Merge branch 'master' of ssh://kirikou/srv/d_kirikou/git/dynare

matlab/parallel/masterParallel.m

@@ -92,10 +92,8 @@ if nargin>8 && initialize==1
         evalin('base','clear PRCDirTmp,')
     else
         % Delete the traces (if existing) of last local session of computations.
-        if Strategy==1,
         mydelete(['slaveParallel_input*.mat']);
     end
-    end
     return
 end
 
@@ -128,12 +126,8 @@ end
 % Save input data for use by the slaves.
 switch Strategy
     case 0
-        if exist('fGlobalVar'),
-            save([fname,'_input.mat'],'fInputVar','fGlobalVar')
-        else
-            save([fname,'_input.mat'],'fInputVar')
-        end
-        save([fname,'_input.mat'],'Parallel','-append')
+        storeGlobalVars([fname,'_input.mat']);
+        save([fname,'_input.mat'],'fInputVar','Parallel','-append')
         
     case 1
         if exist('fGlobalVar'),
@@ -270,7 +264,7 @@ for j=1:totCPU,
         % are created localy, then copied in remote directory and then
         % deleted (loacal)!
         
-        save( ['slaveParallel_input',int2str(j),'.mat'],'Parallel');
+        save( ['slaveParallel_input',int2str(j),'.mat'],'j');
         
         if Parallel(indPC).Local==0,
             dynareParallelSendFiles(['P_',fname,'_',int2str(j),'End.txt'],PRCDir,Parallel(indPC));

tests/parallel/ls2003.mod

@@ -62,8 +62,8 @@ stderr e_pies,inv_gamma_pdf,1.88,0.9827;
 end;
 
 
-estimation(datafile=data_ca1,first_obs=8,nobs=79,mh_replic=0);
-estimation(datafile=data_ca1,first_obs=8,nobs=79,mode_compute=0, mode_file=ls2003_mode, mh_nblocks=4, prefilter=1, mh_jscale=0.5, mh_replic=2000);
-estimation(datafile=data_ca1,first_obs=8,nobs=79,mode_compute=0, mode_file=ls2003_mode, mh_nblocks=4,prefilter=1,mh_jscale=0.5,mh_replic=2000,bayesian_irf,load_mh_file,smoother,forecast=12, filtered_vars, filter_step_ahead=[1 2 3 4]) y y_s R pie dq pie_s de A y_obs pie_obs R_obs;
+estimation(datafile=data_ca1,first_obs=8,nobs=79,mh_replic=0,nodisplay);
+estimation(datafile=data_ca1,first_obs=8,nobs=79,mode_compute=0,nodisplay, mode_file=ls2003_mode, mh_nblocks=4, prefilter=1, mh_jscale=0.5, mh_replic=2000);
+estimation(datafile=data_ca1,first_obs=8,nobs=79,mode_compute=0,nodisplay, mode_file=ls2003_mode, mh_nblocks=4,prefilter=1,mh_jscale=0.5,mh_replic=2000,bayesian_irf,load_mh_file,smoother,forecast=12, filtered_vars, filter_step_ahead=[1 2 3 4]) y y_s R pie dq pie_s de A y_obs pie_obs R_obs;