📄 bandmatrix.java
字号:
/* * Copyright (C) 2003-2006 Bjørn-Ove Heimsund * * This file is part of MTJ. * * This library is free software; you can redistribute it and/or modify it * under the terms of the GNU Lesser General Public License as published by the * Free Software Foundation; either version 2.1 of the License, or (at your * option) any later version. * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License * for more details. * * You should have received a copy of the GNU Lesser General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA */package no.uib.cipr.matrix;import java.util.Arrays;import org.netlib.blas.BLAS;import org.netlib.lapack.LAPACK;import org.netlib.util.intW;/** * Banded matrix. The banded matrix is a useful sparse structure for many kinds * of direct computations, however it should only be used if the band is * sufficiently narrow as wide bands actually wastes both memory and compute * time. The matrix * <p> * <table border="1"> * <tr> * <td>a<sub>11</sub></td> * <td>a<sub>12</sub></td> * <td> </td> * <td> </td> * <td> </td> * </tr> * <tr> * <td>a<sub>21</sub></td> * <td>a<sub>22</sub></td> * <td>a<sub>23</sub></td> * <td> </td> * <td> </td> * </tr> * <tr> * <td>a<sub>31</sub></td> * <td>a<sub>32</sub></td> * <td>a<sub>33</sub></td> * <td>a<sub>34</sub></td> * <td> </td> * </tr> * <tr> * <td> </td> * <td>a<sub>42</sub></td> * <td>a<sub>43</sub></td> * <td>a<sub>44</sub></td> * <td>a<sub>45</sub></td> * </tr> * <tr> * <td> </td> * <td> </td> * <td>a<sub>53</sub></td> * <td>a<sub>54</sub></td> * <td>a<sub>55</sub></td> * </tr> * </table> * </p> * <p> * has two lower diagonals and one upper diagonal. It will be stored in the * array * </p> * <p> * <table border="1"> * <tr> * <td> </td> * <td>a<sub>11</sub></td> * <td>a<sub>21</sub></td> * <td>a<sub>31</sub></td> * <td>a<sub>21</sub></td> * <td>a<sub>22</sub></td> * <td>a<sub>32</sub></td> * <td>a<sub>42</sub></td> * <td>a<sub>23</sub></td> * <td>a<sub>33</sub></td> * <td>a<sub>43</sub></td> * <td>a<sub>53</sub></td> * <td>a<sub>34</sub></td> * <td>a<sub>44</sub></td> * <td>a<sub>54</sub></td> * <td> </td> * <td>a<sub>45</sub></td> * <td>a<sub>55</sub></td> * <td> </td> * <td> </td> * </tr> * </table> * </p> * <p> * Empty cells are allocated, but never referenced. * </p> */public class BandMatrix extends AbstractBandMatrix { /** * Constructor for BandMatrix * * @param n * Size of the matrix. Since the matrix must be square, this * equals both the number of rows and columns * @param kl * Number of bands above the main diagonal (superdiagonals) * @param ku * Number of bands below the main diagonal (subdiagonals) */ public BandMatrix(int n, int kl, int ku) { super(n, kl, ku); } /** * Constructor for BandMatrix * * @param A * Matrix to copy contents from. Only the parts of <code>A</code> * that lie within the allocated band are copied over, the rest * is ignored * @param kl * Number of bands above the main diagonal (superdiagonals) * @param ku * Number of bands below the main diagonal (subdiagonals) */ public BandMatrix(Matrix A, int kl, int ku) { super(A, kl, ku); } /** * Constructor for BandMatrix * * @param A * Matrix to copy contents from. Only the parts of <code>A</code> * that lie within the allocated band are copied over, the rest * is ignored * @param kl * Number of bands above the main diagonal (superdiagonals) * @param ku * Number of bands below the main diagonal (subdiagonals) * @param deep * True for a deep copy. For shallow copies, <code>A</code> * must be a banded matrix */ public BandMatrix(Matrix A, int kl, int ku, boolean deep) { super(A, kl, ku, deep); } @Override public BandMatrix copy() { return new BandMatrix(this, kl, ku); } @Override public Matrix zero() { Arrays.fill(data, 0); return this; } @Override public Vector multAdd(double alpha, Vector x, Vector y) { if (!(x instanceof DenseVector) || !(y instanceof DenseVector)) return super.multAdd(alpha, x, y); checkMultAdd(x, y); double[] xd = ((DenseVector) x).getData(), yd = ((DenseVector) y) .getData(); BLAS.getInstance().dgbmv(Transpose.NoTranspose.netlib(), numRows, numColumns, kl, ku, alpha, data, kl + ku + 1, xd, 1, 1, yd, 1); return y; } @Override public Vector transMultAdd(double alpha, Vector x, Vector y) { if (!(x instanceof DenseVector) || !(y instanceof DenseVector)) return super.transMultAdd(alpha, x, y); checkTransMultAdd(x, y); double[] xd = ((DenseVector) x).getData(), yd = ((DenseVector) y) .getData(); BLAS.getInstance().dgbmv(Transpose.Transpose.netlib(), numRows, numColumns, kl, ku, alpha, data, kl + ku + 1, xd, 1, 1, yd, 1); return y; } @Override public Matrix solve(Matrix B, Matrix X) { if (!(X instanceof DenseMatrix)) throw new UnsupportedOperationException("X must be a DenseMatrix"); checkSolve(B, X); double[] Xd = ((DenseMatrix) X).getData(); X.set(B); // Allocate factorization matrix. The factorization matrix will be // large enough to accomodate any pivots BandMatrix Af = new BandMatrix(this, kl, ku + kl); int[] ipiv = new int[numRows]; intW info = new intW(0); LAPACK.getInstance().dgbsv(numRows, kl, ku, X.numColumns(), Af.getData(), Matrices.ld(2 * kl + ku + 1), ipiv, Xd, Matrices.ld(numRows), info); if (info.val > 0) throw new MatrixSingularException(); else if (info.val < 0) throw new IllegalArgumentException(); return X; } @Override public Vector solve(Vector b, Vector x) { DenseMatrix B = new DenseMatrix(b, false), X = new DenseMatrix(x, false); solve(B, X); return x; } @Override public Matrix transpose() { checkTranspose(); if (kl != ku) throw new IllegalArgumentException("kl != ku"); for (int j = 0; j < numColumns; ++j) for (int i = j + 1; i < Math.min(j + kl + 1, numRows); ++i) { double value = get(i, j); set(i, j, get(j, i)); set(j, i, value); } return this; }}
⌨️ 快捷键说明
复制代码
Ctrl + C
搜索代码
Ctrl + F
全屏模式
F11
切换主题
Ctrl + Shift + D
显示快捷键
?
增大字号
Ctrl + =
减小字号
Ctrl + -