stepan
/
dynare
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
dynare/matlab/model_info.m

339 lines
14 KiB
Matlab
Raw Permalink Blame History

function model_info(options_model_info_)
%function model_info(options_model_info_)
% Copyright © 2008-2022 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 <https://www.gnu.org/licenses/>.
global M_;
dynamic_ = isfield(options_model_info_, 'block_dynamic') && options_model_info_.block_dynamic;
static_ = isfield(options_model_info_, 'block_static') && options_model_info_.block_static;
incidence = isfield(options_model_info_, 'incidence') && options_model_info_.incidence;
if static_
temp_string=sprintf('\nInformation about %s (static model)\n',M_.fname);
fprintf(temp_string);
block_structure_str = 'block_structure_stat';
if ~isfield(M_,'block_structure_stat')
fprintf('\nmodel_info: block information not present; skipping display.\n')
return;
else
nb_leadlag = 1;
end
else
temp_string=sprintf('\nInformation about %s (dynamic model)\n',M_.fname);
fprintf(temp_string);
block_structure_str = 'block_structure';
if dynamic_ && isfield(M_,'block_structure')
fprintf('\nmodel_info: block information not present; skipping display.\n')
return;
elseif dynamic_
nb_leadlag = length([M_.(block_structure_str).incidence.lead_lag]);
end
end
if dynamic_ || static_ || incidence %block information requested
if static_
block_structure = M_.block_structure_stat;
else
block_structure = M_.block_structure;
end
fprintf([char(ones(1,length(temp_string))*'='),'\n']);
nb_blocks=length(block_structure.block);
fprintf('The model has %d equations and is decomposed into %d blocks as follows:\n',M_.endo_nbr,nb_blocks);
fprintf('================================================================================================================================\n');
fprintf('| %10s | %10s | %30s | %31s | %31s |\n','Block no','Size','Block Type','Equation','Dependent variable');
fprintf('|============|============|================================|=================================|=================================|\n');
for i=1:nb_blocks
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 | %-6d %24s | %-6d %24s |\n',i,size_block,Sym_type(block_structure.block(i).Simulation_Type),block_structure.block(i).equation(j),get_equation_name_by_number(block_structure.block(i).equation(j), M_),block_structure.block(i).variable(j),M_.endo_names{block_structure.block(i).variable(j)});
else
fprintf('| %10s | %10s | %30s | %-6d %24s | %-6d %24s |\n','','','',block_structure.block(i).equation(j),get_equation_name_by_number(block_structure.block(i).equation(j), M_),block_structure.block(i).variable(j),M_.endo_names{block_structure.block(i).variable(j)});
end
end
end
fprintf('================================================================================================================================\n');
fprintf('\n');
if static_
fprintf('%-30s %s','The variable','is used contemporaneously in the following equations:');
if(size(block_structure.incidence.sparse_IM,1)>0)
IM=sortrows(block_structure.incidence.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');
else %dynamic model
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 the following equations contemporaneously');
elseif(k<M_.maximum_endo_lag+1)
fprintf('%-30s %s %d','The variable','is used in the following 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
if incidence
%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:nb_leadlag
n = size(block_structure.incidence(i).sparse_IM,1);
for j = 1:n
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(block_structure.incidence(i).sparse_IM(j,1), 3 * (block_structure.incidence(i).sparse_IM(j,2) - 1) + 1) = '1';
end
end
end
seq = 1: M_.endo_nbr;
blank = [ blanks(cellofchararraymaxlength(M_.endo_names)); blanks(cellofchararraymaxlength(M_.endo_names))];
for i = 1:M_.endo_nbr
if i == 1
var_names = char(blank, M_.endo_names{i});
else
var_names = char(var_names, blank, M_.endo_names{i});
end
end
topp = [char(kron(double(blanks(ceil(log10(M_.endo_nbr)))),ones(cellofchararraymaxlength(M_.endo_names),1))) var_names' ];
bott = [int2str(seq') blanks(M_.endo_nbr)' blanks(M_.endo_nbr)' IM_star];
fprintf('\nGross incidence matrix\n');
fprintf('=======================\n');
disp(topp);
skipline;
disp(bott);
%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(block_structure.equation_reordered) = seq;
va(block_structure.variable_reordered) = seq;
barre_blank = [ barre(cellofchararraymaxlength(M_.endo_names)); blanks(cellofchararraymaxlength(M_.endo_names))];
cur_block = 1;
for i = 1:M_.endo_nbr
past_block = cur_block;
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 = char(blank, M_.endo_names{block_structure.variable_reordered(i)});
else
if past_block ~= cur_block
var_names = char(var_names, barre_blank, M_.endo_names{block_structure.variable_reordered(i)});
else
var_names = char(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(cellofchararraymaxlength(M_.endo_names),1))) var_names' ];
n_state_var = length(M_.state_var);
IM_state_var = zeros(n_state_var, n_state_var);
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(block_structure.incidence(i).sparse_IM(j,2), M_.state_var);
if tf
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(block_structure.incidence(i).sparse_IM(j,1)), 3 * (va(block_structure.incidence(i).sparse_IM(j,2)) - 1) + 1) = '1';
end
end
end
fprintf('\n1: non-null element, X: non-null element related to a state variable\n');
cur_block = 1;
i_last = 0;
block = {};
for i = 1:n_state_var
past_block = cur_block;
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)
block(past_block).IM_state_var(1:(i - 1 - i_last), 1:i - 1) = IM_state_var(i_last+1:i - 1, 1:i - 1);
i_last = i - 1;
end
end
cur_block = 1;
for i = 1:M_.endo_nbr
past_block = cur_block;
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
for j = 1:i-1
IM_star_reordered(j, 3 * (i - 1) - 1) = '|';
end
end
end
bott = [int2str(block_structure.equation_reordered') blanks(M_.endo_nbr)' blanks(M_.endo_nbr)' IM_star_reordered];
fprintf('\nReordered incidence matrix\n');
fprintf('==========================\n');
disp(topp);
skipline;
disp(bott);
fprintf('\n1: non-null element, X: non-null element related to a state variable\n');
end
else %non-block information
% print states
if M_.maximum_endo_lag~=0
lag_index=find(M_.lead_lag_incidence(1,:));
fprintf('\nThe following variables appear with a lag and are therefore states:\n')
for var_iter=1:length(lag_index)
print_line(M_.endo_names,lag_index(var_iter),-1,M_)
end
else
lag_index=[];
end
%print forward-looking variables
if M_.maximum_endo_lead~=0
lead_index = find(M_.lead_lag_incidence(M_.maximum_lag+2,:));
fprintf('\nThe following variables appear with a lead and are therefore forward-looking variables:\n')
for var_iter=1:length(lead_index)
print_line(M_.endo_names,lead_index(var_iter),1,M_)
end
else
lead_index=[];
end
%print purely static ones
static_index = setdiff(1:M_.endo_nbr,union(lag_index,lead_index));
if ~isempty(static_index)
fprintf('\nThe following variables do not appear with a lead or lag and are therefore purely static variables:\n')
for var_iter=1:length(static_index)
print_line(M_.endo_names,static_index(var_iter),0,M_)
end
end
skipline;
end
end
function print_line(names,var_index,lead_lag,M_)
if var_index<=M_.orig_endo_nbr
if iscell(names)
if lead_lag==0
fprintf('%s\n',names{var_index})
else
fprintf('%s(%d)\n',names{var_index},lead_lag)
end
else
if lead_lag==0
fprintf('%s\n',names(var_index))
else
fprintf('%s(%d)\n',names(var_index),lead_lag)
end
end
else
aux_index=find([M_.aux_vars(:).endo_index]==var_index);
aux_type=M_.aux_vars(aux_index).type;
if lead_lag==0
str = subst_auxvar(var_index, [], M_);
else
str = subst_auxvar(var_index, lead_lag, M_);
end
aux_orig_expression=M_.aux_vars(aux_index).orig_expr;
if isempty(aux_orig_expression)
fprintf('%s\n',str);
else
fprintf('%s (original expression %s) \n',str,aux_orig_expression);
end
end
end
function ret=Sym_type(type)
UNKNOWN=0;
EVALUATE_FORWARD=1;
EVALUATE_BACKWARD=2;
SOLVE_FORWARD_SIMPLE=3;
SOLVE_BACKWARD_SIMPLE=4;
SOLVE_TWO_BOUNDARIES_SIMPLE=5;
SOLVE_FORWARD_COMPLETE=6;
SOLVE_BACKWARD_COMPLETE=7;
SOLVE_TWO_BOUNDARIES_COMPLETE=8;
EVALUATE_FORWARD_R=9;
EVALUATE_BACKWARD_R=10;
switch (type)
case (UNKNOWN)
ret='UNKNOWN ';
case {EVALUATE_FORWARD,EVALUATE_FORWARD_R}
ret='EVALUATE FORWARD ';
case {EVALUATE_BACKWARD,EVALUATE_BACKWARD_R}
ret='EVALUATE BACKWARD ';
case SOLVE_FORWARD_SIMPLE
ret='SOLVE FORWARD SIMPLE ';
case SOLVE_BACKWARD_SIMPLE
ret='SOLVE BACKWARD SIMPLE ';
case SOLVE_TWO_BOUNDARIES_SIMPLE
ret='SOLVE TWO BOUNDARIES SIMPLE ';
case SOLVE_FORWARD_COMPLETE
ret='SOLVE FORWARD COMPLETE ';
case SOLVE_BACKWARD_COMPLETE
ret='SOLVE BACKWARD COMPLETE ';
case SOLVE_TWO_BOUNDARIES_COMPLETE
ret='SOLVE TWO BOUNDARIES COMPLETE';
end
end
function ret = barre(n)
s = [];
for i=1:n
s = [s '|'];
end
ret = s;
end
Reference in New Issue View Git Blame Copy Permalink