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// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
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//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
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package org.spaceroots.mantissa.quadrature.scalar;
import org.spaceroots.mantissa.functions.scalar.*;
import org.spaceroots.mantissa.functions.FunctionException;
import org.spaceroots.mantissa.functions.ExhaustedSampleException;
/** This class implements an enhanced Simpson integrator as a sample.
* <p>A traditional Simpson integrator is based on a quadratic
* approximation of the function on three equally spaced points. This
* integrator does the same thing but can handle non-equally spaced
* points. If it is used on a regular sample, it behaves exactly as a
* traditional Simpson integrator.</p>
* @see EnhancedSimpsonIntegrator
* @version $Id$
* @author L. Maisonobe
*/
public class EnhancedSimpsonIntegratorSampler
implements SampledFunctionIterator {
/** Underlying sampled function iterator. */
private SampledFunctionIterator iter;
/** Next point. */
private ScalarValuedPair next;
/** Current running sum. */
private double sum;
/** Constructor.
* Build an integrator from an underlying sample iterator.
* @param iter iterator over the base function
*/
public EnhancedSimpsonIntegratorSampler(SampledFunctionIterator iter)
throws ExhaustedSampleException, FunctionException {
this.iter = iter;
// get the first point
next = iter.nextSamplePoint();
// initialize the sum
sum = 0.0;
}
public boolean hasNext() {
return iter.hasNext();
}
public ScalarValuedPair nextSamplePoint()
throws ExhaustedSampleException, FunctionException {
// performs one step of an enhanced Simpson scheme
ScalarValuedPair previous = next;
ScalarValuedPair current = iter.nextSamplePoint();
try {
next = iter.nextSamplePoint();
double h1 = current.getX() - previous.getX();
double h2 = next.getX() - current.getX();
double cP = (h1 + h2) * (2 * h1 - h2) / (6 * h1);
double cC = (h1 + h2) * (h1 + h2) * (h1 + h2) / (6 * h1 * h2);
double cN = (h1 + h2) * (2 * h2 - h1) / (6 * h2);
sum += cP * previous.getY() + cC * current.getY() + cN * next.getY();
} catch(ExhaustedSampleException e) {
// we have an incomplete step at the end of the sample
// we use a trapezoid scheme for this last step
sum += 0.5 * (current.getX() - previous.getX()) * (previous.getY() + current.getY());
return new ScalarValuedPair(current.getX(), sum);
}
return new ScalarValuedPair(next.getX(), sum);
}
}