

Java example source code file (MullerSolverTest.java)
The MullerSolverTest.java Java example source code/* * 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/LICENSE2.0 * * 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.analysis.QuinticFunction; import org.apache.commons.math3.analysis.UnivariateFunction; import org.apache.commons.math3.analysis.function.Expm1; import org.apache.commons.math3.analysis.function.Sin; import org.apache.commons.math3.exception.NoBracketingException; import org.apache.commons.math3.exception.NumberIsTooLargeException; import org.apache.commons.math3.util.FastMath; import org.junit.Assert; import org.junit.Test; /** * Test case for {@link MullerSolver Muller} solver. * <p> * Muller's method converges almost quadratically near roots, but it can * be very slow in regions far away from zeros. Test runs show that for * reasonably good initial values, for a default absolute accuracy of 1E6, * it generally takes 5 to 10 iterations for the solver to converge. * <p> * Tests for the exponential function illustrate the situations where * Muller solver performs poorly. * */ public final class MullerSolverTest { /** * Test of solver for the sine function. */ @Test public void testSinFunction() { UnivariateFunction f = new Sin(); UnivariateSolver solver = new MullerSolver(); double min, max, expected, result, tolerance; min = 3.0; max = 4.0; expected = FastMath.PI; tolerance = FastMath.max(solver.getAbsoluteAccuracy(), FastMath.abs(expected * solver.getRelativeAccuracy())); result = solver.solve(100, f, min, max); Assert.assertEquals(expected, result, tolerance); min = 1.0; max = 1.5; expected = 0.0; tolerance = FastMath.max(solver.getAbsoluteAccuracy(), FastMath.abs(expected * solver.getRelativeAccuracy())); result = solver.solve(100, f, min, max); Assert.assertEquals(expected, result, tolerance); } /** * Test of solver for the quintic function. */ @Test public void testQuinticFunction() { UnivariateFunction f = new QuinticFunction(); UnivariateSolver solver = new MullerSolver(); double min, max, expected, result, tolerance; min = 0.4; max = 0.2; expected = 0.0; tolerance = FastMath.max(solver.getAbsoluteAccuracy(), FastMath.abs(expected * solver.getRelativeAccuracy())); result = solver.solve(100, f, min, max); Assert.assertEquals(expected, result, tolerance); min = 0.75; max = 1.5; expected = 1.0; tolerance = FastMath.max(solver.getAbsoluteAccuracy(), FastMath.abs(expected * solver.getRelativeAccuracy())); result = solver.solve(100, f, min, max); Assert.assertEquals(expected, result, tolerance); min = 0.9; max = 0.2; expected = 0.5; tolerance = FastMath.max(solver.getAbsoluteAccuracy(), FastMath.abs(expected * solver.getRelativeAccuracy())); result = solver.solve(100, f, min, max); Assert.assertEquals(expected, result, tolerance); } /** * Test of solver for the exponential function. * <p> * It takes 10 to 15 iterations for the last two tests to converge. * In fact, if not for the bisection alternative, the solver would * exceed the default maximal iteration of 100. */ @Test public void testExpm1Function() { UnivariateFunction f = new Expm1(); UnivariateSolver solver = new MullerSolver(); double min, max, expected, result, tolerance; min = 1.0; max = 2.0; expected = 0.0; tolerance = FastMath.max(solver.getAbsoluteAccuracy(), FastMath.abs(expected * solver.getRelativeAccuracy())); result = solver.solve(100, f, min, max); Assert.assertEquals(expected, result, tolerance); min = 20.0; max = 10.0; expected = 0.0; tolerance = FastMath.max(solver.getAbsoluteAccuracy(), FastMath.abs(expected * solver.getRelativeAccuracy())); result = solver.solve(100, f, min, max); Assert.assertEquals(expected, result, tolerance); min = 50.0; max = 100.0; expected = 0.0; tolerance = FastMath.max(solver.getAbsoluteAccuracy(), FastMath.abs(expected * solver.getRelativeAccuracy())); result = solver.solve(100, f, min, max); Assert.assertEquals(expected, result, tolerance); } /** * Test of parameters for the solver. */ @Test public void testParameters() { UnivariateFunction f = new Sin(); UnivariateSolver solver = new MullerSolver(); try { // bad interval double root = solver.solve(100, f, 1, 1); System.out.println("root=" + root); Assert.fail("Expecting NumberIsTooLargeException  bad interval"); } catch (NumberIsTooLargeException ex) { // expected } try { // no bracketing solver.solve(100, f, 2, 3); Assert.fail("Expecting NoBracketingException  no bracketing"); } catch (NoBracketingException ex) { // expected } } } Other Java examples (source code examples)Here is a short list of links related to this Java MullerSolverTest.java source code file: 
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