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Changes between Version 10 and Version 11 of HowToUseNUISCOMP


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Timestamp:
Jun 12, 2017, 8:06:53 PM (7 years ago)
Author:
Patrick Stowell
Comment:

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  • HowToUseNUISCOMP

    v10 v11  
    2525= Useful NUISCOMP Commands =
    2626There are also additional card file arguments and run time arguments that can be used with nuiscomp to help with debugging or performing slightly different comparisons.
     27
     28== Specifying fake data ==
     29It is possible to read in the output of a previous NUISANCE comparison run, and use it to create a fake data.
     30
     31For example, say we wanted to see if one model had the uncertainties of similar magnitude to the data, how similar is it to another model.
     32
     33This can be achieved by using the '-d' command line flag in nuiscomp.
     34
     35First we would need to generate a model using nuiscomp, for this example we will use NEUT to generate out predictions.
     36{{{
     37$ nuiscomp -c neut_samples.card -o neut_samples.root
     38}}}
     39Producing the following output
     40
     41
     42Then we can run our second set of comparisons, using this neut output file to create fake data
     43{{{
     44$ nuiscomp -c genie_samples.card -o genie_samples.root -d neut_samples.root
     45}}}
     46
     47
     48
     49Notice that the data has now been shifted to match the original NEUT prediction we made. For comparisons the only real purpose of using this feature is to get a naive idea of how well a dataset may be able to discriminate two different models.
     50
     51Its real strength is clearer when using the same fake data option also present in the nuismin application, as this allows a user approximate how bias a tuning may be if the model being fitted is an incorrect description of nature.
    2752
    2853
     
    101126}}}
    102127
    103 
    104 
    105 == Specifying fake data ==
    106 
    107128== Increasing or decreasing Verbosity ==
    108129The +/-e and +/-v flags are reserved to increase or decrease the NUISANCE verbosity quickly at runtime.