1 | /*
|
---|
2 | * Licensed to the Apache Software Foundation (ASF) under one or more
|
---|
3 | * contributor license agreements. See the NOTICE file distributed with
|
---|
4 | * this work for additional information regarding copyright ownership.
|
---|
5 | * The ASF licenses this file to You under the Apache License, Version 2.0
|
---|
6 | * (the "License"); you may not use this file except in compliance with
|
---|
7 | * the License. You may obtain a copy of the License at
|
---|
8 | *
|
---|
9 | * http://www.apache.org/licenses/LICENSE-2.0
|
---|
10 | *
|
---|
11 | * Unless required by applicable law or agreed to in writing, software
|
---|
12 | * distributed under the License is distributed on an "AS IS" BASIS,
|
---|
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
---|
14 | * See the License for the specific language governing permissions and
|
---|
15 | * limitations under the License.
|
---|
16 | */
|
---|
17 |
|
---|
18 | package agents.anac.y2019.harddealer.math3.linear;
|
---|
19 |
|
---|
20 | import java.util.Arrays;
|
---|
21 |
|
---|
22 | import agents.anac.y2019.harddealer.math3.util.FastMath;
|
---|
23 |
|
---|
24 |
|
---|
25 | /**
|
---|
26 | * Class transforming a symmetrical matrix to tridiagonal shape.
|
---|
27 | * <p>A symmetrical m × m matrix A can be written as the product of three matrices:
|
---|
28 | * A = Q × T × Q<sup>T</sup> with Q an orthogonal matrix and T a symmetrical
|
---|
29 | * tridiagonal matrix. Both Q and T are m × m matrices.</p>
|
---|
30 | * <p>This implementation only uses the upper part of the matrix, the part below the
|
---|
31 | * diagonal is not accessed at all.</p>
|
---|
32 | * <p>Transformation to tridiagonal shape is often not a goal by itself, but it is
|
---|
33 | * an intermediate step in more general decomposition algorithms like {@link
|
---|
34 | * EigenDecomposition eigen decomposition}. This class is therefore intended for internal
|
---|
35 | * use by the library and is not public. As a consequence of this explicitly limited scope,
|
---|
36 | * many methods directly returns references to internal arrays, not copies.</p>
|
---|
37 | * @since 2.0
|
---|
38 | */
|
---|
39 | class TriDiagonalTransformer {
|
---|
40 | /** Householder vectors. */
|
---|
41 | private final double householderVectors[][];
|
---|
42 | /** Main diagonal. */
|
---|
43 | private final double[] main;
|
---|
44 | /** Secondary diagonal. */
|
---|
45 | private final double[] secondary;
|
---|
46 | /** Cached value of Q. */
|
---|
47 | private RealMatrix cachedQ;
|
---|
48 | /** Cached value of Qt. */
|
---|
49 | private RealMatrix cachedQt;
|
---|
50 | /** Cached value of T. */
|
---|
51 | private RealMatrix cachedT;
|
---|
52 |
|
---|
53 | /**
|
---|
54 | * Build the transformation to tridiagonal shape of a symmetrical matrix.
|
---|
55 | * <p>The specified matrix is assumed to be symmetrical without any check.
|
---|
56 | * Only the upper triangular part of the matrix is used.</p>
|
---|
57 | *
|
---|
58 | * @param matrix Symmetrical matrix to transform.
|
---|
59 | * @throws NonSquareMatrixException if the matrix is not square.
|
---|
60 | */
|
---|
61 | TriDiagonalTransformer(RealMatrix matrix) {
|
---|
62 | if (!matrix.isSquare()) {
|
---|
63 | throw new NonSquareMatrixException(matrix.getRowDimension(),
|
---|
64 | matrix.getColumnDimension());
|
---|
65 | }
|
---|
66 |
|
---|
67 | final int m = matrix.getRowDimension();
|
---|
68 | householderVectors = matrix.getData();
|
---|
69 | main = new double[m];
|
---|
70 | secondary = new double[m - 1];
|
---|
71 | cachedQ = null;
|
---|
72 | cachedQt = null;
|
---|
73 | cachedT = null;
|
---|
74 |
|
---|
75 | // transform matrix
|
---|
76 | transform();
|
---|
77 | }
|
---|
78 |
|
---|
79 | /**
|
---|
80 | * Returns the matrix Q of the transform.
|
---|
81 | * <p>Q is an orthogonal matrix, i.e. its transpose is also its inverse.</p>
|
---|
82 | * @return the Q matrix
|
---|
83 | */
|
---|
84 | public RealMatrix getQ() {
|
---|
85 | if (cachedQ == null) {
|
---|
86 | cachedQ = getQT().transpose();
|
---|
87 | }
|
---|
88 | return cachedQ;
|
---|
89 | }
|
---|
90 |
|
---|
91 | /**
|
---|
92 | * Returns the transpose of the matrix Q of the transform.
|
---|
93 | * <p>Q is an orthogonal matrix, i.e. its transpose is also its inverse.</p>
|
---|
94 | * @return the Q matrix
|
---|
95 | */
|
---|
96 | public RealMatrix getQT() {
|
---|
97 | if (cachedQt == null) {
|
---|
98 | final int m = householderVectors.length;
|
---|
99 | double[][] qta = new double[m][m];
|
---|
100 |
|
---|
101 | // build up first part of the matrix by applying Householder transforms
|
---|
102 | for (int k = m - 1; k >= 1; --k) {
|
---|
103 | final double[] hK = householderVectors[k - 1];
|
---|
104 | qta[k][k] = 1;
|
---|
105 | if (hK[k] != 0.0) {
|
---|
106 | final double inv = 1.0 / (secondary[k - 1] * hK[k]);
|
---|
107 | double beta = 1.0 / secondary[k - 1];
|
---|
108 | qta[k][k] = 1 + beta * hK[k];
|
---|
109 | for (int i = k + 1; i < m; ++i) {
|
---|
110 | qta[k][i] = beta * hK[i];
|
---|
111 | }
|
---|
112 | for (int j = k + 1; j < m; ++j) {
|
---|
113 | beta = 0;
|
---|
114 | for (int i = k + 1; i < m; ++i) {
|
---|
115 | beta += qta[j][i] * hK[i];
|
---|
116 | }
|
---|
117 | beta *= inv;
|
---|
118 | qta[j][k] = beta * hK[k];
|
---|
119 | for (int i = k + 1; i < m; ++i) {
|
---|
120 | qta[j][i] += beta * hK[i];
|
---|
121 | }
|
---|
122 | }
|
---|
123 | }
|
---|
124 | }
|
---|
125 | qta[0][0] = 1;
|
---|
126 | cachedQt = MatrixUtils.createRealMatrix(qta);
|
---|
127 | }
|
---|
128 |
|
---|
129 | // return the cached matrix
|
---|
130 | return cachedQt;
|
---|
131 | }
|
---|
132 |
|
---|
133 | /**
|
---|
134 | * Returns the tridiagonal matrix T of the transform.
|
---|
135 | * @return the T matrix
|
---|
136 | */
|
---|
137 | public RealMatrix getT() {
|
---|
138 | if (cachedT == null) {
|
---|
139 | final int m = main.length;
|
---|
140 | double[][] ta = new double[m][m];
|
---|
141 | for (int i = 0; i < m; ++i) {
|
---|
142 | ta[i][i] = main[i];
|
---|
143 | if (i > 0) {
|
---|
144 | ta[i][i - 1] = secondary[i - 1];
|
---|
145 | }
|
---|
146 | if (i < main.length - 1) {
|
---|
147 | ta[i][i + 1] = secondary[i];
|
---|
148 | }
|
---|
149 | }
|
---|
150 | cachedT = MatrixUtils.createRealMatrix(ta);
|
---|
151 | }
|
---|
152 |
|
---|
153 | // return the cached matrix
|
---|
154 | return cachedT;
|
---|
155 | }
|
---|
156 |
|
---|
157 | /**
|
---|
158 | * Get the Householder vectors of the transform.
|
---|
159 | * <p>Note that since this class is only intended for internal use,
|
---|
160 | * it returns directly a reference to its internal arrays, not a copy.</p>
|
---|
161 | * @return the main diagonal elements of the B matrix
|
---|
162 | */
|
---|
163 | double[][] getHouseholderVectorsRef() {
|
---|
164 | return householderVectors;
|
---|
165 | }
|
---|
166 |
|
---|
167 | /**
|
---|
168 | * Get the main diagonal elements of the matrix T of the transform.
|
---|
169 | * <p>Note that since this class is only intended for internal use,
|
---|
170 | * it returns directly a reference to its internal arrays, not a copy.</p>
|
---|
171 | * @return the main diagonal elements of the T matrix
|
---|
172 | */
|
---|
173 | double[] getMainDiagonalRef() {
|
---|
174 | return main;
|
---|
175 | }
|
---|
176 |
|
---|
177 | /**
|
---|
178 | * Get the secondary diagonal elements of the matrix T of the transform.
|
---|
179 | * <p>Note that since this class is only intended for internal use,
|
---|
180 | * it returns directly a reference to its internal arrays, not a copy.</p>
|
---|
181 | * @return the secondary diagonal elements of the T matrix
|
---|
182 | */
|
---|
183 | double[] getSecondaryDiagonalRef() {
|
---|
184 | return secondary;
|
---|
185 | }
|
---|
186 |
|
---|
187 | /**
|
---|
188 | * Transform original matrix to tridiagonal form.
|
---|
189 | * <p>Transformation is done using Householder transforms.</p>
|
---|
190 | */
|
---|
191 | private void transform() {
|
---|
192 | final int m = householderVectors.length;
|
---|
193 | final double[] z = new double[m];
|
---|
194 | for (int k = 0; k < m - 1; k++) {
|
---|
195 |
|
---|
196 | //zero-out a row and a column simultaneously
|
---|
197 | final double[] hK = householderVectors[k];
|
---|
198 | main[k] = hK[k];
|
---|
199 | double xNormSqr = 0;
|
---|
200 | for (int j = k + 1; j < m; ++j) {
|
---|
201 | final double c = hK[j];
|
---|
202 | xNormSqr += c * c;
|
---|
203 | }
|
---|
204 | final double a = (hK[k + 1] > 0) ? -FastMath.sqrt(xNormSqr) : FastMath.sqrt(xNormSqr);
|
---|
205 | secondary[k] = a;
|
---|
206 | if (a != 0.0) {
|
---|
207 | // apply Householder transform from left and right simultaneously
|
---|
208 |
|
---|
209 | hK[k + 1] -= a;
|
---|
210 | final double beta = -1 / (a * hK[k + 1]);
|
---|
211 |
|
---|
212 | // compute a = beta A v, where v is the Householder vector
|
---|
213 | // this loop is written in such a way
|
---|
214 | // 1) only the upper triangular part of the matrix is accessed
|
---|
215 | // 2) access is cache-friendly for a matrix stored in rows
|
---|
216 | Arrays.fill(z, k + 1, m, 0);
|
---|
217 | for (int i = k + 1; i < m; ++i) {
|
---|
218 | final double[] hI = householderVectors[i];
|
---|
219 | final double hKI = hK[i];
|
---|
220 | double zI = hI[i] * hKI;
|
---|
221 | for (int j = i + 1; j < m; ++j) {
|
---|
222 | final double hIJ = hI[j];
|
---|
223 | zI += hIJ * hK[j];
|
---|
224 | z[j] += hIJ * hKI;
|
---|
225 | }
|
---|
226 | z[i] = beta * (z[i] + zI);
|
---|
227 | }
|
---|
228 |
|
---|
229 | // compute gamma = beta vT z / 2
|
---|
230 | double gamma = 0;
|
---|
231 | for (int i = k + 1; i < m; ++i) {
|
---|
232 | gamma += z[i] * hK[i];
|
---|
233 | }
|
---|
234 | gamma *= beta / 2;
|
---|
235 |
|
---|
236 | // compute z = z - gamma v
|
---|
237 | for (int i = k + 1; i < m; ++i) {
|
---|
238 | z[i] -= gamma * hK[i];
|
---|
239 | }
|
---|
240 |
|
---|
241 | // update matrix: A = A - v zT - z vT
|
---|
242 | // only the upper triangular part of the matrix is updated
|
---|
243 | for (int i = k + 1; i < m; ++i) {
|
---|
244 | final double[] hI = householderVectors[i];
|
---|
245 | for (int j = i; j < m; ++j) {
|
---|
246 | hI[j] -= hK[i] * z[j] + z[i] * hK[j];
|
---|
247 | }
|
---|
248 | }
|
---|
249 | }
|
---|
250 | }
|
---|
251 | main[m - 1] = householderVectors[m - 1][m - 1];
|
---|
252 | }
|
---|
253 | }
|
---|