Fixes around latex output: use of longtable for parameter estimates and various fixes for posterior analysis, also for parallel execution.
Marco Ratto
parent
5af1effd8f
commit
4480f5b494
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@ -57,7 +57,7 @@ FirstMhFile = record.KeepedDraws.FirstMhFile;
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NumberOfDraws = TotalNumberOfMhDraws-floor(options_.mh_drop*TotalNumberOfMhDraws);
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clear record;
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pnames=[' ';'beta ';'gamm ';'norm ';'invg ';'unif ';'invg2'];
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pnames=[' ';'beta ';'gamma';'norm ';'invg ';'unif ';'invg2'];
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header_width = row_header_width(M_,estim_params_,bayestopt_);
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tit2 = sprintf('%-*s %10s %10s %16s %6s %10s\n',header_width+2,' ','prior mean','post. mean','conf. interval','prior','pstdev');
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pformat = '%-*s %10.3f %10.4f %10.4f %8.4f %6s %10.4f';
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@ -103,6 +103,8 @@ if np
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pnames(bayestopt_.pshape(ip)+1,:), ...
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bayestopt_.p2(ip)));
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if TeX
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k = estim_params_.param_vals(i,1);
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name = deblank(M_.param_names_tex(k,:));
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TeXCore(fid,name,deblank(pnames(bayestopt_.pshape(ip)+1,:)),bayestopt_.p1(ip),...
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bayestopt_.p2(ip),post_mean,sqrt(post_var),hpd_interval);
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end
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@ -147,7 +149,8 @@ if nvx
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end
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disp(sprintf(pformat,header_width,name,bayestopt_.p1(ip),post_mean,hpd_interval,...
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pnames(bayestopt_.pshape(ip)+1,:),bayestopt_.p2(ip)));
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if TeX
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if TeX,
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name = deblank(M_.exo_names_tex(k,:));
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TeXCore(fid,name,deblank(pnames(bayestopt_.pshape(ip)+1,:)),bayestopt_.p1(ip),...
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bayestopt_.p2(ip),post_mean,sqrt(post_var),hpd_interval);
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end
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@ -188,6 +191,8 @@ if nvn
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disp(sprintf(pformat,header_width,name,bayestopt_.p1(ip),post_mean,hpd_interval, ...
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pnames(bayestopt_.pshape(ip)+1,:),bayestopt_.p2(ip)));
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if TeX
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k = estim_params_.var_endo(i,1);
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name = deblank(M_.endo_names_tex(k,:));
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TeXCore(fid,name,deblank(pnames(bayestopt_.pshape(ip)+1,:)),bayestopt_.p1(ip),...
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bayestopt_.p2(ip),post_mean,sqrt(post_var),hpd_interval);
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end
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@ -241,6 +246,7 @@ if ncx
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disp(sprintf(pformat, header_width,name,bayestopt_.p1(ip),post_mean,hpd_interval, ...
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pnames(bayestopt_.pshape(ip)+1,:),bayestopt_.p2(ip)));
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if TeX
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name = ['(',deblank(M_.exo_names_tex(k1,:)) ',' deblank(M_.exo_names_tex(k2,:)),')'];
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TeXCore(fid,name,deblank(pnames(bayestopt_.pshape(ip)+1,:)),bayestopt_.p1(ip),...
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bayestopt_.p2(ip),post_mean,sqrt(post_var),hpd_interval);
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end
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@ -291,7 +297,8 @@ if ncn
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end
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disp(sprintf(pformat, header_width,name,bayestopt_.p1(ip),post_mean,hpd_interval, ...
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pnames(bayestopt_.pshape(ip)+1,:),bayestopt_.p2(ip)));
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if TeX
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if TeX,
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name = ['(',deblank(M_.endo_names_tex(k1,:)) ',' deblank(M_.endo_names_tex(k2,:)),')'];
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TeXCore(fid,name,deblank(pnames(bayestopt_.pshape(ip)+1,:)),bayestopt_.p1(ip),...
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bayestopt_.p2(ip),post_mean,sqrt(post_var),hpd_interval);
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end
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@ -314,13 +321,25 @@ fprintf(fidTeX,['%% RESULTS FROM METROPOLIS HASTINGS (' title ')\n']);
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fprintf(fidTeX,['%% ' datestr(now,0)]);
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fprintf(fidTeX,' \n');
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fprintf(fidTeX,' \n');
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fprintf(fidTeX,'\\begin{table}\n');
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fprintf(fidTeX,'\\centering\n');
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fprintf(fidTeX,'\\begin{tabular}{l|lcccccc} \n');
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fprintf(fidTeX,'\\begin{center}\n');
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fprintf(fidTeX,'\\begin{longtable}{l|lcccccc} \n');
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fprintf(fidTeX,['\\caption{Results from Metropolis-Hastings (' title ')}\n ']);
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fprintf(fidTeX,['\\label{Table:MHPosterior:' int2str(fnum) '}\\\\\n']);
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fprintf(fidTeX,'\\hline\\hline \\\\ \n');
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fprintf(fidTeX,[' & Prior distribution & Prior mean & Prior ' ...
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's.d. & Posterior mean & Posterior s.d. & HPD inf & HPD sup\\\\ \n']);
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fprintf(fidTeX,'\\hline \\\\ \n');
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fprintf(fidTeX,'\\hline \\endfirsthead \n');
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fprintf(fidTeX,['\\caption{(continued)}']);
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fprintf(fidTeX,['\\label{Table:MHPosterior:' int2str(fnum) '}\\\\\n']);
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fprintf(fidTeX,'\\hline\\hline \\\\ \n');
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fprintf(fidTeX,[' & Prior distribution & Prior mean & Prior ' ...
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's.d. & Posterior mean & Posterior s.d. & HPD inf & HPD sup\\\\ \n']);
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fprintf(fidTeX,'\\hline \\endhead \n');
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fprintf(fidTeX,'\\hline \\multicolumn{8}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
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fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
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fid = fidTeX;
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@ -337,11 +356,8 @@ fprintf(fid,['$%s$ & %s & %7.3f & %6.4f & %7.3f& %6.4f & %7.4f & %7.4f \\\\ \n']
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function TeXEnd(fid,fnum,title)
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fprintf(fid,'\\hline\\hline \n');
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fprintf(fid,'\\end{tabular}\n ');
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fprintf(fid,['\\caption{Results from Metropolis-Hastings (' title ')}\n ']);
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fprintf(fid,['\\label{Table:MHPosterior:' int2str(fnum) '}\n']);
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fprintf(fid,'\\end{table}\n');
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fprintf(fid,'\\end{longtable}\n ');
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fprintf(fid,'\\end{center}\n');
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fprintf(fid,'%% End of TeX file.\n');
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fclose(fid);
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@ -175,7 +175,7 @@ for i = 1:pages
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fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
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end
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fprintf(fidTeX,'\\centering \n');
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fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_udiag%s}\n',M_.fname,int2str(i));
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fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_udiag%s}\n',[DirectoryName '/' M_.fname],int2str(i));
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fprintf(fidTeX,'\\caption{Univariate convergence diagnostics for the Metropolis-Hastings.\n');
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fprintf(fidTeX,'The first, second and third columns are respectively the criteria based on\n');
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fprintf(fidTeX,'the eighty percent interval, the second and third moments.}');
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@ -238,7 +238,7 @@ if reste
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fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
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end
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fprintf(fidTeX,'\\centering \n');
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fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_udiag%s}\n',M_.fname,int2str(pages+1));
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fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_udiag%s}\n',[DirectoryName '/' M_.fname],int2str(pages+1));
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if reste == 2
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fprintf(fidTeX,'\\caption{Univariate convergence diagnostics for the Metropolis-Hastings.\n');
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fprintf(fidTeX,'The first, second and third columns are respectively the criteria based on\n');
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@ -348,7 +348,7 @@ if TeX
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fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(jj,:)),' ');
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end
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fprintf(fidTeX,'\\centering \n');
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fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_mdiag}\n',M_.fname);
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fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_mdiag}\n',[DirectoryName '/' M_.fname]);
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fprintf(fidTeX,'\\caption{Multivariate convergence diagnostics for the Metropolis-Hastings.\n');
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fprintf(fidTeX,'The first, second and third rows are respectively the criteria based on\n');
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fprintf(fidTeX,'the eighty percent interval, the second and third moments. The different \n');
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@ -159,7 +159,7 @@ for i=1:npar
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fprintf(fidTeX,'\\psfrag{%s}[1][][0.5][0]{%s}\n',deblank(NAMES(j,:)),deblank(TeXNAMES(j,:)));
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end
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fprintf(fidTeX,'\\centering\n');
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fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_PriorsAndPosteriors%s}\n',M_.fname,int2str(figunumber));
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fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s/%s_PriorsAndPosteriors%s}\n',OutputDirectoryName,M_.fname,int2str(figunumber));
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fprintf(fidTeX,'\\caption{Priors and posteriors.}');
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fprintf(fidTeX,'\\label{Fig:PriorsAndPosteriors:%s}\n',int2str(figunumber));
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fprintf(fidTeX,'\\end{figure}\n');
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@ -630,15 +630,20 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
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fprintf(fidTeX,['%% ' datestr(now,0)]);
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fprintf(fidTeX,' \n');
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fprintf(fidTeX,' \n');
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fprintf(fidTeX,'{\\tiny \n');
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fprintf(fidTeX,'\\begin{table}\n');
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fprintf(fidTeX,'\\centering\n');
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fprintf(fidTeX,'\\begin{center}\n');
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fprintf(fidTeX,'\\begin{longtable}{l|lcccc} \n');
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fprintf(fidTeX,'\\caption{Results from posterior maximization (parameters)}\n ');
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fprintf(fidTeX,'\\label{Table:Posterior:1}\n');
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fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
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fprintf(fidTeX,'\\label{Table:Posterior:1}\\\\\n');
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fprintf(fidTeX,'\\hline\\hline \\\\ \n');
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fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
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fprintf(fidTeX,'\\hline \\\\ \n');
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fprintf(fidTeX,'\\hline \\endfirsthead \n');
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fprintf(fidTeX,'\\caption{(continued)}\n ');
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fprintf(fidTeX,'\\label{Table:Posterior:1}\\\\\n');
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fprintf(fidTeX,'\\hline\\hline \\\\ \n');
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fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
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fprintf(fidTeX,'\\hline \\endhead \n');
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fprintf(fidTeX,'\\hline \\multicolumn{6}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
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fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
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ip = nvx+nvn+ncx+ncn+1;
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for i=1:np
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fprintf(fidTeX,'$%s$ & %s & %7.3f & %6.4f & %8.4f & %7.4f \\\\ \n',...
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@ -649,24 +654,9 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
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xparam1(ip),...
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stdh(ip));
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ip = ip + 1;
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if ~mod(i,50) && i<np,
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fprintf(fidTeX,'\\hline \n');
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fprintf(fidTeX,'\\multicolumn{6}{c}{(Table continues next page ...)} \\\\ \n')';
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fprintf(fidTeX,'\\end{tabular}\n ');
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fprintf(fidTeX,'\\end{table}\n');
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fprintf(fidTeX,'\\begin{table}\n');
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fprintf(fidTeX,'\\centering\n');
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fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
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fprintf(fidTeX,'\\multicolumn{6}{c}{( ... Table continued)} \\\\ \n')';
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fprintf(fidTeX,'\\hline\\hline \\\\ \n');
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fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
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fprintf(fidTeX,'\\hline \\\\ \n');
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end
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end
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fprintf(fidTeX,'\\hline\\hline \n');
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fprintf(fidTeX,'\\end{tabular}\n ');
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fprintf(fidTeX,'\\end{table}\n');
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fprintf(fidTeX,'} \n');
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fprintf(fidTeX,'\\end{longtable}\n ');
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fprintf(fidTeX,'\\end{center}\n');
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fprintf(fidTeX,'%% End of TeX file.\n');
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fclose(fidTeX);
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end
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@ -678,15 +668,20 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
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fprintf(fidTeX,['%% ' datestr(now,0)]);
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fprintf(fidTeX,' \n');
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fprintf(fidTeX,' \n');
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fprintf(fidTeX,'{\\tiny \n');
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fprintf(fidTeX,'\\begin{table}\n');
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fprintf(fidTeX,'\\centering\n');
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fprintf(fidTeX,'\\begin{center}\n');
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fprintf(fidTeX,'\\begin{longtable}{l|lcccc} \n');
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fprintf(fidTeX,'\\caption{Results from posterior maximization (standard deviation of structural shocks)}\n ');
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fprintf(fidTeX,'\\label{Table:Posterior:2}\n');
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fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
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fprintf(fidTeX,'\\label{Table:Posterior:2}\\\\\n');
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fprintf(fidTeX,'\\hline\\hline \\\\ \n');
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fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
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fprintf(fidTeX,'\\hline \\\\ \n');
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fprintf(fidTeX,'\\hline \\endfirsthead \n');
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fprintf(fidTeX,'\\caption{(continued)}\n ');
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fprintf(fidTeX,'\\label{Table:Posterior:2}\\\\\n');
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fprintf(fidTeX,'\\hline\\hline \\\\ \n');
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fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
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fprintf(fidTeX,'\\hline \\endhead \n');
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fprintf(fidTeX,'\\hline \\multicolumn{6}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
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fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
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ip = 1;
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for i=1:nvx
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k = estim_params_.var_exo(i,1);
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@ -698,24 +693,9 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
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xparam1(ip), ...
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stdh(ip));
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ip = ip+1;
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if ~mod(i,50) && i<nvx,
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fprintf(fidTeX,'\\hline \n');
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fprintf(fidTeX,'\\multicolumn{6}{c}{(Table continues next page ...)} \\\\ \n')';
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fprintf(fidTeX,'\\end{tabular}\n ');
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fprintf(fidTeX,'\\end{table}\n');
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fprintf(fidTeX,'\\begin{table}\n');
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fprintf(fidTeX,'\\centering\n');
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fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
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fprintf(fidTeX,'\\multicolumn{6}{c}{( ... Table continued)} \\\\ \n')';
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fprintf(fidTeX,'\\hline\\hline \\\\ \n');
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fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
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fprintf(fidTeX,'\\hline \\\\ \n');
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end
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end
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fprintf(fidTeX,'\\hline\\hline \n');
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fprintf(fidTeX,'\\end{tabular}\n ');
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fprintf(fidTeX,'\\end{table}\n');
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fprintf(fidTeX,'} \n');
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fprintf(fidTeX,'\\end{longtable}\n ');
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fprintf(fidTeX,'\\end{center}\n');
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fprintf(fidTeX,'%% End of TeX file.\n');
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fclose(fidTeX);
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end
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@ -727,14 +707,20 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
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fprintf(fidTeX,['%% ' datestr(now,0)]);
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fprintf(fidTeX,' \n');
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fprintf(fidTeX,' \n');
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fprintf(fidTeX,'\\begin{table}\n');
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fprintf(fidTeX,'\\centering\n');
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fprintf(fidTeX,'\\begin{center}\n');
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fprintf(fidTeX,'\\begin{longtable}{l|lcccc} \n');
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fprintf(fidTeX,'\\caption{Results from posterior maximization (standard deviation of measurement errors)}\n ');
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fprintf(fidTeX,'\\label{Table:Posterior:3}\n');
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fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
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fprintf(fidTeX,'\\label{Table:Posterior:3}\\\\\n');
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fprintf(fidTeX,'\\hline\\hline \\\\ \n');
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fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n')
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fprintf(fidTeX,'\\hline \\\\ \n');
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fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
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fprintf(fidTeX,'\\hline \\endfirsthead \n');
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fprintf(fidTeX,'\\caption{(continued)}\n ');
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fprintf(fidTeX,'\\label{Table:Posterior:3}\\\\\n');
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fprintf(fidTeX,'\\hline\\hline \\\\ \n');
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fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
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fprintf(fidTeX,'\\hline \\endhead \n');
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fprintf(fidTeX,'\\hline \\multicolumn{6}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
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fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
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ip = nvx+1;
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for i=1:nvn
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idx = strmatch(options_.varobs(estim_params_.var_endo(i,1),:),M_.endo_names);
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@ -746,23 +732,9 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
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xparam1(ip),...
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stdh(ip));
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ip = ip+1;
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if ~mod(i,50) && i<nvn,
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fprintf(fidTeX,'\\hline \n');
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fprintf(fidTeX,'\\multicolumn{6}{c}{(Table continues next page ...)} \\\\ \n')';
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fprintf(fidTeX,'\\end{tabular}\n ');
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fprintf(fidTeX,'\\end{table}\n');
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fprintf(fidTeX,'\\begin{table}\n');
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fprintf(fidTeX,'\\centering\n');
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fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
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fprintf(fidTeX,'\\multicolumn{6}{c}{( ... Table continued)} \\\\ \n')';
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fprintf(fidTeX,'\\hline\\hline \\\\ \n');
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fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
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fprintf(fidTeX,'\\hline \\\\ \n');
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end
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end
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fprintf(fidTeX,'\\hline\\hline \n');
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fprintf(fidTeX,'\\end{tabular}\n ');
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fprintf(fidTeX,'\\end{table}\n');
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fprintf(fidTeX,'\\end{longtable}\n ');
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fprintf(fidTeX,'\\end{center}\n');
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fprintf(fidTeX,'%% End of TeX file.\n');
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fclose(fidTeX);
|
||||
end
|
||||
|
|
@ -774,14 +746,20 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
|
|||
fprintf(fidTeX,['%% ' datestr(now,0)]);
|
||||
fprintf(fidTeX,' \n');
|
||||
fprintf(fidTeX,' \n');
|
||||
fprintf(fidTeX,'\\begin{table}\n');
|
||||
fprintf(fidTeX,'\\centering\n');
|
||||
fprintf(fidTeX,'\\begin{center}\n');
|
||||
fprintf(fidTeX,'\\begin{longtable}{l|lcccc} \n');
|
||||
fprintf(fidTeX,'\\caption{Results from posterior parameters (correlation of structural shocks)}\n ');
|
||||
fprintf(fidTeX,'\\label{Table:Posterior:4}\n');
|
||||
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
|
||||
fprintf(fidTeX,'\\label{Table:Posterior:4}\\\\\n');
|
||||
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
|
||||
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n')
|
||||
fprintf(fidTeX,'\\hline \\\\ \n');
|
||||
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
|
||||
fprintf(fidTeX,'\\hline \\endfirsthead \n');
|
||||
fprintf(fidTeX,'\\caption{(continued)}\n ');
|
||||
fprintf(fidTeX,'\\label{Table:Posterior:4}\\\\\n');
|
||||
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
|
||||
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
|
||||
fprintf(fidTeX,'\\hline \\endhead \n');
|
||||
fprintf(fidTeX,'\\hline \\multicolumn{6}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
|
||||
fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
|
||||
ip = nvx+nvn+1;
|
||||
for i=1:ncx
|
||||
k1 = estim_params_.corrx(i,1);
|
||||
|
|
@ -794,23 +772,9 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
|
|||
xparam1(ip), ...
|
||||
stdh(ip));
|
||||
ip = ip+1;
|
||||
if ~mod(i,50) && i<ncx,
|
||||
fprintf(fidTeX,'\\hline \n');
|
||||
fprintf(fidTeX,'\\multicolumn{6}{c}{(Table continues next page ...)} \\\\ \n')';
|
||||
fprintf(fidTeX,'\\end{tabular}\n ');
|
||||
fprintf(fidTeX,'\\end{table}\n');
|
||||
fprintf(fidTeX,'\\begin{table}\n');
|
||||
fprintf(fidTeX,'\\centering\n');
|
||||
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
|
||||
fprintf(fidTeX,'\\multicolumn{6}{c}{( ... Table continued)} \\\\ \n')';
|
||||
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
|
||||
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
|
||||
fprintf(fidTeX,'\\hline \\\\ \n');
|
||||
end
|
||||
end
|
||||
fprintf(fidTeX,'\\hline\\hline \n');
|
||||
fprintf(fidTeX,'\\end{tabular}\n ');
|
||||
fprintf(fidTeX,'\\end{table}\n');
|
||||
fprintf(fidTeX,'\\end{longtable}\n ');
|
||||
fprintf(fidTeX,'\\end{center}\n');
|
||||
fprintf(fidTeX,'%% End of TeX file.\n');
|
||||
fclose(fidTeX);
|
||||
end
|
||||
|
|
@ -822,14 +786,20 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
|
|||
fprintf(fidTeX,['%% ' datestr(now,0)]);
|
||||
fprintf(fidTeX,' \n');
|
||||
fprintf(fidTeX,' \n');
|
||||
fprintf(fidTeX,'\\begin{table}\n');
|
||||
fprintf(fidTeX,'\\centering\n');
|
||||
fprintf(fidTeX,'\\begin{center}\n');
|
||||
fprintf(fidTeX,'\\begin{longtabe}{l|lcccc} \n');
|
||||
fprintf(fidTeX,'\\caption{Results from posterior parameters (correlation of measurement errors)}\n ');
|
||||
fprintf(fidTeX,'\\label{Table:Posterior:5}\n');
|
||||
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
|
||||
fprintf(fidTeX,'\\label{Table:Posterior:5}\\\\\n');
|
||||
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
|
||||
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n')
|
||||
fprintf(fidTeX,'\\hline \\\\ \n');
|
||||
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
|
||||
fprintf(fidTeX,'\\hline \\endfirsthead \n');
|
||||
fprintf(fidTeX,'\\caption{(continued)}\n ');
|
||||
fprintf(fidTeX,'\\label{Table:Posterior:5}\\\\\n');
|
||||
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
|
||||
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
|
||||
fprintf(fidTeX,'\\hline \\endhead \n');
|
||||
fprintf(fidTeX,'\\hline \\multicolumn{6}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
|
||||
fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
|
||||
ip = nvx+nvn+ncx+1;
|
||||
for i=1:ncn
|
||||
k1 = estim_params_.corrn(i,1);
|
||||
|
|
@ -842,23 +812,9 @@ if any(bayestopt_.pshape > 0) && options_.TeX %% Bayesian estimation (posterior
|
|||
xparam1(ip), ...
|
||||
stdh(ip));
|
||||
ip = ip+1;
|
||||
if ~mod(i,50) && i<ncn,
|
||||
fprintf(fidTeX,'\\hline \n');
|
||||
fprintf(fidTeX,'\\multicolumn{6}{c}{(Table continues next page ...)} \\\\ \n')';
|
||||
fprintf(fidTeX,'\\end{tabular}\n ');
|
||||
fprintf(fidTeX,'\\end{table}\n');
|
||||
fprintf(fidTeX,'\\begin{table}\n');
|
||||
fprintf(fidTeX,'\\centering\n');
|
||||
fprintf(fidTeX,'\\begin{tabular}{l|lcccc} \n');
|
||||
fprintf(fidTeX,'\\multicolumn{6}{c}{( ... Table continued)} \\\\ \n')';
|
||||
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
|
||||
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Posterior mode & s.d. \\\\ \n');
|
||||
fprintf(fidTeX,'\\hline \\\\ \n');
|
||||
end
|
||||
end
|
||||
fprintf(fidTeX,'\\hline\\hline \n');
|
||||
fprintf(fidTeX,'\\end{tabular}\n ');
|
||||
fprintf(fidTeX,'\\end{table}\n');
|
||||
fprintf(fidTeX,'\\end{longtable}\n ');
|
||||
fprintf(fidTeX,'\\end{center}\n');
|
||||
fprintf(fidTeX,'%% End of TeX file.\n');
|
||||
fclose(fidTeX);
|
||||
end
|
||||
|
|
|
|||
94
matlab/pm3.m
94
matlab/pm3.m
|
|
@ -41,12 +41,16 @@ else
|
|||
end
|
||||
if options_.TeX
|
||||
% needs to be fixed
|
||||
if isempty(tit_tex),
|
||||
tit_tex=M_.endo_names_tex;
|
||||
end
|
||||
|
||||
varlist_TeX = [];
|
||||
for i=1:nvar
|
||||
if i==1
|
||||
varlist_TeX = M_.endo_names_tex(SelecVariables(i),:);
|
||||
varlist_TeX = tit_tex(SelecVariables(i),:);
|
||||
else
|
||||
varlist_TeX = char(varlist_TeX,M_.endo_names_tex(SelecVariables(i),:));
|
||||
varlist_TeX = char(varlist_TeX,tit_tex(SelecVariables(i),:));
|
||||
end
|
||||
end
|
||||
end
|
||||
|
|
@ -97,40 +101,6 @@ end
|
|||
% %%% The file .TeX! are not saved in parallel.
|
||||
|
||||
|
||||
subplotnum = 0;
|
||||
|
||||
if options_.TeX
|
||||
fidTeX = fopen([M_.dname '/Output/' M_.fname '_' name3 '.TeX'],'w');
|
||||
fprintf(fidTeX,'%% TeX eps-loader file generated by Dynare.\n');
|
||||
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
|
||||
fprintf(fidTeX,' \n');
|
||||
|
||||
for i=1:nvar
|
||||
NAMES = [];
|
||||
TEXNAMES = [];
|
||||
if max(abs(Mean(:,i))) > 10^(-6)
|
||||
subplotnum = subplotnum+1;
|
||||
name = deblank(varlist(i,:));
|
||||
NAMES = name;
|
||||
texname = deblank(varlist_TeX(i,:));
|
||||
TEXNAMES = ['$' texname '$'];
|
||||
end
|
||||
if subplotnum == MaxNumberOfPlotsPerFigure || i == nvar
|
||||
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_' name3 '_%s}\n'],M_.fname,deblank(tit3(i,:)));
|
||||
fprintf(fidTeX,'\\label{Fig:%s:%s}\n',name3,deblank(tit3(i,:)));
|
||||
fprintf(fidTeX,'\\end{figure}\n');
|
||||
fprintf(fidTeX,' \n');
|
||||
subplotnum = 0;
|
||||
end
|
||||
end
|
||||
fprintf(fidTeX,'%% End of TeX file.\n');
|
||||
fclose(fidTeX);
|
||||
end
|
||||
|
||||
% Store the variable mandatory for local/remote parallel computing.
|
||||
|
||||
|
|
@ -146,7 +116,7 @@ localVars.name3=name3;
|
|||
localVars.tit3=tit3;
|
||||
localVars.Mean=Mean;
|
||||
% Like sequential execution!
|
||||
|
||||
nvar0=nvar;
|
||||
|
||||
if ~exist('OCTAVE_VERSION')
|
||||
% Commenting for testing!
|
||||
|
|
@ -165,7 +135,7 @@ if ~exist('OCTAVE_VERSION')
|
|||
globalVars = struct('M_',M_, ...
|
||||
'options_', options_, ...
|
||||
'oo_', oo_);
|
||||
[fout, nBlockPerCPU, totCPU] = masterParallel(options_.parallel, 1, nvar, [],'pm3_core', localVars,globalVars, options_.parallel_info);
|
||||
[fout, nvar0, totCPU] = masterParallel(options_.parallel, 1, nvar, [],'pm3_core', localVars,globalVars, options_.parallel_info);
|
||||
end
|
||||
end
|
||||
else
|
||||
|
|
@ -175,6 +145,54 @@ else
|
|||
fout = pm3_core(localVars,1,nvar,0);
|
||||
end
|
||||
|
||||
subplotnum = 0;
|
||||
|
||||
if options_.TeX,
|
||||
fidTeX = fopen([M_.dname '/Output/' M_.fname '_' name3 '.TeX'],'w');
|
||||
fprintf(fidTeX,'%% TeX eps-loader file generated by Dynare.\n');
|
||||
fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
|
||||
fprintf(fidTeX,' \n');
|
||||
nvar0=cumsum(nvar0);
|
||||
|
||||
i=0;
|
||||
for j=1:length(nvar0),
|
||||
|
||||
NAMES = [];
|
||||
TEXNAMES = [];
|
||||
nvar=nvar0(j);
|
||||
while i<nvar,
|
||||
i=i+1;
|
||||
if max(abs(Mean(:,i))) > 10^(-6)
|
||||
subplotnum = subplotnum+1;
|
||||
name = deblank(varlist(i,:));
|
||||
texname = deblank(varlist_TeX(i,:));
|
||||
if subplotnum==1
|
||||
NAMES = name;
|
||||
TEXNAMES = ['$' texname '$'];
|
||||
else
|
||||
NAMES = char(NAMES,name);
|
||||
TEXNAMES = char(TEXNAMES,['$' texname '$']);
|
||||
end
|
||||
end
|
||||
if subplotnum == MaxNumberOfPlotsPerFigure || i == nvar
|
||||
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/Output/%s_' name3 '_%s}\n'],M_.dname,M_.fname,deblank(tit3(i,:)));
|
||||
fprintf(fidTeX,'\\label{Fig:%s:%s}\n',name3,deblank(tit3(i,:)));
|
||||
fprintf(fidTeX,'\\end{figure}\n');
|
||||
fprintf(fidTeX,' \n');
|
||||
subplotnum = 0;
|
||||
NAMES = [];
|
||||
TEXNAMES = [];
|
||||
end
|
||||
end
|
||||
end
|
||||
fprintf(fidTeX,'%% End of TeX file.\n');
|
||||
fclose(fidTeX);
|
||||
end
|
||||
|
||||
fprintf(['MH: ' tit1 ', done!\n']);
|
||||
|
||||
|
|
|
|||
|
|
@ -221,13 +221,16 @@ if isnumeric(options_.parallel),
|
|||
% Parallel execution!
|
||||
else
|
||||
[nCPU, totCPU, nBlockPerCPU] = distributeJobs(options_.parallel, 1, B);
|
||||
ifil=zeros(7,totCPU);
|
||||
for j=1:totCPU-1,
|
||||
nfiles = ceil(nBlockPerCPU(j)/MAX_nsmoo);
|
||||
ifil(1,j+1) =ifil(1,j)+nfiles;
|
||||
nfiles = ceil(nBlockPerCPU(j)/MAX_ninno);
|
||||
ifil(2,j+1) =ifil(2,j)+nfiles;
|
||||
nfiles = ceil(nBlockPerCPU(j)/MAX_nerro);
|
||||
ifil(3,j+1) =ifil(3,j)+nfiles;
|
||||
if run_smoother
|
||||
nfiles = ceil(nBlockPerCPU(j)/MAX_nsmoo);
|
||||
ifil(1,j+1) =ifil(1,j)+nfiles;
|
||||
nfiles = ceil(nBlockPerCPU(j)/MAX_ninno);
|
||||
ifil(2,j+1) =ifil(2,j)+nfiles;
|
||||
nfiles = ceil(nBlockPerCPU(j)/MAX_nerro);
|
||||
ifil(3,j+1) =ifil(3,j)+nfiles;
|
||||
end
|
||||
if naK
|
||||
nfiles = ceil(nBlockPerCPU(j)/MAX_naK);
|
||||
ifil(4,j+1) =ifil(4,j)+nfiles;
|
||||
|
|
@ -274,16 +277,16 @@ if ~isnumeric(options_.parallel),
|
|||
leaveSlaveOpen = options_.parallel_info.leaveSlaveOpen;
|
||||
if options_.parallel_info.leaveSlaveOpen == 0,
|
||||
% Commenting for testing!!!
|
||||
% options_.parallel_info.leaveSlaveOpen = 1; % Force locally to leave open remote matlab sessions (repeated pm3 calls)
|
||||
options_.parallel_info.leaveSlaveOpen = 1; % Force locally to leave open remote matlab sessions (repeated pm3 calls)
|
||||
end
|
||||
end
|
||||
|
||||
if options_.smoother
|
||||
pm3(endo_nbr,gend,ifil(1),B,'Smoothed variables',...
|
||||
'',M_.endo_names(1:M_.orig_endo_nbr, :),'tit_tex',M_.endo_names,...
|
||||
'',M_.endo_names(1:M_.orig_endo_nbr, :),M_.endo_names_tex,M_.endo_names,...
|
||||
varlist,'SmoothedVariables',DirectoryName,'_smooth');
|
||||
pm3(exo_nbr,gend,ifil(2),B,'Smoothed shocks',...
|
||||
'',M_.exo_names,'tit_tex',M_.exo_names,...
|
||||
'',M_.exo_names,M_.exo_names_tex,M_.exo_names,...
|
||||
M_.exo_names,'SmoothedShocks',DirectoryName,'_inno');
|
||||
if nvn
|
||||
% needs to be fixed
|
||||
|
|
|
|||
Loading…
Reference in New Issue