/*
 * -----------------------------------------------------------------
 * $Revision: 1.6.2.2 $
 * $Date: 2005/04/06 23:39:12 $
 * ----------------------------------------------------------------- 
 * Programmer(s): Scott D. Cohen, Alan C. Hindmarsh and
 *                Radu Serban @ LLNL
 * -----------------------------------------------------------------
 * Copyright (c) 2002, The Regents of the University of California.
 * Produced at the Lawrence Livermore National Laboratory.
 * All rights reserved.
 * For details, see sundials/cvodes/LICENSE.
 * -----------------------------------------------------------------
 * This is the header file for the CVODE/CVODES dense linear
 * solver, CVDENSE.
 * -----------------------------------------------------------------
 */

#ifndef _CVDENSE_H
#define _CVDENSE_H

#ifdef __cplusplus  /* wrapper to enable C++ usage */
extern "C" {
#endif

#include "dense.h"
#include "nvector.h"
#include "sundialstypes.h"

/*
 * -----------------------------------------------------------------
 * CVDENSE solver constants
 * -----------------------------------------------------------------
 * CVD_MSBJ : maximum number of steps between dense Jacobian
 *            evaluations
 *
 * CVD_DGMAX : maximum change in gamma between dense Jacobian
 *             evaluations
 * -----------------------------------------------------------------
 */

#define CVD_MSBJ  50
#define CVD_DGMAX RCONST(0.2)

/*
 * -----------------------------------------------------------------
 * Type : CVDenseJacFn
 * -----------------------------------------------------------------
 * A dense Jacobian approximation function Jac must have the
 * prototype given below. Its parameters are:
 *
 * N is the problem size.
 *
 * J is the dense matrix (of type DenseMat) that will be loaded
 * by a CVDenseJacFn with an approximation to the Jacobian matrix
 * J = (df_i/dy_j) at the point (t,y).
 * J is preset to zero, so only the nonzero elements need to be
 * loaded. Two efficient ways to load J are:
 *
 * (1) (with macros - no explicit data structure references)
 *     for (j=0; j < n; j++) {
 *       col_j = DENSE_COL(J,j);
 *       for (i=0; i < n; i++) {
 *         generate J_ij = the (i,j)th Jacobian element
 *         col_j[i] = J_ij;
 *       }
 *     }
 *
 * (2) (without macros - explicit data structure references)
 *     for (j=0; j < n; j++) {
 *       col_j = (J->data)[j];
 *       for (i=0; i < n; i++) {
 *         generate J_ij = the (i,j)th Jacobian element
 *         col_j[i] = J_ij;
 *       }
 *     }
 *
 * The DENSE_ELEM(A,i,j) macro is appropriate for use in small
 * problems in which efficiency of access is NOT a major concern.
 *
 * t is the current value of the independent variable.
 *
 * y is the current value of the dependent variable vector,
 *   namely the predicted value of y(t).
 *
 * fy is the vector f(t,y).
 *
 * jac_data is a pointer to user data - the same as the jac_data
 *          parameter passed to CVDense.
 *
 * 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 sundialstypes.h.
 *
 * tmp1, tmp2, and tmp3 are pointers to memory allocated for
 * vectors of length N which can be used by a CVDenseJacFn
 * as temporary storage or work space.
 * -----------------------------------------------------------------
 */

typedef void (*CVDenseJacFn)(long int N, DenseMat J, realtype t,
                             N_Vector y, N_Vector fy, void *jac_data,
                             N_Vector tmp1, N_Vector tmp2, N_Vector tmp3);

/*
 * -----------------------------------------------------------------
 * Function : CVDense
 * -----------------------------------------------------------------
 * A call to the CVDense function links the main integrator with
 * the CVDENSE linear solver.
 *
 * cvode_mem is the pointer to the integrator memory returned by
 *           CVodeCreate.
 *
 * N is the size of the ODE system.
 *
 * The return value of CVDense is one of:
 *    CVDENSE_SUCCESS   if successful
 *    CVDENSE_MEM_NULL  if the cvode memory was NULL
 *    CVDENSE_MEM_FAIL  if there was a memory allocation failure
 *    CVDENSE_ILL_INPUT if a required vector operation is missing
 * -----------------------------------------------------------------
 */

int CVDense(void *cvode_mem, long int N);

/*
 * -----------------------------------------------------------------
 * Optional inputs to the CVDENSE linear solver
 * -----------------------------------------------------------------
 *
 * CVDenseSetJacFn specifies the dense Jacobian approximation
 *                 routine to be used. A user-supplied djac routine
 *                 must be of type CVDenseJacFn. By default, a
 *                 difference quotient routine CVDenseDQJac, supplied
 *                 with this solver is used.                     
 *                 It also specifies a pointer to user data which is
 *                 passed to the djac routine every time it is called.
 *
 * The return value of CVDenseSet* is one of:
 *    CVDENSE_SUCCESS   if successful
 *    CVDENSE_MEM_NULL  if the cvode memory was NULL
 *    CVDENSE_LMEM_NULL if the cvdense memory was NULL
 * -----------------------------------------------------------------
 */

int CVDenseSetJacFn(void *cvode_mem, CVDenseJacFn djac, void *jac_data);

/*
 * -----------------------------------------------------------------
 * Optional outputs from the CVDENSE linear solver
 * -----------------------------------------------------------------
 *
 * CVDenseGetWorkSpace returns the real and integer workspace used
 *                     by CVDENSE.
 * CVDenseGetNumJacEvals returns the number of calls made to the
 *                       Jacobian evaluation routine djac.
 * CVDenseGetNumRhsEvals returns the number of calls to the user
 *                       f routine due to finite difference Jacobian
 *                       evaluation.
 * CVDenseGetLastFlag returns the last error flag set by any of
 *                    the CVDENSE interface functions.
 *
 * The return value of CVDenseGet* is one of:
 *    CVDENSE_SUCCESS   if successful
 *    CVDENSE_MEM_NULL  if the cvode memory was NULL
 *    CVDENSE_LMEM_NULL if the cvdense memory was NULL
 * -----------------------------------------------------------------
 */

int CVDenseGetWorkSpace(void *cvode_mem, long int *lenrwD, long int *leniwD);
int CVDenseGetNumJacEvals(void *cvode_mem, long int *njevalsD);
int CVDenseGetNumRhsEvals(void *cvode_mem, long int *nfevalsD);
int CVDenseGetLastFlag(void *cvode_mem, int *flag);

/* CVDENSE return values */

#define CVDENSE_SUCCESS    0
#define CVDENSE_MEM_NULL  -1
#define CVDENSE_LMEM_NULL -2
#define CVDENSE_ILL_INPUT -3
#define CVDENSE_MEM_FAIL  -4

#ifdef __cplusplus
}
#endif

#endif
