org.apache.commons.math3.analysis.integration

## Class BaseAbstractUnivariateIntegrator

- java.lang.Object
- - org.apache.commons.math3.analysis.integration.BaseAbstractUnivariateIntegrator

All Implemented Interfaces:
  UnivariateIntegrator

Direct Known Subclasses:
  IterativeLegendreGaussIntegrator, LegendreGaussIntegrator, RombergIntegrator, SimpsonIntegrator, TrapezoidIntegrator

    public abstract class BaseAbstractUnivariateIntegrator
    extends java.lang.Object
    implements UnivariateIntegrator

Provide a default implementation for several generic functions.

Since:
  1.2
Version:
  $Id: BaseAbstractUnivariateIntegrator.java 1364387 2012-07-22 18:14:11Z tn $

### Field Summary

Fields
`private double` `absoluteAccuracy` Maximum absolute error.
`static double` `DEFAULT_ABSOLUTE_ACCURACY` Default absolute accuracy.
`static int` `DEFAULT_MAX_ITERATIONS_COUNT` Default maximal iteration count.
`static int` `DEFAULT_MIN_ITERATIONS_COUNT` Default minimal iteration count.
`static double` `DEFAULT_RELATIVE_ACCURACY` Default relative accuracy.
`private Incrementor` `evaluations` The functions evaluation count.
`private UnivariateFunction` `function` Function to integrate.
`protected Incrementor` `iterations` The iteration count.
`private double` `max` Upper bound for the interval.
`private double` `min` Lower bound for the interval.
`private int` `minimalIterationCount` minimum number of iterations
`private double` `relativeAccuracy` Maximum relative error.

### Constructor Summary

Constructors
`protected` `BaseAbstractUnivariateIntegrator(double relativeAccuracy, double absoluteAccuracy)` Construct an integrator with given accuracies.
`protected` `BaseAbstractUnivariateIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Construct an integrator with given accuracies and iteration counts.
`protected` `BaseAbstractUnivariateIntegrator(int minimalIterationCount, int maximalIterationCount)` Construct an integrator with given iteration counts.

### Method Summary

Methods
`protected double` `computeObjectiveValue(double point)` Compute the objective function value.
`protected abstract double` `doIntegrate()` Method for implementing actual integration algorithms in derived classes.
`double` `getAbsoluteAccuracy()` Get the actual absolute accuracy.
`int` `getEvaluations()` Get the number of function evaluations of the last run of the integrator.
`int` `getIterations()` Get the number of iterations of the last run of the integrator.
`protected double` `getMax()`
`int` `getMaximalIterationCount()` Get the upper limit for the number of iterations.
`protected double` `getMin()`
`int` `getMinimalIterationCount()` Get the min limit for the number of iterations.
`double` `getRelativeAccuracy()` Get the actual relative accuracy.
`double` `integrate(int maxEval, UnivariateFunction f, double lower, double upper)` Integrate the function in the given interval.
`protected void` `setup(int maxEval, UnivariateFunction f, double lower, double upper)` Prepare for computation.

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

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

### Field Detail

#### DEFAULT_ABSOLUTE_ACCURACY

    public static final double DEFAULT_ABSOLUTE_ACCURACY

Default absolute accuracy.

See Also:
  Constant Field Values

#### DEFAULT_RELATIVE_ACCURACY

    public static final double DEFAULT_RELATIVE_ACCURACY

Default relative accuracy.

See Also:
  Constant Field Values

#### DEFAULT_MIN_ITERATIONS_COUNT

    public static final int DEFAULT_MIN_ITERATIONS_COUNT

Default minimal iteration count.

See Also:
  Constant Field Values

#### DEFAULT_MAX_ITERATIONS_COUNT

    public static final int DEFAULT_MAX_ITERATIONS_COUNT

Default maximal iteration count.

See Also:
  Constant Field Values

#### iterations

    protected final Incrementor iterations

The iteration count.

#### absoluteAccuracy

    private final double absoluteAccuracy

Maximum absolute error.

#### relativeAccuracy

    private final double relativeAccuracy

Maximum relative error.

#### minimalIterationCount

    private final int minimalIterationCount

minimum number of iterations

#### evaluations

    private final Incrementor evaluations

The functions evaluation count.

#### function

    private UnivariateFunction function

Function to integrate.

#### min

    private double min

Lower bound for the interval.

#### max

    private double max

Upper bound for the interval.

### Constructor Detail

#### BaseAbstractUnivariateIntegrator

    protected BaseAbstractUnivariateIntegrator(double relativeAccuracy,
                                    double absoluteAccuracy,
                                    int minimalIterationCount,
                                    int maximalIterationCount)
                                        throws NotStrictlyPositiveException,
                                               NumberIsTooSmallException

Construct an integrator with given accuracies and iteration counts.

The meanings of the various parameters are:

- relative accuracy: this is used to stop iterations if the absolute accuracy can't be achieved due to large values or short mantissa length. If this should be the primary criterion for convergence rather then a safety measure, set the absolute accuracy to a ridiculously small value, like `Precision.SAFE_MIN`.
- absolute accuracy: The default is usually chosen so that results in the interval -10..-0.1 and +0.1..+10 can be found with a reasonable accuracy. If the expected absolute value of your results is of much smaller magnitude, set this to a smaller value.
- minimum number of iterations: minimal iteration is needed to avoid false early convergence, e.g. the sample points happen to be zeroes of the function. Users can use the default value or choose one that they see as appropriate.
- maximum number of iterations: usually a high iteration count indicates convergence problems. However, the "reasonable value" varies widely for different algorithms. Users are advised to use the default value supplied by the algorithm.

Parameters:
  `relativeAccuracy` - relative accuracy of the result
  `absoluteAccuracy` - absolute accuracy of the result
  `minimalIterationCount` - minimum number of iterations
  `maximalIterationCount` - maximum number of iterations
Throws:
  `NotStrictlyPositiveException` - if minimal number of iterations is not strictly positive
  `NumberIsTooSmallException` - if maximal number of iterations is lesser than or equal to the minimal number of iterations

#### BaseAbstractUnivariateIntegrator

    protected BaseAbstractUnivariateIntegrator(double relativeAccuracy,
                                    double absoluteAccuracy)

Construct an integrator with given accuracies.

Parameters:
  `relativeAccuracy` - relative accuracy of the result
  `absoluteAccuracy` - absolute accuracy of the result

#### BaseAbstractUnivariateIntegrator

    protected BaseAbstractUnivariateIntegrator(int minimalIterationCount,
                                    int maximalIterationCount)
                                        throws NotStrictlyPositiveException,
                                               NumberIsTooSmallException

Construct an integrator with given iteration counts.

Parameters:
  `minimalIterationCount` - minimum number of iterations
  `maximalIterationCount` - maximum number of iterations
Throws:
  `NotStrictlyPositiveException` - if minimal number of iterations is not strictly positive
  `NumberIsTooSmallException` - if maximal number of iterations is lesser than or equal to the minimal number of iterations

### Method Detail

#### getRelativeAccuracy

    public double getRelativeAccuracy()

Get the actual relative accuracy.

Specified by:
  `getRelativeAccuracy` in interface `UnivariateIntegrator`
Returns:
  the accuracy

#### getAbsoluteAccuracy

    public double getAbsoluteAccuracy()

Get the actual absolute accuracy.

Specified by:
  `getAbsoluteAccuracy` in interface `UnivariateIntegrator`
Returns:
  the accuracy

#### getMinimalIterationCount

    public int getMinimalIterationCount()

Get the min limit for the number of iterations.

Specified by:
  `getMinimalIterationCount` in interface `UnivariateIntegrator`
Returns:
  the actual min limit

#### getMaximalIterationCount

    public int getMaximalIterationCount()

Get the upper limit for the number of iterations.

Specified by:
  `getMaximalIterationCount` in interface `UnivariateIntegrator`
Returns:
  the actual upper limit

#### getEvaluations

    public int getEvaluations()

Get the number of function evaluations of the last run of the integrator.

Specified by:
  `getEvaluations` in interface `UnivariateIntegrator`
Returns:
  number of function evaluations

#### getIterations

    public int getIterations()

Get the number of iterations of the last run of the integrator.

Specified by:
  `getIterations` in interface `UnivariateIntegrator`
Returns:
  number of iterations

#### getMin

    protected double getMin()

Returns:
  the lower bound.

#### getMax

    protected double getMax()

Returns:
  the upper bound.

#### computeObjectiveValue

    protected double computeObjectiveValue(double point)
                                    throws TooManyEvaluationsException

Compute the objective function value.

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

#### setup

    protected void setup(int maxEval,
             UnivariateFunction f,
             double lower,
             double upper)
                  throws NullArgumentException,
                         MathIllegalArgumentException

Prepare for computation. Subclasses must call this method if they override any of the `solve` methods.

Parameters:
  `maxEval` - Maximum number of evaluations.
  `f` - the integrand function
  `lower` - the min bound for the interval
  `upper` - the upper bound for the interval
Throws:
  `NullArgumentException` - if `f` is `null`.
  `MathIllegalArgumentException` - if `min >= max`.

#### integrate

    public double integrate(int maxEval,
                   UnivariateFunction f,
                   double lower,
                   double upper)
                     throws TooManyEvaluationsException,
                            MaxCountExceededException,
                            MathIllegalArgumentException,
                            NullArgumentException

Integrate the function in the given interval.

Specified by:
  `integrate` in interface `UnivariateIntegrator`
Parameters:
  `maxEval` - Maximum number of evaluations.
  `f` - the integrand function
  `lower` - the min bound for the interval
  `upper` - the upper bound for the interval
Returns:
  the value of integral
Throws:
  `TooManyEvaluationsException` - if the maximum number of function evaluations is exceeded.
  `MaxCountExceededException` - if the maximum iteration count is exceeded or the integrator detects convergence problems otherwise
  `MathIllegalArgumentException` - if min > max or the endpoints do not satisfy the requirements specified by the integrator
  `NullArgumentException` - if `f` is `null`.

#### doIntegrate

    protected abstract double doIntegrate()
                                   throws TooManyEvaluationsException,
                                          MaxCountExceededException

Method for implementing actual integration algorithms in derived classes.

Returns:
  the root.
Throws:
  `TooManyEvaluationsException` - if the maximal number of evaluations is exceeded.
  `MaxCountExceededException` - if the maximum iteration count is exceeded or the integrator detects convergence problems otherwise