All Downloads are FREE. Search and download functionalities are using the official Maven repository.

pairsD4j.Math_73.BrentSolver.Math_73_BrentSolver_s Maven / Gradle / Ivy

The newest version!
/*
 * 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.math.analysis.solvers;


import org.apache.commons.math.FunctionEvaluationException;
import org.apache.commons.math.MathRuntimeException;
import org.apache.commons.math.MaxIterationsExceededException;
import org.apache.commons.math.analysis.UnivariateRealFunction;

/**
 * Implements the 
 * Brent algorithm for  finding zeros of real univariate functions.
 * 

* The function should be continuous but not necessarily smooth.

* * @version $Revision:670469 $ $Date:2008-06-23 10:01:38 +0200 (lun., 23 juin 2008) $ */ public class BrentSolver extends UnivariateRealSolverImpl { /** Error message for non-bracketing interval. */ private static final String NON_BRACKETING_MESSAGE = "function values at endpoints do not have different signs. " + "Endpoints: [{0}, {1}], Values: [{2}, {3}]"; /** Serializable version identifier */ private static final long serialVersionUID = 7694577816772532779L; /** * Construct a solver for the given function. * * @param f function to solve. * @deprecated as of 2.0 the function to solve is passed as an argument * to the {@link #solve(UnivariateRealFunction, double, double)} or * {@link UnivariateRealSolverImpl#solve(UnivariateRealFunction, double, double, double)} * method. */ @Deprecated public BrentSolver(UnivariateRealFunction f) { super(f, 100, 1E-6); } /** * Construct a solver. */ public BrentSolver() { super(100, 1E-6); } /** {@inheritDoc} */ @Deprecated public double solve(double min, double max) throws MaxIterationsExceededException, FunctionEvaluationException { return solve(f, min, max); } /** {@inheritDoc} */ @Deprecated public double solve(double min, double max, double initial) throws MaxIterationsExceededException, FunctionEvaluationException { return solve(f, min, max, initial); } /** * Find a zero in the given interval with an initial guess. *

Throws IllegalArgumentException if the values of the * function at the three points have the same sign (note that it is * allowed to have endpoints with the same sign if the initial point has * opposite sign function-wise).

* * @param f function to solve. * @param min the lower bound for the interval. * @param max the upper bound for the interval. * @param initial the start value to use (must be set to min if no * initial point is known). * @return the value where the function is zero * @throws MaxIterationsExceededException the maximum iteration count * is exceeded * @throws FunctionEvaluationException if an error occurs evaluating * the function * @throws IllegalArgumentException if initial is not between min and max * (even if it is a root) */ public double solve(final UnivariateRealFunction f, final double min, final double max, final double initial) throws MaxIterationsExceededException, FunctionEvaluationException { clearResult(); verifySequence(min, initial, max); // return the initial guess if it is good enough double yInitial = f.value(initial); if (Math.abs(yInitial) <= functionValueAccuracy) { setResult(initial, 0); return result; } // return the first endpoint if it is good enough double yMin = f.value(min); if (Math.abs(yMin) <= functionValueAccuracy) { setResult(yMin, 0); return result; } // reduce interval if min and initial bracket the root if (yInitial * yMin < 0) { return solve(f, min, yMin, initial, yInitial, min, yMin); } // return the second endpoint if it is good enough double yMax = f.value(max); if (Math.abs(yMax) <= functionValueAccuracy) { setResult(yMax, 0); return result; } // reduce interval if initial and max bracket the root if (yInitial * yMax < 0) { return solve(f, initial, yInitial, max, yMax, initial, yInitial); } // full Brent algorithm starting with provided initial guess return solve(f, min, yMin, max, yMax, initial, yInitial); } /** * Find a zero in the given interval. *

* Requires that the values of the function at the endpoints have opposite * signs. An IllegalArgumentException is thrown if this is not * the case.

* * @param f the function to solve * @param min the lower bound for the interval. * @param max the upper bound for the interval. * @return the value where the function is zero * @throws MaxIterationsExceededException if the maximum iteration count is exceeded * @throws FunctionEvaluationException if an error occurs evaluating the * function * @throws IllegalArgumentException if min is not less than max or the * signs of the values of the function at the endpoints are not opposites */ public double solve(final UnivariateRealFunction f, final double min, final double max) throws MaxIterationsExceededException, FunctionEvaluationException { clearResult(); verifyInterval(min, max); double ret = Double.NaN; double yMin = f.value(min); double yMax = f.value(max); // Verify bracketing double sign = yMin * yMax; if (sign > 0) { // check if either value is close to a zero if (Math.abs(yMin) <= functionValueAccuracy) { setResult(min, 0); ret = min; } else if (Math.abs(yMax) <= functionValueAccuracy) { setResult(max, 0); ret = max; } else { // neither value is close to zero and min and max do not bracket root. throw MathRuntimeException.createIllegalArgumentException( NON_BRACKETING_MESSAGE, min, max, yMin, yMax); } } else if (sign < 0){ // solve using only the first endpoint as initial guess ret = solve(f, min, yMin, max, yMax, min, yMin); } else { // either min or max is a root if (yMin == 0.0) { ret = min; } else { ret = max; } } return ret; } /** * Find a zero starting search according to the three provided points. * @param f the function to solve * @param x0 old approximation for the root * @param y0 function value at the approximation for the root * @param x1 last calculated approximation for the root * @param y1 function value at the last calculated approximation * for the root * @param x2 bracket point (must be set to x0 if no bracket point is * known, this will force starting with linear interpolation) * @param y2 function value at the bracket point. * @return the value where the function is zero * @throws MaxIterationsExceededException if the maximum iteration count * is exceeded * @throws FunctionEvaluationException if an error occurs evaluating * the function */ private double solve(final UnivariateRealFunction f, double x0, double y0, double x1, double y1, double x2, double y2) throws MaxIterationsExceededException, FunctionEvaluationException { double delta = x1 - x0; double oldDelta = delta; int i = 0; while (i < maximalIterationCount) { if (Math.abs(y2) < Math.abs(y1)) { // use the bracket point if is better than last approximation x0 = x1; x1 = x2; x2 = x0; y0 = y1; y1 = y2; y2 = y0; } if (Math.abs(y1) <= functionValueAccuracy) { // Avoid division by very small values. Assume // the iteration has converged (the problem may // still be ill conditioned) setResult(x1, i); return result; } double dx = x2 - x1; double tolerance = Math.max(relativeAccuracy * Math.abs(x1), absoluteAccuracy); if (Math.abs(dx) <= tolerance) { setResult(x1, i); return result; } if ((Math.abs(oldDelta) < tolerance) || (Math.abs(y0) <= Math.abs(y1))) { // Force bisection. delta = 0.5 * dx; oldDelta = delta; } else { double r3 = y1 / y0; double p; double p1; // the equality test (x0 == x2) is intentional, // it is part of the original Brent's method, // it should NOT be replaced by proximity test if (x0 == x2) { // Linear interpolation. p = dx * r3; p1 = 1.0 - r3; } else { // Inverse quadratic interpolation. double r1 = y0 / y2; double r2 = y1 / y2; p = r3 * (dx * r1 * (r1 - r2) - (x1 - x0) * (r2 - 1.0)); p1 = (r1 - 1.0) * (r2 - 1.0) * (r3 - 1.0); } if (p > 0.0) { p1 = -p1; } else { p = -p; } if (2.0 * p >= 1.5 * dx * p1 - Math.abs(tolerance * p1) || p >= Math.abs(0.5 * oldDelta * p1)) { // Inverse quadratic interpolation gives a value // in the wrong direction, or progress is slow. // Fall back to bisection. delta = 0.5 * dx; oldDelta = delta; } else { oldDelta = delta; delta = p / p1; } } // Save old X1, Y1 x0 = x1; y0 = y1; // Compute new X1, Y1 if (Math.abs(delta) > tolerance) { x1 = x1 + delta; } else if (dx > 0.0) { x1 = x1 + 0.5 * tolerance; } else if (dx <= 0.0) { x1 = x1 - 0.5 * tolerance; } y1 = f.value(x1); if ((y1 > 0) == (y2 > 0)) { x2 = x0; y2 = y0; delta = x1 - x0; oldDelta = delta; } i++; } throw new MaxIterationsExceededException(maximalIterationCount); } }




© 2015 - 2024 Weber Informatics LLC | Privacy Policy