BaseAbstractMultivariateVectorOptimizer (Apache Commons Math 3.6.1 API)

org.apache.commons.math3.optimization.direct

## Class BaseAbstractMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>

- java.lang.Object
- - org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateVectorOptimizer<FUNC>

- Type Parameters:
    `FUNC` - the type of the objective function to be optimized
  All Implemented Interfaces:
    BaseMultivariateVectorOptimizer<FUNC>, BaseOptimizer<PointVectorValuePair>
  Direct Known Subclasses:
    AbstractLeastSquaresOptimizer

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

      @Deprecated
      public abstract class BaseAbstractMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>
      extends Object
      implements BaseMultivariateVectorOptimizer<FUNC>

  Base class for implementing optimizers for multivariate scalar functions. This base class handles the boiler-plate methods associated to thresholds settings, iterations and evaluations counting.
  Since:
    3.0

- - ### Field Summary

    Fields
    Modifier and Type | Field and Description
    --- | ---
    `protected Incrementor` | `evaluations` Deprecated. Evaluations counter.

  - ### Constructor Summary

    Constructors
    Modifier | Constructor and Description
    --- | ---
    `protected` | `BaseAbstractMultivariateVectorOptimizer()` Deprecated. See `SimpleVectorValueChecker.SimpleVectorValueChecker()`
    `protected` | `BaseAbstractMultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker)` Deprecated.

  - ### Method Summary

    Methods
    Modifier and Type | Method and Description
    --- | ---
    `protected double[]` | `computeObjectiveValue(double[] point)` Deprecated. Compute the objective function value.
    `protected abstract PointVectorValuePair` | `doOptimize()` Deprecated. Perform the bulk of the optimization algorithm.
    `ConvergenceChecker<PointVectorValuePair>` | `getConvergenceChecker()` Deprecated. Get the convergence checker.
    `int` | `getEvaluations()` Deprecated. Get the number of evaluations of the objective function.
    `int` | `getMaxEvaluations()` Deprecated. Get the maximal number of function evaluations.
    `protected FUNC` | `getObjectiveFunction()` Deprecated. Gets the objective vector function.
    `double[]` | `getStartPoint()` Deprecated. Gets the initial values of the optimized parameters.
    `double[]` | `getTarget()` Deprecated. Gets the observed values to be matched by the objective vector function.
    `protected double[]` | `getTargetRef()` Deprecated. As of 3.1.
    `RealMatrix` | `getWeight()` Deprecated. Gets the weight matrix of the observations.
    `protected double[]` | `getWeightRef()` Deprecated. As of 3.1.
    `PointVectorValuePair` | `optimize(int maxEval, FUNC f, double[] t, double[] w, double[] startPoint)` Deprecated. As of 3.1. Please use `optimize(int,MultivariateVectorFunction,OptimizationData[])` instead.
    `protected PointVectorValuePair` | `optimize(int maxEval, FUNC f, OptimizationData... optData)` Deprecated. Optimize an objective function.
    `protected PointVectorValuePair` | `optimizeInternal(int maxEval, FUNC f, double[] t, double[] w, double[] startPoint)` Deprecated. As of 3.1. Please use `optimizeInternal(int,MultivariateVectorFunction,OptimizationData[])` instead.
    `protected PointVectorValuePair` | `optimizeInternal(int maxEval, FUNC f, OptimizationData... optData)` Deprecated. Optimize an objective function.
    `protected void` | `setUp()` Deprecated. Method which a subclass must override whenever its internal state depend on the `input` parsed by this base class.

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

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

- - ### Field Detail

    - #### evaluations

          protected final Incrementor evaluations

      Deprecated.
      Evaluations counter.

  - ### Constructor Detail

    - #### BaseAbstractMultivariateVectorOptimizer

          @Deprecated
          protected BaseAbstractMultivariateVectorOptimizer()

      Deprecated. See `SimpleVectorValueChecker.SimpleVectorValueChecker()`
      Simple constructor with default settings. The convergence check is set to a `SimpleVectorValueChecker`.

    - #### BaseAbstractMultivariateVectorOptimizer

          protected BaseAbstractMultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker)

      Deprecated.
      Parameters:
        `checker` - Convergence checker.

  - ### Method Detail

    - #### getMaxEvaluations

          public int getMaxEvaluations()

      Deprecated.
      Get the maximal number of function evaluations.
      Specified by:
        `getMaxEvaluations` in interface `BaseOptimizer<PointVectorValuePair>`
      Returns:
        the maximal number of function evaluations.

    - #### getEvaluations

          public int getEvaluations()

      Deprecated.
      Get the number of evaluations of the objective function. The number of evaluations corresponds to the last call to the `optimize` method. It is 0 if the method has not been called yet.
      Specified by:
        `getEvaluations` in interface `BaseOptimizer<PointVectorValuePair>`
      Returns:
        the number of evaluations of the objective function.

    - #### getConvergenceChecker

          public ConvergenceChecker<PointVectorValuePair> getConvergenceChecker()

      Deprecated.
      Get the convergence checker.
      Specified by:
        `getConvergenceChecker` in interface `BaseOptimizer<PointVectorValuePair>`
      Returns:
        the object used to check for convergence.

    - #### computeObjectiveValue

          protected double[] computeObjectiveValue(double[] point)

      Deprecated.
      Compute the objective function value.
      Parameters:
        `point` - Point at which the objective function must be evaluated.
      Returns:
        the objective function value at the specified point.
      Throws:
        `TooManyEvaluationsException` - if the maximal number of evaluations is exceeded.

    - #### optimize

          @Deprecated
          public PointVectorValuePair optimize(int maxEval,
                                                 FUNC f,
                                                 double[] t,
                                                 double[] w,
                                                 double[] startPoint)

      Deprecated. As of 3.1. Please use `optimize(int,MultivariateVectorFunction,OptimizationData[])` instead.
      Optimize an objective function. Optimization is considered to be a weighted least-squares minimization. The cost function to be minimized is `∑weighti(objectivei - targeti)2`
      Specified by:
        `optimize` in interface `BaseMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction>`
      Parameters:
        `maxEval` - Maximum number of function evaluations.
        `f` - Objective function.
        `t` - Target value for the objective functions at optimum.
        `w` - Weights for the least squares cost computation.
        `startPoint` - Start point for optimization.
      Returns:
        the point/value pair giving the optimal value for objective function.

    - #### optimize

          protected PointVectorValuePair optimize(int maxEval,
                                      FUNC f,
                                      OptimizationData... optData)
                                           throws TooManyEvaluationsException,
                                                  DimensionMismatchException

      Deprecated.
      Optimize an objective function.
      Parameters:
        `maxEval` - Allowed number of evaluations of the objective function.
        `f` - Objective function.
        `optData` - Optimization data. The following data will be looked for:
        - `Target`
        - `Weight`
        - `InitialGuess`
      Returns:
        the point/value pair giving the optimal value of the objective function.
      Throws:
        `TooManyEvaluationsException` - if the maximal number of evaluations is exceeded.
        `DimensionMismatchException` - if the initial guess, target, and weight arguments have inconsistent dimensions.
      Since:
        3.1

    - #### optimizeInternal

          @Deprecated
          protected PointVectorValuePair optimizeInternal(int maxEval,
                                                         FUNC f,
                                                         double[] t,
                                                         double[] w,
                                                         double[] startPoint)

      Deprecated. As of 3.1. Please use `optimizeInternal(int,MultivariateVectorFunction,OptimizationData[])` instead.
      Optimize an objective function. Optimization is considered to be a weighted least-squares minimization. The cost function to be minimized is `∑weighti(objectivei - targeti)2`
      Parameters:
        `f` - Objective function.
        `t` - Target value for the objective functions at optimum.
        `w` - Weights for the least squares cost computation.
        `startPoint` - Start point for optimization.
        `maxEval` - Maximum number of function evaluations.
      Returns:
        the point/value pair giving the optimal value for objective function.
      Throws:
        `DimensionMismatchException` - if the start point dimension is wrong.
        `TooManyEvaluationsException` - if the maximal number of evaluations is exceeded.
        `NullArgumentException` - if any argument is `null`.

    - #### optimizeInternal

          protected PointVectorValuePair optimizeInternal(int maxEval,
                                              FUNC f,
                                              OptimizationData... optData)
                                                   throws TooManyEvaluationsException,
                                                          DimensionMismatchException

      Deprecated.
      Optimize an objective function.
      Parameters:
        `maxEval` - Allowed number of evaluations of the objective function.
        `f` - Objective function.
        `optData` - Optimization data. The following data will be looked for:
        - `Target`
        - `Weight`
        - `InitialGuess`
      Returns:
        the point/value pair giving the optimal value of the objective function.
      Throws:
        `TooManyEvaluationsException` - if the maximal number of evaluations is exceeded.
        `DimensionMismatchException` - if the initial guess, target, and weight arguments have inconsistent dimensions.
      Since:
        3.1

    - #### getStartPoint

          public double[] getStartPoint()

      Deprecated.
      Gets the initial values of the optimized parameters.
      Returns:
        the initial guess.

    - #### getWeight

          public RealMatrix getWeight()

      Deprecated.
      Gets the weight matrix of the observations.
      Returns:
        the weight matrix.
      Since:
        3.1

    - #### getTarget

          public double[] getTarget()

      Deprecated.
      Gets the observed values to be matched by the objective vector function.
      Returns:
        the target values.
      Since:
        3.1

    - #### getObjectiveFunction

          protected FUNC getObjectiveFunction()

      Deprecated.
      Gets the objective vector function. Note that this access bypasses the evaluation counter.
      Returns:
        the objective vector function.
      Since:
        3.1

    - #### doOptimize

          protected abstract PointVectorValuePair doOptimize()

      Deprecated.
      Perform the bulk of the optimization algorithm.
      Returns:
        the point/value pair giving the optimal value for the objective function.

    - #### getTargetRef

          @Deprecated
          protected double[] getTargetRef()

      Deprecated. As of 3.1.
      Returns:
        a reference to the `array`.

    - #### getWeightRef

          @Deprecated
          protected double[] getWeightRef()

      Deprecated. As of 3.1.
      Returns:
        a reference to the `array`.

    - #### setUp

          protected void setUp()

      Deprecated.
      Method which a subclass must override whenever its internal state depend on the `input` parsed by this base class. It will be called after the parsing step performed in the `optimize` method and just before `doOptimize()`.
      Since:
        3.1

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