OneDimensionalOptimizer Class

Serves as an abstract base class for classes that implement one-dimensional optimization algorithms.

Definition

Namespace: Extreme.Mathematics.Optimization
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23

public abstract class OneDimensionalOptimizer : ManagedIterativeAlgorithm<double>

Visual Basic

Public MustInherit Class OneDimensionalOptimizer
	Inherits ManagedIterativeAlgorithm(Of Double)

C++/CLI

public ref class OneDimensionalOptimizer abstract : public ManagedIterativeAlgorithm<double>

[<AbstractClassAttribute>]
type OneDimensionalOptimizer = 
    class
        inherit ManagedIterativeAlgorithm<float>
    end

Inheritance: Object → ManagedIterativeAlgorithm<Double, Double, SolutionReport<Double, Double>> → ManagedIterativeAlgorithm<Double> → OneDimensionalOptimizer

Derived: Extreme.Mathematics.Optimization.BrentDerivativeOptimizer
Extreme.Mathematics.Optimization.BrentOptimizer
Extreme.Mathematics.Optimization.GoldenSectionOptimizer
Extreme.Mathematics.Optimization.LineSearches.BacktrackingLineSearch
Extreme.Mathematics.Optimization.LineSearches.MoreThuenteLineSearch
Extreme.Mathematics.Optimization.LineSearches.ParabolicLineSearch
Extreme.Mathematics.Optimization.LineSearches.UnitLineSearch
More Less

Remarks

The OneDimensionalOptimizer class is the abstract base class of all classes that implement algorithms for one-dimensional optimization, including line search algorithms. The class inherits from ManagedIterativeAlgorithm. All the properties and methods exposed by this interface are available to all derived classes.

This class cannot be instantiated directly. Instead, use one of the following derived classes:

BrentOptimizer – Represents a OneDimensionalOptimizer that uses the Brent's algorithm that does not use derivatives of the objective function.
BrentDerivativeOptimizer – Represents a OneDimensionalOptimizer that uses a variation of Brent's algorithm that uses derivatives of the objective function.
GoldenSectionOptimizer – Represents a OneDimensionalOptimizer that uses the Golden Section search algorithm.
MoreThuenteLineSearch – Represents a OneDimensionalOptimizer that uses the classic algorithm of Moré and Thuente.
ParabolicLineSearch – Represents a OneDimensionalOptimizer that uses a parabolic line search algorithm.
UnitLineSearch – Represents a OneDimensionalOptimizer that always returns a unit step.

Constructors

OneDimensionalOptimizer()	Constructs a new one-dimensional optimizer.
OneDimensionalOptimizer(ExtremumType)	Constructs a new one-dimensional optimizer.

Properties

ConvergenceTests	Gets the collection of convergence tests for the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
DerivativeOfObjectiveFunction	Gets or sets the derivative of the objective function.
EstimatedError	Gets a value indicating the size of the absolute error of the result. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
EvaluationsNeeded	Gets the number of evaluations needed to execute the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
EvaluationsRemaining	Gets the number of evaluations still available. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Extremum	Gets the approximation to the extremum after the algorithm has run.
ExtremumType	Gets or sets the type of extremum.
HasSharedDegreeOfParallelism	Indicates whether the degree of parallelism is a property that is shared across instances. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
IsBracketValid	Gets whether the algorithm's current bracket is valid.
IterationsNeeded	Gets the number of iterations needed by the algorithm to reach the desired accuracy. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
IterationsRemaining	Gets the number of iterations remaining. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
MaxDegreeOfParallelism	Gets or sets the maximum degree of parallelism enabled by this instance. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
MaxEvaluations	Gets or sets the maximum number of evaluations during the calculation. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
MaxIterations	Gets or sets the maximum number of iterations to use when approximating the roots of the target function. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
MinIterations	Gets or sets the minimum iterations that have to be performed. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ObjectiveFunction	Gets or sets the objective function.
ObjectiveFunctionWithDerivative	Gets or sets a function that computes the value of the objective function and its derivative.
ParallelOptions	Gets or sets the configuration for the parallel behavior of the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Result	Gets the result of an algorithm after it has executed. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SolutionReport	Gets the result of an algorithm after it has executed. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SolutionTest	Gets the convergence test that uses the solution of the optimization.
Status	Gets the AlgorithmStatus following an execution of the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SymbolicObjectiveFunction	Gets or sets the objective function.
ThrowExceptionOnFailure	Gets or sets a value indicating whether to throw an exception when the algorithm fails to converge. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ValueAtExtremum	Gets the value of the objective function at the approximation to the extremum after the algorithm has run.

Methods

Equals	Determines whether the specified object is equal to the current object. (Inherited from Object)
Evaluate	Evaluates the objective function.
EvaluateDerivative	Evaluates the derivative of the objective function.
EvaluateWithDerivative	Evaluates the objective function and its derivative.
Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object)
FindBracket()	Finds an interval that brackets the extremum, starting from the interval [0,1].
FindBracket(Double)	Finds an interval that brackets the extremum, starting from an interval of unit width centered around the specified point.
FindBracket(Double, Double)	Finds an interval that brackets the extremum, starting from an interval with the specified bounds.
FindBracket(Double, Double, Double)	Finds an interval that brackets the extremum, starting from an interval with the specified bounds and interior point.
FindExtremum	Searches for an extremum.
FindMaximum(Func<Double, Double>, Double)	Computes a maximum of the specified function.
FindMaximum(Func<Double, Double>, Double, Double)	Computes a maximum of the specified function.
FindMinimum(Func<Double, Double>, Double)	Computes a minimum of the specified function.
FindMinimum(Func<Double, Double>, Double, Double)	Computes a minimum of the specified function.
GetHashCode	Serves as the default hash function. (Inherited from Object)
GetType	Gets the Type of the current instance. (Inherited from Object)
IncrementEvaluations()	Increments the number of evaluations by one. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
IncrementEvaluations(Int32)	Increments the number of evaluations by the specified amount. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Iterate	Performs one iteration of the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Iterated	Performs tasks after the iteration is completed, but before the status of the algorithm is finalized. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object)
OnConvergence	Performs any tasks after the main algorithm has converged. (Overrides ManagedIterativeAlgorithm<T, TError, TReport>.OnConvergence())
OnFailure	Performs any tasks after the main algorithm has failed to converge. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
OnInit	Performs initialization before the first iteration. (Overrides ManagedIterativeAlgorithm<T, TError, TReport>.OnInit())
ReportFailure	Records the results of an algorithm in case it fails. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ReportResult	Records the results of an algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ReportSuccess	Records the results of a algorithm that converged successfully. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ResetEvaluations	Resets the number of evaluations to zero. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Restart	Prepares the algorithm to be run again with possibly different inputs. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Run()	Runs the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Run(ParallelOptions)	Runs the algorithm using the specified parallelization options. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SetResult	Sets the results of an algorithm's execution. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
TestConvergence	Checks whether the algorithm has converged. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ThreadSafeIncrementEvaluations()	Increments the number of evaluations by one. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ThreadSafeIncrementEvaluations(Int32)	Increments the number of evaluations by the specified amount. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ThrowConvergenceException	Interprets the AlgorithmStatus and throws the appropriate exception. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ToString	Returns a string that represents the current object. (Inherited from Object)