NeurApp 1.1
NeurApp - software for exploring approximation by artificial neural networks on functions of one or two variables.

IG::Neural::NeuralTadej Class Reference

List of all members.

Static Public Member Functions

static void ReadAnalysisRequest (string filePath, ref IVector parameters, ref bool reqcalcobj, ref bool reqcalcconstr, ref bool reqcalcgradobj, ref bool reqcalcgradconstr, ref string cd)
 Read the analysis data from data file Format: { { p1, p2, … }, { reqcalcobj, reqcalcconstr, reqcalcgradobj, reqcalcgradconstr }, cd }.
static void GetAnalysisRequest (string requestString, ref IVector parameters, ref bool reqcalcobj, ref bool reqcalcconstr, ref bool reqcalcgradobj, ref bool reqcalcgradconstr, ref string cd)
 Read the analysis request data from data file Format: { { p1, p2, … }, { reqcalcobj, reqcalcconstr, reqcalcgradobj, reqcalcgradconstr }, cd }.
static void ReadAnalysisResult (string filePath, ref IVector parameters, ref bool calcobj, ref bool calcconstr, ref bool calcgradobj, ref bool calcgradconstr, ref double obj, ref IVector constr, ref IVector dobjdp, ref IVector[] dconstr, ref int errorcode, ref bool reqcalcobj, ref bool reqcalcconstr, ref bool reqcalcgradobj, ref bool reqcalcgradconstr)
 Read the analysis result data from data file Format:
static void GetAnalysisResult (string requestString, ref IVector parameters, ref bool calcobj, ref bool calcconstr, ref bool calcgradobj, ref bool calcgradconstr, ref double obj, ref IVector constr, ref IVector dobjdp, ref IVector[] dconstr, ref int errorcode, ref bool reqcalcobj, ref bool reqcalcconstr, ref bool reqcalcgradobj, ref bool reqcalcgradconstr)
 Read the analysis result data from data file Format:
static void LoadTrainingDataCSVinOneLine (string filePath, int inputLenght, int outputLenght, bool namesSpecified, bool descriptionSpecified, bool titleSpecified, ref SampledDataSet trainingData, ref InputOutputDataDefiniton definitionData)
 Loads training data and Definition data from single CSV file.

Parameters:
filePathPath to the file where training 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.
trainingDataTraining data set.
definitionDataDefinition data set.

$A Tako78 Mar11; June27;.

static void LoadTrainingDataCSV (string filePath, int inputLenght, int outputLenght, bool namesSpecified, bool titleSpecified, bool descriptionSpecified, ref SampledDataSet trainingData, ref InputOutputDataDefiniton definitionData)
 Loads training data and Definition data from single CSV file.

Parameters:
filePathPath to the file where training 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.
trainingDataTraining 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 SaveTrainingDataCSVinOneLine (string filePath, SampledDataSet trainingData, bool namesSpecified, bool titleSpecified, bool descriptionSpecified, InputOutputDataDefiniton definitionData)
 Saves training data and Definition data to single CSV file.
static void SaveTrainingDataCSV (string filePath, SampledDataSet trainingData, bool namesSpecified, bool titlesSpecified, bool descriptionSpecified, InputOutputDataDefiniton definitionData)
 Saves training 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 training data and Definition data from multible CSV files. Training data consist of one output and multiple input parameters. Input parameters are the same in all files, output parameter are different.
static void LoadTrainingDataCombinedOutputsJSON (ref SampledDataSet trainingData, string directoryPath, params string[] fileNames)
 Loads training data and Definition data from multible CSV files. Training data consist of one output and multiple input parameters. Input parameters are the same in all files, output parameter are different.
static void LoadTrainingDataCombinedOutputsJSON (ref SampledDataSet trainingData, params string[] fileNames)
 Loads training data and Definition data from multible CSV files. Training 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 SaveTrainingDataJson (string filePath, SampledDataSet trainingData)
 Saves network's training data to the specified JSON file. File is owerwritten if it exists.
static void SaveDefinitionDataJson (string filePath, InputOutputDataDefiniton trainingData)
 Saves network's definition data to the specified JSON file. File is owerwritten if it exists.
static void LoadSampledDataJson (string filePath, ref SampledDataSet trainingData)
 Restores training data from the specified file in JSON format.
static void LoadDefinitionDataJson (string filePath, ref InputOutputDataDefiniton definitionData)
 Restores definition data from the specified file in JSON format.
static double getStandardDeviation (List< double > doubleList)
 Returns the standard deviation.
static void SmoothingTrainingData (SampledDataSet trainingData, ref SampledDataSet smoothTrainingData, double numStandardDeviation, bool uniqueInput, bool uniqueOutput, bool zeroData)
 Check the training data set and delete unconsistant datas.
static INeuralApproximator ExampleCasting (int inputLength, int outputLength, ref SampledDataSet trainingData)
static INeuralApproximator ExampleStore (int inputLength, int outputLength, ref SampledDataSet trainingData)
static INeuralApproximator TrainNetwork (ref INeuralApproximator neuralApp)
static void StoreNetwork (string directoryPath, string fileName, string internalStateFileName, INeuralApproximator neuralApp, bool saveRestored)
static INeuralApproximator ExampleQuadratic (int inputLength, int outputLength)
static void neuronsDataRange (SampledDataSet trainingData, ref List< double[]> inputColumnSet, double inputlowerBound, double inputupperBound, ref List< double[]> outputColumnSet, double outputlowerBound, double outputupperBound)
static void CopyTrainingData (SampledDataSet trainingData, ref SampledDataSet newtrainingData)
 Copy training data set to new training data set.

Static Private Member Functions

static void TestArray0Elements ()
 Creates an array with 0 elements.

Member Function Documentation

static void IG::Neural::NeuralTadej::ReadAnalysisRequest ( string  filePath,
ref IVector  parameters,
ref bool  reqcalcobj,
ref bool  reqcalcconstr,
ref bool  reqcalcgradobj,
ref bool  reqcalcgradconstr,
ref string  cd 
) [inline, static]

Read the analysis data from data file Format: { { p1, p2, … }, { reqcalcobj, reqcalcconstr, reqcalcgradobj, reqcalcgradconstr }, cd }.

Parameters:
filePathPath to the file where training data are saved.
parametersInput and output parameters: { p1, p2, … }.
reqcalcobjFlag: reqcalcobj.
reqcalcconstrFlag: reqcalcconstr.
reqcalcgradobjFlag: reqcalcgradobj.
reqcalcgradconstrFlag: reqcalcgradconstr.
cdString: cd.

$A Tako78 Mar11;

static void IG::Neural::NeuralTadej::GetAnalysisRequest ( string  requestString,
ref IVector  parameters,
ref bool  reqcalcobj,
ref bool  reqcalcconstr,
ref bool  reqcalcgradobj,
ref bool  reqcalcgradconstr,
ref string  cd 
) [inline, static]

Read the analysis request data from data file Format: { { p1, p2, … }, { reqcalcobj, reqcalcconstr, reqcalcgradobj, reqcalcgradconstr }, cd }.

Parameters:
requestStringString with request analysis data.
parametersInput and output parameters: { p1, p2, … }.
reqcalcobjFlag: reqcalcobj.
reqcalcconstrFlag: reqcalcconstr.
reqcalcgradobjFlag: reqcalcgradobj.
reqcalcgradconstrFlag: reqcalcgradconstr.
cdString: cd.

$A Tako78 Mar11;

static void IG::Neural::NeuralTadej::ReadAnalysisResult ( string  filePath,
ref IVector  parameters,
ref bool  calcobj,
ref bool  calcconstr,
ref bool  calcgradobj,
ref bool  calcgradconstr,
ref double  obj,
ref IVector  constr,
ref IVector  dobjdp,
ref IVector[]  dconstr,
ref int  errorcode,
ref bool  reqcalcobj,
ref bool  reqcalcconstr,
ref bool  reqcalcgradobj,
ref bool  reqcalcgradconstr 
) [inline, static]

Read the analysis result data from data file Format:

Parameters:
filePathPath to the file where training data are saved.
parametersInput and output parameters: { p1, p2, … }.
calcobjFlag for the objective function.
calcconstrFlag for constraint functions.
calcgradobjGradient of the objective function.
calcgradconstrGradients of constraint functions.
objValue of the objective functions.
constrValues of the constraint functions.
dobjdpDerivatives of the objective function.
dconstrDerivatives of individual constraint functions.
errorcodeInteger error code of analysis.
reqcalcobjFlag for calculation of the various values.
reqcalcconstrFlag for calculation of the various values.
reqcalcgradobjFlag for calculation of the various values.
reqcalcgradconstrFlag for calculation of the various values.

$A Tako78 Apr7;

static void IG::Neural::NeuralTadej::GetAnalysisResult ( string  requestString,
ref IVector  parameters,
ref bool  calcobj,
ref bool  calcconstr,
ref bool  calcgradobj,
ref bool  calcgradconstr,
ref double  obj,
ref IVector  constr,
ref IVector  dobjdp,
ref IVector[]  dconstr,
ref int  errorcode,
ref bool  reqcalcobj,
ref bool  reqcalcconstr,
ref bool  reqcalcgradobj,
ref bool  reqcalcgradconstr 
) [inline, static]

Read the analysis result data from data file Format:

Parameters:
resultStringString with result analysis data.
parametersInput and output parameters: { p1, p2, … }.
calcobjFlag for the objective function.
calcconstrFlag for constraint functions.
calcgradobjGradient of the objective function.
calcgradconstrGradients of constraint functions.
objValue of the objective functions.
constrValues of the constraint functions.
dobjdpDerivatives of the objective function.
dconstrDerivatives of individual constraint functions.
errorcodeInteger error code of analysis.
reqcalcobjFlag for calculation of the various values.
reqcalcconstrFlag for calculation of the various values.
reqcalcgradobjFlag for calculation of the various values.
reqcalcgradconstrFlag for calculation of the various values.

$A Tako78 Apr7;

static void IG::Neural::NeuralTadej::LoadTrainingDataCSVinOneLine ( string  filePath,
int  inputLenght,
int  outputLenght,
bool  namesSpecified,
bool  descriptionSpecified,
bool  titleSpecified,
ref SampledDataSet  trainingData,
ref InputOutputDataDefiniton  definitionData 
) [inline, static]

Loads training data and Definition data from single CSV file.

Parameters:
filePathPath to the file where training 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.
trainingDataTraining data set.
definitionDataDefinition data set.

$A Tako78 Mar11; June27;.

static void IG::Neural::NeuralTadej::LoadTrainingDataCSV ( string  filePath,
int  inputLenght,
int  outputLenght,
bool  namesSpecified,
bool  titleSpecified,
bool  descriptionSpecified,
ref SampledDataSet  trainingData,
ref InputOutputDataDefiniton  definitionData 
) [inline, static]

Loads training data and Definition data from single CSV file.

Parameters:
filePathPath to the file where training 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.
trainingDataTraining data set.
definitionDataDefinition data set.

$A Tako78 Apr11, June24;.

static void IG::Neural::NeuralTadej::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::Neural::NeuralTadej::SaveTrainingDataCSVinOneLine ( string  filePath,
SampledDataSet  trainingData,
bool  namesSpecified,
bool  titleSpecified,
bool  descriptionSpecified,
InputOutputDataDefiniton  definitionData 
) [inline, static]

Saves training data and Definition data to single CSV file.

Parameters:
filePathPath to the file where training data will be saved.
trainingDataTraining 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::Neural::NeuralTadej::SaveTrainingDataCSV ( string  filePath,
SampledDataSet  trainingData,
bool  namesSpecified,
bool  titlesSpecified,
bool  descriptionSpecified,
InputOutputDataDefiniton  definitionData 
) [inline, static]

Saves training data and Definition data to single CSV file.

Parameters:
filePathPath to the file where training data will be saved.
trainingDataTraining 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::Neural::NeuralTadej::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::Neural::NeuralTadej::SampledDataCombineOutputs ( ref SampledDataSet  result,
params SampledDataSet[]  individualSets 
) [inline, static]

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

Parameters:
resultTraining data set with combined outputs.
individualSetsDifferent training data sets with the same inputs and different outputs.

$A Tako78 Mar11;

static void IG::Neural::NeuralTadej::LoadTrainingDataCombinedOutputsJSON ( ref SampledDataSet  trainingData,
string  directoryPath,
params string[]  fileNames 
) [inline, static]

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

Parameters:
trainingDataTraining data set.
directoryPathPath to the file where training data are saved.
fileNamesName of the files where training data are saved.

$A Tako78 Mar11;

static void IG::Neural::NeuralTadej::LoadTrainingDataCombinedOutputsJSON ( ref SampledDataSet  trainingData,
params string[]  fileNames 
) [inline, static]

Loads training data and Definition data from multible CSV files. Training 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 training data are saved.
trainingDataTraining data set.

$A Tako78 Mar11;

static void IG::Neural::NeuralTadej::SaveTrainingDataJson ( string  filePath,
SampledDataSet  trainingData 
) [inline, static]

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

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

$A Tako78 Mar11;

static void IG::Neural::NeuralTadej::SaveDefinitionDataJson ( string  filePath,
InputOutputDataDefiniton  trainingData 
) [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::Neural::NeuralTadej::LoadSampledDataJson ( string  filePath,
ref SampledDataSet  trainingData 
) [inline, static]

Restores training data from the specified file in JSON format.

Parameters:
filePathFile from which training data is restored.

$A Tako78 Mar11;

static void IG::Neural::NeuralTadej::LoadDefinitionDataJson ( string  filePath,
ref InputOutputDataDefiniton  definitionData 
) [inline, static]

Restores definition data from the specified file in JSON format.

Parameters:
filePathFile from which definition data is restored.

$A Tako78 Nov11;

static double IG::Neural::NeuralTadej::getStandardDeviation ( List< double >  doubleList) [inline, static]

Returns the standard deviation.

Parameters:
trainingDataList of dataset.

$A Tako78 Apr11;

static void IG::Neural::NeuralTadej::SmoothingTrainingData ( SampledDataSet  trainingData,
ref SampledDataSet  smoothTrainingData,
double  numStandardDeviation,
bool  uniqueInput,
bool  uniqueOutput,
bool  zeroData 
) [inline, static]

Check the training data set and delete unconsistant datas.

Parameters:
trainingDataTraining data set.
smoothTrainingDataNew training data set after.
numStandardDeviationNumber of standard deviation.

$A Tako78 Apr11;

static INeuralApproximator IG::Neural::NeuralTadej::ExampleCasting ( int  inputLength,
int  outputLength,
ref SampledDataSet  trainingData 
) [inline, static]
Parameters:
inputLength
outputLength
trainingData
Returns:

$A Tako78 Mar11;

static INeuralApproximator IG::Neural::NeuralTadej::ExampleStore ( int  inputLength,
int  outputLength,
ref SampledDataSet  trainingData 
) [inline, static]
Parameters:
inputLength
outputLength
trainingData
Returns:

$A Tako78 Mar11;

static INeuralApproximator IG::Neural::NeuralTadej::TrainNetwork ( ref INeuralApproximator  neuralApp) [inline, static]
static void IG::Neural::NeuralTadej::StoreNetwork ( string  directoryPath,
string  fileName,
string  internalStateFileName,
INeuralApproximator  neuralApp,
bool  saveRestored 
) [inline, static]
static INeuralApproximator IG::Neural::NeuralTadej::ExampleQuadratic ( int  inputLength,
int  outputLength 
) [inline, static]
Parameters:
inputLength
outputLength
Returns:

$A Tako78 Mar11;

static void IG::Neural::NeuralTadej::neuronsDataRange ( SampledDataSet  trainingData,
ref List< double[]>  inputColumnSet,
double  inputlowerBound,
double  inputupperBound,
ref List< double[]>  outputColumnSet,
double  outputlowerBound,
double  outputupperBound 
) [inline, static]
Parameters:
trainingDataTraining Data.
inputColumnSetList of input Parameters.
inputlowerBoundLower coordinate input neurons range.
inputupperBoundUpper coordinate input neurons range.
outputColumnSetList of output Parameters.
outputlowerBoundLower coordinate output neurons range.
outputupperBoundUpper coordinate output neurons range.

$A Tako78 June20;

static void IG::Neural::NeuralTadej::CopyTrainingData ( SampledDataSet  trainingData,
ref SampledDataSet  newtrainingData 
) [inline, static]

Copy training data set to new training data set.

/

Parameters:
trainingDataTraining data set.
newtrainingDataNew training data set.
static void IG::Neural::NeuralTadej::TestArray0Elements ( ) [inline, static, private]

Creates an array with 0 elements.

$A Tako78 Mar11;


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