Difference: RunningTesla (1 vs. 16)

Revision 162014-12-14 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"
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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:

Revision 152014-11-07 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"
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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.

Revision 142014-11-05 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"

General processing path

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 5) Need a customised DaVinci environment to run Tesla (in a clean session)
SetupProject DaVinci v36r0 --build-env
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getpack Phys/Tesla head getpack Phys/TeslaTools head
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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
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* 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

Revision 132014-10-14 - PatrickSKoppenburg

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META TOPICPARENT name="LHCbTeslaProject"

General processing path

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gaudirun.py PrepMC.py
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* Sample PrepMC.py can be found at: /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/
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  • 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
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* Sample ReRun_L0.py can be found at: /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/
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  • 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
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* Sample RemakeSelReports.py can be found at: /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/
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  • 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)
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  Note that you can customise where you want the output on the DST (default '/Event/Tesla')
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* Sample Turbo.py can be found in the options folder of Tesla
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  • 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
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* Sample TupleToolsCheck_MC_Tutorial.py can be found at: /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/
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  • 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.

Revision 122014-10-13 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"

General processing path

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  * Sample TupleToolsCheck_MC_Tutorial.py can be found at: /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/
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8) Missing variables should be added to the RunningListTurboMissing page.
 
META TOPICMOVED by="sbenson" date="1409910101" from="LHCb.TESLADevelopmentNotes" to="LHCb.RunningTesla"

Revision 112014-10-13 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"

General processing path

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 getpack Phys/TeslaTools head getpack Hlt/HltDAQ (take the offered version) cp /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/HltSelReportsDecoder* Hlt/HltDAQ/src/
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cd Hlt/HltDAQ/cmt
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cd Phys/Tesla/cmt
 cmt br cmt make SetupProject DaVinci v36r0

Revision 102014-10-10 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"

General processing path

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  * Sample Turbo.py can be found in the options folder of Tesla
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7) With your usual DaVinci scripts, direct your DecayTreeTuple to '/Event/Tesla/Particles' (or customised prefix). Requires the DaVinci environment with at least v36r0!!!
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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/

 
META TOPICMOVED by="sbenson" date="1409910101" from="LHCb.TESLADevelopmentNotes" to="LHCb.RunningTesla"

Revision 92014-09-19 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"

General processing path

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 cp /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/HltSelReportsDecoder* Hlt/HltDAQ/src/ cd Hlt/HltDAQ/cmt cmt br cmt make
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SetupProject DaVinci v36rX
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SetupProject DaVinci v36r0
 

6) Finally, run the Tesla algorithm

Revision 82014-09-16 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"

General processing path

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  Note that you can customise where you want the output on the DST (default '/Event/Tesla')
Added:
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* Sample Turbo.py can be found in the options folder of Tesla
 7) With your usual DaVinci scripts, direct your DecayTreeTuple to '/Event/Tesla/Particles' (or customised prefix). Requires the DaVinci environment with at least v36r0!!!

META TOPICMOVED by="sbenson" date="1409910101" from="LHCb.TESLADevelopmentNotes" to="LHCb.RunningTesla"

Revision 72014-09-15 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"
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Disclaimer

IF YOU ARE SEEING THIS SENTENCE, YOU NEED TO WAIT FOR THE CODE TO BE PUT IN PLACE - email sean.benson@cernNOSPAMPLEASE.ch to skip the queue

 

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.

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  5) Need a customised DaVinci environment to run Tesla (in a clean session)
Changed:
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SetupProject DaVinci v36rX --build-env
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SetupProject DaVinci v36r0 --build-env getpack Phys/Tesla head getpack Phys/TeslaTools head
 getpack Hlt/HltDAQ (take the offered version) cp /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/HltSelReportsDecoder* Hlt/HltDAQ/src/ cd Hlt/HltDAQ/cmt
Line: 57 to 55
  Note that you can customise where you want the output on the DST (default '/Event/Tesla')
Changed:
<
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7) With your usual DaVinci scripts, direct your DecayTreeTuple to '/Event/Tesla/Particles' (or customised prefix). Requires the DaVinci environment with at least v36rX!!!
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7) With your usual DaVinci scripts, direct your DecayTreeTuple to '/Event/Tesla/Particles' (or customised prefix). Requires the DaVinci environment with at least v36r0!!!
 
META TOPICMOVED by="sbenson" date="1409910101" from="LHCb.TESLADevelopmentNotes" to="LHCb.RunningTesla"

Revision 62014-09-15 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"

Disclaimer

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  2) The raw event must be restored to the format that Moore expects (direct to your DSTs).
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gaudirun.py RunRawEventJug.py
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gaudirun.py PrepMC.py
 
Added:
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* 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).
Changed:
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gaudirun.py RunL0AndRawEventOnSim.py
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gaudirun.py ReRun_L0.py
 
Added:
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* 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
Added:
>
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* 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)

Revision 52014-09-05 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"

Disclaimer

Revision 42014-09-05 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"
Added:
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Disclaimer

 IF YOU ARE SEEING THIS SENTENCE, YOU NEED TO WAIT FOR THE CODE TO BE PUT IN PLACE - email sean.benson@cernNOSPAMPLEASE.ch to skip the queue
Added:
>
>

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.

 
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To run Tesla over MC, you will first need to prepare the MC to run the HLT and remake the Selection Reports:
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Detailed steps

 
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We can first setup the Moore build that we need.
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1) We can first setup the Moore build that we need.
 
SetupProject Moore v22r1p1 --build-env
getpack Hlt/HltRawData (take the offered version)
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 SetupProject Moore v22r1p1
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2) The raw event must be restored to the format that Moore expects (direct to your DSTs).
gaudirun.py RunRawEventJug.py

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

gaudirun.py RunL0AndRawEventOnSim.py

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

gaudirun.py RemakeSelReports.py

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

SetupProject DaVinci v36rX --build-env
getpack Hlt/HltDAQ (take the offered version)
cp /afs/cern.ch/work/s/sbenson/public/forTeslaExtendedReps/HltSelReportsDecoder* Hlt/HltDAQ/src/
cd Hlt/HltDAQ/cmt
cmt br cmt make
SetupProject DaVinci v36rX

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')

7) With your usual DaVinci scripts, direct your DecayTreeTuple to '/Event/Tesla/Particles' (or customised prefix). Requires the DaVinci environment with at least v36rX!!!

 
META TOPICMOVED by="sbenson" date="1409910101" from="LHCb.TESLADevelopmentNotes" to="LHCb.RunningTesla"

Revision 32014-09-05 - SeanBenson

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META TOPICPARENT name="LHCbTeslaProject"
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SetupProject Brunel v44r8 --build-env
cmt create Tesla v1r0 Rec
cd Rec/Tesla
mkdir python/Tesla
cp L0/L0App/python/L0App/Configuration.py python/Tesla
### edit the configurable accordingly
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IF YOU ARE SEEING THIS SENTENCE, YOU NEED TO WAIT FOR THE CODE TO BE PUT IN PLACE - email sean.benson@cernNOSPAMPLEASE.ch to skip the queue
 
Changed:
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Building the DaTesla package

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To run Tesla over MC, you will first need to prepare the MC to run the HLT and remake the Selection Reports:

We can first setup the Moore build that we need.

 
Changed:
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SetupProject DaVinci v33r8 --build-env cmt create DaTesla v1r0 Phys
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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
  \ No newline at end of file
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META TOPICMOVED by="sbenson" date="1409910101" from="LHCb.TESLADevelopmentNotes" to="LHCb.RunningTesla"

Revision 22013-11-07 - MikaVesterinen

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META TOPICPARENT name="LHCbTeslaProject"
SetupProject Brunel v44r8 --build-env
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 cp L0/L0App/python/L0App/Configuration.py python/Tesla ### edit the configurable accordingly \ No newline at end of file
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Building the DaTesla package

SetupProject DaVinci v33r8 --build-env
cmt create DaTesla v1r0 Phys
 \ No newline at end of file

Revision 12013-10-29 - MikaVesterinen

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META TOPICPARENT name="LHCbTeslaProject"
SetupProject Brunel v44r8 --build-env
cmt create Tesla v1r0 Rec
cd Rec/Tesla
mkdir python/Tesla
cp L0/L0App/python/L0App/Configuration.py python/Tesla
### edit the configurable accordingly
 
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