IndependentGaussianMH.C

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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
 
#include "IndependentGaussianMH.h"
#include "Normal.h"
#include "TruncatedNormal.h"
 
registerMooseObject("StochasticToolsApp", IndependentGaussianMH);
 
InputParameters
IndependentGaussianMH::validParams()
{
  InputParameters params = PMCMCBase::validParams();
  params.addClassDescription("Perform M-H MCMC sampling with independent Gaussian propoposals.");
  params.addRequiredParam<ReporterName>("seed_inputs",
                                        "Reporter with seed inputs values for the next proposals.");
  params.addRequiredParam<std::vector<Real>>("std_prop",
                                             "Standard deviations for making the next proposal.");
  return params;
}
 
IndependentGaussianMH::IndependentGaussianMH(const InputParameters & parameters)
  : PMCMCBase(parameters),
    _seed_inputs(getReporterValue<std::vector<Real>>("seed_inputs")),
    _std_prop(getParam<std::vector<Real>>("std_prop"))
{
  // Error check for sizes of proposal stds
  if (_std_prop.size() != _priors.size())
    paramError("std_prop",
               "The number of proposal stds, initial values, and priors should be the same.");
}
 
void
IndependentGaussianMH::proposeSamples()
{
  std::vector<Real> old_sample = (_t_step + 1 > decisionStep()) ? _seed_inputs : _initial_values;
  for (unsigned int j = 0; j < _num_parallel_proposals; ++j)
    for (unsigned int i = 0; i < _priors.size(); ++i)
    {
      if (_lower_bound)
        _new_samples[j][i] = TruncatedNormal::quantile(
            random(), old_sample[i], _std_prop[i], (*_lower_bound)[i], (*_upper_bound)[i]);
      else
        _new_samples[j][i] = Normal::quantile(random(), old_sample[i], _std_prop[i]);
    }
}