/* BiCGSTAB.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 real c_b5 = (float)-1.;
static real c_b6 = (float)1.;
static real c_b25 = (float)0.;


/* Subroutine */ int bicgstab_(n, b, x, work, ldw, iter, resid, matvec, 
	psolve, info)
integer *n;
real *b, *x, *work;
integer *ldw, *iter;
real *resid;
/* Subroutine */ int (*matvec) (), (*psolve) ();
integer *info;
{
    /* System generated locals */
    integer work_dim1, work_offset;
    real r__1;

    /* Local variables */
    static real beta;
    static integer phat, shat;
    extern doublereal getbreak_();
    static integer rtld;
    extern doublereal sdot_();
    static real omegatol, bnrm2;
    extern doublereal snrm2_();
    static integer p, r, s, t;
    static real alpha;
    static integer v;
    static real omega;
    extern /* Subroutine */ int sscal_();
    static integer maxit;
    extern /* Subroutine */ int scopy_(), saxpy_();
    static real rhotol, rho, tol, rho1;


/*  -- 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). */

/*     .. Scalar Arguments .. */
/*     .. */
/*     .. Array Arguments .. */
/*     .. */
/*     .. Function Arguments .. */
/*     .. */

/*  Purpose */
/*  ======= */

/*  BICGSTAB solves the linear system A*x = b using the */
/*  BiConjugate Gradient Stabilized 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) REAL array, dimension N. */
/*          On entry, right hand side vector B. */
/*          Unchanged on exit. */

/*  X       (input/output) REAL 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) REAL array, dimension (LDW,7) */
/*          Workspace for residual, direction vector, etc. */
/*          Note that vectors R and S shared the same workspace. */

/*  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) REAL */
/*          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. */

/*  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 b. */

/*          The call is: */

/*             CALL PSOLVE( 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, or breakdown occurred */
/*                during iteration. */

/*                Illegal 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. */
/*                  -11: OMEGA < BREAKTOL: S and T have become */
/*                                         orthogonal relative to T'*T. */

/*                  BREAKTOL is set in function GETBREAK. */

/*  BLAS CALLS: SAXPY, SCOPY, SDOT, SNRM2, SSCAL */
/*  ============================================================== */

/*     .. Parameters .. */
/*     .. */
/*     .. Local Scalars .. */
/*     .. */
/*     .. External Functions .. */
/*     .. */
/*     .. Intrinsic Functions .. */
/*     .. */
/*     .. 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. */

    r = 1;
    rtld = 2;
    p = 3;
    v = 4;
    t = 5;
    phat = 6;
    shat = 7;
    s = 1;

/*     Set parameter tolerances. */

    rhotol = getbreak_();
    omegatol = getbreak_();

/*     Set initial residual. */

    scopy_(n, &b[1], &c__1, &work[r * work_dim1 + 1], &c__1);
    if (snrm2_(n, &x[1], &c__1) != (float)0.) {
	(*matvec)(&c_b5, &x[1], &c_b6, &work[r * work_dim1 + 1]);
	if (snrm2_(n, &work[r * work_dim1 + 1], &c__1) <= tol) {
	    goto L30;
	}
    }
    scopy_(n, &work[r * work_dim1 + 1], &c__1, &work[rtld * work_dim1 + 1], &
	    c__1);

    bnrm2 = snrm2_(n, &b[1], &c__1);
    if (bnrm2 == (float)0.) {
	bnrm2 = (float)1.;
    }

    *iter = 0;

L10:

/*     Perform BiConjugate Gradient Stabilized iteration. */

    ++(*iter);

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

/*        Compute vector P. */

    if (*iter > 1) {
	beta = rho / rho1 * (alpha / omega);
	r__1 = -(doublereal)omega;
	saxpy_(n, &r__1, &work[v * work_dim1 + 1], &c__1, &work[p * work_dim1 
		+ 1], &c__1);
	sscal_(n, &beta, &work[p * work_dim1 + 1], &c__1);
	saxpy_(n, &c_b6, &work[r * work_dim1 + 1], &c__1, &work[p * work_dim1 
		+ 1], &c__1);
    } else {
	scopy_(n, &work[r * work_dim1 + 1], &c__1, &work[p * work_dim1 + 1], &
		c__1);
    }

/*        Compute direction adjusting vector PHAT and scalar ALPHA. */

    (*psolve)(&work[phat * work_dim1 + 1], &work[p * work_dim1 + 1]);
    (*matvec)(&c_b6, &work[phat * work_dim1 + 1], &c_b25, &work[v * work_dim1 
	    + 1]);
    alpha = rho / sdot_(n, &work[rtld * work_dim1 + 1], &c__1, &work[v * 
	    work_dim1 + 1], &c__1);

/*        Early check for tolerance. */

    r__1 = -(doublereal)alpha;
    saxpy_(n, &r__1, &work[v * work_dim1 + 1], &c__1, &work[r * work_dim1 + 1]
	    , &c__1);
    scopy_(n, &work[r * work_dim1 + 1], &c__1, &work[s * work_dim1 + 1], &
	    c__1);
    if (snrm2_(n, &work[s * work_dim1 + 1], &c__1) <= tol) {
	saxpy_(n, &alpha, &work[phat * work_dim1 + 1], &c__1, &x[1], &c__1);
	*resid = snrm2_(n, &work[s * work_dim1 + 1], &c__1) / bnrm2;
	goto L30;
    } else {

/*           Compute stabilizer vector SHAT and scalar OMEGA. */

	(*psolve)(&work[shat * work_dim1 + 1], &work[s * work_dim1 + 1]);
	(*matvec)(&c_b6, &work[shat * work_dim1 + 1], &c_b25, &work[t * 
		work_dim1 + 1]);
	omega = sdot_(n, &work[t * work_dim1 + 1], &c__1, &work[s * work_dim1 
		+ 1], &c__1) / sdot_(n, &work[t * work_dim1 + 1], &c__1, &
		work[t * work_dim1 + 1], &c__1);

/*           Compute new solution approximation vector X. */

	saxpy_(n, &alpha, &work[phat * work_dim1 + 1], &c__1, &x[1], &c__1);
	saxpy_(n, &omega, &work[shat * work_dim1 + 1], &c__1, &x[1], &c__1);

/*           Compute residual R, check for tolerance. */

	r__1 = -(doublereal)omega;
	saxpy_(n, &r__1, &work[t * work_dim1 + 1], &c__1, &work[r * work_dim1 
		+ 1], &c__1);
	*resid = snrm2_(n, &work[r * work_dim1 + 1], &c__1) / bnrm2;
	if (*resid <= tol) {
	    goto L30;
	}
	if (*iter == maxit) {
	    goto L20;
	}
    }

    if (dabs(omega) < omegatol) {
	goto L25;
    } else {
	rho1 = rho;
	goto L10;
    }

L20:

/*     Iteration fails. */

    *info = 1;
    return 0;

L25:

/*     Set breakdown flag. */

    if (dabs(rho) < rhotol) {
	*info = -10;
    } else if (dabs(omega) < omegatol) {
	*info = -11;
    }
    return 0;

L30:

/*     Iteration successful; return. */

    return 0;

/*     End of BICGSTAB */

} /* bicgstab_ */