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 "ReporterInterface.h"
      14             : 
      15             : /**
      16             :  * A class used to perform Parallel Subset Simulation Sampling
      17             :  */
      18             : class ParallelSubsetSimulation : public Sampler
      19             : {
      20             : public:
      21             :   static InputParameters validParams();
      22             : 
      23             :   ParallelSubsetSimulation(const InputParameters & parameters);
      24             : 
      25             :   /// Access the number samples per subset
      26             :   const unsigned int & getNumSamplesSub() const;
      27             : 
      28             :   /// Access use absolute value bool
      29             :   const bool & getUseAbsoluteValue() const;
      30             : 
      31             :   /// Access the subset probability
      32             :   const Real & getSubsetProbability() const;
      33             : 
      34             :   /**
      35             :    * Returns true if the adaptive sampling is completed
      36             :    */
      37          96 :   virtual bool isAdaptiveSamplingCompleted() const override { return _is_sampling_completed; }
      38             : 
      39             : protected:
      40             :   virtual void sampleSetUp(const Sampler::SampleMode mode) override;
      41             :   virtual Real computeSample(dof_id_type row_index, dof_id_type col_index) override;
      42             : 
      43             :   /// Number of samples per subset
      44             :   const unsigned int & _num_samplessub;
      45             : 
      46             :   /// Number of subsets
      47             :   const unsigned int & _num_subsets;
      48             : 
      49             :   /// Absolute value of the model result. Use this when failure is defined as a non-exceedance rather than an exceedance.
      50             :   const bool & _use_absolute_value;
      51             : 
      52             :   /// The subset conditional failure probability
      53             :   const Real & _subset_probability;
      54             : 
      55             :   /// Initialize a certain number of random seeds. Change from the default only if you have to.
      56             :   const unsigned int & _num_random_seeds;
      57             : 
      58             :   /// Reporter value containing calculated outputs
      59             :   const std::vector<Real> & _outputs;
      60             : 
      61             :   /// Reporter value containing input values from decision reporter
      62             :   const std::vector<std::vector<Real>> & _inputs;
      63             : 
      64             :   /// Track the current step of the main App
      65             :   const int & _step;
      66             : 
      67             :   /// Maximum length of markov chains based on subset probability
      68             :   const unsigned int _count_max;
      69             : 
      70             :   /// Ensure that the MCMC algorithm proceeds in a sequential fashion
      71             :   int _check_step;
      72             : 
      73             :   /// Track the current subset index
      74             :   unsigned int _subset;
      75             : 
      76             :   /// Storage for distribution objects to be utilized
      77             :   std::vector<Distribution const *> _distributions;
      78             : 
      79             :   /// True if the sampling is completed
      80             :   bool _is_sampling_completed;
      81             : 
      82             : private:
      83             :   /// Storage for the previously accepted sample inputs across all the subsets
      84             :   std::vector<std::vector<Real>> _inputs_sto;
      85             : 
      86             :   /// Storage for previously accepted sample outputs across all the subsets
      87             :   std::vector<Real> _outputs_sto;
      88             : 
      89             :   /// Store the sorted input samples according to their corresponding outputs
      90             :   std::vector<std::vector<Real>> _inputs_sorted;
      91             : 
      92             :   /// Mean input vector for the next proposed sample inputs across several processors
      93             :   std::vector<std::vector<Real>> _markov_seed;
      94             : };