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 { SampleMode::GLOBAL, SampleMode::LOCAL }

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

MooseApp &	getMooseApp () const

const std::string &	type () const

virtual const std::string &	name () const

std::string	typeAndName () const

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

void	callMooseError (std::string msg, const bool with_prefix) const

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

const InputParameters &	parameters () const

MooseObjectName	uniqueName () 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 &nm) const

void	paramError (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

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

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

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

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

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

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

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

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

Public Attributes
const ConsoleStream	_console

Protected Types
enum	CommMethod

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

virtual void	sampleSetUp (const Sampler::SampleMode mode) override
	Used to setup matrices for trajectory computation. More...

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. More...

void	setNumberOfRandomSeeds (std::size_t number)

Real	getRand (unsigned int index=0)

uint32_t	getRandl (unsigned int index, uint32_t lower, uint32_t upper)

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 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	sampleTearDown (const SampleMode)

virtual void	sampleTearDown (const SampleMode)

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)

void	shuffle (std::vector< T > &data, const std::size_t seed_index=0, const CommMethod method=CommMethod::LOCAL)

void	shuffle (std::vector< T > &data, const std::size_t seed_index=0, const CommMethod method=CommMethod::LOCAL)

virtual void	executeSetUp ()

virtual void	executeSetUp ()

virtual void	executeTearDown ()

virtual void	executeTearDown ()

void	saveGeneratorState ()

void	saveGeneratorState ()

void	restoreGeneratorState ()

void	restoreGeneratorState ()

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. More...

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

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

	NONE

	LOCAL

	SEMI_LOCAL

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

const std::string	_type

const std::string	_name

const InputParameters &	_pars

Factory &	_factory

ActionFactory &	_action_factory

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)) More...

Private Attributes

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));
 
   setNumberOfCols(_distributions.size());
   setNumberOfRows(_num_trajectories * (_distributions.size() + 1));
 }

Member Function Documentation

◆ computeSample()

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

overrideprotectedvirtual

Implements Sampler.

Definition at line 65 of file MorrisSampler.C.

 {
   const dof_id_type traj_ind = row_index % (getNumberOfCols() + 1);
   if (traj_ind == 0 && col_index == 0)
     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 111 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;
 }

◆ sampleSetUp()

void MorrisSampler::sampleSetUp ( const Sampler::SampleMode mode )

overrideprotectedvirtual

Used to setup matrices for trajectory computation.

Reimplemented from Sampler.

Definition at line 53 of file MorrisSampler.C.

 {
   const dof_id_type nc = getNumberOfCols();
   _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);
 }

◆ 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.

Referenced by computeSample().

 {
   const dof_id_type nc = getNumberOfCols(); // convenience
   _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(0, 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() < 0.5 ? -1.0 : 1.0;
 
   // Initial value
   for (dof_id_type c = 0; c < nc; ++c)
   {
     const auto lind = getRandl(0, 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);
 
   // This matrix represent _n_cols * (_n_cols + 1) samples, but so far we have only
   // advanced the generator 3 * _n_cols times. For the generator state restore
   // to work properly, we need to finish advancing the generator
   if (nc > 2)
     advanceGenerator(0, nc * (nc - 2));
 }

◆ 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 trajector computation

Definition at line 56 of file MorrisSampler.h.

Referenced by sampleSetUp(), and updateBstar().

◆ _bstar

RealEigenMatrix MorrisSampler::_bstar

private

Definition at line 61 of file MorrisSampler.h.

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

◆ _distributions

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

protected

Distribution to determine parameter from perturbations.

Definition at line 45 of file MorrisSampler.h.

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

◆ _dstar

RealEigenMatrix MorrisSampler::_dstar

private

Definition at line 59 of file MorrisSampler.h.

Referenced by sampleSetUp(), and updateBstar().

◆ _j

RealEigenMatrix MorrisSampler::_j

private

Definition at line 58 of file MorrisSampler.h.

Referenced by sampleSetUp(), and updateBstar().

◆ _num_levels

const unsigned int& MorrisSampler::_num_levels

protected

Number of levels used for input space discretization.

Definition at line 43 of file MorrisSampler.h.

Referenced by updateBstar().

◆ _num_trajectories

const dof_id_type& MorrisSampler::_num_trajectories

protected

Number of trajectories.

Definition at line 41 of file MorrisSampler.h.

Referenced by constructRankConfig(), and MorrisSampler().

◆ _pstar

RealEigenMatrix MorrisSampler::_pstar

private

Definition at line 57 of file MorrisSampler.h.

Referenced by sampleSetUp(), and updateBstar().

◆ _xstar

RealEigenMatrix MorrisSampler::_xstar

private

Definition at line 60 of file MorrisSampler.h.

Referenced by sampleSetUp(), 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

Protected Types

Protected Member Functions

Protected Attributes

Private Member Functions

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ MorrisSampler()

Member Function Documentation

◆ computeSample()

◆ constructRankConfig()

◆ sampleSetUp()

◆ updateBstar()

◆ validParams()

Member Data Documentation

◆ _b

◆ _bstar

◆ _distributions

◆ _dstar

◆ _j

◆ _num_levels

◆ _num_trajectories

◆ _pstar

◆ _xstar