A broad range of dataset classes have been implemented into the NUISANCE framework that support the direct comparison between different generator Monte Carlo event samples and published data. These can be specified by providing different sample IDs when writing card files as in the example below comparing GENIE events to MiniBooNE data.
sample MiniBooNE_CCQE_XSec_1DQ2_nu GENIE:prepared_genie_events.root
$ nuiscomp -c mbcomp.card -o mbcomp.root
This produces the output root file mbcomp.root containing a series of histograms that can be directly compared to one another. Histograms follow the naming convention "name_type". Some examples are given below.
- MiniBooNE_CCQE_XSec_1DQ2_nu_data : Published data distribution
- MiniBooNE_CCQE_XSec_1DQ2_nu_MC : Equivalent MC distribution generated from the events files that can be directly compared to the data distribution using the ROOT option "SAME".
- MiniBooNE_CCQE_XSec_1DQ2_nu_MC_FINE : Smooth histogram with much finer binning than the MC histogram.
- MiniBooNE_CCQE_XSec_1DQ2_nu_MC_PDG : MC prediction stacked by true interaction channels. The titles of each individual histogram denotes the name of the interaction channel.
- MiniBooNE_CCQE_XSec_1DQ2_nu_MC_FLUX : Flux histogram the events were generated with.
- MiniBooNE_CCQE_XSec_1DQ2_nu_MC_EVT : Event histogram prediction total number of events given the generated flux.
- MiniBooNE_CCQE_XSec_1DQ2_nu_MC_SHAPE : MC distribution normalised to match the total data normalisation for shape comparisons to be made.
Example data-MC comparison from output ROOT file
Further cardfile examples
- Generate a file comparing NuWro? event files to MiniBooNE CC1pion data.
sample MiniBooNE_CC1pip_XSec_1DTPi_nu NUWRO:/path/to/nuwro_mb_files.root
- Generate a file comparing NEUT event files to MiniBooNE CC1pion data.
sample MiniBooNE_CC1pip_XSec_1DTPi_nu NUWRO:/path/to/neut_mb_files.root
- Generate a file comparing GiBUU event files to MiniBooNE CC1pion data.
sample MiniBooNE_CC1pip_XSec_1DTPi_nu GiBUU:/path/to/gibuu_mb_files.root