DynamicModel.cc 150 KB
Newer Older
sebastien's avatar
sebastien committed
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
/*
 * Copyright (C) 2003-2009 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/>.
 */

20
#include <iostream>
sebastien's avatar
sebastien committed
21
#include <cmath>
22
#include <cstdlib>
23
#include <cassert>
24
25
#include <cstdio>
#include <cerrno>
sebastien's avatar
sebastien committed
26
27
28
29
30
31
32
33
34
35
36
37
38
39

#include "DynamicModel.hh"

// For mkdir() and chdir()
#ifdef _WIN32
# include <direct.h>
#else
# include <unistd.h>
# include <sys/stat.h>
# include <sys/types.h>
#endif

DynamicModel::DynamicModel(SymbolTable &symbol_table_arg,
                           NumericalConstants &num_constants_arg) :
ferhat's avatar
ferhat committed
40
41
42
43
44
45
    ModelTree(symbol_table_arg, num_constants_arg),
    max_lag(0), max_lead(0),
    max_endo_lag(0), max_endo_lead(0),
    max_exo_lag(0), max_exo_lead(0),
    max_exo_det_lag(0), max_exo_det_lead(0),
    dynJacobianColsNbr(0),
46
    mode(eStandardMode),
ferhat's avatar
ferhat committed
47
48
49
    cutoff(1e-15),
    markowitz(0.7),
    block_triangular(symbol_table_arg, num_constants_arg)
sebastien's avatar
sebastien committed
50
51
52
{
}

sebastien's avatar
sebastien committed
53
54
55
56
57
58
NodeID
DynamicModel::AddVariable(const string &name, int lag)
{
  return AddVariableInternal(name, lag);
}

sebastien's avatar
sebastien committed
59
void
sebastien's avatar
sebastien committed
60
DynamicModel::compileDerivative(ofstream &code_file, int eq, int symb_id, int lag, map_idx_type &map_idx) const
ferhat's avatar
ferhat committed
61
62
63
64
65
66
67
68
  {
    //first_derivatives_type::const_iterator it = first_derivatives.find(make_pair(eq, getDerivID(symb_id, lag)));
    first_derivatives_type::const_iterator it = first_derivatives.find(make_pair(eq, getDerivID(symbol_table.getID(eEndogenous, symb_id), lag)));
    if (it != first_derivatives.end())
      (it->second)->compile(code_file, false, temporary_terms, map_idx);
    else
      code_file.write(&FLDZ, sizeof(FLDZ));
  }
sebastien's avatar
sebastien committed
69

70
71
72
73
74
75
76
77
78
79
80
81

void
DynamicModel::compileChainRuleDerivative(ofstream &code_file, int eqr, int varr, int lag, map_idx_type &map_idx) const
{
  map<pair<int, pair<int, int> >, NodeID>::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, false, temporary_terms, map_idx);
  else
    code_file.write(&FLDZ, sizeof(FLDZ));
}


sebastien's avatar
sebastien committed
82
83
84
85
86
87
88
89
90
91
92
93
94
95
void
DynamicModel::BuildIncidenceMatrix()
{
  set<pair<int, int> > endogenous, exogenous;
  for (int eq = 0; eq < (int) equations.size(); eq++)
    {
      BinaryOpNode *eq_node = equations[eq];
      endogenous.clear();
      NodeID Id = eq_node->get_arg1();
      Id->collectEndogenous(endogenous);
      Id = eq_node->get_arg2();
      Id->collectEndogenous(endogenous);
      for (set<pair<int, int> >::iterator it_endogenous=endogenous.begin();it_endogenous!=endogenous.end();it_endogenous++)
        {
ferhat's avatar
ferhat committed
96
          block_triangular.incidencematrix.fill_IM(eq, it_endogenous->first, it_endogenous->second, eEndogenous);
sebastien's avatar
sebastien committed
97
98
99
100
101
102
103
104
        }
      exogenous.clear();
      Id = eq_node->get_arg1();
      Id->collectExogenous(exogenous);
      Id = eq_node->get_arg2();
      Id->collectExogenous(exogenous);
      for (set<pair<int, int> >::iterator it_exogenous=exogenous.begin();it_exogenous!=exogenous.end();it_exogenous++)
        {
ferhat's avatar
ferhat committed
105
          block_triangular.incidencematrix.fill_IM(eq, it_exogenous->first, it_exogenous->second, eExogenous);
sebastien's avatar
sebastien committed
106
107
108
109
110
        }
    }
}

void
111
DynamicModel::computeTemporaryTermsOrdered(Model_Block *ModelBlock)
sebastien's avatar
sebastien committed
112
113
114
115
116
117
118
119
{
  map<NodeID, pair<int, int> > first_occurence;
  map<NodeID, int> reference_count;
  int i, j, m, eq, var, lag;
  temporary_terms_type vect;
  ostringstream tmp_output;
  BinaryOpNode *eq_node;
  first_derivatives_type::const_iterator it;
120
  first_chain_rule_derivatives_type::const_iterator it_chr;
sebastien's avatar
sebastien committed
121
122
123
124
125
126
127
128
129
130
131
  ostringstream tmp_s;

  temporary_terms.clear();
  map_idx.clear();
  for (j = 0;j < ModelBlock->Size;j++)
    {
      // Compute the temporary terms reordered
      for (i = 0;i < ModelBlock->Block_List[j].Size;i++)
        {
          eq_node = equations[ModelBlock->Block_List[j].Equation[i]];
          eq_node->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, j, ModelBlock, i, map_idx);
ferhat's avatar
ferhat committed
132
133
134
          if (ModelBlock->Block_List[j].Equation_Type[i] == E_EVALUATE_S)
            if(ModelBlock->Block_List[j].Equation_Normalized[i])
              ModelBlock->Block_List[j].Equation_Normalized[i]->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, j, ModelBlock, i, map_idx);
sebastien's avatar
sebastien committed
135
136
137
138
139
140
141
142
        }
      for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
        {
          lag=m-ModelBlock->Block_List[j].Max_Lag;
          for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size;i++)
            {
              eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index[i];
              var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index[i];
143
              it=first_derivatives.find(make_pair(eq,getDerivID(symbol_table.getID(eEndogenous, var), lag)));
144
145
              //printf("it=%d eq=%d var=%s (%d)\n",it!=first_derivatives.end(), eq, symbol_table.getName(symbol_table.getID(eEndogenous, var)).c_str(), var);
              //if(it!=first_derivatives.end())
sebastien's avatar
sebastien committed
146
147
              it->second->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, j, ModelBlock, ModelBlock->Block_List[j].Size-1, map_idx);
            }
148
        }
149
			for(i=0; i<ModelBlock->Block_List[j].Chain_Rule_Derivatives->size();i++)
150
        {
151
152
153
154
155
156
          pair< pair<int, pair<int, int> >, pair<int, int> > it = ModelBlock->Block_List[j].Chain_Rule_Derivatives->at(i);
          lag=it.first.first;
          eq=it.first.second.first;
          var=it.first.second.second;
          it_chr=first_chain_rule_derivatives.find(make_pair(eq, make_pair( var, lag)));
          //it_chr->second->writeChainRuleDerivative(output, eq, var, k, oMatlabDynamicModelSparse, temporary_terms);
157
          it_chr->second->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, j, ModelBlock, ModelBlock->Block_List[j].Size-1, map_idx);
sebastien's avatar
sebastien committed
158
        }
159
      /*for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
sebastien's avatar
sebastien committed
160
161
162
163
164
165
        {
          lag=m-ModelBlock->Block_List[j].Max_Lag;
          for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size_exo;i++)
            {
              eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_X_Index[i];
              var=ModelBlock->Block_List[j].IM_lead_lag[m].Exogenous_Index[i];
166
              it=first_derivatives.find(make_pair(eq,getDerivID(symbol_table.getID(eExogenous, var), lag)));
sebastien's avatar
sebastien committed
167
168
              it->second->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, j, ModelBlock, ModelBlock->Block_List[j].Size-1, map_idx);
            }
169
        }*/
sebastien's avatar
sebastien committed
170
171
172
173
174
175
176
177
178
179
      //jacobian_max_exo_col=(variable_table.max_exo_lag+variable_table.max_exo_lead+1)*symbol_table.exo_nbr;
      for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
        {
          lag=m-ModelBlock->Block_List[j].Max_Lag;
          if (block_triangular.incidencematrix.Model_Max_Lag_Endo - ModelBlock->Block_List[j].Max_Lag +m >=0)
            {
              for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size_other_endo;i++)
                {
                  eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index_other_endo[i];
                  var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index_other_endo[i];
180
                  it=first_derivatives.find(make_pair(eq,getDerivID(symbol_table.getID(eEndogenous, var), lag)));
sebastien's avatar
sebastien committed
181
                  //it=first_derivatives.find(make_pair(eq,variable_table.getID(var, lag)));
182
                  //if(it!=first_derivatives.end())
sebastien's avatar
sebastien committed
183
184
185
186
187
188
189
                  it->second->computeTemporaryTerms(reference_count, temporary_terms, first_occurence, j, ModelBlock, ModelBlock->Block_List[j].Size-1, map_idx);
                }
            }
        }
    }
  for (j = 0;j < ModelBlock->Size;j++)
    {
ferhat's avatar
ferhat committed
190
      // Collecte the temporary terms reordered
sebastien's avatar
sebastien committed
191
192
193
194
      for (i = 0;i < ModelBlock->Block_List[j].Size;i++)
        {
          eq_node = equations[ModelBlock->Block_List[j].Equation[i]];
          eq_node->collectTemporary_terms(temporary_terms, ModelBlock, j);
ferhat's avatar
ferhat committed
195
196
197
198
199
          if (ModelBlock->Block_List[j].Equation_Type[i] == E_EVALUATE_S)
            if(ModelBlock->Block_List[j].Equation_Normalized[i])
              ModelBlock->Block_List[j].Equation_Normalized[i]->collectTemporary_terms(temporary_terms, ModelBlock, j);
          for(temporary_terms_type::const_iterator it = ModelBlock->Block_List[j].Temporary_Terms_in_Equation[i]->begin(); it!= ModelBlock->Block_List[j].Temporary_Terms_in_Equation[i]->end(); it++)
            (*it)->collectTemporary_terms(temporary_terms, ModelBlock, j);
sebastien's avatar
sebastien committed
200
201
202
203
204
205
206
207
        }
      for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
        {
          lag=m-ModelBlock->Block_List[j].Max_Lag;
          for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size;i++)
            {
              eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index[i];
              var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index[i];
208
              it=first_derivatives.find(make_pair(eq,getDerivID(symbol_table.getID(eEndogenous, var), lag)));
sebastien's avatar
sebastien committed
209
              //it=first_derivatives.find(make_pair(eq,variable_table.getID(var, lag)));
210
              //if(it!=first_derivatives.end())
sebastien's avatar
sebastien committed
211
212
              it->second->collectTemporary_terms(temporary_terms, ModelBlock, j);
            }
213
        }
214
			for(i=0; i<ModelBlock->Block_List[j].Chain_Rule_Derivatives->size();i++)
215
        {
216
217
218
219
220
221
          pair< pair<int, pair<int, int> >, pair<int, int> > it = ModelBlock->Block_List[j].Chain_Rule_Derivatives->at(i);
          lag=it.first.first;
          eq=it.first.second.first;
          var=it.first.second.second;
          it_chr=first_chain_rule_derivatives.find(make_pair(eq, make_pair( var, lag)));
          //it_chr->second->writeChainRuleDerivative(output, eq, var, k, oMatlabDynamicModelSparse, temporary_terms);
222
          it_chr->second->collectTemporary_terms(temporary_terms, ModelBlock, j);
sebastien's avatar
sebastien committed
223
        }
224
      /*for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
sebastien's avatar
sebastien committed
225
226
227
228
229
230
        {
          lag=m-ModelBlock->Block_List[j].Max_Lag;
          for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size_exo;i++)
            {
              eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_X_Index[i];
              var=ModelBlock->Block_List[j].IM_lead_lag[m].Exogenous_Index[i];
231
              it=first_derivatives.find(make_pair(eq,getDerivID(symbol_table.getID(eExogenous, var), lag)));
sebastien's avatar
sebastien committed
232
233
234
              //it=first_derivatives.find(make_pair(eq,variable_table.getID(var, lag)));
              it->second->collectTemporary_terms(temporary_terms, ModelBlock, j);
            }
235
        }*/
sebastien's avatar
sebastien committed
236
237
238
239
240
241
242
243
244
245
      //jacobian_max_exo_col=(variable_table.max_exo_lag+variable_table.max_exo_lead+1)*symbol_table.exo_nbr;
      for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
        {
          lag=m-ModelBlock->Block_List[j].Max_Lag;
          if (block_triangular.incidencematrix.Model_Max_Lag_Endo - ModelBlock->Block_List[j].Max_Lag +m >=0)
            {
              for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size_other_endo;i++)
                {
                  eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index_other_endo[i];
                  var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index_other_endo[i];
246
                  it=first_derivatives.find(make_pair(eq,getDerivID(symbol_table.getID(eEndogenous, var), lag)));
sebastien's avatar
sebastien committed
247
                  //it=first_derivatives.find(make_pair(eq,variable_table.getID(var, lag)));
248
                  //if(it!=first_derivatives.end())
sebastien's avatar
sebastien committed
249
250
251
252
253
254
255
256
257
258
259
260
261
262
                  it->second->collectTemporary_terms(temporary_terms, ModelBlock, j);
                }
            }
        }
    }
  // Add a mapping form node ID to temporary terms order
  j=0;
  for (temporary_terms_type::const_iterator it = temporary_terms.begin();
       it != temporary_terms.end(); it++)
    map_idx[(*it)->idx]=j++;
}

void
DynamicModel::writeModelEquationsOrdered_M( Model_Block *ModelBlock, const string &dynamic_basename) const
ferhat's avatar
ferhat committed
263
264
265
266
267
268
269
270
271
272
273
274
275
  {
    int i,j,k,m;
    string tmp_s, sps;
    ostringstream tmp_output, tmp1_output, global_output;
    NodeID lhs=NULL, rhs=NULL;
    BinaryOpNode *eq_node;
    ostringstream Uf[symbol_table.endo_nbr()];
    map<NodeID, int> reference_count;
    int prev_Simulation_Type=-1, count_derivates=0;
    int jacobian_max_endo_col;
    ofstream  output;
    //temporary_terms_type::const_iterator it_temp=temporary_terms.begin();
    int nze, nze_exo, nze_other_endo;
276
    //map<int, NodeID> recursive_variables;
ferhat's avatar
ferhat committed
277
278
279
280
281
    vector<int> feedback_variables;
    //----------------------------------------------------------------------
    //For each block
    for (j = 0;j < ModelBlock->Size;j++)
      {
282
        //recursive_variables.clear();
ferhat's avatar
ferhat committed
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
        feedback_variables.clear();
        //For a block composed of a single equation determines wether we have to evaluate or to solve the equation
        nze = nze_exo = nze_other_endo = 0;
        for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
          nze+=ModelBlock->Block_List[j].IM_lead_lag[m].size;
        /*for (m=0;m<=ModelBlock->Block_List[j].Max_Lead_Exo+ModelBlock->Block_List[j].Max_Lag_Exo;m++)
          nze_exo+=ModelBlock->Block_List[j].IM_lead_lag[m].size_exo;*/
        for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
          {
            k=m-ModelBlock->Block_List[j].Max_Lag;
            if (block_triangular.incidencematrix.Model_Max_Lag_Endo - ModelBlock->Block_List[j].Max_Lag +m >=0)
              nze_other_endo+=ModelBlock->Block_List[j].IM_lead_lag[m].size_other_endo;
          }
        tmp1_output.str("");
        tmp1_output << dynamic_basename << "_" << j+1 << ".m";
        output.open(tmp1_output.str().c_str(), ios::out | ios::binary);
        output << "%\n";
        output << "% " << tmp1_output.str() << " : Computes dynamic model for Dynare\n";
        output << "%\n";
        output << "% Warning : this file is generated automatically by Dynare\n";
        output << "%           from model file (.mod)\n\n";
        output << "%/\n";
        if (ModelBlock->Block_List[j].Simulation_Type==EVALUATE_BACKWARD
            ||ModelBlock->Block_List[j].Simulation_Type==EVALUATE_FORWARD
            /*||ModelBlock->Block_List[j].Simulation_Type==EVALUATE_BACKWARD_R
            ||ModelBlock->Block_List[j].Simulation_Type==EVALUATE_FORWARD_R*/)
          {
            output << "function [y, g1, g2, g3, varargout] = " << dynamic_basename << "_" << j+1 << "(y, x, params, jacobian_eval, y_kmin, periods)\n";
          }
        else if (ModelBlock->Block_List[j].Simulation_Type==SOLVE_FORWARD_COMPLETE
                 ||   ModelBlock->Block_List[j].Simulation_Type==SOLVE_BACKWARD_COMPLETE)
          output << "function [residual, y, g1, g2, g3, varargout] = " << dynamic_basename << "_" << j+1 << "(y, x, params, it_, jacobian_eval)\n";
        else if (ModelBlock->Block_List[j].Simulation_Type==SOLVE_BACKWARD_SIMPLE
                 ||   ModelBlock->Block_List[j].Simulation_Type==SOLVE_FORWARD_SIMPLE)
          output << "function [residual, y, g1, g2, g3, varargout] = " << dynamic_basename << "_" << j+1 << "(y, x, params, it_, jacobian_eval)\n";
        else
          output << "function [residual, y, g1, g2, g3, b, varargout] = " << dynamic_basename << "_" << j+1 << "(y, x, params, periods, jacobian_eval, y_kmin, y_size)\n";
        output << "  % ////////////////////////////////////////////////////////////////////////" << endl
        << "  % //" << string("                     Block ").substr(int(log10(j + 1))) << j + 1 << " " << BlockTriangular::BlockType0(ModelBlock->Block_List[j].Type)
        << "          //" << endl
        << "  % //                     Simulation type "
        << BlockTriangular::BlockSim(ModelBlock->Block_List[j].Simulation_Type) << "  //" << endl
        << "  % ////////////////////////////////////////////////////////////////////////" << endl;
        //The Temporary terms
        if (ModelBlock->Block_List[j].Simulation_Type==EVALUATE_BACKWARD
            ||ModelBlock->Block_List[j].Simulation_Type==EVALUATE_FORWARD
            /*||ModelBlock->Block_List[j].Simulation_Type==EVALUATE_BACKWARD_R
            ||ModelBlock->Block_List[j].Simulation_Type==EVALUATE_FORWARD_R*/)
          {
            output << "  if(jacobian_eval)\n";
            output << "    g1 = spalloc(" << ModelBlock->Block_List[j].Size-ModelBlock->Block_List[j].Nb_Recursives
            << ", " << (ModelBlock->Block_List[j].Size-ModelBlock->Block_List[j].Nb_Recursives)*(1+ModelBlock->Block_List[j].Max_Lag_Endo+ModelBlock->Block_List[j].Max_Lead_Endo)
            << ", " << nze << ");\n";
            output << "    g1_x=spalloc(" << ModelBlock->Block_List[j].Size << ", " << (ModelBlock->Block_List[j].nb_exo + ModelBlock->Block_List[j].nb_exo_det)*(1+ModelBlock->Block_List[j].Max_Lag_Exo+ModelBlock->Block_List[j].Max_Lead_Exo) << ", " << nze_exo << ");\n";
            output << "    g1_o=spalloc(" << ModelBlock->Block_List[j].Size << ", " << ModelBlock->Block_List[j].nb_other_endo*(1+ModelBlock->Block_List[j].Max_Lag_Other_Endo+ModelBlock->Block_List[j].Max_Lead_Other_Endo) << ", " << nze_other_endo << ");\n";
            output << "  end;\n";
          }
        else
          {
            output << "  if(jacobian_eval)\n";
            output << "    g1 = spalloc(" << ModelBlock->Block_List[j].Size << ", " << ModelBlock->Block_List[j].Size*(1+ModelBlock->Block_List[j].Max_Lag_Endo+ModelBlock->Block_List[j].Max_Lead_Endo) << ", " << nze << ");\n";
            output << "    g1_x=spalloc(" << ModelBlock->Block_List[j].Size << ", " << (ModelBlock->Block_List[j].nb_exo + ModelBlock->Block_List[j].nb_exo_det)*(1+ModelBlock->Block_List[j].Max_Lag_Exo+ModelBlock->Block_List[j].Max_Lead_Exo) << ", " << nze_exo << ");\n";
            output << "    g1_o=spalloc(" << ModelBlock->Block_List[j].Size << ", " << ModelBlock->Block_List[j].nb_other_endo*(1+ModelBlock->Block_List[j].Max_Lag_Other_Endo+ModelBlock->Block_List[j].Max_Lead_Other_Endo) << ", " << nze_other_endo << ");\n";
            output << "  else\n";
            if (ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_COMPLETE || ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_SIMPLE)
              {
                output << "    g1 = spalloc(" << (ModelBlock->Block_List[j].Size-ModelBlock->Block_List[j].Nb_Recursives)*ModelBlock->Periods
                << ", " << (ModelBlock->Block_List[j].Size-ModelBlock->Block_List[j].Nb_Recursives)*(ModelBlock->Periods+ModelBlock->Block_List[j].Max_Lag+ModelBlock->Block_List[j].Max_Lead+1)
                << ", " << nze*ModelBlock->Periods << ");\n";
352
                /*output << "    g1_tmp_r = spalloc(" << (ModelBlock->Block_List[j].Nb_Recursives)
ferhat's avatar
ferhat committed
353
354
355
356
                << ", " << (ModelBlock->Block_List[j].Size)*(ModelBlock->Block_List[j].Max_Lag+ModelBlock->Block_List[j].Max_Lead+1)
                << ", " << nze << ");\n";
                output << "    g1_tmp_b = spalloc(" << (ModelBlock->Block_List[j].Size-ModelBlock->Block_List[j].Nb_Recursives)
                << ", " << (ModelBlock->Block_List[j].Size)*(ModelBlock->Block_List[j].Max_Lag+ModelBlock->Block_List[j].Max_Lead+1)
357
                << ", " << nze << ");\n";*/
ferhat's avatar
ferhat committed
358
359
360
361
362
363
364
365
366
367
368
369
              }
            else
              {
                output << "    g1 = spalloc(" << ModelBlock->Block_List[j].Size-ModelBlock->Block_List[j].Nb_Recursives
                << ", " << ModelBlock->Block_List[j].Size-ModelBlock->Block_List[j].Nb_Recursives << ", " << nze << ");\n";
                output << "    g1_tmp_r = spalloc(" << ModelBlock->Block_List[j].Nb_Recursives
                << ", " << ModelBlock->Block_List[j].Size << ", " << nze << ");\n";
                output << "    g1_tmp_b = spalloc(" << ModelBlock->Block_List[j].Size-ModelBlock->Block_List[j].Nb_Recursives
                << ", " << ModelBlock->Block_List[j].Size << ", " << nze << ");\n";
              }
            output << "  end;\n";
          }
sebastien's avatar
sebastien committed
370

ferhat's avatar
ferhat committed
371
372
373
374
375
376
377
378
379
        output << "  g2=0;g3=0;\n";
        if (ModelBlock->Block_List[j].Temporary_InUse->size())
          {
            tmp_output.str("");
            for (temporary_terms_inuse_type::const_iterator it = ModelBlock->Block_List[j].Temporary_InUse->begin();
                 it != ModelBlock->Block_List[j].Temporary_InUse->end(); it++)
              tmp_output << " T" << *it;
            output << "  global" << tmp_output.str() << ";\n";
          }
380
        if (ModelBlock->Block_List[j].Simulation_Type!=EVALUATE_BACKWARD && ModelBlock->Block_List[j].Simulation_Type!=EVALUATE_FORWARD)
ferhat's avatar
ferhat committed
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
          output << "  residual=zeros(" << ModelBlock->Block_List[j].Size-ModelBlock->Block_List[j].Nb_Recursives << ",1);\n";
        if (ModelBlock->Block_List[j].Simulation_Type==EVALUATE_BACKWARD)
          output << "  for it_ = (y_kmin+periods):y_kmin+1\n";
        if (ModelBlock->Block_List[j].Simulation_Type==EVALUATE_FORWARD)
          output << "  for it_ = y_kmin+1:(y_kmin+periods)\n";

        if (ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_COMPLETE || ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_SIMPLE)
          {
            output << "  b = zeros(periods*y_size,1);\n";
            output << "  for it_ = y_kmin+1:(periods+y_kmin)\n";
            output << "    Per_y_=it_*y_size;\n";
            output << "    Per_J_=(it_-y_kmin-1)*y_size;\n";
            output << "    Per_K_=(it_-1)*y_size;\n";
            sps="  ";
          }
sebastien's avatar
sebastien committed
396
        else
ferhat's avatar
ferhat committed
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
          if (ModelBlock->Block_List[j].Simulation_Type==EVALUATE_BACKWARD || ModelBlock->Block_List[j].Simulation_Type==EVALUATE_FORWARD )
            sps = "  ";
          else
            sps="";
        // The equations
        for (i = 0;i < ModelBlock->Block_List[j].Size;i++)
          {
            temporary_terms_type tt2;
            tt2.clear();
            if (ModelBlock->Block_List[j].Temporary_Terms_in_Equation[i]->size())
              output << "  " << sps << "% //Temporary variables" << endl;
            for (temporary_terms_type::const_iterator it = ModelBlock->Block_List[j].Temporary_Terms_in_Equation[i]->begin();
                 it != ModelBlock->Block_List[j].Temporary_Terms_in_Equation[i]->end(); it++)
              {
                output << "  " <<  sps;
                (*it)->writeOutput(output, oMatlabDynamicModelSparse, temporary_terms);
                output << " = ";
                (*it)->writeOutput(output, oMatlabDynamicModelSparse, tt2);
                // Insert current node into tt2
                tt2.insert(*it);
                output << ";" << endl;
              }
            string sModel = symbol_table.getName(symbol_table.getID(eEndogenous, ModelBlock->Block_List[j].Variable[i])) ;
            eq_node = equations[ModelBlock->Block_List[j].Equation[i]];
            lhs = eq_node->get_arg1();
            rhs = eq_node->get_arg2();
            tmp_output.str("");
424
            /*if((ModelBlock->Block_List[j].Simulation_Type!=EVALUATE_BACKWARD or ModelBlock->Block_List[j].Simulation_Type!=EVALUATE_FORWARD) and (i<ModelBlock->Block_List[j].Nb_Recursives))
425
              lhs->writeOutput(tmp_output, oMatlabDynamicModelSparse, temporary_terms);
426
427
            else*/
						lhs->writeOutput(tmp_output, oMatlabDynamicModelSparse, temporary_terms);
ferhat's avatar
ferhat committed
428
429
430
431
            switch (ModelBlock->Block_List[j].Simulation_Type)
              {
              case EVALUATE_BACKWARD:
              case EVALUATE_FORWARD:
432
433
434
evaluation:     if (ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_COMPLETE || ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_SIMPLE)
                  output << "    % equation " << ModelBlock->Block_List[j].Equation[i]+1 << " variable : " << sModel
                  << " (" << ModelBlock->Block_List[j].Variable[i]+1 << ") " << block_triangular.c_Equation_Type(ModelBlock->Block_List[j].Equation_Type[i]) << endl;
ferhat's avatar
ferhat committed
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
                output << "    ";
                if (ModelBlock->Block_List[j].Equation_Type[i] == E_EVALUATE)
                  {
                    output << tmp_output.str();
                    output << " = ";
                    rhs->writeOutput(output, oMatlabDynamicModelSparse, temporary_terms);
                  }
                /*else if (ModelBlock->Block_List[j].Equation_Type[i] == E_EVALUATE_R)
                  {
                    rhs->writeOutput(output, oMatlabDynamicModelSparse, temporary_terms);
                    output << " = ";
                    output << tmp_output.str();
                    output << "; %reversed " << ModelBlock->Block_List[j].Equation_Type[i] << " \n";
                  }*/
                else if (ModelBlock->Block_List[j].Equation_Type[i] == E_EVALUATE_S)
                  {
                    output << "%" << tmp_output.str();
                    output << " = ";
                    if (ModelBlock->Block_List[j].Equation_Normalized[i])
                      {
                        rhs->writeOutput(output, oMatlabDynamicModelSparse, temporary_terms);
                        output << "\n    ";
457
458
459
460
461
462
463
464
465
466
467
468
469
                        /*temporary_terms_type tt2;
                        tt2.clear();*/
                        tmp_output.str("");
                        eq_node = (BinaryOpNode *)ModelBlock->Block_List[j].Equation_Normalized[i];
                        lhs = eq_node->get_arg1();
                        rhs = eq_node->get_arg2();
                        if(ModelBlock->Block_List[j].Simulation_Type==EVALUATE_BACKWARD or ModelBlock->Block_List[j].Simulation_Type==EVALUATE_FORWARD)
                         lhs->writeOutput(tmp_output, oMatlabDynamicModelSparse, temporary_terms);
                        else
                         lhs->writeOutput(tmp_output, oMatlabDynamicModelSparse, temporary_terms);
                        output << tmp_output.str();
                        output << " = ";
                        rhs->writeOutput(output, oMatlabDynamicModelSparse, temporary_terms);
ferhat's avatar
ferhat committed
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
                      }
                  }
                else
                  {
                    cerr << "Type missmatch for equation " << ModelBlock->Block_List[j].Equation[i]+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<ModelBlock->Block_List[j].Nb_Recursives)
                  {
485
                    /*if (ModelBlock->Block_List[j].Equation_Type[i] == E_EVALUATE_S)
ferhat's avatar
ferhat committed
486
487
                      recursive_variables[getDerivID(symbol_table.getID(eEndogenous, ModelBlock->Block_List[j].Variable[i]), 0)] = ModelBlock->Block_List[j].Equation_Normalized[i];
                    else
488
                      recursive_variables[getDerivID(symbol_table.getID(eEndogenous, ModelBlock->Block_List[j].Variable[i]), 0)] = equations[ModelBlock->Block_List[j].Equation[i]];*/
ferhat's avatar
ferhat committed
489
490
491
492
493
494
495
496
497
498
499
                    goto evaluation;
                  }
                feedback_variables.push_back(ModelBlock->Block_List[j].Variable[i]);
                output << "  % equation " << ModelBlock->Block_List[j].Equation[i]+1 << " variable : " << sModel
                << " (" << ModelBlock->Block_List[j].Variable[i]+1 << ") " << block_triangular.c_Equation_Type(ModelBlock->Block_List[j].Equation_Type[i]) << endl;
                output << "  " << "residual(" << i+1-ModelBlock->Block_List[j].Nb_Recursives << ") = (";
                goto end;
              case SOLVE_TWO_BOUNDARIES_COMPLETE:
              case SOLVE_TWO_BOUNDARIES_SIMPLE:
                if (i<ModelBlock->Block_List[j].Nb_Recursives)
                  {
500
                    /*if (ModelBlock->Block_List[j].Equation_Type[i] == E_EVALUATE_S)
ferhat's avatar
ferhat committed
501
502
                      recursive_variables[getDerivID(symbol_table.getID(eEndogenous, ModelBlock->Block_List[j].Variable[i]), 0)] = ModelBlock->Block_List[j].Equation_Normalized[i];
                    else
503
                      recursive_variables[getDerivID(symbol_table.getID(eEndogenous, ModelBlock->Block_List[j].Variable[i]), 0)] = equations[ModelBlock->Block_List[j].Equation[i]];*/
ferhat's avatar
ferhat committed
504
505
506
507
508
509
510
511
512
513
514
515
516
517
                    goto evaluation;
                  }
                feedback_variables.push_back(ModelBlock->Block_List[j].Variable[i]);
                output << "    % equation " << ModelBlock->Block_List[j].Equation[i]+1 << " variable : " << sModel
                << " (" << ModelBlock->Block_List[j].Variable[i]+1 << ") " << block_triangular.c_Equation_Type(ModelBlock->Block_List[j].Equation_Type[i]) << endl;
                Uf[ModelBlock->Block_List[j].Equation[i]] << "    b(" << i+1-ModelBlock->Block_List[j].Nb_Recursives << "+Per_J_) = -residual(" << i+1-ModelBlock->Block_List[j].Nb_Recursives << ", it_)";
                output << "    residual(" << i+1-ModelBlock->Block_List[j].Nb_Recursives << ", it_) = (";
                goto end;
              default:
end:
                output << tmp_output.str();
                output << ") - (";
                rhs->writeOutput(output, oMatlabDynamicModelSparse, temporary_terms);
                output << ");\n";
sebastien's avatar
sebastien committed
518
#ifdef CONDITION
ferhat's avatar
ferhat committed
519
520
                if (ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_COMPLETE || ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_SIMPLE)
                  output << "  condition(" << i+1 << ")=0;\n";
sebastien's avatar
sebastien committed
521
#endif
ferhat's avatar
ferhat committed
522
523
524
525
526
527
              }
          }
        // The Jacobian if we have to solve the block
        if (ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_SIMPLE
            ||  ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_COMPLETE)
          output << "  " << sps << "% Jacobian  " << endl;
sebastien's avatar
sebastien committed
528
        else
ferhat's avatar
ferhat committed
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
          if (ModelBlock->Block_List[j].Simulation_Type==SOLVE_BACKWARD_SIMPLE || ModelBlock->Block_List[j].Simulation_Type==SOLVE_FORWARD_SIMPLE ||
              ModelBlock->Block_List[j].Simulation_Type==SOLVE_BACKWARD_COMPLETE || ModelBlock->Block_List[j].Simulation_Type==SOLVE_FORWARD_COMPLETE)
            output << "  % Jacobian  " << endl << "  if jacobian_eval" << endl;
          else
            output << "    % Jacobian  " << endl << "    if jacobian_eval" << endl;
        switch (ModelBlock->Block_List[j].Simulation_Type)
          {
          case EVALUATE_BACKWARD:
          case EVALUATE_FORWARD:
          /*case EVALUATE_BACKWARD_R:
          case EVALUATE_FORWARD_R:*/
            count_derivates++;
            for (m=0;m<ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag+1;m++)
              {
                k=m-ModelBlock->Block_List[j].Max_Lag;
                for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size;i++)
                  {
                    int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index[i];
                    int var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index[i];
                    int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ[i];
                    int varr=ModelBlock->Block_List[j].IM_lead_lag[m].Var[i];
                    output << "      g1(" << eqr+1 << ", " << /*varr+1+(m+variable_table.max_lag-ModelBlock->Block_List[j].Max_Lag)*symbol_table.endo_nbr*/
sebastien's avatar
sebastien committed
551
                    varr+1+m*ModelBlock->Block_List[j].Size << ") = ";
ferhat's avatar
ferhat committed
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
                    writeDerivative(output, eq, symbol_table.getID(eEndogenous, var), k, oMatlabDynamicModelSparse, temporary_terms);
                    output << "; % variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, var))
                    << "(" << k//variable_table.getLag(variable_table.getSymbolID(ModelBlock->Block_List[j].Variable[0]))
                    << ") " << var+1
                    << ", equation=" << eq+1 << endl;
                  }
              }
            //jacobian_max_endo_col=(variable_table.max_endo_lag+variable_table.max_endo_lead+1)*symbol_table.endo_nbr;
            /*for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
              {
                k=m-ModelBlock->Block_List[j].Max_Lag;
                for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size_exo;i++)
                  {
                    int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_X_Index[i];
                    int var=ModelBlock->Block_List[j].IM_lead_lag[m].Exogenous_Index[i];
                    int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_X[i];
                    int varr=ModelBlock->Block_List[j].IM_lead_lag[m].Exogenous[i];
                    output << "      g1_x(" << eqr+1 << ", "
                           << varr+1+(m+max_exo_lag-ModelBlock->Block_List[j].Max_Lag)*symbol_table.exo_nbr() << ") = ";
                    writeDerivative(output, eq, symbol_table.getID(eExogenous, var), k, oMatlabDynamicModelSparse, temporary_terms);
                    output << "; % variable=" << symbol_table.getName(var)
                           << "(" << k << ") " << var+1
                           << ", equation=" << eq+1 << endl;
                  }
              }*/
            for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
              {
                k=m-ModelBlock->Block_List[j].Max_Lag;
                if (block_triangular.incidencematrix.Model_Max_Lag_Endo - ModelBlock->Block_List[j].Max_Lag +m >=0)
                  {
                    for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size_other_endo;i++)
                      {
                        int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index_other_endo[i];
                        int var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index_other_endo[i];
                        int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_other_endo[i];
                        int varr=ModelBlock->Block_List[j].IM_lead_lag[m].Var_other_endo[i];
                        output << "      g1_o(" << eqr+1 << ", "
                        << varr+1+(m+max_endo_lag-ModelBlock->Block_List[j].Max_Lag)*symbol_table.endo_nbr() << ") = ";
                        writeDerivative(output, eq, symbol_table.getID(eEndogenous, var), k, oMatlabDynamicModelSparse, temporary_terms);
                        output << "; % variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, var))
                        << "(" << k << ") " << var+1
                        << ", equation=" << eq+1 << endl;
                      }
                  }
              }
            output << "      varargout{1}=g1_x;\n";
            output << "      varargout{2}=g1_o;\n";
            output << "    end;" << endl;
            //output << "    ya = y;\n";
            output << "  end;" << endl;
            break;
          case SOLVE_BACKWARD_SIMPLE:
          case SOLVE_FORWARD_SIMPLE:
          case SOLVE_BACKWARD_COMPLETE:
          case SOLVE_FORWARD_COMPLETE:
            count_derivates++;
            for (m=0;m<ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag+1;m++)
              {
                k=m-ModelBlock->Block_List[j].Max_Lag;
                for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size;i++)
                  {
613
614
615
616
617
618
619
620
621
622
                    int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index[i];
                    int varr=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index[i];
                    int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ[i];
                    int var=ModelBlock->Block_List[j].IM_lead_lag[m].Var[i];
                    output << "    g1(" << eq+1 << ", "
                    << var+1 + m*(ModelBlock->Block_List[j].Size) << ") = ";
                    writeDerivative(output, eqr, symbol_table.getID(eEndogenous, varr), k, oMatlabDynamicModelSparse, temporary_terms);
                    output << "; % variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, varr))
                    << "(" << k << ") " << varr+1
                    << ", equation=" << eqr+1 << endl;
ferhat's avatar
ferhat committed
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
                  }
              }
            /*for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
              {
                k=m-ModelBlock->Block_List[j].Max_Lag;
                for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size_exo;i++)
                  {
                    int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_X_Index[i];
                    int var=ModelBlock->Block_List[j].IM_lead_lag[m].Exogenous_Index[i];
                    int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_X[i];
                    int varr=ModelBlock->Block_List[j].IM_lead_lag[m].Exogenous[i];
                    output << "    g1_x(" << eqr+1 << ", " << varr+1+(m+max_exo_lag-ModelBlock->Block_List[j].Max_Lag)*ModelBlock->Block_List[j].nb_exo << ") = ";
                    writeDerivative(output, eq, symbol_table.getID(eExogenous, var), k, oMatlabDynamicModelSparse, temporary_terms);
                    output << "; % variable=" << symbol_table.getName(var)
                           << "(" << k << ") " << var+1
                           << ", equation=" << eq+1 << endl;
                  }
              }*/
            for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
              {
                k=m-ModelBlock->Block_List[j].Max_Lag;
                if (block_triangular.incidencematrix.Model_Max_Lag_Endo - ModelBlock->Block_List[j].Max_Lag +m >=0)
                  {
                    for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size_other_endo;i++)
                      {
                        int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index_other_endo[i];
                        int var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index_other_endo[i];
                        int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_other_endo[i];
                        int varr=ModelBlock->Block_List[j].IM_lead_lag[m].Var_other_endo[i];
                        output << "    g1_o(" << eqr+1-ModelBlock->Block_List[j].Nb_Recursives << ", "
                        << varr+1+(m+max_endo_lag-ModelBlock->Block_List[j].Max_Lag)*symbol_table.endo_nbr() << ") = ";
                        writeDerivative(output, eq, symbol_table.getID(eEndogenous, var), k, oMatlabDynamicModelSparse, temporary_terms);
                        output << "; % variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, var))
                        << "(" << k << ") " << var+1
                        << ", equation=" << eq+1 << endl;
                      }
                  }
              }
            output << "    varargout{1}=g1_x;\n";
            output << "    varargout{2}=g1_o;\n";
            output << "  else" << endl;

            m=ModelBlock->Block_List[j].Max_Lag;
            //cout << "\nDerivatives in Block " << j << "\n";
667
            for(i=0; i<ModelBlock->Block_List[j].Chain_Rule_Derivatives->size();i++)
668
              {
669
670
671
672
673
674
675
676
                    //Chain_Rule_Derivatives.insert(make_pair( make_pair(eq, eqr), make_pair(var, make_pair(varr, lag))));
                    pair< pair<int, pair<int, int> >, pair<int, int> > it = ModelBlock->Block_List[j].Chain_Rule_Derivatives->at(i);
                    k=it.first.first;
                    int eq=it.first.second.first;
                    int var=it.first.second.second;
                    int eqr=it.second.first;
                    int varr=it.second.second;

677
            /*for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size;i++)
ferhat's avatar
ferhat committed
678
679
680
681
682
683
684
685
686
              {
                int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index[i];
                int var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index[i];
                int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ[i];
                int varr=ModelBlock->Block_List[j].IM_lead_lag[m].Var[i];
                ostringstream tmp_output;
                if (eqr<ModelBlock->Block_List[j].Nb_Recursives)
                  {
                    if (varr>=ModelBlock->Block_List[j].Nb_Recursives)
687
                      {*/
688
689
690
                        output << "    g1(" << eq+1-ModelBlock->Block_List[j].Nb_Recursives << ", "
                        << var+1-ModelBlock->Block_List[j].Nb_Recursives  << ") = ";
                        writeChainRuleDerivative(output, eqr, varr, k, oMatlabDynamicModelSparse, temporary_terms);
ferhat's avatar
ferhat committed
691
                        output << ";";
692
                        output << " %2 variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, varr))
ferhat's avatar
ferhat committed
693
                        << "(" << k
694
695
                        << ") " << varr+1
                        << ", equation=" << eqr+1 << endl;
ferhat's avatar
ferhat committed
696
                      }
697
                      /*}
ferhat's avatar
ferhat committed
698
                  }
699
              }*/
ferhat's avatar
ferhat committed
700
701
702
703
704
            output << "  end;\n";
            break;
          case SOLVE_TWO_BOUNDARIES_SIMPLE:
          case SOLVE_TWO_BOUNDARIES_COMPLETE:
            output << "    if ~jacobian_eval" << endl;
705
            /*for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
ferhat's avatar
ferhat committed
706
707
708
709
710
711
712
              {
                k=m-ModelBlock->Block_List[j].Max_Lag;
                for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size;i++)
                  {
                    int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index[i];
                    int var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index[i];
                    int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ[i];
713
                    int varr=ModelBlock->Block_List[j].IM_lead_lag[m].Var[i];*/
714
            for(i=0; i<ModelBlock->Block_List[j].Chain_Rule_Derivatives->size();i++)
715
              {
716
717
718
719
720
721
722
                    //Chain_Rule_Derivatives.insert(make_pair( make_pair(eq, eqr), make_pair(var, make_pair(varr, lag))));
                    pair< pair<int, pair<int, int> >, pair<int, int> > it = ModelBlock->Block_List[j].Chain_Rule_Derivatives->at(i);
                    k=it.first.first;
                    int eq=it.first.second.first;
                    int var=it.first.second.second;
                    int eqr=it.second.first;
                    int varr=it.second.second;
723
724
725
726

                    //bool derivative_exist;
                    ostringstream tmp_output;
                    /*if (eqr>=ModelBlock->Block_List[j].Nb_Recursives)
ferhat's avatar
ferhat committed
727
728
                      {
                        if (varr>=ModelBlock->Block_List[j].Nb_Recursives)
729
730
731
732
733
734
                          {*/
                    /*for(int equation = ModelBlock->Block_List[j].Nb_Recursives; equation<ModelBlock->Block_List[j].Size; equation++)
                      {
                        int eq = ModelBlock->Block_List[j].Equation[equation];
                        int eqr = equation - ModelBlock->Block_List[j].Nb_Recursives;
                        for(int variable = ModelBlock->Block_List[j].Nb_Recursives; variable<ModelBlock->Block_List[j].Size; variable++)
ferhat's avatar
ferhat committed
735
                          {
736
737
738
739
740
741
742
                            int var = ModelBlock->Block_List[j].Variable[variable];
                            int varr = variable - ModelBlock->Block_List[j].Nb_Recursives;*/
                            //cout << "eqr=" << eqr << " varr=" << varr;
                        //cout << "k=" << k << " eq=" << eq << " var=" << var << " eqr=" << eqr << " varr=" << varr << " ModelBlock->Block_List[j].Equation[eq]=" << ModelBlock->Block_List[j].Equation[eq] << "\n";
												if(eq>=ModelBlock->Block_List[j].Nb_Recursives and var>=ModelBlock->Block_List[j].Nb_Recursives)
												  {

ferhat's avatar
ferhat committed
743
                            if (k==0)
744
745
746
                              Uf[ModelBlock->Block_List[j].Equation[eq]] << "+g1(" << eq+1-ModelBlock->Block_List[j].Nb_Recursives
                              << "+Per_J_, " << var+1-ModelBlock->Block_List[j].Nb_Recursives
                              << "+Per_K_)*y(it_, " << varr+1 << ")";
ferhat's avatar
ferhat committed
747
                            else if (k==1)
748
749
750
                              Uf[ModelBlock->Block_List[j].Equation[eq]] << "+g1(" << eq+1-ModelBlock->Block_List[j].Nb_Recursives
                              << "+Per_J_, " << var+1-ModelBlock->Block_List[j].Nb_Recursives
                              << "+Per_y_)*y(it_+1, " << varr+1 << ")";
ferhat's avatar
ferhat committed
751
                            else if (k>0)
752
753
754
                              Uf[ModelBlock->Block_List[j].Equation[eq]] << "+g1(" << eq+1-ModelBlock->Block_List[j].Nb_Recursives
                              << "+Per_J_, " << var+1-ModelBlock->Block_List[j].Nb_Recursives
                              << "+y_size*(it_+" << k-1 << "))*y(it_+" << k << ", " << varr+1 << ")";
ferhat's avatar
ferhat committed
755
                            else if (k<0)
756
757
758
                              Uf[ModelBlock->Block_List[j].Equation[eq]] << "+g1(" << eq+1-ModelBlock->Block_List[j].Nb_Recursives
                              << "+Per_J_, " << var+1-ModelBlock->Block_List[j].Nb_Recursives
                              << "+y_size*(it_" << k-1 << "))*y(it_" << k << ", " << varr+1 << ")";
ferhat's avatar
ferhat committed
759
                            if (k==0)
760
761
                              tmp_output << "      g1(" << eq+1-ModelBlock->Block_List[j].Nb_Recursives << "+Per_J_, "
                              << var+1-ModelBlock->Block_List[j].Nb_Recursives << "+Per_K_) = ";
ferhat's avatar
ferhat committed
762
                            else if (k==1)
763
764
                              tmp_output << "      g1(" << eq+1-ModelBlock->Block_List[j].Nb_Recursives << "+Per_J_, "
                              << var+1-ModelBlock->Block_List[j].Nb_Recursives << "+Per_y_) = ";
ferhat's avatar
ferhat committed
765
                            else if (k>0)
766
767
                              tmp_output << "      g1(" << eq+1-ModelBlock->Block_List[j].Nb_Recursives << "+Per_J_, "
                              << var+1-ModelBlock->Block_List[j].Nb_Recursives << "+y_size*(it_+" << k-1 << ")) = ";
ferhat's avatar
ferhat committed
768
                            else if (k<0)
769
770
                              tmp_output << "      g1(" << eq+1-ModelBlock->Block_List[j].Nb_Recursives << "+Per_J_, "
                              << var+1-ModelBlock->Block_List[j].Nb_Recursives << "+y_size*(it_" << k-1 << ")) = ";
ferhat's avatar
ferhat committed
771
772


773
774
                            output << " " << tmp_output.str();

775
                            writeChainRuleDerivative(output, eqr, varr, k, oMatlabDynamicModelSparse, temporary_terms);
776
777
778
779

                            output << ";";
                            output << " %2 variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, varr))
                                   << "(" << k << ") " << varr+1
780
                                   << ", equation=" << eqr+1 << " (" << eq+1 << ")" << endl;
781
782
783
784
												  }
                            //cout << " done\n";
                         /* }
                      }*/
sebastien's avatar
sebastien committed
785
786

#ifdef CONDITION
ferhat's avatar
ferhat committed
787
788
                    output << "  if (fabs(condition[" << eqr << "])<fabs(u[" << u << "+Per_u_]))\n";
                    output << "    condition(" << eqr << ")=u(" << u << "+Per_u_);\n";
sebastien's avatar
sebastien committed
789
#endif
790
                  //}
ferhat's avatar
ferhat committed
791
792
793
794
795
              }
            for (i = 0;i < ModelBlock->Block_List[j].Size;i++)
              {
                if (i>=ModelBlock->Block_List[j].Nb_Recursives)
                  output << "  " << Uf[ModelBlock->Block_List[j].Equation[i]].str() << ";\n";
sebastien's avatar
sebastien committed
796
#ifdef CONDITION
ferhat's avatar
ferhat committed
797
798
                output << "  if (fabs(condition(" << i+1 << "))<fabs(u(" << i << "+Per_u_)))\n";
                output << "    condition(" << i+1 << ")=u(" << i+1 << "+Per_u_);\n";
sebastien's avatar
sebastien committed
799
#endif
ferhat's avatar
ferhat committed
800
              }
sebastien's avatar
sebastien committed
801
#ifdef CONDITION
ferhat's avatar
ferhat committed
802
803
804
805
806
807
808
809
810
811
812
813
814
815
            for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
              {
                k=m-ModelBlock->Block_List[j].Max_Lag;
                for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size;i++)
                  {
                    int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index[i];
                    int var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index[i];
                    int u=ModelBlock->Block_List[j].IM_lead_lag[m].u[i];
                    int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ[i];
                    output << "  u(" << u+1 << "+Per_u_) = u(" << u+1 << "+Per_u_) / condition(" << eqr+1 << ");\n";
                  }
              }
            for (i = 0;i < ModelBlock->Block_List[j].Size;i++)
              output << "  u(" << i+1 << "+Per_u_) = u(" << i+1 << "+Per_u_) / condition(" << i+1 << ");\n";
sebastien's avatar
sebastien committed
816
817
#endif

ferhat's avatar
ferhat committed
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
            output << "    else" << endl;
            for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
              {
                k=m-ModelBlock->Block_List[j].Max_Lag;
                for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size;i++)
                  {
                    int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index[i];
                    int var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index[i];
                    int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ[i];
                    int varr=ModelBlock->Block_List[j].IM_lead_lag[m].Var[i];
                    output << "      g1(" << eqr+1 << ", " << varr+1+(m-ModelBlock->Block_List[j].Max_Lag+ModelBlock->Block_List[j].Max_Lag_Endo)*ModelBlock->Block_List[j].Size << ") = ";
                    writeDerivative(output, eq, symbol_table.getID(eEndogenous, var), k, oMatlabDynamicModelSparse, temporary_terms);
                    output << "; % variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, var))
                    << "(" << k << ") " << var+1
                    << ", equation=" << eq+1 << endl;
                  }
              }
            jacobian_max_endo_col=(ModelBlock->Block_List[j].Max_Lead_Endo+ModelBlock->Block_List[j].Max_Lag_Endo+1)*ModelBlock->Block_List[j].Size;
            /*for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
              {
                k=m-ModelBlock->Block_List[j].Max_Lag;
                for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size_exo;i++)
                  {
                    int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_X_Index[i];
                    int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_X[i];
                    int varr=ModelBlock->Block_List[j].IM_lead_lag[m].Exogenous[i];
                    int var=ModelBlock->Block_List[j].IM_lead_lag[m].Exogenous_Index[i];
                    output << "      g1_x(" << eqr+1 << ", "
                           << jacobian_max_endo_col+(m-(ModelBlock->Block_List[j].Max_Lag-ModelBlock->Block_List[j].Max_Lag_Exo))*ModelBlock->Block_List[j].nb_exo+varr+1 << ") = ";
                    writeDerivative(output, eq, symbol_table.getID(eExogenous, var), k, oMatlabDynamicModelSparse, temporary_terms);
                    output << "; % variable (exogenous)=" << symbol_table.getName(var)
                           << "(" << k << ") " << var+1 << " " << varr+1
                           << ", equation=" << eq+1 << endl;
                  }
              }*/
            for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
              {
                k=m-ModelBlock->Block_List[j].Max_Lag;
                if (block_triangular.incidencematrix.Model_Max_Lag_Endo - ModelBlock->Block_List[j].Max_Lag +m >=0)
                  {
                    for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size_other_endo;i++)
                      {
                        int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index_other_endo[i];
                        int var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index_other_endo[i];
                        int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_other_endo[i];
                        int varr=ModelBlock->Block_List[j].IM_lead_lag[m].Var_other_endo[i];
                        output << "      g1_o(" << eqr+1 << ", "
                        << varr+1+(m+max_endo_lag-ModelBlock->Block_List[j].Max_Lag)*symbol_table.endo_nbr() << ") = ";
                        writeDerivative(output, eq, symbol_table.getID(eEndogenous, var), k, oMatlabDynamicModelSparse, temporary_terms);
                        output << "; % variable=" << symbol_table.getName(symbol_table.getID(eEndogenous, var))
                        << "(" << k << ") " << var+1
                        << ", equation=" << eq+1 << endl;
                      }
                  }
              }
            output << "      varargout{1}=g1_x;\n";
            output << "      varargout{2}=g1_o;\n";
            output << "    end;\n";
            //output << "    ya = y;\n";
            output << "  end;\n";
            break;
          default:
            break;
          }
        prev_Simulation_Type=ModelBlock->Block_List[j].Simulation_Type;
        output.close();
      }
  }
sebastien's avatar
sebastien committed
886
887

void
sebastien's avatar
sebastien committed
888
DynamicModel::writeModelEquationsCodeOrdered(const string file_name, const Model_Block *ModelBlock, const string bin_basename, map_idx_type map_idx) const
sebastien's avatar
sebastien committed
889
  {
ferhat's avatar
ferhat committed
890
891
892
893
894
895
896
897
898
899
900
901
    struct Uff_l
      {
        int u, var, lag;
        Uff_l *pNext;
      };

    struct Uff
      {
        Uff_l *Ufl, *Ufl_First;
        int eqr;
      };

902
    int i,j,k,m, v;
ferhat's avatar
ferhat committed
903
904
905
906
907
908
909
910
    string tmp_s;
    ostringstream tmp_output;
    ofstream code_file;
    NodeID lhs=NULL, rhs=NULL;
    BinaryOpNode *eq_node;
    bool lhs_rhs_done;
    Uff Uf[symbol_table.endo_nbr()];
    map<NodeID, int> reference_count;
911
    vector<int> feedback_variables;
ferhat's avatar
ferhat committed
912
913
914
915
916
917
918
919
920
921
922
923
924
    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())
      {
        cout << "Error : Can't open file \"" << main_name << "\" for writing\n";
        exit(EXIT_FAILURE);
      }
    //Temporary variables declaration
    code_file.write(&FDIMT, sizeof(FDIMT));
    k=temporary_terms.size();
    code_file.write(reinterpret_cast<char *>(&k),sizeof(k));
925
926

    for (j = 0; j < ModelBlock->Size ;j++)
ferhat's avatar
ferhat committed
927
      {
928
929
        feedback_variables.clear();
        if (j>0)
ferhat's avatar
ferhat committed
930
931
          code_file.write(&FENDBLOCK, sizeof(FENDBLOCK));
        code_file.write(&FBEGINBLOCK, sizeof(FBEGINBLOCK));
932
933
        v=ModelBlock->Block_List[j].Size - ModelBlock->Block_List[j].Nb_Recursives;
        //cout << "v (Size) = " << v  << "\n";
ferhat's avatar
ferhat committed
934
935
936
        code_file.write(reinterpret_cast<char *>(&v),sizeof(v));
        v=ModelBlock->Block_List[j].Simulation_Type;
        code_file.write(reinterpret_cast<char *>(&v),sizeof(v));
937
938
        int count_u;
        for (i=ModelBlock->Block_List[j].Nb_Recursives; i < ModelBlock->Block_List[j].Size;i++)
ferhat's avatar
ferhat committed
939
          {
940
941
942
            code_file.write(reinterpret_cast<char *>(&ModelBlock->Block_List[j].Variable[i]),sizeof(ModelBlock->Block_List[j].Variable[i]));
            code_file.write(reinterpret_cast<char *>(&ModelBlock->Block_List[j].Equation[i]),sizeof(ModelBlock->Block_List[j].Equation[i]));
            code_file.write(reinterpret_cast<char *>(&ModelBlock->Block_List[j].Own_Derivative[i]),sizeof(ModelBlock->Block_List[j].Own_Derivative[i]));
ferhat's avatar
ferhat committed
943
944
945
946
          }
        if (ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_SIMPLE || ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_COMPLETE ||
            ModelBlock->Block_List[j].Simulation_Type==SOLVE_BACKWARD_COMPLETE || ModelBlock->Block_List[j].Simulation_Type==SOLVE_FORWARD_COMPLETE)
          {
947
948
949
950
951
            int u_count_int=0;
            //cout << "ModelBlock->Block_List[j].Nb_Recursives = " << ModelBlock->Block_List[j].Nb_Recursives << "\n";
            Write_Inf_To_Bin_File(file_name, bin_basename, j, u_count_int,file_open,
                                  ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_COMPLETE || ModelBlock->Block_List[j].Simulation_Type==SOLVE_TWO_BOUNDARIES_SIMPLE);
						//cout << "u_count_int=" << u_count_int << "\n";
ferhat's avatar
ferhat committed
952
            code_file.write(reinterpret_cast<char *>(&ModelBlock->Block_List[j].is_linear),sizeof(ModelBlock->Block_List[j].is_linear));
953
954
            //v=block_triangular.ModelBlock->Block_List[j].IM_lead_lag[block_triangular.ModelBlock->Block_List[j].Max_Lag + block_triangular.ModelBlock->Block_List[j].Max_Lead].u_finish + 1;
            v = u_count_int ;
ferhat's avatar
ferhat committed
955
956
957
958
959
960
961
            code_file.write(reinterpret_cast<char *>(&v),sizeof(v));
            v=symbol_table.endo_nbr();
            code_file.write(reinterpret_cast<char *>(&v),sizeof(v));
            v=block_triangular.ModelBlock->Block_List[j].Max_Lag;
            code_file.write(reinterpret_cast<char *>(&v),sizeof(v));
            v=block_triangular.ModelBlock->Block_List[j].Max_Lead;
            code_file.write(reinterpret_cast<char *>(&v),sizeof(v));
962

ferhat's avatar
ferhat committed
963
964
965
966
            v=u_count_int;
            code_file.write(reinterpret_cast<char *>(&v),sizeof(v));
            file_open=true;
          }
967
            /*if (ModelBlock->Block_List[j].Size==1)
ferhat's avatar
ferhat committed
968
969
970
971
972
973
974
              {
                lhs_rhs_done=true;
                eq_node = equations[ModelBlock->Block_List[j].Equation[0]];
                lhs = eq_node->get_arg1();
                rhs = eq_node->get_arg2();
              }
            else
975
              lhs_rhs_done=false;*/
ferhat's avatar
ferhat committed
976
977
978
979
980
            // The equations
            for (i = 0;i < ModelBlock->Block_List[j].Size;i++)
              {
                //The Temporary terms
                temporary_terms_type tt2;
981
982
983
                tt2.clear();
                /*if (ModelBlock->Block_List[j].Temporary_Terms_in_Equation[i]->size())
                  output << "  " << sps << "% //Temporary variables" << endl;*/
sebastien's avatar
sebastien committed
984
#ifdef DEBUGC
ferhat's avatar
ferhat committed
985
                k=0;
sebastien's avatar
sebastien committed
986
#endif
ferhat's avatar
ferhat committed
987
988
989
990
991
992
993
994
995
996
                for (temporary_terms_type::const_iterator it = ModelBlock->Block_List[j].Temporary_Terms_in_Equation[i]->begin();
                     it != ModelBlock->Block_List[j].Temporary_Terms_in_Equation[i]->end(); it++)
                  {
                    (*it)->compile(code_file, false, tt2, map_idx);
                    code_file.write(&FSTPT, sizeof(FSTPT));
                    map_idx_type::const_iterator ii=map_idx.find((*it)->idx);
                    v=(int)ii->second;
                    code_file.write(reinterpret_cast<char *>(&v), sizeof(v));
                    // Insert current node into tt2
                    tt2.insert(*it);
sebastien's avatar
sebastien committed
997
#ifdef DEBUGC
ferhat's avatar
ferhat committed
998
999
1000
1001
                    cout << "FSTPT " << v << "\n";
                    code_file.write(&FOK, sizeof(FOK));
                    code_file.write(reinterpret_cast<char *>(&k), sizeof(k));
                    ki++;
sebastien's avatar
sebastien committed
1002
1003
#endif

ferhat's avatar
ferhat committed
1004
                  }
sebastien's avatar
sebastien committed
1005
#ifdef DEBUGC
ferhat's avatar
ferhat committed
1006
1007
1008
1009
1010
1011
                for (temporary_terms_type::const_iterator it = ModelBlock->Block_List[j].Temporary_terms->begin();
                     it != ModelBlock->Block_List[j].Temporary_terms->end(); it++)
                  {
                    map_idx_type::const_iterator ii=map_idx.find((*it)->idx);
                    cout << "map_idx[" << (*it)->idx <<"]=" << ii->second << "\n";
                  }
sebastien's avatar
sebastien committed
1012
#endif
1013
1014
                /*if (!lhs_rhs_done)
                  {*/
ferhat's avatar
ferhat committed
1015
1016
1017
                    eq_node = equations[ModelBlock->Block_List[j].Equation[i]];
                    lhs = eq_node->get_arg1();
                    rhs = eq_node->get_arg2();
1018
                  /*}*/
ferhat's avatar
ferhat committed
1019
1020
                switch (ModelBlock->Block_List[j].Simulation_Type)
                  {
1021
evaluation:
ferhat's avatar
ferhat committed
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
                  case EVALUATE_BACKWARD:
                  case EVALUATE_FORWARD:
                    if (ModelBlock->Block_List[j].Equation_Type[i] == E_EVALUATE)
                      {
                        rhs->compile(code_file, false, temporary_terms, map_idx);
                        lhs->compile(code_file, true, temporary_terms, map_idx);
                      }
                    else if (ModelBlock->Block_List[j].Equation_Type[i] == E_EVALUATE_S)
                      {
                        eq_node = (BinaryOpNode*)ModelBlock->Block_List[j].Equation_Normalized[i];
                        //cout << "EVALUATE_S var " << ModelBlock->Block_List[j].Variable[i] << "\n";
                        lhs = eq_node->get_arg1();
                        rhs = eq_node->get_arg2();
                        rhs->compile(code_file, false, temporary_terms, map_idx);
                        lhs->compile(code_file, true, temporary_terms, map_idx);
                      }
                    break;
                  case SOLVE_BACKWARD_COMPLETE:
                  case SOLVE_FORWARD_COMPLETE:
                  case SOLVE_TWO_BOUNDARIES_COMPLETE:
                  case SOLVE_TWO_BOUNDARIES_SIMPLE:
1043
1044
1045
                    if (i<ModelBlock->Block_List[j].Nb_Recursives)
                      goto evaluation;
                    feedback_variables.push_back(ModelBlock->Block_List[j].Variable[i]);
ferhat's avatar
ferhat committed
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
                    v=ModelBlock->Block_List[j].Equation[i];
                    Uf[v].eqr=i;
                    Uf[v].Ufl=NULL;
                    goto end;
                  default:
end:
                    lhs->compile(code_file, false, temporary_terms, map_idx);
                    rhs->compile(code_file, false, temporary_terms, map_idx);
                    code_file.write(&FBINARY, sizeof(FBINARY));
                    int v=oMinus;
                    code_file.write(reinterpret_cast<char *>(&v),sizeof(v));
                    code_file.write(&FSTPR, sizeof(FSTPR));
1058
1059
1060
                    v = i - ModelBlock->Block_List[j].Nb_Recursives;
                    //cout << "residual[" << v << "]\n";
                    code_file.write(reinterpret_cast<char *>(&v), sizeof(v));
ferhat's avatar
ferhat committed
1061
1062
1063
1064
                  }
              }
            code_file.write(&FENDEQU, sizeof(FENDEQU));
            // The Jacobian if we have to solve the block
1065
            bool feedback_variable =  (feedback_variables.size()>0);
ferhat's avatar
ferhat committed
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
            if (ModelBlock->Block_List[j].Simulation_Type!=EVALUATE_BACKWARD
                && ModelBlock->Block_List[j].Simulation_Type!=EVALUATE_FORWARD
                /*&& ModelBlock->Block_List[j].Simulation_Type!=EVALUATE_BACKWARD_R
                && ModelBlock->Block_List[j].Simulation_Type!=EVALUATE_FORWARD_R*/)
              {
                switch (ModelBlock->Block_List[j].Simulation_Type)
                  {
                  case SOLVE_BACKWARD_SIMPLE:
                  case SOLVE_FORWARD_SIMPLE:
                    compileDerivative(code_file, ModelBlock->Block_List[j].Equation[0], ModelBlock->Block_List[j].Variable[0], 0, map_idx);
                    code_file.write(&FSTPG, sizeof(FSTPG));
                    v=0;
                    code_file.write(reinterpret_cast<char *>(&v), sizeof(v));
                    break;
                  case SOLVE_BACKWARD_COMPLETE:
                  case SOLVE_FORWARD_COMPLETE:
1082
1083
1084
                    count_u = feedback_variables.size();
                    //cout << "todo SOLVE_COMPLETE\n";
                    for(i=0; i<ModelBlock->Block_List[j].Chain_Rule_Derivatives->size();i++)
ferhat's avatar
ferhat committed
1085
                      {
1086
1087
1088
1089
1090
1091
1092
1093
1094
                        //Chain_Rule_Derivatives.insert(make_pair( make_pair(eq, eqr), make_pair(var, make_pair(varr, lag))));
                        pair< pair<int, pair<int, int> >, pair<int, int> > it = ModelBlock->Block_List[j].Chain_Rule_Derivatives->at(i);
                        k=it.first.first;
                        int eq=it.first.second.first;;
                        int var=it.first.second.second;
                        int eqr=it.second.first;
                        int varr=it.second.second;
                        int v=ModelBlock->Block_List[j].Equation[eq];
                        if (!Uf[v].Ufl)
ferhat's avatar
ferhat committed
1095
                          {
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
                            Uf[v].Ufl=(Uff_l*)malloc(sizeof(Uff_l));
                            Uf[v].Ufl_First=Uf[v].Ufl;
                          }
                        else
                          {
                            Uf[v].Ufl->pNext=(Uff_l*)malloc(sizeof(Uff_l));
                            Uf[v].Ufl=Uf[v].Ufl->pNext;
                          }
                        Uf[v].Ufl->pNext=NULL;
                        Uf[v].Ufl->u=count_u;
                        Uf[v].Ufl->var=varr;
                        compileChainRuleDerivative(code_file, eqr, varr, 0, map_idx);
                        code_file.write(&FSTPU, sizeof(FSTPU));
                        code_file.write(reinterpret_cast<char *>(&count_u), sizeof(count_u));
                        count_u++;
                      }
										//cout << "done SOLVE_COMPLETE\n";
                    for (i = 0;i < ModelBlock->Block_List[j].Size;i++)
                      {
                      	if(i>=ModelBlock->Block_List[j].Nb_Recursives)
                      	  {
                            code_file.write(&FLDR, sizeof(FLDR));
                            v = i-ModelBlock->Block_List[j].Nb_Recursives;
                            code_file.write(reinterpret_cast<char *>(&v), sizeof(v));
                            code_file.write(&FLDZ, sizeof(FLDZ));
                            int v=ModelBlock->Block_List[j].Equation[i];
                            for (Uf[v].Ufl=Uf[v].Ufl_First;Uf[v].Ufl;Uf[v].Ufl=Uf[v].Ufl->pNext)
1123
                              {
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
                                code_file.write(&FLDU, sizeof(FLDU));
                                code_file.write(reinterpret_cast<char *>(&Uf[v].Ufl->u), sizeof(Uf[v].Ufl->u));
                                code_file.write(&FLDV, sizeof(FLDV));
                                char vc=eEndogenous;
                                code_file.write(reinterpret_cast<char *>(&vc), sizeof(vc));
                                code_file.write(reinterpret_cast<char *>(&Uf[v].Ufl->var), sizeof(Uf[v].Ufl->var));
                                int v1=0;
                                code_file.write(reinterpret_cast<char *>(&v1), sizeof(v1));
                                code_file.write(&FBINARY, sizeof(FBINARY));
                                v1=oTimes;
                                code_file.write(reinterpret_cast<char *>(&v1), sizeof(v1));
                                code_file.write(&FCUML, sizeof(FCUML));
1136
                              }
1137
1138
                            Uf[v].Ufl=Uf[v].Ufl_First;
                            while (Uf[v].Ufl)
1139
                              {
1140
1141
1142
                                Uf[v].Ufl_First=Uf[v].Ufl->pNext;
                                free(Uf[v].Ufl);
                                Uf[v].Ufl=Uf[v].Ufl_First;
1143
                              }
1144
1145
1146
                            code_file.write(&FBINARY, sizeof(FBINARY));
                            v=oMinus;
                            code_file.write(reinterpret_cast<char *>(&v), sizeof(v));
1147
                            code_file.write(&FSTPU, sizeof(FSTPU));
1148
1149
1150
                            v = i - ModelBlock->Block_List[j].Nb_Recursives;
                            code_file.write(reinterpret_cast<char *>(&v), sizeof(v));
                      	  }
1151
                      }
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
                    break;
                  case SOLVE_TWO_BOUNDARIES_COMPLETE:
                  case SOLVE_TWO_BOUNDARIES_SIMPLE:
										count_u=ModelBlock->Block_List[j].Size - ModelBlock->Block_List[j].Nb_Recursives;
										//cout << "todo SOLVE_TWO_BOUNDARIES\n";
										//cout << "ModelBlock->Block_List[j].Nb_Recursives=" << ModelBlock->Block_List[j].Nb_Recursives << "\n";
                    for(i=0; i<ModelBlock->Block_List[j].Chain_Rule_Derivatives->size();i++)
											{
                        //Chain_Rule_Derivatives.insert(make_pair( make_pair(eq, eqr), make_pair(var, make_pair(varr, lag))));
                        pair< pair<int, pair<int, int> >, pair<int, int> > it = ModelBlock->Block_List[j].Chain_Rule_Derivatives->at(i);
                        k=it.first.first;
                        int eq=it.first.second.first;
                        int var=it.first.second.second;
                        int eqr=it.second.first;
                        int varr=it.second.second;
                        //cout << "k=" << k << " eq=" << eq << " (" << eq-ModelBlock->Block_List[j].Nb_Recursives << ") var=" << var << " (" << var-ModelBlock->Block_List[j].Nb_Recursives << ") eqr=" << eqr << " varr=" << varr << " count_u=" << count_u << "\n";
                        int v=ModelBlock->Block_List[j].Equation[eq];
												/*m = ModelBlock->Block_List[j].Max_Lag + k;
                        int u=ModelBlock->Block_List[j].IM_lead_lag[m].u[i];*/
                        if(eq>=ModelBlock->Block_List[j].Nb_Recursives and var>=ModelBlock->Block_List[j].Nb_Recursives)
												  {
												  	if (!Uf[v].Ufl)
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
                              {
                                Uf[v].Ufl=(Uff_l*)malloc(sizeof(Uff_l));
                                Uf[v].Ufl_First=Uf[v].Ufl;
                              }
                            else
                              {
                                Uf[v].Ufl->pNext=(Uff_l*)malloc(sizeof(Uff_l));
                                Uf[v].Ufl=Uf[v].Ufl->pNext;
                              }
                            Uf[v].Ufl->pNext=NULL;
1184
1185
1186
1187
1188
1189
                            Uf[v].Ufl->u=count_u;
                            Uf[v].Ufl->var=varr;
                            Uf[v].Ufl->lag=k;
                            //writeChainRuleDerivative(cout, eqr, varr, k, oMatlabDynamicModelSparse, /*map_idx*/temporary_terms);
                            //cout <<"\n";
                            compileChainRuleDerivative(code_file, eqr, varr, k, map_idx);
1190
                            code_file.write(&FSTPU, sizeof(FSTPU));
1191
1192
1193
1194
1195
1196
                            code_file.write(reinterpret_cast<char *>(&count_u), sizeof(count_u));
                            count_u++;
												  }
											}
										//cout << "done it SOLVE_TWO_BOUNDARIES\n";
                    /*for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
ferhat's avatar
ferhat committed
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
                      {
                        k=m-ModelBlock->Block_List[j].Max_Lag;
                        for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size;i++)
                          {
                            int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index[i];
                            int var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index[i];
                            int u=ModelBlock->Block_List[j].IM_lead_lag[m].u[i];
                            int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ[i];
                            int v=ModelBlock->Block_List[j].Equation[eqr];
                            if (!Uf[v].Ufl)
                              {
                                Uf[v].Ufl=(Uff_l*)malloc(sizeof(Uff_l));
                                Uf[v].Ufl_First=Uf[v].Ufl;
                              }
                            else
                              {
                                Uf[v].Ufl->pNext=(Uff_l*)malloc(sizeof(Uff_l));
                                Uf[v].Ufl=Uf[v].Ufl->pNext;
                              }
                            Uf[v].Ufl->pNext=NULL;
                            Uf[v].Ufl->u=u;
                            Uf[v].Ufl->var=var;
                            Uf[v].Ufl->lag=k;
                            compileDerivative(code_file, eq, var, k, map_idx);
                            code_file.write(&FSTPU, sizeof(FSTPU));
                            code_file.write(reinterpret_cast<char *>(&u), sizeof(u));
                          }
1224
                      }*/
ferhat's avatar
ferhat committed
1225
1226
                    for (i = 0;i < ModelBlock->Block_List[j].Size;i++)
                      {
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
                      	if(i>=ModelBlock->Block_List[j].Nb_Recursives)
                      	  {
                            code_file.write(&FLDR, sizeof(FLDR));
                            v = i-ModelBlock->Block_List[j].Nb_Recursives;
                            code_file.write(reinterpret_cast<char *>(&v), sizeof(v));
                            code_file.write(&FLDZ, sizeof(FLDZ));
                            int v=ModelBlock->Block_List[j].Equation[i];
                            for (Uf[v].Ufl=Uf[v].Ufl_First; Uf[v].Ufl; Uf[v].Ufl=Uf[v].Ufl->pNext)
                              {
                                code_file.write(&FLDU, sizeof(FLDU));
                                code_file.write(reinterpret_cast<char *>(&Uf[v].Ufl->u), sizeof(Uf[v].Ufl->u));
                                code_file.write(&FLDV, sizeof(FLDV));
                                char vc=eEndogenous;
                                code_file.write(reinterpret_cast<char *>(&vc), sizeof(vc));
                                int v1=Uf[v].Ufl->var;
                                code_file.write(reinterpret_cast<char *>(&v1), sizeof(v1));
                                v1=Uf[v].Ufl->lag;
                                code_file.write(reinterpret_cast<char *>(&v1), sizeof(v1));
                                code_file.write(&FBINARY, sizeof(FBINARY));
                                v1=oTimes;
                                code_file.write(reinterpret_cast<char *>(&v1), sizeof(v1));
                                code_file.write(&FCUML, sizeof(FCUML));
                              }
ferhat's avatar
ferhat committed
1250
                            Uf[v].Ufl=Uf[v].Ufl_First;
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
                            while (Uf[v].Ufl)
                              {
                                Uf[v].Ufl_First=Uf[v].Ufl->pNext;
                                free(Uf[v].Ufl);
                                Uf[v].Ufl=Uf[v].Ufl_First;
                              }
                            code_file.write(&FBINARY, sizeof(FBINARY));
                            v=oMinus;
                            code_file.write(reinterpret_cast<char *>(&v), sizeof(v));
                            code_file.write(&FSTPU, sizeof(FSTPU));
                            v = i - ModelBlock->Block_List[j].Nb_Recursives;
                            code_file.write(reinterpret_cast<char *>(&v), sizeof(v));
                      	  }
ferhat's avatar
ferhat committed
1264
                      }
sebastien's avatar
sebastien committed
1265
#ifdef CONDITION
ferhat's avatar
ferhat committed
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
                    for (m=0;m<=ModelBlock->Block_List[j].Max_Lead+ModelBlock->Block_List[j].Max_Lag;m++)
                      {
                        k=m-ModelBlock->Block_List[j].Max_Lag;
                        for (i=0;i<ModelBlock->Block_List[j].IM_lead_lag[m].size;i++)
                          {
                            int eq=ModelBlock->Block_List[j].IM_lead_lag[m].Equ_Index[i];
                            int var=ModelBlock->Block_List[j].IM_lead_lag[m].Var_Index[i];
                            int u=ModelBlock->Block_List[j].IM_lead_lag[m].u[i];
                            int eqr=ModelBlock->Block_List[j].IM_lead_lag[m].Equ[i];
                            output << "  u[" << u << "+Per_u_] /= condition[" << eqr << "];\n";
                          }
                      }
                    for (i = 0;i < ModelBlock->Block_List[j].Size;i++)
                      output << "  u[" << i << "+Per_u_] /= condition[" << i << "];\n";
sebastien's avatar
sebastien committed
1280
#endif
ferhat's avatar
ferhat committed
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
                    break;
                  default:
                    break;
                  }
              }
      }
    code_file.write(&FENDBLOCK, sizeof(FENDBLOCK));
    code_file.write(&FEND, sizeof(FEND));
    code_file.close();
  }
sebastien's avatar
sebastien committed
1291
1292
1293

void
DynamicModel::writeDynamicMFile(const string &dynamic_basename) const
ferhat's avatar
ferhat committed
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
1309
1310
1311
1312
1313
1314
  {
    string filename = dynamic_basename + ".m";

    ofstream mDynamicModelFile;
    mDynamicModelFile.open(filename.c_str(), ios::out | ios::binary);
    if (!mDynamicModelFile.is_open())
      {
        cerr << "Error: Can't open file " << filename << " for writing" << endl;
        exit(EXIT_FAILURE);
      }
    mDynamicModelFile << "function [residual, g1, g2, g3] = " << dynamic_basename << "(y, x, params, it_)" << endl
    << "%" << endl
    << "% Status : Computes dynamic model for Dynare" << endl
    << "%" << endl
    << "% Warning : this file is generated automatically by Dynare" << endl
    << "%           from model file (.mod)" << endl << endl;

    writeDynamicModel(mDynamicModelFile);

    mDynamicModelFile.close();