org.apache.commons.math3.optim.linear.LinearOptimizer Maven / Gradle / Ivy

Go to download
Show more of this group Show more artifacts with this name
Show all versions of cf4j-recsys Show documentation
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.
The newest version!
/*
 * 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.optim.linear;

import java.util.Collection;
import java.util.Collections;
import org.apache.commons.math3.exception.TooManyIterationsException;
import org.apache.commons.math3.optim.OptimizationData;
import org.apache.commons.math3.optim.PointValuePair;
import org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer;

/**
 * Base class for implementing linear optimizers.
 *
 * @since 3.1
 */
public abstract class LinearOptimizer
    extends MultivariateOptimizer {
    /**
     * Linear objective function.
     */
    private LinearObjectiveFunction function;
    /**
     * Linear constraints.
     */
    private Collection linearConstraints;
    /**
     * Whether to restrict the variables to non-negative values.
     */
    private boolean nonNegative;

    /**
     * Simple constructor with default settings.
     *
     */
    protected LinearOptimizer() {
        super(null); // No convergence checker.
    }

    /**
     * @return {@code true} if the variables are restricted to non-negative values.
     */
    protected boolean isRestrictedToNonNegative() {
        return nonNegative;
    }

    /**
     * @return the optimization type.
     */
    protected LinearObjectiveFunction getFunction() {
        return function;
    }

    /**
     * @return the optimization type.
     */
    protected Collection getConstraints() {
        return Collections.unmodifiableCollection(linearConstraints);
    }

    /**
     * {@inheritDoc}
     *
     * @param optData Optimization data. In addition to those documented in
     * {@link MultivariateOptimizer#parseOptimizationData(OptimizationData[])
     * MultivariateOptimizer}, this method will register the following data:
     * 
     *  {@link LinearObjectiveFunction}
     *  {@link LinearConstraintSet}
     *  {@link NonNegativeConstraint}
     * 
     * @return {@inheritDoc}
     * @throws TooManyIterationsException if the maximal number of
     * iterations is exceeded.
     */
    @Override
    public PointValuePair optimize(OptimizationData... optData)
        throws TooManyIterationsException {
        // Set up base class and perform computation.
        return super.optimize(optData);
    }

    /**
     * Scans the list of (required and optional) optimization data that
     * characterize the problem.
     *
     * @param optData Optimization data.
     * The following data will be looked for:
     * 
     *  {@link LinearObjectiveFunction}
     *  {@link LinearConstraintSet}
     *  {@link NonNegativeConstraint}
     * 
     */
    @Override
    protected void parseOptimizationData(OptimizationData... optData) {
        // Allow base class to register its own data.
        super.parseOptimizationData(optData);

        // The existing values (as set by the previous call) are reused if
        // not provided in the argument list.
        for (OptimizationData data : optData) {
            if (data instanceof LinearObjectiveFunction) {
                function = (LinearObjectiveFunction) data;
                continue;
            }
            if (data instanceof LinearConstraintSet) {
                linearConstraints = ((LinearConstraintSet) data).getConstraints();
                continue;
            }
            if  (data instanceof NonNegativeConstraint) {
                nonNegative = ((NonNegativeConstraint) data).isRestrictedToNonNegative();
                continue;
            }
        }
    }
}