/* * 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.ode.nonstiff; import org.apache.commons.math.linear.Array2DRowRealMatrix; import org.apache.commons.math.ode.DerivativeException; import org.apache.commons.math.ode.FirstOrderDifferentialEquations; import org.apache.commons.math.ode.IntegratorException; import org.apache.commons.math.ode.MultistepIntegrator; /** Base class for {@link AdamsBashforthIntegrator Adams-Bashforth} and * {@link AdamsMoultonIntegrator Adams-Moulton} integrators. * @version $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 févr. 2011) $ * @since 2.0 */ public abstract class AdamsIntegrator extends MultistepIntegrator { /** Transformer. */ private final AdamsNordsieckTransformer transformer; /** * Build an Adams integrator with the given order and step control prameters. * @param name name of the method * @param nSteps number of steps of the method excluding the one being computed * @param order order of the method * @param minStep minimal step (must be positive even for backward * integration), the last step can be smaller than this * @param maxStep maximal step (must be positive even for backward * integration) * @param scalAbsoluteTolerance allowed absolute error * @param scalRelativeTolerance allowed relative error * @exception IllegalArgumentException if order is 1 or less */ public AdamsIntegrator(final String name, final int nSteps, final int order, final double minStep, final double maxStep, final double scalAbsoluteTolerance, final double scalRelativeTolerance) throws IllegalArgumentException { super(name, nSteps, order, minStep, maxStep, scalAbsoluteTolerance, scalRelativeTolerance); transformer = AdamsNordsieckTransformer.getInstance(nSteps); } /** * Build an Adams integrator with the given order and step control parameters. * @param name name of the method * @param nSteps number of steps of the method excluding the one being computed * @param order order of the method * @param minStep minimal step (must be positive even for backward * integration), the last step can be smaller than this * @param maxStep maximal step (must be positive even for backward * integration) * @param vecAbsoluteTolerance allowed absolute error * @param vecRelativeTolerance allowed relative error * @exception IllegalArgumentException if order is 1 or less */ public AdamsIntegrator(final String name, final int nSteps, final int order, final double minStep, final double maxStep, final double[] vecAbsoluteTolerance, final double[] vecRelativeTolerance) throws IllegalArgumentException { super(name, nSteps, order, minStep, maxStep, vecAbsoluteTolerance, vecRelativeTolerance); transformer = AdamsNordsieckTransformer.getInstance(nSteps); } /** {@inheritDoc} */ @Override public abstract double integrate(final FirstOrderDifferentialEquations equations, final double t0, final double[] y0, final double t, final double[] y) throws DerivativeException, IntegratorException; /** {@inheritDoc} */ @Override protected Array2DRowRealMatrix initializeHighOrderDerivatives(final double[] first, final double[][] multistep) { return transformer.initializeHighOrderDerivatives(first, multistep); } /** Update the high order scaled derivatives for Adams integrators (phase 1). * <p>The complete update of high order derivatives has a form similar to: * <pre> * r<sub>n+1</sub> = (s<sub>1</sub>(n) - s<sub>1</sub>(n+1)) P<sup>-1</sup> u + P<sup>-1</sup> A P r<sub>n</sub> * </pre> * this method computes the P<sup>-1</sup> A P r<sub>n</sub> part.</p> * @param highOrder high order scaled derivatives * (h<sup>2</sup>/2 y'', ... h<sup>k</sup>/k! y(k)) * @return updated high order derivatives * @see #updateHighOrderDerivativesPhase2(double[], double[], Array2DRowRealMatrix) */ public Array2DRowRealMatrix updateHighOrderDerivativesPhase1(final Array2DRowRealMatrix highOrder) { return transformer.updateHighOrderDerivativesPhase1(highOrder); } /** Update the high order scaled derivatives Adams integrators (phase 2). * <p>The complete update of high order derivatives has a form similar to: * <pre> * r<sub>n+1</sub> = (s<sub>1</sub>(n) - s<sub>1</sub>(n+1)) P<sup>-1</sup> u + P<sup>-1</sup> A P r<sub>n</sub> * </pre> * this method computes the (s<sub>1</sub>(n) - s<sub>1</sub>(n+1)) P<sup>-1</sup> u part.</p> * <p>Phase 1 of the update must already have been performed.</p> * @param start first order scaled derivatives at step start * @param end first order scaled derivatives at step end * @param highOrder high order scaled derivatives, will be modified * (h<sup>2</sup>/2 y'', ... h<sup>k</sup>/k! y(k)) * @see #updateHighOrderDerivativesPhase1(Array2DRowRealMatrix) */ public void updateHighOrderDerivativesPhase2(final double[] start, final double[] end, final Array2DRowRealMatrix highOrder) { transformer.updateHighOrderDerivativesPhase2(start, end, highOrder); } }