Java tutorial
/* * 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.ode.nonstiff; /** * This class implements a simple Euler integrator for Ordinary * Differential Equations. * * <p>The Euler algorithm is the simplest one that can be used to * integrate ordinary differential equations. It is a simple inversion * of the forward difference expression : * <code>f'=(f(t+h)-f(t))/h</code> which leads to * <code>f(t+h)=f(t)+hf'</code>. The interpolation scheme used for * dense output is the linear scheme already used for integration.</p> * * <p>This algorithm looks cheap because it needs only one function * evaluation per step. However, as it uses linear estimates, it needs * very small steps to achieve high accuracy, and small steps lead to * numerical errors and instabilities.</p> * * <p>This algorithm is almost never used and has been included in * this package only as a comparison reference for more useful * integrators.</p> * * @see MidpointIntegrator * @see ClassicalRungeKuttaIntegrator * @see GillIntegrator * @see ThreeEighthesIntegrator * @version $Id: EulerIntegrator.java 1416643 2012-12-03 19:37:14Z tn $ * @since 1.2 */ public class EulerIntegrator extends RungeKuttaIntegrator { /** Time steps Butcher array. */ private static final double[] STATIC_C = {}; /** Internal weights Butcher array. */ private static final double[][] STATIC_A = {}; /** Propagation weights Butcher array. */ private static final double[] STATIC_B = { 1.0 }; /** Simple constructor. * Build an Euler integrator with the given step. * @param step integration step */ public EulerIntegrator(final double step) { super("Euler", STATIC_C, STATIC_A, STATIC_B, new EulerStepInterpolator(), step); } }