277 lines
6.0 KiB
C
277 lines
6.0 KiB
C
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/*
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* matrix.h, matrix.c: Liner equation solver using LU decomposition.
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* $Id: matrix.c,v 1.4 2001/11/16 22:02:00 ukai Exp $
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*
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* by K.Okabe Aug. 1999
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*
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* LUfactor, LUsolve, Usolve and Lsolve, are based on the functions in
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* Meschach Library Version 1.2b.
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*/
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/**************************************************************************
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**
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** Copyright (C) 1993 David E. Steward & Zbigniew Leyk, all rights reserved.
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**
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** Meschach Library
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**
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** This Meschach Library is provided "as is" without any express
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** or implied warranty of any kind with respect to this software.
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** In particular the authors shall not be liable for any direct,
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** indirect, special, incidental or consequential damages arising
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** in any way from use of the software.
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**
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** Everyone is granted permission to copy, modify and redistribute this
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** Meschach Library, provided:
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** 1. All copies contain this copyright notice.
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** 2. All modified copies shall carry a notice stating who
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** made the last modification and the date of such modification.
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** 3. No charge is made for this software or works derived from it.
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** This clause shall not be construed as constraining other software
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** distributed on the same medium as this software, nor is a
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** distribution fee considered a charge.
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**
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***************************************************************************/
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#include "config.h"
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#include "matrix.h"
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#include "gc.h"
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/*
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* Macros from "fm.h".
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*/
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#define New(type) ((type*)GC_MALLOC(sizeof(type)))
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#define NewAtom(type) ((type*)GC_MALLOC_ATOMIC(sizeof(type)))
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#define New_N(type,n) ((type*)GC_MALLOC((n)*sizeof(type)))
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#define NewAtom_N(type,n) ((type*)GC_MALLOC_ATOMIC((n)*sizeof(type)))
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#define Renew_N(type,ptr,n) ((type*)GC_REALLOC((ptr),(n)*sizeof(type)))
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#define SWAPD(a,b) { double tmp = a; a = b; b = tmp; }
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#define SWAPI(a,b) { int tmp = a; a = b; b = tmp; }
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#ifdef HAVE_FLOAT_H
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#include <float.h>
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#endif /* not HAVE_FLOAT_H */
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#if defined(DBL_MAX)
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static double Tiny = 10.0 / DBL_MAX;
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#elif defined(FLT_MAX)
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static double Tiny = 10.0 / FLT_MAX;
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#else /* not defined(FLT_MAX) */
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static double Tiny = 1.0e-30;
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#endif /* not defined(FLT_MAX */
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/*
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* LUfactor -- gaussian elimination with scaled partial pivoting
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* -- Note: returns LU matrix which is A.
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*/
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int
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LUfactor(Matrix A, int *index)
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{
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int dim = A->dim, i, j, k, i_max, k_max;
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Vector scale;
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double mx, tmp;
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scale = new_vector(dim);
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for (i = 0; i < dim; i++)
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index[i] = i;
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for (i = 0; i < dim; i++) {
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mx = 0.;
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for (j = 0; j < dim; j++) {
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tmp = fabs(M_VAL(A, i, j));
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if (mx < tmp)
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mx = tmp;
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}
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scale->ve[i] = mx;
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}
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k_max = dim - 1;
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for (k = 0; k < k_max; k++) {
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mx = 0.;
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i_max = -1;
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for (i = k; i < dim; i++) {
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if (fabs(scale->ve[i]) >= Tiny * fabs(M_VAL(A, i, k))) {
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tmp = fabs(M_VAL(A, i, k)) / scale->ve[i];
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if (mx < tmp) {
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mx = tmp;
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i_max = i;
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}
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}
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}
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if (i_max == -1) {
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M_VAL(A, k, k) = 0.;
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continue;
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}
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if (i_max != k) {
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SWAPI(index[i_max], index[k]);
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for (j = 0; j < dim; j++)
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SWAPD(M_VAL(A, i_max, j), M_VAL(A, k, j));
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}
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for (i = k + 1; i < dim; i++) {
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tmp = M_VAL(A, i, k) = M_VAL(A, i, k) / M_VAL(A, k, k);
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for (j = k + 1; j < dim; j++)
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M_VAL(A, i, j) -= tmp * M_VAL(A, k, j);
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}
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}
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return 0;
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}
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/*
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* LUsolve -- given an LU factorisation in A, solve Ax=b.
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*/
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int
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LUsolve(Matrix A, int *index, Vector b, Vector x)
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{
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int i, dim = A->dim;
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for (i = 0; i < dim; i++)
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x->ve[i] = b->ve[index[i]];
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if (Lsolve(A, x, x, 1.) == -1 || Usolve(A, x, x, 0.) == -1)
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return -1;
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return 0;
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}
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/* m_inverse -- returns inverse of A, provided A is not too rank deficient
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* * * * * * * -- uses LU factorisation */
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#if 0
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Matrix
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m_inverse(Matrix A, Matrix out)
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{
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int *index = NewAtom_N(int, A->dim);
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Matrix A1 = new_matrix(A->dim);
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m_copy(A, A1);
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LUfactor(A1, index);
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return LUinverse(A1, index, out);
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}
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#endif /* 0 */
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Matrix
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LUinverse(Matrix A, int *index, Matrix out)
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{
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int i, j, dim = A->dim;
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Vector tmp, tmp2;
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if (!out)
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out = new_matrix(dim);
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tmp = new_vector(dim);
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tmp2 = new_vector(dim);
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for (i = 0; i < dim; i++) {
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for (j = 0; j < dim; j++)
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tmp->ve[j] = 0.;
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tmp->ve[i] = 1.;
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if (LUsolve(A, index, tmp, tmp2) == -1)
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return NULL;
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for (j = 0; j < dim; j++)
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M_VAL(out, j, i) = tmp2->ve[j];
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}
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return out;
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}
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/*
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* Usolve -- back substitution with optional over-riding diagonal
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* -- can be in-situ but doesn't need to be.
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*/
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int
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Usolve(Matrix mat, Vector b, Vector out, double diag)
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{
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int i, j, i_lim, dim = mat->dim;
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double sum;
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for (i = dim - 1; i >= 0; i--) {
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if (b->ve[i] != 0.)
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break;
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else
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out->ve[i] = 0.;
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}
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i_lim = i;
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for (; i >= 0; i--) {
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sum = b->ve[i];
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for (j = i + 1; j <= i_lim; j++)
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sum -= M_VAL(mat, i, j) * out->ve[j];
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if (diag == 0.) {
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if (fabs(M_VAL(mat, i, i)) <= Tiny * fabs(sum))
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return -1;
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else
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out->ve[i] = sum / M_VAL(mat, i, i);
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}
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else
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out->ve[i] = sum / diag;
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}
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return 0;
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}
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/*
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* Lsolve -- forward elimination with (optional) default diagonal value.
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*/
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int
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Lsolve(Matrix mat, Vector b, Vector out, double diag)
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{
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int i, j, i_lim, dim = mat->dim;
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double sum;
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for (i = 0; i < dim; i++) {
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if (b->ve[i] != 0.)
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break;
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else
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out->ve[i] = 0.;
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}
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i_lim = i;
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for (; i < dim; i++) {
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sum = b->ve[i];
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for (j = i_lim; j < i; j++)
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sum -= M_VAL(mat, i, j) * out->ve[j];
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if (diag == 0.) {
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if (fabs(M_VAL(mat, i, i)) <= Tiny * fabs(sum))
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return -1;
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else
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out->ve[i] = sum / M_VAL(mat, i, i);
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}
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else
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out->ve[i] = sum / diag;
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}
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return 0;
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}
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/*
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* new_matrix -- generate a nxn matrix.
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*/
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Matrix
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new_matrix(int n)
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{
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Matrix mat;
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mat = New(struct matrix);
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mat->dim = n;
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mat->me = NewAtom_N(double, n * n);
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return mat;
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}
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/*
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* new_matrix -- generate a n-dimension vector.
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*/
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Vector
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new_vector(int n)
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{
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Vector vec;
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vec = New(struct vector);
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vec->dim = n;
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vec->ve = NewAtom_N(double, n);
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return vec;
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}
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