Difference: AtlasDataAnalysis (97 vs. 98)

Revision 982011-08-01 - AlistairGemmell

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Computentp, Neural Nets and MCLIMITS

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Result of FlatAscii_global validation: OK Result of FlatTRntp validation: OK

Changed:

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Variables used by the Neural Net

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Variables used by the GlaNtp package

The variables used by the package can be divided into two sets. The first are those variables that are constant throughout the sample - the 'global' variables (e.g. cross-section of the sample). These can be specified in their own tree, where they will be recorded (and read by GlaNtp) once only. If desired, these variables can be defined within the main tree of the input file - however, then they will be recorded once per event, and read in once per event. This is obviously a bit wasteful, but for historical reasons it can be done. The other variables are those that change on an event-by-event basis. These variables include both the variables we are going to train the Neural Net on (more information relevant to those variables is given in the relevant section of this TWiki), and other useful variables, such as filter flags (that tell GlaNtp whether an event is sensible or not). All of these variables are listed in the file VariableTreeToNTPATLASttHSemiLeptonic-v15.txt

The file maps logical values to their branch/leaf. The tree can be the global tree or the event tree.

GeneralParameter string 1 FlatTupleVar/<variable_name>=<tree>/<variable_name_in_tree>

Also specified are the name of the leaf for the cutmask and invert word -- these are global values for a file.

GeneralParameter string 1 CutMaskString=cutMask
GeneralParameter string 1 InvertWordString=invertWord

There's also something about

ListParameter   EvInfoTree:1  1 NN_BJetWeight_Jet1:NN_BJetWeight_Jet1/NN_BJetWeight_Jet1

that I need to ask Rick about...

Variables used for training the Neural Net

The list of variables on which the neural net is to train is set in the shell script, under TMVAvarset.txt (this file is created when the script runs). At present, these variables are:

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