gov.sandia.cognition.math.matrix

Class NumericalDifferentiator.DoubleJacobian

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.math.matrix.NumericalDifferentiator<java.lang.Double,java.lang.Double,java.lang.Double>

gov.sandia.cognition.math.matrix.NumericalDifferentiator.DoubleJacobian

All Implemented Interfaces:

Evaluator<java.lang.Double,java.lang.Double>, DifferentiableEvaluator<java.lang.Double,java.lang.Double,java.lang.Double>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

NumericalDifferentiator<InputType,OutputType,DerivativeType>

public static class NumericalDifferentiator.DoubleJacobian
extends NumericalDifferentiator<java.lang.Double,java.lang.Double,java.lang.Double>

Numerical differentiator based on a Vector Jacobian.

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class gov.sandia.cognition.math.matrix.NumericalDifferentiator

NumericalDifferentiator.DoubleJacobian, NumericalDifferentiator.MatrixJacobian, NumericalDifferentiator.VectorJacobian

Constructor Summary

Constructors

Constructor and Description
DoubleJacobian() Default constructor
DoubleJacobian(Evaluator<? super java.lang.Double,java.lang.Double> internalFunction) Creates a new instance of VectorJacobian
DoubleJacobian(Evaluator<? super java.lang.Double,java.lang.Double> internalFunction, double delta) Create a new instance of VectorJacobian

Method Summary

Modifier and Type	Method and Description
java.lang.Double	differentiate(java.lang.Double input) Differentiates the output with respect to the input
static java.lang.Double	differentiate(double input, Evaluator<? super java.lang.Double,java.lang.Double> f) Static access to the numerical differentiation procedure.
static java.lang.Double	differentiate(double input, Evaluator<? super java.lang.Double,java.lang.Double> f, double h) Static access to the numerical differentiation procedure.

Methods inherited from class gov.sandia.cognition.math.matrix.NumericalDifferentiator

clone, evaluate, getDelta, getInternalFunction, setDelta, setInternalFunction

Methods inherited from class java.lang.Object

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

Constructor Detail

DoubleJacobian

public DoubleJacobian()

Default constructor

DoubleJacobian

public DoubleJacobian(Evaluator<? super java.lang.Double,java.lang.Double> internalFunction)

Creates a new instance of VectorJacobian

Parameters:

internalFunction - Internal function to numerically differencing.

DoubleJacobian

public DoubleJacobian(Evaluator<? super java.lang.Double,java.lang.Double> internalFunction,
                      double delta)

Create a new instance of VectorJacobian

Parameters:

internalFunction - Internal function to numerically differencing.

delta - Value for x-value differencing

Method Detail

differentiate

public static java.lang.Double differentiate(double input,
                                             Evaluator<? super java.lang.Double,java.lang.Double> f)

Static access to the numerical differentiation procedure.

Parameters:

input - Input about which to approximate the derivative.

f - Function of which to approximate the derivative.

Returns:

Approximated Jacobian, of the same dimension as input

differentiate

public static java.lang.Double differentiate(double input,
                                             Evaluator<? super java.lang.Double,java.lang.Double> f,
                                             double h)

Static access to the numerical differentiation procedure.

Parameters:

input - Input about which to approximate the derivative.

f - Function of which to approximate the derivative.

h - Value for x-value differencing

Returns:

Approximated Jacobian, of the same dimension as input

differentiate

public java.lang.Double differentiate(java.lang.Double input)

Description copied from interface: DifferentiableEvaluator

Differentiates the output with respect to the input

Parameters:

input - Input about which to compute the derivative

Returns:

Derivative of the output with respect to the given input