Saba::Sampler Class Reference

An interface class for custom sample algorithms. More...

Public Member Functions
	Sampler (unsigned int dimension)
virtual	~Sampler ()
virtual void	sample (Eigen::VectorXf &stroreConfig, CSpacePtr space)=0
virtual void	enableMetricWeights (const Eigen::VectorXf &weights)
virtual void	disableMetricWeights ()

Protected Member Functions
void	getUniformlyRandomConfig (Eigen::VectorXf &stroreConfig, CSpacePtr space)
	Returns a uniformly generated random configuration with nDimension components. More...
void	getNormalRandomConfig (Eigen::VectorXf &stroreConfig, const Eigen::VectorXf &mean, const Eigen::MatrixXf &variance)
void	getNormalRandomConfig (Eigen::VectorXf &stroreConfig, const Eigen::VectorXf &mean, float variance)

Protected Attributes
unsigned int	dimension
Eigen::VectorXf	metricWeights

Detailed Description

An interface class for custom sample algorithms.

Constructor & Destructor Documentation

Sampler()

Saba::Sampler::Sampler

(

unsigned int

dimension

)

~Sampler()

Saba::Sampler::~Sampler ( )

virtualdefault

Member Function Documentation

disableMetricWeights()

void Saba::Sampler::disableMetricWeights ( )

virtual

enableMetricWeights()

void Saba::Sampler::enableMetricWeights ( const Eigen::VectorXf &  weights )

virtual

Enable metric weighting. This can be useful for different variance in each dimension. Standard: disabled

getNormalRandomConfig() [1/2]

void Saba::Sampler::getNormalRandomConfig ( Eigen::VectorXf &  stroreConfig, const Eigen::VectorXf &  mean, const Eigen::MatrixXf &  variance  )

protected

Returns a normal distributed random configuration with nDimension components. Note that we assume the covariance-matrix to be a diagonal matrix. This means, that the components of the configuration are uncorrelated. The result value is not checked against any boundaries of the configuration space.

getNormalRandomConfig() [2/2]

void Saba::Sampler::getNormalRandomConfig ( Eigen::VectorXf &  stroreConfig, const Eigen::VectorXf &  mean, float  variance  )

protected

Returns a normal distributed random configuration with nDimension components. This is a convenience function in case you want to apply the same variance in every dimension.

getUniformlyRandomConfig()

void Saba::Sampler::getUniformlyRandomConfig ( Eigen::VectorXf &  stroreConfig, CSpacePtr  space  )

protected

Returns a uniformly generated random configuration with nDimension components.

sample()

virtual void Saba::Sampler::sample ( Eigen::VectorXf &  stroreConfig, CSpacePtr  space  )

pure virtual

Field Documentation

dimension

unsigned int Saba::Sampler::dimension

protected

metricWeights

Eigen::VectorXf Saba::Sampler::metricWeights

protected