Perfect foresight: remove unused nnzJ argument in several stacked problem functions
Sébastien Villemot
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088826a332
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5a36d57b90
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@ -1,6 +1,6 @@
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function [residuals,JJacobian] = linear_perfect_foresight_problem(y, dynamicjacobian, Y0, YT, ...
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exo_simul, params, steady_state, maximum_lag, T, ny, i_cols, ...
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i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0, nnzJ, jendo, jexog)
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i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0, jendo, jexog)
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% Computes the residuals and the Jacobian matrix for a linear perfect foresight problem over T periods.
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%
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@ -76,4 +76,4 @@ end
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if nargout == 2
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iJacobian = cat(1,iJacobian{:});
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JJacobian = sparse(iJacobian(:,1), iJacobian(:,2), iJacobian(:,3), T*ny, T*ny);
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end
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end
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@ -2,12 +2,12 @@ function [residuals,JJacobian] = perfect_foresight_mcp_problem(y, dynamic_functi
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exo_simul, params, steady_state, ...
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maximum_lag, T, ny, i_cols, ...
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i_cols_J1, i_cols_1, i_cols_T, ...
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i_cols_j, i_cols_0,i_cols_J0, nnzJ,eq_index)
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i_cols_j, i_cols_0,i_cols_J0, eq_index)
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% function [residuals,JJacobian] = perfect_foresight_mcp_problem(y, dynamic_function, Y0, YT, ...
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% exo_simul, params, steady_state, ...
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% maximum_lag, T, ny, i_cols, ...
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% i_cols_J1, i_cols_1, i_cols_T, ...
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% i_cols_j,nnzJ,eq_index)
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% i_cols_j,eq_index)
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% Computes the residuals and the Jacobian matrix for a perfect foresight problem over T periods
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% in a mixed complementarity problem context
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%
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@ -33,7 +33,6 @@ function [residuals,JJacobian] = perfect_foresight_mcp_problem(y, dynamic_functi
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% variables (relevant in last period)
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% i_cols_j [double] indices of variables in M.lead_lag_incidence
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% in dynamic Jacobian (relevant in intermediate periods)
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% nnzJ [scalar] number of non-zero elements in Jacobian
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% eq_index [double] N*1 array, index vector describing residual mapping resulting
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% from complementarity setup
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% OUTPUTS
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@ -45,7 +44,7 @@ function [residuals,JJacobian] = perfect_foresight_mcp_problem(y, dynamic_functi
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% SPECIAL REQUIREMENTS
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% None.
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% Copyright (C) 1996-2017 Dynare Team
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% Copyright (C) 1996-2019 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -106,4 +105,4 @@ end
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if nargout == 2
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iJacobian = cat(1,iJacobian{:});
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JJacobian = sparse(iJacobian(:,1),iJacobian(:,2),iJacobian(:,3),T*ny,T*ny);
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end
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end
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@ -2,7 +2,7 @@ function [residuals,JJacobian] = perfect_foresight_problem(y, dynamic_function,
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exo_simul, params, steady_state, ...
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maximum_lag, T, ny, i_cols, ...
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i_cols_J1, i_cols_1, i_cols_T, ...
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i_cols_j, i_cols_0, i_cols_J0, nnzJ)
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i_cols_j, i_cols_0, i_cols_J0)
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% Computes the residuals and the Jacobian matrix for a perfect foresight problem over T periods.
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%
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@ -31,7 +31,6 @@ function [residuals,JJacobian] = perfect_foresight_problem(y, dynamic_function,
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% - i_cols_0 [double] indices of contemporaneous variables in M.lead_lag_incidence in dynamic
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% Jacobian (relevant in problems with periods=1)
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% - i_cols_J0 [double] indices of contemporaneous variables appearing in M.lead_lag_incidence (relevant in problems with periods=1)
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% - nnzJ [scalar] number of non-zero elements in Jacobian
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%
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% OUTPUTS
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% - residuals [double] (N*T)*1 array, residuals of the stacked problem
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@ -100,4 +99,4 @@ end
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if nargout == 2
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iJacobian = cat(1,iJacobian{:});
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JJacobian = sparse(iJacobian(:,1), iJacobian(:,2), iJacobian(:,3), T*ny, T*ny);
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end
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end
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@ -12,7 +12,7 @@ function perfect_foresight_solver()
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% SPECIAL REQUIREMENTS
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% none
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% Copyright (C) 1996-2018 Dynare Team
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% Copyright (C) 1996-2019 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -195,8 +195,7 @@ if ~isreal(oo_.endo_simul(:)) % can only happen without bytecode
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residuals = perfect_foresight_problem(yy(:),str2func([M_.fname '.dynamic']), y0, yT, ...
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oo_.exo_simul,M_.params,oo_.steady_state, ...
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M_.maximum_lag, periods, M_.endo_nbr, i_cols, ...
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i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0, ...
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M_.NNZDerivatives(1));
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i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0);
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if max(abs(residuals))< options_.dynatol.f
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oo_.deterministic_simulation.status = 1;
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oo_.endo_simul=real(oo_.endo_simul);
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@ -223,4 +222,4 @@ else
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end
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ts = dseries(transpose(oo_.endo_simul), initial_period, M_.endo_names);
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assignin('base', 'Simulated_time_series', ts);
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assignin('base', 'Simulated_time_series', ts);
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@ -144,8 +144,7 @@ if nargout>1
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residuals = perfect_foresight_problem(yy(:),str2func([M_.fname '.dynamic']), y0, yT, ...
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oo_.exo_simul,M_.params,oo_.steady_state, ...
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M_.maximum_lag, periods,M_.endo_nbr,i_cols, ...
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i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0, ...
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M_.NNZDerivatives(1));
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i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0);
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end
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maxerror = max(max(abs(residuals)));
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end
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@ -1,6 +1,6 @@
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function [endogenousvariables, info] = solve_stacked_linear_problem(endogenousvariables, exogenousvariables, steadystate_y, steadystate_x, M, options)
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% Copyright (C) 2015-2017 Dynare Team
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% Copyright (C) 2015-2019 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -46,7 +46,7 @@ x = bsxfun(@minus, exogenousvariables, steadystate_x');
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x, M.params, steadystate_y, ...
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M.maximum_lag, options.periods, M.endo_nbr, i_cols, ...
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i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0, ...
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M.NNZDerivatives(1), jendo, jexog);
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jendo, jexog);
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if all(imag(y)<.1*options.dynatol.x)
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if ~isreal(y)
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@ -62,4 +62,4 @@ if check
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info.status = false;
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else
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info.status = true;
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end
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end
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@ -51,14 +51,13 @@ if (options.solve_algo == 10 || options.solve_algo == 11)% mixed complementarity
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exogenousvariables, M.params, steadystate, ...
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M.maximum_lag, options.periods, M.endo_nbr, i_cols, ...
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i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0, ...
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M.NNZDerivatives(1),eq_index);
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eq_index);
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else
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[y, check] = dynare_solve(@perfect_foresight_problem,z(:),options, ...
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dynamicmodel, y0, yT, ...
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exogenousvariables, M.params, steadystate, ...
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M.maximum_lag, options.periods, M.endo_nbr, i_cols, ...
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i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0, ...
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M.NNZDerivatives(1));
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i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0);
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end
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if all(imag(y)<.1*options.dynatol.x)
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@ -75,4 +74,4 @@ if check
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info.status = false;
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else
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info.status = true;
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end
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end
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