Generates pseudo-random Gaussian noise for simulating the Process. More...

#include <gaussian_noise.hpp>

Inheritance diagram for GaussianNoise:

Public Member Functions
virtual GaussianNoise *	clone () const

virtual GaussianNoise *	clone (uint idx) const

	GaussianNoise ()

	GaussianNoise (const DVector &_mean, const DVector &_variance)

	GaussianNoise (uint _dim, double _mean, double _variance)

	GaussianNoise (const GaussianNoise &rhs)

const DVector &	getMean () const

const DVector &	getVariance () const

virtual returnValue	init (uint seed=0)

GaussianNoise &	operator= (const GaussianNoise &rhs)

returnValue	setMean (uint idx, double _mean)

returnValue	setMeans (const DVector &_mean)

returnValue	setMeans (double _mean)

returnValue	setVariance (uint idx, double _variance)

returnValue	setVariances (const DVector &_variance)

returnValue	setVariances (double _variance)

virtual returnValue	step (DVector &_w)

virtual returnValue	step (VariablesGrid &_w)

virtual	~GaussianNoise ()

Public Member Functions inherited from Noise
uint	getDim () const

BlockStatus	getStatus () const

BooleanType	isEmpty () const

	Noise ()

	Noise (const Noise &rhs)

Noise &	operator= (const Noise &rhs)

virtual	~Noise ()

Protected Member Functions
double	getGaussianRandomNumber (double _mean, double _variance) const

Protected Member Functions inherited from Noise
double	getUniformRandomNumber (double _lowerLimit, double _upperLimit) const

returnValue	setStatus (BlockStatus _status)

Protected Attributes
DVector	mean

DVector	variance

Protected Attributes inherited from Noise
BlockStatus	status

VariablesGrid	w

Detailed Description

Generates pseudo-random Gaussian noise for simulating the Process.

The class GaussiaNoise generates pseudo-random Gaussian noise for simulating the Process within the SimulationEnvironment.

Author: Hans Joachim Ferreau, Boris Houska

Definition at line 53 of file gaussian_noise.hpp.

Constructor & Destructor Documentation

BEGIN_NAMESPACE_ACADO GaussianNoise::GaussianNoise ( )

Default constructor.

Definition at line 45 of file gaussian_noise.cpp.

GaussianNoise::GaussianNoise	(	const DVector &	_mean,
		const DVector &	_variance
	)

Constructor which takes mean value and variance of the random variable. The dimension of these limit vector determine the dimension of the random variable.

Parameters

[in]	_mean	Mean value for each component.
[in]	_variance	Variance for each component.

Definition at line 50 of file gaussian_noise.cpp.

GaussianNoise::GaussianNoise	(	uint	_dim,
		double	_mean,
		double	_variance
	)

Constructor which takes the dimension of the random variable as well as as common values for the mean value and variance of the random variable.

Parameters

[in]	_dim	Dimension of random variable.
[in]	_mean	Mean value for each component.
[in]	_variance	Variance for each component.

Definition at line 65 of file gaussian_noise.cpp.

GaussianNoise::GaussianNoise ( const GaussianNoise & rhs )

Copy constructor (deep copy).

@param[in] rhs      Right-hand side object.

Definition at line 83 of file gaussian_noise.cpp.

GaussianNoise::~GaussianNoise ( )

virtual

Destructor.

Definition at line 90 of file gaussian_noise.cpp.

Member Function Documentation

GaussianNoise * GaussianNoise::clone ( ) const

virtual

Clone constructor (deep copy).

\return Pointer to deep copy of base class type

Implements Noise.

Definition at line 109 of file gaussian_noise.cpp.

GaussianNoise * GaussianNoise::clone ( uint idx ) const

virtual

Clone constructor for a given noise component (deep copy).

@param[in] idx              Right-hand side object.

\return Pointer to deep copy of base class type

Implements Noise.

Definition at line 115 of file gaussian_noise.cpp.

double GaussianNoise::getGaussianRandomNumber	(	double	_mean,
		double	_variance
	)		const

protected

Returns a pseudo-random number based on a Gaussian distribution with given mean and variance.

Parameters

[in]	_mean	Mean value of Gaussian distribution.
[in]	_variance	Variance of Gaussian distribution.

Returns: Gaussian distributed pseudo-random number

Definition at line 200 of file gaussian_noise.cpp.

const DVector& GaussianNoise::getMean ( ) const

inline

Returns mean values of the random variable.

\return Mean values of the random variable

const DVector& GaussianNoise::getVariance ( ) const

inline

Returns variances of the random variable.

\return Variances of the random variable

returnValue GaussianNoise::init ( uint seed = 0 )

virtual

Initializes noise generation and performs a couple of consistency checks. Initialization of the pseudo-random number generator can be based on a seed in order to allow exact reproduction of generated noise. If seed is not specified (i.e. 0), a seed is obtain from the system clock.

Parameters

[in] seed Seed for pseudo-random number generator.

Returns: SUCCESSFUL_RETURN,
RET_INVALID_NOISE_SETTINGS,
RET_NO_NOISE_SETTINGS

Implements Noise.

Definition at line 132 of file gaussian_noise.cpp.

GaussianNoise & GaussianNoise::operator= ( const GaussianNoise & rhs )

Assignment Operator (deep copy)

@param[in] rhs      Right-hand side object.

Definition at line 95 of file gaussian_noise.cpp.

returnValue GaussianNoise::setMean	(	uint	idx,
		double	_mean
	)

inline

Assigns new mean value on the component of the random variable with given index.

Parameters

[in]	idx	Index of component.
[in]	_mean	New mean value.

Returns: SUCCESSFUL_RETURN,
RET_INDEX_OUT_OF_BOUNDS

returnValue GaussianNoise::setMeans ( const DVector & _mean )

inline

Assigns new mean values to the random variable.

@param[in] _mean            New mean value for each component.

\return SUCCESSFUL_RETURN, \n
        RET_VECTOR_DIMENSION_MISMATCH

returnValue GaussianNoise::setMeans ( double _mean )

inline

Assigns new mean values to the random variable.

@param[in] _mean            New common mean value for all components.

\return SUCCESSFUL_RETURN, \n
        RET_INVALID_ARGUMENTS

returnValue GaussianNoise::setVariance	(	uint	idx,
		double	_variance
	)

inline

Assigns new variance on the component of the random variable with given index.

Parameters

[in]	idx	Index of component.
[in]	_variance	New variance.

Returns: SUCCESSFUL_RETURN,
RET_INDEX_OUT_OF_BOUNDS

returnValue GaussianNoise::setVariances ( const DVector & _variance )

inline

Assigns new variances to the random variable.

@param[in] _variance        New variances for each component.

\return SUCCESSFUL_RETURN, \n
        RET_VECTOR_DIMENSION_MISMATCH

returnValue GaussianNoise::setVariances ( double _variance )

inline

Assigns new variances to the random variable.

@param[in] _variance        New common variance for all components.

\return SUCCESSFUL_RETURN, \n
        RET_INVALID_ARGUMENTS

returnValue GaussianNoise::step ( DVector & _w )

virtual

Generates a single noise vector based on current internal settings.

@param[out] _w              Generated noise vector.

Returns: SUCCESSFUL_RETURN,
RET_BLOCK_NOT_READY,
RET_VECTOR_DIMENSION_MISMATCH

Implements Noise.

Definition at line 153 of file gaussian_noise.cpp.

returnValue GaussianNoise::step ( VariablesGrid & _w )

virtual

Generates a noise vector sequence based on current internal settings. Noise is generated for each grid point of the VariablesGrid passed.

Parameters

[in,out] _w Generated noise vector sequence.

Returns: SUCCESSFUL_RETURN,
RET_BLOCK_NOT_READY,
RET_VECTOR_DIMENSION_MISMATCH

Implements Noise.

Definition at line 174 of file gaussian_noise.cpp.

Member Data Documentation

DVector GaussianNoise::mean

protected

Mean value for each component.

Definition at line 266 of file gaussian_noise.hpp.

DVector GaussianNoise::variance

protected

Variance for each component.

Definition at line 267 of file gaussian_noise.hpp.

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

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation