preprocessor/src/ModelTree.hh

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/*
* Copyright © 2003-2020 Dynare Team
*
* This file is part of Dynare.
*
* Dynare is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* Dynare is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef _MODELTREE_HH
#define _MODELTREE_HH
using namespace std;
#include <string>
#include <vector>
#include <deque>
#include <map>
#include <ostream>
#include <array>
#include <filesystem>
#include "DataTree.hh"
#include "EquationTags.hh"
#include "ExtendedPreprocessorTypes.hh"
// Helper to convert a vector into a tuple
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template<typename T, size_t... Indices>
auto
vectorToTupleHelper(const vector<T> &v, index_sequence<Indices...>)
{
return tuple(v[Indices] ...);
}
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template<size_t N, typename T>
auto
vectorToTuple(const vector<T> &v)
{
assert(v.size() >= N);
return vectorToTupleHelper(v, make_index_sequence<N>());
}
//! Vector describing equations: BlockSimulationType, if BlockSimulationType == EVALUATE_s then a expr_t on the new normalized equation
using equation_type_and_normalized_equation_t = vector<pair<EquationType, expr_t>>;
//! Vector describing variables: max_lag in the block, max_lead in the block
using lag_lead_vector_t = vector<pair< int, int>>;
//! for each block contains tuple<Simulation_Type, first_equation, Block_Size, Recursive_part_Size>
using block_type_firstequation_size_mfs_t = vector<tuple<BlockSimulationType, int, int, int>>;
//! for a block contains derivatives tuple<block_equation_number, block_variable_number, lead_lag, expr_t>
using block_derivatives_equation_variable_laglead_nodeid_t = vector<tuple<int, int, int, expr_t>>;
//! for all blocks derivatives description
using blocks_derivatives_t = vector<block_derivatives_equation_variable_laglead_nodeid_t>;
//! Shared code for static and dynamic models
class ModelTree : public DataTree
{
friend class DynamicModel;
friend class StaticModel;
public:
// Set via the `compiler` command
string user_set_add_flags, user_set_subst_flags, user_set_add_libs, user_set_subst_libs, user_set_compiler;
protected:
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/*
* ************** BEGIN **************
* The following structures keep track of the model equations and must all be updated
* when adding or removing an equation. Hence, if a new parallel structure is added
* in the future, it must be maintained whereever these structures are updated
* See in particular methods clearEquations(), replaceMyEquations() and
* computeRamseyPolicyFOCs() of DynamicModel class.
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* NB: This message added with the introduction of the `exclude_eqs` option, hence
* that's a place to update future structures.
*/
//! Stores declared and generated auxiliary equations
vector<BinaryOpNode *> equations;
//! Stores line numbers of declared equations; -1 means undefined
vector<int> equations_lineno;
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//! Stores equation tags
EquationTags equation_tags;
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/*
* ************** END **************
*/
//! Only stores generated auxiliary equations, in an order meaningful for evaluation
/*! These equations only contain the definition of auxiliary variables, and
may diverge from those in the main model (equations), if other model
transformations applied subsequently. This is not a problem, since
aux_equations is only used for regenerating the values of auxiliaries
given the others.
For example, such a divergence appears when there is an expectation
operator in a ramsey model, see
tests/optimal_policy/nk_ramsey_expectation.mod */
vector<BinaryOpNode *> aux_equations;
//! Maximum order at which (endogenous) derivatives have been computed
int computed_derivs_order{0};
//! Stores derivatives
/*! Index 0 is not used, index 1 contains first derivatives, ...
For each derivation order, stores a map whose key is a vector of integer: the
first integer is the equation index, the remaining ones are the derivation
IDs of variables (in non-decreasing order, to avoid storing symmetric
elements several times) */
vector<map<vector<int>, expr_t>> derivatives;
//! Number of non-zero derivatives
/*! Index 0 is not used, index 1 contains number of non-zero first
derivatives, ... */
vector<int> NNZDerivatives;
//! Derivatives with respect to parameters
/*! The key of the outer map is a pair (derivation order w.r.t. endogenous,
derivation order w.r.t. parameters). For e.g., { 1, 2 } corresponds to the jacobian
differentiated twice w.r.t. to parameters.
In inner maps, the vector of integers consists of: the equation index, then
the derivation IDs of endogenous (in non-decreasing order),
then the IDs of parameters (in non-decreasing order)*/
map<pair<int,int>, map<vector<int>, expr_t>> params_derivatives;
//! Storage for temporary terms in block/bytecode mode
temporary_terms_t temporary_terms;
//! Used model local variables, that will be treated as temporary terms
/*! See the comments in ModelTree::computeTemporaryTerms() */
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map<expr_t, expr_t, ExprNodeLess> temporary_terms_mlv;
//! Temporary terms for residuals and derivatives
/*! Index 0 is temp. terms of residuals, index 1 for first derivatives, ... */
vector<temporary_terms_t> temporary_terms_derivatives;
//! Stores, for each temporary term, its index in the MATLAB/Julia vector
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temporary_terms_idxs_t temporary_terms_idxs;
//! Temporary terms for block decomposed models
vector<vector<temporary_terms_t>> v_temporary_terms;
vector<temporary_terms_inuse_t> v_temporary_terms_inuse;
//! Temporary terms for parameter derivatives, under a disaggregated form
/*! The pair of integers is to be interpreted as in param_derivatives */
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map<pair<int, int>, temporary_terms_t> params_derivs_temporary_terms;
//! Stores, for each temporary term in param. derivs, its index in the MATLAB/Julia vector
temporary_terms_idxs_t params_derivs_temporary_terms_idxs;
//! Trend variables and their growth factors
map<int, expr_t> trend_symbols_map;
//! for all trends; the boolean is true if this is a log-trend, false otherwise
using nonstationary_symbols_map_t = map<int, pair<bool, expr_t>>;
//! Nonstationary variables and their deflators
nonstationary_symbols_map_t nonstationary_symbols_map;
//! Sparse matrix of double to store the values of the Jacobian
/*! First index is lag, second index is equation number, third index is endogenous type specific ID */
using dynamic_jacob_map_t = map<tuple<int, int, int>, expr_t>;
//! The jacobian without the elements below the cutoff
dynamic_jacob_map_t dynamic_jacobian;
//! vector of block reordered variables and equations
vector<int> equation_reordered, variable_reordered, inv_equation_reordered, inv_variable_reordered;
//! Store the derivatives or the chainrule derivatives:map<tuple<equation, variable, lead_lag>, expr_t>
using first_chain_rule_derivatives_t = map<tuple<int, int, int>, expr_t>;
first_chain_rule_derivatives_t first_chain_rule_derivatives;
map_idx_t map_idx;
//! Vector describing equations: BlockSimulationType, if BlockSimulationType == EVALUATE_s then a expr_t on the new normalized equation
equation_type_and_normalized_equation_t equation_type_and_normalized_equation;
//! for each block contains pair< Simulation_Type, pair < Block_Size, Recursive_part_Size >>
block_type_firstequation_size_mfs_t block_type_firstequation_size_mfs;
//! for all blocks derivatives description
blocks_derivatives_t blocks_derivatives;
//! Vector indicating if the block is linear in endogenous variable (true) or not (false)
vector<bool> blocks_linear;
//! Map the derivatives for a block tuple<lag, eq, var>
using derivative_t = map<tuple<int, int, int>, expr_t>;
//! Vector of derivative for each blocks
vector<derivative_t> derivative_endo, derivative_other_endo, derivative_exo, derivative_exo_det;
//! for each block described the number of static, forward, backward and mixed variables in the block
/*! tuple<static, forward, backward, mixed> */
vector<tuple<int, int, int, int>> block_col_type;
//!Maximum lead and lag for each block on endogenous of the block, endogenous of the previous blocks, exogenous and deterministic exogenous
vector<pair<int, int>> endo_max_leadlag_block, other_endo_max_leadlag_block, exo_max_leadlag_block, exo_det_max_leadlag_block, max_leadlag_block;
//! the file containing the model and the derivatives code
ofstream code_file;
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//! Vector indicating if the equation is linear in endogenous variable (true) or not (false)
vector<bool> is_equation_linear;
//! Computes derivatives
/*! \param order the derivation order
\param vars the derivation IDs w.r.t. which compute the derivatives */
void computeDerivatives(int order, const set<int> &vars);
//! Computes derivatives of the Jacobian and Hessian w.r. to parameters
void computeParamsDerivatives(int paramsDerivsOrder);
//! Write derivative of an equation w.r. to a variable
void writeDerivative(ostream &output, int eq, int symb_id, int lag, ExprNodeOutputType output_type, const temporary_terms_t &temporary_terms) const;
//! Computes temporary terms (for all equations and derivatives)
void computeTemporaryTerms(bool is_matlab, bool no_tmp_terms);
//! Computes temporary terms for the file containing parameters derivatives
void computeParamsDerivativesTemporaryTerms();
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//! Writes temporary terms
void writeTemporaryTerms(const temporary_terms_t &tt, temporary_terms_t &temp_term_union, const temporary_terms_idxs_t &tt_idxs, ostream &output, ExprNodeOutputType output_type, deriv_node_temp_terms_t &tef_terms) const;
void writeJsonTemporaryTerms(const temporary_terms_t &tt, temporary_terms_t &temp_term_union, ostream &output, deriv_node_temp_terms_t &tef_terms, const string &concat) const;
//! Compiles temporary terms
void compileTemporaryTerms(ostream &code_file, unsigned int &instruction_number, const temporary_terms_t &tt, map_idx_t map_idx, bool dynamic, bool steady_dynamic) const;
//! Adds informations for simulation in a binary file
void Write_Inf_To_Bin_File(const string &filename, int &u_count_int, bool &file_open, bool is_two_boundaries, int block_mfs) const;
//! Fixes output when there are more than 32 nested parens, Issue #1201
void fixNestedParenthesis(ostringstream &output, map<string, string> &tmp_paren_vars, bool &message_printed) const;
//! Tests if string contains more than 32 nested parens, Issue #1201
bool testNestedParenthesis(const string &str) const;
void writeModelLocalVariableTemporaryTerms(temporary_terms_t &temp_term_union,
const temporary_terms_idxs_t &tt_idxs,
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ostream &output, ExprNodeOutputType output_type,
deriv_node_temp_terms_t &tef_terms) const;
//! Writes model equations
void writeModelEquations(ostream &output, ExprNodeOutputType output_type) const;
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void writeModelEquations(ostream &output, ExprNodeOutputType output_type,
const temporary_terms_t &temporary_terms) const;
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//! Writes JSON model equations
//! if residuals = true, we are writing the dynamic/static model.
//! Otherwise, just the model equations (with line numbers, no tmp terms)
void writeJsonModelEquations(ostream &output, bool residuals) const;
void writeJsonModelLocalVariables(ostream &output, deriv_node_temp_terms_t &tef_terms) const;
//! Compiles model equations
void compileModelEquations(ostream &code_file, unsigned int &instruction_number, const temporary_terms_t &tt, const map_idx_t &map_idx, bool dynamic, bool steady_dynamic) const;
//! Writes LaTeX model file
void writeLatexModelFile(const string &mod_basename, const string &latex_basename, ExprNodeOutputType output_type, bool write_equation_tags) const;
//! Sparse matrix of double to store the values of the Jacobian
/*! First index is equation number, second index is endogenous type specific ID */
using jacob_map_t = map<pair<int, int>, double>;
//! Normalization of equations
/*! Maps endogenous type specific IDs to equation numbers */
vector<int> endo2eq;
//! number of equation in the prologue and in the epilogue
unsigned int epilogue, prologue;
//! for each block contains pair< max_lag, max_lead>
lag_lead_vector_t block_lag_lead;
//! Compute the matching between endogenous and variable using the jacobian contemporaneous_jacobian
/*!
\param contemporaneous_jacobian Jacobian used as an incidence matrix: all elements declared in the map (even if they are zero), are used as vertices of the incidence matrix
\return True if a complete normalization has been achieved
*/
bool computeNormalization(const jacob_map_t &contemporaneous_jacobian, bool verbose);
//! Try to compute the matching between endogenous and variable using a decreasing cutoff
/*!
Applied to the jacobian contemporaneous_jacobian and stop when a matching is found.
If no matching is found using a strictly positive cutoff, then a zero cutoff is applied (i.e. use a symbolic normalization); in that case, the method adds zeros in the jacobian matrices to reflect all the edges in the symbolic incidence matrix.
If no matching is found with a zero cutoff close to zero an error message is printout.
*/
void computeNonSingularNormalization(jacob_map_t &contemporaneous_jacobian, double cutoff, jacob_map_t &static_jacobian, dynamic_jacob_map_t &dynamic_jacobian);
//! Try to find a natural normalization if all equations are matched to an endogenous variable on the LHS
bool computeNaturalNormalization();
//! Try to normalized each unnormalized equation (matched endogenous variable only on the LHS)
multimap<int, int> computeNormalizedEquations() const;
//! Evaluate the jacobian and suppress all the elements below the cutoff
void evaluateAndReduceJacobian(const eval_context_t &eval_context, jacob_map_t &contemporaneous_jacobian, jacob_map_t &static_jacobian, dynamic_jacob_map_t &dynamic_jacobian, double cutoff, bool verbose);
//! Select and reorder the non linear equations of the model
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vector<pair<int, int>> select_non_linear_equations_and_variables(vector<bool> is_equation_linear, const dynamic_jacob_map_t &dynamic_jacobian, vector<int> &equation_reordered, vector<int> &variable_reordered,
vector<int> &inv_equation_reordered, vector<int> &inv_variable_reordered,
lag_lead_vector_t &equation_lag_lead, lag_lead_vector_t &variable_lag_lead,
vector<unsigned int> &n_static, vector<unsigned int> &n_forward, vector<unsigned int> &n_backward, vector<unsigned int> &n_mixed);
//! Search the equations and variables belonging to the prologue and the epilogue of the model
void computePrologueAndEpilogue(const jacob_map_t &static_jacobian, vector<int> &equation_reordered, vector<int> &variable_reordered);
//! Determine the type of each equation of model and try to normalized the unnormalized equation using computeNormalizedEquations
equation_type_and_normalized_equation_t equationTypeDetermination(const map<tuple<int, int, int>, expr_t> &first_order_endo_derivatives, const vector<int> &Index_Var_IM, const vector<int> &Index_Equ_IM, int mfs) const;
//! Compute the block decomposition and for a non-recusive block find the minimum feedback set
void computeBlockDecompositionAndFeedbackVariablesForEachBlock(const jacob_map_t &static_jacobian, const dynamic_jacob_map_t &dynamic_jacobian, vector<int> &equation_reordered, vector<int> &variable_reordered, vector<pair<int, int>> &blocks, const equation_type_and_normalized_equation_t &Equation_Type, bool verbose_, bool select_feedback_variable, int mfs, vector<int> &inv_equation_reordered, vector<int> &inv_variable_reordered, lag_lead_vector_t &equation_lag_lead, lag_lead_vector_t &variable_lag_lead_t, vector<unsigned int> &n_static, vector<unsigned int> &n_forward, vector<unsigned int> &n_backward, vector<unsigned int> &n_mixed) const;
//! Reduce the number of block merging the same type equation in the prologue and the epilogue and determine the type of each block
block_type_firstequation_size_mfs_t reduceBlocksAndTypeDetermination(const dynamic_jacob_map_t &dynamic_jacobian, vector<pair<int, int>> &blocks, const equation_type_and_normalized_equation_t &Equation_Type, const vector<int> &variable_reordered, const vector<int> &equation_reordered, vector<unsigned int> &n_static, vector<unsigned int> &n_forward, vector<unsigned int> &n_backward, vector<unsigned int> &n_mixed, vector<tuple<int, int, int, int>> &block_col_type, bool linear_decomposition);
//! Determine the maximum number of lead and lag for the endogenous variable in a bloc
void getVariableLeadLagByBlock(const dynamic_jacob_map_t &dynamic_jacobian, const vector<int> &components_set, int nb_blck_sim, lag_lead_vector_t &equation_lead_lag, lag_lead_vector_t &variable_lead_lag, const vector<int> &equation_reordered, const vector<int> &variable_reordered) const;
//! For each equation determine if it is linear or not
vector<bool> equationLinear(map<tuple<int, int, int>, expr_t> first_order_endo_derivatives) const;
//! Print an abstract of the block structure of the model
void printBlockDecomposition(const vector<pair<int, int>> &blocks) const;
//! Determine for each block if it is linear or not
vector<bool> BlockLinear(const blocks_derivatives_t &blocks_derivatives, const vector<int> &variable_reordered) const;
//! Remove equations specified by exclude_eqs
vector<int> includeExcludeEquations(set<pair<string, string>> &eqs, bool exclude_eqs,
vector<BinaryOpNode *> &equations, vector<int> &equations_lineno,
EquationTags &equation_tags, bool static_equations) const;
//! Determine the simulation type of each block
virtual BlockSimulationType getBlockSimulationType(int block_number) const = 0;
//! Return the number of blocks
virtual unsigned int getNbBlocks() const = 0;
//! Return the first equation number of a block
virtual unsigned int getBlockFirstEquation(int block_number) const = 0;
//! Return the size of the block block_number
virtual unsigned int getBlockSize(int block_number) const = 0;
//! Return the number of exogenous variable in the block block_number
virtual unsigned int getBlockExoSize(int block_number) const = 0;
//! Return the number of colums in the jacobian matrix for exogenous variable in the block block_number
virtual unsigned int getBlockExoColSize(int block_number) const = 0;
//! Return the number of feedback variable of the block block_number
virtual unsigned int getBlockMfs(int block_number) const = 0;
//! Return the maximum lag in a block
virtual unsigned int getBlockMaxLag(int block_number) const = 0;
//! Return the maximum lead in a block
virtual unsigned int getBlockMaxLead(int block_number) const = 0;
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inline void
setBlockLeadLag(int block, int max_lag, int max_lead)
{
block_lag_lead[block] = { max_lag, max_lead };
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};
//! Return the type of equation (equation_number) belonging to the block block_number
virtual EquationType getBlockEquationType(int block_number, int equation_number) const = 0;
//! Return true if the equation has been normalized
virtual bool isBlockEquationRenormalized(int block_number, int equation_number) const = 0;
//! Return the expr_t of the equation equation_number belonging to the block block_number
virtual expr_t getBlockEquationExpr(int block_number, int equation_number) const = 0;
//! Return the expr_t of the renormalized equation equation_number belonging to the block block_number
virtual expr_t getBlockEquationRenormalizedExpr(int block_number, int equation_number) const = 0;
//! Return the original number of equation equation_number belonging to the block block_number
virtual int getBlockEquationID(int block_number, int equation_number) const = 0;
//! Return the original number of variable variable_number belonging to the block block_number
virtual int getBlockVariableID(int block_number, int variable_number) const = 0;
//! Return the original number of the exogenous variable varexo_number belonging to the block block_number
virtual int getBlockVariableExoID(int block_number, int variable_number) const = 0;
//! Return the position of equation_number in the block number belonging to the block block_number
virtual int getBlockInitialEquationID(int block_number, int equation_number) const = 0;
//! Return the position of variable_number in the block number belonging to the block block_number
virtual int getBlockInitialVariableID(int block_number, int variable_number) const = 0;
//! Return the position of variable_number in the block number belonging to the block block_number
virtual int getBlockInitialExogenousID(int block_number, int variable_number) const = 0;
//! Return the position of the deterministic exogenous variable_number in the block number belonging to the block block_number
virtual int getBlockInitialDetExogenousID(int block_number, int variable_number) const = 0;
//! Return the position of the other endogenous variable_number in the block number belonging to the block block_number
virtual int getBlockInitialOtherEndogenousID(int block_number, int variable_number) const = 0;
//! Initialize equation_reordered & variable_reordered
void initializeVariablesAndEquations();
private:
//! Internal helper for the copy constructor and assignment operator
/*! Copies all the structures that contain ExprNode*, by the converting the
pointers into their equivalent in the new tree */
void copyHelper(const ModelTree &m);
//! Returns the name of the MATLAB architecture given the extension used for MEX files
static string matlab_arch(const string &mexext);
//! Compiles the MEX file
void compileDll(const string &basename, const string &static_or_dynamic, const string &mexext, const filesystem::path &matlabroot, const filesystem::path &dynareroot) const;
public:
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ModelTree(SymbolTable &symbol_table_arg,
NumericalConstants &num_constants_arg,
ExternalFunctionsTable &external_functions_table_arg,
bool is_dynamic_arg = false);
ModelTree(const ModelTree &m);
ModelTree(ModelTree &&) = delete;
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ModelTree &operator=(const ModelTree &m);
ModelTree &operator=(ModelTree &&) = delete;
//! Absolute value under which a number is considered to be zero
double cutoff{1e-15};
//! Compute the minimum feedback set
/*! 0 : all endogenous variables are considered as feedback variables
1 : the variables belonging to non normalized equation are considered as feedback variables
2 : the variables belonging to a non linear equation are considered as feedback variables
3 : the variables belonging to a non normalizable non linear equation are considered as feedback variables
default value = 0 */
int mfs{0};
//! Declare a node as an equation of the model; also give its line number
void addEquation(expr_t eq, int lineno);
//! Declare a node as an equation of the model, also giving its tags
void addEquation(expr_t eq, int lineno, const map<string, string> &eq_tags);
//! Declare a node as an auxiliary equation of the model, adding it at the end of the list of auxiliary equations
void addAuxEquation(expr_t eq);
//! Returns the number of equations in the model
int equation_number() const;
//! Adds a trend variable with its growth factor
void addTrendVariables(const vector<int> &trend_vars, expr_t growth_factor) noexcept(false);
//! Adds a nonstationary variables with their (common) deflator
void addNonstationaryVariables(const vector<int> &nonstationary_vars, bool log_deflator, expr_t deflator) noexcept(false);
//! Is a given variable non-stationary?
bool isNonstationary(int symb_id) const;
void set_cutoff_to_zero();
//! Simplify model equations: if a variable is equal to a constant, replace that variable elsewhere in the model
/*! Equations with tags are excluded, in particular because of MCPs, see
dynare#1697 */
void simplifyEquations();
/*! Reorder auxiliary variables so that they appear in recursive order in
set_auxiliary_variables.m and dynamic_set_auxiliary_series.m */
void reorderAuxiliaryEquations();
//! Find equations of the form “variable=constant”, excluding equations with tags
void findConstantEquationsWithoutTags(map<VariableNode *, NumConstNode *> &subst_table) const;
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//! Helper for writing the Jacobian elements in MATLAB and C
/*! Writes either (i+1,j+1) or [i+j*no_eq] */
void jacobianHelper(ostream &output, int eq_nb, int col_nb, ExprNodeOutputType output_type) const;
//! Helper for writing the sparse Hessian or third derivatives in MATLAB and C
/*! If order=2, writes either v2(i+1,j+1) or v2[i+j*NNZDerivatives[2]]
If order=3, writes either v3(i+1,j+1) or v3[i+j*NNZDerivatives[3]] */
void sparseHelper(int order, ostream &output, int row_nb, int col_nb, ExprNodeOutputType output_type) const;
//! Returns all the equation tags associated to an equation
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inline map<string, string>
getEquationTags(int eq) const
{
return equation_tags.getTagsByEqn(eq);
}
inline static string
c_Equation_Type(int type)
{
vector<string> c_Equation_Type =
{
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"E_UNKNOWN ",
"E_EVALUATE ",
"E_EVALUATE_S",
"E_SOLVE "
};
return c_Equation_Type[type];
};
inline static string
BlockType0(BlockType type)
{
switch (type)
{
case SIMULTANS:
return "SIMULTANEOUS TIME SEPARABLE ";
case PROLOGUE:
return "PROLOGUE ";
case EPILOGUE:
return "EPILOGUE ";
case SIMULTAN:
return "SIMULTANEOUS TIME UNSEPARABLE";
default:
return "UNKNOWN ";
}
};
inline static string
BlockSim(int type)
{
switch (type)
{
case EVALUATE_FORWARD:
return "EVALUATE FORWARD ";
case EVALUATE_BACKWARD:
return "EVALUATE BACKWARD ";
case SOLVE_FORWARD_SIMPLE:
return "SOLVE FORWARD SIMPLE ";
case SOLVE_BACKWARD_SIMPLE:
return "SOLVE BACKWARD SIMPLE ";
case SOLVE_TWO_BOUNDARIES_SIMPLE:
return "SOLVE TWO BOUNDARIES SIMPLE ";
case SOLVE_FORWARD_COMPLETE:
return "SOLVE FORWARD COMPLETE ";
case SOLVE_BACKWARD_COMPLETE:
return "SOLVE BACKWARD COMPLETE ";
case SOLVE_TWO_BOUNDARIES_COMPLETE:
return "SOLVE TWO BOUNDARIES COMPLETE";
default:
return "UNKNOWN ";
}
};
};
#endif