src/main/java/org/apache/commons/math/ode/nonstiff/AdamsIntegrator.java

/*
 * 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);
    }

}