OneDimensionalOptimizer Class

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

Definition

Namespace: Numerics.NET.Optimization
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.2
C#
public abstract class OneDimensionalOptimizer : ManagedIterativeAlgorithm<double>
Inheritance
Object  →  ManagedIterativeAlgorithm<Double, Double, SolutionReport<Double, Double>>  →  ManagedIterativeAlgorithm<Double>  →  OneDimensionalOptimizer
Derived
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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>)
MaxIterationsGets 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 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

EqualsDetermines 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.
FinalizeAllows 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.
GetHashCodeServes as the default hash function.
(Inherited from Object)
GetTypeGets 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>)
MemberwiseCloneCreates 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>)
ToStringReturns a string that represents the current object.
(Inherited from Object)

See Also