Merge remote-tracking branch 'ferhat/master'

time-shift
Sébastien Villemot 2012-06-06 17:09:27 +02:00
commit 0caaeddb46
7 changed files with 162 additions and 45 deletions

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@ -2667,6 +2667,7 @@ command.
@end defvr
@deffn Command model_info ;
@deffnx Command model_info (@var{OPTIONS}@dots{});
@descriptionhead
@ -2731,6 +2732,22 @@ to @samp{SIMPLE} if the block has only one equation. If several
equation appears in the block, @var{x} is equal to @samp{COMPLETE}.
@end table
@optionshead
@table @code
@item 'static'
Prints out the block decomposition of the static model.
Without 'static' option model_info displays the block decomposition
of the dynamic model.
@item 'incidence'
Displays the gross incidence matrix and the reordered incidence matrix
of the block decomposed model.
@end table
@end deffn
@deffn Command print_bytecode_dynamic_model ;

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@ -131,9 +131,14 @@ Uyy = reshape(Uyy,endo_nbr,endo_nbr);
% set multipliers and auxiliary variables that
% depends on multipliers to 0 to compute residuals
[res,fJ] = feval([fname '_static'],xx,[oo.exo_simul oo.exo_det_simul], ...
if (options_.bytecode)
[chck, res, junk] = bytecode('static',xx,[oo.exo_simul oo.exo_det_simul], ...
M.params, 'evaluate');
fJ = junk.g1;
else
[res,fJ] = feval([fname '_static'],xx,[oo.exo_simul oo.exo_det_simul], ...
M.params);
end
% index of multipliers and corresponding equations
% the auxiliary variables before the Lagrange multipliers are treated
% as ordinary endogenous variables

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@ -19,39 +19,53 @@ function model_info(varargin);
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
global M_;
fprintf(' Informations about %s\n',M_.fname);
if sum(strcmp(varargin,'static')) > 0
static = 1;
else
static = 0;
end;
if sum(strcmp(varargin,'incidence')) > 0
incidence = 1;
else
incidence = 0;
end;
if static
fprintf(' Informations about %s (static model)\n',M_.fname);
block_structre_str = 'block_structure_stat';
block_structure = M_.block_structure_stat;
nb_leadlag = 1;
else
fprintf(' Informations about %s (dynamic model)\n',M_.fname);
block_structre_str = 'block_structure';
block_structure = M_.block_structure;
nb_leadlag = 3;
end;
fprintf(strcat(' ===================',char(ones(1,length(M_.fname))*'='),'\n\n'));
if(isfield(M_,'block_structure'))
nb_blocks=length(M_.block_structure.block);
if(isfield(M_,block_structre_str))
nb_blocks=length(block_structure.block);
fprintf('The model has %d equations and is decomposed in %d blocks as follow:\n',M_.endo_nbr,nb_blocks);
fprintf('===============================================================================================================\n');
fprintf('| %10s | %10s | %30s | %14s | %31s |\n','Block no','Size','Block Type',' Equation','Dependent variable');
fprintf('|============|============|================================|================|=================================|\n');
for i=1:nb_blocks
size_block=length(M_.block_structure.block(i).equation);
size_block=length(block_structure.block(i).equation);
if(i>1)
fprintf('|------------|------------|--------------------------------|----------------|---------------------------------|\n');
end;
for j=1:size_block
if(j==1)
fprintf('| %10d | %10d | %30s | %14d | %-6d %24s |\n',i,size_block,Sym_type(M_.block_structure.block(i).Simulation_Type),M_.block_structure.block(i).equation(j),M_.block_structure.block(i).variable(j),M_.endo_names(M_.block_structure.block(i).variable(j),:));
fprintf('| %10d | %10d | %30s | %14d | %-6d %24s |\n',i,size_block,Sym_type(block_structure.block(i).Simulation_Type),block_structure.block(i).equation(j),block_structure.block(i).variable(j),M_.endo_names(block_structure.block(i).variable(j),:));
else
fprintf('| %10s | %10s | %30s | %14d | %-6d %24s |\n','','','',M_.block_structure.block(i).equation(j),M_.block_structure.block(i).variable(j),M_.endo_names(M_.block_structure.block(i).variable(j),:));
fprintf('| %10s | %10s | %30s | %14d | %-6d %24s |\n','','','',block_structure.block(i).equation(j),block_structure.block(i).variable(j),M_.endo_names(block_structure.block(i).variable(j),:));
end;
end;
end;
fprintf('===============================================================================================================\n');
fprintf('\n');
for k=1:M_.maximum_endo_lag+M_.maximum_endo_lead+1
if(k==M_.maximum_endo_lag+1)
fprintf('%-30s %s','the variable','is used in equations Contemporaneously');
elseif(k<M_.maximum_endo_lag+1)
fprintf('%-30s %s %d','the variable','is used in equations with lag ',M_.maximum_endo_lag+1-k);
else
fprintf('%-30s %s %d','the variable','is used in equations with lead ',k-(M_.maximum_endo_lag+1));
end;
if(size(M_.block_structure.incidence(k).sparse_IM,1)>0)
IM=sortrows(M_.block_structure.incidence(k).sparse_IM,2);
if static
fprintf('%-30s %s','the variable','is used in equations Contemporaneously');
if(size(block_structure.incidence.sparse_IM,1)>0)
IM=sortrows(block_structure.incidence.sparse_IM,2);
else
IM=[];
end;
@ -65,17 +79,42 @@ if(isfield(M_,'block_structure'))
last=IM(i,2);
end;
fprintf('\n\n');
else
for k=1:M_.maximum_endo_lag+M_.maximum_endo_lead+1
if(k==M_.maximum_endo_lag+1)
fprintf('%-30s %s','the variable','is used in equations Contemporaneously');
elseif(k<M_.maximum_endo_lag+1)
fprintf('%-30s %s %d','the variable','is used in equations with lag ',M_.maximum_endo_lag+1-k);
else
fprintf('%-30s %s %d','the variable','is used in equations with lead ',k-(M_.maximum_endo_lag+1));
end;
if(size(block_structure.incidence(k).sparse_IM,1)>0)
IM=sortrows(block_structure.incidence(k).sparse_IM,2);
else
IM=[];
end;
size_IM=size(IM,1);
last=99999999;
for i=1:size_IM
if(last~=IM(i,2))
fprintf('\n%-30s',M_.endo_names(IM(i,2),:));
end;
fprintf(' %5d',IM(i,1));
last=IM(i,2);
end;
fprintf('\n\n');
end;
end;
%printing the gross incidence matrix
IM_star = char([kron(ones(M_.endo_nbr, M_.endo_nbr-1), double(blanks(3))) double(blanks(M_.endo_nbr)')]);
for i = 1:3
n = size(M_.block_structure.incidence(i).sparse_IM,1);
for i = 1:nb_leadlag
n = size(block_structure.incidence(i).sparse_IM,1);
for j = 1:n
if ismember(M_.block_structure.incidence(i).sparse_IM(j,2), M_.state_var)
IM_star(M_.block_structure.incidence(i).sparse_IM(j,1), 3 * (M_.block_structure.incidence(i).sparse_IM(j,2) - 1) + 1) = 'X';
if ismember(block_structure.incidence(i).sparse_IM(j,2), M_.state_var)
IM_star(block_structure.incidence(i).sparse_IM(j,1), 3 * (block_structure.incidence(i).sparse_IM(j,2) - 1) + 1) = 'X';
else
IM_star(M_.block_structure.incidence(i).sparse_IM(j,1), 3 * (M_.block_structure.incidence(i).sparse_IM(j,2) - 1) + 1) = '1';
IM_star(block_structure.incidence(i).sparse_IM(j,1), 3 * (block_structure.incidence(i).sparse_IM(j,2) - 1) + 1) = '1';
end;
end;
end;
@ -88,7 +127,7 @@ if(isfield(M_,'block_structure'))
var_names = [var_names; blank; M_.endo_names(i,:)];
end;
end;
if nargin == 1 && strcmp(varargin{1},'incidence')
if incidence
topp = [char(kron(double(blanks(ceil(log10(M_.endo_nbr)))),ones(size(M_.endo_names,2),1))) var_names' ];
bott = [int2str(seq') blanks(M_.endo_nbr)' blanks(M_.endo_nbr)' IM_star];
fprintf('\n Gross incidence matrix\n');
@ -97,42 +136,42 @@ if(isfield(M_,'block_structure'))
%printing the reordered incidence matrix
IM_star_reordered = char([kron(ones(M_.endo_nbr, M_.endo_nbr-1), double(blanks(3))) double(blanks(M_.endo_nbr)')]);
eq(M_.block_structure.equation_reordered) = seq;
va(M_.block_structure.variable_reordered) = seq;
eq(block_structure.equation_reordered) = seq;
va(block_structure.variable_reordered) = seq;
barre_blank = [ barre(size(M_.endo_names,2)); blanks(size(M_.endo_names,2))];
cur_block = 1;
for i = 1:M_.endo_nbr
past_block = cur_block;
while ismember(M_.block_structure.variable_reordered(i), M_.block_structure.block(cur_block).variable) == 0;
while ismember(block_structure.variable_reordered(i), block_structure.block(cur_block).variable) == 0;
cur_block = cur_block + 1;
end;
if i == 1
var_names = [blank; M_.endo_names(M_.block_structure.variable_reordered(i),:)];
var_names = [blank; M_.endo_names(block_structure.variable_reordered(i),:)];
else
if past_block ~= cur_block
var_names = [var_names; barre_blank; M_.endo_names(M_.block_structure.variable_reordered(i),:)];
var_names = [var_names; barre_blank; M_.endo_names(block_structure.variable_reordered(i),:)];
else
var_names = [var_names; blank; M_.endo_names(M_.block_structure.variable_reordered(i),:)];
var_names = [var_names; blank; M_.endo_names(block_structure.variable_reordered(i),:)];
end
end;
end;
topp = [char(kron(double(blanks(ceil(log10(M_.endo_nbr)))),ones(size(M_.endo_names,2),1))) var_names' ];
n_state_var = length(M_.state_var);
IM_state_var = zeros(n_state_var, n_state_var);
inv_variable_reordered(M_.block_structure.variable_reordered) = 1:M_.endo_nbr;
state_equation = M_.block_structure.equation_reordered(inv_variable_reordered(M_.state_var));
for i = 1:3
n = size(M_.block_structure.incidence(i).sparse_IM,1);
inv_variable_reordered(block_structure.variable_reordered) = 1:M_.endo_nbr;
state_equation = block_structure.equation_reordered(inv_variable_reordered(M_.state_var));
for i = 1:nb_leadlag
n = size(block_structure.incidence(i).sparse_IM,1);
for j = 1:n
[tf, loc] = ismember(M_.block_structure.incidence(i).sparse_IM(j,2), M_.state_var);
[tf, loc] = ismember(block_structure.incidence(i).sparse_IM(j,2), M_.state_var);
if tf
IM_star_reordered(eq(M_.block_structure.incidence(i).sparse_IM(j,1)), 3 * (va(M_.block_structure.incidence(i).sparse_IM(j,2)) - 1) + 1) = 'X';
[tfi, loci] = ismember(M_.block_structure.incidence(i).sparse_IM(j,1), state_equation);
IM_star_reordered(eq(block_structure.incidence(i).sparse_IM(j,1)), 3 * (va(block_structure.incidence(i).sparse_IM(j,2)) - 1) + 1) = 'X';
[tfi, loci] = ismember(block_structure.incidence(i).sparse_IM(j,1), state_equation);
if tfi
IM_state_var(loci, loc) = 1;
end;
else
IM_star_reordered(eq(M_.block_structure.incidence(i).sparse_IM(j,1)), 3 * (va(M_.block_structure.incidence(i).sparse_IM(j,2)) - 1) + 1) = '1';
IM_star_reordered(eq(block_structure.incidence(i).sparse_IM(j,1)), 3 * (va(block_structure.incidence(i).sparse_IM(j,2)) - 1) + 1) = '1';
end;
end;
end;
@ -143,7 +182,7 @@ if(isfield(M_,'block_structure'))
block = {};
for i = 1:n_state_var;
past_block = cur_block;
while ismember(M_.state_var(i), M_.block_structure.block(cur_block).variable) == 0;
while ismember(M_.state_var(i), block_structure.block(cur_block).variable) == 0;
cur_block = cur_block + 1;
end;
if (past_block ~= cur_block) || (past_block == cur_block && i == n_state_var)
@ -154,7 +193,7 @@ if(isfield(M_,'block_structure'))
cur_block = 1;
for i = 1:M_.endo_nbr
past_block = cur_block;
while ismember(M_.block_structure.variable_reordered(i), M_.block_structure.block(cur_block).variable) == 0;
while ismember(block_structure.variable_reordered(i), block_structure.block(cur_block).variable) == 0;
cur_block = cur_block + 1;
end;
if past_block ~= cur_block
@ -164,7 +203,7 @@ if(isfield(M_,'block_structure'))
end;
end
bott = [int2str(M_.block_structure.equation_reordered') blanks(M_.endo_nbr)' blanks(M_.endo_nbr)' IM_star_reordered];
bott = [int2str(block_structure.equation_reordered') blanks(M_.endo_nbr)' blanks(M_.endo_nbr)' IM_star_reordered];
fprintf('\n Reordered incidence matrix\n');
fprintf(' ==========================\n');
disp([topp; bott]);

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@ -113,6 +113,7 @@ end
if options.block
[dr,info,M,options,oo] = dr_block(dr,check_flag,M,options,oo);
oo.dr = dr;
else
[dr,info] = stochastic_solvers(dr,check_flag,M,options,oo);
oo.dr = dr;

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@ -2179,7 +2179,7 @@ SparseMatrix::Singular_display(int block, int Size, bool steady_state, it_code_t
mexCallMATLAB(3, lhs, 1, rhs, "svd");
mxArray* SVD_u = lhs[0];
mxArray* SVD_s = lhs[1];
mxArray* SVD_v = lhs[2];
//mxArray* SVD_v = lhs[2];
double *SVD_ps = mxGetPr(SVD_s);
double *SVD_pu = mxGetPr(SVD_u);
for (int i = 0; i < Size; i++)

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@ -439,9 +439,12 @@ main(int nrhs, const char *prhs[])
for (int i = 0; i < nb_blocks; i++)
{
mxSetFieldByNumber(plhs[2], i, jacob_field_number, interprete.get_jacob(i));
mxSetFieldByNumber(plhs[2], i, jacob_exo_field_number, interprete.get_jacob_exo(i));
mxSetFieldByNumber(plhs[2], i, jacob_exo_det_field_number, interprete.get_jacob_exo_det(i));
mxSetFieldByNumber(plhs[2], i, jacob_other_endo_field_number, interprete.get_jacob_other_endo(i));
if (!steady_state)
{
mxSetFieldByNumber(plhs[2], i, jacob_exo_field_number, interprete.get_jacob_exo(i));
mxSetFieldByNumber(plhs[2], i, jacob_exo_det_field_number, interprete.get_jacob_exo_det(i));
mxSetFieldByNumber(plhs[2], i, jacob_other_endo_field_number, interprete.get_jacob_other_endo(i));
}
}
}
}

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@ -1511,6 +1511,58 @@ StaticModel::writeOutput(ostream &output, bool block) const
output << getBlockEquationID(b, i)+1 << "; ";
output << "];" << endl;
}
for (int b = 0; b < (int) nb_blocks; b++)
{
BlockSimulationType simulation_type = getBlockSimulationType(b);
unsigned int block_size = getBlockSize(b);
unsigned int block_mfs = getBlockMfs(b);
unsigned int block_recursive = block_size - block_mfs;
ostringstream tmp_s, tmp_s_eq;
tmp_s.str("");
tmp_s_eq.str("");
for (int i = 0; i < block_size; i++)
{
tmp_s << " " << getBlockVariableID(b, i)+1;
tmp_s_eq << " " << getBlockEquationID(b, i)+1;
}
output << "block_structure_stat.block(" << b+1 << ").Simulation_Type = " << simulation_type << ";\n";
output << "block_structure_stat.block(" << b+1 << ").endo_nbr = " << block_size << ";\n";
output << "block_structure_stat.block(" << b+1 << ").mfs = " << getBlockMfs(block) << ";\n";
output << "block_structure_stat.block(" << b+1 << ").equation = [" << tmp_s_eq.str() << "];\n";
output << "block_structure_stat.block(" << b+1 << ").variable = [" << tmp_s.str() << "];\n";
}
output << "M_.block_structure_stat.block = block_structure_stat.block;\n";
string cst_s;
int nb_endo = symbol_table.endo_nbr();
output << "M_.block_structure_stat.variable_reordered = [";
for (int i = 0; i < nb_endo; i++)
output << " " << variable_reordered[i]+1;
output << "];\n";
output << "M_.block_structure_stat.equation_reordered = [";
for (int i = 0; i < nb_endo; i++)
output << " " << equation_reordered[i]+1;
output << "];\n";
map<pair<int, int>, int> row_incidence;
for (first_derivatives_t::const_iterator it = first_derivatives.begin();
it != first_derivatives.end(); it++)
{
int deriv_id = it->first.second;
if (getTypeByDerivID(deriv_id) == eEndogenous)
{
int eq = it->first.first;
int symb = getSymbIDByDerivID(deriv_id);
int var = symbol_table.getTypeSpecificID(symb);
//int lag = getLagByDerivID(deriv_id);
row_incidence[make_pair(eq, var)] = 1;
}
}
output << "M_.block_structure_stat.incidence.sparse_IM = [";
for (map<pair< int, int >, int>::const_iterator it = row_incidence.begin(); it != row_incidence.end(); it++)
{
output << it->first.first+1 << " " << it->first.second+1 << ";\n";
}
output << "];\n";
}
SymbolType