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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;
import java.util.Arrays;
import java.util.Collection;
import java.util.HashMap;
import java.util.Map;
import org.apache.commons.math3.exception.DimensionMismatchException;
import org.apache.commons.math3.exception.MaxCountExceededException;
/** Wrapper class to compute Jacobian matrices by finite differences for ODE
* which do not compute them by themselves.
*
* @since 3.0
*/
class ParameterJacobianWrapper implements ParameterJacobianProvider {
/** Main ODE set. */
private final FirstOrderDifferentialEquations fode;
/** Raw ODE without Jacobian computation skill to be wrapped into a ParameterJacobianProvider. */
private final ParameterizedODE pode;
/** Steps for finite difference computation of the Jacobian df/dp w.r.t. parameters. */
private final Map hParam;
/** Wrap a {@link ParameterizedODE} into a {@link ParameterJacobianProvider}.
* @param fode main first order differential equations set
* @param pode secondary problem, without parameter Jacobian computation skill
* @param paramsAndSteps parameters and steps to compute the Jacobians df/dp
* @see JacobianMatrices#setParameterStep(String, double)
*/
ParameterJacobianWrapper(final FirstOrderDifferentialEquations fode,
final ParameterizedODE pode,
final ParameterConfiguration[] paramsAndSteps) {
this.fode = fode;
this.pode = pode;
this.hParam = new HashMap();
// set up parameters for jacobian computation
for (final ParameterConfiguration param : paramsAndSteps) {
final String name = param.getParameterName();
if (pode.isSupported(name)) {
hParam.put(name, param.getHP());
}
}
}
/** {@inheritDoc} */
public Collection getParametersNames() {
return pode.getParametersNames();
}
/** {@inheritDoc} */
public boolean isSupported(String name) {
return pode.isSupported(name);
}
/** {@inheritDoc} */
public void computeParameterJacobian(double t, double[] y, double[] yDot,
String paramName, double[] dFdP)
throws DimensionMismatchException, MaxCountExceededException {
final int n = fode.getDimension();
if (pode.isSupported(paramName)) {
final double[] tmpDot = new double[n];
// compute the jacobian df/dp w.r.t. parameter
final double p = pode.getParameter(paramName);
final double hP = hParam.get(paramName);
pode.setParameter(paramName, p + hP);
fode.computeDerivatives(t, y, tmpDot);
for (int i = 0; i < n; ++i) {
dFdP[i] = (tmpDot[i] - yDot[i]) / hP;
}
pode.setParameter(paramName, p);
} else {
Arrays.fill(dFdP, 0, n, 0.0);
}
}
}
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