Helper class for configuring and evaluating multicanonical umbrella weights. More...

#include <Fitters/MulticanonicalMCMCHandler.h>

Collaboration diagram for MulticanonicalMCMCHandler:

Public Member Functions
	MulticanonicalMCMCHandler ()
	Constructor. More...

virtual	~MulticanonicalMCMCHandler ()
	Destructor. More...

void	FindOscCovParams (const std::vector< ParameterHandlerBase * > &systematics)
	Locate the systematic object which contains the parameters used by the handler. Stores the parameter indices. More...

void	AdjustUmbrellaStepScale (const std::vector< ParameterHandlerBase * > &systematics)
	Adjust the parameter-of-interest's step scale according to the width of the umbrella bias function. More...

void	InitializeMulticanonicalHandlerConfig (Manager fitMan, std::vector< ParameterHandlerBase > &systematics)
	Read multicanonical configuration from the yaml via manager and initialise handler state. More...

void	InitializeMulticanonicalParams (std::vector< ParameterHandlerBase * > &systematics)
	Initialise the starting values used by the multicanonical parameter handling. More...

double	GetMulticanonicalWeight (double deltacp, double delm23_value)
	Compute the multicanonical penalty for the configured bias mode. More...

double	GetMulticanonicalWeightSpline (double deltacp, double delm23_value)
	Compute the multicanonical penalty using a spline. More...

double	GetMulticanonicalWeightGaussian (double deltacp)
	Compute a Gaussian multicanonical penalty. More...

double	GetMulticanonicalWeightTripleGaussian (double deltacp)
	Compute a triple-Gaussian multicanonical penalty. More...

double	GetMulticanonicalWeightVonMises (double deltacp)
	Compute a von Mises multicanonical penalty. More...

double	GetMulticanonicalWeightGenGaussian (double deltacp)
	Compute a generalised-Gaussian multicanonical penalty. More...

double	circularDistance (double x, double mean)
	Compute the circular distance between two angles. More...

double	generalisedGaussian2 (double x, double mean, double width)
	Wraps the generalised gaussian function for a given x, mean, and width. Required to handle the wrappipng of the parameter space at 2pi. More...

Public Attributes
int	oscCovVar
	Index of the oscillation-covariance systematic in the current fit. More...

int	multicanonicalVar
	Parameter index used for the multicanonical delta_cp weight. More...

int	multicanonicalVar_dm23
	Parameter index used for the multicanonical delm2_23 weight. More...

M3::BiasFunction	umbrellaBiasFunction
	Selected bias function for multicanonical weights. More...

std::string	umbrellaBiasFunctionName
	Configured bias function name for logging. More...

bool	multicanonicalSpline
	Toggle for spline-based multicanonical weights. More...

Protected Attributes
double	multicanonicalBeta
	Global scale factor applied to the multicanonical penalty. 1 is full strength, 0 is no penalty. More...

double	delta_cp_value
	delta_cp value used during proposal evaluation. More...

double	delm23_value
	delm2_23 value used during proposal evaluation. More...

TSpline3 *	dcp_spline_IO
	Spline for the IO branch, if spline mode is enabled. More...

TSpline3 *	dcp_spline_NO
	Spline for the NO branch, if spline mode is enabled. More...

double	umbrellaMean
	Umbrella centre used for the current configuration. More...

double	umbrellaWidth
	Umbrella width used for the current configuration. More...

int	umbrellaNumber
	Number of total umbrellas used for the current configuration. More...

bool	umbrellaOverlapMode
	Toggle for deriving umbrella widths from a desired # of sigma overlaps between umbrellas. More...

double	umbrellaSigmaOverlap
	Requested overlap for evenly spaced umbrellas. More...

bool	umbrellaAdjustStepScale
	Toggle for rescaling the step size based on the umbrella width. More...

double	umbrellaStepScaleFactor
	Additional scale factor applied when rescaling the step size. This is for fine tuning. More...

bool	flipWindow
	Optional flip-window control. More...

double	vonMises_kappa
	Von Mises kappa parameter. Analogue of sigma for a gaussian. More...

double	vonMises_I0_kappa
	Cached I0(kappa) value for the von Mises form. More...

Detailed Description

Helper class for configuring and evaluating multicanonical umbrella weights.

this method is used to bias the MCMC sampling of chains to particular regions of the parameter space The method relies on a bias function defined via a yaml configuration file in experimental specific code With a bias function defined chains run as normal and are combined after the fact using the information stored in the chains saved yaml configuration file.

Author: David Riley [26]

Definition at line 31 of file MulticanonicalMCMCHandler.h.

Constructor & Destructor Documentation

◆ MulticanonicalMCMCHandler()

MulticanonicalMCMCHandler::MulticanonicalMCMCHandler ( )

Constructor.

Definition at line 25 of file MulticanonicalMCMCHandler.cpp.

                                                      {
   // Initialize member variables with defaults
   oscCovVar = -1;
   multicanonicalVar = -1;
   multicanonicalVar_dm23 = -1;
   multicanonicalSpline = false;
   multicanonicalBeta = 1.0;
   delta_cp_value = 0.0;
   delm23_value = 0.0;
   dcp_spline_IO = nullptr;
   dcp_spline_NO = nullptr;
   umbrellaMean = 0.0;
   umbrellaWidth = 1.0;
   umbrellaNumber = 5;
   umbrellaOverlapMode = false;
   umbrellaSigmaOverlap = 3.0;
   umbrellaAdjustStepScale = false;
   umbrellaStepScaleFactor = 1.0;
   flipWindow = false;
  
   vonMises_kappa = -1.0;
   vonMises_I0_kappa = -1.0;
   umbrellaBiasFunction = M3::BiasFunction::kGaussian;
   umbrellaBiasFunctionName = "gaussian";
 }

◆ ~MulticanonicalMCMCHandler()

MulticanonicalMCMCHandler::~MulticanonicalMCMCHandler ( )

virtual

Destructor.

Definition at line 51 of file MulticanonicalMCMCHandler.cpp.

                                                       {
   // Destructor
 }

Member Function Documentation

◆ AdjustUmbrellaStepScale()

void MulticanonicalMCMCHandler::AdjustUmbrellaStepScale ( const std::vector< ParameterHandlerBase * > & systematics )

Adjust the parameter-of-interest's step scale according to the width of the umbrella bias function.

This is used to adjust the step scale of the parameter to keep the size of the step scale relative to the new biased space the chain sees the same. Current assumes that your are sampling delta cp (ie cirular on 2pi)

Todo:: grab the step scale from the objejct directly and update based on the radtio to the umbrella width, removing assumption that its dcp

Definition at line 210 of file MulticanonicalMCMCHandler.cpp.

                                                                                                            {
   if (umbrellaAdjustStepScale) {
     MACH3LOG_INFO("Adjusting umbrella step scale to keep ratio of step scale to multicanonical sigma constant");
     MACH3LOG_INFO("Setting umbrella step scale factor to {}", umbrellaStepScaleFactor);
     double stepScale = (umbrellaWidth * umbrellaStepScaleFactor) / (2.0 * TMath::Pi());
     MACH3LOG_INFO("Setting individual step scale for multicanonical separate to {}", stepScale);
     systematics[oscCovVar]->SetIndivStepScale(multicanonicalVar, stepScale);
     MACH3LOG_INFO("Setting individual step scale for {} systematic to {}", multicanonicalVar, stepScale);
   } else {
     MACH3LOG_INFO("Not adjusting umbrella step scale, using value in OscCov config");
   }
 }

◆ circularDistance()

double MulticanonicalMCMCHandler::circularDistance	(	double	x,
		double	mean
	)

Compute the circular distance between two angles.

This is used to calculate the distance between two angles in a circular space, such as delta_cp. It returns the shortest distance between the two angles, taking into account the wrapping at 2pi.

Definition at line 298 of file MulticanonicalMCMCHandler.cpp.

298 { return std::atan2(std::sin(x - mean), std::cos(x - mean)); }

◆ FindOscCovParams()

void MulticanonicalMCMCHandler::FindOscCovParams ( const std::vector< ParameterHandlerBase * > & systematics )

Locate the systematic object which contains the parameters used by the handler. Stores the parameter indices.

Definition at line 62 of file MulticanonicalMCMCHandler.cpp.

                                                                                                     {
   
   bool foundDeltaCP = false;
   bool foundDelm23 = false;
  
   // Loop over the systematics and find the osc_cov systematic and the delta_cp parameter number
   MACH3LOG_INFO("Looping over systematics to find delta_cp parameter");
   MACH3LOG_INFO("Number of systematics: {}", systematics.size());
  
   for (size_t iCov = 0; iCov < systematics.size(); iCov++){
     auto* syst = systematics[static_cast<int>(iCov)];
     for (int i = 0; i < syst->GetNumParams(); i++) {
       if (syst->GetParName(i) == "delta_cp") {
         MACH3LOG_INFO("Found delta_cp parameter in systematic {} at index {}", syst->GetName(), i);
         oscCovVar = static_cast<int>(iCov);
         multicanonicalVar = i;
         foundDeltaCP = true;
       }
       if (syst->GetParName(i) == "delm2_23") {
         MACH3LOG_INFO("Found delm2_23 parameter in systematic {} at index {}", syst->GetName(), i);
         multicanonicalVar_dm23 = i;
         foundDelm23 = true;
       }
     }  
   }
  
   // if we didn't find both parameters we need to throw
   if (!foundDeltaCP) {
     MACH3LOG_ERROR("Could not find delta_cp parameter in osc_cov systematic");
     throw MaCh3Exception(__FILE__, __LINE__, "Could not find delta_cp parameter in osc_cov systematic");
   }
   if (!foundDelm23) {
     MACH3LOG_ERROR("Could not find delm2_23 parameter in osc_cov systematic");
     throw MaCh3Exception(__FILE__, __LINE__, "Could not find delm2_23 parameter in osc_cov systematic");
   }
 }

◆ generalisedGaussian2()

double MulticanonicalMCMCHandler::generalisedGaussian2	(	double	x,
		double	mean,
		double	width
	)

Wraps the generalised gaussian function for a given x, mean, and width. Required to handle the wrappipng of the parameter space at 2pi.

Definition at line 290 of file MulticanonicalMCMCHandler.cpp.

                                                                                           {
   constexpr int n = 2; // this controls the tightness of the gaussian fixed at 2 for now due to normalisation
   // 1/4 * Gamma(1/4) = 0.906402477055 (this factor from 2n/Gamma(1/2n) for n=2)
   const double normFactor = 1 / ((0.906402477055) * 2 * std::sqrt(2) * width); // the normalisation is a little ugly (uses gamma functions), im just going to hardcode them for now
   double likelihood = normFactor * std::exp(-std::pow((std::pow(x - mean, 2) / (2 * std::pow(width, 2))), n));
   return likelihood;
 }

◆ GetMulticanonicalWeight()

double MulticanonicalMCMCHandler::GetMulticanonicalWeight	(	double	deltacp,
		double	delm23_value
	)

Compute the multicanonical penalty for the configured bias mode.

This wraps the various bias function implementations and returns the appropriate penalty

Returns: Returns the log likelihood penalty for the selected bias function at the proposed parameter values.

Definition at line 251 of file MulticanonicalMCMCHandler.cpp.

                                                                                        {
   if (multicanonicalSpline) {
     return GetMulticanonicalWeightSpline(deltacp, delm23);
   }
  
   switch (umbrellaBiasFunction) {
   case M3::BiasFunction::kGaussian:
     return GetMulticanonicalWeightGaussian(deltacp);
   case M3::BiasFunction::kVonMises:
     return GetMulticanonicalWeightVonMises(deltacp);
   case M3::BiasFunction::kGeneralisedGaussian:
     return GetMulticanonicalWeightGenGaussian(deltacp);
   }
  
   return GetMulticanonicalWeightGaussian(deltacp);
 }

◆ GetMulticanonicalWeightGaussian()

double MulticanonicalMCMCHandler::GetMulticanonicalWeightGaussian ( double deltacp )

Compute a Gaussian multicanonical penalty.

Definition at line 283 of file MulticanonicalMCMCHandler.cpp.

                                                                                 {
   const double inv_sqrt_2pi = 1 / std::sqrt(2 * TMath::Pi());
   const double neg_half_sigma_sq = -1 / (2 * umbrellaWidth * umbrellaWidth);
   // return the log likelihood, ie the log of the normalised gaussian
   return (-std::log(inv_sqrt_2pi * (1 / umbrellaWidth) * std::exp(neg_half_sigma_sq * (deltacp - umbrellaMean) * (deltacp - umbrellaMean)))) * (multicanonicalBeta);
 }

◆ GetMulticanonicalWeightGenGaussian()

double MulticanonicalMCMCHandler::GetMulticanonicalWeightGenGaussian ( double deltacp )

Compute a generalised-Gaussian multicanonical penalty.

the generalised gaussian is like a gaussian with an extra factor of n on the exponent of the gaussian. This allows for a stronger constraint in the tails of the distribution, more like a tophat function. The normalisation is a little ugly and uses gamma functions, so for now it is hardcoded to n=2. This is the current recommended configuration for umbrella sampling.

Todo:

implememnt the wrapping with circular distance function to avoid the need to calculate the weight multiple times for each parameter to ensure it recieves a bias even when it jumps the boundary

implement the normalisation for n != 2, and allow n to be set in the yaml configuration file

Definition at line 300 of file MulticanonicalMCMCHandler.cpp.

                                                                                    {
   // implemenetation of the generalised gaussian as a bias function
   // for now with a fixed n = 2 for simplicity
   double g0 = generalisedGaussian2(deltacp, umbrellaMean, umbrellaWidth); // these two repeats are required for wrapping the gaussian around -pi and pi
   double g1 = generalisedGaussian2(deltacp, umbrellaMean - 2 * TMath::Pi(), umbrellaWidth);
   double g2 = generalisedGaussian2(deltacp, umbrellaMean + 2 * TMath::Pi(), umbrellaWidth);
 #ifdef DEBUG
   if (debugStream && debugEnabled) (*debugStream) << " g0: " << g0 << " g1: " << g1 << " g2: " << g2 << std::endl;
 #endif
   return -std::log(g0 + g1 + g2) * (multicanonicalBeta);
 }

◆ GetMulticanonicalWeightSpline()

double MulticanonicalMCMCHandler::GetMulticanonicalWeightSpline	(	double	deltacp,
		double	delm23_value
	)

Compute the multicanonical penalty using a spline.

Definition at line 268 of file MulticanonicalMCMCHandler.cpp.

                                                                                              {
   double dcp_spline_val;
  
   if (delm23 < 0) {
     dcp_spline_val = dcp_spline_IO->Eval(deltacp);
     return -(-std::log(dcp_spline_val) + std::log(dcp_spline_IO->Eval(-TMath::Pi() / 2))) * (multicanonicalBeta); // do I want this offset?? does it matter?
   } else {
     dcp_spline_val = dcp_spline_NO->Eval(deltacp);
     return -(-std::log(dcp_spline_val) + std::log(dcp_spline_NO->Eval(-TMath::Pi() / 2))) * (multicanonicalBeta);
   }
   // std::cout << "Evaluating spline at delta_cp = " << deltacp << " gives value
   // " << dcp_spline_val << "with -log lh of :" << -log(dcp_spline_val) <<
   // std::endl;
 }

◆ GetMulticanonicalWeightTripleGaussian()

double MulticanonicalMCMCHandler::GetMulticanonicalWeightTripleGaussian ( double deltacp )

Compute a triple-Gaussian multicanonical penalty.

This was mostsly for testing the first implementation, probably not used anymore.

delta_cp_log_likelihood = -TMath::Log(TMath::Gaus(deltacp,TMath::Pi(),1,kTRUE)+TMath::Gaus(deltacp,0,1,kTRUE)+TMath::Gaus(deltacp,-TMath::Pi(),1,kTRUE));

Definition at line 312 of file MulticanonicalMCMCHandler.cpp.

                                                                                       { // pretty much deprecated at this point, just here for testing
   // precalculate constants
   constexpr double inv_sqrt_2pi = 0.3989422804014337;
   double sigma = umbrellaWidth;
   const double neg_half_sigma_sq = -1 / (2 * sigma * sigma);
   // three gaussians centered at -pi, 0, pi with sigma pre-defined above
   double exp1 = std::exp(neg_half_sigma_sq * (deltacp - TMath::Pi()) * (deltacp - TMath::Pi()));
   double exp2 = std::exp(neg_half_sigma_sq * (deltacp) * (deltacp));
   double exp3 = std::exp(neg_half_sigma_sq * (deltacp + TMath::Pi()) * (deltacp + TMath::Pi()));
  
   // return the log likelihood, ie the log of the normalised sum of the
   // gaussians
   return -std::log(inv_sqrt_2pi * (1 / sigma) * (exp1 + exp2 + exp3)) * (multicanonicalBeta);
 }

◆ GetMulticanonicalWeightVonMises()

double MulticanonicalMCMCHandler::GetMulticanonicalWeightVonMises ( double deltacp )

Compute a von Mises multicanonical penalty.

This is the circular analogue of a gaussian, meaning it handles the wrapping of the parameter space at 2pi automatically this avoids the need to calculate the weight multiple times for each parameter to ensure it recieves a bias even when it jumps the boundary the normalisation grows extremely quickly, widths of less that 0.05 should not be used until properly tested.

Definition at line 242 of file MulticanonicalMCMCHandler.cpp.

                                                                                 {
   // calculate the Log form of the von Mises instead to avoid numerical issues
   // and return directly
   double log_vonMises = vonMises_kappa * std::cos(deltacp - umbrellaMean) - std::log(2 * TMath::Pi() * vonMises_I0_kappa);
   // return the log likelihood, ie the log of the normalised von Mises
   return -log_vonMises * (multicanonicalBeta);
 }

◆ InitializeMulticanonicalHandlerConfig()

void MulticanonicalMCMCHandler::InitializeMulticanonicalHandlerConfig	(	Manager *	fitMan,
		std::vector< ParameterHandlerBase * > &	systematics
	)

Read multicanonical configuration from the yaml via manager and initialise handler state.

Todo:: DR: I realised this will fail if you set spline to true but don't

Definition at line 99 of file MulticanonicalMCMCHandler.cpp.

                                                                                                                                     {
  
   FindOscCovParams(systematics);
  
   const auto mcmcConfig = fitMan->raw()["General"]["MCMC"];
  
   // Get the multicanonical beta value from the configuration file
   // This acts as a global bias strength factor
   multicanonicalBeta = mcmcConfig["Multicanonical"]["Beta"].as<double>();
   MACH3LOG_INFO("Setting multicanonical beta to {}", multicanonicalBeta);
  
   // delete the umbrella section, thats not ideal
   multicanonicalSpline = GetFromManager<bool>(mcmcConfig["Multicanonical"]["Spline"]["SplineMode"], false);
  
   const std::string biasFunctionName = GetFromManager<std::string>(mcmcConfig["Multicanonical"]["Umbrella"]["UmbrellaBiasFunction"], "");
   const bool hasBiasFunction = !biasFunctionName.empty();
  
   // Spline and umbrella modes are mutually exclusive
   if (multicanonicalSpline && hasBiasFunction) {
     MACH3LOG_ERROR("Cannot use multicanonical spline together with umbrella bias function selection.");
     throw MaCh3Exception(__FILE__, __LINE__, "Cannot use multicanonical spline together with umbrella bias function selection.");
   }
  
   // Umbrella mode requires an explicit bias function selection
   if (!multicanonicalSpline && !hasBiasFunction) {
     MACH3LOG_ERROR("Multicanonical umbrella mode requires UmbrellaBiasFunction to be set (gaussian, vonMises, or generalisedGaussian).");
     throw MaCh3Exception(__FILE__, __LINE__, "Multicanonical umbrella mode requires UmbrellaBiasFunction to be set.");
   }
  
   // Parse and set the umbrella bias function enum
   if (hasBiasFunction) {
     umbrellaBiasFunction = ParseBiasFunction(biasFunctionName);
     umbrellaBiasFunctionName = biasFunctionName;
     MACH3LOG_INFO("Using umbrella bias function {}", umbrellaBiasFunctionName);
   }
  
   // setup for spline bias mode
   if (multicanonicalSpline) {
  
     std::string splineFileName = GetFromManager<std::string>(mcmcConfig["Multicanonical"]["Spline"]["SplineFile"], "nofile");
  
     TFile* splineFile = M3::Open(splineFileName.c_str(), "READ",__FILE__, __LINE__);
  
     // grab the splines and do a quick check that they are evaluatable
     TSpline3* dcp_spline_IO_fromfile = static_cast<TSpline3*>(splineFile->Get("dcp_spline_IO"));
     dcp_spline_IO = static_cast<TSpline3*>(dcp_spline_IO_fromfile->Clone("dcp_spline_IO"));
     MACH3LOG_INFO("Using multicanonical spline from file {}", splineFileName);
     dcp_spline_IO->Eval(0.0); // check that the spline is valid
     MACH3LOG_INFO("Spline evaluated at 0.0 gives value: {}", dcp_spline_IO->Eval(0.0));
  
     TSpline3* dcp_spline_NO_fromfile = static_cast<TSpline3*>(splineFile->Get("dcp_spline_NO"));
     dcp_spline_NO = static_cast<TSpline3*>(dcp_spline_NO_fromfile->Clone("dcp_spline_NO"));
     MACH3LOG_INFO("Using multicanonical spline from file {}", splineFileName);
     dcp_spline_NO->Eval(0.0); // check that the spline is valid
     MACH3LOG_INFO("Spline evaluated at 0.0 gives value {}", dcp_spline_NO->Eval(0.0));
  
     splineFile->Close();
     splineFile = nullptr;
  
   } else {
     // Umbrella mode with explicit bias function selection
     MACH3LOG_INFO("Using umbrella multicanonical method with bias function {}", umbrellaBiasFunctionName);
     umbrellaMean = GetFromManager<double>(mcmcConfig["Multicanonical"]["Umbrella"]["UmbrellaMean"], 0);
     MACH3LOG_INFO("Setting multicanonical mean to {}", umbrellaMean);
  
     umbrellaNumber = GetFromManager<int>(mcmcConfig["Multicanonical"]["Umbrella"]["UmbrellaNumber"], 5);
  
     // dynamically adjust the width of the gaussians to ensure a certain level
     // of overlap? be careful, not enough windows here will lead to posterior
     // (rather than bias) dominated results
     umbrellaOverlapMode = GetFromManager<bool>(mcmcConfig["Multicanonical"]["Umbrella"]["AutoOverlapMode"], false);
  
     if (umbrellaOverlapMode) {
       MACH3LOG_INFO("Setting width based on # of sigma overlapping between umbrellas");
       umbrellaSigmaOverlap = GetFromManager<double>(mcmcConfig["Multicanonical"]["Umbrella"]["SigmaOverlap"], 3.0);
       MACH3LOG_INFO("Setting umbrella number to {}", umbrellaNumber);
       umbrellaWidth = TMath::Pi() / ((umbrellaNumber - 1) * (umbrellaSigmaOverlap));
     } else {
       // just grab the width directly from the config
       umbrellaWidth = GetFromManager<double>(mcmcConfig["Multicanonical"]["Umbrella"]["UmbrellaWidth"], (2 * TMath::Pi()) / umbrellaNumber);
       MACH3LOG_INFO("Setting width based on value in config {}", umbrellaWidth);
     }
  
     // set individual step scale for dcp, so that the ratio of the step scale to
     // the multicanonical sigma is stepscale/1sigmaerror = 1/2pi
     umbrellaAdjustStepScale = GetFromManager<bool>(mcmcConfig["Multicanonical"]["Umbrella"]["UmbrellaAdjustStepScale"], false);
     umbrellaStepScaleFactor = GetFromManager<double>(mcmcConfig["Multicanonical"]["Umbrella"]["UmbrellaStepScaleFactor"], 1.0);
  
     AdjustUmbrellaStepScale(systematics);
  
     // Set the flip window flag for the oscillation systematic DO NOT USE THIS
     // flipWindow =
     // GetFromManager<bool>(mcmcConfig["Multicanonical"]["Umbrella"]["FlipWindow"],
     // false); MACH3LOG_INFO("Flip Window: {}", flipWindow);
   }
  
   // initialize von Mises parameters
   if (umbrellaBiasFunction == M3::BiasFunction::kVonMises) {
     double temp_vonMises_sigma;
     temp_vonMises_sigma = GetFromManager<double>(mcmcConfig["Multicanonical"]["Umbrella"]["UmbrellaWidth"], umbrellaWidth);
     vonMises_kappa = 1.0 / (temp_vonMises_sigma * temp_vonMises_sigma);
     vonMises_I0_kappa = TMath::BesselI0(vonMises_kappa);
     MACH3LOG_INFO("Using von Mises distribution with kappa = {} and I0(kappa) = {}", vonMises_kappa, vonMises_I0_kappa);
   }
  
   if (umbrellaBiasFunction == M3::BiasFunction::kGeneralisedGaussian) {
     MACH3LOG_INFO("Using generalised Gaussian with mean {} and width {}", umbrellaMean, umbrellaWidth);
   }
 }

◆ InitializeMulticanonicalParams()

void MulticanonicalMCMCHandler::InitializeMulticanonicalParams ( std::vector< ParameterHandlerBase * > & systematics )

Initialise the starting values used by the multicanonical parameter handling.

This moves the starting point of the chain to the centre of the umbrella bias function. Only affects the parameter of interest.

Definition at line 223 of file MulticanonicalMCMCHandler.cpp.

                                                                                                             {
   // Set starting point of chain to umbrella center for non-spline umbrella modes
   if (!multicanonicalSpline) {
     systematics[oscCovVar]->PrintPreFitCurrPropValues();
     systematics[oscCovVar]->SetParCurrProp(multicanonicalVar, umbrellaMean);
     MACH3LOG_INFO("Setting starting point of chain to mean value for multicanonical separate: {}", umbrellaMean);
     // pass the mean to the covarianceOsc object for parameter flipping DO NOT USE: UNTESTED
     // if (flipWindow) {
     //  auto* oscCov = dynamic_cast<covarianceOsc*>(syst);
     //  if (oscCov) {
     //    oscCov->setFlipWindow(flipWindow);
     //    oscCov->setMulticanonicalSeparateMean(umbrellaMean);
     //  }
     //}
     systematics[oscCovVar]->PrintPreFitCurrPropValues();
     MACH3LOG_INFO("Setting starting point of chain to umbrella center: {}", umbrellaMean);
   }
 }

Member Data Documentation

◆ dcp_spline_IO

TSpline3* MulticanonicalMCMCHandler::dcp_spline_IO

protected

Spline for the IO branch, if spline mode is enabled.

Definition at line 121 of file MulticanonicalMCMCHandler.h.

◆ dcp_spline_NO

TSpline3* MulticanonicalMCMCHandler::dcp_spline_NO

protected

Spline for the NO branch, if spline mode is enabled.

Definition at line 123 of file MulticanonicalMCMCHandler.h.

◆ delm23_value

double MulticanonicalMCMCHandler::delm23_value

protected

delm2_23 value used during proposal evaluation.

Definition at line 118 of file MulticanonicalMCMCHandler.h.

◆ delta_cp_value

double MulticanonicalMCMCHandler::delta_cp_value

protected

delta_cp value used during proposal evaluation.

Definition at line 116 of file MulticanonicalMCMCHandler.h.

◆ flipWindow

bool MulticanonicalMCMCHandler::flipWindow

protected

Optional flip-window control.

briefly tested feature to mirrow windows about their centres. Not tested but may be useful in the future. Currently disabled and not used.

Definition at line 142 of file MulticanonicalMCMCHandler.h.

◆ multicanonicalBeta

double MulticanonicalMCMCHandler::multicanonicalBeta

protected

Global scale factor applied to the multicanonical penalty. 1 is full strength, 0 is no penalty.

Definition at line 113 of file MulticanonicalMCMCHandler.h.

◆ multicanonicalSpline

bool MulticanonicalMCMCHandler::multicanonicalSpline

Toggle for spline-based multicanonical weights.

Definition at line 109 of file MulticanonicalMCMCHandler.h.

◆ multicanonicalVar

int MulticanonicalMCMCHandler::multicanonicalVar

Parameter index used for the multicanonical delta_cp weight.

Definition at line 98 of file MulticanonicalMCMCHandler.h.

◆ multicanonicalVar_dm23

int MulticanonicalMCMCHandler::multicanonicalVar_dm23

Parameter index used for the multicanonical delm2_23 weight.

Definition at line 100 of file MulticanonicalMCMCHandler.h.

◆ oscCovVar

int MulticanonicalMCMCHandler::oscCovVar

Index of the oscillation-covariance systematic in the current fit.

Definition at line 96 of file MulticanonicalMCMCHandler.h.

◆ umbrellaAdjustStepScale

bool MulticanonicalMCMCHandler::umbrellaAdjustStepScale

protected

Toggle for rescaling the step size based on the umbrella width.

Definition at line 137 of file MulticanonicalMCMCHandler.h.

◆ umbrellaBiasFunction

M3::BiasFunction MulticanonicalMCMCHandler::umbrellaBiasFunction

Selected bias function for multicanonical weights.

Definition at line 103 of file MulticanonicalMCMCHandler.h.

◆ umbrellaBiasFunctionName

std::string MulticanonicalMCMCHandler::umbrellaBiasFunctionName

Configured bias function name for logging.

Definition at line 106 of file MulticanonicalMCMCHandler.h.

◆ umbrellaMean

double MulticanonicalMCMCHandler::umbrellaMean

protected

Umbrella centre used for the current configuration.

Definition at line 126 of file MulticanonicalMCMCHandler.h.

◆ umbrellaNumber

int MulticanonicalMCMCHandler::umbrellaNumber

protected

Number of total umbrellas used for the current configuration.

Currently only used when auto-overlap mode is enabled. This is not fully tested.

Definition at line 131 of file MulticanonicalMCMCHandler.h.

◆ umbrellaOverlapMode

bool MulticanonicalMCMCHandler::umbrellaOverlapMode

protected

Toggle for deriving umbrella widths from a desired # of sigma overlaps between umbrellas.

Definition at line 133 of file MulticanonicalMCMCHandler.h.

◆ umbrellaSigmaOverlap

double MulticanonicalMCMCHandler::umbrellaSigmaOverlap

protected

Requested overlap for evenly spaced umbrellas.

Definition at line 135 of file MulticanonicalMCMCHandler.h.

◆ umbrellaStepScaleFactor

double MulticanonicalMCMCHandler::umbrellaStepScaleFactor

protected

Additional scale factor applied when rescaling the step size. This is for fine tuning.

Definition at line 139 of file MulticanonicalMCMCHandler.h.

◆ umbrellaWidth

double MulticanonicalMCMCHandler::umbrellaWidth

protected

Umbrella width used for the current configuration.

Definition at line 128 of file MulticanonicalMCMCHandler.h.

◆ vonMises_I0_kappa

double MulticanonicalMCMCHandler::vonMises_I0_kappa

protected

Cached I0(kappa) value for the von Mises form.

Definition at line 147 of file MulticanonicalMCMCHandler.h.

◆ vonMises_kappa

double MulticanonicalMCMCHandler::vonMises_kappa

protected

Von Mises kappa parameter. Analogue of sigma for a gaussian.

Definition at line 145 of file MulticanonicalMCMCHandler.h.

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

Fitters/MulticanonicalMCMCHandler.h
Fitters/MulticanonicalMCMCHandler.cpp

Public Member Functions

Public Attributes

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ MulticanonicalMCMCHandler()

◆ ~MulticanonicalMCMCHandler()

Member Function Documentation

◆ AdjustUmbrellaStepScale()

◆ circularDistance()

◆ FindOscCovParams()

◆ generalisedGaussian2()

◆ GetMulticanonicalWeight()

◆ GetMulticanonicalWeightGaussian()

◆ GetMulticanonicalWeightGenGaussian()

◆ GetMulticanonicalWeightSpline()

◆ GetMulticanonicalWeightTripleGaussian()

◆ GetMulticanonicalWeightVonMises()

◆ InitializeMulticanonicalHandlerConfig()

◆ InitializeMulticanonicalParams()

Member Data Documentation

◆ dcp_spline_IO

◆ dcp_spline_NO

◆ delm23_value

◆ delta_cp_value

◆ flipWindow

◆ multicanonicalBeta

◆ multicanonicalSpline

◆ multicanonicalVar

◆ multicanonicalVar_dm23

◆ oscCovVar

◆ umbrellaAdjustStepScale

◆ umbrellaBiasFunction

◆ umbrellaBiasFunctionName

◆ umbrellaMean

◆ umbrellaNumber

◆ umbrellaOverlapMode

◆ umbrellaSigmaOverlap

◆ umbrellaStepScaleFactor

◆ umbrellaWidth

◆ vonMises_I0_kappa

◆ vonMises_kappa