NearestPointTrainer

Loops over and saves sample values for NearestPointSurrogate.

Overview

This trainer is meant to produce training data to be used with NearestPointSurrogate. The data saved (_sample_points) is an array of the sample points and the results from the full model:

_sample_points=[x1,1x1,2x1,Nx2,1x2,2x2,NxD,1xD,2xD,Ny1y2yN]\texttt{\_sample\_points} = \begin{bmatrix} x_{1,1} & x_{1,2} & \dots & x_{1,N} \\ x_{2,1} & x_{2,2} & \dots & x_{2,N} \\ \vdots & \vdots & \ddots & \vdots \\ x_{D,1} & x_{D,2} & \dots & x_{D,N} \\ y_1 & y_2 & \dots & y_N \end{bmatrix}

where xi,jx_{i,j} is the point from the sampler at column ii and sample jj, yjy_j is the result of the full model at sample jj, NN is the number of training samples, and DD is the number of sampler columns. NearestPointSurrogate then uses this array to find the closest point to the given input point and outputs the full model result.

Example Input File Syntax

A sampler is created to produce points for the training data:

[Samplers]
  [sample]
    type = CartesianProduct
    linear_space_items = '0 1 10
                          0 1 10
                          0 1 10'
  []
[]
(contrib/moose/modules/stochastic_tools/test/tests/surrogates/nearest_point/train.i)

The example full model is the GFunction vector postprocessor, see SobolStatistics for more details. This vector postprocessor takes in the sampler and evaluates the function at the training points.

[VectorPostprocessors]
  [values]
    type = GFunction
    sampler = sample
    q_vector = '0 0 0'
    execute_on = INITIAL
    outputs = none
  []
[]
(contrib/moose/modules/stochastic_tools/test/tests/surrogates/nearest_point/train.i)

The trainer then takes in the data from the sampler and the results from the vector postprocessor to create the _sample_points array:

[Trainers]
  [train]
    type = NearestPointTrainer
    sampler = sample
    response = values/g_values
  []
[]
(contrib/moose/modules/stochastic_tools/test/tests/surrogates/nearest_point/train.i)

We then output the training data to file:

[Outputs]
  [out]
    type = SurrogateTrainerOutput
    trainers = 'train'
    execute_on = FINAL
  []
[]
(contrib/moose/modules/stochastic_tools/test/tests/surrogates/nearest_point/train.i)

Input Parameters

  • responseReporter value of response results, can be vpp with / or sampler column with 'sampler/col_'.

    C++ Type:ReporterName

    Unit:(no unit assumed)

    Controllable:No

    Description:Reporter value of response results, can be vpp with / or sampler column with 'sampler/col_'.

  • samplerSampler used to create predictor and response data.

    C++ Type:SamplerName

    Unit:(no unit assumed)

    Controllable:No

    Description:Sampler used to create predictor and response data.

Required Parameters

  • converged_reporterReporter value used to determine if a sample's multiapp solve converged.

    C++ Type:ReporterName

    Unit:(no unit assumed)

    Controllable:No

    Description:Reporter value used to determine if a sample's multiapp solve converged.

  • cv_n_trials1Number of repeated trials of cross-validation to perform.

    Default:1

    C++ Type:unsigned int

    Unit:(no unit assumed)

    Controllable:No

    Description:Number of repeated trials of cross-validation to perform.

  • cv_seed4294967295Seed used to initialize random number generator for data splitting during cross validation.

    Default:4294967295

    C++ Type:unsigned int

    Unit:(no unit assumed)

    Controllable:No

    Description:Seed used to initialize random number generator for data splitting during cross validation.

  • cv_splits10Number of splits (k) to use in k-fold cross-validation.

    Default:10

    C++ Type:unsigned int

    Unit:(no unit assumed)

    Controllable:No

    Description:Number of splits (k) to use in k-fold cross-validation.

  • cv_surrogateName of Surrogate object used for model cross-validation.

    C++ Type:UserObjectName

    Unit:(no unit assumed)

    Controllable:No

    Description:Name of Surrogate object used for model cross-validation.

  • cv_typenoneCross-validation method to use for dataset. Options are 'none' or 'k_fold'.

    Default:none

    C++ Type:MooseEnum

    Unit:(no unit assumed)

    Options:none, k_fold

    Controllable:No

    Description:Cross-validation method to use for dataset. Options are 'none' or 'k_fold'.

  • execute_onTIMESTEP_ENDThe list of flag(s) indicating when this object should be executed. For a description of each flag, see https://mooseframework.inl.gov/source/interfaces/SetupInterface.html.

    Default:TIMESTEP_END

    C++ Type:ExecFlagEnum

    Unit:(no unit assumed)

    Options:NONE, INITIAL, LINEAR, NONLINEAR_CONVERGENCE, NONLINEAR, POSTCHECK, TIMESTEP_END, TIMESTEP_BEGIN, MULTIAPP_FIXED_POINT_END, MULTIAPP_FIXED_POINT_BEGIN, FINAL, CUSTOM

    Controllable:No

    Description:The list of flag(s) indicating when this object should be executed. For a description of each flag, see https://mooseframework.inl.gov/source/interfaces/SetupInterface.html.

  • filenameThe name of the file which will be associated with the saved/loaded data.

    C++ Type:FileName

    Unit:(no unit assumed)

    Controllable:No

    Description:The name of the file which will be associated with the saved/loaded data.

  • predictor_colsSampler columns used as the independent random variables, If 'predictors' and 'predictor_cols' are both empty, all sampler columns are used.

    C++ Type:std::vector<unsigned int>

    Unit:(no unit assumed)

    Controllable:No

    Description:Sampler columns used as the independent random variables, If 'predictors' and 'predictor_cols' are both empty, all sampler columns are used.

  • predictorsReporter values used as the independent random variables, If 'predictors' and 'predictor_cols' are both empty, all sampler columns are used.

    C++ Type:std::vector<ReporterName>

    Unit:(no unit assumed)

    Controllable:No

    Description:Reporter values used as the independent random variables, If 'predictors' and 'predictor_cols' are both empty, all sampler columns are used.

  • prop_getter_suffixAn optional suffix parameter that can be appended to any attempt to retrieve/get material properties. The suffix will be prepended with a '_' character.

    C++ Type:MaterialPropertyName

    Unit:(no unit assumed)

    Controllable:No

    Description:An optional suffix parameter that can be appended to any attempt to retrieve/get material properties. The suffix will be prepended with a '_' character.

  • response_typerealResponse data type.

    Default:real

    C++ Type:MooseEnum

    Unit:(no unit assumed)

    Options:real, vector_real

    Controllable:No

    Description:Response data type.

  • skip_unconverged_samplesFalseTrue to skip samples where the multiapp did not converge, 'stochastic_reporter' is required to do this.

    Default:False

    C++ Type:bool

    Unit:(no unit assumed)

    Controllable:No

    Description:True to skip samples where the multiapp did not converge, 'stochastic_reporter' is required to do this.

  • use_interpolated_stateFalseFor the old and older state use projected material properties interpolated at the quadrature points. To set up projection use the ProjectedStatefulMaterialStorageAction.

    Default:False

    C++ Type:bool

    Unit:(no unit assumed)

    Controllable:No

    Description:For the old and older state use projected material properties interpolated at the quadrature points. To set up projection use the ProjectedStatefulMaterialStorageAction.

Optional Parameters

  • allow_duplicate_execution_on_initialFalseIn the case where this UserObject is depended upon by an initial condition, allow it to be executed twice during the initial setup (once before the IC and again after mesh adaptivity (if applicable).

    Default:False

    C++ Type:bool

    Unit:(no unit assumed)

    Controllable:No

    Description:In the case where this UserObject is depended upon by an initial condition, allow it to be executed twice during the initial setup (once before the IC and again after mesh adaptivity (if applicable).

  • control_tagsAdds user-defined labels for accessing object parameters via control logic.

    C++ Type:std::vector<std::string>

    Unit:(no unit assumed)

    Controllable:No

    Description:Adds user-defined labels for accessing object parameters via control logic.

  • enableTrueSet the enabled status of the MooseObject.

    Default:True

    C++ Type:bool

    Unit:(no unit assumed)

    Controllable:Yes

    Description:Set the enabled status of the MooseObject.

  • execution_order_group0Execution order groups are executed in increasing order (e.g., the lowest number is executed first). Note that negative group numbers may be used to execute groups before the default (0) group. Please refer to the user object documentation for ordering of user object execution within a group.

    Default:0

    C++ Type:int

    Unit:(no unit assumed)

    Controllable:No

    Description:Execution order groups are executed in increasing order (e.g., the lowest number is executed first). Note that negative group numbers may be used to execute groups before the default (0) group. Please refer to the user object documentation for ordering of user object execution within a group.

  • force_postauxFalseForces the UserObject to be executed in POSTAUX

    Default:False

    C++ Type:bool

    Unit:(no unit assumed)

    Controllable:No

    Description:Forces the UserObject to be executed in POSTAUX

  • force_preauxFalseForces the UserObject to be executed in PREAUX

    Default:False

    C++ Type:bool

    Unit:(no unit assumed)

    Controllable:No

    Description:Forces the UserObject to be executed in PREAUX

  • force_preicFalseForces the UserObject to be executed in PREIC during initial setup

    Default:False

    C++ Type:bool

    Unit:(no unit assumed)

    Controllable:No

    Description:Forces the UserObject to be executed in PREIC during initial setup

  • use_displaced_meshFalseWhether or not this object should use the displaced mesh for computation. Note that in the case this is true but no displacements are provided in the Mesh block the undisplaced mesh will still be used.

    Default:False

    C++ Type:bool

    Unit:(no unit assumed)

    Controllable:No

    Description:Whether or not this object should use the displaced mesh for computation. Note that in the case this is true but no displacements are provided in the Mesh block the undisplaced mesh will still be used.

Advanced Parameters