/* Jacobi.f -- translated by f2c (version of 20 August 1993  13:15:44).
   You must link the resulting object file with the libraries:
	-lf2c -lm   (in that order)
*/

#include "f2c.h"

/* Table of constant values */

static doublereal c_b2 = 1.;
static integer c__1 = 1;
static doublereal c_b13 = -1.;

/*  -- Iterative template routine --
*     Univ. of Tennessee and Oak Ridge National Laboratory
*     October 1, 1993
*     Details of this algorithm are described in "Templates for the
*     Solution of Linear Systems: Building Blocks for Iterative
*     Methods", Barrett, Berry, Chan, Demmel, Donato, Dongarra,
*     Eijkhout, Pozo, Romine, and van der Vorst, SIAM Publications,
*     1993. (ftp netlib2.cs.utk.edu; cd linalg; get templates.ps).
*
*  Purpose
*  =======
*
*  JACOBI solves the linear system Ax = b using the Jacobi iterative
*  method. The matrix splitting should be accomplished before calling
*  this routine. The diagonal elements of the matrix must be passed into
*  this routine in the first column of matrix WORK.
*
*  Relative error measured: norm( X - X_1 ) / norm( X ).
*
*  Arguments
*  =========
*
*  N       (input) INTEGER.
*          On entry, the dimension of the matrix.
*          Unchanged on exit.
*
*  B       (input) DOUBLE PRECISION array, dimension N.
*          On entry, right hand side vector B.
*          Unchanged on exit.
*
*  X       (input/output) DOUBLE PRECISION array, dimension N.
*          On input, the initial guess. This is commonly set to
*          the zero vector.
*          On exit, if INFO = 0, the iterated approximate solution.
*
*  WORK    (workspace) DOUBLE PRECISION array, dimension (LDW,4).
*          Workspace for residual, direction vector, etc.
*
*  LDW     (input) INTEGER
*          The leading dimension of the array WORK. LDW >= max(1,N).
*
*  ITER    (input/output) INTEGER
*          On input, the maximum iterations to be performed.
*          On output, actual number of iterations performed.
*
*  RESID   (input/output) DOUBLE PRECISION
*          On input, the allowable convergence measure for
*          norm( b - A*x ) / norm( b ).
*          On output, the final value of this measure.
*
*  MATVEC  (external subroutine)
*          The user must provide a subroutine to perform the
*          matrix-vector product
*
*               y := alpha*A*x + beta*y,
*
*          where alpha and beta are scalars, x and y are vectors,
*          and A is a matrix. Vector x must remain unchanged.
*          The solution is over-written on vector y.
*
*          The call is:
*
*             CALL MATVEC( ALPHA, X, BETA, Y )
*
*          The matrix is passed into the routine in a common block.
*
*  INFO    (output) INTEGER
*
*          =  0: Successful exit. Iterated approximate solution returned.
*
*
*          >  0: Convergence to tolerance not achieved. This will be
*                set to the number of iterations performed.
*
*          <  0: Illegal input parameter.
*
*                   -1: matrix dimension N < 0
*                   -2: LDW < N
*                   -3: Maximum number of iterations ITER <= 0.
*
*  BLAS CALLS:   DAXPY, DCOPY, DNRM2
*  ============================================================ */

int jacobi_(n, b, x, work, ldw, iter, resid, matvec, info)

   integer *n, *ldw, *iter, *info;
   doublereal *b, *x, *work, *resid;
   int (*matvec) ();
{
    /* System generated locals */
    integer work_dim1, work_offset, i__1;

    /* Local variables */
    static integer temp;
    extern /* Subroutine */ int matsplit_();
    extern doublereal dnrm2_();
    static integer i;
    extern /* Subroutine */ int dcopy_();
    static integer maxit;
    extern /* Subroutine */ int daxpy_();
    static integer x1, mm;
    static doublereal tol;

/*     .. Executable Statements .. */

    /* Parameter adjustments */
    work_dim1 = *ldw;
    work_offset = work_dim1 + 1;
    work -= work_offset;
    --x;
    --b;

    /* Function Body */
    *info = 0;

/*     Test the input parameters. */

    if (*n < 0) {
	*info = -1;
    } else if (*ldw < max(1,*n)) {
	*info = -2;
    } else if (*iter <= 0) {
	*info = -3;
    }
    if (*info != 0) {
	return 0;
    }

    maxit = *iter;
    tol = *resid;

/*     Alias workspace columns. */

    mm = 1;
    x1 = 2;
    temp = 3;

    *iter = 0;

/*     Form matrix splitting inv(M) and N. */

    matsplit_(&c_b2, &b[1], &work[mm * work_dim1 + 1], ldw, "JACOBI", "SPLIT",
	     6L, 5L);

L10:

/*        Perform Jacobi iteration */

    ++(*iter);

/*        Save the current approximation to X in X1. */

    dcopy_(n, &x[1], &c__1, &work[x1 * work_dim1 + 1], &c__1);

/*        Apply iteration; result is updated approximation vector x. */

    dcopy_(n, &b[1], &c__1, &work[temp * work_dim1 + 1], &c__1);
    (*matvec)(&c_b2, &x[1], &c_b2, &work[temp * work_dim1 + 1]);
    i__1 = *n;
    for (i = 1; i <= i__1; ++i) {
	x[i] = work[i + mm * work_dim1] * work[i + temp * work_dim1];
/* L15: */
    }

/*        Compute error and check for acceptable convergence. */

    daxpy_(n, &c_b13, &x[1], &c__1, &work[x1 * work_dim1 + 1], &c__1);
    *resid = dnrm2_(n, &work[x1 * work_dim1 + 1], &c__1) / dnrm2_(n, &x[1], &
	    c__1);

    if (*resid <= tol) {
	goto L30;
    }
    if (*iter == maxit) {
	goto L20;
    }

    goto L10;

L20:

/*     Iteration fails */

    *info = 1;
    goto L30;

L30:

/*     Iteration successful. Reconstruct matrix A. */

    matsplit_(&c_b2, &b[1], &work[mm * work_dim1 + 1], ldw, "JACOBI", "RECON\
STRUCT", 6L, 11L);

    return 0;

/*     End of JACOBI */

}