Line data    Source code

       1             : //* This file is part of the MOOSE framework
       2             : //* https://mooseframework.inl.gov
       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             : #pragma once
      11             : 
      12             : #include "StochasticToolsApp.h"
      13             : #include "MooseObject.h"
      14             : #include "SamplerInterface.h"
      15             : #include "SurrogateModelInterface.h"
      16             : #include "RestartableModelInterface.h"
      17             : 
      18             : class SurrogateModel : public MooseObject,
      19             :                        public SamplerInterface,
      20             :                        public SurrogateModelInterface,
      21             :                        public RestartableModelInterface
      22             : {
      23             : public:
      24             :   static InputParameters validParams();
      25             :   SurrogateModel(const InputParameters & parameters);
      26             : 
      27             :   static MooseEnum defaultPredictorTypes() { return MooseEnum("real"); }
      28        2896 :   static MooseEnum defaultResponseTypes() { return MooseEnum("real vector_real"); }
      29             : 
      30             :   /**
      31             :    * Evaluate surrogate model given a row of parameters.
      32             :    */
      33           0 :   virtual Real evaluate(const std::vector<Real> & x) const
      34             :   {
      35           0 :     evaluateError(x, Real());
      36             :     return 0.0;
      37             :   };
      38             : 
      39             :   /// @{
      40             :   /**
      41             :    * Various evaluate methods that can be overriden
      42             :    */
      43           0 :   virtual void evaluate(const std::vector<Real> & x, std::vector<Real> & y) const
      44             :   {
      45           0 :     evaluateError(x, y);
      46             :   }
      47             :   ///@}
      48             : 
      49             :   /// @{
      50             :   /**
      51             :    * Evaluate methods that also return predicted standard deviation (see GaussianProcess.h)
      52             :    */
      53           0 :   virtual Real evaluate(const std::vector<Real> & x, Real & std) const
      54             :   {
      55           0 :     evaluateError(x, std, true);
      56             :     return 0.0;
      57             :   }
      58             :   virtual void
      59           0 :   evaluate(const std::vector<Real> & x, std::vector<Real> & y, std::vector<Real> & /*std*/) const
      60             :   {
      61           0 :     evaluateError(x, y, true);
      62             :   }
      63             :   ///@}
      64             : 
      65             : private:
      66             :   template <typename P, typename R>
      67             :   void evaluateError(P x, R y, bool with_std = false) const;
      68             : };
      69             : 
      70             : template <typename P, typename R>
      71             : void
      72           0 : SurrogateModel::evaluateError(P /*x*/, R /*y*/, bool with_std) const
      73             : {
      74           0 :   std::stringstream ss;
      75           0 :   ss << "Evaluate method";
      76           0 :   if (with_std)
      77           0 :     ss << " (including standard deviation computation)";
      78           0 :   ss << " with predictor type " << MooseUtils::prettyCppType<P>();
      79           0 :   ss << " and response type " << MooseUtils::prettyCppType<R>();
      80           0 :   ss << " has not been implemented.";
      81           0 :   mooseError(ss.str());
      82           0 : }