A class used to perform Monte Carlo sampling for performing Morris sensitivity analysis. More...

#include <MorrisSampler.h>

Inheritance diagram for MorrisSampler:

Public Types
enum	SampleMode

typedef DataFileName	DataFileParameterType

Public Member Functions
	MorrisSampler (const InputParameters &parameters)

std::vector< Real >	getNextLocalRow ()

dof_id_type	getNumberOfRows () const

dof_id_type	getNumberOfCols () const

dof_id_type	getNumberOfLocalRows () const

const LocalRankConfig &	getRankConfig (bool batch_mode) const

virtual bool	isAdaptiveSamplingCompleted () const

libMesh::Parallel::Communicator &	getLocalComm ()

virtual bool	enabled () const

std::shared_ptr< MooseObject >	getSharedPtr ()

std::shared_ptr< const MooseObject >	getSharedPtr () const

bool	isKokkosObject () const

MooseApp &	getMooseApp () const

const std::string &	type () const

const std::string &	name () const

std::string	typeAndName () const

MooseObjectParameterName	uniqueParameterName (const std::string &parameter_name) const

MooseObjectName	uniqueName () const

const InputParameters &	parameters () const

const hit::Node *	getHitNode () const

bool	hasBase () const

const std::string &	getBase () const

const T &	getParam (const std::string &name) const

std::vector< std::pair< T1, T2 > >	getParam (const std::string &param1, const std::string &param2) const

const T *	queryParam (const std::string &name) const

const T &	getRenamedParam (const std::string &old_name, const std::string &new_name) const

T	getCheckedPointerParam (const std::string &name, const std::string &error_string="") const

bool	isParamValid (const std::string &name) const

bool	isParamSetByUser (const std::string &name) const

void	connectControllableParams (const std::string &parameter, const std::string &object_type, const std::string &object_name, const std::string &object_parameter) const

void	paramError (const std::string &param, Args... args) const

void	paramWarning (const std::string &param, Args... args) const

void	paramWarning (const std::string &param, Args... args) const

void	paramInfo (const std::string &param, Args... args) const

std::string	messagePrefix (const bool hit_prefix=true) const

std::string	errorPrefix (const std::string &) const

void	mooseError (Args &&... args) const

void	mooseDocumentedError (const std::string &repo_name, const unsigned int issue_num, Args &&... args) const

void	mooseErrorNonPrefixed (Args &&... args) const

void	mooseWarning (Args &&... args) const

void	mooseWarning (Args &&... args) const

void	mooseWarningNonPrefixed (Args &&... args) const

void	mooseWarningNonPrefixed (Args &&... args) const

void	mooseDeprecated (Args &&... args) const

void	mooseDeprecated (Args &&... args) const

void	mooseDeprecatedNoTrace (Args &&... args) const

void	mooseInfo (Args &&... args) const

void	callMooseError (std::string msg, const bool with_prefix, const hit::Node *node=nullptr, const bool show_trace=true) const

std::string	getDataFileName (const std::string &param) const

std::string	getDataFileNameByName (const std::string &relative_path) const

std::string	getDataFilePath (const std::string &relative_path) const

virtual void	initialSetup ()

virtual void	timestepSetup ()

virtual void	jacobianSetup ()

virtual void	residualSetup ()

virtual void	subdomainSetup ()

virtual void	customSetup (const ExecFlagType &)

const ExecFlagEnum &	getExecuteOnEnum () const

PerfGraph &	perfGraph ()

T &	getSampler (const std::string &name)

Sampler &	getSampler (const std::string &name)

T &	getSamplerByName (const SamplerName &name)

Sampler &	getSamplerByName (const SamplerName &name)

const VectorPostprocessorValue &	getVectorPostprocessorValue (const std::string &param_name, const std::string &vector_name) const

const VectorPostprocessorValue &	getVectorPostprocessorValue (const std::string &param_name, const std::string &vector_name, bool needs_broadcast) const

const VectorPostprocessorValue &	getVectorPostprocessorValueByName (const VectorPostprocessorName &name, const std::string &vector_name) const

const VectorPostprocessorValue &	getVectorPostprocessorValueByName (const VectorPostprocessorName &name, const std::string &vector_name, bool needs_broadcast) const

const VectorPostprocessorValue &	getVectorPostprocessorValueOld (const std::string &param_name, const std::string &vector_name) const

const VectorPostprocessorValue &	getVectorPostprocessorValueOld (const std::string &param_name, const std::string &vector_name, bool needs_broadcast) const

const VectorPostprocessorValue &	getVectorPostprocessorValueOldByName (const VectorPostprocessorName &name, const std::string &vector_name) const

const VectorPostprocessorValue &	getVectorPostprocessorValueOldByName (const VectorPostprocessorName &name, const std::string &vector_name, bool needs_broadcast) const

const ScatterVectorPostprocessorValue &	getScatterVectorPostprocessorValue (const std::string &param_name, const std::string &vector_name) const

const ScatterVectorPostprocessorValue &	getScatterVectorPostprocessorValueByName (const VectorPostprocessorName &name, const std::string &vector_name) const

const ScatterVectorPostprocessorValue &	getScatterVectorPostprocessorValueOld (const std::string &param_name, const std::string &vector_name) const

const ScatterVectorPostprocessorValue &	getScatterVectorPostprocessorValueOldByName (const VectorPostprocessorName &name, const std::string &vector_name) const

bool	hasVectorPostprocessor (const std::string &param_name, const std::string &vector_name) const

bool	hasVectorPostprocessor (const std::string &param_name) const

bool	hasVectorPostprocessorByName (const VectorPostprocessorName &name, const std::string &vector_name) const

bool	hasVectorPostprocessorByName (const VectorPostprocessorName &name) const

const VectorPostprocessorName &	getVectorPostprocessorName (const std::string &param_name) const

DenseMatrix< Real >	getGlobalSamples ()

DenseMatrix< Real >	getGlobalSamples ()

DenseMatrix< Real >	getLocalSamples ()

DenseMatrix< Real >	getLocalSamples ()

dof_id_type	getLocalRowBegin () const

dof_id_type	getLocalRowBegin () const

dof_id_type	getLocalRowEnd () const

dof_id_type	getLocalRowEnd () const

const Distribution &	getDistribution (const std::string &name) const

const T &	getDistribution (const std::string &name) const

const Distribution &	getDistribution (const std::string &name) const

const T &	getDistribution (const std::string &name) const

const Distribution &	getDistributionByName (const DistributionName &name) const

const T &	getDistributionByName (const std::string &name) const

const Distribution &	getDistributionByName (const DistributionName &name) const

const T &	getDistributionByName (const std::string &name) const

bool	isVectorPostprocessorDistributed (const std::string &param_name) const

bool	isVectorPostprocessorDistributed (const std::string &param_name) const

bool	isVectorPostprocessorDistributedByName (const VectorPostprocessorName &name) const

bool	isVectorPostprocessorDistributedByName (const VectorPostprocessorName &name) const

const Parallel::Communicator &	comm () const

processor_id_type	n_processors () const

processor_id_type	processor_id () const

Static Public Member Functions
static InputParameters	validParams ()

static void	callMooseError (MooseApp const app, const InputParameters &params, std::string msg, const bool with_prefix, const hit::Node node, const bool show_trace=true)

Public Attributes
	usingCombinedWarningSolutionWarnings

const ConsoleStream	_console

Static Public Attributes
static const std::string	type_param

static const std::string	name_param

static const std::string	unique_name_param

static const std::string	app_param

static const std::string	moose_base_param

static const std::string	kokkos_object_param

Protected Member Functions
virtual Real	computeSample (dof_id_type row_index, dof_id_type col_index) override

virtual LocalRankConfig	constructRankConfig (bool batch_mode) const override
	Morris sampling should have a slightly different partitioning in order to keep the sample and resample samplers distributed and make computing indices more efficient.

void	setNumberOfRandomSeeds (std::size_t number)

Real	getRand (std::size_t n, unsigned int index=0) const

unsigned int	getRandl (std::size_t n, unsigned int lower, unsigned int upper, unsigned int index=0) const

void	flagInvalidSolutionInternal (const InvalidSolutionID invalid_solution_id) const

InvalidSolutionID	registerInvalidSolutionInternal (const std::string &message, const bool warning) const

PerfID	registerTimedSection (const std::string &section_name, const unsigned int level) const

PerfID	registerTimedSection (const std::string &section_name, const unsigned int level, const std::string &live_message, const bool print_dots=true) const

std::string	timedSectionName (const std::string &section_name) const

virtual void	addVectorPostprocessorDependencyHelper (const VectorPostprocessorName &) const

const ReporterContextBase &	getReporterContextBaseByName (const ReporterName &reporter_name) const

const ReporterName &	getReporterName (const std::string &param_name) const

virtual void	addReporterDependencyHelper (const ReporterName &)

void	setNumberOfRows (dof_id_type n_rows)

void	setNumberOfRows (dof_id_type n_rows)

void	setNumberOfCols (dof_id_type n_cols)

void	setNumberOfCols (dof_id_type n_cols)

virtual void	computeSampleMatrix (DenseMatrix< Real > &matrix)

virtual void	computeSampleMatrix (DenseMatrix< Real > &matrix)

virtual void	computeLocalSampleMatrix (DenseMatrix< Real > &matrix)

virtual void	computeLocalSampleMatrix (DenseMatrix< Real > &matrix)

virtual void	computeSampleRow (dof_id_type i, std::vector< Real > &data)

virtual void	computeSampleRow (dof_id_type i, std::vector< Real > &data)

virtual void	advanceGenerators (const dof_id_type count)

virtual void	advanceGenerators (const dof_id_type count)

virtual void	advanceGenerator (const unsigned int seed_index, const dof_id_type count)

virtual void	advanceGenerator (const unsigned int seed_index, const dof_id_type count)

void	setAutoAdvanceGenerators (const bool state)

void	setAutoAdvanceGenerators (const bool state)

virtual void	executeSetUp ()

virtual void	executeSetUp ()

virtual void	executeTearDown ()

virtual void	executeTearDown ()

const T &	getReporterValue (const std::string &param_name, const std::size_t time_index=0)

const T &	getReporterValue (const std::string &param_name, ReporterMode mode, const std::size_t time_index=0)

const T &	getReporterValue (const std::string &param_name, const std::size_t time_index=0)

const T &	getReporterValue (const std::string &param_name, ReporterMode mode, const std::size_t time_index=0)

const T &	getReporterValueByName (const ReporterName &reporter_name, const std::size_t time_index=0)

const T &	getReporterValueByName (const ReporterName &reporter_name, ReporterMode mode, const std::size_t time_index=0)

const T &	getReporterValueByName (const ReporterName &reporter_name, const std::size_t time_index=0)

const T &	getReporterValueByName (const ReporterName &reporter_name, ReporterMode mode, const std::size_t time_index=0)

bool	hasReporterValue (const std::string &param_name) const

bool	hasReporterValue (const std::string &param_name) const

bool	hasReporterValue (const std::string &param_name) const

bool	hasReporterValue (const std::string &param_name) const

bool	hasReporterValueByName (const ReporterName &reporter_name) const

bool	hasReporterValueByName (const ReporterName &reporter_name) const

bool	hasReporterValueByName (const ReporterName &reporter_name) const

bool	hasReporterValueByName (const ReporterName &reporter_name) const

Protected Attributes
const dof_id_type &	_num_trajectories
	Number of trajectories.

const unsigned int &	_num_levels
	Number of levels used for input space discretization.

std::vector< const Distribution * >	_distributions
	Distribution to determine parameter from perturbations.

const dof_id_type	_min_procs_per_row

const dof_id_type	_max_procs_per_row

libMesh::Parallel::Communicator	_local_comm

const bool &	_enabled

MooseApp &	_app

Factory &	_factory

ActionFactory &	_action_factory

const std::string &	_type

const std::string &	_name

const InputParameters &	_pars

const ExecFlagEnum &	_execute_enum

const ExecFlagType &	_current_execute_flag

MooseApp &	_pg_moose_app

const std::string	_prefix

const Parallel::Communicator &	_communicator

Private Member Functions
void	updateBstar ()
	Function to calculate trajectories This is only called once per trajectory (_n_rows / (_n_cols + 1))

void	execute ()

void	checkReinitStatus () const

void	advanceGeneratorsInternal (const dof_id_type count)

const VectorPostprocessorValue &	getVectorPostprocessorByNameHelper (const VectorPostprocessorName &name, const std::string &vector_name, bool broadcast, std::size_t t_index) const

const VectorPostprocessorContext< VectorPostprocessorValue > &	getVectorPostprocessorContextByNameHelper (const VectorPostprocessorName &name, const std::string &vector_name) const

bool	vectorPostprocessorsAdded () const

bool	reportersAdded () const

void	possiblyCheckHasReporter (const ReporterName &reporter_name, const std::string &param_name="") const

void	init ()

void	init ()

void	reinit ()

void	reinit ()

void	possiblyCheckHasVectorPostprocessor (const std::string &param_name, const std::string &vector_name) const

void	possiblyCheckHasVectorPostprocessor (const std::string &param_name, const std::string &vector_name) const

void	possiblyCheckHasVectorPostprocessorByName (const VectorPostprocessorName &name, const std::string &vector_name) const

void	possiblyCheckHasVectorPostprocessorByName (const VectorPostprocessorName &name, const std::string &vector_name) const

Static Private Member Functions
static const hit::Node *	getHitNode (const InputParameters &params)

static std::string	messagePrefix (const InputParameters &params, const bool hit_prefix)

Private Attributes
dof_id_type	_curr_trajectory = std::numeric_limits<dof_id_type>::max()
	The trajectory the current _bstar represents.

std::vector< std::unique_ptr< MooseRandomStateless > >	_generators

dof_id_type	_n_local_rows

dof_id_type	_local_row_begin

dof_id_type	_local_row_end

dof_id_type	_n_rows

dof_id_type	_n_cols

std::size_t	_n_seeds

dof_id_type	_next_local_row

bool	_next_local_row_requires_state_restore

bool	_initialized

bool	_needs_reinit

bool	_has_executed

const dof_id_type	_limit_get_global_samples

const dof_id_type	_limit_get_local_samples

const dof_id_type	_limit_get_next_local_row

std::pair< LocalRankConfig, LocalRankConfig >	_rank_config

bool	_auto_advance_generators

const ParallelParamObject &	_parent

const MooseBase &	_si_moose_base

const FEProblemBase *	_si_problem

ExecFlagEnum	_empty_execute_enum

const InputParameters &	_dni_params

FEProblemBase &	_dni_feproblem

const MooseObject *const	_dni_moose_object_ptr

const InputParameters &	_si_params

FEProblemBase &	_si_feproblem

THREAD_ID	_si_tid

const bool	_broadcast_by_default

const MooseObject &	_vpi_moose_object

const FEProblemBase &	_vpi_feproblem

const THREAD_ID	_vpi_tid

const InputParameters &	_ri_params

FEProblemBase &	_ri_fe_problem_base

const ReporterData &	_ri_reporter_data

const MooseObject &	_ri_moose_object


RealEigenMatrix	_b

RealEigenMatrix	_pstar

RealEigenMatrix	_j

RealEigenMatrix	_dstar

RealEigenMatrix	_xstar

RealEigenMatrix	_bstar

Detailed Description

A class used to perform Monte Carlo sampling for performing Morris sensitivity analysis.

Definition at line 18 of file MorrisSampler.h.

Constructor & Destructor Documentation

◆ MorrisSampler()

MorrisSampler::MorrisSampler ( const InputParameters & parameters )

Definition at line 39 of file MorrisSampler.C.

  : Sampler(parameters),
    _num_trajectories(getParam<dof_id_type>("trajectories")),
    _num_levels(getParam<unsigned int>("levels"))
 
{
  for (const auto & name : getParam<std::vector<DistributionName>>("distributions"))
    _distributions.push_back(&getDistributionByName(name));
  const dof_id_type nc = _distributions.size();
 
  setNumberOfCols(nc);
  setNumberOfRows(_num_trajectories * (nc + 1));
 
  _b = RealEigenMatrix::Ones(nc + 1, nc).triangularView<Eigen::StrictlyLower>();
  _pstar.resize(nc, nc);
  _j.setOnes(nc + 1, nc);
  _dstar.resize(nc, nc);
  _xstar.resize(nc + 1, nc);
  _bstar.resize(nc + 1, nc);
}

Member Function Documentation

◆ computeSample()

Real MorrisSampler::computeSample	(	dof_id_type	row_index,
		dof_id_type	col_index
	)

overrideprotectedvirtual

Implements Sampler.

Definition at line 61 of file MorrisSampler.C.

{
  const dof_id_type traj = row_index / (getNumberOfCols() + 1);
  const dof_id_type traj_ind = row_index % (getNumberOfCols() + 1);
  if (traj != _curr_trajectory)
  {
    _curr_trajectory = traj;
    updateBstar();
  }
  return _distributions[col_index]->quantile(_bstar(traj_ind, col_index));
}

◆ constructRankConfig()

LocalRankConfig MorrisSampler::constructRankConfig ( bool batch_mode ) const

overrideprotectedvirtual

Morris sampling should have a slightly different partitioning in order to keep the sample and resample samplers distributed and make computing indices more efficient.

Reimplemented from Sampler.

Definition at line 110 of file MorrisSampler.C.

{
  std::vector<LocalRankConfig> all_rc(processor_id() + 1);
  for (processor_id_type r = 0; r <= processor_id(); ++r)
    all_rc[r] = rankConfig(
        r, n_processors(), _num_trajectories, _min_procs_per_row, _max_procs_per_row, batch_mode);
  LocalRankConfig & rc = all_rc.back();
 
  rc.num_local_sims *= _distributions.size() + 1;
  bool found_first = false;
  for (auto it = all_rc.rbegin(); it != all_rc.rend(); ++it)
    if (it->is_first_local_rank)
    {
      if (found_first)
        rc.first_local_sim_index += it->num_local_sims * _distributions.size();
      else
        found_first = true;
    }
 
  if (!batch_mode)
  {
    rc.num_local_apps = rc.num_local_sims;
    rc.first_local_app_index = rc.first_local_sim_index;
  }
 
  return rc;
}

◆ updateBstar()

void MorrisSampler::updateBstar ( )

private

Function to calculate trajectories This is only called once per trajectory (_n_rows / (_n_cols + 1))

Definition at line 74 of file MorrisSampler.C.

{
  mooseAssert(_curr_trajectory < _num_trajectories,
              "Current trajectory index is greater than the prescribed number of trajectories.");
 
  const dof_id_type nc = getNumberOfCols(); // convenience
  dof_id_type rn_ind = _curr_trajectory * nc * (nc + 1);
 
  _pstar.setZero();
  // Which parameter to perturb
  std::vector<dof_id_type> pchoice(nc);
  std::iota(pchoice.begin(), pchoice.end(), 0);
  for (dof_id_type c = 0; c < nc; ++c)
  {
    const unsigned int ind = nc > 1 ? getRandl(rn_ind++, 0, pchoice.size()) : 0;
    _pstar(pchoice[ind], c) = 1.0;
    pchoice.erase(pchoice.begin() + ind);
  }
 
  _dstar.setZero();
  // Direction of perturbation
  for (dof_id_type c = 0; c < nc; ++c)
    _dstar(c, c) = getRand(rn_ind++) < 0.5 ? -1.0 : 1.0;
 
  // Initial value
  for (dof_id_type c = 0; c < nc; ++c)
  {
    const auto lind = getRandl(rn_ind++, 0, _num_levels / 2);
    _xstar.col(c).setConstant((Real)lind * 1.0 / ((Real)_num_levels - 1));
  }
 
  _bstar =
      _xstar + _num_levels / 4.0 / (_num_levels - 1) * ((2.0 * _b * _pstar - _j) * _dstar + _j);
}

Referenced by computeSample().

◆ validParams()

InputParameters MorrisSampler::validParams ( )

static

Definition at line 16 of file MorrisSampler.C.

{
  InputParameters params = Sampler::validParams();
  params.addClassDescription("Morris variance-based sensitivity analysis Sampler.");
  params.addRequiredParam<std::vector<DistributionName>>(
      "distributions",
      "The distribution names to be sampled, the number of distributions provided defines the "
      "number of columns per matrix.");
  params.addRequiredRangeCheckedParam<dof_id_type>(
      "trajectories",
      "trajectories > 0",
      "Number of unique trajectories to perform. The higher number of these usually means a more "
      "accurate sensitivity evaluation, but it is proportional to the number of required model "
      "evaluations: 'trajectoris' x (number of 'distributions' + 1).");
  params.addRangeCheckedParam<unsigned int>(
      "levels",
      4,
      "levels % 2 = 0 & levels > 0",
      "The number of levels in the sampling. This determines the discretization of the input "
      "space, more levels means finer discretization and more possible model perturbations.");
  return params;
}

Member Data Documentation

◆ _b

RealEigenMatrix MorrisSampler::_b

private

Matrices used for trajectory computation

Definition at line 54 of file MorrisSampler.h.

Referenced by MorrisSampler(), and updateBstar().

◆ _bstar

RealEigenMatrix MorrisSampler::_bstar

private

Definition at line 59 of file MorrisSampler.h.

Referenced by computeSample(), MorrisSampler(), and updateBstar().

◆ _curr_trajectory

dof_id_type MorrisSampler::_curr_trajectory = std::numeric_limits<dof_id_type>::max()

private

The trajectory the current _bstar represents.

Definition at line 50 of file MorrisSampler.h.

Referenced by computeSample(), and updateBstar().

◆ _distributions

std::vector<const Distribution *> MorrisSampler::_distributions

protected

Distribution to determine parameter from perturbations.

Definition at line 40 of file MorrisSampler.h.

Referenced by computeSample(), constructRankConfig(), and MorrisSampler().

◆ _dstar

RealEigenMatrix MorrisSampler::_dstar

private

Definition at line 57 of file MorrisSampler.h.

Referenced by MorrisSampler(), and updateBstar().

◆ _j

RealEigenMatrix MorrisSampler::_j

private

Definition at line 56 of file MorrisSampler.h.

Referenced by MorrisSampler(), and updateBstar().

◆ _num_levels

const unsigned int& MorrisSampler::_num_levels

protected

Number of levels used for input space discretization.

Definition at line 38 of file MorrisSampler.h.

Referenced by updateBstar().

◆ _num_trajectories

const dof_id_type& MorrisSampler::_num_trajectories

protected

Number of trajectories.

Definition at line 36 of file MorrisSampler.h.

Referenced by constructRankConfig(), MorrisSampler(), and updateBstar().

◆ _pstar

RealEigenMatrix MorrisSampler::_pstar

private

Definition at line 55 of file MorrisSampler.h.

Referenced by MorrisSampler(), and updateBstar().

◆ _xstar

RealEigenMatrix MorrisSampler::_xstar

private

Definition at line 58 of file MorrisSampler.h.

Referenced by MorrisSampler(), and updateBstar().

The documentation for this class was generated from the following files:

stochastic_tools/include/samplers/MorrisSampler.h
stochastic_tools/src/samplers/MorrisSampler.C

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Static Public Attributes

Protected Member Functions

Protected Attributes

Private Member Functions

Static Private Member Functions

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ MorrisSampler()

Member Function Documentation

◆ computeSample()

◆ constructRankConfig()

◆ updateBstar()

◆ validParams()

Member Data Documentation

◆ _b

◆ _bstar

◆ _curr_trajectory

◆ _distributions

◆ _dstar

◆ _j

◆ _num_levels

◆ _num_trajectories

◆ _pstar

◆ _xstar