88 lines
3.8 KiB
Matlab
88 lines
3.8 KiB
Matlab
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function model_info;
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global M_;
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fprintf(' Informations about %s\n',M_.fname);
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fprintf(strcat(' ===================',char(ones(1,length(M_.fname))*'='),'\n\n'));
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if(isfield(M_,'block_structure'))
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nb_blocks=length(M_.block_structure.block);
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fprintf('The model has %d equations and is decomposed in %d blocks as follow:\n',M_.endo_nbr,nb_blocks);
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fprintf('==============================================================================================================\n');
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fprintf('| %10s | %10s | %30s | %14s | %30s |\n','Block n<>','Size','Block Type','Equation','Dependent variable');
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fprintf('|============|============|================================|================|================================|\n');
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for i=1:nb_blocks
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size_block=length(M_.block_structure.block(i).equation);
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if(i>1)
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fprintf('|------------|------------|--------------------------------|----------------|--------------------------------|\n');
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end;
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for j=1:size_block
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if(j==1)
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fprintf('| %3d (%4d) | %10d | %30s | %14d | %30s |\n',i,M_.block_structure.block(i).num,size_block,Sym_type(M_.block_structure.block(i).Simulation_Type),M_.block_structure.block(i).equation(j),M_.endo_names(M_.block_structure.block(i).variable(j),:));
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else
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fprintf('| %10s | %10s | %30s | %14d | %30s |\n','','','',M_.block_structure.block(i).equation(j),M_.endo_names(M_.block_structure.block(i).variable(j),:));
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end;
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end;
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end;
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fprintf('==============================================================================================================\n');
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fprintf('\n');
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for k=1:M_.maximum_endo_lag+M_.maximum_endo_lead+1
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if(k==M_.maximum_endo_lag+1)
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fprintf('%-30s %s','the variable','is used in equations contemporously');
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elseif(k<M_.maximum_endo_lag+1)
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fprintf('%-30s %s %d','the variable','is used in equations with lag ',M_.maximum_endo_lag+1-k);
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else
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fprintf('%-30s %s %d','the variable','is used in equations with lead ',k-(M_.maximum_endo_lag+1));
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end;
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if(size(M_.block_structure.incidence(k).sparse_IM,1)>0)
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IM=sortrows(M_.block_structure.incidence(k).sparse_IM,2);
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else
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IM=[];
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end;
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size_IM=size(IM,1);
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last=0;
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for i=1:size_IM
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if(last~=IM(i,2))
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fprintf('\n%-30s',M_.endo_names(IM(i,2),:));
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end;
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fprintf(' %5d',IM(i,1));
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last=IM(i,2);
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end;
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fprintf('\n\n');
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end;
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else
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fprintf('There is no block decomposition of the model.\nUse ''sparse'' or ''sparse_dll'' model''s option.\n');
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end;
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function ret=Sym_type(type);
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EVALUATE_FOREWARD=0;
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EVALUATE_BACKWARD=1;
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SOLVE_FOREWARD_SIMPLE=2;
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SOLVE_BACKWARD_SIMPLE=3;
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SOLVE_TWO_BOUNDARIES_SIMPLE=4;
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SOLVE_FOREWARD_COMPLETE=5;
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SOLVE_BACKWARD_COMPLETE=6;
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SOLVE_TWO_BOUNDARIES_COMPLETE=7;
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EVALUATE_FOREWARD_R=8;
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EVALUATE_BACKWARD_R=9;
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switch (type)
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case {EVALUATE_FOREWARD,EVALUATE_FOREWARD_R},
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ret='EVALUATE FOREWARD ';
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case {EVALUATE_BACKWARD,EVALUATE_BACKWARD_R},
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ret='EVALUATE BACKWARD ';
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case SOLVE_FOREWARD_SIMPLE,
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ret='SOLVE FOREWARD SIMPLE ';
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case SOLVE_BACKWARD_SIMPLE,
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ret='SOLVE BACKWARD SIMPLE ';
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case SOLVE_TWO_BOUNDARIES_SIMPLE,
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ret='SOLVE TWO BOUNDARIES SIMPLE ';
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case SOLVE_FOREWARD_COMPLETE,
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ret='SOLVE FOREWARD COMPLETE ';
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case SOLVE_BACKWARD_COMPLETE,
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ret='SOLVE BACKWARD COMPLETE ';
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case SOLVE_TWO_BOUNDARIES_COMPLETE,
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ret='SOLVE TWO BOUNDARIES COMPLETE';
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end;
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