/**
    This file is part of JkernelMachines.

    JkernelMachines is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.

    JkernelMachines 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 General Public License for more details.

    You should have received a copy of the GNU General Public License
    along with JkernelMachines.  If not, see <http://www.gnu.org/licenses/>.

    Copyright David Picard - 2013

 */
package fr.lip6.jkernelmachines.test.density;

import static org.junit.Assert.assertTrue;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

import org.junit.Before;
import org.junit.Test;

import fr.lip6.jkernelmachines.density.SDCADensity;
import fr.lip6.jkernelmachines.density.SMODensity;
import fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2;
import fr.lip6.jkernelmachines.type.TrainingSample;
import fr.lip6.jkernelmachines.util.generators.GaussianGenerator;

/**
 * Test case for the SDCADensity class
 * @author picard
 * 
 */
public class SDCADensityTest {

	List<double[]> train;

	/**
	 * @throws java.lang.Exception
	 */
	@Before
	public void setUp() throws Exception {
		GaussianGenerator gen = new GaussianGenerator(2, 2, 1.0);
		List<TrainingSample<double[]>> list = gen.generateList(100, 100);
		train = new ArrayList<double[]>();
		for (TrainingSample<double[]> t : list) {
			train.add(t.sample);
		}
	}

	/**
	 * Test method for
	 * {@link fr.lip6.jkernelmachines.density.SDCADensity#train(java.lang.Object)}
	 * .
	 */
	@Test
	public final void testTrainT() {
		DoubleGaussL2 k = new DoubleGaussL2();
		SDCADensity<double[]> de = new SDCADensity<double[]>(k);
		de.train(train.get(0));

		for (double[] x : train) {
			assertTrue(!Double.isNaN(de.valueOf(x)));
		}
	}

	/**
	 * Test method for
	 * {@link fr.lip6.jkernelmachines.density.SDCADensity#train(java.util.List)}
	 * .
	 */
	@Test
	public final void testTrainListOfT() {
		DoubleGaussL2 k = new DoubleGaussL2();
//		DoubleLinear k = new DoubleLinear();
		SDCADensity<double[]> de = new SDCADensity<double[]>(k);
		de.setC(1.);
		de.train(train);
		
		for (double[] x : train) {
			assertTrue(!Double.isNaN(de.valueOf(x)));
		}
	}

}

/**
    This file is part of JkernelMachines.

    JkernelMachines is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.

    JkernelMachines 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 General Public License for more details.

    You should have received a copy of the GNU General Public License
    along with JkernelMachines.  If not, see <http://www.gnu.org/licenses/>.

    Copyright David Picard - 2013

 */
package fr.lip6.jkernelmachines.test.density;

import static org.junit.Assert.assertTrue;

import java.util.ArrayList;
import java.util.List;

import org.junit.Before;
import org.junit.Test;

import fr.lip6.jkernelmachines.density.SDCADensity;
import fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2;
import fr.lip6.jkernelmachines.type.TrainingSample;
import fr.lip6.jkernelmachines.util.generators.GaussianGenerator;

/**
 * Test case for the SDCADensity class
 * @author picard
 * 
 */
public class SDCADensityTest {

	List<double[]> train;

	/**
	 * @throws java.lang.Exception
	 */
	@Before
	public void setUp() throws Exception {
		GaussianGenerator gen = new GaussianGenerator(2, 2, 1.0);
		List<TrainingSample<double[]>> list = gen.generateList(100, 100);
		train = new ArrayList<double[]>();
		for (TrainingSample<double[]> t : list) {
			train.add(t.sample);
		}
	}

	/**
	 * Test method for
	 * {@link fr.lip6.jkernelmachines.density.SDCADensity#train(java.lang.Object)}
	 * .
	 */
	@Test
	public final void testTrainT() {
		DoubleGaussL2 k = new DoubleGaussL2();
		SDCADensity<double[]> de = new SDCADensity<double[]>(k);
		de.train(train.get(0));

		for (double[] x : train) {
			assertTrue(!Double.isNaN(de.valueOf(x)));
		}
	}

	/**
	 * Test method for
	 * {@link fr.lip6.jkernelmachines.density.SDCADensity#train(java.util.List)}
	 * .
	 */
	@Test
	public final void testTrainListOfT() {
		DoubleGaussL2 k = new DoubleGaussL2();
		SDCADensity<double[]> de = new SDCADensity<double[]>(k);
		de.setC(1.);
		de.train(train);
		
		for (double[] x : train) {
			assertTrue(!Double.isNaN(de.valueOf(x)));
		}
	}

}

remove useless import