BayesianActiveLearner.h

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//* This file is part of the MOOSE framework
//* https://www.mooseframework.org
//*
//* All rights reserved, see COPYRIGHT for full restrictions
//* https://github.com/idaholab/moose/blob/master/COPYRIGHT
//*
//* Licensed under LGPL 2.1, please see LICENSE for details
//* https://www.gnu.org/licenses/lgpl-2.1.html
#ifdef MOOSE_LIBTORCH_ENABLED
 
#pragma once
 
#include "GenericActiveLearner.h"
#include "BayesianActiveLearningSampler.h"
#include "LikelihoodFunctionBase.h"
#include "LikelihoodInterface.h"
 
class BayesianActiveLearner : public GenericActiveLearnerTempl<BayesianActiveLearningSampler>,
                              public LikelihoodInterface
 
{
public:
  static InputParameters validParams();
 
  BayesianActiveLearner(const InputParameters & parameters);
 
protected:
  virtual void setupGPData(const std::vector<Real> & data_out,
                           const DenseMatrix<Real> & data_in) override;
 
  virtual Real computeConvergenceValue() override;
 
  virtual void evaluateGPTest() override;
 
  virtual void includeAdditionalInputs() override;
 
private:
  void computeLogLikelihood(const std::vector<Real> & data_out);
 
  const std::vector<Real> & _new_var_samples;
 
  const Distribution * _var_prior;
 
  const std::vector<Real> & _var_test;
 
  Real & _noise;
 
  std::vector<const LikelihoodFunctionBase *> _likelihoods;
 
  dof_id_type _num_confg_values;
 
  dof_id_type _num_confg_params;
 
  std::vector<Real> _log_likelihood;
 
  unsigned int _n_dim_plus_var;
};
 
#endif