📄 icc.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.sparse;import java.util.Arrays;import no.uib.cipr.matrix.DenseVector;import no.uib.cipr.matrix.Matrix;import no.uib.cipr.matrix.Vector;/** * Incomplete Cholesky preconditioner without fill-in using a compressed row * matrix as internal storage */public class ICC implements Preconditioner { /** * Factorisation matrix */ private final CompRowMatrix R; /** * Triangular view onto R for solution purposes */ private Matrix Rt; /** * Temporary vector for solving the factorised system */ private final Vector y; /** * Sets up the ICC preconditioner * * @param R * Matrix to use internally. For best performance, its non-zero * pattern must conform to that of the system matrix */ public ICC(CompRowMatrix R) { if (!R.isSquare()) throw new IllegalArgumentException( "ICC only applies to square matrices"); this.R = R; int n = R.numRows(); y = new DenseVector(n); } public Vector apply(Vector b, Vector x) { // R'y = b, y = R'\b Rt.transSolve(b, y); // Rx = R'\b = y return Rt.solve(y, x); } public Vector transApply(Vector b, Vector x) { return apply(b, x); } public void setMatrix(Matrix A) { R.set(A); factor(); } private void factor() { int n = R.numRows(); // Internal CRS matrix storage int[] colind = R.getColumnIndices(); int[] rowptr = R.getRowPointers(); double[] data = R.getData(); // Temporary storage of a dense row double[] Rk = new double[n]; // Find the indices to the diagonal entries int[] diagind = findDiagonalIndices(n, colind, rowptr); // Go down along the main diagonal for (int k = 0; k < n; ++k) { // Expand current row to dense storage Arrays.fill(Rk, 0); for (int i = rowptr[k]; i < rowptr[k + 1]; ++i) Rk[colind[i]] = data[i]; for (int i = 0; i < k; ++i) { // Get the current diagonal entry double Rii = data[diagind[i]]; if (Rii == 0) throw new RuntimeException("Zero pivot encountered on row " + (i + 1) + " during ICC process"); // Elimination factor double Rki = Rk[i] / Rii; if (Rki == 0) continue; // Traverse the sparse row i, reducing on row k for (int j = diagind[i] + 1; j < rowptr[i + 1]; ++j) Rk[colind[j]] -= Rki * data[j]; } // Store the row back into the factorisation matrix if (Rk[k] == 0) throw new RuntimeException( "Zero diagonal entry encountered on row " + (k + 1) + " during ICC process"); double sqRkk = Math.sqrt(Rk[k]); for (int i = diagind[k]; i < rowptr[k + 1]; ++i) data[i] = Rk[colind[i]] / sqRkk; } Rt = new UpperCompRowMatrix(R, diagind); } private int[] findDiagonalIndices(int m, int[] colind, int[] rowptr) { int[] diagind = new int[m]; for (int k = 0; k < m; ++k) { diagind[k] = no.uib.cipr.matrix.sparse.Arrays.binarySearch(colind, k, rowptr[k], rowptr[k + 1]); if (diagind[k] < 0) throw new RuntimeException("Missing diagonal entry on row " + (k + 1)); } return diagind; }}
⌨️ 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 + -