edu.umd.cs.psl.reasoner.admm.SquaredLinearLossTermTest.java Source code

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Here is the source code for edu.umd.cs.psl.reasoner.admm.SquaredLinearLossTermTest.java

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/*
 * This file is part of the PSL software.
 * Copyright 2011-2015 University of Maryland
 * Copyright 2013-2015 The Regents of the University of California
 *
 * Licensed 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 edu.umd.cs.psl.reasoner.admm;

import static org.junit.Assert.assertEquals;

import java.util.Vector;

import org.apache.commons.configuration.ConfigurationException;
import org.junit.Before;
import org.junit.Test;

import edu.umd.cs.psl.config.ConfigBundle;
import edu.umd.cs.psl.config.ConfigManager;

public class SquaredLinearLossTermTest {

    private ConfigBundle config;

    @Before
    public final void setUp() throws ConfigurationException {
        ConfigManager manager = ConfigManager.getManager();
        config = manager.getBundle("dummy");
    }

    @Test
    public void testMinimize() {
        /*
         * Problem 1
         */
        double[] z = { 0.4, 0.5, 0.1 };
        double[] y = { 0.0, 0.0, -0.05 };
        double[] coeffs = { 0.3, -1.0, 0.4 };
        double constant = -20.0;
        double weight = 0.5;
        double stepSize = 2.0;
        double[] expected = { -1.41569, 6.55231, -2.29593 };
        testProblem(z, y, coeffs, constant, weight, stepSize, expected);
    }

    private void testProblem(double[] z, double[] y, double[] coeffs, double constant, double weight,
            final double stepSize, double[] expected) {
        config.setProperty("admmreasoner.stepsize", stepSize);
        ADMMReasoner reasoner = new ADMMReasoner(config);
        reasoner.z = new Vector<Double>(z.length);
        for (int i = 0; i < z.length; i++)
            reasoner.z.add(z[i]);

        int[] zIndices = new int[z.length];
        for (int i = 0; i < z.length; i++)
            zIndices[i] = i;
        SquaredLinearLossTerm term = new SquaredLinearLossTerm(reasoner, zIndices, coeffs, constant, weight);
        for (int i = 0; i < z.length; i++)
            term.y[i] = y[i];
        term.minimize();

        for (int i = 0; i < z.length; i++)
            assertEquals(expected[i], term.x[i], 5e-5);
    }

}