/*
 * 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.commons.math4.linear;

import org.apache.commons.math4.linear.MatrixUtils;
import org.apache.commons.math4.linear.RealMatrix;
import org.apache.commons.math4.linear.RectangularCholeskyDecomposition;
import org.junit.Test;
import org.junit.Assert;

public class RectangularCholeskyDecompositionTest {

    @Test
    public void testDecomposition3x3() {

        RealMatrix m = MatrixUtils.createRealMatrix(new double[][] {
            { 1,   9,   9 },
            { 9, 225, 225 },
            { 9, 225, 625 }
        });

        RectangularCholeskyDecomposition d =
                new RectangularCholeskyDecomposition(m, 1.0e-6);

        // as this decomposition permutes lines and columns, the root is NOT triangular
        // (in fact here it is the lower right part of the matrix which is zero and
        //  the upper left non-zero)
        Assert.assertEquals(0.8,  d.getRootMatrix().getEntry(0, 2), 1.0e-15);
        Assert.assertEquals(25.0, d.getRootMatrix().getEntry(2, 0), 1.0e-15);
        Assert.assertEquals(0.0,  d.getRootMatrix().getEntry(2, 2), 1.0e-15);

        RealMatrix root = d.getRootMatrix();
        RealMatrix rebuiltM = root.multiply(root.transpose());
        Assert.assertEquals(0.0, m.subtract(rebuiltM).getNorm(), 1.0e-15);

    }

    @Test
    public void testFullRank() {

        RealMatrix base = MatrixUtils.createRealMatrix(new double[][] {
            { 0.1159548705,      0.,           0.,           0.      },
            { 0.0896442724, 0.1223540781,      0.,           0.      },
            { 0.0852155322, 4.558668e-3,  0.1083577299,      0.      },
            { 0.0905486674, 0.0213768077, 0.0128878333, 0.1014155693 }
        });

        RealMatrix m = base.multiply(base.transpose());

        RectangularCholeskyDecomposition d =
                new RectangularCholeskyDecomposition(m, 1.0e-10);

        RealMatrix root = d.getRootMatrix();
        RealMatrix rebuiltM = root.multiply(root.transpose());
        Assert.assertEquals(0.0, m.subtract(rebuiltM).getNorm(), 1.0e-15);

        // the pivoted Cholesky decomposition is *not* unique. Here, the root is
        // not equal to the original trianbular base matrix
        Assert.assertTrue(root.subtract(base).getNorm() > 0.3);

    }

    @Test
    public void testMath789() {

        final RealMatrix m1 = MatrixUtils.createRealMatrix(new double[][]{
            {0.013445532, 0.010394690, 0.009881156, 0.010499559},
            {0.010394690, 0.023006616, 0.008196856, 0.010732709},
            {0.009881156, 0.008196856, 0.019023866, 0.009210099},
            {0.010499559, 0.010732709, 0.009210099, 0.019107243}
        });
        composeAndTest(m1, 4);

        final RealMatrix m2 = MatrixUtils.createRealMatrix(new double[][]{
            {0.0, 0.0, 0.0, 0.0, 0.0},
            {0.0, 0.013445532, 0.010394690, 0.009881156, 0.010499559},
            {0.0, 0.010394690, 0.023006616, 0.008196856, 0.010732709},
            {0.0, 0.009881156, 0.008196856, 0.019023866, 0.009210099},
            {0.0, 0.010499559, 0.010732709, 0.009210099, 0.019107243}
        });
        composeAndTest(m2, 4);

        final RealMatrix m3 = MatrixUtils.createRealMatrix(new double[][]{
            {0.013445532, 0.010394690, 0.0, 0.009881156, 0.010499559},
            {0.010394690, 0.023006616, 0.0, 0.008196856, 0.010732709},
            {0.0, 0.0, 0.0, 0.0, 0.0},
            {0.009881156, 0.008196856, 0.0, 0.019023866, 0.009210099},
            {0.010499559, 0.010732709, 0.0, 0.009210099, 0.019107243}
        });
        composeAndTest(m3, 4);

    }

    private void composeAndTest(RealMatrix m, int expectedRank) {
        RectangularCholeskyDecomposition r = new RectangularCholeskyDecomposition(m);
        Assert.assertEquals(expectedRank, r.getRank());
        RealMatrix root = r.getRootMatrix();
        RealMatrix rebuiltMatrix = root.multiply(root.transpose());
        Assert.assertEquals(0.0, m.subtract(rebuiltMatrix).getNorm(), 1.0e-16);
    }

}