org.apache.commons.math3.optim.univariate
Class BrentOptimizer

java.lang.Object
  extended by org.apache.commons.math3.optim.BaseOptimizer<UnivariatePointValuePair>
      extended by org.apache.commons.math3.optim.univariate.UnivariateOptimizer
          extended by org.apache.commons.math3.optim.univariate.BrentOptimizer
Direct Known Subclasses:
PowellOptimizer.LineSearch

public class BrentOptimizer
extends UnivariateOptimizer

For a function defined on some interval (lo, hi), this class finds an approximation x to the point at which the function attains its minimum. It implements Richard Brent's algorithm (from his book "Algorithms for Minimization without Derivatives", p. 79) for finding minima of real univariate functions.
This code is an adaptation, partly based on the Python code from SciPy (module "optimize.py" v0.5); the original algorithm is also modified

Since:
2.0
Version:
$Id: BrentOptimizer.java 1416643 2012-12-03 19:37:14Z tn $

Field Summary
private  double absoluteThreshold
          Absolute threshold.
private static double GOLDEN_SECTION
          Golden section.
private static double MIN_RELATIVE_TOLERANCE
          Minimum relative tolerance.
private  double relativeThreshold
          Relative threshold.
 
Fields inherited from class org.apache.commons.math3.optim.BaseOptimizer
evaluations, iterations
 
Constructor Summary
BrentOptimizer(double rel, double abs)
          The arguments are used for implementing the original stopping criterion of Brent's algorithm.
BrentOptimizer(double rel, double abs, ConvergenceChecker<UnivariatePointValuePair> checker)
          The arguments are used implement the original stopping criterion of Brent's algorithm.
 
Method Summary
private  UnivariatePointValuePair best(UnivariatePointValuePair a, UnivariatePointValuePair b, boolean isMinim)
          Selects the best of two points.
protected  UnivariatePointValuePair doOptimize()
          Performs the bulk of the optimization algorithm.
 
Methods inherited from class org.apache.commons.math3.optim.univariate.UnivariateOptimizer
computeObjectiveValue, getGoalType, getMax, getMin, getStartValue, optimize
 
Methods inherited from class org.apache.commons.math3.optim.BaseOptimizer
getConvergenceChecker, getEvaluations, getIterations, getMaxEvaluations, getMaxIterations, incrementEvaluationCount, incrementIterationCount
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

GOLDEN_SECTION

private static final double GOLDEN_SECTION
Golden section.


MIN_RELATIVE_TOLERANCE

private static final double MIN_RELATIVE_TOLERANCE
Minimum relative tolerance.


relativeThreshold

private final double relativeThreshold
Relative threshold.


absoluteThreshold

private final double absoluteThreshold
Absolute threshold.

Constructor Detail

BrentOptimizer

public BrentOptimizer(double rel,
                      double abs,
                      ConvergenceChecker<UnivariatePointValuePair> checker)
The arguments are used implement the original stopping criterion of Brent's algorithm. abs and rel define a tolerance tol = rel |x| + abs. rel should be no smaller than 2 macheps and preferably not much less than sqrt(macheps), where macheps is the relative machine precision. abs must be positive.

Parameters:
rel - Relative threshold.
abs - Absolute threshold.
checker - Additional, user-defined, convergence checking procedure.
Throws:
NotStrictlyPositiveException - if abs <= 0.
NumberIsTooSmallException - if rel < 2 * Math.ulp(1d).

BrentOptimizer

public BrentOptimizer(double rel,
                      double abs)
The arguments are used for implementing the original stopping criterion of Brent's algorithm. abs and rel define a tolerance tol = rel |x| + abs. rel should be no smaller than 2 macheps and preferably not much less than sqrt(macheps), where macheps is the relative machine precision. abs must be positive.

Parameters:
rel - Relative threshold.
abs - Absolute threshold.
Throws:
NotStrictlyPositiveException - if abs <= 0.
NumberIsTooSmallException - if rel < 2 * Math.ulp(1d).
Method Detail

doOptimize

protected UnivariatePointValuePair doOptimize()
Performs the bulk of the optimization algorithm.

Specified by:
doOptimize in class BaseOptimizer<UnivariatePointValuePair>
Returns:
the point/value pair giving the optimal value of the objective function.

best

private UnivariatePointValuePair best(UnivariatePointValuePair a,
                                      UnivariatePointValuePair b,
                                      boolean isMinim)
Selects the best of two points.

Parameters:
a - Point and value.
b - Point and value.
isMinim - true if the selected point must be the one with the lowest value.
Returns:
the best point, or null if a and b are both null. When a and b have the same function value, a is returned.


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