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java.lang.Object org.apache.commons.math3.analysis.integration.BaseAbstractUnivariateIntegrator org.apache.commons.math3.analysis.integration.RombergIntegrator
public class RombergIntegrator
Implements the Romberg Algorithm for integration of real univariate functions. For reference, see Introduction to Numerical Analysis, ISBN 038795452X, chapter 3.
Romberg integration employs k successive refinements of the trapezoid rule to remove error terms less than order O(N^(-2k)). Simpson's rule is a special case of k = 2.
Field Summary | |
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static int |
ROMBERG_MAX_ITERATIONS_COUNT
Maximal number of iterations for Romberg. |
Fields inherited from class org.apache.commons.math3.analysis.integration.BaseAbstractUnivariateIntegrator |
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DEFAULT_ABSOLUTE_ACCURACY, DEFAULT_MAX_ITERATIONS_COUNT, DEFAULT_MIN_ITERATIONS_COUNT, DEFAULT_RELATIVE_ACCURACY, iterations |
Constructor Summary | |
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RombergIntegrator()
Construct a Romberg integrator with default settings (max iteration count set to ROMBERG_MAX_ITERATIONS_COUNT ) |
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RombergIntegrator(double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Build a Romberg integrator with given accuracies and iterations counts. |
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RombergIntegrator(int minimalIterationCount,
int maximalIterationCount)
Build a Romberg integrator with given iteration counts. |
Method Summary | |
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protected double |
doIntegrate()
Method for implementing actual integration algorithms in derived classes. |
Methods inherited from class org.apache.commons.math3.analysis.integration.BaseAbstractUnivariateIntegrator |
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computeObjectiveValue, getAbsoluteAccuracy, getEvaluations, getIterations, getMax, getMaximalIterationCount, getMin, getMinimalIterationCount, getRelativeAccuracy, integrate, setup |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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public static final int ROMBERG_MAX_ITERATIONS_COUNT
Constructor Detail |
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public RombergIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount) throws NotStrictlyPositiveException, NumberIsTooSmallException, NumberIsTooLargeException
relativeAccuracy
- relative accuracy of the resultabsoluteAccuracy
- absolute accuracy of the resultminimalIterationCount
- minimum number of iterationsmaximalIterationCount
- maximum number of iterations
(must be less than or equal to ROMBERG_MAX_ITERATIONS_COUNT
)
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
NumberIsTooLargeException
- if maximal number of iterations
is greater than ROMBERG_MAX_ITERATIONS_COUNT
public RombergIntegrator(int minimalIterationCount, int maximalIterationCount) throws NotStrictlyPositiveException, NumberIsTooSmallException, NumberIsTooLargeException
minimalIterationCount
- minimum number of iterationsmaximalIterationCount
- maximum number of iterations
(must be less than or equal to ROMBERG_MAX_ITERATIONS_COUNT
)
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
NumberIsTooLargeException
- if maximal number of iterations
is greater than ROMBERG_MAX_ITERATIONS_COUNT
public RombergIntegrator()
ROMBERG_MAX_ITERATIONS_COUNT
)
Method Detail |
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protected double doIntegrate() throws TooManyEvaluationsException, MaxCountExceededException
doIntegrate
in class BaseAbstractUnivariateIntegrator
TooManyEvaluationsException
- if the maximal number of evaluations
is exceeded.
MaxCountExceededException
- if the maximum iteration count is exceeded
or the integrator detects convergence problems otherwise
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