Package org.hipparchus.analysis.integration

Class BaseAbstractUnivariateIntegrator

java.lang.Object
org.hipparchus.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.

  • Field Details

    • DEFAULT_ABSOLUTE_ACCURACY

      public static final double DEFAULT_ABSOLUTE_ACCURACY
      Default absolute accuracy.
      See Also:

    • DEFAULT_RELATIVE_ACCURACY

      public static final double DEFAULT_RELATIVE_ACCURACY
      Default relative accuracy.
      See Also:

    • DEFAULT_MIN_ITERATIONS_COUNT

      public static final int DEFAULT_MIN_ITERATIONS_COUNT
      Default minimal iteration count.
      See Also:

    • DEFAULT_MAX_ITERATIONS_COUNT

      public static final int DEFAULT_MAX_ITERATIONS_COUNT
      Default maximal iteration count.
      See Also:

    • iterations

      protected final Incrementor iterations
      The iteration count.

  • Constructor Details

    • BaseAbstractUnivariateIntegrator

      protected BaseAbstractUnivariateIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount) throws MathIllegalArgumentException
      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:
      MathIllegalArgumentException - if minimal number of iterations is not strictly positive
      MathIllegalArgumentException - 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 MathIllegalArgumentException
      Construct an integrator with given iteration counts.
      Parameters:
      minimalIterationCount - minimum number of iterations
      maximalIterationCount - maximum number of iterations
      Throws:
      MathIllegalArgumentException - if minimal number of iterations is not strictly positive
      MathIllegalArgumentException - if maximal number of iterations is lesser than or equal to the minimal number of iterations

  • Method Details

    • 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()
      Get the lower bound.
      Returns:
      the lower bound.

    • getMax

      protected double getMax()
      Get the upper bound.
      Returns:
      the upper bound.

    • computeObjectiveValue

      protected double computeObjectiveValue(double point) throws MathIllegalStateException
      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:
      MathIllegalStateException - if the maximal number of function evaluations is exceeded.

    • setup

      protected void setup(int maxEval, UnivariateFunction f, double lower, double upper) throws MathIllegalArgumentException, NullArgumentException
      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 MathIllegalArgumentException, MathIllegalStateException, 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 lower bound for the interval
      upper - the upper bound for the interval
      Returns:
      the value of integral
      Throws:
      MathIllegalArgumentException - if min > max or the endpoints do not satisfy the requirements specified by the integrator
      MathIllegalStateException - if the maximum number of function evaluations is exceeded
      NullArgumentException - if f is null.

    • doIntegrate

      protected abstract double doIntegrate() throws MathIllegalStateException
      Method for implementing actual integration algorithms in derived classes.
      Returns:
      the root.
      Throws:
      MathIllegalStateException - if the maximal number of evaluations is exceeded.
      MathIllegalStateException - if the maximum iteration count is exceeded or the integrator detects convergence problems otherwise