ILNumerics Ultimate VS

Optimizationjacobian_prec Method

ILNumerics Ultimate VS Documentation
ILNumerics - Technical Application Development
High precision numerical estimation of the jacobian matrix of the objective function at the position x

[ILNumerics Optimization Toolbox]

Namespace:  ILNumerics.Toolboxes
Assembly:  ILNumerics.Toolboxes.Optimization (in ILNumerics.Toolboxes.Optimization.dll) Version: 5.5.0.0 (5.5.7503.3146)
Syntax

public static RetArray<double> jacobian_prec(
	OptimizationObjectiveFunction<double> func,
	InArray<double> x,
	InArray<double> Fx = null
)

Parameters

func
Type: ILNumerics.ToolboxesOptimizationObjectiveFunctionDouble
Objective function(s)
x
Type: ILNumericsInArrayDouble
Vector giving the current position of evaluation
Fx (Optional)
Type: ILNumericsInArrayDouble
Vector with the result of the evaluation of the functions at x

Return Value

Type: RetArrayDouble
An array of dimension numberOfLines(f) X numberOfColumns(x)
Exceptions

ExceptionCondition
ArgumentNullException If x has a null component
ArgumentOutOfRangeException If f is not defined at x
Remarks

This is a precise version of the jacobian estimation, using (forward+backward) finite differences with automatic step size tuning and Ridders' method of polynomial extrapolation.

If an input array is empty, an empty array will be returned.

[ILNumerics Optimization Toolbox]

Examples

Array<double> x0 = 10 * rand(10, 1);
Array<double> grad = diag(Optimization.jacobian_prec(x => cos(x), x0, null));

See Also

Reference

Other Resources