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A Java's Collaborative Filtering library to carry out experiments in research of Collaborative Filtering based Recommender Systems. The library has been designed from researchers to researchers.
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/*
* 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.solvers;
import org.apache.commons.math3.util.FastMath;
import org.apache.commons.math3.exception.NoBracketingException;
import org.apache.commons.math3.exception.TooManyEvaluationsException;
/**
* Implements the Secant method for root-finding (approximating a
* zero of a univariate real function). The solution that is maintained is
* not bracketed, and as such convergence is not guaranteed.
*
* Implementation 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.
*
* Note that since release 3.0 this class implements the actual
* Secant algorithm, and not a modified one. As such, the 3.0 version
* is not backwards compatible with previous versions. To use an algorithm
* similar to the pre-3.0 releases, use the
* {@link IllinoisSolver Illinois} algorithm or the
* {@link PegasusSolver Pegasus} algorithm.
*
*/
public class SecantSolver extends AbstractUnivariateSolver {
/** Default absolute accuracy. */
protected static final double DEFAULT_ABSOLUTE_ACCURACY = 1e-6;
/** Construct a solver with default accuracy (1e-6). */
public SecantSolver() {
super(DEFAULT_ABSOLUTE_ACCURACY);
}
/**
* Construct a solver.
*
* @param absoluteAccuracy absolute accuracy
*/
public SecantSolver(final double absoluteAccuracy) {
super(absoluteAccuracy);
}
/**
* Construct a solver.
*
* @param relativeAccuracy relative accuracy
* @param absoluteAccuracy absolute accuracy
*/
public SecantSolver(final double relativeAccuracy,
final double absoluteAccuracy) {
super(relativeAccuracy, absoluteAccuracy);
}
/** {@inheritDoc} */
@Override
protected final double doSolve()
throws TooManyEvaluationsException,
NoBracketingException {
// 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 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.
x0 = x1;
f0 = f1;
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) {
return x1;
}
// 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)) {
return x1;
}
}
}
}
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