#include <TMCMC.h>

Inheritance diagram for URANIE::Calibration::TMCMC:

Collaboration diagram for URANIE::Calibration::TMCMC:

Public Member Functions
std::unordered_map< string, vector< int > >	diagESS ()
	Compute Effective Sample Size. More...

Constructors
	TMCMC (URANIE::DataServer::TDataServer tds, URANIE::Relauncher::TRun run, int ns=100, Option_t *option="")

	TMCMC (URANIE::DataServer::TDataServer tds, void(fcn)(Double_t , Double_t ), const char varexpinput, const char varexpoutput, int ns=100, Option_t *option="")
	Default MCMC constructor with the function argument: it contains the assessor to be used. More...

	TMCMC (URANIE::DataServer::TDataServer tds, const char fcn, const char varexpinput, const char varexpoutput, int ns=100, Option_t *option="")
	Default MCMC constructor with the function argument: it contains the assessor to be used. More...

	TMCMC (URANIE::DataServer::TDataServer tds, URANIE::Launcher::TCode fcode, int ns=100, Option_t *option="")
	Default MCMC constructor with the code argument: it contains the assessor to be used. More...

void	checktdsParContent ()
	Initialise the TMCMC object and the strcuture of file to save the result. More...

Destructor
virtual	~TMCMC ()
	Default destructor. More...

Setters
void	setAlgo (const char *algoMCMC)
	Define the seed of the random generator for one or several chains. More...

void	setSeed (int ichain, int seed)
	Define the seed of the random generator for one or several chains. More...

void	setBurnin (int burn)
	Define the burn-in size. More...

void	setLag (int lag)
	Define the lag. More...

void	setNbDump (int nbDump)
	Define nbDump. More...

void	setAcceptationRatioRange (double lower, double higher)
	Define the range of the acceptation ratio (the proposal will be modified so that the acceptation ratio is within this range) More...

void	setLikelihood (const char likelihoodName, URANIE::DataServer::TDataServer tdsRef, const char input, const char output, const char *weight="")
	Set the likelihood function and some needed informations. More...

void	setLikelihood (URANIE::Calibration::TDistanceLikelihoodFunction likelihoodFunc, URANIE::DataServer::TDataServer tdsRef, const char input, const char output, const char *weight="")
	Set the likelihood function and some needed informations. More...

void	setMultistart (int nb_multistart)
	Initialise several chains. More...

void	setStartingPoints (int ichain, vector< double > values)
	Initialise the parameters values. More...

void	setProposalStd (int ichain, vector< double > standDev)
	Initialise the proposal std from vector. More...

Compute the parameters
void	computeParameters (Option_t *option="")
	Compute ns iterations (with ns fixed in the constructor TMCMC) More...

void	continueCalculation (int new_Ns)
	Continue the MCMC computation for new_Ns iterations. More...

MCMC methods
void	MH_multiD (TRandom3 *rand, vector< double > dBase, vector< int > accept, vector< int > reject, int Nstart, int Nend)
	Run Metropolis-Hastings algorithm with candidates drawn in multiple directions (default method) More...

void	MH_1D (TRandom3 *rand, vector< double > dBase, vector< int > accept, vector< int > reject, int Nstart, int Nend)
	Run Metropolis-Hastings algorithm with candidates drawn one direction at a time. More...

Save and read
void	export_chain_MCMC (const char *fileName)
	Save the current state of the Markov Chain in a file. More...

void	read_chain_MCMC (const char *fileName)
	Read a saved Markov Chain. More...

Visualisation
void	drawTrace (TString sTitre, const char variable="", Option_t *option="")
	Draw the evolution of the parameters as a function of the iterator. More...

void	draw2DTrace (TString sTitre, const char variable, Option_t option="")
	Draw the evolution of 2 parameters on a 2D plot. More...

void	drawAcceptationRatio (TString sTitre, const char variable="", Option_t *option="")
	Draw the evolution of the acceptation ratio as a function of the iterator. More...

void	drawParameters (TString sTitre, const char variable="", Option_t *option="")
	Draw samples of the posterior distribution (if converged) More...

Diagnostic
double	diagAutoCorrelation (int lag, int nPoints, Double_t *Data)
	Compute the autocorrelation. More...

std::unordered_map< string, double >	diagGelmanRubin ()
	Compute Gelman-Rubin statistic (multistart only) More...

Printing Log
virtual void	printLog (Option_t *option="")
	Prints the log. More...

Default cut and lag
string	getDefaultCut ()
	Print the actual cut and lag values. More...

void	clearDefaultCut ()
	Reinitialisation of the cut and lag values. More...

Public Member Functions inherited from URANIE::Calibration::TCalibration
	TCalibration (URANIE::DataServer::TDataServer tds, URANIE::Relauncher::TRun run, int ns=1, Option_t *option="")
	Default constructor with the runner argument: it contains the assessor to be used. More...

	TCalibration (URANIE::DataServer::TDataServer tds, void(fcn)(Double_t , Double_t ), const char varexpinput, const char varexpoutput, int ns=1, Option_t *option="")
	Default Calibration constructor with the function argument: it contains the assessor to be used. More...

	TCalibration (URANIE::DataServer::TDataServer tds, const char fcn, const char varexpinput, const char varexpoutput, int ns=1, Option_t *option="")
	Default Calibration constructor with the function argument: it contains the assessor to be used. More...

	TCalibration (URANIE::DataServer::TDataServer tds, URANIE::Launcher::TCode fcode, int ns=1, const char *option="")
	Default Calibration constructor with the code argument: it contains the assessor to be used. More...

virtual	~TCalibration ()
	Default destructor. More...

virtual void	setDistanceAndLikelihood (const char Name, URANIE::DataServer::TDataServer tdsRef, const char input, const char reference, const char *weight="")
	Set the distance or likelihood function and some needed informations. More...

virtual void	setDistanceAndLikelihood (URANIE::Calibration::TDistanceLikelihoodFunction Func, URANIE::DataServer::TDataServer tdsRef, const char input, const char reference, const char *weight="")
	Set the distance of likelihood function and some needed informations. More...

void	estimateParameters (Option_t *option="")

void	estimateCustomResiduals (string resName, int n_theta, double *theta)

void	checkReference (URANIE::DataServer::TDataServer tdsRef, const char input, const char output, const char weight)
	Check the consistency of the formation provided. More...

void	drawResiduals (TString sTitre, const char variable="", const char select="1>0", Option_t option="")

void	setLog ()

void	unsetLog ()

void	changeLog ()

Bool_t	getLog ()

Int_t	getID ()

void	setSeed (UInt_t nval)
	Set the seed of the random generator if one is used. More...

UInt_t	getSeed ()
	Get the seed of the random generator if one is used. More...

const char *	getMethodName ()
	Get the method name. More...

void	setObservationCovarianceMatrix (TMatrixD &mat)
	Set the observatiton covariance matrix. More...

URANIE::Calibration::TDistanceLikelihoodFunction *	getDistanceLikelihoodFunction ()
	Return the distance or likelihood function. More...

Int_t	getNPar ()
	Get the number of parameters to be calibrated. More...

URANIE::DataServer::TDataServer *	getEvaluationTDS ()
	Get the tds in which evaluation will be performed. More...

Public Attributes
vector< double >	_values
	Vector of values to be tested. More...

vector< double >	_vstd
	Vector of standard deviation. More...

vector< double >	_dBaseSaved
	Database containing the values, acceptation rate, ... More...

vector< int >	_acceptSaved
	Vector containing the number of accepted candidates for each parameter. More...

vector< int >	_rejectSaved
	Vector containing the number of rejected candidates for each parameter. More...

TRandom3	_randSaved
	Random generator saved. More...

std::string	_simuName
	name of the simulation (will be the name of the results repository) More...

int	_burnin
	The number of iterations considered as warm-up or burn-in. More...

int	_lag
	The lag value. More...

int	_nbDump
	Frequency to which the algo dump a line. More...

int	_multiStart
	The number of chains initialised. More...

double	_lowAccRange
	lower acceptation ratio bound More...

double	_higAccRange
	higher acceptation ratio bound More...

std::string	_algoMCMC
	MCMC algo to use between ("MH_1D" and "MH_multiD") More...

bool	_bcleaningAtt
	Do not store the underlying att. More...

Public Attributes inherited from URANIE::Calibration::TCalibration
URANIE::DataServer::TDataServer *	_tdsPar
	TDS containing parameters properties (parameters that should be calibrated) More...

URANIE::DataServer::TDataServer *	_tdsObs
	TDS containing observations used for calibration. More...

URANIE::DataServer::TDataServer *	_tdsEval
	TDS containing a priori / a posteriori evaluations. More...

ELauncher	_nLauncher
	The type of launcher. More...

TString	_sFunctionName
	The Name of the evaluatuor. More...

TString	_sEI
	The Name of input. More...

TString	_sEO
	The Name of output. More...

URANIE::Launcher::TCode *	_code
	The tcode. More...

URANIE::Relauncher::TRun *	_run
	Pointer to the runner to be used. More...

void(*	_pFunction )(double , double )
	Function pointer. More...

vector< URANIE::DataServer::TStochasticAttribute * >	_vatt
	internal vector of stochastic attribute for some methods More...

Protected Member Functions
private methods
void	logPriorPdf (double &ret)
	Compute the logarithm of the prior. More...

void	parseOption (Option_t *option="")
	Possible options: More...

Protected Member Functions inherited from URANIE::Calibration::TCalibration
void	checkCanvasCreation (bool newcan)
	Create a canvas if needed. More...

void	initInputs ()
	Initialise some common inputs. More...

void	initResults (vector< string > *ParsedLines)
	Initialise some common inputs. More...

void	computeAPosterioriForDistribution (URANIE::DataServer::TDataServer *tds_chain_i)
	Compute the a posteriori residual for many-solutions method. More...

void	setMethodName (const char *str)
	Set the Method name. More...

Additional Inherited Members
Public Types inherited from URANIE::Calibration::TCalibration
enum	ELauncher { kCode, kFunction, kRun, kUnknown }

Protected Attributes inherited from URANIE::Calibration::TCalibration
URANIE::Calibration::TDistanceLikelihoodFunction *	_dFunc
	Pointer to chosen distance or likelihood function. More...

URANIE::DataServer::TDSNtupleD *	_evTuple
	Pointer to the eval ntuple. More...

TList *	_listOfParameters
	List of the parameters to be calibrated. More...

TCanvas *	_canvas
	Canvas object to deal with. More...

TObjArray *	_drawingGarbageCollector
	Garbage collector for prints. More...

int	_nSam
	The number of sample in a posteriori distributions. More...

int	_nObs
	The number of observations in the reference database. More...

int	_nIterMax
	The maximum number of iteration allowed (meaning total number of code estimation is _nIterMax * _nObs) More...

int	_nPar
	Dimension of the parameters. More...

int	_nVar
	Dimension of the output and references to be compared with. More...

int	_nSeed = 0
	The seed of the random generator (initialized to 0 = random seed) More...

TString	_sMethodName
	The method name. More...

TString	_referenceName
	The reference name. More...

TString	_outputName
	The output name. More...

vector< string >	_vrefName
	The reference names. More...

vector< string >	_voutName
	The output names. More...

TString	_weightName
	The weight name. More...

TMatrixD	_mObsCovMat
	Observation Covariance matrix. More...

bool	_buseMatrix
	Use matrix instead of vectors in the TDistanceLikelihoodFunction. More...

bool	_bsaveAll
	Whether all evaluations should be saved, not only a priori and a posteriori. More...

bool	_bdontKeepAgreement
	Remove the agreement attribute from the tdsPar object. More...

bool	_buseMode
	Use Mode instead of Mean. More...

Bool_t	_blog
	Boolean for edit the log. More...

Constructor & Destructor Documentation

◆ TMCMC() [1/4]

URANIE::Calibration::TMCMC::TMCMC	(	URANIE::DataServer::TDataServer *	tds,
		URANIE::Relauncher::TRun *	run,
		int	ns = `100`,
		Option_t *	option = `""`
	)

Usual MCMC constructor where ns is the number of iterations.

Parameters

tds	the dataserver that contains no data but only one TStochasticAttribute per parameter to be calibrated
run	the runner that would be used to produce evaluations
ns	number of iterations [100 by default]

Referenced by ClassImp().

◆ TMCMC() [2/4]

URANIE::Calibration::TMCMC::TMCMC	(	URANIE::DataServer::TDataServer *	tds,
		void()(Double_t , Double_t *)	fcn,
		const char *	varexpinput,
		const char *	varexpoutput,
		int	ns = `100`,
		Option_t *	option = `""`
	)

Default MCMC constructor with the function argument: it contains the assessor to be used.

Parameters

tds	the dataserver that contains no data but only one TStochasticAttribute per parameter to be calibrated
fcn	the pointer to a function
ns	number of iterations [100 by default]
varexpinput	the input variable for the function in the correct order (both input and parameters)
varexpoutput	the output of the function in the correct order

◆ TMCMC() [3/4]

URANIE::Calibration::TMCMC::TMCMC	(	URANIE::DataServer::TDataServer *	tds,
		const char *	fcn,
		const char *	varexpinput,
		const char *	varexpoutput,
		int	ns = `100`,
		Option_t *	option = `""`
	)

Default MCMC constructor with the function argument: it contains the assessor to be used.

Parameters

tds	the dataserver that contains no data but only one TStochasticAttribute per parameter to be calibrated
fcn	the name of the function
ns	number of iterations [100 by default]
varexpinput	the input variable for the function in the correct order (both input and parameters)
varexpoutput	the output of the function in the correct order

◆ TMCMC() [4/4]

URANIE::Calibration::TMCMC::TMCMC	(	URANIE::DataServer::TDataServer *	tds,
		URANIE::Launcher::TCode *	fcode,
		int	ns = `100`,
		Option_t *	option = `""`
	)

Default MCMC constructor with the code argument: it contains the assessor to be used.

Parameters

tds	the dataserver that contains no data but only one TStochasticAttribute per parameter to be calibrated
code	the code object that will be runned
ns	number of iterations [100 by default]

◆ ~TMCMC()

virtual URANIE::Calibration::TMCMC::~TMCMC ( )

virtual

Default destructor.

Referenced by ClassImp().

Member Function Documentation

◆ checktdsParContent()

void URANIE::Calibration::TMCMC::checktdsParContent ( )

virtual

Initialise the TMCMC object and the strcuture of file to save the result.

Implements URANIE::Calibration::TCalibration.

Referenced by ClassImp().

◆ clearDefaultCut()

void URANIE::Calibration::TMCMC::clearDefaultCut ( )

inline

Reinitialisation of the cut and lag values.

References setBurnin(), setLag(), and setNbDump().

◆ computeParameters()

void URANIE::Calibration::TMCMC::computeParameters ( Option_t * option = "" )

virtual

Compute ns iterations (with ns fixed in the constructor TMCMC)

Parameters

option

possible options are

"clean": remove internal branche from the tdsPar object at the end

Implements URANIE::Calibration::TCalibration.

Referenced by ClassImp().

◆ continueCalculation()

void URANIE::Calibration::TMCMC::continueCalculation ( int new_Ns )

Continue the MCMC computation for new_Ns iterations.

Parameters

new_Ns number of additional iterations

Referenced by ClassImp().

◆ diagAutoCorrelation()

double URANIE::Calibration::TMCMC::diagAutoCorrelation	(	int	lag,
		int	nPoints,
		Double_t *	Data
	)

Compute the autocorrelation.

Parameters

lag	lag interval for which the autocorrelation will be computed
Data	vector for which the autocorrelation will be computed

Referenced by ClassImp().

◆ diagESS()

std::unordered_map<string, vector<int> > URANIE::Calibration::TMCMC::diagESS ( )

Compute Effective Sample Size.

Referenced by ClassImp().

◆ diagGelmanRubin()

std::unordered_map<string, double> URANIE::Calibration::TMCMC::diagGelmanRubin ( )

Compute Gelman-Rubin statistic (multistart only)

Referenced by ClassImp().

◆ draw2DTrace()

void URANIE::Calibration::TMCMC::draw2DTrace	(	TString	sTitre,
		const char *	variable,
		Option_t *	option = `""`
	)

Draw the evolution of 2 parameters on a 2D plot.

Parameters

sTitre	title of the plot if specified
variable	name of the 2 variables that should be plotted (format "x1:x2")
option	possible option for this plot "nonewcanvas": do not create a new canvas, but use the one active

Referenced by ClassImp().

◆ drawAcceptationRatio()

void URANIE::Calibration::TMCMC::drawAcceptationRatio	(	TString	sTitre,
		const char *	variable = `"*"`,
		Option_t *	option = `""`
	)

Draw the evolution of the acceptation ratio as a function of the iterator.

Parameters

sTitre	title of the plot if specified
variable	list of variables that should be plotted
option	possible option for this plot "nonewcanvas": do not create a new canvas, but use the one active

Referenced by ClassImp().

◆ drawParameters()

void URANIE::Calibration::TMCMC::drawParameters	(	TString	sTitre,
		const char *	variable = `"*"`,
		Option_t *	option = `""`
	)

virtual

Draw samples of the posterior distribution (if converged)

Parameters

sTitre	title of the plots if specified
variable	list of variables that should be plotted
option	possible option for this plot "nonewcanvas": do not create a new canvas, but use the one active "vertical": if there are several parameters to be shown put them on top of another instead of side by side

Reimplemented from URANIE::Calibration::TCalibration.

Referenced by ClassImp().

◆ drawTrace()

void URANIE::Calibration::TMCMC::drawTrace	(	TString	sTitre,
		const char *	variable = `"*"`,
		Option_t *	option = `""`
	)

Draw the evolution of the parameters as a function of the iterator.

Parameters

sTitre	title of the plot if specified
variable	list of variables that should be plotted
option	possible option for this plot "nonewcanvas": do not create a new canvas, but use the one active

Referenced by ClassImp().

◆ export_chain_MCMC()

void URANIE::Calibration::TMCMC::export_chain_MCMC ( const char * fileName )

Save the current state of the Markov Chain in a file.

Parameters

fileName name of the save file

Referenced by ClassImp().

◆ getDefaultCut()

string URANIE::Calibration::TMCMC::getDefaultCut ( )

inline

Print the actual cut and lag values.

References _burnin, _lag, and URANIE::Calibration::TCalibration::_tdsPar.

◆ logPriorPdf()

void URANIE::Calibration::TMCMC::logPriorPdf ( double & ret )

protected

Compute the logarithm of the prior.

Referenced by ClassImp().

◆ MH_1D()

void URANIE::Calibration::TMCMC::MH_1D	(	TRandom3 *	rand,
		vector< double >	dBase,
		vector< int >	accept,
		vector< int >	reject,
		int	Nstart,
		int	Nend
	)

Run Metropolis-Hastings algorithm with candidates drawn one direction at a time.

Parameters

rand	random generator
dBase	calculation vector containing the latest value of the chain, the acceptance rate for each parameter, and additional useful values (log-prior, log-likelihood, log-ratio)
accept	vector containing the number of accepted samples for each parameter
reject	vector containing the number of rejected samples for each parameter
Nstart	the number at which the iterations start
Nend	the number at which the iterations stop

Referenced by ClassImp().

◆ MH_multiD()

void URANIE::Calibration::TMCMC::MH_multiD	(	TRandom3 *	rand,
		vector< double >	dBase,
		vector< int >	accept,
		vector< int >	reject,
		int	Nstart,
		int	Nend
	)

Run Metropolis-Hastings algorithm with candidates drawn in multiple directions (default method)

Parameters

rand	random generator
dBase	calculation vector containing the latest value of the chain, the acceptance rate for each parameter, and additional useful values (log-prior, log-likelihood, log-ratio)
accept	vector containing the number of accepted samples for each parameter
reject	vector containing the number of rejected smaples for each parameter
Nstart	the number at which the iterations start
Nend	the number at which the iterations stop

Referenced by ClassImp().

◆ parseOption()

void URANIE::Calibration::TMCMC::parseOption ( Option_t * option = "" )

protectedvirtual

Possible options:

"savealleval": keep all estimation in the _tdsEval (Extremely dangerous as it will keep _nIter branches with _nObs estimations. This option might slow down the process.
"usematrix": option use to specify that computation is done with matrices instead of vector<vector<double> >. Shoud be used only if one is using an home-made TDistanceLikelihoodFunction

Reimplemented from URANIE::Calibration::TCalibration.

Referenced by ClassImp().

◆ printLog()

virtual void URANIE::Calibration::TMCMC::printLog ( Option_t * option = "" )

virtual

Prints the log.

Reimplemented from URANIE::Calibration::TCalibration.

Referenced by ClassImp().

◆ read_chain_MCMC()

void URANIE::Calibration::TMCMC::read_chain_MCMC ( const char * fileName )

Read a saved Markov Chain.

Parameters

fileName name of the save file

Referenced by ClassImp().

◆ setAcceptationRatioRange()

void URANIE::Calibration::TMCMC::setAcceptationRatioRange	(	double	lower,
		double	higher
	)

Define the range of the acceptation ratio (the proposal will be modified so that the acceptation ratio is within this range)

Parameters

lower	lower bound (default = 0)
higher	higher bound (default = 1)

Referenced by ClassImp().

◆ setAlgo()

void URANIE::Calibration::TMCMC::setAlgo ( const char * algoMCMC )

Define the seed of the random generator for one or several chains.

Parameters

algoMCMC

name of the chosen MCMC method among the already implemented ones:

"MH_1D": for component-wise Metropolis-Hastings algorithm with candidates drawn in one direction at a time
"MH_multiD": for classic Metropolis-Hastings algorithm with candidates drawn in multiple directions (default method)

Referenced by ClassImp().

◆ setBurnin()

void URANIE::Calibration::TMCMC::setBurnin ( int burn )

Define the burn-in size.

Parameters

burn	number of samples that will be removed (default = 0)

Referenced by ClassImp(), and clearDefaultCut().

◆ setLag()

void URANIE::Calibration::TMCMC::setLag ( int lag )

Define the lag.

Parameters

lag	interval between two selected sampled points to reduce autocorrelation (default = 1)

Referenced by ClassImp(), and clearDefaultCut().

◆ setLikelihood() [1/2]

void URANIE::Calibration::TMCMC::setLikelihood	(	const char *	likelihoodName,
		URANIE::DataServer::TDataServer *	tdsRef,
		const char *	input,
		const char *	output,
		const char *	weight = `""`
	)

Set the likelihood function and some needed informations.

Parameters

likelihoodName	name of the likelihood function chosen among the already implemented likelihoods: "gauss": for gaussian likelihood
tdsRef	: the dataserver that contains all needed information detailled below
input	the input attributes used by the assessors in run
reference	the reference attributes that will be used to compared the newly done estimations for every iterations
weight	a weight to reweight every event, one-by-one (an experimental uncertainty for instance)

Referenced by ClassImp().

◆ setLikelihood() [2/2]

void URANIE::Calibration::TMCMC::setLikelihood	(	URANIE::Calibration::TDistanceLikelihoodFunction *	likelihoodFunc,
		URANIE::DataServer::TDataServer *	tdsRef,
		const char *	input,
		const char *	output,
		const char *	weight = `""`
	)

Set the likelihood function and some needed informations.

Parameters

likelihoodFunc	a pointer to a TDistanceLikelihoodFunction object (not usual, recommended only when dealing with a home-made distance function compiled on the spot)
tdsRef	the dataserver that contains all needed information detailled below
input	the input attributes used by the assessors in run
reference	the reference attributes that will be used to compared the newly done estimations for every iterations
weight	a weight to reweight every event, one-by-one (an experimental uncertainty for instance)

◆ setMultistart()

void URANIE::Calibration::TMCMC::setMultistart ( int nb_multistart )

Initialise several chains.

Parameters

nb_multistart change the number of chains initialised (default = 1)

Referenced by ClassImp().

◆ setNbDump()

void URANIE::Calibration::TMCMC::setNbDump ( int nbDump )

Define nbDump.

Parameters

nbDump number of iterations between two information displays (default = 1000)

Referenced by ClassImp(), and clearDefaultCut().

◆ setProposalStd()

void URANIE::Calibration::TMCMC::setProposalStd	(	int	ichain,
		vector< double >	standDev
	)

Initialise the proposal std from vector.

Parameters

ichain	chain number for which we set the standard deviation of the proposal standard deviation
standDev	vector containing the values of the proposal standard deviation (size must be equal to the number of parameters)

Referenced by ClassImp().

◆ setSeed()

void URANIE::Calibration::TMCMC::setSeed	(	int	ichain,
		int	seed
	)

Define the seed of the random generator for one or several chains.

Parameters

ichain	chain number for which we set the starting point (if -1 all the chains initialised to the same points -> not recommended)
seed	seed value

Referenced by ClassImp().

◆ setStartingPoints()

void URANIE::Calibration::TMCMC::setStartingPoints	(	int	ichain,
		vector< double >	values
	)

Initialise the parameters values.

Parameters

ichain	chain number for which we set the starting point (if -1 all the chains initialised at the same starting point -> not recommended)
values	vector containing the values of the starting points (size must be equal to the number of parameters)

Referenced by ClassImp().

Member Data Documentation

◆ _acceptSaved

vector<int> URANIE::Calibration::TMCMC::_acceptSaved

Vector containing the number of accepted candidates for each parameter.

Referenced by ClassImp().

◆ _algoMCMC

std::string URANIE::Calibration::TMCMC::_algoMCMC

MCMC algo to use between ("MH_1D" and "MH_multiD")

Referenced by ClassImp().

◆ _bcleaningAtt

bool URANIE::Calibration::TMCMC::_bcleaningAtt

Do not store the underlying att.

Referenced by ClassImp().

◆ _burnin

int URANIE::Calibration::TMCMC::_burnin

The number of iterations considered as warm-up or burn-in.

Referenced by ClassImp(), and getDefaultCut().

◆ _dBaseSaved

vector<double> URANIE::Calibration::TMCMC::_dBaseSaved

Database containing the values, acceptation rate, ...

Referenced by ClassImp().

◆ _higAccRange

double URANIE::Calibration::TMCMC::_higAccRange

higher acceptation ratio bound

Referenced by ClassImp().

◆ _lag

int URANIE::Calibration::TMCMC::_lag

The lag value.

Referenced by ClassImp(), and getDefaultCut().

◆ _lowAccRange

double URANIE::Calibration::TMCMC::_lowAccRange

lower acceptation ratio bound

Referenced by ClassImp().

◆ _multiStart

int URANIE::Calibration::TMCMC::_multiStart

The number of chains initialised.

Referenced by ClassImp().

◆ _nbDump

int URANIE::Calibration::TMCMC::_nbDump

Frequency to which the algo dump a line.

Referenced by ClassImp().

◆ _randSaved

TRandom3 URANIE::Calibration::TMCMC::_randSaved

Random generator saved.

Referenced by ClassImp().

◆ _rejectSaved

vector<int> URANIE::Calibration::TMCMC::_rejectSaved

Vector containing the number of rejected candidates for each parameter.

Referenced by ClassImp().

◆ _simuName

std::string URANIE::Calibration::TMCMC::_simuName

name of the simulation (will be the name of the results repository)

Referenced by ClassImp().

◆ _values

vector<double> URANIE::Calibration::TMCMC::_values

Vector of values to be tested.

Referenced by ClassImp().

◆ _vstd

vector<double> URANIE::Calibration::TMCMC::_vstd

Vector of standard deviation.

Referenced by ClassImp().

Documentation / Developer's manual

Available modules

Public Member Functions

Public Attributes

Protected Member Functions

Additional Inherited Members

Constructor & Destructor Documentation

◆ TMCMC() [1/4]

◆ TMCMC() [2/4]

◆ TMCMC() [3/4]

◆ TMCMC() [4/4]

◆ ~TMCMC()

Member Function Documentation

◆ checktdsParContent()

◆ clearDefaultCut()

◆ computeParameters()

◆ continueCalculation()

◆ diagAutoCorrelation()

◆ diagESS()

◆ diagGelmanRubin()

◆ draw2DTrace()

◆ drawAcceptationRatio()

◆ drawParameters()

◆ drawTrace()

◆ export_chain_MCMC()

◆ getDefaultCut()

◆ logPriorPdf()

◆ MH_1D()

◆ MH_multiD()

◆ parseOption()

◆ printLog()

◆ read_chain_MCMC()

◆ setAcceptationRatioRange()

◆ setAlgo()

◆ setBurnin()

◆ setLag()

◆ setLikelihood() [1/2]

◆ setLikelihood() [2/2]

◆ setMultistart()

◆ setNbDump()

◆ setProposalStd()

◆ setSeed()

◆ setStartingPoints()

Member Data Documentation

◆ _acceptSaved

◆ _algoMCMC

◆ _bcleaningAtt

◆ _burnin

◆ _dBaseSaved

◆ _higAccRange

◆ _lag

◆ _lowAccRange

◆ _multiStart

◆ _nbDump

◆ _randSaved

◆ _rejectSaved

◆ _simuName

◆ _values

◆ _vstd