
virtual void	setInitialApproximation (const double *approx, unsigned lenApprox)
virtual void	clearInitialApproximation ()
virtual const std::vector< double > &	getInitialApproximation () const
virtual void	setFilter (const LocalPolyFilter1D *f)
virtual const LocalPolyFilter1D *	getFilter (bool throwIfNull=false) const
virtual void	useConvolutions (const bool b)
bool	usingConvolutions () const
virtual bool	unfold (const double *observed, unsigned lenObserved, const Matrix< double > *observationCovarianceMatrix, double *unfolded, unsigned lenUnfolded, Matrix< double > *unfoldedCovarianceMatrix)=0

Static Public Member Functions
static double	probDelta (const double *prev, const double *next, const unsigned len)
static Matrix< double >	observationCovariance (const double *yhat, unsigned lenObserved, bool isMultinomial)

Protected Member Functions
void	buildUniformInitialApproximation (const double *observed, unsigned lenObserved, std::vector< double > *result) const
void	validateDimensions (unsigned lenObserved, unsigned lenUnfold) const

Static Protected Member Functions
static void	validateDensity (const double *observ, unsigned lenObserved)

Constructor & Destructor Documentation

AbsUnfold1D()

npstat::AbsUnfold1D::AbsUnfold1D ( const Matrix< double > &  responseMatrix )

explicit

Number of rows of the response matrix should be equal to the number of discretization intervals in the space of observations. Number of columns should be equal to the number of intervals in the original (unfolded) space.

Member Function Documentation

clearInitialApproximation()

virtual void npstat::AbsUnfold1D::clearInitialApproximation ( )

virtual

Clear the initial approximation to the unfolded solution

getFilter()

virtual const LocalPolyFilter1D* npstat::AbsUnfold1D::getFilter ( bool  throwIfNull = false ) const

virtual

Retrieve the smoothing filter used

getInitialApproximation()

virtual const std::vector<double>& npstat::AbsUnfold1D::getInitialApproximation ( ) const

virtual

Return the initial approximation to the unfolded solution

modelNDoF()

std::pair<double, double> npstat::AbsUnfold1D::modelNDoF

(

)

Effective number of degrees of freedom for the smearing model (for use in AIC, etc). Will call "unfold" internally, so can't be a const method.

observationCovariance()

static Matrix<double> npstat::AbsUnfold1D::observationCovariance ( const double *  yhat, unsigned  lenObserved, bool  isMultinomial  )

static

Procedure for building covariance matrix of observations according to either Poisson or multinomial distribution

probDelta()

static double npstat::AbsUnfold1D::probDelta ( const double *  prev, const double *  next, const unsigned  len  )

static

An L1-like relative distance between two unnormalized density-like arrays. Can be used as a convergence measure.

setFilter()

virtual void npstat::AbsUnfold1D::setFilter ( const LocalPolyFilter1D *  f )

virtual

Set the smoothing filter used. The filter will not be copied. It is the responsibility of the user of this class to ensure that the lifetime of the filter exceeds the lifetime of this object.

setInitialApproximation()

virtual void npstat::AbsUnfold1D::setInitialApproximation ( const double *  approx, unsigned  lenApprox  )

virtual

Set the initial approximation to the unfolded solution

smoothingNDoF()

std::pair<double, double> npstat::AbsUnfold1D::smoothingNDoF

(

)

const

The first element of the pair is the entropic nDoF and the second is the nDoF based on the trace

unfold()

virtual bool npstat::AbsUnfold1D::unfold ( const double *  observed, unsigned  lenObserved, const Matrix< double > *  observationCovarianceMatrix, double *  unfolded, unsigned  lenUnfolded, Matrix< double > *  unfoldedCovarianceMatrix  )

pure virtual

Method to be implemented by derived classes. "lenObserved" and "lenUnfolded" should be consistent with the dimensionality of the response matrix provided in the constructor. The "observationCovarianceMatrix" pointer to the covariance matrix of observations can be NULL in which case this covariance matrix will be evaluated internally (typically, assuming either Poisson or multinomial distributions for the observed counts). "unfoldedCovarianceMatrix" pointer, if not NULL, should be used to return the covariance matrix of unfolded values with dimensions (lenUnfolded x lenUnfolded). This function should return "true" on success and "false" on failure.

Implemented in npstat::SmoothedEMUnfold1D.

useConvolutions()

virtual void npstat::AbsUnfold1D::useConvolutions ( const bool  b )

inlinevirtual

Switch between using filtering or convolution

usingConvolutions()

bool npstat::AbsUnfold1D::usingConvolutions ( ) const

inline

Check if the filter should use "filter" or "convolve" method

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The documentation for this class was generated from the following file:

• stat/AbsUnfold1D.hh