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TbUT analysis software

This page provides information about the TbUT package. The software is a part of the Kepler project. The main aim of this software is to perform whole processing of the testbeam data using Gaudi framework.

Contact persons

Adam Dendek Mail

Setup

To setup the TbUT you just need to:

  • Setup project and get source code from LHCb's SVN repository:
    SetupProject Kepler v3r0   
    SetupProject Kepler v3r0 --build-env 
    
    getpack Tb/TbUT
    getpack Tb/TbEvent
    getpack Tb/TbKernel
    getpack Tb/Kepler
     
  • compile the source code
    cd Tb/TbUT
    cd cmt
    cmt br cmt make -j8
     

Running the TbUT software

The TbUT software can be run in two modes, Pedestal and Run. The description below contains instructions on how to run TbUT in standalone mode (no other Kepler stuff).

Pedestal mode -- computing the pedestals

  • The aim of the pedestal training is to calculate the pedestals values, which will then be used in Run mode in order to subtract the pedestal from the raw data during execution of the Pedestal Subtraction algorithm.
  • In this mode only 2 algorithms are executed : Raw Data Reader and Pedestal Subtractor for more detailed description of this algorithms look to the developers section.
  • Preparation of the options. You just need to modify the file ( Tb/TbUT/options/TbUTPedestal.py ):
    option name brief description
    app.inputData type of string, contains path to the input data
    app.eventMax type of integer, number of event to process
    app.app.pedestaOutputData type of string, contains path to the output file ( contains pedestal values)

  • Run the TbUT in Pedestal mode:
    go to Tb/TbUT
    gaudirun.py options/TbUTPedestal.py
         
  • After the execution of the application, the file contains pedestal values, one number per channel is output. The name of the file is specified in the options file ( line app.pedestalOutputData )

Run mode

  • In run mode the TbUT performs the whole processing of testbeam data.
  • In this mode all processing algorithms are executed.
    algorithm brief description
    Raw Data Reader Reads raw data from the DUT (Mamba board output) and saves the output into the TES
    Pedestal Subtractor Gets raw data from the TES, removes the calculated pedestals from the Pedestal mode run, and stores the output into theTES
    Common Mode Subtractor (CMS) Gets data after Pedestal Subtraction; removes the common mode noise, a single value per 32 Beetle channels (mean value of ADC); save the output into the TES
    Cluster Creator Gets data after CMS, create clusters and saves it information in the TES

Beyond the listed algorithms, a set of corresponding monitoring algorithms has been implemented. The detailed descriptions of processing and monitoring algorithms see developers section.

  • Preparation of the options. You just need to modify the file ( Tb/TbUT/options/TbUTRun.py ):
    option name brief description
    app.inputData type of string, contains path to the input data
    app.eventMax type of integer, number of event to process
    app.pedestalInputData type of string, contains path to pedestal file (created during execution TbUT in Pedestal mode)
    app.eventNumberDisplay type of integer, informs how many event snapshots will be saved (see section exemplary outputs )

  • Running TbUT in Run mode:
    go to Tb/TbUT
    gaudirun.py options/TbUTRun.py
         

Example outputs

GUI

Developers section

-- AdamMateuszDendek - 2015-08-03

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Topic revision: r3 - 2015-08-05 - unknown
 
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