diff --git a/matlab/backward/backward_model_inversion.m b/matlab/backward/backward_model_inversion.m
index 8641b8d454b88c9d6ff5803804e0127845795c4b..0dd709e5b2823e402780dfec683e3e46621593ee 100644
--- a/matlab/backward/backward_model_inversion.m
+++ b/matlab/backward/backward_model_inversion.m
@@ -14,7 +14,7 @@ function [endogenousvariables, exogenousvariables] = backward_model_inversion(co
%
% REMARKS
-% Copyright (C) 2017 Dynare Team
+% Copyright © 2017-2022 Dynare Team
%
% This file is part of Dynare.
%
@@ -108,9 +108,9 @@ for t = 1:nobs(constraints)
% values) and the free exogenous variables (initialized with 0).
z = [Y(freeendogenousvariables_id,ity-1); zeros(nxfree, 1)];
% Solves for z.
- [z, failed] = dynare_solve(model_dtransf, z, DynareOptions, model_dynamic, ylag, ycur, X, DynareModel.params, DynareOutput.steady_state, itx, ModelInversion);
+ [z, failed, ~, ~, errorcode] = dynare_solve(model_dtransf, z, DynareOptions, model_dynamic, ylag, ycur, X, DynareModel.params, DynareOutput.steady_state, itx, ModelInversion);
if failed
- error('Enable to solve the system of equations!')
+ error('Nonlinear solver failed with errorcode=%i', errorcode)
end
% Update the matrix of exogenous variables.
X(itx,freeinnovations_id) = z(nyfree+(1:nxfree));
diff --git a/matlab/backward/simul_backward_nonlinear_model_.m b/matlab/backward/simul_backward_nonlinear_model_.m
index bd87796bdd135fea6263e318c71767c69b2c3e2a..d84b605ed35957e97f105cd9ecaac5124a17bde6 100644
--- a/matlab/backward/simul_backward_nonlinear_model_.m
+++ b/matlab/backward/simul_backward_nonlinear_model_.m
@@ -56,17 +56,17 @@ for it = initialconditions.nobs+(1:samplesize)
y = y_; % A good guess for the initial conditions is the previous values for the endogenous variables.
try
if ismember(DynareOptions.solve_algo, [12,14])
- [DynareOutput.endo_simul(:,it), errorflag, ~, ~, exitflag] = ...
+ [DynareOutput.endo_simul(:,it), errorflag, ~, ~, errorcode] = ...
dynare_solve(model_dynamic_s, y, DynareOptions, ...
DynareModel.isloggedlhs, DynareModel.isauxdiffloggedrhs, DynareModel.endo_names, DynareModel.lhs, ...
model_dynamic, ylag, DynareOutput.exo_simul, DynareModel.params, DynareOutput.steady_state, it);
else
- [DynareOutput.endo_simul(:,it), errorflag, ~, ~, exitflag] = ...
+ [DynareOutput.endo_simul(:,it), errorflag, ~, ~, errorcode] = ...
dynare_solve(model_dynamic_s, y, DynareOptions, ...
model_dynamic, ylag, DynareOutput.exo_simul, DynareModel.params, DynareOutput.steady_state, it);
end
if errorflag
- error()
+ error('Nonlinear solver routine failed with errorcode=%i in period %i.', errorcode, it)
end
catch
DynareOutput.endo_simul = DynareOutput.endo_simul(:, 1:it-1);
@@ -108,7 +108,7 @@ for it = initialconditions.nobs+(1:samplesize)
%
% Evaluate and check the residuals
%
- r = feval(model_dynamic, [ytm; ytm(iy1)], DynareOutput.exo_simul, DynareModel.params, DynareOutput.steady_state, it);
+ [r, J] = feval(model_dynamic, [ytm; ytm(iy1)], DynareOutput.exo_simul, DynareModel.params, DynareOutput.steady_state, it);
residuals_evaluating_to_nan = isnan(r);
residuals_evaluating_to_inf = isinf(r);
residuals_evaluating_to_complex = ~isreal(r);
@@ -130,34 +130,6 @@ for it = initialconditions.nobs+(1:samplesize)
display_names_of_problematic_equations(DynareModel, residuals_evaluating_to_nan);
skipline()
end
- %
- % Display value of exitflag if available (fsolve, solve_algo=0, only)
- %
- if ~isnan(exitflag)
- skipline()
- switch exitflag
- case 0
- disp('Returned value for exitflag is 0 (maximum number of iterations or evaluation reached).')
- case -1
- if options.solve_algo==0
- disp('Returned value for exitflag is -1 (objective function stopped algorithm).')
- elseif options.solve_algo==1
- disp('Returned value for exitflag is -1 (objective function cannot be evaluated at the initial guess).')
- end
- case -3
- if options.solve_algo==0
- disp('Returned value for exitflag is -3 (Trust region radius became too small, trust-region-dogleg algorithm).')
- elseif options.solve_algo==1
- disp('Returned value for exitflag is -3 (Convergence too slow).')
- end
- case -2
- if options.solve_algo==0
- disp('Returned value for exitflag is -2.')
- elseif options.solve_algo==1
- disp('Returned value for exitflag is -2 (Spurious convergence).')
- end
- end
- end
break
% TODO Implement same checks with the jacobian matrix.
% TODO Modify other solvers to return an exitflag.
diff --git a/matlab/dynare_solve.m b/matlab/dynare_solve.m
index ff2be72f97b6bc3fb15e109b8d6238b981a8ec93..985ddd47910ca22014165d352f75c6ab52fb05ad 100644
--- a/matlab/dynare_solve.m
+++ b/matlab/dynare_solve.m
@@ -1,4 +1,4 @@
-function [x, errorflag, fvec, fjac, exitflag] = dynare_solve(f, x, options, varargin)
+function [x, errorflag, fvec, fjac, errorcode] = dynare_solve(f, x, options, varargin)
% Solves a nonlinear system of equations, f(x) = 0 with n unknowns
% and n equations.
@@ -14,7 +14,13 @@ function [x, errorflag, fvec, fjac, exitflag] = dynare_solve(f, x, options, vara
% - errorflag [logical] scalar, true iff the model can not be solved.
% - fvec [double] n×1 vector, function value at x (f(x), used for debugging when errorflag is true).
% - fjac [double] n×n matrix, Jacobian value at x (J(x), used for debugging when errorflag is true).
-% - exitflag [integer] scalar,
+% - errorcode [integer] scalar.
+%
+% REMARKS
+% Interpretation of the error code depends on the algorithm, except if value of errorcode is
+%
+% -10 -> System of equation ill-behaved at the initial guess (Inf, Nans or complex numbers).
+% -11 -> Initial guess is a solution of the system of equations.
% Copyright © 2001-2022 Dynare Team
%
@@ -33,8 +39,6 @@ function [x, errorflag, fvec, fjac, exitflag] = dynare_solve(f, x, options, vara
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
-exitflag = nan;
-
jacobian_flag = options.jacobian_flag; % true iff Jacobian is returned by f routine (as a second output argument).
% Set tolerance parameter depending the the caller function.
@@ -49,7 +53,7 @@ else
caller_file_name=stack(1).file;
end
end
-if strcmp(caller_file_name, 'solve_stacked_problem.m') || strcmp(caller_file_name, 'sim1_purely_backward.m')
+if strcmp(caller_file_name, 'solve_stacked_problem.m') || strcmp(caller_file_name, 'sim1_purely_backward.m')
tolf = options.dynatol.f;
tolx = options.dynatol.x;
else
@@ -63,7 +67,7 @@ else
maxit = options.steady.maxit;
end
-errorflag = false;
+errorflag = false; % Let's be optimistic!
nn = size(x,1);
% Keep a copy of the initial guess.
@@ -98,7 +102,7 @@ if jacobian_flag
if ~all(isfinite(fvec)) || any(isinf(fjac(:))) || any(isnan((fjac(:)))) || any(~isreal(fvec)) || any(~isreal(fjac(:)))
if ~ismember(options.solve_algo,[10,11]) && max(abs(fvec))< tolf
% return if initial value solves the problem except if a mixed complementarity problem is to be solved (complementarity conditions may not be satisfied)
- exitflag = -1;
+ errorcode = -11;
return;
end
disp_verbose('Randomize initial guess...', options.verbosity)
@@ -134,7 +138,7 @@ else
fjac = zeros(nn, nn);
if ~ismember(options.solve_algo,[10,11]) && max(abs(fvec)) < tolf
% return if initial value solves the problem except if a mixed complementarity problem is to be solved (complementarity conditions may not be satisfied)
- exitflag = -1;
+ errorcode = -11;
return;
end
wrong_initial_guess_flag = false;
@@ -170,6 +174,7 @@ end
% Exit with error if no initial guess has been found.
if wrong_initial_guess_flag
+ errorcode = -10;
errorflag = true;
x = x0;
return
@@ -196,7 +201,7 @@ if options.solve_algo == 0
options4fsolve.Jacobian = 'off';
end
if ~isoctave
- [x, ~, exitflag] = fsolve(f, x, options4fsolve, arguments{:});
+ [x, ~, errorcode] = fsolve(f, x, options4fsolve, arguments{:});
else
% Under Octave, use a wrapper, since fsolve() does not have a 4th arg
if ischar(f)
@@ -205,19 +210,20 @@ if options.solve_algo == 0
f2 = f;
end
f = @(x) f2(x, arguments{:});
- [x, ~, exitflag] = fsolve(f, x, options4fsolve);
+ [x, ~, errorcode] = fsolve(f, x, options4fsolve);
end
- if exitflag == 1
+ if errorcode==1
errorflag = false;
- elseif exitflag > 1
- if ischar(f)
- f2 = str2func(f);
- else
- f2 = f;
+ elseif errorcode>1
+ if ~isoctave
+ if ischar(f)
+ f2 = str2func(f);
+ else
+ f2 = f;
+ end
+ f = @(x) f2(x, arguments{:});
end
- f = @(x) f2(x, arguments{:});
- fvec = feval(f, x);
- if max(abs(fvec)) >= tolf
+ if max(abs(fvec)) > tolf
errorflag = true;
else
errorflag = false;
@@ -225,10 +231,13 @@ if options.solve_algo == 0
else
errorflag = true;
end
+ [fvec, fjac] = feval(f, x, arguments{:});
elseif options.solve_algo==1
- [x, errorflag, exitflag] = solve1(f, x, 1:nn, 1:nn, jacobian_flag, options.gstep, tolf, tolx, maxit, [], options.debug, arguments{:});
+ [x, errorflag, errorcode] = solve1(f, x, 1:nn, 1:nn, jacobian_flag, options.gstep, tolf, tolx, maxit, [], options.debug, arguments{:});
+ [fvec, fjac] = feval(f, x, arguments{:});
elseif options.solve_algo==9
- [x, errorflag, exitflag] = trust_region(f, x, 1:nn, 1:nn, jacobian_flag, options.gstep, tolf, tolx, maxit, options.trust_region_initial_step_bound_factor, options.debug, arguments{:});
+ [x, errorflag, errorcode] = trust_region(f, x, 1:nn, 1:nn, jacobian_flag, options.gstep, tolf, tolx, maxit, options.trust_region_initial_step_bound_factor, options.debug, arguments{:});
+ [fvec, fjac] = feval(f, x, arguments{:});
elseif ismember(options.solve_algo, [2, 12, 4])
if ismember(options.solve_algo, [2, 12])
solver = @solve1;
@@ -304,11 +313,11 @@ elseif ismember(options.solve_algo, [2, 12, 4])
dprintf('DYNARE_SOLVE (solve_algo=2|4|12): solving block %u with trust_region routine.', i);
end
end
- [x, errorflag, exitflag] = solver(f, x, j1(j), j2(j), jacobian_flag, ...
- options.gstep, ...
- tolf, options.solve_tolx, maxit, ...
- options.trust_region_initial_step_bound_factor, ...
- options.debug, arguments{:});
+ [x, errorflag, errorcode] = solver(f, x, j1(j), j2(j), jacobian_flag, ...
+ options.gstep, ...
+ tolf, options.solve_tolx, maxit, ...
+ options.trust_region_initial_step_bound_factor, ...
+ options.debug, arguments{:});
fre = true;
if errorflag
return
@@ -317,27 +326,34 @@ elseif ismember(options.solve_algo, [2, 12, 4])
fvec = feval(f, x, arguments{:});
if max(abs(fvec))>tolf
disp_verbose('Call solver on the full nonlinear problem.',options.verbosity)
- [x, errorflag, exitflag] = solver(f, x, 1:nn, 1:nn, jacobian_flag, ...
- options.gstep, tolf, options.solve_tolx, maxit, ...
- options.trust_region_initial_step_bound_factor, ...
- options.debug, arguments{:});
+ [x, errorflag, errorcode] = solver(f, x, 1:nn, 1:nn, jacobian_flag, ...
+ options.gstep, tolf, options.solve_tolx, maxit, ...
+ options.trust_region_initial_step_bound_factor, ...
+ options.debug, arguments{:});
end
+ [fvec, fjac] = feval(f, x, arguments{:});
elseif options.solve_algo==3
if jacobian_flag
- [x, errorflag] = csolve(f, x, f, tolf, maxit, arguments{:});
+ [x, errorcode] = csolve(f, x, f, tolf, maxit, arguments{:});
else
- [x, errorflag] = csolve(f, x, [], tolf, maxit, arguments{:});
+ [x, errorcode] = csolve(f, x, [], tolf, maxit, arguments{:});
+ end
+ if errorcode==0
+ errorflag = false;
+ else
+ errorflag = true;
end
[fvec, fjac] = feval(f, x, arguments{:});
elseif options.solve_algo==10
% LMMCP
olmmcp = options.lmmcp;
- [x, ~, exitflag] = lmmcp(f, x, olmmcp.lb, olmmcp.ub, olmmcp, arguments{:});
- if exitflag==1
+ [x, fvec, errorcode, ~, fjac] = lmmcp(f, x, olmmcp.lb, olmmcp.ub, olmmcp, arguments{:});
+ if errorcode==1
errorflag = false;
else
errorflag = true;
end
+ [fvec, fjac] = feval(f, x, arguments{:});
elseif options.solve_algo == 11
% PATH mixed complementary problem
% PATH linear mixed complementary problem
@@ -355,6 +371,8 @@ elseif options.solve_algo == 11
catch
errorflag = true;
end
+ errorcode = nan; % There is no error code for this algorithm, as PATH is closed source it is unlikely we can fix that.
+ [fvec, fjac] = feval(f, x, arguments{:});
elseif ismember(options.solve_algo, [13, 14])
if ~jacobian_flag
error('DYNARE_SOLVE: option solve_algo=13|14 needs computed Jacobian')
@@ -366,7 +384,7 @@ elseif ismember(options.solve_algo, [13, 14])
auxstruct.isloggedlhs = isloggedlhs;
auxstruct.isauxdiffloggedrhs = isauxdiffloggedrhs;
end
- [x, errorflag, exitflag] = block_trust_region(f, x, tolf, options.solve_tolx, maxit, options.trust_region_initial_step_bound_factor, options.debug, auxstruct, arguments{:});
+ [x, errorflag, errorcode] = block_trust_region(f, x, tolf, options.solve_tolx, maxit, options.trust_region_initial_step_bound_factor, options.debug, auxstruct, arguments{:});
[fvec, fjac] = feval(f, x, arguments{:});
else
error('DYNARE_SOLVE: option solve_algo must be one of [0,1,2,3,4,9,10,11,12,13,14]')
diff --git a/matlab/ep/solve_stochastic_perfect_foresight_model_1.m b/matlab/ep/solve_stochastic_perfect_foresight_model_1.m
index 3a9c0d88f05e7e5f11674cdeb1b673bc40f0f7fd..d3f7ec78d275c53aaa25b34a803d2b005946fec3 100644
--- a/matlab/ep/solve_stochastic_perfect_foresight_model_1.m
+++ b/matlab/ep/solve_stochastic_perfect_foresight_model_1.m
@@ -1,6 +1,6 @@
-function [flag,endo_simul,err,y] = solve_stochastic_perfect_foresight_model_1(endo_simul,exo_simul,Options,pfm,order,varargin)
+function [errorflag, endo_simul, errorcode, y] = solve_stochastic_perfect_foresight_model_1(endo_simul, exo_simul, Options, pfm, order, varargin)
-% Copyright (C) 2012-2017 Dynare Team
+% Copyright © 2012-2022 Dynare Team
%
% This file is part of Dynare.
%
@@ -22,9 +22,9 @@ if nargin < 6
else
homotopy_parameter = varargin{1};
end
+
flag = 0;
err = 0;
-stop = 0;
EpOptions = Options.ep;
@@ -143,7 +143,7 @@ Options.steady.maxit = 100;
y = repmat(steady_state,block_nbr,1);
Options.solve_algo = Options.ep.solve_algo;
Options.steady.maxit = Options.ep.maxit;
-[y,info] = dynare_solve(@ep_problem_2,y,Options,exo_simul,pfm);
+[y, errorflag, ~, ~, errorcode] = dynare_solve(@ep_problem_2,y,Options,exo_simul,pfm);
if info
flag = 1;
err = info;
diff --git a/matlab/evaluate_steady_state.m b/matlab/evaluate_steady_state.m
index d369d9586bcffa13deb41acd287b4098fe382eb4..651363dc5cebd4e338a8b4db16554591e769e8b9 100644
--- a/matlab/evaluate_steady_state.m
+++ b/matlab/evaluate_steady_state.m
@@ -22,7 +22,7 @@ function [ys,params,info] = evaluate_steady_state(ys_init,M,options,oo,steadysta
% SPECIAL REQUIREMENTS
% none
-% Copyright (C) 2001-2021 Dynare Team
+% Copyright © 2001-2022 Dynare Team
%
% This file is part of Dynare.
%
@@ -262,17 +262,19 @@ elseif ~options.bytecode && ~options.block
if ~options.linear
% non linear model
static_model = str2func([M.fname '.static']);
- [ys,check] = dynare_solve(@static_problem,...
- ys_init,...
- options, exo_ss, params,...
- M.endo_nbr,...
- static_model);
+ [ys, check] = dynare_solve(@static_problem, ...
+ ys_init, ...
+ options, exo_ss, params, ...
+ M.endo_nbr, ...
+ static_model);
if check && options.debug
- [ys,check,fvec,fjac] = dynare_solve(@static_problem,...
- ys_init,...
- options, exo_ss, params,...
- M.endo_nbr,...
- static_model);
+ [ys, check, fvec, fjac, errorcode] = dynare_solve(@static_problem, ...
+ ys_init, ...
+ options, exo_ss, params, ...
+ M.endo_nbr, ...
+ static_model);
+ dprintf('Nonlinear solver routine returned errorcode=%i.', errorcode)
+ skipline()
[infrow,infcol]=find(isinf(fjac) | isnan(fjac));
if ~isempty(infrow)
fprintf('\nSTEADY: The Jacobian at the initial values contains Inf or NaN. The problem arises from: \n')
diff --git a/matlab/evaluate_steady_state_file.m b/matlab/evaluate_steady_state_file.m
index f2c9ec6b42fe6cc38a8ad7d4364c7704379e9518..4a804962f7f54dc56ba562642018f02e9bfe6792 100644
--- a/matlab/evaluate_steady_state_file.m
+++ b/matlab/evaluate_steady_state_file.m
@@ -19,7 +19,7 @@ function [ys,params,info] = evaluate_steady_state_file(ys_init,exo_ss,M,options,
% SPECIAL REQUIREMENTS
% none
-% Copyright (C) 2001-2019 Dynare Team
+% Copyright © 2001-2022 Dynare Team
%
% This file is part of Dynare.
%
@@ -127,5 +127,5 @@ elseif ~isempty(options.steadystate_partial)
for i = 1:nov
indv(i) = strmatch(ssvar(i), M.endo_names, 'exact');
end
- [ys,~] = dynare_solve('restricted_steadystate', ys(indv), options, exo_ss,indv);
+ ys = dynare_solve('restricted_steadystate', ys(indv), options, exo_ss,indv);
end
diff --git a/matlab/perfect-foresight-models/sim1_purely_backward.m b/matlab/perfect-foresight-models/sim1_purely_backward.m
index 0641b55a12333c72f7f86db3c3dade08065f3b68..81c5e9edc342170836130c4cebe179552bbbee4b 100644
--- a/matlab/perfect-foresight-models/sim1_purely_backward.m
+++ b/matlab/perfect-foresight-models/sim1_purely_backward.m
@@ -2,7 +2,7 @@ function [endogenousvariables, info] = sim1_purely_backward(endogenousvariables,
% Performs deterministic simulation of a purely backward model
-% Copyright © 2012-2021 Dynare Team
+% Copyright © 2012-2022 Dynare Team
%
% This file is part of Dynare.
%
@@ -39,14 +39,17 @@ for it = M.maximum_lag + (1:options.periods)
y = endogenousvariables(:,it-1); % Values at previous period, also used as guess value for current period
ylag = y(iyb);
if ismember(options.solve_algo, [12,14])
- [tmp, check] = dynare_solve(dynamicmodel_s, y, options, M.isloggedlhs, M.isauxdiffloggedrhs, M.endo_names, M.lhs, ...
- dynamicmodel, ylag, exogenousvariables, M.params, steadystate, it);
+ [tmp, check, ~, ~, errorcode] = dynare_solve(dynamicmodel_s, y, options, M.isloggedlhs, M.isauxdiffloggedrhs, M.endo_names, M.lhs, ...
+ dynamicmodel, ylag, exogenousvariables, M.params, steadystate, it);
else
- [tmp, check] = dynare_solve(dynamicmodel_s, y, options, ...
- dynamicmodel, ylag, exogenousvariables, M.params, steadystate, it);
+ [tmp, check, ~, ~, errorcode] = dynare_solve(dynamicmodel_s, y, options, ...
+ dynamicmodel, ylag, exogenousvariables, M.params, steadystate, it);
end
if check
info.status = false;
+ if options.debug
+ dprintf('sim1_purely_backward: Nonlinear solver routine failed with errorcode=%i. in period %i', errorcode, it)
+ end
end
endogenousvariables(:,it) = tmp;
end
\ No newline at end of file
diff --git a/matlab/perfect-foresight-models/sim1_purely_static.m b/matlab/perfect-foresight-models/sim1_purely_static.m
index b1bf5591f112876a7e4f3f381e88c10fc9efc040..373896cff9e54db8a05e2f7c03562e35b6684767 100644
--- a/matlab/perfect-foresight-models/sim1_purely_static.m
+++ b/matlab/perfect-foresight-models/sim1_purely_static.m
@@ -2,7 +2,7 @@ function [endogenousvariables, info] = sim1_purely_static(endogenousvariables, e
% Performs deterministic simulation of a purely static model
-% Copyright © 2021 Dynare Team
+% Copyright © 2021-2022 Dynare Team
%
% This file is part of Dynare.
%
@@ -36,14 +36,17 @@ y = endogenousvariables(:,1);
for it = 1:options.periods
if ismember(options.solve_algo, [12,14])
- [tmp, check] = dynare_solve(dynamicmodel_s, y, options, M.isloggedlhs, M.isauxdiffloggedrhs, M.endo_names, M.lhs, ...
- dynamicmodel, exogenousvariables, M.params, steadystate, it);
+ [tmp, check, ~, ~, errorcode] = dynare_solve(dynamicmodel_s, y, options, M.isloggedlhs, M.isauxdiffloggedrhs, M.endo_names, M.lhs, ...
+ dynamicmodel, exogenousvariables, M.params, steadystate, it);
else
- [tmp, check] = dynare_solve(dynamicmodel_s, y, options, ...
- dynamicmodel, exogenousvariables, M.params, steadystate, it);
+ [tmp, check, ~, ~, errorcode] = dynare_solve(dynamicmodel_s, y, options, ...
+ dynamicmodel, exogenousvariables, M.params, steadystate, it);
end
if check
info.status = false;
+ if options.debug
+ dprintf('sim1_purely_static: Nonlinear solver routine failed with errorcode=%i in period %i.', errorcode, it)
+ end
end
endogenousvariables(:,it) = tmp;
y = endogenousvariables(:,it);
diff --git a/matlab/perfect-foresight-models/solve_stacked_linear_problem.m b/matlab/perfect-foresight-models/solve_stacked_linear_problem.m
index ca54b95310488f41cd0833057f92572212aa9651..2a30699de35bbf56fc5d29bc7a31d09e3c57855b 100644
--- a/matlab/perfect-foresight-models/solve_stacked_linear_problem.m
+++ b/matlab/perfect-foresight-models/solve_stacked_linear_problem.m
@@ -1,6 +1,6 @@
function [endogenousvariables, info] = solve_stacked_linear_problem(endogenousvariables, exogenousvariables, steadystate_y, steadystate_x, M, options)
-% Copyright (C) 2015-2019 Dynare Team
+% Copyright © 2015-2022 Dynare Team
%
% This file is part of Dynare.
%
@@ -41,12 +41,12 @@ jendo = transpose(1:nd);
z = bsxfun(@minus, z, steadystate_y);
x = bsxfun(@minus, exogenousvariables, steadystate_x');
-[y, check] = dynare_solve(@linear_perfect_foresight_problem,z(:), options, ...
- jacobian, y0-steadystate_y, yT-steadystate_y, ...
- x, M.params, steadystate_y, ...
- M.maximum_lag, options.periods, M.endo_nbr, i_cols, ...
- i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0, ...
- jendo, jexog);
+[y, check, ~, ~, errorcode] = dynare_solve(@linear_perfect_foresight_problem,z(:), options, ...
+ jacobian, y0-steadystate_y, yT-steadystate_y, ...
+ x, M.params, steadystate_y, ...
+ M.maximum_lag, options.periods, M.endo_nbr, i_cols, ...
+ i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0, ...
+ jendo, jexog);
if all(imag(y)<.1*options.dynatol.x)
if ~isreal(y)
@@ -60,6 +60,9 @@ endogenousvariables = [y0 bsxfun(@plus,reshape(y,M.endo_nbr,options.periods), st
if check
info.status = false;
+ if options.debug
+ dprintf('solve_stacked_linear_problem: Nonlinear solver routine failed with errorcode=%i.', errorcode)
+ end
else
info.status = true;
end
diff --git a/matlab/perfect-foresight-models/solve_stacked_problem.m b/matlab/perfect-foresight-models/solve_stacked_problem.m
index 53054c4f5f94e9040302ab7aab3a098671d86c76..484d7f9cf6d580321185c33a7627b0b02a07c7b8 100644
--- a/matlab/perfect-foresight-models/solve_stacked_problem.m
+++ b/matlab/perfect-foresight-models/solve_stacked_problem.m
@@ -13,7 +13,7 @@ function [endogenousvariables, info] = solve_stacked_problem(endogenousvariables
% - endogenousvariables [double] N*T array, paths for the endogenous variables (solution of the perfect foresight model).
% - info [struct] contains informations about the results.
-% Copyright (C) 2015-2019 Dynare Team
+% Copyright © 2015-2022 Dynare Team
%
% This file is part of Dynare.
%
@@ -46,14 +46,14 @@ if (options.solve_algo == 10 || options.solve_algo == 11)% mixed complementarity
options.mcppath.lb = repmat(lb,options.periods,1);
options.mcppath.ub = repmat(ub,options.periods,1);
end
- [y, check] = dynare_solve(@perfect_foresight_mcp_problem,z(:),options, ...
- dynamicmodel, y0, yT, ...
- exogenousvariables, M.params, steadystate, ...
- M.maximum_lag, options.periods, M.endo_nbr, i_cols, ...
- i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0, ...
- eq_index);
+ [y, check, ~, ~, errorcode] = dynare_solve(@perfect_foresight_mcp_problem,z(:),options, ...
+ dynamicmodel, y0, yT, ...
+ exogenousvariables, M.params, steadystate, ...
+ M.maximum_lag, options.periods, M.endo_nbr, i_cols, ...
+ i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0, ...
+ eq_index);
else
- [y, check] = dynare_solve(@perfect_foresight_problem,z(:), options, y0, yT, exogenousvariables, M.params, steadystate, options.periods, M, options);
+ [y, check, ~, ~, errorcode] = dynare_solve(@perfect_foresight_problem,z(:), options, y0, yT, exogenousvariables, M.params, steadystate, options.periods, M, options);
end
if all(imag(y)<.1*options.dynatol.x)
@@ -68,6 +68,9 @@ endogenousvariables(:, M.maximum_lag+(1:options.periods)) = reshape(y, M.endo_nb
if check
info.status = false;
+ if options.debug
+ dprintf('solve_stacked_problem: Nonlinear solver routine failed with errorcode=%i.', errorcode)
+ end
else
info.status = true;
end
diff --git a/matlab/simul_static_model.m b/matlab/simul_static_model.m
index 97c3726b10f8632eaebd4bcf66ba508bff68dabb..44e8d09e0a101fe548db03012d55045c4425491b 100644
--- a/matlab/simul_static_model.m
+++ b/matlab/simul_static_model.m
@@ -15,7 +15,7 @@ function simulation = simul_static_model(samplesize, innovations)
% [2] The last input argument is not mandatory. If absent we use random draws and rescale them with the informations provided
% through the shocks block.
-% Copyright (C) 2019 Dynare Team
+% Copyright © 2019-2022 Dynare Team
%
% This file is part of Dynare.
%
@@ -88,9 +88,9 @@ staticmodel = str2fun(sprintf('%s.static', M_.fname));
% Simulations (call a Newton-like algorithm for each period).
for t=1:samplesize
y = zeros(M_.endo_nbr, 1);
- [oo_.endo_simul(:,t), info] = dynare_solve(staticmodel, y, options_, oo_.exo_simul(t,:), M_.params);
+ [oo_.endo_simul(:,t), info, ~, ~, errorcode] = dynare_solve(staticmodel, y, options_, oo_.exo_simul(t,:), M_.params);
if info
- error('Newton failed!')
+ error('Newton failed (with error code %i).', errorcode)
end
end
diff --git a/matlab/solve1.m b/matlab/solve1.m
index 7637f057f03951e6b2b27159f350eebd111e7d8a..fa6a3262fdb72f7e77230ceee43f184117c3f6df 100644
--- a/matlab/solve1.m
+++ b/matlab/solve1.m
@@ -1,4 +1,4 @@
-function [x, errorflag, exitflag] = solve1(func, x, j1, j2, jacobian_flag, gstep, tolf, tolx, maxit, fake, debug, varargin)
+function [x, errorflag, errorcode] = solve1(func, x, j1, j2, jacobian_flag, gstep, tolf, tolx, maxit, fake, debug, varargin)
% Solves systems of non linear equations of several variables
%
@@ -61,7 +61,7 @@ idCpx = ~isreal(fvec);
if any(idInf)
disp('SOLVE1: during the resolution of the non-linear system, the evaluation of the following equation(s) resulted in a non-finite number:')
disp(j1(idInf)')
- exitflag = -1;
+ errorcode = 0;
errorflag = true;
return
end
@@ -69,7 +69,7 @@ end
if any(idNan)
disp('SOLVE1: during the resolution of the non-linear system, the evaluation of the following equation(s) resulted in a nan:')
disp(j1(idNan)')
- exitflag = -1;
+ errorcode = 0;
errorflag = true;
return
end
@@ -77,7 +77,7 @@ end
if any(idNan)
disp('SOLVE1: during the resolution of the non-linear system, the evaluation of the following equation(s) resulted in a complex number:')
disp(j1(idCpx)')
- exitflag = -1;
+ errorcode = 0;
errorflag = true;
return
end
@@ -86,7 +86,7 @@ f = 0.5*(fvec'*fvec);
if max(abs(fvec))<tolf*tolf
% Initial guess is a solution
- exitflag = 1;
+ errorcode = -1;
return
end
@@ -140,7 +140,7 @@ for its = 1:maxit
den = max([f;0.5*nn]) ;
if max(abs(g).*max([abs(x(j2)') ones(1,nn)])')/den < tolmin
if max(abs(x(j2)-xold(j2))./max([abs(x(j2)') ones(1,nn)])') < tolx
- exitflag = -3;
+ errorcode = 3;
if nargout<3
skipline()
dprintf('SOLVE: Iteration %s', num2str(its))
@@ -150,7 +150,7 @@ for its = 1:maxit
return
end
else
- exitflag = -2;
+ errorcode = 4;
if nargout<3
skipline()
dprintf('SOLVE: Iteration %s', num2str(its))
@@ -160,18 +160,19 @@ for its = 1:maxit
return
end
elseif max(abs(fvec)) < tolf
- exitflag = 1;
+ errorcode = 1;
return
end
end
errorflag = true;
-exitflag = 0;
+errorcode = 2;
if nargout<3
skipline()
disp('SOLVE: maxit has been reached')
end
+
% 01/14/01 MJ lnsearch is now a separate function
% 01/16/01 MJ added varargin to function evaluation
% 04/13/01 MJ added test f < tolf !!
diff --git a/matlab/static_model_inversion.m b/matlab/static_model_inversion.m
index 9993d0503cbba2a1cba0846f9a6374c239c3223e..c2b8d80e2f4990c88f69dc40a64d1f99b15a814d 100644
--- a/matlab/static_model_inversion.m
+++ b/matlab/static_model_inversion.m
@@ -13,7 +13,7 @@ function [endogenousvariables, exogenousvariables] = static_model_inversion(cons
%
% REMARKS
-% Copyright (C) 2019 Dynare Team
+% Copyright © 2019-2022 Dynare Team
%
% This file is part of Dynare.
%
@@ -103,9 +103,9 @@ for t = 1:nobs(constraints)
% values) and the free exogenous variables (initialized with 0).
z = [Y(freeendogenousvariables_id,ity); zeros(nxfree, 1)];
% Solves for z.
- [z, failed] = dynare_solve(model_stransf, z, DynareOptions, model_dynamic, ycur, X(itx, :), DynareModel.params, ModelInversion);
- if failed
- error('Enable to solve the system of equations!')
+ [z, errorflag, ~, ~, errorcode] = dynare_solve(model_stransf, z, DynareOptions, model_dynamic, ycur, X(itx, :), DynareModel.params, ModelInversion);
+ if errorflag
+ error('Enable to solve the system of equations (with error code %i).', errorcode)
end
% Update the matrix of exogenous variables.
X(itx,freeinnovations_id) = z(nyfree+(1:nxfree));