void CSparseCholeskyInternal::prepare() {
prepared_ = false;
// Get a reference to the nonzeros of the linear system
const vector<double>& linsys_nz = input().data();
// Make sure that all entries of the linear system are valid
for (int k=0; k<linsys_nz.size(); ++k) {
casadi_assert_message(!isnan(linsys_nz[k]), "Nonzero " << k << " is not-a-number");
casadi_assert_message(!isinf(linsys_nz[k]), "Nonzero " << k << " is infinite");
}
if (verbose()) {
userOut() << "CSparseCholeskyInternal::prepare: numeric factorization" << endl;
userOut() << "linear system to be factorized = " << endl;
input(0).printSparse();
}
if (L_) cs_nfree(L_);
L_ = cs_chol(&AT_, S_) ; // numeric Cholesky factorization
if (L_==0) {
DMatrix temp = input();
temp.makeSparse();
if (temp.sparsity().issingular()) {
stringstream ss;
ss << "CSparseCholeskyInternal::prepare: factorization failed due "
"to matrix being singular. Matrix contains numerical zeros which are"
" structurally non-zero. Promoting these zeros to be structural "
"zeros, the matrix was found to be structurally rank deficient. "
"sprank: " << sprank(temp.sparsity()) << " <-> " << temp.size2() << endl;
if (verbose()) {
ss << "Sparsity of the linear system: " << endl;
input(LINSOL_A).sparsity().print(ss); // print detailed
}
throw CasadiException(ss.str());
} else {
stringstream ss;
ss << "CSparseCholeskyInternal::prepare: factorization failed, "
"check if Jacobian is singular" << endl;
if (verbose()) {
ss << "Sparsity of the linear system: " << endl;
input(LINSOL_A).sparsity().print(ss); // print detailed
}
throw CasadiException(ss.str());
}
}
casadi_assert(L_!=0);
prepared_ = true;
}
void CsparseInterface::prepare() {
double time_start=0;
if (CasadiOptions::profiling && CasadiOptions::profilingBinary) {
time_start = getRealTime(); // Start timer
profileWriteEntry(CasadiOptions::profilingLog, this);
}
if (!called_once_) {
if (verbose()) {
cout << "CsparseInterface::prepare: symbolic factorization" << endl;
}
// ordering and symbolic analysis
int order = 0; // ordering?
if (S_) cs_sfree(S_);
S_ = cs_sqr(order, &A_, 0) ;
}
prepared_ = false;
called_once_ = true;
// Get a referebce to the nonzeros of the linear system
const vector<double>& linsys_nz = input().data();
// Make sure that all entries of the linear system are valid
for (int k=0; k<linsys_nz.size(); ++k) {
casadi_assert_message(!isnan(linsys_nz[k]), "Nonzero " << k << " is not-a-number");
casadi_assert_message(!isinf(linsys_nz[k]), "Nonzero " << k << " is infinite");
}
if (verbose()) {
cout << "CsparseInterface::prepare: numeric factorization" << endl;
cout << "linear system to be factorized = " << endl;
input(0).printSparse();
}
double tol = 1e-8;
if (N_) cs_nfree(N_);
N_ = cs_lu(&A_, S_, tol) ; // numeric LU factorization
if (N_==0) {
DMatrix temp = input();
temp.makeSparse();
if (temp.sparsity().isSingular()) {
stringstream ss;
ss << "CsparseInterface::prepare: factorization failed due to matrix"
" being singular. Matrix contains numerical zeros which are "
"structurally non-zero. Promoting these zeros to be structural "
"zeros, the matrix was found to be structurally rank deficient."
" sprank: " << sprank(temp.sparsity()) << " <-> " << temp.size2() << endl;
if (verbose()) {
ss << "Sparsity of the linear system: " << endl;
input(LINSOL_A).sparsity().print(ss); // print detailed
}
throw CasadiException(ss.str());
} else {
stringstream ss;
ss << "CsparseInterface::prepare: factorization failed, check if Jacobian is singular"
<< endl;
if (verbose()) {
ss << "Sparsity of the linear system: " << endl;
input(LINSOL_A).sparsity().print(ss); // print detailed
}
throw CasadiException(ss.str());
}
}
casadi_assert(N_!=0);
prepared_ = true;
if (CasadiOptions::profiling && CasadiOptions::profilingBinary) {
double time_stop = getRealTime(); // Stop timer
profileWriteTime(CasadiOptions::profilingLog, this, 0,
time_stop-time_start,
time_stop-time_start);
profileWriteExit(CasadiOptions::profilingLog, this, time_stop-time_start);
}
}
void ImplicitFunctionInternal::init() {
// Initialize the residual function
f_.init(false);
// Which input/output correspond to the root-finding problem?
iin_ = getOption("implicit_input");
iout_ = getOption("implicit_output");
// Get the number of equations and check consistency
casadi_assert_message(iin_>=0 && iin_<f_.getNumInputs() && f_.getNumInputs()>0,
"Implicit input not in range");
casadi_assert_message(iout_>=0 && iout_<f_.getNumOutputs() && f_.getNumOutputs()>0,
"Implicit output not in range");
casadi_assert_message(f_.output(iout_).isDense() && f_.output(iout_).isVector(),
"Residual must be a dense vector");
casadi_assert_message(f_.input(iin_).isDense() && f_.input(iin_).isVector(),
"Unknown must be a dense vector");
n_ = f_.output(iout_).size();
casadi_assert_message(n_ == f_.input(iin_).size(),
"Dimension mismatch. Input size is "
<< f_.input(iin_).size()
<< ", while output size is "
<< f_.output(iout_).size());
// Allocate inputs
setNumInputs(f_.getNumInputs());
for (int i=0; i<getNumInputs(); ++i) {
input(i) = f_.input(i);
}
// Allocate output
setNumOutputs(f_.getNumOutputs());
for (int i=0; i<getNumOutputs(); ++i) {
output(i) = f_.output(i);
}
// Same input and output schemes
setInputScheme(f_.getInputScheme());
setOutputScheme(f_.getOutputScheme());
// Call the base class initializer
FunctionInternal::init();
// Generate Jacobian if not provided
if (jac_.isNull()) jac_ = f_.jacobian(iin_, iout_);
jac_.init(false);
// Check for structural singularity in the Jacobian
casadi_assert_message(
!jac_.output().sparsity().isSingular(),
"ImplicitFunctionInternal::init: singularity - the jacobian is structurally rank-deficient. "
"sprank(J)=" << sprank(jac_.output()) << " (instead of "<< jac_.output().size1() << ")");
// Get the linear solver creator function
if (linsol_.isNull()) {
if (hasSetOption("linear_solver")) {
std::string linear_solver_name = getOption("linear_solver");
// Allocate an NLP solver
linsol_ = LinearSolver(linear_solver_name, jac_.output().sparsity(), 1);
// Pass options
if (hasSetOption("linear_solver_options")) {
const Dictionary& linear_solver_options = getOption("linear_solver_options");
linsol_.setOption(linear_solver_options);
}
// Initialize
linsol_.init();
}
} else {
// Initialize the linear solver, if provided
linsol_.init(false);
casadi_assert(linsol_.input().sparsity()==jac_.output().sparsity());
}
// No factorization yet;
fact_up_to_date_ = false;
// Constraints
if (hasSetOption("constraints")) u_c_ = getOption("constraints");
casadi_assert_message(u_c_.size()==n_ || u_c_.empty(),
"Constraint vector if supplied, must be of length n, but got "
<< u_c_.size() << " and n = " << n_);
}
void ImplicitFunctionInternal::init(){
// Initialize the residual function
if(!f_.isInit()) f_.init();
// Allocate inputs
setNumInputs(f_.getNumInputs()-1);
for(int i=0; i<getNumInputs(); ++i){
input(i) = f_.input(i+1);
}
// Allocate outputs
setNumOutputs(f_.getNumOutputs());
output(0) = f_.input(0);
for(int i=1; i<getNumOutputs(); ++i){
output(i) = f_.output(i);
}
// Call the base class initializer
FXInternal::init();
// Number of equations
N_ = output().size();
// Generate Jacobian if not provided
if(J_.isNull()) J_ = f_.jacobian(0,0);
J_.init();
casadi_assert_message(J_.output().size1()==J_.output().size2(),"ImplicitFunctionInternal::init: the jacobian must be square but got " << J_.output().dimString());
casadi_assert_message(!isSingular(J_.output().sparsity()),"ImplicitFunctionInternal::init: singularity - the jacobian is structurally rank-deficient. sprank(J)=" << sprank(J_.output()) << " (in stead of "<< J_.output().size1() << ")");
// Get the linear solver creator function
if(linsol_.isNull() && hasSetOption("linear_solver")){
linearSolverCreator linear_solver_creator = getOption("linear_solver");
// Allocate an NLP solver
linsol_ = linear_solver_creator(CRSSparsity());
// Pass options
if(hasSetOption("linear_solver_options")){
const Dictionary& linear_solver_options = getOption("linear_solver_options");
linsol_.setOption(linear_solver_options);
}
}
// Initialize the linear solver, if provided
if(!linsol_.isNull()){
linsol_.setSparsity(J_.output().sparsity());
linsol_.init();
}
// Allocate memory for directional derivatives
ImplicitFunctionInternal::updateNumSens(false);
}
void SundialsInterface::init(const Dict& opts) {
// Call the base class method
Integrator::init(opts);
// Default options
abstol_ = 1e-8;
reltol_ = 1e-6;
exact_jacobian_ = true;
max_num_steps_ = 10000;
finite_difference_fsens_ = false;
stop_at_end_ = true;
use_preconditioner_ = false;
max_krylov_ = 10;
string linear_solver_type = "dense";
string iterative_solver = "gmres";
string pretype = "none";
string linear_solver;
Dict linear_solver_options;
upper_bandwidth_ = -1;
lower_bandwidth_ = -1;
upper_bandwidthB_ = -1;
lower_bandwidthB_ = -1;
quad_err_con_ = false;
interpolation_type_ = "hermite";
steps_per_checkpoint_ = 20;
disable_internal_warnings_ = false;
max_multistep_order_ = 5;
// Read options
for (auto&& op : opts) {
if (op.first=="abstol") {
abstol_ = op.second;
} else if (op.first=="reltol") {
reltol_ = op.second;
} else if (op.first=="exact_jacobian") {
exact_jacobian_ = op.second;
} else if (op.first=="max_num_steps") {
max_num_steps_ = op.second;
} else if (op.first=="finite_difference_fsens") {
finite_difference_fsens_ = op.second;
} else if (op.first=="stop_at_end") {
stop_at_end_ = op.second;
} else if (op.first=="use_preconditioner") {
use_preconditioner_ = op.second;
} else if (op.first=="max_krylov") {
max_krylov_ = op.second;
} else if (op.first=="linear_solver_type") {
linear_solver_type = op.second.to_string();
} else if (op.first=="iterative_solver") {
iterative_solver = op.second.to_string();
} else if (op.first=="pretype") {
pretype = op.second.to_string();
} else if (op.first=="linear_solver") {
linear_solver = op.second.to_string();
} else if (op.first=="linear_solver_options") {
linear_solver_options = op.second;
} else if (op.first=="upper_bandwidth") {
upper_bandwidth_ = op.second;
} else if (op.first=="lower_bandwidth") {
lower_bandwidth_ = op.second;
} else if (op.first=="upper_bandwidthB") {
upper_bandwidthB_ = op.second;
} else if (op.first=="lower_bandwidthB") {
lower_bandwidthB_ = op.second;
} else if (op.first=="quad_err_con") {
quad_err_con_ = op.second;
} else if (op.first=="interpolation_type") {
interpolation_type_ = op.second.to_string();
} else if (op.first=="steps_per_checkpoint") {
steps_per_checkpoint_ = op.second;
} else if (op.first=="disable_internal_warnings") {
disable_internal_warnings_ = op.second;
} else if (op.first=="max_multistep_order") {
max_multistep_order_ = op.second;
}
}
// Default dependent options
exact_jacobianB_ = exact_jacobian_;
fsens_abstol_ = abstol_;
fsens_reltol_ = reltol_;
abstolB_ = abstol_;
reltolB_ = reltol_;
use_preconditionerB_ = use_preconditioner_;
max_krylovB_ = max_krylov_;
std::string linear_solver_typeB = linear_solver_type;
std::string iterative_solverB = iterative_solver;
std::string pretypeB = pretype;
string linear_solverB = linear_solver;
Dict linear_solver_optionsB = linear_solver_options;
// Read options again
for (auto&& op : opts) {
if (op.first=="exact_jacobianB") {
exact_jacobianB_ = op.second;
} else if (op.first=="fsens_abstol") {
fsens_abstol_ = op.second;
} else if (op.first=="fsens_reltol") {
fsens_reltol_ = op.second;
} else if (op.first=="abstolB") {
abstolB_ = op.second;
} else if (op.first=="reltolB") {
reltolB_ = op.second;
} else if (op.first=="use_preconditionerB") {
use_preconditionerB_ = op.second;
} else if (op.first=="max_krylovB") {
max_krylovB_ = op.second;
} else if (op.first=="linear_solver_typeB") {
linear_solver_typeB = op.second.to_string();
} else if (op.first=="iterative_solverB") {
iterative_solverB = op.second.to_string();
} else if (op.first=="pretypeB") {
pretypeB = op.second.to_string();
} else if (op.first=="linear_solverB") {
linear_solverB = op.second.to_string();
} else if (op.first=="linear_solver_optionsB") {
linear_solver_optionsB = op.second;
}
}
// No Jacobian of g if g doesn't exist
if (g_.is_null()) {
exact_jacobianB_ = false;
}
// Linear solver for forward integration
if (linear_solver_type=="dense") {
linsol_f_ = SD_DENSE;
} else if (linear_solver_type=="banded") {
linsol_f_ = SD_BANDED;
} else if (linear_solver_type=="iterative") {
linsol_f_ = SD_ITERATIVE;
// Iterative solver
if (iterative_solver=="gmres") {
itsol_f_ = SD_GMRES;
} else if (iterative_solver=="bcgstab") {
itsol_f_ = SD_BCGSTAB;
} else if (iterative_solver=="tfqmr") {
itsol_f_ = SD_TFQMR;
} else {
casadi_error("Unknown iterative solver for forward integration: " + iterative_solver);
}
// Preconditioning type
if (pretype=="none") {
pretype_f_ = PREC_NONE;
} else if (pretype=="left") {
pretype_f_ = PREC_LEFT;
} else if (pretype=="right") {
pretype_f_ = PREC_RIGHT;
} else if (pretype=="both") {
pretype_f_ = PREC_BOTH;
} else {
casadi_error("Unknown preconditioning type for forward integration: " + pretype);
}
} else if (linear_solver_type=="user_defined") {
linsol_f_ = SD_USER_DEFINED;
} else {
casadi_error("Unknown linear solver for forward integration: " + linear_solver_type);
}
// Linear solver for backward integration
if (linear_solver_typeB=="dense") {
linsol_g_ = SD_DENSE;
} else if (linear_solver_typeB=="banded") {
linsol_g_ = SD_BANDED;
} else if (linear_solver_typeB=="iterative") {
linsol_g_ = SD_ITERATIVE;
// Iterative solver
if (iterative_solverB=="gmres") {
itsol_g_ = SD_GMRES;
} else if (iterative_solverB=="bcgstab") {
itsol_g_ = SD_BCGSTAB;
} else if (iterative_solverB=="tfqmr") {
itsol_g_ = SD_TFQMR;
} else {
casadi_error("Unknown sparse solver for backward integration: " + iterative_solverB);
}
// Preconditioning type
if (pretypeB=="none") {
pretype_g_ = PREC_NONE;
} else if (pretypeB=="left") {
pretype_g_ = PREC_LEFT;
} else if (pretypeB=="right") {
pretype_g_ = PREC_RIGHT;
} else if (pretypeB=="both") {
pretype_g_ = PREC_BOTH;
} else {
casadi_error("Unknown preconditioning type for backward integration: " + pretypeB);
}
} else if (linear_solver_typeB=="user_defined") {
linsol_g_ = SD_USER_DEFINED;
} else {
casadi_error("Unknown linear solver for backward integration: " + iterative_solverB);
}
// Create a Jacobian if requested
if (exact_jacobian_) {
jac_ = getJac();
alloc(jac_);
alloc_w(jac_.nnz_out(0), true);
}
if (!jac_.is_null()) {
casadi_assert_message(jac_.size2_out(0)==jac_.size1_out(0),
"SundialsInterface::init: the jacobian of the forward problem must "
"be square but got " << jac_.sparsity_out(0).dim());
casadi_assert_message(!jac_.sparsity_out(0).is_singular(),
"SundialsInterface::init: singularity - the jacobian of the forward "
"problem is structurally rank-deficient. sprank(J)="
<< sprank(jac_.sparsity_out(0)) << " (in stead of "<< jac_.size2_out(0)
<< ")");
}
// Create a backwards Jacobian if requested
if (exact_jacobianB_ && !g_.is_null()) jacB_ = getJacB();
if (!jacB_.is_null()) {
alloc(jacB_);
alloc_w(jacB_.nnz_out(0), true);
casadi_assert_message(jacB_.size2_out(0)==jacB_.size1_out(0),
"SundialsInterface::init: the jacobian of the backward problem must be "
"square but got " << jacB_.sparsity_out(0).dim());
casadi_assert_message(!jacB_.sparsity_out(0).is_singular(),
"SundialsInterface::init: singularity - the jacobian of the backward"
" problem is structurally rank-deficient. sprank(J)="
<< sprank(jacB_.sparsity_out(0)) << " (instead of "
<< jacB_.size2_out(0) << ")");
}
// Create a linear solver
if (!linear_solver.empty() && !jac_.is_null()) {
linsol_ = linsol("linsol", linear_solver, jac_.sparsity_out(0),
1, linear_solver_options);
alloc(linsol_);
}
// Create a linear solver
if (!linear_solverB.empty() && !jacB_.is_null()) {
linsolB_ = linsol("linsolB", linear_solverB, jacB_.sparsity_out(0),
1, linear_solver_optionsB);
alloc(linsolB_);
}
// Allocate temporary memory
//alloc_w(np_, true); // p_
//alloc_w(nrp_, true); // rp_
}
