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- separated file for the IncidenceMatrix class 

- List of incidence matrix handled with a map instead of a chained list

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@2257 ac1d8469-bf42-47a9-8791-bf33cf982152
issue#70
ferhat 2008-11-14 20:12:59 +00:00
parent a67a20bf66
commit 09ebde2496
5 changed files with 445 additions and 527 deletions
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625
BlockTriangular.cc
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@ -17,7 +17,6 @@
* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
*/
// TODO Apply Block Decomposition to the static model
#include <iostream>
#include <sstream>
@ -31,9 +30,6 @@ using namespace std;
#include "BlockTriangular.hh"
//------------------------------------------------------------------------------
/*BlockTriangular::BlockTriangular(const SymbolTable &symbol_table_arg) :
symbol_table(symbol_table_arg),
normalization(symbol_table_arg)*/
BlockTriangular::BlockTriangular(const SymbolTable &symbol_table_arg) :
symbol_table(symbol_table_arg),
normalization(symbol_table_arg),
@ -45,394 +41,6 @@ BlockTriangular::BlockTriangular(const SymbolTable &symbol_table_arg) :
}
IncidenceMatrix::IncidenceMatrix(const SymbolTable &symbol_table_arg) :
symbol_table(symbol_table_arg)
{
Model_Max_Lead = Model_Max_Lead_Endo = Model_Max_Lead_Exo = 0;
Model_Max_Lag = Model_Max_Lag_Endo = Model_Max_Lag_Exo = 0;
}
//------------------------------------------------------------------------------
//For a lead or a lag build the Incidence Matrix structures
List_IM*
IncidenceMatrix::Build_IM(int lead_lag, SymbolType type)
{
int i;
List_IM* pIM = new List_IM;
if(type==eEndogenous)
{
Last_IM->pNext = pIM;
pIM->IM = (bool*)malloc(symbol_table.endo_nbr * symbol_table.endo_nbr * sizeof(pIM->IM[0]));
for(i = 0;i < symbol_table.endo_nbr*symbol_table.endo_nbr;i++)
pIM->IM[i] = 0;
pIM->lead_lag = lead_lag;
if(lead_lag > 0)
{
if(lead_lag > Model_Max_Lead_Endo)
{
Model_Max_Lead_Endo = lead_lag;
if(lead_lag > Model_Max_Lead)
Model_Max_Lead = lead_lag;
}
}
else
{
if( -lead_lag > Model_Max_Lag_Endo)
{
Model_Max_Lag_Endo = -lead_lag;
if(-lead_lag > Model_Max_Lag)
Model_Max_Lag = -lead_lag;
}
}
pIM->pNext = NULL;
Last_IM = pIM;
}
else
{ //eExogenous
Last_IM_X->pNext = pIM;
pIM->IM = (bool*)malloc(symbol_table.exo_nbr * symbol_table.endo_nbr * sizeof(pIM->IM[0]));
for(i = 0;i < symbol_table.exo_nbr*symbol_table.endo_nbr;i++)
pIM->IM[i] = 0;
pIM->lead_lag = lead_lag;
if(lead_lag > 0)
{
if(lead_lag > Model_Max_Lead_Exo)
{
Model_Max_Lead_Exo = lead_lag;
if(lead_lag > Model_Max_Lead)
Model_Max_Lead = lead_lag;
}
}
else
{
if( -lead_lag > Model_Max_Lag_Exo)
{
Model_Max_Lag_Exo = -lead_lag;
if(-lead_lag > Model_Max_Lag)
Model_Max_Lag = -lead_lag;
}
}
pIM->pNext = NULL;
Last_IM_X = pIM;
}
return (pIM);
}
//------------------------------------------------------------------------------
// initialize all the incidence matrix structures
void
IncidenceMatrix::init_incidence_matrix()
{
int i;
First_IM = new List_IM;
First_IM->IM = (bool*)malloc(symbol_table.endo_nbr * symbol_table.endo_nbr * sizeof(First_IM->IM[0]));
for(i = 0;i < symbol_table.endo_nbr*symbol_table.endo_nbr;i++)
First_IM->IM[i] = 0;
First_IM->lead_lag = 0;
First_IM->pNext = NULL;
Last_IM = First_IM;
First_IM_X = new List_IM;
First_IM_X->IM = (bool*)malloc(symbol_table.exo_nbr * symbol_table.endo_nbr * sizeof(First_IM_X->IM[0]));
for(i = 0;i < symbol_table.endo_nbr*symbol_table.exo_nbr;i++)
First_IM_X->IM[i] = 0;
First_IM_X->lead_lag = 0;
First_IM_X->pNext = NULL;
Last_IM_X = First_IM_X;
}
void
IncidenceMatrix::Free_IM() const
{
List_IM *Cur_IM, *SFirst_IM;
Cur_IM = SFirst_IM = First_IM;
while(Cur_IM)
{
SFirst_IM = Cur_IM->pNext;
free(Cur_IM->IM);
delete Cur_IM;
Cur_IM = SFirst_IM;
}
Cur_IM = SFirst_IM = First_IM_X;
while(Cur_IM)
{
SFirst_IM = Cur_IM->pNext;
free(Cur_IM->IM);
delete Cur_IM;
Cur_IM = SFirst_IM;
}
}
//------------------------------------------------------------------------------
// Return the incidence matrix related to a lead or a lag
List_IM*
IncidenceMatrix::Get_IM(int lead_lag, SymbolType type) const
{
List_IM* Cur_IM;
if(type==eEndogenous)
Cur_IM = First_IM;
else
Cur_IM = First_IM_X;
while ((Cur_IM != NULL) && (Cur_IM->lead_lag != lead_lag))
Cur_IM = Cur_IM->pNext;
return (Cur_IM);
}
bool*
IncidenceMatrix::bGet_IM(int lead_lag, SymbolType type) const
{
List_IM* Cur_IM;
if(type==eEndogenous)
Cur_IM = First_IM;
else
Cur_IM = First_IM_X;
while ((Cur_IM != NULL) && (Cur_IM->lead_lag != lead_lag))
{
Cur_IM = Cur_IM->pNext;
}
if(Cur_IM)
return (Cur_IM->IM);
else
return(0);
}
//------------------------------------------------------------------------------
// Fill the incidence matrix related to a lead or a lag
void
IncidenceMatrix::fill_IM(int equation, int variable, int lead_lag, SymbolType type)
{
List_IM* Cur_IM;
Cur_IM = Get_IM(lead_lag, type);
if(equation >= symbol_table.endo_nbr)
{
cout << "Error : The model has more equations (at least " << equation + 1 << ") than declared endogenous variables (" << symbol_table.endo_nbr << ")\n";
exit(EXIT_FAILURE);
}
if (!Cur_IM)
Cur_IM = Build_IM(lead_lag, type);
if(type==eEndogenous)
Cur_IM->IM[equation*symbol_table.endo_nbr + variable] = 1;
else
Cur_IM->IM[equation*symbol_table.exo_nbr + variable] = 1;
}
//------------------------------------------------------------------------------
// unFill the incidence matrix related to a lead or a lag
void
IncidenceMatrix::unfill_IM(int equation, int variable, int lead_lag, SymbolType type)
{
List_IM* Cur_IM;
Cur_IM = Get_IM(lead_lag, type);
if (!Cur_IM)
Cur_IM = Build_IM(lead_lag, type);
if(type==eEndogenous)
Cur_IM->IM[equation*symbol_table.endo_nbr + variable] = 0;
else
Cur_IM->IM[equation*symbol_table.exo_nbr + variable] = 0;
}
List_IM*
IncidenceMatrix::Get_First(SymbolType type) const
{
if(type==eEndogenous)
return(First_IM);
else
return(First_IM_X);
}
//------------------------------------------------------------------------------
//For a lead or a lag build the Incidence Matrix structures
/*List_IM*
IncidenceMatrix::Build_IM_X(int lead_lag)
{
List_IM* pIM_X = new List_IM;
int i;
Last_IM_X->pNext = pIM_X;
pIM_X->IM = (bool*)malloc(exo_nbr * endo_nbr * sizeof(pIM_X->IM[0]));
for(i = 0;i < exo_nbr*endo_nbr;i++)
pIM_X->IM[i] = 0;
pIM_X->lead_lag = lead_lag;
if(lead_lag > 0)
{
if(lead_lag > Model_Max_Lead_Exo)
{
Model_Max_Lead_Exo = lead_lag;
if(lead_lag > Model_Max_Lead)
Model_Max_Lead = lead_lag;
}
}
else
{
if( -lead_lag > Model_Max_Lag_Exo)
{
Model_Max_Lag_Exo = -lead_lag;
if(-lead_lag > Model_Max_Lag)
Model_Max_Lag = -lead_lag;
}
}
pIM_X->pNext = NULL;
Last_IM_X = pIM_X;
return (pIM_X);
}
//------------------------------------------------------------------------------
// initialize all the incidence matrix structures
void
IncidenceMatrix::init_incidence_matrix_X(int nb_exo)
{
int i;
//cout << "init_incidence_matrix_X nb_exo = " << nb_exo << " endo_nbr=" << endo_nbr << "\n";
exo_nbr = nb_exo;
First_IM_X = new List_IM;
First_IM_X->IM = (bool*)malloc(nb_exo * endo_nbr * sizeof(First_IM_X->IM[0]));
for(i = 0;i < endo_nbr*nb_exo;i++)
First_IM_X->IM[i] = 0;
First_IM_X->lead_lag = 0;
First_IM_X->pNext = NULL;
Last_IM_X = First_IM_X;
}
void
IncidenceMatrix::Free_IM_X(List_IM* First_IM_X) const
{
List_IM *Cur_IM_X, *SFirst_IM_X;
Cur_IM_X = SFirst_IM_X = First_IM_X;
while(Cur_IM_X)
{
First_IM_X = Cur_IM_X->pNext;
free(Cur_IM_X->IM);
delete Cur_IM_X;
Cur_IM_X = First_IM_X;
}
}
//------------------------------------------------------------------------------
// Return the inceidence matrix related to a lead or a lag
List_IM*
IncidenceMatrix::Get_IM_X(int lead_lag)
{
List_IM* Cur_IM_X;
Cur_IM_X = First_IM_X;
while ((Cur_IM_X != NULL) && (Cur_IM_X->lead_lag != lead_lag))
Cur_IM_X = Cur_IM_X->pNext;
return (Cur_IM_X);
}
bool*
IncidenceMatrix::bGet_IM_X(int lead_lag) const
{
List_IM* Cur_IM_X;
Cur_IM_X = First_IM_X;
while ((Cur_IM_X != NULL) && (Cur_IM_X->lead_lag != lead_lag))
{
Cur_IM_X = Cur_IM_X->pNext;
}
if(Cur_IM_X)
return (Cur_IM_X->IM);
else
return(0);
}
//------------------------------------------------------------------------------
// Fill the incidence matrix related to a lead or a lag
void
IncidenceMatrix::fill_IM_X(int equation, int variable_exo, int lead_lag)
{
List_IM* Cur_IM_X;
Cur_IM_X = Get_IM_X(lead_lag);
if(equation >= endo_nbr)
{
cout << "Error : The model has more equations (at least " << equation + 1 << ") than declared endogenous variables (" << endo_nbr << ")\n";
exit(EXIT_FAILURE);
}
if (!Cur_IM_X)
{
Cur_IM_X = Build_IM_X(lead_lag);
}
Cur_IM_X->IM[equation*exo_nbr + variable_exo] = true;
}
*/
//------------------------------------------------------------------------------
//Print azn incidence matrix
void
IncidenceMatrix::Print_SIM(bool* IM, SymbolType type) const
{
int i, j, n;
if(type == eEndogenous)
n = symbol_table.endo_nbr;
else
n = symbol_table.exo_nbr;
for(i = 0;i < symbol_table.endo_nbr;i++)
{
cout << " ";
for(j = 0;j < n;j++)
cout << IM[i*n + j] << " ";
cout << "\n";
}
}
//------------------------------------------------------------------------------
//Print all incidence matrix
void
IncidenceMatrix::Print_IM(SymbolType type) const
{
List_IM* Cur_IM;
if(type == eEndogenous)
Cur_IM = First_IM;
else
Cur_IM = First_IM_X;
cout << "-------------------------------------------------------------------\n";
while(Cur_IM)
{
cout << "Incidence matrix for lead_lag = " << Cur_IM->lead_lag << "\n";
Print_SIM(Cur_IM->IM, type);
Cur_IM = Cur_IM->pNext;
}
}
//------------------------------------------------------------------------------
// Swap rows and columns of the incidence matrix
void
IncidenceMatrix::swap_IM_c(bool *SIM, int pos1, int pos2, int pos3, simple* Index_Var_IM, simple* Index_Equ_IM, int n) const
{
int tmp_i, j;
bool tmp_b;
/* We exchange equation (row)...*/
if(pos1 != pos2)
{
tmp_i = Index_Equ_IM[pos1].index;
Index_Equ_IM[pos1].index = Index_Equ_IM[pos2].index;
Index_Equ_IM[pos2].index = tmp_i;
for(j = 0;j < n;j++)
{
tmp_b = SIM[pos1 * n + j];
SIM[pos1*n + j] = SIM[pos2 * n + j];
SIM[pos2*n + j] = tmp_b;
}
}
/* ...and variables (column)*/
if(pos1 != pos3)
{
tmp_i = Index_Var_IM[pos1].index;
Index_Var_IM[pos1].index = Index_Var_IM[pos3].index;
Index_Var_IM[pos3].index = tmp_i;
for(j = 0;j < n;j++)
{
tmp_b = SIM[j * n + pos1];
SIM[j*n + pos1] = SIM[j * n + pos3];
SIM[j*n + pos3] = tmp_b;
}
}
}
//------------------------------------------------------------------------------
// Find the prologue and the epilogue of the model
@ -497,7 +105,7 @@ BlockTriangular::Allocate_Block(int size, int *count_Equ, int *count_Block, Bloc
{
int i, j, k, l, ls, m, i_1, Lead, Lag, first_count_equ, i1;
int *tmp_size, *tmp_size_exo, *tmp_var, *tmp_endo, *tmp_exo, tmp_nb_exo, nb_lead_lag_endo;
List_IM *Cur_IM;
bool *Cur_IM;
bool *IM, OK;
ModelBlock->Periods = periods;
int Lag_Endo, Lead_Endo, Lag_Exo, Lead_Exo;
@ -520,7 +128,39 @@ BlockTriangular::Allocate_Block(int size, int *count_Equ, int *count_Block, Bloc
memset(tmp_endo, 0, (incidencematrix.Model_Max_Lead + incidencematrix.Model_Max_Lag + 1)*sizeof(int));
nb_lead_lag_endo = Lead = Lag = 0;
Lag_Endo = Lead_Endo = Lag_Exo = Lead_Exo = 0;
Cur_IM = incidencematrix.Get_First(eEndogenous);
for(k = -incidencematrix.Model_Max_Lag_Endo; k<=incidencematrix.Model_Max_Lead_Endo; k++)
{
Cur_IM = incidencematrix.Get_IM(k, eEndogenous);
if(Cur_IM)
{
i_1 = Index_Equ_IM[*count_Equ].index * symbol_table.endo_nbr;
if(k > 0)
{
if(Cur_IM[i_1 + Index_Var_IM[*count_Equ].index])
{
nb_lead_lag_endo++;
tmp_size[incidencematrix.Model_Max_Lag_Endo + k]++;
if(k > Lead)
Lead = k;
}
}
else
{
k = -k;
if(Cur_IM[i_1 + Index_Var_IM[*count_Equ].index])
{
tmp_size[incidencematrix.Model_Max_Lag_Endo - k]++;
nb_lead_lag_endo++;
if(k > Lag)
Lag = k;
}
}
}
}
/*Cur_IM = incidencematrix.Get_First(eEndogenous);
while(Cur_IM)
{
k = Cur_IM->lead_lag;
@ -547,7 +187,7 @@ BlockTriangular::Allocate_Block(int size, int *count_Equ, int *count_Block, Bloc
}
}
Cur_IM = Cur_IM->pNext;
}
}*/
Lag_Endo = Lag;
Lead_Endo = Lead;
@ -556,35 +196,37 @@ BlockTriangular::Allocate_Block(int size, int *count_Equ, int *count_Block, Bloc
tmp_nb_exo = 0;
Cur_IM = incidencematrix.Get_First(eExogenous);
/*Cur_IM = incidencematrix.Get_First(eExogenous);
k = Cur_IM->lead_lag;
while(Cur_IM)
{*/
for(k = -incidencematrix.Model_Max_Lag_Exo; k<=incidencematrix.Model_Max_Lead_Exo; k++)
{
i_1 = Index_Equ_IM[*count_Equ].index * symbol_table.exo_nbr;
for(j=0;j<symbol_table.exo_nbr;j++)
if(Cur_IM->IM[i_1 + j])
{
if(!tmp_exo[j])
Cur_IM = incidencematrix.Get_IM(k, eExogenous);
if(Cur_IM)
{
i_1 = Index_Equ_IM[*count_Equ].index * symbol_table.exo_nbr;
for(j=0;j<symbol_table.exo_nbr;j++)
if(Cur_IM[i_1 + j])
{
tmp_exo[j] = 1;
tmp_nb_exo++;
if(!tmp_exo[j])
{
tmp_exo[j] = 1;
tmp_nb_exo++;
}
if(k>0 && k>Lead_Exo)
Lead_Exo = k;
else if(k<0 && (-k)>Lag_Exo)
Lag_Exo = -k;
if(k>0 && k>Lead)
Lead = k;
else if(k<0 && (-k)>Lag)
Lag = -k;
tmp_size_exo[k+incidencematrix.Model_Max_Lag_Exo]++;
}
if(k>0 && k>Lead_Exo)
Lead_Exo = k;
else if(k<0 && (-k)>Lag_Exo)
Lag_Exo = -k;
if(k>0 && k>Lead)
Lead = k;
else if(k<0 && (-k)>Lag)
Lag = -k;
tmp_size_exo[k+incidencematrix.Model_Max_Lag_Exo]++;
}
Cur_IM = Cur_IM->pNext;
if(Cur_IM)
k = Cur_IM->lead_lag;
}
}
ModelBlock->Block_List[*count_Block].nb_exo = tmp_nb_exo;
ModelBlock->Block_List[*count_Block].Exogenous = (int*)malloc(tmp_nb_exo * sizeof(int));
k = 0;
@ -615,20 +257,23 @@ BlockTriangular::Allocate_Block(int size, int *count_Equ, int *count_Block, Bloc
else
ModelBlock->Block_List[*count_Block].Simulation_Type = SOLVE_FORWARD_SIMPLE;
Cur_IM = incidencematrix.Get_First(eExogenous);
//Cur_IM = incidencematrix.Get_First(eExogenous);
tmp_exo = (int*)malloc(symbol_table.exo_nbr * sizeof(int));
memset(tmp_exo, 0, symbol_table.exo_nbr * sizeof(int));
tmp_nb_exo = 0;
while(Cur_IM)
/*while(Cur_IM)
{*/
for(k = -incidencematrix.Model_Max_Lag_Exo; k <=incidencematrix.Model_Max_Lead_Exo; k++)
{
Cur_IM = incidencematrix.Get_IM(k, eExogenous);
i_1 = Index_Equ_IM[*count_Equ].index * symbol_table.exo_nbr;
for(j=0;j<symbol_table.exo_nbr;j++)
if(Cur_IM->IM[i_1 + j] && (!tmp_exo[j]))
if(Cur_IM[i_1 + j] && (!tmp_exo[j]))
{
tmp_exo[j] = 1;
tmp_nb_exo++;
}
Cur_IM = Cur_IM->pNext;
//Cur_IM = Cur_IM->pNext;
}
ModelBlock->Block_List[*count_Block].nb_exo = tmp_nb_exo;
ModelBlock->Block_List[*count_Block].Exogenous = (int*)malloc(tmp_nb_exo * sizeof(int));
@ -661,7 +306,7 @@ BlockTriangular::Allocate_Block(int size, int *count_Equ, int *count_Block, Bloc
ModelBlock->Block_List[*count_Block].IM_lead_lag[li].Equ_Index = (int*)malloc(tmp_size[incidencematrix.Model_Max_Lag_Endo - Lag + li] * sizeof(int));
ModelBlock->Block_List[*count_Block].IM_lead_lag[li].u_init = l;
IM = incidencematrix.bGet_IM(li - Lag, eEndogenous);
IM = incidencematrix.Get_IM(li - Lag, eEndogenous);
if(IM)
{
if(IM[Index_Var_IM[*count_Equ].index + Index_Equ_IM[*count_Equ].index*symbol_table.endo_nbr] && nb_lead_lag_endo)
@ -699,7 +344,7 @@ BlockTriangular::Allocate_Block(int size, int *count_Equ, int *count_Block, Bloc
ModelBlock->Block_List[*count_Block].IM_lead_lag[li].Exogenous_Index = (int*)malloc(tmp_size_exo[incidencematrix.Model_Max_Lag_Exo - Lag + li] * sizeof(int));
ModelBlock->Block_List[*count_Block].IM_lead_lag[li].Equ_X = (int*)malloc(tmp_size_exo[incidencematrix.Model_Max_Lag_Exo - Lag + li] * sizeof(int));
ModelBlock->Block_List[*count_Block].IM_lead_lag[li].Equ_X_Index = (int*)malloc(tmp_size_exo[incidencematrix.Model_Max_Lag_Exo - Lag + li] * sizeof(int));
IM = incidencematrix.bGet_IM(li - Lag, eExogenous);
IM = incidencematrix.Get_IM(li - Lag, eExogenous);
if(IM)
{
m = 0;
@ -757,50 +402,54 @@ BlockTriangular::Allocate_Block(int size, int *count_Equ, int *count_Block, Bloc
{
ModelBlock->Block_List[*count_Block].Equation[i] = Index_Equ_IM[*count_Equ].index;
ModelBlock->Block_List[*count_Block].Variable[i] = Index_Var_IM[*count_Equ].index;
Cur_IM = incidencematrix.Get_First(eEndogenous);
//Cur_IM = incidencematrix.Get_First(eEndogenous);
i_1 = Index_Var_IM[*count_Equ].index;
while(Cur_IM)
//while(Cur_IM)
for(k = -incidencematrix.Model_Max_Lag_Endo; k<=incidencematrix.Model_Max_Lead_Endo; k++)
{
k = Cur_IM->lead_lag;
OK = false;
if(k >= 0)
//k = Cur_IM->lead_lag;
Cur_IM = incidencematrix.Get_IM(k, eEndogenous);
if(Cur_IM)
{
for(j = 0;j < size;j++)
OK = false;
if(k >= 0)
{
if(Cur_IM->IM[i_1 + Index_Equ_IM[first_count_equ + j].index*symbol_table.endo_nbr])
for(j = 0;j < size;j++)
{
tmp_size[incidencematrix.Model_Max_Lag_Endo + k]++;
if (!OK)
if(Cur_IM[i_1 + Index_Equ_IM[first_count_equ + j].index*symbol_table.endo_nbr])
{
tmp_endo[incidencematrix.Model_Max_Lag + k]++;
nb_lead_lag_endo++;
OK = true;
tmp_size[incidencematrix.Model_Max_Lag_Endo + k]++;
if (!OK)
{
tmp_endo[incidencematrix.Model_Max_Lag + k]++;
nb_lead_lag_endo++;
OK = true;
}
if(k > Lead)
Lead = k;
}
if(k > Lead)
Lead = k;
}
}
}
else
{
k = -k;
for(j = 0;j < size;j++)
else
{
if(Cur_IM->IM[i_1 + Index_Equ_IM[first_count_equ + j].index*symbol_table.endo_nbr])
k = -k;
for(j = 0;j < size;j++)
{
tmp_size[incidencematrix.Model_Max_Lag_Endo - k]++;
if (!OK)
if(Cur_IM[i_1 + Index_Equ_IM[first_count_equ + j].index*symbol_table.endo_nbr])
{
tmp_endo[incidencematrix.Model_Max_Lag - k]++;
nb_lead_lag_endo++;
OK = true;
tmp_size[incidencematrix.Model_Max_Lag_Endo - k]++;
if (!OK)
{
tmp_endo[incidencematrix.Model_Max_Lag - k]++;
nb_lead_lag_endo++;
OK = true;
}
if(k > Lag)
Lag = k;
}
if(k > Lag)
Lag = k;
}
}
}
Cur_IM = Cur_IM->pNext;
}
}
(*count_Equ)++;
}
@ -829,32 +478,34 @@ BlockTriangular::Allocate_Block(int size, int *count_Equ, int *count_Block, Bloc
tmp_nb_exo = 0;
for(i = 0;i < size;i++)
{
Cur_IM = incidencematrix.Get_First(eExogenous);
k = Cur_IM->lead_lag;
while(Cur_IM)
//Cur_IM = incidencematrix.Get_First(eExogenous);
//k = Cur_IM->lead_lag;
//while(Cur_IM)
for(k = -incidencematrix.Model_Max_Lag_Exo; k<=incidencematrix.Model_Max_Lead_Exo; k++)
{
i_1 = Index_Equ_IM[first_count_equ+i].index * symbol_table.exo_nbr;
for(j=0;j<symbol_table.exo_nbr;j++)
if(Cur_IM->IM[i_1 + j])
{
if(!tmp_exo[j])
Cur_IM = incidencematrix.Get_IM(k, eExogenous);
if(Cur_IM)
{
i_1 = Index_Equ_IM[first_count_equ+i].index * symbol_table.exo_nbr;
for(j=0;j<symbol_table.exo_nbr;j++)
if(Cur_IM[i_1 + j])
{
tmp_exo[j] = 1;
tmp_nb_exo++;
if(!tmp_exo[j])
{
tmp_exo[j] = 1;
tmp_nb_exo++;
}
if(k>0 && k>Lead_Exo)
Lead_Exo = k;
else if(k<0 && (-k)>Lag_Exo)
Lag_Exo = -k;
if(k>0 && k>Lead)
Lead = k;
else if(k<0 && (-k)>Lag)
Lag = -k;
tmp_size_exo[k+incidencematrix.Model_Max_Lag_Exo]++;
}
if(k>0 && k>Lead_Exo)
Lead_Exo = k;
else if(k<0 && (-k)>Lag_Exo)
Lag_Exo = -k;
if(k>0 && k>Lead)
Lead = k;
else if(k<0 && (-k)>Lag)
Lag = -k;
tmp_size_exo[k+incidencematrix.Model_Max_Lag_Exo]++;
}
Cur_IM = Cur_IM->pNext;
if(Cur_IM)
k = Cur_IM->lead_lag;
}
}
}
@ -907,7 +558,7 @@ BlockTriangular::Allocate_Block(int size, int *count_Equ, int *count_Block, Bloc
else
ModelBlock->Block_List[*count_Block].IM_lead_lag[i].size_exo = 0;
ModelBlock->Block_List[*count_Block].IM_lead_lag[i].u_init = l;
IM = incidencematrix.bGet_IM(i - Lag, eEndogenous);
IM = incidencematrix.Get_IM(i - Lag, eEndogenous);
if(IM)
{
for(j = first_count_equ;j < size + first_count_equ;j++)
@ -946,7 +597,7 @@ BlockTriangular::Allocate_Block(int size, int *count_Equ, int *count_Block, Bloc
}
ModelBlock->Block_List[*count_Block].IM_lead_lag[i].u_finish = l - 1;
}
IM = incidencematrix.bGet_IM(i - Lag, eExogenous);
IM = incidencematrix.Get_IM(i - Lag, eExogenous);
if(IM)
{
m = 0;
@ -1204,18 +855,18 @@ void
BlockTriangular::Normalize_and_BlockDecompose_Static_0_Model(const jacob_map &j_m)
{
bool* SIM, *SIM_0;
List_IM* Cur_IM;
int i;
bool* Cur_IM;
int i, k, size;
//First create a static model incidence matrix
SIM = (bool*)malloc(symbol_table.endo_nbr * symbol_table.endo_nbr * sizeof(*SIM));
for(i = 0;i < symbol_table.endo_nbr*symbol_table.endo_nbr;i++)
size = symbol_table.endo_nbr * symbol_table.endo_nbr * sizeof(*SIM);
SIM = (bool*)malloc(size);
memset(SIM, size, 0);
for(k = -incidencematrix.Model_Max_Lag_Endo; k<=incidencematrix.Model_Max_Lead_Endo; k++)
{
SIM[i] = 0;
Cur_IM = incidencematrix.Get_First(eEndogenous);
while(Cur_IM)
Cur_IM = incidencematrix.Get_IM(k, eEndogenous);
for(i = 0;i < symbol_table.endo_nbr*symbol_table.endo_nbr;i++)
{
SIM[i] = (SIM[i]) || (Cur_IM->IM[i]);
Cur_IM = Cur_IM->pNext;
SIM[i] = (SIM[i]) || (Cur_IM[i]);
}
}
if(bt_verbose)
@ -1239,7 +890,7 @@ BlockTriangular::Normalize_and_BlockDecompose_Static_0_Model(const jacob_map &j_
Cur_IM = incidencematrix.Get_IM(0, eEndogenous);
SIM_0 = (bool*)malloc(symbol_table.endo_nbr * symbol_table.endo_nbr * sizeof(*SIM_0));
for(i = 0;i < symbol_table.endo_nbr*symbol_table.endo_nbr;i++)
SIM_0[i] = Cur_IM->IM[i];
SIM_0[i] = Cur_IM[i];
Normalize_and_BlockDecompose(SIM, ModelBlock, symbol_table.endo_nbr, &prologue, &epilogue, Index_Var_IM, Index_Equ_IM, 1, 1, SIM_0, j_m);
free(SIM_0);
free(SIM);

242
InidenceMatrix.cc Normal file
View File

@ -0,0 +1,242 @@
/*
* Copyright (C) 2007-2008 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 "IncidenceMatrix.hh"
IncidenceMatrix::IncidenceMatrix(const SymbolTable &symbol_table_arg) :
symbol_table(symbol_table_arg)
{
Model_Max_Lead = Model_Max_Lead_Endo = Model_Max_Lead_Exo = 0;
Model_Max_Lag = Model_Max_Lag_Endo = Model_Max_Lag_Exo = 0;
}
//------------------------------------------------------------------------------
//For a lead or a lag build the Incidence Matrix structures
bool*
IncidenceMatrix::Build_IM(int lead_lag, SymbolType type)
{
int size;
bool *IM;
if(type==eEndogenous)
{
size = symbol_table.endo_nbr * symbol_table.endo_nbr * sizeof(IM[0]);
List_IM[lead_lag] = IM = (bool*)malloc(size);
memset(IM, size, NULL);
if(lead_lag > 0)
{
if(lead_lag > Model_Max_Lead_Endo)
{
Model_Max_Lead_Endo = lead_lag;
if(lead_lag > Model_Max_Lead)
Model_Max_Lead = lead_lag;
}
}
else
{
if( -lead_lag > Model_Max_Lag_Endo)
{
Model_Max_Lag_Endo = -lead_lag;
if(-lead_lag > Model_Max_Lag)
Model_Max_Lag = -lead_lag;
}
}
}
else
{ //eExogenous
size = symbol_table.endo_nbr * symbol_table.exo_nbr * sizeof(IM[0]);
List_IM_X[lead_lag] = IM = (bool*)malloc(size);
memset(IM, size, NULL);
if(lead_lag > 0)
{
if(lead_lag > Model_Max_Lead_Exo)
{
Model_Max_Lead_Exo = lead_lag;
if(lead_lag > Model_Max_Lead)
Model_Max_Lead = lead_lag;
}
}
else
{
if( -lead_lag > Model_Max_Lag_Exo)
{
Model_Max_Lag_Exo = -lead_lag;
if(-lead_lag > Model_Max_Lag)
Model_Max_Lag = -lead_lag;
}
}
}
return (IM);
}
void
IncidenceMatrix::Free_IM() const
{
IncidenceList::const_iterator it = List_IM.begin();
for(it = List_IM.begin(); it != List_IM.end(); it++)
free(it->second);
for(it = List_IM_X.begin(); it != List_IM_X.end(); it++)
free(it->second);
}
//------------------------------------------------------------------------------
// Return the incidence matrix related to a lead or a lag
bool*
IncidenceMatrix::Get_IM(int lead_lag, SymbolType type) const
{
IncidenceList::const_iterator it;
if(type==eEndogenous)
{
it = List_IM.find(lead_lag);
if(it!=List_IM.end())
return(it->second);
else
return(NULL);
}
else //eExogenous
{
it = List_IM_X.find(lead_lag);
if(it!=List_IM_X.end())
return(it->second);
else
return(NULL);
}
}
//------------------------------------------------------------------------------
// Fill the incidence matrix related to a lead or a lag
void
IncidenceMatrix::fill_IM(int equation, int variable, int lead_lag, SymbolType type)
{
bool* Cur_IM;
Cur_IM = Get_IM(lead_lag, type);
if(equation >= symbol_table.endo_nbr)
{
cout << "Error : The model has more equations (at least " << equation + 1 << ") than declared endogenous variables (" << symbol_table.endo_nbr << ")\n";
exit(EXIT_FAILURE);
}
if (!Cur_IM)
Cur_IM = Build_IM(lead_lag, type);
if(type==eEndogenous)
Cur_IM[equation*symbol_table.endo_nbr + variable] = 1;
else
Cur_IM[equation*symbol_table.exo_nbr + variable] = 1;
}
//------------------------------------------------------------------------------
// unFill the incidence matrix related to a lead or a lag
void
IncidenceMatrix::unfill_IM(int equation, int variable, int lead_lag, SymbolType type)
{
bool* Cur_IM;
Cur_IM = Get_IM(lead_lag, type);
if (!Cur_IM)
Cur_IM = Build_IM(lead_lag, type);
if(type==eEndogenous)
Cur_IM[equation*symbol_table.endo_nbr + variable] = 0;
else
Cur_IM[equation*symbol_table.exo_nbr + variable] = 0;
}
//------------------------------------------------------------------------------
//Print azn incidence matrix
void
IncidenceMatrix::Print_SIM(bool* IM, SymbolType type) const
{
int i, j, n;
if(type == eEndogenous)
n = symbol_table.endo_nbr;
else
n = symbol_table.exo_nbr;
for(i = 0;i < symbol_table.endo_nbr;i++)
{
cout << " ";
for(j = 0;j < n;j++)
cout << IM[i*n + j] << " ";
cout << "\n";
}
}
//------------------------------------------------------------------------------
//Print all incidence matrix
void
IncidenceMatrix::Print_IM(SymbolType type) const
{
IncidenceList::const_iterator it;
cout << "-------------------------------------------------------------------\n";
if(type == eEndogenous)
for(int k=-Model_Max_Lag_Endo; k <= Model_Max_Lead_Endo; k++)
{
it = List_IM.find(k);
if(it!=List_IM.end())
{
cout << "Incidence matrix for lead_lag = " << k << "\n";
Print_SIM(it->second, type);
}
}
else // eExogenous
for(int k=-Model_Max_Lag_Exo; k <= Model_Max_Lead_Exo; k++)
{
it = List_IM_X.find(k);
if(it!=List_IM_X.end())
{
cout << "Incidence matrix for lead_lag = " << k << "\n";
Print_SIM(it->second, type);
}
}
}
//------------------------------------------------------------------------------
// Swap rows and columns of the incidence matrix
void
IncidenceMatrix::swap_IM_c(bool *SIM, int pos1, int pos2, int pos3, simple* Index_Var_IM, simple* Index_Equ_IM, int n) const
{
int tmp_i, j;
bool tmp_b;
/* We exchange equation (row)...*/
if(pos1 != pos2)
{
tmp_i = Index_Equ_IM[pos1].index;
Index_Equ_IM[pos1].index = Index_Equ_IM[pos2].index;
Index_Equ_IM[pos2].index = tmp_i;
for(j = 0;j < n;j++)
{
tmp_b = SIM[pos1 * n + j];
SIM[pos1*n + j] = SIM[pos2 * n + j];
SIM[pos2*n + j] = tmp_b;
}
}
/* ...and variables (column)*/
if(pos1 != pos3)
{
tmp_i = Index_Var_IM[pos1].index;
Index_Var_IM[pos1].index = Index_Var_IM[pos3].index;
Index_Var_IM[pos3].index = tmp_i;
for(j = 0;j < n;j++)
{
tmp_b = SIM[j * n + pos1];
SIM[j*n + pos1] = SIM[j * n + pos3];
SIM[j*n + pos3] = tmp_b;
}
}
}

11
ModelTree.cc
View File

@ -879,7 +879,7 @@ ModelTree::writeModelStaticEquationsOrdered_M(ostream &output, Model_Block *Mode
memset(IM, 0, n*n*sizeof(bool));
for(m=-ModelBlock->Block_List[j].Max_Lag;m<=ModelBlock->Block_List[j].Max_Lead;m++)
{
IMl=block_triangular.incidencematrix.bGet_IM(m, eEndogenous);
IMl=block_triangular.incidencematrix.Get_IM(m, eEndogenous);
if(IMl)
{
for(i=0;i<n;i++)
@ -2976,7 +2976,7 @@ ModelTree::writeOutput(ostream &output) const
for(int l=-max_lag_endo;l<max_lead_endo+1;l++)
{
bool *tmp_IM;
tmp_IM=block_triangular.incidencematrix.bGet_IM(l, eEndogenous);
tmp_IM=block_triangular.incidencematrix.Get_IM(l, eEndogenous);
if(tmp_IM)
{
for(int l_var=0;l_var<block_triangular.ModelBlock->Block_List[j].Size;l_var++)
@ -3008,7 +3008,7 @@ ModelTree::writeOutput(ostream &output) const
{
bool not_increm=true;
bool *tmp_IM;
tmp_IM=block_triangular.incidencematrix.bGet_IM(l, eEndogenous);
tmp_IM=block_triangular.incidencematrix.Get_IM(l, eEndogenous);
int ii=j;
if(tmp_IM)
{
@ -3051,7 +3051,7 @@ ModelTree::writeOutput(ostream &output) const
}
for(int j=-block_triangular.incidencematrix.Model_Max_Lag_Endo;j<=block_triangular.incidencematrix.Model_Max_Lead_Endo;j++)
{
bool* IM = block_triangular.incidencematrix.bGet_IM(j, eEndogenous);
bool* IM = block_triangular.incidencematrix.Get_IM(j, eEndogenous);
if(IM)
{
bool new_entry=true;
@ -3140,7 +3140,7 @@ ModelTree::evaluateJacobian(const eval_context_type &eval_context, jacob_map *j_
int k1=variable_table.getLag(it->first.second);
if (a_variable_lag!=k1)
{
IM=block_triangular.incidencematrix.bGet_IM(k1, eEndogenous);
IM=block_triangular.incidencematrix.Get_IM(k1, eEndogenous);
a_variable_lag=k1;
}
if (k1==0)
@ -3253,7 +3253,6 @@ ModelTree::computingPass(const eval_context_type &eval_context, bool no_tmp_term
if (mode == eSparseDLLMode || mode == eSparseMode)
{
block_triangular.incidencematrix.init_incidence_matrix();
BuildIncidenceMatrix();
jacob_map j_m;

37
include/BlockTriangular.hh
View File

@ -25,43 +25,12 @@
#include "SymbolTable.hh"
#include "ModelNormalization.hh"
#include "ModelBlocks.hh"
#include "ExprNode.hh"
//! List of incidence matrix (one matrix per lead/lag)
struct List_IM
{
List_IM* pNext;
int lead_lag;
bool* IM;
};
#include "IncidenceMatrix.hh"
//! create and manage the incidence matrix
class IncidenceMatrix //: SymbolTable
{
//friend class BlockTriangular;
public:
const SymbolTable &symbol_table;
IncidenceMatrix(const SymbolTable &symbol_table_arg);
List_IM* Build_IM(int lead_lag, SymbolType type);
List_IM* Get_IM(int lead_lag, SymbolType type) const;
bool* bGet_IM(int lead_lag, SymbolType type) const;
void fill_IM(int equation, int variable_endo, int lead_lag, SymbolType type);
void unfill_IM(int equation, int variable_endo, int lead_lag, SymbolType type);
void init_incidence_matrix();
void Free_IM() const;
List_IM* Get_First(SymbolType type) const;
void Print_IM(SymbolType type) const;
void Print_SIM(bool* IM, SymbolType type) const;
void swap_IM_c(bool *SIM, int pos1, int pos2, int pos3, simple* Index_Var_IM, simple* Index_Equ_IM, int n) const;
private:
List_IM *First_IM, *Last_IM, *First_IM_X, *Last_IM_X ;
public:
int Model_Max_Lead, Model_Max_Lag;
int Model_Max_Lead_Endo, Model_Max_Lag_Endo, Model_Max_Lead_Exo, Model_Max_Lag_Exo;
};
//! Matrix of doubles for representing jacobian

57
include/IncidenceMatrix.hh Normal file
View File

@ -0,0 +1,57 @@
/*
* Copyright (C) 2007-2008 Dynare Team
*
* This file is part of Dynare.
*
* Dynare is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* Dynare is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef _INCIDENCEMATRIX_HH
#define _INCIDENCEMATRIX_HH
#include <map>
#include "ExprNode.hh"
#include "SymbolTable.hh"
#include "ModelNormalization.hh"
//! List of incidence matrix (one matrix per lead/lag)
typedef bool* pbool;
typedef map<int,pbool> IncidenceList;
//! create and manage the incidence matrix
class IncidenceMatrix
{
public:
const SymbolTable &symbol_table;
IncidenceMatrix(const SymbolTable &symbol_table_arg);
bool* Build_IM(int lead_lag, SymbolType type);
bool* Get_IM(int lead_lag, SymbolType type) const;
void fill_IM(int equation, int variable_endo, int lead_lag, SymbolType type);
void unfill_IM(int equation, int variable_endo, int lead_lag, SymbolType type);
void Free_IM() const;
void Print_IM(SymbolType type) const;
void Print_SIM(bool* IM, SymbolType type) const;
void swap_IM_c(bool *SIM, int pos1, int pos2, int pos3, simple* Index_Var_IM, simple* Index_Equ_IM, int n) const;
int Model_Max_Lead, Model_Max_Lag;
int Model_Max_Lead_Endo, Model_Max_Lag_Endo, Model_Max_Lead_Exo, Model_Max_Lag_Exo;
private:
IncidenceList List_IM, List_IM_X;
};
#endif