98 lines
4.7 KiB
Matlab
98 lines
4.7 KiB
Matlab
function [endogenousvariables, success] = sim1_purely_forward(endogenousvariables, exogenousvariables, steadystate, M_, options_)
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% Performs deterministic simulation of a purely forward model
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% Copyright © 2012-2023 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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if ismember(options_.solve_algo, [12,14])
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[funcs, feedback_vars_idxs] = setup_time_recursive_block_simul(M_);
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else
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dynamic_resid = str2func([M_.fname '.sparse.dynamic_resid']);
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dynamic_g1 = str2func([M_.fname '.sparse.dynamic_g1']);
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end
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function [r, J] = block_wrapper(z, feedback_vars_idx, func, y_dynamic, x, sparse_rowval, sparse_colval, sparse_colptr, T)
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% NB: do as few computations as possible inside this function, since it is
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% called a very large number of times
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y_dynamic(feedback_vars_idx) = z;
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[~, ~, r, J] = feval(func, y_dynamic, x, M_.params, steadystate, ...
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sparse_rowval, sparse_colval, sparse_colptr, T);
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end
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success = true;
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for it = options_.periods:-1:1
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yf = endogenousvariables(:,it+1); % Values at next period, also used as guess value for current period
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x = exogenousvariables(it,:);
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if ismember(options_.solve_algo, [12,14])
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T = NaN(M_.block_structure.dyn_tmp_nbr);
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y_dynamic = [NaN(M_.endo_nbr, 1); yf; yf];
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for blk = 1:length(M_.block_structure.block)
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sparse_rowval = M_.block_structure.block(blk).g1_sparse_rowval;
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sparse_colval = M_.block_structure.block(blk).g1_sparse_colval;
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sparse_colptr = M_.block_structure.block(blk).g1_sparse_colptr;
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if M_.block_structure.block(blk).Simulation_Type ~= 2 % Not an evaluate backward block
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[z, check, ~, ~, errorcode] = dynare_solve(@block_wrapper, y_dynamic(feedback_vars_idxs{blk}), ...
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options_.simul.maxit, options_.dynatol.f, ...
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options_.dynatol.x, options_, ...
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feedback_vars_idxs{blk}, funcs{blk}, y_dynamic, x, sparse_rowval, sparse_colval, sparse_colptr, T);
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if check
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success = false;
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if options_.debug
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dprintf('sim1_purely_forward: Nonlinear solver routine failed with errorcode=%i in block %i and period %i.', errorcode, blk, it)
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end
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end
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y_dynamic(feedback_vars_idxs{blk}) = z;
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end
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%% Compute endogenous if the block is of type evaluate or if there are recursive variables in a solve block.
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%% Also update the temporary terms vector.
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[y_dynamic, T] = feval(funcs{blk}, y_dynamic, x, M_.params, ...
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steadystate, sparse_rowval, sparse_colval, ...
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sparse_colptr, T);
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end
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endogenousvariables(:,it) = y_dynamic(M_.endo_nbr+(1:M_.endo_nbr));
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else
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[tmp, check, ~, ~, errorcode] = dynare_solve(@dynamic_forward_model_for_simulation, yf, ...
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options_.simul.maxit, options_.dynatol.f, options_.dynatol.x, ...
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options_, dynamic_resid, dynamic_g1, yf, x, M_.params, steadystate, M_.dynamic_g1_sparse_rowval, M_.dynamic_g1_sparse_colval, M_.dynamic_g1_sparse_colptr);
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if check
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success = false;
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dprintf('sim1_purely_forward: Nonlinear solver routine failed with errorcode=%i in period %i.', errorcode, it)
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break
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end
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endogenousvariables(:,it) = tmp(1:M_.endo_nbr);
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end
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end
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end
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function [r, J] = dynamic_forward_model_for_simulation(z, dynamic_resid, dynamic_g1, ylead, x, params, steady_state, sparse_rowval, sparse_colval, sparse_colptr)
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endo_nbr = length(z);
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y = [ NaN(endo_nbr, 1); z; ylead];
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[r, T_order, T] = dynamic_resid(y, x, params, steady_state);
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if nargout>1
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Jacobian = dynamic_g1(y, x, params, steady_state, sparse_rowval, ...
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sparse_colval, sparse_colptr, T_order, T);
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J = Jacobian(:, endo_nbr+(1:endo_nbr));
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end
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end
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