/*
    This file implements QMRCGS (QMRCGStab).
*/
#include <../src/ksp/ksp/impls/bcgs/bcgsimpl.h> /*I  "petscksp.h"  I*/

static PetscErrorCode KSPSetUp_QMRCGS(KSP ksp)
{
  PetscFunctionBegin;
  PetscCall(KSPSetWorkVecs(ksp, 14));
  PetscFunctionReturn(PETSC_SUCCESS);
}

/* Only need a few hacks from KSPSolve_BCGS */

static PetscErrorCode KSPSolve_QMRCGS(KSP ksp)
{
  PetscInt    i;
  PetscScalar eta, rho1, rho2, alpha, eta2, omega, beta, cf, cf1, uu;
  Vec         X, B, R, P, PH, V, D2, X2, S, SH, T, D, S2, RP, AX, Z;
  PetscReal   dp   = 0.0, final, tau, tau2, theta, theta2, c, F, NV, vv;
  KSP_BCGS   *bcgs = (KSP_BCGS *)ksp->data;
  PC          pc;
  Mat         mat;

  PetscFunctionBegin;
  X  = ksp->vec_sol;
  B  = ksp->vec_rhs;
  R  = ksp->work[0];
  P  = ksp->work[1];
  PH = ksp->work[2];
  V  = ksp->work[3];
  D2 = ksp->work[4];
  X2 = ksp->work[5];
  S  = ksp->work[6];
  SH = ksp->work[7];
  T  = ksp->work[8];
  D  = ksp->work[9];
  S2 = ksp->work[10];
  RP = ksp->work[11];
  AX = ksp->work[12];
  Z  = ksp->work[13];

  /*  Only supports right preconditioning */
  PetscCheck(ksp->pc_side == PC_RIGHT, PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "KSP qmrcgs does not support %s", PCSides[ksp->pc_side]);
  if (!ksp->guess_zero) {
    if (!bcgs->guess) PetscCall(VecDuplicate(X, &bcgs->guess));
    PetscCall(VecCopy(X, bcgs->guess));
  } else {
    PetscCall(VecSet(X, 0.0));
  }

  /* Compute initial residual */
  PetscCall(KSPGetPC(ksp, &pc));
  PetscCall(PCGetOperators(pc, &mat, NULL));
  if (!ksp->guess_zero) {
    PetscCall(KSP_MatMult(ksp, mat, X, S2));
    PetscCall(VecCopy(B, R));
    PetscCall(VecAXPY(R, -1.0, S2));
  } else {
    PetscCall(VecCopy(B, R));
  }

  /* Test for nothing to do */
  if (ksp->normtype != KSP_NORM_NONE) PetscCall(VecNorm(R, NORM_2, &dp));
  PetscCall(PetscObjectSAWsTakeAccess((PetscObject)ksp));
  ksp->its   = 0;
  ksp->rnorm = dp;
  PetscCall(PetscObjectSAWsGrantAccess((PetscObject)ksp));
  PetscCall(KSPLogResidualHistory(ksp, dp));
  PetscCall(KSPMonitor(ksp, 0, dp));
  PetscCall((*ksp->converged)(ksp, 0, dp, &ksp->reason, ksp->cnvP));
  if (ksp->reason) PetscFunctionReturn(PETSC_SUCCESS);

  /* Make the initial Rp == R */
  PetscCall(VecCopy(R, RP));

  eta   = 1.0;
  theta = 1.0;
  if (dp == 0.0) {
    PetscCall(VecNorm(R, NORM_2, &tau));
  } else {
    tau = dp;
  }

  PetscCall(VecDot(RP, RP, &rho1));
  PetscCall(VecCopy(R, P));

  i = 0;
  do {
    PetscCall(KSP_PCApply(ksp, P, PH));      /*  ph <- K p */
    PetscCall(KSP_MatMult(ksp, mat, PH, V)); /* v <- A ph */

    PetscCall(VecDot(V, RP, &rho2)); /* rho2 <- (v,rp) */
    if (rho2 == 0.0) {
      PetscCheck(!ksp->errorifnotconverged, PetscObjectComm((PetscObject)ksp), PETSC_ERR_NOT_CONVERGED, "KSPSolve has not converged due to division by zero");
      ksp->reason = KSP_DIVERGED_NANORINF;
      break;
    }

    if (rho1 == 0) {
      PetscCheck(!ksp->errorifnotconverged, PetscObjectComm((PetscObject)ksp), PETSC_ERR_NOT_CONVERGED, "KSPSolve has stagnated");
      ksp->reason = KSP_DIVERGED_BREAKDOWN; /* Stagnation */
      break;
    }

    alpha = rho1 / rho2;
    PetscCall(VecWAXPY(S, -alpha, V, R)); /* s <- r - alpha v */

    /* First quasi-minimization step */
    PetscCall(VecNorm(S, NORM_2, &F)); /* f <- norm(s) */
    theta2 = F / tau;

    c = 1.0 / PetscSqrtReal(1.0 + theta2 * theta2);

    tau2 = tau * theta2 * c;
    eta2 = c * c * alpha;
    cf   = theta * theta * eta / alpha;
    PetscCall(VecWAXPY(D2, cf, D, PH));   /* d2 <- ph + cf d */
    PetscCall(VecWAXPY(X2, eta2, D2, X)); /* x2 <- x + eta2 d2 */

    /* Apply the right preconditioner again */
    PetscCall(KSP_PCApply(ksp, S, SH));      /*  sh <- K s */
    PetscCall(KSP_MatMult(ksp, mat, SH, T)); /* t <- A sh */

    PetscCall(VecDotNorm2(S, T, &uu, &vv));
    if (vv == 0.0) {
      PetscCall(VecDot(S, S, &uu));
      if (uu != 0.0) {
        PetscCheck(!ksp->errorifnotconverged, PetscObjectComm((PetscObject)ksp), PETSC_ERR_NOT_CONVERGED, "KSPSolve has not converged due to division by zero");
        ksp->reason = KSP_DIVERGED_NANORINF;
        break;
      }
      PetscCall(VecAXPY(X, alpha, SH)); /* x <- x + alpha sh */
      PetscCall(PetscObjectSAWsTakeAccess((PetscObject)ksp));
      ksp->its++;
      ksp->rnorm  = 0.0;
      ksp->reason = KSP_CONVERGED_RTOL;
      PetscCall(PetscObjectSAWsGrantAccess((PetscObject)ksp));
      PetscCall(KSPLogResidualHistory(ksp, dp));
      PetscCall(KSPMonitor(ksp, i + 1, 0.0));
      break;
    }
    PetscCall(VecNorm(V, NORM_2, &NV)); /* nv <- norm(v) */

    if (NV == 0) {
      PetscCheck(!ksp->errorifnotconverged, PetscObjectComm((PetscObject)ksp), PETSC_ERR_NOT_CONVERGED, "KSPSolve has not converged due to singular matrix");
      ksp->reason = KSP_DIVERGED_BREAKDOWN;
      break;
    }

    if (uu == 0) {
      PetscCheck(!ksp->errorifnotconverged, PetscObjectComm((PetscObject)ksp), PETSC_ERR_NOT_CONVERGED, "KSPSolve has stagnated");
      ksp->reason = KSP_DIVERGED_BREAKDOWN; /* Stagnation */
      break;
    }
    omega = uu / vv; /* omega <- uu/vv; */

    /* Computing the residual */
    PetscCall(VecWAXPY(R, -omega, T, S)); /* r <- s - omega t */

    /* Second quasi-minimization step */
    if (ksp->normtype != KSP_NORM_NONE && ksp->chknorm < i + 2) PetscCall(VecNorm(R, NORM_2, &dp));

    if (tau2 == 0) {
      PetscCheck(!ksp->errorifnotconverged, PetscObjectComm((PetscObject)ksp), PETSC_ERR_NOT_CONVERGED, "KSPSolve has not converged due to division by zero");
      ksp->reason = KSP_DIVERGED_NANORINF;
      break;
    }
    theta = dp / tau2;
    c     = 1.0 / PetscSqrtReal(1.0 + theta * theta);
    if (dp == 0.0) {
      PetscCall(VecNorm(R, NORM_2, &tau));
    } else {
      tau = dp;
    }
    tau = tau * c;
    eta = c * c * omega;

    cf1 = theta2 * theta2 * eta2 / omega;
    PetscCall(VecWAXPY(D, cf1, D2, SH)); /* d <- sh + cf1 d2 */
    PetscCall(VecWAXPY(X, eta, D, X2));  /* x <- x2 + eta d */

    PetscCall(VecDot(R, RP, &rho2));
    PetscCall(PetscObjectSAWsTakeAccess((PetscObject)ksp));
    ksp->its++;
    ksp->rnorm = dp;
    PetscCall(PetscObjectSAWsGrantAccess((PetscObject)ksp));
    PetscCall(KSPLogResidualHistory(ksp, dp));
    PetscCall(KSPMonitor(ksp, i + 1, dp));

    beta = (alpha * rho2) / (omega * rho1);
    PetscCall(VecAXPBYPCZ(P, 1.0, -omega * beta, beta, R, V)); /* p <- r - omega * beta* v + beta * p */
    rho1 = rho2;
    PetscCall(KSP_MatMult(ksp, mat, X, AX)); /* Ax <- A x */
    PetscCall(VecWAXPY(Z, -1.0, AX, B));     /* r <- b - Ax */
    PetscCall(VecNorm(Z, NORM_2, &final));
    PetscCall((*ksp->converged)(ksp, i + 1, dp, &ksp->reason, ksp->cnvP));
    if (ksp->reason) break;
    i++;
  } while (i < ksp->max_it);

  /* mark lack of convergence */
  if (ksp->its >= ksp->max_it && !ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
  PetscFunctionReturn(PETSC_SUCCESS);
}

/*MC
   KSPQMRCGS - Implements the QMRCGStab method {cite}`chan1994qmrcgs` and Ghai, Lu, and Jiao (NLAA 2019).

   Level: beginner

   Note:
   Only right preconditioning is supported.

   Contributed by:
   Xiangmin Jiao (xiangmin.jiao@stonybrook.edu)

.seealso: [](ch_ksp), `KSPCreate()`, `KSPSetType()`, `KSPType`, `KSP`, `KSPBICG`, `KSPFBICGS`, `KSPBCGSL`, `KSPSetPCSide()`
M*/
PETSC_EXTERN PetscErrorCode KSPCreate_QMRCGS(KSP ksp)
{
  KSP_BCGS         *bcgs;
  static const char citations[] = "@article{chan1994qmrcgs,\n"
                                  "  title={A quasi-minimal residual variant of the {Bi-CGSTAB} algorithm for nonsymmetric systems},\n"
                                  "  author={Chan, Tony F and Gallopoulos, Efstratios and Simoncini, Valeria and Szeto, Tedd and Tong, Charles H},\n"
                                  "  journal={SIAM Journal on Scientific Computing},\n"
                                  "  volume={15},\n"
                                  "  number={2},\n"
                                  "  pages={338--347},\n"
                                  "  year={1994},\n"
                                  "  publisher={SIAM}\n"
                                  "}\n"
                                  "@article{ghai2019comparison,\n"
                                  "  title={A comparison of preconditioned {K}rylov subspace methods for large-scale nonsymmetric linear systems},\n"
                                  "  author={Ghai, Aditi and Lu, Cao and Jiao, Xiangmin},\n"
                                  "  journal={Numerical Linear Algebra with Applications},\n"
                                  "  volume={26},\n"
                                  "  number={1},\n"
                                  "  pages={e2215},\n"
                                  "  year={2019},\n"
                                  "  publisher={Wiley Online Library}\n"
                                  "}\n";
  PetscBool         cite        = PETSC_FALSE;

  PetscFunctionBegin;
  PetscCall(PetscCitationsRegister(citations, &cite));
  PetscCall(PetscNew(&bcgs));

  ksp->data                = bcgs;
  ksp->ops->setup          = KSPSetUp_QMRCGS;
  ksp->ops->solve          = KSPSolve_QMRCGS;
  ksp->ops->destroy        = KSPDestroy_BCGS;
  ksp->ops->reset          = KSPReset_BCGS;
  ksp->ops->buildresidual  = KSPBuildResidualDefault;
  ksp->ops->setfromoptions = KSPSetFromOptions_BCGS;
  ksp->pc_side             = PC_RIGHT; /* set default PC side */

  PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_UNPRECONDITIONED, PC_RIGHT, 2));
  PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_NONE, PC_RIGHT, 1));
  PetscFunctionReturn(PETSC_SUCCESS);
}
