Package com.irurueta.numerical

Class GradientEstimator

java.lang.Object

com.irurueta.numerical.GradientEstimator

Direct Known Subclasses:

SavitzkyGolayGradientEstimator, SymmetricGradientEstimator

public class GradientEstimator
extends Object

Class to estimate the gradient of a multidimensional function. This class evaluates a function at very close locations of a given input point in order to determine the gradient at such point.

Field Summary

Fields

Modifier and Type	Field	Description
static final double	EPS	Constant considered as machine precision.
protected final MultiDimensionFunctionEvaluatorListener	listener	Listener to evaluate a multidimensional function.
private double[]	xh	Internal array to hold input parameter's values.

Constructor Summary

Constructors

Constructor	Description
GradientEstimator(MultiDimensionFunctionEvaluatorListener listener)	Constructor.

Method Summary

Modifier and Type	Method	Description
double[]	gradient(double[] point)	Returns the gradient of a multidimensional function at provided point.
void	gradient(double[] point, double[] result)	Sets estimated gradient in provided result array of a multidimensional function at provided point.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details

EPS

public static final double EPS

Constant considered as machine precision.

See Also:

• Constant Field Values

listener

protected final MultiDimensionFunctionEvaluatorListener listener

Listener to evaluate a multidimensional function.

xh

private double[] xh

Internal array to hold input parameter's values.

Constructor Details

GradientEstimator

public GradientEstimator(MultiDimensionFunctionEvaluatorListener listener)

Constructor.

Parameters:

listener - Listener to evaluate a multidimensional function.

Method Details

gradient

public double[] gradient(double[] point)
                  throws EvaluationException

Returns the gradient of a multidimensional function at provided point.

Parameters:

point - Input point.

Returns:

Gradient.

Throws:

EvaluationException - Raised if function cannot be evaluated.

gradient

public void gradient(double[] point,
 double[] result)
              throws EvaluationException

Sets estimated gradient in provided result array of a multidimensional function at provided point. This method is preferred respect to gradient(double[]) because result array can be reused and hence is more memory efficient.

Parameters:

point - Input point.

result - Output parameter containing estimated array. This parameter must be an array of length equal to point.

Throws:

EvaluationException - Raised if function cannot be evaluated.

IllegalArgumentException - Raised if length of result and point are not equal.