Modifier and Type	Class and Description
public static class	NonLinearConjugateGradientOptimizer.IdentityPreconditioner Deprecated as a consequence of `Preconditioner` being deprecated. Default identity preconditioner.
private class	NonLinearConjugateGradientOptimizer.LineSearchFunction Internal class for line search.

Modifier and Type	Field and Description
private double	initialStep Initial step used to bracket the optimum in line search.
private double[]	point Current point.
private final Preconditioner	preconditioner Deprecated as a consequence of `Preconditioner` being deprecated. Preconditioner (may be null).
private final UnivariateSolver	solver solver to use in the line search (may be null).
private final ConjugateGradientFormula	updateFormula Deprecated as a consequence of `ConjugateGradientFormula` being deprecated. Update formula for the beta parameter.

Constructor Summary

Access	Constructor and Description
public	NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula formula to use for updating the β parameter, must be one of `ConjugateGradientFormula#FLETCHER_REEVES` or `ConjugateGradientFormula#POLAK_RIBIERE`. updateFormula) Deprecated See `SimpleValueChecker#SimpleValueChecker()` Constructor with default `checker`, `line search solver` and `preconditioner`.
public	NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula formula to use for updating the β parameter, must be one of `ConjugateGradientFormula#FLETCHER_REEVES` or `ConjugateGradientFormula#POLAK_RIBIERE`. updateFormula, ConvergenceChecker<PointValuePair> Convergence checker. checker) Deprecated as a consequence of `ConjugateGradientFormula` and `ConvergenceChecker` being deprecated. Constructor with default `line search solver` and `preconditioner`.
public	NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula formula to use for updating the β parameter, must be one of `ConjugateGradientFormula#FLETCHER_REEVES` or `ConjugateGradientFormula#POLAK_RIBIERE`. updateFormula, ConvergenceChecker<PointValuePair> Convergence checker. checker, final UnivariateSolver Solver to use during line search. lineSearchSolver) Deprecated as a consequence of `ConjugateGradientFormula` and `ConvergenceChecker` being deprecated. Constructor with default `preconditioner`.
public	NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula formula to use for updating the β parameter, must be one of `ConjugateGradientFormula#FLETCHER_REEVES` or `ConjugateGradientFormula#POLAK_RIBIERE`. updateFormula, ConvergenceChecker<PointValuePair> Convergence checker. checker, final UnivariateSolver Solver to use during line search. lineSearchSolver, final Preconditioner Preconditioner. preconditioner) Deprecated as a consequence of `ConjugateGradientFormula`, `ConvergenceChecker` and `Preconditioner` being deprecated.

Method Summary

Modifier and Type	Method and Description
protected PointValuePair	doOptimize() Implements abstract org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer.doOptimize. Deprecated as a consequence of `PointValuePair` being deprecated. Perform the bulk of the optimization algorithm.
private double	Returns: b such that f(a) and f(b) have opposite signs. findUpperBound(final UnivariateFunction function whose root must be bracketed. f, final double lower bound of the interval. a, final double initial step to try. h) Find the upper bound b ensuring bracketing of a root between a and b.
public void	setInitialStep(final double initial step used to bracket the optimum in line search, if a non-positive value is used, the initial step is reset to its default value of 1.0 initialStep) Set the initial step used to bracket the optimum in line search.

Inherited from org.apache.commons.math3.optimization.general.AbstractScalarDifferentiableOptimizer:: computeObjectiveGradient optimize optimizeInternal

Field Detail

initialStep	back to summary
private double initialStep Initial step used to bracket the optimum in line search.

point	back to summary
private double[] point Current point.

preconditioner	back to summary
private final Preconditioner preconditioner Deprecated as a consequence of `Preconditioner` being deprecated. See corresponding docs for further information. Preconditioner (may be null).

solver	back to summary
private final UnivariateSolver solver solver to use in the line search (may be null).

updateFormula	back to summary
private final ConjugateGradientFormula updateFormula Deprecated as a consequence of `ConjugateGradientFormula` being deprecated. See corresponding docs for further information. Update formula for the beta parameter.

Constructor Detail

NonLinearConjugateGradientOptimizer back to summary

NonLinearConjugateGradientOptimizer	back to summary
public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula updateFormula) Deprecated See `SimpleValueChecker#SimpleValueChecker()` Constructor with default `checker`, `line search solver` and `preconditioner`. Parameters updateFormula:ConjugateGradientFormula formula to use for updating the β parameter, must be one of `ConjugateGradientFormula#FLETCHER_REEVES` or `ConjugateGradientFormula#POLAK_RIBIERE`. Annotations @Deprecated

public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula updateFormula)

Deprecated

See SimpleValueChecker#SimpleValueChecker()

Constructor with default checker, line search solver and preconditioner.

Parameters

updateFormula:ConjugateGradientFormula: formula to use for updating the β parameter, must be one of ConjugateGradientFormula#FLETCHER_REEVES or ConjugateGradientFormula#POLAK_RIBIERE.

Annotations

@Deprecated

NonLinearConjugateGradientOptimizer back to summary

NonLinearConjugateGradientOptimizer	back to summary
public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula updateFormula, ConvergenceChecker<PointValuePair> checker) Deprecated as a consequence of `ConjugateGradientFormula` and `ConvergenceChecker` being deprecated. See corresponding docs for further information. Constructor with default `line search solver` and `preconditioner`. Parameters updateFormula:ConjugateGradientFormula formula to use for updating the β parameter, must be one of `ConjugateGradientFormula#FLETCHER_REEVES` or `ConjugateGradientFormula#POLAK_RIBIERE`. checker:ConvergenceChecker<PointValuePair> Convergence checker.

public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula updateFormula, ConvergenceChecker<PointValuePair> checker)

Deprecated

as a consequence of ConjugateGradientFormula and ConvergenceChecker being deprecated. See corresponding docs for further information.

Constructor with default line search solver and preconditioner.

Parameters

updateFormula:ConjugateGradientFormula: formula to use for updating the β parameter, must be one of ConjugateGradientFormula#FLETCHER_REEVES or ConjugateGradientFormula#POLAK_RIBIERE.
checker:ConvergenceChecker<PointValuePair>: Convergence checker.

NonLinearConjugateGradientOptimizer back to summary

NonLinearConjugateGradientOptimizer	back to summary
public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula updateFormula, ConvergenceChecker<PointValuePair> checker, final UnivariateSolver lineSearchSolver) Deprecated as a consequence of `ConjugateGradientFormula` and `ConvergenceChecker` being deprecated. See corresponding docs for further information. Constructor with default `preconditioner`. Parameters updateFormula:ConjugateGradientFormula formula to use for updating the β parameter, must be one of `ConjugateGradientFormula#FLETCHER_REEVES` or `ConjugateGradientFormula#POLAK_RIBIERE`. checker:ConvergenceChecker<PointValuePair> Convergence checker. lineSearchSolver:UnivariateSolver Solver to use during line search.

public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula updateFormula, ConvergenceChecker<PointValuePair> checker, final UnivariateSolver lineSearchSolver)

Deprecated

as a consequence of ConjugateGradientFormula and ConvergenceChecker being deprecated. See corresponding docs for further information.

Constructor with default preconditioner.

Parameters

updateFormula:ConjugateGradientFormula: formula to use for updating the β parameter, must be one of ConjugateGradientFormula#FLETCHER_REEVES or ConjugateGradientFormula#POLAK_RIBIERE.
checker:ConvergenceChecker<PointValuePair>: Convergence checker.
lineSearchSolver:UnivariateSolver: Solver to use during line search.

NonLinearConjugateGradientOptimizer back to summary

NonLinearConjugateGradientOptimizer	back to summary
public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula updateFormula, ConvergenceChecker<PointValuePair> checker, final UnivariateSolver lineSearchSolver, final Preconditioner preconditioner) Deprecated as a consequence of `ConjugateGradientFormula`, `ConvergenceChecker` and `Preconditioner` being deprecated. See corresponding docs for further information. Parameters updateFormula:ConjugateGradientFormula formula to use for updating the β parameter, must be one of `ConjugateGradientFormula#FLETCHER_REEVES` or `ConjugateGradientFormula#POLAK_RIBIERE`. checker:ConvergenceChecker<PointValuePair> Convergence checker. lineSearchSolver:UnivariateSolver Solver to use during line search. preconditioner:Preconditioner Preconditioner.

public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula updateFormula, ConvergenceChecker<PointValuePair> checker, final UnivariateSolver lineSearchSolver, final Preconditioner preconditioner)

Deprecated

as a consequence of ConjugateGradientFormula, ConvergenceChecker and Preconditioner being deprecated. See corresponding docs for further information.

Parameters

updateFormula:ConjugateGradientFormula: formula to use for updating the β parameter, must be one of ConjugateGradientFormula#FLETCHER_REEVES or ConjugateGradientFormula#POLAK_RIBIERE.
checker:ConvergenceChecker<PointValuePair>: Convergence checker.
lineSearchSolver:UnivariateSolver: Solver to use during line search.
preconditioner:Preconditioner: Preconditioner.

Method Detail

doOptimize back to summary

doOptimize	back to summary
protected PointValuePair doOptimize() Implements abstract org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer.doOptimize. Doc from org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer.doOptimize. Deprecated as a consequence of `PointValuePair` being deprecated. See corresponding docs for further information. Perform the bulk of the optimization algorithm. Returns:PointValuePair the point/value pair giving the optimal value of the objective function. Annotations @Override

protected PointValuePair doOptimize()

Implements abstract org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer.doOptimize.

Doc from org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer.doOptimize.

Deprecated

as a consequence of PointValuePair being deprecated. See corresponding docs for further information.

Perform the bulk of the optimization algorithm.

Returns:PointValuePair

the point/value pair giving the optimal value of the objective function.

Annotations

@Override

findUpperBound	back to summary
private double findUpperBound(final UnivariateFunction f, final double a, final double h) Find the upper bound b ensuring bracketing of a root between a and b. Parameters f:UnivariateFunction function whose root must be bracketed. a:double lower bound of the interval. h:double initial step to try. Returns:double b such that f(a) and f(b) have opposite signs. Exceptions MathIllegalStateException: if no bracket can be found.

findUpperBound

back to summary

private double findUpperBound(final UnivariateFunction f, final double a, final double h)

Find the upper bound b ensuring bracketing of a root between a and b.

Parameters

f:UnivariateFunction: function whose root must be bracketed.
a:double: lower bound of the interval.
h:double: initial step to try.

Returns:double

b such that f(a) and f(b) have opposite signs.

Exceptions

MathIllegalStateException:: if no bracket can be found.

setInitialStep	back to summary
public void setInitialStep(final double initialStep) Set the initial step used to bracket the optimum in line search. The initial step is a factor with respect to the search direction, which itself is roughly related to the gradient of the function Parameters initialStep:double initial step used to bracket the optimum in line search, if a non-positive value is used, the initial step is reset to its default value of 1.0

setInitialStep

back to summary

public void setInitialStep(final double initialStep)

Set the initial step used to bracket the optimum in line search.

The initial step is a factor with respect to the search direction, which itself is roughly related to the gradient of the function

Parameters

initialStep:double: initial step used to bracket the optimum in line search, if a non-positive value is used, the initial step is reset to its default value of 1.0

org.apache.commons.math3.optimization.general back to summary

public Class NonLinearConjugateGradientOptimizer.IdentityPreconditioner

Class Inheritance

extends Object
implements Preconditioner

java.lang.Object
org.apache.commons.math3.optimization.general.NonLinearConjugateGradientOptimizer.IdentityPreconditioner

All Implemented Interfaces

org.apache.commons.math3.optimization.general.Preconditioner

Deprecated

as a consequence of Preconditioner being deprecated. See corresponding docs for further information.

Default identity preconditioner.

Constructor Summary

Access	Constructor and Description
public	IdentityPreconditioner()

Method Summary

Modifier and Type	Method and Description
public double[]	precondition(double[] current point at which the search direction was computed variables, double[] raw search direction (i.e. opposite of the gradient) r) Implements org.apache.commons.math3.optimization.general.Preconditioner.precondition. Precondition a search direction.

Inherited from java.lang.Object:: clone equals finalize getClass hashCode notify notifyAll toString wait wait wait

Constructor Detail

IdentityPreconditioner	back to summary
public IdentityPreconditioner()

Method Detail

precondition	back to summary
public double[] precondition(double[] variables, double[] r) Implements org.apache.commons.math3.optimization.general.Preconditioner.precondition. Doc from org.apache.commons.math3.optimization.general.Preconditioner.precondition. Precondition a search direction. The returned preconditioned search direction must be computed fast or the algorithm performances will drop drastically. A classical approach is to compute only the diagonal elements of the hessian and to divide the raw search direction by these elements if they are all positive. If at least one of them is negative, it is safer to return a clone of the raw search direction as if the hessian was the identity matrix. The rationale for this simplified choice is that a negative diagonal element means the current point is far from the optimum and preconditioning will not be efficient anyway in this case. Parameters variables:double[] current point at which the search direction was computed r:double[] raw search direction (i.e. opposite of the gradient) Returns:double[] approximation of H^-1r where H is the objective function hessian

precondition

back to summary

public double[] precondition(double[] variables, double[] r)

Implements org.apache.commons.math3.optimization.general.Preconditioner.precondition.

Doc from org.apache.commons.math3.optimization.general.Preconditioner.precondition.

Precondition a search direction.

The returned preconditioned search direction must be computed fast or the algorithm performances will drop drastically. A classical approach is to compute only the diagonal elements of the hessian and to divide the raw search direction by these elements if they are all positive. If at least one of them is negative, it is safer to return a clone of the raw search direction as if the hessian was the identity matrix. The rationale for this simplified choice is that a negative diagonal element means the current point is far from the optimum and preconditioning will not be efficient anyway in this case.

Parameters

variables:double[]: current point at which the search direction was computed
r:double[]: raw search direction (i.e. opposite of the gradient)

Returns:double[]

approximation of H^-1r where H is the objective function hessian

org.apache.commons.math3.optimization.general back to summary

private Class NonLinearConjugateGradientOptimizer.LineSearchFunction

Class Inheritance

extends Object
implements UnivariateFunction

java.lang.Object
org.apache.commons.math3.optimization.general.NonLinearConjugateGradientOptimizer.LineSearchFunction

All Implemented Interfaces

org.apache.commons.math3.analysis.UnivariateFunction

Internal class for line search.

The function represented by this class is the dot product of the objective function gradient and the search direction. Its value is zero when the gradient is orthogonal to the search direction, i.e. when the objective function value is a local extremum along the search direction.

Field Summary

Modifier and Type	Field and Description
private final double[]	searchDirection Search direction.

Constructor Summary

Access	Constructor and Description
pack-priv	LineSearchFunction(final double[] search direction searchDirection) Simple constructor.

Method Summary

Modifier and Type	Method and Description
public double	value(double Point at which the function value should be computed. x) Implements org.apache.commons.math3.analysis.UnivariateFunction.value. Compute the value of the function.

Inherited from java.lang.Object:: clone equals finalize getClass hashCode notify notifyAll toString wait wait wait

Field Detail

searchDirection	back to summary
private final double[] searchDirection Search direction.

Constructor Detail

LineSearchFunction	back to summary
pack-priv LineSearchFunction(final double[] searchDirection) Simple constructor. Parameters searchDirection:double[] search direction

LineSearchFunction

back to summary

pack-priv LineSearchFunction(final double[] searchDirection)

Simple constructor.

Parameters

searchDirection:double[]: search direction

Method Detail

value	back to summary
public double value(double x) Implements org.apache.commons.math3.analysis.UnivariateFunction.value. Doc from org.apache.commons.math3.analysis.UnivariateFunction.value. Compute the value of the function. Parameters x:double Point at which the function value should be computed. Returns:double the value of the function.

value

back to summary

public double value(double x)

Implements org.apache.commons.math3.analysis.UnivariateFunction.value.

Doc from org.apache.commons.math3.analysis.UnivariateFunction.value.

Compute the value of the function.

Parameters

x:double: Point at which the function value should be computed.

Returns:double

the value of the function.

public Class NonLinearConjugateGradientOptimizer

Nested and Inner Type Summary

Field Summary

Constructor Summary

Method Summary

Field Detail

Constructor Detail

Method Detail

public Class NonLinearConjugateGradientOptimizer.IdentityPreconditioner

Constructor Summary

Method Summary

Constructor Detail

Method Detail

private Class NonLinearConjugateGradientOptimizer.LineSearchFunction

Field Summary

Constructor Summary

Method Summary

Field Detail

Constructor Detail

Method Detail