Optimization.jacobian_fast Method

public static RetArray<double> jacobian_fast(
	Optimization.ObjectiveFunction<double> func,
	InArray<double> x,
	InArray<double> Fx = null
)

Public Shared Function jacobian_fast ( 
	func As Optimization.ObjectiveFunction(Of Double),
	x As InArray(Of Double),
	Optional Fx As InArray(Of Double) = Nothing
) As RetArray(Of Double)

Dim func As Optimization.ObjectiveFunction(Of Double)
Dim x As InArray(Of Double)
Dim Fx As InArray(Of Double)
Dim returnValue As RetArray(Of Double)

returnValue = Optimization.jacobian_fast(func, 
	x, Fx)

Parameters

func

Type: ILNumerics.Toolboxes.Optimization.ObjectiveFunction<Double>
Function to be evaluated

x

Type: ILNumerics.InArray<Double>
Vector giving the position of current evaluation

Fx (Optional)

Type: ILNumerics.InArray<Double>
[optional] Vector with results of the evaluation of the objective function

Return Value

This algorithm computes a good estimate of the jacobian matrix, concentrating on speed rather than on exactness.

On empty input x, an empty array will be returned.

[ILNumerics Optimization Toolbox]

Find the minimizer for f(x) = sin(x) + cos(x); x,f in R³, start searching at (1,1,1), using levenberg marquardt algorithm. The jacobian_fast(Optimization.ObjectiveFunction<Double> , InArray<Double> , InArray<Double> ) jacobian estimate is used for computing the jacobian in each step:

Array<double> Minimizer = Optimization.optimlevm(x => sin(x) + cos(x), zeros<double>(3, 1), jacobianFunc: Optimization.jacobian_fast);

Reference

Other Resources