Difference: AtlasDataAnalysis (153 vs. 154)

Revision 1542013-12-17 - AndrewPickford

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  • The BASEBATCHDIR is now set automatically to the working directory when the script is executed.

Getting a copy of GlaNtp

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  • Set yourself up for access into SVN (using a proxy to access SVN, as described here)

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  • Set yourself up for access into SVN (using a proxy to access SVN, as described here)

 source /data/ppe01/sl5x/x86_64/grid/glite-ui/latest/external/etc/profile.d/grid-env.sh svn-grid-proxy-init

  • Create the directory where you want to set up your copy, and get a copy of the setup script (afraid the best place to get this script is from the scripts area of the GlaNtp code you're checking out. I am aware of the tautology of getting a script from the package so you can get the package, but that's the way it is. Just download this one file and go from there - you can delete it later when you've got the whole thing. (The code below assumes you're checking out from the trunk. Generally better to check out a specific tag, but the latest tag and the trunk should be the same, so you should just be able to copy and paste the below code.)

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 cd /home/ahgemmell/GlaNtp svn co https://ppesvn.physics.gla.ac.uk/svn/atlas/GlaNtp/trunk/scripts/GlaNtpScript.sh
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  • You then need to set up your environment ready for the validation. This is done with the setup_glantp.sh script, which is available within the NNFitter package. (Yes, I know - another case of getting the code before getting the code...) You run the script (which is also used for debugging the code) with

    source setup_glantp.sh
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  • You then need to set up your environment ready for the validation. This is done with the setup_glantp.sh script, which is available within the NNFitter package. (Yes, I know - another case of getting the code before getting the code...) You run the script (which is also used for debugging the code) with

    source setup_glantp.sh
 
  • Make a directory to hold the code itself:

    mkdir GlaNtpPackage

  • GlaNtpScript.sh not only checks out and compiles the code, it also then goes and validates it. setup_glantp.sh sets up the environment variables so the validation data can be found.

  • You now run the script in the parent directory of GlaNtpPackage, specifying whether you want a specific tag (e.g. 00-00-10), or just from the head of the trunk (h) so you're more free to play around with it. It's always a good idea to check out a specific tag, so that whatever you do to the head, you can still run over a valid release.

    ./GlaNtpScript.sh SVN 00-00-10
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Variables used by the GlaNtp package

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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. To determine which of these behaviours you use, set LoadGlobalOnEachEvent in FlatPlotter and FlatReader to 1 for the events to be read in on an event-by-event basis, or 0 to be read in once from the global tree (or from the first event only). For more information on this switch, refer to this. 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
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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. To determine which of these behaviours you use, set LoadGlobalOnEachEvent in FlatPlotter and FlatReader to 1 for the events to be read in on an event-by-event basis, or 0 to be read in once from the global tree (or from the first event only). For more information on this switch, refer to this. 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.
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Specifying files as Signal/Background or as real data

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The input datasets need to be specified in a number of peripheral files, so that the ANN can distinguish between signal and background MC files or real data files. There is only one place where data files need to be specified differently to MC - FlatAtlastthPhysicsProc1.txt - and if you are running the fit with data and not pseudodata, this is determined through one single flag, set in genemflat - see here. Errors for each process also need to be specified - how this is done is detailed in that section. The relevant files for adding processes are atlastth_histlist_flat-v15.txt, AtlasttHRealTitles.txt, FlatAtlastthPhysicsProc1.txt and FlatSysSetAtlastth1.txt. There are also some files that are produced through the action of genemflat_batch_Complete2_SL5.sh. At several points in these files, there are common structures for inputting data, relating to ListParameter and ColumnParameter:
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The input datasets need to be specified in a number of peripheral files, so that the ANN can distinguish between signal and background MC files or real data files. There is only one place where data files need to be specified differently to MC - FlatAtlastthPhysicsProc1.txt - and if you are running the fit with data and not pseudodata, this is determined through one single flag, set in genemflat - see here. Errors for each process also need to be specified - how this is done is detailed in that section. The relevant files for adding processes are atlastth_histlist_flat-v15.txt, AtlasttHRealTitles.txt, FlatAtlastthPhysicsProc1.txt and FlatSysSetAtlastth1.txt. There are also some files that are produced through the action of genemflat_batch_Complete2_SL5.sh. At several points in these files, there are common structures for inputting data, relating to ListParameter and ColumnParameter:
 
ListParameter <tag> <onoff> <colon-separated-parameter-list>
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  Computentp120.log
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The log file from Computentp -- more information about the information contained within it is found here
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The log file from Computentp -- more information about the information contained within it is found here
 
  • stackedinput/StackInput/tth120

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      OnOff : 1 Process : 2.19001e-314 SorB : 0
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    These reflect the parameters as set in TMVAsteer.txt (created via genemflat_batch_Complete2_SL5_sh). Note that the number following 'Process' is nonsense (and in later releases of GlaNtp is not present) - that parameter is there in the steering file simply to make it more human-readable. However, the code still tries to read it in, but can only handle doubles - the net result varies from run to run, but can always be safely ignored.
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    These reflect the parameters as set in TMVAsteer.txt (created via genemflat_batch_Complete2_SL5_sh). Note that the number following 'Process' is nonsense (and in later releases of GlaNtp is not present) - that parameter is there in the steering file simply to make it more human-readable. However, the code still tries to read it in, but can only handle doubles - the net result varies from run to run, but can always be safely ignored.
  •   templates/out/FlatPlotter${prefix}.out
     
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