25 #ifndef UQ_MULTI_LEVEL_SAMPLING_H 
   26 #define UQ_MULTI_LEVEL_SAMPLING_H 
   28 #define ML_NEW_CODE_2009_12_29 
   30 #include <queso/MLSamplingOptions.h> 
   31 #include <queso/MetropolisHastingsSG.h> 
   32 #include <queso/FiniteDistribution.h> 
   33 #include <queso/VectorRV.h> 
   34 #include <queso/GenericVectorRV.h> 
   35 #include <queso/VectorSpace.h> 
   36 #include <queso/MarkovChainPositionData.h> 
   37 #include <queso/ScalarFunctionSynchronizer.h> 
   38 #include <queso/SequenceOfVectors.h> 
   39 #include <queso/ArrayOfSequences.h> 
   46 #define ML_CHECKPOINT_FIXED_AMOUNT_OF_DATA 6 
   56 struct BIP_routine_struct {
 
   57   const BaseEnvironment* env;
 
   58   unsigned int                  currLevel;
 
   61 void BIP_routine(glp_tree *tree, 
void *info);
 
   76 template <
class P_V = GslVector>
 
   85 template <
class P_V = GslVector>
 
  121 template <
class P_V = GslVector, 
class P_M = GslMatrix>
 
  202   void   print           (std::ostream& os) 
const;
 
  236                                         unsigned int&                                   unifiedRequestedNumSamples,         
 
  246                                         unsigned int&                                   unifiedRequestedNumSamples);        
 
  260                                         unsigned int&                                   indexOfFirstWeight,                 
 
  261                                         unsigned int&                                   indexOfLastWeight);                 
 
  270                                         double                                          failedExponent,                     
 
  271                                         double&                                         currExponent,                       
 
  280                                         P_M&                                            unifiedCovMatrix);                  
 
  288                                         std::vector<unsigned int>&                      unifiedIndexCountersAtProc0Only,    
 
  289                                         std::vector<double>&                            unifiedWeightStdVectorAtProc0Only); 
 
  296                                         unsigned int                                    indexOfFirstWeight,                 
 
  297                                         unsigned int                                    indexOfLastWeight,                  
 
  298                                         const std::vector<unsigned int>&                unifiedIndexCountersAtProc0Only,    
 
  299                                         bool&                                           useBalancedChains,                  
 
  300                                         std::vector<ExchangeInfoStruct>&              exchangeStdVec);                    
 
  308                                         unsigned int                                    indexOfFirstWeight,                 
 
  309                                         unsigned int                                    indexOfLastWeight,                  
 
  310                                         const std::vector<unsigned int>&                unifiedIndexCountersAtProc0Only,    
 
  318                                         std::vector<ExchangeInfoStruct>&              exchangeStdVec,                     
 
  338                                         unsigned int                                    indexOfFirstWeight,                 
 
  339                                         unsigned int                                    indexOfLastWeight,                  
 
  340                                         const std::vector<double>&                      unifiedWeightStdVectorAtProc0Only,  
 
  345                                         P_M&                                            unifiedCovMatrix,                   
 
  353                                         const P_M&                                      unifiedCovMatrix,                   
 
  355                                         bool                                            useBalancedChains,                  
 
  357                                         unsigned int                                    indexOfFirstWeight,                 
 
  365                                         double&                                         cumulativeRawChainRunTime,          
 
  366                                         unsigned int&                                   cumulativeRawChainRejections,       
 
  376                                         unsigned int                                    unifiedRequestedNumSamples,         
 
  377                                         unsigned int                                    cumulativeRawChainRejections,       
 
  381                                         unsigned int&                                   unifiedNumberOfRejections);         
 
  386                                         const std::vector<double>&                      unifiedWeightStdVectorAtProc0Only,  
 
  387                                         std::vector<unsigned int>&                      unifiedIndexCountersAtProc0Only);   
 
  392                                         unsigned int                                    indexOfFirstWeight,                 
 
  393                                         unsigned int                                    indexOfLastWeight,                  
 
  394                                         const std::vector<unsigned int>&                unifiedIndexCountersAtProc0Only,    
 
  395                                         std::vector<ExchangeInfoStruct>&              exchangeStdVec);                    
 
  405                                          std::vector<ExchangeInfoStruct>&              exchangeStdVec,                     
 
  411                                         unsigned int                                    indexOfLastWeight,                  
 
  412                                         const std::vector<unsigned int>&                unifiedIndexCountersAtProc0Only,    
 
  418                                         const P_M&                                      unifiedCovMatrix,                   
 
  422                                         double&                                         cumulativeRunTime,                  
 
  423                                         unsigned int&                                   cumulativeRejections,               
 
  430                                           const P_M&                                      unifiedCovMatrix,                   
 
  433                                           unsigned int                                    indexOfFirstWeight,                 
 
  440                                           double&                                         cumulativeRunTime,                  
 
  441                                           unsigned int&                                   cumulativeRejections,               
 
  445 #ifdef QUESO_HAS_GLPK 
  448   void   solveBIP_proc0                (std::vector<ExchangeInfoStruct>&              exchangeStdVec);                    
 
  454                                         std::vector<ExchangeInfoStruct>&              exchangeStdVec);                    
 
  463                                         const std::vector<ExchangeInfoStruct>&        exchangeStdVec,                     
 
  464                                         const std::vector<unsigned int>&                finalNumChainsPerNode,              
 
  465                                         const std::vector<unsigned int>&                finalNumPositionsPerNode,           
 
  507 #endif // UQ_MULTI_LEVEL_SAMPLING_H 
double logEvidence() const 
Method to calculate the logarithm of the evidence. 
 
void generateSequence_Step01_inter0(const MLSamplingLevelOptions *currOptions, unsigned int &unifiedRequestedNumSamples)
Reads options for the ML algorithm (Step 01 from ML algorithm). 
 
void generateSequence_Step10_all(MLSamplingLevelOptions &currOptions, const P_M &unifiedCovMatrix, const GenericVectorRV< P_V, P_M > &currRv, bool useBalancedChains, const UnbalancedLinkedChainsPerNodeStruct &unbalancedLinkControl, unsigned int indexOfFirstWeight, const SequenceOfVectors< P_V, P_M > &prevChain, double prevExponent, double currExponent, const ScalarSequence< double > &prevLogLikelihoodValues, const ScalarSequence< double > &prevLogTargetValues, const BalancedLinkedChainsPerNodeStruct< P_V > &balancedLinkControl, SequenceOfVectors< P_V, P_M > &currChain, double &cumulativeRawChainRunTime, unsigned int &cumulativeRawChainRejections, ScalarSequence< double > *currLogLikelihoodValues, ScalarSequence< double > *currLogTargetValues)
Samples the vector RV of current level (Step 10 from ML algorithm). 
 
const BaseScalarFunction< P_V, P_M > & m_likelihoodFunction
Likelihood function. 
 
VectorSet< P_V, P_M > * m_targetDomain
Domain of the target PDF: intersection of the domains of the prior PDf and likelihood function...
 
const VectorSpace< P_V, P_M > & m_vectorSpace
Vector space. 
 
unsigned int numberOfPositions
 
MLSamplingOptions m_options
Options for the ML algorithm. 
 
unsigned int originalIndexOfInitialPosition
 
unsigned int m_currStep
Curret step. 
 
double meanLogLikelihood() const 
Method to calculate the mean of the logarithm of the likelihood. 
 
double m_debugExponent
Exponent for debugging. 
 
void generateSequence_Step03_inter0(const MLSamplingLevelOptions *currOptions, const ScalarSequence< double > &prevLogLikelihoodValues, double prevExponent, double failedExponent, double &currExponent, ScalarSequence< double > &weightSequence)
Computes currExponent and sequence of weights for current level and update 'm_logEvidenceFactors' (St...
 
void generateSequence_Step05_inter0(unsigned int unifiedRequestedNumSamples, const ScalarSequence< double > &weightSequence, std::vector< unsigned int > &unifiedIndexCountersAtProc0Only, std::vector< double > &unifiedWeightStdVectorAtProc0Only)
Creates unified finite distribution for current level (Step 05 from ML algorithm). 
 
This (virtual) class sets up the environment underlying the use of the QUESO library by an executable...
 
void generateBalLinkedChains_all(MLSamplingLevelOptions &inputOptions, const P_M &unifiedCovMatrix, const GenericVectorRV< P_V, P_M > &rv, const BalancedLinkedChainsPerNodeStruct< P_V > &balancedLinkControl, SequenceOfVectors< P_V, P_M > &workingChain, double &cumulativeRunTime, unsigned int &cumulativeRejections, ScalarSequence< double > *currLogLikelihoodValues, ScalarSequence< double > *currLogTargetValues)
 
unsigned int numberOfPositions
 
unsigned int m_numDisabledParameters
 
int originalNodeOfInitialPosition
 
void prepareUnbLinkedChains_inter0(unsigned int indexOfFirstWeight, unsigned int indexOfLastWeight, const std::vector< unsigned int > &unifiedIndexCountersAtProc0Only, UnbalancedLinkedChainsPerNodeStruct &unbalancedLinkControl)
 
bool decideOnBalancedChains_all(const MLSamplingLevelOptions *currOptions, unsigned int indexOfFirstWeight, unsigned int indexOfLastWeight, const std::vector< unsigned int > &unifiedIndexCountersAtProc0Only, std::vector< ExchangeInfoStruct > &exchangeStdVec)
 
void sampleIndexes_proc0(unsigned int unifiedRequestedNumSamples, const std::vector< double > &unifiedWeightStdVectorAtProc0Only, std::vector< unsigned int > &unifiedIndexCountersAtProc0Only)
 
const BaseVectorRV< P_V, P_M > & m_priorRv
Prior RV. 
 
This class provides options for the Multilevel sequence generator if no input file is available...
 
std::vector< bool > m_parameterEnabledStatus
 
const BaseEnvironment & m_env
Queso enviroment. 
 
void print(std::ostream &os) const 
TODO: Prints the sequence. 
 
int finalNodeOfInitialPosition
 
void generateSequence_Step06_all(const MLSamplingLevelOptions *currOptions, unsigned int indexOfFirstWeight, unsigned int indexOfLastWeight, const std::vector< unsigned int > &unifiedIndexCountersAtProc0Only, bool &useBalancedChains, std::vector< ExchangeInfoStruct > &exchangeStdVec)
Decides on wheter or not to use balanced chains (Step 06 from ML algorithm). 
 
void generateSequence_Step04_inter0(const SequenceOfVectors< P_V, P_M > &prevChain, const ScalarSequence< double > &weightSequence, P_M &unifiedCovMatrix)
Creates covariance matrix for current level (Step 04 from ML algorithm). 
 
unsigned int initialPositionIndexInPreviousChain
 
std::vector< UnbalancedLinkedChainControlStruct > unbLinkedChains
 
This class provides options for each level of the Multilevel sequence generator if no input file is a...
 
void generateSequence_Step11_inter0(const MLSamplingLevelOptions *currOptions, unsigned int unifiedRequestedNumSamples, unsigned int cumulativeRawChainRejections, SequenceOfVectors< P_V, P_M > &currChain, ScalarSequence< double > &currLogLikelihoodValues, ScalarSequence< double > &currLogTargetValues, unsigned int &unifiedNumberOfRejections)
Filters chain (Step 11 from ML algorithm). 
 
double eig() const 
Calculates the expected information gain value, EIG. 
 
void generateSequence(BaseVectorSequence< P_V, P_M > &workingChain, ScalarSequence< double > *workingLogLikelihoodValues, ScalarSequence< double > *workingLogTargetValues)
Method to generate the chain. 
 
void generateSequence_Step02_inter0(const MLSamplingLevelOptions *currOptions, SequenceOfVectors< P_V, P_M > &currChain, ScalarSequence< double > &currLogLikelihoodValues, ScalarSequence< double > &currLogTargetValues, SequenceOfVectors< P_V, P_M > &prevChain, ScalarSequence< double > &prevLogLikelihoodValues, ScalarSequence< double > &prevLogTargetValues, unsigned int &indexOfFirstWeight, unsigned int &indexOfLastWeight)
Saves chain and corresponding target pdf values from previous level (Step 02 from ML algorithm)...
 
unsigned int m_currLevel
Current level. 
 
void generateSequence_Step07_inter0(bool useBalancedChains, unsigned int indexOfFirstWeight, unsigned int indexOfLastWeight, const std::vector< unsigned int > &unifiedIndexCountersAtProc0Only, UnbalancedLinkedChainsPerNodeStruct &unbalancedLinkControl, const MLSamplingLevelOptions *currOptions, const SequenceOfVectors< P_V, P_M > &prevChain, double prevExponent, double currExponent, const ScalarSequence< double > &prevLogLikelihoodValues, const ScalarSequence< double > &prevLogTargetValues, std::vector< ExchangeInfoStruct > &exchangeStdVec, BalancedLinkedChainsPerNodeStruct< P_V > &balancedLinkControl)
Plans for number of linked chains for each node so that all nodes generate the closest possible to th...
 
unsigned int numberOfPositions
 
double initialLogLikelihood
 
void restartML(double &currExponent, double &currEta, SequenceOfVectors< P_V, P_M > &currChain, ScalarSequence< double > &currLogLikelihoodValues, ScalarSequence< double > &currLogTargetValues)
Restarts ML algorithm. 
 
std::vector< BalancedLinkedChainControlStruct< P_V > > balLinkedChains
 
void mpiExchangePositions_inter0(const SequenceOfVectors< P_V, P_M > &prevChain, double prevExponent, double currExponent, const ScalarSequence< double > &prevLogLikelihoodValues, const ScalarSequence< double > &prevLogTargetValues, const std::vector< ExchangeInfoStruct > &exchangeStdVec, const std::vector< unsigned int > &finalNumChainsPerNode, const std::vector< unsigned int > &finalNumPositionsPerNode, BalancedLinkedChainsPerNodeStruct< P_V > &balancedLinkControl)
 
void checkpointML(double currExponent, double currEta, const SequenceOfVectors< P_V, P_M > &currChain, const ScalarSequence< double > &currLogLikelihoodValues, const ScalarSequence< double > &currLogTargetValues)
Writes checkpoint data for the ML method. 
 
MLSampling(const char *prefix, const BaseVectorRV< P_V, P_M > &priorRv, const BaseScalarFunction< P_V, P_M > &likelihoodFunction)
Constructor. 
 
friend std::ostream & operator<<(std::ostream &os, const MLSampling< P_V, P_M > &obj)
 
void justBalance_proc0(const MLSamplingLevelOptions *currOptions, std::vector< ExchangeInfoStruct > &exchangeStdVec)
 
double m_meanLogLikelihood
 
A templated class that represents a Multilevel generator of samples. 
 
void prepareBalLinkedChains_inter0(const MLSamplingLevelOptions *currOptions, const SequenceOfVectors< P_V, P_M > &prevChain, double prevExponent, double currExponent, const ScalarSequence< double > &prevLogLikelihoodValues, const ScalarSequence< double > &prevLogTargetValues, std::vector< ExchangeInfoStruct > &exchangeStdVec, BalancedLinkedChainsPerNodeStruct< P_V > &balancedLinkControl)
 
void generateSequence_Step09_all(const SequenceOfVectors< P_V, P_M > &prevChain, double prevExponent, double currExponent, const ScalarSequence< double > &prevLogLikelihoodValues, const ScalarSequence< double > &prevLogTargetValues, unsigned int indexOfFirstWeight, unsigned int indexOfLastWeight, const std::vector< double > &unifiedWeightStdVectorAtProc0Only, const ScalarSequence< double > &weightSequence, double prevEta, const GenericVectorRV< P_V, P_M > &currRv, MLSamplingLevelOptions *currOptions, P_M &unifiedCovMatrix, double &currEta)
Scales the unified covariance matrix until min <= rejection rate <= max (Step 09 from ML algorithm)...
 
std::vector< double > m_logEvidenceFactors
 
void generateSequence_Level0_all(const MLSamplingLevelOptions &currOptions, unsigned int &unifiedRequestedNumSamples, SequenceOfVectors< P_V, P_M > &currChain, ScalarSequence< double > &currLogLikelihoodValues, ScalarSequence< double > &currLogTargetValues)
Generates the sequence at the level 0. 
 
void generateUnbLinkedChains_all(MLSamplingLevelOptions &inputOptions, const P_M &unifiedCovMatrix, const GenericVectorRV< P_V, P_M > &rv, const UnbalancedLinkedChainsPerNodeStruct &unbalancedLinkControl, unsigned int indexOfFirstWeight, const SequenceOfVectors< P_V, P_M > &prevChain, double prevExponent, double currExponent, const ScalarSequence< double > &prevLogLikelihoodValues, const ScalarSequence< double > &prevLogTargetValues, SequenceOfVectors< P_V, P_M > &workingChain, double &cumulativeRunTime, unsigned int &cumulativeRejections, ScalarSequence< double > *currLogLikelihoodValues, ScalarSequence< double > *currLogTargetValues)
 
void generateSequence_Step08_all(BayesianJointPdf< P_V, P_M > &currPdf, GenericVectorRV< P_V, P_M > &currRv)
Creates a vector RV for current level (Step 08 from ML algorithm).