Line data    Source code

       1             : //* This file is part of the MOOSE framework
       2             : //* https://www.mooseframework.org
       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             : #include "ProbabilityofImprovement.h"
      11             : #include "Normal.h"
      12             : #include <cmath>
      13             : 
      14             : registerMooseObject("StochasticToolsApp", ProbabilityofImprovement);
      15             : 
      16             : InputParameters
      17           6 : ProbabilityofImprovement::validParams()
      18             : {
      19           6 :   InputParameters params = ParallelAcquisitionFunctionBase::validParams();
      20           6 :   params.addClassDescription("Probability of improvement acquisition function.");
      21           6 :   return params;
      22           0 : }
      23             : 
      24           3 : ProbabilityofImprovement::ProbabilityofImprovement(const InputParameters & parameters)
      25           3 :   : ParallelAcquisitionFunctionBase(parameters)
      26             : {
      27           3 : }
      28             : 
      29             : void
      30           3 : ProbabilityofImprovement::computeAcquisitionInternal(
      31             :     std::vector<Real> & acq,
      32             :     const std::vector<Real> & gp_mean,
      33             :     const std::vector<Real> & gp_std,
      34             :     const std::vector<std::vector<Real>> & /*test_inputs*/,
      35             :     const std::vector<std::vector<Real>> & /*train_inputs*/,
      36             :     const std::vector<Real> & generic) const
      37             : {
      38             :   auto maxIt = std::max_element(generic.begin(), generic.end());
      39        3003 :   for (unsigned int i = 0; i < gp_mean.size(); ++i)
      40        3000 :     acq[i] = Normal::cdf(gp_mean[i] - *maxIt, 0.0, gp_std[i]);
      41           3 : }