# First part of old mgr.dem # show same data with various spline smoothing choices print "various splines for smoothing" set title "cubic spline fit to data (no weights)" set samples 300 set xlabel "Time (sec)" set ylabel "Rate" plot "silver.dat" t "experimental" w errorb, \ "" smooth csplines t "cubic smooth" lw 2 |

set title "acsplines weighted by relative error" # error is column 3; weight larger errors less # start with rel error = 1/($3/$2) S=1 plot "silver.dat" t "experimental" w errorb,\ "" u 1:2:(S*$2/$3) smooth acsplines t "acspline Y/Z" lw 2 |

set title "acsplines with increasing weight from error estimate" plot "silver.dat" t "rate" w errorb,\ "" u 1:2:($2/($3*1.e1)) sm acs t "acspline Y/(Z*1.e1)" lw 2,\ "" u 1:2:($2/($3*1.e3)) sm acs t " Y/(Z*1.e3)" lw 2,\ "" u 1:2:($2/($3*1.e5)) sm acs t " Y/(Z*1.e5)" lw 2 |

set title "same plot (various weighting) in log scale" set logscale y set grid x y mx my replot |

set title "Bezier curve rather than cubic spline" unset logscale y plot "silver.dat" t "experimental" w errorb,\ "" smooth sbezier t "bezier" lw 2 |

set title "Bezier curve with log scale" set logscale y replot |