Uses of Class
agi.foundation.numericalmethods.FiniteDifferenceMethod

Packages that use FiniteDifferenceMethod

Package	Description
agi.foundation.numericalmethods	Contains general numerical algorithms.
agi.foundation.numericalmethods.advanced	Contains additional advanced numerical algorithms and supporting types.

Uses of FiniteDifferenceMethod in agi.foundation.numericalmethods

Methods in agi.foundation.numericalmethods that return FiniteDifferenceMethod

Modifier and Type	Method and Description
static FiniteDifferenceMethod	FiniteDifferenceMethod.getDefault() Get the enum constant that is considered to be the default.
FiniteDifferenceMethod	TargetedSegmentListParameterOptimizer.getDifferenceMethod() Gets the difference method used to compute the derivative of the function.
FiniteDifferenceMethod	TargetedSegmentListDifferentialCorrector.getDifferenceMethod() Gets the difference method used to compute the derivative of the function.
FiniteDifferenceMethod	SolvableMultivariableFunction.getDifferenceMethod() Gets how the default numerically computed derivative of this function should be computed.
FiniteDifferenceMethod	OptimizerMultivariableFunction.getDifferenceMethod() Gets how the default numerically computed derivatives of this function should be computed.
FiniteDifferenceMethod	NumericallyComputedOptimizerFunctionDerivativeResults.getDifferenceMethod() Gets which difference method was used to compute these results.
FiniteDifferenceMethod	NumericallyComputedMultivariableFunctionDerivativeResults.getDifferenceMethod() Gets which difference method was used to compute these results.
static FiniteDifferenceMethod	FiniteDifferenceMethod.getFromValue(int value) Get the enum constant that is associated with the given numeric value.
static FiniteDifferenceMethod	FiniteDifferenceMethod.valueOf(String name) Returns the enum constant of this type with the specified name.
static FiniteDifferenceMethod[]	FiniteDifferenceMethod.values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods in agi.foundation.numericalmethods with parameters of type FiniteDifferenceMethod

Modifier and Type	Method and Description
static NumericallyComputedOptimizerFunctionDerivativeResults	OptimizerMultivariableFunction.computeGradientsNumerically(OptimizerMultivariableFunction function, double[] variables, double[] perturbationValues, FiniteDifferenceMethod differenceMethod, boolean multithreaded, OptimizerMultivariableFunctionResults precomputedValueResults, ITrackCalculationProgress progressTracker) Computes the gradients of an OptimizerMultivariableFunction numerically.
void	TargetedSegmentListParameterOptimizer.setDifferenceMethod(FiniteDifferenceMethod value) Sets the difference method used to compute the derivative of the function.
void	TargetedSegmentListDifferentialCorrector.setDifferenceMethod(FiniteDifferenceMethod value) Sets the difference method used to compute the derivative of the function.
protected void	SolvableMultivariableFunction.setDifferenceMethod(FiniteDifferenceMethod value) Sets how the default numerically computed derivative of this function should be computed.
protected void	OptimizerMultivariableFunction.setDifferenceMethod(FiniteDifferenceMethod value) Sets how the default numerically computed derivatives of this function should be computed.

Constructors in agi.foundation.numericalmethods with parameters of type FiniteDifferenceMethod

Constructor and Description
NumericallyComputedMultivariableFunctionDerivativeResults(SolvableMultivariableFunctionResults value, double[][] jacobian, SolvableMultivariableFunctionResults[] perturbedResultsUsedToComputeDerivative, boolean validPerturbations, FiniteDifferenceMethod differenceMethod) Initializes a new instance.
NumericallyComputedOptimizerFunctionDerivativeResults(OptimizerMultivariableFunctionResults value, double[] costFunctionGradient, double[][] equalityConstraintGradients, double[][] inequalityConstraintGradients, OptimizerMultivariableFunctionResults[] perturbedResultsUsedToComputeDerivative, FiniteDifferenceMethod differenceMethod) Initializes a new instance.
TargetedSegmentListFunction(List<SegmentPropagatorVariableEvaluator> variableEvaluators, List<SegmentPropagatorConstraintEvaluator> constraintEvaluators, List<SegmentPropagator> segmentPropagators, FiniteDifferenceMethod differenceMethod, TargetedSegmentListResults emptyResults, TargetedSegmentListConfiguration configuration) Initializes a new instance.
TargetedSegmentListOptimizerFunction(List<SegmentPropagatorVariableEvaluator> variableEvaluators, SegmentPropagatorCostFunctionEvaluator costFunctionEvaluator, List<SegmentPropagatorConstraintEvaluator> equalityEvaluators, List<SegmentPropagatorInequalityConstraintEvaluator> inequalityEvaluators, List<SegmentPropagator> segmentPropagators, FiniteDifferenceMethod differenceMethod, TargetedSegmentListResults emptyResults, TargetedSegmentListConfiguration configuration) Initializes a new instance.

Uses of FiniteDifferenceMethod in agi.foundation.numericalmethods.advanced

Methods in agi.foundation.numericalmethods.advanced with parameters of type FiniteDifferenceMethod

Modifier and Type	Method and Description
static NumericallyComputedMultivariableFunctionDerivativeResults	SolvableMultivariableFunctionOperations.computeJacobianNumerically(SolvableMultivariableFunction function, double[] variables, double[] perturbationValues, FiniteDifferenceMethod differenceMethod, boolean multithreaded, SolvableMultivariableFunctionResults precomputedValueResults, ITrackCalculationProgress progressTracker) Computes the Jacobian of a SolvableMultivariableFunction numerically.