Select Git revision
NumericalInitialization.cc
Forked from
Dynare / dynare
Source project has a limited visibility.
-
sebastien authored
git-svn-id: https://www.dynare.org/svn/dynare/trunk@2753 ac1d8469-bf42-47a9-8791-bf33cf982152
sebastien authoredgit-svn-id: https://www.dynare.org/svn/dynare/trunk@2753 ac1d8469-bf42-47a9-8791-bf33cf982152
DynamicModel.cc 291.26 KiB
/*
* Copyright (C) 2003-2018 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/>.
*/
#include <iostream>
#include <cmath>
#include <cstdlib>
#include <cassert>
#include <cstdio>
#include <cerrno>
#include <algorithm>
#include <iterator>
#include <numeric>
#include "DynamicModel.hh"
// For mkdir() and chdir()
#ifdef _WIN32
# include <direct.h>
#else
# include <unistd.h>
# include <sys/stat.h>
# include <sys/types.h>
#endif
DynamicModel::DynamicModel(SymbolTable &symbol_table_arg,
NumericalConstants &num_constants_arg,
ExternalFunctionsTable &external_functions_table_arg) :
ModelTree(symbol_table_arg, num_constants_arg, external_functions_table_arg),
max_lag(0), max_lead(0),
max_endo_lag(0), max_endo_lead(0),
max_exo_lag(0), max_exo_lead(0),
max_exo_det_lag(0), max_exo_det_lead(0),
max_lag_orig(0), max_lead_orig(0),
max_endo_lag_orig(0), max_endo_lead_orig(0),
max_exo_lag_orig(0), max_exo_lead_orig(0),
max_exo_det_lag_orig(0), max_exo_det_lead_orig(0),
dynJacobianColsNbr(0),
global_temporary_terms(true)
{
}
VariableNode *
DynamicModel::AddVariable(int symb_id, int lag)
{
return AddVariableInternal(symb_id, lag);
}
void
DynamicModel::compileDerivative(ofstream &code_file, unsigned int &instruction_number, int eq, int symb_id, int lag, const map_idx_t &map_idx) const
{
auto it = first_derivatives.find({ eq, getDerivID(symbol_table.getID(eEndogenous, symb_id), lag) });
if (it != first_derivatives.end())
(it->second)->compile(code_file, instruction_number, false, temporary_terms, map_idx, true, false);
else
{ FLDZ_ fldz;
fldz.write(code_file, instruction_number);
}
}
void
DynamicModel::compileChainRuleDerivative(ofstream &code_file, unsigned int &instruction_number, int eqr, int varr, int lag, const map_idx_t &map_idx) const
{
auto it = first_chain_rule_derivatives.find({ eqr, { varr, lag } });
if (it != first_chain_rule_derivatives.end())
(it->second)->compile(code_file, instruction_number, false, temporary_terms, map_idx, true, false);
else
{
FLDZ_ fldz;
fldz.write(code_file, instruction_number);
}
}
void
DynamicModel::computeTemporaryTermsOrdered()
{
map<expr_t, pair<int, int>> first_occurence;
map<expr_t, int> reference_count;
BinaryOpNode *eq_node;
first_derivatives_t::const_iterator it;
first_chain_rule_derivatives_t::const_iterator it_chr;
ostringstream tmp_s;
v_temporary_terms.clear();
map_idx.clear();
unsigned int nb_blocks = getNbBlocks();
v_temporary_terms = vector<vector<temporary_terms_t>>(nb_blocks);
v_temporary_terms_inuse = vector<temporary_terms_inuse_t>(nb_blocks);
temporary_terms.clear();
if (!global_temporary_terms)
{
for (unsigned int block = 0; block < nb_blocks; block++)
{
reference_count.clear();
temporary_terms.clear();
unsigned int block_size = getBlockSize(block);
unsigned int block_nb_mfs = getBlockMfs(block);
unsigned int block_nb_recursives = block_size - block_nb_mfs;
v_temporary_terms[block] = vector<temporary_terms_t>(block_size);
for (unsigned int i = 0; i < block_size; i++)
{
if (i < block_nb_recursives && isBlockEquationRenormalized(block, i))
getBlockEquationRenormalizedExpr(block, i)->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, block, v_temporary_terms, i);
else
{
eq_node = (BinaryOpNode *) getBlockEquationExpr(block, i);
eq_node->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, block, v_temporary_terms, i);
}
}
for (block_derivatives_equation_variable_laglead_nodeid_t::const_iterator it = blocks_derivatives[block].begin(); it != (blocks_derivatives[block]).end(); it++)
{
expr_t id = it->second.second;
id->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, block, v_temporary_terms, block_size-1);
}
for (derivative_t::const_iterator it = derivative_endo[block].begin(); it != derivative_endo[block].end(); it++)
it->second->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, block, v_temporary_terms, block_size-1);
for (derivative_t::const_iterator it = derivative_other_endo[block].begin(); it != derivative_other_endo[block].end(); it++)
it->second->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, block, v_temporary_terms, block_size-1);
set<int> temporary_terms_in_use;
temporary_terms_in_use.clear();
v_temporary_terms_inuse[block] = temporary_terms_in_use;
}
}
else {
for (unsigned int block = 0; block < nb_blocks; block++)
{
// Compute the temporary terms reordered
unsigned int block_size = getBlockSize(block);
unsigned int block_nb_mfs = getBlockMfs(block);
unsigned int block_nb_recursives = block_size - block_nb_mfs;
v_temporary_terms[block] = vector<temporary_terms_t>(block_size);
for (unsigned int i = 0; i < block_size; i++)
{
if (i < block_nb_recursives && isBlockEquationRenormalized(block, i))
getBlockEquationRenormalizedExpr(block, i)->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, block, v_temporary_terms, i);
else
{
eq_node = (BinaryOpNode *) getBlockEquationExpr(block, i);
eq_node->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, block, v_temporary_terms, i);
}
}
for (block_derivatives_equation_variable_laglead_nodeid_t::const_iterator it = blocks_derivatives[block].begin(); it != (blocks_derivatives[block]).end(); it++)
{
expr_t id = it->second.second;
id->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, block, v_temporary_terms, block_size-1);
}
for (derivative_t::const_iterator it = derivative_endo[block].begin(); it != derivative_endo[block].end(); it++)
it->second->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, block, v_temporary_terms, block_size-1);
for (derivative_t::const_iterator it = derivative_other_endo[block].begin(); it != derivative_other_endo[block].end(); it++)
it->second->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, block, v_temporary_terms, block_size-1);
}
for (unsigned int block = 0; block < nb_blocks; block++)
{
// Collect the temporary terms reordered
unsigned int block_size = getBlockSize(block);
unsigned int block_nb_mfs = getBlockMfs(block);
unsigned int block_nb_recursives = block_size - block_nb_mfs;
set<int> temporary_terms_in_use;
for (unsigned int i = 0; i < block_size; i++)
{
if (i < block_nb_recursives && isBlockEquationRenormalized(block, i))
getBlockEquationRenormalizedExpr(block, i)->collectTemporary_terms(temporary_terms, temporary_terms_in_use, block);
else
{
eq_node = (BinaryOpNode *) getBlockEquationExpr(block, i);
eq_node->collectTemporary_terms(temporary_terms, temporary_terms_in_use, block);
}
}
for (block_derivatives_equation_variable_laglead_nodeid_t::const_iterator it = blocks_derivatives[block].begin(); it != (blocks_derivatives[block]).end(); it++)
{
expr_t id = it->second.second;
id->collectTemporary_terms(temporary_terms, temporary_terms_in_use, block);
}
for (derivative_t::const_iterator it = derivative_endo[block].begin(); it != derivative_endo[block].end(); it++)
it->second->collectTemporary_terms(temporary_terms, temporary_terms_in_use, block);
for (derivative_t::const_iterator it = derivative_other_endo[block].begin(); it != derivative_other_endo[block].end(); it++)
it->second->collectTemporary_terms(temporary_terms, temporary_terms_in_use, block);
for (derivative_t::const_iterator it = derivative_exo[block].begin(); it != derivative_exo[block].end(); it++)
it->second->collectTemporary_terms(temporary_terms, temporary_terms_in_use, block);
for (derivative_t::const_iterator it = derivative_exo_det[block].begin(); it != derivative_exo_det[block].end(); it++)
it->second->collectTemporary_terms(temporary_terms, temporary_terms_in_use, block);
v_temporary_terms_inuse[block] = temporary_terms_in_use;
}
computeTemporaryTermsMapping();
}
}
void
DynamicModel::computeTemporaryTermsMapping()
{
// Add a mapping form node ID to temporary terms order
int j = 0;
for (auto temporary_term : temporary_terms) map_idx[temporary_term->idx] = j++;
}
void
DynamicModel::writeModelEquationsOrdered_M(const string &dynamic_basename) const
{
string tmp_s, sps;
ostringstream tmp_output, tmp1_output, global_output;
expr_t lhs = nullptr, rhs = nullptr;
BinaryOpNode *eq_node;
ostringstream Ufoss;
vector<string> Uf(symbol_table.endo_nbr(), "");
map<expr_t, int> reference_count;
temporary_terms_t local_temporary_terms;
ofstream output;
int nze, nze_exo, nze_exo_det, nze_other_endo;
vector<int> feedback_variables;
ExprNodeOutputType local_output_type;
Ufoss.str("");
local_output_type = oMatlabDynamicModelSparse;
if (global_temporary_terms)
local_temporary_terms = temporary_terms;
//----------------------------------------------------------------------
//For each block
for (unsigned int block = 0; block < getNbBlocks(); block++)
{
//recursive_variables.clear();
feedback_variables.clear();
//For a block composed of a single equation determines wether we have to evaluate or to solve the equation
nze = derivative_endo[block].size();
nze_other_endo = derivative_other_endo[block].size();
nze_exo = derivative_exo[block].size();
nze_exo_det = derivative_exo_det[block].size();
BlockSimulationType simulation_type = getBlockSimulationType(block);
unsigned int block_size = getBlockSize(block);
unsigned int block_mfs = getBlockMfs(block);
unsigned int block_recursive = block_size - block_mfs;
deriv_node_temp_terms_t tef_terms;
local_output_type = oMatlabDynamicModelSparse;
if (global_temporary_terms)
local_temporary_terms = temporary_terms;
int prev_lag;
unsigned int prev_var, count_col, count_col_endo, count_col_exo, count_col_exo_det, count_col_other_endo;
map<pair<int, pair<int, int>>, expr_t> tmp_block_endo_derivative;
for (auto it = blocks_derivatives[block].begin(); it != (blocks_derivatives[block]).end(); it++)
tmp_block_endo_derivative[{ it->second.first, { it->first.second, it->first.first } }] = it->second.second;
prev_var = 999999999;
prev_lag = -9999999;
count_col_endo = 0;
for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_block_endo_derivative.begin(); it != tmp_block_endo_derivative.end(); it++)
{
int lag = it->first.first;
unsigned int var = it->first.second.first;
if (var != prev_var || lag != prev_lag)
{
prev_var = var;
prev_lag = lag;
count_col_endo++;
}
}
map<pair<int, pair<int, int>>, expr_t> tmp_block_exo_derivative;
for (auto it = derivative_exo[block].begin(); it != (derivative_exo[block]).end(); it++)
tmp_block_exo_derivative[{ it->first.first, { it->first.second.second, it->first.second.first } }] = it->second;
prev_var = 999999999;
prev_lag = -9999999;
count_col_exo = 0; for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_block_exo_derivative.begin(); it != tmp_block_exo_derivative.end(); it++)
{
int lag = it->first.first;
unsigned int var = it->first.second.first;
if (var != prev_var || lag != prev_lag)
{
prev_var = var;
prev_lag = lag;
count_col_exo++;
}
}
map<pair<int, pair<int, int>>, expr_t> tmp_block_exo_det_derivative;
for (auto it = derivative_exo_det[block].begin(); it != (derivative_exo_det[block]).end(); it++)
tmp_block_exo_det_derivative[{ it->first.first, { it->first.second.second, it->first.second.first } }] = it->second;
prev_var = 999999999;
prev_lag = -9999999;
count_col_exo_det = 0;
for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_block_exo_derivative.begin(); it != tmp_block_exo_derivative.end(); it++)
{
int lag = it->first.first;
unsigned int var = it->first.second.first;
if (var != prev_var || lag != prev_lag)
{
prev_var = var;
prev_lag = lag;
count_col_exo_det++;
}
}
map<pair<int, pair<int, int>>, expr_t> tmp_block_other_endo_derivative;
for (auto it = derivative_other_endo[block].begin(); it != (derivative_other_endo[block]).end(); it++)
tmp_block_other_endo_derivative[{ it->first.first, { it->first.second.second, it->first.second.first } }] = it->second;
prev_var = 999999999;
prev_lag = -9999999;
count_col_other_endo = 0;
for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_block_other_endo_derivative.begin(); it != tmp_block_other_endo_derivative.end(); it++)
{
int lag = it->first.first;
unsigned int var = it->first.second.first;
if (var != prev_var || lag != prev_lag)
{
prev_var = var;
prev_lag = lag;
count_col_other_endo++;
}
}
tmp1_output.str("");
tmp1_output << dynamic_basename << "_" << block+1 << ".m";
output.open(tmp1_output.str().c_str(), ios::out | ios::binary);
output << "%\n";
output << "% " << tmp1_output.str() << " : Computes dynamic model for Dynare\n";
output << "%\n";
output << "% Warning : this file is generated automatically by Dynare\n";
output << "% from model file (.mod)\n\n";
output << "%/\n";
if (simulation_type == EVALUATE_BACKWARD || simulation_type == EVALUATE_FORWARD)
{
output << "function [y, g1, g2, g3, varargout] = " << dynamic_basename << "_" << block+1 << "(y, x, params, steady_state, jacobian_eval, y_kmin, periods)\n";
}
else if (simulation_type == SOLVE_FORWARD_COMPLETE || simulation_type == SOLVE_BACKWARD_COMPLETE)
output << "function [residual, y, g1, g2, g3, varargout] = " << dynamic_basename << "_" << block+1 << "(y, x, params, steady_state, it_, jacobian_eval)\n";
else if (simulation_type == SOLVE_BACKWARD_SIMPLE || simulation_type == SOLVE_FORWARD_SIMPLE)
output << "function [residual, y, g1, g2, g3, varargout] = " << dynamic_basename << "_" << block+1 << "(y, x, params, steady_state, it_, jacobian_eval)\n";
else
output << "function [residual, y, g1, g2, g3, b, varargout] = " << dynamic_basename << "_" << block+1 << "(y, x, params, steady_state, periods, jacobian_eval, y_kmin, y_size, Periods)\n";
BlockType block_type;
if (simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE || simulation_type == SOLVE_TWO_BOUNDARIES_SIMPLE)
block_type = SIMULTAN;
else if (simulation_type == SOLVE_FORWARD_COMPLETE || simulation_type == SOLVE_BACKWARD_COMPLETE)
block_type = SIMULTANS; else if ((simulation_type == SOLVE_FORWARD_SIMPLE || simulation_type == SOLVE_BACKWARD_SIMPLE
|| simulation_type == EVALUATE_BACKWARD || simulation_type == EVALUATE_FORWARD)
&& getBlockFirstEquation(block) < prologue)
block_type = PROLOGUE;
else if ((simulation_type == SOLVE_FORWARD_SIMPLE || simulation_type == SOLVE_BACKWARD_SIMPLE
|| simulation_type == EVALUATE_BACKWARD || simulation_type == EVALUATE_FORWARD)
&& getBlockFirstEquation(block) >= equations.size() - epilogue)
block_type = EPILOGUE;
else
block_type = SIMULTANS;
output << " % ////////////////////////////////////////////////////////////////////////" << endl
<< " % //" << string(" Block ").substr(int (log10(block + 1))) << block + 1 << " " << BlockType0(block_type)
<< " //" << endl
<< " % // Simulation type "
<< BlockSim(simulation_type) << " //" << endl
<< " % ////////////////////////////////////////////////////////////////////////" << endl;
//The Temporary terms
if (simulation_type == EVALUATE_BACKWARD || simulation_type == EVALUATE_FORWARD)
{
output << " if(jacobian_eval)\n";
output << " g1 = spalloc(" << block_mfs << ", " << count_col_endo << ", " << nze << ");\n";
output << " g1_x=spalloc(" << block_size << ", " << count_col_exo << ", " << nze_exo << ");\n";
output << " g1_xd=spalloc(" << block_size << ", " << count_col_exo_det << ", " << nze_exo_det << ");\n";
output << " g1_o=spalloc(" << block_size << ", " << count_col_other_endo << ", " << nze_other_endo << ");\n";
output << " end;\n";
}
else
{
output << " if(jacobian_eval)\n";
output << " g1 = spalloc(" << block_size << ", " << count_col_endo << ", " << nze << ");\n";
output << " g1_x=spalloc(" << block_size << ", " << count_col_exo << ", " << nze_exo << ");\n";
output << " g1_xd=spalloc(" << block_size << ", " << count_col_exo_det << ", " << nze_exo_det << ");\n";
output << " g1_o=spalloc(" << block_size << ", " << count_col_other_endo << ", " << nze_other_endo << ");\n";
output << " else\n";
if (simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE || simulation_type == SOLVE_TWO_BOUNDARIES_SIMPLE)
{
output << " g1 = spalloc(" << block_mfs << "*Periods, "
<< block_mfs << "*(Periods+" << max_leadlag_block[block].first+max_leadlag_block[block].second+1 << ")"
<< ", " << nze << "*Periods);\n";
}
else
{
output << " g1 = spalloc(" << block_mfs
<< ", " << block_mfs << ", " << nze << ");\n";
}
output << " end;\n";
}
output << " g2=0;g3=0;\n";
if (v_temporary_terms_inuse[block].size())
{
tmp_output.str("");
for (int it : v_temporary_terms_inuse[block])
tmp_output << " T" << it;
output << " global" << tmp_output.str() << ";\n";
}
if (simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE || simulation_type == SOLVE_TWO_BOUNDARIES_SIMPLE)
{
temporary_terms_t tt2;
tt2.clear();
for (int i = 0; i < (int) block_size; i++)
{
if (v_temporary_terms[block][i].size() && global_temporary_terms)
{
output << " " << "% //Temporary variables initialization" << endl
<< " " << "T_zeros = zeros(y_kmin+periods, 1);" << endl;
for (auto it : v_temporary_terms[block][i])
{
output << " ";
// In the following, "Static" is used to avoid getting the "(it_)" subscripting it->writeOutput(output, oMatlabStaticModelSparse, local_temporary_terms, {});
output << " = T_zeros;" << endl;
}
}
}
}
if (simulation_type == SOLVE_BACKWARD_SIMPLE || simulation_type == SOLVE_FORWARD_SIMPLE || simulation_type == SOLVE_BACKWARD_COMPLETE || simulation_type == SOLVE_FORWARD_COMPLETE)
output << " residual=zeros(" << block_mfs << ",1);\n";
else if (simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE || simulation_type == SOLVE_TWO_BOUNDARIES_SIMPLE)
output << " residual=zeros(" << block_mfs << ",y_kmin+periods);\n";
if (simulation_type == EVALUATE_BACKWARD)
output << " for it_ = (y_kmin+periods):y_kmin+1\n";
if (simulation_type == EVALUATE_FORWARD)
output << " for it_ = y_kmin+1:(y_kmin+periods)\n";
if (simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE || simulation_type == SOLVE_TWO_BOUNDARIES_SIMPLE)
{
output << " b = zeros(periods*y_size,1);" << endl
<< " for it_ = y_kmin+1:(periods+y_kmin)" << endl
<< " Per_y_=it_*y_size;" << endl
<< " Per_J_=(it_-y_kmin-1)*y_size;" << endl
<< " Per_K_=(it_-1)*y_size;" << endl;
sps = " ";
}
else
if (simulation_type == EVALUATE_BACKWARD || simulation_type == EVALUATE_FORWARD)
sps = " ";
else
sps = "";
// The equations
temporary_terms_idxs_t temporary_terms_idxs;
for (unsigned int i = 0; i < block_size; i++)
{
temporary_terms_t tt2;
tt2.clear();
if (v_temporary_terms[block].size())
{
output << " " << "% //Temporary variables" << endl;
for (auto it : v_temporary_terms[block][i])
{
if (dynamic_cast<AbstractExternalFunctionNode *>(it) != nullptr)
it->writeExternalFunctionOutput(output, local_output_type, tt2, temporary_terms_idxs, tef_terms);
output << " " << sps;
it->writeOutput(output, local_output_type, local_temporary_terms, {}, tef_terms);
output << " = ";
it->writeOutput(output, local_output_type, tt2, {}, tef_terms);
// Insert current node into tt2
tt2.insert(it);
output << ";" << endl;
}
}
int variable_ID = getBlockVariableID(block, i);
int equation_ID = getBlockEquationID(block, i);
EquationType equ_type = getBlockEquationType(block, i);
string sModel = symbol_table.getName(symbol_table.getID(eEndogenous, variable_ID));
eq_node = (BinaryOpNode *) getBlockEquationExpr(block, i);
lhs = eq_node->get_arg1();
rhs = eq_node->get_arg2();
tmp_output.str("");
lhs->writeOutput(tmp_output, local_output_type, local_temporary_terms, {});
switch (simulation_type)
{
case EVALUATE_BACKWARD:
case EVALUATE_FORWARD:
evaluation: if (simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE || simulation_type == SOLVE_TWO_BOUNDARIES_SIMPLE)
output << " % equation " << getBlockEquationID(block, i)+1 << " variable : " << sModel
<< " (" << variable_ID+1 << ") " << c_Equation_Type(equ_type) << endl;
output << " "; if (equ_type == E_EVALUATE)
{
output << tmp_output.str();
output << " = ";
rhs->writeOutput(output, local_output_type, local_temporary_terms, {});
}
else if (equ_type == E_EVALUATE_S)
{
output << "%" << tmp_output.str();
output << " = ";
if (isBlockEquationRenormalized(block, i))
{
rhs->writeOutput(output, local_output_type, local_temporary_terms, {});
output << "\n ";
tmp_output.str("");
eq_node = (BinaryOpNode *) getBlockEquationRenormalizedExpr(block, i);
lhs = eq_node->get_arg1();
rhs = eq_node->get_arg2();
lhs->writeOutput(output, local_output_type, local_temporary_terms, {});
output << " = ";
rhs->writeOutput(output, local_output_type, local_temporary_terms, {});
}
}
else
{
cerr << "Type mismatch for equation " << equation_ID+1 << "\n";
exit(EXIT_FAILURE);
}
output << ";\n";
break;
case SOLVE_BACKWARD_SIMPLE:
case SOLVE_FORWARD_SIMPLE:
case SOLVE_BACKWARD_COMPLETE:
case SOLVE_FORWARD_COMPLETE:
if (i < block_recursive)
goto evaluation;
feedback_variables.push_back(variable_ID);
output << " % equation " << equation_ID+1 << " variable : " << sModel
<< " (" << variable_ID+1 << ") " << c_Equation_Type(equ_type) << " symb_id=" << symbol_table.getID(eEndogenous, variable_ID) << endl;
output << " " << "residual(" << i+1-block_recursive << ") = (";
goto end;
case SOLVE_TWO_BOUNDARIES_COMPLETE:
case SOLVE_TWO_BOUNDARIES_SIMPLE:
if (i < block_recursive)
goto evaluation;
feedback_variables.push_back(variable_ID);
output << " % equation " << equation_ID+1 << " variable : " << sModel
<< " (" << variable_ID+1 << ") " << c_Equation_Type(equ_type) << " symb_id=" << symbol_table.getID(eEndogenous, variable_ID) << endl;
Ufoss << " b(" << i+1-block_recursive << "+Per_J_) = -residual(" << i+1-block_recursive << ", it_)";
Uf[equation_ID] += Ufoss.str();
Ufoss.str("");
output << " residual(" << i+1-block_recursive << ", it_) = (";
goto end;
default:
end:
output << tmp_output.str();
output << ") - (";
rhs->writeOutput(output, local_output_type, local_temporary_terms, {});
output << ");\n";
#ifdef CONDITION
if (simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE || simulation_type == SOLVE_TWO_BOUNDARIES_SIMPLE)
output << " condition(" << i+1 << ")=0;\n";
#endif
}
}
// The Jacobian if we have to solve the block
if (simulation_type == SOLVE_TWO_BOUNDARIES_SIMPLE || simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE)
output << " " << sps << "% Jacobian " << endl << " if jacobian_eval" << endl;
else
if (simulation_type == SOLVE_BACKWARD_SIMPLE || simulation_type == SOLVE_FORWARD_SIMPLE || simulation_type == SOLVE_BACKWARD_COMPLETE || simulation_type == SOLVE_FORWARD_COMPLETE)
output << " % Jacobian " << endl << " if jacobian_eval" << endl;
else
output << " % Jacobian " << endl << " if jacobian_eval" << endl;
prev_var = 999999999;
prev_lag = -9999999;
count_col = 0;
for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_block_endo_derivative.begin(); it != tmp_block_endo_derivative.end(); it++)
{
int lag = it->first.first;
unsigned int var = it->first.second.first;
unsigned int eq = it->first.second.second;
int eqr = getBlockEquationID(block, eq);
int varr = getBlockVariableID(block, var);
if (var != prev_var || lag != prev_lag)
{
prev_var = var;
prev_lag = lag;
count_col++;
}
expr_t id = it->second;
output << " g1(" << eq+1 << ", " << count_col << ") = ";
id->writeOutput(output, local_output_type, local_temporary_terms, {});
output << "; % variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, varr))
<< "(" << lag
<< ") " << varr+1 << ", " << var+1
<< ", equation=" << eqr+1 << ", " << eq+1 << endl;
}
prev_var = 999999999;
prev_lag = -9999999;
count_col = 0;
for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_block_exo_derivative.begin(); it != tmp_block_exo_derivative.end(); it++)
{
int lag = it->first.first;
unsigned int var = it->first.second.first;
unsigned int eq = it->first.second.second;
int eqr = getBlockInitialEquationID(block, eq);
if (var != prev_var || lag != prev_lag)
{
prev_var = var;
prev_lag = lag;
count_col++;
}
expr_t id = it->second;
output << " g1_x(" << eqr+1 << ", " << count_col << ") = ";
id->writeOutput(output, local_output_type, local_temporary_terms, {});
output << "; % variable=" << symbol_table.getName(symbol_table.getID(eExogenous, var))
<< "(" << lag
<< ") " << var+1
<< ", equation=" << eq+1 << endl;
}
prev_var = 999999999;
prev_lag = -9999999;
count_col = 0;
for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_block_exo_det_derivative.begin(); it != tmp_block_exo_det_derivative.end(); it++)
{
int lag = it->first.first;
unsigned int var = it->first.second.first;
unsigned int eq = it->first.second.second;
int eqr = getBlockInitialEquationID(block, eq);
if (var != prev_var || lag != prev_lag)
{
prev_var = var;
prev_lag = lag;
count_col++;
}
expr_t id = it->second;
output << " g1_xd(" << eqr+1 << ", " << count_col << ") = "; id->writeOutput(output, local_output_type, local_temporary_terms, {});
output << "; % variable=" << symbol_table.getName(symbol_table.getID(eExogenous, var))
<< "(" << lag
<< ") " << var+1
<< ", equation=" << eq+1 << endl;
}
prev_var = 999999999;
prev_lag = -9999999;
count_col = 0;
for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_block_other_endo_derivative.begin(); it != tmp_block_other_endo_derivative.end(); it++)
{
int lag = it->first.first;
unsigned int var = it->first.second.first;
unsigned int eq = it->first.second.second;
int eqr = getBlockInitialEquationID(block, eq);
if (var != prev_var || lag != prev_lag)
{
prev_var = var;
prev_lag = lag;
count_col++;
}
expr_t id = it->second;
output << " g1_o(" << eqr+1 << ", " << /*var+1+(lag+block_max_lag)*block_size*/ count_col << ") = ";
id->writeOutput(output, local_output_type, local_temporary_terms, {});
output << "; % variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, var))
<< "(" << lag
<< ") " << var+1
<< ", equation=" << eq+1 << endl;
}
output << " varargout{1}=g1_x;\n";
output << " varargout{2}=g1_xd;\n";
output << " varargout{3}=g1_o;\n";
switch (simulation_type)
{
case EVALUATE_FORWARD:
case EVALUATE_BACKWARD:
output << " end;" << endl;
output << " end;" << endl;
break;
case SOLVE_BACKWARD_SIMPLE:
case SOLVE_FORWARD_SIMPLE:
case SOLVE_BACKWARD_COMPLETE:
case SOLVE_FORWARD_COMPLETE:
output << " else" << endl;
for (auto it = blocks_derivatives[block].begin(); it != (blocks_derivatives[block]).end(); it++)
{
unsigned int eq = it->first.first;
unsigned int var = it->first.second;
unsigned int eqr = getBlockEquationID(block, eq);
unsigned int varr = getBlockVariableID(block, var);
expr_t id = it->second.second;
int lag = it->second.first;
if (lag == 0)
{
output << " g1(" << eq+1 << ", " << var+1-block_recursive << ") = ";
id->writeOutput(output, local_output_type, local_temporary_terms, {});
output << "; % variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, varr))
<< "(" << lag
<< ") " << varr+1
<< ", equation=" << eqr+1 << endl;
}
}
output << " end;\n";
break;
case SOLVE_TWO_BOUNDARIES_SIMPLE:
case SOLVE_TWO_BOUNDARIES_COMPLETE:
output << " else" << endl; for (auto it = blocks_derivatives[block].begin(); it != (blocks_derivatives[block]).end(); it++)
{
unsigned int eq = it->first.first;
unsigned int var = it->first.second;
unsigned int eqr = getBlockEquationID(block, eq);
unsigned int varr = getBlockVariableID(block, var);
ostringstream tmp_output;
expr_t id = it->second.second;
int lag = it->second.first;
if (eq >= block_recursive && var >= block_recursive)
{
if (lag == 0)
Ufoss << "+g1(" << eq+1-block_recursive
<< "+Per_J_, " << var+1-block_recursive
<< "+Per_K_)*y(it_, " << varr+1 << ")";
else if (lag == 1)
Ufoss << "+g1(" << eq+1-block_recursive
<< "+Per_J_, " << var+1-block_recursive
<< "+Per_y_)*y(it_+1, " << varr+1 << ")";
else if (lag > 0)
Ufoss << "+g1(" << eq+1-block_recursive
<< "+Per_J_, " << var+1-block_recursive
<< "+y_size*(it_+" << lag-1 << "))*y(it_+" << lag << ", " << varr+1 << ")";
else
Ufoss << "+g1(" << eq+1-block_recursive
<< "+Per_J_, " << var+1-block_recursive
<< "+y_size*(it_" << lag-1 << "))*y(it_" << lag << ", " << varr+1 << ")";
Uf[eqr] += Ufoss.str();
Ufoss.str("");
if (lag == 0)
tmp_output << " g1(" << eq+1-block_recursive << "+Per_J_, "
<< var+1-block_recursive << "+Per_K_) = ";
else if (lag == 1)
tmp_output << " g1(" << eq+1-block_recursive << "+Per_J_, "
<< var+1-block_recursive << "+Per_y_) = ";
else if (lag > 0)
tmp_output << " g1(" << eq+1-block_recursive << "+Per_J_, "
<< var+1-block_recursive << "+y_size*(it_+" << lag-1 << ")) = ";
else if (lag < 0)
tmp_output << " g1(" << eq+1-block_recursive << "+Per_J_, "
<< var+1-block_recursive << "+y_size*(it_" << lag-1 << ")) = ";
output << " " << tmp_output.str();
id->writeOutput(output, local_output_type, local_temporary_terms, {});
output << ";";
output << " %2 variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, varr))
<< "(" << lag << ") " << varr+1
<< ", equation=" << eqr+1 << " (" << eq+1 << ")" << endl;
}
#ifdef CONDITION
output << " if (fabs(condition[" << eqr << "])<fabs(u[" << u << "+Per_u_]))\n";
output << " condition(" << eqr << ")=u(" << u << "+Per_u_);\n";
#endif
}
for (unsigned int i = 0; i < block_size; i++)
{
if (i >= block_recursive)
output << " " << Uf[getBlockEquationID(block, i)] << ";\n";
#ifdef CONDITION
output << " if (fabs(condition(" << i+1 << "))<fabs(u(" << i << "+Per_u_)))\n";
output << " condition(" << i+1 << ")=u(" << i+1 << "+Per_u_);\n";
#endif
}
#ifdef CONDITION
for (m = 0; m <= ModelBlock->Block_List[block].Max_Lead+ModelBlock->Block_List[block].Max_Lag; m++)
{
k = m-ModelBlock->Block_List[block].Max_Lag;
for (i = 0; i < ModelBlock->Block_List[block].IM_lead_lag[m].size; i++)
{ unsigned int eq = ModelBlock->Block_List[block].IM_lead_lag[m].Equ_Index[i];
unsigned int var = ModelBlock->Block_List[block].IM_lead_lag[m].Var_Index[i];
unsigned int u = ModelBlock->Block_List[block].IM_lead_lag[m].u[i];
unsigned int eqr = ModelBlock->Block_List[block].IM_lead_lag[m].Equ[i];
output << " u(" << u+1 << "+Per_u_) = u(" << u+1 << "+Per_u_) / condition(" << eqr+1 << ");\n";
}
}
for (i = 0; i < ModelBlock->Block_List[block].Size; i++)
output << " u(" << i+1 << "+Per_u_) = u(" << i+1 << "+Per_u_) / condition(" << i+1 << ");\n";
#endif
output << " end;" << endl;
output << " end;" << endl;
break;
default:
break;
}
output << "end" << endl;
output.close();
}
}
void
DynamicModel::writeModelEquationsCode(string &file_name, const string &bin_basename, const map_idx_t &map_idx) const
{
ostringstream tmp_output;
ofstream code_file;
unsigned int instruction_number = 0;
bool file_open = false;
string main_name = file_name;
main_name += ".cod";
code_file.open(main_name.c_str(), ios::out | ios::binary | ios::ate);
if (!code_file.is_open())
{
cerr << "Error : Can't open file \"" << main_name << "\" for writing" << endl;
exit(EXIT_FAILURE);
}
int count_u;
int u_count_int = 0;
BlockSimulationType simulation_type;
if ((max_endo_lag > 0) && (max_endo_lead > 0))
simulation_type = SOLVE_TWO_BOUNDARIES_COMPLETE;
else if ((max_endo_lag >= 0) && (max_endo_lead == 0))
simulation_type = SOLVE_FORWARD_COMPLETE;
else
simulation_type = SOLVE_BACKWARD_COMPLETE;
Write_Inf_To_Bin_File(file_name, u_count_int, file_open, simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE, symbol_table.endo_nbr());
file_open = true;
//Temporary variables declaration
FDIMT_ fdimt(temporary_terms.size());
fdimt.write(code_file, instruction_number);
vector<unsigned int> exo, exo_det, other_endo;
for (int i = 0; i < symbol_table.exo_det_nbr(); i++)
exo_det.push_back(i);
for (int i = 0; i < symbol_table.exo_nbr(); i++)
exo.push_back(i);
map<pair< int, pair<int, int>>, expr_t> first_derivatives_reordered_endo;
map<pair< pair<int, int>, pair<int, int>>, expr_t> first_derivatives_reordered_exo;
for (const auto & first_derivative : first_derivatives)
{
int deriv_id = first_derivative.first.second;
unsigned int eq = first_derivative.first.first;
int symb = getSymbIDByDerivID(deriv_id); unsigned int var = symbol_table.getTypeSpecificID(symb);
int lag = getLagByDerivID(deriv_id);
if (getTypeByDerivID(deriv_id) == eEndogenous)
first_derivatives_reordered_endo[{ lag, make_pair(var, eq) }] = first_derivative.second;
else if (getTypeByDerivID(deriv_id) == eExogenous || getTypeByDerivID(deriv_id) == eExogenousDet)
first_derivatives_reordered_exo[{ { lag, getTypeByDerivID(deriv_id) }, { var, eq } }] = first_derivative.second;
}
int prev_var = -1;
int prev_lag = -999999999;
int count_col_endo = 0;
for (map<pair< int, pair<int, int>>, expr_t>::const_iterator it = first_derivatives_reordered_endo.begin();
it != first_derivatives_reordered_endo.end(); it++)
{
int var = it->first.second.first;
int lag = it->first.first;
if (prev_var != var || prev_lag != lag)
{
prev_var = var;
prev_lag = lag;
count_col_endo++;
}
}
prev_var = -1;
prev_lag = -999999999;
int prev_type = -1;
int count_col_exo = 0;
int count_col_det_exo = 0;
for (map<pair< pair<int, int>, pair<int, int>>, expr_t>::const_iterator it = first_derivatives_reordered_exo.begin();
it != first_derivatives_reordered_exo.end(); it++)
{
int var = it->first.second.first;
int lag = it->first.first.first;
int type = it->first.first.second;
if (prev_var != var || prev_lag != lag || prev_type != type)
{
prev_var = var;
prev_lag = lag;
prev_type = type;
if (type == eExogenous)
count_col_exo++;
else if (type == eExogenousDet)
count_col_det_exo++;
}
}
FBEGINBLOCK_ fbeginblock(symbol_table.endo_nbr(),
simulation_type,
0,
symbol_table.endo_nbr(),
variable_reordered,
equation_reordered,
false,
symbol_table.endo_nbr(),
max_endo_lag,
max_endo_lead,
u_count_int,
count_col_endo,
symbol_table.exo_det_nbr(),
count_col_det_exo,
symbol_table.exo_nbr(),
count_col_exo,
0,
0,
exo_det,
exo,
other_endo
);
fbeginblock.write(code_file, instruction_number);
compileTemporaryTerms(code_file, instruction_number, temporary_terms, map_idx, true, false);
compileModelEquations(code_file, instruction_number, temporary_terms, map_idx, true, false);
FENDEQU_ fendequ;
fendequ.write(code_file, instruction_number);
// Get the current code_file position and jump if eval = true
streampos pos1 = code_file.tellp();
FJMPIFEVAL_ fjmp_if_eval(0);
fjmp_if_eval.write(code_file, instruction_number);
int prev_instruction_number = instruction_number;
vector<vector<pair<pair<int, int>, int >>> derivatives;
derivatives.resize(symbol_table.endo_nbr());
count_u = symbol_table.endo_nbr();
for (const auto & first_derivative : first_derivatives)
{
int deriv_id = first_derivative.first.second;
if (getTypeByDerivID(deriv_id) == eEndogenous)
{
expr_t d1 = first_derivative.second;
unsigned int eq = first_derivative.first.first;
int symb = getSymbIDByDerivID(deriv_id);
unsigned int var = symbol_table.getTypeSpecificID(symb);
int lag = getLagByDerivID(deriv_id);
FNUMEXPR_ fnumexpr(FirstEndoDerivative, eq, var, lag);
fnumexpr.write(code_file, instruction_number);
if (!derivatives[eq].size())
derivatives[eq].clear();
derivatives[eq].emplace_back(make_pair(var, lag), count_u);
d1->compile(code_file, instruction_number, false, temporary_terms, map_idx, true, false);
FSTPU_ fstpu(count_u);
fstpu.write(code_file, instruction_number);
count_u++;
}
}
for (int i = 0; i < symbol_table.endo_nbr(); i++)
{
FLDR_ fldr(i);
fldr.write(code_file, instruction_number);
if (derivatives[i].size())
{
for (vector<pair<pair<int, int>, int>>::const_iterator it = derivatives[i].begin();
it != derivatives[i].end(); it++)
{
FLDU_ fldu(it->second);
fldu.write(code_file, instruction_number);
FLDV_ fldv(eEndogenous, it->first.first, it->first.second);
fldv.write(code_file, instruction_number);
FBINARY_ fbinary(oTimes);
fbinary.write(code_file, instruction_number);
if (it != derivatives[i].begin())
{
FBINARY_ fbinary(oPlus);
fbinary.write(code_file, instruction_number);
}
}
FBINARY_ fbinary(oMinus);
fbinary.write(code_file, instruction_number);
}
FSTPU_ fstpu(i);
fstpu.write(code_file, instruction_number);
}
// Get the current code_file position and jump = true
streampos pos2 = code_file.tellp();
FJMP_ fjmp(0);
fjmp.write(code_file, instruction_number); // Set code_file position to previous JMPIFEVAL_ and set the number of instructions to jump
streampos pos3 = code_file.tellp();
code_file.seekp(pos1);
FJMPIFEVAL_ fjmp_if_eval1(instruction_number - prev_instruction_number);
fjmp_if_eval1.write(code_file, instruction_number);
code_file.seekp(pos3);
prev_instruction_number = instruction_number;
// The Jacobian
prev_var = -1;
prev_lag = -999999999;
count_col_endo = 0;
for (map<pair< int, pair<int, int>>, expr_t>::const_iterator it = first_derivatives_reordered_endo.begin();
it != first_derivatives_reordered_endo.end(); it++)
{
unsigned int eq = it->first.second.second;
int var = it->first.second.first;
int lag = it->first.first;
expr_t d1 = it->second;
FNUMEXPR_ fnumexpr(FirstEndoDerivative, eq, var, lag);
fnumexpr.write(code_file, instruction_number);
if (prev_var != var || prev_lag != lag)
{
prev_var = var;
prev_lag = lag;
count_col_endo++;
}
d1->compile(code_file, instruction_number, false, temporary_terms, map_idx, true, false);
FSTPG3_ fstpg3(eq, var, lag, count_col_endo-1);
fstpg3.write(code_file, instruction_number);
}
prev_var = -1;
prev_lag = -999999999;
count_col_exo = 0;
for (map<pair< pair<int, int>, pair<int, int>>, expr_t>::const_iterator it = first_derivatives_reordered_exo.begin();
it != first_derivatives_reordered_exo.end(); it++)
{
unsigned int eq = it->first.second.second;
int var = it->first.second.first;
int lag = it->first.first.first;
expr_t d1 = it->second;
FNUMEXPR_ fnumexpr(FirstExoDerivative, eq, var, lag);
fnumexpr.write(code_file, instruction_number);
if (prev_var != var || prev_lag != lag)
{
prev_var = var;
prev_lag = lag;
count_col_exo++;
}
d1->compile(code_file, instruction_number, false, temporary_terms, map_idx, true, false);
FSTPG3_ fstpg3(eq, var, lag, count_col_exo-1);
fstpg3.write(code_file, instruction_number);
}
// Set codefile position to previous JMP_ and set the number of instructions to jump
pos1 = code_file.tellp();
code_file.seekp(pos2);
FJMP_ fjmp1(instruction_number - prev_instruction_number);
fjmp1.write(code_file, instruction_number);
code_file.seekp(pos1);
FENDBLOCK_ fendblock;
fendblock.write(code_file, instruction_number);
FEND_ fend;
fend.write(code_file, instruction_number);
code_file.close();
}
void
DynamicModel::writeModelEquationsCode_Block(string &file_name, const string &bin_basename, const map_idx_t &map_idx) const
{ struct Uff_l
{
int u, var, lag;
Uff_l *pNext;
};
struct Uff
{
Uff_l *Ufl, *Ufl_First;
};
int i, v;
string tmp_s;
ostringstream tmp_output;
ofstream code_file;
unsigned int instruction_number = 0;
expr_t lhs = nullptr, rhs = nullptr;
BinaryOpNode *eq_node;
Uff Uf[symbol_table.endo_nbr()];
map<expr_t, int> reference_count;
deriv_node_temp_terms_t tef_terms;
vector<int> feedback_variables;
bool file_open = false;
string main_name = file_name;
main_name += ".cod";
code_file.open(main_name.c_str(), ios::out | ios::binary | ios::ate);
if (!code_file.is_open())
{
cerr << "Error : Can't open file \"" << main_name << "\" for writing" << endl;
exit(EXIT_FAILURE);
}
//Temporary variables declaration
FDIMT_ fdimt(temporary_terms.size());
fdimt.write(code_file, instruction_number);
for (unsigned int block = 0; block < getNbBlocks(); block++)
{
feedback_variables.clear();
if (block > 0)
{
FENDBLOCK_ fendblock;
fendblock.write(code_file, instruction_number);
}
int count_u;
int u_count_int = 0;
BlockSimulationType simulation_type = getBlockSimulationType(block);
unsigned int block_size = getBlockSize(block);
unsigned int block_mfs = getBlockMfs(block);
unsigned int block_recursive = block_size - block_mfs;
int block_max_lag = max_leadlag_block[block].first;
int block_max_lead = max_leadlag_block[block].second;
if (simulation_type == SOLVE_TWO_BOUNDARIES_SIMPLE || simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE
|| simulation_type == SOLVE_BACKWARD_COMPLETE || simulation_type == SOLVE_FORWARD_COMPLETE)
{
Write_Inf_To_Bin_File_Block(file_name, bin_basename, block, u_count_int, file_open,
simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE || simulation_type == SOLVE_TWO_BOUNDARIES_SIMPLE);
file_open = true;
}
map<pair<int, pair<int, int>>, expr_t> tmp_block_endo_derivative;
for (auto it = blocks_derivatives[block].begin(); it != (blocks_derivatives[block]).end(); it++)
tmp_block_endo_derivative[{ it->second.first, { it->first.second, it->first.first } }] = it->second.second;
map<pair<int, pair<int, int>>, expr_t> tmp_exo_derivative;
for (auto it = derivative_exo[block].begin(); it != (derivative_exo[block]).end(); it++)
tmp_exo_derivative[{ it->first.first, { it->first.second.second, it->first.second.first } }] = it->second;
map<pair<int, pair<int, int>>, expr_t> tmp_exo_det_derivative;
for (auto it = derivative_exo_det[block].begin(); it != (derivative_exo_det[block]).end(); it++)
tmp_exo_det_derivative[{ it->first.first, { it->first.second.second, it->first.second.first } }] = it->second; map<pair<int, pair<int, int>>, expr_t> tmp_other_endo_derivative;
for (auto it = derivative_other_endo[block].begin(); it != (derivative_other_endo[block]).end(); it++)
tmp_other_endo_derivative[{ it->first.first, { it->first.second.second, it->first.second.first } }] = it->second;
int prev_var = -1;
int prev_lag = -999999999;
int count_col_endo = 0;
for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_block_endo_derivative.begin(); it != tmp_block_endo_derivative.end(); it++)
{
int lag = it->first.first;
int var = it->first.second.first;
if (prev_var != var || prev_lag != lag)
{
prev_var = var;
prev_lag = lag;
count_col_endo++;
}
}
unsigned int count_col_det_exo = 0;
vector<unsigned int> exo_det;
for (const auto & it : exo_det_block[block])
for (auto it1 = it.second.begin(); it1 != it.second.end(); it1++)
{
count_col_det_exo++;
if (find(exo_det.begin(), exo_det.end(), *it1) == exo_det.end())
exo_det.push_back(*it1);
}
unsigned int count_col_exo = 0;
vector<unsigned int> exo;
for (const auto & it : exo_block[block])
for (auto it1 = it.second.begin(); it1 != it.second.end(); it1++)
{
count_col_exo++;
if (find(exo.begin(), exo.end(), *it1) == exo.end())
exo.push_back(*it1);
}
vector<unsigned int> other_endo;
unsigned int count_col_other_endo = 0;
for (const auto & it : other_endo_block[block])
for (auto it1 = it.second.begin(); it1 != it.second.end(); it1++)
{
count_col_other_endo++;
if (find(other_endo.begin(), other_endo.end(), *it1) == other_endo.end())
other_endo.push_back(*it1);
}
FBEGINBLOCK_ fbeginblock(block_mfs,
simulation_type,
getBlockFirstEquation(block),
block_size,
variable_reordered,
equation_reordered,
blocks_linear[block],
symbol_table.endo_nbr(),
block_max_lag,
block_max_lead,
u_count_int,
count_col_endo,
exo_det.size(),
count_col_det_exo,
exo.size(),
getBlockExoColSize(block),
other_endo.size(),
count_col_other_endo,
exo_det,
exo,
other_endo
);
fbeginblock.write(code_file, instruction_number);
// The equations
for (i = 0; i < (int) block_size; i++)
{
//The Temporary terms
temporary_terms_t tt2;
tt2.clear();
if (v_temporary_terms[block][i].size())
{
for (auto it : v_temporary_terms[block][i])
{
if (dynamic_cast<AbstractExternalFunctionNode *>(it) != nullptr)
it->compileExternalFunctionOutput(code_file, instruction_number, false, tt2, map_idx, true, false, tef_terms);
FNUMEXPR_ fnumexpr(TemporaryTerm, (int)(map_idx.find(it->idx)->second));
fnumexpr.write(code_file, instruction_number);
it->compile(code_file, instruction_number, false, tt2, map_idx, true, false, tef_terms);
FSTPT_ fstpt((int)(map_idx.find(it->idx)->second));
fstpt.write(code_file, instruction_number);
// Insert current node into tt2
tt2.insert(it);
#ifdef DEBUGC
cout << "FSTPT " << v << "\n";
instruction_number++;
code_file.write(&FOK, sizeof(FOK));
code_file.write(reinterpret_cast<char *>(&k), sizeof(k));
ki++;
#endif
}
}
#ifdef DEBUGC
for (temporary_terms_t::const_iterator it = v_temporary_terms[block][i].begin();
it != v_temporary_terms[block][i].end(); it++)
{
map_idx_t::const_iterator ii = map_idx.find((*it)->idx);
cout << "map_idx[" << (*it)->idx <<"]=" << ii->second << "\n";
}
#endif
int variable_ID, equation_ID;
EquationType equ_type;
switch (simulation_type)
{
evaluation:
case EVALUATE_BACKWARD:
case EVALUATE_FORWARD:
equ_type = getBlockEquationType(block, i);
{
FNUMEXPR_ fnumexpr(ModelEquation, getBlockEquationID(block, i));
fnumexpr.write(code_file, instruction_number);
}
if (equ_type == E_EVALUATE)
{
eq_node = (BinaryOpNode *) getBlockEquationExpr(block, i);
lhs = eq_node->get_arg1();
rhs = eq_node->get_arg2();
rhs->compile(code_file, instruction_number, false, temporary_terms, map_idx, true, false);
lhs->compile(code_file, instruction_number, true, temporary_terms, map_idx, true, false);
}
else if (equ_type == E_EVALUATE_S)
{
eq_node = (BinaryOpNode *) getBlockEquationRenormalizedExpr(block, i);
lhs = eq_node->get_arg1();
rhs = eq_node->get_arg2();
rhs->compile(code_file, instruction_number, false, temporary_terms, map_idx, true, false);
lhs->compile(code_file, instruction_number, true, temporary_terms, map_idx, true, false);
}
break; case SOLVE_BACKWARD_COMPLETE:
case SOLVE_FORWARD_COMPLETE:
case SOLVE_TWO_BOUNDARIES_COMPLETE:
case SOLVE_TWO_BOUNDARIES_SIMPLE:
if (i < (int) block_recursive)
goto evaluation;
variable_ID = getBlockVariableID(block, i);
equation_ID = getBlockEquationID(block, i);
feedback_variables.push_back(variable_ID);
Uf[equation_ID].Ufl = nullptr;
goto end;
default:
end:
FNUMEXPR_ fnumexpr(ModelEquation, getBlockEquationID(block, i));
fnumexpr.write(code_file, instruction_number);
eq_node = (BinaryOpNode *) getBlockEquationExpr(block, i);
lhs = eq_node->get_arg1();
rhs = eq_node->get_arg2();
lhs->compile(code_file, instruction_number, false, temporary_terms, map_idx, true, false);
rhs->compile(code_file, instruction_number, false, temporary_terms, map_idx, true, false);
FBINARY_ fbinary(oMinus);
fbinary.write(code_file, instruction_number);
FSTPR_ fstpr(i - block_recursive);
fstpr.write(code_file, instruction_number);
}
}
FENDEQU_ fendequ;
fendequ.write(code_file, instruction_number);
// Get the current code_file position and jump if eval = true
streampos pos1 = code_file.tellp();
FJMPIFEVAL_ fjmp_if_eval(0);
fjmp_if_eval.write(code_file, instruction_number);
int prev_instruction_number = instruction_number;
// The Jacobian if we have to solve the block determinsitic block
if (simulation_type != EVALUATE_BACKWARD
&& simulation_type != EVALUATE_FORWARD)
{
switch (simulation_type)
{
case SOLVE_BACKWARD_SIMPLE:
case SOLVE_FORWARD_SIMPLE:
{
FNUMEXPR_ fnumexpr(FirstEndoDerivative, getBlockEquationID(block, 0), getBlockVariableID(block, 0), 0);
fnumexpr.write(code_file, instruction_number);
}
compileDerivative(code_file, instruction_number, getBlockEquationID(block, 0), getBlockVariableID(block, 0), 0, map_idx);
{
FSTPG_ fstpg(0);
fstpg.write(code_file, instruction_number);
}
break;
case SOLVE_BACKWARD_COMPLETE:
case SOLVE_FORWARD_COMPLETE:
case SOLVE_TWO_BOUNDARIES_COMPLETE:
case SOLVE_TWO_BOUNDARIES_SIMPLE:
count_u = feedback_variables.size();
for (auto it = blocks_derivatives[block].begin(); it != (blocks_derivatives[block]).end(); it++)
{
int lag = it->second.first;
unsigned int eq = it->first.first;
unsigned int var = it->first.second;
unsigned int eqr = getBlockEquationID(block, eq);
unsigned int varr = getBlockVariableID(block, var);
if (eq >= block_recursive and var >= block_recursive)
{
if (lag != 0 && (simulation_type == SOLVE_FORWARD_COMPLETE || simulation_type == SOLVE_BACKWARD_COMPLETE))
continue; if (!Uf[eqr].Ufl)
{
Uf[eqr].Ufl = (Uff_l *) malloc(sizeof(Uff_l));
Uf[eqr].Ufl_First = Uf[eqr].Ufl;
}
else
{
Uf[eqr].Ufl->pNext = (Uff_l *) malloc(sizeof(Uff_l));
Uf[eqr].Ufl = Uf[eqr].Ufl->pNext;
}
Uf[eqr].Ufl->pNext = nullptr;
Uf[eqr].Ufl->u = count_u;
Uf[eqr].Ufl->var = varr;
Uf[eqr].Ufl->lag = lag;
FNUMEXPR_ fnumexpr(FirstEndoDerivative, eqr, varr, lag);
fnumexpr.write(code_file, instruction_number);
compileChainRuleDerivative(code_file, instruction_number, eqr, varr, lag, map_idx);
FSTPU_ fstpu(count_u);
fstpu.write(code_file, instruction_number);
count_u++;
}
}
for (i = 0; i < (int) block_size; i++)
{
if (i >= (int) block_recursive)
{
FLDR_ fldr(i-block_recursive);
fldr.write(code_file, instruction_number);
FLDZ_ fldz;
fldz.write(code_file, instruction_number);
v = getBlockEquationID(block, i);
for (Uf[v].Ufl = Uf[v].Ufl_First; Uf[v].Ufl; Uf[v].Ufl = Uf[v].Ufl->pNext)
{
FLDU_ fldu(Uf[v].Ufl->u);
fldu.write(code_file, instruction_number);
FLDV_ fldv(eEndogenous, Uf[v].Ufl->var, Uf[v].Ufl->lag);
fldv.write(code_file, instruction_number);
FBINARY_ fbinary(oTimes);
fbinary.write(code_file, instruction_number);
FCUML_ fcuml;
fcuml.write(code_file, instruction_number);
}
Uf[v].Ufl = Uf[v].Ufl_First;
while (Uf[v].Ufl)
{
Uf[v].Ufl_First = Uf[v].Ufl->pNext;
free(Uf[v].Ufl);
Uf[v].Ufl = Uf[v].Ufl_First;
}
FBINARY_ fbinary(oMinus);
fbinary.write(code_file, instruction_number);
FSTPU_ fstpu(i - block_recursive);
fstpu.write(code_file, instruction_number);
}
}
break;
default:
break;
}
}
// Get the current code_file position and jump = true
streampos pos2 = code_file.tellp();
FJMP_ fjmp(0);
fjmp.write(code_file, instruction_number);
// Set code_file position to previous JMPIFEVAL_ and set the number of instructions to jump streampos pos3 = code_file.tellp();
code_file.seekp(pos1);
FJMPIFEVAL_ fjmp_if_eval1(instruction_number - prev_instruction_number);
fjmp_if_eval1.write(code_file, instruction_number);
code_file.seekp(pos3);
prev_instruction_number = instruction_number;
// The Jacobian if we have to solve the block determinsitic block
prev_var = -1;
prev_lag = -999999999;
count_col_endo = 0;
for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_block_endo_derivative.begin(); it != tmp_block_endo_derivative.end(); it++)
{
int lag = it->first.first;
unsigned int eq = it->first.second.second;
int var = it->first.second.first;
unsigned int eqr = getBlockEquationID(block, eq);
unsigned int varr = getBlockVariableID(block, var);
if (prev_var != var || prev_lag != lag)
{
prev_var = var;
prev_lag = lag;
count_col_endo++;
}
FNUMEXPR_ fnumexpr(FirstEndoDerivative, eqr, varr, lag);
fnumexpr.write(code_file, instruction_number);
compileDerivative(code_file, instruction_number, eqr, varr, lag, map_idx);
FSTPG3_ fstpg3(eq, var, lag, count_col_endo-1);
fstpg3.write(code_file, instruction_number);
}
prev_var = -1;
prev_lag = -999999999;
count_col_exo = 0;
for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_exo_derivative.begin(); it != tmp_exo_derivative.end(); it++)
{
int lag = it->first.first;
int eq = it->first.second.second;
int var = it->first.second.first;
int eqr = getBlockInitialEquationID(block, eq);
int varr = getBlockInitialExogenousID(block, var);
if (prev_var != var || prev_lag != lag)
{
prev_var = var;
prev_lag = lag;
count_col_exo++;
}
expr_t id = it->second;
FNUMEXPR_ fnumexpr(FirstExoDerivative, eqr, varr, lag);
fnumexpr.write(code_file, instruction_number);
id->compile(code_file, instruction_number, false, temporary_terms, map_idx, true, false);
FSTPG3_ fstpg3(eq, var, lag, /*var*/ count_col_exo-1);
fstpg3.write(code_file, instruction_number);
}
prev_var = -1;
prev_lag = -999999999;
int count_col_exo_det = 0;
for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_exo_det_derivative.begin(); it != tmp_exo_det_derivative.end(); it++)
{
int lag = it->first.first;
int eq = it->first.second.second;
int var = it->first.second.first;
int eqr = getBlockInitialEquationID(block, eq);
int varr = getBlockInitialDetExogenousID(block, var);
if (prev_var != var || prev_lag != lag)
{
prev_var = var;
prev_lag = lag;
count_col_exo_det++;
} expr_t id = it->second;
FNUMEXPR_ fnumexpr(FirstExodetDerivative, eqr, varr, lag);
fnumexpr.write(code_file, instruction_number);
id->compile(code_file, instruction_number, false, temporary_terms, map_idx, true, false);
FSTPG3_ fstpg3(eq, var, lag, count_col_exo_det-1);
fstpg3.write(code_file, instruction_number);
}
prev_var = -1;
prev_lag = -999999999;
count_col_other_endo = 0;
for (map<pair<int, pair<int, int>>, expr_t>::const_iterator it = tmp_other_endo_derivative.begin(); it != tmp_other_endo_derivative.end(); it++)
{
int lag = it->first.first;
int eq = it->first.second.second;
int var = it->first.second.first;
int eqr = getBlockInitialEquationID(block, eq);
int varr = getBlockInitialOtherEndogenousID(block, var);;
if (prev_var != var || prev_lag != lag)
{
prev_var = var;
prev_lag = lag;
count_col_other_endo++;
}
expr_t id = it->second;
FNUMEXPR_ fnumexpr(FirstOtherEndoDerivative, eqr, varr, lag);
fnumexpr.write(code_file, instruction_number);
id->compile(code_file, instruction_number, false, temporary_terms, map_idx, true, false);
FSTPG3_ fstpg3(eq, var, lag, count_col_other_endo-1);
fstpg3.write(code_file, instruction_number);
}
// Set codefile position to previous JMP_ and set the number of instructions to jump
pos1 = code_file.tellp();
code_file.seekp(pos2);
FJMP_ fjmp1(instruction_number - prev_instruction_number);
fjmp1.write(code_file, instruction_number);
code_file.seekp(pos1);
}
FENDBLOCK_ fendblock;
fendblock.write(code_file, instruction_number);
FEND_ fend;
fend.write(code_file, instruction_number);
code_file.close();
}
void
DynamicModel::writeDynamicMFile(const string &dynamic_basename) const
{
writeDynamicModel(dynamic_basename, false, false);
}
void
DynamicModel::fillVarExpectationFunctionsToWrite()
{
for (auto &it : var_expectation_node_map)
var_expectation_functions_to_write[get<0>(it.first)].insert(get<2>(it.first));
}
map<string, set<int>>
DynamicModel::getVarExpectationFunctionsToWrite() const
{
return var_expectation_functions_to_write;
}
void
DynamicModel::writeVarExpectationCalls(ostream &output) const
{
for (const auto & it : var_expectation_functions_to_write) {
int i = 0;
output << "dynamic_var_forecast_" << it.first << " = "
<< "var_forecast_" << it.first << "(y);" << endl;
for (auto it1 = it.second.begin(); it1 != it.second.end(); it1++)
output << "dynamic_var_forecast_" << it.first << "_" << *it1 << " = "
<< "dynamic_var_forecast_" << it.first << "(" << ++i << ", :);" << endl;
}
}
void
DynamicModel::writeDynamicJuliaFile(const string &basename) const
{
writeDynamicModel(basename, false, true);
}
void
DynamicModel::writeDynamicCFile(const string &dynamic_basename, const int order) const
{
string filename = dynamic_basename + ".c";
string filename_mex = dynamic_basename + "_mex.c";
ofstream mDynamicModelFile, mDynamicMexFile;
mDynamicModelFile.open(filename.c_str(), ios::out | ios::binary);
if (!mDynamicModelFile.is_open())
{
cerr << "Error: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
mDynamicModelFile << "/*" << endl
<< " * " << filename << " : Computes dynamic model for Dynare" << endl
<< " *" << endl
<< " * Warning : this file is generated automatically by Dynare" << endl
<< " * from model file (.mod)" << endl
<< " */" << endl
#if defined(_WIN32) || defined(__CYGWIN32__) || defined(__MINGW32__)
<< "#ifdef _MSC_VER" << endl
<< "#define _USE_MATH_DEFINES" << endl
<< "#endif" << endl
#endif
<< "#include <math.h>" << endl;
if (external_functions_table.get_total_number_of_unique_model_block_external_functions())
// External Matlab function, implies Dynamic function will call mex
mDynamicModelFile << "#include \"mex.h\"" << endl;
else
mDynamicModelFile << "#include <stdlib.h>" << endl;
mDynamicModelFile << "#define max(a, b) (((a) > (b)) ? (a) : (b))" << endl
<< "#define min(a, b) (((a) > (b)) ? (b) : (a))" << endl;
// Write function definition if oPowerDeriv is used
writePowerDerivCHeader(mDynamicModelFile);
writeNormcdfCHeader(mDynamicModelFile);
// Writing the function body
writeDynamicModel(mDynamicModelFile, true, false);
writePowerDeriv(mDynamicModelFile);
writeNormcdf(mDynamicModelFile);
mDynamicModelFile.close();
mDynamicMexFile.open(filename_mex.c_str(), ios::out | ios::binary);
if (!mDynamicMexFile.is_open())
{
cerr << "Error: Can't open file " << filename_mex << " for writing" << endl;
exit(EXIT_FAILURE);
}
// Writing the gateway routine
mDynamicMexFile << "/*" << endl
<< " * " << filename_mex << " : The gateway routine used to call the Dynamic function "
<< "located in " << filename << endl
<< " *" << endl
<< " * Warning : this file is generated automatically by Dynare" << endl
<< " * from model file (.mod)" << endl
<< endl
<< " */" << endl << endl
<< "#include \"mex.h\"" << endl << endl
<< "void Dynamic(double *y, double *x, int nb_row_x, double *params, double *steady_state, int it_, double *residual, double *g1, double *v2, double *v3);" << endl
<< "void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])" << endl
<< "{" << endl
<< " double *y, *x, *params, *steady_state;" << endl
<< " double *residual, *g1, *v2, *v3;" << endl
<< " int nb_row_x, it_;" << endl
<< endl
<< " /* Check that no derivatives of higher order than computed are being requested */" << endl
<< " if (nlhs > " << order + 1 << ")" << endl
<< " mexErrMsgTxt(\"Derivatives of higher order than computed have been requested\");" << endl
<< " /* Create a pointer to the input matrix y. */" << endl
<< " y = mxGetPr(prhs[0]);" << endl
<< endl
<< " /* Create a pointer to the input matrix x. */" << endl
<< " x = mxGetPr(prhs[1]);" << endl
<< endl
<< " /* Create a pointer to the input matrix params. */" << endl
<< " params = mxGetPr(prhs[2]);" << endl
<< endl
<< " /* Create a pointer to the input matrix steady_state. */" << endl
<< " steady_state = mxGetPr(prhs[3]);" << endl
<< endl
<< " /* Fetch time index */" << endl
<< " it_ = (int) mxGetScalar(prhs[4]) - 1;" << endl
<< endl
<< " /* Gets number of rows of matrix x. */" << endl
<< " nb_row_x = mxGetM(prhs[1]);" << endl
<< endl
<< " residual = NULL;" << endl
<< " if (nlhs >= 1)" << endl
<< " {" << endl
<< " /* Set the output pointer to the output matrix residual. */" << endl
<< " plhs[0] = mxCreateDoubleMatrix(" << equations.size() << ",1, mxREAL);" << endl
<< " /* Create a C pointer to a copy of the output matrix residual. */" << endl
<< " residual = mxGetPr(plhs[0]);" << endl
<< " }" << endl
<< endl
<< " g1 = NULL;" << endl
<< " if (nlhs >= 2)" << endl
<< " {" << endl
<< " /* Set the output pointer to the output matrix g1. */" << endl
<< " plhs[1] = mxCreateDoubleMatrix(" << equations.size() << ", " << dynJacobianColsNbr << ", mxREAL);" << endl
<< " /* Create a C pointer to a copy of the output matrix g1. */" << endl
<< " g1 = mxGetPr(plhs[1]);" << endl
<< " }" << endl
<< endl
<< " v2 = NULL;" << endl
<< " if (nlhs >= 3)" << endl
<< " {" << endl
<< " /* Set the output pointer to the output matrix v2. */" << endl
<< " plhs[2] = mxCreateDoubleMatrix(" << NNZDerivatives[1] << ", " << 3
<< ", mxREAL);" << endl
<< " v2 = mxGetPr(plhs[2]);" << endl
<< " }" << endl
<< endl
<< " v3 = NULL;" << endl
<< " if (nlhs >= 4)" << endl
<< " {" << endl
<< " /* Set the output pointer to the output matrix v3. */" << endl
<< " plhs[3] = mxCreateDoubleMatrix(" << NNZDerivatives[2] << ", " << 3 << ", mxREAL);" << endl << " v3 = mxGetPr(plhs[3]);" << endl
<< " }" << endl
<< endl
<< " /* Call the C subroutines. */" << endl
<< " Dynamic(y, x, nb_row_x, params, steady_state, it_, residual, g1, v2, v3);" << endl
<< "}" << endl;
mDynamicMexFile.close();
}
string
DynamicModel::reform(const string name1) const
{
string name = name1;
int pos = name.find("\\", 0);
while (pos >= 0)
{
if (name.substr(pos + 1, 1) != "\\")
{
name = name.insert(pos, "\\");
pos++;
}
pos++;
pos = name.find("\\", pos);
}
return (name);
}
void
DynamicModel::printNonZeroHessianEquations(ostream &output) const
{
if (nonzero_hessian_eqs.size() != 1)
output << "[";
for (auto it = nonzero_hessian_eqs.begin();
it != nonzero_hessian_eqs.end(); it++)
{
if (it != nonzero_hessian_eqs.begin())
output << " ";
output << it->first;
}
if (nonzero_hessian_eqs.size() != 1)
output << "]";
}
void
DynamicModel::setNonZeroHessianEquations(map<int, string> &eqs)
{
for (const auto &it : second_derivatives)
{
int eq = get<0>(it.first);
if (nonzero_hessian_eqs.find(eq) == nonzero_hessian_eqs.end())
{
nonzero_hessian_eqs[eq] = "";
for (auto & equation_tag : equation_tags)
if (equation_tag.first == eq)
if (equation_tag.second.first == "name")
{
nonzero_hessian_eqs[eq] = equation_tag.second.second;
break;
}
}
}
eqs = nonzero_hessian_eqs;
}
void
DynamicModel::Write_Inf_To_Bin_File_Block(const string &dynamic_basename, const string &bin_basename, const int &num,
int &u_count_int, bool &file_open, bool is_two_boundaries) const
{
int j;
std::ofstream SaveCode; if (file_open)
SaveCode.open((bin_basename + "_dynamic.bin").c_str(), ios::out | ios::in | ios::binary | ios::ate);
else
SaveCode.open((bin_basename + "_dynamic.bin").c_str(), ios::out | ios::binary);
if (!SaveCode.is_open())
{
cerr << "Error : Can't open file \"" << bin_basename << "_dynamic.bin\" for writing" << endl;
exit(EXIT_FAILURE);
}
u_count_int = 0;
unsigned int block_size = getBlockSize(num);
unsigned int block_mfs = getBlockMfs(num);
unsigned int block_recursive = block_size - block_mfs;
for (auto it = blocks_derivatives[num].begin(); it != (blocks_derivatives[num]).end(); it++)
{
unsigned int eq = it->first.first;
unsigned int var = it->first.second;
int lag = it->second.first;
if (lag != 0 && !is_two_boundaries)
continue;
if (eq >= block_recursive && var >= block_recursive)
{
int v = eq - block_recursive;
SaveCode.write(reinterpret_cast<char *>(&v), sizeof(v));
int varr = var - block_recursive + lag * block_mfs;
SaveCode.write(reinterpret_cast<char *>(&varr), sizeof(varr));
SaveCode.write(reinterpret_cast<char *>(&lag), sizeof(lag));
int u = u_count_int + block_mfs;
SaveCode.write(reinterpret_cast<char *>(&u), sizeof(u));
u_count_int++;
}
}
if (is_two_boundaries)
u_count_int += block_mfs;
for (j = block_recursive; j < (int) block_size; j++)
{
unsigned int varr = getBlockVariableID(num, j);
SaveCode.write(reinterpret_cast<char *>(&varr), sizeof(varr));
}
for (j = block_recursive; j < (int) block_size; j++)
{
unsigned int eqr = getBlockEquationID(num, j);
SaveCode.write(reinterpret_cast<char *>(&eqr), sizeof(eqr));
}
SaveCode.close();
}
void
DynamicModel::writeSparseDynamicMFile(const string &dynamic_basename, const string &basename) const
{
string sp;
ofstream mDynamicModelFile;
ostringstream tmp, tmp1, tmp_eq;
bool OK;
chdir(basename.c_str());
string filename = dynamic_basename + ".m";
mDynamicModelFile.open(filename.c_str(), ios::out | ios::binary);
if (!mDynamicModelFile.is_open())
{
cerr << "Error: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
mDynamicModelFile << "%\n";
mDynamicModelFile << "% " << filename << " : Computes dynamic model for Dynare\n";
mDynamicModelFile << "%\n";
mDynamicModelFile << "% Warning : this file is generated automatically by Dynare\n";
mDynamicModelFile << "% from model file (.mod)\n\n";
mDynamicModelFile << "%/\n";
int Nb_SGE = 0;
bool open_par = false;
mDynamicModelFile << "function [varargout] = " << dynamic_basename << "(options_, M_, oo_, varargin)\n";
mDynamicModelFile << " g2=[];g3=[];\n";
//Temporary variables declaration
OK = true;
ostringstream tmp_output;
for (auto temporary_term : temporary_terms)
{
if (OK)
OK = false;
else
tmp_output << " ";
// In the following, "Static" is used to avoid getting the "(it_)" subscripting
temporary_term->writeOutput(tmp_output, oMatlabStaticModelSparse, temporary_terms, {});
}
if (tmp_output.str().length() > 0)
mDynamicModelFile << " global " << tmp_output.str() << ";\n";
mDynamicModelFile << " T_init=zeros(1,options_.periods+M_.maximum_lag+M_.maximum_lead);\n";
tmp_output.str("");
for (auto temporary_term : temporary_terms)
{
tmp_output << " ";
// In the following, "Static" is used to avoid getting the "(it_)" subscripting
temporary_term->writeOutput(tmp_output, oMatlabStaticModelSparse, temporary_terms, {});
tmp_output << "=T_init;\n";
}
if (tmp_output.str().length() > 0)
mDynamicModelFile << tmp_output.str();
mDynamicModelFile << " y_kmin=M_.maximum_lag;" << endl
<< " y_kmax=M_.maximum_lead;" << endl
<< " y_size=M_.endo_nbr;" << endl
<< " if(length(varargin)>0)" << endl
<< " %it is a simple evaluation of the dynamic model for time _it" << endl
<< " y=varargin{1};" << endl
<< " x=varargin{2};" << endl
<< " params=varargin{3};" << endl
<< " steady_state=varargin{4};" << endl
<< " it_=varargin{5};" << endl
<< " dr=varargin{6};" << endl
<< " Per_u_=0;" << endl
<< " Per_y_=it_*y_size;" << endl
<< " ys=y(it_,:);" << endl;
tmp.str("");
tmp_eq.str("");
unsigned int nb_blocks = getNbBlocks();
unsigned int block = 0;
for (int count_call = 1; block < nb_blocks; block++, count_call++)
{
unsigned int block_size = getBlockSize(block);
unsigned int block_mfs = getBlockMfs(block);
unsigned int block_recursive = block_size - block_mfs;
BlockSimulationType simulation_type = getBlockSimulationType(block);
if (simulation_type == EVALUATE_FORWARD || simulation_type == EVALUATE_BACKWARD)
{
for (unsigned int ik = 0; ik < block_size; ik++)
{
tmp << " " << getBlockVariableID(block, ik)+1;
tmp_eq << " " << getBlockEquationID(block, ik)+1;
}
}
else
{
for (unsigned int ik = block_recursive; ik < block_size; ik++)
{
tmp << " " << getBlockVariableID(block, ik)+1; tmp_eq << " " << getBlockEquationID(block, ik)+1;
}
}
mDynamicModelFile << " y_index_eq=[" << tmp_eq.str() << "];\n";
mDynamicModelFile << " y_index=[" << tmp.str() << "];\n";
switch (simulation_type)
{
case EVALUATE_FORWARD:
case EVALUATE_BACKWARD:
mDynamicModelFile << " [y, dr(" << count_call << ").g1, dr(" << count_call << ").g2, dr(" << count_call << ").g3, dr(" << count_call << ").g1_x, dr(" << count_call << ").g1_xd, dr(" << count_call << ").g1_o]=" << dynamic_basename << "_" << block + 1 << "(y, x, params, steady_state, 1, it_-1, 1);\n";
mDynamicModelFile << " residual(y_index_eq)=ys(y_index)-y(it_, y_index);\n";
break;
case SOLVE_FORWARD_SIMPLE:
case SOLVE_BACKWARD_SIMPLE:
mDynamicModelFile << " [r, y, dr(" << count_call << ").g1, dr(" << count_call << ").g2, dr(" << count_call << ").g3, dr(" << count_call << ").g1_x, dr(" << count_call << ").g1_xd, dr(" << count_call << ").g1_o]=" << dynamic_basename << "_" << block + 1 << "(y, x, params, steady_state, it_, 1);\n";
mDynamicModelFile << " residual(y_index_eq)=r;\n";
break;
case SOLVE_FORWARD_COMPLETE:
case SOLVE_BACKWARD_COMPLETE:
mDynamicModelFile << " [r, y, dr(" << count_call << ").g1, dr(" << count_call << ").g2, dr(" << count_call << ").g3, dr(" << count_call << ").g1_x, dr(" << count_call << ").g1_xd, dr(" << count_call << ").g1_o]=" << dynamic_basename << "_" << block + 1 << "(y, x, params, steady_state, it_, 1);\n";
mDynamicModelFile << " residual(y_index_eq)=r;\n";
break;
case SOLVE_TWO_BOUNDARIES_COMPLETE:
case SOLVE_TWO_BOUNDARIES_SIMPLE:
mDynamicModelFile << " [r, y, dr(" << count_call << ").g1, dr(" << count_call << ").g2, dr(" << count_call << ").g3, b, dr(" << count_call << ").g1_x, dr(" << count_call << ").g1_xd, dr(" << count_call << ").g1_o]=" << dynamic_basename << "_" << block + 1 << "(y, x, params, steady_state, it_-" << max_lag << ", 1, " << max_lag << ", " << block_recursive << "," << "options_.periods" << ");\n";
mDynamicModelFile << " residual(y_index_eq)=r(:,M_.maximum_lag+1);\n";
break;
default:
break;
}
tmp_eq.str("");
tmp.str("");
}
if (tmp1.str().length())
{
mDynamicModelFile << tmp1.str();
tmp1.str("");
}
mDynamicModelFile << " varargout{1}=residual;" << endl
<< " varargout{2}=dr;" << endl
<< " return;" << endl
<< " end;" << endl
<< " %it is the deterministic simulation of the block decomposed dynamic model" << endl
<< " if(options_.stack_solve_algo==0)" << endl
<< " mthd='Sparse LU';" << endl
<< " elseif(options_.stack_solve_algo==1)" << endl
<< " mthd='Relaxation';" << endl
<< " elseif(options_.stack_solve_algo==2)" << endl
<< " mthd='GMRES';" << endl
<< " elseif(options_.stack_solve_algo==3)" << endl
<< " mthd='BICGSTAB';" << endl
<< " elseif(options_.stack_solve_algo==4)" << endl
<< " mthd='OPTIMPATH';" << endl
<< " else" << endl
<< " mthd='UNKNOWN';" << endl
<< " end;" << endl
<< " if options_.verbosity" << endl
<< " printline(41)" << endl
<< " disp(sprintf('MODEL SIMULATION (method=%s):',mthd))" << endl
<< " skipline()" << endl
<< " end" << endl
<< " periods=options_.periods;" << endl
<< " maxit_=options_.simul.maxit;" << endl
<< " solve_tolf=options_.solve_tolf;" << endl
<< " y=oo_.endo_simul';" << endl
<< " x=oo_.exo_simul;" << endl;
mDynamicModelFile << " params=M_.params;\n";
mDynamicModelFile << " steady_state=oo_.steady_state;\n"; mDynamicModelFile << " oo_.deterministic_simulation.status = 0;\n";
for (block = 0; block < nb_blocks; block++)
{
unsigned int block_size = getBlockSize(block);
unsigned int block_mfs = getBlockMfs(block);
unsigned int block_recursive = block_size - block_mfs;
BlockSimulationType simulation_type = getBlockSimulationType(block);
if ((simulation_type == EVALUATE_FORWARD) && (block_size))
{
if (open_par)
{
mDynamicModelFile << " end\n";
}
mDynamicModelFile << " oo_.deterministic_simulation.status = 1;\n";
mDynamicModelFile << " oo_.deterministic_simulation.error = 0;\n";
mDynamicModelFile << " oo_.deterministic_simulation.iterations = 0;\n";
mDynamicModelFile << " if(isfield(oo_.deterministic_simulation,'block'))\n";
mDynamicModelFile << " blck_num = length(oo_.deterministic_simulation.block)+1;\n";
mDynamicModelFile << " else\n";
mDynamicModelFile << " blck_num = 1;\n";
mDynamicModelFile << " end;\n";
mDynamicModelFile << " oo_.deterministic_simulation.block(blck_num).status = 1;\n";
mDynamicModelFile << " oo_.deterministic_simulation.block(blck_num).error = 0;\n";
mDynamicModelFile << " oo_.deterministic_simulation.block(blck_num).iterations = 0;\n";
mDynamicModelFile << " g1=[];g2=[];g3=[];\n";
mDynamicModelFile << " y=" << dynamic_basename << "_" << block + 1 << "(y, x, params, steady_state, 0, y_kmin, periods);\n";
mDynamicModelFile << " tmp = y(:,M_.block_structure.block(" << block + 1 << ").variable);\n";
mDynamicModelFile << " if any(isnan(tmp) | isinf(tmp))\n";
mDynamicModelFile << " disp(['Inf or Nan value during the evaluation of block " << block <<"']);\n";
mDynamicModelFile << " oo_.deterministic_simulation.status = 0;\n";
mDynamicModelFile << " oo_.deterministic_simulation.error = 100;\n";
mDynamicModelFile << " varargout{1} = oo_;\n";
mDynamicModelFile << " return;\n";
mDynamicModelFile << " end;\n";
}
else if ((simulation_type == EVALUATE_BACKWARD) && (block_size))
{
if (open_par)
{
mDynamicModelFile << " end\n";
}
mDynamicModelFile << " oo_.deterministic_simulation.status = 1;\n";
mDynamicModelFile << " oo_.deterministic_simulation.error = 0;\n";
mDynamicModelFile << " oo_.deterministic_simulation.iterations = 0;\n";
mDynamicModelFile << " if(isfield(oo_.deterministic_simulation,'block'))\n";
mDynamicModelFile << " blck_num = length(oo_.deterministic_simulation.block)+1;\n";
mDynamicModelFile << " else\n";
mDynamicModelFile << " blck_num = 1;\n";
mDynamicModelFile << " end;\n";
mDynamicModelFile << " oo_.deterministic_simulation.block(blck_num).status = 1;\n";
mDynamicModelFile << " oo_.deterministic_simulation.block(blck_num).error = 0;\n";
mDynamicModelFile << " oo_.deterministic_simulation.block(blck_num).iterations = 0;\n";
mDynamicModelFile << " g1=[];g2=[];g3=[];\n";
mDynamicModelFile << " " << dynamic_basename << "_" << block + 1 << "(y, x, params, steady_state, 0, y_kmin, periods);\n";
mDynamicModelFile << " tmp = y(:,M_.block_structure.block(" << block + 1 << ").variable);\n";
mDynamicModelFile << " if any(isnan(tmp) | isinf(tmp))\n";
mDynamicModelFile << " disp(['Inf or Nan value during the evaluation of block " << block <<"']);\n";
mDynamicModelFile << " oo_.deterministic_simulation.status = 0;\n";
mDynamicModelFile << " oo_.deterministic_simulation.error = 100;\n";
mDynamicModelFile << " varargout{1} = oo_;\n";
mDynamicModelFile << " return;\n";
mDynamicModelFile << " end;\n";
}
else if ((simulation_type == SOLVE_FORWARD_COMPLETE || simulation_type == SOLVE_FORWARD_SIMPLE) && (block_size))
{
if (open_par)
mDynamicModelFile << " end\n";
open_par = false;
mDynamicModelFile << " g1=0;\n"; mDynamicModelFile << " r=0;\n";
tmp.str("");
for (unsigned int ik = block_recursive; ik < block_size; ik++)
{
tmp << " " << getBlockVariableID(block, ik)+1;
}
mDynamicModelFile << " y_index = [" << tmp.str() << "];\n";
int nze = blocks_derivatives[block].size();
mDynamicModelFile << " if(isfield(oo_.deterministic_simulation,'block'))\n";
mDynamicModelFile << " blck_num = length(oo_.deterministic_simulation.block)+1;\n";
mDynamicModelFile << " else\n";
mDynamicModelFile << " blck_num = 1;\n";
mDynamicModelFile << " end;\n";
mDynamicModelFile << " y = solve_one_boundary('" << dynamic_basename << "_" << block + 1 << "'"
<<", y, x, params, steady_state, y_index, " << nze
<<", options_.periods, " << blocks_linear[block]
<<", blck_num, y_kmin, options_.simul.maxit, options_.solve_tolf, options_.slowc, " << cutoff << ", options_.stack_solve_algo, 1, 1, 0);\n";
mDynamicModelFile << " tmp = y(:,M_.block_structure.block(" << block + 1 << ").variable);\n";
mDynamicModelFile << " if any(isnan(tmp) | isinf(tmp))\n";
mDynamicModelFile << " disp(['Inf or Nan value during the resolution of block " << block <<"']);\n";
mDynamicModelFile << " oo_.deterministic_simulation.status = 0;\n";
mDynamicModelFile << " oo_.deterministic_simulation.error = 100;\n";
mDynamicModelFile << " varargout{1} = oo_;\n";
mDynamicModelFile << " return;\n";
mDynamicModelFile << " end;\n";
}
else if ((simulation_type == SOLVE_BACKWARD_COMPLETE || simulation_type == SOLVE_BACKWARD_SIMPLE) && (block_size))
{
if (open_par)
mDynamicModelFile << " end\n";
open_par = false;
mDynamicModelFile << " g1=0;\n";
mDynamicModelFile << " r=0;\n";
tmp.str("");
for (unsigned int ik = block_recursive; ik < block_size; ik++)
{
tmp << " " << getBlockVariableID(block, ik)+1;
}
mDynamicModelFile << " y_index = [" << tmp.str() << "];\n";
int nze = blocks_derivatives[block].size();
mDynamicModelFile << " if(isfield(oo_.deterministic_simulation,'block'))\n";
mDynamicModelFile << " blck_num = length(oo_.deterministic_simulation.block)+1;\n";
mDynamicModelFile << " else\n";
mDynamicModelFile << " blck_num = 1;\n";
mDynamicModelFile << " end;\n";
mDynamicModelFile << " y = solve_one_boundary('" << dynamic_basename << "_" << block + 1 << "'"
<<", y, x, params, steady_state, y_index, " << nze
<<", options_.periods, " << blocks_linear[block]
<<", blck_num, y_kmin, options_.simul.maxit, options_.solve_tolf, options_.slowc, " << cutoff << ", options_.stack_solve_algo, 1, 1, 0);\n";
mDynamicModelFile << " tmp = y(:,M_.block_structure.block(" << block + 1 << ").variable);\n";
mDynamicModelFile << " if any(isnan(tmp) | isinf(tmp))\n";
mDynamicModelFile << " disp(['Inf or Nan value during the resolution of block " << block <<"']);\n";
mDynamicModelFile << " oo_.deterministic_simulation.status = 0;\n";
mDynamicModelFile << " oo_.deterministic_simulation.error = 100;\n";
mDynamicModelFile << " varargout{1} = oo_;\n";
mDynamicModelFile << " return;\n";
mDynamicModelFile << " end;\n";
}
else if ((simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE || simulation_type == SOLVE_TWO_BOUNDARIES_SIMPLE) && (block_size))
{
if (open_par)
mDynamicModelFile << " end\n";
open_par = false;
Nb_SGE++;
int nze = blocks_derivatives[block].size();
mDynamicModelFile << " y_index=[";
for (unsigned int ik = block_recursive; ik < block_size; ik++)
{
mDynamicModelFile << " " << getBlockVariableID(block, ik)+1; }
mDynamicModelFile << " ];\n";
mDynamicModelFile << " if(isfield(oo_.deterministic_simulation,'block'))\n";
mDynamicModelFile << " blck_num = length(oo_.deterministic_simulation.block)+1;\n";
mDynamicModelFile << " else\n";
mDynamicModelFile << " blck_num = 1;\n";
mDynamicModelFile << " end;\n";
mDynamicModelFile << " [y oo_] = solve_two_boundaries('" << dynamic_basename << "_" << block + 1 << "'"
<<", y, x, params, steady_state, y_index, " << nze
<<", options_.periods, " << max_leadlag_block[block].first
<<", " << max_leadlag_block[block].second
<<", " << blocks_linear[block]
<<", blck_num, y_kmin, options_.simul.maxit, options_.solve_tolf, options_.slowc, " << cutoff << ", options_.stack_solve_algo, options_, M_, oo_);\n";
mDynamicModelFile << " tmp = y(:,M_.block_structure.block(" << block + 1 << ").variable);\n";
mDynamicModelFile << " if any(isnan(tmp) | isinf(tmp))\n";
mDynamicModelFile << " disp(['Inf or Nan value during the resolution of block " << block <<"']);\n";
mDynamicModelFile << " oo_.deterministic_simulation.status = 0;\n";
mDynamicModelFile << " oo_.deterministic_simulation.error = 100;\n";
mDynamicModelFile << " varargout{1} = oo_;\n";
mDynamicModelFile << " return;\n";
mDynamicModelFile << " end;\n";
}
}
if (open_par)
mDynamicModelFile << " end;\n";
open_par = false;
mDynamicModelFile << " oo_.endo_simul = y';\n";
mDynamicModelFile << " varargout{1} = oo_;\n";
mDynamicModelFile << "return;\n";
mDynamicModelFile << "end" << endl;
mDynamicModelFile.close();
writeModelEquationsOrdered_M(dynamic_basename);
chdir("..");
}
void
DynamicModel::writeWrapperFunctions(const string &basename, const string &ending) const
{
string name;
if (ending == "g1")
name = basename + "_resid_g1";
else if (ending == "g2")
name= basename + "_resid_g1_g2";
else if (ending == "g3")
name = basename + "_resid_g1_g2_g3";
string filename = name + ".m";
ofstream output;
output.open(filename.c_str(), ios::out | ios::binary);
if (!output.is_open())
{
cerr << "Error: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
if (ending == "g1")
output << "function [residual, g1] = " << name << "(T, y, x, params, steady_state, it_, T_flag)" << endl
<< "% function [residual, g1] = " << name << "(T, y, x, params, steady_state, it_, T_flag)" << endl;
else if (ending == "g2")
output << "function [residual, g1, g2] = " << name << "(T, y, x, params, steady_state, it_, T_flag)" << endl
<< "% function [residual, g1, g2] = " << name << "(T, y, x, params, steady_state, it_, T_flag)" << endl;
else if (ending == "g3")
output << "function [residual, g1, g2, g3] = " << name << "(T, y, x, params, steady_state, it_, T_flag)" << endl
<< "% function [residual, g1, g2, g3] = " << name << "(T, y, x, params, steady_state, it_, T_flag)" << endl;
output << "%" << endl
<< "% Wrapper function automatically created by Dynare" << endl << "%" << endl
<< endl
<< " if T_flag" << endl
<< " T = " << basename + "_" + ending + "_tt(T, y, x, params, steady_state, it_);" << endl
<< " end" << endl;
if (ending == "g1")
output << " residual = " << basename + "_resid(T, y, x, params, steady_state, it_, false);" << endl
<< " g1 = " << basename + "_g1(T, y, x, params, steady_state, it_, false);" << endl;
else if (ending == "g2")
output << " [residual, g1] = " << basename + "_resid_g1(T, y, x, params, steady_state, it_, false);" << endl
<< " g2 = " << basename + "_g2(T, y, x, params, steady_state, it_, false);" << endl;
else if (ending == "g3")
output << " [residual, g1, g2] = " << basename + "_resid_g1_g2(T, y, x, params, steady_state, it_, false);" << endl
<< " g3 = " << basename + "_g3(T, y, x, params, steady_state, it_, false);" << endl;
output << endl << "end" << endl;
output.close();
}
void
DynamicModel::writeDynamicModelHelper(const string &name, const string &retvalname,
const string &name_tt, size_t ttlen,
const string &previous_tt_name,
const ostringstream &init_s,
const ostringstream &end_s,
const ostringstream &s, const ostringstream &s_tt) const
{
string filename = name_tt + ".m";
ofstream output;
output.open(filename.c_str(), ios::out | ios::binary);
if (!output.is_open())
{
cerr << "Error: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
output << "function T = " << name_tt << "(T, y, x, params, steady_state, it_)" << endl
<< "% function T = " << name_tt << "(T, y, x, params, steady_state, it_)" << endl
<< "%" << endl
<< "% File created by Dynare Preprocessor from .mod file" << endl
<< "%" << endl
<< "% Inputs:" << endl
<< "% T [#temp variables by 1] double vector of temporary terms to be filled by function" << endl
<< "% y [#dynamic variables by 1] double vector of endogenous variables in the order stored" << endl
<< "% in M_.lead_lag_incidence; see the Manual" << endl
<< "% x [nperiods by M_.exo_nbr] double matrix of exogenous variables (in declaration order)" << endl
<< "% for all simulation periods" << endl
<< "% steady_state [M_.endo_nbr by 1] double vector of steady state values" << endl
<< "% params [M_.param_nbr by 1] double vector of parameter values in declaration order" << endl
<< "% it_ scalar double time period for exogenous variables for which" << endl
<< "% to evaluate the model" << endl
<< "%" << endl
<< "% Output:" << endl
<< "% T [#temp variables by 1] double vector of temporary terms" << endl
<< "%" << endl << endl
<< "assert(length(T) >= " << ttlen << ");" << endl
<< endl;
if (!previous_tt_name.empty())
output << "T = " << previous_tt_name << "(T, y, x, params, steady_state, it_);" << endl << endl;
output << s_tt.str() << endl
<< "end" << endl;
output.close();
filename = name + ".m";
output.open(filename.c_str(), ios::out | ios::binary);
if (!output.is_open())
{ cerr << "Error: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
output << "function " << retvalname << " = " << name << "(T, y, x, params, steady_state, it_, T_flag)" << endl
<< "% function " << retvalname << " = " << name << "(T, y, x, params, steady_state, it_, T_flag)" << endl
<< "%" << endl
<< "% File created by Dynare Preprocessor from .mod file" << endl
<< "%" << endl
<< "% Inputs:" << endl
<< "% T [#temp variables by 1] double vector of temporary terms to be filled by function" << endl
<< "% y [#dynamic variables by 1] double vector of endogenous variables in the order stored" << endl
<< "% in M_.lead_lag_incidence; see the Manual" << endl
<< "% x [nperiods by M_.exo_nbr] double matrix of exogenous variables (in declaration order)" << endl
<< "% for all simulation periods" << endl
<< "% steady_state [M_.endo_nbr by 1] double vector of steady state values" << endl
<< "% params [M_.param_nbr by 1] double vector of parameter values in declaration order" << endl
<< "% it_ scalar double time period for exogenous variables for which" << endl
<< "% to evaluate the model" << endl
<< "% T_flag boolean boolean flag saying whether or not to calculate temporary terms" << endl
<< "%" << endl
<< "% Output:" << endl
<< "% " << retvalname << endl
<< "%" << endl << endl;
if (!name_tt.empty())
output << "if T_flag" << endl
<< " T = " << name_tt << "(T, y, x, params, steady_state, it_);" << endl
<< "end" << endl;
output << init_s.str() << endl
<< s.str()
<< end_s.str() << endl
<< "end" << endl;
output.close();
}
void
DynamicModel::writeDynamicMatlabCompatLayer(const string &name) const
{
string filename = name + ".m";
ofstream output;
output.open(filename.c_str(), ios::out | ios::binary);
if (!output.is_open())
{
cerr << "Error: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
int ntt = temporary_terms_mlv.size() + temporary_terms_res.size() + temporary_terms_g1.size() + temporary_terms_g2.size() + temporary_terms_g3.size();
output << "function [residual, g1, g2, g3] = " << name << "(y, x, params, steady_state, it_)" << endl
<< " T = NaN(" << ntt << ", 1);" << endl
<< " if nargout <= 1" << endl
<< " residual = " << name << "_resid(T, y, x, params, steady_state, it_, true);" << endl
<< " elseif nargout == 2" << endl
<< " [residual, g1] = " << name << "_resid_g1(T, y, x, params, steady_state, it_, true);" << endl
<< " elseif nargout == 3" << endl
<< " [residual, g1, g2] = " << name << "_resid_g1_g2(T, y, x, params, steady_state, it_, true);" << endl
<< " else" << endl
<< " [residual, g1, g2, g3] = " << name << "_resid_g1_g2_g3(T, y, x, params, steady_state, it_, true);" << endl
<< " end" << endl
<< "end" << endl;
output.close();
}
void
DynamicModel::writeDynamicModel(ostream &DynamicOutput, bool use_dll, bool julia) const
{
writeDynamicModel("", DynamicOutput, use_dll, julia);}
void
DynamicModel::writeDynamicModel(const string &dynamic_basename, bool use_dll, bool julia) const
{
ofstream DynamicOutput;
writeDynamicModel(dynamic_basename, DynamicOutput, use_dll, julia);
}
void
DynamicModel::writeDynamicModel(const string &dynamic_basename, ostream &DynamicOutput, bool use_dll, bool julia) const
{
ostringstream model_tt_output; // Used for storing model temp vars
ostringstream model_output; // Used for storing model equations
ostringstream jacobian_tt_output; // Used for storing jacobian temp vars
ostringstream jacobian_output; // Used for storing jacobian equations
ostringstream hessian_tt_output; // Used for storing Hessian temp vars
ostringstream hessian_output; // Used for storing Hessian equations
ostringstream third_derivatives_tt_output; // Used for storing third order derivatives temp terms
ostringstream third_derivatives_output; // Used for storing third order derivatives equations
ExprNodeOutputType output_type = (use_dll ? oCDynamicModel :
julia ? oJuliaDynamicModel : oMatlabDynamicModel);
deriv_node_temp_terms_t tef_terms;
temporary_terms_t temp_term_union;
for (auto it : temporary_terms_mlv)
temp_term_union.insert(it.first);
writeModelLocalVariableTemporaryTerms(temp_term_union, temporary_terms_mlv,
model_tt_output, output_type, tef_terms);
writeTemporaryTerms(temporary_terms_res,
temp_term_union,
temporary_terms_idxs,
model_tt_output, output_type, tef_terms);
temp_term_union.insert(temporary_terms_res.begin(), temporary_terms_res.end());
writeModelEquations(model_output, output_type, temp_term_union);
int nrows = equations.size();
int hessianColsNbr = dynJacobianColsNbr * dynJacobianColsNbr;
// Writing Jacobian
if (!first_derivatives.empty())
{
writeTemporaryTerms(temporary_terms_g1,
temp_term_union,
temporary_terms_idxs,
jacobian_tt_output, output_type, tef_terms);
temp_term_union.insert(temporary_terms_g1.begin(), temporary_terms_g1.end());
for (const auto & first_derivative : first_derivatives)
{
int eq, var;
tie(eq, var) = first_derivative.first;
expr_t d1 = first_derivative.second;
jacobianHelper(jacobian_output, eq, getDynJacobianCol(var), output_type);
jacobian_output << "=";
d1->writeOutput(jacobian_output, output_type,
temp_term_union, temporary_terms_idxs, tef_terms);
jacobian_output << ";" << endl;
}
}
// Writing Hessian
if (!second_derivatives.empty())
{
writeTemporaryTerms(temporary_terms_g2, temp_term_union,
temporary_terms_idxs,
hessian_tt_output, output_type, tef_terms);
temp_term_union.insert(temporary_terms_g2.begin(), temporary_terms_g2.end());
int k = 0; // Keep the line of a 2nd derivative in v2
for (const auto & second_derivative : second_derivatives)
{
int eq, var1, var2;
tie(eq, var1, var2) = second_derivative.first;
expr_t d2 = second_derivative.second;
int id1 = getDynJacobianCol(var1);
int id2 = getDynJacobianCol(var2);
int col_nb = id1 * dynJacobianColsNbr + id2;
int col_nb_sym = id2 * dynJacobianColsNbr + id1;
ostringstream for_sym;
if (output_type == oJuliaDynamicModel)
{
for_sym << "g2[" << eq + 1 << "," << col_nb + 1 << "]";
hessian_output << " @inbounds " << for_sym.str() << " = ";
d2->writeOutput(hessian_output, output_type, temp_term_union, temporary_terms_idxs, tef_terms);
hessian_output << endl;
}
else
{
sparseHelper(2, hessian_output, k, 0, output_type);
hessian_output << "=" << eq + 1 << ";" << endl;
sparseHelper(2, hessian_output, k, 1, output_type);
hessian_output << "=" << col_nb + 1 << ";" << endl;
sparseHelper(2, hessian_output, k, 2, output_type);
hessian_output << "=";
d2->writeOutput(hessian_output, output_type, temp_term_union, temporary_terms_idxs, tef_terms);
hessian_output << ";" << endl;
k++;
}
// Treating symetric elements
if (id1 != id2)
if (output_type == oJuliaDynamicModel)
hessian_output << " @inbounds g2[" << eq + 1 << "," << col_nb_sym + 1 << "] = "
<< for_sym.str() << endl;
else
{
sparseHelper(2, hessian_output, k, 0, output_type);
hessian_output << "=" << eq + 1 << ";" << endl;
sparseHelper(2, hessian_output, k, 1, output_type);
hessian_output << "=" << col_nb_sym + 1 << ";" << endl;
sparseHelper(2, hessian_output, k, 2, output_type);
hessian_output << "=";
sparseHelper(2, hessian_output, k-1, 2, output_type);
hessian_output << ";" << endl;
k++;
}
}
}
// Writing third derivatives
if (!third_derivatives.empty())
{
writeTemporaryTerms(temporary_terms_g3,
temp_term_union, temporary_terms_idxs,
third_derivatives_tt_output, output_type, tef_terms);
temp_term_union.insert(temporary_terms_g3.begin(), temporary_terms_g3.end());
int k = 0; // Keep the line of a 3rd derivative in v3
for (const auto & third_derivative : third_derivatives)
{
int eq, var1, var2, var3;
tie(eq, var1, var2, var3) = third_derivative.first;
expr_t d3 = third_derivative.second;
int id1 = getDynJacobianCol(var1);
int id2 = getDynJacobianCol(var2);
int id3 = getDynJacobianCol(var3);
// Reference column number for the g3 matrix
int ref_col = id1 * hessianColsNbr + id2 * dynJacobianColsNbr + id3;
ostringstream for_sym;
if (output_type == oJuliaDynamicModel)
{
for_sym << "g3[" << eq + 1 << "," << ref_col + 1 << "]";
third_derivatives_output << " @inbounds " << for_sym.str() << " = ";
d3->writeOutput(third_derivatives_output, output_type, temp_term_union, temporary_terms_idxs, tef_terms);
third_derivatives_output << endl;
}
else
{
sparseHelper(3, third_derivatives_output, k, 0, output_type);
third_derivatives_output << "=" << eq + 1 << ";" << endl;
sparseHelper(3, third_derivatives_output, k, 1, output_type);
third_derivatives_output << "=" << ref_col + 1 << ";" << endl;
sparseHelper(3, third_derivatives_output, k, 2, output_type);
third_derivatives_output << "=";
d3->writeOutput(third_derivatives_output, output_type, temp_term_union, temporary_terms_idxs, tef_terms);
third_derivatives_output << ";" << endl;
}
// Compute the column numbers for the 5 other permutations of (id1,id2,id3)
// and store them in a set (to avoid duplicates if two indexes are equal)
set<int> cols;
cols.insert(id1 * hessianColsNbr + id3 * dynJacobianColsNbr + id2);
cols.insert(id2 * hessianColsNbr + id1 * dynJacobianColsNbr + id3);
cols.insert(id2 * hessianColsNbr + id3 * dynJacobianColsNbr + id1);
cols.insert(id3 * hessianColsNbr + id1 * dynJacobianColsNbr + id2);
cols.insert(id3 * hessianColsNbr + id2 * dynJacobianColsNbr + id1);
int k2 = 1; // Keeps the offset of the permutation relative to k
for (int col : cols)
if (col != ref_col)
if (output_type == oJuliaDynamicModel)
third_derivatives_output << " @inbounds g3[" << eq + 1 << "," << col + 1 << "] = "
<< for_sym.str() << endl;
else
{
sparseHelper(3, third_derivatives_output, k+k2, 0, output_type);
third_derivatives_output << "=" << eq + 1 << ";" << endl;
sparseHelper(3, third_derivatives_output, k+k2, 1, output_type);
third_derivatives_output << "=" << col + 1 << ";" << endl;
sparseHelper(3, third_derivatives_output, k+k2, 2, output_type);
third_derivatives_output << "=";
sparseHelper(3, third_derivatives_output, k, 2, output_type);
third_derivatives_output << ";" << endl;
k2++;
} k += k2;
}
}
if (output_type == oMatlabDynamicModel)
{
// Check that we don't have more than 32 nested parenthesis because Matlab does not suppor this. See Issue #1201
map<string, string> tmp_paren_vars;
bool message_printed = false;
fixNestedParenthesis(model_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(model_tt_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(jacobian_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(jacobian_tt_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(hessian_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(hessian_tt_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(third_derivatives_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(third_derivatives_tt_output, tmp_paren_vars, message_printed);
ostringstream init_output, end_output;
init_output << "residual = zeros(" << nrows << ", 1);";
writeDynamicModelHelper(dynamic_basename + "_resid", "residual",
dynamic_basename + "_resid_tt",
temporary_terms_mlv.size() + temporary_terms_res.size(),
"", init_output, end_output,
model_output, model_tt_output);
init_output.str(string());
init_output.clear();
init_output << "g1 = zeros(" << nrows << ", " << dynJacobianColsNbr << ");";
writeDynamicModelHelper(dynamic_basename + "_g1", "g1",
dynamic_basename + "_g1_tt",
temporary_terms_mlv.size() + temporary_terms_res.size() + temporary_terms_g1.size(),
dynamic_basename + "_resid_tt",
init_output, end_output,
jacobian_output, jacobian_tt_output);
writeWrapperFunctions(dynamic_basename, "g1");
init_output.str(string());
init_output.clear();
if (second_derivatives.size())
{
init_output << "v2 = zeros(" << NNZDerivatives[1] << ",3);";
end_output << "g2 = sparse(v2(:,1),v2(:,2),v2(:,3)," << nrows << "," << hessianColsNbr << ");";
}
else
init_output << "g2 = sparse([],[],[]," << nrows << "," << hessianColsNbr << ");";
writeDynamicModelHelper(dynamic_basename + "_g2", "g2",
dynamic_basename + "_g2_tt",
temporary_terms_mlv.size() + temporary_terms_res.size() + temporary_terms_g1.size()
+ temporary_terms_g2.size(),
dynamic_basename + "_g1_tt",
init_output, end_output,
hessian_output, hessian_tt_output);
writeWrapperFunctions(dynamic_basename, "g2");
init_output.str(string());
init_output.clear();
end_output.str(string());
end_output.clear();
int ncols = hessianColsNbr * dynJacobianColsNbr;
if (third_derivatives.size())
{
init_output << "v3 = zeros(" << NNZDerivatives[2] << ",3);";
end_output << "g3 = sparse(v3(:,1),v3(:,2),v3(:,3)," << nrows << "," << ncols << ");";
}
else
init_output << "g3 = sparse([],[],[]," << nrows << "," << ncols << ");";
writeDynamicModelHelper(dynamic_basename + "_g3", "g3",
dynamic_basename + "_g3_tt",
temporary_terms_mlv.size() + temporary_terms_res.size() + temporary_terms_g1.size() + temporary_terms_g2.size() + temporary_terms_g3.size(),
dynamic_basename + "_g2_tt",
init_output, end_output,
third_derivatives_output, third_derivatives_tt_output);
writeWrapperFunctions(dynamic_basename, "g3");
writeDynamicMatlabCompatLayer(dynamic_basename);
}
else if (output_type == oCDynamicModel)
{
DynamicOutput << "void Dynamic(double *y, double *x, int nb_row_x, double *params, double *steady_state, int it_, double *residual, double *g1, double *v2, double *v3)" << endl
<< "{" << endl
<< " double lhs, rhs;" << endl
<< endl
<< " /* Residual equations */" << endl
<< model_tt_output.str()
<< model_output.str()
<< " /* Jacobian */" << endl
<< " if (g1 == NULL)" << endl
<< " return;" << endl
<< endl
<< jacobian_tt_output.str()
<< jacobian_output.str()
<< endl;
if (second_derivatives.size())
DynamicOutput << " /* Hessian for endogenous and exogenous variables */" << endl
<< " if (v2 == NULL)" << endl
<< " return;" << endl
<< endl
<< hessian_tt_output.str()
<< hessian_output.str()
<< endl;
if (third_derivatives.size())
DynamicOutput << " /* Third derivatives for endogenous and exogenous variables */" << endl
<< " if (v3 == NULL)" << endl
<< " return;" << endl
<< endl
<< third_derivatives_tt_output.str()
<< third_derivatives_output.str()
<< endl;
DynamicOutput << "}" << endl << endl;
}
else
{
string filename = dynamic_basename + "Dynamic.jl";
ofstream output;
output.open(filename.c_str(), ios::out | ios::binary);
if (!output.is_open())
{
cerr << "Error: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
output << "module " << dynamic_basename << "Dynamic" << endl
<< "#" << endl
<< "# NB: this file was automatically generated by Dynare" << endl
<< "# from " << dynamic_basename << ".mod" << endl
<< "#" << endl
<< "using Utils" << endl << endl
<< "export tmp_nbr, dynamic!, dynamicResid!, dynamicG1!, dynamicG2!, dynamicG3!" << endl << endl
<< "#=" << endl
<< "# The comments below apply to all functions contained in this module #" << endl
<< " NB: The arguments contained on the first line of the function" << endl
<< " definition are those that are modified in place" << endl << endl
<< "## Exported Functions ##" << endl
<< " dynamic! : Wrapper function; computes residuals, Jacobian, Hessian," << endl
<< " and third derivatives depending on the arguments provided" << endl << " dynamicResid! : Computes the dynamic model residuals" << endl
<< " dynamicG1! : Computes the dynamic model Jacobian" << endl
<< " dynamicG2! : Computes the dynamic model Hessian" << endl
<< " dynamicG3! : Computes the dynamic model third derivatives" << endl << endl
<< "## Exported Variables ##" << endl
<< " tmp_nbr : Vector{Int}(4) respectively the number of temporary variables" << endl
<< " for the residuals, g1, g2 and g3." << endl << endl
<< "## Local Functions ##" << endl
<< " dynamicResidTT! : Computes the dynamic model temporary terms for the residuals" << endl
<< " dynamicG1TT! : Computes the dynamic model temporary terms for the Jacobian" << endl
<< " dynamicG2TT! : Computes the dynamic model temporary terms for the Hessian" << endl
<< " dynamicG3TT! : Computes the dynamic model temporary terms for the third derivatives" << endl << endl
<< "## Function Arguments ##" << endl
<< " T : Vector{Float64}(num_temp_terms), temporary terms" << endl
<< " y : Vector{Float64}(num_dynamic_vars), endogenous variables in the order stored model_.lead_lag_incidence; see the manual" << endl
<< " x : Matrix{Float64}(nperiods,model_.exo_nbr), exogenous variables (in declaration order) for all simulation periods" << endl
<< " params : Vector{Float64}(model_.param_nbr), parameter values in declaration order" << endl
<< " steady_state : Vector{Float64}(model_endo_nbr)" << endl
<< " it_ : Int, time period for exogenous variables for which to evaluate the model" << endl
<< " residual : Vector{Float64}(model_.eq_nbr), residuals of the dynamic model equations in order of declaration of the equations." << endl
<< " g1 : Matrix{Float64}(model_.eq_nbr, num_dynamic_vars), Jacobian matrix of the dynamic model equations" << endl
<< " The rows and columns respectively correspond to equations in order of declaration and variables in order" << endl
<< " stored in model_.lead_lag_incidence" << endl
<< " g2 : spzeros(model_.eq_nbr, (num_dynamic_vars)^2) Hessian matrix of the dynamic model equations" << endl
<< " The rows and columns respectively correspond to equations in order of declaration and variables in order" << endl
<< " stored in model_.lead_lag_incidence" << endl
<< " g3 : spzeros(model_.eq_nbr, (num_dynamic_vars)^3) Third order derivative matrix of the dynamic model equations;" << endl
<< " The rows and columns respectively correspond to equations in order of declaration and variables in order" << endl
<< " stored in model_.lead_lag_incidence" << endl << endl
<< "## Remarks ##" << endl
<< " [1] `num_dynamic_vars` is the number of non zero entries in the lead lag incidence matrix, `model_.lead_lag_incidence.`" << endl
<< " [2] The size of `T`, ie the value of `num_temp_terms`, depends on the version of the dynamic model called. The number of temporary variables" << endl
<< " used for the different returned objects (residuals, jacobian, hessian or third order derivatives) is given by the elements in `tmp_nbr`" << endl
<< " exported vector. The first element is the number of temporaries used for the computation of the residuals, the second element is the" << endl
<< " number of temporaries used for the evaluation of the jacobian matrix, etc. If one calls the version of the dynamic model computing the" << endl
<< " residuals, the jacobian and hessian matrices, then `T` must have at least `sum(tmp_nbr[1:3])` elements." << endl
<< "=#" << endl << endl;
// Write the number of temporary terms
output << "tmp_nbr = zeros(Int,4)" << endl
<< "tmp_nbr[1] = " << temporary_terms_mlv.size() + temporary_terms_res.size() << "# Number of temporary terms for the residuals" << endl
<< "tmp_nbr[2] = " << temporary_terms_g1.size() << "# Number of temporary terms for g1 (jacobian)" << endl
<< "tmp_nbr[3] = " << temporary_terms_g2.size() << "# Number of temporary terms for g2 (hessian)" << endl
<< "tmp_nbr[4] = " << temporary_terms_g3.size() << "# Number of temporary terms for g3 (third order derivates)" << endl << endl;
// dynamicResidTT!
output << "function dynamicResidTT!(T::Vector{Float64}," << endl
<< " y::Vector{Float64}, x::Matrix{Float64}, "
<< "params::Vector{Float64}, steady_state::Vector{Float64}, it_::Int)" << endl
<< model_tt_output.str()
<< " return nothing" << endl
<< "end" << endl << endl;
// dynamic!
output << "function dynamicResid!(T::Vector{Float64}, residual::Vector{Float64}," << endl
<< " y::Vector{Float64}, x::Matrix{Float64}, "
<< "params::Vector{Float64}, steady_state::Vector{Float64}, it_::Int, T_flag::Bool)" << endl
<< " @assert length(T) >= " << temporary_terms_mlv.size() + temporary_terms_res.size() << endl
<< " @assert length(residual) == " << nrows << endl
<< " @assert length(y)+size(x, 2) == " << dynJacobianColsNbr << endl
<< " @assert length(params) == " << symbol_table.param_nbr() << endl
<< " if T_flag" << endl
<< " dynamicResidTT!(T, y, x, params, steady_state, it_)" << endl
<< " end" << endl
<< model_output.str()
<< " return nothing" << endl
<< "end" << endl << endl;
// dynamicG1TT!
output << "function dynamicG1TT!(T::Vector{Float64}," << endl << " y::Vector{Float64}, x::Matrix{Float64}, "
<< "params::Vector{Float64}, steady_state::Vector{Float64}, it_::Int)" << endl
<< " dynamicResidTT!(T, y, x, params, steady_state, it_)" << endl
<< jacobian_tt_output.str()
<< " return nothing" << endl
<< "end" << endl << endl;
// dynamicG1!
output << "function dynamicG1!(T::Vector{Float64}, g1::Matrix{Float64}," << endl
<< " y::Vector{Float64}, x::Matrix{Float64}, "
<< "params::Vector{Float64}, steady_state::Vector{Float64}, it_::Int, T_flag::Bool)" << endl
<< " @assert length(T) >= "
<< temporary_terms_mlv.size() + temporary_terms_res.size() + temporary_terms_g1.size() << endl
<< " @assert size(g1) == (" << nrows << ", " << dynJacobianColsNbr << ")" << endl
<< " @assert length(y)+size(x, 2) == " << dynJacobianColsNbr << endl
<< " @assert length(params) == " << symbol_table.param_nbr() << endl
<< " if T_flag" << endl
<< " dynamicG1TT!(T, y, x, params, steady_state, it_)" << endl
<< " end" << endl
<< " fill!(g1, 0.0)" << endl
<< jacobian_output.str()
<< " return nothing" << endl
<< "end" << endl << endl;
// dynamicG2TT!
output << "function dynamicG2TT!(T::Vector{Float64}," << endl
<< " y::Vector{Float64}, x::Matrix{Float64}, "
<< "params::Vector{Float64}, steady_state::Vector{Float64}, it_::Int)" << endl
<< " dynamicG1TT!(T, y, x, params, steady_state, it_)" << endl
<< hessian_tt_output.str()
<< " return nothing" << endl
<< "end" << endl << endl;
// dynamicG2!
output << "function dynamicG2!(T::Vector{Float64}, g2::Matrix{Float64}," << endl
<< " y::Vector{Float64}, x::Matrix{Float64}, "
<< "params::Vector{Float64}, steady_state::Vector{Float64}, it_::Int, T_flag::Bool)" << endl
<< " @assert length(T) >= " << temporary_terms_mlv.size() + temporary_terms_res.size() + temporary_terms_g1.size() + temporary_terms_g2.size() << endl
<< " @assert size(g2) == (" << nrows << ", " << hessianColsNbr << ")" << endl
<< " @assert length(y)+size(x, 2) == " << dynJacobianColsNbr << endl
<< " @assert length(params) == " << symbol_table.param_nbr() << endl
<< " if T_flag" << endl
<< " dynamicG2TT!(T, y, x, params, steady_state, it_)" << endl
<< " end" << endl
<< " fill!(g2, 0.0)" << endl
<< hessian_output.str()
<< " return nothing" << endl
<< "end" << endl << endl;
// dynamicG3TT!
output << "function dynamicG3TT!(T::Vector{Float64}," << endl
<< " y::Vector{Float64}, x::Matrix{Float64}, "
<< "params::Vector{Float64}, steady_state::Vector{Float64}, it_::Int)" << endl
<< " dynamicG2TT!(T, y, x, params, steady_state, it_)" << endl
<< third_derivatives_tt_output.str()
<< " return nothing" << endl
<< "end" << endl << endl;
// dynamicG3!
int ncols = hessianColsNbr * dynJacobianColsNbr;
output << "function dynamicG3!(T::Vector{Float64}, g3::Matrix{Float64}," << endl
<< " y::Vector{Float64}, x::Matrix{Float64}, "
<< "params::Vector{Float64}, steady_state::Vector{Float64}, it_::Int, T_flag::Bool)" << endl
<< " @assert length(T) >= "
<< temporary_terms_mlv.size() + temporary_terms_res.size() + temporary_terms_g1.size() + temporary_terms_g2.size() + temporary_terms_g3.size() << endl
<< " @assert size(g3) == (" << nrows << ", " << ncols << ")" << endl
<< " @assert length(y)+size(x, 2) == " << dynJacobianColsNbr << endl
<< " @assert length(params) == " << symbol_table.param_nbr() << endl
<< " if T_flag" << endl
<< " dynamicG3TT!(T, y, x, params, steady_state, it_)" << endl << " end" << endl
<< " fill!(g3, 0.0)" << endl
<< third_derivatives_output.str()
<< " return nothing" << endl
<< "end" << endl << endl;
// dynamic!
output << "function dynamic!(T::Vector{Float64}, residual::Vector{Float64}," << endl
<< " y::Vector{Float64}, x::Matrix{Float64}, "
<< "params::Vector{Float64}, steady_state::Vector{Float64}, it_::Int)" << endl
<< " dynamicResid!(T, residual, y, x, params, steady_state, it_, true)" << endl
<< " return nothing" << endl
<< "end" << endl
<< endl
<< "function dynamic!(T::Vector{Float64}, residual::Vector{Float64}, g1::Matrix{Float64}," << endl
<< " y::Vector{Float64}, x::Matrix{Float64}, "
<< "params::Vector{Float64}, steady_state::Vector{Float64}, it_::Int)" << endl
<< " dynamicG1!(T, g1, y, x, params, steady_state, it_, true)" << endl
<< " dynamicResid!(T, residual, y, x, params, steady_state, it_, false)" << endl
<< " return nothing" << endl
<< "end" << endl
<< endl
<< "function dynamic!(T::Vector{Float64}, residual::Vector{Float64}, g1::Matrix{Float64}, g2::Matrix{Float64}," << endl
<< " y::Vector{Float64}, x::Matrix{Float64}, "
<< "params::Vector{Float64}, steady_state::Vector{Float64}, it_::Int)" << endl
<< " dynamicG2!(T, g2, y, x, params, steady_state, it_, true)" << endl
<< " dynamicG1!(T, g1, y, x, params, steady_state, it_, false)" << endl
<< " dynamicResid!(T, residual, y, x, params, steady_state, it_, false)" << endl
<< " return nothing" << endl
<< "end" << endl
<< endl
<< "function dynamic!(T::Vector{Float64}, residual::Vector{Float64}, g1::Matrix{Float64}, g2::Matrix{Float64}, g3::Matrix{Float64}," << endl
<< " y::Vector{Float64}, x::Matrix{Float64}, "
<< "params::Vector{Float64}, steady_state::Vector{Float64}, it_::Int)" << endl
<< " dynamicG3!(T, g3, y, x, params, steady_state, it_, true)" << endl
<< " dynamicG2!(T, g2, y, x, params, steady_state, it_, false)" << endl
<< " dynamicG1!(T, g1, y, x, params, steady_state, it_, false)" << endl
<< " dynamicResid!(T, residual, y, x, params, steady_state, it_, false)" << endl
<< " return nothing" << endl
<< "end" << endl
<< "end" << endl;
output.close();
}
}
void
DynamicModel::writeOutput(ostream &output, const string &basename, bool block_decomposition, bool byte_code, bool use_dll, int order, bool estimation_present, bool compute_xrefs, bool julia) const
{
/* Writing initialisation for M_.lead_lag_incidence matrix
M_.lead_lag_incidence is a matrix with as many columns as there are
endogenous variables and as many rows as there are periods in the
models (nbr of rows = M_.max_lag+M_.max_lead+1)
The matrix elements are equal to zero if a variable isn't present in the
model at a given period.
*/
string modstruct;
string outstruct;
if (julia)
{
modstruct = "model_.";
outstruct = "oo_.";
}
else
{
modstruct = "M_.";
outstruct = "oo_.";
}
output << modstruct << "orig_maximum_endo_lag = " << max_endo_lag_orig << ";" << endl
<< modstruct << "orig_maximum_endo_lead = " << max_endo_lead_orig << ";" << endl
<< modstruct << "orig_maximum_exo_lag = " << max_exo_lag_orig << ";" << endl
<< modstruct << "orig_maximum_exo_lead = " << max_exo_lead_orig << ";" << endl
<< modstruct << "orig_maximum_exo_det_lag = " << max_exo_det_lag_orig << ";" << endl
<< modstruct << "orig_maximum_exo_det_lead = " << max_exo_det_lead_orig << ";" << endl
<< modstruct << "orig_maximum_lag = " << max_lag_orig << ";" << endl
<< modstruct << "orig_maximum_lead = " << max_lead_orig << ";" << endl
<< modstruct << "lead_lag_incidence = [";
// Loop on endogenous variables
int nstatic = 0,
nfwrd = 0,
npred = 0,
nboth = 0;
for (int endoID = 0; endoID < symbol_table.endo_nbr(); endoID++)
{
output << endl;
int sstatic = 1,
sfwrd = 0,
spred = 0,
sboth = 0;
// Loop on periods
for (int lag = -max_endo_lag; lag <= max_endo_lead; lag++)
{
// Print variableID if exists with current period, otherwise print 0
try
{
int varID = getDerivID(symbol_table.getID(eEndogenous, endoID), lag);
output << " " << getDynJacobianCol(varID) + 1;
if (lag == -1)
{
sstatic = 0;
spred = 1;
}
else if (lag == 1)
{
if (spred == 1)
{
sboth = 1;
spred = 0;
}
else
{
sstatic = 0;
sfwrd = 1;
}
}
}
catch (UnknownDerivIDException &e)
{
output << " 0";
}
}
nstatic += sstatic;
nfwrd += sfwrd;
npred += spred;
nboth += sboth;
output << ";";
}
output << "]';" << endl;
output << modstruct << "nstatic = " << nstatic << ";" << endl
<< modstruct << "nfwrd = " << nfwrd << ";" << endl
<< modstruct << "npred = " << npred << ";" << endl
<< modstruct << "nboth = " << nboth << ";" << endl
<< modstruct << "nsfwrd = " << nfwrd+nboth << ";" << endl
<< modstruct << "nspred = " << npred+nboth << ";" << endl
<< modstruct << "ndynamic = " << npred+nboth+nfwrd << ";" << endl;
if (!julia)
output << modstruct << "dynamic_tmp_nbr = zeros(4,1); % Number of temporaries used for the dynamic model" << endl
<< modstruct << "dynamic_tmp_nbr(1) = " << temporary_terms_res.size() << "; % Number of temporaries used for the evaluation of the residuals" << endl << modstruct << "dynamic_tmp_nbr(2) = " << temporary_terms_g1.size() << "; % Number of temporaries used for the evaluation of g1 (jacobian)" << endl
<< modstruct << "dynamic_tmp_nbr(3) = " << temporary_terms_g2.size() << "; % Number of temporaries used for the evaluation of g2 (hessian)" << endl
<< modstruct << "dynamic_tmp_nbr(4) = " << temporary_terms_g3.size() << "; % Number of temporaries used for the evaluation of g3 (third order derivatives)" << endl;
// Write equation tags
if (julia)
{
output << modstruct << "equation_tags = [" << endl;
for (const auto & equation_tag : equation_tags)
output << " EquationTag("
<< equation_tag.first + 1 << " , \""
<< equation_tag.second.first << "\" , \""
<< equation_tag.second.second << "\")" << endl;
output << " ]" << endl;
}
else
{
output << modstruct << "equations_tags = {" << endl;
for (const auto & equation_tag : equation_tags)
output << " " << equation_tag.first + 1 << " , '"
<< equation_tag.second.first << "' , '"
<< equation_tag.second.second << "' ;" << endl;
output << "};" << endl;
}
/* Say if static and dynamic models differ (because of [static] and [dynamic]
equation tags) */
output << modstruct << "static_and_dynamic_models_differ = "
<< (static_only_equations.size() > 0 ?
(julia ? "true" : "1") :
(julia ? "false" : "0"))
<< ";" << endl;
vector<int> state_var;
for (int endoID = 0; endoID < symbol_table.endo_nbr(); endoID++)
// Loop on periods
for (int lag = -max_endo_lag; lag < 0; lag++)
try
{
getDerivID(symbol_table.getID(eEndogenous, variable_reordered[endoID]), lag);
if (lag < 0 && find(state_var.begin(), state_var.end(), variable_reordered[endoID]+1) == state_var.end())
state_var.push_back(variable_reordered[endoID]+1);
}
catch (UnknownDerivIDException &e)
{
}
//In case of sparse model, writes the block_decomposition structure of the model
if (block_decomposition)
{
vector<int> state_equ;
int count_lead_lag_incidence = 0;
int max_lead, max_lag, max_lag_endo, max_lead_endo, max_lag_exo, max_lead_exo, max_lag_exo_det, max_lead_exo_det;
unsigned int nb_blocks = getNbBlocks();
for (unsigned int block = 0; block < nb_blocks; block++)
{
//For a block composed of a single equation determines wether we have to evaluate or to solve the equation
count_lead_lag_incidence = 0;
BlockSimulationType simulation_type = getBlockSimulationType(block);
int block_size = getBlockSize(block);
max_lag = max_leadlag_block[block].first;
max_lead = max_leadlag_block[block].second;
max_lag_endo = endo_max_leadlag_block[block].first;
max_lead_endo = endo_max_leadlag_block[block].second;
max_lag_exo = exo_max_leadlag_block[block].first;
max_lead_exo = exo_max_leadlag_block[block].second;
max_lag_exo_det = exo_det_max_leadlag_block[block].first;
max_lead_exo_det = exo_det_max_leadlag_block[block].second;
ostringstream tmp_s, tmp_s_eq;
tmp_s.str(""); tmp_s_eq.str("");
for (int i = 0; i < block_size; i++)
{
tmp_s << " " << getBlockVariableID(block, i)+1;
tmp_s_eq << " " << getBlockEquationID(block, i)+1;
}
set<int> exogenous;
exogenous.clear();
for (const auto & it : exo_block[block])
for (auto it1 = it.second.begin(); it1 != it.second.end(); it1++)
exogenous.insert(*it1);
set<int> exogenous_det;
exogenous_det.clear();
for (const auto & it : exo_det_block[block])
for (auto it1 = it.second.begin(); it1 != it.second.end(); it1++)
exogenous_det.insert(*it1);
set<int> other_endogenous;
other_endogenous.clear();
for (const auto & it : other_endo_block[block])
for (auto it1 = it.second.begin(); it1 != it.second.end(); it1++)
other_endogenous.insert(*it1);
output << "block_structure.block(" << block+1 << ").Simulation_Type = " << simulation_type << ";\n";
output << "block_structure.block(" << block+1 << ").maximum_lag = " << max_lag << ";\n";
output << "block_structure.block(" << block+1 << ").maximum_lead = " << max_lead << ";\n";
output << "block_structure.block(" << block+1 << ").maximum_endo_lag = " << max_lag_endo << ";\n";
output << "block_structure.block(" << block+1 << ").maximum_endo_lead = " << max_lead_endo << ";\n";
output << "block_structure.block(" << block+1 << ").maximum_exo_lag = " << max_lag_exo << ";\n";
output << "block_structure.block(" << block+1 << ").maximum_exo_lead = " << max_lead_exo << ";\n";
output << "block_structure.block(" << block+1 << ").maximum_exo_det_lag = " << max_lag_exo_det << ";\n";
output << "block_structure.block(" << block+1 << ").maximum_exo_det_lead = " << max_lead_exo_det << ";\n";
output << "block_structure.block(" << block+1 << ").endo_nbr = " << block_size << ";\n";
output << "block_structure.block(" << block+1 << ").mfs = " << getBlockMfs(block) << ";\n";
output << "block_structure.block(" << block+1 << ").equation = [" << tmp_s_eq.str() << "];\n";
output << "block_structure.block(" << block+1 << ").variable = [" << tmp_s.str() << "];\n";
output << "block_structure.block(" << block+1 << ").exo_nbr = " << getBlockExoSize(block) << ";\n";
output << "block_structure.block(" << block+1 << ").exogenous = [";
int i = 0;
for (int exogenou : exogenous)
if (exogenou >= 0)
{
output << " " << exogenou+1;
i++;
}
output << "];\n";
output << "block_structure.block(" << block+1 << ").exogenous_det = [";
i = 0;
for (int it_exogenous_det : exogenous_det)
if (it_exogenous_det >= 0)
{
output << " " << it_exogenous_det+1;
i++;
}
output << "];\n";
output << "block_structure.block(" << block+1 << ").exo_det_nbr = " << i << ";\n";
output << "block_structure.block(" << block+1 << ").other_endogenous = [";
i = 0;
for (int other_endogenou : other_endogenous)
if (other_endogenou >= 0)
{
output << " " << other_endogenou+1;
i++;
}
output << "];\n";
output << "block_structure.block(" << block+1 << ").other_endogenous_block = [";
i = 0;
for (int other_endogenou : other_endogenous)
if (other_endogenou >= 0)
{ bool OK = true;
unsigned int j;
for (j = 0; j < block && OK; j++)
for (unsigned int k = 0; k < getBlockSize(j) && OK; k++)
{
//printf("*it_other_endogenous=%d, getBlockVariableID(%d, %d)=%d\n",*it_other_endogenous, j, k, getBlockVariableID(j, k));
OK = other_endogenou != getBlockVariableID(j, k);
}
if (!OK)
output << " " << j;
i++;
}
output << "];\n";
//vector<int> inter_state_var;
output << "block_structure.block(" << block+1 << ").tm1 = zeros(" << i << ", " << state_var.size() << ");\n";
int count_other_endogenous = 1;
for (int other_endogenou : other_endogenous)
{
for (vector<int>::const_iterator it = state_var.begin(); it != state_var.end(); it++)
{
//cout << "block = " << block+1 << " state_var = " << *it << " it_other_endogenous=" << *it_other_endogenous + 1 << "\n";
if (*it == other_endogenou + 1)
{
output << "block_structure.block(" << block+1 << ").tm1("
<< count_other_endogenous << ", "
<< it - state_var.begin()+1 << ") = 1;\n";
/*output << "block_structure.block(" << block+1 << ").tm1("
<< it - state_var.begin()+1 << ", "
<< count_other_endogenous << ") = 1;\n";*/
//cout << "=>\n";
}
}
count_other_endogenous++;
}
output << "block_structure.block(" << block+1 << ").other_endo_nbr = " << i << ";\n";
tmp_s.str("");
count_lead_lag_incidence = 0;
dynamic_jacob_map_t reordered_dynamic_jacobian;
for (const auto & it : blocks_derivatives[block])
reordered_dynamic_jacobian[{ it.second.first, { it.first.second, it.first.first } }] = it.second.second;
output << "block_structure.block(" << block+1 << ").lead_lag_incidence = [];\n";
int last_var = -1;
vector<int> local_state_var;
vector<int> local_stat_var;
int n_static = 0, n_backward = 0, n_forward = 0, n_mixed = 0;
for (int lag = -1; lag < 1+1; lag++)
{
last_var = -1;
for (dynamic_jacob_map_t::const_iterator it = reordered_dynamic_jacobian.begin(); it != reordered_dynamic_jacobian.end(); it++)
{
if (lag == it->first.first && last_var != it->first.second.first)
{
if (lag == -1)
{
local_state_var.push_back(getBlockVariableID(block, it->first.second.first)+1);
n_backward++;
}
else if (lag == 0)
{
if (find(local_state_var.begin(), local_state_var.end(), getBlockVariableID(block, it->first.second.first)+1) == local_state_var.end())
{
local_stat_var.push_back(getBlockVariableID(block, it->first.second.first)+1);
n_static++;
}
}
else
{ if (find(local_state_var.begin(), local_state_var.end(), getBlockVariableID(block, it->first.second.first)+1) != local_state_var.end())
{
n_backward--;
n_mixed++;
}
else
{
if (find(local_stat_var.begin(), local_stat_var.end(), getBlockVariableID(block, it->first.second.first)+1) != local_stat_var.end())
n_static--;
n_forward++;
}
}
count_lead_lag_incidence++;
for (int i = last_var; i < it->first.second.first-1; i++)
tmp_s << " 0";
if (tmp_s.str().length())
tmp_s << " ";
tmp_s << count_lead_lag_incidence;
last_var = it->first.second.first;
}
}
for (int i = last_var + 1; i < block_size; i++)
tmp_s << " 0";
output << "block_structure.block(" << block+1 << ").lead_lag_incidence = [ block_structure.block(" << block+1 << ").lead_lag_incidence; " << tmp_s.str() << "]; %lag = " << lag << "\n";
tmp_s.str("");
}
vector<int> inter_state_var;
for (vector<int>::const_iterator it_l = local_state_var.begin(); it_l != local_state_var.end(); it_l++)
for (vector<int>::const_iterator it = state_var.begin(); it != state_var.end(); it++)
if (*it == *it_l)
inter_state_var.push_back(it - state_var.begin()+1);
output << "block_structure.block(" << block+1 << ").sorted_col_dr_ghx = [";
for (vector<int>::const_iterator it = inter_state_var.begin(); it != inter_state_var.end(); it++)
output << *it << " ";
output << "];\n";
count_lead_lag_incidence = 0;
output << "block_structure.block(" << block+1 << ").lead_lag_incidence_other = [];\n";
for (int lag = -1; lag <= 1; lag++)
{
tmp_s.str("");
for (int other_endogenou : other_endogenous)
{
bool done = false;
for (int i = 0; i < block_size; i++)
{
unsigned int eq = getBlockEquationID(block, i);
auto it = derivative_other_endo[block].find({ lag, { eq, other_endogenou } });
if (it != derivative_other_endo[block].end())
{
count_lead_lag_incidence++;
tmp_s << " " << count_lead_lag_incidence;
done = true;
break;
}
}
if (!done)
tmp_s << " 0";
}
output << "block_structure.block(" << block+1 << ").lead_lag_incidence_other = [ block_structure.block(" << block+1 << ").lead_lag_incidence_other; " << tmp_s.str() << "]; %lag = " << lag << "\n";
}
output << "block_structure.block(" << block+1 << ").n_static = " << n_static << ";\n";
output << "block_structure.block(" << block+1 << ").n_forward = " << n_forward << ";\n";
output << "block_structure.block(" << block+1 << ").n_backward = " << n_backward << ";\n";
output << "block_structure.block(" << block+1 << ").n_mixed = " << n_mixed << ";\n";
}
output << modstruct << "block_structure.block = block_structure.block;\n";
string cst_s;
int nb_endo = symbol_table.endo_nbr();
output << modstruct << "block_structure.variable_reordered = [";
for (int i = 0; i < nb_endo; i++) output << " " << variable_reordered[i]+1;
output << "];\n";
output << modstruct << "block_structure.equation_reordered = [";
for (int i = 0; i < nb_endo; i++)
output << " " << equation_reordered[i]+1;
output << "];\n";
vector<int> variable_inv_reordered(nb_endo);
for (int i = 0; i < nb_endo; i++)
variable_inv_reordered[variable_reordered[i]] = i;
for (vector<int>::const_iterator it = state_var.begin(); it != state_var.end(); it++)
state_equ.push_back(equation_reordered[variable_inv_reordered[*it - 1]]+1);
map<pair< int, pair<int, int>>, int> lag_row_incidence;
for (const auto & first_derivative : first_derivatives)
{
int deriv_id = first_derivative.first.second;
if (getTypeByDerivID(deriv_id) == eEndogenous)
{
int eq = first_derivative.first.first;
int symb = getSymbIDByDerivID(deriv_id);
int var = symbol_table.getTypeSpecificID(symb);
int lag = getLagByDerivID(deriv_id);
lag_row_incidence[{ lag, { eq, var } }] = 1;
}
}
int prev_lag = -1000000;
for (map<pair< int, pair<int, int>>, int>::const_iterator it = lag_row_incidence.begin(); it != lag_row_incidence.end(); it++)
{
if (prev_lag != it->first.first)
{
if (prev_lag != -1000000)
output << "];\n";
prev_lag = it->first.first;
output << modstruct << "block_structure.incidence(" << max_endo_lag+it->first.first+1 << ").lead_lag = " << prev_lag << ";\n";
output << modstruct << "block_structure.incidence(" << max_endo_lag+it->first.first+1 << ").sparse_IM = [";
}
output << it->first.second.first+1 << " " << it->first.second.second+1 << ";\n";
}
output << "];\n";
if (estimation_present)
{
ofstream KF_index_file;
string main_name = basename;
main_name += ".kfi";
KF_index_file.open(main_name.c_str(), ios::out | ios::binary | ios::ate);
int n_obs = symbol_table.observedVariablesNbr();
int n_state = state_var.size();
for (vector<int>::const_iterator it = state_var.begin(); it != state_var.end(); it++)
if (symbol_table.isObservedVariable(symbol_table.getID(eEndogenous, *it-1)))
n_obs--;
int n = n_obs + n_state;
output << modstruct << "nobs_non_statevar = " << n_obs << ";" << endl;
int nb_diag = 0;
//map<pair<int,int>, int>::const_iterator row_state_var_incidence_it = row_state_var_incidence.begin();
vector<int> i_nz_state_var(n);
for (int i = 0; i < n_obs; i++)
i_nz_state_var[i] = n;
unsigned int lp = n_obs;
for (unsigned int block = 0; block < nb_blocks; block++)
{
int block_size = getBlockSize(block);
int nze = 0;
for (int i = 0; i < block_size; i++)
{ int var = getBlockVariableID(block, i);
vector<int>::const_iterator it_state_var = find(state_var.begin(), state_var.end(), var+1);
if (it_state_var != state_var.end())
nze++;
}
if (block == 0)
{
set<pair<int, int>> row_state_var_incidence;
for (auto it = blocks_derivatives[block].begin(); it != (blocks_derivatives[block]).end(); it++)
{
vector<int>::const_iterator it_state_var = find(state_var.begin(), state_var.end(), getBlockVariableID(block, it->first.second)+1);
if (it_state_var != state_var.end())
{
vector<int>::const_iterator it_state_equ = find(state_equ.begin(), state_equ.end(), getBlockEquationID(block, it->first.first)+1);
if (it_state_equ != state_equ.end())
row_state_var_incidence.emplace(it_state_equ - state_equ.begin(), it_state_var - state_var.begin());
}
}
/*tmp_block_endo_derivative[make_pair(it->second.first, make_pair(it->first.second, it->first.first))] = it->second.second;
if (block == 0)
{
vector<int>::const_iterator it_state_equ = find(state_equ.begin(), state_equ.end(), getBlockEquationID(block, i)+1);
if (it_state_equ != state_equ.end())
{
cout << "row_state_var_incidence[make_pair([" << *it_state_equ << "] " << it_state_equ - state_equ.begin() << ", [" << *it_state_var << "] " << it_state_var - state_var.begin() << ")] = 1;\n";
row_state_var_incidence.insert(make_pair(it_state_equ - state_equ.begin(), it_state_var - state_var.begin()));
}
}*/
auto row_state_var_incidence_it = row_state_var_incidence.begin();
bool diag = true;
int nb_diag_r = 0;
while (row_state_var_incidence_it != row_state_var_incidence.end() && diag)
{
diag = (row_state_var_incidence_it->first == row_state_var_incidence_it->second);
if (diag)
{
int equ = row_state_var_incidence_it->first;
row_state_var_incidence_it++;
if (equ != row_state_var_incidence_it->first)
nb_diag_r++;
}
}
set<pair<int, int>> col_state_var_incidence;
for (const auto & row_state_var_incidence_it : row_state_var_incidence)
col_state_var_incidence.emplace(row_state_var_incidence_it.second, row_state_var_incidence_it.first);
auto col_state_var_incidence_it = col_state_var_incidence.begin();
diag = true;
int nb_diag_c = 0;
while (col_state_var_incidence_it != col_state_var_incidence.end() && diag)
{
diag = (col_state_var_incidence_it->first == col_state_var_incidence_it->second);
if (diag)
{
int var = col_state_var_incidence_it->first;
col_state_var_incidence_it++;
if (var != col_state_var_incidence_it->first)
nb_diag_c++;
}
}
nb_diag = min(nb_diag_r, nb_diag_c);
row_state_var_incidence.clear();
col_state_var_incidence.clear();
}
for (int i = 0; i < nze; i++)
i_nz_state_var[lp + i] = lp + nze;
lp += nze;
} output << modstruct << "nz_state_var = [";
for (unsigned int i = 0; i < lp; i++)
output << i_nz_state_var[i] << " ";
output << "];" << endl;
output << modstruct << "n_diag = " << nb_diag << ";" << endl;
KF_index_file.write(reinterpret_cast<char *>(&nb_diag), sizeof(nb_diag));
using index_KF = pair<int, pair<int, int >>;
vector<index_KF> v_index_KF;
for (int i = 0; i < n; i++)
//int i = 0;
for (int j = n_obs; j < n; j++)
{
int j1 = j - n_obs;
int j1_n_state = j1 * n_state - n_obs;
if ((i < n_obs) || (i >= nb_diag + n_obs) || (j1 >= nb_diag))
for (int k = n_obs; k < i_nz_state_var[i]; k++)
{
v_index_KF.emplace_back(i + j1 * n, make_pair(i + k * n, k + j1_n_state));
}
}
int size_v_index_KF = v_index_KF.size();
KF_index_file.write(reinterpret_cast<char *>(&size_v_index_KF), sizeof(size_v_index_KF));
for (auto & it : v_index_KF)
KF_index_file.write(reinterpret_cast<char *>(&it), sizeof(index_KF));
vector<index_KF> v_index_KF_2;
int n_n_obs = n * n_obs;
for (int i = 0; i < n; i++)
//i = 0;
for (int j = i; j < n; j++)
{
if ((i < n_obs) || (i >= nb_diag + n_obs) || (j < n_obs) || (j >= nb_diag + n_obs))
for (int k = n_obs; k < i_nz_state_var[j]; k++)
{
int k_n = k * n;
v_index_KF_2.emplace_back(i * n + j, make_pair(i + k_n - n_n_obs, j + k_n));
}
}
int size_v_index_KF_2 = v_index_KF_2.size();
KF_index_file.write(reinterpret_cast<char *>(&size_v_index_KF_2), sizeof(size_v_index_KF_2));
for (auto & it : v_index_KF_2)
KF_index_file.write(reinterpret_cast<char *>(&it), sizeof(index_KF));
KF_index_file.close();
}
}
output << modstruct << "state_var = [";
for (vector<int>::const_iterator it=state_var.begin(); it != state_var.end(); it++)
output << *it << (julia ? "," : " ");
output << "];" << endl;
// Writing initialization for some other variables
if (!julia)
output << modstruct << "exo_names_orig_ord = [1:" << symbol_table.exo_nbr() << "];" << endl;
else
output << modstruct << "exo_names_orig_ord = collect(1:" << symbol_table.exo_nbr() << ");" << endl;
output << modstruct << "maximum_lag = " << max_lag << ";" << endl
<< modstruct << "maximum_lead = " << max_lead << ";" << endl;
output << modstruct << "maximum_endo_lag = " << max_endo_lag << ";" << endl
<< modstruct << "maximum_endo_lead = " << max_endo_lead << ";" << endl
<< outstruct << "steady_state = zeros(" << symbol_table.endo_nbr() << (julia ? ")" : ", 1);") << endl;
output << modstruct << "maximum_exo_lag = " << max_exo_lag << ";" << endl
<< modstruct << "maximum_exo_lead = " << max_exo_lead << ";" << endl
<< outstruct << "exo_steady_state = zeros(" << symbol_table.exo_nbr() << (julia ? ")" : ", 1);") << endl;
if (symbol_table.exo_det_nbr())
{
output << modstruct << "maximum_exo_det_lag = " << max_exo_det_lag << ";" << endl
<< modstruct << "maximum_exo_det_lead = " << max_exo_det_lead << ";" << endl
<< outstruct << "exo_det_steady_state = zeros(" << symbol_table.exo_det_nbr() << (julia ? ")" : ", 1);") << endl;
}
output << modstruct << "params = " << (julia ? "fill(NaN, " : "NaN(")
<< symbol_table.param_nbr() << (julia ? ")" : ", 1);") << endl;
if (compute_xrefs)
writeXrefs(output);
// Write number of non-zero derivatives
// Use -1 if the derivatives have not been computed
output << modstruct << (julia ? "nnzderivatives" : "NNZDerivatives")
<< " = [" << NNZDerivatives[0] << "; ";
if (order > 1)
output << NNZDerivatives[1] << "; ";
else
output << "-1; ";
if (order > 2)
output << NNZDerivatives[2];
else
output << "-1";
output << "];" << endl;
// Write PacExpectationInfo
for (auto it : pac_expectation_info)
it->ExprNode::writeOutput(output, oMatlabDynamicModel);
}
map<pair<int, pair<int, int >>, expr_t>
DynamicModel::collect_first_order_derivatives_endogenous()
{
map<pair<int, pair<int, int >>, expr_t> endo_derivatives;
for (auto & first_derivative : first_derivatives)
{
if (getTypeByDerivID(first_derivative.first.second) == eEndogenous)
{
int eq = first_derivative.first.first;
int var = symbol_table.getTypeSpecificID(getSymbIDByDerivID(first_derivative.first.second));
int lag = getLagByDerivID(first_derivative.first.second);
endo_derivatives[{ eq, { var, lag } }] = first_derivative.second;
}
}
return endo_derivatives;
}
void
DynamicModel::runTrendTest(const eval_context_t &eval_context)
{
computeDerivIDs();
testTrendDerivativesEqualToZero(eval_context);
}
void
DynamicModel::getVarModelVariablesFromEqTags(vector<string> &var_model_eqtags,
vector<int> &eqnumber,
vector<int> &lhs,
vector<expr_t> &lhs_expr_t,
vector<set<pair<int, int>>> &rhs,
vector<bool> &nonstationary) const
{
for (vector<string>::const_iterator itvareqs = var_model_eqtags.begin();
itvareqs != var_model_eqtags.end(); itvareqs++)
{
int eqn = -1; set<pair<int, int>> lhs_set, lhs_tmp_set, rhs_set;
string eqtag (*itvareqs);
for (const auto & equation_tag : equation_tags)
if (equation_tag.second.first == "name"
&& equation_tag.second.second == eqtag)
{
eqn = equation_tag.first;
break;
}
if (eqn == -1)
{
cerr << "ERROR: equation tag '" << eqtag << "' not found" << endl;
exit(EXIT_FAILURE);
}
bool nonstationary_bool = false;
for (const auto & equation_tag : equation_tags)
if (equation_tag.first == eqn)
if (equation_tag.second.first == "data_type"
&& equation_tag.second.second == "nonstationary")
{
nonstationary_bool = true;
break;
}
nonstationary.push_back(nonstationary_bool);
equations[eqn]->get_arg1()->collectDynamicVariables(eEndogenous, lhs_set);
equations[eqn]->get_arg1()->collectDynamicVariables(eExogenous, lhs_tmp_set);
equations[eqn]->get_arg1()->collectDynamicVariables(eParameter, lhs_tmp_set);
if (lhs_set.size() != 1 || !lhs_tmp_set.empty())
{
cerr << "ERROR: in Equation " << eqtag
<< ". A VAR may only have one endogenous variable on the LHS. " << endl;
exit(EXIT_FAILURE);
}
auto it = lhs_set.begin();
if (it->second != 0)
{
cerr << "ERROR: in Equation " << eqtag
<< ". The variable on the LHS of a VAR may not appear with a lead or a lag. "
<< endl;
exit(EXIT_FAILURE);
}
eqnumber.push_back(eqn);
lhs.push_back(it->first);
lhs_set.clear();
set<expr_t> lhs_expr_t_set;
equations[eqn]->get_arg1()->collectVARLHSVariable(lhs_expr_t_set);
lhs_expr_t.push_back(*(lhs_expr_t_set.begin()));
equations[eqn]->get_arg2()->collectDynamicVariables(eEndogenous, rhs_set);
for (it = rhs_set.begin(); it != rhs_set.end(); it++)
if (it->second > 0)
{
cerr << "ERROR: in Equation " << eqtag
<< ". A VAR may not have leaded or contemporaneous variables on the RHS. " << endl;
exit(EXIT_FAILURE);
}
rhs.push_back(rhs_set);
}
}
void
DynamicModel::checkVarMinLag(vector<int> &eqnumber) const
{
int eqn = 1; for (vector<int>::const_iterator it = eqnumber.begin();
it != eqnumber.end(); it++, eqn++)
{
int min_lag = -1;
min_lag = equations[*it]->get_arg2()->VarMinLag();
if (min_lag <= 0)
{
cerr << "ERROR in VAR Equation #" << eqn << ". "
<< "Leaded exogenous variables and leaded or contemporaneous endogenous variables not allowed in VAR";
exit(EXIT_FAILURE);
}
}
}
int
DynamicModel::getVarMaxLag(StaticModel &static_model, vector<int> &eqnumber) const
{
set<expr_t> lhs;
for (vector<int>::const_iterator it = eqnumber.begin();
it != eqnumber.end(); it++)
equations[*it]->get_arg1()->collectVARLHSVariable(lhs);
if (eqnumber.size() != lhs.size())
{
cerr << "The LHS variables of the VAR are not unique" << endl;
exit(EXIT_FAILURE);
}
set<expr_t> lhs_static;
for(auto lh : lhs)
lhs_static.insert(lh->toStatic(static_model));
int max_lag = 0;
for (vector<int>::const_iterator it = eqnumber.begin();
it != eqnumber.end(); it++)
max_lag = max(max_lag,
equations[*it]->get_arg2()->VarMaxLag(static_model, lhs_static));
return max_lag;
}
void
DynamicModel::getVarLhsDiffAndInfo(vector<int> &eqnumber, vector<bool> &diff,
vector<int> &orig_diff_var) const
{
for (vector<int>::const_iterator it = eqnumber.begin();
it != eqnumber.end(); it++)
{
equations[*it]->get_arg1()->countDiffs() > 0 ? diff.push_back(true) : diff.push_back(false);
if (diff.back())
{
set<pair<int, int>> diff_set;
equations[*it]->get_arg1()->collectDynamicVariables(eEndogenous, diff_set);
if (diff_set.size() != 1)
{
cerr << "ERROR: problem getting variable for LHS diff operator in equation " << *it << endl;
exit(EXIT_FAILURE);
}
orig_diff_var.push_back(diff_set.begin()->first);
}
else
orig_diff_var.push_back(-1);
}
}
void
DynamicModel::setVarExpectationIndices(map<string, pair<SymbolList, int>> &var_model_info)
{
for (auto & equation : equations) equation->setVarExpectationIndex(var_model_info);
}
void
DynamicModel::addEquationsForVar(map<string, pair<SymbolList, int>> &var_model_info)
{
// List of endogenous variables and the minimum lag value that must exist in the model equations
map<string, int> var_endos_and_lags, model_endos_and_lags;
for (map<string, pair<SymbolList, int>>::const_iterator it = var_model_info.begin();
it != var_model_info.end(); it++)
for (auto & equation : equations)
if (equation->isVarModelReferenced(it->first))
{
vector<string> symbol_list = it->second.first.get_symbols();
int order = it->second.second;
for (vector<string>::const_iterator it1 = symbol_list.begin();
it1 != symbol_list.end(); it1++)
if (order > 2)
if (var_endos_and_lags.find(*it1) != var_endos_and_lags.end())
var_endos_and_lags[*it1] = min(var_endos_and_lags[*it1], -1*order);
else
var_endos_and_lags[*it1] = -1*order;
break;
}
if (var_endos_and_lags.empty())
return;
// Ensure that the minimum lag value exists in the model equations. If not, add an equation for it
for (auto & equation : equations)
equation->getEndosAndMaxLags(model_endos_and_lags);
int count = 0;
for (map<string, int>::const_iterator it = var_endos_and_lags.begin();
it != var_endos_and_lags.end(); it++)
{
map<string, int>::const_iterator it1 = model_endos_and_lags.find(it->first);
if (it1 == model_endos_and_lags.end())
cerr << "WARNING: Variable used in VAR that is not used in the model: " << it->first << endl;
else
if (it->second < it1->second)
{
int symb_id = symbol_table.getID(it->first);
expr_t newvar = AddVariable(symb_id, it->second);
expr_t auxvar = AddVariable(symbol_table.addVarModelEndoLagAuxiliaryVar(symb_id, it->second, newvar), 0);
addEquation(AddEqual(newvar, auxvar), -1);
addAuxEquation(AddEqual(newvar, auxvar));
count++;
}
}
if (count > 0)
cout << "Accounting for var_model lags not in model block: added " << count << " auxiliary variables and equations." << endl;
}
void
DynamicModel::getUndiffLHSForPac(vector<int> &lhs, vector<expr_t> &lhs_expr_t, vector<bool> &diff, vector<int> &orig_diff_var,
vector<int> &eqnumber, map<string, int> &undiff, ExprNode::subst_table_t &diff_subst_table)
{
if (undiff.empty())
return;
for (map<string, int>::const_iterator it = undiff.begin();
it != undiff.end(); it++)
{
int eqn = -1;
string eqtag (it->first);
for (vector<pair<int, pair<string, string>>>::const_iterator iteqtag =
equation_tags.begin(); iteqtag != equation_tags.end(); iteqtag++)
if (iteqtag->second.first == "name" && iteqtag->second.second == eqtag)
{
eqn = iteqtag->first;
break;
}
if (eqn == -1)
{
cerr << "ERROR: undiff equation tag '" << eqtag << "' not found" << endl;
exit(EXIT_FAILURE);
}
int i = 0;
for (vector<int>::const_iterator it1 = eqnumber.begin();
it1 != eqnumber.end(); it1++, i++)
if (*it1 == eqn)
break;
if (eqnumber[i] != eqn)
{
cerr << "ERROR: equation " << eqn << " not found in VAR" << endl;
exit(EXIT_FAILURE);
}
if (diff.at(i) != true)
{
cerr << "ERROR: the variable on the LHS of equation #" << eqn << " (VAR equation #" << i
<< " with equation tag '" << eqtag
<< "') does not have the diff operator applied to it yet you are trying to undiff it." << endl;
exit(EXIT_FAILURE);
}
bool printerr = false;
ExprNode::subst_table_t::const_iterator it1;
expr_t node = nullptr;
expr_t aux_var = lhs_expr_t.at(i);
for (it1 = diff_subst_table.begin(); it1 != diff_subst_table.end(); it1++)
if (it1->second == aux_var)
{
node = const_cast<expr_t>(it1->first);
break;
}
if (node == nullptr)
{
cerr << "Unexpected error encountered." << endl;
exit(EXIT_FAILURE);
}
for (int j = it->second; j > 0; j--)
if (printerr)
{
cerr << "You are undiffing the LHS of equation #" << eqn << " "
<< it->second << " times but it has only been diffed " << j << " time(s)" << endl;
exit(EXIT_FAILURE);
}
else
{
node = node->undiff();
it1 = diff_subst_table.find(node);
if (it1 == diff_subst_table.end())
printerr = true;
}
if (printerr)
{ // we have undiffed something like diff(x), hence x is not in diff_subst_table
lhs_expr_t.at(i) = node;
lhs.at(i) = dynamic_cast<VariableNode *>(node)->get_symb_id();
}
else {
lhs_expr_t.at(i) = const_cast<expr_t>(it1->first);
lhs.at(i) = const_cast<VariableNode *>(it1->second)->get_symb_id();
}
}
}
void
DynamicModel::walkPacParameters()
{
for (auto & equation : equations)
{
bool pac_encountered = false;
pair<int, int> lhs (-1, -1);
set<pair<int, pair<int, int>>> params_and_vars;
set<pair<int, pair<int, int>>> ecm_params_and_vars;
equation->walkPacParameters(pac_encountered, lhs, ecm_params_and_vars, params_and_vars);
if (pac_encountered)
equation->addParamInfoToPac(lhs, ecm_params_and_vars, params_and_vars);
}
}
void
DynamicModel::fillPacExpectationVarInfo(string &var_model_name,
vector<int> &lhs,
int max_lag,
vector<bool> &nonstationary,
int growth_symb_id)
{
for (size_t i = 0; i < equations.size(); i++)
equations[i]->fillPacExpectationVarInfo(var_model_name, lhs, max_lag, nonstationary, growth_symb_id, i);
}
void
DynamicModel::substitutePacExpectation()
{
map<const PacExpectationNode *, const BinaryOpNode *> subst_table;
for (auto & it : local_variables_table)
it.second = it.second->substitutePacExpectation(subst_table);
for (auto & equation : equations)
{
auto *substeq = dynamic_cast<BinaryOpNode *>(equation->substitutePacExpectation(subst_table));
assert(substeq != nullptr);
equation = substeq;
}
for (map<const PacExpectationNode *, const BinaryOpNode *>::const_iterator it = subst_table.begin();
it != subst_table.end(); it++)
pac_expectation_info.insert(const_cast<PacExpectationNode *>(it->first));
}
void
DynamicModel::computingPass(bool jacobianExo, bool hessian, bool thirdDerivatives, int paramsDerivsOrder,
const eval_context_t &eval_context, bool no_tmp_terms, bool block, bool use_dll,
bool bytecode, const bool nopreprocessoroutput)
{
assert(jacobianExo || !(hessian || thirdDerivatives || paramsDerivsOrder));
initializeVariablesAndEquations();
// Prepare for derivation
computeDerivIDs();
// Computes dynamic jacobian columns, must be done after computeDerivIDs()
computeDynJacobianCols(jacobianExo);
// Compute derivatives w.r. to all endogenous, and possibly exogenous and exogenous deterministic
set<int> vars;
for (deriv_id_table_t::const_iterator it = deriv_id_table.begin(); it != deriv_id_table.end(); it++)
{
SymbolType type = symbol_table.getType(it->first.first);
if (type == eEndogenous || (jacobianExo && (type == eExogenous || type == eExogenousDet)))
vars.insert(it->second);
}
// Launch computations
if (!nopreprocessoroutput)
cout << "Computing dynamic model derivatives:" << endl
<< " - order 1" << endl;
computeJacobian(vars);
if (hessian)
{
if (!nopreprocessoroutput)
cout << " - order 2" << endl;
computeHessian(vars);
}
if (paramsDerivsOrder > 0)
{
if (!nopreprocessoroutput)
cout << " - derivatives of Jacobian/Hessian w.r. to parameters" << endl;
computeParamsDerivatives(paramsDerivsOrder);
if (!no_tmp_terms)
computeParamsDerivativesTemporaryTerms();
}
if (thirdDerivatives)
{
if (!nopreprocessoroutput)
cout << " - order 3" << endl;
computeThirdDerivatives(vars);
}
if (block)
{
vector<unsigned int> n_static, n_forward, n_backward, n_mixed;
jacob_map_t contemporaneous_jacobian, static_jacobian;
// for each block contains pair<Size, Feddback_variable>
vector<pair<int, int>> blocks;
evaluateAndReduceJacobian(eval_context, contemporaneous_jacobian, static_jacobian, dynamic_jacobian, cutoff, false);
computeNonSingularNormalization(contemporaneous_jacobian, cutoff, static_jacobian, dynamic_jacobian);
computePrologueAndEpilogue(static_jacobian, equation_reordered, variable_reordered);
map<pair<int, pair<int, int>>, expr_t> first_order_endo_derivatives = collect_first_order_derivatives_endogenous();
equation_type_and_normalized_equation = equationTypeDetermination(first_order_endo_derivatives, variable_reordered, equation_reordered, mfs);
if (!nopreprocessoroutput)
cout << "Finding the optimal block decomposition of the model ...\n";
lag_lead_vector_t equation_lag_lead, variable_lag_lead;
computeBlockDecompositionAndFeedbackVariablesForEachBlock(static_jacobian, dynamic_jacobian, equation_reordered, variable_reordered, blocks, equation_type_and_normalized_equation, false, true, mfs, inv_equation_reordered, inv_variable_reordered, equation_lag_lead, variable_lag_lead, n_static, n_forward, n_backward, n_mixed);
block_type_firstequation_size_mfs = reduceBlocksAndTypeDetermination(dynamic_jacobian, blocks, equation_type_and_normalized_equation, variable_reordered, equation_reordered, n_static, n_forward, n_backward, n_mixed, block_col_type);
printBlockDecomposition(blocks);
computeChainRuleJacobian(blocks_derivatives);
blocks_linear = BlockLinear(blocks_derivatives, variable_reordered);
collect_block_first_order_derivatives();
collectBlockVariables();
global_temporary_terms = true;
if (!no_tmp_terms)
computeTemporaryTermsOrdered();
int k = 0;
equation_block = vector<int>(equations.size());
variable_block_lead_lag = vector< pair< int, pair< int, int>>>(equations.size());
for (unsigned int i = 0; i < getNbBlocks(); i++)
{
for (unsigned int j = 0; j < getBlockSize(i); j++)
{
equation_block[equation_reordered[k]] = i;
int l = variable_reordered[k];
variable_block_lead_lag[l] = { i, { variable_lag_lead[l].first, variable_lag_lead[l].second } };
k++;
}
}
}
else
if (!no_tmp_terms)
{
computeTemporaryTerms(!use_dll);
if (bytecode)
computeTemporaryTermsMapping();
}
}
void
DynamicModel::computeXrefs()
{
int i = 0;
for (auto & equation : equations)
{
ExprNode::EquationInfo ei;
equation->computeXrefs(ei);
xrefs[i++] = ei;
}
i = 0;
for (map<int, ExprNode::EquationInfo>::const_iterator it = xrefs.begin();
it != xrefs.end(); it++, i++)
{
computeRevXref(xref_param, it->second.param, i);
computeRevXref(xref_endo, it->second.endo, i);
computeRevXref(xref_exo, it->second.exo, i);
computeRevXref(xref_exo_det, it->second.exo_det, i);
}
}
void
DynamicModel::computeRevXref(map<pair<int, int>, set<int>> &xrefset, const set<pair<int, int>> &eiref, int eqn)
{
for (const auto & it : eiref)
{
set<int> eq;
if (xrefset.find(it) != xrefset.end())
eq = xrefset[it];
eq.insert(eqn);
xrefset[it] = eq;
}
}
void
DynamicModel::writeXrefs(ostream &output) const
{
output << "M_.xref1.param = cell(1, M_.eq_nbr);" << endl
<< "M_.xref1.endo = cell(1, M_.eq_nbr);" << endl << "M_.xref1.exo = cell(1, M_.eq_nbr);" << endl
<< "M_.xref1.exo_det = cell(1, M_.eq_nbr);" << endl;
int i = 1;
for (auto it = xrefs.begin();
it != xrefs.end(); it++, i++)
{
output << "M_.xref1.param{" << i << "} = [ ";
for (const auto & it1 : it->second.param)
output << symbol_table.getTypeSpecificID(it1.first) + 1 << " ";
output << "];" << endl;
output << "M_.xref1.endo{" << i << "} = [ ";
for (const auto & it1 : it->second.endo)
output << "struct('id', " << symbol_table.getTypeSpecificID(it1.first) + 1 << ", 'shift', " << it1.second << ");";
output << "];" << endl;
output << "M_.xref1.exo{" << i << "} = [ ";
for (const auto & it1 : it->second.exo)
output << "struct('id', " << symbol_table.getTypeSpecificID(it1.first) + 1 << ", 'shift', " << it1.second << ");";
output << "];" << endl;
output << "M_.xref1.exo_det{" << i << "} = [ ";
for (const auto & it1 : it->second.exo_det)
output << "struct('id', " << symbol_table.getTypeSpecificID(it1.first) + 1 << ", 'shift', " << it1.second << ");";
output << "];" << endl;
}
output << "M_.xref2.param = cell(1, M_.param_nbr);" << endl
<< "M_.xref2.endo = cell(1, M_.endo_nbr);" << endl
<< "M_.xref2.exo = cell(1, M_.exo_nbr);" << endl
<< "M_.xref2.exo_det = cell(1, M_.exo_det_nbr);" << endl;
writeRevXrefs(output, xref_param, "param");
writeRevXrefs(output, xref_endo, "endo");
writeRevXrefs(output, xref_exo, "exo");
writeRevXrefs(output, xref_exo_det, "exo_det");
}
void
DynamicModel::writeRevXrefs(ostream &output, const map<pair<int, int>, set<int>> &xrefmap, const string &type) const
{
int last_tsid = -1;
for (const auto & it : xrefmap)
{
int tsid = symbol_table.getTypeSpecificID(it.first.first) + 1;
output << "M_.xref2." << type << "{" << tsid << "} = [ ";
if (last_tsid == tsid)
output << "M_.xref2." << type << "{" << tsid << "}; ";
else
last_tsid = tsid;
for (auto it1 = it.second.begin();
it1 != it.second.end(); it1++)
if (type == "param")
output << *it1 + 1 << " ";
else
output << "struct('shift', " << it.first.second << ", 'eq', " << *it1+1 << ");";
output << "];" << endl;
}
}
map<pair<pair<int, pair<int, int>>, pair<int, int>>, int>
DynamicModel::get_Derivatives(int block)
{
int max_lag, max_lead;
map<pair<pair<int, pair<int, int>>, pair<int, int>>, int> Derivatives;
Derivatives.clear();
BlockSimulationType simulation_type = getBlockSimulationType(block);
if (simulation_type == EVALUATE_BACKWARD || simulation_type == EVALUATE_FORWARD)
{
max_lag = 1; max_lead = 1;
setBlockLeadLag(block, max_lag, max_lead);
}
else
{
max_lag = getBlockMaxLag(block);
max_lead = getBlockMaxLead(block);
}
int block_size = getBlockSize(block);
int block_nb_recursive = block_size - getBlockMfs(block);
for (int lag = -max_lag; lag <= max_lead; lag++)
{
for (int eq = 0; eq < block_size; eq++)
{
int eqr = getBlockEquationID(block, eq);
for (int var = 0; var < block_size; var++)
{
int varr = getBlockVariableID(block, var);
if (dynamic_jacobian.find({ lag, { eqr, varr } }) != dynamic_jacobian.end())
{
bool OK = true;
map<pair<pair<int, pair<int, int>>, pair<int, int>>, int>::const_iterator its = Derivatives.find({ { lag, { eq, var } }, { eqr, varr } });
if (its != Derivatives.end())
{
if (its->second == 2)
OK = false;
}
if (OK)
{
if (getBlockEquationType(block, eq) == E_EVALUATE_S && eq < block_nb_recursive)
//It's a normalized equation, we have to recompute the derivative using chain rule derivative function
Derivatives[{ { lag, { eq, var } }, { eqr, varr } }] = 1;
else
//It's a feedback equation we can use the derivatives
Derivatives[{ { lag, { eq, var } }, { eqr, varr } }] = 0;
}
if (var < block_nb_recursive)
{
int eqs = getBlockEquationID(block, var);
for (int vars = block_nb_recursive; vars < block_size; vars++)
{
int varrs = getBlockVariableID(block, vars);
//A new derivative needs to be computed using the chain rule derivative function (a feedback variable appears in a recursive equation)
if (Derivatives.find({ { lag, { var, vars } }, { eqs, varrs } }) != Derivatives.end())
Derivatives[{ { lag, { eq, vars } }, { eqr, varrs } }] = 2;
}
}
}
}
}
}
return (Derivatives);
}
void
DynamicModel::computeChainRuleJacobian(blocks_derivatives_t &blocks_endo_derivatives)
{
map<int, expr_t> recursive_variables;
unsigned int nb_blocks = getNbBlocks();
blocks_endo_derivatives = blocks_derivatives_t(nb_blocks);
for (unsigned int block = 0; block < nb_blocks; block++)
{
block_derivatives_equation_variable_laglead_nodeid_t tmp_derivatives;
recursive_variables.clear();
int block_size = getBlockSize(block);
int block_nb_mfs = getBlockMfs(block);
int block_nb_recursives = block_size - block_nb_mfs;
blocks_endo_derivatives.push_back(block_derivatives_equation_variable_laglead_nodeid_t(0));
for (int i = 0; i < block_nb_recursives; i++) {
if (getBlockEquationType(block, i) == E_EVALUATE_S)
recursive_variables[getDerivID(symbol_table.getID(eEndogenous, getBlockVariableID(block, i)), 0)] = getBlockEquationRenormalizedExpr(block, i);
else
recursive_variables[getDerivID(symbol_table.getID(eEndogenous, getBlockVariableID(block, i)), 0)] = getBlockEquationExpr(block, i);
}
map<pair<pair<int, pair<int, int>>, pair<int, int>>, int> Derivatives = get_Derivatives(block);
map<pair<pair<int, pair<int, int>>, pair<int, int>>, int>::const_iterator it = Derivatives.begin();
for (int i = 0; i < (int) Derivatives.size(); i++)
{
int Deriv_type = it->second;
pair<pair<int, pair<int, int>>, pair<int, int>> it_l(it->first);
it++;
int lag = it_l.first.first;
int eq = it_l.first.second.first;
int var = it_l.first.second.second;
int eqr = it_l.second.first;
int varr = it_l.second.second;
if (Deriv_type == 0)
first_chain_rule_derivatives[{ eqr, { varr, lag } }] = first_derivatives[{ eqr, getDerivID(symbol_table.getID(eEndogenous, varr), lag) }];
else if (Deriv_type == 1)
first_chain_rule_derivatives[{ eqr, { varr, lag } }] = (equation_type_and_normalized_equation[eqr].second)->getChainRuleDerivative(getDerivID(symbol_table.getID(eEndogenous, varr), lag), recursive_variables);
else if (Deriv_type == 2)
{
if (getBlockEquationType(block, eq) == E_EVALUATE_S && eq < block_nb_recursives)
first_chain_rule_derivatives[{ eqr, { varr, lag } }] = (equation_type_and_normalized_equation[eqr].second)->getChainRuleDerivative(getDerivID(symbol_table.getID(eEndogenous, varr), lag), recursive_variables);
else
first_chain_rule_derivatives[{ eqr, { varr, lag } }] = equations[eqr]->getChainRuleDerivative(getDerivID(symbol_table.getID(eEndogenous, varr), lag), recursive_variables);
}
tmp_derivatives.emplace_back(make_pair(eq, var), make_pair(lag, first_chain_rule_derivatives[{ eqr, { varr, lag } }]));
}
blocks_endo_derivatives[block] = tmp_derivatives;
}
}
void
DynamicModel::collect_block_first_order_derivatives()
{
//! vector for an equation or a variable indicates the block number
vector<int> equation_2_block, variable_2_block;
unsigned int nb_blocks = getNbBlocks();
equation_2_block = vector<int>(equation_reordered.size());
variable_2_block = vector<int>(variable_reordered.size());
for (unsigned int block = 0; block < nb_blocks; block++)
{
unsigned int block_size = getBlockSize(block);
for (unsigned int i = 0; i < block_size; i++)
{
equation_2_block[getBlockEquationID(block, i)] = block;
variable_2_block[getBlockVariableID(block, i)] = block;
}
}
other_endo_block = vector<lag_var_t>(nb_blocks);
exo_block = vector<lag_var_t>(nb_blocks);
exo_det_block = vector<lag_var_t>(nb_blocks);
derivative_endo = vector<derivative_t>(nb_blocks);
derivative_other_endo = vector<derivative_t>(nb_blocks);
derivative_exo = vector<derivative_t>(nb_blocks);
derivative_exo_det = vector<derivative_t>(nb_blocks);
endo_max_leadlag_block = vector<pair<int, int>>(nb_blocks, { 0, 0 });
other_endo_max_leadlag_block = vector<pair<int, int>>(nb_blocks, { 0, 0 });
exo_max_leadlag_block = vector<pair<int, int>>(nb_blocks, { 0, 0 });
exo_det_max_leadlag_block = vector<pair<int, int>>(nb_blocks, { 0, 0 });
max_leadlag_block = vector<pair<int, int>>(nb_blocks, { 0, 0 });
for (auto & first_derivative : first_derivatives)
{
int eq = first_derivative.first.first;
int var = symbol_table.getTypeSpecificID(getSymbIDByDerivID(first_derivative.first.second));
int lag = getLagByDerivID(first_derivative.first.second);
int block_eq = equation_2_block[eq]; int block_var = 0;
derivative_t tmp_derivative;
lag_var_t lag_var;
switch (getTypeByDerivID(first_derivative.first.second))
{
case eEndogenous:
block_var = variable_2_block[var];
if (block_eq == block_var)
{
if (lag < 0 && lag < -endo_max_leadlag_block[block_eq].first)
endo_max_leadlag_block[block_eq] = { -lag, endo_max_leadlag_block[block_eq].second };
if (lag > 0 && lag > endo_max_leadlag_block[block_eq].second)
endo_max_leadlag_block[block_eq] = { endo_max_leadlag_block[block_eq].first, lag };
tmp_derivative = derivative_endo[block_eq];
tmp_derivative[{ lag, { eq, var } }] = first_derivatives[{ eq, getDerivID(symbol_table.getID(eEndogenous, var), lag) }];
derivative_endo[block_eq] = tmp_derivative;
}
else
{
if (lag < 0 && lag < -other_endo_max_leadlag_block[block_eq].first)
other_endo_max_leadlag_block[block_eq] = { -lag, other_endo_max_leadlag_block[block_eq].second };
if (lag > 0 && lag > other_endo_max_leadlag_block[block_eq].second)
other_endo_max_leadlag_block[block_eq] = { other_endo_max_leadlag_block[block_eq].first, lag };
tmp_derivative = derivative_other_endo[block_eq];
{
map< int, map<int, int>>::const_iterator it = block_other_endo_index.find(block_eq);
if (it == block_other_endo_index.end())
block_other_endo_index[block_eq][var] = 0;
else
{
auto it1 = it->second.find(var);
if (it1 == it->second.end())
{
int size = block_other_endo_index[block_eq].size();
block_other_endo_index[block_eq][var] = size;
}
}
}
tmp_derivative[{ lag, { eq, var } }] = first_derivatives[{ eq, getDerivID(symbol_table.getID(eEndogenous, var), lag) }];
derivative_other_endo[block_eq] = tmp_derivative;
lag_var = other_endo_block[block_eq];
if (lag_var.find(lag) == lag_var.end())
lag_var[lag].clear();
lag_var[lag].insert(var);
other_endo_block[block_eq] = lag_var;
}
break;
case eExogenous:
if (lag < 0 && lag < -exo_max_leadlag_block[block_eq].first)
exo_max_leadlag_block[block_eq] = { -lag, exo_max_leadlag_block[block_eq].second };
if (lag > 0 && lag > exo_max_leadlag_block[block_eq].second)
exo_max_leadlag_block[block_eq] = { exo_max_leadlag_block[block_eq].first, lag };
tmp_derivative = derivative_exo[block_eq];
{
map< int, map<int, int>>::const_iterator it = block_exo_index.find(block_eq);
if (it == block_exo_index.end())
block_exo_index[block_eq][var] = 0;
else
{
auto it1 = it->second.find(var);
if (it1 == it->second.end())
{
int size = block_exo_index[block_eq].size();
block_exo_index[block_eq][var] = size;
}
}
}
tmp_derivative[{ lag, { eq, var } }] = first_derivatives[{ eq, getDerivID(symbol_table.getID(eExogenous, var), lag) }];
derivative_exo[block_eq] = tmp_derivative;
lag_var = exo_block[block_eq]; if (lag_var.find(lag) == lag_var.end())
lag_var[lag].clear();
lag_var[lag].insert(var);
exo_block[block_eq] = lag_var;
break;
case eExogenousDet:
if (lag < 0 && lag < -exo_det_max_leadlag_block[block_eq].first)
exo_det_max_leadlag_block[block_eq] = { -lag, exo_det_max_leadlag_block[block_eq].second };
if (lag > 0 && lag > exo_det_max_leadlag_block[block_eq].second)
exo_det_max_leadlag_block[block_eq] = { exo_det_max_leadlag_block[block_eq].first, lag };
tmp_derivative = derivative_exo_det[block_eq];
{
map< int, map<int, int>>::const_iterator it = block_det_exo_index.find(block_eq);
if (it == block_det_exo_index.end())
block_det_exo_index[block_eq][var] = 0;
else
{
auto it1 = it->second.find(var);
if (it1 == it->second.end())
{
int size = block_det_exo_index[block_eq].size();
block_det_exo_index[block_eq][var] = size;
}
}
}
tmp_derivative[{ lag, { eq, var } }] = first_derivatives[{ eq, getDerivID(symbol_table.getID(eExogenous, var), lag) }];
derivative_exo_det[block_eq] = tmp_derivative;
lag_var = exo_det_block[block_eq];
if (lag_var.find(lag) == lag_var.end())
lag_var[lag].clear();
lag_var[lag].insert(var);
exo_det_block[block_eq] = lag_var;
break;
default:
break;
}
if (lag < 0 && lag < -max_leadlag_block[block_eq].first)
max_leadlag_block[block_eq] = { -lag, max_leadlag_block[block_eq].second };
if (lag > 0 && lag > max_leadlag_block[block_eq].second)
max_leadlag_block[block_eq] = { max_leadlag_block[block_eq].first, lag };
}
}
void
DynamicModel::collectBlockVariables()
{
for (unsigned int block = 0; block < getNbBlocks(); block++)
{
int prev_var = -1;
int prev_lag = -999999999;
int count_col_exo = 0;
var_t tmp_var_exo;
for (lag_var_t::const_iterator it = exo_block[block].begin(); it != exo_block[block].end(); it++)
{
int lag = it->first;
for (int var : it->second)
{
tmp_var_exo.insert(var);
if (prev_var != var || prev_lag != lag)
{
prev_var = var;
prev_lag = lag;
count_col_exo++;
}
}
}
block_var_exo.emplace_back(tmp_var_exo, count_col_exo);
}
}
void
DynamicModel::writeDynamicFile(const string &basename, bool block, bool bytecode, bool use_dll, int order, bool julia) const
{
int r;
string t_basename = basename + "_dynamic";
if (block && bytecode)
writeModelEquationsCode_Block(t_basename, basename, map_idx);
else if (!block && bytecode)
writeModelEquationsCode(t_basename, basename, map_idx);
else if (block && !bytecode)
{
#ifdef _WIN32
r = mkdir(basename.c_str());
#else
r = mkdir(basename.c_str(), 0777);
#endif
if (r < 0 && errno != EEXIST)
{
perror("ERROR");
exit(EXIT_FAILURE);
}
writeSparseDynamicMFile(t_basename, basename);
}
else if (use_dll)
writeDynamicCFile(t_basename, order);
else if (julia)
writeDynamicJuliaFile(basename);
else
{
writeDynamicMFile(t_basename);
writeSetAuxiliaryVariables(t_basename, julia);
}
}
void
DynamicModel::writeSetAuxiliaryVariables(const string &basename, const bool julia) const
{
ostringstream output_func_body;
writeAuxVarRecursiveDefinitions(output_func_body, oMatlabDseries);
if (output_func_body.str().empty())
return;
string func_name = basename + "_set_auxiliary_series";
string filename = julia ? func_name + ".jl" : func_name + ".m";
string comment = julia ? "#" : "%";
ofstream output;
output.open(filename.c_str(), ios::out | ios::binary);
if (!output.is_open())
{
cerr << "ERROR: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
output << "function ds = " << func_name + "(ds, params)" << endl
<< comment << endl
<< comment << " Status : Computes Auxiliary variables of the dynamic model and returns a dseries" << endl
<< comment << endl
<< comment << " Warning : this file is generated automatically by Dynare" << endl
<< comment << " from model file (.mod)" << endl << endl
<< output_func_body.str();
output.close();
}
void
DynamicModel::writeAuxVarRecursiveDefinitions(ostream &output, ExprNodeOutputType output_type) const
{ deriv_node_temp_terms_t tef_terms;
temporary_terms_t temporary_terms;
temporary_terms_idxs_t temporary_terms_idxs;
for (auto aux_equation : aux_equations)
if (dynamic_cast<ExprNode *>(aux_equation)->containsExternalFunction())
dynamic_cast<ExprNode *>(aux_equation)->writeExternalFunctionOutput(output, output_type,
temporary_terms,
temporary_terms_idxs,
tef_terms);
for (auto aux_equation : aux_equations)
{
dynamic_cast<ExprNode *>(aux_equation)->writeOutput(output, output_type, temporary_terms, temporary_terms_idxs, tef_terms);
output << ";" << endl;
}
}
void
DynamicModel::updateAfterVariableChange(DynamicModel &dm)
{
variable_node_map.clear();
unary_op_node_map.clear();
binary_op_node_map.clear();
trinary_op_node_map.clear();
external_function_node_map.clear();
first_deriv_external_function_node_map.clear();
second_deriv_external_function_node_map.clear();
cloneDynamic(dm);
dm.replaceMyEquations(*this);
}
void
DynamicModel::cloneDynamic(DynamicModel &dynamic_model) const
{
/* Ensure that we are using the same symbol table, because at many places we manipulate
symbol IDs rather than strings */
assert(&symbol_table == &dynamic_model.symbol_table);
// Convert model local variables (need to be done first)
for (int it : local_variables_vector)
dynamic_model.AddLocalVariable(it, local_variables_table.find(it)->second->cloneDynamic(dynamic_model));
// Convert equations
for (size_t i = 0; i < equations.size(); i++)
{
vector<pair<string, string>> eq_tags;
for (const auto & equation_tag : equation_tags)
if (equation_tag.first == (int)i)
eq_tags.push_back(equation_tag.second);
dynamic_model.addEquation(equations[i]->cloneDynamic(dynamic_model), equations_lineno[i], eq_tags);
}
// Convert auxiliary equations
for (auto aux_equation : aux_equations)
dynamic_model.addAuxEquation(aux_equation->cloneDynamic(dynamic_model));
// Convert static_only equations
for (size_t i = 0; i < static_only_equations.size(); i++)
dynamic_model.addStaticOnlyEquation(static_only_equations[i]->cloneDynamic(dynamic_model),
static_only_equations_lineno[i],
static_only_equations_equation_tags[i]);
dynamic_model.setLeadsLagsOrig();
}
void
DynamicModel::replaceMyEquations(DynamicModel &dynamic_model) const
{
dynamic_model.equations.clear();
for (size_t i = 0; i < equations.size(); i++) dynamic_model.addEquation(equations[i]->cloneDynamic(dynamic_model),
equations_lineno[i]);
}
void
DynamicModel::computeRamseyPolicyFOCs(const StaticModel &static_model, const bool nopreprocessoroutput)
{
// Add aux LM to constraints in equations
// equation[i]->lhs = rhs becomes equation[i]->MULT_(i+1)*(lhs-rhs) = 0
int i;
for (i = 0; i < (int) equations.size(); i++)
{
auto *substeq = dynamic_cast<BinaryOpNode *>(equations[i]->addMultipliersToConstraints(i));
assert(substeq != nullptr);
equations[i] = substeq;
}
if (!nopreprocessoroutput)
cout << "Ramsey Problem: added " << i << " Multipliers." << endl;
// Add Planner Objective to equations to include in computeDerivIDs
assert(static_model.equations.size() == 1);
addEquation(static_model.equations[0]->cloneDynamic(*this), static_model.equations_lineno[0]);
// Get max endo lead and max endo lag
set<pair<int, int>> dynvars;
int max_eq_lead = 0;
int max_eq_lag = 0;
for (auto & equation : equations)
equation->collectDynamicVariables(eEndogenous, dynvars);
for (const auto & dynvar : dynvars)
{
int lag = dynvar.second;
if (max_eq_lead < lag)
max_eq_lead = lag;
else if (-max_eq_lag > lag)
max_eq_lag = -lag;
}
// Get Discount Factor
assert(symbol_table.exists("optimal_policy_discount_factor"));
int symb_id = symbol_table.getID("optimal_policy_discount_factor");
assert(symbol_table.getType(symb_id) == eParameter);
expr_t discount_factor_node = AddVariable(symb_id, 0);
// Create (modified) Lagrangian (so that we can take the derivative once at time t)
expr_t lagrangian = Zero;
for (i = 0; i < (int) equations.size(); i++)
for (int lag = -max_eq_lag; lag <= max_eq_lead; lag++)
{
expr_t dfpower = nullptr;
std::stringstream lagstream;
lagstream << abs(lag);
if (lag < 0)
dfpower = AddNonNegativeConstant(lagstream.str());
else if (lag == 0)
dfpower = Zero;
else
dfpower = AddMinus(Zero, AddNonNegativeConstant(lagstream.str()));
lagrangian = AddPlus(AddTimes(AddPower(discount_factor_node, dfpower),
equations[i]->getNonZeroPartofEquation()->decreaseLeadsLags(lag)), lagrangian);
}
equations.clear();
addEquation(AddEqual(lagrangian, Zero), -1);
computeDerivIDs();
//Compute derivatives and overwrite equations
vector<expr_t> neweqs; for (deriv_id_table_t::const_iterator it = deriv_id_table.begin();
it != deriv_id_table.end(); it++)
// For all endogenous variables with zero lag
if (symbol_table.getType(it->first.first) == eEndogenous && it->first.second == 0)
neweqs.push_back(AddEqual(equations[0]->getNonZeroPartofEquation()->getDerivative(it->second), Zero));
// Add new equations
equations.clear();
for (auto & neweq : neweqs)
addEquation(neweq, -1);
}
void
DynamicModel::toStatic(StaticModel &static_model) const
{
/* Ensure that we are using the same symbol table, because at many places we manipulate
symbol IDs rather than strings */
assert(&symbol_table == &static_model.symbol_table);
// Convert model local variables (need to be done first)
for (int it : local_variables_vector)
static_model.AddLocalVariable(it, local_variables_table.find(it)->second->toStatic(static_model));
// Convert equations
int static_only_index = 0;
for (int i = 0; i < (int) equations.size(); i++)
{
// Detect if equation is marked [dynamic]
bool is_dynamic_only = false;
vector<pair<string, string>> eq_tags;
for (const auto & equation_tag : equation_tags)
if (equation_tag.first == i)
{
eq_tags.push_back(equation_tag.second);
if (equation_tag.second.first == "dynamic")
is_dynamic_only = true;
}
try
{
// If yes, replace it by an equation marked [static]
if (is_dynamic_only)
{
static_model.addEquation(static_only_equations[static_only_index]->toStatic(static_model), static_only_equations_lineno[static_only_index], static_only_equations_equation_tags[static_only_index]);
static_only_index++;
}
else
static_model.addEquation(equations[i]->toStatic(static_model), equations_lineno[i], eq_tags);
}
catch (DataTree::DivisionByZeroException)
{
cerr << "...division by zero error encountred when converting equation " << i << " to static" << endl;
exit(EXIT_FAILURE);
}
}
// Convert auxiliary equations
for (auto aux_equation : aux_equations)
static_model.addAuxEquation(aux_equation->toStatic(static_model));
}
bool
DynamicModel::ParamUsedWithLeadLag() const
{
return ParamUsedWithLeadLagInternal();
}
set<int>
DynamicModel::findUnusedEndogenous()
{ set<int> usedEndo, unusedEndo;
for (auto & equation : equations)
equation->collectVariables(eEndogenous, usedEndo);
set<int> allEndo = symbol_table.getEndogenous();
set_difference(allEndo.begin(), allEndo.end(),
usedEndo.begin(), usedEndo.end(),
inserter(unusedEndo, unusedEndo.begin()));
return unusedEndo;
}
set<int>
DynamicModel::findUnusedExogenous()
{
set<int> usedExo, unusedExo, unobservedExo;
for (auto & equation : equations)
equation->collectVariables(eExogenous, usedExo);
set<int> observedExo = symbol_table.getObservedExogenous();
set<int> allExo = symbol_table.getExogenous();
set_difference(allExo.begin(), allExo.end(),
observedExo.begin(), observedExo.end(),
inserter(unobservedExo, unobservedExo.begin()));
set_difference(unobservedExo.begin(), unobservedExo.end(),
usedExo.begin(), usedExo.end(),
inserter(unusedExo, unusedExo.begin()));
return unusedExo;
}
void
DynamicModel::setLeadsLagsOrig()
{
set<pair<int, int>> dynvars;
for (auto & equation : equations)
{
equation->collectDynamicVariables(eEndogenous, dynvars);
equation->collectDynamicVariables(eExogenous, dynvars);
equation->collectDynamicVariables(eExogenousDet, dynvars);
}
for (const auto & dynvar : dynvars)
{
int lag = dynvar.second;
SymbolType type = symbol_table.getType(dynvar.first);
if (max_lead_orig < lag)
max_lead_orig= lag;
else if (-max_lag_orig > lag)
max_lag_orig = -lag;
switch (type)
{
case eEndogenous:
if (max_endo_lead_orig < lag)
max_endo_lead_orig = lag;
else if (-max_endo_lag_orig > lag)
max_endo_lag_orig = -lag;
break;
case eExogenous:
if (max_exo_lead_orig < lag)
max_exo_lead_orig = lag;
else if (-max_exo_lag_orig > lag)
max_exo_lag_orig = -lag;
break;
case eExogenousDet:
if (max_exo_det_lead_orig < lag)
max_exo_det_lead_orig = lag;
else if (-max_exo_det_lag_orig > lag)
max_exo_det_lag_orig = -lag;
break;
default: break;
}
}
}
void
DynamicModel::computeDerivIDs()
{
set<pair<int, int>> dynvars;
for (auto & equation : equations)
equation->collectDynamicVariables(eEndogenous, dynvars);
dynJacobianColsNbr = dynvars.size();
for (auto & equation : equations)
{
equation->collectDynamicVariables(eExogenous, dynvars);
equation->collectDynamicVariables(eExogenousDet, dynvars);
equation->collectDynamicVariables(eParameter, dynvars);
equation->collectDynamicVariables(eTrend, dynvars);
equation->collectDynamicVariables(eLogTrend, dynvars);
}
for (const auto & dynvar : dynvars)
{
int lag = dynvar.second;
SymbolType type = symbol_table.getType(dynvar.first);
/* Setting maximum and minimum lags.
We don't want these to be affected by lead/lags on parameters: they
are accepted for facilitating variable flipping, but are simply
ignored. */
if (max_lead < lag && type != eParameter)
max_lead = lag;
else if (-max_lag > lag && type != eParameter)
max_lag = -lag;
switch (type)
{
case eEndogenous:
if (max_endo_lead < lag)
max_endo_lead = lag;
else if (-max_endo_lag > lag)
max_endo_lag = -lag;
break;
case eExogenous:
if (max_exo_lead < lag)
max_exo_lead = lag;
else if (-max_exo_lag > lag)
max_exo_lag = -lag;
break;
case eExogenousDet:
if (max_exo_det_lead < lag)
max_exo_det_lead = lag;
else if (-max_exo_det_lag > lag)
max_exo_det_lag = -lag;
break;
default:
break;
}
// Create a new deriv_id
int deriv_id = deriv_id_table.size();
deriv_id_table[dynvar] = deriv_id;
inv_deriv_id_table.push_back(dynvar);
}
}
SymbolType
DynamicModel::getTypeByDerivID(int deriv_id) const noexcept(false)
{
return symbol_table.getType(getSymbIDByDerivID(deriv_id));
}
int
DynamicModel::getLagByDerivID(int deriv_id) const noexcept(false)
{
if (deriv_id < 0 || deriv_id >= (int) inv_deriv_id_table.size())
throw UnknownDerivIDException();
return inv_deriv_id_table[deriv_id].second;
}
int
DynamicModel::getSymbIDByDerivID(int deriv_id) const noexcept(false)
{
if (deriv_id < 0 || deriv_id >= (int) inv_deriv_id_table.size())
throw UnknownDerivIDException();
return inv_deriv_id_table[deriv_id].first;
}
int
DynamicModel::getDerivID(int symb_id, int lag) const noexcept(false)
{
auto it = deriv_id_table.find({ symb_id, lag });
if (it == deriv_id_table.end())
throw UnknownDerivIDException();
else
return it->second;
}
void
DynamicModel::addAllParamDerivId(set<int> &deriv_id_set)
{
for (size_t i = 0; i < inv_deriv_id_table.size(); i++)
if (symbol_table.getType(inv_deriv_id_table[i].first) == eParameter)
deriv_id_set.insert(i);
}
void
DynamicModel::computeDynJacobianCols(bool jacobianExo)
{
/* Sort the dynamic endogenous variables by lexicographic order over (lag, type_specific_symbol_id)
and fill the dynamic columns for exogenous and exogenous deterministic */
map<pair<int, int>, int> ordered_dyn_endo;
for (deriv_id_table_t::const_iterator it = deriv_id_table.begin();
it != deriv_id_table.end(); it++)
{
const int &symb_id = it->first.first;
const int &lag = it->first.second;
const int &deriv_id = it->second;
SymbolType type = symbol_table.getType(symb_id);
int tsid = symbol_table.getTypeSpecificID(symb_id);
switch (type)
{
case eEndogenous:
ordered_dyn_endo[{ lag, tsid }] = deriv_id;
break;
case eExogenous:
// At this point, dynJacobianColsNbr contains the number of dynamic endogenous
if (jacobianExo)
dyn_jacobian_cols_table[deriv_id] = dynJacobianColsNbr + tsid;
break;
case eExogenousDet: // At this point, dynJacobianColsNbr contains the number of dynamic endogenous
if (jacobianExo)
dyn_jacobian_cols_table[deriv_id] = dynJacobianColsNbr + symbol_table.exo_nbr() + tsid;
break;
case eParameter:
case eTrend:
case eLogTrend:
// We don't assign a dynamic jacobian column to parameters or trend variables
break;
default:
// Shut up GCC
cerr << "DynamicModel::computeDynJacobianCols: impossible case" << endl;
exit(EXIT_FAILURE);
}
}
// Fill in dynamic jacobian columns for endogenous
int sorted_id = 0;
for (map<pair<int, int>, int>::const_iterator it = ordered_dyn_endo.begin();
it != ordered_dyn_endo.end(); it++)
dyn_jacobian_cols_table[it->second] = sorted_id++;
// Set final value for dynJacobianColsNbr
if (jacobianExo)
dynJacobianColsNbr += symbol_table.exo_nbr() + symbol_table.exo_det_nbr();
}
int
DynamicModel::getDynJacobianCol(int deriv_id) const noexcept(false)
{
auto it = dyn_jacobian_cols_table.find(deriv_id);
if (it == dyn_jacobian_cols_table.end())
throw UnknownDerivIDException();
else
return it->second;
}
void
DynamicModel::testTrendDerivativesEqualToZero(const eval_context_t &eval_context)
{
for (deriv_id_table_t::const_iterator it = deriv_id_table.begin();
it != deriv_id_table.end(); it++)
if (symbol_table.getType(it->first.first) == eTrend
|| symbol_table.getType(it->first.first) == eLogTrend)
for (int eq = 0; eq < (int) equations.size(); eq++)
{
expr_t homogeneq = AddMinus(equations[eq]->get_arg1(),
equations[eq]->get_arg2());
// Do not run the test if the term inside the log is zero
if (fabs(homogeneq->eval(eval_context)) > ZERO_BAND)
{
expr_t testeq = AddLog(homogeneq); // F = log(lhs-rhs)
testeq = testeq->getDerivative(it->second); // d F / d Trend
for (deriv_id_table_t::const_iterator endogit = deriv_id_table.begin();
endogit != deriv_id_table.end(); endogit++)
if (symbol_table.getType(endogit->first.first) == eEndogenous)
{
double nearZero = testeq->getDerivative(endogit->second)->eval(eval_context); // eval d F / d Trend d Endog
if (fabs(nearZero) > ZERO_BAND)
{
cerr << "WARNING: trends not compatible with balanced growth path; the second-order cross partial of equation " << eq + 1 << " (line "
<< equations_lineno[eq] << ") w.r.t. trend variable "
<< symbol_table.getName(it->first.first) << " and endogenous variable "
<< symbol_table.getName(endogit->first.first) << " is not null. " << endl;
// Changed to warning. See discussion in #1389
}
}
}
}}
void
DynamicModel::writeParamsDerivativesFile(const string &basename, bool julia) const
{
if (!residuals_params_derivatives.size()
&& !residuals_params_second_derivatives.size()
&& !jacobian_params_derivatives.size()
&& !jacobian_params_second_derivatives.size()
&& !hessian_params_derivatives.size())
return;
ExprNodeOutputType output_type = (julia ? oJuliaDynamicModel : oMatlabDynamicModel);
ostringstream model_local_vars_output; // Used for storing model local vars
ostringstream model_output; // Used for storing model temp vars and equations
ostringstream jacobian_output; // Used for storing jacobian equations
ostringstream hessian_output; // Used for storing Hessian equations
ostringstream hessian1_output; // Used for storing Hessian equations
ostringstream third_derivs_output; // Used for storing third order derivatives equations
ostringstream third_derivs1_output; // Used for storing third order derivatives equations
deriv_node_temp_terms_t tef_terms;
writeTemporaryTerms(params_derivs_temporary_terms, {}, params_derivs_temporary_terms_idxs, model_output, output_type, tef_terms);
for (const auto & residuals_params_derivative : residuals_params_derivatives)
{
int eq, param;
tie(eq, param) = residuals_params_derivative.first;
expr_t d1 = residuals_params_derivative.second;
int param_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param)) + 1;
jacobian_output << "rp" << LEFT_ARRAY_SUBSCRIPT(output_type) << eq+1 << ", " << param_col
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << " = ";
d1->writeOutput(jacobian_output, output_type, params_derivs_temporary_terms, params_derivs_temporary_terms_idxs, tef_terms);
jacobian_output << ";" << endl;
}
for (const auto & jacobian_params_derivative : jacobian_params_derivatives)
{
int eq, var, param;
tie(eq, var, param) = jacobian_params_derivative.first;
expr_t d2 = jacobian_params_derivative.second;
int var_col = getDynJacobianCol(var) + 1;
int param_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param)) + 1;
hessian_output << "gp" << LEFT_ARRAY_SUBSCRIPT(output_type) << eq+1 << ", " << var_col
<< ", " << param_col << RIGHT_ARRAY_SUBSCRIPT(output_type) << " = ";
d2->writeOutput(hessian_output, output_type, params_derivs_temporary_terms, params_derivs_temporary_terms_idxs, tef_terms);
hessian_output << ";" << endl;
}
int i = 1;
for (const auto &it : residuals_params_second_derivatives)
{
int eq, param1, param2;
tie(eq, param1, param2) = it.first;
expr_t d2 = it.second;
int param1_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param1)) + 1;
int param2_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param2)) + 1;
hessian1_output << "rpp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",1"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=" << eq+1 << ";" << endl
<< "rpp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",2"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=" << param1_col << ";" << endl
<< "rpp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",3"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=" << param2_col << ";" << endl << "rpp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",4"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=";
d2->writeOutput(hessian1_output, output_type, params_derivs_temporary_terms, params_derivs_temporary_terms_idxs, tef_terms);
hessian1_output << ";" << endl;
i++;
}
i = 1;
for (const auto &it : jacobian_params_second_derivatives)
{
int eq, var, param1, param2;
tie(eq, var, param1, param2) = it.first;
expr_t d2 = it.second;
int var_col = getDynJacobianCol(var) + 1;
int param1_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param1)) + 1;
int param2_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param2)) + 1;
third_derivs_output << "gpp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",1"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=" << eq+1 << ";" << endl
<< "gpp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",2"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=" << var_col << ";" << endl
<< "gpp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",3"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=" << param1_col << ";" << endl
<< "gpp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",4"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=" << param2_col << ";" << endl
<< "gpp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",5"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=";
d2->writeOutput(third_derivs_output, output_type, params_derivs_temporary_terms, params_derivs_temporary_terms_idxs, tef_terms);
third_derivs_output << ";" << endl;
i++;
}
i = 1;
for (const auto &it : hessian_params_derivatives)
{
int eq, var1, var2, param;
tie(eq, var1, var2, param) = it.first;
expr_t d2 = it.second;
int var1_col = getDynJacobianCol(var1) + 1;
int var2_col = getDynJacobianCol(var2) + 1;
int param_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param)) + 1;
third_derivs1_output << "hp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",1"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=" << eq+1 << ";" << endl
<< "hp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",2"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=" << var1_col << ";" << endl
<< "hp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",3"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=" << var2_col << ";" << endl
<< "hp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",4"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=" << param_col << ";" << endl
<< "hp" << LEFT_ARRAY_SUBSCRIPT(output_type) << i << ",5"
<< RIGHT_ARRAY_SUBSCRIPT(output_type) << "=";
d2->writeOutput(third_derivs1_output, output_type, params_derivs_temporary_terms, params_derivs_temporary_terms_idxs, tef_terms);
third_derivs1_output << ";" << endl;
i++;
}
string filename = julia ? basename + "DynamicParamsDerivs.jl" : basename + "_params_derivs.m";
ofstream paramsDerivsFile;
paramsDerivsFile.open(filename.c_str(), ios::out | ios::binary);
if (!paramsDerivsFile.is_open())
{
cerr << "ERROR: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
if (!julia)
{
// Check that we don't have more than 32 nested parenthesis because Matlab does not suppor this. See Issue #1201
map<string, string> tmp_paren_vars;
bool message_printed = false;
fixNestedParenthesis(model_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(model_local_vars_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(jacobian_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(hessian_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(hessian1_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(third_derivs_output, tmp_paren_vars, message_printed);
fixNestedParenthesis(third_derivs1_output, tmp_paren_vars, message_printed);
paramsDerivsFile << "function [rp, gp, rpp, gpp, hp] = " << basename << "_params_derivs(y, x, params, steady_state, it_, ss_param_deriv, ss_param_2nd_deriv)" << endl
<< "%" << endl
<< "% Compute the derivatives of the dynamic model with respect to the parameters" << endl
<< "% Inputs :" << endl
<< "% y [#dynamic variables by 1] double vector of endogenous variables in the order stored" << endl
<< "% in M_.lead_lag_incidence; see the Manual" << endl
<< "% x [nperiods by M_.exo_nbr] double matrix of exogenous variables (in declaration order)" << endl
<< "% for all simulation periods" << endl
<< "% params [M_.param_nbr by 1] double vector of parameter values in declaration order" << endl
<< "% steady_state [M_.endo_nbr by 1] double vector of steady state values" << endl
<< "% it_ scalar double time period for exogenous variables for which to evaluate the model" << endl
<< "% ss_param_deriv [M_.eq_nbr by #params] Jacobian matrix of the steady states values with respect to the parameters" << endl
<< "% ss_param_2nd_deriv [M_.eq_nbr by #params by #params] Hessian matrix of the steady states values with respect to the parameters" << endl
<< "%" << endl
<< "% Outputs:" << endl
<< "% rp [M_.eq_nbr by #params] double Jacobian matrix of dynamic model equations with respect to parameters " << endl
<< "% Dynare may prepend or append auxiliary equations, see M_.aux_vars" << endl
<< "% gp [M_.endo_nbr by #dynamic variables by #params] double Derivative of the Jacobian matrix of the dynamic model equations with respect to the parameters" << endl
<< "% rows: equations in order of declaration" << endl
<< "% columns: variables in order stored in M_.lead_lag_incidence" << endl
<< "% rpp [#second_order_residual_terms by 4] double Hessian matrix of second derivatives of residuals with respect to parameters;" << endl
<< "% rows: respective derivative term" << endl
<< "% 1st column: equation number of the term appearing" << endl
<< "% 2nd column: number of the first parameter in derivative" << endl
<< "% 3rd column: number of the second parameter in derivative" << endl
<< "% 4th column: value of the Hessian term" << endl
<< "% gpp [#second_order_Jacobian_terms by 5] double Hessian matrix of second derivatives of the Jacobian with respect to the parameters;" << endl
<< "% rows: respective derivative term" << endl
<< "% 1st column: equation number of the term appearing" << endl
<< "% 2nd column: column number of variable in Jacobian of the dynamic model" << endl
<< "% 3rd column: number of the first parameter in derivative" << endl
<< "% 4th column: number of the second parameter in derivative" << endl
<< "% 5th column: value of the Hessian term" << endl
<< "% hp [#first_order_Hessian_terms by 5] double Jacobian matrix of derivatives of the dynamic Hessian with respect to the parameters;" << endl
<< "% rows: respective derivative term" << endl
<< "% 1st column: equation number of the term appearing" << endl
<< "% 2nd column: column number of first variable in Hessian of the dynamic model" << endl
<< "% 3rd column: column number of second variable in Hessian of the dynamic model" << endl
<< "% 4th column: number of the parameter in derivative" << endl
<< "% 5th column: value of the Hessian term" << endl
<< "%" << endl
<< "%" << endl
<< "% Warning : this file is generated automatically by Dynare" << endl
<< "% from model file (.mod)" << endl << endl
<< "T = NaN(" << params_derivs_temporary_terms_idxs.size() << ",1);" << endl
<< model_local_vars_output.str()
<< model_output.str()
<< "rp = zeros(" << equations.size() << ", "
<< symbol_table.param_nbr() << ");" << endl
<< jacobian_output.str()
<< "gp = zeros(" << equations.size() << ", " << dynJacobianColsNbr << ", " << symbol_table.param_nbr() << ");" << endl
<< hessian_output.str()
<< "if nargout >= 3" << endl
<< "rpp = zeros(" << residuals_params_second_derivatives.size() << ",4);" << endl
<< hessian1_output.str()
<< "gpp = zeros(" << jacobian_params_second_derivatives.size() << ",5);" << endl
<< third_derivs_output.str() << "end" << endl
<< "if nargout >= 5" << endl
<< "hp = zeros(" << hessian_params_derivatives.size() << ",5);" << endl
<< third_derivs1_output.str()
<< "end" << endl
<< "end" << endl;
}
else
paramsDerivsFile << "module " << basename << "DynamicParamsDerivs" << endl
<< "#" << endl
<< "# NB: this file was automatically generated by Dynare" << endl
<< "# from " << basename << ".mod" << endl
<< "#" << endl
<< "export params_derivs" << endl << endl
<< "function params_derivs(y, x, paramssteady_state, it_, "
<< "ss_param_deriv, ss_param_2nd_deriv)" << endl
<< model_local_vars_output.str()
<< model_output.str()
<< "rp = zeros(" << equations.size() << ", "
<< symbol_table.param_nbr() << ");" << endl
<< jacobian_output.str()
<< "gp = zeros(" << equations.size() << ", " << dynJacobianColsNbr << ", " << symbol_table.param_nbr() << ");" << endl
<< hessian_output.str()
<< "rpp = zeros(" << residuals_params_second_derivatives.size() << ",4);" << endl
<< hessian1_output.str()
<< "gpp = zeros(" << jacobian_params_second_derivatives.size() << ",5);" << endl
<< third_derivs_output.str()
<< "hp = zeros(" << hessian_params_derivatives.size() << ",5);" << endl
<< third_derivs1_output.str()
<< "(rp, gp, rpp, gpp, hp)" << endl
<< "end" << endl
<< "end" << endl;
paramsDerivsFile.close();
}
void
DynamicModel::writeLatexFile(const string &basename, const bool write_equation_tags) const
{
writeLatexModelFile(basename + "_dynamic", oLatexDynamicModel, write_equation_tags);
}
void
DynamicModel::writeLatexOriginalFile(const string &basename, const bool write_equation_tags) const
{
writeLatexModelFile(basename + "_original", oLatexDynamicModel, write_equation_tags);
}
void
DynamicModel::substituteEndoLeadGreaterThanTwo(bool deterministic_model)
{
substituteLeadLagInternal(avEndoLead, deterministic_model, vector<string>());
}
void
DynamicModel::substituteEndoLagGreaterThanTwo(bool deterministic_model)
{
substituteLeadLagInternal(avEndoLag, deterministic_model, vector<string>());
}
void
DynamicModel::substituteExoLead(bool deterministic_model)
{
substituteLeadLagInternal(avExoLead, deterministic_model, vector<string>());
}
void
DynamicModel::substituteExoLag(bool deterministic_model)
{
substituteLeadLagInternal(avExoLag, deterministic_model, vector<string>());}
void
DynamicModel::substituteLeadLagInternal(aux_var_t type, bool deterministic_model, const vector<string> &subset)
{
ExprNode::subst_table_t subst_table;
vector<BinaryOpNode *> neweqs;
// Substitute in used model local variables
set<int> used_local_vars;
for (auto & equation : equations)
equation->collectVariables(eModelLocalVariable, used_local_vars);
for (int used_local_var : used_local_vars)
{
const expr_t value = local_variables_table.find(used_local_var)->second;
expr_t subst;
switch (type)
{
case avEndoLead:
subst = value->substituteEndoLeadGreaterThanTwo(subst_table, neweqs, deterministic_model);
break;
case avEndoLag:
subst = value->substituteEndoLagGreaterThanTwo(subst_table, neweqs);
break;
case avExoLead:
subst = value->substituteExoLead(subst_table, neweqs, deterministic_model);
break;
case avExoLag:
subst = value->substituteExoLag(subst_table, neweqs);
break;
case avDiffForward:
subst = value->differentiateForwardVars(subset, subst_table, neweqs);
break;
default:
cerr << "DynamicModel::substituteLeadLagInternal: impossible case" << endl;
exit(EXIT_FAILURE);
}
local_variables_table[used_local_var] = subst;
}
// Substitute in equations
for (auto & equation : equations)
{
expr_t subst;
switch (type)
{
case avEndoLead:
subst = equation->substituteEndoLeadGreaterThanTwo(subst_table, neweqs, deterministic_model);
break;
case avEndoLag:
subst = equation->substituteEndoLagGreaterThanTwo(subst_table, neweqs);
break;
case avExoLead:
subst = equation->substituteExoLead(subst_table, neweqs, deterministic_model);
break;
case avExoLag:
subst = equation->substituteExoLag(subst_table, neweqs);
break;
case avDiffForward:
subst = equation->differentiateForwardVars(subset, subst_table, neweqs);
break;
default:
cerr << "DynamicModel::substituteLeadLagInternal: impossible case" << endl;
exit(EXIT_FAILURE);
}
auto *substeq = dynamic_cast<BinaryOpNode *>(subst);
assert(substeq != nullptr);
equation = substeq;
}
// Substitute in aux_equations
// Without this loop, the auxiliary equations in equations
// will diverge from those in aux_equations
for (auto & aux_equation : aux_equations)
{
expr_t subst;
switch (type)
{
case avEndoLead:
subst = aux_equation->substituteEndoLeadGreaterThanTwo(subst_table,
neweqs, deterministic_model);
break;
case avEndoLag:
subst = aux_equation->substituteEndoLagGreaterThanTwo(subst_table, neweqs);
break;
case avExoLead:
subst = aux_equation->substituteExoLead(subst_table, neweqs, deterministic_model);
break;
case avExoLag:
subst = aux_equation->substituteExoLag(subst_table, neweqs);
break;
case avDiffForward:
subst = aux_equation->differentiateForwardVars(subset, subst_table, neweqs);
break;
default:
cerr << "DynamicModel::substituteLeadLagInternal: impossible case" << endl;
exit(EXIT_FAILURE);
}
auto *substeq = dynamic_cast<BinaryOpNode *>(subst);
assert(substeq != nullptr);
aux_equation = substeq;
}
// Substitute in diff_aux_equations
// Without this loop, the auxiliary equations in equations
// will diverge from those in diff_aux_equations
for (auto & diff_aux_equation : diff_aux_equations)
{
expr_t subst;
switch (type)
{
case avEndoLead:
subst = diff_aux_equation->substituteEndoLeadGreaterThanTwo(subst_table,
neweqs, deterministic_model);
break;
case avEndoLag:
subst = diff_aux_equation->substituteEndoLagGreaterThanTwo(subst_table, neweqs);
break;
case avExoLead:
subst = diff_aux_equation->substituteExoLead(subst_table, neweqs, deterministic_model);
break;
case avExoLag:
subst = diff_aux_equation->substituteExoLag(subst_table, neweqs);
break;
case avDiffForward:
subst = diff_aux_equation->differentiateForwardVars(subset, subst_table, neweqs);
break;
default:
cerr << "DynamicModel::substituteLeadLagInternal: impossible case" << endl;
exit(EXIT_FAILURE);
}
auto *substeq = dynamic_cast<BinaryOpNode *>(subst);
assert(substeq != nullptr);
diff_aux_equation = substeq;
}
// Add new equations
for (auto & neweq : neweqs)
addEquation(neweq, -1);
// Order of auxiliary variable definition equations:
// - expectation (entered before this function is called)
// - lead variables from lower lead to higher lead
// - lag variables from lower lag to higher lag
copy(neweqs.begin(), neweqs.end(), back_inserter(aux_equations));
if (neweqs.size() > 0)
{
cout << "Substitution of ";
switch (type)
{
case avEndoLead:
cout << "endo leads >= 2";
break;
case avEndoLag:
cout << "endo lags >= 2";
break;
case avExoLead:
cout << "exo leads";
break;
case avExoLag:
cout << "exo lags";
break;
case avExpectation:
cout << "expectation";
break;
case avDiffForward:
cout << "forward vars";
break;
default:
cerr << "DynamicModel::substituteLeadLagInternal: impossible case" << endl;
exit(EXIT_FAILURE);
}
cout << ": added " << neweqs.size() << " auxiliary variables and equations." << endl;
}
}
void
DynamicModel::substituteAdl()
{
for (auto & equation : equations)
equation = dynamic_cast<BinaryOpNode *>(equation->substituteAdl());
}
void
DynamicModel::getEquationNumbersFromTags(vector<int> &eqnumbers, set<string> &eqtags) const
{
for (auto & eqtag : eqtags)
for (const auto & equation_tag : equation_tags)
if (equation_tag.second.first == "name"
&& equation_tag.second.second == eqtag)
{
eqnumbers.push_back(equation_tag.first);
break;
}
}
void
DynamicModel::findPacExpectationEquationNumbers(vector<int> &eqnumbers) const
{
int i = 0;
for (auto & equation : equations)
{
if (equation->containsPacExpectation())
if (find(eqnumbers.begin(), eqnumbers.end(), i) == eqnumbers.end())
eqnumbers.push_back(i);
i++;
}
}
void
DynamicModel::substituteUnaryOps(StaticModel &static_model)
{
vector<int> eqnumbers(equations.size());
iota(eqnumbers.begin(), eqnumbers.end(), 0);
substituteUnaryOps(static_model, eqnumbers);
}
void
DynamicModel::substituteUnaryOps(StaticModel &static_model, set<string> &var_model_eqtags)
{
vector<int> eqnumbers;
getEquationNumbersFromTags(eqnumbers, var_model_eqtags);
findPacExpectationEquationNumbers(eqnumbers);
substituteUnaryOps(static_model, eqnumbers);
}
void
DynamicModel::substituteUnaryOps(StaticModel &static_model, vector<int> &eqnumbers)
{
diff_table_t nodes;
// Find matching unary ops that may be outside of diffs (i.e., those with different lags)
set<int> used_local_vars;
for (int eqnumber : eqnumbers)
equations[eqnumber]->collectVariables(eModelLocalVariable, used_local_vars);
// Only substitute unary ops in model local variables that appear in VAR equations
for (auto & it : local_variables_table)
if (used_local_vars.find(it.first) != used_local_vars.end())
it.second->findUnaryOpNodesForAuxVarCreation(static_model, nodes);
for (int eqnumber : eqnumbers)
equations[eqnumber]->findUnaryOpNodesForAuxVarCreation(static_model, nodes);
// Substitute in model local variables
ExprNode::subst_table_t subst_table;
vector<BinaryOpNode *> neweqs;
for (auto & it : local_variables_table)
it.second = it.second->substituteUnaryOpNodes(static_model, nodes, subst_table, neweqs);
// Substitute in equations
for (auto & equation : equations)
{
auto *substeq = dynamic_cast<BinaryOpNode *>(equation->
substituteUnaryOpNodes(static_model, nodes, subst_table, neweqs));
assert(substeq != nullptr);
equation = substeq;
}
// Add new equations
for (auto & neweq : neweqs)
addEquation(neweq, -1);
copy(neweqs.begin(), neweqs.end(), front_inserter(diff_aux_equations));
if (subst_table.size() > 0)
cout << "Substitution of Unary Ops: added " << neweqs.size() << " auxiliary variables and equations." << endl;
}
void
DynamicModel::substituteDiff(StaticModel &static_model, ExprNode::subst_table_t &diff_subst_table)
{
set<int> used_local_vars;
for (const auto & equation : equations)
equation->collectVariables(eModelLocalVariable, used_local_vars);
// Only substitute diffs in model local variables that appear in VAR equations
diff_table_t diff_table; for (auto & it : local_variables_table)
if (used_local_vars.find(it.first) != used_local_vars.end())
it.second->findDiffNodes(static_model, diff_table);
for (const auto & equation : equations)
equation->findDiffNodes(static_model, diff_table);
// Substitute in model local variables
vector<BinaryOpNode *> neweqs;
for (auto & it : local_variables_table)
it.second = it.second->substituteDiff(static_model, diff_table, diff_subst_table, neweqs);
// Substitute in equations
for (auto & equation : equations)
{
auto *substeq = dynamic_cast<BinaryOpNode *>(equation->
substituteDiff(static_model, diff_table, diff_subst_table, neweqs));
assert(substeq != nullptr);
equation = substeq;
}
// Add new equations
for (auto & neweq : neweqs)
addEquation(neweq, -1);
copy(neweqs.begin(), neweqs.end(), front_inserter(diff_aux_equations));
if (diff_subst_table.size() > 0)
cout << "Substitution of Diff operator: added " << neweqs.size() << " auxiliary variables and equations." << endl;
}
void
DynamicModel::combineDiffAuxEquations()
{
copy(diff_aux_equations.begin(), diff_aux_equations.end(), front_inserter(aux_equations));
}
void
DynamicModel::substituteExpectation(bool partial_information_model)
{
ExprNode::subst_table_t subst_table;
vector<BinaryOpNode *> neweqs;
// Substitute in model local variables
for (auto & it : local_variables_table)
it.second = it.second->substituteExpectation(subst_table, neweqs, partial_information_model);
// Substitute in equations
for (auto & equation : equations)
{
auto *substeq = dynamic_cast<BinaryOpNode *>(equation->substituteExpectation(subst_table, neweqs, partial_information_model));
assert(substeq != nullptr);
equation = substeq;
}
// Add new equations
for (auto & neweq : neweqs)
addEquation(neweq, -1);
// Add the new set of equations at the *beginning* of aux_equations
copy(neweqs.rbegin(), neweqs.rend(), front_inserter(aux_equations));
if (subst_table.size() > 0)
{
if (partial_information_model)
cout << "Substitution of Expectation operator: added " << subst_table.size() << " auxiliary variables and " << neweqs.size() << " auxiliary equations." << endl;
else
cout << "Substitution of Expectation operator: added " << neweqs.size() << " auxiliary variables and equations." << endl;
}
}
void
DynamicModel::transformPredeterminedVariables()
{
for (auto & it : local_variables_table)
it.second = it.second->decreaseLeadsLagsPredeterminedVariables();
for (auto & equation : equations)
{
auto *substeq = dynamic_cast<BinaryOpNode *>(equation->decreaseLeadsLagsPredeterminedVariables());
assert(substeq != nullptr);
equation = substeq;
}
}
void
DynamicModel::detrendEquations()
{
// We go backwards in the list of trend_vars, to deal correctly with I(2) processes
for (nonstationary_symbols_map_t::const_reverse_iterator it = nonstationary_symbols_map.rbegin();
it != nonstationary_symbols_map.rend(); ++it)
for (auto & equation : equations)
{
auto *substeq = dynamic_cast<BinaryOpNode *>(equation->detrend(it->first, it->second.first, it->second.second));
assert(substeq != nullptr);
equation = dynamic_cast<BinaryOpNode *>(substeq);
}
for (auto & equation : equations)
{
BinaryOpNode *substeq = dynamic_cast<BinaryOpNode *>(equation->removeTrendLeadLag(trend_symbols_map));
assert(substeq != nullptr);
equation = dynamic_cast<BinaryOpNode *>(substeq);
}
}
void
DynamicModel::removeTrendVariableFromEquations()
{
for (auto & equation : equations)
{
auto *substeq = dynamic_cast<BinaryOpNode *>(equation->replaceTrendVar());
assert(substeq != nullptr);
equation = dynamic_cast<BinaryOpNode *>(substeq);
}
}
void
DynamicModel::differentiateForwardVars(const vector<string> &subset)
{
substituteLeadLagInternal(avDiffForward, true, subset);
}
void
DynamicModel::fillEvalContext(eval_context_t &eval_context) const
{
// First, auxiliary variables
for (auto aux_equation : aux_equations)
{
assert(aux_equation->get_op_code() == oEqual);
auto *auxvar = dynamic_cast<VariableNode *>(aux_equation->get_arg1());
assert(auxvar != nullptr);
try
{
double val = aux_equation->get_arg2()->eval(eval_context);
eval_context[auxvar->get_symb_id()] = val;
}
catch (ExprNode::EvalException &e)
{
// Do nothing }
}
// Second, model local variables
for (auto it : local_variables_table)
{
try
{
const expr_t expression = it.second;
double val = expression->eval(eval_context);
eval_context[it.first] = val;
}
catch (ExprNode::EvalException &e)
{
// Do nothing
}
}
//Third, trend variables
vector <int> trendVars = symbol_table.getTrendVarIds();
for (vector <int>::const_iterator it = trendVars.begin();
it != trendVars.end(); it++)
eval_context[*it] = 2; //not <= 0 bc of log, not 1 bc of powers
}
bool
DynamicModel::isModelLocalVariableUsed() const
{
set<int> used_local_vars;
size_t i = 0;
while (i < equations.size() && used_local_vars.size() == 0)
{
equations[i]->collectVariables(eModelLocalVariable, used_local_vars);
i++;
}
return used_local_vars.size() > 0;
}
void
DynamicModel::addStaticOnlyEquation(expr_t eq, int lineno, const vector<pair<string, string>> &eq_tags)
{
auto *beq = dynamic_cast<BinaryOpNode *>(eq);
assert(beq != nullptr && beq->get_op_code() == oEqual);
vector<pair<string, string>> soe_eq_tags;
for (const auto & eq_tag : eq_tags)
soe_eq_tags.push_back(eq_tag);
static_only_equations.push_back(beq);
static_only_equations_lineno.push_back(lineno);
static_only_equations_equation_tags.push_back(soe_eq_tags);
}
size_t
DynamicModel::staticOnlyEquationsNbr() const
{
return static_only_equations.size();
}
size_t
DynamicModel::dynamicOnlyEquationsNbr() const
{
set<int> eqs;
for (const auto & equation_tag : equation_tags)
if (equation_tag.second.first == "dynamic")
eqs.insert(equation_tag.first);
return eqs.size();
}
#ifndef PRIVATE_BUFFER_SIZE
# define PRIVATE_BUFFER_SIZE 1024
#endif
bool
DynamicModel::isChecksumMatching(const string &basename) const
{
boost::crc_32_type result;
std::stringstream buffer;
// Write equation tags
for (const auto & equation_tag : equation_tags)
buffer << " " << equation_tag.first + 1
<< equation_tag.second.first
<< equation_tag.second.second;
ExprNodeOutputType buffer_type = oCDynamicModel;
for (int eq = 0; eq < (int) equations.size(); eq++)
{
BinaryOpNode *eq_node = equations[eq];
expr_t lhs = eq_node->get_arg1();
expr_t rhs = eq_node->get_arg2();
// Test if the right hand side of the equation is empty.
double vrhs = 1.0;
try
{
vrhs = rhs->eval(eval_context_t());
}
catch (ExprNode::EvalException &e)
{
}
if (vrhs != 0) // The right hand side of the equation is not empty ==> residual=lhs-rhs;
{
buffer << "lhs =";
lhs->writeOutput(buffer, buffer_type, temporary_terms, temporary_terms_idxs);
buffer << ";" << endl;
buffer << "rhs =";
rhs->writeOutput(buffer, buffer_type, temporary_terms, temporary_terms_idxs);
buffer << ";" << endl;
buffer << "residual" << LEFT_ARRAY_SUBSCRIPT(buffer_type)
<< eq + ARRAY_SUBSCRIPT_OFFSET(buffer_type)
<< RIGHT_ARRAY_SUBSCRIPT(buffer_type)
<< "= lhs-rhs;" << endl;
}
else // The right hand side of the equation is empty ==> residual=lhs;
{
buffer << "residual" << LEFT_ARRAY_SUBSCRIPT(buffer_type)
<< eq + ARRAY_SUBSCRIPT_OFFSET(buffer_type)
<< RIGHT_ARRAY_SUBSCRIPT(buffer_type)
<< " = ";
lhs->writeOutput(buffer, buffer_type, temporary_terms, temporary_terms_idxs);
buffer << ";" << endl;
}
}
char private_buffer[PRIVATE_BUFFER_SIZE];
while (buffer)
{
buffer.get(private_buffer, PRIVATE_BUFFER_SIZE);
result.process_bytes(private_buffer, strlen(private_buffer));
}
bool basename_dir_exists = false;#ifdef _WIN32
int r = mkdir(basename.c_str());
#else
int r = mkdir(basename.c_str(), 0777);
#endif
if (r < 0)
if (errno != EEXIST)
{
perror("ERROR");
exit(EXIT_FAILURE);
}
else
basename_dir_exists = true;
// check whether basename directory exist. If not, create it.
// If it does, read old checksum if it exist
fstream checksum_file;
string filename = basename + "/checksum";
unsigned int old_checksum = 0;
// read old checksum if it exists
if (basename_dir_exists)
{
checksum_file.open(filename.c_str(), ios::in | ios::binary);
if (checksum_file.is_open())
{
checksum_file >> old_checksum;
checksum_file.close();
}
}
// write new checksum file if none or different from old checksum
if (old_checksum != result.checksum())
{
checksum_file.open(filename.c_str(), ios::out | ios::binary);
if (!checksum_file.is_open())
{
cerr << "ERROR: Can't open file " << filename << endl;
exit(EXIT_FAILURE);
}
checksum_file << result.checksum();
checksum_file.close();
return false;
}
return true;
}
void
DynamicModel::writeCOutput(ostream &output, const string &basename, bool block_decomposition, bool byte_code, bool use_dll, int order, bool estimation_present) const
{
int lag_presence[3];
// Loop on endogenous variables
vector<int> zeta_back, zeta_mixed, zeta_fwrd, zeta_static;
for (int endoID = 0; endoID < symbol_table.endo_nbr(); endoID++)
{
// Loop on periods
for (int lag = 0; lag <= 2; lag++)
{
lag_presence[lag] = 1;
try
{
getDerivID(symbol_table.getID(eEndogenous, endoID), lag-1);
}
catch (UnknownDerivIDException &e)
{
lag_presence[lag] = 0;
}
}
if (lag_presence[0] == 1)
if (lag_presence[2] == 1)
zeta_mixed.push_back(endoID); else
zeta_back.push_back(endoID);
else if (lag_presence[2] == 1)
zeta_fwrd.push_back(endoID);
else
zeta_static.push_back(endoID);
}
output << "size_t nstatic = " << zeta_static.size() << ";" << endl
<< "size_t nfwrd = " << zeta_fwrd.size() << ";" << endl
<< "size_t nback = " << zeta_back.size() << ";" << endl
<< "size_t nmixed = " << zeta_mixed.size() << ";" << endl;
output << "size_t zeta_static[" << zeta_static.size() << "] = {";
for (auto i = zeta_static.begin(); i != zeta_static.end(); ++i)
{
if (i != zeta_static.begin())
output << ",";
output << *i;
}
output << "};" << endl;
output << "size_t zeta_back[" << zeta_back.size() << "] = {";
for (auto i = zeta_back.begin(); i != zeta_back.end(); ++i)
{
if (i != zeta_back.begin())
output << ",";
output << *i;
}
output << "};" << endl;
output << "size_t zeta_fwrd[" << zeta_fwrd.size() << "] = {";
for (auto i = zeta_fwrd.begin(); i != zeta_fwrd.end(); ++i)
{
if (i != zeta_fwrd.begin())
output << ",";
output << *i;
}
output << "};" << endl;
output << "size_t zeta_mixed[" << zeta_mixed.size() << "] = {";
for (auto i = zeta_mixed.begin(); i != zeta_mixed.end(); ++i)
{
if (i != zeta_mixed.begin())
output << ",";
output << *i;
}
output << "};" << endl;
// Write number of non-zero derivatives
// Use -1 if the derivatives have not been computed
output << "int *NNZDerivatives[3] = {";
switch (order)
{
case 0:
output << NNZDerivatives[0] << ",-1,-1};" << endl;
break;
case 1:
output << NNZDerivatives[0] << "," << NNZDerivatives[1] << ",-1};" << endl;
break;
case 2:
output << NNZDerivatives[0] << "," << NNZDerivatives[1] << "," << NNZDerivatives[2] << "};" << endl;
break;
default:
cerr << "Order larger than 3 not implemented" << endl;
exit(EXIT_FAILURE);
}
}
void
DynamicModel::writeResidualsC(const string &basename, bool cuda) const{
string filename = basename + "_residuals.c";
ofstream mDynamicModelFile, mDynamicMexFile;
mDynamicModelFile.open(filename.c_str(), ios::out | ios::binary);
if (!mDynamicModelFile.is_open())
{
cerr << "Error: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
mDynamicModelFile << "/*" << endl
<< " * " << filename << " : Computes residuals of the model for Dynare" << endl
<< " *" << endl
<< " * Warning : this file is generated automatically by Dynare" << endl
<< " * from model " << basename << "(.mod)" << endl
<< " */" << endl
#if defined(_WIN32) || defined(__CYGWIN32__) || defined(__MINGW32__)
<< "#ifdef _MSC_VER" << endl
<< "#define _USE_MATH_DEFINES" << endl
<< "#endif" << endl
#endif
<< "#include <math.h>" << endl;
mDynamicModelFile << "#include <stdlib.h>" << endl;
mDynamicModelFile << "#define max(a, b) (((a) > (b)) ? (a) : (b))" << endl
<< "#define min(a, b) (((a) > (b)) ? (b) : (a))" << endl;
// Write function definition if oPowerDeriv is used
// even for residuals if doing Ramsey
writePowerDerivCHeader(mDynamicModelFile);
writeNormcdfCHeader(mDynamicModelFile);
mDynamicModelFile << "void Residuals(const double *y, double *x, int nb_row_x, double *params, double *steady_state, int it_, double *residual)" << endl
<< "{" << endl;
ostringstream model_output; // Used for storing model equations
writeModelEquations(model_output, oCDynamic2Model);
mDynamicModelFile << " double lhs, rhs;" << endl
<< endl
<< " /* Residual equations */" << endl
<< model_output.str()
<< "}" << endl;
writePowerDeriv(mDynamicModelFile);
writeNormcdf(mDynamicModelFile);
mDynamicModelFile.close();
}
void
DynamicModel::writeFirstDerivativesC(const string &basename, bool cuda) const
{
string filename = basename + "_first_derivatives.c";
ofstream mDynamicModelFile, mDynamicMexFile;
mDynamicModelFile.open(filename.c_str(), ios::out | ios::binary);
if (!mDynamicModelFile.is_open())
{
cerr << "Error: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
mDynamicModelFile << "/*" << endl
<< " * " << filename << " : Computes first order derivatives of the model for Dynare" << endl
<< " *" << endl
<< " * Warning : this file is generated automatically by Dynare" << endl
<< " * from model " << basename << "(.mod)" << endl
<< " */" << endl
#if defined(_WIN32) || defined(__CYGWIN32__) || defined(__MINGW32__) << "#ifdef _MSC_VER" << endl
<< "#define _USE_MATH_DEFINES" << endl
<< "#endif" << endl
#endif
<< "#include <math.h>" << endl;
mDynamicModelFile << "#include <stdlib.h>" << endl;
mDynamicModelFile << "#define max(a, b) (((a) > (b)) ? (a) : (b))" << endl
<< "#define min(a, b) (((a) > (b)) ? (b) : (a))" << endl;
// Write function definition if oPowerDeriv is used
writePowerDerivCHeader(mDynamicModelFile);
writeNormcdfCHeader(mDynamicModelFile);
mDynamicModelFile << "void FirstDerivatives(const double *y, double *x, int nb_row_x, double *params, double *steady_state, int it_, double *residual, double *g1, double *v2, double *v3)" << endl
<< "{" << endl;
// Writing Jacobian
for (const auto & first_derivative : first_derivatives)
{
int eq = first_derivative.first.first;
int var = first_derivative.first.second;
expr_t d1 = first_derivative.second;
jacobianHelper(mDynamicModelFile, eq, getDynJacobianCol(var), oCDynamicModel);
mDynamicModelFile << "=";
// oCStaticModel makes reference to the static variables
// oCDynamicModel makes reference to the dynamic variables
d1->writeOutput(mDynamicModelFile, oCDynamicModel, temporary_terms, {}, {});
mDynamicModelFile << ";" << endl;
}
mDynamicModelFile << "}" << endl;
mDynamicModelFile.close();
}
// using compressed sparse row format (CSR)
void
DynamicModel::writeFirstDerivativesC_csr(const string &basename, bool cuda) const
{
string filename = basename + "_first_derivatives.c";
ofstream mDynamicModelFile, mDynamicMexFile;
mDynamicModelFile.open(filename.c_str(), ios::out | ios::binary);
if (!mDynamicModelFile.is_open())
{
cerr << "Error: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
mDynamicModelFile << "/*" << endl
<< " * " << filename << " : Computes first order derivatives of the model for Dynare" << endl
<< " *" << endl
<< " * Warning : this file is generated automatically by Dynare" << endl
<< " * from model " << basename << "(.mod)" << endl
<< " */" << endl
#if defined(_WIN32) || defined(__CYGWIN32__) || defined(__MINGW32__)
<< "#ifdef _MSC_VER" << endl
<< "#define _USE_MATH_DEFINES" << endl
<< "#endif" << endl
#endif
<< "#include <math.h>" << endl;
mDynamicModelFile << "#include <stdlib.h>" << endl;
mDynamicModelFile << "#define max(a, b) (((a) > (b)) ? (a) : (b))" << endl
<< "#define min(a, b) (((a) > (b)) ? (b) : (a))" << endl;
// Write function definition if oPowerDeriv is used
writePowerDerivCHeader(mDynamicModelFile);
writeNormcdfCHeader(mDynamicModelFile);
mDynamicModelFile << "void FirstDerivatives(const double *y, double *x, int nb_row_x, double *params, double *steady_state, int it_, double *residual, int *row_ptr, int *col_ptr, double *value)" << endl
<< "{" << endl;
int cols_nbr = 3*symbol_table.endo_nbr() + symbol_table.exo_nbr() + symbol_table.exo_det_nbr();
// Indexing derivatives in column order
vector<derivative> D;
for (const auto & first_derivative : first_derivatives)
{
int eq = first_derivative.first.first;
int dynvar = first_derivative.first.second;
int lag = getLagByDerivID(dynvar);
int symb_id = getSymbIDByDerivID(dynvar);
SymbolType type = getTypeByDerivID(dynvar);
int tsid = symbol_table.getTypeSpecificID(symb_id);
int col_id;
switch (type)
{
case eEndogenous:
col_id = tsid+(lag+1)*symbol_table.endo_nbr();
break;
case eExogenous:
col_id = tsid+3*symbol_table.endo_nbr();
break;
case eExogenousDet:
col_id = tsid+3*symbol_table.endo_nbr()+symbol_table.exo_nbr();
break;
default:
std::cerr << "This case shouldn't happen" << std::endl;
exit(EXIT_FAILURE);
}
derivative deriv(col_id + eq *cols_nbr, col_id, eq, first_derivative.second);
D.push_back(deriv);
}
sort(D.begin(), D.end(), derivative_less_than());
// writing sparse Jacobian
vector<int> row_ptr(equations.size());
fill(row_ptr.begin(), row_ptr.end(), 0.0);
int k = 0;
for (vector<derivative>::const_iterator it = D.begin(); it != D.end(); ++it)
{
row_ptr[it->row_nbr]++;
mDynamicModelFile << "col_ptr[" << k << "] "
<< "=" << it->col_nbr << ";" << endl;
mDynamicModelFile << "value[" << k << "] = ";
// oCstaticModel makes reference to the static variables
it->value->writeOutput(mDynamicModelFile, oCDynamic2Model, temporary_terms, {}, {});
mDynamicModelFile << ";" << endl;
k++;
}
// row_ptr must point to the relative address of the first element of the row
int cumsum = 0;
mDynamicModelFile << "int row_ptr_data[" << row_ptr.size() + 1 << "] = { 0";
for (int & it : row_ptr)
{
cumsum += it;
mDynamicModelFile << ", " << cumsum;
}
mDynamicModelFile << "};" << endl
<< "int i;" << endl
<< "for (i=0; i < " << row_ptr.size() + 1 << "; i++) row_ptr[i] = row_ptr_data[i];" << endl;
mDynamicModelFile << "}" << endl;
mDynamicModelFile.close();
}
void
DynamicModel::writeSecondDerivativesC_csr(const string &basename, bool cuda) const
{
string filename = basename + "_second_derivatives.c";
ofstream mDynamicModelFile, mDynamicMexFile;
mDynamicModelFile.open(filename.c_str(), ios::out | ios::binary);
if (!mDynamicModelFile.is_open())
{
cerr << "Error: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
mDynamicModelFile << "/*" << endl
<< " * " << filename << " : Computes second order derivatives of the model for Dynare" << endl
<< " *" << endl
<< " * Warning : this file is generated automatically by Dynare" << endl
<< " * from model " << basename << "(.mod)" << endl
<< " */" << endl
#if defined(_WIN32) || defined(__CYGWIN32__) || defined(__MINGW32__)
<< "#ifdef _MSC_VER" << endl
<< "#define _USE_MATH_DEFINES" << endl
<< "#endif" << endl
#endif
<< "#include <math.h>" << endl;
mDynamicModelFile << "#include <stdlib.h>" << endl;
mDynamicModelFile << "#define max(a, b) (((a) > (b)) ? (a) : (b))" << endl
<< "#define min(a, b) (((a) > (b)) ? (b) : (a))" << endl;
// write function definition if oPowerDeriv is used
writePowerDerivCHeader(mDynamicModelFile);
writeNormcdfCHeader(mDynamicModelFile);
mDynamicModelFile << "void SecondDerivatives(const double *y, double *x, int nb_row_x, double *params, double *steady_state, int it_, double *residual, int *row_ptr, int *col_ptr, double *value)" << endl
<< "{" << endl;
// Indexing derivatives in column order
vector<derivative> D;
int hessianColsNbr = dynJacobianColsNbr*dynJacobianColsNbr;
for (const auto & second_derivative : second_derivatives)
{
int eq, var1, var2;
tie(eq, var1, var2) = second_derivative.first;
int id1 = getDynJacobianCol(var1);
int id2 = getDynJacobianCol(var2);
int col_nb = id1 * dynJacobianColsNbr + id2;
derivative deriv(col_nb + eq *hessianColsNbr, col_nb, eq, second_derivative.second);
D.push_back(deriv);
if (id1 != id2)
{
col_nb = id2 * dynJacobianColsNbr + id1;
derivative deriv(col_nb + eq *hessianColsNbr, col_nb, eq, second_derivative.second);
D.push_back(deriv);
}
}
sort(D.begin(), D.end(), derivative_less_than());
// Writing Hessian
vector<int> row_ptr(equations.size());
fill(row_ptr.begin(), row_ptr.end(), 0.0);
int k = 0;
for (vector<derivative>::const_iterator it = D.begin(); it != D.end(); ++it)
{ row_ptr[it->row_nbr]++;
mDynamicModelFile << "col_ptr[" << k << "] "
<< "=" << it->col_nbr << ";" << endl;
mDynamicModelFile << "value[" << k << "] = ";
// oCstaticModel makes reference to the static variables
it->value->writeOutput(mDynamicModelFile, oCStaticModel, temporary_terms, {}, {});
mDynamicModelFile << ";" << endl;
k++;
}
// row_ptr must point to the relative address of the first element of the row
int cumsum = 0;
mDynamicModelFile << "row_ptr = [ 0";
for (int & it : row_ptr)
{
cumsum += it;
mDynamicModelFile << ", " << cumsum;
}
mDynamicModelFile << "];" << endl;
mDynamicModelFile << "}" << endl;
writePowerDeriv(mDynamicModelFile);
writeNormcdf(mDynamicModelFile);
mDynamicModelFile.close();
}
void
DynamicModel::writeThirdDerivativesC_csr(const string &basename, bool cuda) const
{
string filename = basename + "_third_derivatives.c";
ofstream mDynamicModelFile, mDynamicMexFile;
mDynamicModelFile.open(filename.c_str(), ios::out | ios::binary);
if (!mDynamicModelFile.is_open())
{
cerr << "Error: Can't open file " << filename << " for writing" << endl;
exit(EXIT_FAILURE);
}
mDynamicModelFile << "/*" << endl
<< " * " << filename << " : Computes third order derivatives of the model for Dynare" << endl
<< " *" << endl
<< " * Warning : this file is generated automatically by Dynare" << endl
<< " * from model " << basename << "(.mod)" << endl
<< " */" << endl
#if defined(_WIN32) || defined(__CYGWIN32__) || defined(__MINGW32__)
<< "#ifdef _MSC_VER" << endl
<< "#define _USE_MATH_DEFINES" << endl
<< "#endif" << endl
#endif
<< "#include <math.h>" << endl;
mDynamicModelFile << "#include <stdlib.h>" << endl;
mDynamicModelFile << "#define max(a, b) (((a) > (b)) ? (a) : (b))" << endl
<< "#define min(a, b) (((a) > (b)) ? (b) : (a))" << endl;
// Write function definition if oPowerDeriv is used
writePowerDerivCHeader(mDynamicModelFile);
writeNormcdfCHeader(mDynamicModelFile);
mDynamicModelFile << "void ThirdDerivatives(const double *y, double *x, int nb_row_x, double *params, double *steady_state, int it_, double *residual, double *g1, double *v2, double *v3)" << endl
<< "{" << endl;
vector<derivative> D;
int hessianColsNbr = dynJacobianColsNbr*dynJacobianColsNbr;
int thirdDerivativesColsNbr = hessianColsNbr*dynJacobianColsNbr;
for (const auto & third_derivative : third_derivatives)
{
int eq, var1, var2, var3; tie(eq, var1, var2, var3) = third_derivative.first;
int id1 = getDynJacobianCol(var1);
int id2 = getDynJacobianCol(var2);
int id3 = getDynJacobianCol(var3);
// Reference column number for the g3 matrix (with symmetrical derivatives)
vector<long unsigned int> cols;
long unsigned int col_nb = id1 * hessianColsNbr + id2 * dynJacobianColsNbr + id3;
int thirdDColsNbr = hessianColsNbr*dynJacobianColsNbr;
derivative deriv(col_nb + eq *thirdDColsNbr, col_nb, eq, third_derivative.second);
D.push_back(deriv);
cols.push_back(col_nb);
col_nb = id1 * hessianColsNbr + id3 * dynJacobianColsNbr + id2;
if (find(cols.begin(), cols.end(), col_nb) == cols.end())
{
derivative deriv(col_nb + eq *thirdDerivativesColsNbr, col_nb, eq, third_derivative.second);
D.push_back(deriv);
cols.push_back(col_nb);
}
col_nb = id2 * hessianColsNbr + id1 * dynJacobianColsNbr + id3;
if (find(cols.begin(), cols.end(), col_nb) == cols.end())
{
derivative deriv(col_nb + eq *thirdDerivativesColsNbr, col_nb, eq, third_derivative.second);
D.push_back(deriv);
cols.push_back(col_nb);
}
col_nb = id2 * hessianColsNbr + id3 * dynJacobianColsNbr + id1;
if (find(cols.begin(), cols.end(), col_nb) == cols.end())
{
derivative deriv(col_nb + eq *thirdDerivativesColsNbr, col_nb, eq, third_derivative.second);
D.push_back(deriv);
cols.push_back(col_nb);
}
col_nb = id3 * hessianColsNbr + id1 * dynJacobianColsNbr + id2;
if (find(cols.begin(), cols.end(), col_nb) == cols.end())
{
derivative deriv(col_nb + eq *thirdDerivativesColsNbr, col_nb, eq, third_derivative.second);
D.push_back(deriv);
cols.push_back(col_nb);
}
col_nb = id3 * hessianColsNbr + id2 * dynJacobianColsNbr + id1;
if (find(cols.begin(), cols.end(), col_nb) == cols.end())
{
derivative deriv(col_nb + eq *thirdDerivativesColsNbr, col_nb, eq, third_derivative.second);
D.push_back(deriv);
}
}
sort(D.begin(), D.end(), derivative_less_than());
vector<int> row_ptr(equations.size());
fill(row_ptr.begin(), row_ptr.end(), 0.0);
int k = 0;
for (vector<derivative>::const_iterator it = D.begin(); it != D.end(); ++it)
{
row_ptr[it->row_nbr]++;
mDynamicModelFile << "col_ptr[" << k << "] "
<< "=" << it->col_nbr << ";" << endl;
mDynamicModelFile << "value[" << k << "] = ";
// oCstaticModel makes reference to the static variables
it->value->writeOutput(mDynamicModelFile, oCStaticModel, temporary_terms, {}, {});
mDynamicModelFile << ";" << endl;
k++;
}
// row_ptr must point to the relative address of the first element of the row
int cumsum = 0;
mDynamicModelFile << "row_ptr = [ 0";
for (int & it : row_ptr) {
cumsum += it;
mDynamicModelFile << ", " << cumsum;
}
mDynamicModelFile << "];" << endl;
mDynamicModelFile << "}" << endl;
writePowerDeriv(mDynamicModelFile);
writeNormcdf(mDynamicModelFile);
mDynamicModelFile.close();
}
void
DynamicModel::writeCCOutput(ostream &output, const string &basename, bool block_decomposition, bool byte_code, bool use_dll, int order, bool estimation_present) const
{
int lag_presence[3];
// Loop on endogenous variables
for (int endoID = 0; endoID < symbol_table.endo_nbr(); endoID++)
{
// Loop on periods
for (int lag = 0; lag <= 2; lag++)
{
lag_presence[lag] = 1;
try
{
getDerivID(symbol_table.getID(eEndogenous, endoID), lag-1);
}
catch (UnknownDerivIDException &e)
{
lag_presence[lag] = 0;
}
}
if (lag_presence[0] == 1)
if (lag_presence[2] == 1)
output << "zeta_mixed.push_back(" << endoID << ");" << endl;
else
output << "zeta_back.push_back(" << endoID << ");" << endl;
else if (lag_presence[2] == 1)
output << "zeta_fwrd.push_back(" << endoID << ");" << endl;
else
output << "zeta_static.push_back(" << endoID << ");" << endl;
}
output << "nstatic = zeta_static.size();" << endl
<< "nfwrd = zeta_fwrd.size();" << endl
<< "nback = zeta_back.size();" << endl
<< "nmixed = zeta_mixed.size();" << endl;
// Write number of non-zero derivatives
// Use -1 if the derivatives have not been computed
output << endl
<< "NNZDerivatives.push_back(" << NNZDerivatives[0] << ");" << endl;
if (order > 1)
{
output << "NNZDerivatives.push_back(" << NNZDerivatives[1] << ");" << endl;
if (order > 2)
output << "NNZDerivatives.push_back(" << NNZDerivatives[2] << ");" << endl;
else
output << "NNZDerivatives.push_back(-1);" << endl;
}
else
output << "NNZDerivatives.push_back(-1);" << endl
<< "NNZDerivatives.push_back(-1);" << endl;
}
void
DynamicModel::writeJsonOutput(ostream &output) const
{ writeJsonModelEquations(output, false);
output << ", ";
writeJsonXrefs(output);
}
void
DynamicModel::writeJsonXrefsHelper(ostream &output, const map<pair<int, int>, set<int>> &xrefs) const
{
for (auto it = xrefs.begin();
it != xrefs.end(); it++)
{
if (it != xrefs.begin())
output << ", ";
output << "{\"name\": \"" << symbol_table.getName(it->first.first) << "\""
<< ", \"shift\": " << it->first.second
<< ", \"equations\": [";
for (auto it1 = it->second.begin();
it1 != it->second.end(); it1++)
{
if (it1 != it->second.begin())
output << ", ";
output << *it1 + 1;
}
output << "]}";
}
}
void
DynamicModel::writeJsonXrefs(ostream &output) const
{
output << "\"xrefs\": {"
<< "\"parameters\": [";
writeJsonXrefsHelper(output, xref_param);
output << "]"
<< ", \"endogenous\": [";
writeJsonXrefsHelper(output, xref_endo);
output << "]"
<< ", \"exogenous\": [";
writeJsonXrefsHelper(output, xref_exo);
output << "]"
<< ", \"exogenous_deterministic\": [";
writeJsonXrefsHelper(output, xref_exo_det);
output << "]}" << endl;
}
void
DynamicModel::writeJsonOriginalModelOutput(ostream &output) const
{
writeJsonModelEquations(output, false);
}
void
DynamicModel::writeJsonDynamicModelInfo(ostream &output) const
{
output << "\"model_info\": {"
<< "\"lead_lag_incidence\": [";
// Loop on endogenous variables
int nstatic = 0,
nfwrd = 0,
npred = 0,
nboth = 0;
for (int endoID = 0; endoID < symbol_table.endo_nbr(); endoID++)
{
if (endoID != 0)
output << ",";
output << "[";
int sstatic = 1,
sfwrd = 0,
spred = 0,
sboth = 0; // Loop on periods
for (int lag = -max_endo_lag; lag <= max_endo_lead; lag++)
{
// Print variableID if exists with current period, otherwise print 0
try
{
if (lag != -max_endo_lag)
output << ",";
int varID = getDerivID(symbol_table.getID(eEndogenous, endoID), lag);
output << " " << getDynJacobianCol(varID) + 1;
if (lag == -1)
{
sstatic = 0;
spred = 1;
}
else if (lag == 1)
{
if (spred == 1)
{
sboth = 1;
spred = 0;
}
else
{
sstatic = 0;
sfwrd = 1;
}
}
}
catch (UnknownDerivIDException &e)
{
output << " 0";
}
}
nstatic += sstatic;
nfwrd += sfwrd;
npred += spred;
nboth += sboth;
output << "]";
}
output << "], "
<< "\"nstatic\": " << nstatic << ", "
<< "\"nfwrd\": " << nfwrd << ", "
<< "\"npred\": " << npred << ", "
<< "\"nboth\": " << nboth << ", "
<< "\"nsfwrd\": " << nfwrd+nboth << ", "
<< "\"nspred\": " << npred+nboth << ", "
<< "\"ndynamic\": " << npred+nboth+nfwrd << endl;
output << "}";
}
void
DynamicModel::writeJsonComputingPassOutput(ostream &output, bool writeDetails) const
{
ostringstream model_local_vars_output; // Used for storing model local vars
ostringstream model_output; // Used for storing model temp vars and equations
ostringstream jacobian_output; // Used for storing jacobian equations
ostringstream hessian_output; // Used for storing Hessian equations
ostringstream third_derivatives_output; // Used for storing third order derivatives equations
deriv_node_temp_terms_t tef_terms;
temporary_terms_t temp_term_empty;
temporary_terms_t temp_term_union = temporary_terms_res;
temporary_terms_t temp_term_union_m_1;
string concat = "";
int hessianColsNbr = dynJacobianColsNbr * dynJacobianColsNbr;
writeJsonModelLocalVariables(model_local_vars_output, tef_terms);
writeJsonTemporaryTerms(temporary_terms_res, temp_term_union_m_1, model_output, tef_terms, concat);
model_output << ", ";
writeJsonModelEquations(model_output, true);
// Writing Jacobian
temp_term_union_m_1 = temp_term_union;
temp_term_union.insert(temporary_terms_g1.begin(), temporary_terms_g1.end());
concat = "jacobian";
writeJsonTemporaryTerms(temp_term_union, temp_term_union_m_1, jacobian_output, tef_terms, concat);
jacobian_output << ", \"jacobian\": {"
<< " \"nrows\": " << equations.size()
<< ", \"ncols\": " << dynJacobianColsNbr
<< ", \"entries\": [";
for (auto it = first_derivatives.begin();
it != first_derivatives.end(); it++)
{
if (it != first_derivatives.begin())
jacobian_output << ", ";
int eq, var;
tie(eq, var) = it->first;
int col = getDynJacobianCol(var);
expr_t d1 = it->second;
if (writeDetails)
jacobian_output << "{\"eq\": " << eq + 1;
else
jacobian_output << "{\"row\": " << eq + 1;
jacobian_output << ", \"col\": " << col + 1;
if (writeDetails)
jacobian_output << ", \"var\": \"" << symbol_table.getName(getSymbIDByDerivID(var)) << "\""
<< ", \"shift\": " << getLagByDerivID(var);
jacobian_output << ", \"val\": \"";
d1->writeJsonOutput(jacobian_output, temp_term_union, tef_terms);
jacobian_output << "\"}" << endl;
}
jacobian_output << "]}";
// Writing Hessian
temp_term_union_m_1 = temp_term_union;
temp_term_union.insert(temporary_terms_g2.begin(), temporary_terms_g2.end());
concat = "hessian";
writeJsonTemporaryTerms(temp_term_union, temp_term_union_m_1, hessian_output, tef_terms, concat);
hessian_output << ", \"hessian\": {"
<< " \"nrows\": " << equations.size()
<< ", \"ncols\": " << hessianColsNbr
<< ", \"entries\": [";
for (auto it = second_derivatives.begin();
it != second_derivatives.end(); it++)
{
if (it != second_derivatives.begin())
hessian_output << ", ";
int eq, var1, var2;
tie(eq, var1, var2) = it->first;
expr_t d2 = it->second;
int id1 = getDynJacobianCol(var1);
int id2 = getDynJacobianCol(var2);
int col_nb = id1 * dynJacobianColsNbr + id2;
int col_nb_sym = id2 * dynJacobianColsNbr + id1;
if (writeDetails)
hessian_output << "{\"eq\": " << eq + 1;
else
hessian_output << "{\"row\": " << eq + 1;
hessian_output << ", \"col\": [" << col_nb + 1; if (id1 != id2)
hessian_output << ", " << col_nb_sym + 1;
hessian_output << "]";
if (writeDetails)
hessian_output << ", \"var1\": \"" << symbol_table.getName(getSymbIDByDerivID(var1)) << "\""
<< ", \"shift1\": " << getLagByDerivID(var1)
<< ", \"var2\": \"" << symbol_table.getName(getSymbIDByDerivID(var2)) << "\""
<< ", \"shift2\": " << getLagByDerivID(var2);
hessian_output << ", \"val\": \"";
d2->writeJsonOutput(hessian_output, temp_term_union, tef_terms);
hessian_output << "\"}" << endl;
}
hessian_output << "]}";
// Writing third derivatives
temp_term_union_m_1 = temp_term_union;
temp_term_union.insert(temporary_terms_g3.begin(), temporary_terms_g3.end());
concat = "third_derivatives";
writeJsonTemporaryTerms(temp_term_union, temp_term_union_m_1, third_derivatives_output, tef_terms, concat);
third_derivatives_output << ", \"third_derivative\": {"
<< " \"nrows\": " << equations.size()
<< ", \"ncols\": " << hessianColsNbr * dynJacobianColsNbr
<< ", \"entries\": [";
for (auto it = third_derivatives.begin();
it != third_derivatives.end(); it++)
{
if (it != third_derivatives.begin())
third_derivatives_output << ", ";
int eq, var1, var2, var3;
tie(eq, var1, var2, var3) = it->first;
expr_t d3 = it->second;
if (writeDetails)
third_derivatives_output << "{\"eq\": " << eq + 1;
else
third_derivatives_output << "{\"row\": " << eq + 1;
int id1 = getDynJacobianCol(var1);
int id2 = getDynJacobianCol(var2);
int id3 = getDynJacobianCol(var3);
set<int> cols;
cols.insert(id1 * hessianColsNbr + id2 * dynJacobianColsNbr + id3);
cols.insert(id1 * hessianColsNbr + id3 * dynJacobianColsNbr + id2);
cols.insert(id2 * hessianColsNbr + id1 * dynJacobianColsNbr + id3);
cols.insert(id2 * hessianColsNbr + id3 * dynJacobianColsNbr + id1);
cols.insert(id3 * hessianColsNbr + id1 * dynJacobianColsNbr + id2);
cols.insert(id3 * hessianColsNbr + id2 * dynJacobianColsNbr + id1);
third_derivatives_output << ", \"col\": [";
for (auto it2 = cols.begin(); it2 != cols.end(); it2++)
{
if (it2 != cols.begin())
third_derivatives_output << ", ";
third_derivatives_output << *it2 + 1;
}
third_derivatives_output << "]";
if (writeDetails)
third_derivatives_output << ", \"var1\": \"" << symbol_table.getName(getSymbIDByDerivID(var1)) << "\""
<< ", \"shift1\": " << getLagByDerivID(var1)
<< ", \"var2\": \"" << symbol_table.getName(getSymbIDByDerivID(var2)) << "\""
<< ", \"shift2\": " << getLagByDerivID(var2)
<< ", \"var3\": \"" << symbol_table.getName(getSymbIDByDerivID(var3)) << "\""
<< ", \"shift3\": " << getLagByDerivID(var3);
third_derivatives_output << ", \"val\": \"";
d3->writeJsonOutput(third_derivatives_output, temp_term_union, tef_terms); third_derivatives_output << "\"}" << endl;
}
third_derivatives_output << "]}";
if (writeDetails)
output << "\"dynamic_model\": {";
else
output << "\"dynamic_model_simple\": {";
output << model_local_vars_output.str()
<< ", " << model_output.str()
<< ", " << jacobian_output.str()
<< ", " << hessian_output.str()
<< ", " << third_derivatives_output.str()
<< "}";
}
void
DynamicModel::writeJsonParamsDerivativesFile(ostream &output, bool writeDetails) const
{
if (!residuals_params_derivatives.size()
&& !residuals_params_second_derivatives.size()
&& !jacobian_params_derivatives.size()
&& !jacobian_params_second_derivatives.size()
&& !hessian_params_derivatives.size())
return;
ostringstream model_local_vars_output; // Used for storing model local vars
ostringstream model_output; // Used for storing model temp vars and equations
ostringstream jacobian_output; // Used for storing jacobian equations
ostringstream hessian_output; // Used for storing Hessian equations
ostringstream hessian1_output; // Used for storing Hessian equations
ostringstream third_derivs_output; // Used for storing third order derivatives equations
ostringstream third_derivs1_output; // Used for storing third order derivatives equations
deriv_node_temp_terms_t tef_terms;
writeJsonModelLocalVariables(model_local_vars_output, tef_terms);
temporary_terms_t temp_terms_empty;
string concat = "all";
writeJsonTemporaryTerms(params_derivs_temporary_terms, temp_terms_empty, model_output, tef_terms, concat);
jacobian_output << "\"deriv_wrt_params\": {"
<< " \"neqs\": " << equations.size()
<< ", \"nparamcols\": " << symbol_table.param_nbr()
<< ", \"entries\": [";
for (auto it = residuals_params_derivatives.begin();
it != residuals_params_derivatives.end(); it++)
{
if (it != residuals_params_derivatives.begin())
jacobian_output << ", ";
int eq, param;
tie(eq, param) = it->first;
expr_t d1 = it->second;
int param_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param)) + 1;
if (writeDetails)
jacobian_output << "{\"eq\": " << eq + 1;
else
jacobian_output << "{\"row\": " << eq + 1;
jacobian_output << ", \"param_col\": " << param_col + 1;
if (writeDetails)
jacobian_output << ", \"param\": \"" << symbol_table.getName(getSymbIDByDerivID(param)) << "\"";
jacobian_output << ", \"val\": \"";
d1->writeJsonOutput(jacobian_output, params_derivs_temporary_terms, tef_terms);
jacobian_output << "\"}" << endl;
} jacobian_output << "]}";
hessian_output << "\"deriv_jacobian_wrt_params\": {"
<< " \"neqs\": " << equations.size()
<< ", \"nvarcols\": " << dynJacobianColsNbr
<< ", \"nparamcols\": " << symbol_table.param_nbr()
<< ", \"entries\": [";
for (auto it = jacobian_params_derivatives.begin();
it != jacobian_params_derivatives.end(); it++)
{
if (it != jacobian_params_derivatives.begin())
hessian_output << ", ";
int eq, var, param;
tie(eq, var, param) = it->first;
expr_t d2 = it->second;
int var_col = getDynJacobianCol(var) + 1;
int param_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param)) + 1;
if (writeDetails)
hessian_output << "{\"eq\": " << eq + 1;
else
hessian_output << "{\"row\": " << eq + 1;
hessian_output << ", \"var_col\": " << var_col + 1
<< ", \"param_col\": " << param_col + 1;
if (writeDetails)
hessian_output << ", \"var\": \"" << symbol_table.getName(getSymbIDByDerivID(var)) << "\""
<< ", \"lag\": " << getLagByDerivID(var)
<< ", \"param\": \"" << symbol_table.getName(getSymbIDByDerivID(param)) << "\"";
hessian_output << ", \"val\": \"";
d2->writeJsonOutput(hessian_output, params_derivs_temporary_terms, tef_terms);
hessian_output << "\"}" << endl;
}
hessian_output << "]}";
hessian1_output << "\"second_deriv_residuals_wrt_params\": {"
<< " \"nrows\": " << equations.size()
<< ", \"nparam1cols\": " << symbol_table.param_nbr()
<< ", \"nparam2cols\": " << symbol_table.param_nbr()
<< ", \"entries\": [";
for (auto it = residuals_params_second_derivatives.begin();
it != residuals_params_second_derivatives.end(); ++it)
{
if (it != residuals_params_second_derivatives.begin())
hessian1_output << ", ";
int eq, param1, param2;
tie(eq, param1, param2) = it->first;
expr_t d2 = it->second;
int param1_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param1)) + 1;
int param2_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param2)) + 1;
if (writeDetails)
hessian1_output << "{\"eq\": " << eq + 1;
else
hessian1_output << "{\"row\": " << eq + 1;
hessian1_output << ", \"param1_col\": " << param1_col + 1
<< ", \"param2_col\": " << param2_col + 1;
if (writeDetails)
hessian1_output << ", \"param1\": \"" << symbol_table.getName(getSymbIDByDerivID(param1)) << "\""
<< ", \"param2\": \"" << symbol_table.getName(getSymbIDByDerivID(param2)) << "\"";
hessian1_output << ", \"val\": \"";
d2->writeJsonOutput(hessian1_output, params_derivs_temporary_terms, tef_terms);
hessian1_output << "\"}" << endl; }
hessian1_output << "]}";
third_derivs_output << "\"second_deriv_jacobian_wrt_params\": {"
<< " \"neqs\": " << equations.size()
<< ", \"nvarcols\": " << dynJacobianColsNbr
<< ", \"nparam1cols\": " << symbol_table.param_nbr()
<< ", \"nparam2cols\": " << symbol_table.param_nbr()
<< ", \"entries\": [";
for (auto it = jacobian_params_second_derivatives.begin();
it != jacobian_params_second_derivatives.end(); ++it)
{
if (it != jacobian_params_second_derivatives.begin())
third_derivs_output << ", ";
int eq, var, param1, param2;
tie(eq, var, param1, param2) = it->first;
expr_t d2 = it->second;
int var_col = getDynJacobianCol(var) + 1;
int param1_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param1)) + 1;
int param2_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param2)) + 1;
if (writeDetails)
third_derivs_output << "{\"eq\": " << eq + 1;
else
third_derivs_output << "{\"row\": " << eq + 1;
third_derivs_output << ", \"var_col\": " << var_col + 1
<< ", \"param1_col\": " << param1_col + 1
<< ", \"param2_col\": " << param2_col + 1;
if (writeDetails)
third_derivs_output << ", \"var\": \"" << symbol_table.getName(var) << "\""
<< ", \"lag\": " << getLagByDerivID(var)
<< ", \"param1\": \"" << symbol_table.getName(getSymbIDByDerivID(param1)) << "\""
<< ", \"param2\": \"" << symbol_table.getName(getSymbIDByDerivID(param2)) << "\"";
third_derivs_output << ", \"val\": \"";
d2->writeJsonOutput(third_derivs_output, params_derivs_temporary_terms, tef_terms);
third_derivs_output << "\"}" << endl;
}
third_derivs_output << "]}" << endl;
third_derivs1_output << "\"derivative_hessian_wrt_params\": {"
<< " \"neqs\": " << equations.size()
<< ", \"nvar1cols\": " << dynJacobianColsNbr
<< ", \"nvar2cols\": " << dynJacobianColsNbr
<< ", \"nparamcols\": " << symbol_table.param_nbr()
<< ", \"entries\": [";
for (auto it = hessian_params_derivatives.begin();
it != hessian_params_derivatives.end(); ++it)
{
if (it != hessian_params_derivatives.begin())
third_derivs1_output << ", ";
int eq, var1, var2, param;
tie(eq, var1, var2, param) = it->first;
expr_t d2 = it->second;
int var1_col = getDynJacobianCol(var1) + 1;
int var2_col = getDynJacobianCol(var2) + 1;
int param_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param)) + 1;
if (writeDetails)
third_derivs1_output << "{\"eq\": " << eq + 1;
else
third_derivs1_output << "{\"row\": " << eq + 1;
third_derivs1_output << ", \"var1_col\": " << var1_col + 1
<< ", \"var2_col\": " << var2_col + 1 << ", \"param_col\": " << param_col + 1;
if (writeDetails)
third_derivs1_output << ", \"var1\": \"" << symbol_table.getName(getSymbIDByDerivID(var1)) << "\""
<< ", \"lag1\": " << getLagByDerivID(var1)
<< ", \"var2\": \"" << symbol_table.getName(getSymbIDByDerivID(var2)) << "\""
<< ", \"lag2\": " << getLagByDerivID(var2)
<< ", \"param\": \"" << symbol_table.getName(getSymbIDByDerivID(param)) << "\"";
third_derivs1_output << ", \"val\": \"";
d2->writeJsonOutput(third_derivs1_output, params_derivs_temporary_terms, tef_terms);
third_derivs1_output << "\"}" << endl;
}
third_derivs1_output << "]}" << endl;
if (writeDetails)
output << "\"dynamic_model_params_derivative\": {";
else
output << "\"dynamic_model_params_derivatives_simple\": {";
output << model_local_vars_output.str()
<< ", " << model_output.str()
<< ", " << jacobian_output.str()
<< ", " << hessian_output.str()
<< ", " << hessian1_output.str()
<< ", " << third_derivs_output.str()
<< ", " << third_derivs1_output.str()
<< "}";
}