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📄 ilu.java

📁 另一个功能更强大的矩阵运算软件开源代码
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/* * 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 no.uib.cipr.matrix.DenseVector;import no.uib.cipr.matrix.Matrix;import no.uib.cipr.matrix.Vector;/** * ILU(0) preconditioner using a compressed row matrix as internal storage */public class ILU implements Preconditioner {    /**     * Factorisation matrix     */    private final CompRowMatrix LU;    /**     * The L and U factors     */    private Matrix L, U;    /**     * Temporary vector for solving the factorised system     */    private final Vector y;    /**     * Sets up the ILU preconditioner     *      * @param LU     *            Matrix to use internally. For best performance, its non-zero     *            pattern must conform to that of the system matrix     */    public ILU(CompRowMatrix LU) {        if (!LU.isSquare())            throw new IllegalArgumentException(                    "ILU only applies to square matrices");        this.LU = LU;        int n = LU.numRows();        y = new DenseVector(n);    }    public Vector apply(Vector b, Vector x) {        // Ly = b, y = L\b        L.solve(b, y);        // Ux = L\b = y        return U.solve(y, x);    }    public Vector transApply(Vector b, Vector x) {        // U'y = b, y = U'\b        U.transSolve(b, y);        // L'x = U'\b = y        return L.transSolve(y, x);    }    public void setMatrix(Matrix A) {        LU.set(A);        factor();    }    private void factor() {        int n = LU.numRows();        // Internal CRS matrix storage        int[] colind = LU.getColumnIndices();        int[] rowptr = LU.getRowPointers();        double[] data = LU.getData();        // Find the indices to the diagonal entries        int[] diagind = findDiagonalIndices(n, colind, rowptr);        // Go down along the main diagonal        for (int k = 1; k < n; ++k)            for (int i = rowptr[k]; i < diagind[k]; ++i) {                // Get the current diagonal entry                int index = colind[i];                double LUii = data[diagind[index]];                if (LUii == 0)                    throw new RuntimeException("Zero pivot encountered on row "                            + (i + 1) + " during ILU process");                // Elimination factor                double LUki = (data[i] /= LUii);                // Traverse the sparse row i, reducing on row k                for (int j = diagind[index] + 1, l = rowptr[k] + 1; j < rowptr[index + 1]; ++j) {                    while (l < rowptr[k + 1] && colind[l] < colind[j])                        l++;                    if (colind[l] == colind[j])                        data[l] -= LUki * data[j];                }            }        L = new UnitLowerCompRowMatrix(LU, diagind);        U = new UpperCompRowMatrix(LU, diagind);    }    private int[] findDiagonalIndices(int m, int[] colind, int[] rowptr) {        int[] diagind = new int[m];        for (int k = 0; k < m; ++k) {            diagind[k] = 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;    }}

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