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## org.apache.commons.math.optimization.general
Class NonLinearConjugateGradientOptimizer

    java.lang.Object
      org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
          org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer

All Implemented Interfaces:
  DifferentiableMultivariateRealOptimizer

    public class NonLinearConjugateGradientOptimizer

extends AbstractScalarDifferentiableOptimizer
implements DifferentiableMultivariateRealOptimizer

Non-linear conjugate gradient optimizer.

This class supports both the Fletcher-Reeves and the Polak-Ribière update formulas for the conjugate search directions. It also supports optional preconditioning.

Since:
  2.0
Version:
  $Revision: 811685 $ $Date: 2009-09-05 13:36:48 -0400 (Sat, 05 Sep 2009) $

Nested Class Summary
`private static class` | `NonLinearConjugateGradientOptimizer.IdentityPreconditioner` Default identity preconditioner.
`private class` | `NonLinearConjugateGradientOptimizer.LineSearchFunction` Internal class for line search.

Field Summary
`private double` | `initialStep` Initial step used to bracket the optimum in line search.
`private Preconditioner` | `preconditioner` Preconditioner (may be null).
`private UnivariateRealSolver` | `solver` solver to use in the line search (may be null).
`private ConjugateGradientFormula` | `updateFormula` Update formula for the beta parameter.

Fields inherited from class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
`checker, DEFAULT_MAX_ITERATIONS, goal, point`

Constructor Summary
`NonLinearConjugateGradientOptimizer(ConjugateGradientFormula updateFormula)` Simple constructor with default settings.

Method Summary
`protected RealPointValuePair` | `doOptimize()` Perform the bulk of optimization algorithm.
`private double` | `findUpperBound(UnivariateRealFunction f, double a, double h)` Find the upper bound b ensuring bracketing of a root between a and b
`void` | `setInitialStep(double initialStep)` Set the initial step used to bracket the optimum in line search.
`void` | `setLineSearchSolver(UnivariateRealSolver lineSearchSolver)` Set the solver to use during line search.
`void` | `setPreconditioner(Preconditioner preconditioner)` Set the preconditioner.

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`

Methods inherited from interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
`getConvergenceChecker, getEvaluations, getGradientEvaluations, getIterations, getMaxEvaluations, getMaxIterations, optimize, setConvergenceChecker, setMaxEvaluations, setMaxIterations`

Field Detail

### updateFormula

    private final ConjugateGradientFormula updateFormula

  Update formula for the beta parameter.

### preconditioner

    private Preconditioner preconditioner

  Preconditioner (may be null).

### solver

    private UnivariateRealSolver solver

  solver to use in the line search (may be null).

### initialStep

    private double initialStep

  Initial step used to bracket the optimum in line search.

Constructor Detail

### NonLinearConjugateGradientOptimizer

    public NonLinearConjugateGradientOptimizer(ConjugateGradientFormula updateFormula)

  Simple constructor with default settings.

  The convergence check is set to a `SimpleVectorialValueChecker` and the maximal number of iterations is set to `AbstractScalarDifferentiableOptimizer.DEFAULT_MAX_ITERATIONS`.

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

Method Detail

### setPreconditioner

    public void setPreconditioner(Preconditioner preconditioner)

  Set the preconditioner.

  Parameters:
    `preconditioner` - preconditioner to use for next optimization, may be null to remove an already registered preconditioner

### setLineSearchSolver

    public void setLineSearchSolver(UnivariateRealSolver lineSearchSolver)

  Set the solver to use during line search.

  Parameters:
    `lineSearchSolver` - solver to use during line search, may be null to remove an already registered solver and fall back to the default `Brent solver`.

### setInitialStep

    public void setInitialStep(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` - 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

### doOptimize

    protected RealPointValuePair doOptimize()
                                     throws FunctionEvaluationException,
                                            OptimizationException,
                                            java.lang.IllegalArgumentException

  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
    `java.lang.IllegalArgumentException` - if the start point dimension is wrong

### findUpperBound

    private double findUpperBound(UnivariateRealFunction f,
                                  double a,
                                  double h)
                           throws FunctionEvaluationException,
                                  OptimizationException

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

  Parameters:
    `f` - function whose root must be bracketed
    `a` - lower bound of the interval
    `h` - initial step to try
  Returns:
    b such that f(a) and f(b) have opposite signs
  Throws:
    `FunctionEvaluationException` - if the function cannot be computed
    `OptimizationException` - if no bracket can be found

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