//
//  OpenForecast - open source, general-purpose forecasting package.
//  Copyright (C) 2004-2011  Steven R. Gould
//
//  This library is free software; you can redistribute it and/or
//  modify it under the terms of the GNU Lesser General Public
//  License as published by the Free Software Foundation; either
//  version 2.1 of the License, or (at your option) any later version.
//
//  This library is distributed in the hope that it will be useful,
//  but WITHOUT ANY WARRANTY; without even the implied warranty of
//  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
//  Lesser General Public License for more details.
//
//  You should have received a copy of the GNU Lesser General Public
//  License along with this library; if not, write to the Free Software
//  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
//

package net.sourceforge.openforecast.tests;


import net.sourceforge.openforecast.ForecastingModel;
import net.sourceforge.openforecast.DataPoint;
import net.sourceforge.openforecast.DataSet;
import net.sourceforge.openforecast.Observation;
import net.sourceforge.openforecast.models.DoubleExponentialSmoothingModel;


/**
 * Tests the implementation of the Double Exponential Smoothing forecasting
 * model.
 * @author Steven R. Gould
 * @since 0.4
 */
public class DoubleExponentialSmoothingTest extends OpenForecastTestCase
{
    /**
     * The amount of error in the forecast values where the forecast is
     * considered "correct" by the test.
     */
    private static double TOLERANCE = 0.005;
    
    /**
     * The amount of error/tolerance in the Mean Squared Error where the
     * forecast is still considered "correct" by the test.
     */
    private static double MSE_TOLERANCE = 0.1;
    
    /**
     * Constructor required by the JUnit framework.
     */
    public DoubleExponentialSmoothingTest( String name )
    {
        super(name);
    }
    
    /**
     * A simple exponential smoothing test where the observed data is
     * constant. This should result in the same constant forecast for
     * any value of the smoothing constant.
     */
    public void testConstantDoubleExponentialSmoothing()
    {
        final int NUMBER_OF_OBSERVATIONS = 25;
        
        // Set up some constant observed values
        DataSet observedData = new DataSet();
        DataPoint dp;
        
        for ( int t=0; t