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Statistical sampling library for use in virtdata libraries, based
on apache commons math 4
/*
* 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.math4.analysis.solvers;
import org.apache.commons.math4.analysis.UnivariateFunction;
import org.apache.commons.math4.exception.ConvergenceException;
import org.apache.commons.math4.exception.MathInternalError;
import org.apache.commons.math4.util.FastMath;
/**
* Base class for all bracketing Secant-based methods for root-finding
* (approximating a zero of a univariate real function).
*
* Implementation of the {@link RegulaFalsiSolver Regula Falsi} and
* {@link IllinoisSolver Illinois} methods is based on the
* following article: M. Dowell and P. Jarratt,
* A modified regula falsi method for computing the root of an
* equation, BIT Numerical Mathematics, volume 11, number 2,
* pages 168-174, Springer, 1971.
*
* Implementation of the {@link PegasusSolver Pegasus} method is
* based on the following article: M. Dowell and P. Jarratt,
* The "Pegasus" method for computing the root of an equation,
* BIT Numerical Mathematics, volume 12, number 4, pages 503-508, Springer,
* 1972.
*
* The {@link SecantSolver Secant} method is not a
* bracketing method, so it is not implemented here. It has a separate
* implementation.
*
* @since 3.0
*/
public abstract class BaseSecantSolver
extends AbstractUnivariateSolver
implements BracketedUnivariateSolver {
/** Default absolute accuracy. */
protected static final double DEFAULT_ABSOLUTE_ACCURACY = 1e-6;
/** The kinds of solutions that the algorithm may accept. */
private AllowedSolution allowed;
/** The Secant-based root-finding method to use. */
private final Method method;
/**
* Construct a solver.
*
* @param absoluteAccuracy Absolute accuracy.
* @param method Secant-based root-finding method to use.
*/
protected BaseSecantSolver(final double absoluteAccuracy, final Method method) {
super(absoluteAccuracy);
this.allowed = AllowedSolution.ANY_SIDE;
this.method = method;
}
/**
* Construct a solver.
*
* @param relativeAccuracy Relative accuracy.
* @param absoluteAccuracy Absolute accuracy.
* @param method Secant-based root-finding method to use.
*/
protected BaseSecantSolver(final double relativeAccuracy,
final double absoluteAccuracy,
final Method method) {
super(relativeAccuracy, absoluteAccuracy);
this.allowed = AllowedSolution.ANY_SIDE;
this.method = method;
}
/**
* Construct a solver.
*
* @param relativeAccuracy Maximum relative error.
* @param absoluteAccuracy Maximum absolute error.
* @param functionValueAccuracy Maximum function value error.
* @param method Secant-based root-finding method to use
*/
protected BaseSecantSolver(final double relativeAccuracy,
final double absoluteAccuracy,
final double functionValueAccuracy,
final Method method) {
super(relativeAccuracy, absoluteAccuracy, functionValueAccuracy);
this.allowed = AllowedSolution.ANY_SIDE;
this.method = method;
}
/** {@inheritDoc} */
@Override
public double solve(final int maxEval, final UnivariateFunction f,
final double min, final double max,
final AllowedSolution allowedSolution) {
return solve(maxEval, f, min, max, min + 0.5 * (max - min), allowedSolution);
}
/** {@inheritDoc} */
@Override
public double solve(final int maxEval, final UnivariateFunction f,
final double min, final double max, final double startValue,
final AllowedSolution allowedSolution) {
this.allowed = allowedSolution;
return super.solve(maxEval, f, min, max, startValue);
}
/** {@inheritDoc} */
@Override
public double solve(final int maxEval, final UnivariateFunction f,
final double min, final double max, final double startValue) {
return solve(maxEval, f, min, max, startValue, AllowedSolution.ANY_SIDE);
}
/**
* {@inheritDoc}
*
* @throws ConvergenceException if the algorithm failed due to finite
* precision.
*/
@Override
protected final double doSolve()
throws ConvergenceException {
// Get initial solution
double x0 = getMin();
double x1 = getMax();
double f0 = computeObjectiveValue(x0);
double f1 = computeObjectiveValue(x1);
// If one of the bounds is the exact root, return it. Since these are
// not under-approximations or over-approximations, we can return them
// regardless of the allowed solutions.
if (f0 == 0.0) {
return x0;
}
if (f1 == 0.0) {
return x1;
}
// Verify bracketing of initial solution.
verifyBracketing(x0, x1);
// Get accuracies.
final double ftol = getFunctionValueAccuracy();
final double atol = getAbsoluteAccuracy();
final double rtol = getRelativeAccuracy();
// Keep track of inverted intervals, meaning that the left bound is
// larger than the right bound.
boolean inverted = false;
// Keep finding better approximations.
while (true) {
// Calculate the next approximation.
final double x = x1 - ((f1 * (x1 - x0)) / (f1 - f0));
final double fx = computeObjectiveValue(x);
// If the new approximation is the exact root, return it. Since
// this is not an under-approximation or an over-approximation,
// we can return it regardless of the allowed solutions.
if (fx == 0.0) {
return x;
}
// Update the bounds with the new approximation.
if (f1 * fx < 0) {
// The value of x1 has switched to the other bound, thus inverting
// the interval.
x0 = x1;
f0 = f1;
inverted = !inverted;
} else {
switch (method) {
case ILLINOIS:
f0 *= 0.5;
break;
case PEGASUS:
f0 *= f1 / (f1 + fx);
break;
case REGULA_FALSI:
// Detect early that algorithm is stuck, instead of waiting
// for the maximum number of iterations to be exceeded.
if (x == x1) {
throw new ConvergenceException();
}
break;
default:
// Should never happen.
throw new MathInternalError();
}
}
// Update from [x0, x1] to [x0, x].
x1 = x;
f1 = fx;
// If the function value of the last approximation is too small,
// given the function value accuracy, then we can't get closer to
// the root than we already are.
if (FastMath.abs(f1) <= ftol) {
switch (allowed) {
case ANY_SIDE:
return x1;
case LEFT_SIDE:
if (inverted) {
return x1;
}
break;
case RIGHT_SIDE:
if (!inverted) {
return x1;
}
break;
case BELOW_SIDE:
if (f1 <= 0) {
return x1;
}
break;
case ABOVE_SIDE:
if (f1 >= 0) {
return x1;
}
break;
default:
throw new MathInternalError();
}
}
// If the current interval is within the given accuracies, we
// are satisfied with the current approximation.
if (FastMath.abs(x1 - x0) < FastMath.max(rtol * FastMath.abs(x1),
atol)) {
switch (allowed) {
case ANY_SIDE:
return x1;
case LEFT_SIDE:
return inverted ? x1 : x0;
case RIGHT_SIDE:
return inverted ? x0 : x1;
case BELOW_SIDE:
return (f1 <= 0) ? x1 : x0;
case ABOVE_SIDE:
return (f1 >= 0) ? x1 : x0;
default:
throw new MathInternalError();
}
}
}
}
/** Secant-based root-finding methods. */
protected enum Method {
/**
* The {@link RegulaFalsiSolver Regula Falsi} or
* False Position method.
*/
REGULA_FALSI,
/** The {@link IllinoisSolver Illinois} method. */
ILLINOIS,
/** The {@link PegasusSolver Pegasus} method. */
PEGASUS;
}
}