/* BiCG.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 integer c__1 = 1;
static doublereal c_b5 = -1.;
static doublereal c_b6 = 0.;
static doublereal c_b28 = 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
*  =======
*
*  BiCG solves the linear system Ax = b using the
*  BiConjugate Gradient iterative method with preconditioning.
*
*  Convergence test: ( norm( b - A*x ) / norm( b ) ) < TOL.
*  For other measures, see the above reference.
*
*  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,6).
*          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.
*
*  MATVECTRANS  (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 the tranpose of a matrix A. Vector x must remain
*          unchanged.
*          The solution is over-written on vector y.
*
*          The call is:
*
*             CALL MATVECTRANS( ALPHA, X, BETA, Y )
*
*          The matrix is passed into the routine in a common block.
*
*  PSOLVE  (external subroutine)
*          The user must provide a subroutine to perform the
*          preconditioner solve routine for the linear system
*
*               M*x = b,
*
*          where x and b are vectors, and M a matrix. Vector b must
*          remain unchanged.
*          The solution is over-written on vector x.
*
*          The call is:
*
*             CALL PSOLVE( X, B )
*
*         The preconditioner is passed into the routine in a common block
*
*  PSOLVETRANS  (external subroutine)
*          The user must provide a subroutine to perform the
*          preconditioner solve routine for the linear system
*
*               M'*x = b,
*
*          where x and y are vectors, and M' is the tranpose of a
*          matrix M. Vector b must remain unchanged. The solution 
*          is over-written on vector x.
*
*          The call is:
*
*             CALL PSOLVETRANS( X, B )
*
*         The preconditioner 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.
*
*                BREAKDOWN: If parameters RHO or OMEGA become smaller
*                   than some tolerance, the program will terminate.
*                   Here we check against tolerance BREAKTOL.
*
*                  -10: RHO < BREAKTOL: RHO and RTLD have become
*                                       orthogonal.
*
*                  BREAKTOL is set in function GETBREAK.
*
*  BLAS CALLS:   DAXPY, DCOPY, DDOT, DNRM2
*  ============================================================ */

int bicg_(n, b, x, work, ldw, iter, resid, matvec, matvectrans, 
          psolve, psolvetrans, info)
   integer *n, *ldw, *iter, *info;
   doublereal *b, *x, *work, *resid;
   int (*matvec) (), (*matvectrans) (), (*psolve) (), (*psolvetrans) ();
{
    /* System generated locals */
    integer work_dim1, work_offset;
    doublereal d__1;

    /* Local variables */
    static doublereal beta;
    extern doublereal ddot_();
    static integer ptld, rtld, qtld;
    extern doublereal getbreak_();
    static integer ztld;
    static doublereal bnrm2;
    extern doublereal dnrm2_();
    static integer p, q, r;
    static doublereal alpha;
    static integer z;
    extern /* Subroutine */ int dcopy_();
    static integer maxit;
    extern /* Subroutine */ int daxpy_();
    static doublereal rhotol, rho, tol, rho1;

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

/*  Executable Statements */

    *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. */

    r = 1;
    rtld = 2;
    z = 3;
    ztld = 4;
    p = 5;
    ptld = 6;
    q = 3;
    qtld = 4;

/*     Set breakdown parameters. */

    rhotol = getbreak_();

/*     Set initial residual. */

    dcopy_(n, &b[1], &c__1, &work[r * work_dim1 + 1], &c__1);
    if (dnrm2_(n, &x[1], &c__1) != 0.) {
	(*matvec)(&c_b5, &x[1], &c_b28, &work[r * work_dim1 + 1]);
	if (dnrm2_(n, &work[r * work_dim1 + 1], &c__1) <= tol) {
	    goto L30;
	}
    }
    dcopy_(n, &work[r * work_dim1 + 1], &c__1, &work[rtld * work_dim1 + 1], &
	    c__1);
    bnrm2 = dnrm2_(n, &b[1], &c__1);
    if (bnrm2 == 0.) {
	bnrm2 = 1.;
    }

    *iter = 0;

L10:

/*     Perform BiConjugate Gradient iteration. */

    ++(*iter);

/*        Compute direction vectors PK and PTLD. */

    (*psolve)(&work[z * work_dim1 + 1], &work[r * work_dim1 + 1]);
    (*psolvetrans)(&work[ztld * work_dim1 + 1], &work[rtld * work_dim1 + 1]);

    rho = ddot_(n, &work[z * work_dim1 + 1], &c__1, &work[rtld * work_dim1 + 
	    1], &c__1);
    if (abs(rho) < rhotol) {
	goto L25;
    }

    if (*iter > 1) {
	beta = rho / rho1;
	daxpy_(n, &beta, &work[p * work_dim1 + 1], &c__1, &work[z * work_dim1 
		+ 1], &c__1);
	daxpy_(n, &beta, &work[ptld * work_dim1 + 1], &c__1, &work[ztld * 
		work_dim1 + 1], &c__1);
	dcopy_(n, &work[z * work_dim1 + 1], &c__1, &work[p * work_dim1 + 1], &
		c__1);
	dcopy_(n, &work[ztld * work_dim1 + 1], &c__1, &work[ptld * work_dim1 
		+ 1], &c__1);
    } else {
	dcopy_(n, &work[z * work_dim1 + 1], &c__1, &work[p * work_dim1 + 1], &
		c__1);
	dcopy_(n, &work[ztld * work_dim1 + 1], &c__1, &work[ptld * work_dim1 
		+ 1], &c__1);
    }

    (*matvec)(&c_b28, &work[p * work_dim1 + 1], &c_b6, &work[q * work_dim1 + 
	    1]);
    (*matvectrans)(&c_b28, &work[ptld * work_dim1 + 1], &c_b6, &work[qtld * 
	    work_dim1 + 1]);
    alpha = rho / ddot_(n, &work[ptld * work_dim1 + 1], &c__1, &work[q * 
	    work_dim1 + 1], &c__1);

/*        Compute current solution vector x. */

    daxpy_(n, &alpha, &work[p * work_dim1 + 1], &c__1, &x[1], &c__1);

/*        Compute residual vector rk, find norm, */
/*        then check for tolerance. */

    d__1 = -alpha;
    daxpy_(n, &d__1, &work[q * work_dim1 + 1], &c__1, &work[r * work_dim1 + 1]
	    , &c__1);

    *resid = dnrm2_(n, &work[r * work_dim1 + 1], &c__1) / bnrm2;
    if (*resid <= tol) {
	goto L30;
    }
    if (*iter == maxit) {
	goto L20;
    }

    d__1 = -alpha;
    daxpy_(n, &d__1, &work[qtld * work_dim1 + 1], &c__1, &work[rtld * 
	    work_dim1 + 1], &c__1);
    rho1 = rho;

    goto L10;

L20:

/*     Iteration fails. */

    *info = 1;
    return 0;

L25:

/*     Set breakdown flag. */

    *info = -10;
    return 0;

L30:

/*     Iteration successful; return. */

    return 0;

/*     End of BICG */

}
