Save conditional forecast output in oo_. Closes: Dynare/dynare#1672

doc/manual/source/the-model-file.rst

@@ -7675,9 +7675,7 @@ the :comm:`bvar_forecast` command.
 
     *Output*
 
-    The results are not stored in the ``oo_`` structure but in a
+    The results are stored in ``oo_.conditional_forecast``, which is described below.
-    separate structure ``forecasts``, described below, saved to the
-    hard disk into a file called ``conditional_forecasts.mat.``
 
     *Example*
 
@@ -7702,7 +7700,7 @@ the :comm:`bvar_forecast` command.
             plot_conditional_forecast(periods = 10) a y;
 
 
-    .. matvar:: forecasts.cond
+    .. matvar:: oo_.conditional_forecast.cond
 
         Variable set by the ``conditional_forecast`` command. It
         stores the conditional forecasts. Fields are ``periods+1`` by
@@ -7710,7 +7708,7 @@ the :comm:`bvar_forecast` command.
         subsequent ``periods`` forecasts periods. Fields are of the
         form::
 
-            forecasts.cond.FORECAST_MOMENT.VARIABLE_NAME
+            oo_.conditional_forecast.cond.FORECAST_MOMENT.VARIABLE_NAME
 
         where FORECAST_MOMENT is one of the following:
 
@@ -7724,12 +7722,12 @@ the :comm:`bvar_forecast` command.
                 distribution. The size corresponds to ``conf_sig``.
 
 
-    .. matvar:: forecasts.uncond
+    .. matvar:: oo_.conditional_forecast.uncond
 
         Variable set by the ``conditional_forecast`` command. It stores
         the unconditional forecasts. Fields are of the form::
 
-            forecasts.uncond.FORECAST_MOMENT.VARIABLE_NAME
+            oo_.conditional_forecast.uncond.FORECAST_MOMENT.VARIABLE_NAME
 
 
     .. matvar:: forecasts.instruments
@@ -7738,14 +7736,14 @@ the :comm:`bvar_forecast` command.
         the names of the exogenous instruments.
 
 
-    .. matvar:: forecasts.controlled_variables
+    .. matvar:: oo_.conditional_forecast.controlled_variables
 
         Variable set by the ``conditional_forecast`` command. Stores
         the position of the constrained endogenous variables in
         declaration order.
 
 
-    .. matvar:: forecasts.controlled_exo_variables
+    .. matvar:: oo_.conditional_forecast.controlled_exo_variables
 
         Variable set by the ``conditional_forecast`` command. Stores
         the values of the controlled exogenous variables underlying
@@ -7753,9 +7751,9 @@ the :comm:`bvar_forecast` command.
         endogenous variables. Fields are ``[number of constrained
         periods]`` by ``1`` vectors and are of the form::
 
-            forecasts.controlled_exo_variables.FORECAST_MOMENT.SHOCK_NAME
+            oo_.conditional_forecast.controlled_exo_variables.FORECAST_MOMENT.SHOCK_NAME
 
-    .. matvar:: forecasts.graphs
+    .. matvar:: oo_.conditional_forecast.graphs
 
         Variable set by the ``conditional_forecast`` command. Stores
         the information for generating the conditional forecast plots.

matlab/imcforecast.m

@@ -25,10 +25,10 @@ function imcforecast(constrained_paths, constrained_vars, options_cond_fcst)
 % This routine has to be called after an estimation statement or an estimated_params block.
 %
 % REMARKS
-% [1] Results are stored in a structure which is saved in a mat file called conditional_forecasts.mat.
+% [1] Results are stored in oo_.conditional_forecast.
 % [2] Use the function plot_icforecast to plot the results.
 
-% Copyright (C) 2006-2018 Dynare Team
+% Copyright (C) 2006-2019 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -310,5 +310,4 @@ forecasts.graph.fname = M_.fname;
 
 %reset qz_criterium
 options_.qz_criterium=qz_criterium_old;
-
+oo_.conditional_forecast = forecasts;
-save('conditional_forecasts.mat','forecasts');

matlab/plot_icforecast.m

@@ -1,8 +1,11 @@
-function plot_icforecast(Variables,periods,options_)
+function plot_icforecast(Variables,periods,options_,oo_)
 % Build plots for the conditional forecasts.
 %
 % INPUTS
-%  o Variables     [cell]        names of the endogenous variables to be plotted.
+%  o Variables     [cell]        Names of the endogenous variables to be plotted.
+%  o periods       [int]         Number of periods to be plotted.
+%  o options_      [structure]   Options.
+%  o oo_           [structure]   Storage of results.
 %
 % OUTPUTS
 %  None.
@@ -10,7 +13,7 @@ function plot_icforecast(Variables,periods,options_)
 % SPECIAL REQUIREMENTS
 %  This routine has to be called after imcforecast.m.
 
-% Copyright (C) 2006-2018 Dynare Team
+% Copyright (C) 2006-2019 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -27,7 +30,11 @@ function plot_icforecast(Variables,periods,options_)
 % You should have received a copy of the GNU General Public License
 % along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
 
-load conditional_forecasts;
+if ~isfield(oo_, 'conditional_forecast')
+    error('Can''t find conditional forecasts');
+else
+    forecasts = oo_.conditional_forecast;
+end
 
 forecast_periods = length(forecasts.cond.Mean.(Variables{1}));
 if nargin==1 || isempty(periods) % Set default number of periods.

tests/conditional_forecasts/3/fs2000_conditional_forecast_initval.mod

@@ -85,8 +85,8 @@ plot_conditional_forecast(periods=100) gy_obs gp_obs k;
 forecast(periods=100);
 
 %compare unconditional forecasts
-cond_forecast=load('conditional_forecasts.mat');
+cond_forecast=oo_.conditional_forecast;
-if max(abs(cond_forecast.forecasts.uncond.Mean.k(2:end)-oo_.forecast.Mean.k))>1e-8
+if max(abs(cond_forecast.uncond.Mean.k(2:end)-oo_.forecast.Mean.k))>1e-8
     error('Unconditional Forecasts do not match')
 end
         
@@ -94,11 +94,11 @@ end
 %conditions need to be set with histval; 
 initial_condition_states = oo_.dr.ys; 
 shock_matrix = zeros(options_cond_fcst_.periods ,M_.exo_nbr); %create shock matrix with found controlled shocks
-shock_matrix(1:5,strmatch('e_a',M_.exo_names,'exact')) = cond_forecast.forecasts.controlled_exo_variables.Mean.e_a; %set controlled shocks to their values
+shock_matrix(1:5,strmatch('e_a',M_.exo_names,'exact')) = cond_forecast.controlled_exo_variables.Mean.e_a; %set controlled shocks to their values
-shock_matrix(1:5,strmatch('e_m',M_.exo_names,'exact')) = cond_forecast.forecasts.controlled_exo_variables.Mean.e_m; %set controlled shocks to their values
+shock_matrix(1:5,strmatch('e_m',M_.exo_names,'exact')) = cond_forecast.controlled_exo_variables.Mean.e_m; %set controlled shocks to their values
 
 y_simult = simult_(M_,options_,initial_condition_states,oo_.dr,shock_matrix,1);
 
-if max(abs(y_simult(strmatch('k',M_.endo_names,'exact'),:)'-cond_forecast.forecasts.cond.Mean.k))>1e-8
+if max(abs(y_simult(strmatch('k',M_.endo_names,'exact'),:)'-cond_forecast.cond.Mean.k))>1e-8
     error('Unconditional Forecasts do not match')
 end

tests/conditional_forecasts/4/fs2000_conditional_forecast_histval.mod

@@ -86,8 +86,8 @@ plot_conditional_forecast(periods=100) gy_obs gp_obs k;
 forecast(periods=100);
 
 %compare unconditional forecasts
-cond_forecast=load('conditional_forecasts.mat');
+cond_forecast=oo_.conditional_forecast;
-if max(abs(cond_forecast.forecasts.uncond.Mean.k(2:end)-oo_.forecast.Mean.k))>1e-8
+if max(abs(cond_forecast.uncond.Mean.k(2:end)-oo_.forecast.Mean.k))>1e-8
     error('Unconditional Forecasts do not match')
 end
         
@@ -95,11 +95,11 @@ end
 initial_condition_states = oo_.dr.ys;
 initial_condition_states(strmatch('k',M_.endo_names,'exact')) = 6;
 shock_matrix = zeros(options_cond_fcst_.periods ,M_.exo_nbr); %create shock matrix with found controlled shocks
-shock_matrix(1:5,strmatch('e_a',M_.exo_names,'exact')) = cond_forecast.forecasts.controlled_exo_variables.Mean.e_a; %set controlled shocks to their values
+shock_matrix(1:5,strmatch('e_a',M_.exo_names,'exact')) = cond_forecast.controlled_exo_variables.Mean.e_a; %set controlled shocks to their values
-shock_matrix(1:5,strmatch('e_m',M_.exo_names,'exact')) = cond_forecast.forecasts.controlled_exo_variables.Mean.e_m; %set controlled shocks to their values
+shock_matrix(1:5,strmatch('e_m',M_.exo_names,'exact')) = cond_forecast.controlled_exo_variables.Mean.e_m; %set controlled shocks to their values
 
 y_simult = simult_(M_,options_,initial_condition_states,oo_.dr,shock_matrix,1);
 
-if max(abs(y_simult(strmatch('k',M_.endo_names,'exact'),:)'-cond_forecast.forecasts.cond.Mean.k))>1e-8
+if max(abs(y_simult(strmatch('k',M_.endo_names,'exact'),:)'-cond_forecast.cond.Mean.k))>1e-8
     error('Unconditional Forecasts do not match')
 end

tests/loglinear/example4_exp.mod

@@ -77,6 +77,5 @@ end;
 conditional_forecast(parameter_set=calibration, controlled_varexo=(u,e));
 
 oo_exp=oo_;
-load('conditional_forecasts.mat')
+conditional_forecasts_exp=oo_.conditional_forecast;
-conditional_forecasts_exp=forecasts;
 save results_exp.mat oo_exp conditional_forecasts_exp

tests/loglinear/example4_exp_histval.mod

@@ -85,8 +85,7 @@ end;
 conditional_forecast(parameter_set=calibration, controlled_varexo=(u,e));
 
 oo_exp=oo_;
-load('conditional_forecasts.mat')
+conditional_forecasts_exp=oo_.conditional_forecast;
-conditional_forecasts_exp=forecasts;
 
 oo_exp=oo_;
 save results_exp_histval.mat oo_exp conditional_forecasts_exp

tests/loglinear/example4_loglinear.mod

@@ -118,7 +118,7 @@ if max(max(abs(struct2array(oo_.forecast.Mean)-struct2array(oo_exp.forecast.Mean
     error('Option loglinear wrong, forecast not equal')
 end
 
-load('conditional_forecasts.mat')
+forecasts=oo_.conditional_forecast;
 
 if max(max(abs(struct2array(forecasts.cond.Mean)-struct2array(conditional_forecasts_exp.cond.Mean))))>1e-10 || ...
     max(max(abs(struct2array(forecasts.cond.ci)-struct2array(conditional_forecasts_exp.cond.ci))))>1e-10 || ...

tests/loglinear/example4_loglinear_histval.mod

@@ -114,7 +114,7 @@ end;
 conditional_forecast(parameter_set=calibration, controlled_varexo=(u,e));
 
 
-load('conditional_forecasts.mat')
+forecasts=oo_.conditional_forecast;
 
 if max(max(abs(struct2array(forecasts.cond.Mean)-struct2array(conditional_forecasts_exp.cond.Mean))))>1e-10 || ...
     max(max(abs(struct2array(forecasts.cond.ci)-struct2array(conditional_forecasts_exp.cond.ci))))>1e-10 || ...

tests/observation_trends_and_prefiltering/Trend_no_prefilter_conditional_forecast.inc

@@ -12,8 +12,8 @@ conditional_forecast(periods=100,parameter_set=posterior_mode,replic=1000, contr
 plot_conditional_forecast(periods=100) Y_obs P_obs;
 
 %compare unconditional forecasts
-cond_forecast=load('conditional_forecasts.mat');
+cond_forecast=oo_.conditional_forecast;
-if max(abs(cond_forecast.forecasts.uncond.Mean.P_obs(2:end)-oo_.forecast.Mean.P_obs))>1e-8
+if max(abs(cond_forecast.uncond.Mean.P_obs(2:end)-oo_.forecast.Mean.P_obs))>1e-8
     error('Unconditional Forecasts do not match')
 end
         
@@ -24,16 +24,16 @@ initial_condition_states(strmatch('P_obs',M_.endo_names,'exact')) = oo_.Smoothed
 initial_condition_states(strmatch('junk1',M_.endo_names,'exact')) = oo_.SmoothedVariables.junk1(end);
 initial_condition_states(strmatch('junk2',M_.endo_names,'exact')) = oo_.SmoothedVariables.junk2(end)-oo_.Smoother.Trend.junk2(end);
 shock_matrix = zeros(options_cond_fcst_.periods ,M_.exo_nbr); %create shock matrix with found controlled shocks
-shock_matrix(1:5,strmatch('e_y',M_.exo_names,'exact')) = cond_forecast.forecasts.controlled_exo_variables.Mean.e_y; %set controlled shocks to their values
+shock_matrix(1:5,strmatch('e_y',M_.exo_names,'exact')) = cond_forecast.controlled_exo_variables.Mean.e_y; %set controlled shocks to their values
-shock_matrix(1:5,strmatch('e_p',M_.exo_names,'exact')) = cond_forecast.forecasts.controlled_exo_variables.Mean.e_p; %set controlled shocks to their values
+shock_matrix(1:5,strmatch('e_p',M_.exo_names,'exact')) = cond_forecast.controlled_exo_variables.Mean.e_p; %set controlled shocks to their values
 
 y_simult = simult_(M_,options_,initial_condition_states,oo_.dr,shock_matrix,1);
 
-if max(abs(y_simult(strmatch('Y_obs',M_.endo_names,'exact'),:)'+(options_.first_obs-1+options_.nobs:options_.first_obs-1+options_.nobs+options_.forecast)'*g_y-cond_forecast.forecasts.cond.Mean.Y_obs))>1e-8
+if max(abs(y_simult(strmatch('Y_obs',M_.endo_names,'exact'),:)'+(options_.first_obs-1+options_.nobs:options_.first_obs-1+options_.nobs+options_.forecast)'*g_y-cond_forecast.cond.Mean.Y_obs))>1e-8
     error('Conditional Forecasts do not match')
 end
 
-if max(abs(y_simult(strmatch('P_obs',M_.endo_names,'exact'),:)'+(options_.first_obs-1+options_.nobs:options_.first_obs-1+options_.nobs+options_.forecast)'*g_p-cond_forecast.forecasts.cond.Mean.P_obs))>1e-8
+if max(abs(y_simult(strmatch('P_obs',M_.endo_names,'exact'),:)'+(options_.first_obs-1+options_.nobs:options_.first_obs-1+options_.nobs+options_.forecast)'*g_p-cond_forecast.cond.Mean.P_obs))>1e-8
     error('Conditional Forecasts do not match')
 end