Gauss function object. More...

#include <JGauss.hh>

Inheritance diagram for JMATH::JGauss< ID_t, normalised >:

Public Types
typedef double JGauss::*	parameter_type
	Type definition of fit parameter.

Public Member Functions
	JGauss ()
	Default constructor.

	JGauss (const JGauss_t &gauss)
	Copy constructor.

	JGauss (const double mean, const double sigma, const double signal=1.0, const double background=0.0)
	Constructor.

double	getValue (const double x) const
	Function value.

double	getDerivative (const double x) const
	Derivative value.

double	operator() (const double x) const
	Function value.

const JGauss_t &	getGradient (const double x) const
	Get gradient.

	JGauss ()
	Default constructor.

	JGauss (const double center, const double sigma)
	Constructor.

double	getValue (const double x) const
	Function value.

double	getDerivative (const double x) const
	Derivative value.

const JGauss &	getGradient (const double x) const
	Get gradient.

bool	equals (const JGauss_t &gauss, const double eps=std::numeric_limits< double >::min()) const
	Equality.

JGauss_t &	add (const JGauss_t &gauss)
	Add gauss.

JGauss_t &	sub (const JGauss_t &gauss)
	Subtract gauss.

JGauss_t &	mul (const double factor)
	Scale gauss.

JGauss_t &	mul (const JSecond_t &object)
	Multiply with object.

double	operator() (const Args &...args) const
	Function value.

JGauss< ID_t > &	negate ()
	Negate function.

JGauss< ID_t > &	add (const JGauss< ID_t > &f1)
	Add function.

JGauss< ID_t > &	sub (const JGauss< ID_t > &f1)
	Subtract function.

JGauss< ID_t > &	mul (const double factor)
	Scale function.

JGauss< ID_t > &	div (const double factor)
	Scale function.

Public Attributes
double	center
	center

double	sigma
	sigma

double	mean

double	signal

double	background

Static Public Attributes
static const int	ID = ID_t

static const parameter_list< JGauss >	parameters = { &JGauss<ID_t, normalised>::center, &JGauss<ID_t, normalised>::sigma }
	parameters

Private Member Functions
double	get (const double u) const
	Get ordinate value.

double	get (const double u) const
	Get ordinate value.

Private Attributes
JGauss_t	gradient

Detailed Description

template<int ID_t, bool normalised = false>
struct JMATH::JGauss< ID_t, normalised >

Gauss function object.

Gauss function.

Evaluates function, derivative and gradient values.

Definition at line 1586 of file JMathlib.hh.

Member Typedef Documentation

◆ parameter_type

template<int ID_t, bool normalised = false>

double JGauss::* JMATH::JGauss< ID_t, normalised >::parameter_type

Type definition of fit parameter.

Definition at line 179 of file JGauss.hh.

Constructor & Destructor Documentation

◆ JGauss() [1/5]

template<int ID_t, bool normalised = false>

JMATH::JGauss< ID_t, normalised >::JGauss ( )

inline

Default constructor.

Definition at line 185 of file JGauss.hh.

             :
      JGauss_t()
    {}

◆ JGauss() [2/5]

template<int ID_t, bool normalised = false>

JMATH::JGauss< ID_t, normalised >::JGauss ( const JGauss_t & gauss )

inline

Copy constructor.

Parameters

gauss gauss

Definition at line 195 of file JGauss.hh.

                                  :
      JGauss_t(gauss)
    {}

◆ JGauss() [3/5]

template<int ID_t, bool normalised = false>

JMATH::JGauss< ID_t, normalised >::JGauss	(	const double	mean,
		const double	sigma,
		const double	signal = 1.0,
		const double	background = 0.0 )

inline

Constructor.

Parameters

mean	mean
sigma	sigma
signal	signal
background	background

Definition at line 208 of file JGauss.hh.

                                          :
      JGauss_t(mean, sigma, signal, background)
    {}

◆ JGauss() [4/5]

template<int ID_t, bool normalised = false>

JMATH::JGauss< ID_t, normalised >::JGauss ( )

inline

Default constructor.

Definition at line 1596 of file JMathlib.hh.

             :
      center(0.0),
      sigma (0.0)
    {}

◆ JGauss() [5/5]

template<int ID_t, bool normalised = false>

JMATH::JGauss< ID_t, normalised >::JGauss	(	const double	center,
		const double	sigma )

inline

Constructor.

Parameters

center	center
sigma	sigma

Definition at line 1608 of file JMathlib.hh.

                               :
      center(center),
      sigma (sigma)
    {}

Member Function Documentation

◆ getValue() [1/2]

template<int ID_t, bool normalised = false>

double JMATH::JGauss< ID_t, normalised >::getValue ( const double x ) const

inline

Function value.

Parameters

x	abscissa value

Returns: function value

Definition at line 222 of file JGauss.hh.

    {
      const double u  = (x - mean) / sigma;
 
      return signal * get(u) + background;
    }

◆ getDerivative() [1/2]

template<int ID_t, bool normalised = false>

double JMATH::JGauss< ID_t, normalised >::getDerivative ( const double x ) const

inline

Derivative value.

Parameters

x	abscissa value

Returns: derivative value

Definition at line 236 of file JGauss.hh.

    {
      const double u  = (x - mean) / sigma;
 
      return signal * get(u) * -u / sigma;
    }

◆ operator()() [1/2]

template<int ID_t, bool normalised = false>

double JMATH::JGauss< ID_t, normalised >::operator() ( const double x ) const

inline

Function value.

Parameters

x	abscissa value

Returns: function value

Definition at line 250 of file JGauss.hh.

    {
      return getValue(x);
    }

◆ getGradient() [1/2]

template<int ID_t, bool normalised = false>

const JGauss_t & JMATH::JGauss< ID_t, normalised >::getGradient ( const double x ) const

inline

Get gradient.

Parameters

x	abscissa value

Returns: gradient

Definition at line 262 of file JGauss.hh.

    {
      const double w  = 1.0 / sigma;
      const double u  = (x - mean) * w;
      const double f0 =  get(u);
      const double fs =  signal * f0;
 
      gradient.mean       =  fs * (u)                   * w;             // d(f)/d(mean)
      gradient.sigma      =  fs * (u + 1.0) * (u - 1.0) * w;             // d(f)/d(sigma)
      gradient.signal     =  f0;                                         // d(f)/d(signal)
      gradient.background =  1.0;                                        // d(f)/d(background)
 
      return gradient;
    }

◆ get() [1/2]

template<int ID_t, bool normalised = false>

double JMATH::JGauss< ID_t, normalised >::get ( const double u ) const

inlineprivate

Get ordinate value.

Parameters

u	abscissa value

Returns: ordinate value

Definition at line 284 of file JGauss.hh.

    {
      return exp(-0.5*u*u) / (sqrt(2.0*PI) * sigma);
    }

◆ getValue() [2/2]

template<int ID_t, bool normalised = false>

double JMATH::JGauss< ID_t, normalised >::getValue ( const double x ) const

inline

Function value.

Parameters

x	abscissa value

Returns: function value

Definition at line 1621 of file JMathlib.hh.

    {
      const double u  = (x - center) / sigma;
 
      return get(u);
    }

◆ getDerivative() [2/2]

template<int ID_t, bool normalised = false>

double JMATH::JGauss< ID_t, normalised >::getDerivative ( const double x ) const

inline

Derivative value.

Parameters

x	abscissa value

Returns: derivative value

Definition at line 1635 of file JMathlib.hh.

    {
      const double w  = 1.0 / sigma;
      const double u  = (x - center) / sigma;
 
      return get(u) * -u * w;
    }

◆ getGradient() [2/2]

template<int ID_t, bool normalised = false>

const JGauss & JMATH::JGauss< ID_t, normalised >::getGradient ( const double x ) const

inline

Get gradient.

Parameters

x	abscissa value

Returns: gradient

Definition at line 1650 of file JMathlib.hh.

    {
      static JGauss gradient;
 
      const double w  = 1.0 / sigma;
      const double u  = (x - center) * w;
      const double f0 =  get(u);
 
      gradient.center =  f0 * u * w;                          // d(f)/d(center)
      gradient.sigma  =  f0 * u * u * w;                      // d(f)/d(sigma)
 
      return gradient;
    }

◆ get() [2/2]

template<int ID_t, bool normalised = false>

double JMATH::JGauss< ID_t, normalised >::get ( const double u ) const

inlineprivate

Get ordinate value.

Parameters

u	abscissa value

Returns: ordinate value

Definition at line 1675 of file JMathlib.hh.

    {
      return exp(-0.5*u*u);
    }

◆ equals()

bool JMATH::JGauss_t::equals	(	const JGauss_t &	gauss,
		const double	eps = std::numeric_limits<double>::min() ) const

inlineinherited

Equality.

Parameters

gauss	gauss
eps	numerical precision

Returns: true if gauss's identical; else false

Definition at line 70 of file JGauss.hh.

    {
      return (fabs(mean       - gauss.mean)       <=  eps  &&
              fabs(sigma      - gauss.sigma)      <=  eps  &&
              fabs(signal     - gauss.signal)     <=  eps  &&
              fabs(background - gauss.background) <=  eps);
    }

◆ add() [1/2]

JGauss_t & JMATH::JGauss_t::add ( const JGauss_t & gauss )

inlineinherited

Add gauss.

Parameters

gauss gauss

Returns: this gauss

Definition at line 86 of file JGauss.hh.

    {
      mean       += gauss.mean;
      sigma      += gauss.sigma;
      signal     += gauss.signal;
      background += gauss.background;
 
      return *this;
    }

◆ sub() [1/2]

JGauss_t & JMATH::JGauss_t::sub ( const JGauss_t & gauss )

inlineinherited

Subtract gauss.

Parameters

gauss gauss

Returns: this gauss

Definition at line 103 of file JGauss.hh.

    {
      mean       -= gauss.mean;
      sigma      -= gauss.sigma;
      signal     -= gauss.signal;
      background -= gauss.background;
 
      return *this;
    }

◆ mul() [1/3]

JGauss_t & JMATH::JGauss_t::mul ( const double factor )

inlineinherited

Scale gauss.

Parameters

factor multiplication factor

Returns: this gauss

Definition at line 120 of file JGauss.hh.

    {
      mean       *= factor;
      sigma      *= factor;
      signal     *= factor;
      background *= factor;
 
      return *this;
    }

◆ mul() [2/3]

JGauss_t & JMATH::JMath< JGauss_t, JSecond_t >::mul ( const JSecond_t & object )

inlineinherited

Multiply with object.

Parameters

object object

Returns: result object

Definition at line 354 of file JMath.hh.

    {
      return static_cast<JFirst_t&>(*this) = JFirst_t().mul(static_cast<const JFirst_t&>(*this), object);
    }

◆ operator()() [2/2]

double JMATH::JMathlib< JGauss< ID_t > >::operator() ( const Args &... args ) const

inlineinherited

Function value.

Parameters

args	abscissa value(s)

Returns: function value

Definition at line 362 of file JMathlib.hh.

    {
      return static_cast<const JF1_t&>(*this).getValue(args...);
    }

◆ negate()

JGauss< ID_t > & JMATH::JCalculus< JGauss< ID_t > >::negate ( )

inlineinherited

Negate function.

Returns: this function

Definition at line 203 of file JMathlib.hh.

    {
      for (const auto& i : JF1_t::parameters) {
        static_cast<JF1_t&>(*this).*i = -(static_cast<JF1_t&>(*this).*i);
      }
 
      return static_cast<JF1_t&>(*this);
    }

◆ add() [2/2]

JGauss< ID_t > & JMATH::JCalculus< JGauss< ID_t > >::add ( const JGauss< ID_t > & f1 )

inlineinherited

Add function.

Parameters

f1 function

Returns: this function

Definition at line 219 of file JMathlib.hh.

    {
      for (const auto& i : JF1_t::parameters) {
        static_cast<JF1_t&>(*this).*i += f1.*i;
      }
 
      return static_cast<JF1_t&>(*this);
    }

◆ sub() [2/2]

JGauss< ID_t > & JMATH::JCalculus< JGauss< ID_t > >::sub ( const JGauss< ID_t > & f1 )

inlineinherited

Subtract function.

Parameters

f1 function

Returns: this function

Definition at line 235 of file JMathlib.hh.

    {
      for (const auto& i : JF1_t::parameters) {
        static_cast<JF1_t&>(*this).*i -= f1.*i;
      }
 
      return static_cast<JF1_t&>(*this);
    }

◆ mul() [3/3]

JGauss< ID_t > & JMATH::JCalculus< JGauss< ID_t > >::mul ( const double factor )

inlineinherited

Scale function.

Parameters

factor factor

Returns: this function

Definition at line 251 of file JMathlib.hh.

    {
      for (const auto& i : JF1_t::parameters) {
        static_cast<JF1_t&>(*this).*i *= factor;
      }
 
      return static_cast<JF1_t&>(*this);
    }

◆ div()

JGauss< ID_t > & JMATH::JCalculus< JGauss< ID_t > >::div ( const double factor )

inlineinherited

Scale function.

Parameters

factor factor

Returns: this function

Definition at line 267 of file JMathlib.hh.

    {
      for (const auto& i : JF1_t::parameters) {
        static_cast<JF1_t&>(*this).*i /= factor;
      }
 
      return static_cast<JF1_t&>(*this);
    }

Member Data Documentation

◆ gradient

template<int ID_t, bool normalised = false>

JGauss_t JMATH::JGauss< ID_t, normalised >::gradient

mutableprivate

Definition at line 289 of file JGauss.hh.

◆ ID

template<int ID_t, bool normalised = false>

const int JMATH::JGauss< ID_t, normalised >::ID = ID_t

static

Definition at line 1590 of file JMathlib.hh.

◆ center

template<int ID_t, bool normalised = false>

double JMATH::JGauss< ID_t, normalised >::center

center

Definition at line 1664 of file JMathlib.hh.

◆ sigma

template<int ID_t, bool normalised = false>

double JMATH::JGauss< ID_t, normalised >::sigma

sigma

Definition at line 1665 of file JMathlib.hh.

◆ parameters

template<int ID_t>

const parameter_list< JGauss< ID_t, true > > JMATH::JGauss< ID_t >::parameters = { &JGauss<ID_t, normalised>::center, &JGauss<ID_t, normalised>::sigma }

static

parameters

Set parameters.

Definition at line 1666 of file JMathlib.hh.

◆ mean

double JMATH::JGauss_t::mean

inherited

Definition at line 161 of file JGauss.hh.

◆ signal

double JMATH::JGauss_t::signal

inherited

Definition at line 163 of file JGauss.hh.

◆ background

double JMATH::JGauss_t::background

inherited

Definition at line 164 of file JGauss.hh.

The documentation for this struct was generated from the following files:

Public Types

Public Member Functions

Public Attributes

Static Public Attributes

Private Member Functions

Private Attributes

Detailed Description

Member Typedef Documentation

◆ parameter_type

Constructor & Destructor Documentation

◆ JGauss() [1/5]

◆ JGauss() [2/5]

◆ JGauss() [3/5]

◆ JGauss() [4/5]

◆ JGauss() [5/5]

Member Function Documentation

◆ getValue() [1/2]

◆ getDerivative() [1/2]

◆ operator()() [1/2]

◆ getGradient() [1/2]

◆ get() [1/2]

◆ getValue() [2/2]

◆ getDerivative() [2/2]

◆ getGradient() [2/2]

◆ get() [2/2]

◆ equals()

◆ add() [1/2]

◆ sub() [1/2]

◆ mul() [1/3]

◆ mul() [2/3]

◆ operator()() [2/2]

◆ negate()

◆ add() [2/2]

◆ sub() [2/2]

◆ mul() [3/3]

◆ div()

Member Data Documentation

◆ gradient

◆ ID

◆ center

◆ sigma

◆ parameters

◆ mean

◆ signal

◆ background