/****************************************************************** * * * File : cvdense.h * * Programmers : Scott D. Cohen and Alan C. Hindmarsh @ LLNL * * Last Modified : 1 September 1994 * *----------------------------------------------------------------* * This is the header file for the CVODE dense linear solver, * * CVDENSE. * * * * Note: The type integer must be large enough to store the value * * of the linear system size N. * * * ******************************************************************/ #ifndef _cvdense_h #define _cvdense_h #include #include "cvode.h" #include "llnltyps.h" #include "dense.h" #include "vector.h" /****************************************************************** * * * CVDENSE solver statistics indices * *----------------------------------------------------------------* * The following enumeration gives a symbolic name to each * * CVDENSE statistic. The symbolic names are used as indices into * * the iopt and ropt arrays passed to CVodeMalloc. * * The CVDENSE statistics are: * * * * iopt[DENSE_NJE] : number of Jacobian evaluations, i.e. of * * calls made to the dense Jacobian routine * * (default or user-supplied). * * * * iopt[DENSE_LRW] : size (in real words) of real workspace * * matrices and vectors used by this solver. * * * * iopt[DENSE_LIW] : size (in integer words) of integer * * workspace vectors used by this solver. * * * ******************************************************************/ enum { DENSE_NJE=CVODE_IOPT_SIZE, DENSE_LRW, DENSE_LIW }; /****************************************************************** * * * 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 length of all vector arguments. * * * * 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. * * * * f is the right hand side function for the ODE problem. * * * * f_data is a pointer to user data to be passed to f, the same * * as the F_data parameter passed to CVodeMalloc. * * * * 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). * * * * ewt is the error weight vector. * * * * h is a tentative step size in t. * * * * uround is the machine unit roundoff. * * * * jac_data is a pointer to user data - the same as the jac_data * * parameter passed to CVDense. * * * * nfePtr is a pointer to the memory location containing the * * CVODE problem data nfe = number of calls to f. The Jacobian * * routine should update this counter by adding on the number * * of f calls made in order to approximate the Jacobian, if any. * * For example, if the routine calls f a total of N times, then * * the update is *nfePtr += N. * * * * vtemp1, vtemp2, and vtemp3 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)(integer N, DenseMat J, RhsFn f, void *f_data, real t, N_Vector y, N_Vector fy, N_Vector ewt, real h, real uround, void *jac_data, int *nfePtr, N_Vector vtemp1, N_Vector vtemp2, N_Vector vtemp3); /****************************************************************** * * * Function : CVDense * *----------------------------------------------------------------* * A call to the CVDense function links the main CVODE integrator * * with the CVDENSE linear solver. * * * * cvode_mem is the pointer to CVODE memory returned by * * CVodeMalloc. * * * * djac is the dense Jacobian approximation routine to be used. * * A user-supplied djac routine must be of type * * CVDenseJacFn. Pass NULL for djac to use the default * * difference quotient routine CVDenseDQJac supplied * * with this solver. * * * * jac_data is a pointer to user data which is passed to the * * djac routine every time it is called. * * * ******************************************************************/ void CVDense(void *cvode_mem, CVDenseJacFn djac, void *jac_data); /****************************************************************** * * * Function : CVDenseDQJac * *----------------------------------------------------------------* * This routine generates a dense difference quotient * * approximation to the Jacobian of f(t,y). * * * ******************************************************************/ void CVDenseDQJac(integer N, DenseMat J, RhsFn f, void *f_data, real t, N_Vector y, N_Vector fy, N_Vector ewt, real h, real uround, void *jac_data, int *nfePtr, N_Vector vtemp1, N_Vector vtemp2, N_Vector vtemp3); #endif