BrentOptimizer (Apache Commons Math 3.6.1 API)

org.apache.commons.math3.optimization.univariate

## Class BrentOptimizer

- java.lang.Object
- - org.apache.commons.math3.optimization.univariate.BaseAbstractUnivariateOptimizer
  - - org.apache.commons.math3.optimization.univariate.BrentOptimizer

- All Implemented Interfaces:
    BaseOptimizer<UnivariatePointValuePair>, BaseUnivariateOptimizer<UnivariateFunction>, UnivariateOptimizer

  Deprecated.
  As of 3.1 (to be removed in 4.0).

      @Deprecated
      public class BrentOptimizer
      extends BaseAbstractUnivariateOptimizer

  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
  - to use an initial guess provided by the user,
  - to ensure that the best point encountered is the one returned.
  Since:
    2.0

- - ### Constructor Summary

    Constructors
    Constructor and Description
    `BrentOptimizer(double rel, double abs)` Deprecated. The arguments are used for implementing the original stopping criterion of Brent's algorithm.
    `BrentOptimizer(double rel, double abs, ConvergenceChecker<UnivariatePointValuePair> checker)` Deprecated. The arguments are used implement the original stopping criterion of Brent's algorithm.

  - ### Method Summary

    Methods
    Modifier and Type | Method and Description
    --- | ---
    `protected UnivariatePointValuePair` | `doOptimize()` Deprecated. Method for implementing actual optimization algorithms in derived classes.

    - ### Methods inherited from class org.apache.commons.math3.optimization.univariate.BaseAbstractUnivariateOptimizer

      `computeObjectiveValue, getConvergenceChecker, getEvaluations, getGoalType, getMax, getMaxEvaluations, getMin, getStartValue, optimize, optimize`

    - ### Methods inherited from class java.lang.Object

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

- - ### Constructor Detail

    - #### BrentOptimizer

          public BrentOptimizer(double rel,
                        double abs,
                        ConvergenceChecker<UnivariatePointValuePair> checker)

      Deprecated.
      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)

      Deprecated.
      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()

      Deprecated.
      Method for implementing actual optimization algorithms in derived classes.
      Specified by:
        `doOptimize` in class `BaseAbstractUnivariateOptimizer`
      Returns:
        the optimum and its corresponding function value.

Copyright © 2003–2016 The Apache Software Foundation. All rights reserved.