Class containing direct analysis (in optimization) based on neural network optimization.
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List of all members.
Public Member Functions |
| AnalysisFileServerNeural (string workingDirectoryPath) |
| Constructor, sets object's working directory to the specified path.
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virtual void | Analyse (IAnalysisResults analysisData) |
| Performs analysis - calculates requested results and writes them to the provided data structure.
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override void | ClearMessages () |
| Clears all messages in the neural network approximator's file client/server directory.
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virtual void | ServerAnalyse () |
| Performs server-side direct analysis. Reads analysis input from standard location, calculates output and writes it to the standard location.
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virtual void | ClientCalculateAnalysisResults (AnalysisResults anRes) |
| Calculates analysis results by using the analysis server.
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virtual void | ClientTestCalculateAnalysisResults (string inputFilePath, bool reqObjective, bool reqConstraints, bool reqObjectiveGradient, bool reqConstraintGradients, string outputFilePath) |
| Performs client-side test calculation of analysis response.
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Protected Member Functions |
virtual void | AnalysisToApproximationInput (IVector anInput, ref IVector approximationInput) |
| Converts analysis input parameters to approximation input parameters.
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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.
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Properties |
OptFileManager | OptimizationFileManager [get, set] |
int | NumParameters [get, set] |
| Number of parameters.
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int | NumObjectives [get, set] |
| Number of objective functions (normally 1 for this type, but can be 0).
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int | NumConstraints [get, set] |
| Number of constraints.
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int | NumEqualityConstraints [get, set] |
| Number of equality constraints.
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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:
-
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:
-
analysisData | Data 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:
-
anInput | Input parameters for direct analysis. |
approximationInput | Input 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:
-
approxOuptut | Vector of approximated output values. |
anResults | Direct analysis results. |
override void IG::Neural::AnalysisFileServerNeural::ClearMessages |
( |
| ) |
[inline, virtual] |
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:
-
inputParameters | Intput parameters for which approximation is calculated. |
outputValues | Vector where approximation output values are stored. |
virtual void IG::Neural::AnalysisFileServerNeural::ClientTestCalculateAnalysisResults |
( |
string |
inputFilePath, |
|
|
bool |
reqObjective, |
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bool |
reqConstraints, |
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|
bool |
reqObjectiveGradient, |
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bool |
reqConstraintGradients, |
|
|
string |
outputFilePath |
|
) |
| [inline, virtual] |
Performs client-side test calculation of analysis response.
- Parameters:
-
inputFilePath | Path to the JSON file where input parameters are read from. The file pointed at must exist. |
reqObjective | Flag indicating whether objective function must be calculated. |
reqConstraints | Flag indicating whether constraint functions must be calculated. |
reqGradObjective | Flag indicating whether objective function gradientmust be calculated. |
reqGradOConstraints | Fleg indicating whether constraint function gradients must be calculated. |
outputFilePath | Path 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] |
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] |
int IG::Neural::AnalysisFileServerNeural::NumEqualityConstraints [get, set] |
Number of equality constraints.
The documentation for this class was generated from the following file: