org.apache.commons.math.optimization.direct

Class PowellOptimizer

java.lang.Object

org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer

org.apache.commons.math.optimization.direct.PowellOptimizer

All Implemented Interfaces:

DifferentiableMultivariateRealOptimizer

public class PowellOptimizer
extends AbstractScalarDifferentiableOptimizer

Powell algorithm. This code is translated and adapted from the Python version of this algorithm (as implemented in module optimize.py v0.5 of SciPy).

Since:

2.2

Version:

$Revision$ $Date$

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
private class	PowellOptimizer.LineSearch Class for finding the minimum of the objective function along a given direction.

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_LS_ABSOLUTE_TOLERANCE Default absolute tolerance for line search (1.0E-11).
static double	DEFAULT_LS_RELATIVE_TOLERANCE Default relative tolerance for line search (1.0E-7).
private PowellOptimizer.LineSearch	line Line search.

Fields inherited from class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer

checker, DEFAULT_MAX_ITERATIONS, goal, point

Constructor Summary

Constructors

Constructor and Description
PowellOptimizer() Constructor with default line search tolerances (see the other constructor).
PowellOptimizer(double lsRelativeTolerance) Constructor with default absolute line search tolerances (see the other constructor).
PowellOptimizer(double lsRelativeTolerance, double lsAbsoluteTolerance)

Method Summary

Methods

Modifier and Type	Method and Description
private double[]	copyOf(double[] source, int newLen) Java 1.5 does not support Arrays.copyOf()
protected RealPointValuePair	doOptimize() Perform the bulk of optimization algorithm.
private double[][]	newPointAndDirection(double[] p, double[] d, double optimum) Compute a new point (in the original space) and a new direction vector, resulting from the line search.

Methods inherited from class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer

computeObjectiveGradient, computeObjectiveValue, getConvergenceChecker, getEvaluations, getGradientEvaluations, getIterations, getMaxEvaluations, getMaxIterations, incrementIterationsCounter, optimize, setConvergenceChecker, setMaxEvaluations, setMaxIterations

Methods inherited from class java.lang.Object

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

Field Detail

DEFAULT_LS_RELATIVE_TOLERANCE

public static final double DEFAULT_LS_RELATIVE_TOLERANCE

Default relative tolerance for line search (1.0E-7).

See Also:

Constant Field Values

DEFAULT_LS_ABSOLUTE_TOLERANCE

public static final double DEFAULT_LS_ABSOLUTE_TOLERANCE

Default absolute tolerance for line search (1.0E-11).

See Also:

Constant Field Values

line

private final PowellOptimizer.LineSearch line

Line search.

Constructor Detail

PowellOptimizer

public PowellOptimizer()

Constructor with default line search tolerances (see the other constructor).

PowellOptimizer

public PowellOptimizer(double lsRelativeTolerance)

Constructor with default absolute line search tolerances (see the other constructor).

Parameters:

lsRelativeTolerance - Relative error tolerance for the line search algorithm (BrentOptimizer).

PowellOptimizer

public PowellOptimizer(double lsRelativeTolerance,
               double lsAbsoluteTolerance)

Parameters:

lsRelativeTolerance - Relative error tolerance for the line search algorithm (BrentOptimizer).

lsAbsoluteTolerance - Relative error tolerance for the line search algorithm (BrentOptimizer).

Method Detail

doOptimize

protected RealPointValuePair doOptimize()
                                 throws FunctionEvaluationException,
                                        OptimizationException

Perform the bulk of optimization algorithm.

Specified by:

doOptimize in class AbstractScalarDifferentiableOptimizer

Returns:

the point/value pair giving the optimal value for objective function

Throws:

FunctionEvaluationException - if the objective function throws one during the search

OptimizationException - if the algorithm failed to converge

newPointAndDirection

private double[][] newPointAndDirection(double[] p,
                              double[] d,
                              double optimum)

Compute a new point (in the original space) and a new direction vector, resulting from the line search. The parameters p and d will be changed in-place.

Parameters:

p - Point used in the line search.

d - Direction used in the line search.

optimum - Optimum found by the line search.

Returns:

a 2-element array containing the new point (at index 0) and the new direction (at index 1).

copyOf

private double[] copyOf(double[] source,
              int newLen)

Java 1.5 does not support Arrays.copyOf()

Parameters:

source - the array to be copied

newLen - the length of the copy to be returned

Returns:

the copied array, truncated or padded as necessary.