void RefSol(realtype tout, N_Vector yref)
{
void *cpode_mem;
N_Vector yy, yp;
realtype tol, t, th, thd;
int flag;
yy = N_VNew_Serial(2);
yp = N_VNew_Serial(2);
Ith(yy,1) = 0.0; /* theta */
Ith(yy,2) = 0.0; /* thetad */
tol = TOL_REF;
cpode_mem = CPodeCreate(CP_EXPL, CP_BDF, CP_NEWTON);
flag = CPodeSetMaxNumSteps(cpode_mem, 100000);
flag = CPodeInit(cpode_mem, (void *)fref, NULL, 0.0, yy, yp, CP_SS, tol, &tol);
flag = CPDense(cpode_mem, 2);
flag = CPodeSetStopTime(cpode_mem, tout);
flag = CPode(cpode_mem, tout, &t, yy, yp, CP_NORMAL_TSTOP);
th = Ith(yy,1);
thd = Ith(yy,2);
Ith(yref,1) = cos(th);
Ith(yref,2) = sin(th);
Ith(yref,3) = -thd*sin(th);
Ith(yref,4) = thd*cos(th);
N_VDestroy_Serial(yy);
N_VDestroy_Serial(yp);
CPodeFree(&cpode_mem);
return;
}
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;
}
int main(void)
{
realtype dx, dy, reltol, abstol, t, tout, umax;
N_Vector u, up;
UserData data;
void *cvode_mem;
int iout, flag;
long int nst;
u = NULL;
data = NULL;
cvode_mem = NULL;
u = N_VNew_Serial(NEQ);
up = N_VNew_Serial(NEQ);
reltol = ZERO;
abstol = ATOL;
data = (UserData) malloc(sizeof *data);
dx = data->dx = XMAX/(MX+1);
dy = data->dy = YMAX/(MY+1);
data->hdcoef = ONE/(dx*dx);
data->hacoef = HALF/(TWO*dx);
data->vdcoef = ONE/(dy*dy);
SetIC(u, data);
cvode_mem = CPodeCreate(CP_EXPL, CP_BDF, CP_NEWTON);
flag = CPodeInit(cvode_mem, (void *)f, data, T0, u, NULL, CP_SS, reltol, &abstol);
flag = CPLapackBand(cvode_mem, NEQ, MY, MY);
flag = CPDlsSetJacFn(cvode_mem, (void *)Jac, data);
/* In loop over output points: call CPode, print results, test for errors */
umax = N_VMaxNorm(u);
PrintHeader(reltol, abstol, umax);
for(iout=1, tout=T1; iout <= NOUT; iout++, tout += DTOUT) {
flag = CPode(cvode_mem, tout, &t, u, up, CP_NORMAL);
umax = N_VMaxNorm(u);
flag = CPodeGetNumSteps(cvode_mem, &nst);
PrintOutput(t, umax, nst);
}
PrintFinalStats(cvode_mem);
N_VDestroy_Serial(u);
CPodeFree(&cvode_mem);
free(data);
return(0);
}
void OpenSMOKE_CVODE_Sundials<T>::MemoryAllocation(const int n)
{
this->n_ = n; // Number of equations
this->y0_ = new double[this->n_];
this->y_ = new double[this->n_];
y0Sundials_ = N_VNew_Serial(this->n_);
if (check_flag((void *)y0Sundials_, std::string("N_VNew_Serial"), 0)) exit(-1);
ySundials_ = N_VNew_Serial(this->n_);
if (check_flag((void *)ySundials_, std::string("N_VNew_Serial"), 0)) exit(-1);
}
void SundialsInterface::init_memory(void* mem) const {
Integrator::init_memory(mem);
auto m = static_cast<SundialsMemory*>(mem);
// Allocate n-vectors
m->xz = N_VNew_Serial(nx_+nz_);
m->q = N_VNew_Serial(nq_);
m->rxz = N_VNew_Serial(nrx_+nrz_);
m->rq = N_VNew_Serial(nrq_);
// Allocate memory
m->p.resize(np_);
m->rp.resize(nrp_);
}
static WebData AllocUserData(void)
{
int i, ngrp = NGRP, ns = NS;
WebData wdata;
wdata = (WebData) malloc(sizeof *wdata);
for(i=0; i < ngrp; i++) {
(wdata->P)[i] = newDenseMat(ns, ns);
(wdata->pivot)[i] = newIndexArray(ns);
}
wdata->rewt = N_VNew_Serial(NEQ+1);
wdata->vtemp = N_VNew_Serial(NEQ+1);
return(wdata);
}
void CVodesIntegrator::sensInit(double t0, FuncEval& func)
{
m_np = func.nparams();
m_sens_ok = false;
N_Vector y = N_VNew_Serial(static_cast<sd_size_t>(func.neq()));
m_yS = N_VCloneVectorArray_Serial(static_cast<sd_size_t>(m_np), y);
for (size_t n = 0; n < m_np; n++) {
N_VConst(0.0, m_yS[n]);
}
N_VDestroy_Serial(y);
int flag = CVodeSensInit(m_cvode_mem, static_cast<sd_size_t>(m_np),
CV_STAGGERED, CVSensRhsFn(0), m_yS);
if (flag != CV_SUCCESS) {
throw CanteraError("CVodesIntegrator::sensInit", "Error in CVodeSensInit");
}
vector_fp atol(m_np);
for (size_t n = 0; n < m_np; n++) {
// This scaling factor is tuned so that reaction and species enthalpy
// sensitivities can be computed simultaneously with the same abstol.
atol[n] = m_abstolsens / func.m_paramScales[n];
}
flag = CVodeSensSStolerances(m_cvode_mem, m_reltolsens, atol.data());
}
N_Vector Cvode::nvnew(long int n) {
#if PARANEURON
if (use_partrans_) {
if (net_cvode_instance->use_long_double_) {
return N_VNew_NrnParallelLD(0, n, global_neq_);
}else{
return N_VNew_Parallel(0, n, global_neq_);
}
}
#endif
if (nctd_ > 1) {
assert(n == neq_);
if (!nthsizes_) {
nthsizes_ = new long int[nrn_nthread];
for (int i = 0; i < nrn_nthread; ++i) {
nthsizes_[i] = ctd_[i].nvsize_;
}
}
#if 1
int sum = 0;
for (int i=0; i < nctd_; ++i) { sum += nthsizes_[i];}
assert(sum == neq_);
#endif
if (net_cvode_instance->use_long_double_) {
return N_VNew_NrnThreadLD(n, nctd_, nthsizes_);
}else{
return N_VNew_NrnThread(n, nctd_, nthsizes_);
}
}
if (net_cvode_instance->use_long_double_) {
return N_VNew_NrnSerialLD(n);
}else{
return N_VNew_Serial(n);
}
}
void CVodesIntegrator::sensInit(double t0, FuncEval& func)
{
m_np = func.nparams();
size_t nv = func.neq();
m_sens_ok = false;
doublereal* data;
N_Vector y;
y = N_VNew_Serial(static_cast<sd_size_t>(nv));
m_yS = N_VCloneVectorArray_Serial(static_cast<sd_size_t>(m_np), y);
for (size_t n = 0; n < m_np; n++) {
data = NV_DATA_S(m_yS[n]);
for (size_t j = 0; j < nv; j++) {
data[j] =0.0;
}
}
int flag = CVodeSensInit(m_cvode_mem, static_cast<sd_size_t>(m_np),
CV_STAGGERED, CVSensRhsFn(0), m_yS);
if (flag != CV_SUCCESS) {
throw CVodesErr("Error in CVodeSensMalloc");
}
vector_fp atol(m_np, m_abstolsens);
double rtol = m_reltolsens;
flag = CVodeSensSStolerances(m_cvode_mem, rtol, atol.data());
}
void SundialsInterface::init_memory(void* mem) const {
Integrator::init_memory(mem);
auto m = static_cast<SundialsMemory*>(mem);
// Allocate n-vectors
m->xz = N_VNew_Serial(nx_+nz_);
m->q = N_VNew_Serial(nq_);
m->rxz = N_VNew_Serial(nrx_+nrz_);
m->rq = N_VNew_Serial(nrq_);
// Reset linear solvers
linsolF_.reset(get_function("jacF").sparsity_out(0));
if (nrx_>0) {
linsolB_.reset(get_function("jacB").sparsity_out(0));
}
}
int ViCaRS::init(SimEquations *eqns) {
unsigned int num_local, i;
int flag;
_eqns = eqns;
_num_equations = eqns->num_equations();
//flag = fill_greens_matrix();
//if (flag) return flag;
num_local = (unsigned int)_bdata.size();
_vars = N_VNew_Serial(_num_global_blocks*_num_equations);
if (_vars == NULL) return 1;
// Init CVodes structures
flag = _eqns->init(this);
if (flag) return flag;
for (i=0;i<_solvers.size();++i) _solvers[i]->init_solver(this);
_cur_solver = 0;
_cur_time = 0;
return 0;
}
static void Problem2(void)
{
void *fct;
void *cpode_mem;
N_Vector y, yp;
realtype reltol=RTOL, abstol=ATOL, t, tout, erm, hu;
int flag, iout, qu;
y = NULL;
yp = NULL;
cpode_mem = NULL;
y = N_VNew_Serial(P2_NEQ);
N_VConst(ZERO, y);
NV_Ith_S(y,0) = ONE;
yp = N_VNew_Serial(P2_NEQ);
if (ODE == CP_EXPL) {
fct = (void *)f2;
} else {
fct = (void *)res2;
f2(P2_T0, y, yp, NULL);
}
cpode_mem = CPodeCreate(ODE, CP_ADAMS, CP_FUNCTIONAL);
/* flag = CPodeSetInitStep(cpode_mem, 2.0e-9);*/
flag = CPodeInit(cpode_mem, fct, NULL, P2_T0, y, yp, CP_SS, reltol, &abstol);
printf("\n t max.err qu hu \n");
for(iout=1, tout=P2_T1; iout <= P2_NOUT; iout++, tout*=P2_TOUT_MULT) {
flag = CPode(cpode_mem, tout, &t, y, yp, CP_NORMAL);
if (flag != CP_SUCCESS) break;
erm = MaxError(y, t);
flag = CPodeGetLastOrder(cpode_mem, &qu);
flag = CPodeGetLastStep(cpode_mem, &hu);
printf("%10.3f %12.4le %2d %12.4le\n", t, erm, qu, hu);
}
PrintFinalStats(cpode_mem);
CPodeFree(&cpode_mem);
N_VDestroy_Serial(y);
N_VDestroy_Serial(yp);
return;
}
int main()
{
void *fct;
void *cpode_mem;
N_Vector y, yp;
realtype reltol=RTOL, abstol=ATOL, t, tout, hu;
int flag, iout, qu;
y = NULL;
yp = NULL;
cpode_mem = NULL;
y = N_VNew_Serial(P1_NEQ);
NV_Ith_S(y,0) = TWO;
NV_Ith_S(y,1) = ZERO;
yp = N_VNew_Serial(P1_NEQ);
if (ODE == CP_EXPL) {
fct = (void *)f;
} else {
fct = (void *)res;
f(P1_T0, y, yp, NULL);
}
cpode_mem = CPodeCreate(ODE, CP_ADAMS, CP_FUNCTIONAL);
/* flag = CPodeSetInitStep(cpode_mem, 4.0e-9);*/
flag = CPodeInit(cpode_mem, fct, NULL, P1_T0, y, yp, CP_SS, reltol, &abstol);
printf("\n t x xdot qu hu \n");
for(iout=1, tout=P1_T1; iout <= P1_NOUT; iout++, tout += P1_DTOUT) {
flag = CPode(cpode_mem, tout, &t, y, yp, CP_NORMAL);
if (flag != CP_SUCCESS) break;
flag = CPodeGetLastOrder(cpode_mem, &qu);
flag = CPodeGetLastStep(cpode_mem, &hu);
printf("%10.5f %12.5le %12.5le %2d %6.4le\n", t, NV_Ith_S(y,0), NV_Ith_S(y,1), qu, hu);
}
PrintFinalStats(cpode_mem);
CPodeFree(&cpode_mem);
N_VDestroy_Serial(y);
N_VDestroy_Serial(yp);
return 0;
}
sdVector::sdVector(unsigned int N)
{
alloc = true;
v = N_VNew_Serial(N);
n = N;
if (SundialsCvode::check_flag((void *)v, "N_VNew_Serial", 0)) {
throw DebugException("sdVector: error allocating vector");
}
}
int main()
{
void *cpode_mem;
N_Vector yref, yy0;
realtype tol, tout;
int i, flag;
tout = 30.0;
/* Get reference solution */
yref = N_VNew_Serial(4);
RefSol(tout, yref);
/* Initialize solver */
tol = TOL;
cpode_mem = CPodeCreate(CP_EXPL, CP_BDF, CP_NEWTON);
yy0 = N_VNew_Serial(4);
Ith(yy0,1) = 1.0; /* x */
Ith(yy0,2) = 0.0; /* y */
Ith(yy0,3) = 0.0; /* xd */
Ith(yy0,4) = 0.0; /* yd */
flag = CPodeInit(cpode_mem, (void *)f, NULL, 0.0, yy0, NULL, CP_SS, tol, &tol);
flag = CPodeSetMaxNumSteps(cpode_mem, 50000);
flag = CPodeSetStopTime(cpode_mem, tout);
flag = CPodeProjDefine(cpode_mem, proj, NULL);
flag = CPDense(cpode_mem, 4);
for (i=0;i<5;i++) {
printf("\n\n%.2e\n", tol);
GetSol(cpode_mem, yy0, tol, tout, TRUE, yref);
GetSol(cpode_mem, yy0, tol, tout, FALSE, yref);
tol /= 10.0;
}
N_VDestroy_Serial(yref);
CPodeFree(&cpode_mem);
return(0);
}
void CVodesIntegrator::setTolerances(double reltol, int n, double* abstol) {
m_itol = CV_SV;
m_nabs = n;
if (n != m_neq) {
if (m_abstol) N_VDestroy_Serial(nv(m_abstol));
m_abstol = reinterpret_cast<void*>(N_VNew_Serial(n));
}
for (int i=0; i<n; i++) {
NV_Ith_S(nv(m_abstol), i) = abstol[i];
}
m_reltol = reltol;
}
static WebData AllocUserData(void)
{
int i, ngrp = NGRP, ns = NS;
WebData wdata;
wdata = (WebData) malloc(sizeof *wdata);
for(i=0; i < ngrp; i++) {
(wdata->P)[i] = denalloc(ns);
(wdata->pivot)[i] = denallocpiv(ns);
}
wdata->rewt = N_VNew_Serial(NEQ+1);
return(wdata);
}
//main
int main(int argc, char **argv){
int i, j, n, pv=0;
char* file_name;
cs *jac;
N_Vector u;
Gen *gens;
double *u0;
//load ps file, populate ps, and grab some data
if(argc > 1)
file_name = argv[1];
else{
printf("Please specify PS data file.");
return 1;
}
PS ps=GetPS(file_name);
if(ps==NULL){
printf("Unable to build PS data.\n");
return 1;
}
n=(ps->num_buses-1)<<1;
gens=ps->gens;
u=N_VNew_Serial(n);
u0=NV_DATA_S(u);
//create an initial condition
if(gens[pv].index==ps->swing_bus)pv++;
for(i=0;i<ps->ybus->n;i++){
if(i==ps->swing_bus) continue;
j=(i>ps->swing_bus?(i-1)<<1:i<<1);
if(gens[pv].index==i){
u0[j]=0.1;
u0[j+1]=0.1;
pv++;
if(pv<ps->num_gens&&gens[pv].index==ps->swing_bus)pv++;
continue;
}
u0[j]=1.0; u0[j+1]=0.1;
}
//numerically evaluate the jacobian at initial condition
jac=CheckDerivativeN(n, n, ComputeF, u, (void*)ps);
cs_di_print(jac, 0);
//free memory and return
N_VDestroy_Serial(u);
return 0;
}
void CVodesIntegrator::setTolerances(double reltol, size_t n, double* abstol)
{
m_itol = CV_SV;
m_nabs = n;
if (n != m_neq) {
if (m_abstol) {
N_VDestroy_Serial(m_abstol);
}
m_abstol = N_VNew_Serial(static_cast<sd_size_t>(n));
}
for (size_t i=0; i<n; i++) {
NV_Ith_S(m_abstol, i) = abstol[i];
}
m_reltol = reltol;
}
string CVodesIntegrator::getErrorInfo(int N)
{
N_Vector errs = N_VNew_Serial(static_cast<sd_size_t>(m_neq));
N_Vector errw = N_VNew_Serial(static_cast<sd_size_t>(m_neq));
CVodeGetErrWeights(m_cvode_mem, errw);
CVodeGetEstLocalErrors(m_cvode_mem, errs);
vector<tuple<double, double, size_t> > weightedErrors;
for (size_t i=0; i<m_neq; i++) {
double err = NV_Ith_S(errs, i) * NV_Ith_S(errw, i);
weightedErrors.emplace_back(-abs(err), err, i);
}
N_VDestroy(errs);
N_VDestroy(errw);
N = std::min(N, static_cast<int>(m_neq));
sort(weightedErrors.begin(), weightedErrors.end());
stringstream s;
for (int i=0; i<N; i++) {
s << get<2>(weightedErrors[i]) << ": "
<< get<1>(weightedErrors[i]) << endl;
}
return s.str();
}
N_Vector NewVector(long int n)
{
N_Vector v;
long int nlocal, nglobal;
if (sundials_VecType == 1) {
v = N_VNew_Serial((long int)n);
} else {
nlocal = n;
MPI_Allreduce(&nlocal, &nglobal, 1, MPI_INT, MPI_SUM, sundials_comm);
v = N_VNew_Parallel(sundials_comm, nlocal, nglobal);
}
return(v);
}
N_Vector *N_VNewVectorArray_Serial(int count, long int length)
{
N_Vector *vs;
int j;
if (count <= 0) return(NULL);
vs = (N_Vector *) malloc(count * sizeof(N_Vector));
if(vs == NULL) return(NULL);
for (j=0; j<count; j++) {
vs[j] = N_VNew_Serial(length);
if (vs[j] == NULL) {
N_VDestroyVectorArray_Serial(vs, j-1);
return(NULL);
}
}
return(vs);
}
void KinsolSolver::initialize(ComputeSystemFunction pComputeSystem,
double *pParameters, int pSize, void *pUserData)
{
if (mSolver)
// The solver has already been initialised, so reset things...
reset();
// Initialise the ODE solver itself
OpenCOR::CoreSolver::CoreNlaSolver::initialize(pComputeSystem, pParameters, pSize);
// Create some vectors
mParametersVector = N_VMake_Serial(pSize, pParameters);
mOnesVector = N_VNew_Serial(pSize);
N_VConst(1.0, mOnesVector);
// Create the KINSOL solver
mSolver = KINCreate();
// Use our own error handler
KINSetErrHandlerFn(mSolver, errorHandler, this);
// Initialise the KINSOL solver
KINInit(mSolver, systemFunction, mParametersVector);
// Set some user data
mUserData = new KinsolSolverUserData(pUserData, pComputeSystem);
KINSetUserData(mSolver, mUserData);
// Set the linear solver
KINDense(mSolver, pSize);
}
void CVodesIntegrator::sensInit(double t0, FuncEval& func) {
m_np = func.nparams();
long int nv = func.neq();
doublereal* data;
int n, j;
N_Vector y;
y = N_VNew_Serial(nv);
m_yS = N_VCloneVectorArray_Serial(m_np, y);
for (n = 0; n < m_np; n++) {
data = NV_DATA_S(m_yS[n]);
for (j = 0; j < nv; j++) {
data[j] =0.0;
}
}
int flag;
#if defined(SUNDIALS_VERSION_22) || defined(SUNDIALS_VERSION_23)
flag = CVodeSensMalloc(m_cvode_mem, m_np, CV_STAGGERED, m_yS);
if (flag != CV_SUCCESS) {
throw CVodesErr("Error in CVodeSensMalloc");
}
vector_fp atol(m_np, m_abstolsens);
double rtol = m_reltolsens;
flag = CVodeSetSensTolerances(m_cvode_mem, CV_SS, rtol, DATA_PTR(atol));
#elif defined(SUNDIALS_VERSION_24)
flag = CVodeSensInit(m_cvode_mem, m_np, CV_STAGGERED,
CVSensRhsFn (0), m_yS);
if (flag != CV_SUCCESS) {
throw CVodesErr("Error in CVodeSensMalloc");
}
vector_fp atol(m_np, m_abstolsens);
double rtol = m_reltolsens;
flag = CVodeSensSStolerances(m_cvode_mem, rtol, DATA_PTR(atol));
#endif
}
N_Vector N_VNew_NrnThread(long int length, int nthread, long int* sizes)
{
int i;
N_Vector v;
N_Vector data;
N_VectorContent_NrnThread* content;
v = N_VNewEmpty_NrnThread(length, nthread, sizes);
if (v == NULL) return(NULL);
/* Create data */
if (length > 0) {
/* Allocate memory */
NV_OWN_DATA_NT(v) = TRUE;
for (i=0; i < nthread; ++i) {
data = N_VNew_Serial(sizes[i]);
if(data == NULL) {N_VDestroy_NrnThread(v);return(NULL);}
NV_SUBVEC_NT(v, i) = data;
}
}
return(v);
}
int main()
{
void *mem;
UserData data;
N_Vector uu, up, constraints, res;
int ier, iout;
realtype rtol, atol, t0, t1, tout, tret;
long int netf, ncfn, ncfl;
mem = NULL;
data = NULL;
uu = up = constraints = res = NULL;
/* Allocate N-vectors and the user data structure. */
uu = N_VNew_Serial(NEQ);
if(check_flag((void *)uu, "N_VNew_Serial", 0)) return(1);
up = N_VNew_Serial(NEQ);
if(check_flag((void *)up, "N_VNew_Serial", 0)) return(1);
res = N_VNew_Serial(NEQ);
if(check_flag((void *)res, "N_VNew_Serial", 0)) return(1);
constraints = N_VNew_Serial(NEQ);
if(check_flag((void *)constraints, "N_VNew_Serial", 0)) return(1);
data = (UserData) malloc(sizeof *data);
data->pp = NULL;
if(check_flag((void *)data, "malloc", 2)) return(1);
/* Assign parameters in the user data structure. */
data->mm = MGRID;
data->dx = ONE/(MGRID-ONE);
data->coeff = ONE/(data->dx * data->dx);
data->pp = N_VNew_Serial(NEQ);
if(check_flag((void *)data->pp, "N_VNew_Serial", 0)) return(1);
/* Initialize uu, up. */
SetInitialProfile(data, uu, up, res);
/* Set constraints to all 1's for nonnegative solution values. */
N_VConst(ONE, constraints);
/* Assign various parameters. */
t0 = ZERO;
t1 = RCONST(0.01);
rtol = ZERO;
atol = RCONST(1.0e-3);
/* Call IDACreate and IDAMalloc to initialize solution */
mem = IDACreate();
if(check_flag((void *)mem, "IDACreate", 0)) return(1);
ier = IDASetUserData(mem, data);
if(check_flag(&ier, "IDASetUserData", 1)) return(1);
ier = IDASetConstraints(mem, constraints);
if(check_flag(&ier, "IDASetConstraints", 1)) return(1);
N_VDestroy_Serial(constraints);
ier = IDAInit(mem, resHeat, t0, uu, up);
if(check_flag(&ier, "IDAInit", 1)) return(1);
ier = IDASStolerances(mem, rtol, atol);
if(check_flag(&ier, "IDASStolerances", 1)) return(1);
/* Call IDASpgmr to specify the linear solver. */
ier = IDASpgmr(mem, 0);
if(check_flag(&ier, "IDASpgmr", 1)) return(1);
ier = IDASpilsSetPreconditioner(mem, PsetupHeat, PsolveHeat);
if(check_flag(&ier, "IDASpilsSetPreconditioner", 1)) return(1);
/* Print output heading. */
PrintHeader(rtol, atol);
/*
* -------------------------------------------------------------------------
* CASE I
* -------------------------------------------------------------------------
*/
/* Print case number, output table heading, and initial line of table. */
printf("\n\nCase 1: gsytpe = MODIFIED_GS\n");
printf("\n Output Summary (umax = max-norm of solution) \n\n");
printf(" time umax k nst nni nje nre nreLS h npe nps\n" );
printf("----------------------------------------------------------------------\n");
/* Loop over output times, call IDASolve, and print results. */
for (tout = t1,iout = 1; iout <= NOUT ; iout++, tout *= TWO) {
ier = IDASolve(mem, tout, &tret, uu, up, IDA_NORMAL);
if(check_flag(&ier, "IDASolve", 1)) return(1);
PrintOutput(mem, tret, uu);
}
/* Print remaining counters. */
ier = IDAGetNumErrTestFails(mem, &netf);
check_flag(&ier, "IDAGetNumErrTestFails", 1);
ier = IDAGetNumNonlinSolvConvFails(mem, &ncfn);
check_flag(&ier, "IDAGetNumNonlinSolvConvFails", 1);
ier = IDASpilsGetNumConvFails(mem, &ncfl);
check_flag(&ier, "IDASpilsGetNumConvFails", 1);
printf("\nError test failures = %ld\n", netf);
printf("Nonlinear convergence failures = %ld\n", ncfn);
printf("Linear convergence failures = %ld\n", ncfl);
/*
* -------------------------------------------------------------------------
* CASE II
* -------------------------------------------------------------------------
*/
/* Re-initialize uu, up. */
SetInitialProfile(data, uu, up, res);
/* Re-initialize IDA and IDASPGMR */
ier = IDAReInit(mem, t0, uu, up);
if(check_flag(&ier, "IDAReInit", 1)) return(1);
ier = IDASpilsSetGSType(mem, CLASSICAL_GS);
if(check_flag(&ier, "IDASpilsSetGSType",1)) return(1);
/* Print case number, output table heading, and initial line of table. */
printf("\n\nCase 2: gstype = CLASSICAL_GS\n");
printf("\n Output Summary (umax = max-norm of solution) \n\n");
printf(" time umax k nst nni nje nre nreLS h npe nps\n" );
printf("----------------------------------------------------------------------\n");
/* Loop over output times, call IDASolve, and print results. */
for (tout = t1,iout = 1; iout <= NOUT ; iout++, tout *= TWO) {
ier = IDASolve(mem, tout, &tret, uu, up, IDA_NORMAL);
if(check_flag(&ier, "IDASolve", 1)) return(1);
PrintOutput(mem, tret, uu);
}
/* Print remaining counters. */
ier = IDAGetNumErrTestFails(mem, &netf);
check_flag(&ier, "IDAGetNumErrTestFails", 1);
ier = IDAGetNumNonlinSolvConvFails(mem, &ncfn);
check_flag(&ier, "IDAGetNumNonlinSolvConvFails", 1);
ier = IDASpilsGetNumConvFails(mem, &ncfl);
check_flag(&ier, "IDASpilsGetNumConvFails", 1);
printf("\nError test failures = %ld\n", netf);
printf("Nonlinear convergence failures = %ld\n", ncfn);
printf("Linear convergence failures = %ld\n", ncfl);
/* Free Memory */
IDAFree(&mem);
N_VDestroy_Serial(uu);
N_VDestroy_Serial(up);
N_VDestroy_Serial(res);
N_VDestroy_Serial(data->pp);
free(data);
return(0);
}
int main()
{
realtype abstol, reltol, t, tout;
N_Vector u;
UserData data;
void *cvode_mem;
int flag, iout, jpre;
long int ml, mu;
u = NULL;
data = NULL;
cvode_mem = NULL;
/* Allocate and initialize u, and set problem data and tolerances */
u = N_VNew_Serial(NEQ);
if(check_flag((void *)u, "N_VNew_Serial", 0)) return(1);
data = (UserData) malloc(sizeof *data);
if(check_flag((void *)data, "malloc", 2)) return(1);
InitUserData(data);
SetInitialProfiles(u, data->dx, data->dy);
abstol = ATOL;
reltol = RTOL;
/* Call CVodeCreate to create the solver memory and specify the
* Backward Differentiation Formula and the use of a Newton iteration */
cvode_mem = CVodeCreate(CV_BDF, CV_NEWTON);
if(check_flag((void *)cvode_mem, "CVodeCreate", 0)) return(1);
/* Set the pointer to user-defined data */
flag = CVodeSetUserData(cvode_mem, data);
if(check_flag(&flag, "CVodeSetUserData", 1)) return(1);
/* Call CVodeInit to initialize the integrator memory and specify the
* user's right hand side function in u'=f(t,u), the inital time T0, and
* the initial dependent variable vector u. */
flag = CVodeInit(cvode_mem, f, T0, u);
if(check_flag(&flag, "CVodeInit", 1)) return(1);
/* Call CVodeSStolerances to specify the scalar relative tolerance
* and scalar absolute tolerances */
flag = CVodeSStolerances(cvode_mem, reltol, abstol);
if (check_flag(&flag, "CVodeSStolerances", 1)) return(1);
/* Call CVSpgmr to specify the linear solver CVSPGMR
with left preconditioning and the maximum Krylov dimension maxl */
flag = CVSpgmr(cvode_mem, PREC_LEFT, 0);
if(check_flag(&flag, "CVSpgmr", 1)) return(1);
/* Call CVBandPreInit to initialize band preconditioner */
ml = mu = 2;
flag = CVBandPrecInit(cvode_mem, NEQ, mu, ml);
if(check_flag(&flag, "CVBandPrecInit", 0)) return(1);
PrintIntro(mu, ml);
/* Loop over jpre (= PREC_LEFT, PREC_RIGHT), and solve the problem */
for (jpre = PREC_LEFT; jpre <= PREC_RIGHT; jpre++) {
/* On second run, re-initialize u, the solver, and CVSPGMR */
if (jpre == PREC_RIGHT) {
SetInitialProfiles(u, data->dx, data->dy);
flag = CVodeReInit(cvode_mem, T0, u);
if(check_flag(&flag, "CVodeReInit", 1)) return(1);
flag = CVSpilsSetPrecType(cvode_mem, PREC_RIGHT);
check_flag(&flag, "CVSpilsSetPrecType", 1);
printf("\n\n-------------------------------------------------------");
printf("------------\n");
}
printf("\n\nPreconditioner type is: jpre = %s\n\n",
(jpre == PREC_LEFT) ? "PREC_LEFT" : "PREC_RIGHT");
/* In loop over output points, call CVode, print results, test for error */
for (iout = 1, tout = TWOHR; iout <= NOUT; iout++, tout += TWOHR) {
flag = CVode(cvode_mem, tout, u, &t, CV_NORMAL);
check_flag(&flag, "CVode", 1);
PrintOutput(cvode_mem, u, t);
if (flag != CV_SUCCESS) {
break;
}
}
/* Print final statistics */
PrintFinalStats(cvode_mem);
} /* End of jpre loop */
/* Free memory */
N_VDestroy_Serial(u);
free(data);
CVodeFree(&cvode_mem);
return(0);
}
int nlsKinsolAllocate(int size, NONLINEAR_SYSTEM_DATA *nlsData, int linearSolverMethod)
{
int i, flag, printLevel;
NLS_KINSOL_DATA *kinsolData = (NLS_KINSOL_DATA*) malloc(sizeof(NLS_KINSOL_DATA));
/* allocate system data */
nlsData->solverData = (void*)kinsolData;
kinsolData->size = size;
kinsolData->linearSolverMethod = linearSolverMethod;
kinsolData->solved = 0;
kinsolData->fnormtol = sqrt(newtonFTol); /* function tolerance */
kinsolData->scsteptol = sqrt(newtonXTol); /* step tolerance */
kinsolData->initialGuess = N_VNew_Serial(size);
kinsolData->xScale = N_VNew_Serial(size);
kinsolData->fScale = N_VNew_Serial(size);
kinsolData->fRes = N_VNew_Serial(size);
kinsolData->kinsolMemory = KINCreate();
/* setup user defined functions */
KINSetErrHandlerFn(kinsolData->kinsolMemory, nlsKinsolErrorPrint, kinsolData);
KINSetInfoHandlerFn(kinsolData->kinsolMemory, nlsKinsolInfoPrint, kinsolData);
KINSetUserData(kinsolData->kinsolMemory, (void*)&(kinsolData->userData));
flag = KINInit(kinsolData->kinsolMemory, nlsKinsolResiduals, kinsolData->initialGuess);
if (checkReturnFlag(flag)){
errorStreamPrint(LOG_STDOUT, 0, "##KINSOL## Something goes wrong while initialize KINSOL solver!");
}
/* Specify linear solver and/or corresponding jacobian function*/
if (kinsolData->linearSolverMethod == 3)
{
if(nlsData->isPatternAvailable)
{
kinsolData->nnz = nlsData->sparsePattern.numberOfNoneZeros;
flag = KINKLU(kinsolData->kinsolMemory, size, kinsolData->nnz);
if (checkReturnFlag(flag)){
errorStreamPrint(LOG_STDOUT, 0, "##KINSOL## Something goes wrong while initialize KINSOL solver!");
}
flag = KINSlsSetSparseJacFn(kinsolData->kinsolMemory, nlsSparseJac);
if (checkReturnFlag(flag)){
errorStreamPrint(LOG_STDOUT, 0, "##KINSOL## Something goes wrong while initialize KINSOL Sparse Solver!");
}
}
else
{
flag = KINDense(kinsolData->kinsolMemory, size);
if (checkReturnFlag(flag)){
errorStreamPrint(LOG_STDOUT, 0, "##KINSOL## Something goes wrong while initialize KINSOL solver!");
}
}
}
else if (kinsolData->linearSolverMethod == 1)
{
flag = KINDense(kinsolData->kinsolMemory, size);
if (checkReturnFlag(flag)){
errorStreamPrint(LOG_STDOUT, 0, "##KINSOL## Something goes wrong while initialize KINSOL solver!");
}
}
else if (kinsolData->linearSolverMethod == 2)
{
flag = KINDense(kinsolData->kinsolMemory, size);
if (checkReturnFlag(flag)){
errorStreamPrint(LOG_STDOUT, 0, "##KINSOL## Something goes wrong while initialize KINSOL solver!");
}
flag = KINDlsSetDenseJacFn(kinsolData->kinsolMemory, nlsDenseJac);
if (checkReturnFlag(flag)){
errorStreamPrint(LOG_STDOUT, 0, "##KINSOL## Something goes wrong while initialize KINSOL Sparse Solver!");
}
}
/* configuration */
nlsKinsolConfigSetup(kinsolData);
/* debug print level of kinsol */
if (ACTIVE_STREAM(LOG_NLS))
printLevel = 1;
else if (ACTIVE_STREAM(LOG_NLS_V))
printLevel = 3;
else
printLevel = 0;
KINSetPrintLevel(kinsolData->kinsolMemory, printLevel);
return 0;
}
/* creates CVODES forward sensitivity solver structures
return 1 => success
return 0 => failure
*/
int
IntegratorInstance_createCVODESSolverStructures(integratorInstance_t *engine)
{
int i, j, flag, neq, ns;
realtype *ydata, *abstoldata, *ySdata, *senstoldata;
odeModel_t *om = engine->om;
cvodeData_t *data = engine->data;
cvodeSolver_t *solver = engine->solver;
cvodeSettings_t *opt = engine->opt;
/* realtype pbar[data->nsens+1]; */
/*int *plist; removed by AMF 8/11/05
realtype *pbar;
ASSIGN_NEW_MEMORY_BLOCK(plist, data->nsens+1, int, 0)
ASSIGN_NEW_MEMORY_BLOCK(pbar, data->nsens+1, realtype, 0)*/
/***** adding sensitivity specific structures ******/
/**
* construct sensitivity related structures
*/
/* free sensitivity from former runs (changed for non-default cases!) */
ODEModel_freeSensitivity(om);
/* if jacobian matrix has been constructed successfully,
construct sensitivity matrix dx/dp, sets om->sensitivity
to 1 if successful, 0 otherwise */
/*!!! this function will require additional input for
non-default case, via sensitivity input settings! !!!*/
if ( om->jacobian )
ODEModel_constructSensitivity(om);
else {
om->sensitivity = 0;
om->jacob_sens = NULL;
om->nsens = om->nconst;
ASSIGN_NEW_MEMORY_BLOCK(om->index_sens, om->nsens, int, 0);
/*!!! non-default case:
these values should be passed for other cases !!!*/
for ( i=0; i<om->nsens; i++ )
om->index_sens[i] = om->neq + om->nass + i;
}
engine->solver->nsens = data->nsens;
solver->yS = N_VNewVectorArray_Serial(data->nsens, data->neq);
if (check_flag((void *)solver->yS, "N_VNewVectorArray_Serial",
1, stderr))
return(0);
/*
* (re)initialize ySdata sensitivities
*/
/* absolute tolerance for sensitivity error control */
solver->senstol = N_VNew_Serial(data->nsens);
abstoldata = NV_DATA_S(solver->senstol);
for ( j=0; j<data->nsens; j++ ) {
abstoldata[j] = 1e-4;
ySdata = NV_DATA_S(solver->yS[j]);
for ( i=0; i<data->neq; i++ )
ySdata[i] = data->sensitivity[i][j];
}
/*
* set method
*/
if ( opt->SensMethod == 0 )
flag =CVodeSensMalloc(solver->cvode_mem,data->nsens,
CV_SIMULTANEOUS, solver->yS);
else if ( opt->SensMethod == 1 )
flag = CVodeSensMalloc(solver->cvode_mem, data->nsens,
CV_STAGGERED, solver->yS);
else if ( opt->SensMethod == 2 )
flag = CVodeSensMalloc(solver->cvode_mem, data->nsens,
CV_STAGGERED1, solver->yS);
if(check_flag(&flag, "CVodeSensMalloc", 1, stderr)) {
return 0;
/* ERROR HANDLING CODE if failes */
}
/* *** set parameter values or R.H.S function fS *****/
/* NOTES: */
/* !!! plist could later be used to specify requested parameters
for sens.analysis !!! */
/* was construction of Jacobian and
parametric matrix successfull ? */
if ( om->sensitivity && om->jacobian ) {
flag = CVodeSetSensRhs1Fn(solver->cvode_mem, fS);
if (check_flag(&flag, "CVodeSetSensRhs1Fn", 1, stderr)) {
return 0;
/* ERROR HANDLING CODE if failes */
}
flag = CVodeSetSensFdata(solver->cvode_mem, data);
if (check_flag(&flag, "CVodeSetSensFdata", 1, stderr)) {
return 0;
/* ERROR HANDLING CODE if failes */
}
data->p = NULL;
}
else {
ASSIGN_NEW_MEMORY_BLOCK(data->p, data->nsens, realtype, 0);
for ( i=0; i<data->nsens; i++ ) {
/* data->p is only required if R.H.S. fS cannot be supplied */
/* plist[i] = i+1; */
data->p[i] = data->value[om->index_sens[i]];
/* pbar[i] = abs(data->p[i]); */ /*??? WHAT IS PBAR ???*/
}
flag = CVodeSetSensParams(solver->cvode_mem, data->p, NULL, NULL);
if (check_flag(&flag, "CVodeSetSensParams", 1, stderr)) {
return 0;
/* ERROR HANDLING CODE if failes */
}
flag = CVodeSetSensRho(solver->cvode_mem, 0.0); /* what is it? */
if (check_flag(&flag, "CVodeSetSensRhs1Fn", 1, stderr)) {
/* ERROR HANDLING CODE if failes */
return 0;
}
}
/* CVodeSetSensTolerances(solver->cvode_mem, CV_SS, */
/* solver->reltol, &solver->senstol); */
/* difference FALSE/TRUE ? */
flag = CVodeSetSensErrCon(solver->cvode_mem, FALSE);
if (check_flag(&flag, "CVodeSetSensFdata", 1, stderr)) {
return 0;
/* ERROR HANDLING CODE if failes */
}
return 1; /* OK */
}
int main()
{
realtype abstol=ATOL, reltol=RTOL, t, tout;
N_Vector c;
WebData wdata;
void *cvode_mem;
booleantype firstrun;
int jpre, gstype, flag;
int ns, mxns, iout;
c = NULL;
wdata = NULL;
cvode_mem = NULL;
/* Initializations */
c = N_VNew_Serial(NEQ);
if(check_flag((void *)c, "N_VNew_Serial", 0)) return(1);
wdata = AllocUserData();
if(check_flag((void *)wdata, "AllocUserData", 2)) return(1);
InitUserData(wdata);
ns = wdata->ns;
mxns = wdata->mxns;
/* Print problem description */
PrintIntro();
/* Loop over jpre and gstype (four cases) */
for (jpre = PREC_LEFT; jpre <= PREC_RIGHT; jpre++) {
for (gstype = MODIFIED_GS; gstype <= CLASSICAL_GS; gstype++) {
/* Initialize c and print heading */
CInit(c, wdata);
PrintHeader(jpre, gstype);
/* Call CVodeInit or CVodeReInit, then CVSpgmr to set up problem */
firstrun = (jpre == PREC_LEFT) && (gstype == MODIFIED_GS);
if (firstrun) {
cvode_mem = CVodeCreate(CV_BDF, CV_NEWTON);
if(check_flag((void *)cvode_mem, "CVodeCreate", 0)) return(1);
wdata->cvode_mem = cvode_mem;
flag = CVodeSetUserData(cvode_mem, wdata);
if(check_flag(&flag, "CVodeSetUserData", 1)) return(1);
flag = CVodeInit(cvode_mem, f, T0, c);
if(check_flag(&flag, "CVodeInit", 1)) return(1);
flag = CVodeSStolerances(cvode_mem, reltol, abstol);
if (check_flag(&flag, "CVodeSStolerances", 1)) return(1);
flag = CVSpgmr(cvode_mem, jpre, MAXL);
if(check_flag(&flag, "CVSpgmr", 1)) return(1);
flag = CVSpilsSetGSType(cvode_mem, gstype);
if(check_flag(&flag, "CVSpilsSetGSType", 1)) return(1);
flag = CVSpilsSetEpsLin(cvode_mem, DELT);
if(check_flag(&flag, "CVSpilsSetEpsLin", 1)) return(1);
flag = CVSpilsSetPreconditioner(cvode_mem, Precond, PSolve);
if(check_flag(&flag, "CVSpilsSetPreconditioner", 1)) return(1);
} else {
flag = CVodeReInit(cvode_mem, T0, c);
if(check_flag(&flag, "CVodeReInit", 1)) return(1);
flag = CVSpilsSetPrecType(cvode_mem, jpre);
check_flag(&flag, "CVSpilsSetPrecType", 1);
flag = CVSpilsSetGSType(cvode_mem, gstype);
if(check_flag(&flag, "CVSpilsSetGSType", 1)) return(1);
}
/* Print initial values */
if (firstrun) PrintAllSpecies(c, ns, mxns, T0);
/* Loop over output points, call CVode, print sample solution values. */
tout = T1;
for (iout = 1; iout <= NOUT; iout++) {
flag = CVode(cvode_mem, tout, c, &t, CV_NORMAL);
PrintOutput(cvode_mem, t);
if (firstrun && (iout % 3 == 0)) PrintAllSpecies(c, ns, mxns, t);
if(check_flag(&flag, "CVode", 1)) break;
if (tout > RCONST(0.9)) tout += DTOUT;
else tout *= TOUT_MULT;
}
/* Print final statistics, and loop for next case */
PrintFinalStats(cvode_mem);
}
}
/* Free all memory */
CVodeFree(&cvode_mem);
N_VDestroy_Serial(c);
FreeUserData(wdata);
return(0);
}
