List of all members | Classes | Public Types | Public Member Functions | Static Public Member Functions | Public Attributes | Protected Member Functions | Friends
casadi::OptiNode Class Reference

A simplified interface for NLP modeling/solving. More...

#include <optistack_internal.hpp>

Detailed Description

Date
2017
Author
Joris Gillis, Erik Lambrechts

Extra doc: https://github.com/casadi/casadi/wiki/L_172

Definition at line 55 of file optistack_internal.hpp.

Inheritance diagram for casadi::OptiNode:
Inheritance graph
[legend]
Collaboration diagram for casadi::OptiNode:
Collaboration graph
[legend]

Public Types

using weak_ref_type = WeakRefInternal
 

Public Member Functions

 OptiNode (const std::string &problem_type)
 Create Opti Context. More...
 
 ~OptiNode ()
 Destructor. More...
 
MX variable (casadi_int n=1, casadi_int m=1, const std::string &attribute="full")
 Create a decision variable (symbol) More...
 
MX variable (const Sparsity &sp, const std::string &attribute="full")
 
MX variable (const MX &symbol, const std::string &attribute="full")
 
MX parameter (casadi_int n=1, casadi_int m=1, const std::string &attribute="full")
 Create a parameter (symbol); fixed during optimization. More...
 
MX parameter (const Sparsity &sp, const std::string &attribute="full")
 Create a parameter (symbol); fixed during optimization. More...
 
MX parameter (const MX &symbol, const std::string &attribute="full")
 
void minimize (const MX &f, double linear_scale=1)
 Set objective. More...
 
void subject_to (const MX &g, const DM &linear_scale=1, const Dict &options=Dict())
 brief Add constraints More...
 
void subject_to ()
 Clear constraints. More...
 
void solver (const std::string &solver, const Dict &plugin_options=Dict(), const Dict &solver_options=Dict())
 Solver. More...
 
void set_domain (const MX &x, const std::string &domain)
 Set domain of variable. More...
 
void set_linear_scale (const MX &x, const DM &scale, const DM &offset)
 Set scale of a decision variable. More...
 
OptiSol solve (bool accept_limit)
 Crunch the numbers; solve the problem. More...
 
Opti copy () const
 Copy. More...
 
Dict stats () const
 Get statistics. More...
 
std::string return_status () const
 Get return status of solver. More...
 
bool return_success (bool accept_limit) const
 Did the solver return successfully? More...
 
Function casadi_solver () const
 Get the underlying CasADi solver of the Opti stack. More...
 
Function scale_helper (const Function &h) const
 Scale a helper function constructed via opti.x, opti.g, ... More...
 
std::vector< MX > initial () const
 get assignment expressions for initial values More...
 
std::vector< MX > value_variables () const
 get assignment expressions for latest values More...
 
std::vector< MX > value_parameters () const
 
void callback_class (OptiCallback *callback)
 
void callback_class ()
 
bool has_callback_class () const
 
bool is_parametric (const MX &expr) const
 return true if expression is only dependant on Opti parameters, not variables More...
 
MetaCon canon_expr (const MX &expr, const DM &linear_scale=1) const
 Interpret an expression (for internal use only) More...
 
MetaVar get_meta (const MX &m) const
 Get meta-data of symbol (for internal use only) More...
 
MetaCon get_meta_con (const MX &m) const
 Get meta-data of symbol (for internal use only) More...
 
void set_meta (const MX &m, const MetaVar &meta)
 Set meta-data of an expression. More...
 
void set_meta_con (const MX &m, const MetaCon &meta)
 Set meta-data of an expression. More...
 
void update_user_dict (const MX &m, const Dict &meta)
 add meta-data of an expression More...
 
Dict user_dict (const MX &m) const
 
MX dual (const MX &m) const
 get the dual variable More...
 
void assert_active_symbol (const MX &m) const
 
std::vector< MX > symvar (VariableType type) const
 
std::vector< MX > active_symvar (VariableType type) const
 
std::vector< DM > active_values (VariableType type) const
 
std::vector< DM > active_values (VariableType type, const std::map< VariableType, std::vector< DM > > &store) const
 
MX x_lookup (casadi_int i) const
 
MX g_lookup (casadi_int i) const
 
std::string x_describe (casadi_int i, const Dict &opts=Dict()) const
 
std::string g_describe (casadi_int i, const Dict &opts=Dict()) const
 
std::string describe (const MX &x, casadi_int indent=0, const Dict &opts=Dict()) const
 
void solve_prepare ()
 
Function solver_construct (bool callback=true)
 
DMDict solve_actual (const DMDict &args)
 
DMDict arg () const
 
void res (const DMDict &res)
 
DMDict res () const
 
std::vector< MX > constraints () const
 
MX objective () const
 
OptiAdvanced baked_copy () const
 
std::string class_name () const override
 Readable name of the internal class. More...
 
casadi_int nx () const
 Number of (scalarised) decision variables. More...
 
casadi_int np () const
 Number of (scalarised) parameters. More...
 
casadi_int ng () const
 Number of (scalarised) constraints. More...
 
MX x () const
 Get all (scalarised) decision variables as a symbolic column vector. More...
 
MX p () const
 Get all (scalarised) parameters as a symbolic column vector. More...
 
MX g () const
 Get all (scalarised) constraint expressions as a column vector. More...
 
MX f () const
 Get objective expression. More...
 
MX lbg () const
 
MX ubg () const
 
MX lam_g () const
 Get dual variables as a symbolic column vector. More...
 
DM x_linear_scale () const
 
DM x_linear_scale_offset () const
 
DM g_linear_scale () const
 
double f_linear_scale () const
 
void assert_empty () const
 
void show_infeasibilities (double tol=0, const Dict &opts=Dict()) const
 
Function to_function (const std::string &name, const std::vector< MX > &args, const std::vector< MX > &res, const std::vector< std::string > &name_in, const std::vector< std::string > &name_out, const Dict &opts)
 Create a CasADi Function from the Opti solver. More...
 
void disp (std::ostream &stream, bool more=false) const override
 Print representation. More...
 
void bake ()
 Fix the structure of the optimization problem. More...
 
casadi_int instance_number () const
 
void mark_problem_dirty (bool flag=true)
 
bool problem_dirty () const
 
void mark_solver_dirty (bool flag=true)
 
bool solver_dirty () const
 
void mark_solved (bool flag=true)
 
bool solved () const
 
void assert_solved () const
 
void assert_baked () const
 
casadi_int g_index_reduce_g (casadi_int i) const
 
casadi_int g_index_reduce_x (casadi_int i) const
 
casadi_int g_index_unreduce_g (casadi_int i) const
 
casadi_int getCount () const
 Get the reference count. More...
 
std::string debug_repr (const SharedObjectInternal *) const
 
GenericWeakRef< SharedObject, SharedObjectInternal > * weak ()
 Get a weak reference to the object. More...
 
void set_initial (const MX &x, const DM &v)
 
void set_initial (const std::vector< MX > &assignments)
 
void set_value (const MX &x, const DM &v)
 Set value of parameter. More...
 
void set_value (const std::vector< MX > &assignments)
 Set value of parameter. More...
 
DM value (const MX &x, const std::vector< MX > &values=std::vector< MX >(), bool scaled=false) const
 
DM value (const DM &x, const std::vector< MX > &values=std::vector< MX >(), bool scaled=false) const
 
DM value (const SX &x, const std::vector< MX > &values=std::vector< MX >(), bool scaled=false) const
 
std::vector< MX > symvar () const
 
std::vector< MX > symvar (const MX &expr) const
 
std::vector< MX > symvar (const MX &expr, VariableType type) const
 

Static Public Member Functions

static OptiNode * create (const std::string &problem_type)
 

Public Attributes

bool problem_dirty_
 
bool solver_dirty_
 
bool solved_
 

Protected Member Functions

void initSingleton ()
 
void destroySingleton ()
 
B shared_from_this ()
 Get a shared object from the current internal object. More...
 
const B shared_from_this () const
 Get a shared object from the current internal object. More...
 

Friends

class InternalOptiCallback
 

Member Typedef Documentation

◆ weak_ref_type

Definition at line 152 of file shared_object.hpp.

Constructor & Destructor Documentation

◆ OptiNode()

casadi::OptiNode::OptiNode ( const std::string &  problem_type)

Definition at line 256 of file optistack_internal.cpp.

256  :
257  count_(0), count_var_(0), count_par_(0), count_dual_(0) {
258  f_ = 0;
259  f_linear_scale_ = 1;
260  instance_number_ = instance_count_++;
261  user_callback_ = nullptr;
262  store_initial_[OPTI_VAR] = {};
263  store_initial_[OPTI_PAR] = {};
264  store_initial_[OPTI_DUAL_G] = {};
265  store_latest_[OPTI_VAR] = {};
266  store_latest_[OPTI_DUAL_G] = {};
267  casadi_assert(problem_type=="nlp" || problem_type=="conic",
268  "Specified problem type '" + problem_type + "'unknown. "
269  "Choose 'nlp' (default) or 'conic'.");
270  problem_type_ = problem_type;
272  helpers_ = std::make_shared<ValueCache>();
273 }
void mark_problem_dirty(bool flag=true)
@ OPTI_DUAL_G
Definition: optistack.hpp:2714

References mark_problem_dirty(), casadi::OPTI_DUAL_G, casadi::OPTI_PAR, and casadi::OPTI_VAR.

Referenced by copy(), and create().

◆ ~OptiNode()

casadi::OptiNode::~OptiNode ( )

Definition at line 275 of file optistack_internal.cpp.

275  {
276 }

Member Function Documentation

◆ active_symvar()

std::vector< MX > casadi::OptiNode::active_symvar ( VariableType  type) const

Definition at line 1656 of file optistack_internal.cpp.

1656  {
1657  if (symbol_active_.empty()) return std::vector<MX>{};
1658  std::vector<MX> ret;
1659  for (const auto& s : symbols_) {
1660  if (symbol_active_[meta(s).count] && meta(s).type==type)
1661  ret.push_back(s);
1662  }
1663  return ret;
1664 }

Referenced by bake(), res(), solve_prepare(), to_function(), and x_lookup().

◆ active_values() [1/2]

std::vector< DM > casadi::OptiNode::active_values ( VariableType  type) const

Definition at line 1676 of file optistack_internal.cpp.

1676  {
1677  return active_values(type, store_initial_);
1678 }
std::vector< DM > active_values(VariableType type) const

Referenced by bake(), solve_prepare(), and to_function().

◆ active_values() [2/2]

std::vector< DM > casadi::OptiNode::active_values ( VariableType  type,
const std::map< VariableType, std::vector< DM > > &  store 
) const

Definition at line 1680 of file optistack_internal.cpp.

1681  {
1682  if (symbol_active_.empty()) return std::vector<DM>{};
1683  std::vector<DM> ret;
1684  for (const auto& s : symbols_) {
1685  if (symbol_active_[meta(s).count] && meta(s).type==type) {
1686  ret.push_back(store.at(meta(s).type)[meta(s).i]);
1687  }
1688  }
1689  return ret;
1690 }

◆ arg()

DMDict casadi::OptiNode::arg ( ) const
inline

Definition at line 211 of file optistack_internal.hpp.

211 { return arg_; }

Referenced by scale_helper(), solve_actual(), solve_prepare(), to_function(), and value().

◆ assert_active_symbol()

void casadi::OptiNode::assert_active_symbol ( const MX &  m) const

Definition at line 1498 of file optistack_internal.cpp.

1498  {
1499  assert_has(m);
1500  assert_baked();
1501  casadi_assert(symbol_active_[meta(m).count], "Opti symbol is not used in Solver."
1502  " It does not make sense to assign a value to it:\n" + describe(m, 1));
1503 }
std::string describe(const MX &x, casadi_int indent=0, const Dict &opts=Dict()) const

References assert_baked(), and describe().

◆ assert_baked()

void casadi::OptiNode::assert_baked ( ) const

Definition at line 1188 of file optistack_internal.cpp.

1188  {
1189  casadi_assert(!problem_dirty(),
1190  "This action is forbidden since you have not baked the Opti stack yet "
1191  "(with calling 'solve').");
1192 }
bool problem_dirty() const

References problem_dirty().

Referenced by assert_active_symbol().

◆ assert_empty()

void casadi::OptiNode::assert_empty ( ) const

Definition at line 1194 of file optistack_internal.cpp.

1194  {
1195  casadi_assert_dev(g_.empty());
1196  casadi_assert_dev(f_.is_empty());
1197 }
bool is_empty(bool both=false) const
Check if the matrix is empty, i.e. if one of the dimensions is zero.

References casadi::GenericMatrix< MatType >::is_empty().

◆ assert_solved()

void casadi::OptiNode::assert_solved ( ) const

Definition at line 1182 of file optistack_internal.cpp.

1182  {
1183  casadi_assert(solved(),
1184  "This action is forbidden since you have not solved the Opti stack yet "
1185  "(with calling 'solve').");
1186 }

References solved().

Referenced by stats(), and value().

◆ bake()

void casadi::OptiNode::bake ( )

Definition at line 739 of file optistack_internal.cpp.

739  {
740  casadi_assert(!f_.is_empty() || !g_.empty(),
741  "You need to specify at least an objective (y calling 'minimize'), "
742  "or a constraint (by calling 'subject_to').");
743 
744  symbol_active_.clear();
745  symbol_active_.resize(symbols_.size());
746  helpers_ = std::make_shared<ValueCache>();
747 
748  // Gather all expressions
749  MX total_expr = vertcat(f_, veccat(g_));
750 
751  // Categorize the symbols appearing in those expressions
752  for (const auto& d : symvar(total_expr))
753  symbol_active_[meta(d).count] = true;
754 
755  std::vector<MX> x = active_symvar(OPTI_VAR);
756  for (casadi_int i=0;i<x.size();++i) meta(x[i]).active_i = i;
757 
758  casadi_int offset = 0;
759  for (const auto& v : x) {
760  meta(v).start = offset;
761  offset+= v.nnz();
762  meta(v).stop = offset;
763  }
764  std::vector<MX> p = active_symvar(OPTI_PAR);
765  for (casadi_int i=0;i<p.size();++i) meta(p[i]).active_i = i;
766 
767  // Fill the nlp definition
768  nlp_["x"] = veccat(x);
769  nlp_["p"] = veccat(p);
770 
771  nlp_unscaled_["x"] = veccat(x);
772  nlp_unscaled_["p"] = veccat(p);
773 
774  discrete_.clear();
775  for (const MX& e : x) {
776  discrete_.insert(discrete_.end(), e.nnz(), meta(e).domain == OPTI_DOMAIN_INTEGER);
777  }
778 
779  nlp_["f"] = f_;
780  nlp_unscaled_["f"] = f_;
781 
782  offset = 0;
783  for (casadi_int i=0;i<g_.size();++i) {
784  MetaCon& r = meta_con(g_[i]);
785  MetaVar& r2 = meta(r.dual_canon);
786  symbol_active_[r2.count] = true;
787 
788  // Compute offsets for this constraint:
789  // location into the global constraint variable
790  r.start = offset;
791  offset+= r.canon.nnz();
792  r.stop = offset;
793 
794  r2.start = r.start;
795  r2.stop = r.stop;
796 
797  }
798  index_all_to_g_.resize(offset);
799  offset = 0;
800  casadi_int offset_g = 0;
801  for (const auto& g : g_) {
802  const MetaCon& r = meta_con(g);
803  if (r.type==OPTI_PSD) {
804  for (casadi_int i=0;i<r.stop-r.start;++i) {
805  index_all_to_g_[r.start+i] = -1;
806  }
807  } else {
808  for (casadi_int i=0;i<r.stop-r.start;++i) {
809  index_all_to_g_[r.start+i] = offset_g+i;
810  }
811  offset_g += r.canon.nnz();
812  }
813  }
814 
815  std::vector<MX> lam = active_symvar(OPTI_DUAL_G);
816  for (casadi_int i=0;i<lam.size();++i) meta(lam[i]).active_i = i;
817 
818  lam_ = veccat(lam);
819 
820  // Collect bounds and canonical form of constraints
821  std::vector<MX> g_all, g_unscaled_all;
822  std::vector<MX> h_all, h_unscaled_all;
823  std::vector<MX> lbg_all, lbg_unscaled_all;
824  std::vector<MX> ubg_all, ubg_unscaled_all;
825 
826  g_linear_scale_.clear();
827  h_linear_scale_.clear();
828  std::vector<DM> g_linear_scale, h_linear_scale;
829 
830  equality_.clear();
831  for (const auto& g : g_) {
832  if (meta_con(g).type==OPTI_PSD) {
833  h_all.push_back(meta_con(g).canon/meta_con(g).linear_scale);
834  if (meta_con(g).canon.numel()==meta_con(g).linear_scale.numel()) {
835  h_linear_scale.push_back(meta_con(g).linear_scale);
836  } else {
837  casadi_assert_dev(meta_con(g).linear_scale.numel()==1);
838  h_linear_scale.push_back(DM::ones(meta_con(g).canon.sparsity())*meta_con(g).linear_scale);
839  }
840  h_unscaled_all.push_back(meta_con(g).canon);
841  } else {
842  g_all.push_back(meta_con(g).canon/meta_con(g).linear_scale);
843  if (meta_con(g).canon.numel()==meta_con(g).linear_scale.numel()) {
844  g_linear_scale.push_back(meta_con(g).linear_scale);
845  } else {
846  casadi_assert_dev(meta_con(g).linear_scale.numel()==1);
847  g_linear_scale.push_back(DM::ones(meta_con(g).canon.sparsity())*meta_con(g).linear_scale);
848  }
849  g_unscaled_all.push_back(meta_con(g).canon);
850  lbg_all.push_back(meta_con(g).lb/meta_con(g).linear_scale);
851  lbg_unscaled_all.push_back(meta_con(g).lb);
852  ubg_all.push_back(meta_con(g).ub/meta_con(g).linear_scale);
853  ubg_unscaled_all.push_back(meta_con(g).ub);
854 
855  equality_.insert(equality_.end(),
856  meta_con(g).canon.numel(),
857  meta_con(g).type==OPTI_EQUALITY || meta_con(g).type==OPTI_GENERIC_EQUALITY);
858  }
859  }
860 
861  nlp_["g"] = veccat(g_all);
862  g_linear_scale_ = veccat(g_linear_scale).nonzeros();
863  nlp_unscaled_["g"] = veccat(g_unscaled_all);
864  if (problem_type_=="conic") {
865  nlp_["h"] = diagcat(h_all);
866  nlp_unscaled_["h"] = diagcat(h_unscaled_all);
867  h_linear_scale_ = veccat(h_linear_scale).nonzeros();
868  }
869 
870  // Get scaling data
871  std::vector<DM> linear_scale = active_values(OPTI_VAR, store_linear_scale_);
872  std::vector<DM> linear_scale_offset = active_values(OPTI_VAR, store_linear_scale_offset_);
873 
874  linear_scale_ = veccat(linear_scale).nonzeros();
875  linear_scale_offset_ = veccat(linear_scale_offset).nonzeros();
876 
877  // Unscaled version of x
878  std::vector<MX> x_unscaled(x.size());
879  for (casadi_int i=0;i<x.size();++i) {
880  x_unscaled[i] = x[i]*linear_scale[i] + linear_scale_offset[i];
881  }
882 
883  // Perform substitution
884  std::vector<MX> expr = {nlp_["f"], nlp_["g"]};
885  if (problem_type_=="conic") expr.push_back(nlp_["h"]);
886  std::vector<MX> fgh = substitute(expr, x, x_unscaled);
887  nlp_["f"] = fgh[0];
888  nlp_["g"] = fgh[1];
889  if (problem_type_=="conic") {
890  nlp_["h"] = fgh[2];
891  }
892 
893  // Scale of objective
894  nlp_["f"] = nlp_["f"]/f_linear_scale_;
895 
896  // Create bounds helper function
897  MXDict bounds;
898  bounds["p"] = nlp_["p"];
899  bounds_lbg_ = veccat(lbg_all);
900  bounds_ubg_ = veccat(ubg_all);
901  bounds_unscaled_lbg_ = veccat(lbg_unscaled_all);
902  bounds_unscaled_ubg_ = veccat(ubg_unscaled_all);
903 
904  bounds["lbg"] = bounds_lbg_;
905  bounds["ubg"] = bounds_ubg_;
906 
907  bounds_ = Function("bounds", bounds, {"p"}, {"lbg", "ubg"});
908  mark_problem_dirty(false);
909 }
std::pair< casadi_int, casadi_int > size() const
Get the shape as a pair (number of rows, number of columns)
static MatType ones(casadi_int nrow=1, casadi_int ncol=1)
Create a dense matrix or a matrix with specified sparsity with all entries one.
std::vector< MX > active_symvar(VariableType type) const
MX g() const
Get all (scalarised) constraint expressions as a column vector.
MX x() const
Get all (scalarised) decision variables as a symbolic column vector.
std::vector< MX > symvar() const
MX p() const
Get all (scalarised) parameters as a symbolic column vector.
std::map< std::string, MX > MXDict
Definition: mx.hpp:5151
@ OPTI_DOMAIN_INTEGER
Definition: optistack.hpp:2719
@ OPTI_EQUALITY
Definition: optistack.hpp:2705
@ OPTI_GENERIC_EQUALITY
Definition: optistack.hpp:2703
casadi_int active_i
Definition: optistack.hpp:2753
casadi_int count
Definition: optistack.hpp:2751

References casadi::MetaVar::active_i, active_symvar(), active_values(), casadi::MetaCon::canon, casadi::MetaVar::count, casadi::MetaCon::dual_canon, g(), g_linear_scale(), casadi::GenericMatrix< MatType >::is_empty(), mark_problem_dirty(), casadi::GenericMatrix< MatType >::nnz(), casadi::GenericMatrix< MatType >::ones(), casadi::OPTI_DOMAIN_INTEGER, casadi::OPTI_DUAL_G, casadi::OPTI_EQUALITY, casadi::OPTI_GENERIC_EQUALITY, casadi::OPTI_PAR, casadi::OPTI_PSD, casadi::OPTI_VAR, p(), casadi::GenericMatrix< MatType >::size(), casadi::IndexAbstraction::start, casadi::IndexAbstraction::stop, symvar(), casadi::MetaCon::type, and x().

Referenced by solve(), and solver_construct().

◆ baked_copy()

OptiAdvanced casadi::OptiNode::baked_copy ( ) const
inline

Definition at line 217 of file optistack_internal.hpp.

217  {
218  OptiAdvanced s = copy();
219  if (s.problem_dirty()) s.bake();
220  return s;
221  }
Opti copy() const
Copy.

References casadi::OptiAdvanced::bake(), casadi::copy(), and casadi::OptiAdvanced::problem_dirty().

Referenced by casadi::OptiAdvanced::baked_copy(), describe(), g_describe(), g_lookup(), scale_helper(), to_function(), x_describe(), and x_lookup().

◆ callback_class() [1/2]

void casadi::OptiNode::callback_class ( )

Definition at line 104 of file optistack_internal.cpp.

104  {
105  user_callback_ = nullptr;
106 }

◆ callback_class() [2/2]

void casadi::OptiNode::callback_class ( OptiCallback *  callback)

Definition at line 100 of file optistack_internal.cpp.

100  {
101  user_callback_ = callback;
102 }

◆ canon_expr()

MetaCon casadi::OptiNode::canon_expr ( const MX &  expr,
const DM &  linear_scale = 1 
) const

Definition at line 1047 of file optistack_internal.cpp.

1047  {
1048  MX c = expr;
1049 
1050  MetaCon con;
1051  con.original = expr;
1052  casadi_assert(linear_scale.is_scalar() || linear_scale.size()==expr.size(),
1053  "Linear scale must have the same size as the expression. "
1054  "You got linear_scale " + con.linear_scale.dim() + " while " + expr.dim() + " is expected.");
1055  con.linear_scale = linear_scale;
1056 
1057  if (c.is_op(OP_LE) || c.is_op(OP_LT)) { // Inequalities
1058  std::vector<MX> ret;
1059  bool flipped;
1060  std::vector<MX> args = ineq_unchain(c, flipped);
1061  std::vector<bool> parametric;
1062  for (auto &a : args) parametric.push_back(is_parametric(a));
1063 
1064  if (args.size()==2 && (parametric[0] || parametric[1])) {
1065  // case: g(x,p) <= bound(p)
1066  MX e = args[0]-args[1];
1067  if (e.is_vector()) {
1068  casadi_assert(!parametric[0] || !parametric[1],
1069  "Constraint must contain decision variables.");
1070  if (problem_type_=="conic") {
1071  if (args[0].op()==OP_NORMF || args[0].op()==OP_NORM2) {
1072  args[0] = -soc(args[0].dep(), args[1]);
1073  args[1] = 0;
1074  }
1075  } else {
1076  con.type = OPTI_INEQUALITY;
1077  if (parametric[0]) {
1078  con.lb = args[0]*DM::ones(e.sparsity());
1079  con.ub = inf*DM::ones(e.sparsity());
1080  con.canon = args[1]*DM::ones(e.sparsity());
1081  } else {
1082  con.lb = -inf*DM::ones(e.sparsity());
1083  con.ub = args[1]*DM::ones(e.sparsity());
1084  con.canon = args[0]*DM::ones(e.sparsity());
1085  }
1086  return con;
1087  }
1088  }
1089  // Fall through to generic inequalities
1090  } else if (args.size()==3 && parametric[0] && parametric[2]) {
1091  // lb(p) <= g(x,p) <= ub(p)
1092  casadi_assert(!parametric[1], "Constraint must contain decision variables.");
1093  con.type = OPTI_DOUBLE_INEQUALITY;
1094  con.lb = args[0]*DM::ones(args[1].sparsity());
1095  con.ub = args[2]*DM::ones(args[1].sparsity());
1096  con.canon = args[1]*DM::ones(args[1].sparsity());
1097  con.flipped = flipped;
1098  con.n = 2;
1099  return con;
1100  }
1101 
1102  bool type_known = false;
1103  for (casadi_int j=0;j<args.size()-1;++j) {
1104  MX e = args[j]-args[j+1];
1105  if (problem_type_=="conic") {
1106  if (args[j].op()==OP_NORMF || args[j].op()==OP_NORM2) {
1107  args[j] = -soc(args[j].dep(), args[j+1]);
1108  args[j+1] = 0;
1109  e = args[j]-args[j+1];
1110  }
1111  }
1112  if (e.is_vector()) {
1113  // g1(x,p) <= g2(x,p)
1114  ret.push_back(e);
1115  casadi_assert_dev(!type_known || con.type==OPTI_GENERIC_INEQUALITY);
1116  type_known = true;
1117  con.type = OPTI_GENERIC_INEQUALITY;
1118  con.flipped = flipped;
1119  } else {
1120  // A(x,p) >= b(p)
1121  MX a = args[j+1];
1122  MX b = args[j];
1123  e = a-b;
1124 
1125  casadi_assert(e.size1()==e.size2(),
1126  "Matrix inequalities must be square. Did you mean element-wise inequality instead?");
1127  if (a.is_scalar()) a*= MX::eye(e.size1());
1128  if (b.is_scalar()) b*= MX::eye(e.size1());
1129  e = a-b;
1130 
1131  ret.push_back(e);
1132  casadi_assert_dev(!type_known || con.type==OPTI_PSD);
1133  type_known = true;
1134  con.type = OPTI_PSD;
1135  }
1136  }
1137 
1138  if (con.type==OPTI_GENERIC_INEQUALITY) {
1139  con.canon = veccat(ret);
1140  con.lb = -inf*DM::ones(con.canon.sparsity());
1141  con.ub = DM::zeros(con.canon.sparsity());
1142  con.n = ret.size();
1143  if (!con.linear_scale.is_scalar()) {
1144  con.linear_scale = repmat(con.linear_scale, ret.size(), 1);
1145  }
1146  } else {
1147  con.canon = diagcat(ret);
1148  con.n = ret.size();
1149  }
1150  return con;
1151  } else if (c.is_op(OP_EQ)) { // Inequalities
1152  casadi_assert(!is_parametric(c.dep(0)) || !is_parametric(c.dep(1)),
1153  "Constraint must contain decision variables.");
1154  MX e = c.dep(0)-c.dep(1);
1155  if (is_parametric(c.dep(0))) {
1156  con.canon = c.dep(1)*DM::ones(e.sparsity());
1157  con.lb = c.dep(0)*DM::ones(e.sparsity());
1158  con.type = OPTI_EQUALITY;
1159  casadi_assert(c.dep(0).size1()<=c.dep(1).size1() && c.dep(0).size2()<=c.dep(1).size2(),
1160  "Constraint shape mismatch.");
1161  } else if (is_parametric(c.dep(1))) {
1162  con.canon = c.dep(0)*DM::ones(e.sparsity());
1163  con.lb = c.dep(1)*DM::ones(e.sparsity());
1164  con.type = OPTI_EQUALITY;
1165  casadi_assert(c.dep(1).size1()<=c.dep(0).size1() && c.dep(1).size2()<=c.dep(0).size2(),
1166  "Constraint shape mismatch.");
1167  } else {
1168  con.lb = DM::zeros(e.sparsity());
1169  con.canon = e;
1170  con.type = OPTI_GENERIC_EQUALITY;
1171  }
1172  con.ub = con.lb;
1173  return con;
1174  } else { // Something else
1175  con.type = OPTI_UNKNOWN;
1176  con.canon = c;
1177  return con;
1178  }
1179 
1180 }
static MatType zeros(casadi_int nrow=1, casadi_int ncol=1)
Create a dense matrix or a matrix with specified sparsity with all entries zero.
static MX eye(casadi_int n)
Identity matrix constant of size n-by-n, with a diagonal sparsity pattern.
Definition: mx.cpp:603
bool is_parametric(const MX &expr) const
return true if expression is only dependant on Opti parameters, not variables
const double inf
infinity
Definition: calculus.hpp:50
@ OPTI_DOUBLE_INEQUALITY
Definition: optistack.hpp:2707
@ OPTI_INEQUALITY
Definition: optistack.hpp:2706
@ OPTI_GENERIC_INEQUALITY
Definition: optistack.hpp:2704
@ OPTI_UNKNOWN
Definition: optistack.hpp:2709
@ OP_LT
Definition: calculus.hpp:70
@ OP_EQ
Definition: calculus.hpp:70
@ OP_NORM2
Definition: calculus.hpp:178
@ OP_LE
Definition: calculus.hpp:70
@ OP_NORMF
Definition: calculus.hpp:178

References casadi::MetaCon::canon, casadi::MX::dep(), casadi::GenericMatrix< MatType >::dim(), casadi::MX::eye(), casadi::MetaCon::flipped, casadi::inf, casadi::MX::is_op(), is_parametric(), casadi::GenericMatrix< MatType >::is_scalar(), casadi::GenericMatrix< MatType >::is_vector(), casadi::MetaCon::lb, casadi::MetaCon::linear_scale, casadi::MetaCon::n, casadi::GenericMatrix< MatType >::ones(), casadi::OP_EQ, casadi::OP_LE, casadi::OP_LT, casadi::OP_NORM2, casadi::OP_NORMF, casadi::OPTI_DOUBLE_INEQUALITY, casadi::OPTI_EQUALITY, casadi::OPTI_GENERIC_EQUALITY, casadi::OPTI_GENERIC_INEQUALITY, casadi::OPTI_INEQUALITY, casadi::OPTI_PSD, casadi::OPTI_UNKNOWN, casadi::MetaCon::original, casadi::GenericMatrix< MatType >::size(), casadi::GenericMatrix< MatType >::size1(), casadi::GenericMatrix< MatType >::size2(), casadi::MX::sparsity(), casadi::MetaCon::type, casadi::MetaCon::ub, and casadi::GenericMatrix< MatType >::zeros().

Referenced by subject_to().

◆ casadi_solver()

Function casadi::OptiNode::casadi_solver ( ) const

Definition at line 574 of file optistack_internal.cpp.

574  {
575  return solver_;
576 }

◆ class_name()

std::string casadi::OptiNode::class_name ( ) const
inlineoverridevirtual

Implements casadi::SharedObjectInternal.

Definition at line 223 of file optistack_internal.hpp.

223 { return "OptiNode"; }

◆ constraints()

std::vector<MX> casadi::OptiNode::constraints ( ) const
inline

Definition at line 214 of file optistack_internal.hpp.

214 { return g_; }

◆ copy()

Opti casadi::OptiNode::copy ( ) const

Definition at line 365 of file optistack_internal.cpp.

365  {
366  return Opti::create(new OptiNode(*this));
367 }
OptiNode(const std::string &problem_type)
Create Opti Context.
static Opti create(OptiNode *node)
Definition: optistack.cpp:86

References casadi::Opti::create(), and OptiNode().

Referenced by casadi::Opti::copy(), and solve().

◆ create()

OptiNode * casadi::OptiNode::create ( const std::string &  problem_type)
static

Definition at line 95 of file optistack_internal.cpp.

95  {
96 return new OptiNode(problem_type);
97 }

References OptiNode().

Referenced by casadi::Opti::Opti().

◆ debug_repr()

std::string casadi::GenericSharedInternal< SharedObject , SharedObjectInternal >::debug_repr ( const Internal *  i) const
inherited

Definition at line 62 of file generic_shared_internal.hpp.

180  {
181  // Note: i != this because of something something multiple inheritance
182  return str( (casadi_int)(i)) + "/" + static_cast<const Internal*>(this)->class_name();
183  }
std::string str(const T &v)
String representation, any type.

◆ describe()

std::string casadi::OptiNode::describe ( const MX &  x,
casadi_int  indent = 0,
const Dict &  opts = Dict() 
) const

Definition at line 141 of file optistack_internal.cpp.

141  {
142  if (problem_dirty()) return baked_copy().describe(expr, indent, opts);
143  casadi_int max_stacktrace_depth = 1;
144  for (const auto& op : opts) {
145  if (op.first=="max_stacktrace_depth") {
146  max_stacktrace_depth = op.second.as_int();
147  } else {
148  casadi_warning("Unknown option '" + op.first + "'");
149  }
150  }
151  std::string s_indent;
152  for (casadi_int i=0;i<indent;++i) {
153  s_indent+= " ";
154  }
155  std::string description = s_indent;
156  if (expr.is_symbolic()) {
157  if (has(expr)) {
158  description += "Opti " + variable_type_to_string(meta(expr).type) + " '" + expr.name() +
159  "' of shape " + expr.dim();
160  const Dict& extra = meta(expr).extra;
161  auto it = extra.find("stacktrace");
162  if (it!=extra.end()) {
163  for (const Dict& stacktrace : it->second.as_dict_vector()) {
164  description += ", " + format_stacktrace(stacktrace, indent+1);
165  if (--max_stacktrace_depth==0) break;
166  }
167  }
168  } else {
169  VariableType vt;
170  if (parse_opti_name(expr.name(), vt)) {
171  description += "Opti " + variable_type_to_string(vt) + " '" + expr.name() +
172  "' of shape " + expr.dim()+
173  ", belonging to a different instance of Opti.";
174  } else {
175  description += "MX symbol '" + expr.name() + "' of shape " + expr.dim();
176  description += ", declared outside of Opti.";
177  }
178  }
179  } else {
180  if (has_con(expr)) {
181  description = "Opti constraint of shape " + expr.dim();
182  const Dict& extra = meta_con(expr).extra;
183  auto it = extra.find("stacktrace");
184  if (it!=extra.end()) {
185  for (const Dict& stacktrace : it->second.as_dict_vector()) {
186  description += ", " + format_stacktrace(stacktrace, indent+1);
187  if (--max_stacktrace_depth==0) break;
188  }
189  }
190  } else {
191  std::vector<MX> s = symvar(expr);
192  if (s.empty()) {
193  description+= "Constant epxression.";
194  } else {
195  description+= "General expression, dependent on " + str(s.size()) + " symbols:";
196  for (casadi_int i=0;i<s.size();++i) {
197  description+= "\n"+describe(s[i], indent+1);
198  if (i>5) {
199  description+= "\n...";
200  break;
201  }
202  }
203  }
204  }
205  }
206 
207  return description;
208 }
std::string describe(const MX &x, casadi_index indent=0, const Dict &opts=Dict()) const
Describe an expression in terms of this instance.
Definition: optistack.cpp:663
OptiAdvanced baked_copy() const
std::string description(Category v)
VariableType
Kind of an Opti symbol (MetaVar::type)
Definition: optistack.hpp:2711
GenericType::Dict Dict
C++ equivalent of Python's dict or MATLAB's struct.

References baked_copy(), casadi::OptiAdvanced::describe(), casadi::description(), casadi::GenericMatrix< MatType >::dim(), casadi::MetaCon::extra, casadi::MetaVar::extra, casadi::MX::is_symbolic(), casadi::MX::name(), problem_dirty(), casadi::str(), and symvar().

Referenced by assert_active_symbol(), g_describe(), solve_prepare(), value(), and x_describe().

◆ destroySingleton()

void casadi::GenericSharedInternal< SharedObject , SharedObjectInternal >::destroySingleton ( )
inlineprotectedinherited

Called in the destructor of singletons

Definition at line 77 of file generic_shared_internal.hpp.

77  {
78  static_cast<Internal*>(this)->count--;
79  }

◆ disp()

void casadi::OptiNode::disp ( std::ostream &  stream,
bool  more = false 
) const
overridevirtual

Implements casadi::SharedObjectInternal.

Definition at line 1750 of file optistack_internal.cpp.

1750  {
1751 
1752 }

◆ dual()

MX casadi::OptiNode::dual ( const MX &  m) const

Definition at line 616 of file optistack_internal.cpp.

616  {
617  return meta_con(m).dual;
618 }

References casadi::MetaCon::dual.

◆ f()

MX casadi::OptiNode::f ( ) const
inline

Definition at line 262 of file optistack_internal.hpp.

262  {
263  if (problem_dirty()) return baked_copy().f();
264  return nlp_unscaled_.at("f");
265  }
MX f() const
Get the objective expression.
Definition: optistack.cpp:358

Referenced by minimize().

◆ f_linear_scale()

double casadi::OptiNode::f_linear_scale ( ) const
inline

Definition at line 295 of file optistack_internal.hpp.

295  {
296  if (problem_dirty()) return baked_copy().f_linear_scale();
297  return f_linear_scale_;
298  }
double f_linear_scale() const
Scale of the objective (see minimize); a Python property.
Definition: optistack.cpp:415

Referenced by scale_helper().

◆ g()

MX casadi::OptiNode::g ( ) const
inline

Definition at line 256 of file optistack_internal.hpp.

256  {
257  if (problem_dirty()) return baked_copy().g();
258  return nlp_unscaled_.at("g");
259  }
MX g() const
Get all (scalarised) constraint expressions as a column vector.
Definition: optistack.cpp:350

Referenced by bake(), show_infeasibilities(), solve_prepare(), solver_construct(), and subject_to().

◆ g_describe()

std::string casadi::OptiNode::g_describe ( casadi_int  i,
const Dict &  opts = Dict() 
) const

Definition at line 210 of file optistack_internal.cpp.

210  {
211  if (problem_dirty()) return baked_copy().g_describe(i, opts);
212  MX expr = g_lookup(i);
213  casadi_int local_i = i-meta_con(expr).start + GlobalOptions::start_index;
214  std::string description = describe(expr, 0, opts);
215  if (expr.numel()>1)
216  description += "\nAt nonzero " + str(local_i % expr.numel()) +
217  ", part " + str((casadi_int) local_i / expr.numel()) + ".";
218  return description;
219 }
static casadi_int start_index
std::string g_describe(casadi_index i, const Dict &opts=Dict()) const
Describe row i of the constraint vector g.
Definition: optistack.cpp:656
MX g_lookup(casadi_int i) const

References baked_copy(), describe(), casadi::description(), casadi::OptiAdvanced::g_describe(), g_lookup(), casadi::GenericMatrix< MatType >::numel(), problem_dirty(), casadi::IndexAbstraction::start, casadi::GlobalOptions::start_index, and casadi::str().

Referenced by show_infeasibilities().

◆ g_index_reduce_g()

casadi_int casadi::OptiNode::g_index_reduce_g ( casadi_int  i) const

Definition at line 529 of file optistack_internal.cpp.

529  {
530  stats();
531  return g_index_reduce_g_[i];
532 }
Dict stats() const
Get statistics.

References stats().

◆ g_index_reduce_x()

casadi_int casadi::OptiNode::g_index_reduce_x ( casadi_int  i) const

Definition at line 537 of file optistack_internal.cpp.

537  {
538  stats();
539  return g_index_reduce_x_[i];
540 }

References stats().

◆ g_index_unreduce_g()

casadi_int casadi::OptiNode::g_index_unreduce_g ( casadi_int  i) const

Definition at line 533 of file optistack_internal.cpp.

533  {
534  stats();
535  return g_index_unreduce_g_[i];
536 }

References stats().

◆ g_linear_scale()

DM casadi::OptiNode::g_linear_scale ( ) const
inline

Definition at line 291 of file optistack_internal.hpp.

291  {
292  if (problem_dirty()) return baked_copy().g_linear_scale();
293  return DM(g_linear_scale_);
294  }
DM g_linear_scale() const
Per-row scale of g (see subject_to); a Python property.
Definition: optistack.cpp:407
Matrix< double > DM
Definition: dm_fwd.hpp:33

Referenced by bake(), and scale_helper().

◆ g_lookup()

MX casadi::OptiNode::g_lookup ( casadi_int  i) const

Definition at line 244 of file optistack_internal.cpp.

244  {
245  if (problem_dirty()) return baked_copy().g_lookup(i);
246  casadi_assert(i>=0 && i<ng(),
247  "Index " + str(i) + " out of range for " + str(ng()) + " constraints");
248  for (const auto& e : g_) {
249  const MetaCon& m = meta_con(e);
250  if (i>=m.start && i<m.stop) return e;
251  }
252  casadi_error("Internal error");
253  return MX();
254 }
MX g_lookup(casadi_index i) const
Get the constraint expression that owns row i of g.
Definition: optistack.cpp:641
casadi_int ng() const
Number of (scalarised) constraints.

References baked_copy(), casadi::OptiAdvanced::g_lookup(), ng(), problem_dirty(), casadi::IndexAbstraction::start, casadi::IndexAbstraction::stop, and casadi::str().

Referenced by g_describe().

◆ get_meta()

MetaVar casadi::OptiNode::get_meta ( const MX &  m) const

Definition at line 644 of file optistack_internal.cpp.

644  {
645  return meta(m);
646 }

Referenced by update_user_dict(), and user_dict().

◆ get_meta_con()

MetaCon casadi::OptiNode::get_meta_con ( const MX &  m) const

Definition at line 648 of file optistack_internal.cpp.

648  {
649  return meta_con(m);
650 }

Referenced by update_user_dict(), and user_dict().

◆ getCount()

Definition at line 60 of file generic_shared_internal.hpp.

210  {
211  return static_cast<const Internal*>(this)->count;
212  }

◆ has_callback_class()

bool casadi::OptiNode::has_callback_class ( ) const

Definition at line 108 of file optistack_internal.cpp.

108  {
109  return user_callback_ != 0;
110 }

◆ initial()

std::vector< MX > casadi::OptiNode::initial ( ) const

Definition at line 712 of file optistack_internal.cpp.

712  {
713  std::vector<MX> ret;
714  for (const auto& e : symvar()) {
715  if (meta(e).type==OPTI_VAR || meta(e).type==OPTI_DUAL_G)
716  ret.push_back(e==store_initial_.at(meta(e).type)[meta(e).i]);
717  }
718  return ret;
719 }

References casadi::OPTI_DUAL_G, casadi::OPTI_VAR, and symvar().

◆ initSingleton()

void casadi::GenericSharedInternal< SharedObject , SharedObjectInternal >::initSingleton ( )
inlineprotectedinherited

Called in the constructor of singletons to avoid that the counter reaches zero

Definition at line 71 of file generic_shared_internal.hpp.

71  {
72  casadi_assert_dev(static_cast<Internal*>(this)->count==0);
73  static_cast<Internal*>(this)->count++;
74  }

◆ instance_number()

casadi_int casadi::OptiNode::instance_number ( ) const

Definition at line 1754 of file optistack_internal.cpp.

1754  {
1755  return instance_number_;
1756 }

◆ is_parametric()

bool casadi::OptiNode::is_parametric ( const MX &  expr) const

Definition at line 1043 of file optistack_internal.cpp.

1043  {
1044  return symvar(expr, OPTI_VAR).empty();
1045 }

References casadi::OPTI_VAR, and symvar().

Referenced by canon_expr().

◆ lam_g()

MX casadi::OptiNode::lam_g ( ) const
inline

Definition at line 278 of file optistack_internal.hpp.

278  {
279  if (problem_dirty()) return baked_copy().lam_g();
280  return lam_;
281  }
MX lam_g() const
Get all (scalarised) dual variables as a symbolic column vector.
Definition: optistack.cpp:383

Referenced by to_function().

◆ lbg()

MX casadi::OptiNode::lbg ( ) const
inline

Definition at line 267 of file optistack_internal.hpp.

267  {
268  if (problem_dirty()) return baked_copy().lbg();
269  return bounds_unscaled_lbg_;
270  }
MX lbg() const
Get all (scalarised) bounds on constraints as a column vector.
Definition: optistack.cpp:366

Referenced by show_infeasibilities().

◆ mark_problem_dirty()

void casadi::OptiNode::mark_problem_dirty ( bool  flag = true)
inline

Definition at line 323 of file optistack_internal.hpp.

void mark_solver_dirty(bool flag=true)

Referenced by bake(), minimize(), OptiNode(), set_domain(), and subject_to().

◆ mark_solved()

void casadi::OptiNode::mark_solved ( bool  flag = true)
inline

Definition at line 331 of file optistack_internal.hpp.

331 { solved_ = flag;}

Referenced by res(), and set_domain().

◆ mark_solver_dirty()

void casadi::OptiNode::mark_solver_dirty ( bool  flag = true)
inline

Definition at line 327 of file optistack_internal.hpp.

327 { solver_dirty_=flag; mark_solved(false); }
void mark_solved(bool flag=true)

Referenced by solve(), and solver().

◆ minimize()

void casadi::OptiNode::minimize ( const MX &  f,
double  linear_scale = 1 
)

Definition at line 1199 of file optistack_internal.cpp.

1199  {
1200  assert_only_opti_nondual(f);
1202  casadi_assert(f.is_scalar(), "Objective must be scalar, got " + f.dim() + ".");
1203  f_ = f;
1204  f_linear_scale_ = linear_scale;
1205 }
std::string dim(bool with_nz=false) const
Get string representation of dimensions.
bool is_scalar(bool scalar_and_dense=false) const
Check if the matrix is scalar, i.e. 1-by-1.
MX f() const
Get objective expression.

References casadi::GenericMatrix< MatType >::dim(), f(), casadi::GenericMatrix< MatType >::is_scalar(), and mark_problem_dirty().

◆ ng()

casadi_int casadi::OptiNode::ng ( ) const
inline

Definition at line 238 of file optistack_internal.hpp.

238  {
239  if (problem_dirty()) return baked_copy().ng();
240  return nlp_.at("g").size1();
241  }
casadi_int ng() const
Number of (scalarised) constraints.
Definition: optistack.cpp:326

Referenced by g_lookup(), scale_helper(), and stats().

◆ np()

casadi_int casadi::OptiNode::np ( ) const
inline

Definition at line 232 of file optistack_internal.hpp.

232  {
233  if (problem_dirty()) return baked_copy().np();
234  return nlp_.at("p").size1();
235  }
casadi_int np() const
Number of (scalarised) parameters.
Definition: optistack.cpp:318

Referenced by scale_helper().

◆ nx()

casadi_int casadi::OptiNode::nx ( ) const
inline

Definition at line 226 of file optistack_internal.hpp.

226  {
227  if (problem_dirty()) return baked_copy().nx();
228  return nlp_.at("x").size1();
229  }
casadi_int nx() const
Number of (scalarised) decision variables.
Definition: optistack.cpp:310

Referenced by scale_helper(), and x_lookup().

◆ objective()

MX casadi::OptiNode::objective ( ) const
inline

Definition at line 215 of file optistack_internal.hpp.

215 { return f_; }

◆ p()

MX casadi::OptiNode::p ( ) const
inline

Definition at line 250 of file optistack_internal.hpp.

250  {
251  if (problem_dirty()) return baked_copy().p();
252  return nlp_.at("p");
253  }
MX p() const
Get all (scalarised) parameters as a symbolic column vector.
Definition: optistack.cpp:342

Referenced by bake(), to_function(), and value().

◆ parameter() [1/3]

MX casadi::OptiNode::parameter ( casadi_int  n = 1,
casadi_int  m = 1,
const std::string &  attribute = "full" 
)

Definition at line 463 of file optistack_internal.cpp.

463  {
464  // Prepare metadata
465  MetaVar meta_data;
466  meta_data.attribute = attribute;
467  meta_data.n = n;
468  meta_data.m = m;
469  meta_data.type = OPTI_PAR;
470  meta_data.count = count_++;
471  meta_data.i = count_par_++;
472 
473  MX symbol, ret;
474  if (attribute=="symmetric") {
475  casadi_assert(n==m, "You specified attribute 'symmetric', "
476  "while matrix is not even square, but " + str(n) + "-by-" + str(m) + ".");
477  symbol = MX::sym(name_prefix() + "p_" + str(count_par_), n*(n+1)/2);
478  ret = tril2symm(MX(Sparsity::lower(n), symbol));
479  } else if (attribute=="full") {
480  symbol = MX::sym(name_prefix() + "p_" + str(count_par_), n, m);
481  ret = symbol;
482  } else {
483  casadi_error("Unknown attribute '" + attribute + "'. Choose from 'full' or 'symmetric'.");
484  }
485 
486  symbols_.push_back(symbol);
487  store_initial_[OPTI_PAR].push_back(DM::nan(symbol.sparsity()));
488 
489  set_meta(symbol, meta_data);
490  return ret;
491 }
static MX sym(const std::string &name, casadi_int nrow=1, casadi_int ncol=1)
Create an nrow-by-ncol symbolic primitive.
static Matrix< double > nan(const Sparsity &sp)
Create a matrix with every nonzero equal to nan.
void set_meta(const MX &m, const MetaVar &meta)
Set meta-data of an expression.
static Sparsity lower(casadi_int n)
Create a lower triangular square sparsity pattern.
Definition: sparsity.cpp:1078

References casadi::MetaVar::attribute, casadi::MetaVar::count, casadi::MetaVar::i, casadi::Sparsity::lower(), casadi::MetaVar::m, casadi::MetaVar::n, casadi::Matrix< double >::nan(), casadi::OPTI_PAR, set_meta(), casadi::str(), casadi::GenericMatrix< MX >::sym(), and casadi::MetaVar::type.

◆ parameter() [2/3]

MX casadi::OptiNode::parameter ( const MX &  symbol,
const std::string &  attribute = "full" 
)

Definition at line 424 of file optistack_internal.cpp.

424  {
425  casadi_assert_dev(attribute=="full");
426 
427  // Prepare metadata
428  MetaVar meta_data;
429  meta_data.attribute = attribute;
430  meta_data.n = symbol.size1();
431  meta_data.m = symbol.size2();
432  meta_data.type = OPTI_PAR;
433  meta_data.count = count_++;
434  meta_data.i = count_par_++;
435 
436  symbols_.push_back(symbol);
437  store_initial_[OPTI_PAR].push_back(DM::nan(symbol.sparsity()));
438 
439  set_meta(symbol, meta_data);
440  return symbol;
441 }

References casadi::MetaVar::attribute, casadi::MetaVar::count, casadi::MetaVar::i, casadi::MetaVar::m, casadi::MetaVar::n, casadi::Matrix< double >::nan(), casadi::OPTI_PAR, set_meta(), and casadi::MetaVar::type.

◆ parameter() [3/3]

MX casadi::OptiNode::parameter ( const Sparsity &  sp,
const std::string &  attribute = "full" 
)

Definition at line 443 of file optistack_internal.cpp.

443  {
444  casadi_assert_dev(attribute=="full");
445 
446  // Prepare metadata
447  MetaVar meta_data;
448  meta_data.attribute = attribute;
449  meta_data.n = sp.size1();
450  meta_data.m = sp.size2();
451  meta_data.type = OPTI_PAR;
452  meta_data.count = count_++;
453  meta_data.i = count_par_++;
454 
455  MX symbol = MX::sym(name_prefix() + "p_" + str(count_par_), sp);
456  symbols_.push_back(symbol);
457  store_initial_[OPTI_PAR].push_back(DM::nan(symbol.sparsity()));
458 
459  set_meta(symbol, meta_data);
460  return symbol;
461 }

References casadi::MetaVar::attribute, casadi::MetaVar::count, casadi::MetaVar::i, casadi::MetaVar::m, casadi::MetaVar::n, casadi::Matrix< double >::nan(), casadi::OPTI_PAR, set_meta(), casadi::Sparsity::size1(), casadi::Sparsity::size2(), casadi::str(), casadi::GenericMatrix< MX >::sym(), and casadi::MetaVar::type.

◆ problem_dirty()

bool casadi::OptiNode::problem_dirty ( ) const
inline

◆ res() [1/2]

DMDict casadi::OptiNode::res ( ) const
inline

Definition at line 213 of file optistack_internal.hpp.

213 { return res_; }

Referenced by res(), scale_helper(), solve(), solve_prepare(), and to_function().

◆ res() [2/2]

void casadi::OptiNode::res ( const DMDict &  res)

Definition at line 1256 of file optistack_internal.cpp.

1256  {
1257  const std::vector<double> & x_v = res.at("x").nonzeros();
1258  for (const auto &v : active_symvar(OPTI_VAR)) {
1259  casadi_int i = meta(v).i;
1260  std::vector<double> & data_v = store_latest_[OPTI_VAR][i].nonzeros();
1261  for (casadi_int i=0;i<data_v.size();++i) {
1262  casadi_int j = meta(v).start+i;
1263  data_v[i] = x_v[j]*linear_scale_[j] + linear_scale_offset_[j];
1264  }
1265  }
1266  if (res.find("lam_g")!=res.end()) {
1267  const std::vector<double> & lam_v = res.at("lam_g").nonzeros();
1268  for (const auto &v : active_symvar(OPTI_DUAL_G)) {
1269  casadi_int i = meta(v).i;
1270  std::vector<double> & data_v = store_latest_[OPTI_DUAL_G][i].nonzeros();
1271  for (casadi_int i=0;i<data_v.size();++i) {
1272  casadi_int j = meta(v).start+i;
1273  j = index_all_to_g_.at(j);
1274  if (j<0) continue;
1275  data_v[i] = lam_v.at(j)/g_linear_scale_.at(j)*f_linear_scale_;
1276  }
1277  }
1278  }
1279  res_ = res;
1280  mark_solved();
1281 }
casadi_int i
Definition: optistack.hpp:2752

References active_symvar(), casadi::MetaVar::i, mark_solved(), casadi::OPTI_DUAL_G, casadi::OPTI_VAR, res(), and casadi::IndexAbstraction::start.

◆ return_status()

std::string casadi::OptiNode::return_status ( ) const

Definition at line 542 of file optistack_internal.cpp.

542  {
543  Dict mystats;
544  try {
545  mystats = stats();
546  } catch (...) {
547  return "unknown";
548  }
549  if (mystats.find("return_status")!=mystats.end()) {
550  std::stringstream ss;
551  ss << mystats.at("return_status");
552  return ss.str();
553  }
554  return "unknown";
555 }

References stats().

Referenced by solve().

◆ return_success()

bool casadi::OptiNode::return_success ( bool  accept_limit) const

Definition at line 557 of file optistack_internal.cpp.

557  {
558  Dict mystats;
559  try {
560  mystats = stats();
561  } catch (...) {
562  return false;
563  }
564  bool success = false;
565  if (mystats.find("success")!=mystats.end()) success = mystats.at("success");
566  if (!accept_limit) return success;
567 
568  bool limited = false;
569  if (mystats.find("unified_return_status")!=mystats.end())
570  limited = mystats.at("unified_return_status")=="SOLVER_RET_LIMITED";
571  return success || limited;
572 }

References stats().

Referenced by solve().

◆ scale_helper()

Function casadi::OptiNode::scale_helper ( const Function &  h) const

Extra doc: https://github.com/casadi/casadi/wiki/L_2cd

Definition at line 911 of file optistack_internal.cpp.

911  {
912  if (problem_dirty()) return baked_copy().scale_helper(h);
913  std::string name = h.name();
914  MX g_linear_scale_mx = g_linear_scale();
915  MX g_linear_scale_inv = 1/g_linear_scale();
916  MX f_linear_scale_mx = f_linear_scale();
917  MX x_linear_scale_mx = x_linear_scale();
918  MX x_linear_scale_offset_mx = x_linear_scale_offset();
919  if (name=="nlp_jac_g") {
920  MXDict arg;
921  arg["x"] = MX::sym("x", nx());
922  arg["p"] = MX::sym("p", np());
923  MXDict args;
924  args["x"] = arg["x"]*x_linear_scale_mx+x_linear_scale_offset_mx;
925  args["p"] = arg["p"];
926  MXDict res = h(args);
927  for (const auto & it : res) {
928  if (it.first=="g") {
929  arg[it.first] = it.second*g_linear_scale_inv;
930  } else if (it.first=="jac_g_x") {
931  arg[it.first] = mtimes(
932  mtimes(diag(g_linear_scale_inv), it.second),
933  diag(x_linear_scale_mx));
934  } else {
935  casadi_error("Unknown output '" + it.first + "'. Expecting g, jac_g_x.");
936  }
937  }
938  Function ret(name, arg, h.name_in(), h.name_out());
939  return ret;
940  } else if (name=="nlp_hess_l") {
941  MXDict arg;
942  arg["x"] = MX::sym("x", nx());
943  arg["p"] = MX::sym("p", np());
944  arg["lam_f"] = MX::sym("lam_f");
945  arg["lam_g"] = MX::sym("lam_g", ng());
946  MXDict args;
947  args["x"] = arg["x"]*x_linear_scale_mx+x_linear_scale_offset_mx;
948  args["p"] = arg["p"];
949  args["lam_f"] = arg["lam_f"]/f_linear_scale_mx;
950  args["lam_g"] = arg["lam_g"]/g_linear_scale_mx;
951  MXDict res = h(args);
952  for (const auto & it : res) {
953  if (it.first=="triu_hess_gamma_x_x" ||
954  it.first=="hess_gamma_x_x" ||
955  (it.second.size1()==nx() && it.second.is_square())) {
956  MX D = diag(x_linear_scale_mx);
957  arg[it.first] = mtimes(mtimes(D, it.second), D);
958  } else {
959  casadi_error("Unknown output '" + it.first + "'. Expecting triu_hess_gamma_x_x");
960  }
961  }
962  Function ret(name, arg, h.name_in(), h.name_out());
963  return ret;
964  } else {
965  casadi_error("Unknown helper function '" + name + "'");
966  }
967 }
const std::string & name() const
Get the name given at construction ("null" for a null object)
Definition: function.cpp:1504
casadi_int nx() const
Number of (scalarised) decision variables.
casadi_int np() const
Number of (scalarised) parameters.
DM x_linear_scale_offset() const
double f_linear_scale() const
Function scale_helper(const Function &h) const
Scale a helper function constructed via opti.x, opti.g, ...
Definition: optistack.cpp:254

References arg(), baked_copy(), casadi::D, f_linear_scale(), g_linear_scale(), casadi::Function::name(), casadi::Function::name_in(), casadi::Function::name_out(), ng(), np(), nx(), problem_dirty(), res(), casadi::Opti::scale_helper(), casadi::GenericMatrix< MX >::sym(), x_linear_scale(), and x_linear_scale_offset().

◆ set_domain()

void casadi::OptiNode::set_domain ( const MX &  x,
const std::string &  domain 
)

Definition at line 1514 of file optistack_internal.cpp.

1514  {
1515  mark_solved(false);
1517  casadi_assert(x.is_valid_input(), "First argument to set_domain should be a variable.");
1518  DomainType type;
1519  if (domain=="real") {
1520  type = OPTI_DOMAIN_REAL;
1521  } else if (domain=="integer") {
1522  type = OPTI_DOMAIN_INTEGER;
1523  } else {
1524  casadi_error("Unknown domain '" + domain + "'. Known values are 'real', 'integer'.");
1525  }
1526  for (const auto& prim : x.primitives()) {
1527  MetaVar& m = meta(prim);
1528  m.domain = type;
1529  }
1530 }
bool is_valid_input() const
Check if the expression can be used as a Function input.
Definition: mx.cpp:957
std::vector< MX > primitives() const
Get the symbolic primitives of a valid Function input.
Definition: mx.cpp:965
DomainType
Domain of a decision variable (see Opti::set_domain)
Definition: optistack.hpp:2717
@ OPTI_DOMAIN_REAL
Definition: optistack.hpp:2718

References casadi::MetaVar::domain, casadi::MX::is_valid_input(), mark_problem_dirty(), mark_solved(), casadi::OPTI_DOMAIN_INTEGER, casadi::OPTI_DOMAIN_REAL, casadi::MX::primitives(), and x().

◆ set_initial() [1/2]

void casadi::OptiNode::set_initial ( const MX &  x,
const DM &  v 
)

Set initial value for decision variables

Definition at line 1629 of file optistack_internal.cpp.

1629  {
1630  for (const auto & s : MX::symvar(x))
1631  casadi_assert(meta(s).type!=OPTI_PAR,
1632  "You cannot set an initial value for a parameter. Did you mean 'set_value'?");
1633  set_value_internal(x, v, store_initial_);
1634 }
static std::vector< MX > symvar(const MX &x)
Definition: mx.cpp:2034

References casadi::OPTI_PAR, casadi::MX::symvar(), and x().

Referenced by set_initial().

◆ set_initial() [2/2]

void casadi::OptiNode::set_initial ( const std::vector< MX > &  assignments)

Set initial value for decision variables

Definition at line 1505 of file optistack_internal.cpp.

1505  {
1506  for (const auto& v : assignments) {
1507  casadi_assert_dev(v.is_op(OP_EQ));
1508  casadi_assert_dev(v.dep(0).is_constant());
1509  if (has(v.dep(1)))
1510  set_initial(v.dep(1), static_cast<DM>(v.dep(0)));
1511  }
1512 }
void set_initial(const MX &x, const DM &v)

References casadi::OP_EQ, and set_initial().

◆ set_linear_scale()

void casadi::OptiNode::set_linear_scale ( const MX &  x,
const DM &  scale,
const DM &  offset 
)

Definition at line 1643 of file optistack_internal.cpp.

1643  {
1644  for (const auto & s : MX::symvar(x))
1645  casadi_assert(meta(s).type!=OPTI_PAR,
1646  "You cannot set a scale value for a parameter.");
1647  casadi_assert(scale.is_scalar() || scale.size()==x.size(),
1648  "Dimension mismatch in linear_scale. Expected " + x.dim() + ", got " + scale.dim()+ ".");
1649  set_value_internal(x, scale, store_linear_scale_);
1650  casadi_assert(offset.is_scalar() || offset.size()==x.size(),
1651  "Dimension mismatch in linear_scale offset. Expected " + x.dim() +
1652  ", got " + scale.dim()+ ".");
1653  set_value_internal(x, offset, store_linear_scale_offset_);
1654 }

References casadi::GenericMatrix< MatType >::dim(), casadi::GenericMatrix< MatType >::is_scalar(), casadi::OPTI_PAR, casadi::GenericMatrix< MatType >::size(), casadi::MX::symvar(), and x().

◆ set_meta()

void casadi::OptiNode::set_meta ( const MX &  m,
const MetaVar &  meta 
)

Definition at line 578 of file optistack_internal.cpp.

578  {
579  meta_[m.get()] = meta;
580 }

References casadi::MX::get().

Referenced by parameter(), update_user_dict(), and variable().

◆ set_meta_con()

void casadi::OptiNode::set_meta_con ( const MX &  m,
const MetaCon &  meta 
)

Definition at line 582 of file optistack_internal.cpp.

582  {
583  meta_con_[m.get()] = meta;
584 }

References casadi::MX::get().

Referenced by subject_to(), and update_user_dict().

◆ set_value() [1/2]

void casadi::OptiNode::set_value ( const MX &  x,
const DM &  v 
)

Each parameter must be given a value before 'solve' can be called

Extra doc: https://github.com/casadi/casadi/wiki/L_173

Definition at line 1636 of file optistack_internal.cpp.

1636  {
1637  for (const auto & s : MX::symvar(x))
1638  casadi_assert(meta(s).type!=OPTI_VAR,
1639  "You cannot set a value for a variable. Did you mean 'set_initial'?");
1640  set_value_internal(x, v, store_initial_);
1641 }

References casadi::OPTI_VAR, casadi::MX::symvar(), and x().

Referenced by set_value().

◆ set_value() [2/2]

void casadi::OptiNode::set_value ( const std::vector< MX > &  assignments)

Each parameter must be given a value before 'solve' can be called

Extra doc: https://github.com/casadi/casadi/wiki/L_173

Definition at line 1532 of file optistack_internal.cpp.

1532  {
1533  for (const auto& v : assignments) {
1534  casadi_assert_dev(v.is_op(OP_EQ));
1535  casadi_assert_dev(v.dep(0).is_constant());
1536  if (has(v.dep(1)))
1537  set_value(v.dep(1), static_cast<DM>(v.dep(0)));
1538  }
1539 }
void set_value(const MX &x, const DM &v)
Set value of parameter.

References casadi::OP_EQ, and set_value().

◆ shared_from_this() [1/2]

B casadi::GenericSharedInternal< SharedObject , SharedObjectInternal >::shared_from_this ( )
inlineprotectedinherited

Definition at line 83 of file generic_shared_internal.hpp.

83  {
84  casadi_assert_dev(B::test_cast(static_cast<Internal*>(this)));
85  B ret;
86  ret.own(static_cast<Internal*>(this));
87  return ret;
88  }

◆ shared_from_this() [2/2]

const B casadi::GenericSharedInternal< SharedObject , SharedObjectInternal >::shared_from_this ( ) const
inlineprotectedinherited

Definition at line 92 of file generic_shared_internal.hpp.

92  {
93  casadi_assert_dev(B::test_cast(static_cast<const Internal*>(this)));
94  B ret;
95  ret.own(const_cast<Internal*>(static_cast<const Internal*>(this)));
96  return ret;
97  }

◆ show_infeasibilities()

void casadi::OptiNode::show_infeasibilities ( double  tol = 0,
const Dict &  opts = Dict() 
) const

Definition at line 1758 of file optistack_internal.cpp.

1758  {
1759  stats();
1760  std::vector<double> lbg_ = value(lbg()).get_elements();
1761  std::vector<double> ubg_ = value(ubg()).get_elements();
1762  std::vector<double> g_scaled_ = value(nlp_.at("g"), std::vector<MX>(), true).get_elements();
1763  std::vector<double> lbg_scaled_ = value(bounds_lbg_, std::vector<MX>(), true).get_elements();
1764  std::vector<double> ubg_scaled_ = value(bounds_ubg_, std::vector<MX>(), true).get_elements();
1765 
1766 
1767  std::vector<double> g_ = value(g()).get_elements();
1768  uout() << "Violated constraints (tol " << tol << "), in order of declaration:" << std::endl;
1769 
1770  for (casadi_int i=0;i<g_.size();++i) {
1771  double err = std::max(g_[i]-ubg_[i], lbg_[i]-g_[i]);
1772  double err_scaled = std::max(g_scaled_[i]-ubg_scaled_[i], lbg_scaled_[i]-g_scaled_[i]);
1773  if (err>=tol) {
1774  uout() << "------- i = " << i+GlobalOptions::start_index;
1775  uout() << "/" << g_.size();
1776 
1777  if (reduced_) {
1778  if (is_simple_[i]) {
1779  if (GlobalOptions::start_index==0) {
1780  uout() << " reduced to bound on x[" << g_index_reduce_x_.at(i) << "]";
1781  } else {
1782  uout() << " reduced to bound on x(" << g_index_reduce_x_.at(i)+1 << ")";
1783  }
1784  } else {
1785  uout() << " reduced to g[" << g_index_reduce_g_.at(i) << "]";
1786  }
1787  }
1788 
1789  uout() << " ------ " << std::endl;
1790  uout() << lbg_[i] << " <= " << g_[i] << " <= " << ubg_[i];
1791  uout() << " (viol " << err << ")" << std::endl;
1792  if (g_[i]!=g_scaled_[i]) {
1793  uout() << lbg_scaled_[i] << " <= " << g_scaled_[i] << " <= " << ubg_scaled_[i];
1794  uout() << " (scaled) (viol " << err_scaled << ")" << std::endl;
1795  }
1796  uout() << g_describe(i, opts) << std::endl;
1797  }
1798  }
1799 }
std::vector< Scalar > get_elements() const
Get all elements as a flat list in column-major order (Python: elements())
DM value(const MX &x, const std::vector< MX > &values=std::vector< MX >(), bool scaled=false) const
std::string g_describe(casadi_int i, const Dict &opts=Dict()) const
std::ostream & uout()

References g(), g_describe(), casadi::Matrix< Scalar >::get_elements(), lbg(), casadi::GlobalOptions::start_index, stats(), ubg(), casadi::uout(), and value().

◆ solve()

OptiSol casadi::OptiNode::solve ( bool  accept_limit)

Definition at line 1335 of file optistack_internal.cpp.

1335  {
1336 
1337  if (problem_dirty()) {
1338  bake();
1339  }
1340 
1341  bool solver_update = solver_dirty() || old_callback() || (user_callback_ && callback_.is_null());
1342 
1343  if (solver_update) {
1344  solver_ = solver_construct(true);
1345  mark_solver_dirty(false);
1346  }
1347 
1348  solve_prepare();
1349  res(solve_actual(arg_));
1350 
1351  std::string ret = return_status();
1352 
1353  casadi_assert(return_success(accept_limit),
1354  "Solver failed. You may use opti.debug.value to investigate the latest values of variables."
1355  " return_status is '" + ret + "'");
1356 
1357  return copy();
1358 }
bool is_null() const
Is a null pointer?
Function solver_construct(bool callback=true)
void bake()
Fix the structure of the optimization problem.
bool return_success(bool accept_limit) const
Did the solver return successfully?
std::string return_status() const
Get return status of solver.
DMDict solve_actual(const DMDict &args)

References bake(), copy(), casadi::GenericShared< Shared, Internal >::is_null(), mark_solver_dirty(), problem_dirty(), res(), return_status(), return_success(), solve_actual(), solve_prepare(), solver_construct(), and solver_dirty().

◆ solve_actual()

DMDict casadi::OptiNode::solve_actual ( const DMDict &  args)

Definition at line 1400 of file optistack_internal.cpp.

1400  {
1401  return solver_(arg);
1402 }

References arg().

Referenced by solve().

◆ solve_prepare()

void casadi::OptiNode::solve_prepare ( )

Definition at line 1361 of file optistack_internal.cpp.

1361  {
1362 
1363 
1364  // Verify the constraint types
1365  for (const auto& g : g_) {
1366  if (meta_con(g).type==OPTI_UNKNOWN)
1367  casadi_error("Constraint type unknown. Use ==, >= or <= .");
1368  }
1369 
1370  if (user_callback_) {
1371  InternalOptiCallback* cb = static_cast<InternalOptiCallback*>(callback_.get());
1372  cb->reset();
1373  }
1374 
1375  // Get initial guess and parameter values
1376  arg_["x0"] = (veccat(active_values(OPTI_VAR))-linear_scale_offset_)/linear_scale_;
1377  arg_["p"] = veccat(active_values(OPTI_PAR));
1378  arg_["lam_g0"] = veccat(active_values(OPTI_DUAL_G));
1379  if (!arg_["p"].is_regular()) {
1380  std::vector<MX> s = active_symvar(OPTI_PAR);
1381  std::vector<DM> v = active_values(OPTI_PAR);
1382  for (casadi_int i=0;i<s.size();++i) {
1383  casadi_assert(v[i].is_regular(),
1384  "You have forgotten to assign a value to a parameter ('set_value'), "
1385  "or have set it to NaN/Inf:\n" + describe(s[i], 1));
1386  }
1387  }
1388 
1389 
1390  // Evaluate bounds for given parameter values
1391  DMDict arg;
1392  arg["p"] = arg_["p"];
1393  DMDict res = bounds_(arg);
1394  arg_["lbg"] = res["lbg"];
1395  arg_["ubg"] = res["ubg"];
1396 
1397  stats_.clear();
1398 }
FunctionInternal * get() const
Definition: function.cpp:505
friend class InternalOptiCallback
bool is_regular(const std::vector< T > &v)
Checks if array does not contain NaN or Inf.
std::map< std::string, DM > DMDict
Definition: dm_fwd.hpp:36

References active_symvar(), active_values(), arg(), describe(), g(), casadi::Function::get(), InternalOptiCallback, casadi::is_regular(), casadi::OPTI_DUAL_G, casadi::OPTI_PAR, casadi::OPTI_UNKNOWN, casadi::OPTI_VAR, and res().

Referenced by solve().

◆ solved()

bool casadi::OptiNode::solved ( ) const
inline

Definition at line 332 of file optistack_internal.hpp.

332 { return solved_; }

Referenced by assert_solved().

◆ solver()

void casadi::OptiNode::solver ( const std::string &  solver,
const Dict &  plugin_options = Dict(),
const Dict &  solver_options = Dict() 
)

Definition at line 969 of file optistack_internal.cpp.

970  {
971  solver_name_ = solver_name;
972  solver_options_ = plugin_options;
973  if (!solver_options.empty())
974  solver_options_[solver_name] = solver_options;
976 }

References mark_solver_dirty().

Referenced by to_function().

◆ solver_construct()

Function casadi::OptiNode::solver_construct ( bool  callback = true)

Definition at line 1289 of file optistack_internal.cpp.

1289  {
1290  if (problem_dirty()) {
1291  bake();
1292  }
1293 
1294  // Verify the constraint types
1295  for (const auto& g : g_) {
1296  if (problem_type_!="conic") {
1297  if (meta_con(g).type==OPTI_PSD)
1298  casadi_error("Psd constraints not implemented yet. "
1299  "Perhaps you intended an element-wise inequality? "
1300  "In that case, make sure that the matrix is flattened (e.g. mat(:)).");
1301  }
1302  }
1303 
1304  Dict solver_options_all = solver_options_;
1305 
1306  if (solver_options_all.find("equality")==solver_options_all.end()) {
1307  solver_options_all["equality"] = equality_;
1308  }
1309 
1310  if (solver_options_all.find("discrete")==solver_options_all.end()) {
1311  solver_options_all["discrete"] = discrete_;
1312  }
1313 
1314  Dict opts = solver_options_all;
1315 
1316  // Handle callbacks
1317  if (callback && user_callback_) {
1318  callback_ = Function::create(new InternalOptiCallback(*this), Dict());
1319  opts["iteration_callback"] = callback_;
1320  }
1321 
1322  casadi_assert(!solver_name_.empty(),
1323  "You must call 'solver' on the Opti stack to select a solver. "
1324  "Suggestion: opti.solver('ipopt')");
1325 
1326  if (problem_type_=="conic") {
1327  return qpsol("solver", solver_name_, nlp_, opts);
1328  } else {
1329  return nlpsol("solver", solver_name_, nlp_, opts);
1330  }
1331 
1332 }
static Function create(FunctionInternal *node)
Create from node.
Definition: function.cpp:488
Function qpsol(const std::string &name, const std::string &solver, const SXDict &qp, const Dict &opts)
Definition: conic.cpp:261
Function nlpsol(const std::string &name, const std::string &solver, const SXDict &nlp, const Dict &opts)
Definition: nlpsol.cpp:196

References bake(), casadi::Function::create(), g(), InternalOptiCallback, casadi::nlpsol(), casadi::OPTI_PSD, problem_dirty(), and casadi::qpsol().

Referenced by solve(), and to_function().

◆ solver_dirty()

bool casadi::OptiNode::solver_dirty ( ) const
inline

Definition at line 328 of file optistack_internal.hpp.

328 { return solver_dirty_; }

Referenced by solve().

◆ stats()

Dict casadi::OptiNode::stats ( ) const

Definition at line 493 of file optistack_internal.cpp.

493  {
494  assert_solved();
495  if (stats_.empty()) {
496  stats_ = solver_.stats();
497  is_simple_ = get_from_dict(stats_,
498  "detect_simple_bounds_is_simple",
499  std::vector<bool>(ng(), false));
500  target_x_ = get_from_dict(stats_,
501  "detect_simple_bounds_target_x",
502  std::vector<casadi_int>{});
503  casadi_assert_dev(is_simple_.size()==ng());
504 
505  g_index_reduce_g_.resize(ng());
506  g_index_reduce_x_.resize(ng(), -1);
507  g_index_unreduce_g_.resize(ng(), -1);
508 
509  casadi_int* target_x_ptr = target_x_.data();
510 
511  casadi_int k=0;
512  for (casadi_int i=0;i<is_simple_.size();++i) {
513  if (!is_simple_[i]) {
514  g_index_reduce_g_[i] = k;
515  g_index_unreduce_g_[k] = i;
516  k++;
517  } else {
518  g_index_reduce_g_[i] = -1;
519  g_index_reduce_x_[i] = *target_x_ptr;
520  target_x_ptr++;
521  }
522  }
523 
524  reduced_ = any(is_simple_);
525  }
526  return stats_;
527 }
Dict stats(int mem=0) const
Get the statistics recorded by the last numerical evaluation.
Definition: function.cpp:1080
T get_from_dict(const std::map< std::string, T > &d, const std::string &key, const T &default_value)
bool any(const std::vector< bool > &v)
Check if any arguments are true.
Definition: casadi_misc.cpp:88

References casadi::any(), assert_solved(), casadi::get_from_dict(), ng(), and casadi::Function::stats().

Referenced by g_index_reduce_g(), g_index_reduce_x(), g_index_unreduce_g(), return_status(), return_success(), and show_infeasibilities().

◆ subject_to() [1/2]

void casadi::OptiNode::subject_to ( )

Definition at line 1239 of file optistack_internal.cpp.

1239  {
1241  g_.clear();
1242  store_initial_[OPTI_DUAL_G].clear();
1243  store_latest_[OPTI_DUAL_G].clear();
1244  count_dual_ = 0;
1245 }

References mark_problem_dirty(), and casadi::OPTI_DUAL_G.

◆ subject_to() [2/2]

void casadi::OptiNode::subject_to ( const MX &  g,
const DM &  linear_scale = 1,
const Dict &  options = Dict() 
)

Definition at line 1207 of file optistack_internal.cpp.

1207  {
1208  assert_only_opti_nondual(g);
1210 
1211  casadi_assert(!g.is_empty(), "You passed an empty expression to `subject_to`. "
1212  "Make sure the number of rows and columns is non-zero. "
1213  "Got " + g.dim(true) + ".");
1214  casadi_assert(g.nnz()>0, "You passed a fully sparse expression to `subject_to`. "
1215  "Make sure the expression has at least one nonzero. "
1216  "Got " + g.dim(true) + ".");
1217  casadi_assert(!g.is_constant(), "You passed a constant to `subject_to`. "
1218  "You need a symbol to form a constraint.");
1219 
1220  // Store the meta-data
1221  MetaCon con = canon_expr(g, linear_scale);
1222  casadi_assert(con.type!=OPTI_UNKNOWN, "Constraint type unknown. Use ==, >= or <= .");
1223  set_meta_con(g, con);
1224  register_dual(meta_con(g));
1225  g_.push_back(g);
1226 
1227  for (auto && it : options) {
1228  if (it.first=="stacktrace") {
1229  meta_con(g).extra["stacktrace"] = it.second.to_dict_vector();
1230  meta(meta_con(g).dual_canon).extra["stacktrace"] = it.second.to_dict_vector();
1231  } else if (it.first=="meta") {
1232  update_user_dict(g, it.second.to_dict());
1233  } else {
1234  casadi_error("Unknown option: " + it.first);
1235  }
1236  }
1237 }
casadi_int nnz() const
Get the number of structural nonzeros.
bool is_constant() const
Check if the node is a constant.
Definition: mx.cpp:802
void update_user_dict(const MX &m, const Dict &meta)
add meta-data of an expression
MetaCon canon_expr(const MX &expr, const DM &linear_scale=1) const
Interpret an expression (for internal use only)
void set_meta_con(const MX &m, const MetaCon &meta)
Set meta-data of an expression.

References canon_expr(), casadi::GenericMatrix< MatType >::dim(), casadi::MetaCon::extra, casadi::MetaVar::extra, g(), casadi::MX::is_constant(), casadi::GenericMatrix< MatType >::is_empty(), mark_problem_dirty(), casadi::GenericMatrix< MatType >::nnz(), casadi::OPTI_UNKNOWN, set_meta_con(), casadi::MetaCon::type, and update_user_dict().

◆ symvar() [1/4]

std::vector< MX > casadi::OptiNode::symvar ( ) const

Get symbols present in expression

Definition at line 993 of file optistack_internal.cpp.

993  {
994  return symbols_;
995 }

Referenced by bake(), describe(), initial(), is_parametric(), symvar(), value(), value_parameters(), and value_variables().

◆ symvar() [2/4]

std::vector< MX > casadi::OptiNode::symvar ( const MX &  expr) const

Get symbols present in expression

Definition at line 997 of file optistack_internal.cpp.

997  {
998  return sort(MX::symvar(expr));
999 }

References casadi::MX::symvar().

◆ symvar() [3/4]

std::vector< MX > casadi::OptiNode::symvar ( const MX &  expr,
VariableType  type 
) const

Get symbols present in expression

Definition at line 1247 of file optistack_internal.cpp.

1247  {
1248  std::vector<MX> ret;
1249  for (const auto& d : symvar(expr)) {
1250  if (meta(d).type==type) ret.push_back(d);
1251  }
1252 
1253  return ret;
1254 }

References symvar().

◆ symvar() [4/4]

std::vector< MX > casadi::OptiNode::symvar ( VariableType  type) const

Definition at line 1666 of file optistack_internal.cpp.

1666  {
1667  if (symbols_.empty()) return std::vector<MX>{};
1668  std::vector<MX> ret;
1669  for (const auto& s : symbols_) {
1670  if (meta(s).type==type)
1671  ret.push_back(s);
1672  }
1673  return ret;
1674 }

◆ to_function()

Function casadi::OptiNode::to_function ( const std::string &  name,
const std::vector< MX > &  args,
const std::vector< MX > &  res,
const std::vector< std::string > &  name_in,
const std::vector< std::string > &  name_out,
const Dict &  opts 
)

Extra doc: https://github.com/casadi/casadi/wiki/L_174

Definition at line 1692 of file optistack_internal.cpp.

1696  {
1697  if (problem_dirty()) return baked_copy().to_function(name, args, res, name_in, name_out, opts);
1698 
1699  Function solver = solver_construct(false);
1700 
1701  // Get initial guess and parameter values
1702  std::vector<MX> x0, p, lam_g;
1706 
1707  casadi_int k = 0;
1708  for (const auto& a : args) {
1709  casadi_assert(a.is_valid_input(), "Argument " + str(k) + " is not purely symbolic.");
1710  k++;
1711  for (const auto& prim : a.primitives()) {
1712  if (!symbol_active_[meta(prim).count]) continue;
1713  casadi_int i = meta(prim).active_i;
1714  if (meta(prim).type==OPTI_VAR) {
1715  x0.at(i) = prim;
1716  } else if (meta(prim).type==OPTI_PAR) {
1717  p.at(i) = prim;
1718  } else if (meta(prim).type==OPTI_DUAL_G) {
1719  lam_g.at(i) = prim;
1720  } else {
1721  casadi_error("Unknown");
1722  }
1723  }
1724  }
1725  MXDict arg;
1726  arg["p"] = veccat(p);
1727 
1728  // Evaluate bounds for given parameter values
1729  MXDict r = bounds_(arg);
1730  arg["x0"] = veccat(x0);
1731  arg["lam_g0"] = veccat(lam_g);
1732  arg["lbg"] = r["lbg"];
1733  arg["ubg"] = r["ubg"];
1734 
1735  r = solver(arg);
1736 
1737  std::vector<MX> helper_in = {veccat(active_symvar(OPTI_VAR)),
1738  veccat(active_symvar(OPTI_PAR)),
1739  veccat(active_symvar(OPTI_DUAL_G))};
1740  Dict h_opts;
1741  Dict opts_remainder = extract_from_dict(opts, "helper_options", h_opts);
1742  Function helper("helper", helper_in, {res}, h_opts);
1743 
1744  std::vector<MX> arg_in = helper(std::vector<MX>{r.at("x"), arg["p"], r.at("lam_g")});
1745 
1746  return Function(name, args, arg_in, name_in, name_out, opts_remainder);
1747 
1748 }
MX lam_g() const
Get dual variables as a symbolic column vector.
void solver(const std::string &solver, const Dict &plugin_options=Dict(), const Dict &solver_options=Dict())
Solver.
Function to_function(const std::string &name, const std::vector< MX > &args, const std::vector< MX > &res, const Dict &opts=Dict())
Create a CasADi Function from the Opti solver.
Definition: optistack.cpp:435
void assign_vector(const std::vector< S > &s, std::vector< D > &d)
Dict extract_from_dict(const Dict &d, const std::string &key, T &value)

References casadi::MetaVar::active_i, active_symvar(), active_values(), arg(), casadi::assign_vector(), baked_copy(), casadi::extract_from_dict(), casadi::MX::is_valid_input(), lam_g(), casadi::OPTI_DUAL_G, casadi::OPTI_PAR, casadi::OPTI_VAR, p(), casadi::MX::primitives(), problem_dirty(), res(), solver(), solver_construct(), casadi::str(), and casadi::Opti::to_function().

◆ ubg()

MX casadi::OptiNode::ubg ( ) const
inline

Definition at line 272 of file optistack_internal.hpp.

272  {
273  if (problem_dirty()) return baked_copy().ubg();
274  return bounds_unscaled_ubg_;
275  }
MX ubg() const
Definition: optistack.cpp:374

Referenced by show_infeasibilities().

◆ update_user_dict()

void casadi::OptiNode::update_user_dict ( const MX &  m,
const Dict &  meta 
)

Definition at line 586 of file optistack_internal.cpp.

586  {
587  if (has_con(m)) {
588  MetaCon m_update = get_meta_con(m);
589  MetaVar m_update2 = get_meta(m_update.dual_canon);
590  for (const auto & it : meta) {
591  m_update.extra[it.first] = it.second;
592  m_update2.extra[it.first] = it.second;
593  }
594  set_meta_con(m, m_update);
595  set_meta(m_update.dual_canon, m_update2);
596  } else {
597  for (const auto & s : MX::symvar(m)) {
598  MetaVar m_update = get_meta(s);
599  for (const auto & it : meta)
600  m_update.extra[it.first] = it.second;
601  set_meta(s, m_update);
602  }
603  }
604 }
MetaCon get_meta_con(const MX &m) const
Get meta-data of symbol (for internal use only)
MetaVar get_meta(const MX &m) const
Get meta-data of symbol (for internal use only)

References casadi::MetaCon::dual_canon, casadi::MetaCon::extra, casadi::MetaVar::extra, get_meta(), get_meta_con(), set_meta(), set_meta_con(), and casadi::MX::symvar().

Referenced by subject_to().

◆ user_dict()

Dict casadi::OptiNode::user_dict ( const MX &  m) const

Definition at line 606 of file optistack_internal.cpp.

606  {
607  if (has_con(m)) {
608  MetaCon meta = get_meta_con(m);
609  return meta.extra;
610  } else {
611  MetaVar meta = get_meta(m);
612  return meta.extra;
613  }
614 }

References casadi::MetaCon::extra, casadi::MetaVar::extra, get_meta(), and get_meta_con().

◆ value() [1/3]

DM casadi::OptiNode::value ( const DM &  x,
const std::vector< MX > &  values = std::vector<MX>(),
bool  scaled = false 
) const
inline

Obtain value of expression at the current value

Definition at line 121 of file optistack_internal.hpp.

122  { return x; }

◆ value() [2/3]

DM casadi::OptiNode::value ( const MX &  x,
const std::vector< MX > &  values = std::vector<MX>(),
bool  scaled = false 
) const

Obtain value of expression at the current value

Definition at line 1418 of file optistack_internal.cpp.

1418  {
1419 
1420  std::shared_ptr<ValueHelper> vh;
1421  if (!helpers_->incache(expr, vh)) {
1422  vh = std::make_shared<ValueHelper>();
1423  std::vector<MX> x = symvar(expr, OPTI_VAR);
1424  std::vector<MX> p = symvar(expr, OPTI_PAR);
1425  std::vector<MX> lam = symvar(expr, OPTI_DUAL_G);
1426  vh->x = x;
1427  vh->p = p;
1428  vh->lam = lam;
1429  vh->helper = Function("helper", std::vector<MX>{veccat(x), veccat(p), veccat(lam)}, {expr});
1430  if (vh->helper.has_free())
1431  casadi_error("This expression has symbols that are not defined "
1432  "within Opti using variable/parameter.");
1433  helpers_->tocache_if_missing(expr, vh);
1434  }
1435 
1436  const std::vector<MX>& x = vh->x;
1437  const std::vector<MX>& p = vh->p;
1438  const std::vector<MX>& lam = vh->lam;
1439  const Function& helper = vh->helper;
1440 
1441  std::map<VariableType, std::map<casadi_int, MX> > temp;
1442  temp[OPTI_DUAL_G] = std::map<casadi_int, MX>();
1443  for (const auto& v : values) {
1444  casadi_assert_dev(v.is_op(OP_EQ));
1445  casadi_int i = meta(v.dep(1)).i;
1446  casadi_assert_dev(v.dep(0).is_constant());
1447  temp[meta(v.dep(1)).type][i] = v.dep(0);
1448  }
1449 
1450  bool undecided_vars = false;
1451  std::vector<DM> x_num;
1452  for (const auto& e : x) {
1453  casadi_int i = meta(e).i;
1454  x_num.push_back(store_latest_.at(OPTI_VAR).at(i));
1455  undecided_vars |= override_num(temp[OPTI_VAR], x_num, i);
1456  if (scaled) {
1457  x_num.back() = x_num.back()/store_linear_scale_.at(OPTI_VAR)[meta(e).i] -
1458  store_linear_scale_offset_.at(OPTI_VAR)[meta(e).i];
1459  }
1460  }
1461 
1462  std::vector<DM> lam_num;
1463  for (const auto& e : lam) {
1464  casadi_int i = meta(e).i;
1465  casadi_assert(i<store_latest_.at(OPTI_DUAL_G).size(),
1466  "This expression has a dual for a constraint that is not given to Opti:\n" +
1467  describe(e, 1));
1468  lam_num.push_back(store_latest_.at(OPTI_DUAL_G).at(i));
1469  undecided_vars |= override_num(temp[OPTI_DUAL_G], lam_num, i);
1470  }
1471 
1472  std::vector<DM> p_num;
1473  for (const auto& e : p) {
1474  casadi_int i = meta(e).i;
1475  p_num.push_back(store_initial_.at(OPTI_PAR).at(i));
1476  override_num(temp[OPTI_PAR], p_num, i);
1477  casadi_assert(p_num.back().is_regular(),
1478  "This expression depends on a parameter with unset value:\n"+
1479  describe(e, 1));
1480  }
1481 
1482  if (undecided_vars) {
1483  assert_solved();
1484  for (const auto& e : x)
1485  casadi_assert(symbol_active_[meta(e).count],
1486  "This expression has symbols that do not appear in the constraints and objective:\n" +
1487  describe(e, 1));
1488  for (const auto& e : lam)
1489  casadi_assert(symbol_active_[meta(e).count],
1490  "This expression has a dual for a constraint that is not given to Opti:\n" +
1491  describe(e, 1));
1492  }
1493 
1494  std::vector<DM> arg = helper(std::vector<DM>{veccat(x_num), veccat(p_num), veccat(lam_num)});
1495  return arg[0];
1496 }
bool override_num(const std::map< casadi_int, MX > &temp, std::vector< DM > &num, casadi_int i)
VariableType type
Definition: optistack.hpp:2749

References arg(), assert_solved(), describe(), casadi::MetaVar::i, casadi::OP_EQ, casadi::OPTI_DUAL_G, casadi::OPTI_PAR, casadi::OPTI_VAR, casadi::override_num(), p(), symvar(), casadi::MetaVar::type, and x().

Referenced by show_infeasibilities().

◆ value() [3/3]

DM casadi::OptiNode::value ( const SX &  x,
const std::vector< MX > &  values = std::vector<MX>(),
bool  scaled = false 
) const
inline

Obtain value of expression at the current value

Definition at line 123 of file optistack_internal.hpp.

124  {
125  casadi_assert(x.is_constant(), "Opti works with MX: cannot evaluate SX expression " + str(x));
126  return evalf(x);
127  }

References casadi::Matrix< Scalar >::is_constant(), and casadi::str().

◆ value_parameters()

std::vector< MX > casadi::OptiNode::value_parameters ( ) const

Definition at line 730 of file optistack_internal.cpp.

730  {
731  std::vector<MX> ret;
732  for (const auto& e : symvar()) {
733  if (meta(e).type==OPTI_PAR)
734  ret.push_back(e==store_initial_.at(meta(e).type)[meta(e).i]);
735  }
736  return ret;
737 }

References casadi::OPTI_PAR, and symvar().

◆ value_variables()

std::vector< MX > casadi::OptiNode::value_variables ( ) const

Definition at line 721 of file optistack_internal.cpp.

721  {
722  std::vector<MX> ret;
723  for (const auto& e : symvar()) {
724  if (meta(e).type==OPTI_VAR)
725  ret.push_back(e==store_latest_.at(meta(e).type)[meta(e).i]);
726  }
727  return ret;
728 }

References casadi::OPTI_VAR, and symvar().

◆ variable() [1/3]

MX casadi::OptiNode::variable ( casadi_int  n = 1,
casadi_int  m = 1,
const std::string &  attribute = "full" 
)

Definition at line 278 of file optistack_internal.cpp.

278  {
279 
280  // Prepare metadata
281  MetaVar meta_data;
282  meta_data.attribute = attribute;
283  meta_data.n = n;
284  meta_data.m = m;
285  meta_data.type = OPTI_VAR;
286  meta_data.count = count_++;
287  meta_data.i = count_var_++;
288  meta_data.domain = OPTI_DOMAIN_REAL;
289 
290  MX symbol, ret;
291 
292  if (attribute=="symmetric") {
293  casadi_assert(n==m, "You specified attribute 'symmetric', "
294  "while matrix is not even square, but " + str(n) + "-by-" + str(m) + ".");
295  symbol = MX::sym(name_prefix() + "x_" + str(count_var_), n*(n+1)/2);
296  ret = tril2symm(MX(Sparsity::lower(n), symbol));
297  } else if (attribute=="full") {
298  symbol = MX::sym(name_prefix() + "x_" + str(count_var_), n, m);
299  ret = symbol;
300  } else {
301  casadi_error("Unknown attribute '" + attribute + "'. Choose from 'full' or 'symmetric'.");
302  }
303 
304  // Store the symbol; preventing it from going ut of scope
305  symbols_.push_back(symbol);
306  store_initial_[OPTI_VAR].push_back(DM::zeros(symbol.sparsity()));
307  store_latest_[OPTI_VAR].push_back(DM::nan(symbol.sparsity()));
308  store_linear_scale_[OPTI_VAR].push_back(DM::ones(symbol.sparsity()));
309  store_linear_scale_offset_[OPTI_VAR].push_back(DM::zeros(symbol.sparsity()));
310 
311  set_meta(symbol, meta_data);
312  return ret;
313 }

References casadi::MetaVar::attribute, casadi::MetaVar::count, casadi::MetaVar::domain, casadi::MetaVar::i, casadi::Sparsity::lower(), casadi::MetaVar::m, casadi::MetaVar::n, casadi::Matrix< double >::nan(), casadi::GenericMatrix< MatType >::ones(), casadi::OPTI_DOMAIN_REAL, casadi::OPTI_VAR, set_meta(), casadi::str(), casadi::GenericMatrix< MX >::sym(), casadi::MetaVar::type, and casadi::GenericMatrix< MatType >::zeros().

◆ variable() [2/3]

MX casadi::OptiNode::variable ( const MX &  symbol,
const std::string &  attribute = "full" 
)

Definition at line 315 of file optistack_internal.cpp.

315  {
316 
317  // Prepare metadata
318  MetaVar meta_data;
319  meta_data.attribute = attribute;
320  meta_data.n = symbol.size1();
321  meta_data.m = symbol.size2();
322  meta_data.type = OPTI_VAR;
323  meta_data.count = count_++;
324  meta_data.i = count_var_++;
325 
326  // Store the symbol; preventing it from going ut of scope
327  symbols_.push_back(symbol);
328  store_initial_[OPTI_VAR].push_back(DM::zeros(symbol.sparsity()));
329  store_latest_[OPTI_VAR].push_back(DM::nan(symbol.sparsity()));
330  store_linear_scale_[OPTI_VAR].push_back(DM::ones(symbol.sparsity()));
331  store_linear_scale_offset_[OPTI_VAR].push_back(DM::zeros(symbol.sparsity()));
332 
333  set_meta(symbol, meta_data);
334  return symbol;
335 }

References casadi::MetaVar::attribute, casadi::MetaVar::count, casadi::MetaVar::i, casadi::MetaVar::m, casadi::MetaVar::n, casadi::Matrix< double >::nan(), casadi::GenericMatrix< MatType >::ones(), casadi::OPTI_VAR, set_meta(), casadi::MetaVar::type, and casadi::GenericMatrix< MatType >::zeros().

◆ variable() [3/3]

MX casadi::OptiNode::variable ( const Sparsity &  sp,
const std::string &  attribute = "full" 
)

Definition at line 337 of file optistack_internal.cpp.

337  {
338 
339  // Prepare metadata
340  MetaVar meta_data;
341  meta_data.attribute = attribute;
342  meta_data.n = sp.size1();
343  meta_data.m = sp.size2();
344  meta_data.type = OPTI_VAR;
345  meta_data.count = count_++;
346  meta_data.i = count_var_++;
347 
348  MX symbol = MX::sym(name_prefix() + "x_" + str(count_var_), sp);
349 
350  // Store the symbol; preventing it from going ut of scope
351  symbols_.push_back(symbol);
352  store_initial_[OPTI_VAR].push_back(DM::zeros(symbol.sparsity()));
353  store_latest_[OPTI_VAR].push_back(DM::nan(symbol.sparsity()));
354  store_linear_scale_[OPTI_VAR].push_back(DM::ones(symbol.sparsity()));
355  store_linear_scale_offset_[OPTI_VAR].push_back(DM::zeros(symbol.sparsity()));
356 
357  set_meta(symbol, meta_data);
358  return symbol;
359 }

References casadi::MetaVar::attribute, casadi::MetaVar::count, casadi::MetaVar::i, casadi::MetaVar::m, casadi::MetaVar::n, casadi::Matrix< double >::nan(), casadi::GenericMatrix< MatType >::ones(), casadi::OPTI_VAR, set_meta(), casadi::Sparsity::size1(), casadi::Sparsity::size2(), casadi::str(), casadi::GenericMatrix< MX >::sym(), casadi::MetaVar::type, and casadi::GenericMatrix< MatType >::zeros().

◆ weak()

Extra doc: https://github.com/casadi/casadi/wiki/L_1ai

Definition at line 67 of file generic_shared_internal.hpp.

215  {
216 #ifdef CASADI_WITH_THREADSAFE_SYMBOLICS
217  auto* w = weak_ref_.load(std::memory_order_acquire);
218  if (!w) {
219  auto* nw = new GenericWeakRef<Shared, Internal>(static_cast<Internal*>(this));
220  GenericWeakRef<Shared, Internal>* expected = nullptr;
221  if (weak_ref_.compare_exchange_strong(
222  expected, nw, std::memory_order_release, std::memory_order_acquire)) {
223  w = nw;
224  } else {
225  delete nw; // lost the race; another thread published first
226  w = expected;
227  }
228  }
229  return w;
230 #else
231  if (weak_ref_==nullptr) {
232  weak_ref_ = new GenericWeakRef<Shared, Internal>(static_cast<Internal*>(this));
233  }
234  return weak_ref_;
235 #endif // CASADI_WITH_THREADSAFE_SYMBOLICS
236  }

◆ x()

MX casadi::OptiNode::x ( ) const
inline

Definition at line 244 of file optistack_internal.hpp.

244  {
245  if (problem_dirty()) return baked_copy().x();
246  return nlp_.at("x");
247  }
MX x() const
Get all (scalarised) decision variables as a symbolic column vector.
Definition: optistack.cpp:334

Referenced by bake(), set_domain(), set_initial(), set_linear_scale(), set_value(), value(), and x_lookup().

◆ x_describe()

std::string casadi::OptiNode::x_describe ( casadi_int  i,
const Dict &  opts = Dict() 
) const

Definition at line 221 of file optistack_internal.cpp.

221  {
222  if (problem_dirty()) return baked_copy().x_describe(i, opts);
223  MX symbol = x_lookup(i);
224  casadi_int local_i = i-meta(symbol).start + GlobalOptions::start_index;
225  std::string description = describe(symbol, 0, opts);
226  if (symbol.numel()>1)
227  description += "\nAt nonzero " + str(local_i) + ".";
228  return description;
229 }
std::string x_describe(casadi_index i, const Dict &opts=Dict()) const
Describe entry i of the flattened x vector.
Definition: optistack.cpp:649
MX x_lookup(casadi_int i) const

References baked_copy(), describe(), casadi::description(), problem_dirty(), casadi::IndexAbstraction::start, casadi::GlobalOptions::start_index, casadi::str(), casadi::OptiAdvanced::x_describe(), and x_lookup().

◆ x_linear_scale()

DM casadi::OptiNode::x_linear_scale ( ) const
inline

Definition at line 283 of file optistack_internal.hpp.

283  {
284  if (problem_dirty()) return baked_copy().x_linear_scale();
285  return DM(linear_scale_);
286  }
DM x_linear_scale() const
Per-entry scale of x (see set_linear_scale); a Python property.
Definition: optistack.cpp:391

Referenced by scale_helper().

◆ x_linear_scale_offset()

DM casadi::OptiNode::x_linear_scale_offset ( ) const
inline

Definition at line 287 of file optistack_internal.hpp.

287  {
289  return DM(linear_scale_offset_);
290  }
DM x_linear_scale_offset() const
Per-entry offset of x (see set_linear_scale); a Python property.
Definition: optistack.cpp:399

Referenced by scale_helper().

◆ x_lookup()

MX casadi::OptiNode::x_lookup ( casadi_int  i) const

Definition at line 231 of file optistack_internal.cpp.

231  {
232  if (problem_dirty()) return baked_copy().x_lookup(i);
233  casadi_assert(i>=0 && i<nx(),
234  "Index " + str(i) + " out of range for " + str(nx()) + " decision variables");
235  std::vector<MX> x = active_symvar(OPTI_VAR);
236  for (const auto& e : x) {
237  const MetaVar& m = meta(e);
238  if (i>=m.start && i<m.stop) return e;
239  }
240  casadi_error("Internal error");
241  return MX();
242 }
MX x_lookup(casadi_index i) const
Get the variable that owns entry i of the flattened x vector.
Definition: optistack.cpp:609

References active_symvar(), baked_copy(), nx(), casadi::OPTI_VAR, problem_dirty(), casadi::IndexAbstraction::start, casadi::IndexAbstraction::stop, casadi::str(), x(), and casadi::OptiAdvanced::x_lookup().

Referenced by x_describe().

Friends And Related Function Documentation

◆ InternalOptiCallback

friend class InternalOptiCallback
friend

Definition at line 57 of file optistack_internal.hpp.

Referenced by solve_prepare(), and solver_construct().

Member Data Documentation

◆ problem_dirty_

bool casadi::OptiNode::problem_dirty_

Definition at line 322 of file optistack_internal.hpp.

◆ solved_

bool casadi::OptiNode::solved_

Definition at line 330 of file optistack_internal.hpp.

◆ solver_dirty_

bool casadi::OptiNode::solver_dirty_

Definition at line 326 of file optistack_internal.hpp.


The documentation for this class was generated from the following files: