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solve_two_boundaries.m: strip down the number of input arguments

kalman_mex
Sébastien Villemot 2023-11-08 13:29:03 +01:00
parent b36507d005
commit 158b7462bf
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GPG Key ID: 2CECE9350ECEBE4A
2 changed files with 16 additions and 27 deletions
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4
matlab/perfect-foresight-models/solve_block_decomposed_problem.m
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@ -59,7 +59,6 @@ nblocks = length(M_.block_structure.block);
per_block_status = struct('success', cell(1, nblocks), 'error', cell(1, nblocks), 'iterations', cell(1, nblocks));
for blk = 1:nblocks
y_index = M_.block_structure.block(blk).variable(end-M_.block_structure.block(blk).mfs+1:end);
fh_dynamic = str2func(sprintf('%s.sparse.block.dynamic_%d', M_.fname, blk));
switch M_.block_structure.block(blk).Simulation_Type
@ -90,9 +89,10 @@ for blk = 1:nblocks
iter = [];
case {3, 4, 6, 7} % solve{Forward,Backward}{Simple,Complete}
is_forward = M_.block_structure.block(blk).Simulation_Type == 3 || M_.block_structure.block(blk).Simulation_Type == 6;
y_index = M_.block_structure.block(blk).variable(end-M_.block_structure.block(blk).mfs+1:end);
[y, T, success, maxblkerror, iter] = solve_one_boundary(fh_dynamic, y, exo_simul, M_.params, 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_);
case {5, 8} % solveTwoBoundaries{Simple,Complete}
[y, T, success, maxblkerror, iter] = solve_two_boundaries(fh_dynamic, y, exo_simul, M_.params, 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_);
[y, T, success, maxblkerror, iter] = solve_two_boundaries(fh_dynamic, y, exo_simul, steady_state, T, blk, cutoff, options_, M_);
end
tmp = y(M_.block_structure.block(blk).variable, :);

39
matlab/solve_two_boundaries.m
View File

@ -1,4 +1,4 @@
function [y, T, success, max_res, iter] = solve_two_boundaries(fh, y, x, params, steady_state, T, y_index, nze, periods, is_linear, Block_Num, y_kmin, maxit_, solve_tolf, cutoff, stack_solve_algo,options_,M_)
function [y, T, success, max_res, iter] = solve_two_boundaries(fh, y, x, steady_state, T, Block_Num, cutoff, options_, M_)
% Computes the deterministic simulation of a block of equation containing
% both lead and lag variables using relaxation methods
%
@ -6,27 +6,11 @@ function [y, T, success, max_res, iter] = solve_two_boundaries(fh, y, x, params,
% fh [handle] function handle to the dynamic file for the block
% y [matrix] All the endogenous variables of the model
% x [matrix] All the exogenous variables of the model
% params [vector] All the parameters of the model
% steady_state [vector] steady state of the model
% T [matrix] Temporary terms
% y_index [vector of int] The index of the endogenous variables of
% the block
% nze [integer] number of non-zero elements in the
% jacobian matrix
% periods [integer] number of simulation periods
% is_linear [logical] Whether the block is linear
% Block_Num [integer] block number
% y_kmin [integer] maximum number of lag in the model
% maxit_ [integer] maximum number of iteration in Newton
% solve_tolf [double] convergence criteria
% cutoff [double] cutoff to correct the direction in Newton in case
% of singular jacobian matrix
% stack_solve_algo [integer] linear solver method used in the
% Newton algorithm :
% - 1 sprse LU
% - 2 GMRES
% - 3 BicGStab
% - 4 Optimal path length
% options_ [structure] storing the options
% M_ [structure] Model description
%
@ -57,11 +41,16 @@ function [y, T, success, max_res, iter] = solve_two_boundaries(fh, y, x, params,
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
Blck_size = M_.block_structure.block(Block_Num).mfs;
y_index = M_.block_structure.block(Block_Num).variable(end-Blck_size+1:end);
periods = options_.periods;
y_kmin = M_.maximum_lag;
stack_solve_algo = options_.stack_solve_algo;
verbose = options_.verbosity;
cvg=false;
iter=0;
Blck_size=size(y_index,2);
correcting_factor=0.01;
ilu_setup.droptol=1e-10;
ilu_setup.type = 'ilutp';
@ -72,11 +61,11 @@ ilu_setup.udiag = 0;
max_resa=1e100;
lambda = 1; % Length of Newton step (unused for stack_solve_algo=4)
reduced = 0;
while ~(cvg || iter>maxit_)
while ~(cvg || iter > options_.simul.maxit)
r = NaN(Blck_size, periods);
g1a = spalloc(Blck_size*periods, Blck_size*periods, nze*periods);
g1a = spalloc(Blck_size*periods, Blck_size*periods, M_.block_structure.block(Block_Num).NNZDerivatives*periods);
for it_ = y_kmin+(1:periods)
[yy, T(:, it_), r(:, it_-y_kmin), g1]=fh(dynendo(y, it_, M_), x(it_, :), params, steady_state, ...
[yy, T(:, it_), r(:, it_-y_kmin), g1]=fh(dynendo(y, it_, M_), x(it_, :), M_.params, steady_state, ...
M_.block_structure.block(Block_Num).g1_sparse_rowval, ...
M_.block_structure.block(Block_Num).g1_sparse_colval, ...
M_.block_structure.block(Block_Num).g1_sparse_colptr, T(:, it_));
@ -101,10 +90,10 @@ while ~(cvg || iter>maxit_)
end
if ~isreal(max_res) || isnan(max_res)
cvg = false;
elseif is_linear && iter>0
elseif M_.block_structure.block(Block_Num).is_linear && iter>0
cvg = true;
else
cvg=(max_res<solve_tolf);
cvg = (max_res < options_.dynatol.f);
end
if ~cvg
if iter>0
@ -308,7 +297,7 @@ while ~(cvg || iter>maxit_)
g = (ra'*g1a)';
f = 0.5*ra'*ra;
p = -g1a\ra;
[yn,f,ra,check]=lnsrch1(ya,f,g,p,stpmax,@lnsrch1_wrapper_two_boundaries,nn,nn, options_.solve_tolx, fh, Block_Num, y, y_index,x, params, steady_state, T, periods, Blck_size, M_);
[yn,f,ra,check]=lnsrch1(ya,f,g,p,stpmax,@lnsrch1_wrapper_two_boundaries,nn,nn, options_.solve_tolx, fh, Block_Num, y, y_index,x, M_.params, steady_state, T, periods, Blck_size, M_);
dx = ya - yn;
y(y_index, y_kmin+(1:periods))=reshape(yn',length(y_index),periods);
end
@ -319,7 +308,7 @@ while ~(cvg || iter>maxit_)
end
end
if (iter>maxit_)
if iter > options_.simul.maxit
if verbose
printline(41)
%disp(['No convergence after ' num2str(iter,'%4d') ' iterations in Block ' num2str(Block_Num,'%d')])