static int cvNlsFPFunction(N_Vector ycor, N_Vector res, void* cvode_mem)
{
CVodeMem cv_mem;
int retval;
if (cvode_mem == NULL) {
cvProcessError(NULL, CV_MEM_NULL, "CVODE", "cvNlsFPFunction", MSGCV_NO_MEM);
return(CV_MEM_NULL);
}
cv_mem = (CVodeMem) cvode_mem;
/* update the state based on the current correction */
N_VLinearSum(ONE, cv_mem->cv_zn[0], ONE, ycor, cv_mem->cv_y);
/* evaluate the rhs function */
retval = cv_mem->cv_f(cv_mem->cv_tn, cv_mem->cv_y, res,
cv_mem->cv_user_data);
cv_mem->cv_nfe++;
if (retval < 0) return(CV_RHSFUNC_FAIL);
if (retval > 0) return(RHSFUNC_RECVR);
N_VLinearSum(cv_mem->cv_h, res, -ONE, cv_mem->cv_zn[1], res);
N_VScale(cv_mem->cv_rl1, res, res);
return(CV_SUCCESS);
}
static int CVSpgmrDQJtimes(N_Vector v, N_Vector Jv, realtype t,
N_Vector y, N_Vector fy,
void *jac_data, N_Vector work)
{
CVodeMem cv_mem;
CVSpgmrMem cvspgmr_mem;
realtype vnrm;
/* jac_data is cvode_mem */
cv_mem = (CVodeMem) jac_data;
cvspgmr_mem = (CVSpgmrMem) lmem;
/* Evaluate norm of v */
vnrm = N_VWrmsNorm(v, ewt);
/* Set work = y + (1/vnrm) v */
N_VLinearSum(ONE/vnrm, v, ONE, y, work);
/* Set Jv = f(tn, work) */
f(t, work, Jv, f_data);
nfeSG++;
/* Replace Jv by vnrm*(Jv - fy) */
N_VLinearSum(ONE, Jv, -ONE, fy, Jv);
N_VScale(vnrm, Jv, Jv);
return(0);
}
static int cvNlsFPFunctionSensStg1(N_Vector ycor, N_Vector res, void* cvode_mem)
{
CVodeMem cv_mem;
int retval, is;
if (cvode_mem == NULL) {
cvProcessError(NULL, CV_MEM_NULL, "CVODES",
"cvNlsFPFunctionSensStg1", MSGCV_NO_MEM);
return(CV_MEM_NULL);
}
cv_mem = (CVodeMem) cvode_mem;
/* get index of current sensitivity solve */
is = cv_mem->sens_solve_idx;
/* update the sensitivities based on the current correction */
N_VLinearSum(ONE, cv_mem->cv_znS[0][is], ONE, ycor, cv_mem->cv_yS[is]);
/* evaluate the sensitivity rhs function */
retval = cvSensRhs1Wrapper(cv_mem, cv_mem->cv_tn,
cv_mem->cv_y, cv_mem->cv_ftemp,
is, cv_mem->cv_yS[is], res,
cv_mem->cv_vtemp1, cv_mem->cv_vtemp2);
if (retval < 0) return(CV_SRHSFUNC_FAIL);
if (retval > 0) return(SRHSFUNC_RECVR);
/* evaluate sensitivity fixed point function */
N_VLinearSum(cv_mem->cv_h, res, -ONE, cv_mem->cv_znS[1][is], res);
N_VScale(cv_mem->cv_rl1, res, res);
return(CV_SUCCESS);
}
static int IDANewyyp(IDAMem IDA_mem, realtype lambda)
{
int retval;
retval = IDA_SUCCESS;
/* IDA_YA_YDP_INIT case: ynew = yy0 - lambda*delta where id_i = 0
ypnew = yp0 - cj*lambda*delta where id_i = 1. */
if(icopt == IDA_YA_YDP_INIT) {
N_VProd(id, delta, dtemp);
N_VLinearSum(ONE, yp0, -cj*lambda, dtemp, ypnew);
N_VLinearSum(ONE, delta, -ONE, dtemp, dtemp);
N_VLinearSum(ONE, yy0, -lambda, dtemp, ynew);
}else if(icopt == IDA_Y_INIT) {
/* IDA_Y_INIT case: ynew = yy0 - lambda*delta. (ypnew = yp0 preset.) */
N_VLinearSum(ONE, yy0, -lambda, delta, ynew);
}
if(sensi && (ism==IDA_SIMULTANEOUS))
retval = IDASensNewyyp(IDA_mem, lambda);
return(retval);
}
static int IDASensNewyyp(IDAMem IDA_mem, realtype lambda)
{
int is;
if(icopt == IDA_YA_YDP_INIT) {
/* IDA_YA_YDP_INIT case:
- ySnew = yS0 - lambda*deltaS where id_i = 0
- ypSnew = ypS0 - cj*lambda*delta where id_i = 1. */
for(is=0; is<Ns; is++) {
/* It is ok to use dtemp as temporary vector here. */
N_VProd(id, deltaS[is], dtemp);
N_VLinearSum(ONE, ypS0[is], -cj*lambda, dtemp, ypS0new[is]);
N_VLinearSum(ONE, deltaS[is], -ONE, dtemp, dtemp);
N_VLinearSum(ONE, yyS0[is], -lambda, dtemp, yyS0new[is]);
} /* end loop is */
}else {
/* IDA_Y_INIT case:
- ySnew = yS0 - lambda*deltaS. (ypnew = yp0 preset.) */
for(is=0; is<Ns; is++)
N_VLinearSum(ONE, yyS0[is], -lambda, deltaS[is], yyS0new[is]);
} /* end loop is */
return(IDA_SUCCESS);
}
/*---------------------------------------------------------------
ARKSpilsAtimes:
This routine generates the matrix-vector product z = Av, where
A = M - gamma*J. The product M*v is obtained either by calling
the mtimes routine or by just using v (if M=I). The product
J*v is obtained by calling the jtimes routine. It is then scaled
by -gamma and added to M*v to obtain A*v. The return value is
the same as the values returned by jtimes and mtimes --
0 if successful, nonzero otherwise.
---------------------------------------------------------------*/
int ARKSpilsAtimes(void *arkode_mem, N_Vector v, N_Vector z)
{
ARKodeMem ark_mem;
ARKSpilsMem arkspils_mem;
int jtflag, mtflag;
ark_mem = (ARKodeMem) arkode_mem;
arkspils_mem = (ARKSpilsMem) ark_mem->ark_lmem;
jtflag = arkspils_mem->s_jtimes(v, z, ark_mem->ark_tn,
arkspils_mem->s_ycur,
arkspils_mem->s_fcur,
arkspils_mem->s_j_data,
arkspils_mem->s_ytemp);
arkspils_mem->s_njtimes++;
if (jtflag != 0) return(jtflag);
/* Compute mass matrix vector product and add to result */
if (ark_mem->ark_mass_matrix) {
mtflag = ARKSpilsMtimes(arkode_mem, v, arkspils_mem->s_ytemp);
if (mtflag != 0) return(mtflag);
N_VLinearSum(ONE, arkspils_mem->s_ytemp, -ark_mem->ark_gamma, z, z);
} else {
N_VLinearSum(ONE, v, -ark_mem->ark_gamma, z, z);
}
return(0);
}
static int idaNlsResidual(N_Vector ycor, N_Vector res, void* ida_mem)
{
IDAMem IDA_mem;
int retval;
if (ida_mem == NULL) {
IDAProcessError(NULL, IDA_MEM_NULL, "IDA", "idaNlsResidual", MSG_NO_MEM);
return(IDA_MEM_NULL);
}
IDA_mem = (IDAMem) ida_mem;
/* update yy and yp based on the current correction */
N_VLinearSum(ONE, IDA_mem->ida_yypredict, ONE, ycor, IDA_mem->ida_yy);
N_VLinearSum(ONE, IDA_mem->ida_yppredict, IDA_mem->ida_cj, ycor, IDA_mem->ida_yp);
/* evaluate residual */
retval = IDA_mem->ida_res(IDA_mem->ida_tn, IDA_mem->ida_yy, IDA_mem->ida_yp,
res, IDA_mem->ida_user_data);
/* increment the number of residual evaluations */
IDA_mem->ida_nre++;
/* save a copy of the residual vector in savres */
N_VScale(ONE, res, IDA_mem->ida_savres);
if (retval < 0) return(IDA_RES_FAIL);
if (retval > 0) return(IDA_RES_RECVR);
return(IDA_SUCCESS);
}
int KINSpilsDQJtimes(N_Vector v, N_Vector Jv,
N_Vector u, booleantype *new_u,
void *data)
{
realtype sigma, sigma_inv, sutsv, sq1norm, sign, vtv;
KINMem kin_mem;
KINSpilsMem kinspils_mem;
int retval;
/* data is kin_mem */
kin_mem = (KINMem) data;
kinspils_mem = (KINSpilsMem) lmem;
/* scale the vector v and put Du*v into vtemp1 */
N_VProd(v, uscale, vtemp1);
/* scale u and put into Jv (used as a temporary storage) */
N_VProd(u, uscale, Jv);
/* compute dot product (Du*u).(Du*v) */
sutsv = N_VDotProd(Jv, vtemp1);
/* compute dot product (Du*v).(Du*v) */
vtv = N_VDotProd(vtemp1, vtemp1);
sq1norm = N_VL1Norm(vtemp1);
sign = (sutsv >= ZERO) ? ONE : -ONE ;
/* this expression for sigma is from p. 469, Brown and Saad paper */
sigma = sign*sqrt_relfunc*SUNMAX(SUNRabs(sutsv),sq1norm)/vtv;
sigma_inv = ONE/sigma;
/* compute the u-prime at which to evaluate the function func */
N_VLinearSum(ONE, u, sigma, v, vtemp1);
/* call the system function to calculate func(u+sigma*v) */
retval = func(vtemp1, vtemp2, user_data);
nfes++;
if (retval != 0) return(retval);
/* finish the computation of the difference quotient */
N_VLinearSum(sigma_inv, vtemp2, -sigma_inv, fval, Jv);
return(0);
}
int IDASpilsDQJtimes(realtype tt,
N_Vector yy, N_Vector yp, N_Vector rr,
N_Vector v, N_Vector Jv,
realtype c_j, void *data,
N_Vector work1, N_Vector work2)
{
IDAMem IDA_mem;
IDASpilsMem idaspils_mem;
N_Vector y_tmp, yp_tmp;
realtype sig, siginv;
int iter, retval;
/* data is ida_mem */
IDA_mem = (IDAMem) data;
idaspils_mem = (IDASpilsMem) lmem;
switch(ils_type) {
case SPILS_SPGMR:
sig = sqrtN*dqincfac;
break;
case SPILS_SPBCG:
sig = dqincfac/N_VWrmsNorm(v, ewt);
break;
case SPILS_SPTFQMR:
sig = dqincfac/N_VWrmsNorm(v, ewt);
break;
}
/* Rename work1 and work2 for readibility */
y_tmp = work1;
yp_tmp = work2;
for (iter=0; iter<MAX_ITERS; iter++) {
/* Set y_tmp = yy + sig*v, yp_tmp = yp + cj*sig*v. */
N_VLinearSum(sig, v, ONE, yy, y_tmp);
N_VLinearSum(c_j*sig, v, ONE, yp, yp_tmp);
/* Call res for Jv = F(t, y_tmp, yp_tmp), and return if it failed. */
retval = res(tt, y_tmp, yp_tmp, Jv, user_data);
nres++;
if (retval == 0) break;
if (retval < 0) return(-1);
sig *= PT25;
}
if (retval > 0) return(+1);
/* Set Jv to [Jv - rr]/sig and return. */
siginv = ONE/sig;
N_VLinearSum(siginv, Jv, -siginv, rr, Jv);
return(0);
}
static int cpNewtonIterationImpl(CPodeMem cp_mem)
{
int m, retval;
realtype del, delp, dcon;
/* Initialize counters */
mnewt = m = 0;
/* Initialize delp to avoid compiler warning message */
del = delp = ZERO;
/* Looping point for Newton iteration */
loop {
/* Evaluate the residual of the nonlinear system*/
N_VScale(-gamma, ftemp, tempv);
/* Call the lsolve function (solution in tempv) */
retval = lsolve(cp_mem, tempv, ewt, y, yp, ftemp);
nni++;
if (retval < 0) return(CP_LSOLVE_FAIL);
if (retval > 0) return(CONV_FAIL);
/* Get WRMS norm of correction and add correction to acor, y, and yp */
del = N_VWrmsNorm(tempv, ewt);
N_VLinearSum(ONE, acor, ONE, tempv, acor);
N_VLinearSum(ONE, y, ONE, tempv, y);
N_VLinearSum(ONE, yp, ONE/gamma, tempv, yp);
/* Test for convergence. If m > 0, an estimate of the convergence
rate constant is stored in crate, and used in the test. */
if (m > 0) crate = MAX(NLS_CRDOWN * crate, del/delp);
dcon = del * MIN(ONE, crate) / tq[4];
if (dcon <= ONE) {
acnrm = (m==0) ? del : N_VWrmsNorm(acor, ewt);
return(CP_SUCCESS);
}
mnewt = ++m;
/* Stop at maxcor iterations or if iter. seems to be diverging. */
if ((m == maxcor) || ((m >= 2) && (del > NLS_RDIV*delp))) return(CONV_FAIL);
/* Save norm of correction, evaluate f, and loop again */
delp = del;
retval = fi(tn, y, yp, ftemp, f_data);
nfe++;
if (retval < 0) return(CP_ODEFUNC_FAIL);
if (retval > 0) return(ODEFUNC_RECVR);
} /* end loop */
}
int ModifiedGS(N_Vector *v, realtype **h, int k, int p,
realtype *new_vk_norm)
{
int i, k_minus_1, i0;
realtype new_norm_2, new_product, vk_norm, temp;
vk_norm = RSqrt(N_VDotProd(v[k],v[k]));
k_minus_1 = k - 1;
i0 = MAX(k-p, 0);
/* Perform modified Gram-Schmidt */
for (i=i0; i < k; i++) {
h[i][k_minus_1] = N_VDotProd(v[i], v[k]);
N_VLinearSum(ONE, v[k], -h[i][k_minus_1], v[i], v[k]);
}
/* Compute the norm of the new vector at v[k] */
*new_vk_norm = RSqrt(N_VDotProd(v[k], v[k]));
/* If the norm of the new vector at v[k] is less than
FACTOR (== 1000) times unit roundoff times the norm of the
input vector v[k], then the vector will be reorthogonalized
in order to ensure that nonorthogonality is not being masked
by a very small vector length. */
temp = FACTOR * vk_norm;
if ((temp + (*new_vk_norm)) != temp) return(0);
new_norm_2 = ZERO;
for (i=i0; i < k; i++) {
new_product = N_VDotProd(v[i], v[k]);
temp = FACTOR * h[i][k_minus_1];
if ((temp + new_product) == temp) continue;
h[i][k_minus_1] += new_product;
N_VLinearSum(ONE, v[k],-new_product, v[i], v[k]);
new_norm_2 += SQR(new_product);
}
if (new_norm_2 != ZERO) {
new_product = SQR(*new_vk_norm) - new_norm_2;
*new_vk_norm = (new_product > ZERO) ? RSqrt(new_product) : ZERO;
}
return(0);
}
int ClassicalGS(N_Vector *v, realtype **h, int k, int p,
realtype *new_vk_norm, N_Vector temp, realtype *s)
{
int i, k_minus_1, i0;
realtype vk_norm;
k_minus_1 = k - 1;
/* Perform Classical Gram-Schmidt */
vk_norm = RSqrt(N_VDotProd(v[k], v[k]));
i0 = MAX(k-p, 0);
for (i=i0; i < k; i++) {
h[i][k_minus_1] = N_VDotProd(v[i], v[k]);
}
for (i=i0; i < k; i++) {
N_VLinearSum(ONE, v[k], -h[i][k_minus_1], v[i], v[k]);
}
/* Compute the norm of the new vector at v[k] */
*new_vk_norm = RSqrt(N_VDotProd(v[k], v[k]));
/* Reorthogonalize if necessary */
if ((FACTOR * (*new_vk_norm)) < vk_norm) {
for (i=i0; i < k; i++) {
s[i] = N_VDotProd(v[i], v[k]);
}
if (i0 < k) {
N_VScale(s[i0], v[i0], temp);
h[i0][k_minus_1] += s[i0];
}
for (i=i0+1; i < k; i++) {
N_VLinearSum(s[i], v[i], ONE, temp, temp);
h[i][k_minus_1] += s[i];
}
N_VLinearSum(ONE, v[k], -ONE, temp, v[k]);
*new_vk_norm = RSqrt(N_VDotProd(v[k],v[k]));
}
return(0);
}
/*-----------------------------------------------------------------
cvLsATimes
This routine generates the matrix-vector product z = Mv, where
M = I - gamma*J. The product J*v is obtained by calling the jtimes
routine. It is then scaled by -gamma and added to v to obtain M*v.
The return value is the same as the value returned by jtimes --
0 if successful, nonzero otherwise.
-----------------------------------------------------------------*/
int cvLsATimes(void *cvode_mem, N_Vector v, N_Vector z)
{
CVodeMem cv_mem;
CVLsMem cvls_mem;
int retval;
/* access CVLsMem structure */
retval = cvLs_AccessLMem(cvode_mem, "cvLsATimes",
&cv_mem, &cvls_mem);
if (retval != CVLS_SUCCESS) return(retval);
/* call Jacobian-times-vector product routine
(either user-supplied or internal DQ) */
retval = cvls_mem->jtimes(v, z, cv_mem->cv_tn,
cvls_mem->ycur,
cvls_mem->fcur,
cvls_mem->jt_data,
cvls_mem->ytemp);
cvls_mem->njtimes++;
if (retval != 0) return(retval);
/* add contribution from identity matrix */
N_VLinearSum(ONE, v, -cv_mem->cv_gamma, z, z);
return(0);
}
/*-----------------------------------------------------------------
cvDlsDenseDQJac
-----------------------------------------------------------------
This routine generates a dense difference quotient approximation
to the Jacobian of f(t,y). It assumes that a dense SUNMatrix is
stored column-wise, and that elements within each column are
contiguous. The address of the jth column of J is obtained via
the accessor function SUNDenseMatrix_Column, and this pointer
is associated with an N_Vector using the N_VSetArrayPointer
function. Finally, the actual computation of the jth column of
the Jacobian is done with a call to N_VLinearSum.
-----------------------------------------------------------------*/
int cvDlsDenseDQJac(realtype t, N_Vector y, N_Vector fy,
SUNMatrix Jac, CVodeMem cv_mem, N_Vector tmp1)
{
realtype fnorm, minInc, inc, inc_inv, yjsaved, srur;
realtype *y_data, *ewt_data;
N_Vector ftemp, jthCol;
sunindextype j, N;
int retval = 0;
CVDlsMem cvdls_mem;
/* access DlsMem interface structure */
cvdls_mem = (CVDlsMem) cv_mem->cv_lmem;
/* access matrix dimension */
N = SUNDenseMatrix_Rows(Jac);
/* Rename work vector for readibility */
ftemp = tmp1;
/* Create an empty vector for matrix column calculations */
jthCol = N_VCloneEmpty(tmp1);
/* Obtain pointers to the data for ewt, y */
ewt_data = N_VGetArrayPointer(cv_mem->cv_ewt);
y_data = N_VGetArrayPointer(y);
/* Set minimum increment based on uround and norm of f */
srur = SUNRsqrt(cv_mem->cv_uround);
fnorm = N_VWrmsNorm(fy, cv_mem->cv_ewt);
minInc = (fnorm != ZERO) ?
(MIN_INC_MULT * SUNRabs(cv_mem->cv_h) * cv_mem->cv_uround * N * fnorm) : ONE;
for (j = 0; j < N; j++) {
/* Generate the jth col of J(tn,y) */
N_VSetArrayPointer(SUNDenseMatrix_Column(Jac,j), jthCol);
yjsaved = y_data[j];
inc = SUNMAX(srur*SUNRabs(yjsaved), minInc/ewt_data[j]);
y_data[j] += inc;
retval = cv_mem->cv_f(t, y, ftemp, cv_mem->cv_user_data);
cvdls_mem->nfeDQ++;
if (retval != 0) break;
y_data[j] = yjsaved;
inc_inv = ONE/inc;
N_VLinearSum(inc_inv, ftemp, -inc_inv, fy, jthCol);
/* DENSE_COL(Jac,j) = N_VGetArrayPointer(jthCol); /\*UNNECESSARY?? *\/ */
}
/* Destroy jthCol vector */
N_VSetArrayPointer(NULL, jthCol); /* SHOULDN'T BE NEEDED */
N_VDestroy(jthCol);
return(retval);
}
static int KINDenseDQJac(long int n, DenseMat J,
N_Vector u, N_Vector fu, void *jac_data,
N_Vector tmp1, N_Vector tmp2)
{
realtype inc, inc_inv, ujsaved, ujscale, sign;
realtype *tmp2_data, *u_data, *uscale_data;
N_Vector ftemp, jthCol;
long int j;
int retval;
KINMem kin_mem;
KINDenseMem kindense_mem;
/* jac_data points to kin_mem */
kin_mem = (KINMem) jac_data;
kindense_mem = (KINDenseMem) lmem;
/* Save pointer to the array in tmp2 */
tmp2_data = N_VGetArrayPointer(tmp2);
/* Rename work vectors for readibility */
ftemp = tmp1;
jthCol = tmp2;
/* Obtain pointers to the data for u and uscale */
u_data = N_VGetArrayPointer(u);
uscale_data = N_VGetArrayPointer(uscale);
/* This is the only for loop for 0..N-1 in KINSOL */
for (j = 0; j < n; j++) {
/* Generate the jth col of J(u) */
N_VSetArrayPointer(DENSE_COL(J,j), jthCol);
ujsaved = u_data[j];
ujscale = ONE/uscale_data[j];
sign = (ujsaved >= ZERO) ? ONE : -ONE;
inc = sqrt_relfunc*MAX(ABS(ujsaved), ujscale)*sign;
u_data[j] += inc;
retval = func(u, ftemp, f_data);
if (retval != 0) return(-1);
u_data[j] = ujsaved;
inc_inv = ONE/inc;
N_VLinearSum(inc_inv, ftemp, -inc_inv, fu, jthCol);
}
/* Restore original array pointer in tmp2 */
N_VSetArrayPointer(tmp2_data, tmp2);
/* Increment counter nfeD */
nfeD += n;
return(0);
}
static int IDANewy(IDAMem IDA_mem)
{
/* IDA_YA_YDP_INIT case: ynew = yy0 - delta where id_i = 0. */
if(icopt == IDA_YA_YDP_INIT) {
N_VProd(id, delta, dtemp);
N_VLinearSum(ONE, delta, -ONE, dtemp, dtemp);
N_VLinearSum(ONE, yy0, -ONE, dtemp, ynew);
return(IDA_SUCCESS);
}
/* IDA_Y_INIT case: ynew = yy0 - delta. */
N_VLinearSum(ONE, yy0, -ONE, delta, ynew);
return(IDA_SUCCESS);
}
static void CVDenseDQJac(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)
{
realtype fnorm, minInc, inc, inc_inv, yjsaved, srur;
realtype *tmp2_data, *y_data, *ewt_data;
N_Vector ftemp, jthCol;
long int j;
CVodeMem cv_mem;
CVDenseMem cvdense_mem;
/* jac_data points to cvode_mem */
cv_mem = (CVodeMem) jac_data;
cvdense_mem = (CVDenseMem) lmem;
/* Save pointer to the array in tmp2 */
tmp2_data = N_VGetArrayPointer(tmp2);
/* Rename work vectors for readibility */
ftemp = tmp1;
jthCol = tmp2;
/* Obtain pointers to the data for ewt, y */
ewt_data = N_VGetArrayPointer(ewt);
y_data = N_VGetArrayPointer(y);
/* Set minimum increment based on uround and norm of f */
srur = RSqrt(uround);
fnorm = N_VWrmsNorm(fy, ewt);
minInc = (fnorm != ZERO) ?
(MIN_INC_MULT * ABS(h) * uround * N * fnorm) : ONE;
/* This is the only for loop for 0..N-1 in CVODE */
for (j = 0; j < N; j++) {
/* Generate the jth col of J(tn,y) */
N_VSetArrayPointer(DENSE_COL(J,j), jthCol);
yjsaved = y_data[j];
inc = MAX(srur*ABS(yjsaved), minInc/ewt_data[j]);
y_data[j] += inc;
f(tn, y, ftemp, f_data);
y_data[j] = yjsaved;
inc_inv = ONE/inc;
N_VLinearSum(inc_inv, ftemp, -inc_inv, fy, jthCol);
DENSE_COL(J,j) = N_VGetArrayPointer(jthCol);
}
/* Restore original array pointer in tmp2 */
N_VSetArrayPointer(tmp2_data, tmp2);
/* Increment counter nfeD */
nfeD += N;
}
void GetSol(void *cpode_mem, N_Vector yy0, realtype tol,
realtype tout, booleantype proj, N_Vector yref)
{
N_Vector yy, yp;
realtype t, x, y, xd, yd, g;
int flag;
long int nst, nfe, nsetups, nje, nfeLS, ncfn, netf;
if (proj) {
printf(" YES ");
CPodeSetProjFrequency(cpode_mem, 1);
} else {
CPodeSetProjFrequency(cpode_mem, 0);
printf(" NO ");
}
yy = N_VNew_Serial(4);
yp = N_VNew_Serial(4);
flag = CPodeReInit(cpode_mem, (void *)f, NULL, 0.0, yy0, NULL, CP_SS, tol, &tol);
flag = CPode(cpode_mem, tout, &t, yy, yp, CP_NORMAL_TSTOP);
x = Ith(yy,1);
y = Ith(yy,2);
g = ABS(x*x + y*y - 1.0);
N_VLinearSum(1.0, yy, -1.0, yref, yy);
N_VAbs(yy, yy);
x = Ith(yy,1);
y = Ith(yy,2);
xd = Ith(yy,3);
yd = Ith(yy,4);
printf("%9.2e %9.2e %9.2e %9.2e | %9.2e |",
Ith(yy,1),Ith(yy,2),Ith(yy,3),Ith(yy,4),g);
CPodeGetNumSteps(cpode_mem, &nst);
CPodeGetNumFctEvals(cpode_mem, &nfe);
CPodeGetNumLinSolvSetups(cpode_mem, &nsetups);
CPodeGetNumErrTestFails(cpode_mem, &netf);
CPodeGetNumNonlinSolvConvFails(cpode_mem, &ncfn);
CPDlsGetNumJacEvals(cpode_mem, &nje);
CPDlsGetNumFctEvals(cpode_mem, &nfeLS);
printf(" %6ld %6ld+%-4ld %4ld (%3ld) | %3ld %3ld\n",
nst, nfe, nfeLS, nsetups, nje, ncfn, netf);
N_VDestroy_Serial(yy);
N_VDestroy_Serial(yp);
return;
}
void N_VLinearSum_SensWrapper(realtype a, N_Vector x, realtype b, N_Vector y, N_Vector z)
{
int i;
for (i=0; i < NV_NVECS_SW(x); i++)
N_VLinearSum(a, NV_VEC_SW(x,i), b, NV_VEC_SW(y,i), NV_VEC_SW(z,i));
return;
}
static int IDANewyyp(IDAMem IDA_mem, realtype lambda)
{
/* IDA_YA_YDP_INIT case: ynew = yy0 - lambda*delta where id_i = 0
ypnew = yp0 - cj*lambda*delta where id_i = 1. */
if(icopt == IDA_YA_YDP_INIT) {
N_VProd(id, delta, dtemp);
N_VLinearSum(ONE, yp0, -cj*lambda, dtemp, ypnew);
N_VLinearSum(ONE, delta, -ONE, dtemp, dtemp);
N_VLinearSum(ONE, yy0, -lambda, dtemp, ynew);
return(IDA_SUCCESS);
}
/* IDA_Y_INIT case: ynew = yy0 - lambda*delta. (ypnew = yp0 preset.) */
N_VLinearSum(ONE, yy0, -lambda, delta, ynew);
return(IDA_SUCCESS);
}
static real KINScSteplength(KINMem kin_mem, N_Vector ucur,
N_Vector ss, N_Vector usc)
{
N_VInv(usc, vtemp1);
N_VAbs(ucur, vtemp2);
N_VLinearSum(ONE, vtemp1, ONE, vtemp2, vtemp1);
N_VDiv(ss, vtemp1, vtemp1);
return(N_VMaxNorm(vtemp1));
}
/*-----------------------------------------------------------------
cvLsDQJtimes
This routine generates a difference quotient approximation to
the Jacobian times vector f_y(t,y) * v. The approximation is
Jv = [f(y + v*sig) - f(y)]/sig, where sig = 1 / ||v||_WRMS,
i.e. the WRMS norm of v*sig is 1.
-----------------------------------------------------------------*/
int cvLsDQJtimes(N_Vector v, N_Vector Jv, realtype t,
N_Vector y, N_Vector fy, void *cvode_mem,
N_Vector work)
{
CVodeMem cv_mem;
CVLsMem cvls_mem;
realtype sig, siginv;
int iter, retval;
/* access CVLsMem structure */
retval = cvLs_AccessLMem(cvode_mem, "cvLsDQJtimes",
&cv_mem, &cvls_mem);
if (retval != CVLS_SUCCESS) return(retval);
/* Initialize perturbation to 1/||v|| */
sig = ONE/N_VWrmsNorm(v, cv_mem->cv_ewt);
for (iter=0; iter<MAX_DQITERS; iter++) {
/* Set work = y + sig*v */
N_VLinearSum(sig, v, ONE, y, work);
/* Set Jv = f(tn, y+sig*v) */
retval = cv_mem->cv_f(t, work, Jv, cv_mem->cv_user_data);
cvls_mem->nfeDQ++;
if (retval == 0) break;
if (retval < 0) return(-1);
/* If f failed recoverably, shrink sig and retry */
sig *= PT25;
}
/* If retval still isn't 0, return with a recoverable failure */
if (retval > 0) return(+1);
/* Replace Jv by (Jv - fy)/sig */
siginv = ONE/sig;
N_VLinearSum(siginv, Jv, -siginv, fy, Jv);
return(0);
}
/*---------------------------------------------------------------
ARKSpilsDQJtimes:
This routine generates a difference quotient approximation to
the Jacobian times vector f_y(t,y) * v. The approximation is
Jv = vnrm[f(y + v/vnrm) - f(y)], where vnrm = (WRMS norm of v)
is input, i.e. the WRMS norm of v/vnrm is 1.
---------------------------------------------------------------*/
int ARKSpilsDQJtimes(N_Vector v, N_Vector Jv, realtype t,
N_Vector y, N_Vector fy,
void *data, N_Vector work)
{
ARKodeMem ark_mem;
ARKSpilsMem arkspils_mem;
realtype sig, siginv;
int iter, retval;
/* data is arkode_mem */
ark_mem = (ARKodeMem) data;
arkspils_mem = (ARKSpilsMem) ark_mem->ark_lmem;
/* Initialize perturbation to 1/||v|| */
sig = ONE/N_VWrmsNorm(v, ark_mem->ark_ewt);
for (iter=0; iter<MAX_DQITERS; iter++) {
/* Set work = y + sig*v */
N_VLinearSum(sig, v, ONE, y, work);
/* Set Jv = f(tn, y+sig*v) */
retval = ark_mem->ark_fi(t, work, Jv, ark_mem->ark_user_data);
arkspils_mem->s_nfes++;
if (retval == 0) break;
if (retval < 0) return(-1);
/* If fi failed recoverably, shrink sig and retry */
sig *= PT25;
}
/* If retval still isn't 0, return with a recoverable failure */
if (retval > 0) return(+1);
/* Replace Jv by (Jv - fy)/sig */
siginv = ONE/sig;
N_VLinearSum(siginv, Jv, -siginv, fy, Jv);
return(0);
}
static int CVDiagSetup(CVodeMem cv_mem, int convfail, N_Vector ypred,
N_Vector fpred, booleantype *jcurPtr, N_Vector vtemp1,
N_Vector vtemp2, N_Vector vtemp3)
{
realtype r;
N_Vector ftemp, y;
booleantype invOK;
CVDiagMem cvdiag_mem;
int retval;
cvdiag_mem = (CVDiagMem) lmem;
/* Rename work vectors for use as temporary values of y and f */
ftemp = vtemp1;
y = vtemp2;
/* Form y with perturbation = FRACT*(func. iter. correction) */
r = FRACT * rl1;
N_VLinearSum(h, fpred, -ONE, zn[1], ftemp);
N_VLinearSum(r, ftemp, ONE, ypred, y);
/* Evaluate f at perturbed y */
retval = f(tn, y, M, cv_mem->cv_user_data);
nfeDI++;
if (retval < 0) {
cvProcessError(cv_mem, CVDIAG_RHSFUNC_UNRECVR, "CVDIAG", "CVDiagSetup", MSGDG_RHSFUNC_FAILED);
last_flag = CVDIAG_RHSFUNC_UNRECVR;
return(-1);
}
if (retval > 0) {
last_flag = CVDIAG_RHSFUNC_RECVR;
return(1);
}
/* Construct M = I - gamma*J with J = diag(deltaf_i/deltay_i) */
N_VLinearSum(ONE, M, -ONE, fpred, M);
N_VLinearSum(FRACT, ftemp, -h, M, M);
N_VProd(ftemp, ewt, y);
/* Protect against deltay_i being at roundoff level */
N_VCompare(uround, y, bit);
N_VAddConst(bit, -ONE, bitcomp);
N_VProd(ftemp, bit, y);
N_VLinearSum(FRACT, y, -ONE, bitcomp, y);
N_VDiv(M, y, M);
N_VProd(M, bit, M);
N_VLinearSum(ONE, M, -ONE, bitcomp, M);
/* Invert M with test for zero components */
invOK = N_VInvTest(M, M);
if (!invOK) {
last_flag = CVDIAG_INV_FAIL;
return(1);
}
/* Set jcur = TRUE, save gamma in gammasv, and return */
*jcurPtr = TRUE;
gammasv = gamma;
last_flag = CVDIAG_SUCCESS;
return(0);
}
int CVSpilsDQJtimes(N_Vector v, N_Vector Jv, realtype t,
N_Vector y, N_Vector fy,
void *jac_data, N_Vector work)
{
CVodeMem cv_mem;
CVSpilsMem cvspils_mem;
realtype sig, siginv;
int iter, retval;
/* jac_data is cvode_mem */
cv_mem = (CVodeMem) jac_data;
cvspils_mem = (CVSpilsMem) lmem;
/* Initialize perturbation to 1/||v|| */
sig = ONE/N_VWrmsNorm(v, ewt);
for (iter=0; iter<MAX_ITERS; iter++) {
/* Set work = y + sig*v */
N_VLinearSum(sig, v, ONE, y, work);
/* Set Jv = f(tn, y+sig*v) */
retval = f(t, work, Jv, f_data);
nfes++;
if (retval == 0) break;
if (retval < 0) return(-1);
sig *= PT25;
}
if (retval > 0) return(+1);
/* Replace Jv by (Jv - fy)/sig */
siginv = ONE/sig;
N_VLinearSum(siginv, Jv, -siginv, fy, Jv);
return(0);
}
static void
CVDenseDQJac(integertype N, DenseMat J, RhsFn f, void *f_data,
realtype tn, N_Vector y, N_Vector fy, N_Vector ewt,
realtype h, realtype uround, void *jac_data,
long int *nfePtr, N_Vector vtemp1,
N_Vector vtemp2, N_Vector vtemp3)
{
realtype fnorm, minInc, inc, inc_inv, yjsaved, srur;
realtype *y_data, *ewt_data;
N_Vector ftemp, jthCol;
M_Env machEnv;
integertype j;
machEnv = y->menv; /* Get machine environment */
ftemp = vtemp1; /* Rename work vector for use as f vector value */
/* Obtain pointers to the data for ewt, y */
ewt_data = N_VGetData(ewt);
y_data = N_VGetData(y);
/* Set minimum increment based on uround and norm of f */
srur = RSqrt(uround);
fnorm = N_VWrmsNorm(fy, ewt);
minInc = (fnorm != ZERO) ?
(MIN_INC_MULT * ABS(h) * uround * N * fnorm) : ONE;
jthCol = N_VMake(N, y_data, machEnv); /* j loop overwrites this data address */
/* This is the only for loop for 0..N-1 in CVODE */
for (j = 0; j < N; j++)
{
/* Generate the jth col of J(tn,y) */
N_VSetData(DENSE_COL(J, j), jthCol);
yjsaved = y_data[j];
inc = MAX(srur * ABS(yjsaved), minInc / ewt_data[j]);
y_data[j] += inc;
f(N, tn, y, ftemp, f_data);
inc_inv = ONE / inc;
N_VLinearSum(inc_inv, ftemp, -inc_inv, fy, jthCol);
y_data[j] = yjsaved;
}
N_VDispose(jthCol);
/* Increment counter nfe = *nfePtr */
*nfePtr += N;
}
static void CVAhermitePrepare(CVadjMem ca_mem, DtpntMem *dt_mem, long int i)
{
realtype t0, t1;
HermiteDataMem content0, content1;
N_Vector y0, y1, yd0, yd1;
t0 = dt_mem[i-1]->t;
content0 = (HermiteDataMem) (dt_mem[i-1]->content);
y0 = content0->y;
yd0 = content0->yd;
t1 = dt_mem[i]->t;
content1 = (HermiteDataMem) (dt_mem[i]->content);
y1 = content1->y;
yd1 = content1->yd;
delta = t1 - t0;
N_VLinearSum(ONE, y1, -ONE, y0, Y0);
N_VLinearSum(ONE, yd1, ONE, yd0, Y1);
N_VLinearSum(delta, Y1, -TWO, Y0, Y1);
N_VLinearSum(ONE, Y0, -delta, yd0, Y0);
}
static void CVAhermiteInterpolate(CVadjMem ca_mem, DtpntMem *dt_mem,
long int i, realtype t, N_Vector y)
{
realtype t0, t1;
HermiteDataMem content0;
N_Vector y0, yd0;
realtype factor;
t0 = dt_mem[i-1]->t;
t1 = dt_mem[i]->t;
content0 = (HermiteDataMem) (dt_mem[i-1]->content);
y0 = content0->y;
yd0 = content0->yd;
factor = t - t0;
N_VLinearSum(ONE, y0, factor, yd0, y);
factor = factor/delta;
factor = factor*factor;
N_VLinearSum(ONE, y, factor, Y0, y);
factor = factor*(t-t1)/delta;
N_VLinearSum(ONE, y, factor, Y1, y);
}
static int CVSpgmrAtimes(void *cvode_mem, N_Vector v, N_Vector z)
{
CVodeMem cv_mem;
CVSpgmrMem cvspgmr_mem;
int jtflag;
cv_mem = (CVodeMem) cvode_mem;
cvspgmr_mem = (CVSpgmrMem) lmem;
jtflag = jtimes(v, z, tn, ycur, fcur, j_data, ytemp);
njtimes++;
if (jtflag != 0) return(jtflag);
N_VLinearSum(ONE, v, -gamma, z, z);
return(0);
}
int CVSpilsAtimes(void *cvode_mem, N_Vector v, N_Vector z)
{
CVodeMem cv_mem;
CVSpilsMem cvspils_mem;
int retval;
cv_mem = (CVodeMem) cvode_mem;
cvspils_mem = (CVSpilsMem) lmem;
retval = jtimes(v, z, tn, ycur, fcur, j_data, ytemp);
njtimes++;
if (retval != 0) return(retval);
N_VLinearSum(ONE, v, -gamma, z, z);
return(0);
}