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@ -31,10 +31,10 @@ do
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time scripts/${analysis_script} data/lc/${ref_band}.lc $lightcurve >> logs/${echo_band}
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time scripts/${analysis_script} data/lc/${ref_band}.lc $lightcurve >> logs/${echo_band}
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# process_tables perl script reads *.out files from the python script,
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# process_output perl script reads *.out files from the python script,
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# then creates other useful tables
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# then creates other useful tables
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scripts/process_tables.pl $echo_band
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scripts/process_output.pl $echo_band
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# saves the tables to data/tables/
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# saves the tables to data/tables/
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mv -v tmp.echopsd $echopsd_tabfile
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mv -v tmp.echopsd $echopsd_tabfile
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@ -22,10 +22,11 @@ case $1 in
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done
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done
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echo "$gnuplot_input"|perl -pe 's||\n|g' > ${gnuplot_file}
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echo "$gnuplot_input"|perl -pe 's||\n|g' > ${gnuplot_file}
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gnuplot $gnuplot_file
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gnuplot $gnuplot_file
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rm $gnuplot_file
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;;
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;;
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"lags"|"lag"|"delay"|"delays")
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"lags"|"lag"|"delay"|"delays")
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gnuplot_file=timelag_atlas.gp
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gnuplot_file=lag_atlas.gp
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gnuplot_input=$(cat scripts/templates/${gnuplot_file}|perl -pe 's|\n||g')
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gnuplot_input=$(cat scripts/templates/${gnuplot_file}|perl -pe 's|\n||g')
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for tabfile in data/tables/lag_*.tab;
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for tabfile in data/tables/lag_*.tab;
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do
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do
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@ -41,6 +42,7 @@ case $1 in
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done
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done
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echo "$gnuplot_input"|perl -pe 's||\n|g' > ${gnuplot_file}
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echo "$gnuplot_input"|perl -pe 's||\n|g' > ${gnuplot_file}
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gnuplot $gnuplot_file
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gnuplot $gnuplot_file
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rm $gnuplot_file
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;;
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;;
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"tophat"|"th")
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"tophat"|"th")
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@ -192,7 +192,11 @@ foreach ( sort {$a <=> $b} keys %function_bin ) {
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say $datafile encode($charset,
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say $datafile encode($charset,
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sprintf("%e %e %e %e %e %e",
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sprintf("%e %e %e %e %e %e",
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($_ - $function_bin{$_}{"Δ"}),
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($_ - $function_bin{$_}{"Δ"}),
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($_ + $function_bin{$_}{"Δ"})
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($_ + $function_bin{$_}{"Δ"}),
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$function_bin{$_}{"echo_PSD_μ"},
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$function_bin{$_}{"echo_PSD_σ"},
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$function_bin{$_}{"timelag_μ"},
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$function_bin{$_}{"timelag_σ"}
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));
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));
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}
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}
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close($datafile)
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close($datafile)
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@ -23,12 +23,10 @@ t1, l1, l1e = np.loadtxt(ref_file).T
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fqL = np.array([0.0049999999, 0.018619375, 0.044733049, 0.069336227, 0.10747115, 0.16658029,
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0.25819945, 0.40020915, 0.62032418])
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fqL = np.array([0.0049999999, 0.044733049, 0.10747115,
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fqL = np.array([0.0049999999, 0.044733049, 0.10747115,
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0.25819945, 0.62032418])
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0.25819945, 0.62032418])
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fqL = np.array([0.0049999999, 0.018619375, 0.069336227, 0.10747115, 0.62032418])
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#fqL = np.array([0.0049999999, 0.018619375, 0.069336227, 0.10747115, 0.62032418])
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fqL = np.logspace(np.log10(0.005),np.log10(0.6),5)
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#fqL = np.logspace(np.log10(0.005),np.log10(0.6),5)
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nfq = len(fqL) - 1
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nfq = len(fqL) - 1
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fqd = 10**(np.log10( (fqL[:-1]*fqL[1:]) )/2.)
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fqd = 10**(np.log10( (fqL[:-1]*fqL[1:]) )/2.)
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