java.lang.Object
- org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator

All Implemented Interfaces:

UnivariateIntegrator

Direct Known Subclasses:

IterativeLegendreGaussIntegrator, MidPointIntegrator, RombergIntegrator, SimpsonIntegrator, TrapezoidIntegrator
```
public abstract class BaseAbstractUnivariateIntegrator
extends Object
implements UnivariateIntegrator
```
Provide a default implementation for several generic functions.

Since:

1.2

Field Summary

Fields
Modifier and Type	Field	Description
`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.
`protected IntegerSequence.Incrementor`	`iterations`	The iteration count.

Constructor Summary

Constructors
Modifier	Constructor	Description
`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

All Methods Instance Methods Abstract Methods Concrete Methods
Modifier and Type	Method	Description
`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 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 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 IntegerSequence.Incrementor iterations
```
    The iteration count.
- Constructor Detail
  - BaseAbstractUnivariateIntegrator
```
protected BaseAbstractUnivariateIntegrator(double relativeAccuracy,
                                           double absoluteAccuracy,
                                           int minimalIterationCount,
                                           int maximalIterationCount)
```
    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)
```
    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 relative accuracy.
    
    Specified by:
    
    getRelativeAccuracy in interface UnivariateIntegrator
    
    Returns:
    
    the accuracy
  - getAbsoluteAccuracy
```
public double getAbsoluteAccuracy()
```
    Get the 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)
```
    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)
```
    Prepare for computation. Subclasses must call this method if they the integrate method.
    
    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)
```
    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 lower bound for the interval
    
    upper - the upper bound for the interval
    
    Returns:
    
    the value of integral
  - doIntegrate
```
protected abstract double doIntegrate()
```
    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

Class BaseAbstractUnivariateIntegrator

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

DEFAULT_ABSOLUTE_ACCURACY

DEFAULT_RELATIVE_ACCURACY

DEFAULT_MIN_ITERATIONS_COUNT

DEFAULT_MAX_ITERATIONS_COUNT

iterations

Constructor Detail

BaseAbstractUnivariateIntegrator

BaseAbstractUnivariateIntegrator

BaseAbstractUnivariateIntegrator

Method Detail

getRelativeAccuracy

getAbsoluteAccuracy

getMinimalIterationCount

getMaximalIterationCount

getEvaluations

getIterations

getMin

getMax

computeObjectiveValue

setup

integrate

doIntegrate