update

scripts/compute_psdlags.sh

@@ -31,10 +31,10 @@ do
     time scripts/${analysis_script} data/lc/${ref_band}.lc $lightcurve >> logs/${echo_band}
 
 
-    # process_tables perl script reads *.out files from the python script,
+    # process_output perl script reads *.out files from the python script,
     # then creates other useful tables
 
-    scripts/process_tables.pl $echo_band 
+    scripts/process_output.pl $echo_band 
 
     # saves the tables to data/tables/
     mv -v tmp.echopsd $echopsd_tabfile

scripts/plot.sh

@@ -22,10 +22,11 @@ case $1 in
         done
         echo "$gnuplot_input"|perl -pe 's|␤|\n|g' > ${gnuplot_file}
         gnuplot $gnuplot_file
+        rm $gnuplot_file
     ;;
 
     "lags"|"lag"|"delay"|"delays")
-        gnuplot_file=timelag_atlas.gp
+        gnuplot_file=lag_atlas.gp
         gnuplot_input=$(cat scripts/templates/${gnuplot_file}|perl -pe 's|\n|␤|g')
         for tabfile in data/tables/lag_*.tab;
         do
@@ -41,6 +42,7 @@ case $1 in
         done
         echo "$gnuplot_input"|perl -pe 's|␤|\n|g' > ${gnuplot_file}
         gnuplot $gnuplot_file
+        rm $gnuplot_file
     ;;
 
     "tophat"|"th")

scripts/process_output.pl

@@ -192,7 +192,11 @@ foreach ( sort {$a <=> $b} keys %function_bin ) {
     say $datafile encode($charset,
         sprintf("%e   %e   %e   %e   %e   %e",
             ($_ - $function_bin{$_}{"Δ"}), 
-            ($_ + $function_bin{$_}{"Δ"})
+            ($_ + $function_bin{$_}{"Δ"}),
+            $function_bin{$_}{"echo_PSD_μ"},
+            $function_bin{$_}{"echo_PSD_σ"},
+            $function_bin{$_}{"timelag_μ"},
+            $function_bin{$_}{"timelag_σ"}
         ));
 }
 close($datafile)

scripts/psdlag_4bin.py

@@ -23,12 +23,10 @@ t1, l1, l1e = np.loadtxt(ref_file).T
 
 
 
-fqL = np.array([0.0049999999, 0.018619375, 0.044733049, 0.069336227, 0.10747115, 0.16658029, 
-                0.25819945, 0.40020915, 0.62032418])
 fqL = np.array([0.0049999999, 0.044733049, 0.10747115,  
                 0.25819945, 0.62032418])
-fqL = np.array([0.0049999999, 0.018619375, 0.069336227, 0.10747115, 0.62032418])
-fqL = np.logspace(np.log10(0.005),np.log10(0.6),5)
+#fqL = np.array([0.0049999999, 0.018619375, 0.069336227, 0.10747115, 0.62032418])
+#fqL = np.logspace(np.log10(0.005),np.log10(0.6),5)
 nfq = len(fqL) - 1
 fqd = 10**(np.log10( (fqL[:-1]*fqL[1:]) )/2.)