ActiveLearningMonteCarloSampler.h

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//* This file is part of the MOOSE framework
//* https://mooseframework.inl.gov
//*
//* 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 "Sampler.h"

class ActiveLearningMonteCarloSampler : public Sampler
{
public:
  static InputParameters validParams();

  ActiveLearningMonteCarloSampler(const InputParameters & parameters);

  virtual bool isAdaptiveSamplingCompleted() const override { return _is_sampling_completed; }

protected:
  virtual void sampleSetUp(const Sampler::SampleMode mode) override;
  virtual Real computeSample(dof_id_type row_index, dof_id_type col_index) override;

  std::vector<Distribution const *> _distributions;

  const std::vector<bool> & _flag_sample;

  bool _is_sampling_completed = false;

private:
  const int & _step;

  const unsigned int _num_batch;

  int _check_step;

  const int & _num_samples;

  int _retraining_steps = 0;

  std::vector<std::vector<Real>> _inputs_sto;

  std::vector<std::vector<Real>> _inputs_gp_fails;
};