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* -----------------------------------------------------------------
* $Revision: 1.9 $
* $Date: 2010/12/01 22:14:09 $
* -----------------------------------------------------------------
* Programmers: Alan Hindmarsh, Radu Serban and Aaron Collier @ LLNL
* -----------------------------------------------------------------
* Copyright (c) 2002, The Regents of the University of California
* Produced at the Lawrence Livermore National Laboratory
* All rights reserved
* For details, see the LICENSE file
* -----------------------------------------------------------------
* This is the common header file for the Scaled and Preconditioned
* Iterative Linear Solvers in IDA.
* -----------------------------------------------------------------
*/
#ifndef _IDASPILS_H
#define _IDASPILS_H
#ifdef __cplusplus /* wrapper to enable C++ usage */
extern "C" {
#endif
#include <sundials/sundials_iterative.h>
#include <sundials/sundials_nvector.h>
/*
* -----------------------------------------------------------------
* IDASPILS return values
* -----------------------------------------------------------------
*/
#define IDASPILS_SUCCESS 0
#define IDASPILS_MEM_NULL -1
#define IDASPILS_LMEM_NULL -2
#define IDASPILS_ILL_INPUT -3
#define IDASPILS_MEM_FAIL -4
#define IDASPILS_PMEM_NULL -5
/*
* -----------------------------------------------------------------
* Type : IDASpilsPrecSetupFn
* -----------------------------------------------------------------
* The optional user-supplied functions PrecSetup and PrecSolve
* together must define the left preconditoner matrix P
* approximating the system Jacobian matrix
* J = dF/dy + c_j*dF/dy'
* (where the DAE system is F(t,y,y') = 0), and solve the linear
* systems P z = r. PrecSetup is to do any necessary setup
* operations, and PrecSolve is to compute the solution of
* P z = r.
*
* The preconditioner setup function PrecSetup is to evaluate and
* preprocess any Jacobian-related data needed by the
* preconditioner solve function PrecSolve. This might include
* forming a crude approximate Jacobian, and performing an LU
* factorization on it. This function will not be called in
* advance of every call to PrecSolve, but instead will be called
* only as often as necessary to achieve convergence within the
* Newton iteration. If the PrecSolve function needs no
* preparation, the PrecSetup function can be NULL.
*
* Each call to the PrecSetup function is preceded by a call to
* the system function res with the same (t,y,y') arguments.
* Thus the PrecSetup function can use any auxiliary data that is
* computed and saved by the res function and made accessible
* to PrecSetup.
*
* A preconditioner setup function PrecSetup must have the
* prototype given below. Its parameters are as follows:
*
* tt is the current value of the independent variable t.
*
* yy is the current value of the dependent variable vector,
* namely the predicted value of y(t).
*
* yp is the current value of the derivative vector y',
* namely the predicted value of y'(t).
*
* rr is the current value of the residual vector F(t,y,y').
*
* c_j is the scalar in the system Jacobian, proportional to 1/hh.
*
* user_data is a pointer to user data, the same as the user_data
* parameter passed to IDASetUserData.
*
* tmp1, tmp2, tmp3 are pointers to vectors of type N_Vector
* which can be used by an IDASpilsPrecSetupFn routine
* as temporary storage or work space.
*
* NOTE: If the user's preconditioner needs other quantities,
* they are accessible as follows: hcur (the current stepsize)
* and ewt (the error weight vector) are accessible through
* IDAGetCurrentStep and IDAGetErrWeights, respectively (see
* ida.h). The unit roundoff is available as
* UNIT_ROUNDOFF defined in sundials_types.h
*
* The IDASpilsPrecSetupFn should return
* 0 if successful,
* a positive int if a recoverable error occurred, or
* a negative int if a nonrecoverable error occurred.
* In the case of a recoverable error return, the integrator will
* attempt to recover by reducing the stepsize (which changes cj).
* -----------------------------------------------------------------
*/
typedef int (*IDASpilsPrecSetupFn)(realtype tt,
N_Vector yy, N_Vector yp, N_Vector rr,
realtype c_j, void *user_data,
N_Vector tmp1, N_Vector tmp2,
N_Vector tmp3);
/*
* -----------------------------------------------------------------
* Type : IDASpilsPrecSolveFn
* -----------------------------------------------------------------
* The optional user-supplied function PrecSolve must compute a
* solution to the linear system P z = r, where P is the left
* preconditioner defined by the user. If no preconditioning
* is desired, pass NULL for PrecSolve to IDASp*.
*
* A preconditioner solve function PrecSolve must have the
* prototype given below. Its parameters are as follows:
*
* tt is the current value of the independent variable t.
*
* yy is the current value of the dependent variable vector y.
*
* yp is the current value of the derivative vector y'.
*
* rr is the current value of the residual vector F(t,y,y').
*
* rvec is the input right-hand side vector r.
*
* zvec is the computed solution vector z.
*
* c_j is the scalar in the system Jacobian, proportional to 1/hh.
*
* delta is an input tolerance for use by PrecSolve if it uses an
* iterative method in its solution. In that case, the
* the residual vector r - P z of the system should be
* made less than delta in weighted L2 norm, i.e.,
* sqrt [ Sum (Res[i]*ewt[i])^2 ] < delta .
* Note: the error weight vector ewt can be obtained
* through a call to the routine IDAGetErrWeights.
*
* user_data is a pointer to user data, the same as the user_data
* parameter passed to IDASetUserData.
*
* tmp is an N_Vector which can be used by the PrecSolve
* routine as temporary storage or work space.
*
* The IDASpilsPrecSolveFn should return
* 0 if successful,
* a positive int if a recoverable error occurred, or
* a negative int if a nonrecoverable error occurred.
* Following a recoverable error, the integrator will attempt to
* recover by updating the preconditioner and/or reducing the
* stepsize.
* -----------------------------------------------------------------
*/
typedef int (*IDASpilsPrecSolveFn)(realtype tt,
N_Vector yy, N_Vector yp, N_Vector rr,
N_Vector rvec, N_Vector zvec,
realtype c_j, realtype delta, void *user_data,
N_Vector tmp);
/*
* -----------------------------------------------------------------
* Type : IDASpilsJacTimesVecFn
* -----------------------------------------------------------------
* The user-supplied function jtimes is to generate the product
* J*v for given v, where J is the Jacobian matrix
* J = dF/dy + c_j*dF/dy'
* or an approximation to it, and v is a given vector.
* It should return 0 if successful and a nonzero int otherwise.
*
* A function jtimes must have the prototype given below. Its
* parameters are as follows:
*
* tt is the current value of the independent variable.
*
* yy is the current value of the dependent variable vector,
* namely the predicted value of y(t).
*
* yp is the current value of the derivative vector y',
* namely the predicted value of y'(t).
*
* rr is the current value of the residual vector F(t,y,y').
*
* v is the N_Vector to be multiplied by J.
*
* Jv is the output N_Vector containing J*v.
*
* c_j is the scalar in the system Jacobian, proportional
* to 1/hh.
*
* user_data is a pointer to user data, the same as the
* pointer passed to IDASetUserData.
*
* tmp1, tmp2 are two N_Vectors which can be used by Jtimes for
* work space.
* -----------------------------------------------------------------
*/
typedef int (*IDASpilsJacTimesVecFn)(realtype tt,
N_Vector yy, N_Vector yp, N_Vector rr,
N_Vector v, N_Vector Jv,
realtype c_j, void *user_data,
N_Vector tmp1, N_Vector tmp2);
/*
* -----------------------------------------------------------------
* Optional inputs to the IDASPILS linear solver
* -----------------------------------------------------------------
*
* IDASpilsSetPreconditioner specifies the PrecSetup and PrecSolve
* functions.
* Default is NULL for both arguments.
* IDASpilsSetJacTimesVecFn specifies the jtimes function.
* Default is to use an internal finite difference
* approximation routine.
* IDASpilsSetGSType specifies the type of Gram-Schmidt
* orthogonalization to be used. This must be one of
* the two enumeration constants MODIFIED_GS or
* CLASSICAL_GS defined in iterativ.h. These correspond
* to using modified Gram-Schmidt and classical
* Gram-Schmidt, respectively.
* Default value is MODIFIED_GS.
* Only for IDASPGMR.
* IDASpilsSetMaxRestarts specifies the maximum number of restarts
* to be used in the GMRES algorithm. maxrs must be a
* non-negative integer. Pass 0 to specify no restarts.
* Default is 5.
* Only for IDASPGMR.
* IDASpbcgSetMaxl specifies the maximum Krylov subspace size.
* Default is 5.
* Only for IDASPBCG and IDASPTFQMR.
* IDASpilsSetEpsLin specifies the factor in the linear iteration
* convergence test constant.
* Default is 0.05
* IDASpilsSetIncrementFactor specifies a factor in the increments
* to yy used in the difference quotient approximations
* to matrix-vector products Jv.
* Default is 1.0
*
* The return value of IDASpilsSet* is one of:
* IDASPILS_SUCCESS if successful
* IDASPILS_MEM_NULL if the ida memory was NULL
* IDASPILS_LMEM_NULL if the linear solver memory was NULL
* -----------------------------------------------------------------
*/
SUNDIALS_EXPORT int IDASpilsSetPreconditioner(void *ida_mem,
IDASpilsPrecSetupFn pset,
IDASpilsPrecSolveFn psolve);
SUNDIALS_EXPORT int IDASpilsSetJacTimesVecFn(void *ida_mem,
IDASpilsJacTimesVecFn jtv);
SUNDIALS_EXPORT int IDASpilsSetGSType(void *ida_mem, int gstype);
SUNDIALS_EXPORT int IDASpilsSetMaxRestarts(void *ida_mem, int maxrs);
SUNDIALS_EXPORT int IDASpilsSetMaxl(void *ida_mem, int maxl);
SUNDIALS_EXPORT int IDASpilsSetEpsLin(void *ida_mem, realtype eplifac);
SUNDIALS_EXPORT int IDASpilsSetIncrementFactor(void *ida_mem, realtype dqincfac);
/*
* -----------------------------------------------------------------
* Optional outputs from the IDASPILS linear solver
*----------------------------------------------------------------
*
* IDASpilsGetWorkSpace returns the real and integer workspace used
* by IDASPILS.
* IDASpilsGetNumPrecEvals returns the number of preconditioner
* evaluations, i.e. the number of calls made to PrecSetup
* with jok==FALSE.
* IDASpilsGetNumPrecSolves returns the number of calls made to
* PrecSolve.
* IDASpilsGetNumLinIters returns the number of linear iterations.
* IDASpilsGetNumConvFails returns the number of linear
* convergence failures.
* IDASpilsGetNumJtimesEvals returns the number of calls to jtimes
* IDASpilsGetNumResEvals returns the number of calls to the user
* res routine due to finite difference Jacobian times vector
* evaluation.
* IDASpilsGetLastFlag returns the last error flag set by any of
* the IDASPILS interface functions.
*
* The return value of IDASpilsGet* is one of:
* IDASPILS_SUCCESS if successful
* IDASPILS_MEM_NULL if the ida memory was NULL
* IDASPILS_LMEM_NULL if the linear solver memory was NULL
* -----------------------------------------------------------------
*/
SUNDIALS_EXPORT int IDASpilsGetWorkSpace(void *ida_mem, long int *lenrwLS, long int *leniwLS);
SUNDIALS_EXPORT int IDASpilsGetNumPrecEvals(void *ida_mem, long int *npevals);
SUNDIALS_EXPORT int IDASpilsGetNumPrecSolves(void *ida_mem, long int *npsolves);
SUNDIALS_EXPORT int IDASpilsGetNumLinIters(void *ida_mem, long int *nliters);
SUNDIALS_EXPORT int IDASpilsGetNumConvFails(void *ida_mem, long int *nlcfails);
SUNDIALS_EXPORT int IDASpilsGetNumJtimesEvals(void *ida_mem, long int *njvevals);
SUNDIALS_EXPORT int IDASpilsGetNumResEvals(void *ida_mem, long int *nrevalsLS);
SUNDIALS_EXPORT int IDASpilsGetLastFlag(void *ida_mem, long int *flag);
/*
* -----------------------------------------------------------------
* The following function returns the name of the constant
* associated with an IDASPILS return flag
* -----------------------------------------------------------------
*/
SUNDIALS_EXPORT char *IDASpilsGetReturnFlagName(long int flag);
#ifdef __cplusplus
}
#endif
#endif
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