of quality statistics gnuplot < '$gnuplot_commands' 2>&1 || echo "Error running gnuplot." >&2 gnuplot set output '$output_file' set term png size ${graph_size} set boxwidth 0.8 set key right tmargin set xlabel "${xlabel}" set ylabel "${ylabel}" set title "${title}" set xtics 1 set ytics 1 set grid ytics set offsets 1, 1, 1, 1 plot '${input_file}' using ${xcol}:${q1col}:${lwcol}:${rwcol}:${q3col} with candlesticks lt 1 lw 1 title 'Quartiles' whiskerbars, \ '' using ${xcol}:${medcol}:${medcol}:${medcol}:${medcol} with candlesticks lt -1 lw 2 title 'Medians'\ #if str( $use_outliers['use_outliers_type'] ) == 'use_outliers': , "< python -c \"for xval, yvals in [ ( fields[${xcol} - 1], fields[${use_outliers['outliercol']} - 1].split( ',' ) ) for fields in [ line.rstrip( '\\n\\r' ).split( '\\t' ) for line in open( '${input_file}' ) if not line.startswith( '#' ) ] if len( fields ) > max( ${xcol} - 1, ${use_outliers['outliercol']} - 1 ) ]: print '\\n'.join( [ '%s\\t%s' % ( xval, yval ) for yval in yvals if yval ] )\"" using 1:2 with points pt 29 title 'Outliers' #end if This tool creates a boxplot from a tabular file containing summary statistics. Outliers are optionally defined using a comma-separated list of values.