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

#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;
};