Interface for optimization algorithms. $A Igor Feb10; More...

Inheritance diagram for IG.Num.IOptimizer:

Collaboration diagram for IG.Num.IOptimizer:

Public Member Functions
void	Optimize ()
	Performs optimization using initial data and problem definition contained in this object. More...

Properties
bool	CopyReferences `[get, set]`
	Indicates whether just references can be copied when setting optimization parameters or results or auxiliary data. If false then deep copy is always be performed. Default is false. More...

int	NumParameters `[get]`
	Number of parameters. More...

int	NumObjectives `[get]`
	Number of objective functions (normally 1 for this type, but can be 0). More...

int	NumConstraints `[get]`
	Number of constraints. More...

int	NumEqualityConstraints `[get]`
	Number of equality constraints. More...

IAnalysis	Analysis `[get, set]`
	Definition of the direct problem (direct analysis that calculates the response functions). More...

IVector	InitialGuess `[get, set]`
	Gets or sets initial guess used in optimization. More...

IVector	InitialStep `[get, set]`
	Gets or sets initial step used in optimization. More...

double	Tolerance `[get, set]`
	Gets or sets the main tolerance (its exact meaning depends on the algorithm in use). More...

int	MaxIterations `[get, set]`
	Gets or sets maximal number of iterations. More...

int	MaxAnalyses `[get, set]`
	Gets or sets maximal number of analyses. More...

IAnalysisResults	Results `[get]`
	Optimization results. More...

bool	KeepCurrentGuess `[get]`
	Whether current guess is kept or not. More...

IAnalysisResults	CurrentGuess `[get]`
	Results of the current guess (usually last analysis that has been performed). More...

bool	KeepBestGuess `[get]`
	Whether best results are kept or not. More...

IAnalysisResults	BestGuess `[get]`
	The best results so far. More...

Properties inherited from IG.Lib.ILockable
object	Lock `[get]`

Detailed Description

Interface for optimization algorithms. $A Igor Feb10;

Member Function Documentation

void IG.Num.IOptimizer.Optimize ( )

Performs optimization using initial data and problem definition contained in this object.

Implemented in IG.Num.OptimizerBase.

Property Documentation

bool IG.Num.IOptimizer.CopyReferences

getset

Indicates whether just references can be copied when setting optimization parameters or results or auxiliary data. If false then deep copy is always be performed. Default is false.

int IG.Num.IOptimizer.NumParameters

get

Number of parameters.

int IG.Num.IOptimizer.NumObjectives

get

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

int IG.Num.IOptimizer.NumConstraints

get

Number of constraints.

int IG.Num.IOptimizer.NumEqualityConstraints

get

Number of equality constraints.

IAnalysis IG.Num.IOptimizer.Analysis

getset

Definition of the direct problem (direct analysis that calculates the response functions).

IVector IG.Num.IOptimizer.InitialGuess

getset

Gets or sets initial guess used in optimization.

IVector IG.Num.IOptimizer.InitialStep

getset

Gets or sets initial step used in optimization.

double IG.Num.IOptimizer.Tolerance

getset

Gets or sets the main tolerance (its exact meaning depends on the algorithm in use).

int IG.Num.IOptimizer.MaxIterations

getset

Gets or sets maximal number of iterations.

int IG.Num.IOptimizer.MaxAnalyses

getset

Gets or sets maximal number of analyses.

IAnalysisResults IG.Num.IOptimizer.Results

get

Optimization results.

bool IG.Num.IOptimizer.KeepCurrentGuess

get

Whether current guess is kept or not.

IAnalysisResults IG.Num.IOptimizer.CurrentGuess

get

Results of the current guess (usually last analysis that has been performed).

bool IG.Num.IOptimizer.KeepBestGuess

get

Whether best results are kept or not.

IAnalysisResults IG.Num.IOptimizer.BestGuess

get

The best results so far.

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

igbase/optimization/Optimizer.cs

Public Member Functions

Properties

Detailed Description

Member Function Documentation

Property Documentation