/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.commons.math3.analysis.integration;
import org.apache.commons.math3.analysis.UnivariateFunction;
import org.apache.commons.math3.analysis.integration.gauss.GaussIntegratorFactory;
import org.apache.commons.math3.analysis.integration.gauss.GaussIntegrator;
import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.exception.MaxCountExceededException;
import org.apache.commons.math3.exception.NotStrictlyPositiveException;
import org.apache.commons.math3.exception.NumberIsTooSmallException;
import org.apache.commons.math3.exception.TooManyEvaluationsException;
import org.apache.commons.math3.exception.util.LocalizedFormats;
import org.apache.commons.math3.util.FastMath;
/**
* This algorithm divides the integration interval into equally-sized
* sub-interval and on each of them performs a
* <a href="http://mathworld.wolfram.com/Legendre-GaussQuadrature.html">
* Legendre-Gauss</a> quadrature.
* Because of its <em>non-adaptive</em> nature, this algorithm can
* converge to a wrong value for the integral (for example, if the
* function is significantly different from zero toward the ends of the
* integration interval).
* In particular, a change of variables aimed at estimating integrals
* over infinite intervals as proposed
* <a href="http://en.wikipedia.org/w/index.php?title=Numerical_integration#Integrals_over_infinite_intervals">
* here</a> should be avoided when using this class.
*
* @since 3.1
*/
public class IterativeLegendreGaussIntegrator
extends BaseAbstractUnivariateIntegrator {
/** Factory that computes the points and weights. */
private static final GaussIntegratorFactory FACTORY
= new GaussIntegratorFactory();
/** Number of integration points (per interval). */
private final int numberOfPoints;
/**
* Builds an integrator with given accuracies and iterations counts.
*
* @param n Number of integration points.
* @param relativeAccuracy Relative accuracy of the result.
* @param absoluteAccuracy Absolute accuracy of the result.
* @param minimalIterationCount Minimum number of iterations.
* @param maximalIterationCount Maximum number of iterations.
* @throws NotStrictlyPositiveException if minimal number of iterations
* or number of points are not strictly positive.
* @throws NumberIsTooSmallException if maximal number of iterations
* is smaller than or equal to the minimal number of iterations.
*/
public IterativeLegendreGaussIntegrator(final int n,
final double relativeAccuracy,
final double absoluteAccuracy,
final int minimalIterationCount,
final int maximalIterationCount)
throws NotStrictlyPositiveException, NumberIsTooSmallException {
super(relativeAccuracy, absoluteAccuracy, minimalIterationCount, maximalIterationCount);
if (n <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.NUMBER_OF_POINTS, n);
}
numberOfPoints = n;
}
/**
* Builds an integrator with given accuracies.
*
* @param n Number of integration points.
* @param relativeAccuracy Relative accuracy of the result.
* @param absoluteAccuracy Absolute accuracy of the result.
* @throws NotStrictlyPositiveException if {@code n < 1}.
*/
public IterativeLegendreGaussIntegrator(final int n,
final double relativeAccuracy,
final double absoluteAccuracy)
throws NotStrictlyPositiveException {
this(n, relativeAccuracy, absoluteAccuracy,
DEFAULT_MIN_ITERATIONS_COUNT, DEFAULT_MAX_ITERATIONS_COUNT);
}
/**
* Builds an integrator with given iteration counts.
*
* @param n Number of integration points.
* @param minimalIterationCount Minimum number of iterations.
* @param maximalIterationCount Maximum number of iterations.
* @throws NotStrictlyPositiveException if minimal number of iterations
* is not strictly positive.
* @throws NumberIsTooSmallException if maximal number of iterations
* is smaller than or equal to the minimal number of iterations.
* @throws NotStrictlyPositiveException if {@code n < 1}.
*/
public IterativeLegendreGaussIntegrator(final int n,
final int minimalIterationCount,
final int maximalIterationCount)
throws NotStrictlyPositiveException, NumberIsTooSmallException {
this(n, DEFAULT_RELATIVE_ACCURACY, DEFAULT_ABSOLUTE_ACCURACY,
minimalIterationCount, maximalIterationCount);
}
/** {@inheritDoc} */
@Override
protected double doIntegrate()
throws MathIllegalArgumentException, TooManyEvaluationsException, MaxCountExceededException {
// Compute first estimate with a single step.
double oldt = stage(1);
int n = 2;
while (true) {
// Improve integral with a larger number of steps.
final double t = stage(n);
// Estimate the error.
final double delta = FastMath.abs(t - oldt);
final double limit =
FastMath.max(getAbsoluteAccuracy(),
getRelativeAccuracy() * (FastMath.abs(oldt) + FastMath.abs(t)) * 0.5);
// check convergence
if (iterations.getCount() + 1 >= getMinimalIterationCount() &&
delta <= limit) {
return t;
}
// Prepare next iteration.
final double ratio = FastMath.min(4, FastMath.pow(delta / limit, 0.5 / numberOfPoints));
n = FastMath.max((int) (ratio * n), n + 1);
oldt = t;
iterations.incrementCount();
}
}
/**
* Compute the n-th stage integral.
*
* @param n Number of steps.
* @return the value of n-th stage integral.
* @throws TooManyEvaluationsException if the maximum number of evaluations
* is exceeded.
*/
private double stage(final int n)
throws TooManyEvaluationsException {
// Function to be integrated is stored in the base class.
final UnivariateFunction f = new UnivariateFunction() {
public double value(double x)
throws MathIllegalArgumentException, TooManyEvaluationsException {
return computeObjectiveValue(x);
}
};
final double min = getMin();
final double max = getMax();
final double step = (max - min) / n;
double sum = 0;
for (int i = 0; i < n; i++) {
// Integrate over each sub-interval [a, b].
final double a = min + i * step;
final double b = a + step;
final GaussIntegrator g = FACTORY.legendreHighPrecision(numberOfPoints, a, b);
sum += g.integrate(f);
}
return sum;
}
}