lar::util::GaussianFit< T > Class Template Reference

"Fast" Gaussian fit More...

#include "SimpleFits.h"

Inheritance diagram for lar::util::GaussianFit< T >:

Classes
struct	EncodeExtractor
struct	EncodeExtractor< Pred, void >
struct	Value_t
	< type of value and error More...

Public Types
using	Data_t = typename Base_t::Data_t
	type of the data More...
using	Measurement_t = typename Fitter_t::Measurement_t
	type of measurement without uncertainty More...
using	MeasurementAndUncertainty_t = typename Fitter_t::MeasurementAndUncertainty_t
	type of measurement with uncertainty More...
using	FitParameters_t = typename Fitter_t::FitParameters_t
using	FitMatrix_t = typename Fitter_t::FitMatrix_t
using	MatrixOps = FastMatrixOperations< Data_t, NParams >

Public Member Functions
virtual bool	FillResults (FitParameters_t &params, FitMatrix_t &Xmat, Data_t &det, FitMatrix_t &Smat) const override
	Fills the specified parameters. More...
virtual bool	FillResults (FitParameters_t &params, FitParameters_t &paramerrors, FitMatrix_t &Xmat, Data_t &det, FitMatrix_t &Smat) const override
	Fills the specified parameters. More...
virtual bool	FillResults (FitParameters_t &params, FitParameters_t &paramerrors) const override
	Fills the specified parameters. More...
virtual Data_t	Evaluate (Data_t x) const override
	Evaluates the fitted function at the specified point. More...
virtual Fitter_t const &	Fitter () const
	Returns the internal fitter (mostly for debugging) More...
virtual bool	FillResults (FitParameters_t &params, FitMatrix_t &Xmat, Data_t &det, FitMatrix_t &Smat) const =0
	Fills the specified parameters. More...
virtual bool	FillResults (FitParameters_t &params, FitParameters_t &paramerrors, FitMatrix_t &Xmat, Data_t &det, FitMatrix_t &Smat) const =0
	Fills the specified parameters. More...
virtual bool	FillResults (FitParameters_t &params, FitParameters_t &paramerrors) const =0
	Fills the specified parameters. More...
virtual Data_t	Evaluate (Data_t x) const =0
	Evaluates the fitted function at the specified point. More...
Data_t	operator() (Data_t x) const
	Evaluates the fitted function; alias of Evaluate() More...
Add elements
See also FitDataCollector
bool	add (Data_t x, Data_t y, Data_t sy=Data_t(1.0))
	Clears all the input statistics. More...
bool	add (Measurement_t value, Data_t sy=Data_t(1.0))
	Clears all the input statistics. More...
bool	add (MeasurementAndUncertainty_t value)
	Clears all the input statistics. More...
template<typename Iter >
void	add_without_uncertainty (Iter begin, Iter end)
	Clears all the input statistics. More...
template<typename Iter , typename Pred >
void	add_without_uncertainty (Iter begin, Iter end, Pred extractor)
	Clears all the input statistics. More...
template<typename Cont , typename Pred >
void	add_without_uncertainty (Cont cont, Pred extractor)
	Clears all the input statistics. More...
template<typename Cont >
void	add_without_uncertainty (Cont cont)
	Clears all the input statistics. More...
template<typename VIter , typename UIter , typename VPred , typename UPred = identity>
unsigned int	add_with_uncertainty (VIter begin_value, VIter end_value, UIter begin_uncertainty, VPred value_extractor, UPred uncertainty_extractor=UPred())
	Clears all the input statistics. More...
template<typename Iter >
unsigned int	add_with_uncertainty (Iter begin, Iter end)
	Clears all the input statistics. More...
template<typename Cont >
unsigned int	add_with_uncertainty (Cont cont)
	Clears all the input statistics. More...
void	clear ()
	Clears all the input statistics. More...
int	N () const
	Returns the number of (valid) points added. More...
template<typename Stream >
void	PrintStats (Stream &out) const
	Prints the collected statistics into a stream. More...
Fitting
virtual bool	isValid () const override
	Returns if the fit has valid results. More...
virtual FitParameters_t	FitParameters () const override
	Computes and returns all the parameters of the fit result. More...
virtual FitParameters_t	FitParameterErrors () const override
	Computes and returns all the parameter errors of the fit result. More...
virtual FitMatrix_t	FitParameterCovariance () const override
	Computes and returns all the covariance matrix of the fit result. More...
virtual Data_t	ChiSquare () const override
	Returns the of the original fit. More...
virtual int	NDF () const override
	Returns the degrees of freedom in the determination of the fit. More...
Fitting
virtual Data_t	FitParameter (unsigned int n) const
	Returns the parameter n of the fit result. More...
virtual Data_t	FitParameterError (unsigned int n) const
	Returns the error on parameter n of the fit result. More...

Static Public Member Functions
static Data_t	Evaluate (Data_t x, Data_t const *params)
	Evaluates a Gaussian with given parameters at one point. More...
static constexpr Data_t	sqr (Data_t v)
	Returns the square of the specified data value. More...
static constexpr Data_t	cube (Data_t v)
	Returns the cube of the specified data value. More...

Static Public Attributes
static constexpr unsigned int	NParams = Base_t::NParams
	Number of parameters in the fit. More...

Protected Member Functions
virtual Data_t	Determinant (FitMatrix_t const &mat) const
	Computes the determinant of a matrix. More...
virtual FitMatrix_t	InvertMatrix (FitMatrix_t const &mat, Data_t det) const
	Computes the inverse of a matrix (using provided determinant) More...
virtual FitMatrix_t	InvertMatrix (FitMatrix_t const &mat) const
	Computes the inverse of a matrix. More...
virtual FitParameters_t	MatrixProduct (FitMatrix_t const &mat, FitParameters_t const &vec) const
	Computes the product of a FitMatrix_t and a FitParameters_t. More...

Static Protected Member Functions
static FitParameters_t	ConvertParameters (FitParameters_t const &qpars)
	Converts the specified quadratic fit parameters into Gaussian. More...
static void	ConvertParametersAndErrors (FitParameters_t const &qpars, FitMatrix_t const &qparerrmat, FitParameters_t &params, FitParameters_t &paramerrors)
	Converts the specified quadratic fit parameters and errors. More...
static void	ConvertParametersAndVariances (FitParameters_t const &qpars, FitMatrix_t const &qparerrmat, FitParameters_t &params, FitParameters_t &paramvariances)
	Converts the specified quadratic fit parameters and errors. More...
static void	ConvertParametersAndErrorMatrix (FitParameters_t const &qpars, FitMatrix_t const &qparerrmat, FitParameters_t &params, FitMatrix_t &Smat)
	Converts the specified quadratic fit parameters and errors. More...
static bool	isValid (FitParameters_t const &params, FitParameters_t const &qpars)
	Returns whether the specified parameters represent a valid fit. More...
static void	ThrowNotImplemented (std::string method)
Mumbo-jumbo to convert the values for a quadratic fit
static Data_t	EncodeValue (Data_t value)
static Data_t	DecodeValue (Data_t value)
	Converts a value from the quadratic fit into a proper value. More...
static Value_t	EncodeValue (Data_t value, Data_t error)
	Converts a value and error into a proper input for the quadratic fit. More...
static Value_t	EncodeValue (Value_t const &value)
	Converts a value and error into a proper input for the quadratic fit. More...
static Value_t	DecodeValue (Value_t const &value)
	Converts a value from the quadratic fit into a proper value. More...
static Measurement_t	EncodeValue (Measurement_t const &meas)
	Converts a value and error into a proper input for the quadratic fit. More...
static MeasurementAndUncertainty_t	EncodeValue (MeasurementAndUncertainty_t const &meas)
	Converts a value and error into a proper input for the quadratic fit. More...
static MeasurementAndUncertainty_t	EncodeValue (Measurement_t const &meas, Data_t error)
	Converts a value and error into a proper input for the quadratic fit. More...
template<typename Pred >
static EncodeExtractor< Pred >	Encoder (Pred &pred)
template<typename VPred , typename UPred >
static EncodeExtractor< VPred, UPred >	Encoder (VPred &vpred, UPred &upred)

Protected Attributes
Fitter_t	fitter
	the actual fitter and data holder More...

Private Types
using	Base_t = details::SimpleFitterInterface< T, 3 >
	base class More...
using	Fitter_t = QuadraticFit< T >
	base class More...

Detailed Description

template<typename T>
class lar::util::GaussianFit< T >

"Fast" Gaussian fit

---

Template Parameters

T

data type

This class performs a Gaussian fit on demand. This fit translates the data to its logarithm and then internally performs a quadratic fit. Note that as a consequence this fitter does not accept negative values for the y variable. Negative values in input will be completely ignored.

Methods that do not change functionality respect to the base class are not documented here – see the base class(es) documentation (mostly SimplePolyFitterBase).

Definition at line 993 of file SimpleFits.h.

Member Typedef Documentation

template<typename T>

using lar::util::GaussianFit< T >::Base_t = details::SimpleFitterInterface<T, 3>

private

base class

Definition at line 994 of file SimpleFits.h.

template<typename T>

using lar::util::GaussianFit< T >::Data_t = typename Base_t::Data_t

type of the data

Definition at line 1001 of file SimpleFits.h.

template<typename T>

using lar::util::GaussianFit< T >::FitMatrix_t = typename Fitter_t::FitMatrix_t

Definition at line 1010 of file SimpleFits.h.

template<typename T>

using lar::util::GaussianFit< T >::FitParameters_t = typename Fitter_t::FitParameters_t

Definition at line 1009 of file SimpleFits.h.

template<typename T>

using lar::util::GaussianFit< T >::Fitter_t = QuadraticFit<T>

private

base class

Definition at line 995 of file SimpleFits.h.

using lar::util::details::SimpleFitterInterface< T, N >::MatrixOps = FastMatrixOperations<Data_t, NParams>

inherited

Definition at line 465 of file SimpleFits.h.

template<typename T>

using lar::util::GaussianFit< T >::Measurement_t = typename Fitter_t::Measurement_t

type of measurement without uncertainty

Definition at line 1004 of file SimpleFits.h.

template<typename T>

using lar::util::GaussianFit< T >::MeasurementAndUncertainty_t = typename Fitter_t::MeasurementAndUncertainty_t

type of measurement with uncertainty

Definition at line 1007 of file SimpleFits.h.

Member Function Documentation

template<typename T >

bool lar::util::GaussianFit< T >::add	(	Data_t	x,
		Data_t	y,
		Data_t	sy = Data_t(1.0)
	)

Clears all the input statistics.

Definition at line 1719 of file SimpleFits.h.

References lar::util::GaussianFit< T >::Value_t::error(), value, and lar::util::GaussianFit< T >::Value_t::value().

Referenced by hit::CCHitFinderAlg::FastGaussianFit().

{
  if (y <= Data_t(0)) return false; // ignore the non-positive values
  Value_t value = EncodeValue(Value_t(y, sy));
  return fitter.add(x, value.value(), value.error());
} // GaussianFit<T>::add(Data_t, Data_t, Data_t)

template<typename T>

bool lar::util::GaussianFit< T >::add ( Measurement_t  value, Data_t  sy = Data_t(1.0)  )

inline

Clears all the input statistics.

Definition at line 1023 of file SimpleFits.h.

References lar::util::details::FitDataCollector< T, D >::add().

      {
        return add(std::get<0>(value), std::get<1>(value), sy);
      }

template<typename T>

bool lar::util::GaussianFit< T >::add ( MeasurementAndUncertainty_t  value )

inline

Clears all the input statistics.

Definition at line 1028 of file SimpleFits.h.

References lar::util::details::FitDataCollector< T, D >::add().

      {
        return add(std::get<0>(value), std::get<1>(value), std::get<2>(value));
      }

template<typename T >

template<typename VIter , typename UIter , typename VPred , typename UPred >

unsigned int lar::util::GaussianFit< T >::add_with_uncertainty	(	VIter	begin_value,
		VIter	end_value,
		UIter	begin_uncertainty,
		VPred	value_extractor,
		UPred	uncertainty_extractor = UPred()
	)

Clears all the input statistics.

Definition at line 1735 of file SimpleFits.h.

References lar::util::details::FitDataCollector< T, D >::add_with_uncertainty().

{
  return add_with_uncertainty(
    begin_value, end_value, begin_uncertainty, Encoder(value_extractor, uncertainty_extractor));
} // GaussianFit<T>::add_with_uncertainty()

template<typename T >

template<typename Iter >

unsigned int lar::util::GaussianFit< T >::add_with_uncertainty	(	Iter	begin,
		Iter	end
	)

Clears all the input statistics.

Definition at line 1749 of file SimpleFits.h.

References lar::util::details::FitDataCollector< T, D >::add(), and lar::util::details::FitDataCollector< T, D >::N().

{
  unsigned int old_n = N();
  std::for_each(begin, end, [this](auto p) { this->add(p); });
  return N() - old_n;
} // GaussianFit<T>::add_with_uncertainty()

template<typename T>

template<typename Cont >

unsigned int lar::util::GaussianFit< T >::add_with_uncertainty ( Cont  cont )

inline

Clears all the input statistics.

Definition at line 1065 of file SimpleFits.h.

References lar::util::details::FitDataCollector< T, D >::add_with_uncertainty(), util::begin(), and util::end().

      {
        return add_with_uncertainty(std::begin(cont), std::end(cont));
      }

template<typename T>

template<typename Iter >

void lar::util::GaussianFit< T >::add_without_uncertainty ( Iter  begin, Iter  end  )

inline

Clears all the input statistics.

Definition at line 1034 of file SimpleFits.h.

References lar::util::details::FitDataCollector< T, D >::add_without_uncertainty(), util::begin(), and util::end().

      {
        add_without_uncertainty(begin, end, identity());
      }

template<typename T >

template<typename Iter , typename Pred >

void lar::util::GaussianFit< T >::add_without_uncertainty	(	Iter	begin,
		Iter	end,
		Pred	extractor
	)

Clears all the input statistics.

Definition at line 1728 of file SimpleFits.h.

{
  return fitter.add_without_uncertainty(begin, end, Encoder(extractor));
} // GaussianFit<>::add_without_uncertainty(Iter, Iter, Pred)

template<typename T>

template<typename Cont , typename Pred >

void lar::util::GaussianFit< T >::add_without_uncertainty ( Cont  cont, Pred  extractor  )

inline

Clears all the input statistics.

Definition at line 1043 of file SimpleFits.h.

References lar::util::details::FitDataCollector< T, D >::add_without_uncertainty(), util::begin(), and util::end().

      {
        add_without_uncertainty(std::begin(cont), std::end(cont), extractor);
      }

template<typename T>

template<typename Cont >

void lar::util::GaussianFit< T >::add_without_uncertainty ( Cont  cont )

inline

Clears all the input statistics.

Definition at line 1049 of file SimpleFits.h.

References lar::util::details::FitDataCollector< T, D >::add_with_uncertainty(), lar::util::details::FitDataCollector< T, D >::add_without_uncertainty(), util::begin(), and util::end().

      {
        add_without_uncertainty(std::begin(cont), std::end(cont));
      }

template<typename T>

virtual Data_t lar::util::GaussianFit< T >::ChiSquare ( ) const

inlineoverridevirtual

Returns the of the original fit.

Returns

the of the original fit (not divided by NDF())

This is not defined in the space of the Gaussian, but in the space of the internal quadratic fit. Where one is minimum, the other also is, but the actual value is different.

Implements lar::util::details::SimpleFitterInterface< T, 3 >.

Definition at line 1135 of file SimpleFits.h.

Referenced by hit::CCHitFinderAlg::FastGaussianFit().

{ return fitter.ChiSquare(); }

template<typename T>

void lar::util::GaussianFit< T >::clear ( )

inline

Clears all the input statistics.

Definition at line 1071 of file SimpleFits.h.

{ fitter.clear(); }

template<typename T >

auto lar::util::GaussianFit< T >::ConvertParameters ( FitParameters_t const &  qpars )

staticprotected

Converts the specified quadratic fit parameters into Gaussian.

Parameters

qpars

the quadratic fit parameters

Returns

Gaussian function parameters

Definition at line 1835 of file SimpleFits.h.

References lar::util::details::FitDataCollector< T, D >::sqr().

{
  FitParameters_t params;

  Data_t sigma2 = -0.5 / qpars[2]; // sigma^2 = -1 / (2 a2)
  params[2] = std::sqrt(sigma2);   // sigma

  params[1] = sigma2 * qpars[1]; // mean = sigma2 a1

  params[0] = std::exp(qpars[0] - 0.25 * sqr(qpars[1]) / qpars[2]);

  return params;
} // GaussianFit<>::ConvertParameters()

template<typename T >

void lar::util::GaussianFit< T >::ConvertParametersAndErrorMatrix ( FitParameters_t const &  qpars, FitMatrix_t const &  qparerrmat, FitParameters_t &  params, FitMatrix_t &  Smat  )

staticprotected

Converts the specified quadratic fit parameters and errors.

Parameters

qpars	the quadratic fit parameters
qparerrmat	the quadratic fit parameter error matrix
params	the Gaussian fit parameters
Smat	the covariance matrix of the Gaussian fit parameters

Definition at line 1891 of file SimpleFits.h.

References lar::util::details::FitDataCollector< T, D >::sqr().

{
  FitParameters_t paramvariances;
  ConvertParametersAndVariances(qpars, qparerrmat, params, paramvariances);

  // let's call things with their names
  FitParameters_t const& a = qpars;
  Data_t const& A = params[0];
  Data_t const& mu = params[1];
  Data_t const& sigma = params[2];

  // variance on sigma
  Smat[3 * 2 + 2] = paramvariances[2];

  // variance on mu
  Smat[3 * 1 + 1] = paramvariances[1];

  // variance on A
  Smat[3 * 0 + 0] = paramvariances[0];

  // covariance on sigma and mu
  Smat[3 * 1 + 2] = Smat[3 * 2 + 1] =
    (qparerrmat[3 * 1 + 2] + 2 * mu * qparerrmat[3 * 2 + 2]) / sigma;

  // this is the sum of the derivatives of A vs. all a parameters, each one
  // multiplied by the covariance of that parameter with a2
  const Data_t dA_dak_cov_aka2 =
    A * (qparerrmat[3 * 0 + 2] + qparerrmat[3 * 1 + 2] * mu + qparerrmat[3 * 2 + 2] * sqr(mu));
  // covariance on A and sigma
  Smat[3 * 0 + 2] = Smat[3 * 2 + 0] = dA_dak_cov_aka2 / cube(sigma);

  // this other is the same as dA_dak_cov_aka2, but for a1
  const Data_t dA_dak_cov_aka1 =
    A * (qparerrmat[3 * 0 + 1] + qparerrmat[3 * 1 + 1] * mu + qparerrmat[3 * 2 + 1] * sqr(mu));

  // covariance on A and mu
  Smat[3 * 0 + 1] = Smat[3 * 1 + 0] = mu * (dA_dak_cov_aka1 / a[1] - dA_dak_cov_aka2 / a[2]);

} // GaussianFit<>::ConvertParametersAndErrors()

template<typename T >

void lar::util::GaussianFit< T >::ConvertParametersAndErrors ( FitParameters_t const &  qpars, FitMatrix_t const &  qparerrmat, FitParameters_t &  params, FitParameters_t &  paramerrors  )

staticprotected

Converts the specified quadratic fit parameters and errors.

Parameters

qpars	the quadratic fit parameters
qparerrmat	the quadratic fit parameter error matrix
params	the Gaussian fit parameters
paramerrors	the Gaussian fit parameter errors

Definition at line 1879 of file SimpleFits.h.

{
  ConvertParametersAndVariances(qpars, qparerrmat, params, paramerrors);
  // paramerrors actually stores the square of the error; fix it:
  for (Data_t& paramerror : paramerrors)
    paramerror = std::sqrt(paramerror);
} // GaussianFit<>::ConvertParametersAndErrors()

template<typename T >

void lar::util::GaussianFit< T >::ConvertParametersAndVariances ( FitParameters_t const &  qpars, FitMatrix_t const &  qparerrmat, FitParameters_t &  params, FitParameters_t &  paramvariances  )

staticprotected

Converts the specified quadratic fit parameters and errors.

Parameters

qpars	the quadratic fit parameters
qparerrmat	the quadratic fit parameter error matrix
params	the Gaussian fit parameters
paramvariances	the Gaussian fit parameter variance

Definition at line 1850 of file SimpleFits.h.

References lar::util::details::FitDataCollector< T, D >::sqr().

{
  params = ConvertParameters(qpars);

  FitParameters_t const& a = qpars;
  Data_t const& A = params[0];
  Data_t const& mu = params[1];
  Data_t const& sigma = params[2];

  // error on sigma
  paramvariances[2] = qparerrmat[3 * 2 + 2] / sqr(cube(sigma));

  // error on mu
  paramvariances[1] =
    sqr(mu * (+qparerrmat[3 * 1 + 1] / sqr(a[1]) - 2. * qparerrmat[3 * 2 + 1] / (a[1] * a[2]) +
              qparerrmat[3 * 2 + 2] / sqr(a[2])));

  // error on A
  paramvariances[0] =
    sqr(A * (+qparerrmat[3 * 0 + 0] + 2. * qparerrmat[3 * 0 + 1] * mu +
             (qparerrmat[3 * 1 + 1] + 2. * qparerrmat[3 * 0 + 2]) * sqr(mu) +
             2. * qparerrmat[3 * 1 + 2] * cube(mu) + qparerrmat[3 * 2 + 2] * sqr(sqr(mu))));

} // GaussianFit<>::ConvertParametersAndVariances()

static constexpr Data_t lar::util::details::SimpleFitterInterface< T, N >::cube ( Data_t  v )

inlinestaticinherited

Returns the cube of the specified data value.

Definition at line 603 of file SimpleFits.h.

{ return v * v * v; }

template<typename T>

static Data_t lar::util::GaussianFit< T >::DecodeValue ( Data_t  value )

inlinestaticprotected

Converts a value from the quadratic fit into a proper value.

Definition at line 1240 of file SimpleFits.h.

{ return std::exp(value); }

template<typename T>

static Value_t lar::util::GaussianFit< T >::DecodeValue ( Value_t const &  value )

inlinestaticprotected

Converts a value from the quadratic fit into a proper value.

Definition at line 1255 of file SimpleFits.h.

References lar::util::GaussianFit< T >::Value_t::error(), and lar::util::GaussianFit< T >::Value_t::value().

      {
        const Data_t v = std::exp(value.value());
        return {v, v * value.error()};
      } // DecodeValue()

virtual Data_t lar::util::details::SimpleFitterInterface< T, N >::Determinant ( FitMatrix_t const &  mat ) const

inlineprotectedvirtualinherited

Computes the determinant of a matrix.

Definition at line 607 of file SimpleFits.h.

        {
          return MatrixOps::Determinant(mat);
        }

template<typename T>

template<typename Pred >

static EncodeExtractor<Pred> lar::util::GaussianFit< T >::Encoder ( Pred &  pred )

inlinestaticprotected

Converts a value into a proper input for the quadratic fit; does not accept 0 or negative values!

Definition at line 1329 of file SimpleFits.h.

      {
        return {pred};
      }

template<typename T>

template<typename VPred , typename UPred >

static EncodeExtractor<VPred, UPred> lar::util::GaussianFit< T >::Encoder ( VPred &  vpred, UPred &  upred  )

inlinestaticprotected

Converts a value into a proper input for the quadratic fit; does not accept 0 or negative values!

Definition at line 1335 of file SimpleFits.h.

      {
        return {vpred, upred};
      }

template<typename T>

static Data_t lar::util::GaussianFit< T >::EncodeValue ( Data_t  value )

inlinestaticprotected

Converts a value into a proper input for the quadratic fit; does not accept 0 or negative values!

Definition at line 1237 of file SimpleFits.h.

{ return std::log(value); }

template<typename T>

static Value_t lar::util::GaussianFit< T >::EncodeValue ( Data_t  value, Data_t  error  )

inlinestaticprotected

Converts a value and error into a proper input for the quadratic fit.

Definition at line 1243 of file SimpleFits.h.

References util::abs().

      {
        return {std::log(value), error / std::abs(value)};
      }

template<typename T>

static Value_t lar::util::GaussianFit< T >::EncodeValue ( Value_t const &  value )

inlinestaticprotected

Converts a value and error into a proper input for the quadratic fit.

Definition at line 1249 of file SimpleFits.h.

References lar::util::GaussianFit< T >::Value_t::error(), and lar::util::GaussianFit< T >::Value_t::value().

      {
        return EncodeValue(value.value(), value.error());
      }

template<typename T>

static Measurement_t lar::util::GaussianFit< T >::EncodeValue ( Measurement_t const &  meas )

inlinestaticprotected

Converts a value and error into a proper input for the quadratic fit.

Definition at line 1262 of file SimpleFits.h.

      {
        return Measurement_t(std::get<0>(meas), EncodeValue(std::get<1>(meas)));
      }

template<typename T>

static MeasurementAndUncertainty_t lar::util::GaussianFit< T >::EncodeValue ( MeasurementAndUncertainty_t const &  meas )

inlinestaticprotected

Converts a value and error into a proper input for the quadratic fit.

Definition at line 1268 of file SimpleFits.h.

References lar::util::GaussianFit< T >::Value_t::error(), and lar::util::GaussianFit< T >::Value_t::value().

      {
        Value_t value = EncodeValue(Value_t(meas));
        return {std::get<0>(meas), value.value(), value.error()};
      } // EncodeValue(MeasurementAndUncertainty_t)

template<typename T>

static MeasurementAndUncertainty_t lar::util::GaussianFit< T >::EncodeValue ( Measurement_t const &  meas, Data_t  error  )

inlinestaticprotected

Converts a value and error into a proper input for the quadratic fit.

Definition at line 1275 of file SimpleFits.h.

References lar::util::GaussianFit< T >::Value_t::error(), and lar::util::GaussianFit< T >::Value_t::value().

      {
        Value_t value = EncodeValue(Value_t(std::get<1>(meas), error));
        return {std::get<0>(meas), value.value(), value.error()};
      } // EncodeValue(Measurement_t, Data_t)

virtual Data_t lar::util::details::SimpleFitterInterface< T, N >::Evaluate ( Data_t  x ) const

pure virtualinherited

Evaluates the fitted function at the specified point.

Parameters

x	the point where to evaluate the fit function

Returns

the value of the fit function

No check is performed whether the fit is valid.

template<typename T>

virtual Data_t lar::util::GaussianFit< T >::Evaluate ( Data_t  x ) const

inlineoverridevirtual

Evaluates the fitted function at the specified point.

Parameters

x	the point where to evaluate the fit function

Returns

the value of the fit function

No check is performed whether the fit is valid.

Definition at line 1198 of file SimpleFits.h.

      {
        return Evaluate(x, FitParameters().data());
      }

template<typename T >

auto lar::util::GaussianFit< T >::Evaluate ( Data_t  x, Data_t const *  params  )

static

Evaluates a Gaussian with given parameters at one point.

Parameters

x	the point where to evaluate the fit function
params	Gaussian parameters: amplitude, mean, sigma

Returns

the Gaussian function evaluated at x

Definition at line 1828 of file SimpleFits.h.

References lar::util::details::FitDataCollector< T, D >::sqr(), and z.

{
  Data_t z = (x - params[1]) / params[2];
  return params[0] * std::exp(-0.5 * sqr(z));
} // GaussianFit<>::Evaluate()

virtual bool lar::util::details::SimpleFitterInterface< T, N >::FillResults ( FitParameters_t &  params, FitMatrix_t &  Xmat, Data_t &  det, FitMatrix_t &  Smat  ) const

pure virtualinherited

Fills the specified parameters.

Parameters

params	the fitted values of the parameters
Xmat	the matrix of the x^n/s^2 sums
Smat	the covariance matrix
det	the determinant of Xmat

Returns

true if the fit is valid (i.e. if a unique solution exists)

virtual bool lar::util::details::SimpleFitterInterface< T, N >::FillResults ( FitParameters_t &  params, FitParameters_t &  paramerrors, FitMatrix_t &  Xmat, Data_t &  det, FitMatrix_t &  Smat  ) const

pure virtualinherited

Fills the specified parameters.

Parameters

params	the fitted values of the parameters
paramerrors	the uncertainty on the fitted parameters
Xmat	the matrix of the x^n/s^2 sums
Smat	the covariance matrix
det	the determinant of Xmat

Returns

true if the fit is valid (i.e. if a unique solution exists)

virtual bool lar::util::details::SimpleFitterInterface< T, N >::FillResults ( FitParameters_t &  params, FitParameters_t &  paramerrors  ) const

pure virtualinherited

Fills the specified parameters.

Parameters

params	the fitted values of the parameters
paramerrors	the uncertainty on the fitted parameters

Returns

true if the fit is valid (i.e. if a unique solution exists)

template<typename T >

bool lar::util::GaussianFit< T >::FillResults ( FitParameters_t &  params, FitMatrix_t &  Xmat, Data_t &  det, FitMatrix_t &  Smat  ) const

overridevirtual

Fills the specified parameters.

Parameters

params	the fitted values of the parameters
Xmat	the matrix of the x^n/s^2 sums
Smat	the covariance matrix
det	the determinant of Xmat

Returns

true if the fit is valid (i.e. if a unique solution exists)

Unsupported.

Definition at line 1803 of file SimpleFits.h.

Referenced by hit::CCHitFinderAlg::FastGaussianFit().

{
  FitParameters_t qpars;
  FitMatrix_t qparerrmat;
  if (!fitter.FillResults(qpars, Xmat, det, qparerrmat)) return false;
  ConvertParametersAndErrorMatrix(qpars, qparerrmat, params, Smat);
  return isValid(params, qpars);
} // GaussianFit::FillResults()

template<typename T >

bool lar::util::GaussianFit< T >::FillResults ( FitParameters_t &  params, FitParameters_t &  paramerrors, FitMatrix_t &  Xmat, Data_t &  det, FitMatrix_t &  Smat  ) const

overridevirtual

Fills the specified parameters.

Parameters

params	the fitted values of the parameters
paramerrors	the uncertainty on the fitted parameters
Xmat	the matrix of the x^n/s^2 sums
Smat	the covariance matrix
det	the determinant of Xmat

Returns

true if the fit is valid (i.e. if a unique solution exists)

Unsupported.

Definition at line 1816 of file SimpleFits.h.

{
  if (!FillResults(params, Xmat, det, Smat)) return false;
  paramerrors = fitter.ExtractParameterErrors(Smat);
  return true;
} // GaussianFit::FillResults()

template<typename T >

bool lar::util::GaussianFit< T >::FillResults ( FitParameters_t &  params, FitParameters_t &  paramerrors  ) const

overridevirtual

Fills the specified parameters.

Parameters

params	the fitted values of the parameters
paramerrors	the uncertainty on the fitted parameters

Returns

true if the fit is valid (i.e. if a unique solution exists)

Only the version returning the parameters and errors is supported.

Definition at line 1790 of file SimpleFits.h.

{
  FitParameters_t qpars;
  FitMatrix_t qparerrmat;
  FitMatrix_t Xmat; // not used
  Data_t det;       // not used
  if (!fitter.FillResults(qpars, Xmat, det, qparerrmat)) return false;
  ConvertParametersAndErrors(qpars, qparerrmat, params, paramerrors);
  return isValid(params, qpars);
} // GaussianFit<>::FillResults()

virtual Data_t lar::util::details::SimpleFitterInterface< T, N >::FitParameter ( unsigned int  n ) const

inlinevirtualinherited

Returns the parameter n of the fit result.

Parameters

n	degree of the parameter; must be no larger than Degree

Returns

the parameter of the fit, in y/x^n units

Exceptions

std::runtime_error

if there is no unique solution

Definition at line 521 of file SimpleFits.h.

{ return FitParameters()[n]; }

template<typename T >

auto lar::util::GaussianFit< T >::FitParameterCovariance ( ) const

overridevirtual

Computes and returns all the covariance matrix of the fit result.

Returns

the the covariance matrix of the fit

Exceptions

std::runtime_error

if there is no unique solution

Not supported. It's fairly too complicate to fill the whole matrix. Doable, on request.

Implements lar::util::details::SimpleFitterInterface< T, 3 >.

Definition at line 1776 of file SimpleFits.h.

{
  // we need to go through the whole chain to get the error matrix
  FitParameters_t params;
  FitMatrix_t Xmat;
  Data_t det;
  FitMatrix_t Smat;
  if (!FillResults(params, Xmat, det, Smat)) {
    throw std::runtime_error("GaussianFit::FitParameterCovariance() yielded invalid results");
  }
  return Smat;
} // SimplePolyFitterBase<>::FitParameterCovariance()

virtual Data_t lar::util::details::SimpleFitterInterface< T, N >::FitParameterError ( unsigned int  n ) const

inlinevirtualinherited

Returns the error on parameter n of the fit result.

Parameters

n	degree of the parameter; must be no larger than Degree

Returns

the error on the parameter of the fit, in y/x^n units

Exceptions

std::runtime_error

if there is no unique solution

Definition at line 529 of file SimpleFits.h.

        {
          return std::sqrt(FitParameterCovariance()[n * (NParams + 1)]);
        }

template<typename T >

auto lar::util::GaussianFit< T >::FitParameterErrors ( ) const

overridevirtual

Computes and returns all the parameter errors of the fit result.

Returns

the full set of parameter errors of the fit

Exceptions

std::runtime_error

if there is no unique solution

Implements lar::util::details::SimpleFitterInterface< T, 3 >.

Definition at line 1766 of file SimpleFits.h.

{
  FitParameters_t qpars, qparerrors;
  if (!FillResults(qpars, qparerrors)) {
    throw std::runtime_error("GaussianFit::FitParameterErrors() yielded invalid results");
  }
  return qparerrors;
} // GaussianFit<>::FitParameterErrors()

template<typename T >

auto lar::util::GaussianFit< T >::FitParameters ( ) const

overridevirtual

Computes and returns all the parameters of the fit result.

Returns

the full set of parameters of the fit

Exceptions

std::runtime_error

if there is no unique solution

Implements lar::util::details::SimpleFitterInterface< T, 3 >.

Definition at line 1760 of file SimpleFits.h.

{
  return ConvertParameters(fitter.FitParameters());
} // GaussianFit<>::FitParameters()

template<typename T>

virtual Fitter_t const& lar::util::GaussianFit< T >::Fitter ( ) const

inlinevirtual

Returns the internal fitter (mostly for debugging)

Definition at line 1204 of file SimpleFits.h.

{ return fitter; }

virtual FitMatrix_t lar::util::details::SimpleFitterInterface< T, N >::InvertMatrix ( FitMatrix_t const &  mat, Data_t  det  ) const

inlineprotectedvirtualinherited

Computes the inverse of a matrix (using provided determinant)

Definition at line 613 of file SimpleFits.h.

        {
          return MatrixOps::InvertSymmetricMatrix(mat, det);
        }

virtual FitMatrix_t lar::util::details::SimpleFitterInterface< T, N >::InvertMatrix ( FitMatrix_t const &  mat ) const

inlineprotectedvirtualinherited

Computes the inverse of a matrix.

Definition at line 619 of file SimpleFits.h.

        {
          return MatrixOps::InvertSymmetricMatrix(mat);
        }

template<typename T>

virtual bool lar::util::GaussianFit< T >::isValid ( ) const

inlineoverridevirtual

Returns if the fit has valid results.

Returns

if the fit has valid results

The fit has no valid results if:

1. insufficient data has been add()ed (no more than the fit Degree)
2. if input points are vertically aligned

Note that checking point 2 is expensive in terms of time.

Implements lar::util::details::SimpleFitterInterface< T, 3 >.

Definition at line 1097 of file SimpleFits.h.

{ return fitter.isValid(); }

template<typename T >

bool lar::util::GaussianFit< T >::isValid ( FitParameters_t const &  params, FitParameters_t const &  qpars  )

staticprotected

Returns whether the specified parameters represent a valid fit.

Parameters

params	Gaussian parameters
qpars	quadratic fit parameters

Returns

whether specified parameters represent a valid Gaussian fit

Definition at line 1935 of file SimpleFits.h.

{
  return (qpars[2] < Data_t(0)) && (params[0] >= Data_t(0));
} // GaussianFit<>::isValid(FitParameters_t)

virtual FitParameters_t lar::util::details::SimpleFitterInterface< T, N >::MatrixProduct ( FitMatrix_t const &  mat, FitParameters_t const &  vec  ) const

inlineprotectedvirtualinherited

Computes the product of a FitMatrix_t and a FitParameters_t.

Definition at line 625 of file SimpleFits.h.

        {
          return MatrixOps::MatrixVectorProduct(mat, vec);
        }

template<typename T>

int lar::util::GaussianFit< T >::N ( ) const

inline

Returns the number of (valid) points added.

Definition at line 1074 of file SimpleFits.h.

{ return fitter.N(); }

template<typename T>

virtual int lar::util::GaussianFit< T >::NDF ( ) const

inlineoverridevirtual

Returns the degrees of freedom in the determination of the fit.

Returns

the degrees of freedom in the determination of the fit

The return value may be 0 or negative if insufficient points have been added.

Implements lar::util::details::SimpleFitterInterface< T, 3 >.

Definition at line 1144 of file SimpleFits.h.

Referenced by hit::CCHitFinderAlg::FastGaussianFit().

{ return fitter.NDF(); }

Data_t lar::util::details::SimpleFitterInterface< T, N >::operator() ( Data_t  x ) const

inlineinherited

Evaluates the fitted function; alias of Evaluate()

Definition at line 597 of file SimpleFits.h.

{ return Evaluate(x); }

template<typename T>

template<typename Stream >

void lar::util::GaussianFit< T >::PrintStats ( Stream &  out ) const

inline

Prints the collected statistics into a stream.

Definition at line 1078 of file SimpleFits.h.

      {
        fitter.PrintStats(out);
      }

static constexpr Data_t lar::util::details::SimpleFitterInterface< T, N >::sqr ( Data_t  v )

inlinestaticinherited

Returns the square of the specified data value.

Definition at line 600 of file SimpleFits.h.

{ return v * v; }

template<typename T>

static void lar::util::GaussianFit< T >::ThrowNotImplemented ( std::string  method )

inlinestaticprotected

Definition at line 1393 of file SimpleFits.h.

      {
        throw std::logic_error("Method " + method + "() not implemented");
      }

Member Data Documentation

template<typename T>

Fitter_t lar::util::GaussianFit< T >::fitter

protected

the actual fitter and data holder

Definition at line 1215 of file SimpleFits.h.

template<typename T>

constexpr unsigned int lar::util::GaussianFit< T >::NParams = Base_t::NParams

static

Number of parameters in the fit.

Definition at line 999 of file SimpleFits.h.

---

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

• lardata/v09_16_03/source/lardata/Utilities/SimpleFits.h