hops
Public Member Functions | Friends | List of all members
hops::RunBase< Model, Proposal > Class Template Reference

#include <Problem.hpp>

Collaboration diagram for hops::RunBase< Model, Proposal >:
Collaboration graph

Public Member Functions

 RunBase (MarkovChainType markovChainType, unsigned long numberOfSamples=1000, unsigned long numberOfChains=1)
 
 RunBase (const Problem< Model > &problem, MarkovChainType markovChainType=MarkovChainType::HitAndRun, unsigned long numberOfSamples=1000, unsigned long numberOfChains=1)
 
 RunBase (Proposal m_proposal, unsigned long numberOfSamples=1000, unsigned long numberOfChains=1)
 
 RunBase (const Problem< Model > &problem, Proposal m_proposal, unsigned long numberOfSamples=1000, unsigned long numberOfChains=1)
 
 RunBase ()=default
 
void setProblem (const Problem< Model > &problem)
 
const Problem< Model > & getProblem ()
 
void setStartingPoints (const std::vector< Eigen::VectorXd > &startingPoints)
 
const std::vector< Eigen::VectorXd > & getStartingPoints ()
 
void setMarkovChainType (MarkovChainType markovChainType)
 
MarkovChainType getMarkovChainType ()
 
void setNumberOfChains (unsigned long numberOfChains)
 
unsigned long getNumberOfChains ()
 
void setNumberOfSamples (unsigned long numberOfSamples)
 
unsigned long getNumberOfSamples ()
 
void setThinning (unsigned long thinning)
 
unsigned long getThinning ()
 
void setUseRounding (bool useRounding)
 
bool getUseRounding ()
 
void setStepSize (double stepSize)
 
double getStepSize ()
 
void setFisherWeight (double fisherWeight)
 
double getFisherWeight ()
 
void setRandomSeed (double randomSeed)
 
double getRandomSeed ()
 
void setSamplingUntilConvergence (bool sampleUntilConvergence)
 
bool getSamplingUntilConvergence ()
 
void setConvergenceThreshold (double convergenceThreshold)
 
double getConvergenceThreshold ()
 
void setMaxRepetitions (double maxRepetitions)
 
double getMaxRepetitions ()
 
Data & getData ()
 
void init ()
 
void sample ()
 
void sample (unsigned long numberOfSamples, unsigned long thinning=1)
 

Friends

void tune (RunBase &run, AcceptanceRateTuner::param_type &parameters)
 
void tune (RunBase &run, ExpectedSquaredJumpDistanceTuner::param_type &parameters)
 
void tune (RunBase &run, SimpleExpectedSquaredJumpDistanceTuner::param_type &parameters)
 

Constructor & Destructor Documentation

◆ RunBase() [1/5]

template<typename Model , typename Proposal >
hops::RunBase< Model, Proposal >::RunBase ( MarkovChainType  markovChainType,
unsigned long  numberOfSamples = 1000,
unsigned long  numberOfChains = 1 
)
inline

◆ RunBase() [2/5]

template<typename Model , typename Proposal >
hops::RunBase< Model, Proposal >::RunBase ( const Problem< Model > &  problem,
MarkovChainType  markovChainType = MarkovChainType::HitAndRun,
unsigned long  numberOfSamples = 1000,
unsigned long  numberOfChains = 1 
)
inline

◆ RunBase() [3/5]

template<typename Model , typename Proposal >
hops::RunBase< Model, Proposal >::RunBase ( Proposal  m_proposal,
unsigned long  numberOfSamples = 1000,
unsigned long  numberOfChains = 1 
)
inline

◆ RunBase() [4/5]

template<typename Model , typename Proposal >
hops::RunBase< Model, Proposal >::RunBase ( const Problem< Model > &  problem,
Proposal  m_proposal,
unsigned long  numberOfSamples = 1000,
unsigned long  numberOfChains = 1 
)
inline

◆ RunBase() [5/5]

template<typename Model , typename Proposal >
hops::RunBase< Model, Proposal >::RunBase ( )
default

Member Function Documentation

◆ getConvergenceThreshold()

template<typename Model , typename Proposal >
double hops::RunBase< Model, Proposal >::getConvergenceThreshold

◆ getData()

template<typename Model , typename Proposal >
Data & hops::RunBase< Model, Proposal >::getData

◆ getFisherWeight()

template<typename Model , typename Proposal >
double hops::RunBase< Model, Proposal >::getFisherWeight

◆ getMarkovChainType()

template<typename Model , typename Proposal >
MarkovChainType hops::RunBase< Model, Proposal >::getMarkovChainType

◆ getMaxRepetitions()

template<typename Model , typename Proposal >
double hops::RunBase< Model, Proposal >::getMaxRepetitions

◆ getNumberOfChains()

template<typename Model , typename Proposal >
unsigned long hops::RunBase< Model, Proposal >::getNumberOfChains

◆ getNumberOfSamples()

template<typename Model , typename Proposal >
unsigned long hops::RunBase< Model, Proposal >::getNumberOfSamples

◆ getProblem()

template<typename Model , typename Proposal >
const Problem< Model > & hops::RunBase< Model, Proposal >::getProblem

◆ getRandomSeed()

template<typename Model , typename Proposal >
double hops::RunBase< Model, Proposal >::getRandomSeed

◆ getSamplingUntilConvergence()

template<typename Model , typename Proposal >
bool hops::RunBase< Model, Proposal >::getSamplingUntilConvergence

◆ getStartingPoints()

template<typename Model , typename Proposal >
const std::vector< Eigen::VectorXd > & hops::RunBase< Model, Proposal >::getStartingPoints

◆ getStepSize()

template<typename Model , typename Proposal >
double hops::RunBase< Model, Proposal >::getStepSize

◆ getThinning()

template<typename Model , typename Proposal >
unsigned long hops::RunBase< Model, Proposal >::getThinning

◆ getUseRounding()

template<typename Model , typename Proposal >
bool hops::RunBase< Model, Proposal >::getUseRounding

◆ init()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::init ( )
inline

◆ sample() [1/2]

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::sample ( )
inline

◆ sample() [2/2]

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::sample ( unsigned long  numberOfSamples,
unsigned long  thinning = 1 
)
inline

◆ setConvergenceThreshold()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setConvergenceThreshold ( double  convergenceThreshold)

◆ setFisherWeight()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setFisherWeight ( double  fisherWeight)

◆ setMarkovChainType()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setMarkovChainType ( MarkovChainType  markovChainType)

◆ setMaxRepetitions()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setMaxRepetitions ( double  maxRepetitions)

◆ setNumberOfChains()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setNumberOfChains ( unsigned long  numberOfChains)

◆ setNumberOfSamples()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setNumberOfSamples ( unsigned long  numberOfSamples)

◆ setProblem()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setProblem ( const Problem< Model > &  problem)

◆ setRandomSeed()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setRandomSeed ( double  randomSeed)

◆ setSamplingUntilConvergence()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setSamplingUntilConvergence ( bool  sampleUntilConvergence)

◆ setStartingPoints()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setStartingPoints ( const std::vector< Eigen::VectorXd > &  startingPoints)

◆ setStepSize()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setStepSize ( double  stepSize)

◆ setThinning()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setThinning ( unsigned long  thinning)

◆ setUseRounding()

template<typename Model , typename Proposal >
void hops::RunBase< Model, Proposal >::setUseRounding ( bool  useRounding)

Friends And Related Function Documentation

◆ tune [1/3]

template<typename Model , typename Proposal >
void tune ( RunBase< Model, Proposal > &  run,
AcceptanceRateTuner::param_type &  parameters 
)
friend

◆ tune [2/3]

template<typename Model , typename Proposal >
void tune ( RunBase< Model, Proposal > &  run,
ExpectedSquaredJumpDistanceTuner::param_type &  parameters 
)
friend

◆ tune [3/3]

template<typename Model , typename Proposal >
void tune ( RunBase< Model, Proposal > &  run,
SimpleExpectedSquaredJumpDistanceTuner::param_type &  parameters 
)
friend
The documentation for this class was generated from the following files:
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