Line data    Source code

       1             : //* This file is part of the MOOSE framework
       2             : //* https://mooseframework.inl.gov
       3             : //*
       4             : //* All rights reserved, see COPYRIGHT for full restrictions
       5             : //* https://github.com/idaholab/moose/blob/master/COPYRIGHT
       6             : //*
       7             : //* Licensed under LGPL 2.1, please see LICENSE for details
       8             : //* https://www.gnu.org/licenses/lgpl-2.1.html
       9             : 
      10             : #pragma once
      11             : 
      12             : #include "Sampler.h"
      13             : #include "TransientInterface.h"
      14             : #include "Distribution.h"
      15             : 
      16             : /**
      17             :  * A base class used to perform Parallel Markov Chain Monte Carlo (MCMC) sampling
      18             :  */
      19             : class PMCMCBase : public Sampler, public TransientInterface
      20             : {
      21             : public:
      22             :   static InputParameters validParams();
      23             : 
      24             :   PMCMCBase(const InputParameters & parameters);
      25             : 
      26             :   /**
      27             :    * Return the number of configuration parameters.
      28             :    */
      29             :   dof_id_type getNumberOfConfigValues() const { return _confg_values[0].size(); }
      30             : 
      31             :   /**
      32             :    * Return the number of configuration parameters.
      33             :    */
      34             :   dof_id_type getNumberOfConfigParams() const { return _confg_values.size(); }
      35             : 
      36             :   /**
      37             :    * Return the number of parallel proposals.
      38             :    */
      39         124 :   dof_id_type getNumParallelProposals() const { return _num_parallel_proposals; }
      40             : 
      41             :   /**
      42             :    * Return the random numbers to facilitate decision making in reporters
      43             :    */
      44             :   const std::vector<Real> & getRandomNumbers() const;
      45             : 
      46             :   /**
      47             :    * Return the proposed variance samples to facilitate decision making in reporters
      48             :    */
      49             :   const std::vector<Real> & getVarSamples() const;
      50             : 
      51             :   /**
      52             :    * Return the proposed samples to facilitate decision making in reporters.
      53             :    * In MCMC schemes, there is a decision-making step after evaluating the
      54             :    * computational model on whether or not to accept the proposed samples.
      55             :    * To facilitate this decision-making, which happens in the Reporter, we
      56             :    * have to provide it the proposed samples.
      57             :    */
      58             :   const std::vector<std::vector<Real>> & getSamples() const;
      59             : 
      60             :   /**
      61             :    * Return the priors to facilitate decision making in reporters
      62             :    */
      63             :   const std::vector<const Distribution *> getPriors() const;
      64             : 
      65             :   /**
      66             :    * Return the prior over variance to facilitate decision making in reporters
      67             :    */
      68             :   const Distribution * getVarPrior() const;
      69             : 
      70             :   /**
      71             :    * Return the step after which decision making can begin
      72             :    */
      73         200 :   virtual int decisionStep() const { return 1; }
      74             : 
      75             : protected:
      76             :   /**
      77             :    * Fill in the _new_samples vector of vectors (happens within sampleSetUp)
      78             :    * @param seed_value The seed for the random number generator
      79             :    */
      80             :   virtual void proposeSamples();
      81             : 
      82             :   // See Sampler.h for description
      83             :   virtual void executeSetUp() override;
      84             : 
      85             :   // See Sampler.h for description
      86             :   virtual Real computeSample(dof_id_type row_index, dof_id_type col_index) override;
      87             : 
      88             :   /**
      89             :    * Sample a random number between 0 and 1
      90             :    * @param upper_bound The upper bound provided
      91             :    * @return The required index
      92             :    */
      93             :   Real random();
      94             : 
      95             :   /**
      96             :    * Sample a random index excluding a specified index
      97             :    * @param upper_bound The upper bound provided
      98             :    * @return The required index
      99             :    */
     100             :   unsigned int randomIndex(const unsigned int & upper_bound, const unsigned int & exclude);
     101             : 
     102             :   /**
     103             :    * Sample two random indices without repitition excluding a specified index
     104             :    * @param upper_bound The upper bound provided
     105             :    * @param exclude The index to be excluded from sampling
     106             :    * @return Pair of required indices
     107             :    */
     108             :   std::pair<unsigned int, unsigned int> randomIndexPair(const unsigned int & upper_bound,
     109             :                                                         const unsigned int & exclude);
     110             : 
     111             :   /// Number of parallel proposals to be made and subApps to be executed
     112             :   const unsigned int _num_parallel_proposals;
     113             : 
     114             :   /// Storage for prior distribution objects to be utilized
     115             :   std::vector<const Distribution *> _priors;
     116             : 
     117             :   /// Storage for prior distribution object of the variance to be utilized
     118             :   const Distribution * _var_prior;
     119             : 
     120             :   /// Lower bounds for making the next proposal
     121             :   const std::vector<Real> * _lower_bound;
     122             : 
     123             :   /// Upper bounds for making the next proposal
     124             :   const std::vector<Real> * _upper_bound;
     125             : 
     126             :   /// Upper bound for variance for making the next proposal
     127             :   const Real & _variance_bound;
     128             : 
     129             :   /// Initial values of the input params to get the MCMC scheme started
     130             :   const std::vector<Real> & _initial_values;
     131             : 
     132             :   /// Vectors of new proposed samples
     133             :   std::vector<std::vector<Real>> _new_samples;
     134             : 
     135             :   /// Vector of new proposed variance samples
     136             :   std::vector<Real> _new_var_samples;
     137             : 
     138             :   /// Vector of random numbers for decision making
     139             :   std::vector<Real> _rnd_vec;
     140             : 
     141             : private:
     142             :   /**
     143             :    * Generates combinations of the new samples with the experimental configurations
     144             :    */
     145             :   void combineWithExperimentalConfig();
     146             : 
     147             :   /// Initialize a certain number of random seeds. Change from the default only if you have to.
     148             :   const unsigned int _num_random_seeds;
     149             : 
     150             :   /// Generator index when requesting random numbers
     151             :   unsigned int _seed_index;
     152             : 
     153             :   /// Running index for the random number generators
     154             :   std::size_t _rand_index;
     155             : 
     156             :   /// Configuration values
     157             :   std::vector<std::vector<Real>> _confg_values;
     158             : 
     159             :   /// Vectors of new proposed samples combined with the experimental configuration values
     160             :   std::vector<std::vector<Real>> _new_samples_confg;
     161             : };