gov.sandia.cognition.math.matrix

Class NumericalDifferentiator<InputType,OutputType,DerivativeType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.math.matrix.NumericalDifferentiator<InputType,OutputType,DerivativeType>

Type Parameters:

InputType - Class of the input to the Evaluator

OutputType - Class of the output from the Evaluator

DerivativeType - Class of the derivative of the Evaluator

All Implemented Interfaces:

Evaluator<InputType,OutputType>, DifferentiableEvaluator<InputType,OutputType,DerivativeType>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

NumericalDifferentiator.DoubleJacobian, NumericalDifferentiator.MatrixJacobian, NumericalDifferentiator.VectorJacobian

@PublicationReference(author="Wikipedia",
                      title="Numerical differentiation",
                      type=WebPage,
                      url="http://en.wikipedia.org/wiki/Numerical_differentiation",
                      year=2008)
public abstract class NumericalDifferentiator<InputType,OutputType,DerivativeType>
extends AbstractCloneableSerializable
implements DifferentiableEvaluator<InputType,OutputType,DerivativeType>

Automatically differentiates a function by the method of forward differences.

Since:

2.1

Author:

Kevin R. Dixon

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	NumericalDifferentiator.DoubleJacobian Numerical differentiator based on a Vector Jacobian.
static class	NumericalDifferentiator.MatrixJacobian Numerical differentiator based on a Matrix Jacobian.
static class	NumericalDifferentiator.VectorJacobian Numerical differentiator based on a Vector Jacobian.

Constructor Summary

Constructors

Constructor and Description
NumericalDifferentiator(Evaluator<? super InputType,OutputType> internalFunction, double delta) Creates a new instance of NumericalDifferentiator

Method Summary

Modifier and Type	Method and Description
NumericalDifferentiator<InputType,OutputType,DerivativeType>	clone() This makes public the clone method on the Object class and removes the exception that it throws.
OutputType	evaluate(InputType input) Evaluates the function on the given input and returns the output.
double	getDelta() Getter for delta
Evaluator<? super InputType,OutputType>	getInternalFunction() Getter for internalFunction
void	setDelta(double delta) Setter for delta
void	setInternalFunction(Evaluator<? super InputType,OutputType> internalFunction) Setter for internalFunction

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.math.DifferentiableEvaluator

differentiate

Constructor Detail

NumericalDifferentiator

public NumericalDifferentiator(Evaluator<? super InputType,OutputType> internalFunction,
                               double delta)

Creates a new instance of NumericalDifferentiator

Parameters:

internalFunction - Internal function to numerically differencing.

delta - Value for x-value differencing, must be greater than 0.0

Method Detail

clone

public NumericalDifferentiator<InputType,OutputType,DerivativeType> clone()

Description copied from class: AbstractCloneableSerializable

This makes public the clone method on the Object class and removes the exception that it throws. Its default behavior is to automatically create a clone of the exact type of object that the clone is called on and to copy all primitives but to keep all references, which means it is a shallow copy. Extensions of this class may want to override this method (but call super.clone() to implement a "smart copy". That is, to target the most common use case for creating a copy of the object. Because of the default behavior being a shallow copy, extending classes only need to handle fields that need to have a deeper copy (or those that need to be reset). Some of the methods in ObjectUtil may be helpful in implementing a custom clone method. Note: The contract of this method is that you must use super.clone() as the basis for your implementation.

Specified by:

clone in interface CloneableSerializable

Overrides:

clone in class AbstractCloneableSerializable

Returns:

A clone of this object.

getInternalFunction

public Evaluator<? super InputType,OutputType> getInternalFunction()

Getter for internalFunction

Returns:

Internal function to numerically differencing.

setInternalFunction

public void setInternalFunction(Evaluator<? super InputType,OutputType> internalFunction)

Setter for internalFunction

Parameters:

internalFunction - Internal function to numerically differencing.

getDelta

public double getDelta()

Getter for delta

Returns:

Value for x-value differencing, must be greater than 0.0

setDelta

public void setDelta(double delta)

Setter for delta

Parameters:

delta - Value for x-value differencing, must be greater than 0.0

evaluate

public OutputType evaluate(InputType input)

Description copied from interface: Evaluator

Evaluates the function on the given input and returns the output.

Specified by:

evaluate in interface Evaluator<InputType,OutputType>

Parameters:

input - The input to evaluate.

Returns:

The output produced by evaluating the input.