OBSOLETE, please see the MakeLineForTurbo and MakeLineForTurboSimplified tutorials

Disclaimer

This tutorial is intended to get started with the general steps of the Turbo stream and has specially made DSTs for those who would like to skip steps in:

/afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/TutorialFiles

Those who wish to write a new line for the Turbo stream are advised to follow the MakeLineForTurbo tutorial instead.

General processing path

To run Tesla over MC, you will first need to prepare the MC to run the HLT and remake the Selection Reports. The Tesla algorithm is then run. Normal DecayTreeTuple tools are then ran over the output of Tesla.

For the case of running over data in 2015, Tesla will be run and the resulting output will be ready for use with the normal DecayTreeTuple tools.

Detailed steps

1) We can first setup the Moore build that we need.

SetupProject Moore v22r1p1 --build-env
getpack Hlt/HltRawData (take the offered version)
cp /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/HltSelReportsMaker* Hlt/HltRawData/src/
getpack Hlt/Moore
cd Hlt/Moore/cmt
cmt br cmt make
SetupProject Moore v22r1p1

2) The raw event must be restored to the format that Moore expects (direct to your DSTs).

gaudirun.py PrepMC.py
  • Sample PrepMC.py can be found at: /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/

3) The L0 must be re-simulated with the TCK we will use (direct to your DSTs).

gaudirun.py ReRun_L0.py
  • Sample ReRun_L0.py can be found at: /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/

4) The Hlt is ready to be re-run producing our updated selection reports (direct to your DSTs).

gaudirun.py RemakeSelReports.py
  • Sample RemakeSelReports.py can be found at: /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/

5) Need a customised DaVinci environment to run Tesla (in a clean session)

SetupProject DaVinci v36r0 --build-env
getpack Phys/Tesla v1r0
getpack Phys/TeslaTools v1r0
getpack Hlt/HltDAQ (take the offered version)
cp /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/HltSelReportsDecoder* Hlt/HltDAQ/src/
cd Phys/Tesla/cmt
cmt br cmt make
SetupProject DaVinci v36r0
* Note that versions of Tesla (TeslaTools) after v1r0 assume a post-split Hlt. To follow this tutorial make sure that v1r0 is used, to use the latest version and make a new line for the Turbo stream, please follow the MakeLineForTurbo tutorial.

6) Finally, run the Tesla algorithm

gaudirun.py Turbo.py
Note that you can customise where you want the output on the DST (default '/Event/Tesla')

  • Sample Turbo.py can be found in the options folder of Tesla

7) You can now direct DecayTreeTuple to '/Event/Tesla/Particles' (or customised prefix). Requires the DaVinci environment with at least v36r0!!!

gaudirun.py TupleToolsCheck_MC_Tutorial.py

  • Sample TupleToolsCheck_MC_Tutorial.py can be found at: /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/

8) Missing variables should be added to the RunningListTurboMissing page.

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Topic revision: r16 - 2014-12-14 - SeanBenson
 
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