#include <GreedySampler.h>

Inheritance diagram for CAROM::GreedySampler:

Public Member Functions
	GreedySampler (std::vector< Vector > parameter_points, bool check_local_rom, double relative_error_tolerance, double alpha, double max_clamp, int subset_size, int convergence_subset_size, std::string output_log_path="", std::string warm_start_file_name="", bool use_centroid=true, int random_seed=1, bool debug_algorithm=false)
	Constructor. More...

	GreedySampler (std::vector< double > parameter_points, bool check_local_rom, double relative_error_tolerance, double alpha, double max_clamp, int subset_size, int convergence_subset_size, std::string output_log_path="", std::string warm_start_file_name="", bool use_centroid=true, int random_seed=1, bool debug_algorithm=false)
	Constructor. More...

	GreedySampler (Vector param_space_min, Vector param_space_max, int num_parameter_points, bool check_local_rom, double relative_error_tolerance, double alpha, double max_clamp, int subset_size, int convergence_subset_size, std::string output_log_path="", std::string warm_start_file_name="", bool use_centroid=true, int random_seed=1, bool debug_algorithm=false)
	Constructor. More...

	GreedySampler (double param_space_min, double param_space_max, int num_parameter_points, bool check_local_rom, double relative_error_tolerance, double alpha, double max_clamp, int subset_size, int convergence_subset_size, std::string output_log_path="", std::string warm_start_file_name="", bool use_centroid=true, int random_seed=1, bool debug_algorithm=false)
	Constructor. More...

	GreedySampler (std::string base_file_name, std::string output_log_path="")
	Constructor. More...

	~GreedySampler ()
	Destructor.

std::shared_ptr< Vector >	getNextParameterPoint ()
	Returns the next parameter point for which sampling is required. More...

struct GreedyErrorIndicatorPoint	getNextPointRequiringRelativeError ()
	Returns the next parameter point for which a relative error is required. More...

struct GreedyErrorIndicatorPoint	getNextPointRequiringErrorIndicator ()
	Returns the next parameter point for which an error indicator is required. More...

void	setPointRelativeError (double error)
	Set the relative error of the specified point. More...

void	setPointErrorIndicator (double error, int vec_size)
	Set the error indicator error of the specified parameter point. More...

int	getNearestNonSampledPoint (Vector point)
	Returns the index of the nearest non-sampled parameter point to the given point. More...

std::shared_ptr< Vector >	getNearestROM (Vector point)
	Returns the nearest local ROM to the specified parameter point. More...

std::vector< Vector >	getParameterPointDomain ()
	Get the domain of the parameter points. More...

std::vector< Vector >	getSampledParameterPoints ()
	Get the sampled parameter points. More...

virtual void	save (std::string base_file_name)
	Save the object state to a file. More...

bool	isComplete ()
	Check if the greedy algorithm procedure is complete. More...

Protected Member Functions
void	addDatabaseFromFile (std::string const &warm_start_file_name)
	Do a warm start by adding the sampled parameters from the database in a file to the current database. More...

virtual void	load (std::string base_file_name)
	Load the object state from a file. More...

virtual void	constructParameterPoints ()=0
	Construct the list of parameter point candidates to sample.

void	checkParameterPointInput ()
	Construct the list of parameter point candidates to sample.

void	constructObject (bool check_local_rom, double relative_error_tolerance, double alpha, double max_clamp, int subset_size, int convergence_subset_size, std::string output_log_path, bool use_centroid, int random_seed, bool debug_algorithm)
	Construct the GreedySampler object.

void	initializeParameterPoints ()
	Initialize the list of parameter point candidates to sample.

struct GreedyErrorIndicatorPoint	getNextSubsetPointRequiringErrorIndicator ()
	Get the next subset point requiring an error indicator. More...

struct GreedyErrorIndicatorPoint	getNextConvergencePointRequiringErrorIndicator ()
	Get the next convergence point requiring an error indicator. More...

std::vector< Vector >	generateRandomPoints (int num_points)
	Generate a vector of random points. More...

void	agnosticPrint (std::string str)
	Print to output_log_file or cout.

void	printErrorIndicator (Vector errorIndicatorPoint, double proc_errors)
	Print the error indicator. More...

void	printErrorIndicatorToleranceNotMet ()
	Print that the error indicator was not met.

void	printSamplingType (std::string sampling_type)
	Print the sampling type. More...

void	printConvergenceAchieved ()
	Print that convergence was achieved.

void	setSubsetErrorIndicator (double proc_errors)
	Set the error indicator for a subset point. More...

void	setConvergenceErrorIndicator (double proc_errors)
	Set the error indicator for a convergence point. More...

void	generateConvergenceSubset ()
	Generate a new set of convergence points.

void	startConvergence ()
	Switch to convergence mode.

virtual void	getNextParameterPointAfterConvergenceFailure ()=0
	Get the next parameter point to sample after a convergence failure.

int	getNearestROMIndexToParameterPoint (int index, bool ignore_self)
	Returns the index to the nearest local ROM to the specified parameter point index in the parameter point list. More...

Protected Attributes
std::vector< Vector >	d_parameter_points
	The parameter points to explore.

std::vector< Vector >	d_convergence_points
	The convergence parameter points to explore.

Vector	d_min_param_point
	The minimum value of the parameter space.

Vector	d_max_param_point
	The maximum value of the parameter space.

std::set< int >	d_parameter_sampled_indices
	The parameter points that were already sampled.

std::vector< int >	d_parameter_point_random_indices
	The parameter point indices (used to generate the random subsets).

std::vector< double >	d_parameter_point_errors
	The current errors of the parameter points.

std::vector< int >	d_parameter_point_local_rom
	The local ROMs used to obtain the current errors of the parameter points.

std::string	d_output_log_path
	Output log path.

double	d_max_error
	The current max error of the parameter points of the current iteration.

double	d_curr_relative_error
	The current relative error of the current iteration.

double	d_alpha
	The alpha constant.

double	d_max_clamp
	The max_clamp constant.

double	d_error_indicator_tol
	The error indicator tolerance used to terminate the greedy procedure.

double	d_relative_error_tol
	The relative error tolerance used to terminate the greedy procedure.

int	d_num_parameter_points
	The maximum number of parameter points to sample.

int	d_subset_size
	The size of the subset of parameter points used per iteration.

int	d_convergence_subset_size
	The size of the subset of parameter points used to check convergence.

int	d_next_point_to_sample
	The next parameter point to sample.

int	d_next_point_requiring_error_indicator
	The next parameter point requiring a error indicator.

bool	d_use_centroid
	Whether the use the centroid heuristic for obtaining the first parameter point.

bool	d_check_local_rom
	Whether the check the last sampled local ROM's error indicator after each iteration.

bool	d_iteration_started
	Whether the database has already computed a new parameter point for the current iteration.

bool	d_convergence_started
	Whether the database is in the convergence verifying phase.

bool	d_next_parameter_point_computed
	Whether the database has already computed a new parameter point to sample.

bool	d_point_requiring_error_indicator_computed
	Whether the database has already computed a new paramter point requiring a error indicator.

bool	d_subset_created
	Whether the database has already created a random subset for this iteration.

bool	d_debug_algorithm
	Turn off randomness for debugging purposes.

int	d_counter
	An internal counter.

int	d_subset_counter
	An internal subset counter.

bool	d_procedure_completed
	Whether the greedy procedure has completed.

int	d_rank
	The rank of the given processor.

int	d_random_seed
	Then random seed used to generate subsets.

std::default_random_engine	rng
	Random engine used to generate subsets.

Detailed Description

Class GreedySampler is a class defining the interface of a greedy algorithm that given a domain of parameter points, iteratively returns the next best parameter point to sample in order to create a ROM database efficiently.

Constructor & Destructor Documentation

CAROM::GreedySampler::GreedySampler	(	std::vector< Vector >	parameter_points,
		bool	check_local_rom,
		double	relative_error_tolerance,
		double	alpha,
		double	max_clamp,
		int	subset_size,
		int	convergence_subset_size,
		std::string	output_log_path = `""`,
		std::string	warm_start_file_name = `""`,
		bool	use_centroid = `true`,
		int	random_seed = `1`,
		bool	debug_algorithm = `false`
	)

Constructor.

Parameters

[in]	parameter_points	A vector of CAROM::Vectors containing many user-defined parameter points from which a subset will be chosen for building ROMs.
[in]	check_local_rom	Compute local ROM error indicator each iteration.
[in]	relative_error_tolerance	The relative error tolerance value for which to end the algorithm.
[in]	alpha	A constant factor to increase the error indicator tolerance each iteration.
[in]	max_clamp	A scalar factor representing the maximum amount the error indicator tolerance can change per iteration.
[in]	subset_size	The size of the random subset.
[in]	convergence_subset_size	The size of the convergence subset.
[in]	output_log_path	The path to the output log file. If not used, outputs to stdout.
[in]	warm_start_file_name	The path to the HDF5 file of a previous database to use as a warm start.
[in]	use_centroid	Whether to use the centroid heuristic when determining the first parameter point to sample.
[in]	random_seed	A random seed.
[in]	debug_algorithm	Whether to turn off all randomness for debugging purposes.

CAROM::GreedySampler::GreedySampler	(	std::vector< double >	parameter_points,
		bool	check_local_rom,
		double	relative_error_tolerance,
		double	alpha,
		double	max_clamp,
		int	subset_size,
		int	convergence_subset_size,
		std::string	output_log_path = `""`,
		std::string	warm_start_file_name = `""`,
		bool	use_centroid = `true`,
		int	random_seed = `1`,
		bool	debug_algorithm = `false`
	)

Constructor.

Parameters

[in]	parameter_points	A vector of doubles containing the different parameter points.
[in]	check_local_rom	Compute local ROM error indicator each iteration.
[in]	relative_error_tolerance	The relative error tolerance value for which to end the algorithm.
[in]	alpha	A alpha constant to increase greedy algorithm by each iteration.
[in]	max_clamp	A scalar factor representing the maximum amount the error indicator tolerance can change per iteration.
[in]	subset_size	The size of the random subset.
[in]	convergence_subset_size	The size of the convergence subset.
[in]	output_log_path	The path to the output log file. If not used, outputs to stdout.
[in]	warm_start_file_name	The path to the HDF5 file of a previous database to use as a warm start.
[in]	use_centroid	Whether to use the centroid heuristic when determining the first parameter point to sample.
[in]	random_seed	A random seed.
[in]	debug_algorithm	Whether to turn off all randomness for debugging purposes.

CAROM::GreedySampler::GreedySampler	(	Vector	param_space_min,
		Vector	param_space_max,
		int	num_parameter_points,
		bool	check_local_rom,
		double	relative_error_tolerance,
		double	alpha,
		double	max_clamp,
		int	subset_size,
		int	convergence_subset_size,
		std::string	output_log_path = `""`,
		std::string	warm_start_file_name = `""`,
		bool	use_centroid = `true`,
		int	random_seed = `1`,
		bool	debug_algorithm = `false`
	)

Constructor.

Parameters

[in]	param_space_min	A CAROM::Vector representing the minimum of the parameter space domain.
[in]	param_space_max	A CAROM::Vector representing the maximum of the parameter space domain.
[in]	num_parameter_points	The maximum number of parameter points to sample.
[in]	check_local_rom	Compute local ROM error indicator each iteration.
[in]	relative_error_tolerance	The relative error tolerance value for which to end the algorithm.
[in]	alpha	A alpha constant to increase greedy algorithm by each iteration.
[in]	max_clamp	A scalar factor representing the maximum amount the error indicator tolerance can change per iteration.
[in]	subset_size	The size of the random subset.
[in]	convergence_subset_size	The size of the convergence subset.
[in]	output_log_path	The path to the output log file. If not used, outputs to stdout.
[in]	warm_start_file_name	The path to the HDF5 file of a previous database to use as a warm start.
[in]	use_centroid	Whether to use the centroid heuristic when determining the first parameter point to sample.
[in]	random_seed	A random seed.
[in]	debug_algorithm	Whether to turn off all randomness for debugging purposes.

CAROM::GreedySampler::GreedySampler	(	double	param_space_min,
		double	param_space_max,
		int	num_parameter_points,
		bool	check_local_rom,
		double	relative_error_tolerance,
		double	alpha,
		double	max_clamp,
		int	subset_size,
		int	convergence_subset_size,
		std::string	output_log_path = `""`,
		std::string	warm_start_file_name = `""`,
		bool	use_centroid = `true`,
		int	random_seed = `1`,
		bool	debug_algorithm = `false`
	)

Constructor.

Parameters

[in]	param_space_min	A double representing the minimum of the parameter space domain.
[in]	param_space_max	A double representing the maximum of the parameter space domain.
[in]	num_parameter_points	The maximum number of parameter points to sample.
[in]	check_local_rom	Compute local ROM error indicator each iteration.
[in]	relative_error_tolerance	The relative error tolerance value for which to end the algorithm.
[in]	alpha	A alpha constant to increase greedy algorithm by each iteration.
[in]	max_clamp	A scalar factor representing the maximum amount the error indicator tolerance can change per iteration.
[in]	subset_size	The size of the random subset.
[in]	convergence_subset_size	The size of the convergence subset.
[in]	output_log_path	The path to the output log file. If not used, outputs to stdout.
[in]	warm_start_file_name	The path to the HDF5 file of a previous database to use as a warm start.
[in]	use_centroid	Whether to use the centroid heuristic when determining the first parameter point to sample.
[in]	random_seed	A random seed.
[in]	debug_algorithm	Whether to turn off all randomness for debugging purposes.

CAROM::GreedySampler::GreedySampler	(	std::string	base_file_name,
		std::string	output_log_path = `""`
	)

Constructor.

Parameters

[in]	base_file_name	The base part of the file of the database to load when restarting from a save.
[in]	output_log_path	The path to the output log file. If not used, outputs to stdout.

Member Function Documentation

void CAROM::GreedySampler::addDatabaseFromFile ( std::string const & warm_start_file_name )

protected

Do a warm start by adding the sampled parameters from the database in a file to the current database.

Parameters

[in] warm_start_file_name The path to the HDF5 file of a previous database to use as a warm start.

std::vector<Vector> CAROM::GreedySampler::generateRandomPoints ( int num_points )

protected

Generate a vector of random points.

Parameters

[in] num_points The number of points to generate

Returns: A vector of random points.

int CAROM::GreedySampler::getNearestNonSampledPoint ( Vector point )

Returns the index of the nearest non-sampled parameter point to the given point.

Parameters

[in] point The CAROM::Vector holding the point.

Returns: An integer holding the nearest non-sampled point to the given point or -1 if none exist.

std::shared_ptr<Vector> CAROM::GreedySampler::getNearestROM ( Vector point )

Returns the nearest local ROM to the specified parameter point.

Parameters

[in] point The CAROM::Vector holding the point.

Returns: A shared pointer holding the point or NULL if no local ROM exists.

int CAROM::GreedySampler::getNearestROMIndexToParameterPoint	(	int	index,
		bool	ignore_self
	)

protected

Returns the index to the nearest local ROM to the specified parameter point index in the parameter point list.

Parameters

[in]	index	The index of the specified parameter point.
[in]	ignore_self	Whether to ignore the specified parameter point if a local ROM was built there.

Returns: The index of the point in the list of parameters.

struct GreedyErrorIndicatorPoint CAROM::GreedySampler::getNextConvergencePointRequiringErrorIndicator ( )

protected

Get the next convergence point requiring an error indicator.

Returns: A struct holding the point and the location of the nearest local ROM or NULL if no point is required.

std::shared_ptr<Vector> CAROM::GreedySampler::getNextParameterPoint ( )

Returns the next parameter point for which sampling is required.

Returns: A shared pointer holding the point or NULL if a point is not ready to be sampled.

struct GreedyErrorIndicatorPoint CAROM::GreedySampler::getNextPointRequiringErrorIndicator ( )

Returns the next parameter point for which an error indicator is required.

Returns: A struct holding the point and the location of the nearest local ROM or NULL if no point is required.

struct GreedyErrorIndicatorPoint CAROM::GreedySampler::getNextPointRequiringRelativeError ( )

Returns the next parameter point for which a relative error is required.

Returns: A struct holding the point and the location of the nearest local ROM or NULL if no point is required.

struct GreedyErrorIndicatorPoint CAROM::GreedySampler::getNextSubsetPointRequiringErrorIndicator ( )

protected

Get the next subset point requiring an error indicator.

Returns: A struct holding the point and the location of the nearest local ROM or NULL if no point is required.

std::vector<Vector> CAROM::GreedySampler::getParameterPointDomain ( )

Get the domain of the parameter points.

Returns: A vector holding all parameter point candidates.

std::vector<Vector> CAROM::GreedySampler::getSampledParameterPoints ( )

Get the sampled parameter points.

Returns: A vector holding all sampled parameter points.

bool CAROM::GreedySampler::isComplete ( )

Check if the greedy algorithm procedure is complete.

Returns: A boolean representing if the greedy algorithm procedure is complete.

virtual void CAROM::GreedySampler::load ( std::string base_file_name )

protectedvirtual

Load the object state from a file.

Parameters

[in] base_file_name The base part of the file to load the database from.

Reimplemented in CAROM::GreedyRandomSampler.

void CAROM::GreedySampler::printErrorIndicator	(	Vector	errorIndicatorPoint,
		double	proc_errors
	)

protected

Print the error indicator.

Parameters

[in]	errorIndicatorPoint	The vector where the error indicator was obtained.
[in]	proc_errors	The error indicator value.

void CAROM::GreedySampler::printSamplingType ( std::string sampling_type )

protected

Print the sampling type.

Parameters

[in] sampling_type The sampling type.

virtual void CAROM::GreedySampler::save ( std::string base_file_name )

virtual

Save the object state to a file.

Parameters

[in] base_file_name The base part of the file to save the database to.

Reimplemented in CAROM::GreedyRandomSampler.

void CAROM::GreedySampler::setConvergenceErrorIndicator ( double proc_errors )

protected

Set the error indicator for a convergence point.

Parameters

[in] proc_errors The error indicator value.

void CAROM::GreedySampler::setPointErrorIndicator	(	double	error,
		int	vec_size
	)

Set the error indicator error of the specified parameter point.

Parameters

[in]	error	The error indicator value.
[in]	vec_size	The size of the vector the error indicator was obtained from. This is used for normalization.

void CAROM::GreedySampler::setPointRelativeError ( double error )

Set the relative error of the specified point.

Parameters

[in] error The relative error.

void CAROM::GreedySampler::setSubsetErrorIndicator ( double proc_errors )

protected

Set the error indicator for a subset point.

Parameters

[in] proc_errors The error indicator value.

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

lib/algo/greedy/GreedySampler.h

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation