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18 package org.apache.commons.math4.legacy.linear;
19
20 import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException;
21 import org.junit.Assert;
22 import org.junit.Test;
23
24 public class SingularValueSolverTest {
25
26 private double[][] testSquare = {
27 { 24.0 / 25.0, 43.0 / 25.0 },
28 { 57.0 / 25.0, 24.0 / 25.0 }
29 };
30 private double[][] bigSingular = {
31 { 1.0, 2.0, 3.0, 4.0 },
32 { 2.0, 5.0, 3.0, 4.0 },
33 { 7.0, 3.0, 256.0, 1930.0 },
34 { 3.0, 7.0, 6.0, 8.0 }
35 };
36
37 private static final double normTolerance = 10e-14;
38
39
40 @Test
41 public void testSolveDimensionErrors() {
42 DecompositionSolver solver =
43 new SingularValueDecomposition(MatrixUtils.createRealMatrix(testSquare)).getSolver();
44 RealMatrix b = MatrixUtils.createRealMatrix(new double[3][2]);
45 try {
46 solver.solve(b);
47 Assert.fail("an exception should have been thrown");
48 } catch (MathIllegalArgumentException iae) {
49
50 }
51 try {
52 solver.solve(b.getColumnVector(0));
53 Assert.fail("an exception should have been thrown");
54 } catch (MathIllegalArgumentException iae) {
55
56 }
57 try {
58 solver.solve(new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(0)));
59 Assert.fail("an exception should have been thrown");
60 } catch (MathIllegalArgumentException iae) {
61
62 }
63 }
64
65
66 @Test
67 public void testLeastSquareSolve() {
68 RealMatrix m =
69 MatrixUtils.createRealMatrix(new double[][] {
70 { 1.0, 0.0 },
71 { 0.0, 0.0 }
72 });
73 DecompositionSolver solver = new SingularValueDecomposition(m).getSolver();
74 RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
75 { 11, 12 }, { 21, 22 }
76 });
77 RealMatrix xMatrix = solver.solve(b);
78 Assert.assertEquals(11, xMatrix.getEntry(0, 0), 1.0e-15);
79 Assert.assertEquals(12, xMatrix.getEntry(0, 1), 1.0e-15);
80 Assert.assertEquals(0, xMatrix.getEntry(1, 0), 1.0e-15);
81 Assert.assertEquals(0, xMatrix.getEntry(1, 1), 1.0e-15);
82 RealVector xColVec = solver.solve(b.getColumnVector(0));
83 Assert.assertEquals(11, xColVec.getEntry(0), 1.0e-15);
84 Assert.assertEquals(0, xColVec.getEntry(1), 1.0e-15);
85 RealVector xColOtherVec = solver.solve(new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(0)));
86 Assert.assertEquals(11, xColOtherVec.getEntry(0), 1.0e-15);
87 Assert.assertEquals(0, xColOtherVec.getEntry(1), 1.0e-15);
88 }
89
90
91 @Test
92 public void testSolve() {
93 DecompositionSolver solver =
94 new SingularValueDecomposition(MatrixUtils.createRealMatrix(testSquare)).getSolver();
95 RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
96 { 1, 2, 3 }, { 0, -5, 1 }
97 });
98 RealMatrix xRef = MatrixUtils.createRealMatrix(new double[][] {
99 { -8.0 / 25.0, -263.0 / 75.0, -29.0 / 75.0 },
100 { 19.0 / 25.0, 78.0 / 25.0, 49.0 / 25.0 }
101 });
102
103
104 Assert.assertEquals(0, solver.solve(b).subtract(xRef).getNorm(), normTolerance);
105
106
107 for (int i = 0; i < b.getColumnDimension(); ++i) {
108 Assert.assertEquals(0,
109 solver.solve(b.getColumnVector(i)).subtract(xRef.getColumnVector(i)).getNorm(),
110 1.0e-13);
111 }
112
113
114 for (int i = 0; i < b.getColumnDimension(); ++i) {
115 ArrayRealVectorTest.RealVectorTestImpl v =
116 new ArrayRealVectorTest.RealVectorTestImpl(b.getColumn(i));
117 Assert.assertEquals(0,
118 solver.solve(v).subtract(xRef.getColumnVector(i)).getNorm(),
119 1.0e-13);
120 }
121 }
122
123
124 @Test
125 public void testConditionNumber() {
126 SingularValueDecomposition svd =
127 new SingularValueDecomposition(MatrixUtils.createRealMatrix(testSquare));
128
129 Assert.assertEquals(3.0, svd.getConditionNumber(), 1.5e-15);
130 }
131
132 @Test
133 public void testMath320B() {
134 RealMatrix rm = new Array2DRowRealMatrix(new double[][] {
135 { 1.0, 2.0 }, { 1.0, 2.0 }
136 });
137 SingularValueDecomposition svd =
138 new SingularValueDecomposition(rm);
139 RealMatrix recomposed = svd.getU().multiply(svd.getS()).multiply(svd.getVT());
140 Assert.assertEquals(0.0, recomposed.subtract(rm).getNorm(), 2.0e-15);
141 }
142
143 @Test
144 public void testSingular() {
145 SingularValueDecomposition svd =
146 new SingularValueDecomposition(MatrixUtils.createRealMatrix(bigSingular));
147 RealMatrix pseudoInverse = svd.getSolver().getInverse();
148 RealMatrix expected = new Array2DRowRealMatrix(new double[][] {
149 {-0.0355022687,0.0512742236,-0.0001045523,0.0157719549},
150 {-0.3214992438,0.3162419255,0.0000348508,-0.0052573183},
151 {0.5437098346,-0.4107754586,-0.0008256918,0.132934376},
152 {-0.0714905202,0.053808742,0.0006279816,-0.0176817782}
153 });
154 Assert.assertEquals(0, expected.subtract(pseudoInverse).getNorm(), 1.0e-9);
155 }
156 }