preprocessor/src/StaticModel.cc

2883 lines
125 KiB
C++

/*
* Copyright (C) 2003-2017 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 "StaticModel.hh"
// For mkdir() and chdir()
#ifdef _WIN32
# include <direct.h>
#else
# include <unistd.h>
# include <sys/stat.h>
# include <sys/types.h>
#endif
StaticModel::StaticModel(SymbolTable &symbol_table_arg,
NumericalConstants &num_constants_arg,
ExternalFunctionsTable &external_functions_table_arg) :
ModelTree(symbol_table_arg, num_constants_arg, external_functions_table_arg),
global_temporary_terms(true)
{
}
void
StaticModel::compileDerivative(ofstream &code_file, unsigned int &instruction_number, int eq, int symb_id, map_idx_t &map_idx, temporary_terms_t temporary_terms) const
{
first_derivatives_t::const_iterator it = first_derivatives.find(make_pair(eq, getDerivID(symbol_table.getID(eEndogenous, symb_id), 0)));
if (it != first_derivatives.end())
(it->second)->compile(code_file, instruction_number, false, temporary_terms, map_idx, false, false);
else
{
FLDZ_ fldz;
fldz.write(code_file, instruction_number);
}
}
void
StaticModel::compileChainRuleDerivative(ofstream &code_file, unsigned int &instruction_number, int eqr, int varr, int lag, map_idx_t &map_idx, temporary_terms_t temporary_terms) const
{
map<pair<int, pair<int, int> >, expr_t>::const_iterator it = first_chain_rule_derivatives.find(make_pair(eqr, make_pair(varr, lag)));
if (it != first_chain_rule_derivatives.end())
(it->second)->compile(code_file, instruction_number, false, temporary_terms, map_idx, false, false);
else
{
FLDZ_ fldz;
fldz.write(code_file, instruction_number);
}
}
void
StaticModel::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_local = vector< vector<temporary_terms_t> >(nb_blocks);
v_temporary_terms_inuse = vector<temporary_terms_inuse_t>(nb_blocks);
map_idx2 = vector<map_idx_t>(nb_blocks);
temporary_terms.clear();
//local temporay terms
for (unsigned int block = 0; block < nb_blocks; block++)
{
map<expr_t, int> reference_count_local;
reference_count_local.clear();
map<expr_t, pair<int, int> > first_occurence_local;
first_occurence_local.clear();
temporary_terms_t temporary_terms_l;
temporary_terms_l.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_local[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_local, temporary_terms_l, first_occurence_local, block, v_temporary_terms_local, i);
else
{
eq_node = (BinaryOpNode *) getBlockEquationExpr(block, i);
eq_node->computeTemporaryTerms(reference_count_local, temporary_terms_l, first_occurence_local, block, v_temporary_terms_local, 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_local, temporary_terms_l, first_occurence_local, block, v_temporary_terms_local, block_size-1);
}
set<int> temporary_terms_in_use;
temporary_terms_in_use.clear();
v_temporary_terms_inuse[block] = temporary_terms_in_use;
computeTemporaryTermsMapping(temporary_terms_l, map_idx2[block]);
}
// global temporay terms
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 (unsigned int block = 0; block < nb_blocks; block++)
{
// Collecte 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 (int i = 0; i < (int) getBlockSize(block); i++)
for (temporary_terms_t::const_iterator it = v_temporary_terms[block][i].begin();
it != v_temporary_terms[block][i].end(); it++)
(*it)->collectTemporary_terms(temporary_terms, temporary_terms_in_use, block);
v_temporary_terms_inuse[block] = temporary_terms_in_use;
}
computeTemporaryTermsMapping(temporary_terms, map_idx);
}
void
StaticModel::computeTemporaryTermsMapping(temporary_terms_t &temporary_terms, map_idx_t &map_idx)
{
// Add a mapping form node ID to temporary terms order
int j = 0;
for (temporary_terms_t::const_iterator it = temporary_terms.begin();
it != temporary_terms.end(); it++)
map_idx[(*it)->idx] = j++;
}
void
StaticModel::writeModelEquationsOrdered_M(const string &static_basename) const
{
string tmp_s, sps;
ostringstream tmp_output, tmp1_output, global_output;
expr_t lhs = NULL, rhs = NULL;
BinaryOpNode *eq_node;
map<expr_t, int> reference_count;
temporary_terms_t local_temporary_terms;
ofstream output;
vector<int> feedback_variables;
deriv_node_temp_terms_t tef_terms;
ExprNodeOutputType local_output_type;
local_output_type = oMatlabStaticModelSparse;
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
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;
tmp1_output.str("");
tmp1_output << static_basename << "_" << block+1 << ".m";
output.open(tmp1_output.str().c_str(), ios::out | ios::binary);
output << "%\n";
output << "% " << tmp1_output.str() << " : Computes static 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 = " << static_basename << "_" << block+1 << "(y, x, params)\n";
else
output << "function [residual, y, g1] = " << static_basename << "_" << block+1 << "(y, x, params)\n";
BlockType block_type;
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;
output << " global options_;" << endl;
//The Temporary terms
if (simulation_type != EVALUATE_BACKWARD && simulation_type != EVALUATE_FORWARD)
output << " g1 = spalloc(" << block_mfs << ", " << block_mfs << ", " << derivative_endo[block].size() << ");" << endl;
if (v_temporary_terms_inuse[block].size())
{
tmp_output.str("");
for (temporary_terms_inuse_t::const_iterator it = v_temporary_terms_inuse[block].begin();
it != v_temporary_terms_inuse[block].end(); it++)
tmp_output << " T" << *it;
output << " global" << tmp_output.str() << ";\n";
}
if (simulation_type != EVALUATE_BACKWARD && simulation_type != EVALUATE_FORWARD)
output << " residual=zeros(" << block_mfs << ",1);\n";
// The equations
for (unsigned int i = 0; i < block_size; i++)
{
if (!global_temporary_terms)
local_temporary_terms = v_temporary_terms[block][i];
temporary_terms_t tt2;
tt2.clear();
if (v_temporary_terms[block].size())
{
output << " " << "% //Temporary variables" << endl;
for (temporary_terms_t::const_iterator it = v_temporary_terms[block][i].begin();
it != v_temporary_terms[block][i].end(); it++)
{
if (dynamic_cast<AbstractExternalFunctionNode *>(*it) != NULL)
(*it)->writeExternalFunctionOutput(output, local_output_type, tt2, 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:
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) << endl;
output << " " << "residual(" << i+1-block_recursive << ") = (";
goto end;
default:
end:
output << tmp_output.str();
output << ") - (";
rhs->writeOutput(output, local_output_type, local_temporary_terms);
output << ");\n";
}
}
// The Jacobian if we have to solve the block
if (simulation_type == SOLVE_BACKWARD_SIMPLE || simulation_type == SOLVE_FORWARD_SIMPLE
|| simulation_type == SOLVE_BACKWARD_COMPLETE || simulation_type == SOLVE_FORWARD_COMPLETE)
output << " " << sps << "% Jacobian " << endl;
switch (simulation_type)
{
case SOLVE_BACKWARD_SIMPLE:
case SOLVE_FORWARD_SIMPLE:
case SOLVE_BACKWARD_COMPLETE:
case SOLVE_FORWARD_COMPLETE:
for (block_derivatives_equation_variable_laglead_nodeid_t::const_iterator 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;
output << " g1(" << eq+1-block_recursive << ", " << var+1-block_recursive << ") = ";
id->writeOutput(output, local_output_type, local_temporary_terms);
output << "; % variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, varr))
<< "(" << 0
<< ") " << varr+1
<< ", equation=" << eqr+1 << endl;
}
break;
default:
break;
}
output << "end" << endl;
output.close();
}
}
void
StaticModel::writeModelEquationsCode(const string file_name, const string bin_basename, 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;
Write_Inf_To_Bin_File(file_name, u_count_int, file_open, false, symbol_table.endo_nbr());
file_open = true;
//Temporary variables declaration
FDIMST_ fdimst(temporary_terms.size());
fdimst.write(code_file, instruction_number);
FBEGINBLOCK_ fbeginblock(symbol_table.endo_nbr(),
SOLVE_FORWARD_COMPLETE,
0,
symbol_table.endo_nbr(),
variable_reordered,
equation_reordered,
false,
symbol_table.endo_nbr(),
0,
0,
u_count_int,
symbol_table.endo_nbr()
);
fbeginblock.write(code_file, instruction_number);
// Add a mapping form node ID to temporary terms order
int j = 0;
for (temporary_terms_t::const_iterator it = temporary_terms.begin();
it != temporary_terms.end(); it++)
map_idx[(*it)->idx] = j++;
compileTemporaryTerms(code_file, instruction_number, temporary_terms, map_idx, false, false);
compileModelEquations(code_file, instruction_number, temporary_terms, map_idx, false, 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<int, int> > > derivatives;
derivatives.resize(symbol_table.endo_nbr());
count_u = symbol_table.endo_nbr();
for (first_derivatives_t::const_iterator it = first_derivatives.begin();
it != first_derivatives.end(); it++)
{
int deriv_id = it->first.second;
if (getTypeByDerivID(deriv_id) == eEndogenous)
{
expr_t d1 = it->second;
unsigned int eq = it->first.first;
int symb = getSymbIDByDerivID(deriv_id);
unsigned int var = symbol_table.getTypeSpecificID(symb);
FNUMEXPR_ fnumexpr(FirstEndoDerivative, eq, var);
fnumexpr.write(code_file, instruction_number);
if (!derivatives[eq].size())
derivatives[eq].clear();
derivatives[eq].push_back(make_pair(var, count_u));
d1->compile(code_file, instruction_number, false, temporary_terms, map_idx, false, false);
FSTPSU_ fstpsu(count_u);
fstpsu.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<int, int> >::const_iterator it = derivatives[i].begin();
it != derivatives[i].end(); it++)
{
FLDSU_ fldsu(it->second);
fldsu.write(code_file, instruction_number);
FLDSV_ fldsv(eEndogenous, it->first);
fldsv.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);
}
FSTPSU_ fstpsu(i);
fstpsu.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;
temporary_terms_t tt2;
tt2.clear();
temporary_terms_t tt3;
tt3.clear();
// The Jacobian if we have to solve the block determinsitic bloc
for (first_derivatives_t::const_iterator it = first_derivatives.begin();
it != first_derivatives.end(); it++)
{
int deriv_id = it->first.second;
if (getTypeByDerivID(deriv_id) == eEndogenous)
{
expr_t d1 = it->second;
unsigned int eq = it->first.first;
int symb = getSymbIDByDerivID(deriv_id);
unsigned int var = symbol_table.getTypeSpecificID(symb);
FNUMEXPR_ fnumexpr(FirstEndoDerivative, eq, var);
fnumexpr.write(code_file, instruction_number);
if (!derivatives[eq].size())
derivatives[eq].clear();
derivatives[eq].push_back(make_pair(var, count_u));
d1->compile(code_file, instruction_number, false, temporary_terms, map_idx, false, false);
FSTPG2_ fstpg2(eq, var);
fstpg2.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
StaticModel::writeModelEquationsCode_Block(const string file_name, const string bin_basename, map_idx_t map_idx, vector<map_idx_t> map_idx2) 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 = NULL, rhs = NULL;
BinaryOpNode *eq_node;
Uff Uf[symbol_table.endo_nbr()];
map<expr_t, int> reference_count;
vector<int> feedback_variables;
deriv_node_temp_terms_t tef_terms;
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
FDIMST_ fdimst(temporary_terms.size());
fdimst.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;
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);
file_open = true;
}
FBEGINBLOCK_ fbeginblock(block_mfs,
simulation_type,
getBlockFirstEquation(block),
block_size,
variable_reordered,
equation_reordered,
blocks_linear[block],
symbol_table.endo_nbr(),
0,
0,
u_count_int,
/*symbol_table.endo_nbr()*/ block_size
);
fbeginblock.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;
for (i = 0; i < (int) block_size; i++)
{
//The Temporary terms
temporary_terms_t tt2;
tt2.clear();
if (v_temporary_terms[block].size())
{
for (temporary_terms_t::const_iterator it = v_temporary_terms[block][i].begin();
it != v_temporary_terms[block][i].end(); it++)
{
if (dynamic_cast<AbstractExternalFunctionNode *>(*it) != NULL)
(*it)->compileExternalFunctionOutput(code_file, instruction_number, false, tt2, map_idx, false, 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, false, false, tef_terms);
FSTPST_ fstpst((int)(map_idx.find((*it)->idx)->second));
fstpst.write(code_file, instruction_number);
// Insert current node into tt2
tt2.insert(*it);
}
}
// The equations
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, false, false);
lhs->compile(code_file, instruction_number, true, temporary_terms, map_idx, false, 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, false, false);
lhs->compile(code_file, instruction_number, true, temporary_terms, map_idx, false, false);
}
break;
case SOLVE_BACKWARD_COMPLETE:
case SOLVE_FORWARD_COMPLETE:
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 = NULL;
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, false, false);
rhs->compile(code_file, instruction_number, false, temporary_terms, map_idx, false, 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);
// The Jacobian if we have to solve the block
if (simulation_type != EVALUATE_BACKWARD
&& simulation_type != EVALUATE_FORWARD)
{
switch (simulation_type)
{
case SOLVE_BACKWARD_SIMPLE:
case SOLVE_FORWARD_SIMPLE:
{
FNUMEXPR_ fnumexpr(FirstEndoDerivative, 0, 0);
fnumexpr.write(code_file, instruction_number);
}
compileDerivative(code_file, instruction_number, getBlockEquationID(block, 0), getBlockVariableID(block, 0), map_idx, temporary_terms);
{
FSTPG_ fstpg(0);
fstpg.write(code_file, instruction_number);
}
break;
case SOLVE_BACKWARD_COMPLETE:
case SOLVE_FORWARD_COMPLETE:
count_u = feedback_variables.size();
for (block_derivatives_equation_variable_laglead_nodeid_t::const_iterator 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);
if (eq >= block_recursive && var >= block_recursive)
{
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 = NULL;
Uf[eqr].Ufl->u = count_u;
Uf[eqr].Ufl->var = varr;
FNUMEXPR_ fnumexpr(FirstEndoDerivative, eqr, varr);
fnumexpr.write(code_file, instruction_number);
compileChainRuleDerivative(code_file, instruction_number, eqr, varr, 0, map_idx, temporary_terms);
FSTPSU_ fstpsu(count_u);
fstpsu.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)
{
FLDSU_ fldsu(Uf[v].Ufl->u);
fldsu.write(code_file, instruction_number);
FLDSV_ fldsv(eEndogenous, Uf[v].Ufl->var);
fldsv.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);
FSTPSU_ fstpsu(i - block_recursive);
fstpsu.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;
temporary_terms_t tt2;
tt2.clear();
temporary_terms_t tt3;
tt3.clear();
deriv_node_temp_terms_t tef_terms2;
for (i = 0; i < (int) block_size; i++)
{
if (v_temporary_terms_local[block].size())
{
for (temporary_terms_t::const_iterator it = v_temporary_terms_local[block][i].begin();
it != v_temporary_terms_local[block][i].end(); it++)
{
if (dynamic_cast<AbstractExternalFunctionNode *>(*it) != NULL)
(*it)->compileExternalFunctionOutput(code_file, instruction_number, false, tt3, map_idx2[block], false, false, tef_terms2);
FNUMEXPR_ fnumexpr(TemporaryTerm, (int)(map_idx2[block].find((*it)->idx)->second));
fnumexpr.write(code_file, instruction_number);
(*it)->compile(code_file, instruction_number, false, tt3, map_idx2[block], false, false, tef_terms);
FSTPST_ fstpst((int)(map_idx2[block].find((*it)->idx)->second));
fstpst.write(code_file, instruction_number);
// Insert current node into tt2
tt3.insert(*it);
tt2.insert(*it);
}
}
// The equations
int variable_ID, equation_ID;
EquationType equ_type;
switch (simulation_type)
{
evaluation_l:
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, tt2, map_idx2[block], false, false);
lhs->compile(code_file, instruction_number, true, tt2, map_idx2[block], false, 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, tt2, map_idx2[block], false, false);
lhs->compile(code_file, instruction_number, true, tt2, map_idx2[block], false, false);
}
break;
case SOLVE_BACKWARD_COMPLETE:
case SOLVE_FORWARD_COMPLETE:
if (i < (int) block_recursive)
goto evaluation_l;
variable_ID = getBlockVariableID(block, i);
equation_ID = getBlockEquationID(block, i);
feedback_variables.push_back(variable_ID);
Uf[equation_ID].Ufl = NULL;
goto end_l;
default:
end_l:
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, tt2, map_idx2[block], false, false);
rhs->compile(code_file, instruction_number, false, tt2, map_idx2[block], false, false);
FBINARY_ fbinary(oMinus);
fbinary.write(code_file, instruction_number);
FSTPR_ fstpr(i - block_recursive);
fstpr.write(code_file, instruction_number);
}
}
FENDEQU_ fendequ_l;
fendequ_l.write(code_file, instruction_number);
// The Jacobian if we have to solve the block determinsitic bloc
switch (simulation_type)
{
case SOLVE_BACKWARD_SIMPLE:
case SOLVE_FORWARD_SIMPLE:
{
FNUMEXPR_ fnumexpr(FirstEndoDerivative, 0, 0);
fnumexpr.write(code_file, instruction_number);
}
compileDerivative(code_file, instruction_number, getBlockEquationID(block, 0), getBlockVariableID(block, 0), map_idx2[block], tt2 /*temporary_terms*/);
{
FSTPG2_ fstpg2(0, 0);
fstpg2.write(code_file, instruction_number);
}
break;
case EVALUATE_BACKWARD:
case EVALUATE_FORWARD:
case SOLVE_BACKWARD_COMPLETE:
case SOLVE_FORWARD_COMPLETE:
count_u = feedback_variables.size();
for (block_derivatives_equation_variable_laglead_nodeid_t::const_iterator 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);
FNUMEXPR_ fnumexpr(FirstEndoDerivative, eqr, varr, 0);
fnumexpr.write(code_file, instruction_number);
compileChainRuleDerivative(code_file, instruction_number, eqr, varr, 0, map_idx2[block], tt2 /*temporary_terms*/);
FSTPG2_ fstpg2(eq, var);
fstpg2.write(code_file, instruction_number);
}
break;
default:
break;
}
// 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
StaticModel::Write_Inf_To_Bin_File_Block(const string &static_basename, const string &bin_basename, const int &num,
int &u_count_int, bool &file_open) const
{
int j;
std::ofstream SaveCode;
if (file_open)
SaveCode.open((bin_basename + "_static.bin").c_str(), ios::out | ios::in | ios::binary | ios::ate);
else
SaveCode.open((bin_basename + "_static.bin").c_str(), ios::out | ios::binary);
if (!SaveCode.is_open())
{
cerr << "Error : Can't open file \"" << bin_basename << "_static.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 (block_derivatives_equation_variable_laglead_nodeid_t::const_iterator 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 = 0;
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;
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++;
}
}
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();
}
map<pair<int, pair<int, int > >, expr_t>
StaticModel::collect_first_order_derivatives_endogenous()
{
map<pair<int, pair<int, int > >, expr_t> endo_derivatives;
for (first_derivatives_t::iterator it2 = first_derivatives.begin();
it2 != first_derivatives.end(); it2++)
{
if (getTypeByDerivID(it2->first.second) == eEndogenous)
{
int eq = it2->first.first;
int var = symbol_table.getTypeSpecificID(getSymbIDByDerivID(it2->first.second));
int lag = 0;
endo_derivatives[make_pair(eq, make_pair(var, lag))] = it2->second;
}
}
return endo_derivatives;
}
void
StaticModel::computingPass(const eval_context_t &eval_context, bool no_tmp_terms, bool hessian, bool thirdDerivatives, int paramsDerivsOrder, bool block, bool bytecode, const bool nopreprocessoroutput)
{
initializeVariablesAndEquations();
vector<BinaryOpNode *> neweqs;
for (unsigned int eq = 0; eq < equations.size() - aux_equations.size(); eq++)
{
expr_t eq_tmp = equations[eq]->substituteStaticAuxiliaryVariable();
neweqs.push_back(dynamic_cast<BinaryOpNode *>(eq_tmp->toStatic(*this)));
}
for (unsigned int eq = 0; eq < aux_equations.size(); eq++)
{
expr_t eq_tmp = aux_equations[eq]->substituteStaticAuxiliaryDefinition();
neweqs.push_back(dynamic_cast<BinaryOpNode *>(eq_tmp->toStatic(*this)));
}
equations.clear();
copy(neweqs.begin(), neweqs.end(), back_inserter(equations));
// Compute derivatives w.r. to all endogenous, and possibly exogenous and exogenous deterministic
set<int> vars;
for (int i = 0; i < symbol_table.endo_nbr(); i++)
{
int id = symbol_table.getID(eEndogenous, i);
// if (!symbol_table.isAuxiliaryVariableButNotMultiplier(id))
vars.insert(getDerivID(id, 0));
}
// Launch computations
if (!nopreprocessoroutput)
cout << "Computing static model derivatives:" << endl
<< " - order 1" << endl;
first_derivatives.clear();
computeJacobian(vars);
if (hessian)
{
if (!nopreprocessoroutput)
cout << " - order 2" << endl;
computeHessian(vars);
}
if (thirdDerivatives)
{
if (!nopreprocessoroutput)
cout << " - order 3" << endl;
computeThirdDerivatives(vars);
}
if (paramsDerivsOrder > 0)
{
if (!nopreprocessoroutput)
cout << " - derivatives of Jacobian/Hessian w.r. to parameters" << endl;
computeParamsDerivatives(paramsDerivsOrder);
if (!no_tmp_terms)
computeParamsDerivativesTemporaryTerms();
}
if (block)
{
jacob_map_t contemporaneous_jacobian, static_jacobian;
vector<unsigned int> n_static, n_forward, n_backward, n_mixed;
// 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, false, 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();
global_temporary_terms = true;
if (!no_tmp_terms)
computeTemporaryTermsOrdered();
}
else
{
if (!no_tmp_terms)
{
computeTemporaryTerms(true);
if (bytecode)
computeTemporaryTermsMapping(temporary_terms, map_idx);
}
}
}
void
StaticModel::writeStaticMFile(const string &func_name) const
{
// Writing comments and function definition command
string filename = func_name + "_static.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 [residual, g1, g2, g3] = " << func_name + "_static(y, x, params)" << endl
<< "%" << endl
<< "% Status : Computes static model for Dynare" << endl
<< "%" << endl
<< "% Inputs : " << endl
<< "% y [M_.endo_nbr by 1] double vector of endogenous variables in declaration order" << endl
<< "% x [M_.exo_nbr by 1] double vector of exogenous variables in declaration order" << endl
<< "% params [M_.param_nbr by 1] double vector of parameter values in declaration order" << endl
<< "%" << endl
<< "% Outputs:" << endl
<< "% residual [M_.endo_nbr by 1] double vector of residuals of the static model equations " << endl
<< "% in order of declaration of the equations." << endl
<< "% Dynare may prepend or append auxiliary equations, see M_.aux_vars" << endl
<< "% g1 [M_.endo_nbr by M_.endo_nbr] double Jacobian matrix of the static model equations;" << endl
<< "% columns: variables in declaration order" << endl
<< "% rows: equations in order of declaration" << endl
<< "% g2 [M_.endo_nbr by (M_.endo_nbr)^2] double Hessian matrix of the static model equations;" << endl
<< "% columns: variables in declaration order" << endl
<< "% rows: equations in order of declaration" << endl
<< "% g3 [M_.endo_nbr by (M_.endo_nbr)^3] double Third derivatives matrix of the static model equations;" << endl
<< "% columns: variables in declaration order" << endl
<< "% rows: equations in order of declaration" << endl
<< "%" << endl
<< "%" << endl
<< "% Warning : this file is generated automatically by Dynare" << endl
<< "% from model file (.mod)" << endl << endl;
writeStaticModel(output, false, false);
output << "end" << endl;
output.close();
}
void
StaticModel::writeStaticModel(ostream &StaticOutput, bool use_dll, bool julia) const
{
ostringstream model_local_vars_output; // Used for storing model local vars
ostringstream model_output; // Used for storing model
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
ostringstream for_sym;
ExprNodeOutputType output_type = (use_dll ? oCStaticModel :
julia ? oJuliaStaticModel : oMatlabStaticModel);
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;
writeModelLocalVariables(model_local_vars_output, output_type, tef_terms);
writeTemporaryTerms(temporary_terms_res, temp_term_union_m_1, model_output, output_type, tef_terms);
writeModelEquations(model_output, output_type);
int nrows = equations.size();
int JacobianColsNbr = symbol_table.endo_nbr();
int hessianColsNbr = JacobianColsNbr*JacobianColsNbr;
// Write Jacobian w.r. to endogenous only
temp_term_union_m_1 = temp_term_union;
temp_term_union.insert(temporary_terms_g1.begin(), temporary_terms_g1.end());
if (!first_derivatives.empty())
if (julia)
writeTemporaryTerms(temp_term_union, temp_term_empty, jacobian_output, output_type, tef_terms);
else
writeTemporaryTerms(temp_term_union, temp_term_union_m_1, jacobian_output, output_type, tef_terms);
for (first_derivatives_t::const_iterator it = first_derivatives.begin();
it != first_derivatives.end(); it++)
{
int eq = it->first.first;
int symb_id = getSymbIDByDerivID(it->first.second);
expr_t d1 = it->second;
jacobianHelper(jacobian_output, eq, symbol_table.getTypeSpecificID(symb_id), output_type);
jacobian_output << "=";
d1->writeOutput(jacobian_output, output_type, temp_term_union, tef_terms);
jacobian_output << ";" << endl;
}
int g2ncols = symbol_table.endo_nbr() * symbol_table.endo_nbr();
// Write Hessian w.r. to endogenous only (only if 2nd order derivatives have been computed)
temp_term_union_m_1 = temp_term_union;
temp_term_union.insert(temporary_terms_g2.begin(), temporary_terms_g2.end());
if (!second_derivatives.empty())
if (julia)
writeTemporaryTerms(temp_term_union, temp_term_empty, hessian_output, output_type, tef_terms);
else
writeTemporaryTerms(temp_term_union, temp_term_union_m_1, hessian_output, output_type, tef_terms);
int k = 0; // Keep the line of a 2nd derivative in v2
for (second_derivatives_t::const_iterator it = second_derivatives.begin();
it != second_derivatives.end(); it++)
{
int eq = it->first.first;
int symb_id1 = getSymbIDByDerivID(it->first.second.first);
int symb_id2 = getSymbIDByDerivID(it->first.second.second);
expr_t d2 = it->second;
int tsid1 = symbol_table.getTypeSpecificID(symb_id1);
int tsid2 = symbol_table.getTypeSpecificID(symb_id2);
int col_nb = tsid1*symbol_table.endo_nbr()+tsid2;
int col_nb_sym = tsid2*symbol_table.endo_nbr()+tsid1;
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, 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, tef_terms);
hessian_output << ";" << endl;
k++;
}
// Treating symetric elements
if (symb_id1 != symb_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
temp_term_union_m_1 = temp_term_union;
temp_term_union.insert(temporary_terms_g3.begin(), temporary_terms_g3.end());
if (!third_derivatives.empty())
if (julia)
writeTemporaryTerms(temp_term_union, temp_term_empty, third_derivatives_output, output_type, tef_terms);
else
writeTemporaryTerms(temp_term_union, temp_term_union_m_1, third_derivatives_output, output_type, tef_terms);
k = 0; // Keep the line of a 3rd derivative in v3
for (third_derivatives_t::const_iterator it = third_derivatives.begin();
it != third_derivatives.end(); it++)
{
int eq = it->first.first;
int var1 = it->first.second.first;
int var2 = it->first.second.second.first;
int var3 = it->first.second.second.second;
expr_t d3 = it->second;
int id1 = getSymbIDByDerivID(var1);
int id2 = getSymbIDByDerivID(var2);
int id3 = getSymbIDByDerivID(var3);
// Reference column number for the g3 matrix
int ref_col = id1 * hessianColsNbr + id2 * JacobianColsNbr + id3;
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, 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, 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 * JacobianColsNbr + id2);
cols.insert(id2 * hessianColsNbr + id1 * JacobianColsNbr + id3);
cols.insert(id2 * hessianColsNbr + id3 * JacobianColsNbr + id1);
cols.insert(id3 * hessianColsNbr + id1 * JacobianColsNbr + id2);
cols.insert(id3 * hessianColsNbr + id2 * JacobianColsNbr + id1);
int k2 = 1; // Keeps the offset of the permutation relative to k
for (set<int>::iterator it2 = cols.begin(); it2 != cols.end(); it2++)
if (*it2 != ref_col)
if (output_type == oJuliaDynamicModel)
third_derivatives_output << " @inbounds g3[" << eq + 1 << "," << *it2 + 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 << "=" << *it2 + 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 == oMatlabStaticModel)
{
// 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(third_derivatives_output, tmp_paren_vars, message_printed);
StaticOutput << "residual = zeros( " << equations.size() << ", 1);" << endl << endl
<< "%" << endl
<< "% Model equations" << endl
<< "%" << endl << endl
<< model_local_vars_output.str()
<< model_output.str()
<< "if ~isreal(residual)" << endl
<< " residual = real(residual)+imag(residual).^2;" << endl
<< "end" << endl
<< "if nargout >= 2," << endl
<< " g1 = zeros(" << equations.size() << ", " << symbol_table.endo_nbr() << ");" << endl << endl
<< " %" << endl
<< " % Jacobian matrix" << endl
<< " %" << endl << endl
<< jacobian_output.str()
<< " if ~isreal(g1)" << endl
<< " g1 = real(g1)+2*imag(g1);" << endl
<< " end" << endl
<< "if nargout >= 3," << endl
<< " %" << endl
<< " % Hessian matrix" << endl
<< " %" << endl
<< endl;
if (second_derivatives.size())
StaticOutput << " v2 = zeros(" << NNZDerivatives[1] << ",3);" << endl
<< hessian_output.str()
<< " g2 = sparse(v2(:,1),v2(:,2),v2(:,3)," << equations.size() << "," << g2ncols << ");" << endl;
else
StaticOutput << " g2 = sparse([],[],[]," << equations.size() << "," << g2ncols << ");" << endl;
// Initialize g3 matrix
StaticOutput << "if nargout >= 4," << endl
<< " %" << endl
<< " % Third order derivatives" << endl
<< " %" << endl
<< endl;
int ncols = hessianColsNbr * JacobianColsNbr;
if (third_derivatives.size())
StaticOutput << " v3 = zeros(" << NNZDerivatives[2] << ",3);" << endl
<< third_derivatives_output.str()
<< " g3 = sparse(v3(:,1),v3(:,2),v3(:,3)," << nrows << "," << ncols << ");" << endl;
else // Either 3rd derivatives is all zero, or we didn't compute it
StaticOutput << " g3 = sparse([],[],[]," << nrows << "," << ncols << ");" << endl;
StaticOutput << "end" << endl
<< "end" << endl
<< "end" << endl;
}
else if (output_type == oCStaticModel)
{
StaticOutput << "void Static(double *y, double *x, int nb_row_x, double *params, double *residual, double *g1, double *v2)" << endl
<< "{" << endl
<< " double lhs, rhs;" << endl
<< endl
<< " /* Residual equations */" << endl
<< model_local_vars_output.str()
<< model_output.str()
<< " /* Jacobian */" << endl
<< " if (g1 == NULL)" << endl
<< " return;" << endl
<< endl
<< jacobian_output.str()
<< endl;
if (second_derivatives.size())
StaticOutput << " /* Hessian for endogenous and exogenous variables */" << endl
<< " if (v2 == NULL)" << endl
<< " return;" << endl
<< endl
<< hessian_output.str()
<< endl;
if (third_derivatives.size())
StaticOutput << " /* Third derivatives for endogenous and exogenous variables */" << endl
<< " if (v3 == NULL)" << endl
<< " return;" << endl
<< endl
<< third_derivatives_output.str()
<< endl;
}
else
{
ostringstream comments;
comments << "## Function Arguments" << endl
<< endl
<< "## Input" << endl
<< " 1 y: Array{Float64, length(model.endo), 1} Vector of endogenous variables in declaration order" << endl
<< " 2 x: Array{Float64, length(model.exo), 1} Vector of exogenous variables in declaration order" << endl
<< " 3 params: Array{Float64, length(model.param), 1} Vector of parameter values in declaration order" << endl
<< endl
<< "## Output" << endl
<< " 4 residual: Array(Float64, model.eq_nbr, 1) Vector of residuals of the static model equations" << endl
<< " in order of declaration of the equations." << endl
<< " Dynare may prepend auxiliary equations, see model.aux_vars" << endl;
StaticOutput << "function static!(y::Vector{Float64}, x::Vector{Float64}, "
<< "params::Vector{Float64}," << endl
<< " residual::Vector{Float64})" << endl
<< "#=" << endl << comments.str() << "=#" << endl
<< " @assert length(y) == " << symbol_table.endo_nbr() << endl
<< " @assert length(x) == " << symbol_table.exo_nbr() << endl
<< " @assert length(params) == " << symbol_table.param_nbr() << endl
<< " @assert length(residual) == " << equations.size() << endl
<< " #" << endl
<< " # Model equations" << endl
<< " #" << endl
<< model_local_vars_output.str()
<< model_output.str()
<< "if ~isreal(residual)" << endl
<< " residual = real(residual)+imag(residual).^2;" << endl
<< "end" << endl
<< "end" << endl << endl
<< "function static!(y::Vector{Float64}, x::Vector{Float64}, "
<< "params::Vector{Float64}," << endl
<< " residual::Vector{Float64}, g1::Matrix{Float64})" << endl;
comments << " 5 g1: Array(Float64, model.eq_nbr, length(model.endo)) Jacobian matrix of the static model equations;" << endl
<< " columns: variables in declaration order" << endl
<< " rows: equations in order of declaration" << endl;
StaticOutput << "#=" << endl << comments.str() << "=#" << endl
<< " @assert size(g1) == (" << equations.size() << ", " << symbol_table.endo_nbr()
<< ")" << endl
<< " fill!(g1, 0.0)" << endl
<< " static!(y, x, params, residual)" << endl
<< model_local_vars_output.str()
<< " #" << endl
<< " # Jacobian matrix" << endl
<< " #" << endl
<< jacobian_output.str()
<< " if ~isreal(g1)" << endl
<< " g1 = real(g1)+2*imag(g1);" << endl
<< " end" << endl
<< "end" << endl << endl
<< "function static!(y::Vector{Float64}, x::Vector{Float64}, "
<< "params::Vector{Float64}," << endl
<< " residual::Vector{Float64}, g1::Matrix{Float64}, "
<< "g2::Matrix{Float64})" << endl;
comments << " 6 g2: spzeros(model.eq_nbr, length(model.endo)^2) Hessian matrix of the static model equations;" << endl
<< " columns: variables in declaration order" << endl
<< " rows: equations in order of declaration" << endl;
StaticOutput << "#=" << endl << comments.str() << "=#" << endl
<< " @assert size(g2) == (" << equations.size() << ", " << g2ncols << ")" << endl
<< " fill!(g2, 0.0)" << endl
<< " static!(y, x, params, residual, g1)" << endl;
if (second_derivatives.size())
StaticOutput << model_local_vars_output.str()
<< " #" << endl
<< " # Hessian matrix" << endl
<< " #" << endl
<< hessian_output.str();
// Initialize g3 matrix
int ncols = hessianColsNbr * JacobianColsNbr;
StaticOutput << "end" << endl << endl
<< "function static!(y::Vector{Float64}, x::Vector{Float64}, "
<< "params::Vector{Float64}," << endl
<< " residual::Vector{Float64}, g1::Matrix{Float64}, "
<< "g2::Matrix{Float64}," << endl
<< " g3::Matrix{Float64})" << endl;
comments << " 7 g3: spzeros(model.eq_nbr, length(model.endo)^3) Third derivatives matrix of the static model equations;" << endl
<< " columns: variables in declaration order" << endl
<< " rows: equations in order of declaration" << endl;
StaticOutput << "#=" << endl << comments.str() << "=#" << endl
<< " @assert size(g3) == (" << nrows << ", " << ncols << ")" << endl
<< " fill!(g3, 0.0)" << endl
<< " static!(y, x, params, residual, g1, g2)" << endl;
if (third_derivatives.size())
StaticOutput << model_local_vars_output.str()
<< " #" << endl
<< " # Third order derivatives" << endl
<< " #" << endl
<< third_derivatives_output.str();
StaticOutput << "end" << endl;
}
}
void
StaticModel::writeStaticCFile(const string &func_name) const
{
// Writing comments and function definition command
string filename = func_name + "_static.c";
string filename_mex = func_name + "_static_mex.c";
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 << "/*" << endl
<< " * " << filename << " : Computes static model for Dynare" << endl
<< " *" << endl
<< " * Warning : this file is generated automatically by Dynare" << endl
<< " * from model file (.mod)" << endl << 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 Static function will call mex
output << "#include \"mex.h\"" << endl;
else
output << "#include <stdlib.h>" << endl;
output << "#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(output);
writeNormcdfCHeader(output);
// Writing the function body
writeStaticModel(output, true, false);
output << "}" << endl << endl;
writePowerDeriv(output);
writeNormcdf(output);
output.close();
output.open(filename_mex.c_str(), ios::out | ios::binary);
if (!output.is_open())
{
cerr << "ERROR: Can't open file " << filename_mex << " for writing" << endl;
exit(EXIT_FAILURE);
}
// Writing the gateway routine
output << "/*" << endl
<< " * " << filename_mex << " : The gateway routine used to call the Static 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 Static(double *y, double *x, int nb_row_x, double *params, double *residual, double *g1, double *v2);" << endl
<< "void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])" << endl
<< "{" << endl
<< " double *y, *x, *params;" << endl
<< " double *residual, *g1, *v2;" << endl
<< " int nb_row_x;" << endl
<< 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
<< " /* 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() << ", " << symbol_table.endo_nbr() << ", 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
<< " /* Call the C subroutines. */" << endl
<< " Static(y, x, nb_row_x, params, residual, g1, v2);" << endl
<< "}" << endl << endl;
output.close();
}
void
StaticModel::writeStaticJuliaFile(const string &basename) const
{
string filename = basename + "Static.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 " << basename << "Static" << endl
<< "#" << endl
<< "# NB: this file was automatically generated by Dynare" << endl
<< "# from " << basename << ".mod" << endl
<< "#" << endl
<< "using Utils" << endl << endl
<< "export static!" << endl << endl;
writeStaticModel(output, false, true);
output << "end" << endl;
}
void
StaticModel::writeStaticFile(const string &basename, bool block, bool bytecode, bool use_dll, bool julia) const
{
int r;
//assert(block);
#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);
}
if (block && bytecode)
writeModelEquationsCode_Block(basename + "_static", basename, map_idx, map_idx2);
else if (!block && bytecode)
writeModelEquationsCode(basename + "_static", basename, map_idx);
else if (block && !bytecode)
{
chdir(basename.c_str());
writeModelEquationsOrdered_M(basename + "_static");
chdir("..");
writeStaticBlockMFSFile(basename);
}
else if (use_dll)
writeStaticCFile(basename);
else if (julia)
writeStaticJuliaFile(basename);
else
writeStaticMFile(basename);
writeSetAuxiliaryVariables(basename, julia);
}
bool
StaticModel::exoPresentInEqs() const
{
for (int i = 0; i < (int) equations.size(); i++)
if (equations[i]->containsExogenous())
return true;
return false;
}
void
StaticModel::writeStaticBlockMFSFile(const string &basename) const
{
string filename = basename + "_static.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);
}
string func_name = basename + "_static";
output << "function [residual, g1, y, var_index] = " << func_name << "(nblock, y, x, params)" << endl
<< " residual = [];" << endl
<< " g1 = [];" << endl
<< " var_index = [];\n" << endl
<< " switch nblock" << endl;
unsigned int nb_blocks = getNbBlocks();
for (int b = 0; b < (int) nb_blocks; b++)
{
set<int> local_var;
output << " case " << b+1 << endl;
BlockSimulationType simulation_type = getBlockSimulationType(b);
if (simulation_type == EVALUATE_BACKWARD || simulation_type == EVALUATE_FORWARD)
{
output << " y_tmp = " << func_name << "_" << b+1 << "(y, x, params);\n";
ostringstream tmp;
for (int i = 0; i < (int) getBlockSize(b); i++)
tmp << " " << getBlockVariableID(b, i)+1;
output << " var_index = [" << tmp.str() << "];\n";
output << " residual = y(var_index) - y_tmp(var_index);\n";
output << " y = y_tmp;\n";
}
else
output << " [residual, y, g1] = " << func_name << "_" << b+1 << "(y, x, params);\n";
}
output << " end" << endl
<< "end" << endl;
output.close();
}
void
StaticModel::writeOutput(ostream &output, bool block) const
{
if (!block)
return;
unsigned int nb_blocks = getNbBlocks();
for (int b = 0; b < (int) nb_blocks; b++)
{
BlockSimulationType simulation_type = getBlockSimulationType(b);
unsigned int block_size = getBlockSize(b);
ostringstream tmp_s, tmp_s_eq;
tmp_s.str("");
tmp_s_eq.str("");
for (unsigned int i = 0; i < block_size; i++)
{
tmp_s << " " << getBlockVariableID(b, i)+1;
tmp_s_eq << " " << getBlockEquationID(b, i)+1;
}
output << "block_structure_stat.block(" << b+1 << ").Simulation_Type = " << simulation_type << ";\n";
output << "block_structure_stat.block(" << b+1 << ").endo_nbr = " << block_size << ";\n";
output << "block_structure_stat.block(" << b+1 << ").mfs = " << getBlockMfs(block) << ";\n";
output << "block_structure_stat.block(" << b+1 << ").equation = [" << tmp_s_eq.str() << "];\n";
output << "block_structure_stat.block(" << b+1 << ").variable = [" << tmp_s.str() << "];\n";
}
output << "M_.block_structure_stat.block = block_structure_stat.block;\n";
string cst_s;
int nb_endo = symbol_table.endo_nbr();
output << "M_.block_structure_stat.variable_reordered = [";
for (int i = 0; i < nb_endo; i++)
output << " " << variable_reordered[i]+1;
output << "];\n";
output << "M_.block_structure_stat.equation_reordered = [";
for (int i = 0; i < nb_endo; i++)
output << " " << equation_reordered[i]+1;
output << "];\n";
map<pair<int, int>, int> row_incidence;
for (first_derivatives_t::const_iterator it = first_derivatives.begin();
it != first_derivatives.end(); it++)
{
int deriv_id = it->first.second;
if (getTypeByDerivID(deriv_id) == eEndogenous)
{
int eq = it->first.first;
int symb = getSymbIDByDerivID(deriv_id);
int var = symbol_table.getTypeSpecificID(symb);
//int lag = getLagByDerivID(deriv_id);
row_incidence[make_pair(eq, var)] = 1;
}
}
output << "M_.block_structure_stat.incidence.sparse_IM = [";
for (map<pair< int, int >, int>::const_iterator it = row_incidence.begin(); it != row_incidence.end(); it++)
{
output << it->first.first+1 << " " << it->first.second+1 << ";\n";
}
output << "];\n";
}
SymbolType
StaticModel::getTypeByDerivID(int deriv_id) const throw (UnknownDerivIDException)
{
if (deriv_id < symbol_table.endo_nbr())
return eEndogenous;
else if (deriv_id < symbol_table.endo_nbr() + symbol_table.param_nbr())
return eParameter;
else
throw UnknownDerivIDException();
}
int
StaticModel::getLagByDerivID(int deriv_id) const throw (UnknownDerivIDException)
{
return 0;
}
int
StaticModel::getSymbIDByDerivID(int deriv_id) const throw (UnknownDerivIDException)
{
if (deriv_id < symbol_table.endo_nbr())
return symbol_table.getID(eEndogenous, deriv_id);
else if (deriv_id < symbol_table.endo_nbr() + symbol_table.param_nbr())
return symbol_table.getID(eParameter, deriv_id - symbol_table.endo_nbr());
else
throw UnknownDerivIDException();
}
int
StaticModel::getDerivID(int symb_id, int lag) const throw (UnknownDerivIDException)
{
if (symbol_table.getType(symb_id) == eEndogenous)
return symbol_table.getTypeSpecificID(symb_id);
else if (symbol_table.getType(symb_id) == eParameter)
return symbol_table.getTypeSpecificID(symb_id) + symbol_table.endo_nbr();
else
return -1;
}
void
StaticModel::addAllParamDerivId(set<int> &deriv_id_set)
{
for (int i = 0; i < symbol_table.param_nbr(); i++)
deriv_id_set.insert(i + symbol_table.endo_nbr());
}
map<pair<pair<int, pair<int, int> >, pair<int, int> >, int>
StaticModel::get_Derivatives(int block)
{
map<pair<pair<int, pair<int, int> >, pair<int, int> >, int> Derivatives;
Derivatives.clear();
int block_size = getBlockSize(block);
int block_nb_recursive = block_size - getBlockMfs(block);
int lag = 0;
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(make_pair(lag, make_pair(eqr, varr))) != dynamic_jacobian.end())
{
bool OK = true;
map<pair<pair<int, pair<int, int> >, pair<int, int> >, int>::const_iterator its = Derivatives.find(make_pair(make_pair(lag, make_pair(eq, var)), make_pair(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[make_pair(make_pair(lag, make_pair(eq, var)), make_pair(eqr, varr))] = 1;
else
//It's a feedback equation we can use the derivatives
Derivatives[make_pair(make_pair(lag, make_pair(eq, var)), make_pair(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(make_pair(make_pair(lag, make_pair(var, vars)), make_pair(eqs, varrs))) != Derivatives.end())
Derivatives[make_pair(make_pair(lag, make_pair(eq, vars)), make_pair(eqr, varrs))] = 2;
}
}
}
}
}
return (Derivatives);
}
void
StaticModel::computeChainRuleJacobian(blocks_derivatives_t &blocks_derivatives)
{
map<int, expr_t> recursive_variables;
unsigned int nb_blocks = getNbBlocks();
blocks_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();
BlockSimulationType simulation_type = getBlockSimulationType(block);
int block_size = getBlockSize(block);
int block_nb_mfs = getBlockMfs(block);
int block_nb_recursives = block_size - block_nb_mfs;
if (simulation_type == SOLVE_TWO_BOUNDARIES_COMPLETE || simulation_type == SOLVE_TWO_BOUNDARIES_SIMPLE)
{
blocks_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[make_pair(eqr, make_pair(varr, lag))] = first_derivatives[make_pair(eqr, getDerivID(symbol_table.getID(eEndogenous, varr), lag))];
else if (Deriv_type == 1)
first_chain_rule_derivatives[make_pair(eqr, make_pair(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[make_pair(eqr, make_pair(varr, lag))] = (equation_type_and_normalized_equation[eqr].second)->getChainRuleDerivative(getDerivID(symbol_table.getID(eEndogenous, varr), lag), recursive_variables);
else
first_chain_rule_derivatives[make_pair(eqr, make_pair(varr, lag))] = equations[eqr]->getChainRuleDerivative(getDerivID(symbol_table.getID(eEndogenous, varr), lag), recursive_variables);
}
tmp_derivatives.push_back(make_pair(make_pair(eq, var), make_pair(lag, first_chain_rule_derivatives[make_pair(eqr, make_pair(varr, lag))])));
}
}
else
{
blocks_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);
}
for (int eq = block_nb_recursives; eq < block_size; eq++)
{
int eqr = getBlockEquationID(block, eq);
for (int var = block_nb_recursives; var < block_size; var++)
{
int varr = getBlockVariableID(block, var);
expr_t d1 = equations[eqr]->getChainRuleDerivative(getDerivID(symbol_table.getID(eEndogenous, varr), 0), recursive_variables);
if (d1 == Zero)
continue;
first_chain_rule_derivatives[make_pair(eqr, make_pair(varr, 0))] = d1;
tmp_derivatives.push_back(
make_pair(make_pair(eq, var), make_pair(0, first_chain_rule_derivatives[make_pair(eqr, make_pair(varr, 0))])));
}
}
}
blocks_derivatives[block] = tmp_derivatives;
}
}
void
StaticModel::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;
}
}
derivative_endo = vector<derivative_t>(nb_blocks);
endo_max_leadlag_block = vector<pair<int, int> >(nb_blocks, make_pair(0, 0));
max_leadlag_block = vector<pair<int, int> >(nb_blocks, make_pair(0, 0));
for (first_derivatives_t::iterator it2 = first_derivatives.begin();
it2 != first_derivatives.end(); it2++)
{
int eq = it2->first.first;
int var = symbol_table.getTypeSpecificID(getSymbIDByDerivID(it2->first.second));
int lag = 0;
int block_eq = equation_2_block[eq];
int block_var = variable_2_block[var];
max_leadlag_block[block_eq] = make_pair(0, 0);
max_leadlag_block[block_eq] = make_pair(0, 0);
endo_max_leadlag_block[block_eq] = make_pair(0, 0);
endo_max_leadlag_block[block_eq] = make_pair(0, 0);
derivative_t tmp_derivative;
lag_var_t lag_var;
if (getTypeByDerivID(it2->first.second) == eEndogenous && block_eq == block_var)
{
tmp_derivative = derivative_endo[block_eq];
tmp_derivative[make_pair(lag, make_pair(eq, var))] = first_derivatives[make_pair(eq, getDerivID(symbol_table.getID(eEndogenous, var), lag))];
derivative_endo[block_eq] = tmp_derivative;
}
}
}
void
StaticModel::writeChainRuleDerivative(ostream &output, int eqr, int varr, int lag,
ExprNodeOutputType output_type,
const temporary_terms_t &temporary_terms) const
{
map<pair<int, pair<int, int> >, expr_t>::const_iterator it = first_chain_rule_derivatives.find(make_pair(eqr, make_pair(varr, lag)));
if (it != first_chain_rule_derivatives.end())
(it->second)->writeOutput(output, output_type, temporary_terms);
else
output << 0;
}
void
StaticModel::writeLatexFile(const string &basename, bool write_equation_tags) const
{
writeLatexModelFile(basename + "_static", oLatexStaticModel, write_equation_tags);
}
void
StaticModel::writeAuxVarInitval(ostream &output, ExprNodeOutputType output_type) const
{
for (int i = 0; i < (int) aux_equations.size(); i++)
{
dynamic_cast<ExprNode *>(aux_equations[i])->writeOutput(output, output_type);
output << ";" << endl;
}
}
void
StaticModel::writeSetAuxiliaryVariables(const string &basename, const bool julia) const
{
ostringstream output_func_body;
writeAuxVarRecursiveDefinitions(output_func_body, oMatlabStaticModel);
if (output_func_body.str().empty())
return;
string func_name = basename + "_set_auxiliary_variables";
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 y = " << func_name + "(y, x, params)" << endl
<< comment << endl
<< comment << " Status : Computes static model for Dynare" << endl
<< comment << endl
<< comment << " Warning : this file is generated automatically by Dynare" << endl
<< comment << " from model file (.mod)" << endl << endl
<< output_func_body.str();
}
void
StaticModel::writeAuxVarRecursiveDefinitions(ostream &output, ExprNodeOutputType output_type) const
{
deriv_node_temp_terms_t tef_terms;
temporary_terms_t temporary_terms;
for (int i = 0; i < (int) aux_equations.size(); i++)
if (dynamic_cast<ExprNode *>(aux_equations[i])->containsExternalFunction())
dynamic_cast<ExprNode *>(aux_equations[i])->writeExternalFunctionOutput(output, oMatlabStaticModel,
temporary_terms, tef_terms);
for (int i = 0; i < (int) aux_equations.size(); i++)
{
dynamic_cast<ExprNode *>(aux_equations[i]->substituteStaticAuxiliaryDefinition())->writeOutput(output, output_type, temporary_terms, tef_terms);
output << ";" << endl;
}
}
void
StaticModel::writeLatexAuxVarRecursiveDefinitions(ostream &output) const
{
deriv_node_temp_terms_t tef_terms;
temporary_terms_t temporary_terms;
for (int i = 0; i < (int) aux_equations.size(); i++)
if (dynamic_cast<ExprNode *>(aux_equations[i])->containsExternalFunction())
dynamic_cast<ExprNode *>(aux_equations[i])->writeExternalFunctionOutput(output, oLatexStaticModel,
temporary_terms, tef_terms);
for (int i = 0; i < (int) aux_equations.size(); i++)
{
output << "\\begin{dmath}" << endl;
dynamic_cast<ExprNode *>(aux_equations[i]->substituteStaticAuxiliaryDefinition())->writeOutput(output, oLatexStaticModel);
output << endl << "\\end{dmath}" << endl;
}
}
void
StaticModel::writeJsonAuxVarRecursiveDefinitions(ostream &output) const
{
deriv_node_temp_terms_t tef_terms;
temporary_terms_t temporary_terms;
for (int i = 0; i < (int) aux_equations.size(); i++)
if (dynamic_cast<ExprNode *>(aux_equations[i])->containsExternalFunction())
{
vector<string> efout;
dynamic_cast<ExprNode *>(aux_equations[i])->writeJsonExternalFunctionOutput(efout,
temporary_terms,
tef_terms,
false);
for (vector<string>::const_iterator it = efout.begin(); it != efout.end(); it++)
{
if (it != efout.begin())
output << ", ";
output << *it;
}
}
for (int i = 0; i < (int) aux_equations.size(); i++)
{
output << ", {\"lhs\": \"";
aux_equations[i]->get_arg1()->writeJsonOutput(output, temporary_terms, tef_terms, false);
output << "\", \"rhs\": \"";
dynamic_cast<BinaryOpNode *>(aux_equations[i]->substituteStaticAuxiliaryDefinition())->get_arg2()->writeJsonOutput(output, temporary_terms, tef_terms, false);
output << "\"}";
}
}
void
StaticModel::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 ? oJuliaStaticModel : oMatlabStaticModel);
ostringstream model_local_vars_output; // Used for storing model local vars
ostringstream model_output; // Used for storing model
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;
writeModelLocalVariables(model_local_vars_output, output_type, tef_terms);
temporary_terms_t temp_terms_empty;
writeTemporaryTerms(params_derivs_temporary_terms, temp_terms_empty, model_output, output_type, tef_terms);
for (first_derivatives_t::const_iterator it = residuals_params_derivatives.begin();
it != residuals_params_derivatives.end(); it++)
{
int eq = it->first.first;
int param = it->first.second;
expr_t d1 = it->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, tef_terms);
jacobian_output << ";" << endl;
}
for (second_derivatives_t::const_iterator it = jacobian_params_derivatives.begin();
it != jacobian_params_derivatives.end(); it++)
{
int eq = it->first.first;
int var = it->first.second.first;
int param = it->first.second.second;
expr_t d2 = it->second;
int var_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(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, tef_terms);
hessian_output << ";" << endl;
}
int i = 1;
for (second_derivatives_t::const_iterator it = residuals_params_second_derivatives.begin();
it != residuals_params_second_derivatives.end(); ++it, i++)
{
int eq = it->first.first;
int param1 = it->first.second.first;
int param2 = it->first.second.second;
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, tef_terms);
hessian1_output << ";" << endl;
}
i = 1;
for (third_derivatives_t::const_iterator it = jacobian_params_second_derivatives.begin();
it != jacobian_params_second_derivatives.end(); ++it, i++)
{
int eq = it->first.first;
int var = it->first.second.first;
int param1 = it->first.second.second.first;
int param2 = it->first.second.second.second;
expr_t d2 = it->second;
int var_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(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, tef_terms);
third_derivs_output << ";" << endl;
}
i = 1;
for (third_derivatives_t::const_iterator it = hessian_params_derivatives.begin();
it != hessian_params_derivatives.end(); ++it, i++)
{
int eq = it->first.first;
int var1 = it->first.second.first;
int var2 = it->first.second.second.first;
int param = it->first.second.second.second;
expr_t d2 = it->second;
int var1_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(var1)) + 1;
int var2_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(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, tef_terms);
third_derivs1_output << ";" << endl;
}
ofstream paramsDerivsFile;
string filename = julia ? basename + "StaticParamsDerivs.jl" : basename + "_static_params_derivs.m";
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 << "_static_params_derivs(y, x, params)" << endl
<< "%" << endl
<< "% Status : Computes derivatives of the static model with respect to the parameters" << endl
<< "%" << endl
<< "% Inputs : " << endl
<< "% y [M_.endo_nbr by 1] double vector of endogenous variables in declaration order" << endl
<< "% x [M_.exo_nbr by 1] double vector of exogenous variables in declaration order" << endl
<< "% params [M_.param_nbr by 1] double vector of parameter values in declaration order" << endl
<< "%" << endl
<< "% Outputs:" << endl
<< "% rp [M_.eq_nbr by #params] double Jacobian matrix of static model equations with respect to parameters " << endl
<< "% Dynare may prepend or append auxiliary equations, see M_.aux_vars" << endl
<< "% gp [M_.endo_nbr by M_.endo_nbr by #params] double Derivative of the Jacobian matrix of the static model equations with respect to the parameters" << endl
<< "% rows: variables in declaration order" << endl
<< "% rows: equations in order of declaration" << 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 static 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
<< "%" << endl
<< "%" << endl
<< "% Warning : this file is generated automatically by Dynare" << endl
<< "% from model file (.mod)" << endl << 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() << ", " << symbol_table.endo_nbr() << ", "
<< 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 << "StaticParamsDerivs" << 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, params)" << 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() << ", " << symbol_table.endo_nbr() << ", "
<< 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
StaticModel::writeJsonOutput(ostream &output) const
{
writeJsonModelEquations(output, false);
}
void
StaticModel::writeJsonComputingPassOutput(ostream &output, bool writeDetails) const
{
ostringstream model_local_vars_output; // Used for storing model local vars
ostringstream model_output; // Used for storing model
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 = "";
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);
int nrows = equations.size();
int JacobianColsNbr = symbol_table.endo_nbr();
int hessianColsNbr = JacobianColsNbr*JacobianColsNbr;
// Write Jacobian w.r. to endogenous only
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\": " << nrows
<< ", \"ncols\": " << JacobianColsNbr
<< ", \"entries\": [";
for (first_derivatives_t::const_iterator it = first_derivatives.begin();
it != first_derivatives.end(); it++)
{
if (it != first_derivatives.begin())
jacobian_output << ", ";
int eq = it->first.first;
int var = it->first.second;
int symb_id = getSymbIDByDerivID(var);
int col = symbol_table.getTypeSpecificID(symb_id);
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(symb_id) << "\"";
jacobian_output << ", \"val\": \"";
d1->writeJsonOutput(jacobian_output, temp_term_union, tef_terms);
jacobian_output << "\"}" << endl;
}
jacobian_output << "]}";
int g2ncols = symbol_table.endo_nbr() * symbol_table.endo_nbr();
// Write Hessian w.r. to endogenous only (only if 2nd order derivatives have been computed)
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\": " << g2ncols
<< ", \"entries\": [";
for (second_derivatives_t::const_iterator it = second_derivatives.begin();
it != second_derivatives.end(); it++)
{
if (it != second_derivatives.begin())
hessian_output << ", ";
int eq = it->first.first;
int symb_id1 = getSymbIDByDerivID(it->first.second.first);
int symb_id2 = getSymbIDByDerivID(it->first.second.second);
expr_t d2 = it->second;
int tsid1 = symbol_table.getTypeSpecificID(symb_id1);
int tsid2 = symbol_table.getTypeSpecificID(symb_id2);
int col = tsid1*symbol_table.endo_nbr()+tsid2;
int col_sym = tsid2*symbol_table.endo_nbr()+tsid1;
if (writeDetails)
hessian_output << "{\"eq\": " << eq + 1;
else
hessian_output << "{\"row\": " << eq + 1;
hessian_output << ", \"col\": [" << col + 1;
if (writeDetails)
hessian_output << ", \"var1\": \"" << symbol_table.getName(symb_id1) << "\""
<< ", \"var2\": \"" << symbol_table.getName(symb_id2) << "\"";
if (symb_id1 != symb_id2)
hessian_output << ", " << col_sym + 1;
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 * JacobianColsNbr
<< ", \"entries\": [";
for (third_derivatives_t::const_iterator it = third_derivatives.begin();
it != third_derivatives.end(); it++)
{
if (it != third_derivatives.begin())
third_derivatives_output << ", ";
int eq = it->first.first;
int var1 = it->first.second.first;
int var2 = it->first.second.second.first;
int var3 = it->first.second.second.second;
expr_t d3 = it->second;
if (writeDetails)
third_derivatives_output << "{\"eq\": " << eq + 1;
else
third_derivatives_output << "{\"row\": " << eq + 1;
int id1 = getSymbIDByDerivID(var1);
int id2 = getSymbIDByDerivID(var2);
int id3 = getSymbIDByDerivID(var3);
set<int> cols;
cols.insert(id1 * hessianColsNbr + id2 * JacobianColsNbr + id3);
cols.insert(id1 * hessianColsNbr + id3 * JacobianColsNbr + id2);
cols.insert(id2 * hessianColsNbr + id1 * JacobianColsNbr + id3);
cols.insert(id2 * hessianColsNbr + id3 * JacobianColsNbr + id1);
cols.insert(id3 * hessianColsNbr + id1 * JacobianColsNbr + id2);
cols.insert(id3 * hessianColsNbr + id2 * JacobianColsNbr + id1);
third_derivatives_output << ", \"col\": [";
for (set<int>::iterator 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)) << "\""
<< ", \"var2\": \"" << symbol_table.getName(getSymbIDByDerivID(var2)) << "\""
<< ", \"var3\": \"" << symbol_table.getName(getSymbIDByDerivID(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 << "\"static_model\": {";
else
output << "\"static_model_simple\": {";
output << model_local_vars_output.str()
<< ", " << model_output.str()
<< ", " << jacobian_output.str()
<< ", " << hessian_output.str()
<< ", " << third_derivatives_output.str()
<< "}";
}
void
StaticModel::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 (first_derivatives_t::const_iterator it = residuals_params_derivatives.begin();
it != residuals_params_derivatives.end(); it++)
{
if (it != residuals_params_derivatives.begin())
jacobian_output << ", ";
int eq = it->first.first;
int param = it->first.second;
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;
if (writeDetails)
jacobian_output << ", \"param_col\": " << param_col;
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\": " << symbol_table.endo_nbr()
<< ", \"nparamcols\": " << symbol_table.param_nbr()
<< ", \"entries\": [";
for (second_derivatives_t::const_iterator it = jacobian_params_derivatives.begin();
it != jacobian_params_derivatives.end(); it++)
{
if (it != jacobian_params_derivatives.begin())
hessian_output << ", ";
int eq = it->first.first;
int var = it->first.second.first;
int param = it->first.second.second;
expr_t d2 = it->second;
int var_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(var)) + 1;
int param_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(param)) + 1;
if (writeDetails)
hessian_output << "{\"eq\": " << eq + 1;
else
hessian_output << "{\"row\": " << eq + 1;
if (writeDetails)
hessian_output << ", \"var\": \"" << symbol_table.getName(getSymbIDByDerivID(var)) << "\""
<< ", \"param\": \"" << symbol_table.getName(getSymbIDByDerivID(param)) << "\"";
hessian_output << ", \"var_col\": " << var_col
<< ", \"param_col\": " << param_col
<< ", \"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 (second_derivatives_t::const_iterator it = residuals_params_second_derivatives.begin();
it != residuals_params_second_derivatives.end(); ++it)
{
if (it != residuals_params_second_derivatives.begin())
hessian1_output << ", ";
int eq = it->first.first;
int param1 = it->first.second.first;
int param2 = it->first.second.second;
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
<< ", \"param2_col\": " << param2_col;
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\": " << symbol_table.endo_nbr()
<< ", \"nparam1cols\": " << symbol_table.param_nbr()
<< ", \"nparam2cols\": " << symbol_table.param_nbr()
<< ", \"entries\": [";
for (third_derivatives_t::const_iterator 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 = it->first.first;
int var = it->first.second.first;
int param1 = it->first.second.second.first;
int param2 = it->first.second.second.second;
expr_t d2 = it->second;
int var_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(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
<< ", \"param1_col\": " << param1_col
<< ", \"param2_col\": " << param2_col;
if (writeDetails)
third_derivs_output << ", \"var\": \"" << symbol_table.getName(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\": " << symbol_table.endo_nbr()
<< ", \"nvar2cols\": " << symbol_table.endo_nbr()
<< ", \"nparamcols\": " << symbol_table.param_nbr()
<< ", \"entries\": [";
for (third_derivatives_t::const_iterator it = hessian_params_derivatives.begin();
it != hessian_params_derivatives.end(); ++it)
{
if (it != hessian_params_derivatives.begin())
third_derivs1_output << ", ";
int eq = it->first.first;
int var1 = it->first.second.first;
int var2 = it->first.second.second.first;
int param = it->first.second.second.second;
expr_t d2 = it->second;
int var1_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(var1)) + 1;
int var2_col = symbol_table.getTypeSpecificID(getSymbIDByDerivID(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
<< ", \"var2_col\": " << var2_col
<< ", \"param_col\": " << param_col;
if (writeDetails)
third_derivs1_output << ", \"var1\": \"" << symbol_table.getName(getSymbIDByDerivID(var1)) << "\""
<< ", \"var2\": \"" << symbol_table.getName(getSymbIDByDerivID(var2)) << "\""
<< ", \"param1\": \"" << 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 << "\"static_model_params_derivative\": {";
else
output << "\"static_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()
<< "}";
}