IG.Num.SampledDataSet Class Reference

Sampled data consisting of elements of which each contains vector of input parameters and output values. More...

Classes
class	ComparerInputDistance
	Comparer that compares two data elements of type SampledDataElement according to the distance of their input parameter vectors to a specified reference point (vector) in the input parameter space. More...
class	ComparerOutputDistance
	Comparer that compares two data elements of type SampledDataElement according to the distance of their output values vectors to a specified reference point (vector) in the output values space. More...

Public Member Functions
	SampledDataSet ()
	SampledDataSet (int inputLength, int outputLength)
List< SampledDataElement >	GetElementList ()
void	UpdateElementIndices ()
	Updates indices of sampled data elements contained in the current sampled set in such a way that they correspond with their (current) sequential position in the set. More...
List< SampledDataElement >	GetElementListCopy ()
	Returna a copy of the list of data elements. More...
List< SampledDataElement >	GetSortedElemetnList (IComparer< SampledDataElement > comparer)
	Creates and returns a list of all sampled data elemets of the current object that are sorted according to the specified comparer object (that implements the IComparer{SampledDataElement} interface). More...
List< SampledDataElement >	GetInputDistanceSortedElemetnList (IVector referencePoint, DistanceDelegate distanceFunction)
	Creates and returns a list of all sampled data elemets of the current object that are sorted according to distance between input parameters and a specified reference point. More...
List< SampledDataElement >	GetOutputDistanceSortedElemetnList (IVector referencePoint, DistanceDelegate distanceFunction)
	Creates and returns a list of all sampled data elemets of the current object that are sorted according to distance between output values and a specified reference point in the output values space. More...
virtual void	Clear ()
void	AddElement (SampledDataElement element)
	Adda a new element to sampled data. More...
void	Add (SampledDataSet addedSet)
	Adds elements of another sampled data ser to the current sampled data. Only references are copied. More...
void	Add (params SampledDataElement[] addedSet)
	Adds array of sampled data elements to teh current sampled data set. Only references are copied. More...
IVector	GetInputParameters (int which)
	Returns the vector of input parameters of the specified element of the sampled data set. More...
void	SetInputParameters (int which, IVector parameters)
	Sets the vector of input parameters of the specified element of the sampled data set. More...
virtual IVector	GetOutputValues (int which)
	Returns the vector of output values of the specified element of the sampled data set. More...
void	SetOutputValues (int which, IVector values)
	Sets the vector of output values of the specified element of the sampled data set. More...
void	GetInputRange (ref IBoundingBox bounds)
	Calculates range of input parameters of the current sampled data set, and stores it to the specified bounding box. More...
void	GetOutputRange (ref IBoundingBox bounds)
	Calculates range of output values of the current sampled data set, and stores it to the specified bounding box. More...
void	ExtractInputs (ref IVector[] extracted)
	Extracts vectors of input parameters from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). More...
void	ExtractInputs (IndexList filterIndices, ref IVector[] extracted)
	Extracts the specified vectors of input parameters from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors to extract (i.e. which data elements to exclude). More...
void	ExtractInputsComplement (IndexList filterIndices, ref IVector[] extracted)
	Extracts the specified vectors (complement of the index list) of input parameters from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors NOT to extract (i.e. which data elements to include). More...
void	ExtractOutputs (ref IVector[] extracted)
	Extracts vectors of output values from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). More...
void	ExtractOutputs (IndexList filterIndices, ref IVector[] extracted)
	Extracts the specified vectors of output values from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors to extract (i.e. which data elements to exclude). More...
void	ExtractOutputsComplement (IndexList filterIndices, ref IVector[] extracted)
	Extracts the specified vectors (complement of the index list) of output values from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors NOT to extract (i.e. which data elements to include). More...
void	CopyInputs (ref IVector[] extracted)
	Copies vectors of input parameters from the current sampled data set, and stores them to the specified array. References of the extracted vectors aer stored (no deep copying performed). More...
void	CopyInputs (IndexList filterIndices, ref IVector[] extracted)
	Copies the specified vectors of input parameters from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors to extract (i.e. which sampled elements to exclude). More...
void	CopyInputsComplement (IndexList filterIndices, ref IVector[] extracted)
	Copies the specified vectors (complement of the index list) of input parameters from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors NOT to extract (i.e. which data elements to include). More...
void	CopyOutputs (ref IVector[] extracted)
	Copies vectors of output values from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). More...
void	CopyOutputs (IndexList filterIndices, ref IVector[] extracted)
	Copies the specified vectors of output values from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors to extract (i.e. which data elements to exclude). More...
void	CopyOutputsComplement (IndexList filterIndices, ref IVector[] extracted)
	Copies the specified vectors (complement of the index list) of output values from the current data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors NOT to extract (i.e. which sampled data elements to include). More...
void	ExtractFilteredData (IndexList filterIndices, ref IVector[] extracted, bool complement, bool outputData, bool copyValues)
	Extract extracts. More...
int	GetNumNullElemets ()
	Returns number of null elements of the current sampled data set. More...
int	GetNumInputDuplicates ()
	Returns number of elements of the current sampled data set with duplicated input parameters. More...
void	RemoveInputDuplicates ()
	Removes elements with duplibated input parameters from the current sampled data set, leaving only a single element with specified input parameters. Elements that are null are also removed. More...
delegate double	DistanceDelegate (IVector v1, IVector v2)
override string	ToString ()

Static Public Member Functions
static void	SaveBinary (SampledDataSet sampledData, string filePath)
	Saves the specified sempled data to the specified file in binary format. The file is owerwritten if it exists. More...
static void	LoadBinary (string filePath, ref SampledDataSet dataDefRestored)
	Restores sampled data from the specified file in binary format. More...
static void	SaveJson (SampledDataSet sampledData, string filePath)
	Saves the specified sempled data to the specified JSON file. The file is owerwritten if it exists. More...
static void	LoadJson (string filePath, ref SampledDataSet dataDefRestored)
	Restores sampled data from the specified file in JSON format. More...
static void	LoadSampledDataCombinedOutputsJSON (ref SampledDataSet sampledDat, string directoryPath, params string[] fileNames)
	Loads sampled data and Definition data from multible CSV files. Sampled data consist of one output and multiple input parameters. Input parameters are the same in all files, output parameter are different. More...
static void	LoadSampledDataCombinedOutputsJSON (ref SampledDataSet sampledData, params string[] fileNames)
	Loads sampled data and Definition data from multiple CSV files. Sampled data consist of one output and multiple input parameters. Input parameters are the same in all files but output parameter should be different. More...
static void	SaveSampledDataJson (string filePath, SampledDataSet sampledData)
	Saves network's sampled data to the specified JSON file. File is owerwritten if it exists. More...
static void	SaveDefinitionDataJson (string filePath, InputOutputDataDefiniton definitionData)
	Saves network's definition data to the specified JSON file. File is owerwritten if it exists. More...
static void	LoadSampledDataJson (string filePath, ref SampledDataSet sampledData)
	Restores sampled data from the specified file in JSON format. More...
static void	LoadSampledDataCSVinOneLine (string filePath, int inputLenght, int outputLenght, bool namesSpecified, bool descriptionSpecified, bool titleSpecified, ref SampledDataSet sampledData, ref InputOutputDataDefiniton definitionData)
	Loads sampled data and definition data from single CSV file. More...
static void	LoadSampledDataCSV (string filePath, int inputLenght, int outputLenght, bool namesSpecified, bool titleSpecified, bool descriptionSpecified, ref SampledDataSet sampledData, ref InputOutputDataDefiniton definitionData)
	Loads sampled data and definition data from single CSV file. More...
static void	LoadDefinitionDataCSV (string filePath, int inputLenght, int outputLenght, ref InputOutputDataDefiniton definitionData)
	Loads definition data from CSV file. More...
static void	SaveSampledDataCSVinOneLine (string filePath, SampledDataSet sampledData, bool namesSpecified, bool titleSpecified, bool descriptionSpecified, InputOutputDataDefiniton definitionData)
	Saves sampled data and Definition data to single CSV file. More...
static void	SaveSampledDataCSV (string filePath, SampledDataSet sampledData, bool namesSpecified, bool titlesSpecified, bool descriptionSpecified, InputOutputDataDefiniton definitionData)
	Saves sampled data and Definition data to single CSV file. More...
static void	SaveDefinitionDataCSV (string filePath, InputOutputDataDefiniton definitionData)
	Saves definition data to CSV file. More...
static void	SampledDataCombineOutputs (ref SampledDataSet result, params SampledDataSet[] individualSets)
	Loads sampled data and Definition data from multible CSV files. Sampled data consist of one output and multiple input parameters. Input parameters are the same in all files, output parameter are different. More...
static int	GetNumNullElemets (SampledDataSet sampledDataSet)
	Returns number of null elements of the specified sampled data set. More...
static int	GetNumInputDuplicates (SampledDataSet sampledSet)
	Returns the number of elements of the specified sampled data set with duplicated input parameters. More...
static void	RemoveInputDuplicates (SampledDataSet sampledSet)
	Removes elements with duplicated input parameters, leaving only a single element with specified input parameters. Elements that are null are also removed. More...
static SampledDataSet	CreateExampleLinear (int inputLength, int outputLength, int numElements)
	Craates and returns a sample data set object where input parameters are calculated randomly in a box-like domain, and output parameters are calculated by quadratic functions with random coefficients. Domain where sampling points are generated is a cartesian product of intervals [-1, 1]. More...
static SampledDataSet	CreateExampleLinear (int inputLength, int outputLength, int numElements, IBoundingBox region)
	Craates and returns a sample data set object where input parameters are calculated randomly in the specified box-like domain, and output parameters are calculated by quadratic functions with random coefficients. More...
static SampledDataSet	CreateExampleLinear (int inputLength, int outputLength, int numElements, IBoundingBox region, IRandomGenerator rand)
	Craates and returns a sample data set object where input parameters are calculated randomly in the specified box-like domain, and output parameters are calculated by quadratic functions with random coefficients. More...
static SampledDataSet	CreateExampleQuadratic (int inputLength, int outputLength, int numElements)
	Craates and returns a sample data set object where input parameters are calculated randomly in a box-like domain, and output parameters are calculated by quadratic functions with random coefficients. Domain where sampling points are generated is a cartesian product of intervals [-1, 1]. More...
static SampledDataSet	CreateExampleQuadratic (int inputLength, int outputLength, int numElements, IBoundingBox region)
	Craates and returns a sample data set object where input parameters are calculated randomly in the specified box-like domain, and output parameters are calculated by quadratic functions with random coefficients. More...
static SampledDataSet	CreateExampleQuadratic (int inputLength, int outputLength, int numElements, IBoundingBox region, IRandomGenerator rand)
	Craates and returns a sample data set object where input parameters are calculated randomly in the specified box-like domain, and output parameters are calculated by quadratic functions with random coefficients. More...
static SampledDataSet	CreateExample (int inputLength, int outputLength, int numElements, IBoundingBox region, IScalarFunctionUntransformed[] functions, IRandomGenerator rand)
	Craates and returns a sample data set object where input parameters are calculated randomly in the specified box-like domain, and output parameters are calculated by the specified scalar functions. More...
static SampledDataSet	CreateExampleSimple (int inputLength, int outputLength, int numElements)
	Craates and returns a sample object of the encompassing class. More...

Protected Attributes
int	_inputLength = -1
int	_outputLength = -1

Properties
SampledDataElement[]	Data [get, set]
	Gets or sets sampled data, as an array of data elements. More...
int	Length [get]
	Gets the number of sampled data elements (input/output pairs) contained by the current sampled data set. More...
int	InputLength [get, set]
	Number of input parameters in sampled data elements. Less than 0 means unspecified. More...
int	OutputLength [get, set]
	Number of output values in sampled data elements. Less than 0 means unspecified. More...
SampledDataElement	this[int which] [get, set]
	Gets or sets specific data element. More...

Detailed Description

Sampled data consisting of elements of which each contains vector of input parameters and output values.

NOT thread safe.

$A Igor Jun08;

Constructor & Destructor Documentation

IG.Num.SampledDataSet.SampledDataSet ( )

inline

IG.Num.SampledDataSet.SampledDataSet ( int  inputLength, int  outputLength  )

inline

Member Function Documentation

List<SampledDataElement> IG.Num.SampledDataSet.GetElementList ( )

inline

Referenced by IG.Neural.NeuralTadej.SmoothingTrainingData().

void IG.Num.SampledDataSet.UpdateElementIndices ( )

inline

Updates indices of sampled data elements contained in the current sampled set in such a way that they correspond with their (current) sequential position in the set.

In this way, element indices can be used to directly access sampled data elements (without a search).

References IG.Num.SampledDataElement.UpdateElemetIndices().

List<SampledDataElement> IG.Num.SampledDataSet.GetElementListCopy ( )

inline

Returna a copy of the list of data elements.

WARNING:

List returned is a copy of the internal list, therefore changes performed on the list are not reflected on internal state of the data set object, but changes performed on its elements are.

List<SampledDataElement> IG.Num.SampledDataSet.GetSortedElemetnList ( IComparer< SampledDataElement >  comparer )

inline

Creates and returns a list of all sampled data elemets of the current object that are sorted according to the specified comparer object (that implements the IComparer{SampledDataElement} interface).

Parameters

comparer

Comparer that is used for sorting the returned list.

List<SampledDataElement> IG.Num.SampledDataSet.GetInputDistanceSortedElemetnList ( IVector  referencePoint, DistanceDelegate  distanceFunction  )

inline

Creates and returns a list of all sampled data elemets of the current object that are sorted according to distance between input parameters and a specified reference point.

Parameters

referencePoint	Reference point, sampled data elements are sorted according to the distance to this point.
distanceFunction	Delegate that definines distance between two vectors for the purpose of sorting.

List<SampledDataElement> IG.Num.SampledDataSet.GetOutputDistanceSortedElemetnList ( IVector  referencePoint, DistanceDelegate  distanceFunction  )

inline

Creates and returns a list of all sampled data elemets of the current object that are sorted according to distance between output values and a specified reference point in the output values space.

Parameters

referencePoint	Reference point, sampled data elements are sorted according to the distance to this point.
distanceFunction	Delegate that definines distance between two vectors for the purpose of sorting.

virtual void IG.Num.SampledDataSet.Clear ( )

inlinevirtual

Referenced by IG.Num.NeuralApproximatorBase.SetTrainingAndVerificationData().

void IG.Num.SampledDataSet.AddElement ( SampledDataElement  element )

inline

Adda a new element to sampled data.

Parameters

element

Data element that is added to the sampled data set. If element is null then nothing is added (but no exception thrown).

References IG.Num.SampledDataElement.InputLength, and IG.Num.SampledDataElement.OutputLength.

Referenced by IG.Num.SampledDataSet.CreateExample(), IG.Num.SampledDataSet.CreateExampleSimple(), IG.Script.LoadableScriptShellNeuralBase.ParSimAddResults(), and IG.Script.LoadableScriptShellNeuralBase.ParSimRunJob().

void IG.Num.SampledDataSet.Add ( SampledDataSet  addedSet )

inline

Adds elements of another sampled data ser to the current sampled data. Only references are copied.

Parameters

addedSet

Sampled data whose elements are added to the current sampled data.

References IG.Num.SampledDataSet.Length.

Referenced by IG.Script.LoadableScriptShellNeuralBase.CreateDistortedModelData(), and IG.Num.NeuralApproximatorBase.SetTrainingAndVerificationData().

void IG.Num.SampledDataSet.Add ( params SampledDataElement[]  addedSet )

inline

Adds array of sampled data elements to teh current sampled data set. Only references are copied.

Parameters

addedSet

Sampled data whose elements are added to the current sampled data set.

IVector IG.Num.SampledDataSet.GetInputParameters ( int  which )

inline

Returns the vector of input parameters of the specified element of the sampled data set.

Parameters

which

Index of the sampled data element within the sampled data set.

References IG.Num.SampledDataElement.InputParameters.

Referenced by IG.Neural.NeuralTadej.CopyTrainingData(), IG.Neural.NeuralTadej.ExampleCasting(), IG.Neural.NeuralTadej.ExampleQuadratic(), IG.Num.NeuralApproximatorBase.ExampleQuadratic(), IG.Neural.NeuralTadej.ExampleStore(), IG.Neural.NeuralTadej.neuronsDataRange(), IG.Neural.NeuralTadej.SampledDataCombineOutputs(), IG.Num.SampledDataSet.SampledDataCombineOutputs(), IG.Num.SampledDataSet.SaveSampledDataCSV(), IG.Num.SampledDataSet.SaveSampledDataCSVinOneLine(), IG.Neural.NeuralTadej.SaveTrainingDataCSV(), IG.Neural.NeuralTadej.SaveTrainingDataCSVinOneLine(), IG.Neural.NeuralTadej.SmoothingTrainingData(), IG.Script.LoadableScriptShellNeuralBase.TrainANN(), and IG.Neural.NeuralTadej.TrainNetwork().

void IG.Num.SampledDataSet.SetInputParameters ( int  which, IVector  parameters  )

inline

Sets the vector of input parameters of the specified element of the sampled data set.

Parameters

which	Index of the sampled data element within the sampled data set.
parameters	Vector of input parameters to be set.

References IG.Num.SampledDataElement.InputParameters.

virtual IVector IG.Num.SampledDataSet.GetOutputValues ( int  which )

inlinevirtual

Returns the vector of output values of the specified element of the sampled data set.

Parameters

which

Index of the data element within the sampled set.

References IG.Num.SampledDataElement.OutputValues.

Referenced by IG.Neural.NeuralTadej.CopyTrainingData(), IG.Neural.NeuralTadej.ExampleCasting(), IG.Neural.NeuralTadej.ExampleQuadratic(), IG.Num.NeuralApproximatorBase.ExampleQuadratic(), IG.Neural.NeuralTadej.ExampleStore(), IG.Neural.NeuralTadej.neuronsDataRange(), IG.Neural.NeuralTadej.SampledDataCombineOutputs(), IG.Num.SampledDataSet.SampledDataCombineOutputs(), IG.Num.SampledDataSet.SaveSampledDataCSV(), IG.Num.SampledDataSet.SaveSampledDataCSVinOneLine(), IG.Neural.NeuralTadej.SaveTrainingDataCSV(), IG.Neural.NeuralTadej.SaveTrainingDataCSVinOneLine(), IG.Neural.NeuralTadej.SmoothingTrainingData(), IG.Script.LoadableScriptShellNeuralBase.TrainANN(), and IG.Neural.NeuralTadej.TrainNetwork().

void IG.Num.SampledDataSet.SetOutputValues ( int  which, IVector  values  )

inline

Sets the vector of output values of the specified element of the sampled data set.

Parameters

which	Index of the data element within the sampled data set.
values	Vector of output values to be set.

References IG.Num.SampledDataElement.OutputValues.

void IG.Num.SampledDataSet.GetInputRange ( ref IBoundingBox  bounds )

inline

Calculates range of input parameters of the current sampled data set, and stores it to the specified bounding box.

Parameters

bounds

Bounding box wehere bounds on input parameters are stored.

Referenced by IG.Num.NeuralTrainingParameters.CopyFrom(), IG.Num.NeuralApproximatorBase.RecalculateInputDataBounds(), and IG.Num.InputOutputDataDefiniton.SupplementDataDefinition().

void IG.Num.SampledDataSet.GetOutputRange ( ref IBoundingBox  bounds )

inline

Calculates range of output values of the current sampled data set, and stores it to the specified bounding box.

Parameters

bounds

Bounding box wehere bounds on output values are stored.

Referenced by IG.Num.NeuralTrainingParameters.CopyFrom(), IG.Neural.NeuralTadej.ExampleStore(), IG.Num.NeuralApproximatorBase.RecalculateOutputDataBounds(), and IG.Num.InputOutputDataDefiniton.SupplementDataDefinition().

void IG.Num.SampledDataSet.ExtractInputs ( ref IVector[]  extracted )

inline

Extracts vectors of input parameters from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed).

Parameters

extracted

Table where extracted vectors are stored.

void IG.Num.SampledDataSet.ExtractInputs ( IndexList  filterIndices, ref IVector[]  extracted  )

inline

Extracts the specified vectors of input parameters from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors to extract (i.e. which data elements to exclude).

Parameters

extracted	Table where extracted vectors are stored.
filterIndices	List of indices of those elements of the current sampled data set that are extracted.

void IG.Num.SampledDataSet.ExtractInputsComplement ( IndexList  filterIndices, ref IVector[]  extracted  )

inline

Extracts the specified vectors (complement of the index list) of input parameters from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors NOT to extract (i.e. which data elements to include).

Parameters

extracted	Table where extracted vectors are stored.
filterIndices	List of indices of those elements of the current sampled data set that are extracted.

void IG.Num.SampledDataSet.ExtractOutputs ( ref IVector[]  extracted )

inline

Extracts vectors of output values from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed).

Parameters

extracted

Table where extracted vectors are stored.

void IG.Num.SampledDataSet.ExtractOutputs ( IndexList  filterIndices, ref IVector[]  extracted  )

inline

Extracts the specified vectors of output values from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors to extract (i.e. which data elements to exclude).

Parameters

extracted	Table where extracted vectors are stored.
filterIndices	List of indices of those elements of the current sampled data set that are extracted.

void IG.Num.SampledDataSet.ExtractOutputsComplement ( IndexList  filterIndices, ref IVector[]  extracted  )

inline

Extracts the specified vectors (complement of the index list) of output values from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors NOT to extract (i.e. which data elements to include).

Parameters

extracted	Table where extracted vectors are stored.
filterIndices	List of indices of those elements of the current sampled data set that are extracted.

void IG.Num.SampledDataSet.CopyInputs ( ref IVector[]  extracted )

inline

Copies vectors of input parameters from the current sampled data set, and stores them to the specified array. References of the extracted vectors aer stored (no deep copying performed).

Parameters

extracted

Table where extracted vectors are stored.

void IG.Num.SampledDataSet.CopyInputs ( IndexList  filterIndices, ref IVector[]  extracted  )

inline

Copies the specified vectors of input parameters from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors to extract (i.e. which sampled elements to exclude).

Parameters

extracted	Table where extracted vectors are stored.
filterIndices	List of indices of those elements of the current sampled data set that are extracted.

void IG.Num.SampledDataSet.CopyInputsComplement ( IndexList  filterIndices, ref IVector[]  extracted  )

inline

Copies the specified vectors (complement of the index list) of input parameters from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors NOT to extract (i.e. which data elements to include).

Parameters

extracted	Table where extracted vectors are stored.
filterIndices	List of indices of those elements of the current sampled data set that are extracted.

void IG.Num.SampledDataSet.CopyOutputs ( ref IVector[]  extracted )

inline

Copies vectors of output values from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed).

Parameters

extracted

Table where extracted vectors are stored.

void IG.Num.SampledDataSet.CopyOutputs ( IndexList  filterIndices, ref IVector[]  extracted  )

inline

Copies the specified vectors of output values from the current sampled data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors to extract (i.e. which data elements to exclude).

Parameters

extracted	Table where extracted vectors are stored.
filterIndices	List of indices of those elements of the current sampled data set that are extracted.

void IG.Num.SampledDataSet.CopyOutputsComplement ( IndexList  filterIndices, ref IVector[]  extracted  )

inline

Copies the specified vectors (complement of the index list) of output values from the current data set, and stores them to the specified table. References of the extracted vectors aer stored (no deep copying performed). An index list determines which vectors NOT to extract (i.e. which sampled data elements to include).

Parameters

extracted	Table where extracted vectors are stored.
filterIndices	List of indices of those elements of the current data set that are extracted.

void IG.Num.SampledDataSet.ExtractFilteredData ( IndexList  filterIndices, ref IVector[]  extracted, bool  complement, bool  outputData, bool  copyValues  )

inline

Extract extracts.

Extract the specified input or output vectors from the current set, and stored them in the specified array of vectors.

Parameters

filterIndices	List of filter indices that specify which element to extract from or omit. Can be null, in this case it is taken that there are no filter indices.
extracted	Array where the extracted vectors are stored.
complement	If true then vectors are extracted from those elements whose indices are NOT contained in filterIndices list. If false then vectors are extracted from those elements whose indices ARE i nthe filterIndices list.
outputData	If true then vectors of output values are extracted, otherwise vectors of input parameters are extracted.
copyValues	If true then extracted vectors are copied component-wise. If false then only references of extracted vectors are copied.

References IG.Num.VectorBase.Copy(), and IG.Lib.SortedUniqueItemList< Type >.Length.

int IG.Num.SampledDataSet.GetNumNullElemets ( )

inline

Returns number of null elements of the current sampled data set.

$A Igor Feb12;

Referenced by IG.Script.LoadableScriptShellNeuralBase.GatherParallelResults().

int IG.Num.SampledDataSet.GetNumInputDuplicates ( )

inline

Returns number of elements of the current sampled data set with duplicated input parameters.

Vectors of input parameters are considered the same if both are null or all components are the same (i.e., comparison is performed component-wise rather than by reference).

elements that are null are not counted as duplicates.

For each group of n elements with the same input parameters, n-1 is added to the returned number.

$A Igor Feb12;

Referenced by IG.Script.LoadableScriptShellNeuralBase.GatherParallelResults().

void IG.Num.SampledDataSet.RemoveInputDuplicates ( )

inline

Removes elements with duplibated input parameters from the current sampled data set, leaving only a single element with specified input parameters. Elements that are null are also removed.

$A Igor Feb12;

Referenced by IG.Script.LoadableScriptShellNeuralBase.GatherParallelResults().

delegate double IG.Num.SampledDataSet.DistanceDelegate	(	IVector	v1,
		IVector	v2
	)

static void IG.Num.SampledDataSet.SaveBinary ( SampledDataSet  sampledData, string  filePath  )

inlinestatic

Saves the specified sempled data to the specified file in binary format. The file is owerwritten if it exists.

Parameters

sampledData	Object that is saved to a file.
filePath	Path to the file where sampled data is saved.

References IG.Lib.UtilSystem.SaveBinary().

static void IG.Num.SampledDataSet.LoadBinary ( string  filePath, ref SampledDataSet  dataDefRestored  )

inlinestatic

Restores sampled data from the specified file in binary format.

Parameters

filePath	File from which sampled data is restored.
dataDefRestored	Sampled data that is restored.

References IG.Lib.UtilSystem.LoadBinary().

static void IG.Num.SampledDataSet.SaveJson ( SampledDataSet  sampledData, string  filePath  )

inlinestatic

Saves the specified sempled data to the specified JSON file. The file is owerwritten if it exists.

Parameters

sampledData	Object that is saved to a file.
filePath	Path to the file where sampled data is saved.

Referenced by IG.Script.LoadableScriptShellNeuralBase.CreateDistortedModelData(), IG.Script.LoadableScriptShellNeuralBase.GatherParallelResults(), and IG.Script.LoadableScriptShellNeuralBase.ParSimRunJob().

static void IG.Num.SampledDataSet.LoadJson ( string  filePath, ref SampledDataSet  dataDefRestored  )

inlinestatic

Restores sampled data from the specified file in JSON format.

Parameters

filePath	File from which sampled data is restored.
dataDefRestored	Sampled data that is restored by deserialization.

Referenced by IG.Script.ScriptAppBase.DataStructuresFunctionTestCsvWriteDefinitionAndData(), IG.Script.LoadableScriptShellNeuralBase.ParSimAddResults(), IG.Num.InputOutputDataDefiniton.SupplementDataDefinition(), and IG.Script.LoadableScriptShellNeuralBase.TrainANN().

static void IG.Num.SampledDataSet.LoadSampledDataCombinedOutputsJSON ( ref SampledDataSet  sampledDat, string  directoryPath, params string[]  fileNames  )

inlinestatic

Loads sampled data and Definition data from multible CSV files. Sampled data consist of one output and multiple input parameters. Input parameters are the same in all files, output parameter are different.

Parameters

sampledDat	Sampled data set.
directoryPath	Path to the file where sampled data are saved.
fileNames	Name of the files where sampled data are saved.

$A Tako78 Mar11;

static void IG.Num.SampledDataSet.LoadSampledDataCombinedOutputsJSON ( ref SampledDataSet  sampledData, params string[]  fileNames  )

inlinestatic

Loads sampled data and Definition data from multiple CSV files. Sampled data consist of one output and multiple input parameters. Input parameters are the same in all files but output parameter should be different.

Parameters

fileNames	Path to the file where sampled data are saved.
sampledData	Sampled data set.

$A Tako78 Mar11;

static void IG.Num.SampledDataSet.SaveSampledDataJson ( string  filePath, SampledDataSet  sampledData  )

inlinestatic

Saves network's sampled data to the specified JSON file. File is owerwritten if it exists.

Parameters

filePath	Path to the file where sampled data is saved.
sampledData	Sampled data to be saved to a JSON file.

$A Tako78 Mar11;

static void IG.Num.SampledDataSet.SaveDefinitionDataJson ( string  filePath, InputOutputDataDefiniton  definitionData  )

inlinestatic

Saves network's definition data to the specified JSON file. File is owerwritten if it exists.

Parameters

filePath	Path to the file where definition data is saved.
definitionData	Definition data to be saved to a JSON file.

$A Tako78 Maj31;

static void IG.Num.SampledDataSet.LoadSampledDataJson ( string  filePath, ref SampledDataSet  sampledData  )

inlinestatic

Restores sampled data from the specified file in JSON format.

Parameters

filePath	File from which sampled data is restored.
sampledData	Sampled data to be loaded.

$A Tako78 Mar11;

Referenced by IG.Num.TestClass.LoadSampledDataCombinedOutputsJSON().

static void IG.Num.SampledDataSet.LoadSampledDataCSVinOneLine ( string  filePath, int  inputLenght, int  outputLenght, bool  namesSpecified, bool  descriptionSpecified, bool  titleSpecified, ref SampledDataSet  sampledData, ref InputOutputDataDefiniton  definitionData  )

inlinestatic

Loads sampled data and definition data from single CSV file.

Parameters

filePath	Path to the file where sampled data are saved.
inputLenght	Lenght of input parameters.
outputLenght	Lenght of output parameters.
namesSpecified	Flag if names are specified in the file.
descriptionSpecified	Flag if definitions (descriptions, defaultValue, boundDefiner, minValue, maxValue) are specified in the file.
titleSpecified	Specifies whether title is specified in the file.
sampledData	Sampled data set.
definitionData	Definition data set.

$A Tako78 Mar11; June27;

References IG.Num.InputOutputElementDefinition.BoundsDefined, IG.Num.InputElementDefinition.DefaultValue, IG.Num.InputOutputElementDefinition.MaximalValue, and IG.Num.InputOutputElementDefinition.MinimalValue.

static void IG.Num.SampledDataSet.LoadSampledDataCSV ( string  filePath, int  inputLenght, int  outputLenght, bool  namesSpecified, bool  titleSpecified, bool  descriptionSpecified, ref SampledDataSet  sampledData, ref InputOutputDataDefiniton  definitionData  )

inlinestatic

Loads sampled data and definition data from single CSV file.

Parameters

filePath	Path to the file where sampled data are saved.
inputLenght	Lenght of input parameters.
outputLenght	Lenght of output parameters.
namesSpecified	Flag if names are specified in the file.
titleSpecified	Determines whether title is specified in the file.
descriptionSpecified	Flag if descriptions are specified in the file.
sampledData	Sampled data set.
definitionData	Definition data set.

$A Tako78 Apr11, June24;

Referenced by IG.Neural.NeuralAllpicationCommands.cmdTestSerializationNeuralCSV().

static void IG.Num.SampledDataSet.LoadDefinitionDataCSV ( string  filePath, int  inputLenght, int  outputLenght, ref InputOutputDataDefiniton  definitionData  )

inlinestatic

Loads definition data from CSV file.

Parameters

filePath	Path to the file where definition data are saved.
inputLenght	Lenght of input parameters.
outputLenght	Lenght of output parameters.
definitionData	Definition data set.

$A Tako78 Mar11; June24;

References IG.Num.InputOutputElementDefinition.BoundsDefined, IG.Num.InputElementDefinition.DefaultValue, IG.Num.InputOutputElementDefinition.MaximalValue, and IG.Num.InputOutputElementDefinition.MinimalValue.

static void IG.Num.SampledDataSet.SaveSampledDataCSVinOneLine ( string  filePath, SampledDataSet  sampledData, bool  namesSpecified, bool  titleSpecified, bool  descriptionSpecified, InputOutputDataDefiniton  definitionData  )

inlinestatic

Saves sampled data and Definition data to single CSV file.

Parameters

filePath	Path to the file where sampled data will be saved.
sampledData	Sampled data set.
namesSpecified	Flag if names will be written in the file.
titleSpecified	Whether title will be written.
descriptionSpecified	Flag if descriptions (descriptions, defaultValue, boundDefiner, minValue, maxValue) will be written in the file.
definitionData	Definition data set.

$A Tako78 Mar11; June27;

References IG.Num.InputOutputElementDefinition.BoundsDefined, IG.Num.InputElementDefinition.DefaultValue, IG.Num.InputOutputElementDefinition.Description, IG.Num.InputOutputDataDefiniton.GetInputElement(), IG.Num.SampledDataSet.GetInputParameters(), IG.Num.InputOutputDataDefiniton.GetOutputElement(), IG.Num.SampledDataSet.GetOutputValues(), IG.Num.SampledDataSet.InputLength, IG.Num.SampledDataSet.Length, IG.Num.InputOutputElementDefinition.MaximalValue, IG.Num.InputOutputElementDefinition.MinimalValue, IG.Num.InputOutputElementDefinition.Name, IG.Num.SampledDataSet.OutputLength, and IG.Num.InputOutputElementDefinition.Title.

static void IG.Num.SampledDataSet.SaveSampledDataCSV ( string  filePath, SampledDataSet  sampledData, bool  namesSpecified, bool  titlesSpecified, bool  descriptionSpecified, InputOutputDataDefiniton  definitionData  )

inlinestatic

Saves sampled data and Definition data to single CSV file.

Parameters

filePath	Path to the file where sampled data will be saved.
sampledData	Sampled data set.
namesSpecified	Flag if names will be written in the file.
titlesSpecified	Whether title will be written to the file.
descriptionSpecified	Flag if descriptions will be written in the file.
definitionData	Definition data set.

$A Tako78 Mar11; June27;

References IG.Num.InputOutputElementDefinition.Description, IG.Num.InputOutputDataDefiniton.GetInputElement(), IG.Num.SampledDataSet.GetInputParameters(), IG.Num.InputOutputDataDefiniton.GetOutputElement(), IG.Num.SampledDataSet.GetOutputValues(), IG.Num.SampledDataSet.InputLength, IG.Num.SampledDataSet.Length, IG.Num.InputOutputElementDefinition.Name, IG.Num.SampledDataSet.OutputLength, and IG.Num.InputOutputElementDefinition.Title.

Referenced by IG.Neural.NeuralAllpicationCommands.cmdTestSerializationNeuralCSV().

static void IG.Num.SampledDataSet.SaveDefinitionDataCSV ( string  filePath, InputOutputDataDefiniton  definitionData  )

inlinestatic

Saves definition data to CSV file.

Parameters

filePath	Path to the file where definition data will be saved.
definitionData	Definition data set.

$A Tako78 Mar11; June27;

References IG.Num.InputOutputElementDefinition.BoundsDefined, IG.Num.InputElementDefinition.DefaultValue, IG.Num.InputOutputElementDefinition.Description, IG.Num.InputOutputDataDefiniton.GetInputElement(), IG.Num.InputOutputDataDefiniton.InputLength, IG.Num.InputOutputElementDefinition.MaximalValue, IG.Num.InputOutputElementDefinition.MinimalValue, IG.Num.InputOutputElementDefinition.Name, IG.Num.InputOutputDataDefiniton.OutputLength, and IG.Num.InputOutputElementDefinition.Title.

static void IG.Num.SampledDataSet.SampledDataCombineOutputs ( ref SampledDataSet  result, params SampledDataSet[]  individualSets  )

inlinestatic

Loads sampled data and Definition data from multible CSV files. Sampled data consist of one output and multiple input parameters. Input parameters are the same in all files, output parameter are different.

Parameters

result	Sampled data set with combined outputs.
individualSets	Different sampled data sets with the same inputs and different outputs.

$A Tako78 Mar11;

References IG.Num.SampledDataSet.GetInputParameters(), IG.Num.SampledDataSet.GetOutputValues(), IG.Num.SampledDataSet.InputLength, IG.Num.SampledDataSet.Length, and IG.Num.SampledDataSet.OutputLength.

Referenced by IG.Num.TestClass.LoadSampledDataCombinedOutputsJSON().

static int IG.Num.SampledDataSet.GetNumNullElemets ( SampledDataSet  sampledDataSet )

inlinestatic

Returns number of null elements of the specified sampled data set.

Parameters

sampledDataSet

Sampled set for which number of null elements is returned.

$A Igor Feb12;

References IG.Num.SampledDataSet.Length.

static int IG.Num.SampledDataSet.GetNumInputDuplicates ( SampledDataSet  sampledSet )

inlinestatic

Returns the number of elements of the specified sampled data set with duplicated input parameters.

Vectors of input parameters are considered the same if both are null or all components are the same (i.e., comparison is performed component-wise rather than by reference).

elements that are null are not counted as duplicates.

For each group of n elements with the same input parameters, n-1 is added to the returned number.

Parameters

sampledSet

Sampled data set for which number of duplicated input parameters is returned.

$A Igor Feb12;

References IG.Num.VectorBase.Compare(), IG.Num.SampledDataElement.Index, IG.Num.SampledDataElement.InputParameters, and IG.Num.SampledDataSet.Length.

static void IG.Num.SampledDataSet.RemoveInputDuplicates ( SampledDataSet  sampledSet )

inlinestatic

Removes elements with duplicated input parameters, leaving only a single element with specified input parameters. Elements that are null are also removed.

Vectors of input parameters are considered the same if both are null or all components are the same (i.e., comparison is performed component-wise rather than by reference).

Parameters

sampledSet

Sampled data set from which elemets with duplicated input parameters are removed.

$A Igor Feb12;

References IG.Num.VectorBase.Compare(), IG.Num.SampledDataElement.Index, IG.Num.SampledDataElement.InputParameters, and IG.Num.SampledDataSet.Length.

static SampledDataSet IG.Num.SampledDataSet.CreateExampleLinear ( int  inputLength, int  outputLength, int  numElements  )

inlinestatic

Craates and returns a sample data set object where input parameters are calculated randomly in a box-like domain, and output parameters are calculated by quadratic functions with random coefficients. Domain where sampling points are generated is a cartesian product of intervals [-1, 1].

Parameters

inputLength	Dimension of input data (parameters).
outputLength	Number of output values.
numElements	Number of input/output pairs used as sampled data.

References IG.Num.BoundingBoxBase.Create().

static SampledDataSet IG.Num.SampledDataSet.CreateExampleLinear ( int  inputLength, int  outputLength, int  numElements, IBoundingBox  region  )

inlinestatic

Craates and returns a sample data set object where input parameters are calculated randomly in the specified box-like domain, and output parameters are calculated by quadratic functions with random coefficients.

Parameters

inputLength	Dimension of input data (parameters).
outputLength	Number of output values.
numElements	Number of input/output pairs used as sampled data.
region	Bounding box defining the region in the space (of dimension inputLength) from which samples (input parameters) are taken randomly.

References IG.Num.RandomGenerator.Global.

static SampledDataSet IG.Num.SampledDataSet.CreateExampleLinear ( int  inputLength, int  outputLength, int  numElements, IBoundingBox  region, IRandomGenerator  rand  )

inlinestatic

Craates and returns a sample data set object where input parameters are calculated randomly in the specified box-like domain, and output parameters are calculated by quadratic functions with random coefficients.

Parameters

inputLength	Dimension of input data (parameters).
outputLength	Number of output values.
numElements	Number of input/output pairs used as sampled dataa.
region	Bounding box defining the region in the space (of dimension inputLength) from which samples (input parameters) are taken randomly.
rand	Random number generator that is used for sampling.

References IG.Num.IRandomGenerator.NextDouble(), and IG.Num.IVector.SetRandom().

static SampledDataSet IG.Num.SampledDataSet.CreateExampleQuadratic ( int  inputLength, int  outputLength, int  numElements  )

inlinestatic

Craates and returns a sample data set object where input parameters are calculated randomly in a box-like domain, and output parameters are calculated by quadratic functions with random coefficients. Domain where sampling points are generated is a cartesian product of intervals [-1, 1].

Parameters

inputLength	Dimension of input data (parameters).
outputLength	Number of output values.
numElements	Number of input/output pairs used as sampled data.

References IG.Num.BoundingBoxBase.Create().

Referenced by IG.Neural.NeuralTadej.ExampleQuadratic(), and IG.Num.NeuralApproximatorBase.ExampleQuadratic().

static SampledDataSet IG.Num.SampledDataSet.CreateExampleQuadratic ( int  inputLength, int  outputLength, int  numElements, IBoundingBox  region  )

inlinestatic

Craates and returns a sample data set object where input parameters are calculated randomly in the specified box-like domain, and output parameters are calculated by quadratic functions with random coefficients.

Parameters

inputLength	Dimension of input data (parameters).
outputLength	Number of output values.
numElements	Number of input/output pairs used as sampled data.
region	Bounding box defining the region in the space (of dimension inputLength) from which samples (input parameters) are taken randomly.

References IG.Num.RandomGenerator.Global.

static SampledDataSet IG.Num.SampledDataSet.CreateExampleQuadratic ( int  inputLength, int  outputLength, int  numElements, IBoundingBox  region, IRandomGenerator  rand  )

inlinestatic

Craates and returns a sample data set object where input parameters are calculated randomly in the specified box-like domain, and output parameters are calculated by quadratic functions with random coefficients.

Parameters

inputLength	Dimension of input data (parameters).
outputLength	Number of output values.
numElements	Number of input/output pairs used as sampled data.
region	Bounding box defining the region in the space (of dimension inputLength) from which samples (input parameters) are taken randomly.
rand	Random number generator that is used for sampling.

References IG.Num.ScalarFunctionQuadratic.GetNumConstants(), IG.Num.IRandomGenerator.NextDouble(), IG.Num.IMatrix.SetRandom(), IG.Num.IVector.SetRandom(), and IG.Num.MatrixBase.SymmetricPartPlain().

static SampledDataSet IG.Num.SampledDataSet.CreateExample ( int  inputLength, int  outputLength, int  numElements, IBoundingBox  region, IScalarFunctionUntransformed[]  functions, IRandomGenerator  rand  )

inlinestatic

Craates and returns a sample data set object where input parameters are calculated randomly in the specified box-like domain, and output parameters are calculated by the specified scalar functions.

Parameters

inputLength	Dimension of input data (parameters).
outputLength	Number of output values.
numElements	Number of input/output pairs used as sampled data.
region	Bounding box defining the region in the space (of dimension inputLength) from which samples (input parameters) are taken randomly.
functions	Scalar-valued functions (of vector argument) that are applied to input parameters to produce output values of the sampled data.
rand	Random number generator that is used for sampling.

References IG.Num.SampledDataSet.AddElement(), IG.Num.IBoundingBox.Dimension, and IG.Num.IBoundingBox.GetRandomPoint().

static SampledDataSet IG.Num.SampledDataSet.CreateExampleSimple ( int  inputLength, int  outputLength, int  numElements  )

inlinestatic

Craates and returns a sample object of the encompassing class.

Parameters

inputLength	Dimension of input data (parameters).
outputLength	Number of output values.
numElements	Number of input/output pairs used as sampled data.

References IG.Num.SampledDataSet.AddElement(), IG.Num.SampledDataSet.InputLength, and IG.Num.SampledDataSet.OutputLength.

Referenced by IG.Neural.NeuralAllpicationCommands.cmdTestSerializationNeural(), and IG.Neural.NeuralAllpicationCommands.cmdTestSerializationNeuralCSV().

override string IG.Num.SampledDataSet.ToString ( )

inline

References IG.Num.SampledDataElement.InputParameters, IG.Num.SampledDataElement.OutputValues, and IG.Num.IVector.ToString().

Member Data Documentation

int IG.Num.SampledDataSet._inputLength = -1

protected

int IG.Num.SampledDataSet._outputLength = -1

protected

Property Documentation

SampledDataElement [] IG.Num.SampledDataSet.Data

getset

Gets or sets sampled data, as an array of data elements.

int IG.Num.SampledDataSet.Length

get

Gets the number of sampled data elements (input/output pairs) contained by the current sampled data set.

Referenced by IG.Num.SampledDataSet.Add(), IG.Num.SampledDataSetDto.CopyFromPlain(), IG.Neural.NeuralTadej.CopyTrainingData(), IG.Script.LoadableScriptShellNeuralBase.GatherParallelResults(), IG.Num.SampledDataSet.GetNumInputDuplicates(), IG.Num.SampledDataSet.GetNumNullElemets(), IG.Num.NeuralApproximatorBase.GetTrainingData(), IG.Num.NeuralApproximatorBase.GetVerificationData(), IG.Neural.NeuralTadej.neuronsDataRange(), IG.Script.LoadableScriptShellNeuralBase.ParSimAddResults(), IG.Num.SampledDataSet.RemoveInputDuplicates(), IG.Neural.NeuralTadej.SampledDataCombineOutputs(), IG.Num.SampledDataSet.SampledDataCombineOutputs(), IG.Num.SampledDataSet.SaveSampledDataCSV(), IG.Num.SampledDataSet.SaveSampledDataCSVinOneLine(), IG.Neural.NeuralTadej.SaveTrainingDataCSV(), IG.Neural.NeuralTadej.SaveTrainingDataCSVinOneLine(), IG.Num.NeuralApproximatorBase.SetTrainingAndVerificationData(), and IG.Neural.NeuralTadej.SmoothingTrainingData().

int IG.Num.SampledDataSet.InputLength

getset

Number of input parameters in sampled data elements. Less than 0 means unspecified.

Referenced by IG.Num.SampledDataSetDto.CopyFromPlain(), IG.Neural.NeuralTadej.CopyTrainingData(), IG.Num.SampledDataSet.CreateExampleSimple(), IG.Neural.NeuralTadej.neuronsDataRange(), IG.Num.SampledDataCsv.RestoreData(), IG.Neural.NeuralTadej.SampledDataCombineOutputs(), IG.Num.SampledDataSet.SampledDataCombineOutputs(), IG.Num.SampledDataSet.SaveSampledDataCSV(), IG.Num.SampledDataSet.SaveSampledDataCSVinOneLine(), IG.Neural.NeuralTadej.SaveTrainingDataCSV(), IG.Neural.NeuralTadej.SaveTrainingDataCSVinOneLine(), and IG.Neural.NeuralTadej.SmoothingTrainingData().

int IG.Num.SampledDataSet.OutputLength

getset

Number of output values in sampled data elements. Less than 0 means unspecified.

Referenced by IG.Num.SampledDataSetDto.CopyFromPlain(), IG.Neural.NeuralTadej.CopyTrainingData(), IG.Num.SampledDataSet.CreateExampleSimple(), IG.Neural.NeuralTadej.neuronsDataRange(), IG.Num.SampledDataCsv.RestoreData(), IG.Neural.NeuralTadej.SampledDataCombineOutputs(), IG.Num.SampledDataSet.SampledDataCombineOutputs(), IG.Num.SampledDataSet.SaveSampledDataCSV(), IG.Num.SampledDataSet.SaveSampledDataCSVinOneLine(), IG.Neural.NeuralTadej.SaveTrainingDataCSV(), IG.Neural.NeuralTadej.SaveTrainingDataCSVinOneLine(), and IG.Neural.NeuralTadej.SmoothingTrainingData().

SampledDataElement IG.Num.SampledDataSet.this[int which]

getset

Gets or sets specific data element.

Parameters

which

Index of data element.

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

• igbase/numeric/approximation/sampleddata/SampledData.cs