IGLib 1.4
The IGLib base library for development of numerical, technical and business applications.

IG::Num::SampledDataSet Class Reference

Sampled data consisting of elements of which each contains vector of input parameters and output values. NOT thread safe. More...

List of all members.

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. Measure of distance is defined by the DistanceDelegate delegate.Beside its basic comparison function, this class also contains a number of methods for calculation of distance between vectors or data elemets according to definition by the distacnce calculation delegate. 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. Measure of distance is defined by the DistanceDelegate delegate.Beside its basic comparison function, this class also contains a number of methods for calculation of distance between vectors or data elemets according to definition by the distacnce calculation delegate. More...

Public Member Functions

 SampledDataSet ()
 SampledDataSet (int inputLength, int outputLength)
List< SampledDataElementGetElementList ()
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. In this way, element indices can be used to directly access sampled data elements (without a search).
List< SampledDataElementGetElementListCopy ()
 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< SampledDataElementGetSortedElemetnList (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).
List< SampledDataElementGetInputDistanceSortedElemetnList (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.
List< SampledDataElementGetOutputDistanceSortedElemetnList (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.
virtual void Clear ()
void AddElement (SampledDataElement element)
 Adda a new element to sampled data.
void Add (SampledDataSet addedSet)
 Adds elements of another sampled data ser to the current sampled data. Only references are copied.
void Add (params SampledDataElement[] addedSet)
 Adds array of sampled data elements to teh current sampled data set. Only references are copied.
IVector GetInputParameters (int which)
 Returns the vector of input parameters of the specified element of the sampled data set.
void SetInputParameters (int which, IVector parameters)
 Sets the vector of input parameters of the specified element of the sampled data set.
virtual IVector GetOutputValues (int which)
 Returns the vector of output values of the specified element of the sampled data set.
void SetOutputValues (int which, IVector values)
 Sets the vector of output values of the specified element of the sampled data set.
void GetInputRange (ref IBoundingBox bounds)
 Calculates range of input parameters of the current sampled data set, and stores it to the specified bounding box.
void GetOutputRange (ref IBoundingBox bounds)
 Calculates range of output values of the current sampled data set, and stores it to the specified bounding box.
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
void ExtractFilteredData (IndexList filterIndices, ref IVector[] extracted, bool complement, bool outputData, bool copyValues)
 Extract extracts.
int GetNumNullElemets ()
 Returns number of null elements of the current sampled data set.
int GetNumInputDuplicates ()
 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.
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.
delegate double DistanceDelegate (IVector v1, IVector v2)
override string ToString ()

Static Public Member Functions

static void SaveJson (SampledDataSet sampledData, string filePath)
 Saves the specified sempled data to the specified JSON file. The file is owerwritten if it exists.
static void LoadJson (string filePath, ref SampledDataSet dataDefRestored)
 Restores sampled data from the specified file in JSON format.
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.
static void LoadSampledDataCombinedOutputsJSON (ref SampledDataSet sampledData, 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 but output parameter should be different.
static void SaveSampledDataJson (string filePath, SampledDataSet sampledData)
 Saves network's sampled data to the specified JSON file. File is owerwritten if it exists.
static void SaveDefinitionDataJson (string filePath, InputOutputDataDefiniton sampledData)
 Saves network's definition data to the specified JSON file. File is owerwritten if it exists.
static void LoadSampledDataJson (string filePath, ref SampledDataSet sampledData)
 Restores sampled data from the specified file in JSON format.
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.

Parameters:
filePathPath to the file where sampled data are saved.
inputLenghtLenght of input parameters.
outputLenghtLenght of output parameters.
namesSpecifiedFlag if names are specified in the file.
descriptionSpecifiedFlag if definitions (descriptions, defaultValue, boundDefiner, minValue, maxValue) are specified in the file.
trainingDataSampled data set.
definitionDataDefinition data set.

$A Tako78 Mar11; June27;.

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.

Parameters:
filePathPath to the file where sampled data are saved.
inputLenghtLenght of input parameters.
outputLenghtLenght of output parameters.
namesSpecifiedFlag if names are specified in the file.
descriptionSpecifiedFlag if descriptions are specified in the file.
trainingDataSampled data set.
definitionDataDefinition data set.

$A Tako78 Apr11, June24;.

static void LoadDefinitionDataCSV (string filePath, int inputLenght, int outputLenght, ref InputOutputDataDefiniton definitionData)
 Loads definition data from CSV file.
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.
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.
static void SaveDefinitionDataCSV (string filePath, InputOutputDataDefiniton definitionData)
 Saves definition data to CSV file.
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.
static int GetNumNullElemets (SampledDataSet sampledDataSet)
 Returns number of null elements of the specified sampled data set.
static int GetNumInputDuplicates (SampledDataSet sampledSet)
 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.
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. 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).
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].
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.
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.
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].
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.
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.
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.
static SampledDataSet CreateExampleSimple (int inputLength, int outputLength, int numElements)
 Craates and returns a sample object of the encompassing class.

Protected Attributes

internal List< SampledDataElementElementList = new List<SampledDataElement>()
int _inputLength = -1
int _outputLength = -1

Properties

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

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]
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).

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:
comparerComparer 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:
referencePointReference point, sampled data elements are sorted according to the distance to this point.
distanceFunctionDelegate 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:
referencePointReference point, sampled data elements are sorted according to the distance to this point.
distanceFunctionDelegate that definines distance between two vectors for the purpose of sorting.
virtual void IG::Num::SampledDataSet::Clear ( ) [inline, virtual]
void IG::Num::SampledDataSet::AddElement ( SampledDataElement  element) [inline]

Adda a new element to sampled data.

Parameters:
elementData element that is added to the sampled data set. If element is null then nothing is added (but no exception thrown).
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:
addedSetSampled data whose elements are added to the current sampled data.
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:
addedSetSampled 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:
whichIndex of the sampled data element within the sampled data set.
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:
whichIndex of the sampled data element within the sampled data set.
parametersVector of input parameters to be set.
virtual IVector IG::Num::SampledDataSet::GetOutputValues ( int  which) [inline, virtual]

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

Parameters:
whichIndex of the data element within the sampled set.
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:
whichIndex of the data element within the sampled data set.
valuesVector of output values to be set.
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:
boundsBounding box wehere bounds on input parameters are stored.
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:
boundsBounding box wehere bounds on output values are stored.
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:
extractedTable 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:
extractedTable where extracted vectors are stored.
filterIndicesList 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:
extractedTable where extracted vectors are stored.
filterIndicesList 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:
extractedTable 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:
extractedTable where extracted vectors are stored.
filterIndicesList 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:
extractedTable where extracted vectors are stored.
filterIndicesList 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:
extractedTable 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:
extractedTable where extracted vectors are stored.
filterIndicesList 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:
extractedTable where extracted vectors are stored.
filterIndicesList 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:
extractedTable 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:
extractedTable where extracted vectors are stored.
filterIndicesList 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:
extractedTable where extracted vectors are stored.
filterIndicesList 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:
filterIndicesList 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.
extractedArray where the extracted vectors are stored.
complementIf 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.
outputDataIf true then vectors of output values are extracted, otherwise vectors of input parameters are extracted.
copyValuesIf true then extracted vectors are copied component-wise. If false then only references of extracted vectors are copied.
int IG::Num::SampledDataSet::GetNumNullElemets ( ) [inline]

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

$A Igor Feb12;

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;

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;

delegate double IG::Num::SampledDataSet::DistanceDelegate ( IVector  v1,
IVector  v2 
)
static void IG::Num::SampledDataSet::SaveJson ( SampledDataSet  sampledData,
string  filePath 
) [inline, static]

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

Parameters:
sampledDataObject that is saved to a file.
filePathPath to the file where sampled data is saved.
static void IG::Num::SampledDataSet::LoadJson ( string  filePath,
ref SampledDataSet  dataDefRestored 
) [inline, static]

Restores sampled data from the specified file in JSON format.

Parameters:
filePathFile from which sampled data is restored.
dataDefRestoredSampled data that is restored by deserialization.
static void IG::Num::SampledDataSet::LoadSampledDataCombinedOutputsJSON ( ref SampledDataSet  sampledDat,
string  directoryPath,
params string[]  fileNames 
) [inline, static]

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:
sampledDatSampled data set.
directoryPathPath to the file where sampled data are saved.
fileNamesName of the files where sampled data are saved.

$A Tako78 Mar11;

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

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 but output parameter should be different.

Parameters:
fileNamesPath to the file where sampled data are saved.
sampledDataSampled data set.

$A Tako78 Mar11;

static void IG::Num::SampledDataSet::SaveSampledDataJson ( string  filePath,
SampledDataSet  sampledData 
) [inline, static]

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

Parameters:
filePathPath to the file where sampled data is saved.

$A Tako78 Mar11;

static void IG::Num::SampledDataSet::SaveDefinitionDataJson ( string  filePath,
InputOutputDataDefiniton  sampledData 
) [inline, static]

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

Parameters:
filePathPath to the file where definition data is saved.

$A Tako78 Maj31;

static void IG::Num::SampledDataSet::LoadSampledDataJson ( string  filePath,
ref SampledDataSet  sampledData 
) [inline, static]

Restores sampled data from the specified file in JSON format.

Parameters:
filePathFile from which sampled data is restored.

$A Tako78 Mar11;

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

Loads sampled data and definition data from single CSV file.

Parameters:
filePathPath to the file where sampled data are saved.
inputLenghtLenght of input parameters.
outputLenghtLenght of output parameters.
namesSpecifiedFlag if names are specified in the file.
descriptionSpecifiedFlag if definitions (descriptions, defaultValue, boundDefiner, minValue, maxValue) are specified in the file.
trainingDataSampled data set.
definitionDataDefinition data set.

$A Tako78 Mar11; June27;.

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

Loads sampled data and definition data from single CSV file.

Parameters:
filePathPath to the file where sampled data are saved.
inputLenghtLenght of input parameters.
outputLenghtLenght of output parameters.
namesSpecifiedFlag if names are specified in the file.
descriptionSpecifiedFlag if descriptions are specified in the file.
trainingDataSampled data set.
definitionDataDefinition data set.

$A Tako78 Apr11, June24;.

static void IG::Num::SampledDataSet::LoadDefinitionDataCSV ( string  filePath,
int  inputLenght,
int  outputLenght,
ref InputOutputDataDefiniton  definitionData 
) [inline, static]

Loads definition data from CSV file.

Parameters:
filePathPath to the file where definition data are saved.
inputLenghtLenght of input parameters.
outputLenghtLenght of output parameters.
definitionDataDefinition data set.

$A Tako78 Mar11; June24;

static void IG::Num::SampledDataSet::SaveSampledDataCSVinOneLine ( string  filePath,
SampledDataSet  sampledData,
bool  namesSpecified,
bool  titleSpecified,
bool  descriptionSpecified,
InputOutputDataDefiniton  definitionData 
) [inline, static]

Saves sampled data and Definition data to single CSV file.

Parameters:
filePathPath to the file where sampled data will be saved.
sampledDataSampled data set.
namesSpecifiedFlag if names will be written in the file.
descriptionSpecifiedFlag if descriptions (descriptions, defaultValue, boundDefiner, minValue, maxValue) will be written in the file.
definitionDataDefinition data set.

$A Tako78 Mar11; June27;

static void IG::Num::SampledDataSet::SaveSampledDataCSV ( string  filePath,
SampledDataSet  sampledData,
bool  namesSpecified,
bool  titlesSpecified,
bool  descriptionSpecified,
InputOutputDataDefiniton  definitionData 
) [inline, static]

Saves sampled data and Definition data to single CSV file.

Parameters:
filePathPath to the file where sampled data will be saved.
sampledDataSampled data set.
namesSpecifiedFlag if names will be written in the file.
descriptionSpecifiedFlag if descriptions will be written in the file.
definitionDataDefinition data set.

$A Tako78 Mar11; June27;

static void IG::Num::SampledDataSet::SaveDefinitionDataCSV ( string  filePath,
InputOutputDataDefiniton  definitionData 
) [inline, static]

Saves definition data to CSV file.

Parameters:
filePathPath to the file where definition data will be saved.
definitionDataDefinition data set.

$A Tako78 Mar11; June27;

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

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:
resultSampled data set with combined outputs.
individualSetsDifferent sampled data sets with the same inputs and different outputs.

$A Tako78 Mar11;

static int IG::Num::SampledDataSet::GetNumNullElemets ( SampledDataSet  sampledDataSet) [inline, static]

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

Parameters:
sampledDataSetSampled set for which number of null elements is returned.

$A Igor Feb12;

static int IG::Num::SampledDataSet::GetNumInputDuplicates ( SampledDataSet  sampledSet) [inline, static]

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

$A Igor Feb12;

static void IG::Num::SampledDataSet::RemoveInputDuplicates ( SampledDataSet  sampledSet) [inline, static]

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

$A Igor Feb12;

static SampledDataSet IG::Num::SampledDataSet::CreateExampleLinear ( int  inputLength,
int  outputLength,
int  numElements 
) [inline, static]

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:
inputLengthDimension of input data (parameters).
outputLengthNumber of output values.
numElementsNumber of input/output pairs used as sampled data.
static SampledDataSet IG::Num::SampledDataSet::CreateExampleLinear ( int  inputLength,
int  outputLength,
int  numElements,
IBoundingBox  region 
) [inline, static]

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:
inputLengthDimension of input data (parameters).
outputLengthNumber of output values.
numElementsNumber of input/output pairs used as sampled data.
regionBounding box defining the region in the space (of dimension inputLength) from which samples (input parameters) are taken randomly.
static SampledDataSet IG::Num::SampledDataSet::CreateExampleLinear ( int  inputLength,
int  outputLength,
int  numElements,
IBoundingBox  region,
IRandomGenerator  rand 
) [inline, static]

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:
inputLengthDimension of input data (parameters).
outputLengthNumber of output values.
numElementsNumber of input/output pairs used as sampled dataa.
regionBounding box defining the region in the space (of dimension inputLength) from which samples (input parameters) are taken randomly.
randRandom number generator that is used for sampling.
static SampledDataSet IG::Num::SampledDataSet::CreateExampleQuadratic ( int  inputLength,
int  outputLength,
int  numElements 
) [inline, static]

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:
inputLengthDimension of input data (parameters).
outputLengthNumber of output values.
numElementsNumber of input/output pairs used as sampled data.
static SampledDataSet IG::Num::SampledDataSet::CreateExampleQuadratic ( int  inputLength,
int  outputLength,
int  numElements,
IBoundingBox  region 
) [inline, static]

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:
inputLengthDimension of input data (parameters).
outputLengthNumber of output values.
numElementsNumber of input/output pairs used as sampled data.
regionBounding box defining the region in the space (of dimension inputLength) from which samples (input parameters) are taken randomly.
static SampledDataSet IG::Num::SampledDataSet::CreateExampleQuadratic ( int  inputLength,
int  outputLength,
int  numElements,
IBoundingBox  region,
IRandomGenerator  rand 
) [inline, static]

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:
inputLengthDimension of input data (parameters).
outputLengthNumber of output values.
numElementsNumber of input/output pairs used as sampled data.
regionBounding box defining the region in the space (of dimension inputLength) from which samples (input parameters) are taken randomly.
randRandom number generator that is used for sampling.
static SampledDataSet IG::Num::SampledDataSet::CreateExample ( int  inputLength,
int  outputLength,
int  numElements,
IBoundingBox  region,
IScalarFunctionUntransformed[]  functions,
IRandomGenerator  rand 
) [inline, static]

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:
inputLengthDimension of input data (parameters).
outputLengthNumber of output values.
numElementsNumber of input/output pairs used as sampled data.
regionBounding box defining the region in the space (of dimension inputLength) from which samples (input parameters) are taken randomly.
functionsScalar-valued functions (of vector argument) that are applied to input parameters to produce output values of the sampled data.
randRandom number generator that is used for sampling.
static SampledDataSet IG::Num::SampledDataSet::CreateExampleSimple ( int  inputLength,
int  outputLength,
int  numElements 
) [inline, static]

Craates and returns a sample object of the encompassing class.

Parameters:
inputLengthDimension of input data (parameters).
outputLengthNumber of output values.
numElementsNumber of input/output pairs used as sampled data.
override string IG::Num::SampledDataSet::ToString ( ) [inline]

Member Data Documentation


Property Documentation

SampledDataElement [] IG::Num::SampledDataSet::Data [get, set]

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.

int IG::Num::SampledDataSet::InputLength [get, set]

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

int IG::Num::SampledDataSet::OutputLength [get, set]

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

SampledDataElement IG::Num::SampledDataSet::this[int which] [get, set]

Gets or sets specific data element.

Parameters:
whichIndex of data element.

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