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Commons Math example source code file (RungeKuttaIntegrator.java)

This example Commons Math source code file (RungeKuttaIntegrator.java) is included in the DevDaily.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Java - Commons Math tags/keywords

abstractintegrator, abstractstepinterpolator, combinedeventsmanager, derivativeexception, firstorderdifferentialequations, firstorderdifferentialequations, integratorexception, rungekuttaintegrator, rungekuttaintegrator, rungekuttastepinterpolator, rungekuttastepinterpolator, stephandler, stephandler, string

The Commons Math RungeKuttaIntegrator.java 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/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.ode.AbstractIntegrator;
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.events.CombinedEventsManager;
import org.apache.commons.math.ode.sampling.AbstractStepInterpolator;
import org.apache.commons.math.ode.sampling.DummyStepInterpolator;
import org.apache.commons.math.ode.sampling.StepHandler;

/**
 * This class implements the common part of all fixed step Runge-Kutta
 * integrators for Ordinary Differential Equations.
 *
 * <p>These methods are explicit Runge-Kutta methods, their Butcher
 * arrays are as follows :
 * <pre>
 *    0  |
 *   c2  | a21
 *   c3  | a31  a32
 *   ... |        ...
 *   cs  | as1  as2  ...  ass-1
 *       |--------------------------
 *       |  b1   b2  ...   bs-1  bs
 * </pre>
 * </p>
 *
 * @see EulerIntegrator
 * @see ClassicalRungeKuttaIntegrator
 * @see GillIntegrator
 * @see MidpointIntegrator
 * @version $Revision: 927202 $ $Date: 2010-03-24 18:11:51 -0400 (Wed, 24 Mar 2010) $
 * @since 1.2
 */

public abstract class RungeKuttaIntegrator extends AbstractIntegrator {

    /** Time steps from Butcher array (without the first zero). */
    private final double[] c;

    /** Internal weights from Butcher array (without the first empty row). */
    private final double[][] a;

    /** External weights for the high order method from Butcher array. */
    private final double[] b;

    /** Prototype of the step interpolator. */
    private final RungeKuttaStepInterpolator prototype;

    /** Integration step. */
    private final double step;

  /** Simple constructor.
   * Build a Runge-Kutta integrator with the given
   * step. The default step handler does nothing.
   * @param name name of the method
   * @param c time steps from Butcher array (without the first zero)
   * @param a internal weights from Butcher array (without the first empty row)
   * @param b propagation weights for the high order method from Butcher array
   * @param prototype prototype of the step interpolator to use
   * @param step integration step
   */
  protected RungeKuttaIntegrator(final String name,
                                 final double[] c, final double[][] a, final double[] b,
                                 final RungeKuttaStepInterpolator prototype,
                                 final double step) {
    super(name);
    this.c          = c;
    this.a          = a;
    this.b          = b;
    this.prototype  = prototype;
    this.step       = Math.abs(step);
  }

  /** {@inheritDoc} */
  public double integrate(final FirstOrderDifferentialEquations equations,
                          final double t0, final double[] y0,
                          final double t, final double[] y)
  throws DerivativeException, IntegratorException {

    sanityChecks(equations, t0, y0, t, y);
    setEquations(equations);
    resetEvaluations();
    final boolean forward = t > t0;

    // create some internal working arrays
    final int stages = c.length + 1;
    if (y != y0) {
      System.arraycopy(y0, 0, y, 0, y0.length);
    }
    final double[][] yDotK = new double[stages][];
    for (int i = 0; i < stages; ++i) {
      yDotK [i] = new double[y0.length];
    }
    final double[] yTmp = new double[y0.length];

    // set up an interpolator sharing the integrator arrays
    AbstractStepInterpolator interpolator;
    if (requiresDenseOutput() || (! eventsHandlersManager.isEmpty())) {
      final RungeKuttaStepInterpolator rki = (RungeKuttaStepInterpolator) prototype.copy();
      rki.reinitialize(this, yTmp, yDotK, forward);
      interpolator = rki;
    } else {
      interpolator = new DummyStepInterpolator(yTmp, yDotK[stages - 1], forward);
    }
    interpolator.storeTime(t0);

    // set up integration control objects
    stepStart = t0;
    stepSize  = forward ? step : -step;
    for (StepHandler handler : stepHandlers) {
        handler.reset();
    }
    CombinedEventsManager manager = addEndTimeChecker(t0, t, eventsHandlersManager);
    boolean lastStep = false;

    // main integration loop
    while (!lastStep) {

      interpolator.shift();

      for (boolean loop = true; loop;) {

        // first stage
        computeDerivatives(stepStart, y, yDotK[0]);

        // next stages
        for (int k = 1; k < stages; ++k) {

          for (int j = 0; j < y0.length; ++j) {
            double sum = a[k-1][0] * yDotK[0][j];
            for (int l = 1; l < k; ++l) {
              sum += a[k-1][l] * yDotK[l][j];
            }
            yTmp[j] = y[j] + stepSize * sum;
          }

          computeDerivatives(stepStart + c[k-1] * stepSize, yTmp, yDotK[k]);

        }

        // estimate the state at the end of the step
        for (int j = 0; j < y0.length; ++j) {
          double sum    = b[0] * yDotK[0][j];
          for (int l = 1; l < stages; ++l) {
            sum    += b[l] * yDotK[l][j];
          }
          yTmp[j] = y[j] + stepSize * sum;
        }

        // discrete events handling
        interpolator.storeTime(stepStart + stepSize);
        if (manager.evaluateStep(interpolator)) {
            final double dt = manager.getEventTime() - stepStart;
            if (Math.abs(dt) <= Math.ulp(stepStart)) {
                // we cannot simply truncate the step, reject the current computation
                // and let the loop compute another state with the truncated step.
                // it is so small (much probably exactly 0 due to limited accuracy)
                // that the code above would fail handling it.
                // So we set up an artificial 0 size step by copying states
                interpolator.storeTime(stepStart);
                System.arraycopy(y, 0, yTmp, 0, y0.length);
                stepSize = 0;
                loop     = false;
            } else {
                // reject the step to match exactly the next switch time
                stepSize = dt;
            }
        } else {
          loop = false;
        }

      }

      // the step has been accepted
      final double nextStep = stepStart + stepSize;
      System.arraycopy(yTmp, 0, y, 0, y0.length);
      manager.stepAccepted(nextStep, y);
      lastStep = manager.stop();

      // provide the step data to the step handler
      interpolator.storeTime(nextStep);
      for (StepHandler handler : stepHandlers) {
          handler.handleStep(interpolator, lastStep);
      }
      stepStart = nextStep;

      if (manager.reset(stepStart, y) && ! lastStep) {
        // some events handler has triggered changes that
        // invalidate the derivatives, we need to recompute them
        computeDerivatives(stepStart, y, yDotK[0]);
      }

      // make sure step size is set to default before next step
      stepSize = forward ? step : -step;

    }

    final double stopTime = stepStart;
    stepStart = Double.NaN;
    stepSize  = Double.NaN;
    return stopTime;

  }

}

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