NUISCOMP

The NUISANCE comparison application can be used to generate MC predictions that can be directly compared with published scatter data by automatically selecting the correct event topologies from a provided event sample and binning them to match the data.

Wiki content

1. NUISCOMP
   1. Running NUISCOMP
   2. Generating GENIE Events
   3. Running gevgen
   4. Running PrepareGENIE
   5. Running gevgen_nuisance (optional)
   6. Setting up a GENIE Comparison
   7. Analysing the output
   8. Providing reweight parameters

Running NUISCOMP

Author: Patrick Stowell

Date: June 2017

Versions: NUISANCE v2r0, GENIE 2.12.6

The following example details how to run NUISANCE and produce MiniBooNE pion production comparisons to a generator of choice. Each generator requires very slightly different ways to handle NUISANCE, therefore multiple versions of this tutorial have been provided. Please use the following links to choose what generator you would like to use.

• I want to use GENIE
• I want to use NuWro?
• I want to use NEUT?

Generating GENIE Events

If we want to see how a given GENIE model behaves, first we need to generate events. This can be done using the standard gevgen application, using the appropriate target and flux for a given data sample.

If all you want to do is check your NUSIANCE is built correctly, you can skip this step by downloading MC files from our online storage area by following the steps found here:LinkToNUISANCEMCFiles

Running gevgen

The standard gevgen application options can be ran using

 $ gevgen -f  -n -e 

We need to provide a flux and target list to GENIE when running gevgen. To see our list of compiled flux and target combinations for each sample please see here:

Note: If building NUISANCE v2r0 or higher against GENIE 2-12-0 or higher an option is provided to use an easier and quicker gevgen_nuisance application to generate NUISANCE-ready event files. Please see section 2.3 if you would like to use this.

We want to run comparisons to MiniBooNE muon-neutrino scattering data on a mineral oil target, therefore to generate events we can run

 $ gevgen -f  MiniBooNE -t CH 

Once our events have been generated we can check that they have finished correctly by opening the output event file has a ‘gtree’ object and the flux spectrum file contains the correct histogram.

$ root gntp.2063030.ghep.root
root [0]
Attaching file gntp.2063030.ghep.root as _file0...
Warning in <TClass::TClass>: no dictionary for class genie::NtpMCEventRecord is available
Warning in <TClass::TClass>: no dictionary for class genie::NtpMCRecordI is available
Warning in <TClass::TClass>: no dictionary for class genie::NtpMCRecHeader is available
Warning in <TClass::TClass>: no dictionary for class genie::EventRecord is available
Warning in <TClass::TClass>: no dictionary for class genie::GHepRecord is available
Warning in <TClass::TClass>: no dictionary for class genie::Interaction is available
Warning in <TClass::TClass>: no dictionary for class genie::InitialState is available
Warning in <TClass::TClass>: no dictionary for class genie::Target is available
Warning in <TClass::TClass>: no dictionary for class genie::ProcessInfo is available
Warning in <TClass::TClass>: no dictionary for class genie::Kinematics is available
Warning in <TClass::TClass>: no dictionary for class genie::XclsTag is available
Warning in <TClass::TClass>: no dictionary for class genie::KPhaseSpace is available
Warning in <TClass::TClass>: no dictionary for class genie::GHepParticle is available
Warning in <TClass::TClass>: no dictionary for class pair<genie::EKineVar,double> is available
root [1] _file0->ls();
TFile**		gntp.2063030.ghep.root
 TFile*		gntp.2063030.ghep.root
  KEY: genie::NtpMCTreeHeader	header;1	GENIE output tree header
  KEY: TFolder	gconfig;1	GENIE configs
  KEY: TFolder	genv;1	GENIE user environment
  KEY: TTree	gtree;1	GENIE MC Truth TTree, Format: [NtpMCEventRecord]

$ root input-flux.root
root [0]
Attaching file input-flux.root as _file0...
root [1] _file0->ls();
TFile**		input-flux.root
 TFile*		input-flux.root
  KEY: TH1D	spectrum;1	neutrino_flux

Now that the event samples have been generated correctly, we need to prepare them for use in NUISANCE.

Running PrepareGENIE

The standard gevgen application doesn’t save the total event rate predictions into the event file itself. NUISANCE needs these to correctly normalise predictions so before we can use these new events we need to prepare them.

The PrepareGENIE application is built when NUISANCE is built with GENIE support should be available after the NUISANCE environmental setup script is ran.

$ PrepareGENIE -h
PrepareGENIEEvents NUISANCE app.
Takes GHep Outputs and prepares events for NUISANCE.

PrepareGENIEEvents  [-h,-help,--h,--help] 
                                    [-i inputfile1.root,inputfile2.root,inputfile3.root,...] 
                                    [-f flux_root_file.root,flux_hist_name] 
                                    [-t target1[frac1],target2[frac2],...]

Prepare Mode [Default] : Takes a single GHep file, reconstructs the original GENIE splines,  and creates a duplicate file that 
also contains the flux, event rate, and xsec predictions that NUISANCE needs.
Following options are required for Prepare Mode:
 [ -i inputfile.root  ] : Reads in a single GHep input file that needs the xsec calculation ran on it.
 [ -f flux_file.root,hist_name ] : Path to root file containing the flux histogram the GHep records were generated with. A 
simple method is to point this to the flux histogram genie generatrs '-f /path/to/events/input-flux.root,spectrum'.
 [ -t target ] : Target that GHepRecords were generated with. Comma seperated list. E.g. for CH2 
target=1000060120,1000010010,1000010010

The PrepareGENIE application, when ran, loops over all the events, extracts the cross-section as a function of energy for each discrete interaction mode and uses this information to reconstruct the cross-section splines for each target that were used to generate events.

These splines are then multiplied by specified flux and added according to the target definition provided to produce total flux and event rate predictions as a function of energy for the sample and saves them into the events file.

We want to prepare our MiniBooNE events so we pass in the event files, the input flux, and the CH2 target definition.

 $ PrepareGENIE -i gntp.2063030.ghep.root -f input-flux.root,spectrum -t  1000060120,1000010010,1000010010  

Now when we open our event file again, we should see the flux and event rate histograms are now saved into the file ready for NUISANCE to read them.

  KEY: genie::NtpMCTreeHeader	header;1	GENIE output tree header
  KEY: TFolder	gconfig;1	GENIE configs
  KEY: TFolder	genv;1	GENIE user environment
  KEY: TTree	gtree;1	GENIE MC Truth TTree, Format: [NtpMCEventRecord]
  KEY: TDirectoryFile	IndividualGENIESplines;1	IndividualGENIESplines
  KEY: TDirectoryFile	TargetGENIESplines;1	TargetGENIESplines
  KEY: TH1F	nuisance_xsec;1
  KEY: TH1F	nuisance_events;1
  KEY: TH1F	nuisance_flux;1

Running gevgen_nuisance (optional)

Other than the standard gevgen application, if built against GENIE events later than GENIE 2.12.0, NUISANCE can also provide a gevgen_nuisance app, with additional features to support the creation of ‘NUISANCE-ready’ events.

To build gevgen_nuisance, you will need to build with the option ‘-DBUILD_GEVGEN=ON’ during the cmake configure statement as shown in the build notes here:

 $ cmake ../ -DUSE_GENIE=1 -DBUILD_GEVGEN=1 

The gevgen_nuisance can be ran in a similar way to the normal gevgen application but flux inputs and target definitions can be provided in simpler formats

In our example we want to generate events for a MiniBooNE muon neutrino flux on a CH2 target. Therefore we run

 $ gevgen_nuisance -n 250000 -f MiniBooNE_fhc_numu -t CH2  

We should then open the output event file to check it constrains the GENIE event tree ‘gtree’ object and the flux and event rate predictions.

Notice that we no longer need to run PrepareGENIE on gevgen_nuisance events before using them nuisance.

gevgen_nuisance also provides extra support for mixed target and flux specifications. For further notes on these see:

Setting up a GENIE Comparison

Now that we have an event sample we can load them load them into NUISANCE by specifying them at run time. To do that we need to write a NUISANCE card file that lists all comparisons that should be made and the event files that should be used for each one.

We want to produce comparisons to MiniBooNE pion production data, so first we should search the NUISANCE sample list.

The ‘nuissamples’ script is provided for easy access of the sample list. Running it without any arguments will return a full sample list of available data comparisons. Providing an additional argument will return only samples containing the provided substring.

We can list the MIniBooNE samples using

 [stowell@hepgw1 ~]$ nuissamples MiniBooNE
MiniBooNE_CCQE_XSec_1DQ2_nu
MiniBooNE_CCQELike_XSec_1DQ2_nu
MiniBooNE_CCQE_XSec_1DQ2_antinu
MiniBooNE_CCQELike_XSec_1DQ2_antinu
MiniBooNE_CCQE_CTarg_XSec_1DQ2_antinu
MiniBooNE_CCQE_XSec_2DTcos_nu
MiniBooNE_CCQELike_XSec_2DTcos_nu
MiniBooNE_CCQE_XSec_2DTcos_antinu
MiniBooNE_CCQELike_XSec_2DTcos_antinu
MiniBooNE_CC1pip_XSec_1DEnu_nu
MiniBooNE_CC1pip_XSec_1DQ2_nu
MiniBooNE_CC1pip_XSec_1DTpi_nu
MiniBooNE_CC1pip_XSec_1DTu_nu
MiniBooNE_CC1pip_XSec_2DQ2Enu_nu
MiniBooNE_CC1pip_XSec_2DTpiCospi_nu
MiniBooNE_CC1pip_XSec_2DTpiEnu_nu
MiniBooNE_CC1pip_XSec_2DTuCosmu_nu
MiniBooNE_CC1pip_XSec_2DTuEnu_nu
MiniBooNE_CC1pi0_XSec_1DEnu_nu
MiniBooNE_CC1pi0_XSec_1DQ2_nu
MiniBooNE_CC1pi0_XSec_1DTu_nu
MiniBooNE_CC1pi0_XSec_1Dcosmu_nu
MiniBooNE_CC1pi0_XSec_1Dcospi0_nu
MiniBooNE_CC1pi0_XSec_1Dppi0_nu
MiniBooNE_NC1pi0_XSec_1Dcospi0_antinu
MiniBooNE_NC1pi0_XSec_1Dcospi0_rhc
MiniBooNE_NC1pi0_XSec_1Dcospi0_nu
MiniBooNE_NC1pi0_XSec_1Dcospi0_fhc
MiniBooNE_NC1pi0_XSec_1Dppi0_antinu
MiniBooNE_NC1pi0_XSec_1Dppi0_rhc
MiniBooNE_NC1pi0_XSec_1Dppi0_nu
MiniBooNE_NC1pi0_XSec_1Dppi0_fhc
MiniBooNE_NCEL_XSec_Treco_nu

We only care about CC1pip data therefore the following samples are of interest

[stowell@hepgw1 ~]$ nuissamples MiniBooNE_CC1pip
MiniBooNE_CC1pip_XSec_1DEnu_nu
MiniBooNE_CC1pip_XSec_1DQ2_nu
MiniBooNE_CC1pip_XSec_1DTpi_nu
MiniBooNE_CC1pip_XSec_1DTu_nu
MiniBooNE_CC1pip_XSec_2DQ2Enu_nu
MiniBooNE_CC1pip_XSec_2DTpiCospi_nu
MiniBooNE_CC1pip_XSec_2DTpiEnu_nu
MiniBooNE_CC1pip_XSec_2DTuCosmu_nu
MiniBooNE_CC1pip_XSec_2DTuEnu_nu

In this example we will compare to the 1Dtpi and 1DTu distributions, but we could provide any number of the samples seen in the lists.

We write our card file with these two datasets using the following sample object format:

sample NAME_OF_SAMPLE  INPUT_TYPE:FILE_INPUT    

So for our genie files generated in step 2.1, our card file would be :

genie_tutorial.card

sample MiniBooNE_CC1pip_XSec_1DTpi_nu  GENIE: gntp.2063030.ghep.root
sample MiniBooNE_CC1pip_XSec_1DTu_nu GENIE: gntp.2063030.ghep.root  

We can now run our cardfile using the standard nuisance application like so:

$ nuiscomp -c genie_tutorial.card  -o genie_samples.root

In total this will produce a lot of logging output, so only some snippets are included below for comparison.

[LOG Fitter]: Starting nuiscomp.exe

...

[LOG Minmzr]:- Loading Sample : MiniBooNE_CC1pip_XSec_1DTpi_nu
[LOG Sample]:-- Loading Sample : MiniBooNE_CC1pip_XSec_1DTpi_nu
[LOG Sample]:-- Creating GENIEInputHandler : MiniBooNE_CC1pip_XSec_1DTpi_nu
		|-> Total Entries    : 2500000
		|-> Event Integral   : 1.47491e-28 events/nucleon
		|-> Flux Integral    : 1.67753e+10 /cm2
		|-> Event/Flux       : 8.79217e-39 cm2/nucleon

...

[LOG Fitter]: Generating Comparison.
[LOG Reconf]:--- Starting Reconfigure iter. 0
[LOG Reconf]:--- Event Manager Reconfigure
[LOG Reconf]:--- MiniBooNE_CC1pip_XSec_1DTpi_nu : Processed 0 events. [M, W] = [33, 1]
[LOG Reconf]:--- MiniBooNE_CC1pip_XSec_1DTpi_nu : Processed 500000 events. [M, W] = [13, 1]

...

[LOG Fitter]: Saving current full FCN predictions
[LOG Minmzr]:- Writing each of the data classes...
[LOG Sample]:-- Written Histograms: MiniBooNE_CC1pip_XSec_1DTpi_nu
[LOG Sample]:-- Written Histograms: MiniBooNE_CC1pip_XSec_1DTu_nu
[LOG Fitter]: ------------------------------------ -
[LOG Fitter]: Comparison Complete.
[LOG Fitter]: ------------------------------------ -

To check that the comparison definitely finished successfully, lets open the root file and check the file is not empty.

$ root genie_allsamples.root
Attaching file genie_allsamples.root as _file0...
root [0] TBrowser b

If you see something similar to this then the comparisons should have ran successfully.

Analysing the output

When we open the NUISANCE output file in ROOT we can see that it contains a series of histograms all with names similar to the sample names we specified in our card file. By default NUISANCE preppends the name of the sample to any histogram when writing it so that you know from what sample each histogram originated from.

Lets go through some of the histograms of interest.

• MiniBooNE_CC1pip_XSec_1DTpi_nu_data : This is the data histogram we are trying to compare to for the Tpi distribution. Drawing this with the ROOT draw option 'E1' will draw us the error bands.

• MiniBooNE_CC1pip_XSec_1DTpi_nu_MC : This is the MC histogram for our model binned in exactly the same binning as the data. Error bars attached to the MC histogram are defined as the statistical error in each bin given your MC event sample. This histogram is also used to calculate a likelihood by directly comparing to the data. By default the title of the MC histogram is also set to the value of the likelihood for easy reference. In the plot below the chi2 was calculated to be : 25.749.

We can also directly compare the MC and data histograms, by drawing the data with the option 'E1' then drawing the MC histogram with the option "same hist".

• MiniBooNE_CC1pip_XSec_1DTpi_nu_MC_FINE : A finer binned version of the MC histogram that can be used to make smoother more detailed curves for comparison.

• MiniBooNE_CC1pip_XSec_1DTpi_nu_MC_SHAPE : A histogram with the same binning as the MC histogram, but this time the MC prediction has been normalised to match the total cross-section of the data. Useful for comparing the shape of the MC to the data whilst neglecting normalisation differences.

• MiniBooNE_CC1pip_XSec_1DTpi_nu_MC_RATIO : A copy of the MC histogram that has been divided by the MC histogram. This should return a flat histogram with each bin content equal to 1.0, and is used to set the unity line in a data/MC ratio histogram.

• MiniBooNE_CC1pip_XSec_1DTpi_nu_MC_RATIO : A copy of the data histogram that has been divided by the MC histogram. This is provided to make it easier to make data/MC comparisons by combining it with MiniBooNE_CC1pip_XSec_1DTpi_nu_MC_RATIO.

Providing reweight parameters

The comparisons application also allows different GENIE reweight parameters to be provided in our card file.

The format for this is:

genie_parameter  NAME   VALUE   STATE

• NAME : Specifies the name of the reweight dial. These can be found in '$GENIE/src/ReWeight/GSyst.cxx'
• VALUE: Value of the reweight dial in units of 1-sigma variations (1-sigma defined by GENIE)
• STATE: State of this parameter dial, for most cases this should be left as 'FIX'.

In our example we shall generate another set of comparisons this time with two parameters shifted.

• Charged Current Resonant Axial Mass : Axial mass parameter used in the resonant form factor
• Charged Current Resonant Normalisation : Total normalisation of CCRES events.

First we look for the possible name in GENIE reweight:

$GENIE/src/ReWeight/GSyst.h

class GSyst {
public:
 //......................................................................................
 static string AsString(GSyst_t syst)
 {
   switch(syst) {
     case ( kXSecTwkDial_MaNCEL           ) : return "MaNCEL";               break;
     
     ...

     case ( kXSecTwkDial_NormCCRES        ) : return "NormCCRES";            break;
     case ( kXSecTwkDial_MaCCRESshape     ) : return "MaCCRESshape";         break;
     case ( kXSecTwkDial_MvCCRESshape     ) : return "MvCCRESshape";         break;
     case ( kXSecTwkDial_MaCCRES          ) : return "MaCCRES";              break;
     case ( kXSecTwkDial_MvCCRES          ) : return "MvCCRES";              break;

We can see the dials we are interested in this list, specified by the strings: 'MaCCRES' and 'NormCCRES' respectively.

Now we want to change these dials to +1 for MaCCES and -1 sigma for NormCCRES. Therefore we add the following lines to our card file:

genie_parameter MaCCRES       +1.0  FIX
genie_parameter NormCCRES   -1.0   FIX

so that it now looks like the following

genie_tutorial.card

genie_parameter MaCCRES       +1.0  FIX
genie_parameter NormCCRES   -1.0   FIX

sample MiniBooNE_CC1pip_XSec_1DTpi_nu  GENIE: gntp.2063030.ghep.root
sample MiniBooNE_CC1pip_XSec_1DTu_nu GENIE: gntp.2063030.ghep.root  

With this new card file we can then run our comparisons again, but this time save the output to a different file

$ nuiscomp -c genie_tutorial.card -o genie_samples_reweighted.root

[LOG Fitter]: Starting nuiscomp.exe

...

[LOG Fitter]: Setting up nuiscomp
[LOG Fitter]: Number of parameters :  2
[LOG Fitter]: Read genie_parameter : MaCCRES = 1 :
[LOG Fitter]: Read genie_parameter : NormCCRES = -1 :

...

[LOG Fitter]: Setting up FitWeight Engine
[LOG Fitter]: Registed Dial Enum : MaCCRES 5 5011
[LOG Fitter]: Setting up GENIE RW : genierw

...

[LOG Reconf]:--- Starting Reconfigure iter. 0
[LOG Reconf]:--- Event Manager Reconfigure
[LOG Reconf]:--- MiniBooNE_CC1pip_XSec_1DTpi_nu : Processed 0 events. [M, W] = [33, 1]
[LOG Reconf]:--- MiniBooNE_CC1pip_XSec_1DTpi_nu : Processed 500000 events. [M, W] = [13, 1]
[LOG Reconf]:--- MiniBooNE_CC1pip_XSec_1DTpi_nu : Processed 1000000 events. [M, W] = [13, 1]
[LOG Reconf]:--- MiniBooNE_CC1pip_XSec_1DTpi_nu : Processed 1500000 events. [M, W] = [11, 1.17986]
[LOG Reconf]:--- MiniBooNE_CC1pip_XSec_1DTpi_nu : Processed 2000000 events. [M, W] = [51, 1]

...

[LOG Minmzr]:- Writing each of the data classes...
[LOG Sample]:-- Written Histograms: MiniBooNE_CC1pip_XSec_1DTpi_nu
[LOG Sample]:-- Written Histograms: MiniBooNE_CC1pip_XSec_1DTu_nu
[LOG Fitter]: ------------------------------------ -
[LOG Fitter]: Comparison Complete.
[LOG Fitter]: ------------------------------------ -

You might have noticed that now during the event processing stage, the values [M, W] correspond to the [Mode, Weight] for the event processed at that point, and that now we have added reweight dials, the weights are not always equal to 1.0.

Now lets open up both our comparison files and compare the outputs

$ root genie_samples.root genie_samples_reweighted.root
root [2] TBrowser b

We now have two files with the exact same structure, the only differences between these will be the values given in each of the MC histograms.

If we compare the MiniBooNE_CC1pip_XSec_1DTpi_nu_MC histograms on a single plot against the data we can see that the normalisation of the reweighed prediction has shifted upwards, and the likelihood for that prediction given the data has gotten worse as a result.