GaussianDer Class Reference

Defines the derivative of the normal probability function by. More...

#include <gaussian_der.h>

Inheritance diagram for GaussianDer:

Collaboration diagram for GaussianDer:

Public Member Functions
	GaussianDer (double mu_, double sigma_)
	Sets the default for the parameter mu to 0.0 and for the parameter sigma to 1.0.
virtual float	function (const float lambda_) const
virtual double	function (const double lambda_) const
virtual long double	function (const long double lambda_) const
Public Member Functions inherited from Function
virtual	~Function ()
	Default virtual destructor.

Public Attributes
double	mu
double	sigma

Detailed Description

Defines the derivative of the normal probability function by.

\[ f: \lambda \mapsto -\frac{x}{\sigma^2 \sqrt{2 \pi}} e^{-\frac{1}{2} x^2}, \]

where

\[ x = \frac{\lambda - \mu}{\sigma}, \]

and \( \mu \) and \( \sigma \) parameters are the mean and standard deviation of the Gaussian function and should be set by this->mu and this->sigma members, respectively.

The matrix function \( f: \mathbb{R}^{n \times n} \to \mathbb{R}^{n \times n} \) is used in

\[ \mathrm{trace} \left( f(\mathbf{A}) \right). \]

However, instead of a matrix function, the equivalent scalar function \( f: \mathbb{R} \to \mathbb{R} \) is defiend which acts on the eigenvalues of the matrix.

Definition at line 51 of file gaussian_der.h.

Constructor & Destructor Documentation

GaussianDer()

GaussianDer::GaussianDer	(	double	mu_,
		double	sigma_
	)

Sets the default for the parameter mu to 0.0 and for the parameter sigma to 1.0.

Definition at line 34 of file gaussian_der.cpp.

{
    this->mu = mu_;
    this->sigma = sigma_;
}

References mu, and sigma.

Member Function Documentation

function() [1/3]

double GaussianDer::function ( const double  lambda_ ) const

virtual

Parameters

[in]

lambda_

Eigenvalue (or singular value) of matrix.

Returns

The value of matrix function for the given eigenvalue.

Implements Function.

Definition at line 67 of file gaussian_der.cpp.

{
    double x = (lambda_ - this->mu) / this->sigma;
    double sigma2 = this->sigma * this->sigma;
    return -(x * 0.5 * M_SQRT1_2 * M_2_SQRTPI / sigma2) * \
        std::exp(-0.5 * x * x);
}

References mu, and sigma.

function() [2/3]

float GaussianDer::function ( const float  lambda_ ) const

virtual

Parameters

[in]

lambda_

Eigenvalue (or singular value) of matrix.

Returns

The value of matrix function for the given eigenvalue.

Implements Function.

Definition at line 48 of file gaussian_der.cpp.

{
    float mu_ = static_cast<float>(this->mu);
    float sigma_ = static_cast<float>(this->sigma);
    float sigma2 = sigma_ * sigma_;
    float x = (lambda_ - mu_) / sigma_;
    return -(x * 0.5f * M_SQRT1_2 * M_2_SQRTPI / sigma2) * \
        std::exp(-0.5 * x * x);
}

References mu, and sigma.

function() [3/3]

long double GaussianDer::function ( const long double  lambda_ ) const

virtual

Parameters

[in]

lambda_

Eigenvalue (or singular value) of matrix.

Returns

The value of matrix function for the given eigenvalue.

Implements Function.

Definition at line 84 of file gaussian_der.cpp.

{
    long double mu_ = static_cast<long double>(this->mu);
    long double sigma_ = static_cast<long double>(this->sigma);
    long double sigma2 = sigma_ * sigma_;
    long double x = (lambda_ - mu_) / sigma_;
    return -(x * 0.5l * M_SQRT1_2 * M_2_SQRTPI / sigma2) * \
        std::exp(-0.5 * x * x);
}

References mu, and sigma.

Member Data Documentation

mu

double GaussianDer::mu

Definition at line 58 of file gaussian_der.h.

Referenced by function(), function(), function(), and GaussianDer().

sigma

double GaussianDer::sigma

Definition at line 59 of file gaussian_der.h.

Referenced by function(), function(), function(), and GaussianDer().

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

• /home/runner/work/imate/imate/imate/functions/gaussian_der.h
• /home/runner/work/imate/imate/imate/functions/gaussian_der.cpp