minimizer_v1

The module creates a minimizer instance which then may be used for a fit with fit_v1 module or elsewhere.

The minimizer is stored in env.future[‘minimizer’] under its name.

Positional arguments

• name – define name of the minimizer

• statistic – define the statistics function that has to be minimized (created by stats module)

• pargroups – define parameter groups for the minimization (created by pargroups module)

Options

• -t, --type – define type of minimizer

  • choices: minuit, minuit2, iminuit

  • default: minuit2

• --minopts – options that are passed to the minimizer

• -s, --strict – raise an exception if a parameter is skipped because it does not affect the output

• --initial-value – define what initial value to use

  • choices: central or value

  • default: central

• -v, --verbose – define verbosity level

Examples

• Create a minimizer and do a fit of a function ‘stats’ and a group of parameters ‘minpars’:

  ./gna \
      -- gaussianpeak --name peak_MC --nbins 50 \
      -- gaussianpeak --name peak_f  --nbins 50 \
      -- ns --name peak_MC --print \
          --set E0             values=2    fixed \
          --set Width          values=0.5  fixed \
          --set Mu             values=2000 fixed \
          --set BackgroundRate values=1000 fixed \
      -- ns --name peak_f --print \
          --set E0             values=2.5  relsigma=0.2 \
          --set Width          values=0.3  relsigma=0.2 \
          --set Mu             values=1500 relsigma=0.25 \
          --set BackgroundRate values=1100 relsigma=0.25 \
      -- dataset-v1  --name peak --theory-data peak_f.spectrum peak_MC.spectrum \
      -- analysis-v1 --name analysis --datasets peak \
      -- stats stats --chi2 analysis \
      -- pargroup minpars peak_f -vv \
      -- minimizer-v1 min stats minpars -vv
  

• Create a minimizer and do a fit of a function ‘stats’ and a group of parameters ‘minpars’ using a iminuit minimizer:

  ./gna \
      -- gaussianpeak --name peak_MC --nbins 50 \
      -- gaussianpeak --name peak_f  --nbins 50 \
      -- ns --name peak_MC --print \
          --set E0             values=2    fixed \
          --set Width          values=0.5  fixed \
          --set Mu             values=2000 fixed \
          --set BackgroundRate values=1000 fixed \
      -- ns --name peak_f --print \
          --set E0             values=2.5  relsigma=0.2 \
          --set Width          values=0.3  relsigma=0.2 \
          --set Mu             values=1500 relsigma=0.25 \
          --set BackgroundRate values=1100 relsigma=0.25 \
      -- dataset-v1  --name peak --theory-data peak_f.spectrum peak_MC.spectrum \
      -- analysis-v1 --name analysis --datasets peak \
      -- stats stats --chi2 analysis \
      -- pargroup minpars peak_f -vv \
      -- minimizer-v1 min stats minpars -vv -t iminuit