TrainingPlan assigns a in a set of sample each sample a status on how the sample is to be treated during the training of a model. More...

Public Member Functions
virtual std::vector< string >	getInputNames (::data_handler::DataHandlerBase datahandler)=0
	Returns the input names from the datahandler. More...

virtual Matrix	getInputs (::data_handler::DataHandlerBase datahandler)=0
	Returns the inputs fitting the training plan from the datahandler. More...

virtual string	getMOPIdent ()=0
	Returns the MOP ident the TrainingPlan is created for. More...

virtual std::vector< string >	getOutputNames (::data_handler::DataHandlerBase datahandler)=0
	Returns the output names from the datahandler. More...

virtual Matrix	getOutputs (::data_handler::DataHandlerBase datahandler)=0
	Returns the outputs fitting the training plan from the datahandler. More...

virtual SampleUsage	getSampleUsageInSet (uint64_t i, uint64_t j)=0
	getSampleUsageInSet accessor of the j-th sample in the i-th training set More...

virtual SampleUsage	getSampleUsageInSetRef (uint64_t i, uint64_t j)=0
	getSampleUsageInSetRef non- accessor of the j-th sample in the i-th training set More...

virtual ParameterImportance	inputImportance (uint64_t i)=0
	parameter returns the ParameterImportance for the i-th parameter More...

virtual ParameterImportance	inputImportanceInSubspace (uint64_t i, uint64_t j, uint64_t o)=0
	inputImportanceInSubspace returns true if the input j is in the subspace i. More...

virtual bool	isValid (::data_handler::DataHandlerBase)=0
	Checks if the training plan is valid for the give datahandler. More...

virtual uint64_t	numInputs ()=0
	numInputs returns the number of inputs used and defined in this training plan More...

virtual uint64_t	numOutputs ()=0
	numOutputs returns the number of outputs used in this training plan More...

virtual uint64_t	numSamplesInSet (uint64_t i)=0
	numSamplesInSet returns the number of elements (samples) in the training set More...

virtual uint64_t	numSets ()=0
	numSets returns the number of training sets in the training plan More...

virtual uint64_t	numSubspaces (uint64_t o)=0
	numSubspaces returns the number of filtered subspaces available in the Training Plan to the i-th output in the output matrix More...

virtual uint64_t	numTestSamplesInSet (uint64_t i)=0
	numTestSamplesInSet returns the number of elements (samples) in the training set that are labeled SampleUsage::Test More...

virtual uint64_t	numTrainingSamplesInSet (uint64_t i)=0
	numTrainingSamplesInSet returns the number of elements (samples) in the training set that are labeled SampleUsage::Training More...

virtual uint64_t	output (uint64_t i)=0
	parameter returns the index of the i-th output in the output matrix More...

Detailed Description

TrainingPlan assigns a in a set of sample each sample a status on how the sample is to be treated during the training of a model.

Member Function Documentation

◆ getInputNames()

virtual std::vector<string> getInputNames ( ::data_handler::DataHandlerBase datahandler )

pure virtual

Returns the input names from the datahandler.

Parameters

datahandler The datahandler to get the data from

Returns: The input data names

Implemented in SimpleTrainingPlan.

◆ getInputs()

virtual Matrix getInputs ( ::data_handler::DataHandlerBase datahandler )

pure virtual

Returns the inputs fitting the training plan from the datahandler.

Parameters

datahandler The datahandler to get the data from

Returns: The (scalar) input data

Implemented in SimpleTrainingPlan.

◆ getMOPIdent()

virtual string getMOPIdent ( )

pure virtual

Returns the MOP ident the TrainingPlan is created for.

Returns: The ident for the MOP

Implemented in SimpleTrainingPlan.

◆ getOutputNames()

virtual std::vector<string> getOutputNames ( ::data_handler::DataHandlerBase datahandler )

pure virtual

Returns the output names from the datahandler.

Parameters

datahandler The datahandler to get the data from

Returns: The output data names

Implemented in SimpleTrainingPlan.

◆ getOutputs()

virtual Matrix getOutputs ( ::data_handler::DataHandlerBase datahandler )

pure virtual

Returns the outputs fitting the training plan from the datahandler.

Parameters

datahandler The datahandler to get the data from

Returns: The (scalar) output data

Implemented in SimpleTrainingPlan.

◆ getSampleUsageInSet()

virtual SampleUsage getSampleUsageInSet	(	uint64_t	i,
		uint64_t	j
	)

pure virtual

getSampleUsageInSet accessor of the j-th sample in the i-th training set

Parameters

i	Index of the training set
j	Index of the sample in training set i

Returns: The sample at the given indices

Implemented in SimpleTrainingPlan.

◆ getSampleUsageInSetRef()

virtual SampleUsage getSampleUsageInSetRef	(	uint64_t	i,
		uint64_t	j
	)

pure virtual

getSampleUsageInSetRef non- accessor of the j-th sample in the i-th training set

Parameters

i	Index of the training set
j	Index of the sample in training set i

Returns: The sample at the given indices

Implemented in SimpleTrainingPlan.

◆ inputImportance()

virtual ParameterImportance inputImportance ( uint64_t i )

pure virtual

parameter returns the ParameterImportance for the i-th parameter

Parameters

i	The index of the parameter

Returns: The ParameterUsage of parameter i

Implemented in SimpleTrainingPlan.

◆ inputImportanceInSubspace()

virtual ParameterImportance inputImportanceInSubspace	(	uint64_t	i,
		uint64_t	j,
		uint64_t	o
	)

pure virtual

inputImportanceInSubspace returns true if the input j is in the subspace i.

Parameters

i	Index of the subspace
j	Index of the input parameter
o	The o-th output the input is important to

Returns: ParameterImportance of input j is in subspace i for the given output

Implemented in SimpleTrainingPlan.

◆ isValid()

virtual bool isValid ( ::data_handler::DataHandlerBase )

pure virtual

Checks if the training plan is valid for the give datahandler.

Returns: true iff the training plan is valid

Implemented in SimpleTrainingPlan.

◆ numInputs()

virtual uint64_t numInputs ( )

pure virtual

numInputs returns the number of inputs used and defined in this training plan

Returns: The number of parameters the training plan is defined on

Implemented in SimpleTrainingPlan.

◆ numOutputs()

virtual uint64_t numOutputs ( )

pure virtual

numOutputs returns the number of outputs used in this training plan

Returns: The number of outputs the training plan is defined on

Implemented in SimpleTrainingPlan.

◆ numSamplesInSet()

virtual uint64_t numSamplesInSet ( uint64_t i )

pure virtual

numSamplesInSet returns the number of elements (samples) in the training set

Parameters

i	The index of the training set

Returns: The number of elements in set i

Implemented in SimpleTrainingPlan.

◆ numSets()

virtual uint64_t numSets ( )

pure virtual

numSets returns the number of training sets in the training plan

Returns: The number of training sets

Implemented in SimpleTrainingPlan.

◆ numSubspaces()

virtual uint64_t numSubspaces ( uint64_t o )

pure virtual

numSubspaces returns the number of filtered subspaces available in the Training Plan to the i-th output in the output matrix

Parameters

o	The index of the output

Returns: The number of Subspaces for the given output

Implemented in SimpleTrainingPlan.

◆ numTestSamplesInSet()

virtual uint64_t numTestSamplesInSet ( uint64_t i )

pure virtual

numTestSamplesInSet returns the number of elements (samples) in the training set that are labeled SampleUsage::Test

Parameters

i	The index of the training set

Returns: The number of elements in set i

Implemented in SimpleTrainingPlan.

◆ numTrainingSamplesInSet()

virtual uint64_t numTrainingSamplesInSet ( uint64_t i )

pure virtual

numTrainingSamplesInSet returns the number of elements (samples) in the training set that are labeled SampleUsage::Training

Parameters

i	The index of the training set

Returns: The number of elements in set i

Implemented in SimpleTrainingPlan.

◆ output()

virtual uint64_t output ( uint64_t i )

pure virtual

parameter returns the index of the i-th output in the output matrix

Parameters

i	The index of the parameter

Returns: The index of output i in the output matrix

Implemented in SimpleTrainingPlan.

optiSLang 3D Postprocessing Script API 2025 R1

TrainingPlanBase Struct Reference

Public Member Functions

Detailed Description

Member Function Documentation

◆ getInputNames()

◆ getInputs()

◆ getMOPIdent()

◆ getOutputNames()

◆ getOutputs()

◆ getSampleUsageInSet()

◆ getSampleUsageInSetRef()

◆ inputImportance()

◆ inputImportanceInSubspace()

◆ isValid()

◆ numInputs()

◆ numOutputs()

◆ numSamplesInSet()

◆ numSets()

◆ numSubspaces()

◆ numTestSamplesInSet()

◆ numTrainingSamplesInSet()

◆ output()

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