/*
* Copyright (c) 2009-2012, Peter Abeles. All Rights Reserved.
*
* This file is part of Efficient Java Matrix Library (EJML).
*
* EJML 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 3
* of the License, or (at your option) any later version.
*
* EJML 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 EJML. If not, see <http://www.gnu.org/licenses/>.
*/
package org.ejml.alg.dense.misc;
import org.ejml.alg.dense.decomposition.lu.LUDecompositionAlt;
import org.ejml.data.DenseMatrix64F;
import org.ejml.ops.RandomMatrices;
import org.junit.Test;
import java.util.Random;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertTrue;
/**
* @author Peter Abeles
*/
public class TestUnrolledDeterminantFromMinor {
Random rand = new Random(234234);
@Test
public void testAll() {
for( int N = 2; N <= UnrolledDeterminantFromMinor.MAX; N++ ) {
DenseMatrix64F A = RandomMatrices.createRandom(N,N,rand);
double unrolled = UnrolledDeterminantFromMinor.det(A);
LUDecompositionAlt alg = new LUDecompositionAlt();
assertTrue( alg.decompose(A) );
double expected = alg.computeDeterminant();
assertEquals(expected,unrolled,1e-8);
}
}
}