MR2T2 Class Reference

MCMC algorithm implementing the Metropolis–Rosenbluth–Rosenbluth–Teller–Teller (MR \(^2\)T \(^2\)) method. More...

#include <Fitters/MR2T2.h>

Inheritance diagram for MR2T2:

Collaboration diagram for MR2T2:

Public Member Functions
	MR2T2 (manager *const manager)
	Constructor. More...
virtual	~MR2T2 ()=default
	Destructor. More...
Public Member Functions inherited from MCMCBase
	MCMCBase (manager *const fitMan)
	Constructor. More...
virtual	~MCMCBase ()=default
	Destructor. More...
void	RunMCMC () override
	Actual implementation of MCMC fitting algorithm. More...
void	StartFromPreviousFit (const std::string &FitName) override
	Allow to start from previous fit/chain. More...
void	setChainLength (unsigned int L)
	Set how long chain should be. More...
Public Member Functions inherited from FitterBase
	FitterBase (manager *const fitMan)
	Constructor. More...
virtual	~FitterBase ()
	Destructor for the FitterBase class. More...
void	AddSampleHandler (SampleHandlerBase *sample)
	This function adds a sample PDF object to the analysis framework. The sample PDF object will be utilized in fitting procedures or likelihood scans. More...
void	AddSystObj (ParameterHandlerBase *cov)
	This function adds a Covariance object to the analysis framework. The Covariance object will be utilized in fitting procedures or likelihood scans. More...
void	DragRace (const int NLaps=100)
	Calculates the required time for each sample or covariance object in a drag race simulation. Inspired by Dan's feature. More...
void	RunLLHScan ()
	Perform a 1D likelihood scan. More...
void	GetStepScaleBasedOnLLHScan ()
	LLH scan is good first estimate of step scale. More...
void	Run2DLLHScan ()
	Perform a 2D likelihood scan. More...
void	RunSigmaVar ()
	Perform a 2D and 1D sigma var for all samples. More...
void	RunSigmaVarFD ()
	Perform a 1D sigma var for all samples. More...
std::string	GetName () const
	Get name of class. More...

Protected Member Functions
void	DoStep () override
	The MCMC step proposal and acceptance. More...
void	ProposeStep () override
	Propose a step. More...
double	AcceptanceProbability () override
	Step acceptance probability. More...
Protected Member Functions inherited from MCMCBase
void	DoMCMCStep ()
	The full StartStep->DoStep->EndStep chain. More...
void	PreStepProcess ()
	Actions before step proposal [start stopwatch]. More...
void	PostStepProcess ()
	Actions after step proposal [end stopwatch, fill tree]. More...
bool	IsStepAccepted (const double acc_prob)
	Is step accepted? More...
void	AcceptStep ()
	Accept a step. More...
void	AdaptiveStep ()
	Adaptive MCMC step. More...
void	PrintProgress ()
	Print the progress. More...
Protected Member Functions inherited from FitterBase
void	ProcessMCMC ()
	Process MCMC output. More...
void	PrepareOutput ()
	Prepare the output file. More...
void	SaveOutput ()
	Save output and close files. More...
void	SanitiseInputs ()
	Remove obsolete memory and make other checks before fit starts. More...
void	SaveSettings ()
	Save the settings that the MCMC was run with. More...
bool	GetScaneRange (std::map< std::string, std::vector< double >> &scanRanges)
	YSP: Set up a mapping to store parameters with user-specified ranges, suggested by D. Barrow. More...
bool	CheckSkipParameter (const std::vector< std::string > &SkipVector, const std::string &ParamName) const
	KS: Check whether we want to skip parameter using skip vector. More...
void	CustomRange (const std::string &ParName, const double sigma, double &ParamShiftValue)
	For comparison with P-Theta we usually have to apply different parameter values then usual 1, 3 sigma. More...

Additional Inherited Members
Protected Attributes inherited from MCMCBase
bool	out_of_bounds
	Do we reject based on hitting boundaries in systs. More...
bool	accept
	Accept. More...
unsigned int	chainLength
	number of steps in chain More...
bool	anneal
	simulated annealing More...
double	AnnealTemp
	simulated annealing temperature More...
Protected Attributes inherited from FitterBase
manager *	fitMan
	The manager. More...
unsigned int	step
	current state More...
double	logLCurr
	current likelihood More...
double	logLProp
	proposed likelihood More...
double	accProb
	current acceptance prob More...
int	accCount
	counts accepted steps More...
unsigned int	stepStart
	step start, by default 0 if we start from previous chain then it will be different More...
std::vector< double >	sample_llh
	store the llh breakdowns More...
std::vector< double >	syst_llh
	systematic llh breakdowns More...
std::vector< SampleHandlerBase * >	samples
	Sample holder. More...
unsigned int	TotalNSamples
	Total number of samples used. More...
std::vector< ParameterHandlerBase * >	systematics
	Systematic holder. More...
std::unique_ptr< TStopwatch >	clock
	tells global time how long fit took More...
std::unique_ptr< TStopwatch >	stepClock
	tells how long single step/fit iteration took More...
double	stepTime
	Time of single step. More...
std::unique_ptr< TRandom3 >	random
	Random number. More...
TFile *	outputFile
	Output. More...
TDirectory *	CovFolder
	Output cov folder. More...
TDirectory *	SampleFolder
	Output sample folder. More...
TTree *	outTree
	Output tree with posteriors. More...
int	auto_save
	auto save every N steps More...
bool	fTestLikelihood
	Necessary for some fitting algorithms like PSO. More...
bool	FileSaved
	Checks if file saved not repeat some operations. More...
bool	SettingsSaved
	Checks if setting saved not repeat some operations. More...
bool	OutputPrepared
	Checks if output prepared not repeat some operations. More...
std::string	AlgorithmName
	Name of fitting algorithm that is being used. More...

Detailed Description

MCMC algorithm implementing the Metropolis–Rosenbluth–Rosenbluth–Teller–Teller (MR \(^2\)T \(^2\)) method.

Note

MR \(^2\)T \(^2\) is also known as Metropolis-Hastings [16]

The acceptance probability for a proposed step is given by

\[ \alpha = \min \Biggl( 1, \exp\bigl( \log \mathcal{L}_\text{prop} - \log \mathcal{L}_\text{curr} \bigr) \Biggr), \]

where \(\log \mathcal{L}_\text{prop}\) is the log-likelihood of the proposed state and \(\log \mathcal{L}_\text{curr}\) is the log-likelihood of the current state.

If annealing is enabled, the acceptance probability is modified as

\[ \alpha_\text{anneal} = \min \Biggl( 1, \exp\Bigl( -\frac{\log \mathcal{L}_\text{prop} - \log \mathcal{L}_\text{curr}} {\exp(-\text{step}/T_\text{anneal})} \Bigr) \Biggr), \]

where \(T_\text{anneal}\) is the current annealing temperature and \(\text{step}\) is the iteration index.

Author

Asher Kaboth

Definition at line 25 of file MR2T2.h.

Constructor & Destructor Documentation

MR2T2()

MR2T2::MR2T2

(

manager *const

manager

)

Constructor.

Parameters

fitMan

A pointer to a manager object, which will handle all settings.

Definition at line 5 of file MR2T2.cpp.

                         : MCMCBase(man) {
// ***************
    AlgorithmName = "MR2T2";
}

~MR2T2()

virtual MR2T2::~MR2T2 ( )

virtualdefault

Destructor.

Member Function Documentation

AcceptanceProbability()

double MR2T2::AcceptanceProbability ( )

overrideprotectedvirtual

Step acceptance probability.

Implements MCMCBase.

Definition at line 103 of file MR2T2.cpp.

                                    {
// **********************
    // Set the acceptance probability to zero
    double acc_prob = 0.0;
 
    // Calculate acceptance probability
    if (anneal)
        acc_prob = std::min(1., std::exp(-(logLProp - logLCurr) / (std::exp(-step / AnnealTemp))));
    else
        acc_prob = std::min(1., std::exp(logLCurr - logLProp));
 
    return acc_prob;
}

DoStep()

void MR2T2::DoStep ( )

overrideprotectedvirtual

The MCMC step proposal and acceptance.

Implements MCMCBase.

Definition at line 11 of file MR2T2.cpp.

                   {
// *******************
    ProposeStep();
    // Does the MCMC accept this step?
    accProb = AcceptanceProbability();
 
    if (!out_of_bounds && IsStepAccepted(accProb))
    {
        AcceptStep();
    }
}

ProposeStep()

void MR2T2::ProposeStep ( )

overrideprotectedvirtual

Propose a step.

Implements MCMCBase.

Definition at line 25 of file MR2T2.cpp.

                        {
// *******************
    // Initial likelihood
    out_of_bounds = false;
    
    double llh = 0.0;
 
    // Loop over the systematics and propose the initial step
    for (size_t s = 0; s < systematics.size(); ++s)
    {
        // Could throw the initial value here to do MCMC stability studies
        // Propose the steps for the systematics
        systematics[s]->ProposeStep();
 
        // Get the likelihood from the systematics
        syst_llh[s] = systematics[s]->GetLikelihood();
        llh += syst_llh[s];
 
#ifdef DEBUG
        if (debug)
            debugFile << "LLH after " << systematics[s]->GetName() << " " << llh << std::endl;
#endif
    }
 
    // Check if we've hit a boundary in the systematics
    // In this case we can save time by not having to reconfigure the simulation
    if (llh >= M3::_LARGE_LOGL_)
    {
        out_of_bounds = true;
#ifdef DEBUG
        if (debug)
            debugFile << "Rejecting based on boundary" << std::endl;
#endif
    }
 
    // Only reweight when we have a good parameter configuration
    // This speeds things up considerably because for every bad parameter configuration we don't have to reweight the MC
    if (!out_of_bounds)
    {
        // Could multi-thread this
        // But since sample reweight is multi-threaded it's probably better to do that
        for (size_t i = 0; i < samples.size(); ++i)
        {
            samples[i]->Reweight();
        }
 
        // DB for atmospheric event by event sample migration, need to fully reweight all samples to allow event passing prior to likelihood evaluation
        for (size_t i = 0; i < samples.size(); ++i)
        {
            // Get the sample likelihoods and add them
            sample_llh[i] = samples[i]->GetLikelihood();
            llh += sample_llh[i];
#ifdef DEBUG
            if (debug)
                debugFile << "LLH after sample " << i << " " << llh << std::endl;
#endif
        }
 
        // For when we don't have to reweight, set sample to madness
    }
    else
    {
        for (size_t i = 0; i < samples.size(); ++i)
        {
            // Set the sample_llh[i] to be madly high also to signify a step out of bounds
            sample_llh[i] = M3::_LARGE_LOGL_;
#ifdef DEBUG
            if (debug)
                debugFile << "LLH after REJECT sample " << i << " " << llh << std::endl;
#endif
        }
    }
    // Save the proposed likelihood (class member)
    logLProp = llh;
}

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

• Fitters/MR2T2.h
• Fitters/MR2T2.cpp