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1) Detailed Sensitivity plots moved under the advanced option; 

2) Fixes around saving figures;
time-shift
Marco Ratto 2011-05-30 14:38:43 +02:00
parent 58dc9557d9
commit 338fdf216c
1 changed files with 55 additions and 28 deletions
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83
matlab/plot_identification.m
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@ -52,7 +52,7 @@ siLREnorm = idelre.siLREnorm;
% else
% tittxt = '';
% end
tittxt1=regexprep(tittxt, ' ', '_');
if SampleSize == 1,
siJ = idemoments.siJ;
normJ = max(abs(siJ)')';
@ -69,38 +69,59 @@ if SampleSize == 1,
end
legend('relative to param value','relative to prior std','Location','Best')
if idehess.flag_score,
title('Identification strength in the asymptotic Information matrix (log-scale)')
title('Identification strength with asymptotic Information matrix (log-scale)')
else
title('Identification strength in the moments (log-scale)')
title('Identification strength with moments Information matrix (log-scale)')
end
subplot(212)
mmm = (siJnorm)'./max(siJnorm);
if advanced,
mmm1 = (siHnorm)'./max(siHnorm);
mmm=[mmm mmm1];
mmm1 = (siLREnorm)'./max(siLREnorm);
offset=length(siHnorm)-length(siLREnorm);
mmm1 = [NaN(offset,1); mmm1];
mmm=[mmm mmm1];
end
bar(mmm(is,:))
bar(log([idehess.deltaM(is) idehess.deltaM_prior(is)]))
set(gca,'xlim',[0 nparam+1])
set(gca,'xticklabel','')
dy = get(gca,'ylim');
for ip=1:nparam,
text(ip,dy(1),name{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
if advanced,
legend('Moments','Model','LRE model','Location','Best')
legend('relative to param value','relative to prior std','Location','Best')
if idehess.flag_score,
title('Sensitivity component with asymptotic Information matrix (log-scale)')
else
title('Sensitivity component with moments Information matrix (log-scale)')
end
title('Sensitivity bars')
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_ident_strength_',tittxt1])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_strength_' tittxt1]);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_strength_' tittxt1]);
if advanced
if advanced,
disp(' ')
disp('Press ENTER to display advanced diagnostics'), pause,
figure('Name',[tittxt, ' - Sensitivity plot']),
subplot(211)
mmm = (siJnorm)'./max(siJnorm);
mmm1 = (siHnorm)'./max(siHnorm);
mmm=[mmm mmm1];
mmm1 = (siLREnorm)'./max(siLREnorm);
offset=length(siHnorm)-length(siLREnorm);
mmm1 = [NaN(offset,1); mmm1];
mmm=[mmm mmm1];
bar(log(mmm(is,:).*100))
set(gca,'xlim',[0 nparam+1])
set(gca,'xticklabel','')
dy = get(gca,'ylim');
for ip=1:nparam,
text(ip,dy(1),name{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
if advanced,
legend('Moments','Model','LRE model','Location','Best')
end
title('Sensitivity bars using derivatives (log-scale)')
if save_figure
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_sensitivity_',tittxt1])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_sensitivity_' tittxt1]);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_sensitivity_' tittxt1]);
end
% identificaton patterns
for j=1:size(idemoments.cosnJ,2),
pax=NaN(nparam,nparam);
@ -138,10 +159,11 @@ if SampleSize == 1,
end
set(gca,'xgrid','on')
set(gca,'ygrid','on')
xlabel([tittxt,' - Collinearity patterns with ', int2str(j) ,' parameter(s)'])
if save_figure
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_ident_collinearity_', int2str(j)])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_collinearity_', int2str(j)]);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_collinearity_', int2str(j)]);
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_ident_collinearity_', tittxt1, '_', int2str(j)])
eval(['print -depsc ' IdentifDirectoryName '/' M_.fname '_ident_collinearity_' tittxt1 '_' int2str(j)]);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_collinearity_' tittxt1 '_' int2str(j)]);
if options_.nograph, close(gcf); end
end
end
@ -189,20 +211,21 @@ if SampleSize == 1,
end
if save_figure,
figure(f1);
saveas(f1,[IdentifDirectoryName,'/',M_.fname,'_ident_pattern_1'])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_pattern_1']);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_pattern_1']);
saveas(f1,[IdentifDirectoryName,'/',M_.fname,'_ident_pattern_',tittxt1,'_1'])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_1']);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_1']);
if nparam>4,
figure(f2),
saveas(f2,[IdentifDirectoryName,'/',M_.fname,'_ident_pattern_2'])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_pattern_2']);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_pattern_2']);
saveas(f2,[IdentifDirectoryName,'/',M_.fname,'_ident_pattern_',tittxt1,'_2'])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_2']);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_2']);
end
end
end
else
figure('Name',['MC sensitivities']),
subplot(211)
mmm = (idehess.ide_strength_J);
[ss, is] = sort(mmm);
mmm = mean(siJnorm)';
@ -227,6 +250,10 @@ else
legend('Moments','Model','LRE model','Location','Best')
end
title('MC mean of sensitivity measures')
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_MC_sensitivity'])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_MC_sensitivity']);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_MC_sensitivity']);
if options_.nograph, close(gcf); end
if advanced,
disp(' ')
disp('Press ENTER to display advanced diagnostics'), pause,