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+/*
+ * 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.math.linear;
+
+import java.util.Arrays;
+
+import org.apache.commons.math.util.FastMath;
+
+
+/**
+ * Class transforming a symmetrical matrix to tridiagonal shape.
+ * <p>A symmetrical m &times; m matrix A can be written as the product of three matrices:
+ * A = Q &times; T &times; Q<sup>T</sup> with Q an orthogonal matrix and T a symmetrical
+ * tridiagonal matrix. Both Q and T are m &times; m matrices.</p>
+ * <p>This implementation only uses the upper part of the matrix, the part below the
+ * diagonal is not accessed at all.</p>
+ * <p>Transformation to tridiagonal shape is often not a goal by itself, but it is
+ * an intermediate step in more general decomposition algorithms like {@link
+ * EigenDecomposition eigen decomposition}. This class is therefore intended for internal
+ * use by the library and is not public. As a consequence of this explicitly limited scope,
+ * many methods directly returns references to internal arrays, not copies.</p>
+ * @version $Revision: 990655 $ $Date: 2010-08-29 23:49:40 +0200 (dim. 29 août 2010) $
+ * @since 2.0
+ */
+class TriDiagonalTransformer {
+
+ /** Householder vectors. */
+ private final double householderVectors[][];
+
+ /** Main diagonal. */
+ private final double[] main;
+
+ /** Secondary diagonal. */
+ private final double[] secondary;
+
+ /** Cached value of Q. */
+ private RealMatrix cachedQ;
+
+ /** Cached value of Qt. */
+ private RealMatrix cachedQt;
+
+ /** Cached value of T. */
+ private RealMatrix cachedT;
+
+ /**
+ * Build the transformation to tridiagonal shape of a symmetrical matrix.
+ * <p>The specified matrix is assumed to be symmetrical without any check.
+ * Only the upper triangular part of the matrix is used.</p>
+ * @param matrix the symmetrical matrix to transform.
+ * @exception InvalidMatrixException if matrix is not square
+ */
+ public TriDiagonalTransformer(RealMatrix matrix)
+ throws InvalidMatrixException {
+ if (!matrix.isSquare()) {
+ throw new NonSquareMatrixException(matrix.getRowDimension(), matrix.getColumnDimension());
+ }
+
+ final int m = matrix.getRowDimension();
+ householderVectors = matrix.getData();
+ main = new double[m];
+ secondary = new double[m - 1];
+ cachedQ = null;
+ cachedQt = null;
+ cachedT = null;
+
+ // transform matrix
+ transform();
+
+ }
+
+ /**
+ * Returns the matrix Q of the transform.
+ * <p>Q is an orthogonal matrix, i.e. its transpose is also its inverse.</p>
+ * @return the Q matrix
+ */
+ public RealMatrix getQ() {
+ if (cachedQ == null) {
+ cachedQ = getQT().transpose();
+ }
+ return cachedQ;
+ }
+
+ /**
+ * Returns the transpose of the matrix Q of the transform.
+ * <p>Q is an orthogonal matrix, i.e. its transpose is also its inverse.</p>
+ * @return the Q matrix
+ */
+ public RealMatrix getQT() {
+
+ if (cachedQt == null) {
+
+ final int m = householderVectors.length;
+ cachedQt = MatrixUtils.createRealMatrix(m, m);
+
+ // build up first part of the matrix by applying Householder transforms
+ for (int k = m - 1; k >= 1; --k) {
+ final double[] hK = householderVectors[k - 1];
+ final double inv = 1.0 / (secondary[k - 1] * hK[k]);
+ cachedQt.setEntry(k, k, 1);
+ if (hK[k] != 0.0) {
+ double beta = 1.0 / secondary[k - 1];
+ cachedQt.setEntry(k, k, 1 + beta * hK[k]);
+ for (int i = k + 1; i < m; ++i) {
+ cachedQt.setEntry(k, i, beta * hK[i]);
+ }
+ for (int j = k + 1; j < m; ++j) {
+ beta = 0;
+ for (int i = k + 1; i < m; ++i) {
+ beta += cachedQt.getEntry(j, i) * hK[i];
+ }
+ beta *= inv;
+ cachedQt.setEntry(j, k, beta * hK[k]);
+ for (int i = k + 1; i < m; ++i) {
+ cachedQt.addToEntry(j, i, beta * hK[i]);
+ }
+ }
+ }
+ }
+ cachedQt.setEntry(0, 0, 1);
+
+ }
+
+ // return the cached matrix
+ return cachedQt;
+
+ }
+
+ /**
+ * Returns the tridiagonal matrix T of the transform.
+ * @return the T matrix
+ */
+ public RealMatrix getT() {
+
+ if (cachedT == null) {
+
+ final int m = main.length;
+ cachedT = MatrixUtils.createRealMatrix(m, m);
+ for (int i = 0; i < m; ++i) {
+ cachedT.setEntry(i, i, main[i]);
+ if (i > 0) {
+ cachedT.setEntry(i, i - 1, secondary[i - 1]);
+ }
+ if (i < main.length - 1) {
+ cachedT.setEntry(i, i + 1, secondary[i]);
+ }
+ }
+
+ }
+
+ // return the cached matrix
+ return cachedT;
+
+ }
+
+ /**
+ * Get the Householder vectors of the transform.
+ * <p>Note that since this class is only intended for internal use,
+ * it returns directly a reference to its internal arrays, not a copy.</p>
+ * @return the main diagonal elements of the B matrix
+ */
+ double[][] getHouseholderVectorsRef() {
+ return householderVectors;
+ }
+
+ /**
+ * Get the main diagonal elements of the matrix T of the transform.
+ * <p>Note that since this class is only intended for internal use,
+ * it returns directly a reference to its internal arrays, not a copy.</p>
+ * @return the main diagonal elements of the T matrix
+ */
+ double[] getMainDiagonalRef() {
+ return main;
+ }
+
+ /**
+ * Get the secondary diagonal elements of the matrix T of the transform.
+ * <p>Note that since this class is only intended for internal use,
+ * it returns directly a reference to its internal arrays, not a copy.</p>
+ * @return the secondary diagonal elements of the T matrix
+ */
+ double[] getSecondaryDiagonalRef() {
+ return secondary;
+ }
+
+ /**
+ * Transform original matrix to tridiagonal form.
+ * <p>Transformation is done using Householder transforms.</p>
+ */
+ private void transform() {
+
+ final int m = householderVectors.length;
+ final double[] z = new double[m];
+ for (int k = 0; k < m - 1; k++) {
+
+ //zero-out a row and a column simultaneously
+ final double[] hK = householderVectors[k];
+ main[k] = hK[k];
+ double xNormSqr = 0;
+ for (int j = k + 1; j < m; ++j) {
+ final double c = hK[j];
+ xNormSqr += c * c;
+ }
+ final double a = (hK[k + 1] > 0) ? -FastMath.sqrt(xNormSqr) : FastMath.sqrt(xNormSqr);
+ secondary[k] = a;
+ if (a != 0.0) {
+ // apply Householder transform from left and right simultaneously
+
+ hK[k + 1] -= a;
+ final double beta = -1 / (a * hK[k + 1]);
+
+ // compute a = beta A v, where v is the Householder vector
+ // this loop is written in such a way
+ // 1) only the upper triangular part of the matrix is accessed
+ // 2) access is cache-friendly for a matrix stored in rows
+ Arrays.fill(z, k + 1, m, 0);
+ for (int i = k + 1; i < m; ++i) {
+ final double[] hI = householderVectors[i];
+ final double hKI = hK[i];
+ double zI = hI[i] * hKI;
+ for (int j = i + 1; j < m; ++j) {
+ final double hIJ = hI[j];
+ zI += hIJ * hK[j];
+ z[j] += hIJ * hKI;
+ }
+ z[i] = beta * (z[i] + zI);
+ }
+
+ // compute gamma = beta vT z / 2
+ double gamma = 0;
+ for (int i = k + 1; i < m; ++i) {
+ gamma += z[i] * hK[i];
+ }
+ gamma *= beta / 2;
+
+ // compute z = z - gamma v
+ for (int i = k + 1; i < m; ++i) {
+ z[i] -= gamma * hK[i];
+ }
+
+ // update matrix: A = A - v zT - z vT
+ // only the upper triangular part of the matrix is updated
+ for (int i = k + 1; i < m; ++i) {
+ final double[] hI = householderVectors[i];
+ for (int j = i; j < m; ++j) {
+ hI[j] -= hK[i] * z[j] + z[i] * hK[j];
+ }
+ }
+
+ }
+
+ }
+ main[m - 1] = householderVectors[m - 1][m - 1];
+ }
+
+}