109 lines
5.2 KiB
Matlab
109 lines
5.2 KiB
Matlab
function [y, success, maxerror, per_block_status] = solve_block_decomposed_problem(options_, M_, oo_)
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% Computes deterministic simulation with block option without bytecode
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% Copyright © 2020-2023 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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cutoff = 1e-15;
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if options_.stack_solve_algo==0
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mthd='Sparse LU';
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elseif options_.stack_solve_algo==1 || options_.stack_solve_algo==6
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mthd='LBJ';
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elseif options_.stack_solve_algo==2
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mthd='GMRES';
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elseif options_.stack_solve_algo==3
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mthd='BICGSTAB';
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elseif options_.stack_solve_algo==4
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mthd='OPTIMPATH';
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else
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mthd='UNKNOWN';
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end
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if options_.verbosity
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printline(41)
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disp(sprintf('MODEL SIMULATION (method=%s):',mthd))
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skipline()
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end
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y=oo_.endo_simul;
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T=NaN(M_.block_structure.dyn_tmp_nbr, options_.periods+M_.maximum_lag+M_.maximum_lead);
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maxerror = 0;
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nblocks = length(M_.block_structure.block);
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per_block_status = struct('success', cell(1, nblocks), 'error', cell(1, nblocks), 'iterations', cell(1, nblocks));
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funcname = [ M_.fname '.dynamic'];
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for blk = 1:nblocks
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recursive_size = M_.block_structure.block(blk).endo_nbr - M_.block_structure.block(blk).mfs;
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y_index = M_.block_structure.block(blk).variable((recursive_size+1):end);
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fh_dynamic = str2func(sprintf('%s.sparse.block.dynamic_%d', M_.fname, blk));
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if M_.block_structure.block(blk).Simulation_Type == 1 || ... % evaluateForward
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M_.block_structure.block(blk).Simulation_Type == 2 % evaluateBackward
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if M_.block_structure.block(blk).Simulation_Type == 1
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range = M_.maximum_lag+1:M_.maximum_lag+options_.periods;
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else
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range = M_.maximum_lag+options_.periods:-1:M_.maximum_lag+1;
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end
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for it_ = range
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if it_ > 1 && it_ < size(y, 2)
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y3n = reshape(y(:, it_+(-1:1)), 3*M_.endo_nbr, 1);
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elseif it_ > 1 % Purely backward model (in last period)
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y3n = [ reshape(y(:, it_+(-1:0)), 2*M_.endo_nbr, 1); NaN(M_.endo_nbr, 1) ];
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elseif it_ < size(y, 2) % Purely forward model (in first period)
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y3n = [ NaN(M_.endo_nbr, 1); reshape(y(:, it_+(0:1)), 2*M_.endo_nbr, 1) ];
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else % Static model
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y3n = [ NaN(M_.endo_nbr, 1); y(:, it_); NaN(M_.endo_nbr, 1) ]
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end
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[y3n, T(:, it_)] = fh_dynamic(y3n, oo_.exo_simul(it_, :), M_.params, oo_.steady_state, ...
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M_.block_structure.block(blk).g1_sparse_rowval, ...
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M_.block_structure.block(blk).g1_sparse_colval, ...
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M_.block_structure.block(blk).g1_sparse_colptr, T(:, it_));
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y(:, it_) = y3n(M_.endo_nbr+(1:M_.endo_nbr));
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end
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success = true;
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maxblkerror = 0;
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iter = [];
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elseif M_.block_structure.block(blk).Simulation_Type == 3 || ... % solveForwardSimple
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M_.block_structure.block(blk).Simulation_Type == 4 || ... % solveBackwardSimple
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M_.block_structure.block(blk).Simulation_Type == 6 || ... % solveForwardComplete
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M_.block_structure.block(blk).Simulation_Type == 7 % solveBackwardComplete
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is_forward = M_.block_structure.block(blk).Simulation_Type == 3 || M_.block_structure.block(blk).Simulation_Type == 6;
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[y, T, success, maxblkerror, iter] = solve_one_boundary(fh_dynamic, y, oo_.exo_simul, M_.params, oo_.steady_state, T, y_index, M_.block_structure.block(blk).NNZDerivatives, options_.periods, M_.block_structure.block(blk).is_linear, blk, M_.maximum_lag, options_.simul.maxit, options_.dynatol.f, cutoff, options_.stack_solve_algo, is_forward, true, false, M_, options_);
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elseif M_.block_structure.block(blk).Simulation_Type == 5 || ... % solveTwoBoundariesSimple
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M_.block_structure.block(blk).Simulation_Type == 8 % solveTwoBoundariesComplete
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[y, T, success, maxblkerror, iter] = solve_two_boundaries(fh_dynamic, y, oo_.exo_simul, M_.params, oo_.steady_state, T, y_index, M_.block_structure.block(blk).NNZDerivatives, options_.periods, M_.block_structure.block(blk).is_linear, blk, M_.maximum_lag, options_.simul.maxit, options_.dynatol.f, cutoff, options_.stack_solve_algo, options_, M_);
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end
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tmp = y(M_.block_structure.block(blk).variable, :);
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if any(isnan(tmp) | isinf(tmp))
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disp(['Inf or Nan value during the resolution of block ' num2str(blk)]);
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success = false;
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end
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per_block_status(blk).success = success;
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per_block_status(blk).error = maxblkerror;
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per_block_status(blk).iter = iter;
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maxerror = max(maxblkerror, maxerror);
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if ~success
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return
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end
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end
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