ManagedIterativeAlgorithm<T, TError, TReport> Class

Represents an implementation of an iterative algorithm that uses a managed driver routine.

Definition

Namespace: Numerics.NET.Algorithms
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.1.5

public abstract class ManagedIterativeAlgorithm<T, TError, TReport> : IParallelized
where TReport : new(), SolutionReport<T, TError>

Visual Basic

Public MustInherit Class ManagedIterativeAlgorithm(Of T, TError, TReport As {New, SolutionReport(Of T, TError)})
	Implements IParallelized

C++/CLI

generic<typename T, typename TError, typename TReport>
where TReport : gcnew(), SolutionReport<T, TError>
public ref class ManagedIterativeAlgorithm abstract : IParallelized

[<AbstractClassAttribute>]
type ManagedIterativeAlgorithm<'T, 'TError, 'TReport when 'TReport : new() and SolutionReport<'T, 'TError>> = 
    class
        interface IParallelized
    end

Inheritance: Object → ManagedIterativeAlgorithm<T, TError, TReport>

Derived: Numerics.NET.Algorithms.IterativeAlgorithm<T>
Numerics.NET.Algorithms.ManagedIterativeAlgorithm<T>
Numerics.NET.LinearAlgebra.IterativeSolvers.IterativeSparseSolver<T>
Numerics.NET.Optimization.MultidimensionalOptimizer<T, TReport>

Implements: IParallelized

Type Parameters

T
TError
TReport

Remarks

Use ManagedIterativeAlgorithm as the base class for classes that implement iterative algorithms.

Note to inheritors: You must override the following methods: Iterate(), TestConvergence(). You may also override OnInit() and OnConvergence().

Constructors

ManagedIterativeAlgorithm<T, TError, TReport>

Constructs a new managed iterative algorithm object.

Properties

ConvergenceTests	Gets the collection of convergence tests for the algorithm.
EstimatedError	Gets a value indicating the size of the absolute error of the result.
EvaluationsNeeded	Gets the number of evaluations needed to execute the algorithm.
EvaluationsRemaining	Gets the number of evaluations still available.
HasSharedDegreeOfParallelism	Indicates whether the degree of parallelism is a property that is shared across instances.
IterationsNeeded	Gets the number of iterations needed by the algorithm to reach the desired accuracy.
IterationsRemaining	Gets the number of iterations remaining.
MaxDegreeOfParallelism	Gets or sets the maximum degree of parallelism enabled by this instance.
MaxEvaluations	Gets or sets the maximum number of evaluations during the calculation.
MaxIterations	Gets or sets the maximum number of iterations to use when approximating the roots of the target function.
MinIterations	Gets or sets the minimum iterations that have to be performed.
ParallelOptions	Gets or sets the configuration for the parallel behavior of the algorithm.
Result	Gets the result of an algorithm after it has executed.
SolutionReport	Gets the result of an algorithm after it has executed.
Status	Gets the AlgorithmStatus following an execution of the algorithm.
ThrowExceptionOnFailure	Gets or sets whether to throw an exception when the algorithm fails to converge.

Methods

Equals	Determines whether the specified object is equal to the current object. (Inherited from Object)
Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object)
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.
IncrementEvaluations(Int32)	Increments the number of evaluations by the specified amount.
Iterate	Performs one iteration of the algorithm.
Iterated	Performs tasks after the iteration is completed, but before the status of the algorithm is finalized.
MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object)
OnConvergence	Performs any tasks after the main algorithm has converged.
OnFailure	Performs any tasks after the main algorithm has failed to converge.
OnInit	Performs initialization before the first iteration.
ReportFailure	Records the results of an algorithm in case it fails.
ReportResult	Records the results of an algorithm.
ReportSuccess	Records the results of a algorithm that converged successfully.
ResetEvaluations	Resets the number of evaluations to zero.
Restart	Prepares the algorithm to be run again with possibly different inputs.
Run()	Runs the algorithm.
Run(ParallelOptions)	Runs the algorithm using the specified parallelization options.
SetResult	Sets the results of an algorithm's execution.
TestConvergence	Checks whether the algorithm has converged.
ThreadSafeIncrementEvaluations()	Increments the number of evaluations by one.
ThreadSafeIncrementEvaluations(Int32)	Increments the number of evaluations by the specified amount.
ThrowConvergenceException	Interprets the AlgorithmStatus and throws the appropriate exception.
ToString	Returns a string that represents the current object. (Inherited from Object)

Fields

DefaultConvergenceCriterion	Gets the default convergence criterion.
DefaultTolerance	Gets the default absolute and relative tolerance.