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## org.apache.commons.math3.optim.nonlinear.scalar
Class GradientMultivariateOptimizer

    java.lang.Object
      org.apache.commons.math3.optim.BaseOptimizer<PAIR>
          org.apache.commons.math3.optim.BaseMultivariateOptimizer<PointValuePair>
              org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer
                  org.apache.commons.math3.optim.nonlinear.scalar.GradientMultivariateOptimizer

Direct Known Subclasses:
  NonLinearConjugateGradientOptimizer

    public abstract class GradientMultivariateOptimizer

extends MultivariateOptimizer

Base class for implementing optimizers for multivariate scalar differentiable functions. It contains boiler-plate code for dealing with gradient evaluation.

Since:
  3.1
Version:
  $Id$

Field Summary

Fields inherited from class org.apache.commons.math3.optim.BaseOptimizer
`evaluations, iterations`

Constructor Summary
`protected` | `GradientMultivariateOptimizer(ConvergenceChecker<PointValuePair> checker)`

Method Summary
`protected double[]` | `computeObjectiveGradient(double[] params)` Compute the gradient vector.
`PointValuePair` | `optimize(OptimizationData... optData)` Stores data and performs the optimization.

Methods inherited from class org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer
`computeObjectiveValue, getGoalType`

Methods inherited from class org.apache.commons.math3.optim.BaseMultivariateOptimizer
`getLowerBound, getStartPoint, getUpperBound`

Methods inherited from class org.apache.commons.math3.optim.BaseOptimizer
`doOptimize, 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`

Constructor Detail

### GradientMultivariateOptimizer

    protected GradientMultivariateOptimizer(ConvergenceChecker<PointValuePair> checker)

Parameters:
  `checker` - Convergence checker.

Method Detail

### computeObjectiveGradient

    protected double[] computeObjectiveGradient(double[] params)

  Compute the gradient vector.

  Parameters:
    `params` - Point at which the gradient must be evaluated.
  Returns:
    the gradient at the specified point.

### optimize

    public PointValuePair optimize(OptimizationData... optData)
                            throws TooManyEvaluationsException

  Stores data and performs the optimization.
  The list of parameters is open-ended so that sub-classes can extend it with arguments specific to their concrete implementations.
  When the method is called multiple times, instance data is overwritten only when actually present in the list of arguments: when not specified, data set in a previous call is retained (and thus is optional in subsequent calls).

  Overrides:
    `optimize` in class `MultivariateOptimizer`
  Parameters:
    `optData` - Optimization data. The following data will be looked for:
    - `MaxEval`
    - `InitialGuess`
    - `SimpleBounds`
    - `ObjectiveFunction`
    - `GoalType`
    - `ObjectiveFunctionGradient`
  Returns:
    a point/value pair that satifies the convergence criteria.
  Throws:
    `TooManyEvaluationsException` - if the maximal number of evaluations (of the objective function) is exceeded.

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