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

IG::Neural::AnalysisFileServerNeural Class Reference

Class containing direct analysis (in optimization) based on neural network optimization. More...

Inheritance diagram for IG::Neural::AnalysisFileServerNeural:
Collaboration diagram for IG::Neural::AnalysisFileServerNeural:

List of all members.

Public Member Functions

 AnalysisFileServerNeural (string workingDirectoryPath)
 Constructor, sets object's working directory to the specified path.
virtual void Analyse (IAnalysisResults analysisData)
 Performs analysis - calculates requested results and writes them to the provided data structure.
override void ClearMessages ()
 Clears all messages in the neural network approximator's file client/server directory.
virtual void ServerAnalyse ()
 Performs server-side direct analysis. Reads analysis input from standard location, calculates output and writes it to the standard location.
virtual void ClientCalculateAnalysisResults (AnalysisResults anRes)
 Calculates analysis results by using the analysis server.
virtual void ClientTestCalculateAnalysisResults (string inputFilePath, bool reqObjective, bool reqConstraints, bool reqObjectiveGradient, bool reqConstraintGradients, string outputFilePath)
 Performs client-side test calculation of analysis response.

Protected Member Functions

virtual void AnalysisToApproximationInput (IVector anInput, ref IVector approximationInput)
 Converts analysis input parameters to approximation input parameters.
virtual void ApproximationToAnalysisOutput (IVector approxOuptut, IAnalysisResults anResults)
 Converts approximation output to direct analysis results.
Sets objective function to sum of squares of approximated values.
WARNING:
This method should be overridden in derived classes.

Properties

OptFileManager OptimizationFileManager [get, set]
int NumParameters [get, set]
 Number of parameters.
int NumObjectives [get, set]
 Number of objective functions (normally 1 for this type, but can be 0).
int NumConstraints [get, set]
 Number of constraints.
int NumEqualityConstraints [get, set]
 Number of equality constraints.

Private Attributes

OptFileManager _optFileManager

Detailed Description

Class containing direct analysis (in optimization) based on neural network optimization.


Constructor & Destructor Documentation

IG::Neural::AnalysisFileServerNeural::AnalysisFileServerNeural ( string  workingDirectoryPath) [inline]

Constructor, sets object's working directory to the specified path.

Parameters:
workingDirectoryPath

Member Function Documentation

virtual void IG::Neural::AnalysisFileServerNeural::Analyse ( IAnalysisResults  analysisData) [inline, virtual]

Performs analysis - calculates requested results and writes them to the provided data structure.

Parameters:
analysisDataData structure where analysis request parameters are obtained and where analysis results are written.
virtual void IG::Neural::AnalysisFileServerNeural::AnalysisToApproximationInput ( IVector  anInput,
ref IVector  approximationInput 
) [inline, protected, virtual]

Converts analysis input parameters to approximation input parameters.

Parameters:
anInputInput parameters for direct analysis.
approximationInputInput parameters for response approximation.
virtual void IG::Neural::AnalysisFileServerNeural::ApproximationToAnalysisOutput ( IVector  approxOuptut,
IAnalysisResults  anResults 
) [inline, protected, virtual]

Converts approximation output to direct analysis results.
Sets objective function to sum of squares of approximated values.
WARNING:
This method should be overridden in derived classes.

Parameters:
approxOuptutVector of approximated output values.
anResultsDirect analysis results.
override void IG::Neural::AnalysisFileServerNeural::ClearMessages ( ) [inline, virtual]

Clears all messages in the neural network approximator's file client/server directory.

Reimplemented from IG::Neural::ApproximationFileServerNeural.

virtual void IG::Neural::AnalysisFileServerNeural::ServerAnalyse ( ) [inline, virtual]

Performs server-side direct analysis. Reads analysis input from standard location, calculates output and writes it to the standard location.

virtual void IG::Neural::AnalysisFileServerNeural::ClientCalculateAnalysisResults ( AnalysisResults  anRes) [inline, virtual]

Calculates analysis results by using the analysis server.

Parameters:
inputParametersIntput parameters for which approximation is calculated.
outputValuesVector where approximation output values are stored.
virtual void IG::Neural::AnalysisFileServerNeural::ClientTestCalculateAnalysisResults ( string  inputFilePath,
bool  reqObjective,
bool  reqConstraints,
bool  reqObjectiveGradient,
bool  reqConstraintGradients,
string  outputFilePath 
) [inline, virtual]

Performs client-side test calculation of analysis response.

Parameters:
inputFilePathPath to the JSON file where input parameters are read from. The file pointed at must exist.
reqObjectiveFlag indicating whether objective function must be calculated.
reqConstraintsFlag indicating whether constraint functions must be calculated.
reqGradObjectiveFlag indicating whether objective function gradientmust be calculated.
reqGradOConstraintsFleg indicating whether constraint function gradients must be calculated.
outputFilePathPath of a file where the calculated analysis response in JSON is written to. It can be null or empty string, in this case response is not written to a file (but it is output on console).

Member Data Documentation


Property Documentation

OptFileManager IG::Neural::AnalysisFileServerNeural::OptimizationFileManager [get, set]
int IG::Neural::AnalysisFileServerNeural::NumParameters [get, set]

Number of parameters.

int IG::Neural::AnalysisFileServerNeural::NumObjectives [get, set]

Number of objective functions (normally 1 for this type, but can be 0).

int IG::Neural::AnalysisFileServerNeural::NumConstraints [get, set]

Number of constraints.

int IG::Neural::AnalysisFileServerNeural::NumEqualityConstraints [get, set]

Number of equality constraints.


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