Commit 757a9067 authored by Sébastien Villemot's avatar Sébastien Villemot
Browse files

Global reindentation of MATLAB files

parent 2b8b32a2
This diff is collapsed.
......@@ -166,7 +166,7 @@ if kalman_algo == 1 || kalman_algo == 3
end
end
end
if kalman_algo == 2 || kalman_algo == 4
if estim_params_.ncn
ST = [ zeros(nobs,nobs) Z; zeros(np,nobs) T];
......@@ -180,7 +180,7 @@ if kalman_algo == 2 || kalman_algo == 4
end
[alphahat,epsilonhat,etahat,ahat,P,aK,PK,d,decomp] = missing_DiffuseKalmanSmootherH3_Z(ST, ...
Z,R1,Q,diag(H),Pinf,Pstar,data1,nobs,np,smpl,data_index);
Z,R1,Q,diag(H),Pinf,Pstar,data1,nobs,np,smpl,data_index);
end
if kalman_algo == 3 || kalman_algo == 4
......@@ -218,7 +218,7 @@ if estim_params_.ncn && (kalman_algo == 2 || kalman_algo == 4)
P = P(k,k,:);
end
end
% $$$ if any(any(H ~= 0)) % should be replaced by a flag
% $$$ if kalman_algo == 1
% $$$ [alphahat,epsilonhat,etahat,ahat,P,aK,PK,decomp] = ...
......
......@@ -110,7 +110,7 @@ if isnumeric(options_.parallel),
fout = McMCDiagnostics_core(localVars,1,npar,0);
UDIAG = fout.UDIAG;
clear fout
% Parallel execution!
% Parallel execution!
else
ModelName = M_.fname;
if ~isempty(M_.bvar)
......
......@@ -85,17 +85,17 @@ for j=fpar:npar,
for n = 1:NumberOfMcFilesPerBlock
%load([MhDirectoryName '/' mcfiles(n,1,b).name],'x2');
load([MhDirectoryName '/' M_.fname '_mh',int2str(n),'_blck' int2str(b) ...
'.mat'],'x2');
'.mat'],'x2');
nx2 = size(x2,1);
tmp((b-1)*NumberOfDraws+startline+(1:nx2),1) = x2(:,j);
% clear x2;
startline = startline + nx2;
end
% $$$ %load([MhDirectoryName '/' mcfiles(NumberOfMcFilesPerBlock,1,b).name],'x2');
% $$$ load([MhDirectoryName '/' M_.fname '_mh',int2str(NumberOfMcFilesPerBlock),'_blck' int2str(b) '.mat'],'x2');
% $$$ tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*(LastFileNumber-1)+LastLineNumber,1) = x2(:,j);
% $$$ clear x2;
% $$$ startline = startline + LastLineNumber;
% $$$ %load([MhDirectoryName '/' mcfiles(NumberOfMcFilesPerBlock,1,b).name],'x2');
% $$$ load([MhDirectoryName '/' M_.fname '_mh',int2str(NumberOfMcFilesPerBlock),'_blck' int2str(b) '.mat'],'x2');
% $$$ tmp((b-1)*NumberOfDraws+startline+1:(b-1)*NumberOfDraws+MAX_nruns*(LastFileNumber-1)+LastLineNumber,1) = x2(:,j);
% $$$ clear x2;
% $$$ startline = startline + LastLineNumber;
end
tmp(:,2) = kron(transpose(1:nblck),ones(NumberOfDraws,1));
tmp(:,3) = kron(ones(nblck,1),time');
......
......@@ -100,7 +100,7 @@ else% type = 'prior'
NumberOfDraws = 500;
end
if ~strcmpi(type,'gsa')
B = min([round(.5*NumberOfDraws),500]); options_.B = B;
B = min([round(.5*NumberOfDraws),500]); options_.B = B;
end
try
delete([MhDirectoryName filesep M_.fname '_irf_dsge*.mat'])
......@@ -198,7 +198,7 @@ localVars.ifil2=ifil2;
if isnumeric(options_.parallel),
[fout] = PosteriorIRF_core1(localVars,1,B,0);
else
% Parallel execution!
% Parallel execution!
[nCPU, totCPU, nBlockPerCPU] = distributeJobs(options_.parallel, 1, B);
for j=1:totCPU-1,
nfiles = ceil(nBlockPerCPU(j)/MAX_nirfs_dsge);
......@@ -217,10 +217,10 @@ else
localVars.ifil2=ifil2;
globalVars = struct('M_',M_, ...
'options_', options_, ...
'bayestopt_', bayestopt_, ...
'estim_params_', estim_params_, ...
'oo_', oo_);
'options_', options_, ...
'bayestopt_', bayestopt_, ...
'estim_params_', estim_params_, ...
'oo_', oo_);
% which files have to be copied to run remotely
NamFileInput(1,:) = {'',[M_.fname '_static.m']};
......@@ -228,14 +228,14 @@ else
if options_.steadystate_flag,
NamFileInput(length(NamFileInput)+1,:)={'',[M_.fname '_steadystate.m']};
end
[fout] = masterParallel(options_.parallel, 1, B,NamFileInput,'PosteriorIRF_core1', localVars, globalVars, options_.parallel_info);
[fout] = masterParallel(options_.parallel, 1, B,NamFileInput,'PosteriorIRF_core1', localVars, globalVars, options_.parallel_info);
end
% END first parallel section!
if nosaddle
disp(['PosteriorIRF :: Percentage of discarded posterior draws = ' num2str(nosaddle/(B+nosaddle))])
disp(['PosteriorIRF :: Percentage of discarded posterior draws = ' num2str(nosaddle/(B+nosaddle))])
end
ReshapeMatFiles('irf_dsge')
......@@ -244,7 +244,7 @@ if MAX_nirfs_dsgevar
end
if strcmpi(type,'gsa')
return
return
end
IRF_DSGEs = dir([MhDirectoryName filesep M_.fname '_IRF_DSGEs*.mat']);
......@@ -260,13 +260,13 @@ DistribIRF = zeros(options_.irf,9,nvar,M_.exo_nbr);
HPDIRF = zeros(options_.irf,2,nvar,M_.exo_nbr);
if options_.TeX
for i=1:nvar
if i==1
varlist_TeX = M_.endo_names_tex(IndxVariables(i),:);
else
varlist_TeX = char(varlist_TeX,M_.endo_names_tex(IndxVariables(i),:));
end
end
for i=1:nvar
if i==1
varlist_TeX = M_.endo_names_tex(IndxVariables(i),:);
else
varlist_TeX = char(varlist_TeX,M_.endo_names_tex(IndxVariables(i),:));
end
end
end
fprintf('MH: Posterior (dsge) IRFs...\n');
......@@ -274,32 +274,32 @@ tit(M_.exo_names_orig_ord,:) = M_.exo_names;
kdx = 0;
for file = 1:NumberOfIRFfiles_dsge
load([MhDirectoryName filesep M_.fname '_IRF_DSGEs' int2str(file) '.mat']);
for i = 1:M_.exo_nbr
for j = 1:nvar
for k = 1:size(STOCK_IRF_DSGE,1)
kk = k+kdx;
[MeanIRF(kk,j,i),MedianIRF(kk,j,i),VarIRF(kk,j,i),HPDIRF(kk,:,j,i),...
DistribIRF(kk,:,j,i)] = posterior_moments(squeeze(STOCK_IRF_DSGE(k,j,i,:)),0,options_.mh_conf_sig);
load([MhDirectoryName filesep M_.fname '_IRF_DSGEs' int2str(file) '.mat']);
for i = 1:M_.exo_nbr
for j = 1:nvar
for k = 1:size(STOCK_IRF_DSGE,1)
kk = k+kdx;
[MeanIRF(kk,j,i),MedianIRF(kk,j,i),VarIRF(kk,j,i),HPDIRF(kk,:,j,i),...
DistribIRF(kk,:,j,i)] = posterior_moments(squeeze(STOCK_IRF_DSGE(k,j,i,:)),0,options_.mh_conf_sig);
end
end
end
end
kdx = kdx + size(STOCK_IRF_DSGE,1);
kdx = kdx + size(STOCK_IRF_DSGE,1);
end
clear STOCK_IRF_DSGE;
for i = 1:M_.exo_nbr
for j = 1:nvar
name = [deblank(M_.endo_names(IndxVariables(j),:)) '_' deblank(tit(i,:))];
eval(['oo_.PosteriorIRF.dsge.Mean.' name ' = MeanIRF(:,j,i);']);
eval(['oo_.PosteriorIRF.dsge.Median.' name ' = MedianIRF(:,j,i);']);
eval(['oo_.PosteriorIRF.dsge.Var.' name ' = VarIRF(:,j,i);']);
eval(['oo_.PosteriorIRF.dsge.Distribution.' name ' = DistribIRF(:,:,j,i);']);
eval(['oo_.PosteriorIRF.dsge.HPDinf.' name ' = HPDIRF(:,1,j,i);']);
eval(['oo_.PosteriorIRF.dsge.HPDsup.' name ' = HPDIRF(:,2,j,i);']);
end
for j = 1:nvar
name = [deblank(M_.endo_names(IndxVariables(j),:)) '_' deblank(tit(i,:))];
eval(['oo_.PosteriorIRF.dsge.Mean.' name ' = MeanIRF(:,j,i);']);
eval(['oo_.PosteriorIRF.dsge.Median.' name ' = MedianIRF(:,j,i);']);
eval(['oo_.PosteriorIRF.dsge.Var.' name ' = VarIRF(:,j,i);']);
eval(['oo_.PosteriorIRF.dsge.Distribution.' name ' = DistribIRF(:,:,j,i);']);
eval(['oo_.PosteriorIRF.dsge.HPDinf.' name ' = HPDIRF(:,1,j,i);']);
eval(['oo_.PosteriorIRF.dsge.HPDsup.' name ' = HPDIRF(:,2,j,i);']);
end
end
......@@ -340,7 +340,7 @@ if MAX_nirfs_dsgevar
end
end
%%
%% Finally I build the plots.
%% Finally I build the plots.
%%
......@@ -352,11 +352,11 @@ end
% Save the local variables.
localVars=[];
Check=options_.TeX;
if (Check)
localVars.varlist_TeX=varlist_TeX;
end
Check=options_.TeX;
if (Check)
localVars.varlist_TeX=varlist_TeX;
end
localVars.nvar=nvar;
localVars.MeanIRF=MeanIRF;
......@@ -374,57 +374,57 @@ end
%%% The files .TeX are genereted in sequential way always!
if options_.TeX
fidTeX = fopen([DirectoryName filesep M_.fname '_BayesianIRF.TeX'],'w');
fprintf(fidTeX,'%% TeX eps-loader file generated by PosteriorIRF.m (Dynare).\n');
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
fprintf(fidTeX,' \n');
titTeX(M_.exo_names_orig_ord,:) = M_.exo_names_tex;
for i=1:M_.exo_nbr
fidTeX = fopen([DirectoryName filesep M_.fname '_BayesianIRF.TeX'],'w');
fprintf(fidTeX,'%% TeX eps-loader file generated by PosteriorIRF.m (Dynare).\n');
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
fprintf(fidTeX,' \n');
titTeX(M_.exo_names_orig_ord,:) = M_.exo_names_tex;
for i=1:M_.exo_nbr
NAMES = [];
TEXNAMES = [];
for j=1:nvar
if max(abs(MeanIRF(:,j,i))) > 10^(-6)
name = deblank(varlist(j,:));
texname = deblank(varlist_TeX(j,:));
if j==1
NAMES = name;
TEXNAMES = ['$' texname '$'];
else
NAMES = char(NAMES,name);
TEXNAMES = char(TEXNAMES,['$' texname '$']);
end
end
end
fprintf(fidTeX,'\\begin{figure}[H]\n');
for jj = 1:size(TEXNAMES,1)
fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
end
fprintf(fidTeX,'\\centering \n');
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_Bayesian_IRF_%s}\n',M_.fname,deblank(tit(i,:)));
if options_.relative_irf
fprintf(fidTeX,['\\caption{Bayesian relative IRF.}']);
else
fprintf(fidTeX,'\\caption{Bayesian IRF.}');
if max(abs(MeanIRF(:,j,i))) > 10^(-6)
name = deblank(varlist(j,:));
texname = deblank(varlist_TeX(j,:));
if j==1
NAMES = name;
TEXNAMES = ['$' texname '$'];
else
NAMES = char(NAMES,name);
TEXNAMES = char(TEXNAMES,['$' texname '$']);
end
end
fprintf(fidTeX,'\\label{Fig:BayesianIRF:%s}\n',deblank(tit(i,:)));
fprintf(fidTeX,'\\end{figure}\n');
fprintf(fidTeX,' \n');
end
fprintf(fidTeX,'%% End of TeX file.\n');
fclose(fidTeX);
end
fprintf(fidTeX,'\\begin{figure}[H]\n');
for jj = 1:size(TEXNAMES,1)
fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
end
fprintf(fidTeX,'\\centering \n');
fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_Bayesian_IRF_%s}\n',M_.fname,deblank(tit(i,:)));
if options_.relative_irf
fprintf(fidTeX,['\\caption{Bayesian relative IRF.}']);
else
fprintf(fidTeX,'\\caption{Bayesian IRF.}');
end
fprintf(fidTeX,'\\label{Fig:BayesianIRF:%s}\n',deblank(tit(i,:)));
fprintf(fidTeX,'\\end{figure}\n');
fprintf(fidTeX,' \n');
end
fprintf(fidTeX,'%% End of TeX file.\n');
fclose(fidTeX);
end
% The others file format are generated in parallel by PosteriorIRF_core2!
% Comment for testing!
% Comment for testing!
if ~exist('OCTAVE_VERSION')
if isnumeric(options_.parallel) || (M_.exo_nbr*ceil(size(varlist,1)/MaxNumberOfPlotPerFigure))<8,
[fout] = PosteriorIRF_core2(localVars,1,M_.exo_nbr,0);
......
......@@ -184,10 +184,10 @@ while fpar<npar
while explosive_var
% draw from the marginal posterior of SIGMA
SIGMAu_draw = rand_inverse_wishart(nvobs, DSGE_PRIOR_WEIGHT-NumberOfParametersPerEquation, ...
SIGMA_inv_upper_chol);
SIGMA_inv_upper_chol);
% draw from the conditional posterior of PHI
PHI_draw = rand_matrix_normal(NumberOfParametersPerEquation,nvobs, PHI, ...
chol(SIGMAu_draw)', chol(iXX)');
chol(SIGMAu_draw)', chol(iXX)');
Companion_matrix(1:nvobs,:) = transpose(PHI_draw(1:NumberOfLagsTimesNvobs,:));
% Check for stationarity
explosive_var = any(abs(eig(Companion_matrix))>1.000000001);
......@@ -222,7 +222,7 @@ while fpar<npar
else
stock_irf_bvardsge(:,:,:,IRUN) = reshape(tmp_dsgevar,options_.irf,nvobs,M_.exo_nbr);
instr = [MhDirectoryName '/' M_.fname '_irf_bvardsge' ...
int2str(NumberOfIRFfiles_dsgevar) '.mat stock_irf_bvardsge;'];,
int2str(NumberOfIRFfiles_dsgevar) '.mat stock_irf_bvardsge;'];,
eval(['save ' instr]);
if RemoteFlag==1,
OutputFileName_bvardsge = [OutputFileName_bvardsge; {[MhDirectoryName filesep], [M_.fname '_irf_bvardsge' int2str(NumberOfIRFfiles_dsgevar) '.mat']}];
......@@ -238,7 +238,7 @@ while fpar<npar
if MAX_nirfs_dsgevar & (fpar == npar | IRUN == npar)
stock_irf_bvardsge = stock_irf_bvardsge(:,:,:,1:IRUN);
instr = [MhDirectoryName '/' M_.fname '_irf_bvardsge' ...
int2str(NumberOfIRFfiles_dsgevar) '.mat stock_irf_bvardsge;'];,
int2str(NumberOfIRFfiles_dsgevar) '.mat stock_irf_bvardsge;'];,
eval(['save ' instr]);
NumberOfIRFfiles_dsgevar = NumberOfIRFfiles_dsgevar+1;
if RemoteFlag==1,
......@@ -299,8 +299,8 @@ end
% directory on call machine that contain the model).
myoutput.OutputFileName = [OutputFileName_dsge;
OutputFileName_param;
OutputFileName_bvardsge];
OutputFileName_param;
OutputFileName_bvardsge];
......
......@@ -44,10 +44,10 @@ end
% In order to avoid confusion in the name space, the instruction struct2local(myinputs) is replaced by:
Check=options_.TeX;
if (Check)
varlist_TeX=myinputs.varlist_TeX;
end
if (Check)
varlist_TeX=myinputs.varlist_TeX;
end
nvar=myinputs.nvar;
MeanIRF=myinputs.MeanIRF;
tit=myinputs.tit;
......@@ -64,7 +64,7 @@ MaxNumberOfPlotPerFigure=myinputs.MaxNumberOfPlotPerFigure;
% Necessary only for remote computing!
if whoiam
Parallel=myinputs.Parallel;
Parallel=myinputs.Parallel;
end
% To save the figures where the function is computed!
......@@ -87,85 +87,85 @@ OutputFileName={};
subplotnum = 0;
for i=fpar:npar,
figunumber = 0;
for j=1:nvar
if max(abs(MeanIRF(:,j,i))) > 10^(-6)
subplotnum = subplotnum+1;
if options_.nograph
if subplotnum == 1 & options_.relative_irf
hh = figure('Name',['Relative response to orthogonalized shock to ' tit(i,:)],'Visible','off');
elseif subplotnum == 1 & ~options_.relative_irf
hh = figure('Name',['Orthogonalized shock to ' tit(i,:)],'Visible','off');
figunumber = 0;
for j=1:nvar
if max(abs(MeanIRF(:,j,i))) > 10^(-6)
subplotnum = subplotnum+1;
if options_.nograph
if subplotnum == 1 & options_.relative_irf
hh = figure('Name',['Relative response to orthogonalized shock to ' tit(i,:)],'Visible','off');
elseif subplotnum == 1 & ~options_.relative_irf
hh = figure('Name',['Orthogonalized shock to ' tit(i,:)],'Visible','off');
end
else
if subplotnum == 1 & options_.relative_irf
hh = figure('Name',['Relative response to orthogonalized shock to ' tit(i,:)]);
elseif subplotnum == 1 & ~options_.relative_irf
hh = figure('Name',['Orthogonalized shock to ' tit(i,:)]);
end
end
set(0,'CurrentFigure',hh)
subplot(nn,nn,subplotnum);
if ~MAX_nirfs_dsgevar
h1 = area(1:options_.irf,HPDIRF(:,2,j,i));
set(h1,'FaceColor',[.9 .9 .9]);
set(h1,'BaseValue',min(HPDIRF(:,1,j,i)));
hold on
h2 = area(1:options_.irf,HPDIRF(:,1,j,i),'FaceColor',[1 1 1],'BaseValue',min(HPDIRF(:,1,j,i)));
set(h2,'FaceColor',[1 1 1]);
set(h2,'BaseValue',min(HPDIRF(:,1,j,i)));
plot(1:options_.irf,MeanIRF(:,j,i),'-k','linewidth',3)
% plot([1 options_.irf],[0 0],'-r','linewidth',0.5);
box on
axis tight
xlim([1 options_.irf]);
hold off
else
h1 = area(1:options_.irf,HPDIRF(:,2,j,i));
set(h1,'FaceColor',[.9 .9 .9]);
set(h1,'BaseValue',min([min(HPDIRF(:,1,j,i)),min(HPDIRFdsgevar(:,1,j,i))]));
hold on;
h2 = area(1:options_.irf,HPDIRF(:,1,j,i));
set(h2,'FaceColor',[1 1 1]);
set(h2,'BaseValue',min([min(HPDIRF(:,1,j,i)),min(HPDIRFdsgevar(:,1,j,i))]));
plot(1:options_.irf,MeanIRF(:,j,i),'-k','linewidth',3)
% plot([1 options_.irf],[0 0],'-r','linewidth',0.5);
plot(1:options_.irf,MeanIRFdsgevar(:,j,i),'--k','linewidth',2)
plot(1:options_.irf,HPDIRFdsgevar(:,1,j,i),'--k','linewidth',1)
plot(1:options_.irf,HPDIRFdsgevar(:,2,j,i),'--k','linewidth',1)
box on
axis tight
xlim([1 options_.irf]);
hold off
end
name = deblank(varlist(j,:));
title(name,'Interpreter','none')
end
else
if subplotnum == 1 & options_.relative_irf
hh = figure('Name',['Relative response to orthogonalized shock to ' tit(i,:)]);
elseif subplotnum == 1 & ~options_.relative_irf
hh = figure('Name',['Orthogonalized shock to ' tit(i,:)]);
if subplotnum == MaxNumberOfPlotPerFigure | (j == nvar & subplotnum> 0)
figunumber = figunumber+1;
set(hh,'visible','on')
eval(['print -depsc2 ' DirectoryName '/' M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber) '.eps']);
if ~exist('OCTAVE_VERSION')
eval(['print -dpdf ' DirectoryName '/' M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber)]);
saveas(hh,[DirectoryName '/' M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber) '.fig']);
end
if RemoteFlag==1,
OutputFileName = [OutputFileName; {[DirectoryName,filesep], [M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber) '.*']}];
end
set(hh,'visible','off')
if options_.nograph, close(hh), end
subplotnum = 0;
end
end
set(0,'CurrentFigure',hh)
subplot(nn,nn,subplotnum);
if ~MAX_nirfs_dsgevar
h1 = area(1:options_.irf,HPDIRF(:,2,j,i));
set(h1,'FaceColor',[.9 .9 .9]);
set(h1,'BaseValue',min(HPDIRF(:,1,j,i)));
hold on
h2 = area(1:options_.irf,HPDIRF(:,1,j,i),'FaceColor',[1 1 1],'BaseValue',min(HPDIRF(:,1,j,i)));
set(h2,'FaceColor',[1 1 1]);
set(h2,'BaseValue',min(HPDIRF(:,1,j,i)));
plot(1:options_.irf,MeanIRF(:,j,i),'-k','linewidth',3)
% plot([1 options_.irf],[0 0],'-r','linewidth',0.5);
box on
axis tight
xlim([1 options_.irf]);
hold off
else
h1 = area(1:options_.irf,HPDIRF(:,2,j,i));
set(h1,'FaceColor',[.9 .9 .9]);
set(h1,'BaseValue',min([min(HPDIRF(:,1,j,i)),min(HPDIRFdsgevar(:,1,j,i))]));
hold on;
h2 = area(1:options_.irf,HPDIRF(:,1,j,i));
set(h2,'FaceColor',[1 1 1]);
set(h2,'BaseValue',min([min(HPDIRF(:,1,j,i)),min(HPDIRFdsgevar(:,1,j,i))]));
plot(1:options_.irf,MeanIRF(:,j,i),'-k','linewidth',3)
% plot([1 options_.irf],[0 0],'-r','linewidth',0.5);
plot(1:options_.irf,MeanIRFdsgevar(:,j,i),'--k','linewidth',2)
plot(1:options_.irf,HPDIRFdsgevar(:,1,j,i),'--k','linewidth',1)
plot(1:options_.irf,HPDIRFdsgevar(:,2,j,i),'--k','linewidth',1)
box on
axis tight
xlim([1 options_.irf]);
hold off
end
name = deblank(varlist(j,:));
title(name,'Interpreter','none')
end
if subplotnum == MaxNumberOfPlotPerFigure | (j == nvar & subplotnum> 0)
figunumber = figunumber+1;
set(hh,'visible','on')
eval(['print -depsc2 ' DirectoryName '/' M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber) '.eps']);
if ~exist('OCTAVE_VERSION')
eval(['print -dpdf ' DirectoryName '/' M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber)]);
saveas(hh,[DirectoryName '/' M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber) '.fig']);
end
if RemoteFlag==1,
OutputFileName = [OutputFileName; {[DirectoryName,filesep], [M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber) '.*']}];
end
set(hh,'visible','off')
if options_.nograph, close(hh), end
subplotnum = 0;
end
end% loop over selected endo_var
end% loop over selected endo_var
if whoiam,
fprintf('Done! \n');
waitbarString = [ 'Exog. shocks ' int2str(i) '/' int2str(npar) ' done.'];
fMessageStatus((i-fpar+1)/(npar-fpar+1),whoiam,waitbarString, waitbarTitle, Parallel(ThisMatlab));
fprintf('Done! \n');
waitbarString = [ 'Exog. shocks ' int2str(i) '/' int2str(npar) ' done.'];
fMessageStatus((i-fpar+1)/(npar-fpar+1),whoiam,waitbarString, waitbarTitle, Parallel(ThisMatlab));
end
end% loop over exo_var
myoutput.OutputFileName = OutputFileName;
......
......@@ -34,8 +34,8 @@ end
for i=1:aux_lead_nbr+1;
if byte_code
[info, res] = bytecode('static','evaluate',ys1,...
[exo_steady_state; ...
exo_det_steady_state],params);
[exo_steady_state; ...
exo_det_steady_state],params);
else
res = feval([fname '_static'],ys1,...
[exo_steady_state; ...
......
......@@ -35,24 +35,24 @@ function [info] = convertAimCodeToInfo(aimCode)
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
switch aimCode
case 1
info = 0; % no problem encountered
case 2
info = 102;
case 3
info = 103;
case 35
info = 135;
case 4
info = 104;
case 45
info = 145;
case 5
info = 105;
case 61
info = 161;
case 62
info = 162;
otherwise
info = 1;
case 1
info = 0; % no problem encountered
case 2
info = 102;
case 3
info = 103;
case 35
info = 135;
case 4
info = 104;
case 45
info = 145;
case 5
info = 105;
case 61
info = 161;
case 62