gov.sandia.cognition.learning.function.scalar

Class PolynomialFunction.Linear

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.math.AbstractScalarFunction<java.lang.Double>

gov.sandia.cognition.math.AbstractUnivariateScalarFunction

gov.sandia.cognition.math.AbstractDifferentiableUnivariateScalarFunction

gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Linear

All Implemented Interfaces:

Evaluator<java.lang.Double,java.lang.Double>, PolynomialFunction.ClosedForm, DifferentiableEvaluator<java.lang.Double,java.lang.Double,java.lang.Double>, DifferentiableUnivariateScalarFunction, ScalarFunction<java.lang.Double>, UnivariateScalarFunction, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

AdaptiveRejectionSampling.LineSegment, PolynomialFunction.Quadratic

Enclosing class:

PolynomialFunction

public static class PolynomialFunction.Linear
extends AbstractDifferentiableUnivariateScalarFunction
implements PolynomialFunction.ClosedForm

Utilities for algebraic treatment of a linear polynomial of the form y(x) = q0 + q1*x

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static double	COLLINEAR_TOLERANCE Tolerance below which to consider something zero, 0.0

Constructor Summary

Constructors

Constructor and Description
Linear(double q0, double q1) Creates a new instance of Linear

Method Summary

Modifier and Type	Method and Description
PolynomialFunction.Linear	clone() This makes public the clone method on the Object class and removes the exception that it throws.
double	differentiate(double input) Differentiates the output of the function about the given input
double	evaluate(double input) Produces a double output for the given double input
static PolynomialFunction.Linear	fit(InputOutputPair<java.lang.Double,java.lang.Double> p0, InputOutputPair<java.lang.Double,java.lang.Double> p1) Fits a linear (straight-line) curve to the given data points
static PolynomialFunction.Linear	fit(InputOutputSlopeTriplet p0) Fits a linear (stright-line) curve to the given data point
double	getQ0() Getter for q0
double	getQ1() Getter for q1
java.lang.Double[]	roots() Finds the real-valued roots (zero crossings) of the polynomial
void	setQ0(double q0) Setter for q0
void	setQ1(double q1) Setter for q1
java.lang.Double[]	stationaryPoints() Finds the real-valued stationary points (zero slope) maxima or minima of the polynomial
java.lang.String	toString()

Methods inherited from class java.lang.Object

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

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

differentiate

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

evaluate, evaluateAsDouble

Field Detail

COLLINEAR_TOLERANCE

public static final double COLLINEAR_TOLERANCE

Tolerance below which to consider something zero, 0.0

See Also:

Constant Field Values

Constructor Detail

Linear

public Linear(double q0,
              double q1)

Creates a new instance of Linear

Parameters:

q0 - Constant (zeroth-order) coefficient

q1 - Linear (first-order) coefficient

Method Detail

clone

public PolynomialFunction.Linear 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.

evaluate

public double evaluate(double input)

Description copied from interface: UnivariateScalarFunction

Produces a double output for the given double input

Specified by:

evaluate in interface UnivariateScalarFunction

Parameters:

input - Input to the Evaluator

Returns:

output at the given input

differentiate

public double differentiate(double input)

Description copied from interface: DifferentiableUnivariateScalarFunction

Differentiates the output of the function about the given input

Specified by:

differentiate in interface DifferentiableUnivariateScalarFunction

Parameters:

input - Input about which to compute the derivative of the function output

Returns:

Derivative of the output with respect to the input

roots

public java.lang.Double[] roots()

Description copied from interface: PolynomialFunction.ClosedForm

Finds the real-valued roots (zero crossings) of the polynomial

Specified by:

roots in interface PolynomialFunction.ClosedForm

Returns:

Array of roots, will never be null

stationaryPoints

public java.lang.Double[] stationaryPoints()

Description copied from interface: PolynomialFunction.ClosedForm

Finds the real-valued stationary points (zero slope) maxima or minima of the polynomial

Specified by:

stationaryPoints in interface PolynomialFunction.ClosedForm

Returns:

Array of stationary points, will never be null

fit

public static PolynomialFunction.Linear fit(InputOutputPair<java.lang.Double,java.lang.Double> p0,
                                            InputOutputPair<java.lang.Double,java.lang.Double> p1)

Fits a linear (straight-line) curve to the given data points

Parameters:

p0 - First point

p1 - Second point

Returns:

closed-form Linear function representing the data points

fit

public static PolynomialFunction.Linear fit(InputOutputSlopeTriplet p0)

Fits a linear (stright-line) curve to the given data point

Parameters:

p0 - First point

Returns:

closed-form Linear function representing the data points

getQ0

public double getQ0()

Getter for q0

Returns:

Zeroth order coefficient

setQ0

public void setQ0(double q0)

Setter for q0

Parameters:

q0 - Zeroth order coefficient

getQ1

public double getQ1()

Getter for q1

Returns:

First-order coefficient

setQ1

public void setQ1(double q1)

Setter for q1

Parameters:

q1 - First-order coefficient

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object