emlab.util.GeometricTrendRegressionTest.java Source code

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Here is the source code for emlab.util.GeometricTrendRegressionTest.java

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/*******************************************************************************
 * Copyright 2012 the original author or authors.
 * 
 * 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 emlab.util;

import static org.junit.Assert.*;

import org.apache.commons.math.stat.regression.SimpleRegression;
import org.apache.log4j.Logger;
import org.junit.Before;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.neo4j.template.Neo4jOperations;
import org.springframework.test.context.ContextConfiguration;
import org.springframework.test.context.junit4.SpringJUnit4ClassRunner;
import org.springframework.transaction.annotation.Transactional;

import emlab.domain.market.ClearingPoint;
import emlab.domain.market.CommodityMarket;
import emlab.domain.technology.Substance;
import emlab.repository.ClearingPointRepository;
import emlab.util.GeometricTrendRegression;

@RunWith(SpringJUnit4ClassRunner.class)
@ContextConfiguration({ "/emlab-test-context.xml" })
@Transactional
public class GeometricTrendRegressionTest {

    Logger logger = Logger.getLogger(GeometricTrendRegressionTest.class);

    @Autowired
    Neo4jOperations template;

    @Autowired
    ClearingPointRepository clearingPointRepository;

    @Before
    @Transactional
    public void setUp() throws Exception {

    }

    @Test
    public void testLinearTrendEstimation() {
        double[][] input = { { 0, 1 }, { 1, 1.1 }, { 2, 1.2 }, { 3, 1.3 }, { 4, 1.4 } };
        double[] predictionYears = { 5, 6, 7, 8 };
        double[] expectedResults = { 1.5, 1.6, 1.7, 1.8 };
        SimpleRegression sr = new SimpleRegression();
        sr.addData(input);
        for (int i = 0; i < predictionYears.length; i++) {
            assert (expectedResults[i] == sr.predict(predictionYears[i]));
        }
    }

    @Test
    public void testGeometricTrendEstimation() {
        double[][] input = { { 0, 1 }, { 1, 1.1 }, { 2, 1.21 }, { 3, 1.331 }, { 4, 1.4641 } };
        double[] predictionYears = { 5, 6, 7, 8 };
        double[] expectedResults = { 1.61051, 1.771561, 1.9487171, 2.14358881 };
        GeometricTrendRegression gtr = new GeometricTrendRegression();
        gtr.addData(input);
        for (int i = 0; i < predictionYears.length; i++) {
            assert (expectedResults[i] == gtr.predict(predictionYears[i]));
        }
    }

    @Test
    public void testGeometricTrendEstimationFromQuery() {
        double[][] input = { { 0, 1 }, { 1, 1.1 }, { 2, 1.21 }, { 3, 1.331 }, { 4, 1.4641 } };
        Substance substance = new Substance();
        substance.persist();
        CommodityMarket market = new CommodityMarket();
        market.setSubstance(substance);
        market.persist();
        for (double[] d : input) {
            ClearingPoint cp = new ClearingPoint();
            cp.setTime((long) d[0]);
            cp.setPrice(d[1]);
            cp.setAbstractMarket(market);
            template.save(cp);
        }
        Iterable<ClearingPoint> cps = clearingPointRepository
                .findAllClearingPointsForSubstanceAndTimeRange(substance, 0, 4);
        GeometricTrendRegression gtr = new GeometricTrendRegression();
        for (ClearingPoint clearingPoint : cps) {
            gtr.addData(clearingPoint.getTime(), clearingPoint.getPrice());
        }
        double[] predictionYears = { 5, 6, 7, 8 };
        double[] expectedResults = { 1.61051, 1.771561, 1.9487171, 2.14358881 };
        for (int i = 0; i < predictionYears.length; i++) {
            assert (expectedResults[i] == gtr.predict(predictionYears[i]));
        }
    }

}