📄 densecholeskytest.java
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/* * Copyright (C) 2003-2006 Bjørn-Ove Heimsund * * This file is part of MTJ. * * 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 no.uib.cipr.matrix;import no.uib.cipr.matrix.DenseCholesky;import no.uib.cipr.matrix.DenseMatrix;import no.uib.cipr.matrix.LowerSPDDenseMatrix;import no.uib.cipr.matrix.Matrices;import no.uib.cipr.matrix.Matrix;import no.uib.cipr.matrix.UpperSPDDenseMatrix;import junit.framework.TestCase;/** * Tests the dense Cholesky decomposition */public class DenseCholeskyTest extends TestCase { private LowerSPDDenseMatrix L; private UpperSPDDenseMatrix U; private DenseMatrix I; private final int max = 50; public DenseCholeskyTest(String arg0) { super(arg0); } @Override protected void setUp() throws Exception { int n = Utilities.getInt(1, max); L = new LowerSPDDenseMatrix(n); Utilities.lowerPopulate(L); Utilities.addDiagonal(L, 1); while (!Utilities.spd(L)) Utilities.addDiagonal(L, 1); U = new UpperSPDDenseMatrix(n); Utilities.upperPopulate(U); Utilities.addDiagonal(U, 1); while (!Utilities.spd(U)) Utilities.addDiagonal(U, 1); I = Matrices.identity(n); } @Override protected void tearDown() throws Exception { L = null; U = null; I = null; } public void testLowerDenseCholesky() { int n = L.numRows(); DenseCholesky c = new DenseCholesky(n, false); c.factor(L.copy()); assert I != null; c.solve(I); Matrix J = I.mult(L, new DenseMatrix(n, n)); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (i != j) assertEquals(J.get(i, j), 0, 1e-10); else assertEquals(J.get(i, j), 1, 1e-10); } public void testUpperDenseCholesky() { int n = U.numRows(); DenseCholesky c = new DenseCholesky(n, true); c.factor(U.copy()); c.solve(I); Matrix J = I.mult(U, new DenseMatrix(n, n)); for (int i = 0; i < n; ++i) for (int j = 0; j < n; ++j) if (i != j) assertEquals(J.get(i, j), 0, 1e-10); else assertEquals(J.get(i, j), 1, 1e-10); } public void testLowerDenseCholeskyrcond() { int n = L.numRows(); DenseCholesky c = new DenseCholesky(n, false); c.factor(L.copy()); c.rcond(L); } public void testUpperDenseCholeskyrcond() { int n = U.numRows(); DenseCholesky c = new DenseCholesky(n, true); c.factor(U.copy()); c.rcond(U); }}
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