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A Java's Collaborative Filtering library to carry out experiments in research of Collaborative Filtering based Recommender Systems. The library has been designed from researchers to researchers.

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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;


/** This class converts second order differential equations to first
 * order ones.
 *
 * 

This class is a wrapper around a {@link * SecondOrderDifferentialEquations} which allow to use a {@link * FirstOrderIntegrator} to integrate it.

* *

The transformation is done by changing the n dimension state * vector to a 2n dimension vector, where the first n components are * the initial state variables and the n last components are their * first time derivative. The first time derivative of this state * vector then really contains both the first and second time * derivative of the initial state vector, which can be handled by the * underlying second order equations set.

* *

One should be aware that the data is duplicated during the * transformation process and that for each call to {@link * #computeDerivatives computeDerivatives}, this wrapper does copy 4n * scalars : 2n before the call to {@link * SecondOrderDifferentialEquations#computeSecondDerivatives * computeSecondDerivatives} in order to dispatch the y state vector * into z and zDot, and 2n after the call to gather zDot and zDDot * into yDot. Since the underlying problem by itself perhaps also * needs to copy data and dispatch the arrays into domain objects, * this has an impact on both memory and CPU usage. The only way to * avoid this duplication is to perform the transformation at the * problem level, i.e. to implement the problem as a first order one * and then avoid using this class.

* * @see FirstOrderIntegrator * @see FirstOrderDifferentialEquations * @see SecondOrderDifferentialEquations * @since 1.2 */ public class FirstOrderConverter implements FirstOrderDifferentialEquations { /** Underlying second order equations set. */ private final SecondOrderDifferentialEquations equations; /** second order problem dimension. */ private final int dimension; /** state vector. */ private final double[] z; /** first time derivative of the state vector. */ private final double[] zDot; /** second time derivative of the state vector. */ private final double[] zDDot; /** Simple constructor. * Build a converter around a second order equations set. * @param equations second order equations set to convert */ public FirstOrderConverter (final SecondOrderDifferentialEquations equations) { this.equations = equations; dimension = equations.getDimension(); z = new double[dimension]; zDot = new double[dimension]; zDDot = new double[dimension]; } /** Get the dimension of the problem. *

The dimension of the first order problem is twice the * dimension of the underlying second order problem.

* @return dimension of the problem */ public int getDimension() { return 2 * dimension; } /** Get the current time derivative of the state vector. * @param t current value of the independent time variable * @param y array containing the current value of the state vector * @param yDot placeholder array where to put the time derivative of the state vector */ public void computeDerivatives(final double t, final double[] y, final double[] yDot) { // split the state vector in two System.arraycopy(y, 0, z, 0, dimension); System.arraycopy(y, dimension, zDot, 0, dimension); // apply the underlying equations set equations.computeSecondDerivatives(t, z, zDot, zDDot); // build the result state derivative System.arraycopy(zDot, 0, yDot, 0, dimension); System.arraycopy(zDDot, 0, yDot, dimension, dimension); } }




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