a Code for the Combination of Indirect and Direct Constraints on High Energy Physics Models Logo
Public Member Functions | Private Member Functions | Private Attributes | List of all members
MonteCarlo Class Reference
MonteCarlo

A class for Monte Carlo. More...

#include <MonteCarlo.h>

Detailed Description

A class for Monte Carlo.

Author
HEPfit Collaboration
Copyright
GNU General Public License

This class is responsible for the MCMC runs using the MCMCEngine class together with input parameters from the InputParser class. The Monte Carlo mode is the default run mode if the –noMC flag is not specified. The settings for the Monte Carlo run can be fixed in in the format specified in the MonteCarlo.conf file, the name of this configuration file should be specified as the second argument to the executable.

Examples
MCMC.cpp, and myModel_MCMC.cpp.

Definition at line 35 of file MonteCarlo.h.

Public Member Functions

void addCustomObservableType (const std::string name, boost::function< Observable *() > funct)
 
std::map< std::string, BCH1D > getHistograms1D () const
 
std::map< std::string, BCH2D > getHistograms2D () const
 
 MonteCarlo (ModelFactory &ModelF, ThObsFactory &ThObsF, const std::string &ModelConf_i, const std::string &MonteCarloConf_i, const std::string &OutFile_i, const std::string &JobTag_i)
 Constructor. More...
 
void Run (const int rank)
 This member is responsible for setting the Monte Carlo run parameters and conducting the Monte Carlo run including initiating all output generation. More...
 
void TestRun (int rank)
 This member is used for test runa to generate a single event. More...
 
virtual ~MonteCarlo ()
 The default destructor. More...
 

Private Member Functions

void ParseMCMCConfig (std::string file)
 
void ReadPreRunData (std::string file)
 

Private Attributes

std::string CalculateNormalization
 < Flag for calculating the evidence. More...
 
std::vector< CorrelatedGaussianObservables > CGO
 Vector for the Correlated Gaussian Observables defined in SomeModel.conf. More...
 
std::vector< CorrelatedGaussianParameters > CGP
 Vector for the Correlated Gaussian Parameters defined in SomeModel.conf. More...
 
bool checkrun
 A check to make sure TestRun()and Run() are not called consecutively. More...
 
bool FindModeWithMinuit
 Flag for using Minuit libraries. More...
 
std::string JobTag
 String for the optional JobTag argument to be passes to the executable. More...
 
MonteCarloEngine MCEngine
 An object of the MonteCarloEngine class. More...
 
std::string MCMCConf
 String for the name of the MonteCarlo.conf file. More...
 
std::string ModelConf
 String for the name of the SomeModel.conf file. More...
 
std::string ModelName
 The name of the model. More...
 
std::vector< ModelParameter > ModPars
 Vector for the model parameters defined in SomeModel.conf. More...
 
InputParser myInputParser
 An object of the InputParser class. More...
 
int NIterationNormalizationMC
 < Number of iterations for MC integral done to compute normalization of a model More...
 
boost::ptr_vector< Observable > Obs
 Vector for the observables defined in SomeModel.conf. More...
 
std::vector< Observable2D > Obs2D
 Vector for the Observables2D defined in SomeModel.conf. More...
 
std::string ObsDirName
 String for the output directory name. More...
 
std::string OutFile
 String for the name of the output root file without the .root extension. More...
 
bool PrintAllMarginalized
 Flag for printing all Marginalized distributions to be passed on to the BAT routines. More...
 
bool PrintCorrelationMatrix
 Flag for printing the correlation matrix. More...
 
bool PrintKnowledgeUpdatePlots
 Flag for printing plots to compare prior vs. posterior knowledge of parameters. More...
 
bool PrintParameterPlot
 Flag for printing the overview parameter plots. More...
 
bool PrintTrianglePlot
 Flag for printing the triangle plot. More...
 
bool RunMinuitOnly
 Flag for running Minuit only. More...
 
bool writechains
 Flag for writing the chains of paramters and observables during the MCMC run. More...
 
bool WritePreRunData
 Flag for printing the overview parameter plots. More...
 

Constructor & Destructor Documentation

◆ MonteCarlo()

MonteCarlo::MonteCarlo ( ModelFactory &  ModelF,
ThObsFactory &  ThObsF,
const std::string &  ModelConf_i,
const std::string &  MonteCarloConf_i,
const std::string &  OutFile_i,
const std::string &  JobTag_i 
)

Constructor.

The default constructor sets the names of the configuration files and the names of the output root file and specific output directory if a job ID is specified as an argument to the executable. The constructor also sets the default values of some flags related to the Monte Carlo run. The boolean flags (FindModeWithMinuit, PrintAllMarginalized, PrintCorrelationMatrix, PrintKnowledgeUpdatePlots, PrintParameterPlot) attain their run time values after the MonteCarlo.conf file is parsed by MonteCarlo::Run().

Parameters
[in]ModelF
[in]ThObsF
[in]ModelConf_ithe name of the input configuration file for the model name, the model parameters and observables to be calculated (Observables, Observables2D, Model Parameters vs. Observables and Correlated Gaussian Observables)
[in]MonteCarloConf_ithe name of the Monte Carlo configuration file that specifies the parameters of the Monte Carlo run like no. of chains, no. of pre run iterations etc.
[in]OutFile_ithe name of the root output file to be given without the .root extention
[in]JobTag_ioptional job tag that might be specified

Definition at line 26 of file MonteCarlo.cpp.

32 : myInputParser(ModelF, ThObsF), MCEngine(ModPars, Obs, Obs2D, CGO, CGP) {
33  ModelConf = ModelConf_i;
34  MCMCConf = MonteCarloConf_i;
35  JobTag = JobTag_i;
36  if (OutFile_i.compare("") == 0) OutFile = "MCout" + JobTag + ".root";
37  else OutFile = OutFile_i + JobTag + ".root";
38  ObsDirName = "Observables" + JobTag;
39  FindModeWithMinuit = false;
40  RunMinuitOnly = false;
41  CalculateNormalization = "false";
42  NIterationNormalizationMC = 0;
43  PrintAllMarginalized = false;
44  PrintCorrelationMatrix = false;
45  PrintKnowledgeUpdatePlots = false;
46  PrintParameterPlot = false;
47  PrintTrianglePlot = false;
48  WritePreRunData = false;
49  checkrun = false;
50  writechains = false;
51 }

◆ ~MonteCarlo()

MonteCarlo::~MonteCarlo ( )
virtual

The default destructor.

Definition at line 53 of file MonteCarlo.cpp.

54 {
55  Obs.clear();
56  boost::ptr_vector<Observable>().swap(Obs);
57 }

Member Function Documentation

◆ addCustomObservableType()

void MonteCarlo::addCustomObservableType ( const std::string  name,
boost::function< Observable *() >  funct 
)

Definition at line 734 of file MonteCarlo.cpp.

734  {
735  myInputParser.addCustomObservableType(name, funct);
736 }

◆ getHistograms1D()

std::map<std::string, BCH1D> MonteCarlo::getHistograms1D ( ) const
inline

Definition at line 142 of file MonteCarlo.h.

143  {
144  return MCEngine.getHistograms1D();
145  }

◆ getHistograms2D()

std::map<std::string, BCH2D> MonteCarlo::getHistograms2D ( ) const
inline

Definition at line 147 of file MonteCarlo.h.

148  {
149  return MCEngine.getHistograms2D();
150  }

◆ ParseMCMCConfig()

void MonteCarlo::ParseMCMCConfig ( std::string  file)
private

Definition at line 478 of file MonteCarlo.cpp.

479 {
480  std::ifstream ifile(file.c_str());
481  if (!ifile.is_open())
482  throw std::runtime_error("\nERROR: " + MCMCConf + " does not exist. Make sure to specify a valid Monte Carlo configuration file.\n");
483  std::string line;
484  bool IsEOF = false;
485  do {
486  IsEOF = getline(ifile, line).eof();
487  if (*line.rbegin() == '\r') line.erase(line.length() - 1); // for CR+LF
488  if (line.empty() || line.at(0) == '#')
489  continue;
490  boost::char_separator<char> sep(" \t");
491  boost::tokenizer<boost::char_separator<char> > tok(line, sep);
492  boost::tokenizer<boost::char_separator<char> >::iterator beg = tok.begin();
493  if (beg->compare("NChains") == 0) {
494  ++beg;
495  if (isdigit(beg->at(0)) && atoi((*beg).c_str()) > 0) MCEngine.setNChains(atoi((*beg).c_str()));
496  else if (isdigit(beg->at(0)) && atoi((*beg).c_str()) == 0)
497  if (MCEngine.getMPIWorldSize() > 1) MCEngine.setNChains(MCEngine.getMPIWorldSize());
498  else throw std::runtime_error("\nERROR: NChains in the MonteCarlo configuration file: " + MCMCConf + " can only be an integer > 0.\n");
499  else
500  throw std::runtime_error("\nERROR: NChains in the MonteCarlo configuration file: " + MCMCConf + " can only be an integer >= 0.\n");
501  } else if (beg->compare("PrerunMaxIter") == 0) {
502  ++beg;
503  if (isdigit(beg->at(0)) && atoi((*beg).c_str()) > 0) MCEngine.SetNIterationsPreRunMax(atoi((*beg).c_str()));
504  else
505  throw std::runtime_error("\nERROR: PrerunMaxIter in the MonteCarlo configuration file: " + MCMCConf + " can only be an integer > 0.\n");
506  } else if (beg->compare("NIterationsUpdateMax") == 0) {
507  ++beg;
508  if (isdigit(beg->at(0)) && atoi((*beg).c_str()) > 0) MCEngine.SetNIterationsPreRunCheck(atoi((*beg).c_str()));
509  else
510  throw std::runtime_error("\nERROR: NIterationsUpdateMax in the MonteCarlo configuration file: " + MCMCConf + " can only be an integer > 0.\n");
511  } else if (beg->compare("Seed") == 0) {
512  ++beg;
513  if (!isdigit(beg->at(0))) throw std::runtime_error("\nERROR: Seed in the MonteCarlo configuration file: " + MCMCConf + " can only be a number.\n");
514  int seed = atoi((*beg).c_str());
515  if (seed != 0)
516  MCEngine.SetRandomSeed(seed);
517  } else if (beg->compare("Iterations") == 0) {
518  ++beg;
519  if (isdigit(beg->at(0))) MCEngine.SetNIterationsRun(atoi((*beg).c_str()));
520  else
521  throw std::runtime_error("\nERROR: Iterations in the MonteCarlo configuration file: " + MCMCConf + " can only be an integer.\n");
522  } else if (beg->compare("MinimumEfficiency") == 0) {
523  ++beg;
524  double efficiency = atof((*beg).c_str());
525  if (efficiency > 0. && efficiency <= 1.) MCEngine.SetMinimumEfficiency(efficiency);
526  else
527  throw std::runtime_error("\nERROR: MinimumEfficiency in the MonteCarlo configuration file: " + MCMCConf + " can only be a real number greater than 0.0 and less than or equal to 1.0.\n");
528  } else if (beg->compare("MaximumEfficiency") == 0) {
529  ++beg;
530  double efficiency = atof((*beg).c_str());
531  if (efficiency > 0. && efficiency <= 1.) MCEngine.SetMaximumEfficiency(efficiency);
532  else
533  throw std::runtime_error("\nERROR: MaximumEfficiency in the MonteCarlo configuration file: " + MCMCConf + " can only be a real number greater than 0.0 and less than or equal to 1.0.\n");
534  } else if (beg->compare("RValueForConvergence") == 0) {
535  ++beg;
536  double rvalue = atof((*beg).c_str());
537  if (rvalue > 1. ) MCEngine.SetRValueParametersCriterion(rvalue);
538  else
539  throw std::runtime_error("\nERROR: RValueForConvergence in the MonteCarlo configuration file: " + MCMCConf + " can only be a real number greater than 1.0.\n");
540  } else if (beg->compare("WriteChain") == 0) {
541  ++beg;
542  if (beg->compare("true") == 0 || beg->compare("false") == 0) writechains = (beg->compare("true") == 0);
543  else
544  throw std::runtime_error("\nERROR: WriteChain in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
545  } else if (beg->compare("FindModeWithMinuit") == 0) {
546  ++beg;
547  if (beg->compare("true") == 0 || beg->compare("false") == 0) FindModeWithMinuit = (beg->compare("true") == 0);
548  else
549  throw std::runtime_error("\nERROR: FindModeWithMinuit in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
550  } else if (beg->compare("RunMinuitOnly") == 0) {
551  ++beg;
552  if (beg->compare("true") == 0 || beg->compare("false") == 0) RunMinuitOnly = (beg->compare("true") == 0);
553  else
554  throw std::runtime_error("\nERROR: RunMinuitOnly in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
555  } else if (beg->compare("CalculateNormalization") == 0) {
556  ++beg;
557  if (beg->compare("true") == 0 || beg->compare("false") == 0) CalculateNormalization = *beg;
558  else
559  throw std::runtime_error("\nERROR: CalculateNormalization in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
560  } else if (beg->compare("NIterationNormalizationMC") == 0) {
561  ++beg;
562  if (isdigit(beg->at(0))) NIterationNormalizationMC = atoi((*beg).c_str());
563  else
564  throw std::runtime_error("\nERROR: NIterationNormalizationMC in the MonteCarlo configuration file: " + MCMCConf + " can only be an integer.\n");
565  } else if (beg->compare("PrintAllMarginalized") == 0) {
566  ++beg;
567  if (beg->compare("true") == 0 || beg->compare("false") == 0) PrintAllMarginalized = (beg->compare("true") == 0);
568  else
569  throw std::runtime_error("\nERROR: PrintAllMarginalized in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
570  } else if (beg->compare("PrintCorrelationMatrix") == 0) {
571  ++beg;
572  if (beg->compare("true") == 0 || beg->compare("false") == 0) PrintCorrelationMatrix = (beg->compare("true") == 0);
573  else
574  throw std::runtime_error("\nERROR: PrintCorrelationMatrix in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
575  } else if (beg->compare("PrintKnowledgeUpdatePlots") == 0) {
576  ++beg;
577  if (beg->compare("true") == 0 || beg->compare("false") == 0) PrintKnowledgeUpdatePlots = (beg->compare("true") == 0);
578  else
579  throw std::runtime_error("\nERROR: PrintKnowledgeUpdatePlots in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
580  } else if (beg->compare("PrintParameterPlot") == 0) {
581  ++beg;
582  if (beg->compare("true") == 0 || beg->compare("false") == 0) PrintParameterPlot = (beg->compare("true") == 0);
583  else
584  throw std::runtime_error("\nERROR: PrintParameterPlot in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
585  } else if (beg->compare("PrintTrianglePlot") == 0) {
586  ++beg;
587  if (beg->compare("true") == 0 || beg->compare("false") == 0) PrintTrianglePlot = (beg->compare("true") == 0);
588  else
589  throw std::runtime_error("\nERROR: PrintTrianglePlot in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
590  } else if (beg->compare("WritePreRunData") == 0) {
591  ++beg;
592  if (beg->compare("true") == 0 || beg->compare("false") == 0) WritePreRunData = (beg->compare("true") == 0);
593  else
594  throw std::runtime_error("\nERROR: WritePreRunData in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
595  } else if (beg->compare("ReadPreRunData") == 0) {
596  ++beg;
597  ReadPreRunData(*beg);
598  } else if (beg->compare("MultivariateProposal") == 0) {
599  ++beg;
600  if (beg->compare("true") == 0 || beg->compare("false") == 0) MCEngine.SetProposeMultivariate((beg->compare("true") == 0));
601  else
602  throw std::runtime_error("\nERROR: MultivariateProposal in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
603  } else if (beg->compare("Histogram1DSmooth") == 0) {
604  ++beg;
605  if (beg->compare("true") == 0) {
606  MCEngine.setSmooth(1);
607  } else if (beg->compare("false") == 0) {
608  MCEngine.setSmooth(0); /* Default */
609  } else if (isdigit(beg->at(0))) {
610  if (atoi((*beg).c_str()) >= 0 && atoi((*beg).c_str()) <= 5) MCEngine.setSmooth(atoi((*beg).c_str()));
611  } else
612  throw std::runtime_error("\nERROR: Histogram1DSmooth in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true', 'false' or an integer from 0 to 5.\n");
613  } else if (beg->compare("Histogram2DType") == 0) {
614  ++beg;
615  if (!isdigit(beg->at(0)))
616  throw std::runtime_error("\nERROR: Histogram2DType in the MonteCarlo configuration file : " + MCMCConf + "can only be an integer amongst 1001 -> Lego, 101 -> Filled, 1 -> Contour.\n");
617  int type = atoi((*beg).c_str());
618  if (type == 1 || type == 101 || type == 1001) {
619  MCEngine.setHistogram2DType(type);
620  } else
621  throw std::runtime_error("\nERROR: Histogram2DType in the MonteCarlo configuration file : " + MCMCConf + "can only be an integer amongst 1001 -> Lego, 101 -> Filled, 1 -> Contour.\n");
622  } else if (beg->compare("MCMCInitialPosition") == 0) {
623  ++beg;
624  if (beg->compare("Center") == 0) {
625  MCEngine.SetInitialPositionScheme(BCEngineMCMC::kInitCenter); /* Default */
626  } else if (beg->compare("RandomUniform") == 0) {
627  MCEngine.SetInitialPositionScheme(BCEngineMCMC::kInitRandomUniform);
628  } else if (beg->compare("RandomPrior") == 0) {
629  MCEngine.SetInitialPositionScheme(BCEngineMCMC::kInitRandomPrior);
630  } else
631  throw std::runtime_error("\nERROR: MCMCInitialPosition in MonteCarlo config file: " + MCMCConf + " can only be 'Center', 'RandomUniform' or 'RandomPrior'.\n");
632  } else if (beg->compare("PrintLogo") == 0) {
633  ++beg;
634  if (beg->compare("true") == 0 || beg->compare("false") == 0) MCEngine.setPrintLogo((beg->compare("true") == 0));
635  else
636  throw std::runtime_error("\nERROR: PrintLogo in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
637  } else if (beg->compare("NoHistogramLegend") == 0) {
638  ++beg;
639  if (beg->compare("true") == 0 || beg->compare("false") == 0) MCEngine.setNoLegend((beg->compare("true") == 0));
640  else
641  throw std::runtime_error("\nERROR: PrintLogo in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
642  } else if (beg->compare("PrintLoglikelihoodPlots") == 0) {
643  ++beg;
644  if (beg->compare("true") == 0 || beg->compare("false") == 0) MCEngine.setPrintLoglikelihoodPlots((beg->compare("true") == 0));
645  else
646  throw std::runtime_error("\nERROR: PrintLoglikelihoodPlots in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
647  if (beg->compare("true") == 0) gSystem->MakeDirectory((ObsDirName + "/LogLikelihoodPlots").c_str());
648  } else if (beg->compare("WriteLogLikelihoodChain") == 0) {
649  ++beg;
650  if (beg->compare("true") == 0 || beg->compare("false") == 0) MCEngine.setWriteLogLikelihoodChain((beg->compare("true") == 0));
651  else
652  throw std::runtime_error("\nERROR: WriteLogLikelihoodChain in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
653  } else if (beg->compare("WriteParametersChains") == 0) {
654  ++beg;
655  if (beg->compare("true") == 0 || beg->compare("false") == 0) MCEngine.setWriteParametersChain((beg->compare("true") == 0));
656  else
657  throw std::runtime_error("\nERROR: WriteParametersChain in the MonteCarlo configuration file: " + MCMCConf + " can only be 'true' or 'false'.\n");
658  } else if (beg->compare("Histogram2DAlpha") == 0) {
659  ++beg;
660  double alpha = atof((*beg).c_str());
661  if (alpha > 0. && alpha <= 1.) MCEngine.setAlpha2D(alpha);
662  else
663  throw std::runtime_error("\nERROR: Histogram2DAlpha in the MonteCarlo configuration file: " + MCMCConf + " can only be a real number greater than 0.0 and less than or equal to 1.0.\n");
664  } else if (beg->compare("NBinsHistogram1D") == 0) {
665  ++beg;
666  unsigned int nBins1D = atoi((*beg).c_str());
667  if (nBins1D >= 0) MCEngine.setNBins1D(nBins1D);
668  else throw std::runtime_error("\nERROR: NBinsHistogram1D in the MonteCarlo configuration file: " + MCMCConf + " can only be a integer greater than 0 or 0 to set to default value (100).\n");
669  } else if (beg->compare("NBinsHistogram2D") == 0) {
670  ++beg;
671  unsigned int nBins2D = atoi((*beg).c_str());
672  if (nBins2D >= 0) MCEngine.setNBins2D(nBins2D);
673  else throw std::runtime_error("\nERROR: NBinsHistogram2D in the MonteCarlo configuration file: " + MCMCConf + " can only be a integer greater than 0 or 0 to set to default value (100).\n");
674  } else if (beg->compare("InitialPositionAttemptLimit") == 0) {
675  ++beg;
676  unsigned int max_tries = atoi((*beg).c_str());
677  if (max_tries > 0) MCEngine.SetInitialPositionAttemptLimit(max_tries);
678  else if (max_tries == 0) MCEngine.SetInitialPositionAttemptLimit(10000);
679  else throw std::runtime_error("\nERROR: InitialPositionAttemptLimit in the MonteCarlo configuration file: " + MCMCConf + " can only be a integer greater than 0 or 0 to set to default value (100).\n");
680  } else if (beg->compare("SignificantDigits") == 0) {
681  ++beg;
682  unsigned int significants = atoi((*beg).c_str());
683  if (significants >= 0) MCEngine.setSignificants(significants);
684  else throw std::runtime_error("\nERROR: SignificantDigits in the MonteCarlo configuration file: " + MCMCConf + " can only be a integer greater than 0 or 0 to set to default values.\n");
685  } else if (beg->compare("HistogramBufferSize") == 0) {
686  ++beg;
687  unsigned int histogramBufferSize = atoi((*beg).c_str());
688  if (histogramBufferSize >= 0) MCEngine.setHistogramBufferSize(histogramBufferSize);
689  else throw std::runtime_error("\nERROR: HistogramBufferSize in the MonteCarlo configuration file: " + MCMCConf + " can only be a integer greater than 0 or 0 to set to default values.\n");
690  } else
691  throw std::runtime_error("\nERROR: Wrong keyword in MonteCarlo config file: " + MCMCConf + "\n Make sure to specify a valid Monte Carlo configuration file.\n");
692  } while (!IsEOF);
693  if (FindModeWithMinuit || RunMinuitOnly)
694  MCEngine.SetOptimizationMethod(BCIntegrate::kOptMinuit);
695  if (MCEngine.GetMaximumEfficiency() <= MCEngine.GetMinimumEfficiency())
696  throw std::runtime_error("\nERROR: MaximumEfficiency (default 0.5) must be greater than MaximumEfficiency (default 0.15) in the MonteCarlo configuration file: " + MCMCConf + ".\n");
697  if (CalculateNormalization.compare("MC") == 0 && NIterationNormalizationMC <= 0)
698  throw std::runtime_error(("\nMonteCarlo ERROR: CalculateNormalization cannot be set to MC without setting NIterationNormalizationMC > 0 in " + MCMCConf + " .\n").c_str());
699 }

◆ ReadPreRunData()

void MonteCarlo::ReadPreRunData ( std::string  file)
private

Definition at line 701 of file MonteCarlo.cpp.

702 {
703  std::ifstream ifile(file.c_str());
704  if (!ifile.is_open())
705  throw std::runtime_error("\nMonteCarlo::ReadPreRunData ERROR: " + file + " does not exist.\n");
706  std::string line;
707  bool IsEOF = false;
708  std::vector<double> mode;
709  std::vector<double> scale;
710  do {
711  IsEOF = getline(ifile, line).eof();
712  if (line.empty())
713  continue;
714  boost::char_separator<char> sep(" ");
715  boost::tokenizer<boost::char_separator<char> > tok(line, sep);
716  boost::tokenizer<boost::char_separator<char> >::iterator beg = tok.begin();
717  ++beg;
718  mode.push_back(atof((*beg).c_str()));
719  ++beg;
720  scale.push_back(atof((*beg).c_str()));
721  } while (!IsEOF);
722  if (mode.size() != MCEngine.GetNParameters())
723  throw std::runtime_error("\nMonteCarlo::ReadPreRunData ERROR: wrong data size.\n");
724  std::vector<double> mode_all;
725  std::vector<double> scale_all;
726  for (unsigned int i = 0; i < MCEngine.GetNChains(); i++){
727  mode_all.insert(mode_all.end(), mode.begin(), mode.end());
728  scale_all.insert(scale_all.end(), scale.begin(), scale.end());
729  }
730  MCEngine.SetInitialPositions(mode_all);
731  MCEngine.SetInitialScaleFactors(scale_all);
732 }

◆ Run()

void MonteCarlo::Run ( const int  rank)

This member is responsible for setting the Monte Carlo run parameters and conducting the Monte Carlo run including initiating all output generation.

The algorithm implemented by this member is as follows:

  • Initiate InputParser::ReadParameters() which read the SomeModel.conf file for setting the model parameters and the observables to be generated. This call also passes on the name of the model to the private member ModelName.
  • Map the model parameter mean values with the map DP and calculate buffsize which can be used for implementing MPI runs. The variable buffsize is incremented only for those model parameters that are varied in the Monte Carlo run.
  • Initiate the model using the map DP checking for consistency between required model parameters and the ones supplied in the SomeModel.conf file
  • Set the model name and initialize the MCMC engine with the model at hand.
  • For MPI runs, send the evaluates of the loglikelihood for the prerun to the slave processes (rank != 0)
  • The master in an MPI run or the process in a serial run then parses the MonterCarlo.conf file to read the parameters for the Monte Carlo run.
  • The root output file is handed over to the object out of type BCModelOutput and some BAT options are set for the log and output histograms.
  • The MCMC is run and all the out put is generated according to the options set in the MonteCarlo.conf file.
  • For a MPI run, the final call to the MPI class prepares the processes for finalizing.

The details for BCSummaryTool, BCLog, BCAux and BCModelOutput can be found in the BAT website. These are used mainly to generate logs and output.

The details of the object MCEngine of type MonteCarloEngine which overloads the BCEngineMCMC class can be found in our documentation of the former class.

Parameters
[in]rank= MPI::COMM_WORLD.Get_rank(), specifies the rank of the process. This carries a non zero value only when the executable is compiled with the parallelized version of BAT and run as parallel processes with MPI.
Examples
MCMC.cpp, and myModel_MCMC.cpp.

Definition at line 128 of file MonteCarlo.cpp.

128  {
129  if (checkrun == true) {
130  if (rank == 0) throw std::runtime_error("ERROR: MonteCarlo::Run() cannot be called after calling MonteCarlo::TestRun().\n");
131  else sleep(2);
132  } else {
133  checkrun = true;
134  }
135 
136  try {
137 
138  /* set model parameters */
139  ModelName = myInputParser.ReadParameters(ModelConf, rank, ModPars, Obs, Obs2D, CGO, CGP);
140  int buffsize = 0;
141  std::map<std::string, double> DP;
142  for (std::vector<ModelParameter>::iterator it = ModPars.begin(); it < ModPars.end(); it++) {
143  if (it->geterrg() > 0. || it->geterrf() > 0.)
144  buffsize++;
145  if (it->IsCorrelated()) {
146  for (unsigned int i = 0; i < CGP.size(); i++) {
147  if (CGP[i].getName().compare(it->getCgp_name()) == 0) {
148  std::string index = it->getname().substr(CGP[i].getName().size());
149  long int lindex = strtol(index.c_str(), NULL, 10);
150  if (lindex > 0)
151  DP[CGP[i].getPar(lindex - 1).getname()] = CGP[i].getPar(lindex - 1).getave();
152  else {
153  std::stringstream out;
154  out << it->getname();
155  throw std::runtime_error("MonteCarlo::Run(): " + out.str() + "seems to be part of a CorrelatedGaussianParameters object, but I couldn't find the corresponding object");
156  }
157  }
158  }
159  } else
160  DP[it->getname()] = it->getave();
161  }
162  if (buffsize == 0){
163  if (rank == 0) throw std::runtime_error("No parameters being varied. Aborting MCMC run.\n");
164  else sleep(2);
165  }
166  buffsize++;
167  if (!myInputParser.getModel()->Init(DP)) {
168  if (myInputParser.getModel()->getmissingModelParameters().size() > 0) {
169  if (rank == 0) std::cout << "\nPlease set the following parameters in the model configuration files:\n" << std::endl;
170  for (std::vector<std::string>::iterator it = myInputParser.getModel()->getmissingModelParameters().begin(); it != myInputParser.getModel()->getmissingModelParameters().end(); it++) {
171  if (rank == 0) std::cout << "ModelParameter\t" << *it << std::endl;
172  }
173  std::cout << std::endl;
174  myInputParser.getModel()->getmissingModelParameters().clear();
175  }
176 
177  if (rank == 0) throw std::runtime_error("\nERROR: " + ModelName + " cannot be initialized.\n");
178  else sleep(2);
179  }
180  int discardbuffer = 0;
181  std::vector<std::string> unknownParameters = myInputParser.getModel()->getUnknownParameters();
182  for (std::vector<ModelParameter>::iterator it = ModPars.begin(); it < ModPars.end(); it++) {
183  if (std::find(unknownParameters.begin(), unknownParameters.end(), it->getname()) != unknownParameters.end()) {
184  if (it->geterrg() > 0. || it->geterrf() > 0.) {
185  discardbuffer++;
186  if (rank == 0) std::cout << "\nWARNING: " << it->getname() << " has a flat or Gaussian error in the configuration file even though it is an unknown parameter!!!\n";
187  }
188  }
189  }
190  buffsize = buffsize - discardbuffer;
191  if (buffsize == 1){
192  if (rank == 0) throw std::runtime_error("No relevant parameters being varied. Aborting MCMC run.\n");
193  else sleep(2);
194  }
195 
196  /* create a directory for outputs */
197  if (rank == 0) {
198  FileStat_t info;
199  if (gSystem->GetPathInfo(ObsDirName.c_str(), info) != 0) {
200  if (gSystem->MakeDirectory(ObsDirName.c_str()) == 0) std::cout << ObsDirName << " directory has been created." << std::endl;
201  else throw std::runtime_error("ERROR: " + ObsDirName + " directory cannot be created.\n");
202  }
203  }
204 
205  MCEngine.SetName(ModelName.c_str());
206  MCEngine.Initialize(myInputParser.getModel());
207  MCEngine.SetInitialPositionAttemptLimit(10000);
208 
209 #ifdef _MPI
210  double *recvbuff = new double[buffsize];
211 #endif
212 
213  if (rank != 0) {
214 #ifdef _MPI
215  double **sendbuff = new double*[1];
216  sendbuff[0] = new double[1];
217 
218  std::vector<double> pars;
219  int obsbuffsize = Obs.size() + 2 * Obs2D.size();
220  for (std::vector<CorrelatedGaussianObservables>::iterator it1 = CGO.begin(); it1 < CGO.end(); it1++)
221  obsbuffsize += it1->getObs().size();
222 
223  while (true) {
224  MPI_Scatter(sendbuff[0], buffsize, MPI_DOUBLE, recvbuff, buffsize, MPI_DOUBLE, 0, MPI_COMM_WORLD);
225 
226  if (recvbuff[0] == 0.) { // do nothing and return ll
227  double ll = log(0.);
228  MPI_Gather(&ll, 1, MPI_DOUBLE, sendbuff[0], 1, MPI_DOUBLE, 0, MPI_COMM_WORLD);
229  } else if (recvbuff[0] == 1.) { //compute log likelihood
230  pars.assign(recvbuff + 1, recvbuff + buffsize);
231  double ll = MCEngine.LogEval(pars);
232  MPI_Gather(&ll, 1, MPI_DOUBLE, sendbuff[0], 1, MPI_DOUBLE, 0, MPI_COMM_WORLD);
233  } else if (recvbuff[0] == 2.) { // compute observables
234  double sbuff[obsbuffsize];
235  std::map<std::string, double> DPars;
236  pars.assign(recvbuff + 1, recvbuff + buffsize);
237  MCEngine.setDParsFromParameters(pars,DPars);
238  myInputParser.getModel()->Update(DPars);
239 
240  int k = 0;
241  for (boost::ptr_vector<Observable>::iterator it = Obs.begin(); it < Obs.end(); it++) {
242  sbuff[k++] = it->computeTheoryValue();
243  }
244  for (std::vector<Observable2D>::iterator it = Obs2D.begin(); it < Obs2D.end(); it++) {
245  sbuff[k++] = it->computeTheoryValue();
246  sbuff[k++] = it->computeTheoryValue2();
247  }
248 
249  for (std::vector<CorrelatedGaussianObservables>::iterator it1 = CGO.begin(); it1 < CGO.end(); it1++) {
250  std::vector<Observable> pino(it1->getObs());
251  for (std::vector<Observable>::iterator it = pino.begin(); it != pino.end(); ++it)
252  sbuff[k++] = it->computeTheoryValue();
253  }
254  MPI_Gather(sbuff, obsbuffsize, MPI_DOUBLE, sendbuff[0], obsbuffsize, MPI_DOUBLE, 0, MPI_COMM_WORLD);
255  } else if (recvbuff[0] == 3.) { // do not compute observables, but gather the buffer
256  double sbuff[obsbuffsize];
257  MPI_Gather(sbuff, obsbuffsize, MPI_DOUBLE, sendbuff[0], obsbuffsize, MPI_DOUBLE, 0, MPI_COMM_WORLD);
258  } else if (recvbuff[0] == -1.)
259  break;
260  else {
261  std::cout << "recvbuff = " << recvbuff[0] << " rank " << rank << std::endl;
262  throw std::runtime_error("MonteCarlo::Run(): error in MPI message!\n");
263  }
264  }
265  delete sendbuff[0];
266  delete [] sendbuff;
267 #endif
268  } else {
269  ParseMCMCConfig(MCMCConf);
270  if (!RunMinuitOnly) std::cout << std::endl << "\nRunning in MonteCarlo mode...\n" << std::endl;
271  else std::cout << std::endl << "\nRunning Minuit Minimizer..." << std::endl;
272  std::cout << std::endl;
273  if (ModPars.size() > 0) std::cout << ModPars.size() - unknownParameters.size() << " parameters defined." << std::endl;
274  if (Obs.size() > 0) std::cout << Obs.size() << " observables defined." << std::endl;
275  if (Obs2D.size() > 0) std::cout << Obs2D.size() << " 2D observables defined." << std::endl;
276  if (CGO.size() > 0) std::cout << CGO.size() << " correlated gaussian observables defined:" << std::endl;
277  for (std::vector<CorrelatedGaussianObservables>::iterator it1 = CGO.begin();
278  it1 != CGO.end(); ++it1)
279  std::cout << " " << it1->getName() << " containing "
280  << it1->getObs().size() << " observables." << std::endl;
281  std::cout << std::endl;
282 
283  if (RunMinuitOnly) {
284  BCLog::OpenLog(("MinuitMinimizationResults" + JobTag + ".txt").c_str(), BCLog::debug, BCLog::debug);
285  RedirectHandle_t * rHandle = NULL;
286  gSystem->RedirectOutput(("MinuitMinimizationResults" + JobTag + ".txt").c_str(), "a", rHandle);
287  std::time_t ti = std::time(NULL);
288 #if __GNUC__ >= 5 || defined __clang__
289  std::cout << "\nMinuit Minimization started at " << std::put_time(std::localtime(&ti), "%c %Z") << " (" << ti << "s since the Epoch)" << "\n" << std::endl;
290 #else
291  char mitime[128];
292  strftime(mitime,sizeof(mitime),"%c %Z", std::localtime(&ti));
293  std::cout << "\nMinuit Minimization started at " << mitime << " (" << ti << "s since the Epoch)" << "\n" << std::endl;
294 #endif
295  std::cout << " " <<std::endl;
296  std::cout << "\t\t*** Minimizer Options ***" << std::endl;
297  MCEngine.GetMinuit().Options().Print();
298  std::cout << " " <<std::endl;
299  MCEngine.FindMode();
300  std::time_t tf = std::time(NULL);
301 #if __GNUC__ >= 5 || defined __clang__
302  std::cout << "\nMinuit Minimization ended at " << std::put_time(std::localtime(&tf), "%c %Z") << " (" << tf << "s since the Epoch)" << "\n" << std::endl;
303 #else
304  char mftime[128];
305  strftime(mitime,sizeof(mftime),"%c %Z", std::localtime(&tf));
306  std::cout << "\nMinuit Minimization ended at " << mftime << " (" << tf << "s since the Epoch)" << "\n" << std::endl;
307 #endif
308  gSystem->RedirectOutput(0);
309  BCLog::OutSummary(("Minuit results printed in MinuitMinimizationResults" + JobTag + ".txt").c_str());
310  BCLog::SetPrefix(false);
311  BCLog::OutSummary("");
312  BCLog::SetPrefix(true);
313  BCLog::CloseLog();
314  MCEngine.GetMinuit().PrintResults();
315  std::cout << std::endl;
316  return;
317  }
318 
319  MCEngine.CreateHistogramMaps();
320 
321  /* Open root file for storing data. */
322  if (writechains) {
323  MCEngine.WriteMarkovChain(OutFile, "RECREATE", true, false); /*Run: true, PreRun: false*/
324  MCEngine.AddChains();
325  } else {
326  MCEngine.WriteMarkovChain(OutFile, "RECREATE", false, false);
327  MCEngine.InitializeMarkovChainTree();
328  MCEngine.WriteMarkovChainRun(false);
329  MCEngine.WriteMarkovChainPreRun(false);
330  if (MCEngine.getchainedObsSize() > 0 || MCEngine.getWriteLogLikelihoodChain() || MCEngine.getWriteParametersChain()) MCEngine.AddChains();
331  }
332 
333  std::time_t ti = std::time(NULL);
334 #if __GNUC__ >= 5 || defined __clang__
335  std::cout << "\nMCMC run started at " << std::put_time(std::localtime(&ti), "%c %Z") << " (" << ti << "s since the Epoch)" << "\n" << std::endl;
336 #else
337  char mitime[128];
338  strftime(mitime,sizeof(mitime),"%c %Z", std::localtime(&ti));
339  std::cout << "\nMCMC run started at " << mitime << " (" << ti << "s since the Epoch)" << "\n" << std::endl;
340 #endif
341  // open log file
342  BCLog::OpenLog(("log" + JobTag + ".txt").c_str(), BCLog::debug, BCLog::debug);
343  // run the MCMC and marginalize w.r.t. to all parameters
344  MCEngine.BCIntegrate::SetNbins(NBINSMODELPARS);
345  MCEngine.SetMarginalizationMethod(BCIntegrate::kMargMetropolis);
346  MCEngine.MarginalizeAll();
347  std::time_t tf = std::time(NULL);
348 #if __GNUC__ >= 5 || defined __clang__
349  std::cout << "\nMCMC run ended at " << std::put_time(std::localtime(&tf), "%c %Z") << " (" << tf << "s since the Epoch)" << std::endl;
350 #else
351  char mftime[128];
352  strftime(mftime,sizeof(mftime),"%c %Z", std::localtime(&tf));
353  std::cout << "\nMCMC run ended at " << mftime << " (" << tf << "s since the Epoch)" << "\n" << std::endl;
354 #endif
355  int hour = (tf-ti)/3600;
356  int min = ((tf-ti)%3600) / 60;
357  int sec = ((tf-ti)%3600) % 60;
358  std::cout << "Time taken by the MCMC run: ";
359  std::cout << std::setfill('0') << std::setw(2) << hour << ":";
360  std::cout << std::setfill('0') << std::setw(2) << min << ":" ;
361  std::cout << std::setfill('0') << std::setw(2) << sec << "\n" << std::endl;
362 
363  // find mode using the best fit parameters as start values
364  if (FindModeWithMinuit) MCEngine.FindMode(MCEngine.GetBestFitParameters());
365 
366  // draw all marginalized distributions into a pdf file
367  if (PrintAllMarginalized) MCEngine.PrintAllMarginalized(("MonteCarlo_plots" + JobTag + ".pdf").c_str());
368 
369  // print histograms
370  MCEngine.PrintHistogram(OutFile, ObsDirName);
371 
372  // draw the correlation matrix into a pdf file and make the tex files
373  if (PrintCorrelationMatrix) {
374  MCEngine.PrintCorrelationMatrix(("CorrelationMatrix" + JobTag + ".pdf").c_str());
375  MCEngine.PrintCorrelationMatrix(("CorrelationMatrix" + JobTag + ".tex").c_str());
376  MCEngine.PrintCorrelationMatrixToLaTeX(("ParameterCorrelations" + JobTag + ".tex").c_str());
377  }
378 
379  // print comparisons of the prior knowledge to the posterior knowledge
380  // for all parameters into a pdf file
381  if (PrintKnowledgeUpdatePlots) MCEngine.PrintKnowledgeUpdatePlots(("ParamUpdate" + JobTag + ".pdf").c_str());
382 
383  // draw an overview plot of the parameters into a pdf file
384  if (PrintParameterPlot) MCEngine.PrintParameterPlot(("ParamSummary" + JobTag + ".pdf").c_str());
385 
386  MCEngine.WriteMarginalizedDistributions(OutFile, "UPDATE");
387 
388  // print logs for the histograms of the observables into a text file
389  std::ofstream outHistoLog;
390  outHistoLog.open((ObsDirName + "/HistoLog" + JobTag + ".txt").c_str(), std::ios::out);
391  outHistoLog << MCEngine.getHistoLog();
392  outHistoLog.close();
393 
394  // print statistics for the theory values of the observables into a text file
395  std::ofstream outStatLog;
396  outStatLog.open((ObsDirName + "/Statistics" + JobTag + ".txt").c_str(), std::ios::out);
397  outStatLog << MCEngine.computeStatistics();
398  outStatLog.close();
399 
400  // print global mode and scale factors for the 1st chain into a text file
401  if (WritePreRunData) {
402  std::ofstream outPreRun;
403  outPreRun.open(("PreRun" + JobTag + ".txt").c_str(), std::ios::out);
404  outPreRun << MCEngine.writePreRunData();
405  outPreRun.close();
406  }
407 
408  /* Number of events */
409  std::stringstream ss;
410  ss << "";
411  BCLog::SetPrefix(false);
412  BCLog::OutSummary(ss.str().c_str());
413  BCLog::SetPrefix(true);
414  ss << "Number of used events: " << MCEngine.getNumOfUsedEvents();
415  BCLog::OutSummary(ss.str().c_str());
416  ss.str("");
417  ss << "Number of discarded events: " << MCEngine.getNumOfDiscardedEvents() << "\n";
418  BCLog::OutSummary(ss.str().c_str());
419  // close log file
420  BCLog::CloseLog();
421 
422  // print results of the analysis into a text file
423  BCLog::SetPrefix(false);
424  BCLog::OpenLog(("MonteCarlo_results" + JobTag + ".txt").c_str(), BCLog::summary, BCLog::nothing);
425  MCEngine.PrintSummary();
426  BCLog::CloseLog();
427 
428  // Calculate and print normalization
429  if (CalculateNormalization.compare("false") != 0) {
430  std::ofstream outStatLog;
431  outStatLog.open((ObsDirName + "/Statistics" + JobTag + ".txt").c_str(), std::ios::app);
432 
433  if (CalculateNormalization.compare("LME") == 0) {
434  // Make sure mode is found by MINUIT for normalization computation.
435  if (!FindModeWithMinuit) MCEngine.FindMode(MCEngine.GetBestFitParameters());
436  outStatLog << "\nNormalization for " << ModelName.c_str() << ": " << MCEngine.computeNormalizationLME() << "\n" << std::endl;
437  }
438  else if (CalculateNormalization.compare("MC") == 0) {
439  std::vector<double> normalizationMC = MCEngine.computeNormalizationMC(NIterationNormalizationMC);
440  outStatLog << "\nNormalization for " << ModelName.c_str() << ": " << normalizationMC[0] << " +- " << normalizationMC[1] << "\n" << std::endl;
441  }
442  else
443  throw std::runtime_error(("\n ERROR: Normalization method" + CalculateNormalization + " not implemented.\n").c_str());
444 
445  outStatLog.close();
446  }
447 
448  // Print the triangle plot (the size of the file is quite large for large number of parameters).
449  // this is done last for now since BAT sometimes crashes while doing this. Did not look for the fix.
450  if (PrintTrianglePlot) {
451  BCLog::OpenLog(("log_CorrelationPlots" + JobTag + ".txt").c_str(), BCLog::debug, BCLog::debug);
452  MCEngine.PrintCorrelationPlot("CorrelationPlots" + JobTag + ".pdf");
453  BCLog::CloseLog();
454  }
455 
456 
457 #ifdef _MPI
458  double ** sendbuff = new double *[MCEngine.procnum];
459  sendbuff[0] = new double[MCEngine.procnum * buffsize];
460  for (int il = 1; il < MCEngine.procnum; il++) {
461  sendbuff[il] = sendbuff[il - 1] + buffsize;
462  sendbuff[il][0] = -1.; //Exit command
463  }
464  MPI_Scatter(sendbuff[0], buffsize, MPI_DOUBLE, recvbuff, buffsize, MPI_DOUBLE, 0, MPI_COMM_WORLD);
465  delete sendbuff[0];
466  delete [] sendbuff;
467 #endif
468  }
469 #ifdef _MPI
470  delete [] recvbuff;
471 #endif
472  } catch (std::string message) {
473  std::cerr << message << std::endl;
474  exit(EXIT_FAILURE);
475  }
476 }

◆ TestRun()

void MonteCarlo::TestRun ( int  rank)

This member is used for test runa to generate a single event.

The values of the parameters that are used to generate the single event is the average value passed from the SomeModel.conf file.

The algorithm implemented by this member is as follows:

  • Initiate InputParser::ReadParameters() which read the SomeModel.conf file for setting the model parameters and the observables to be generated. This call also passes on the name of the model to the private member ModelName.
  • Map the model parameter mean values with the map DP and calculate buffsize which can be used for implementing MPI runs. The variable buffsize is incremented only for those model parameters that are varied in the Monte Carlo run.
  • Initiate the model using the map DP checking for consistency between required model parameters and the ones supplied in the SomeModel.conf file
  • Generate a single set of observables and correlated Gaussian observables as listed in the SomeModel.conf file. The output is passes to the standard output.
Parameters
[in]rank= MPI::COMM_WORLD.Get_rank(), specifies the rank of the process. This carries a non zero value only when the executable is compiled with the parallelized version of BAT and run as parallel processes with MPI.
Examples
MCMC.cpp.

Definition at line 59 of file MonteCarlo.cpp.

59  {
60  if (checkrun == true) {
61  if (rank == 0) throw std::runtime_error("ERROR: MonteCarlo::TestRun() cannot be called after calling MonteCarlo::Run().\n");
62  else sleep (2);
63  } else {
64  checkrun = true;
65  }
66 
67  if (rank == 0) {
68  ModelName = myInputParser.ReadParameters(ModelConf, rank, ModPars, Obs, Obs2D, CGO, CGP);
69  std::map<std::string, double> DP;
70  if (Obs.size() == 0 && CGO.size() == 0) throw std::runtime_error("\nMonteCarlo::TestRun(): No observables or correlated Gaussian observables defined in SomeModel.conf file\n");
71 
72  for (std::vector<ModelParameter>::iterator it = ModPars.begin(); it < ModPars.end(); it++) {
73  if (it->IsCorrelated()) {
74  for (unsigned int i = 0; i < CGP.size(); i++) {
75  if (CGP[i].getName().compare(it->getCgp_name()) == 0) {
76  std::string index = it->getname().substr(CGP[i].getName().size());
77  long int lindex = strtol(index.c_str(), NULL, 10);
78  if (lindex > 0)
79  DP[CGP[i].getPar(lindex - 1).getname()] = CGP[i].getPar(lindex - 1).getave();
80  else {
81  std::stringstream out;
82  out << it->getname();
83  throw std::runtime_error("MonteCarlo::Run(): " + out.str() + "seems to be part of a CorrelatedGaussianParameters object, but I couldn't find the corresponding object");
84  }
85  }
86  }
87  } else
88  DP[it->getname()] = it->getave();
89  }
90 
91  if (!myInputParser.getModel()->Init(DP)) {
92  if (myInputParser.getModel()->getmissingModelParameters().size() > 0) {
93  std::cout << "\nPlease set the following parameters in the model configuration files:\n" << std::endl;
94  for (std::vector<std::string>::iterator it = myInputParser.getModel()->getmissingModelParameters().begin(); it != myInputParser.getModel()->getmissingModelParameters().end(); it++) {
95  std::cout << "ModelParameter\t" << *it << std::endl;
96  }
97  std::cout << std::endl;
98  myInputParser.getModel()->getmissingModelParameters().clear();
99  }
100  if (rank == 0) throw std::runtime_error("ERROR: Parameter(s) missing in model initialization. \n");
101  else sleep (2);
102  }
103  std::vector<std::string> unknownParameters = myInputParser.getModel()->getUnknownParameters();
104  if (unknownParameters.size() > 0 && rank == 0) {
105  std::cout << "\n" << std::endl;
106  for (std::vector<std::string>::iterator it = unknownParameters.begin(); it != unknownParameters.end(); it++)
107  std::cout << "WARNING: unknown parameter " << *it << " not added to MCMC Test Run" << std::endl;
108  }
109  if (Obs.size() > 0) std::cout << "\nObservables: \n" << std::endl;
110  for (boost::ptr_vector<Observable>::iterator it = Obs.begin(); it < Obs.end(); it++) {
111  double th = it->computeTheoryValue();
112  std::cout << it->getName() << " = " << th << std::endl;
113  }
114 
115  if (CGO.size() > 0) std::cout << "\nCorrelated Gaussian Observables: \n" << std::endl;
116  for (std::vector<CorrelatedGaussianObservables>::iterator it1 = CGO.begin(); it1 < CGO.end(); it1++) {
117  std::cout << it1->getName() << ":" << std::endl;
118  std::vector<Observable> ObsInCGO = it1->getObs();
119  for (std::vector<Observable>::iterator it2 = ObsInCGO.begin(); it2 < ObsInCGO.end(); it2++) {
120  double th = it2->computeTheoryValue();
121  std::cout << it2->getName() << " = " << th << std::endl;
122  }
123  std::cout << std::endl;
124  }
125  }
126 }

Member Data Documentation

◆ CalculateNormalization

std::string MonteCarlo::CalculateNormalization
private

< Flag for calculating the evidence.

Definition at line 170 of file MonteCarlo.h.

◆ CGO

std::vector<CorrelatedGaussianObservables> MonteCarlo::CGO
private

Vector for the Correlated Gaussian Observables defined in SomeModel.conf.

Definition at line 161 of file MonteCarlo.h.

◆ CGP

std::vector<CorrelatedGaussianParameters> MonteCarlo::CGP
private

Vector for the Correlated Gaussian Parameters defined in SomeModel.conf.

Definition at line 162 of file MonteCarlo.h.

◆ checkrun

bool MonteCarlo::checkrun
private

A check to make sure TestRun()and Run() are not called consecutively.

Definition at line 178 of file MonteCarlo.h.

◆ FindModeWithMinuit

bool MonteCarlo::FindModeWithMinuit
private

Flag for using Minuit libraries.

Definition at line 168 of file MonteCarlo.h.

◆ JobTag

std::string MonteCarlo::JobTag
private

String for the optional JobTag argument to be passes to the executable.

Definition at line 166 of file MonteCarlo.h.

◆ MCEngine

MonteCarloEngine MonteCarlo::MCEngine
private

An object of the MonteCarloEngine class.

Definition at line 157 of file MonteCarlo.h.

◆ MCMCConf

std::string MonteCarlo::MCMCConf
private

String for the name of the MonteCarlo.conf file.

Definition at line 164 of file MonteCarlo.h.

◆ ModelConf

std::string MonteCarlo::ModelConf
private

String for the name of the SomeModel.conf file.

Definition at line 163 of file MonteCarlo.h.

◆ ModelName

std::string MonteCarlo::ModelName
private

The name of the model.

Definition at line 155 of file MonteCarlo.h.

◆ ModPars

std::vector<ModelParameter> MonteCarlo::ModPars
private

Vector for the model parameters defined in SomeModel.conf.

Definition at line 158 of file MonteCarlo.h.

◆ myInputParser

InputParser MonteCarlo::myInputParser
private

An object of the InputParser class.

Definition at line 156 of file MonteCarlo.h.

◆ NIterationNormalizationMC

int MonteCarlo::NIterationNormalizationMC
private

< Number of iterations for MC integral done to compute normalization of a model

Definition at line 171 of file MonteCarlo.h.

◆ Obs

boost::ptr_vector<Observable> MonteCarlo::Obs
private

Vector for the observables defined in SomeModel.conf.

Definition at line 159 of file MonteCarlo.h.

◆ Obs2D

std::vector<Observable2D> MonteCarlo::Obs2D
private

Vector for the Observables2D defined in SomeModel.conf.

Definition at line 160 of file MonteCarlo.h.

◆ ObsDirName

std::string MonteCarlo::ObsDirName
private

String for the output directory name.

Definition at line 167 of file MonteCarlo.h.

◆ OutFile

std::string MonteCarlo::OutFile
private

String for the name of the output root file without the .root extension.

Definition at line 165 of file MonteCarlo.h.

◆ PrintAllMarginalized

bool MonteCarlo::PrintAllMarginalized
private

Flag for printing all Marginalized distributions to be passed on to the BAT routines.

Definition at line 172 of file MonteCarlo.h.

◆ PrintCorrelationMatrix

bool MonteCarlo::PrintCorrelationMatrix
private

Flag for printing the correlation matrix.

Definition at line 173 of file MonteCarlo.h.

◆ PrintKnowledgeUpdatePlots

bool MonteCarlo::PrintKnowledgeUpdatePlots
private

Flag for printing plots to compare prior vs. posterior knowledge of parameters.

Definition at line 174 of file MonteCarlo.h.

◆ PrintParameterPlot

bool MonteCarlo::PrintParameterPlot
private

Flag for printing the overview parameter plots.

Definition at line 175 of file MonteCarlo.h.

◆ PrintTrianglePlot

bool MonteCarlo::PrintTrianglePlot
private

Flag for printing the triangle plot.

Definition at line 176 of file MonteCarlo.h.

◆ RunMinuitOnly

bool MonteCarlo::RunMinuitOnly
private

Flag for running Minuit only.

Definition at line 169 of file MonteCarlo.h.

◆ writechains

bool MonteCarlo::writechains
private

Flag for writing the chains of paramters and observables during the MCMC run.

Definition at line 179 of file MonteCarlo.h.

◆ WritePreRunData

bool MonteCarlo::WritePreRunData
private

Flag for printing the overview parameter plots.

Definition at line 177 of file MonteCarlo.h.

The documentation for this class was generated from the following files:
gslpp::sec
complex sec(const complex &z)
Definition: gslpp_complex.cpp:447
MonteCarlo::checkrun
bool checkrun
A check to make sure TestRun()and Run() are not called consecutively.
Definition: MonteCarlo.h:178
MonteCarlo::ObsDirName
std::string ObsDirName
String for the output directory name.
Definition: MonteCarlo.h:167
MonteCarloEngine::setAlpha2D
void setAlpha2D(double alpha)
A set method to toggle the printing of legends in 1D and 2D histograms.
Definition: MonteCarloEngine.h:359
MonteCarlo::CalculateNormalization
std::string CalculateNormalization
< Flag for calculating the evidence.
Definition: MonteCarlo.h:170
MonteCarloEngine::PrintHistogram
void PrintHistogram(std::string &OutFile, Observable &it, const std::string OutputDir)
Overloaded from PrintHistogram(BCModelOutput&, const std::string) to print histogram for observables.
Definition: MonteCarloEngine.cpp:786
MonteCarlo::RunMinuitOnly
bool RunMinuitOnly
Flag for running Minuit only.
Definition: MonteCarlo.h:169
MonteCarloEngine::CreateHistogramMaps
void CreateHistogramMaps()
Creation of the histogram maps for Observables, Observable2D and Correlated Gaussian Observable.
Definition: MonteCarloEngine.cpp:121
MonteCarlo::myInputParser
InputParser myInputParser
An object of the InputParser class.
Definition: MonteCarlo.h:156
Model::getmissingModelParameters
std::vector< std::string > getmissingModelParameters()
Definition: Model.h:245
MonteCarloEngine::setHistogramBufferSize
void setHistogramBufferSize(unsigned int histogramBufferSize_i)
A set method to set the size of the buffer used by the histograms.
Definition: MonteCarloEngine.h:413
MonteCarlo::JobTag
std::string JobTag
String for the optional JobTag argument to be passes to the executable.
Definition: MonteCarlo.h:166
MonteCarloEngine::PrintCorrelationMatrixToLaTeX
void PrintCorrelationMatrixToLaTeX(const std::string filename)
This member generates the correlation matrix using BCH2D from the BAT libraries.
Definition: MonteCarloEngine.cpp:973
MonteCarlo::PrintAllMarginalized
bool PrintAllMarginalized
Flag for printing all Marginalized distributions to be passed on to the BAT routines.
Definition: MonteCarlo.h:172
MonteCarloEngine::getWriteLogLikelihoodChain
bool getWriteLogLikelihoodChain()
A get method to get the value of the bool the writing of Loglikelihood in the ROOT tree.
Definition: MonteCarloEngine.h:333
gslpp::log
complex log(const complex &z)
Definition: gslpp_complex.cpp:342
MonteCarlo::NIterationNormalizationMC
int NIterationNormalizationMC
< Number of iterations for MC integral done to compute normalization of a model
Definition: MonteCarlo.h:171
MonteCarloEngine::AddChains
void AddChains()
A method to add the observable values and weights to the chain information.
Definition: MonteCarloEngine.cpp:884
MonteCarloEngine::setPrintLogo
void setPrintLogo(bool print)
A set method to toggle the printing of logo on the histogram pdf.
Definition: MonteCarloEngine.h:298
MonteCarloEngine::setNBins1D
void setNBins1D(unsigned int nbins)
A set method to set the number of bins for a 1D histograms.
Definition: MonteCarloEngine.h:386
MonteCarloEngine::getMPIWorldSize
int getMPIWorldSize()
A get method to get the number of MPI world size.
Definition: MonteCarloEngine.h:422
MonteCarlo::Obs2D
std::vector< Observable2D > Obs2D
Vector for the Observables2D defined in SomeModel.conf.
Definition: MonteCarlo.h:160
InputParser::ReadParameters
std::string ReadParameters(const std::string filename_i, const int rank, std::vector< ModelParameter > &ModelPars, boost::ptr_vector< Observable > &Observables, std::vector< Observable2D > &Observables2D, std::vector< CorrelatedGaussianObservables > &CGO, std::vector< CorrelatedGaussianParameters > &CGP)
The member that parses the Observable2D directives from SomeModel.conf file.
Definition: InputParser.cpp:35
StandardModel::Init
virtual bool Init(const std::map< std::string, double > &DPars)
A method to initialize the model parameters.
Definition: StandardModel.cpp:185
MonteCarloEngine::setNBins2D
void setNBins2D(unsigned int nbins)
A set method to set the number of bins for a 2D histograms.
Definition: MonteCarloEngine.h:395
MonteCarloEngine::getchainedObsSize
int getchainedObsSize() const
A get method to access the number of Observable chains requested.
Definition: MonteCarloEngine.h:195
MonteCarlo::CGP
std::vector< CorrelatedGaussianParameters > CGP
Vector for the Correlated Gaussian Parameters defined in SomeModel.conf.
Definition: MonteCarlo.h:162
MonteCarlo::PrintTrianglePlot
bool PrintTrianglePlot
Flag for printing the triangle plot.
Definition: MonteCarlo.h:176
MonteCarloEngine::setDParsFromParameters
void setDParsFromParameters(const std::vector< double > &parameters, std::map< std::string, double > &DPars_i)
A method to rotate the diagonalized parameters to the original basis for correlated parameters.
Definition: MonteCarloEngine.cpp:261
MonteCarlo::OutFile
std::string OutFile
String for the name of the output root file without the .root extension.
Definition: MonteCarlo.h:165
MonteCarloEngine::getNumOfUsedEvents
int getNumOfUsedEvents() const
A get method to access the number of events used in the MCMC run.
Definition: MonteCarloEngine.h:233
MonteCarlo::writechains
bool writechains
Flag for writing the chains of paramters and observables during the MCMC run.
Definition: MonteCarlo.h:179
MonteCarlo::ParseMCMCConfig
void ParseMCMCConfig(std::string file)
Definition: MonteCarlo.cpp:478
MonteCarlo::PrintCorrelationMatrix
bool PrintCorrelationMatrix
Flag for printing the correlation matrix.
Definition: MonteCarlo.h:173
MonteCarloEngine::computeNormalizationLME
double computeNormalizationLME()
A method to calculate the normalization based on the Laplace-Metropolis Estimator.
Definition: MonteCarloEngine.cpp:1335
MonteCarlo::Obs
boost::ptr_vector< Observable > Obs
Vector for the observables defined in SomeModel.conf.
Definition: MonteCarlo.h:159
MonteCarloEngine::computeStatistics
std::string computeStatistics()
A get method to compute the mean and rms of the computed observables.
Definition: MonteCarloEngine.cpp:1012
InputParser::getModel
StandardModel * getModel() const
A get method to access the pointer to the object of the StandardModel class.
Definition: InputParser.h:109
MonteCarloEngine::setHistogram2DType
void setHistogram2DType(int type)
A set method to set the band fill type for 2D histograms.
Definition: MonteCarloEngine.h:377
MonteCarlo::ModPars
std::vector< ModelParameter > ModPars
Vector for the model parameters defined in SomeModel.conf.
Definition: MonteCarlo.h:158
MonteCarlo::WritePreRunData
bool WritePreRunData
Flag for printing the overview parameter plots.
Definition: MonteCarlo.h:177
MonteCarloEngine::writePreRunData
std::string writePreRunData()
A method to write in a text file the best fit parameters and the prerun scale factors.
Definition: MonteCarloEngine.cpp:1306
MonteCarloEngine::setNChains
void setNChains(unsigned int i)
A set method to fix the number of chains.
Definition: MonteCarloEngine.cpp:178
MonteCarlo::ReadPreRunData
void ReadPreRunData(std::string file)
Definition: MonteCarlo.cpp:701
MonteCarlo::CGO
std::vector< CorrelatedGaussianObservables > CGO
Vector for the Correlated Gaussian Observables defined in SomeModel.conf.
Definition: MonteCarlo.h:161
MonteCarlo::MCEngine
MonteCarloEngine MCEngine
An object of the MonteCarloEngine class.
Definition: MonteCarlo.h:157
MonteCarlo::PrintKnowledgeUpdatePlots
bool PrintKnowledgeUpdatePlots
Flag for printing plots to compare prior vs. posterior knowledge of parameters.
Definition: MonteCarlo.h:174
MonteCarloEngine::getHistoLog
std::string getHistoLog() const
A get method to access the stream that stores the log messages coming from histogram printing and che...
Definition: MonteCarloEngine.h:186
MonteCarloEngine::getHistograms2D
std::map< std::string, BCH2D > getHistograms2D() const
A get method to access the map of 2D histograms.
Definition: MonteCarloEngine.h:251
MonteCarlo::PrintParameterPlot
bool PrintParameterPlot
Flag for printing the overview parameter plots.
Definition: MonteCarlo.h:175
InputParser::addCustomObservableType
void addCustomObservableType(const std::string name, boost::function< Observable *() > funct)
Definition: InputParser.cpp:250
MonteCarloEngine::setNoLegend
void setNoLegend(bool legend)
A set method to toggle the printing of legends in 1D and 2D histograms.
Definition: MonteCarloEngine.h:307
MonteCarlo::FindModeWithMinuit
bool FindModeWithMinuit
Flag for using Minuit libraries.
Definition: MonteCarlo.h:168
MonteCarloEngine::computeNormalizationMC
std::vector< double > computeNormalizationMC(int NIterationNormalizationMC)
A method to calculate the normalization based on the Monte Carlo Simulation.
Definition: MonteCarloEngine.cpp:1319
StandardModel::Update
virtual bool Update(const std::map< std::string, double > &DPars)
The update method for StandardModel.
Definition: StandardModel.cpp:209
MonteCarloEngine::getHistograms1D
std::map< std::string, BCH1D > getHistograms1D() const
A get method to access the map of 1D histograms.
Definition: MonteCarloEngine.h:242
MonteCarloEngine::setSmooth
void setSmooth(int int_N)
A set method to set the number of smoothing passes for ROOT in 1D histograms.
Definition: MonteCarloEngine.h:368
MonteCarlo::ModelConf
std::string ModelConf
String for the name of the SomeModel.conf file.
Definition: MonteCarlo.h:163
MonteCarloEngine::setSignificants
void setSignificants(unsigned int significants_i)
A set method to set the number of significant digits in the output.
Definition: MonteCarloEngine.h:404
MonteCarloEngine::getWriteParametersChain
bool getWriteParametersChain()
A get method to get the value of the bool the writing of parameters in the ROOT tree.
Definition: MonteCarloEngine.h:350
MonteCarloEngine::setWriteParametersChain
void setWriteParametersChain(bool LL)
A set method to toggle the writing of parameters in the ROOT tree.
Definition: MonteCarloEngine.h:342
MonteCarlo::MCMCConf
std::string MCMCConf
String for the name of the MonteCarlo.conf file.
Definition: MonteCarlo.h:164
MonteCarloEngine::Initialize
void Initialize(StandardModel *Mod_i)
Initialization of the Monte Carlo Engine.
Definition: MonteCarloEngine.cpp:76
MonteCarloEngine::setWriteLogLikelihoodChain
void setWriteLogLikelihoodChain(bool LL)
A set method to toggle the writing of Loglikelihood in the ROOT tree.
Definition: MonteCarloEngine.h:325
MonteCarlo::ModelName
std::string ModelName
The name of the model.
Definition: MonteCarlo.h:155
QCD::getUnknownParameters
std::vector< std::string > getUnknownParameters()
A method to get the vector of the parameters that have been specified in the configuration file but n...
Definition: QCD.h:467
MonteCarloEngine::getNumOfDiscardedEvents
int getNumOfDiscardedEvents() const
A get method to access the number of events discarded due to failure to update model....
Definition: MonteCarloEngine.h:224
MonteCarloEngine::setPrintLoglikelihoodPlots
void setPrintLoglikelihoodPlots(bool plot)
A set method to toggle the printing of Parameters vs. Loglikelihood.
Definition: MonteCarloEngine.h:316