org.apache.commons.math3.ode.nonstiff.DormandPrince54Integrator.java Source code

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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.ode.nonstiff;

import org.apache.commons.math3.util.FastMath;

/**
 * This class implements the 5(4) Dormand-Prince integrator for Ordinary
 * Differential Equations.
    
 * <p>This integrator is an embedded Runge-Kutta integrator
 * of order 5(4) used in local extrapolation mode (i.e. the solution
 * is computed using the high order formula) with stepsize control
 * (and automatic step initialization) and continuous output. This
 * method uses 7 functions evaluations per step. However, since this
 * is an <i>fsal</i>, the last evaluation of one step is the same as
 * the first evaluation of the next step and hence can be avoided. So
 * the cost is really 6 functions evaluations per step.</p>
 *
 * <p>This method has been published (whithout the continuous output
 * that was added by Shampine in 1986) in the following article :
 * <pre>
 *  A family of embedded Runge-Kutta formulae
 *  J. R. Dormand and P. J. Prince
 *  Journal of Computational and Applied Mathematics
 *  volume 6, no 1, 1980, pp. 19-26
 * </pre></p>
 *
 * @version $Id: DormandPrince54Integrator.java 1416643 2012-12-03 19:37:14Z tn $
 * @since 1.2
 */

public class DormandPrince54Integrator extends EmbeddedRungeKuttaIntegrator {

    /** Integrator method name. */
    private static final String METHOD_NAME = "Dormand-Prince 5(4)";

    /** Time steps Butcher array. */
    private static final double[] STATIC_C = { 1.0 / 5.0, 3.0 / 10.0, 4.0 / 5.0, 8.0 / 9.0, 1.0, 1.0 };

    /** Internal weights Butcher array. */
    private static final double[][] STATIC_A = { { 1.0 / 5.0 }, { 3.0 / 40.0, 9.0 / 40.0 },
            { 44.0 / 45.0, -56.0 / 15.0, 32.0 / 9.0 },
            { 19372.0 / 6561.0, -25360.0 / 2187.0, 64448.0 / 6561.0, -212.0 / 729.0 },
            { 9017.0 / 3168.0, -355.0 / 33.0, 46732.0 / 5247.0, 49.0 / 176.0, -5103.0 / 18656.0 },
            { 35.0 / 384.0, 0.0, 500.0 / 1113.0, 125.0 / 192.0, -2187.0 / 6784.0, 11.0 / 84.0 } };

    /** Propagation weights Butcher array. */
    private static final double[] STATIC_B = { 35.0 / 384.0, 0.0, 500.0 / 1113.0, 125.0 / 192.0, -2187.0 / 6784.0,
            11.0 / 84.0, 0.0 };

    /** Error array, element 1. */
    private static final double E1 = 71.0 / 57600.0;

    // element 2 is zero, so it is neither stored nor used

    /** Error array, element 3. */
    private static final double E3 = -71.0 / 16695.0;

    /** Error array, element 4. */
    private static final double E4 = 71.0 / 1920.0;

    /** Error array, element 5. */
    private static final double E5 = -17253.0 / 339200.0;

    /** Error array, element 6. */
    private static final double E6 = 22.0 / 525.0;

    /** Error array, element 7. */
    private static final double E7 = -1.0 / 40.0;

    /** Simple constructor.
     * Build a fifth order Dormand-Prince integrator with the given step bounds
     * @param minStep minimal step (sign is irrelevant, regardless of
     * integration direction, forward or backward), the last step can
     * be smaller than this
     * @param maxStep maximal step (sign is irrelevant, regardless of
     * integration direction, forward or backward), the last step can
     * be smaller than this
     * @param scalAbsoluteTolerance allowed absolute error
     * @param scalRelativeTolerance allowed relative error
     */
    public DormandPrince54Integrator(final double minStep, final double maxStep, final double scalAbsoluteTolerance,
            final double scalRelativeTolerance) {
        super(METHOD_NAME, true, STATIC_C, STATIC_A, STATIC_B, new DormandPrince54StepInterpolator(), minStep,
                maxStep, scalAbsoluteTolerance, scalRelativeTolerance);
    }

    /** Simple constructor.
     * Build a fifth order Dormand-Prince integrator with the given step bounds
     * @param minStep minimal step (sign is irrelevant, regardless of
     * integration direction, forward or backward), the last step can
     * be smaller than this
     * @param maxStep maximal step (sign is irrelevant, regardless of
     * integration direction, forward or backward), the last step can
     * be smaller than this
     * @param vecAbsoluteTolerance allowed absolute error
     * @param vecRelativeTolerance allowed relative error
     */
    public DormandPrince54Integrator(final double minStep, final double maxStep,
            final double[] vecAbsoluteTolerance, final double[] vecRelativeTolerance) {
        super(METHOD_NAME, true, STATIC_C, STATIC_A, STATIC_B, new DormandPrince54StepInterpolator(), minStep,
                maxStep, vecAbsoluteTolerance, vecRelativeTolerance);
    }

    /** {@inheritDoc} */
    @Override
    public int getOrder() {
        return 5;
    }

    /** {@inheritDoc} */
    @Override
    protected double estimateError(final double[][] yDotK, final double[] y0, final double[] y1, final double h) {

        double error = 0;

        for (int j = 0; j < mainSetDimension; ++j) {
            final double errSum = E1 * yDotK[0][j] + E3 * yDotK[2][j] + E4 * yDotK[3][j] + E5 * yDotK[4][j]
                    + E6 * yDotK[5][j] + E7 * yDotK[6][j];

            final double yScale = FastMath.max(FastMath.abs(y0[j]), FastMath.abs(y1[j]));
            final double tol = (vecAbsoluteTolerance == null)
                    ? (scalAbsoluteTolerance + scalRelativeTolerance * yScale)
                    : (vecAbsoluteTolerance[j] + vecRelativeTolerance[j] * yScale);
            final double ratio = h * errSum / tol;
            error += ratio * ratio;

        }

        return FastMath.sqrt(error / mainSetDimension);

    }

}