/usr/include/cvodes/cvodes_sparse.h is in libsundials-dev 2.7.0+dfsg-2build1.
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* -----------------------------------------------------------------
* $Revision: 4488 $
* $Date: 2015-04-29 16:39:48 -0700 (Wed, 29 Apr 2015) $
* -----------------------------------------------------------------
* Programmer: Carol S. Woodward @ LLNL
* -----------------------------------------------------------------
* LLNS Copyright Start
* Copyright (c) 2014, Lawrence Livermore National Security
* This work was performed under the auspices of the U.S. Department
* of Energy by Lawrence Livermore National Laboratory in part under
* Contract W-7405-Eng-48 and in part under Contract DE-AC52-07NA27344.
* Produced at the Lawrence Livermore National Laboratory.
* All rights reserved.
* For details, see the LICENSE file.
* LLNS Copyright End
* -----------------------------------------------------------------
* This is the header file for the Sparse linear solver module in CVODES.
* -----------------------------------------------------------------
*/
#ifndef _CVSSPARSE_H
#define _CVSSPARSE_H
#include <sundials/sundials_sparse.h>
#include <sundials/sundials_nvector.h>
#ifdef __cplusplus /* wrapper to enable C++ usage */
extern "C" {
#endif
/*
* =================================================================
* C V S S P A R S E C O N S T A N T S
* =================================================================
*/
/*
* -----------------------------------------------------------------
* CVSSPARSE return values
* -----------------------------------------------------------------
*/
#define CVSLS_SUCCESS 0
#define CVSLS_MEM_NULL -1
#define CVSLS_LMEM_NULL -2
#define CVSLS_ILL_INPUT -3
#define CVSLS_MEM_FAIL -4
#define CVSLS_JAC_NOSET -5
#define CVSLS_PACKAGE_FAIL -6
/* Additional last_flag values */
#define CVSLS_JACFUNC_UNRECVR -7
#define CVSLS_JACFUNC_RECVR -8
/* Return values for the adjoint module */
#define CVSLS_NO_ADJ -101
#define CVSLS_LMEMB_NULL -102
/*
* =================================================================
* PART I: F O R W A R D P R O B L E M S
* =================================================================
*/
/*
* -----------------------------------------------------------------
* FUNCTION TYPES
* -----------------------------------------------------------------
*/
/*
* -----------------------------------------------------------------
* Types : CVSlsSparseJacFn
* -----------------------------------------------------------------
*
* A sparse Jacobian approximation function jac must be of type
* CVSlsSparseJacFn.
* Its parameters are:
*
* t is the current value of the independent variable t.
*
* y is the current value of the dependent variable vector,
* namely the predicted value of y(t).
*
* fy is the vector f(t,y).
* namely the predicted value of y'(t).
*
* JacMat is the compressed sparse column matrix (of type SlsMat)
* to be loaded by an CVSlsSparseJacFn routine with an approximation
* to the system Jacobian matrix
* J = J = (df_i/dy_j) at the point (t,y).
* Note that JacMat is NOT preset to zero!
* Matrix data is for the nonzero entries of the Jacobian stored in
* compressed column format. Row indices of entries in
* column j are stored in J->rowvals[colptrs[j]]
* through J->rowvals[colptrs[j+i]-1]
* and corresponding numerical values of the Jacobian are stored
* in the same entries of J->data.
*
* J_data is a pointer to user Jacobian data - the same as the
* user_data parameter passed to CVodeSetFdata.
*
* tmp1, tmp2, tmp3 are pointers to memory allocated for
* N_Vectors which can be used by an CVSparseJacFn routine
* as temporary storage or work space.
*
* A CVSlsSparseJacFn should return
* 0 if successful,
* a positive int if a recoverable error occurred, or
* a negative int if a nonrecoverable error occurred.
*
* -----------------------------------------------------------------
*
* NOTE: If the user's Jacobian routine needs other quantities,
* they are accessible as follows: hcur (the current stepsize)
* and ewt (the error weight vector) are accessible through
* CVodeGetCurrentStep and CVodeGetErrWeights, respectively
* (see cvode.h). The unit roundoff is available as
* UNIT_ROUNDOFF defined in sundials_types.h.
*
* -----------------------------------------------------------------
*/
typedef int (*CVSlsSparseJacFn)(realtype t,
N_Vector y, N_Vector fy,
SlsMat JacMat, void *user_data,
N_Vector tmp1, N_Vector tmp2, N_Vector tmp3);
/*
* =================================================================
* E X P O R T E D F U N C T I O N S
* =================================================================
*/
/*
* -----------------------------------------------------------------
* Optional inputs to the CVSPARSE linear solver
* -----------------------------------------------------------------
* CVSlsSetSparseJacFn specifies the Jacobian approximation
* routine to be used for a sparse direct linear solver.
*
* The return value is one of:
* CVSLS_SUCCESS if successful
* CVSLS_MEM_NULL if the CVODE memory was NULL
* CVSLS_LMEM_NULL if the linear solver memory was NULL
* -----------------------------------------------------------------
*/
SUNDIALS_EXPORT int CVSlsSetSparseJacFn(void *cvode_mem, CVSlsSparseJacFn jac);
/*
* -----------------------------------------------------------------
* Optional outputs from the CVSLS linear solver
* -----------------------------------------------------------------
*
* CVSlsGetNumJacEvals returns the number of calls made to the
* Jacobian evaluation routine jac.
* CVSlsGetLastFlag returns the last error flag set by any of
* the CVSLS interface functions.
*
* The return value of CVSlsGet* is one of:
* CVSLS_SUCCESS if successful
* CVSLS_MEM_NULL if the IDA memory was NULL
* CVSLS_LMEM_NULL if the linear solver memory was NULL
* -----------------------------------------------------------------
*/
SUNDIALS_EXPORT int CVSlsGetNumJacEvals(void *cvode_mem, long int *njevals);
SUNDIALS_EXPORT int CVSlsGetLastFlag(void *cvode_mem, long int *flag);
/*
* -----------------------------------------------------------------
* The following function returns the name of the constant
* associated with a CVSLS return flag
* -----------------------------------------------------------------
*/
SUNDIALS_EXPORT char *CVSlsGetReturnFlagName(long int flag);
/*
* =================================================================
* PART II: B A C K W A R D P R O B L E M S
* =================================================================
*/
/*
* -----------------------------------------------------------------
* FUNCTION TYPES
* -----------------------------------------------------------------
*/
/*
* -----------------------------------------------------------------
* Type: CVSlsSparseJacFnB
* -----------------------------------------------------------------
* A sparse Jacobian approximation function jacB for the adjoint
* (backward) problem must have the prototype given below.
* -----------------------------------------------------------------
*/
typedef int (*CVSlsSparseJacFnB)(realtype t, N_Vector y,
N_Vector yB, N_Vector fyB,
SlsMat JB, void *user_dataB,
N_Vector tmp1B, N_Vector tmp2B, N_Vector tmp3B);
/*
* -----------------------------------------------------------------
* Type: CVSlsSparseJacFnBS
* -----------------------------------------------------------------
* A sparse Jacobian approximation function jacBS for the adjoint
* (backward) problem, sensitivity-dependent case, must have the
* prototype given below.
* -----------------------------------------------------------------
*/
typedef int (*CVSlsSparseJacFnBS)(realtype t,
N_Vector y, N_Vector *yS,
N_Vector yB, N_Vector fyB,
SlsMat JB, void *user_dataB,
N_Vector tmp1B, N_Vector tmp2B, N_Vector tmp3B);
/*
* -----------------------------------------------------------------
* EXPORTED FUNCTIONS
* -----------------------------------------------------------------
*/
/*
* -----------------------------------------------------------------
* Functions: CVSlsSetSparseJacFnB and CVSlsSetSparseJacFnBS
* -----------------------------------------------------------------
* CVSlsSetSparseJacFnB specifies the sparse Jacobian functions to
* be used by a CVSPARSE linear solver for the backward integration phase
* when the backward problem does not depend on forward sensitivities.
* CVSlsSetSparseJacFnBS specifies the Jacobian
* functions when the backward problem does depend on sensitivities.
* The 'which' argument is the int returned by CVodeCreateB.
* -----------------------------------------------------------------
*/
SUNDIALS_EXPORT int CVSlsSetSparseJacFnB(void *cv_mem, int which,
CVSlsSparseJacFnB jacB);
SUNDIALS_EXPORT int CVSlsSetSparseJacFnBS(void *cv_mem, int which,
CVSlsSparseJacFnBS jacBS);
#ifdef __cplusplus
}
#endif
#endif
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