/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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 org.apache.ignite.ml.math.decompositions;
import org.apache.ignite.ml.math.Matrix;
import org.apache.ignite.ml.math.Vector;
import org.apache.ignite.ml.math.exceptions.CardinalityException;
import org.apache.ignite.ml.math.exceptions.NonPositiveDefiniteMatrixException;
import org.apache.ignite.ml.math.exceptions.NonSymmetricMatrixException;
import org.apache.ignite.ml.math.impls.matrix.DenseLocalOnHeapMatrix;
import org.apache.ignite.ml.math.impls.matrix.PivotedMatrixView;
import org.apache.ignite.ml.math.impls.vector.DenseLocalOnHeapVector;
import org.apache.ignite.ml.math.util.MatrixUtil;
import org.junit.Test;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertNotNull;
/** */
public class CholeskyDecompositionTest {
/** */
@Test
public void basicTest() {
basicTest(new DenseLocalOnHeapMatrix(new double[][] {
{2.0d, -1.0d, 0.0d},
{-1.0d, 2.0d, -1.0d},
{0.0d, -1.0d, 2.0d}
}));
}
/**
* Test for {@link MatrixUtil} features (more specifically, we test matrix which does not have
* a native like/copy methods support).
*/
@Test
public void matrixUtilTest() {
basicTest(new PivotedMatrixView(new DenseLocalOnHeapMatrix(new double[][] {
{2.0d, -1.0d, 0.0d},
{-1.0d, 2.0d, -1.0d},
{0.0d, -1.0d, 2.0d}
})));
}
/** */
@Test(expected = AssertionError.class)
public void nullMatrixTest() {
new CholeskyDecomposition(null);
}
/** */
@Test(expected = CardinalityException.class)
public void wrongMatrixSizeTest() {
new CholeskyDecomposition(new DenseLocalOnHeapMatrix(2, 3));
}
/** */
@Test(expected = NonSymmetricMatrixException.class)
public void nonSymmetricMatrixTest() {
new CholeskyDecomposition(new DenseLocalOnHeapMatrix(new double[][] {
{2.0d, -1.0d, 10.0d},
{-1.0d, 2.0d, -1.0d},
{-10.0d, -1.0d, 2.0d}
}));
}
/** */
@Test(expected = NonPositiveDefiniteMatrixException.class)
public void nonAbsPositiveMatrixTest() {
new CholeskyDecomposition(new DenseLocalOnHeapMatrix(new double[][] {
{2.0d, -1.0d, 0.0d},
{-1.0d, 0.0d, -1.0d},
{0.0d, -1.0d, 2.0d}
}));
}
/** */
@Test(expected = CardinalityException.class)
public void solveWrongVectorSizeTest() {
new CholeskyDecomposition(new DenseLocalOnHeapMatrix(new double[][] {
{2.0d, -1.0d, 0.0d},
{-1.0d, 2.0d, -1.0d},
{0.0d, -1.0d, 2.0d}
})).solve(new DenseLocalOnHeapVector(2));
}
/** */
@Test(expected = CardinalityException.class)
public void solveWrongMatrixSizeTest() {
new CholeskyDecomposition(new DenseLocalOnHeapMatrix(new double[][] {
{2.0d, -1.0d, 0.0d},
{-1.0d, 2.0d, -1.0d},
{0.0d, -1.0d, 2.0d}
})).solve(new DenseLocalOnHeapMatrix(2, 3));
}
/** */
private void basicTest(Matrix m) {
// This decomposition is useful when dealing with systems of linear equations of the form
// m x = b where m is a Hermitian matrix.
// For such systems Cholesky decomposition provides
// more effective method of solving compared to LU decomposition.
// Suppose we want to solve system
// m x = b for various bs. Then after we computed Cholesky decomposition, we can feed various bs
// as a matrix of the form
// (b1, b2, ..., bm)
// to the method Cholesky::solve which returns solutions in the form
// (sol1, sol2, ..., solm)
CholeskyDecomposition dec = new CholeskyDecomposition(m);
assertEquals("Unexpected value for decomposition determinant.",
4d, dec.getDeterminant(), 0d);
Matrix l = dec.getL();
Matrix lt = dec.getLT();
assertNotNull("Matrix l is expected to be not null.", l);
assertNotNull("Matrix lt is expected to be not null.", lt);
for (int row = 0; row < l.rowSize(); row++)
for (int col = 0; col < l.columnSize(); col++)
assertEquals("Unexpected value transposed matrix at (" + row + "," + col + ").",
l.get(row, col), lt.get(col, row), 0d);
Matrix bs = new DenseLocalOnHeapMatrix(new double[][] {
{4.0, -6.0, 7.0},
{1.0, 1.0, 1.0}
}).transpose();
Matrix sol = dec.solve(bs);
assertNotNull("Solution matrix is expected to be not null.", sol);
assertEquals("Solution rows are not as expected.", bs.rowSize(), sol.rowSize());
assertEquals("Solution columns are not as expected.", bs.columnSize(), sol.columnSize());
for (int i = 0; i < sol.columnSize(); i++)
assertNotNull("Solution matrix column is expected to be not null at index " + i, sol.viewColumn(i));
Vector b = new DenseLocalOnHeapVector(new double[] {4.0, -6.0, 7.0});
Vector solVec = dec.solve(b);
for (int idx = 0; idx < b.size(); idx++)
assertEquals("Unexpected value solution vector at " + idx,
b.get(idx), solVec.get(idx), 0d);
dec.destroy();
}
}